habitat-performance relationships on an island: fitness...

50
Habitat-performance relationships on an island: fitness landscape of moose in Öland, Sweden Augusta MX Dorey September 2014 A thesis submitted for the partial fulfilment of the requirements for the degree of Master of Science at Imperial College London Formatted in the journal style of Oecologia Submitted for the MSc in Ecology, Evolution and Conservation

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Page 1: Habitat-performance relationships on an island: fitness ...navinderjsingh.weebly.com/uploads/1/1/2/2/11224342/... · Conditions on Öland are milder than those found in other areas

Habitat-performance relationships on an island fitness

landscape of moose in Oumlland Sweden

Augusta MX Dorey

September 2014

A thesis submitted for the partial fulfilment of the requirements for the degree of Master of Science at

Imperial College London

Formatted in the journal style of Oecologia

Submitted for the MSc in Ecology Evolution and Conservation

2

DECLARATION OF OWN WORK

I declare that this thesis ldquoHabitat ndash performance relationships on an island fitness landscape of moose in

Ӧland Swedenrdquo is entirely my own work and that where material was constructed by others it is fully cited

and referenced andor with appropriate acknowledgement given

This research was funded by Swedish University of Agricultural Sciences Umearing Sweden (SLU)

Data was provided by the Moose Research Group SLU

Codes were conceived and designed by Augusta Dorey Navinder Singh and Andrew Allen

Andrew Allen provided information on the migratory status of moose individuals

Jacobs Index and habitat compositional R code was written by Andrew Allen

The data was analysed by Augusta Dorey

Augusta Dorey wrote the manuscript Navinder Singh and Andrew Allen provided editorial advice

In Collaboration with Swedish University of Agricultural Sciences Umearing Sweden

Word Count 5885

Name of Supervisors

Supervisor Dr Navinder J Singh1

Assistant Supervisor Mr Andrew Allen1

Internal Supervisor Dr David Orme2

1Department of Wildlife Fish and Environmental Studies Swedish University of Agricultural Sciences

Skogsmarksgraumlnd Umearing SE-90183

2Department of Life Sciences Imperial College London Silwood Park Campus Ascot Berkshire SL57PY

3 Contents

Abstract 4

Introduction 5

Materials and Methods 7

Study area 7

Capture and Handling 8

Data Screening 8

Home rangeUtilization distribution 8

Habitat 9

Activity 10

Diet analysis 10

Survival analysis 10

Results 11

Home RangeUtilization Distribution 11

Activity 12

Habitat ndash Proportions 13

Habitat - Selection 14

Diet 17

Calf Survival 18

Discussion 19

Acknowledgements 22

References 23

Appendix A 30

Introduction 30

Appendix B 31

Method and Materials 31

Appendix C 33

Home ranges 33

Appendix D 35

Activity 35

Appendix E 36

Habitat Proportions 36

Habitat Selection 37

Appendix F 50

Background 50

4

Abstract

Moose (Alces alces) the largest among the deer have both high recreational and economic value in

Scandinavia and elsewhere To efficiently manage such a valuable species the key factors affecting their

fitness and performance must be understood Moose generally have high productivity and calf survival in

predator free areas however in recent years populations at the southern edge of their distribution such as on

the predator free island of Ӧland in Sweden there have been reports of low calf survival Individuals are found

to carry Anaplasma phagocytophilum which has been thought to be one of the factors causing the low survival

The aim of this study was to identify what abiotic and biotic factors may also be affecting female moose

performance and their calf survival GPS data from 18 collared moose was used in conjunction with home

range activity diet survival and habitat analysis Moose did not alter the size of their seasonal home ranges

or their activity level Agricultural areas and feeding stations have become the preferred areas in the core home

ranges during the winter season The diet analysis revealed that nearly two thirds of the moosersquos winter diet

contained agricultural produce Moose are having to utilise areas where in other populations individuals tend

to avoid This could probably be one of the reasons for females to be of lower quality and therefore not being

able to ensure calf survival With changing climates and human land use moose continue to be under such

environmental pressures which may therefore jeopardize their future survival and reproduction

Key Words Population dynamics Habitat selection Performance Fitness Climate Survival Alces

alces Sweden Ӧland

Image by Fredrik Stenbacka

5 Introduction

The population size of animals varies in space and time (Turchin 2001) This variation is driven by a

combination of internal as well as external factors that drive changes in survival and reproduction of

individuals (Brown 2011) Internal factors are associated with life history such as sex age body mass and

generation time whereas the external factors include climatic factors (characterised as density independent)

competition food disease (characterised as density dependent) and human influence (appendix A) Long-term

changes in population size therefore determine the long-term fitness of individuals and cohorts in a population

(Albon et al 1987) However little is known about how these factors interact to produce short and long term

variation in demography and population dynamics across space Although difficult understanding causes of

variation of population size is crucial to effective population conservation and management (Lavsund et al

2003 McLoughlin et al 2011) The interplay and relative contribution of the above factors are best shown

from species with short generation times or from long-term monitoring studies

Ungulates are most commonly studied due to their international economic and recreational value large body

sizes and the relative ease of marking handling and capturing them (Forchhammer et al 2002 Bradshaw et

al 2003 Gordon et al 2004 Clutton-Brock and Sheldon 2010) Large herbivores tend to display low fecundity

and high adult survivorship (Gaillard et al 2000a) Past studies have revealed important details about the

factors affecting their population dynamics An ungulate life cycle is usually classified based on defined age

classes new-born weaned young yearlings two-year-olds prime-aged adults and senescent adults (older than

seven years) New-born survival is highly dependent on climatic conditions predation and the level of maternal

care and condition ie quality of milk and reproductive experience (Gaillard et al 2000a Testa 2004 Baringrdsen

et al 2008) Weaned young and yearlings survival tends to be independent of the mothers care and affected

most often by climatic conditions ie severe winters disease and predation (Bartmann et al 1992) Survival

of two-year olds and adults is influenced mainly by predation (Modafferi 1997) Males generally experience a

lower survival rate than females due to the pressure of the rut and male biased hunting (Mysterud et al 2005)

Conditions experienced during a calfrsquos early development not only cause immediate effects on its future

performance but also delayed effects Calf development (weight) affects its future reproductive success

(performance) by effecting adult body size and future calf body size (Albon et al 1987 Lindstroumlm 1999

Forchhammer et al 2002)

The moose (Alces alces) is a large ungulate widely distributed across the northern hemisphere It is the largest

and only solitary member of the deer family (Cervidae) In Sweden it is found throughout the country in boreal

forests with the exception of the island of Gotland (Brandin 2009) Sweden has the largest population of moose

in Europe with approximately 300000-350000 individuals (Singh et al 2014) A part of Swedenrsquos moose

population is influenced to some extent by predators such as brown bears (Ursus arctos) and wolves (Canis

lupus) however in predator free populations individuals are influenced mainly by stochastic environmental

conditions population density traffic and above all hunting (Sӕther 1997) (appendix A) Moose are hunted

all across Scandinavia and the overall value of moose hunting is estimated to be 145 billion SEK per year

6

(158 billion Euro) (Boman et al 2011) Each year in Sweden 90000-100000 individuals are harvested

providing approximately 85 million kilograms of moose meat (Kindberg et al 2009) A common method of

selecting which individuals are to be harvested is to assess the reproductive value of an individual and remove

the lownon-reproductive individuals such as calves bulls and cows without calves (Ball et al 1999 Ericsson

et al 2001) Hunting is biased towards bulls with large trophy antlers often resulting in a skewed sex ratio

(Laurian et al 2000 Harris et al 2002 Milner et al 2007)

Moose are known to have a generally high calf survival noted through studies from predator free areas in both

North America and Europe (Linnell et al 1995 Crecircte and Courtois 1997 Swenson et al 2007) A number of

other factors are nevertheless known to affect the survival during their first summer such as climatic variation

malnutrition abandonment disease and poor maternal investment (Verme and Ullrey 1984 Gaillard et al

2000b Lomas and Bender 2007 Ericsson et al 2002 Herfindal et al 2006 Lenarz et al 2010) Low survival

in single odd years has been attributed to weather and low food quality

During recent years moose populations appear to be under environmental stress across their southern range

ascertained by studies reporting low calf survival from both North America and Sweden (Monteith et al in

press Ericsson et al submitted) A similar situation has been reported recently on the island of Oumlland in

southern Sweden where the harvesting of moose was postponed from 2001 to 2005 by mutual agreement

between hunters This was due to a fear of population collapse due to poor management strategies in previous

years that lead to a suspected unsustainable harvest The four-year harvesting break resulted in a balanced sex

ratio and age distribution (Jonsson 2007) In 2006 however it was brought to the attention of the department

of Pathology and Wildlife Diseases at the Swedish National Veterinary Institute in Uppsala (SVA) that there

was an unusually low number of calves observed on the island Malmsten (2014a) conducted a follow up study

during 2012 and 2013 and found that summer calf survival of individuals from Oumlland was only 318 and

158 respectively When compared to calf survival from two other sites in southern Sweden (Kronoberg and

Soumldermanland) with rates all above 73 for both years this figure was regarded as very worrying and

prompted a need for an in-depth exanimation of the factors determining such low calf survival With this above

rationale in mind this study investigates the habitat performance relationships of female moose on the island

of Oumlland This study also provides a model for examining the factors affecting population dynamics on an

island

7 Materials and Methods

Study area

Ӧland (567333deg N 166667deg E) a Baltic island located in Kalmar county (Fig 1) is Swedenrsquos second largest

island (~140km in length) It can be split broadly into three areas the north (N) centre (C) and south (S) There

are three typical habitats found on the island boreal forests Stora Alvaret and agricultural land The largest

portions of boreal forests are found in the far north the centre and a patch in the far south Forest stands are

dominated by birch (Betula pubescens B pendula) and Scots pine (Pinus sylvestris) with rowan (Sorbus

aucuparia) aspen (Populus tremula) grey alder (Alnus incana) and yew (Taxus baccata) interspersed

throughout with willow sp (Salix spp) in areas near water sources (Sӕther and Heim 1993) The field layer is

made up of primarily bilberry (Vaccinium myrtillus) lowbush cranberry (Vaccinium vitis-idӕa) and heather

(Calluna vulgaris) (Cederlund 1989) The patches of boreal forest in the north centre and south are isolated

from each other by agricultural areas which are distributed throughout the island particularly along the coastal

regions and the island centre The most southerly patch of forest was protected from becoming agricultural

due to its status as a royal hunting ground and an important stopover for migratory birds (Lars Edenius

personal communication April 09 2014) The southern part of Oumlland has the largest expanse of steppe-like

alvar grassland (Stora Alvaret) found in the world (~25500 ha) (Roseacuten 2006) which is found over dry shallow

nutrient-poor grazed soil (Bakker et al 1996) on top of superficial Ordovician limestone (Dengler et al 2006)

Conditions on Oumlland are milder than those found in other areas of Sweden as it is positioned in the ldquorain-

shadowrdquo of mainland Sweden (Prentice 2007) The only predators of moose found on Oumlland are hunters which

were banned from hunting in previous years

Fig 1 Location of Oumlland

8

Capture and Handling

A random sample of adult moose (n = 25) were darted sedated and equipped with GPSGSM neck collars

(Vectronic Aerospace GmbH Berlin Germany) during the winter of 2012 by the Moose Research Group

SLU Movement data were collected from GPS collars dating from 22022012 ndash 24042014 Collars were

fixed to return GPS locations approximately every 30 minutes

Data Screening

The sample contained both males and females (six males 19 females x female age = 95 years range 4-17

years) An initial inspection revealed that one female individual only returned fixed locations for a period of

eight months Locations ceased during the hunting period so the individual was presumed shot and was

removed from the data along with the males

The exact time between each location varied and sometimes no fix could be made The adehabitatLT package

(Calenge 2006) was used to standardise the data and overcome the location fixing errors The function setNA

was used to place NAs where relocations were missing The function sett0 was used to round the timing of

collection obtaining a regular trajectory with 30 minute intervals The final dataset used in the analysis

consisted of 302710 regular GPS data points from a sample size of n=18 individuals two individuals from the

north ten individuals from the centre and six individuals from the south

To address the question and to investigate the influence of climate on the space use patterns of moose the

analysis was performed at two scales The first included all annual movements of moose and the second at a

seasonal scale ie summer and winter The seasonal scales were defined according to the growing season (GS)

and winter season (WS) In Scandinavia the current method used to define the start of season (SOS) is the

period when the daily mean air temperature is above 5degC (GS) Methods of calculating SOS are advancing

with the use of the Normalized Difference vegetation Index (NDVI) becoming more popular The start and

end of the GS and WS were derived using the mean start and end dates for Oumlland suggested by the Norwegian

Meteorological Institute (DNMI) Nordic climate map report (Tveito et al 2001) The GS of this study is

defined as the period between 23-April-2012 to 07-Nov-2012 and the WS is defined as the period between 08-

Nov-2012 to 22-April-2013 (based on the current standard normal period 1961-90)

Home rangeUtilization distribution

Variation in ungulate home range size is known to be caused by changes in energy requirements and variation

in food availability (Tufto et al 1996 Kie et al 2010 Moreller et al 2013) With shifting climate causes shifts

in plant phenology and therefore the spatial and temporal distribution of ungulate food (Maringrell et al 2006)

Individuals alter their home ranges to meet their energy requirements to maintain their fitness (Albon et al

1987 White 1997 Festa-Bianchet et al 1998 Forchhammer et al 2001)

The most commonly cited definition of a home range is ldquothat area traversed by the animal during its normal

activities of food gathering mating and caring for youngrdquo (Burt 1943) This has now been expanded to

9 incorporate measures of space use using the utilization distribution (UD van Winkle 1975) which can be

described as the ldquorelative frequency distribution of an animalrsquos occurrence in all four dimensions of space

and timerdquo (Keating and Cherry 2009) Home range is viewed as a constant 2D polygon whereas UDs are

viewed as multiple 3D polygons that take into account the distribution as well as the intensity of animalrsquos

movements and space use within their home range (Kranstauber et al 2012) (see appendix A)

Estimations of each individualrsquos annual and seasonal UDs were found using the Biased Random Bridge (BRB)

kernel approach (Benhamou 2011) from the adehabitatHR package (Calenge 2006) in R It was chosen as it is

considered an improvement on the previously preferred Brownian bridge (BB) method (Horne et al 2007) The

BB is purely a diffusive movement process whereas the BRB is an advective-diffusive movement process BB

does not take into account changes in advection direction (drift) or strength BB assumes an animalrsquos

movement is purely random it moves from a starting point and ends up at the end location randomly By

adding the advection component the BRB takes into account that the animalrsquos movement is biased towards a

certain direction This allows for a more biologically relevant analysis (Benhamou and Corneacutelis 2010)

A grid was created using the minmax XY coordinates of all individuals (plusmn 10 km to increase the extent and

prevent the grid directly touching the XY locations) The resolution of the grid was fixed at a 25 m x 25 m

scale to match the resolution of the relevant habitat maps (Hagner et al 2005) By specifying these criteria the

resolution of the data remains consistent between individuals The diffusion coefficient determines the variance

in the location of the kernels between two locations This was calculated from each individualrsquos dataset using

the BRBD function and added to the BRB model (see Benhamou 2011) The strength and direction of BRB

advection can change between bridges whilst having to remaining constant To remain constant an upper Tmax

and lower Lmin time thresholds were set Successive relocations that exceeded Tmax or under Lmin were

removed from the UD calculations The 50 (UD50) and 95 (UD95) isopleths were then calculated from

the UD using the kernelarea function

Habitat

The scale of analysis was further divided following Johnson (1980) Habitat selection within the landscape

(second order selection) was studied by comparing the UD95 with available habitats in each of the three study

areas of Oumlland (UD95Area) Habitat selection within the home range (third order selection) was studied by

comparing the UD50 with the UD95 (UD50UD95)

12 habitat classes were used in the analysis agricultural land broad leaved forests clear felled areas coastal

coniferous forests freshwater areas moorsgrassland miresmarshes mixed forest sparsely vegetated areas

urban areas and younger forests The proportion of area covered by each of these habitat classes was

determined in the UD50 and UD95 Habitat data was obtained from satellite imagery generated by Svenska

Marktaumlckedata (Hagner et al 2005) The habitat maps were last updated in 2002 and have a resolution of 25

m

Compositional analysis ( habitat used habitat available) (Aebischer 1993) was used in conjunction with

the Jacobrsquos index (D) (eqn1) to quantify habitat selection (Jacobs 1974) Coastal areas were removed as not

10

all home ranges contained them This combined approach allowed identification of habitats that are used

disproportionally to their availability ie in a non-random manner (Beyer et al 2010) This is an indication of

which habitats are important for an individual

119863 = ( 119903minus119901

119903+119901minus2119903119901 ) (eqn1)

r = Proportion of habitat type used

p = Total proportion of habitat available

D = Jacobs index varies from -1 (strong avoidance) to +1 (strong preference) with values close to 0 indicating

the habitat is used in proportion to its availability

Activity

Activity level is measured as the mean daily movement (MDM) by the individual to investigate if individuals

in an areaseason moved more and hence were more active than those in other areasseasons Unfortunately

only two cows were collared in the north and were therefore left out of this analysis Moose were identified as

migratory using a modelling approach (see Bunnefeld et al 2011 for methods) Migratory individuals were

initially removed from the activity analysis (n=4)The reason is that both migratory journeys were completed

during the winter season thus increasing the mean daily distance travelled and potentially biasing the analysis

One individual was also removed due it its collar not returning relocations during the entirety of the WS

Diet analysis

The Ӧland project team conducted histology diet analysis on the rumen content of five individuals that were

shot in the centre and south of the island during the WS of 2013

Survival analysis

The Ӧland project team measured calf survival using the mark-resight method The presenceabsence of a calf

was recorded by tracking the cows at six occasions throughout the year These were at the start of the calving

season (mid-May to early June) twice through the summer before the hunt after the hunt and after winter

Survival trend was estimated using a Kaplan-Meier curve (Kaplan and Meier 1958) The Kaplan-Meier curve

shows the survival function (S (t)) ie the probability of an individual surviving until at least time t (Bewick

et al 2004) The probability of surviving from one period to the next is multiplied together to give the survival

function The S(t) of this study is the probability of an individual surviving from birth to after the hunt

(Method summary see appendix B)

11 Results

Home RangeUtilization Distribution

A total of 51 home ranges were estimated (17 annual 17 within growing season 17 within winter season)

Annual x = 9613 ha GS x = 6345 ha and WS x = 6023 ha (appendix C)

At the UD50 scale the largest annual and seasonal mean home ranges were located in the north Mean annual

and seasonal home ranges in the centre were slightly larger than the south This difference was not significant

(F(113)= 22 p= 87) (ANOVA) There was no significant difference between the seasonal home ranges (x

plusmnSD for GS = 116 plusmn38 for WS = 98 plusmn32 ha) (t(11) = 105 p = 32) or the seasonal home ranges in the centre

(t(8) = 101 p = 34 and the south (t(5) = 87 p = 42) (paired-sample t-test) (Table 1)

At the UD95 scale the largest annual and WS mean home ranges were located in the north The largest GS

mean home ranges were located in the centre Mean annual and seasonal home ranges in the centre were

slightly larger than the south This difference was not significant (F(113) = 59 p = 63) (ANOVA) There

was no significant difference between the seasonal home ranges (x plusmnSD for GS = 635 plusmn225 for WS = 602

plusmn161) (t(11) = 373 p = 71) or the seasonal home ranges in the centre (t(8)= 20 p = 84) or south (t(5) = 34

p = 74) (paired-sample t-test) (Table 1)

Table 1 Seasonal and annual mean UD50 and UD95 BRB kernel area in hectares (1ha = 001km2) for the north centre

and south of Oumlland (smoothing factor (h) =100)

Are

a

Annual UD50 GS UD50 WS UD50

n Mean SD Range n Mean SD Range n Mean SD Range

N 2 209 49 139-279 2 1215 39 67-176 2 1615 106 160-163

C 9 178 56 114-277 9 116 44 48-165 9 943 4 61-173

S 6 160 21 142-177 6 1085 51 65-149 6 933 35 69-125

Annual UD95 GS UD95 WS UD95

N 2 10905 5 1084-1097 2 630 199 349-911 2 809 11 794-824

C 9 997 32 682-1536 9 6531 22 295-945 9 637 17 454-941

S 6 9298 30 605-1088 6 5985 373 442-575 6 5526 20 349-679

12

Activity

MDM rates in the three areas (sedentary individuals) during the GS ranged from 14 ndash31 km day During the

WS ranged they ranged from 11-24 km day (Table 2) Movement rates during the GS were higher than the

WS (x plusmnSD for GS = 202 plusmn043 for WS = 161 plusmn043) but it was not statistically significant (t(11) = 200 p=

07) (paired sample t-test)

Table 2 Seasonal mean daily movement rates (km day) for each area and for both areas (total)

Are

a

GS WS

n Mean SE Range n Mean SE Range

C 8 20 003 14-18 8 20 004 12-24

S 4 22 016 17-31 4 12 02 11-13

Total 12 202 003 14-31 12 16 003 11-24

The seasonal MDM rates of all individuals (migratory and sedentary) were not significantly different (x plusmnSD

for GS = 20 plusmn04 for WS = 18 plusmn061) (t(14) = 139 p= 19) (paired sample t-test)

The WS home range size affects the WS MDM (F(110) = 927 p = 01) (ANOVA) The GS home range size

does not affect the GS MDM (F(110) = 36 p = 56) (ANOVA) When the WS home range outlier was

removed the home range size did not affect the WS MDM (F(111) = 186 p= 19) (ANOVA) The MDM was

lowest in February and highest in April (Table 3) there appeared to be no significant pattern in MDM between

the months (appendix D)

Table 3 Mean daily distance moved (km day) for sedentary individuals

Month Season Distance

April GS 0051

May GS 0044

June GS 0039

July GS 0041

August GS 0042

September GS 0044

October GS 0043

November WS 0043

December WS 0038

January WS 0035

February WS 0028

13 Habitat ndash Proportions

The largest proportion of habitat on the island is agriculture the lowest proportion of habitat (excluding coastal

and freshwater) is urban areas (Fig 2) The largest proportion of habitat in the north was coniferous forests

whilst agricultural areas were the dominant habitat types in the centre and south (Fig 3) The lowest proportion

(excluding coastal and freshwater areas) was urban

Fig 2 Proportion of different types of habitats found on Ӧland

Fig 3 Mean proportion of habitats contained within UD95 in the three areas of Oumlland C = Centre N = North S =

South

14

Habitat - Selection

Generally forest habitat types are the highest ranked whilst sparsely vegetated and urban areas are the lowest

ranked Both the second and third order habitat selection analyses gave significant results in the compositional

analysis (Table 4) In the third order analysis (UD50UD95) the centre displayed significant differences

between habitat types The coniferous forests are significantly preferred to sparsely vegetated areas and the

sparsely vegetated areas are significantly preferred to urban areas In the second order analysis (UD95Area)

significance was observed in the north and centre In the north younger forests are significantly preferred to

miresmarshes clear felled areas are significantly preferred to agriculture and freshwater areas are significantly

preferred to sparsely vegetated areas In the centre clear felled areas are significantly preferred to agricultural

land freshwater areas are significantly preferred to urban areas and grasslandmoors are significantly preferred

to sparsely vegetated areas

Table 4 Summary of second (UD95Area bottom) and third order (UD50UD95 top) ranked habitat preferences between

the three areas according to the compositional analysis (see appendix B)

Rank North Centre South

1 Broad Leaf Younger Coniferous

2 Mixed Broad Leaf Younger

3 MiresMarshes Clear Fell GrasslandMoors

4 Younger Mixed Clear Fell

5 Clear Fell GrasslandMoors Mixed

6 Coniferous MiresMarshes Broad Leaf

7 Freshwater Agriculture Freshwater

8 Agriculture Coniferous Agriculture

9 Sparse Veg Sparse Veg MiresMarshes

10 GrasslandMoors Urban Sparse Veg

11 Urban Freshwater Urban

Rank North Centre South

1 Broad Leaf Mixed Coniferous

2 Mixed Younger Clear Fell

3 GrasslandMoors Broad Leaf Younger

4 Younger Coniferous GrasslandMoors

5 MiresMarshes Clear Fell Agriculture

6 Coniferous Agriculture MiresMarshes

7 Clear Fell MiresMarshes Broad Leaf

8 Agriculture Freshwater Freshwater

9 Urban Urban Sparse Veg

10 Freshwater GrasslandMoors Mixed

11 Sparse Veg Sparse Veg Urban

Indicates significantly preferred to the habitat below (significant deviation from random at P lt05)

15 The Jacobs index revealed that generally the habitats preferred during the GS within the home range (third

order) are younger (0187) and broad leaf forests (0154) The strongest avoidance was for urban areas (-0627)

During the WS only agricultural areas are preferred (0129) and the strongest avoidance was for urban areas (-

0393) (Fig 4)

Fig 4 Third order seasonal habitat preference (UD50UD95) all individuals The index ranges from -1 (total avoidance)

to 1 (strongest preference) Close to 0 indicates used in proportion to its availability

Third order habitat preferencesavoidances by area

North During the GS the strongest preference was for broad leaf (0218) and mixed forests (0161) The

strongest avoidance was for urban (-1) and sparsely vegetated areas (-05) During the WS the strongest

preference was for miresmarshes (0228) The strongest avoidance was for grasslandmoors (-05)

Centre During the GS the strongest preference was for broad leaf (0233) and younger forests (0223) The

strongest avoidance was for urban (-0527) and agricultural land (-0362) During the WS preference was only

shown for agricultural land (0327) The strongest avoidance was for urban areas (-0679) and miresmarshes

(-0638)

South During the GS the strongest preference was for coniferous (0312) and younger forests (0242) The

strongest avoidance was for urban (-0353) and sparsely vegetated areas (-0330) During the WS

grasslandmoors (0106) were the strongest preference The strongest avoidance was for urban (-0666) and

sparsely vegetated areas (-0351)

16

The Jacobs indices revealed that generally the habitats preferred during the GS within the landscape

(UD95Area) are broad leaf (0216) and younger forests (0201) The strongest avoidance was for urban (-

0717) and freshwater areas (-0694) The strongest preference during the WS are coniferous forests (0242)

and the strongest avoidance was for freshwater (-0674) and urban areas (-0648) (Fig 5)

Fig 5 Second order seasonal habitat preference (UD50UD95) all individuals The index ranges from -1 (total avoidance)

to 1 (strongest preference) Close to 0 indicates used in proportion to its availability

Second order habitat preferencesavoidances by area

North During the GS the strongest preference was for broad leaf (0363) and mixed forests (00291) The

strongest avoidance was for sparsely vegetated (-0909) and freshwater areas (-0780) During the WS mixed

(0335) and coniferous forests (0316) were the strongest preference The strongest avoidance was for

freshwater (-0731) and urban areas (-05333)

Centre During the GS the strongest preference for mixed (0394) and younger forests (0286) The strongest

avoidance was for urban (-0733) and sparsely vegetated (-0708) areas During the WS mixed (0404) and

coniferous forests (0255) were the strongest preference The strongest avoidance was for freshwater (-0704)

and sparsely vegetated areas (-0655)

South During the GS the strongest preference for grasslandmoors (0287) and clear fells (0165) The

strongest avoidance was for urban areas (-0678) and mixed forests (-0491) During the WS grasslandmoors

(0425) and coniferous forests (0154) were the strongest preference The strongest avoidance was for urban (-

0876) and freshwater areas (-0587) (appendix E)

17 Diet

Diet analysis of the rumen content sampled from five individuals (C=2 S=3) revealed that almost two thirds

(69) of the diet is comprised of agricultural produce (apple winter rape and sugar beet) (Fig 6)

Fig 6 Diet analysis from the rumen samples of five moose individuals that were culled in 2013

31

2117

9

8

5

22

1 1

1

1

1 00 0

0

0Diet (2610-911 2013 5 individuals)

AppleWinter RapeSugar BeetUndefined WoodSallowBroad-leaf GrassPineAshOakCloverCurrantsUndefined plantElderberryJuniperRaspberry

18

Calf Survival

Of the 18 individuals 13 produced calves in which 7 produced twins giving a total of 20 calves A Kaplan-

Meier estimate was conducted to measure the fraction of calves living up to each period of the study (Fig 7)

The mean survival time is until period 235 (midend of summer) At the start of summer 85 of calves

remained (3 still born) The period between summer and before the hunt survival drops to 30 The survival

at the end of the study (after hunt) drops further to 20 leaving 4 calves surviving (see appendix B)

Fig 7 Kaplan-Meier estimate of moose calf survival during the study period Period 0 (Start of summer) period 1

(midend of summer) period 2 (before hunt) period 3 (after hunt) period 4 (after winter)

19 Discussion

The results of this study emphasised how strikingly different the habitat composition is along the latitudinal

gradient of Oumlland The three areas show contrasting proportions of the key habitat types The starkest

difference is the high proportion of coniferous forests and lack of agriculture in the north compared to the

centre and south The proportion of coniferous forest in the north is almost 5 times greater than in the centre

and south whereas the proportion of agriculture in the centre and south is more than double that in the north

The north is perceived to be composed of the most suitable habitat for moose (Dussault et al 2006) It has the

largest proportions of each forest type and a low proportion of agricultural land This provides suitable forage

and shelter throughout the year The south has a contrasting habitat composition to the north The proportions

of agricultural and sparsely vegetated areas are the highest between the three areas and the proportions of forest

habitats are the lowest The large proportion of sparsely vegetated areas and low proportions of forest habitat

corresponds to the large area of Stora Alvaret This is perceived to be the least suitable area due to a lack of

shelter (coniferous forest) and suitable forage The strong preference for coniferous and younger forest habitats

in the south would suggest that moose exhibit a functional response in habitat selection (Godvik et al 2009)

ie as the proportion of a particular habitat decreases the selection for that habitat increases in this case

coniferous forests which provide shelter and younger forest which provide good forage Similarly in the centre

moose show strong preference for mixed forests a habitat that is of low proportion

In view of the large variation in habitat proportions between the areas it is surprising that there is not a large

variation in the home range sizes or the activity levels annually or seasonally Home ranges are ultimately

chosen to maximise fitness and meet energy requirements by utilizing the available forage Seasonal conditions

change the availability and necessity of resources (food quality shelter) Unlike the GS during the WS

deciduous trees and shrubs are leafless and low-lying shrubs are under snow cover (Dussault et al 2005)

These changes are well known to cause populations to alter their activity and home ranges to meet energy

requirements (Mysterud et al 2001) Populations have been shown to increase or decrease their home ranges

during the two seasons The GS home ranges are often larger than the WS home ranges (Philips et al 1973

Mysterud et al 2001) In some cases they can be found to be almost double the size of the WS home ranges

(Cederlund and Okarma 1988) In other populations the WS home ranges are double the size of the GS home

ranges (Lynch and Morgantini 1984) or sizes do not significantly differ (Cederlund and Sand 1994)

Previous studies on moose find females generally show increased activity from the start on the GS due to

various factors eg reduced ruminating times increased metabolic needs and increased foraging bursts

(Wattles and DeStefano 2013) Increased metabolic needs during this time are a results of pregnancy and

lactation (Georgii 1980) During the height of the GS they usually show reduced activity levels through times

of increased thermal stress (Renecker and Hudson 1989 van Beest et al 2012) During the WS the depth and

the duration of snow cover are well known to affect the activity level (Telfer 1970 Mysterud and Oslashstbye 1999

Bjoslashrneraas et al 2011) During the WS generally home ranges are smaller and activity less due to lower

metabolic needs Moose activity is constrained by rumination during the WS this period is known to be longer

due to the change in diet (Cederlund 1989 Renecker Hudson 1989) This was not the case on Ӧland activity

20

was lowest in February which is a similar result to Cederlundrsquos (1989) paper However Ӧland moose did not

significantly alter their seasonal activity levels The fact that the annual and seasonal activity levels and home

ranges were similar could be a result of the mild winters on Oumlland during the study period (Smhise 2014)

During the study period the average number of snow days was 80 and the mean snow depth was 10cm

(appendix F) (Swedish Meterological and Hydrological Institute- SMHI) These mild conditions do not restrict

the movement of moose or obscure forage Moose are well adapted for movement in deep snow depths of 60-

86cm (Prescott 1968) are needed to truly restrict movement This finding was similar to the Sweanor and

Sandegren (1989) and Cederlund and Sand (1994) where the snow depth at their sites did not reach movement

restricting depths

The survival curve illustrates just how bad the calf survival is on Ӧland Survival falls from 85 at the start to

20 Out of 20 calves only four were alive at the end of the study The sharpest fall in survival was the period

between end of summer and before the hunt so the deaths were not due to hunting Previous calf autopsies

(Malmsten 2014a) have shown that cause of death was starvation mothers possibly either did not have milk

the calf was unable to feed or the mother abandoned the calf Closer field based observations are needed to

attain this knowledge Moose are seasonal polyoestral mammals (Monfort et al 1993) coming into oestrus

during late September early October (Garel et al 2009) (appendix F) The diet of the mother influences the

health of the calf and this period is when sodium is hard to find sodium is a key mineral in moose diets for

features such as reproduction (Belovsky and Jordan 1981) Moose gain sodium mainly through aquatic plants

(MacCracken et al 1993) However the compositional analysis shows that freshwater areas are often ranked

as one of the lowest used habitats and coastal areas were removed as the proportion found in the home ranges

was extremely low The Jacobs Index shows that the moose only prefer freshwater areas in the north UD50

during the WS The north individuals again are those that are showing typical moose habitat selection

It is known that habitat selection is hierarchical with habitats that increase fitness selected for and the effects

of limiting factors are reduced (Rettie and Messier 2000) At the UD95 during the GS moose preferred areas

of good forage (forests) and avoided areas of low forage (freshwater and sparsely vegetated areas) and areas

close to humans (urban) This is consistent with other reports (Laurian et al 2008 Torres et al 2011) Within

the UD50 there is a shift in preferences The good forage areas are again preferred during the GS however

during WS the only preferred habitat is often agricultural land During the WS there could be a steady supply

of supplementary feed available hence the high levels of agricultural produce found in the rumen content

samples and the high preference of agricultural areas This diet is unusual for moose previous studies of

Swedish moose diet have found the GS diet was dominated by birch willow and herbaceous plants and the

WS diet dominated by pine and birch (Cederlund and Nystrom 1981) The diet analysis was conducted during

the WS instead of being dominant pine composed just 2 Birch did not appear however unidentified wood

composed only 9 whereas agricultural produce accounted for 69 Supplementary feed may be perceived

by the moose in the centre and south as a vital forage source during the WS In fact in the centre the

agricultural land is the only preferred habitat at the UD50 It is unknown whether there are salt licks provided

in these areas Selection for a critical habitat is often thought to be a fixed factor The Oumlland population from

21 the three areas are close in proximity however they displayed contrasting preferences This is supported by the

Osko et al (2004) report that found two neighbouring moose populations that had access to the same habitats

displayed contrasting preferences Habitat preferences for populations of the same species are not necessarily

fixed They alter with varying levels of habitat abundance and limiting factors skewing what is preserved to

be critical

The main limitation encountered in this study was with the limited sample There was only data on two

individuals from the north of the island which led it being removed from many of the analysis Similarly due

to a lack of relocations from the collars being turned off at points throughout the year two further individuals

had to be removed from a majority of the analysis This reduced the sample size to 17 or 18 individuals

Similarly only 13 of the individuals from the study produced calves This unfortunately prevented including

survival into models Although the sample size was small it was accurate it was of high resolution over

300000 GPS points In future it would be beneficial to have a more standardised data set An equal sample of

individuals from the three areas would be advised along with ensuring the GPS collars are kept turned on for

the entirety of the growing and winter season to allow comparisons between years It would also be

advantageous to collect coordinates of the feeding sites along with the composition This could then be

compared with high use UD coordinates to look if moose are truly spending a majority of their foraging time

at feeding stations A study on the population densities of moose and the increasing population of roe deer

(Capreolus capreolus) would add the factor of competition into the model

The low calf survival on Ӧland is most likely the result of a combination of factors The lack of suitable habitat

reported in this study in conjunction with Malmstenrsquos (2014a) report on the threat of disease (Anaplasma

phagocytophilum) are probable influences on the calf survival on Ӧland On Ӧland there is an increasing

population of roe deer and large numbers of migratory birds both carriers of ticks and diseases The mild

conditions on Ӧland are advantageous for ticks the carriers of A phagocytophilum Fewer snow days and

shorter periods of snow cover along with dry conditions are favourable for ticks This could probably be one

of the reasons for females to be of lower quality and therefore not being able to ensure calf survival Moose

have to utilise areas where in other populations individuals tend to avoid Finally similar to many studies I

advocate further research using a stronger dataset and longer term monitoring

22

Acknowledgements

I am indebted to NJ Singh and A Allen for all their help and guidance through the whole of this study I

thank SLU for the support provided during this study in terms of data finances and facilities Thank you to

everyone at the Department of Wildlife Fish and Environmental Studies for being so friendly and

supportive I would like to thank L Edenius for driving me around the study area and S Michon and H

Khalil for keeping me sane with fika and training

23 References

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Bradshaw RHW Hannon GE Lister AM (2003) A long-term perspective on ungulate-vegetation

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24346-352

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Bunnefeld N Boumlrger L van Moorter B Rolandsen CM Dettki H Solberg EJ Ericsson G(2011) A model-

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ranging moose Alces alces Ecology 821613-1620

Ericsson G Ball JP Danell K (2002) Moose offspring body mass along an altitudinal gradient Journal of

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Ericsson G Malmsten J Neumann W Singh NJ Dali AM Submitted Summer Calf Survival of

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30

Appendix A

Introduction

Fig 1 Summary chart of factors affecting the life history and therefore the long term fitness of a population

Fig 2 Summary chart 2

Movement

Habitat

Climate

Topography

Competition

FoodWater

Disease

Die

Survive

Reproduce

Population long term fitness

31 Appendix B

Method and Materials

Fig 1 Summary of processes

32

Fig 2 Examples of classical kernel home range output and Brownian bridge kernel home range (Calenge 2011) The

right image includes the area between relocations ie the movement path in contrast to the classic kernel home range

in the left image

33 Appendix C

Home ranges

Fig 1 Example of a non-migratory (ID006) individuals BRB kernel area From top left annual growing and winter

season UD50 (black contour) and UD95 (red contour)

Fig 2 Example of a migratory (ID012) individuals BRB kernel area From the left annual growing and winter season

UD50 (black contour) and UD95 (red contour)

34

Table 1 Annual and seasonal UD50 and UD95 areas (ha) for all individuals

ID Annual GS WS

UD50 UD95 UD50 UD95 UD50 UD95

ID004 190 924 93 531 173 941

ID005 230 1364 132 945 72 682

ID006 162 1036 89 736 70 611

ID008 277 1536 156 809 78 738

ID009 137 834 48 295 126 653

ID010 114 682 83 448 96 488

ID012 177 963 123 544 76 545

ID014 160 1018 87 575 89 662

ID015 172 858 128 532 109 679

ID016 156 1047 65 455 92 534

ID017 153 1088 149 1043 69 349

ID019 279 1097 176 911 163 824

ID020 139 1084 67 349 160 794

ID022 159 811 131 638 61 454

ID023 187 1061 147 771 72 705

ID024 146 725 165 705 101 458

ID026 142 605 99 442 125 547

ID027 126 567 75 461 48 277

35 Appendix D

Activity

Fig 1 Mean daily movement during the study period GS 23-April-2012 to 07-Nov-2012 WS 08-Nov-2012 to

22-April-2013 (number indicates month)

Fig 2 Mean daily movement in the centre and south during the GS and WS

36

Appendix E

Habitat Proportions

Fig 1 All individualsrsquo seasonal habitat proportions within the UD95

37 Habitat Selection

Table 1 Simplified ranking matrices comparing proportional habitat use within the second order (UD95Area) with

proportions of total available habitat types Mean value on the matrix was replaced by a sign a triple sign represents

significant deviation from random at P lt05 Highlighted habitat is ranked 1st

North A

gri

cult

ure

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 --- --- - +++ --- --- --- +++ +++ --- 8

Broad Leaf +++ 0 +++ + +++ +++ +++ + +++ +++ +++ 1

Clear Fell +++ --- 0 + +++ - - --- +++ +++ --- 7

Coniferous + - - 0 +++ - - --- +++ +++ - 6

Freshwater --- --- --- --- 0 --- --- --- +++ - --- 10

Grassland

Moors +++ --- + + +++ 0 +++ - +++ +++ + 3

MiresMarshes +++ --- + + +++ --- 0 - +++ +++ --- 5

Mixed +++ - +++ +++ +++ + + 0 +++ +++ + 2

Sparse Veg --- --- --- --- --- --- --- --- 0 --- --- 11

Urban --- --- --- --- + --- --- --- +++ 0 --- 9

Younger +++ --- +++ + +++ - +++ - +++ +++ 0 4

Rank Order and

Significance

Broad Leafgt Mixedgt GrasslandMoorsgt Youngergtgtgt MiresMarshesgt Coniferousgt

Clear Fellgtgtgt Agriculturegtgtgt Urbangt Freshwatergtgtgt Sparse Veg

Central

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 --- --- --- + +++ + --- +++ +++ --- 6

Broad Leaf +++ 0 +++ + +++ +++ + - +++ +++ - 3

Clear Fell +++ --- 0 - +++ +++ + --- +++ +++ --- 5

Coniferous +++ - + 0 +++ +++ + --- +++ +++ - 4

Freshwater - --- --- --- 0 +++ - --- +++ +++ --- 8

Grassland

Moors --- --- --- --- --- 0 --- --- +++ - --- 10

MiresMarshes - - - - + +++ 0 - +++ +++ - 7

Mixed +++ + +++ +++ +++ +++ + 0 +++ +++ + 1

Sparse Veg --- --- --- --- --- --- --- --- 0 - --- 11

Urban --- --- --- --- --- + --- --- + 0 --- 9

Younger +++ + +++ + +++ +++ + - +++ +++ 0 2

Rank Order and

Significance

Mixedgt Youngergt Broad Leafgt Coniferousgt Clear Fellgtgtgt Agriculturegt

MiresMarshesgt Freshwatergtgtgt Urbangt GrasslandMoorsgtgtgt Sparse Veg

38

South

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 + - - + - + +++ +++ +++ - 5

Broad Leaf - 0 - - + - - +++ + +++ - 7

Clear Fell + + 0 - + + + +++ + +++ + 2

Coniferous + + + 0 +++ + + +++ + +++ + 1

Freshwater - - - --- 0 - - + + +++ - 8

Grassland

Moors + + - - + 0 + + +++ + - 4

MiresMarshes - + - - + - 0 +++ + +++ - 6

Mixed --- --- --- --- - - --- 0 + + --- 10

Sparse Veg --- - - - - --- - - 0 + - 9

Urban --- --- --- --- --- - --- - - 0 --- 11

Younger + + - - + + + +++ + +++ 0 3

Rank Order

and

Significance

Coniferousgt Clear Fellgt Youngergt GrasslandMoorsgt Agriculturegt MiresMarshesgt Broad Leafgt

Freshwatergt Sparse Veggt Mixedgt Urban

Table 2 Simplified ranking matrices comparing proportional habitat use within the third order (UD50UD95) with

proportions of total available habitat types Mean value on the matrix was replaced by a sign a triple sign represents

significant deviation from random at P lt05 Highlighted habitat is ranked 1st

North

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 --- --- --- - + --- --- + +++ --- 8

Broad Leaf +++ 0 +++ + + + + + +++ +++ + 1

Clear Fell +++ --- 0 + + + - - + +++ - 5

Coniferous +++ - - 0 + + --- --- +++ +++ - 6

Freshwater + - - - 0 +++ - - +++ +++ - 7

GrasslandMoors - - - - --- 0 - - - + - 10

MiresMarshes +++ - + +++ + + 0 - +++ +++ + 3

Mixed +++ - + +++ + + + 0 +++ +++ + 2

Sparse Veg - --- - --- --- + --- --- 0 +++ --- 9

Urban --- --- --- --- --- - --- --- --- 0 --- 11

Younger +++ - + + + + - - +++ +++ 0 4

Rank Order and

Significance

Broad Leafgt Mixedgt MiresMarshesgt Youngergt Clear Fellgt Coniferousgt Freshwatergt

Agriculturegt Sparse Veggt GrasslandMoorsgt Urban

39

Central

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 --- --- + + - - - + +++ --- 7

Broad Leaf +++ 0 + +++ + + + + + +++ - 2

Clear Fell +++ - 0 +++ + + + + + +++ - 3

Coniferous - --- --- 0 + - - --- +++ + --- 8

Freshwater - - - - 0 --- - - --- - - 11

GrasslandMoors + - - + +++ 0 + - + +++ - 5

MiresMarshes + - - + + - 0 + + +++ - 6

Mixed + - - +++ + + - 0 +++ +++ - 4

Sparse Veg - - - --- +++ - - --- 0 +++ - 9

Urban --- --- --- - + --- --- --- --- 0 --- 10

Younger +++ + + +++ + + + + + +++ 0 1

Rank Order and

Significance

Youngergt Broad Leafgt Clear Fellgt Mixedgt GrasslandMoorsgt MiresMarshesgt

Agriculturegt Coniferousgtgtgt Sparse Veggtgtgt Urbangt Freshwater

South

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 - - - - - + - +++ + --- 8

Broad Leaf + 0 - --- + - + - +++ + - 6

Clear Fell + + 0 - + - + - +++ + - 4

Coniferous + +++ + 0 + + +++ + +++ + + 1

Freshwater + - - - 0 - - + + + - 7

GrasslandMoors + + + - + 0 + + + + - 3

MiresMarshes - - - --- + - 0 - + + - 9

Mixed + + + - - - + 0 + + - 5

Sparse Veg --- --- --- --- - - - - 0 + --- 10

Urban - - - - - - - - - 0 - 11

Younger +++ + + - + + + + +++ + 0 2

Rank Order and

Significance

Coniferousgt Youngergt GrasslandMoorsgt Clear Fellgt Mixedgt Broad Leafgt Freshwatergt

Agriculturegt MiresMarshesgt Sparse Veggt Urban

40

Table 3 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the GS according to Jacobs index

Ran

k North Centre South

50 95 50 95 50 95

+ - + - + - + - + - + -

1 Broad

Leaf Urban Broad Leaf Sparse Veg

Broad

Leaf Urban Mixed Urban Coniferous Urban

Grassland

Moors Urban

2 Mixed Sparse Veg Mixed Freshwater Younger Agriculture Younger Sparse Veg Younger Sparse Veg Clear Fell Mixed

3 Mires

Agriculture Grassland

Urban Clear

Fell Coniferous Broad Leaf

Grassland

Moors

Clear Fell Agriculture Coniferous Sparse Veg

Marshes Moors

4 Younger Grassland

Younger Agriculture

Freshwater Coniferous Freshwater

Broad Leaf Mires

Younger Freshwater

Moors Marshes

5 Clear

Fell Freshwater

Mires Coniferous

Sparse Veg Clear Fell Agriculture

Freshwater Agriculture

Marshes

6 Coniferous Clear Fell

Mires

Marshes

Mires

Grassland

Moors

Mires

Marshes Marshes

7 Mixed Mixed Broad Leaf

8 Grassland

Moors

41

Table 4 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the WS according to Jacobs index

Ran

k North Centre South

50 95 50 95 50 95

+ - + - + - + - + - + -

1 Mires

Marshes

Grassland

Moors Mixed Freshwater Agriculture Urban Mixed Freshwater

Grassland

Moors Urban GrasslandMoors Urban

2 Freshwater Mixed Coniferous Urban Mires

Marshes Coniferous Sparse Veg Agriculture

Sparse

Veg Coniferous Freshwater

3 Urban Coniferous Younger Grassland

Moors Freshwater Younger Urban Freshwater

Broad

Leaf Agriculture Mixed

4 Younger Agriculture Sparse Veg Broad

Leaf

Broad

Leaf

Grassland

Moors Mixed Broad Leaf

5 Clear Fell Agriculture Coniferous Agriculture Mires

Marshes Clear Fell

6 Sparse

Veg

Mires

Marshes Mixed

Mires

Marshes

Clear

Fell

Mires

Marshes

7 Broad

Leaf Clear Fell Younger Clear Fell Younger Sparse Veg

8 Clear Fell Younger

9 Sparse

Veg

10 Grassland

Moors

42

Table 5 Second order (UD95Area) individual selectionavoidance for the GS and WS according to the Jacobs index

ID GS WS

Select Avoid Select Avoid

ID004 Younger Sparsely Vegetated MiresMarshes Sparsely Vegetated

ID005 MiresMarshes Sparsely Vegetated Coniferous GrasslandMoors

ID006 Coniferous Sparsely Vegetated Mixed Freshwater

ID008 Mixed Sparsely Vegetated Mixed Freshwater

ID009 Mixed Sparsely Vegetated Mixed GrasslandMoors

ID010 MiresMarshes Freshwater GrasslandMoors Freshwater

ID012 Broad Leaf Sparsely Vegetated Coniferous Urban

ID014 Clear Fell Sparsely Vegetated GrasslandMoors Sparsely Vegetated

ID015 GrasslandMoors Urban GrasslandMoors Freshwater

ID016 GrasslandMoors Freshwater GrasslandMoors Freshwater

ID017 GrasslandMoors Mixed Sparsely Vegetated Mixed

ID019 Mixed Sparsely Vegetated Mixed Urban

ID020 Broad Leaf Sparsely Vegetated Coniferous GrasslandMoors

ID022 MiresMarshes Freshwater MiresMarshes Freshwater

ID023 MiresMarshes GrasslandMoors Mixed Freshwater

ID024 Broadleaf Urban Broad Leaf Urban

ID026 GrasslandMoors Freshwater GrasslandMoors Freshwater

ID027 GrasslandMoors Urban Sparsely Vegetated Freshwater

43 Table 6 Third order (UD50UD95) individual selectionavoidance for the GS and WS according to the Jacobs index

ID GS WS

Select Avoid Select Avoid

ID004 Broad Leaf Mixed GrasslandMoors Freshwater

ID005 Broad Leaf Freshwater Agriculture Freshwater

ID006 Clear Fell Freshwater Agriculture MiresMarshes

ID008 MiresMarshes Freshwater Agriculture Urban

ID009 Freshwater Agriculture Agriculture Freshwater

ID010 Mixed Urban Sparsely Vegetated Urban

ID012 Coniferous GrasslandMoors Freshwater Urban

ID014 Urban Agriculture Freshwater Urban

ID015 Mixed Forest Urban Clear Fell Urban

ID016 Freshwater Urban GrasslandMoors Mixed

ID017 Coniferous Mixed Coniferous Broad Leaf

ID019 Broad Leaf GrasslandMoors Urban GrasslandMoors

ID020 Freshwater Urban Freshwater Agriculture

ID022 MiresMarshes Urban Broad Leaf GrasslandMoors

ID023 Freshwater Mixed Agriculture Freshwater

ID024 Mixed Freshwater Mixed Freshwater

ID026 Mixed MiresMarshes Sparsely Vegetated GrasslandMoors

ID027 Freshwater MiresMarshes GrasslandMoors Broad Leaf

44

Fig 2 North third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)

45

Fig 3 Centre third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)

46

Fig 4 South third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)

47

Fig 5 North second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)

48

Fig 6 Centre second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)

49

Fig 7 South second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)

50

Appendix F

Background

Fig 1 Daily mean snow depth and duration during the study period (Andrew Allen)

Female Moose Reproduction

Moose are seasonal polyoestral mammals (Monfort et al 1993) coming into oestrus during late September

early October (Garel et al 2009) The Swedish moose cow population reaches puberty between the ages 25

and 35 (Sand and Cederlund 1993) during which the reproductive period begins with the onset of ovulation

The age an individual reaches puberty is dependent on their body condition they have to reach a weight

threshold to reach puberty and become reproductive (Sand 1996) If she is over the weight threshold she will

go into oestrus in the autumn If she does not reach the weight threshold then she will go into oestrus the

following autumn if successful she will give birth to individual or twin calves in late May to early June

(Ericsson et al 2001) and therefore reach sexual maturity (Malmsten et al 2014b) Fecundity is related to

both the condition and the age of the cow Cows go through senescence at 12 years of age (Ericsson et al

2001) Providing calves with the required level of nutrition demands high energy and protein resources from

the mother during senescence this becomes harder to achieve leading to decreased levels of parental care

and higher levels of calf mortality

Page 2: Habitat-performance relationships on an island: fitness ...navinderjsingh.weebly.com/uploads/1/1/2/2/11224342/... · Conditions on Öland are milder than those found in other areas

2

DECLARATION OF OWN WORK

I declare that this thesis ldquoHabitat ndash performance relationships on an island fitness landscape of moose in

Ӧland Swedenrdquo is entirely my own work and that where material was constructed by others it is fully cited

and referenced andor with appropriate acknowledgement given

This research was funded by Swedish University of Agricultural Sciences Umearing Sweden (SLU)

Data was provided by the Moose Research Group SLU

Codes were conceived and designed by Augusta Dorey Navinder Singh and Andrew Allen

Andrew Allen provided information on the migratory status of moose individuals

Jacobs Index and habitat compositional R code was written by Andrew Allen

The data was analysed by Augusta Dorey

Augusta Dorey wrote the manuscript Navinder Singh and Andrew Allen provided editorial advice

In Collaboration with Swedish University of Agricultural Sciences Umearing Sweden

Word Count 5885

Name of Supervisors

Supervisor Dr Navinder J Singh1

Assistant Supervisor Mr Andrew Allen1

Internal Supervisor Dr David Orme2

1Department of Wildlife Fish and Environmental Studies Swedish University of Agricultural Sciences

Skogsmarksgraumlnd Umearing SE-90183

2Department of Life Sciences Imperial College London Silwood Park Campus Ascot Berkshire SL57PY

3 Contents

Abstract 4

Introduction 5

Materials and Methods 7

Study area 7

Capture and Handling 8

Data Screening 8

Home rangeUtilization distribution 8

Habitat 9

Activity 10

Diet analysis 10

Survival analysis 10

Results 11

Home RangeUtilization Distribution 11

Activity 12

Habitat ndash Proportions 13

Habitat - Selection 14

Diet 17

Calf Survival 18

Discussion 19

Acknowledgements 22

References 23

Appendix A 30

Introduction 30

Appendix B 31

Method and Materials 31

Appendix C 33

Home ranges 33

Appendix D 35

Activity 35

Appendix E 36

Habitat Proportions 36

Habitat Selection 37

Appendix F 50

Background 50

4

Abstract

Moose (Alces alces) the largest among the deer have both high recreational and economic value in

Scandinavia and elsewhere To efficiently manage such a valuable species the key factors affecting their

fitness and performance must be understood Moose generally have high productivity and calf survival in

predator free areas however in recent years populations at the southern edge of their distribution such as on

the predator free island of Ӧland in Sweden there have been reports of low calf survival Individuals are found

to carry Anaplasma phagocytophilum which has been thought to be one of the factors causing the low survival

The aim of this study was to identify what abiotic and biotic factors may also be affecting female moose

performance and their calf survival GPS data from 18 collared moose was used in conjunction with home

range activity diet survival and habitat analysis Moose did not alter the size of their seasonal home ranges

or their activity level Agricultural areas and feeding stations have become the preferred areas in the core home

ranges during the winter season The diet analysis revealed that nearly two thirds of the moosersquos winter diet

contained agricultural produce Moose are having to utilise areas where in other populations individuals tend

to avoid This could probably be one of the reasons for females to be of lower quality and therefore not being

able to ensure calf survival With changing climates and human land use moose continue to be under such

environmental pressures which may therefore jeopardize their future survival and reproduction

Key Words Population dynamics Habitat selection Performance Fitness Climate Survival Alces

alces Sweden Ӧland

Image by Fredrik Stenbacka

5 Introduction

The population size of animals varies in space and time (Turchin 2001) This variation is driven by a

combination of internal as well as external factors that drive changes in survival and reproduction of

individuals (Brown 2011) Internal factors are associated with life history such as sex age body mass and

generation time whereas the external factors include climatic factors (characterised as density independent)

competition food disease (characterised as density dependent) and human influence (appendix A) Long-term

changes in population size therefore determine the long-term fitness of individuals and cohorts in a population

(Albon et al 1987) However little is known about how these factors interact to produce short and long term

variation in demography and population dynamics across space Although difficult understanding causes of

variation of population size is crucial to effective population conservation and management (Lavsund et al

2003 McLoughlin et al 2011) The interplay and relative contribution of the above factors are best shown

from species with short generation times or from long-term monitoring studies

Ungulates are most commonly studied due to their international economic and recreational value large body

sizes and the relative ease of marking handling and capturing them (Forchhammer et al 2002 Bradshaw et

al 2003 Gordon et al 2004 Clutton-Brock and Sheldon 2010) Large herbivores tend to display low fecundity

and high adult survivorship (Gaillard et al 2000a) Past studies have revealed important details about the

factors affecting their population dynamics An ungulate life cycle is usually classified based on defined age

classes new-born weaned young yearlings two-year-olds prime-aged adults and senescent adults (older than

seven years) New-born survival is highly dependent on climatic conditions predation and the level of maternal

care and condition ie quality of milk and reproductive experience (Gaillard et al 2000a Testa 2004 Baringrdsen

et al 2008) Weaned young and yearlings survival tends to be independent of the mothers care and affected

most often by climatic conditions ie severe winters disease and predation (Bartmann et al 1992) Survival

of two-year olds and adults is influenced mainly by predation (Modafferi 1997) Males generally experience a

lower survival rate than females due to the pressure of the rut and male biased hunting (Mysterud et al 2005)

Conditions experienced during a calfrsquos early development not only cause immediate effects on its future

performance but also delayed effects Calf development (weight) affects its future reproductive success

(performance) by effecting adult body size and future calf body size (Albon et al 1987 Lindstroumlm 1999

Forchhammer et al 2002)

The moose (Alces alces) is a large ungulate widely distributed across the northern hemisphere It is the largest

and only solitary member of the deer family (Cervidae) In Sweden it is found throughout the country in boreal

forests with the exception of the island of Gotland (Brandin 2009) Sweden has the largest population of moose

in Europe with approximately 300000-350000 individuals (Singh et al 2014) A part of Swedenrsquos moose

population is influenced to some extent by predators such as brown bears (Ursus arctos) and wolves (Canis

lupus) however in predator free populations individuals are influenced mainly by stochastic environmental

conditions population density traffic and above all hunting (Sӕther 1997) (appendix A) Moose are hunted

all across Scandinavia and the overall value of moose hunting is estimated to be 145 billion SEK per year

6

(158 billion Euro) (Boman et al 2011) Each year in Sweden 90000-100000 individuals are harvested

providing approximately 85 million kilograms of moose meat (Kindberg et al 2009) A common method of

selecting which individuals are to be harvested is to assess the reproductive value of an individual and remove

the lownon-reproductive individuals such as calves bulls and cows without calves (Ball et al 1999 Ericsson

et al 2001) Hunting is biased towards bulls with large trophy antlers often resulting in a skewed sex ratio

(Laurian et al 2000 Harris et al 2002 Milner et al 2007)

Moose are known to have a generally high calf survival noted through studies from predator free areas in both

North America and Europe (Linnell et al 1995 Crecircte and Courtois 1997 Swenson et al 2007) A number of

other factors are nevertheless known to affect the survival during their first summer such as climatic variation

malnutrition abandonment disease and poor maternal investment (Verme and Ullrey 1984 Gaillard et al

2000b Lomas and Bender 2007 Ericsson et al 2002 Herfindal et al 2006 Lenarz et al 2010) Low survival

in single odd years has been attributed to weather and low food quality

During recent years moose populations appear to be under environmental stress across their southern range

ascertained by studies reporting low calf survival from both North America and Sweden (Monteith et al in

press Ericsson et al submitted) A similar situation has been reported recently on the island of Oumlland in

southern Sweden where the harvesting of moose was postponed from 2001 to 2005 by mutual agreement

between hunters This was due to a fear of population collapse due to poor management strategies in previous

years that lead to a suspected unsustainable harvest The four-year harvesting break resulted in a balanced sex

ratio and age distribution (Jonsson 2007) In 2006 however it was brought to the attention of the department

of Pathology and Wildlife Diseases at the Swedish National Veterinary Institute in Uppsala (SVA) that there

was an unusually low number of calves observed on the island Malmsten (2014a) conducted a follow up study

during 2012 and 2013 and found that summer calf survival of individuals from Oumlland was only 318 and

158 respectively When compared to calf survival from two other sites in southern Sweden (Kronoberg and

Soumldermanland) with rates all above 73 for both years this figure was regarded as very worrying and

prompted a need for an in-depth exanimation of the factors determining such low calf survival With this above

rationale in mind this study investigates the habitat performance relationships of female moose on the island

of Oumlland This study also provides a model for examining the factors affecting population dynamics on an

island

7 Materials and Methods

Study area

Ӧland (567333deg N 166667deg E) a Baltic island located in Kalmar county (Fig 1) is Swedenrsquos second largest

island (~140km in length) It can be split broadly into three areas the north (N) centre (C) and south (S) There

are three typical habitats found on the island boreal forests Stora Alvaret and agricultural land The largest

portions of boreal forests are found in the far north the centre and a patch in the far south Forest stands are

dominated by birch (Betula pubescens B pendula) and Scots pine (Pinus sylvestris) with rowan (Sorbus

aucuparia) aspen (Populus tremula) grey alder (Alnus incana) and yew (Taxus baccata) interspersed

throughout with willow sp (Salix spp) in areas near water sources (Sӕther and Heim 1993) The field layer is

made up of primarily bilberry (Vaccinium myrtillus) lowbush cranberry (Vaccinium vitis-idӕa) and heather

(Calluna vulgaris) (Cederlund 1989) The patches of boreal forest in the north centre and south are isolated

from each other by agricultural areas which are distributed throughout the island particularly along the coastal

regions and the island centre The most southerly patch of forest was protected from becoming agricultural

due to its status as a royal hunting ground and an important stopover for migratory birds (Lars Edenius

personal communication April 09 2014) The southern part of Oumlland has the largest expanse of steppe-like

alvar grassland (Stora Alvaret) found in the world (~25500 ha) (Roseacuten 2006) which is found over dry shallow

nutrient-poor grazed soil (Bakker et al 1996) on top of superficial Ordovician limestone (Dengler et al 2006)

Conditions on Oumlland are milder than those found in other areas of Sweden as it is positioned in the ldquorain-

shadowrdquo of mainland Sweden (Prentice 2007) The only predators of moose found on Oumlland are hunters which

were banned from hunting in previous years

Fig 1 Location of Oumlland

8

Capture and Handling

A random sample of adult moose (n = 25) were darted sedated and equipped with GPSGSM neck collars

(Vectronic Aerospace GmbH Berlin Germany) during the winter of 2012 by the Moose Research Group

SLU Movement data were collected from GPS collars dating from 22022012 ndash 24042014 Collars were

fixed to return GPS locations approximately every 30 minutes

Data Screening

The sample contained both males and females (six males 19 females x female age = 95 years range 4-17

years) An initial inspection revealed that one female individual only returned fixed locations for a period of

eight months Locations ceased during the hunting period so the individual was presumed shot and was

removed from the data along with the males

The exact time between each location varied and sometimes no fix could be made The adehabitatLT package

(Calenge 2006) was used to standardise the data and overcome the location fixing errors The function setNA

was used to place NAs where relocations were missing The function sett0 was used to round the timing of

collection obtaining a regular trajectory with 30 minute intervals The final dataset used in the analysis

consisted of 302710 regular GPS data points from a sample size of n=18 individuals two individuals from the

north ten individuals from the centre and six individuals from the south

To address the question and to investigate the influence of climate on the space use patterns of moose the

analysis was performed at two scales The first included all annual movements of moose and the second at a

seasonal scale ie summer and winter The seasonal scales were defined according to the growing season (GS)

and winter season (WS) In Scandinavia the current method used to define the start of season (SOS) is the

period when the daily mean air temperature is above 5degC (GS) Methods of calculating SOS are advancing

with the use of the Normalized Difference vegetation Index (NDVI) becoming more popular The start and

end of the GS and WS were derived using the mean start and end dates for Oumlland suggested by the Norwegian

Meteorological Institute (DNMI) Nordic climate map report (Tveito et al 2001) The GS of this study is

defined as the period between 23-April-2012 to 07-Nov-2012 and the WS is defined as the period between 08-

Nov-2012 to 22-April-2013 (based on the current standard normal period 1961-90)

Home rangeUtilization distribution

Variation in ungulate home range size is known to be caused by changes in energy requirements and variation

in food availability (Tufto et al 1996 Kie et al 2010 Moreller et al 2013) With shifting climate causes shifts

in plant phenology and therefore the spatial and temporal distribution of ungulate food (Maringrell et al 2006)

Individuals alter their home ranges to meet their energy requirements to maintain their fitness (Albon et al

1987 White 1997 Festa-Bianchet et al 1998 Forchhammer et al 2001)

The most commonly cited definition of a home range is ldquothat area traversed by the animal during its normal

activities of food gathering mating and caring for youngrdquo (Burt 1943) This has now been expanded to

9 incorporate measures of space use using the utilization distribution (UD van Winkle 1975) which can be

described as the ldquorelative frequency distribution of an animalrsquos occurrence in all four dimensions of space

and timerdquo (Keating and Cherry 2009) Home range is viewed as a constant 2D polygon whereas UDs are

viewed as multiple 3D polygons that take into account the distribution as well as the intensity of animalrsquos

movements and space use within their home range (Kranstauber et al 2012) (see appendix A)

Estimations of each individualrsquos annual and seasonal UDs were found using the Biased Random Bridge (BRB)

kernel approach (Benhamou 2011) from the adehabitatHR package (Calenge 2006) in R It was chosen as it is

considered an improvement on the previously preferred Brownian bridge (BB) method (Horne et al 2007) The

BB is purely a diffusive movement process whereas the BRB is an advective-diffusive movement process BB

does not take into account changes in advection direction (drift) or strength BB assumes an animalrsquos

movement is purely random it moves from a starting point and ends up at the end location randomly By

adding the advection component the BRB takes into account that the animalrsquos movement is biased towards a

certain direction This allows for a more biologically relevant analysis (Benhamou and Corneacutelis 2010)

A grid was created using the minmax XY coordinates of all individuals (plusmn 10 km to increase the extent and

prevent the grid directly touching the XY locations) The resolution of the grid was fixed at a 25 m x 25 m

scale to match the resolution of the relevant habitat maps (Hagner et al 2005) By specifying these criteria the

resolution of the data remains consistent between individuals The diffusion coefficient determines the variance

in the location of the kernels between two locations This was calculated from each individualrsquos dataset using

the BRBD function and added to the BRB model (see Benhamou 2011) The strength and direction of BRB

advection can change between bridges whilst having to remaining constant To remain constant an upper Tmax

and lower Lmin time thresholds were set Successive relocations that exceeded Tmax or under Lmin were

removed from the UD calculations The 50 (UD50) and 95 (UD95) isopleths were then calculated from

the UD using the kernelarea function

Habitat

The scale of analysis was further divided following Johnson (1980) Habitat selection within the landscape

(second order selection) was studied by comparing the UD95 with available habitats in each of the three study

areas of Oumlland (UD95Area) Habitat selection within the home range (third order selection) was studied by

comparing the UD50 with the UD95 (UD50UD95)

12 habitat classes were used in the analysis agricultural land broad leaved forests clear felled areas coastal

coniferous forests freshwater areas moorsgrassland miresmarshes mixed forest sparsely vegetated areas

urban areas and younger forests The proportion of area covered by each of these habitat classes was

determined in the UD50 and UD95 Habitat data was obtained from satellite imagery generated by Svenska

Marktaumlckedata (Hagner et al 2005) The habitat maps were last updated in 2002 and have a resolution of 25

m

Compositional analysis ( habitat used habitat available) (Aebischer 1993) was used in conjunction with

the Jacobrsquos index (D) (eqn1) to quantify habitat selection (Jacobs 1974) Coastal areas were removed as not

10

all home ranges contained them This combined approach allowed identification of habitats that are used

disproportionally to their availability ie in a non-random manner (Beyer et al 2010) This is an indication of

which habitats are important for an individual

119863 = ( 119903minus119901

119903+119901minus2119903119901 ) (eqn1)

r = Proportion of habitat type used

p = Total proportion of habitat available

D = Jacobs index varies from -1 (strong avoidance) to +1 (strong preference) with values close to 0 indicating

the habitat is used in proportion to its availability

Activity

Activity level is measured as the mean daily movement (MDM) by the individual to investigate if individuals

in an areaseason moved more and hence were more active than those in other areasseasons Unfortunately

only two cows were collared in the north and were therefore left out of this analysis Moose were identified as

migratory using a modelling approach (see Bunnefeld et al 2011 for methods) Migratory individuals were

initially removed from the activity analysis (n=4)The reason is that both migratory journeys were completed

during the winter season thus increasing the mean daily distance travelled and potentially biasing the analysis

One individual was also removed due it its collar not returning relocations during the entirety of the WS

Diet analysis

The Ӧland project team conducted histology diet analysis on the rumen content of five individuals that were

shot in the centre and south of the island during the WS of 2013

Survival analysis

The Ӧland project team measured calf survival using the mark-resight method The presenceabsence of a calf

was recorded by tracking the cows at six occasions throughout the year These were at the start of the calving

season (mid-May to early June) twice through the summer before the hunt after the hunt and after winter

Survival trend was estimated using a Kaplan-Meier curve (Kaplan and Meier 1958) The Kaplan-Meier curve

shows the survival function (S (t)) ie the probability of an individual surviving until at least time t (Bewick

et al 2004) The probability of surviving from one period to the next is multiplied together to give the survival

function The S(t) of this study is the probability of an individual surviving from birth to after the hunt

(Method summary see appendix B)

11 Results

Home RangeUtilization Distribution

A total of 51 home ranges were estimated (17 annual 17 within growing season 17 within winter season)

Annual x = 9613 ha GS x = 6345 ha and WS x = 6023 ha (appendix C)

At the UD50 scale the largest annual and seasonal mean home ranges were located in the north Mean annual

and seasonal home ranges in the centre were slightly larger than the south This difference was not significant

(F(113)= 22 p= 87) (ANOVA) There was no significant difference between the seasonal home ranges (x

plusmnSD for GS = 116 plusmn38 for WS = 98 plusmn32 ha) (t(11) = 105 p = 32) or the seasonal home ranges in the centre

(t(8) = 101 p = 34 and the south (t(5) = 87 p = 42) (paired-sample t-test) (Table 1)

At the UD95 scale the largest annual and WS mean home ranges were located in the north The largest GS

mean home ranges were located in the centre Mean annual and seasonal home ranges in the centre were

slightly larger than the south This difference was not significant (F(113) = 59 p = 63) (ANOVA) There

was no significant difference between the seasonal home ranges (x plusmnSD for GS = 635 plusmn225 for WS = 602

plusmn161) (t(11) = 373 p = 71) or the seasonal home ranges in the centre (t(8)= 20 p = 84) or south (t(5) = 34

p = 74) (paired-sample t-test) (Table 1)

Table 1 Seasonal and annual mean UD50 and UD95 BRB kernel area in hectares (1ha = 001km2) for the north centre

and south of Oumlland (smoothing factor (h) =100)

Are

a

Annual UD50 GS UD50 WS UD50

n Mean SD Range n Mean SD Range n Mean SD Range

N 2 209 49 139-279 2 1215 39 67-176 2 1615 106 160-163

C 9 178 56 114-277 9 116 44 48-165 9 943 4 61-173

S 6 160 21 142-177 6 1085 51 65-149 6 933 35 69-125

Annual UD95 GS UD95 WS UD95

N 2 10905 5 1084-1097 2 630 199 349-911 2 809 11 794-824

C 9 997 32 682-1536 9 6531 22 295-945 9 637 17 454-941

S 6 9298 30 605-1088 6 5985 373 442-575 6 5526 20 349-679

12

Activity

MDM rates in the three areas (sedentary individuals) during the GS ranged from 14 ndash31 km day During the

WS ranged they ranged from 11-24 km day (Table 2) Movement rates during the GS were higher than the

WS (x plusmnSD for GS = 202 plusmn043 for WS = 161 plusmn043) but it was not statistically significant (t(11) = 200 p=

07) (paired sample t-test)

Table 2 Seasonal mean daily movement rates (km day) for each area and for both areas (total)

Are

a

GS WS

n Mean SE Range n Mean SE Range

C 8 20 003 14-18 8 20 004 12-24

S 4 22 016 17-31 4 12 02 11-13

Total 12 202 003 14-31 12 16 003 11-24

The seasonal MDM rates of all individuals (migratory and sedentary) were not significantly different (x plusmnSD

for GS = 20 plusmn04 for WS = 18 plusmn061) (t(14) = 139 p= 19) (paired sample t-test)

The WS home range size affects the WS MDM (F(110) = 927 p = 01) (ANOVA) The GS home range size

does not affect the GS MDM (F(110) = 36 p = 56) (ANOVA) When the WS home range outlier was

removed the home range size did not affect the WS MDM (F(111) = 186 p= 19) (ANOVA) The MDM was

lowest in February and highest in April (Table 3) there appeared to be no significant pattern in MDM between

the months (appendix D)

Table 3 Mean daily distance moved (km day) for sedentary individuals

Month Season Distance

April GS 0051

May GS 0044

June GS 0039

July GS 0041

August GS 0042

September GS 0044

October GS 0043

November WS 0043

December WS 0038

January WS 0035

February WS 0028

13 Habitat ndash Proportions

The largest proportion of habitat on the island is agriculture the lowest proportion of habitat (excluding coastal

and freshwater) is urban areas (Fig 2) The largest proportion of habitat in the north was coniferous forests

whilst agricultural areas were the dominant habitat types in the centre and south (Fig 3) The lowest proportion

(excluding coastal and freshwater areas) was urban

Fig 2 Proportion of different types of habitats found on Ӧland

Fig 3 Mean proportion of habitats contained within UD95 in the three areas of Oumlland C = Centre N = North S =

South

14

Habitat - Selection

Generally forest habitat types are the highest ranked whilst sparsely vegetated and urban areas are the lowest

ranked Both the second and third order habitat selection analyses gave significant results in the compositional

analysis (Table 4) In the third order analysis (UD50UD95) the centre displayed significant differences

between habitat types The coniferous forests are significantly preferred to sparsely vegetated areas and the

sparsely vegetated areas are significantly preferred to urban areas In the second order analysis (UD95Area)

significance was observed in the north and centre In the north younger forests are significantly preferred to

miresmarshes clear felled areas are significantly preferred to agriculture and freshwater areas are significantly

preferred to sparsely vegetated areas In the centre clear felled areas are significantly preferred to agricultural

land freshwater areas are significantly preferred to urban areas and grasslandmoors are significantly preferred

to sparsely vegetated areas

Table 4 Summary of second (UD95Area bottom) and third order (UD50UD95 top) ranked habitat preferences between

the three areas according to the compositional analysis (see appendix B)

Rank North Centre South

1 Broad Leaf Younger Coniferous

2 Mixed Broad Leaf Younger

3 MiresMarshes Clear Fell GrasslandMoors

4 Younger Mixed Clear Fell

5 Clear Fell GrasslandMoors Mixed

6 Coniferous MiresMarshes Broad Leaf

7 Freshwater Agriculture Freshwater

8 Agriculture Coniferous Agriculture

9 Sparse Veg Sparse Veg MiresMarshes

10 GrasslandMoors Urban Sparse Veg

11 Urban Freshwater Urban

Rank North Centre South

1 Broad Leaf Mixed Coniferous

2 Mixed Younger Clear Fell

3 GrasslandMoors Broad Leaf Younger

4 Younger Coniferous GrasslandMoors

5 MiresMarshes Clear Fell Agriculture

6 Coniferous Agriculture MiresMarshes

7 Clear Fell MiresMarshes Broad Leaf

8 Agriculture Freshwater Freshwater

9 Urban Urban Sparse Veg

10 Freshwater GrasslandMoors Mixed

11 Sparse Veg Sparse Veg Urban

Indicates significantly preferred to the habitat below (significant deviation from random at P lt05)

15 The Jacobs index revealed that generally the habitats preferred during the GS within the home range (third

order) are younger (0187) and broad leaf forests (0154) The strongest avoidance was for urban areas (-0627)

During the WS only agricultural areas are preferred (0129) and the strongest avoidance was for urban areas (-

0393) (Fig 4)

Fig 4 Third order seasonal habitat preference (UD50UD95) all individuals The index ranges from -1 (total avoidance)

to 1 (strongest preference) Close to 0 indicates used in proportion to its availability

Third order habitat preferencesavoidances by area

North During the GS the strongest preference was for broad leaf (0218) and mixed forests (0161) The

strongest avoidance was for urban (-1) and sparsely vegetated areas (-05) During the WS the strongest

preference was for miresmarshes (0228) The strongest avoidance was for grasslandmoors (-05)

Centre During the GS the strongest preference was for broad leaf (0233) and younger forests (0223) The

strongest avoidance was for urban (-0527) and agricultural land (-0362) During the WS preference was only

shown for agricultural land (0327) The strongest avoidance was for urban areas (-0679) and miresmarshes

(-0638)

South During the GS the strongest preference was for coniferous (0312) and younger forests (0242) The

strongest avoidance was for urban (-0353) and sparsely vegetated areas (-0330) During the WS

grasslandmoors (0106) were the strongest preference The strongest avoidance was for urban (-0666) and

sparsely vegetated areas (-0351)

16

The Jacobs indices revealed that generally the habitats preferred during the GS within the landscape

(UD95Area) are broad leaf (0216) and younger forests (0201) The strongest avoidance was for urban (-

0717) and freshwater areas (-0694) The strongest preference during the WS are coniferous forests (0242)

and the strongest avoidance was for freshwater (-0674) and urban areas (-0648) (Fig 5)

Fig 5 Second order seasonal habitat preference (UD50UD95) all individuals The index ranges from -1 (total avoidance)

to 1 (strongest preference) Close to 0 indicates used in proportion to its availability

Second order habitat preferencesavoidances by area

North During the GS the strongest preference was for broad leaf (0363) and mixed forests (00291) The

strongest avoidance was for sparsely vegetated (-0909) and freshwater areas (-0780) During the WS mixed

(0335) and coniferous forests (0316) were the strongest preference The strongest avoidance was for

freshwater (-0731) and urban areas (-05333)

Centre During the GS the strongest preference for mixed (0394) and younger forests (0286) The strongest

avoidance was for urban (-0733) and sparsely vegetated (-0708) areas During the WS mixed (0404) and

coniferous forests (0255) were the strongest preference The strongest avoidance was for freshwater (-0704)

and sparsely vegetated areas (-0655)

South During the GS the strongest preference for grasslandmoors (0287) and clear fells (0165) The

strongest avoidance was for urban areas (-0678) and mixed forests (-0491) During the WS grasslandmoors

(0425) and coniferous forests (0154) were the strongest preference The strongest avoidance was for urban (-

0876) and freshwater areas (-0587) (appendix E)

17 Diet

Diet analysis of the rumen content sampled from five individuals (C=2 S=3) revealed that almost two thirds

(69) of the diet is comprised of agricultural produce (apple winter rape and sugar beet) (Fig 6)

Fig 6 Diet analysis from the rumen samples of five moose individuals that were culled in 2013

31

2117

9

8

5

22

1 1

1

1

1 00 0

0

0Diet (2610-911 2013 5 individuals)

AppleWinter RapeSugar BeetUndefined WoodSallowBroad-leaf GrassPineAshOakCloverCurrantsUndefined plantElderberryJuniperRaspberry

18

Calf Survival

Of the 18 individuals 13 produced calves in which 7 produced twins giving a total of 20 calves A Kaplan-

Meier estimate was conducted to measure the fraction of calves living up to each period of the study (Fig 7)

The mean survival time is until period 235 (midend of summer) At the start of summer 85 of calves

remained (3 still born) The period between summer and before the hunt survival drops to 30 The survival

at the end of the study (after hunt) drops further to 20 leaving 4 calves surviving (see appendix B)

Fig 7 Kaplan-Meier estimate of moose calf survival during the study period Period 0 (Start of summer) period 1

(midend of summer) period 2 (before hunt) period 3 (after hunt) period 4 (after winter)

19 Discussion

The results of this study emphasised how strikingly different the habitat composition is along the latitudinal

gradient of Oumlland The three areas show contrasting proportions of the key habitat types The starkest

difference is the high proportion of coniferous forests and lack of agriculture in the north compared to the

centre and south The proportion of coniferous forest in the north is almost 5 times greater than in the centre

and south whereas the proportion of agriculture in the centre and south is more than double that in the north

The north is perceived to be composed of the most suitable habitat for moose (Dussault et al 2006) It has the

largest proportions of each forest type and a low proportion of agricultural land This provides suitable forage

and shelter throughout the year The south has a contrasting habitat composition to the north The proportions

of agricultural and sparsely vegetated areas are the highest between the three areas and the proportions of forest

habitats are the lowest The large proportion of sparsely vegetated areas and low proportions of forest habitat

corresponds to the large area of Stora Alvaret This is perceived to be the least suitable area due to a lack of

shelter (coniferous forest) and suitable forage The strong preference for coniferous and younger forest habitats

in the south would suggest that moose exhibit a functional response in habitat selection (Godvik et al 2009)

ie as the proportion of a particular habitat decreases the selection for that habitat increases in this case

coniferous forests which provide shelter and younger forest which provide good forage Similarly in the centre

moose show strong preference for mixed forests a habitat that is of low proportion

In view of the large variation in habitat proportions between the areas it is surprising that there is not a large

variation in the home range sizes or the activity levels annually or seasonally Home ranges are ultimately

chosen to maximise fitness and meet energy requirements by utilizing the available forage Seasonal conditions

change the availability and necessity of resources (food quality shelter) Unlike the GS during the WS

deciduous trees and shrubs are leafless and low-lying shrubs are under snow cover (Dussault et al 2005)

These changes are well known to cause populations to alter their activity and home ranges to meet energy

requirements (Mysterud et al 2001) Populations have been shown to increase or decrease their home ranges

during the two seasons The GS home ranges are often larger than the WS home ranges (Philips et al 1973

Mysterud et al 2001) In some cases they can be found to be almost double the size of the WS home ranges

(Cederlund and Okarma 1988) In other populations the WS home ranges are double the size of the GS home

ranges (Lynch and Morgantini 1984) or sizes do not significantly differ (Cederlund and Sand 1994)

Previous studies on moose find females generally show increased activity from the start on the GS due to

various factors eg reduced ruminating times increased metabolic needs and increased foraging bursts

(Wattles and DeStefano 2013) Increased metabolic needs during this time are a results of pregnancy and

lactation (Georgii 1980) During the height of the GS they usually show reduced activity levels through times

of increased thermal stress (Renecker and Hudson 1989 van Beest et al 2012) During the WS the depth and

the duration of snow cover are well known to affect the activity level (Telfer 1970 Mysterud and Oslashstbye 1999

Bjoslashrneraas et al 2011) During the WS generally home ranges are smaller and activity less due to lower

metabolic needs Moose activity is constrained by rumination during the WS this period is known to be longer

due to the change in diet (Cederlund 1989 Renecker Hudson 1989) This was not the case on Ӧland activity

20

was lowest in February which is a similar result to Cederlundrsquos (1989) paper However Ӧland moose did not

significantly alter their seasonal activity levels The fact that the annual and seasonal activity levels and home

ranges were similar could be a result of the mild winters on Oumlland during the study period (Smhise 2014)

During the study period the average number of snow days was 80 and the mean snow depth was 10cm

(appendix F) (Swedish Meterological and Hydrological Institute- SMHI) These mild conditions do not restrict

the movement of moose or obscure forage Moose are well adapted for movement in deep snow depths of 60-

86cm (Prescott 1968) are needed to truly restrict movement This finding was similar to the Sweanor and

Sandegren (1989) and Cederlund and Sand (1994) where the snow depth at their sites did not reach movement

restricting depths

The survival curve illustrates just how bad the calf survival is on Ӧland Survival falls from 85 at the start to

20 Out of 20 calves only four were alive at the end of the study The sharpest fall in survival was the period

between end of summer and before the hunt so the deaths were not due to hunting Previous calf autopsies

(Malmsten 2014a) have shown that cause of death was starvation mothers possibly either did not have milk

the calf was unable to feed or the mother abandoned the calf Closer field based observations are needed to

attain this knowledge Moose are seasonal polyoestral mammals (Monfort et al 1993) coming into oestrus

during late September early October (Garel et al 2009) (appendix F) The diet of the mother influences the

health of the calf and this period is when sodium is hard to find sodium is a key mineral in moose diets for

features such as reproduction (Belovsky and Jordan 1981) Moose gain sodium mainly through aquatic plants

(MacCracken et al 1993) However the compositional analysis shows that freshwater areas are often ranked

as one of the lowest used habitats and coastal areas were removed as the proportion found in the home ranges

was extremely low The Jacobs Index shows that the moose only prefer freshwater areas in the north UD50

during the WS The north individuals again are those that are showing typical moose habitat selection

It is known that habitat selection is hierarchical with habitats that increase fitness selected for and the effects

of limiting factors are reduced (Rettie and Messier 2000) At the UD95 during the GS moose preferred areas

of good forage (forests) and avoided areas of low forage (freshwater and sparsely vegetated areas) and areas

close to humans (urban) This is consistent with other reports (Laurian et al 2008 Torres et al 2011) Within

the UD50 there is a shift in preferences The good forage areas are again preferred during the GS however

during WS the only preferred habitat is often agricultural land During the WS there could be a steady supply

of supplementary feed available hence the high levels of agricultural produce found in the rumen content

samples and the high preference of agricultural areas This diet is unusual for moose previous studies of

Swedish moose diet have found the GS diet was dominated by birch willow and herbaceous plants and the

WS diet dominated by pine and birch (Cederlund and Nystrom 1981) The diet analysis was conducted during

the WS instead of being dominant pine composed just 2 Birch did not appear however unidentified wood

composed only 9 whereas agricultural produce accounted for 69 Supplementary feed may be perceived

by the moose in the centre and south as a vital forage source during the WS In fact in the centre the

agricultural land is the only preferred habitat at the UD50 It is unknown whether there are salt licks provided

in these areas Selection for a critical habitat is often thought to be a fixed factor The Oumlland population from

21 the three areas are close in proximity however they displayed contrasting preferences This is supported by the

Osko et al (2004) report that found two neighbouring moose populations that had access to the same habitats

displayed contrasting preferences Habitat preferences for populations of the same species are not necessarily

fixed They alter with varying levels of habitat abundance and limiting factors skewing what is preserved to

be critical

The main limitation encountered in this study was with the limited sample There was only data on two

individuals from the north of the island which led it being removed from many of the analysis Similarly due

to a lack of relocations from the collars being turned off at points throughout the year two further individuals

had to be removed from a majority of the analysis This reduced the sample size to 17 or 18 individuals

Similarly only 13 of the individuals from the study produced calves This unfortunately prevented including

survival into models Although the sample size was small it was accurate it was of high resolution over

300000 GPS points In future it would be beneficial to have a more standardised data set An equal sample of

individuals from the three areas would be advised along with ensuring the GPS collars are kept turned on for

the entirety of the growing and winter season to allow comparisons between years It would also be

advantageous to collect coordinates of the feeding sites along with the composition This could then be

compared with high use UD coordinates to look if moose are truly spending a majority of their foraging time

at feeding stations A study on the population densities of moose and the increasing population of roe deer

(Capreolus capreolus) would add the factor of competition into the model

The low calf survival on Ӧland is most likely the result of a combination of factors The lack of suitable habitat

reported in this study in conjunction with Malmstenrsquos (2014a) report on the threat of disease (Anaplasma

phagocytophilum) are probable influences on the calf survival on Ӧland On Ӧland there is an increasing

population of roe deer and large numbers of migratory birds both carriers of ticks and diseases The mild

conditions on Ӧland are advantageous for ticks the carriers of A phagocytophilum Fewer snow days and

shorter periods of snow cover along with dry conditions are favourable for ticks This could probably be one

of the reasons for females to be of lower quality and therefore not being able to ensure calf survival Moose

have to utilise areas where in other populations individuals tend to avoid Finally similar to many studies I

advocate further research using a stronger dataset and longer term monitoring

22

Acknowledgements

I am indebted to NJ Singh and A Allen for all their help and guidance through the whole of this study I

thank SLU for the support provided during this study in terms of data finances and facilities Thank you to

everyone at the Department of Wildlife Fish and Environmental Studies for being so friendly and

supportive I would like to thank L Edenius for driving me around the study area and S Michon and H

Khalil for keeping me sane with fika and training

23 References

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Albon SD Clutton-Brock TH Guinness FE (1987) Early development and population dynamics in red deer

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Bakker JP Bakker ES Roseacuten E Verweij GL Bekker RM (1996) Soil seed bank composition along a

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Benhamou S Corneacutelis D (2010) Incorporating movement behaviour and barriers to improve kernel home

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Bradshaw RHW Hannon GE Lister AM (2003) A long-term perspective on ungulate-vegetation

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24

Bunnefeld N Boumlrger L van Moorter B Rolandsen CM Dettki H Solberg EJ Ericsson G(2011) A model-

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Cooke SJ Hinch SG Wikelski M Andrews RD Kuchel LJ Wolcott TG Butler PJ (2004) Biotelemerty a

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Ericsson G Malmsten J Neumann W Singh NJ Dali AM Submitted Summer Calf Survival of

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reproductive costs in a capital breeder The American Naturalist 152367-379

Forchhammer MC Clutton-Brock TH Lindstroumlm J Albon SD (2001) Climate and population density induce

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dynamics to changes in climatic trophic processes Population Ecology 44113-120

Gaillard JM Festa-Bianchet M Yoccoz NG (1998) Population dynamics of large herbivores variable

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Gaillard JM Festa-Bianchet M Yoccoz NG Loison A Toiumlgo C (2000a) Temporal variation in fitness

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Systematics 31367-393

Gaillard JM Festa-Bianchet M Delorme D Jorgenson J (2000b) Body mass and individual fitness in female

ungulate bigger is not always better Proceedings Biological Sciences 267471-477

Gaillard JM Hearingblewhite M Loison A Fuller M Powell R Basille M van Moorter B (2010) Habitat-

performance relationships finding the right metric at a given Spatial scale Philosophical

Transactions of the Royal Society B 3652255-2265

Garel M Solberg EJ Sӕther B-E Groslashtan V Tufto J Heim M (2009) Age size and spatiotemporal variation

in ovulation patterns of a seasonal breeder the Norwegian moose (Alces alces) The American

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Georgii B (1980) Home range patterns of female red deer (Cervus elaphus L) in the Alps Oecologia

47278-285

Godvik IMR Loe LE Vik JO Veiberg V Langvatn R Mysterud A (2009) Temporal scales trade-offs and

functional responses in red deer habitat selection Ecology 90699ndash710

Gordon IJ Hester AJ Festa-Bianchet M (2004) Review The management of wild large herbivores to meet

economic conservation and environmental objectives Journal of Applied Ecology 411021-

1031

Hagner O Nilsson M Reese H Egberth M Olsson H (2005) Procedure for classification of forests for

CORINE land cover in Sweden In Oluić M (ed) New strategies for European remote sensing

Millpress Rotterdam pp 523ndash530

Hall LS Krausman PR Morrison ML (1997) The habitat concept and a plea for standard terminology

Wildlife Society Bulletin 25173-182

Harris RB Wall WA Allendorf FW (2002) Genetic consequences of hunting what do we know and what

should we do Wildlife Society Bulletin 30634-643

Herfindal I Saeligther B-E Solberg EJ Andersen R Hoslashgda KA (2006) Population characteristics predict

responses in moose body mass to temporal variation in the environment Journal of Animal

Ecology 75 (5) 1110-1118

Horne JS Garton ED Krone SM Lewis JS (2007) Analysing animal movements using Brownian bridges

Ecological Society of America Ecology 882354-2363

Hornok S Kovaacutets D Csoumlrgo T Meli M Goumlnczi E Hadnagy Z Takaacutecs N Farkas R Hofmann-Lehmann R

(2014) Birds as potential reservoirs of tick-borne pathogens first evidence of bacteraemia

with Rickettsia Helvetica Parasites and Vectors 7128

26

Jacobs J (1974) Quantitative measurement of food selection a modification of the forage ratio and Ivlevrsquos

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Jenkins KJ Manly FJ (2008) A double-observer method for reducing bias in faecal pellet surveys of forest

ungulates Journal of Applied Ecology 451339-1348

Johnson DH (1980) The comparison of usage and availability measurements for evaluating resource

preference Ecology 6165-71

Jonsson F (2007) rsquoDen oumllaumlndska aringlgstammens foumlrvaltingrsquo Departement of Wildlife Fish and Environmental

Studies SLU Examensarbete I aumlmnet biologi vol 20072

Kaplan EL Meier P (1958) Nonparametric estimation from incomplete observation Journal of the American

Statistical Association 53457-481

Keating KA Cherry S (2009) Modelling utilization distributions in space and time Ecology 90(7)1971-

1980

Kie JG Matthiopolos J Fieberg J Powell RA Cagnacci F Mitchell SM Gaillard JM Moorcroft PR (2010)

The home range concept are traditional estimators still relevant with modern telemetry

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Jaumlgarefoumlrbundet Oumlster-Malma 20092

Kranstauber B Kays R LaPoint SD Wikelski M Safi K (2012) A dynamic Brownian bridge movement

model to estimate utilization distributions for heterogeneous Animal movement Journal of

Animal Ecology 81738-746

Laurian C Ouellet JP Courtois R Breton L St-Onge S (2000) Effects of intensive harvesting on moose

reproduction Journal of Applied Ecology 37515-531

Laurian C Dussault C Ouellet JP Courtois R Poulin M Breton L (2008) Behaviour of moose relative to a

road network The Journal of Wildlife Management 72(7)1550-1557

Lavsund S Nygreacuten T Solberg EJ (2003) Status of moose populations and challenges to moose management

in Fennoscandia Alces 39109-130

Lenarz MS Fieberg J Schrage MW Edwards AJ (2010) Living on the edge viability of moose in

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14343-348

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mortality of temperate ungulates Wildlife Biology 1209-223

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Lynch GM Morgantini LE (1984) Sex and age differential in seasonal home range size of moose in

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MacCracken JG Ballenberghe VV Peek JM (1993) Use of aquatic plants by moose sodium hunger or

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27

Malmsten J Wideacuten DG Rydevik G Yon L Hutchings MR Thulin CG Soumlderquist L Aspan A Stuen S

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University of Agricultural Sciences (SLU) Umearing

Malmsten J Soumlderquist L Thulin C Wideacuten DG Yon L Hutchings MR Dalin A (2014b) Reproductive

characteristics in female Swedish moose (Alces alces) with emphasis on puberty timing of

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Marsh DM Hanlon TJ (2004) Observer gender and observation bias in animal behaviour research

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28

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29

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van Beest FM van Moorter B Milner JM (2012) Temperature-mediated habitat use and selection by a heat

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Management 39118-123

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Halls LK) pp 91-118 Stackpole Harrisburg Pennsylvania

Wattles DW DeStefano (2013) Space use and movements of moose in Massachusetts Implications for

conservation of large mammals in a fragmented environment Alces 4965-81

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success in muskoxen Journal of Zoology 24313-20

30

Appendix A

Introduction

Fig 1 Summary chart of factors affecting the life history and therefore the long term fitness of a population

Fig 2 Summary chart 2

Movement

Habitat

Climate

Topography

Competition

FoodWater

Disease

Die

Survive

Reproduce

Population long term fitness

31 Appendix B

Method and Materials

Fig 1 Summary of processes

32

Fig 2 Examples of classical kernel home range output and Brownian bridge kernel home range (Calenge 2011) The

right image includes the area between relocations ie the movement path in contrast to the classic kernel home range

in the left image

33 Appendix C

Home ranges

Fig 1 Example of a non-migratory (ID006) individuals BRB kernel area From top left annual growing and winter

season UD50 (black contour) and UD95 (red contour)

Fig 2 Example of a migratory (ID012) individuals BRB kernel area From the left annual growing and winter season

UD50 (black contour) and UD95 (red contour)

34

Table 1 Annual and seasonal UD50 and UD95 areas (ha) for all individuals

ID Annual GS WS

UD50 UD95 UD50 UD95 UD50 UD95

ID004 190 924 93 531 173 941

ID005 230 1364 132 945 72 682

ID006 162 1036 89 736 70 611

ID008 277 1536 156 809 78 738

ID009 137 834 48 295 126 653

ID010 114 682 83 448 96 488

ID012 177 963 123 544 76 545

ID014 160 1018 87 575 89 662

ID015 172 858 128 532 109 679

ID016 156 1047 65 455 92 534

ID017 153 1088 149 1043 69 349

ID019 279 1097 176 911 163 824

ID020 139 1084 67 349 160 794

ID022 159 811 131 638 61 454

ID023 187 1061 147 771 72 705

ID024 146 725 165 705 101 458

ID026 142 605 99 442 125 547

ID027 126 567 75 461 48 277

35 Appendix D

Activity

Fig 1 Mean daily movement during the study period GS 23-April-2012 to 07-Nov-2012 WS 08-Nov-2012 to

22-April-2013 (number indicates month)

Fig 2 Mean daily movement in the centre and south during the GS and WS

36

Appendix E

Habitat Proportions

Fig 1 All individualsrsquo seasonal habitat proportions within the UD95

37 Habitat Selection

Table 1 Simplified ranking matrices comparing proportional habitat use within the second order (UD95Area) with

proportions of total available habitat types Mean value on the matrix was replaced by a sign a triple sign represents

significant deviation from random at P lt05 Highlighted habitat is ranked 1st

North A

gri

cult

ure

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 --- --- - +++ --- --- --- +++ +++ --- 8

Broad Leaf +++ 0 +++ + +++ +++ +++ + +++ +++ +++ 1

Clear Fell +++ --- 0 + +++ - - --- +++ +++ --- 7

Coniferous + - - 0 +++ - - --- +++ +++ - 6

Freshwater --- --- --- --- 0 --- --- --- +++ - --- 10

Grassland

Moors +++ --- + + +++ 0 +++ - +++ +++ + 3

MiresMarshes +++ --- + + +++ --- 0 - +++ +++ --- 5

Mixed +++ - +++ +++ +++ + + 0 +++ +++ + 2

Sparse Veg --- --- --- --- --- --- --- --- 0 --- --- 11

Urban --- --- --- --- + --- --- --- +++ 0 --- 9

Younger +++ --- +++ + +++ - +++ - +++ +++ 0 4

Rank Order and

Significance

Broad Leafgt Mixedgt GrasslandMoorsgt Youngergtgtgt MiresMarshesgt Coniferousgt

Clear Fellgtgtgt Agriculturegtgtgt Urbangt Freshwatergtgtgt Sparse Veg

Central

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 --- --- --- + +++ + --- +++ +++ --- 6

Broad Leaf +++ 0 +++ + +++ +++ + - +++ +++ - 3

Clear Fell +++ --- 0 - +++ +++ + --- +++ +++ --- 5

Coniferous +++ - + 0 +++ +++ + --- +++ +++ - 4

Freshwater - --- --- --- 0 +++ - --- +++ +++ --- 8

Grassland

Moors --- --- --- --- --- 0 --- --- +++ - --- 10

MiresMarshes - - - - + +++ 0 - +++ +++ - 7

Mixed +++ + +++ +++ +++ +++ + 0 +++ +++ + 1

Sparse Veg --- --- --- --- --- --- --- --- 0 - --- 11

Urban --- --- --- --- --- + --- --- + 0 --- 9

Younger +++ + +++ + +++ +++ + - +++ +++ 0 2

Rank Order and

Significance

Mixedgt Youngergt Broad Leafgt Coniferousgt Clear Fellgtgtgt Agriculturegt

MiresMarshesgt Freshwatergtgtgt Urbangt GrasslandMoorsgtgtgt Sparse Veg

38

South

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 + - - + - + +++ +++ +++ - 5

Broad Leaf - 0 - - + - - +++ + +++ - 7

Clear Fell + + 0 - + + + +++ + +++ + 2

Coniferous + + + 0 +++ + + +++ + +++ + 1

Freshwater - - - --- 0 - - + + +++ - 8

Grassland

Moors + + - - + 0 + + +++ + - 4

MiresMarshes - + - - + - 0 +++ + +++ - 6

Mixed --- --- --- --- - - --- 0 + + --- 10

Sparse Veg --- - - - - --- - - 0 + - 9

Urban --- --- --- --- --- - --- - - 0 --- 11

Younger + + - - + + + +++ + +++ 0 3

Rank Order

and

Significance

Coniferousgt Clear Fellgt Youngergt GrasslandMoorsgt Agriculturegt MiresMarshesgt Broad Leafgt

Freshwatergt Sparse Veggt Mixedgt Urban

Table 2 Simplified ranking matrices comparing proportional habitat use within the third order (UD50UD95) with

proportions of total available habitat types Mean value on the matrix was replaced by a sign a triple sign represents

significant deviation from random at P lt05 Highlighted habitat is ranked 1st

North

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 --- --- --- - + --- --- + +++ --- 8

Broad Leaf +++ 0 +++ + + + + + +++ +++ + 1

Clear Fell +++ --- 0 + + + - - + +++ - 5

Coniferous +++ - - 0 + + --- --- +++ +++ - 6

Freshwater + - - - 0 +++ - - +++ +++ - 7

GrasslandMoors - - - - --- 0 - - - + - 10

MiresMarshes +++ - + +++ + + 0 - +++ +++ + 3

Mixed +++ - + +++ + + + 0 +++ +++ + 2

Sparse Veg - --- - --- --- + --- --- 0 +++ --- 9

Urban --- --- --- --- --- - --- --- --- 0 --- 11

Younger +++ - + + + + - - +++ +++ 0 4

Rank Order and

Significance

Broad Leafgt Mixedgt MiresMarshesgt Youngergt Clear Fellgt Coniferousgt Freshwatergt

Agriculturegt Sparse Veggt GrasslandMoorsgt Urban

39

Central

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 --- --- + + - - - + +++ --- 7

Broad Leaf +++ 0 + +++ + + + + + +++ - 2

Clear Fell +++ - 0 +++ + + + + + +++ - 3

Coniferous - --- --- 0 + - - --- +++ + --- 8

Freshwater - - - - 0 --- - - --- - - 11

GrasslandMoors + - - + +++ 0 + - + +++ - 5

MiresMarshes + - - + + - 0 + + +++ - 6

Mixed + - - +++ + + - 0 +++ +++ - 4

Sparse Veg - - - --- +++ - - --- 0 +++ - 9

Urban --- --- --- - + --- --- --- --- 0 --- 10

Younger +++ + + +++ + + + + + +++ 0 1

Rank Order and

Significance

Youngergt Broad Leafgt Clear Fellgt Mixedgt GrasslandMoorsgt MiresMarshesgt

Agriculturegt Coniferousgtgtgt Sparse Veggtgtgt Urbangt Freshwater

South

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 - - - - - + - +++ + --- 8

Broad Leaf + 0 - --- + - + - +++ + - 6

Clear Fell + + 0 - + - + - +++ + - 4

Coniferous + +++ + 0 + + +++ + +++ + + 1

Freshwater + - - - 0 - - + + + - 7

GrasslandMoors + + + - + 0 + + + + - 3

MiresMarshes - - - --- + - 0 - + + - 9

Mixed + + + - - - + 0 + + - 5

Sparse Veg --- --- --- --- - - - - 0 + --- 10

Urban - - - - - - - - - 0 - 11

Younger +++ + + - + + + + +++ + 0 2

Rank Order and

Significance

Coniferousgt Youngergt GrasslandMoorsgt Clear Fellgt Mixedgt Broad Leafgt Freshwatergt

Agriculturegt MiresMarshesgt Sparse Veggt Urban

40

Table 3 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the GS according to Jacobs index

Ran

k North Centre South

50 95 50 95 50 95

+ - + - + - + - + - + -

1 Broad

Leaf Urban Broad Leaf Sparse Veg

Broad

Leaf Urban Mixed Urban Coniferous Urban

Grassland

Moors Urban

2 Mixed Sparse Veg Mixed Freshwater Younger Agriculture Younger Sparse Veg Younger Sparse Veg Clear Fell Mixed

3 Mires

Agriculture Grassland

Urban Clear

Fell Coniferous Broad Leaf

Grassland

Moors

Clear Fell Agriculture Coniferous Sparse Veg

Marshes Moors

4 Younger Grassland

Younger Agriculture

Freshwater Coniferous Freshwater

Broad Leaf Mires

Younger Freshwater

Moors Marshes

5 Clear

Fell Freshwater

Mires Coniferous

Sparse Veg Clear Fell Agriculture

Freshwater Agriculture

Marshes

6 Coniferous Clear Fell

Mires

Marshes

Mires

Grassland

Moors

Mires

Marshes Marshes

7 Mixed Mixed Broad Leaf

8 Grassland

Moors

41

Table 4 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the WS according to Jacobs index

Ran

k North Centre South

50 95 50 95 50 95

+ - + - + - + - + - + -

1 Mires

Marshes

Grassland

Moors Mixed Freshwater Agriculture Urban Mixed Freshwater

Grassland

Moors Urban GrasslandMoors Urban

2 Freshwater Mixed Coniferous Urban Mires

Marshes Coniferous Sparse Veg Agriculture

Sparse

Veg Coniferous Freshwater

3 Urban Coniferous Younger Grassland

Moors Freshwater Younger Urban Freshwater

Broad

Leaf Agriculture Mixed

4 Younger Agriculture Sparse Veg Broad

Leaf

Broad

Leaf

Grassland

Moors Mixed Broad Leaf

5 Clear Fell Agriculture Coniferous Agriculture Mires

Marshes Clear Fell

6 Sparse

Veg

Mires

Marshes Mixed

Mires

Marshes

Clear

Fell

Mires

Marshes

7 Broad

Leaf Clear Fell Younger Clear Fell Younger Sparse Veg

8 Clear Fell Younger

9 Sparse

Veg

10 Grassland

Moors

42

Table 5 Second order (UD95Area) individual selectionavoidance for the GS and WS according to the Jacobs index

ID GS WS

Select Avoid Select Avoid

ID004 Younger Sparsely Vegetated MiresMarshes Sparsely Vegetated

ID005 MiresMarshes Sparsely Vegetated Coniferous GrasslandMoors

ID006 Coniferous Sparsely Vegetated Mixed Freshwater

ID008 Mixed Sparsely Vegetated Mixed Freshwater

ID009 Mixed Sparsely Vegetated Mixed GrasslandMoors

ID010 MiresMarshes Freshwater GrasslandMoors Freshwater

ID012 Broad Leaf Sparsely Vegetated Coniferous Urban

ID014 Clear Fell Sparsely Vegetated GrasslandMoors Sparsely Vegetated

ID015 GrasslandMoors Urban GrasslandMoors Freshwater

ID016 GrasslandMoors Freshwater GrasslandMoors Freshwater

ID017 GrasslandMoors Mixed Sparsely Vegetated Mixed

ID019 Mixed Sparsely Vegetated Mixed Urban

ID020 Broad Leaf Sparsely Vegetated Coniferous GrasslandMoors

ID022 MiresMarshes Freshwater MiresMarshes Freshwater

ID023 MiresMarshes GrasslandMoors Mixed Freshwater

ID024 Broadleaf Urban Broad Leaf Urban

ID026 GrasslandMoors Freshwater GrasslandMoors Freshwater

ID027 GrasslandMoors Urban Sparsely Vegetated Freshwater

43 Table 6 Third order (UD50UD95) individual selectionavoidance for the GS and WS according to the Jacobs index

ID GS WS

Select Avoid Select Avoid

ID004 Broad Leaf Mixed GrasslandMoors Freshwater

ID005 Broad Leaf Freshwater Agriculture Freshwater

ID006 Clear Fell Freshwater Agriculture MiresMarshes

ID008 MiresMarshes Freshwater Agriculture Urban

ID009 Freshwater Agriculture Agriculture Freshwater

ID010 Mixed Urban Sparsely Vegetated Urban

ID012 Coniferous GrasslandMoors Freshwater Urban

ID014 Urban Agriculture Freshwater Urban

ID015 Mixed Forest Urban Clear Fell Urban

ID016 Freshwater Urban GrasslandMoors Mixed

ID017 Coniferous Mixed Coniferous Broad Leaf

ID019 Broad Leaf GrasslandMoors Urban GrasslandMoors

ID020 Freshwater Urban Freshwater Agriculture

ID022 MiresMarshes Urban Broad Leaf GrasslandMoors

ID023 Freshwater Mixed Agriculture Freshwater

ID024 Mixed Freshwater Mixed Freshwater

ID026 Mixed MiresMarshes Sparsely Vegetated GrasslandMoors

ID027 Freshwater MiresMarshes GrasslandMoors Broad Leaf

44

Fig 2 North third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)

45

Fig 3 Centre third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)

46

Fig 4 South third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)

47

Fig 5 North second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)

48

Fig 6 Centre second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)

49

Fig 7 South second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)

50

Appendix F

Background

Fig 1 Daily mean snow depth and duration during the study period (Andrew Allen)

Female Moose Reproduction

Moose are seasonal polyoestral mammals (Monfort et al 1993) coming into oestrus during late September

early October (Garel et al 2009) The Swedish moose cow population reaches puberty between the ages 25

and 35 (Sand and Cederlund 1993) during which the reproductive period begins with the onset of ovulation

The age an individual reaches puberty is dependent on their body condition they have to reach a weight

threshold to reach puberty and become reproductive (Sand 1996) If she is over the weight threshold she will

go into oestrus in the autumn If she does not reach the weight threshold then she will go into oestrus the

following autumn if successful she will give birth to individual or twin calves in late May to early June

(Ericsson et al 2001) and therefore reach sexual maturity (Malmsten et al 2014b) Fecundity is related to

both the condition and the age of the cow Cows go through senescence at 12 years of age (Ericsson et al

2001) Providing calves with the required level of nutrition demands high energy and protein resources from

the mother during senescence this becomes harder to achieve leading to decreased levels of parental care

and higher levels of calf mortality

Page 3: Habitat-performance relationships on an island: fitness ...navinderjsingh.weebly.com/uploads/1/1/2/2/11224342/... · Conditions on Öland are milder than those found in other areas

3 Contents

Abstract 4

Introduction 5

Materials and Methods 7

Study area 7

Capture and Handling 8

Data Screening 8

Home rangeUtilization distribution 8

Habitat 9

Activity 10

Diet analysis 10

Survival analysis 10

Results 11

Home RangeUtilization Distribution 11

Activity 12

Habitat ndash Proportions 13

Habitat - Selection 14

Diet 17

Calf Survival 18

Discussion 19

Acknowledgements 22

References 23

Appendix A 30

Introduction 30

Appendix B 31

Method and Materials 31

Appendix C 33

Home ranges 33

Appendix D 35

Activity 35

Appendix E 36

Habitat Proportions 36

Habitat Selection 37

Appendix F 50

Background 50

4

Abstract

Moose (Alces alces) the largest among the deer have both high recreational and economic value in

Scandinavia and elsewhere To efficiently manage such a valuable species the key factors affecting their

fitness and performance must be understood Moose generally have high productivity and calf survival in

predator free areas however in recent years populations at the southern edge of their distribution such as on

the predator free island of Ӧland in Sweden there have been reports of low calf survival Individuals are found

to carry Anaplasma phagocytophilum which has been thought to be one of the factors causing the low survival

The aim of this study was to identify what abiotic and biotic factors may also be affecting female moose

performance and their calf survival GPS data from 18 collared moose was used in conjunction with home

range activity diet survival and habitat analysis Moose did not alter the size of their seasonal home ranges

or their activity level Agricultural areas and feeding stations have become the preferred areas in the core home

ranges during the winter season The diet analysis revealed that nearly two thirds of the moosersquos winter diet

contained agricultural produce Moose are having to utilise areas where in other populations individuals tend

to avoid This could probably be one of the reasons for females to be of lower quality and therefore not being

able to ensure calf survival With changing climates and human land use moose continue to be under such

environmental pressures which may therefore jeopardize their future survival and reproduction

Key Words Population dynamics Habitat selection Performance Fitness Climate Survival Alces

alces Sweden Ӧland

Image by Fredrik Stenbacka

5 Introduction

The population size of animals varies in space and time (Turchin 2001) This variation is driven by a

combination of internal as well as external factors that drive changes in survival and reproduction of

individuals (Brown 2011) Internal factors are associated with life history such as sex age body mass and

generation time whereas the external factors include climatic factors (characterised as density independent)

competition food disease (characterised as density dependent) and human influence (appendix A) Long-term

changes in population size therefore determine the long-term fitness of individuals and cohorts in a population

(Albon et al 1987) However little is known about how these factors interact to produce short and long term

variation in demography and population dynamics across space Although difficult understanding causes of

variation of population size is crucial to effective population conservation and management (Lavsund et al

2003 McLoughlin et al 2011) The interplay and relative contribution of the above factors are best shown

from species with short generation times or from long-term monitoring studies

Ungulates are most commonly studied due to their international economic and recreational value large body

sizes and the relative ease of marking handling and capturing them (Forchhammer et al 2002 Bradshaw et

al 2003 Gordon et al 2004 Clutton-Brock and Sheldon 2010) Large herbivores tend to display low fecundity

and high adult survivorship (Gaillard et al 2000a) Past studies have revealed important details about the

factors affecting their population dynamics An ungulate life cycle is usually classified based on defined age

classes new-born weaned young yearlings two-year-olds prime-aged adults and senescent adults (older than

seven years) New-born survival is highly dependent on climatic conditions predation and the level of maternal

care and condition ie quality of milk and reproductive experience (Gaillard et al 2000a Testa 2004 Baringrdsen

et al 2008) Weaned young and yearlings survival tends to be independent of the mothers care and affected

most often by climatic conditions ie severe winters disease and predation (Bartmann et al 1992) Survival

of two-year olds and adults is influenced mainly by predation (Modafferi 1997) Males generally experience a

lower survival rate than females due to the pressure of the rut and male biased hunting (Mysterud et al 2005)

Conditions experienced during a calfrsquos early development not only cause immediate effects on its future

performance but also delayed effects Calf development (weight) affects its future reproductive success

(performance) by effecting adult body size and future calf body size (Albon et al 1987 Lindstroumlm 1999

Forchhammer et al 2002)

The moose (Alces alces) is a large ungulate widely distributed across the northern hemisphere It is the largest

and only solitary member of the deer family (Cervidae) In Sweden it is found throughout the country in boreal

forests with the exception of the island of Gotland (Brandin 2009) Sweden has the largest population of moose

in Europe with approximately 300000-350000 individuals (Singh et al 2014) A part of Swedenrsquos moose

population is influenced to some extent by predators such as brown bears (Ursus arctos) and wolves (Canis

lupus) however in predator free populations individuals are influenced mainly by stochastic environmental

conditions population density traffic and above all hunting (Sӕther 1997) (appendix A) Moose are hunted

all across Scandinavia and the overall value of moose hunting is estimated to be 145 billion SEK per year

6

(158 billion Euro) (Boman et al 2011) Each year in Sweden 90000-100000 individuals are harvested

providing approximately 85 million kilograms of moose meat (Kindberg et al 2009) A common method of

selecting which individuals are to be harvested is to assess the reproductive value of an individual and remove

the lownon-reproductive individuals such as calves bulls and cows without calves (Ball et al 1999 Ericsson

et al 2001) Hunting is biased towards bulls with large trophy antlers often resulting in a skewed sex ratio

(Laurian et al 2000 Harris et al 2002 Milner et al 2007)

Moose are known to have a generally high calf survival noted through studies from predator free areas in both

North America and Europe (Linnell et al 1995 Crecircte and Courtois 1997 Swenson et al 2007) A number of

other factors are nevertheless known to affect the survival during their first summer such as climatic variation

malnutrition abandonment disease and poor maternal investment (Verme and Ullrey 1984 Gaillard et al

2000b Lomas and Bender 2007 Ericsson et al 2002 Herfindal et al 2006 Lenarz et al 2010) Low survival

in single odd years has been attributed to weather and low food quality

During recent years moose populations appear to be under environmental stress across their southern range

ascertained by studies reporting low calf survival from both North America and Sweden (Monteith et al in

press Ericsson et al submitted) A similar situation has been reported recently on the island of Oumlland in

southern Sweden where the harvesting of moose was postponed from 2001 to 2005 by mutual agreement

between hunters This was due to a fear of population collapse due to poor management strategies in previous

years that lead to a suspected unsustainable harvest The four-year harvesting break resulted in a balanced sex

ratio and age distribution (Jonsson 2007) In 2006 however it was brought to the attention of the department

of Pathology and Wildlife Diseases at the Swedish National Veterinary Institute in Uppsala (SVA) that there

was an unusually low number of calves observed on the island Malmsten (2014a) conducted a follow up study

during 2012 and 2013 and found that summer calf survival of individuals from Oumlland was only 318 and

158 respectively When compared to calf survival from two other sites in southern Sweden (Kronoberg and

Soumldermanland) with rates all above 73 for both years this figure was regarded as very worrying and

prompted a need for an in-depth exanimation of the factors determining such low calf survival With this above

rationale in mind this study investigates the habitat performance relationships of female moose on the island

of Oumlland This study also provides a model for examining the factors affecting population dynamics on an

island

7 Materials and Methods

Study area

Ӧland (567333deg N 166667deg E) a Baltic island located in Kalmar county (Fig 1) is Swedenrsquos second largest

island (~140km in length) It can be split broadly into three areas the north (N) centre (C) and south (S) There

are three typical habitats found on the island boreal forests Stora Alvaret and agricultural land The largest

portions of boreal forests are found in the far north the centre and a patch in the far south Forest stands are

dominated by birch (Betula pubescens B pendula) and Scots pine (Pinus sylvestris) with rowan (Sorbus

aucuparia) aspen (Populus tremula) grey alder (Alnus incana) and yew (Taxus baccata) interspersed

throughout with willow sp (Salix spp) in areas near water sources (Sӕther and Heim 1993) The field layer is

made up of primarily bilberry (Vaccinium myrtillus) lowbush cranberry (Vaccinium vitis-idӕa) and heather

(Calluna vulgaris) (Cederlund 1989) The patches of boreal forest in the north centre and south are isolated

from each other by agricultural areas which are distributed throughout the island particularly along the coastal

regions and the island centre The most southerly patch of forest was protected from becoming agricultural

due to its status as a royal hunting ground and an important stopover for migratory birds (Lars Edenius

personal communication April 09 2014) The southern part of Oumlland has the largest expanse of steppe-like

alvar grassland (Stora Alvaret) found in the world (~25500 ha) (Roseacuten 2006) which is found over dry shallow

nutrient-poor grazed soil (Bakker et al 1996) on top of superficial Ordovician limestone (Dengler et al 2006)

Conditions on Oumlland are milder than those found in other areas of Sweden as it is positioned in the ldquorain-

shadowrdquo of mainland Sweden (Prentice 2007) The only predators of moose found on Oumlland are hunters which

were banned from hunting in previous years

Fig 1 Location of Oumlland

8

Capture and Handling

A random sample of adult moose (n = 25) were darted sedated and equipped with GPSGSM neck collars

(Vectronic Aerospace GmbH Berlin Germany) during the winter of 2012 by the Moose Research Group

SLU Movement data were collected from GPS collars dating from 22022012 ndash 24042014 Collars were

fixed to return GPS locations approximately every 30 minutes

Data Screening

The sample contained both males and females (six males 19 females x female age = 95 years range 4-17

years) An initial inspection revealed that one female individual only returned fixed locations for a period of

eight months Locations ceased during the hunting period so the individual was presumed shot and was

removed from the data along with the males

The exact time between each location varied and sometimes no fix could be made The adehabitatLT package

(Calenge 2006) was used to standardise the data and overcome the location fixing errors The function setNA

was used to place NAs where relocations were missing The function sett0 was used to round the timing of

collection obtaining a regular trajectory with 30 minute intervals The final dataset used in the analysis

consisted of 302710 regular GPS data points from a sample size of n=18 individuals two individuals from the

north ten individuals from the centre and six individuals from the south

To address the question and to investigate the influence of climate on the space use patterns of moose the

analysis was performed at two scales The first included all annual movements of moose and the second at a

seasonal scale ie summer and winter The seasonal scales were defined according to the growing season (GS)

and winter season (WS) In Scandinavia the current method used to define the start of season (SOS) is the

period when the daily mean air temperature is above 5degC (GS) Methods of calculating SOS are advancing

with the use of the Normalized Difference vegetation Index (NDVI) becoming more popular The start and

end of the GS and WS were derived using the mean start and end dates for Oumlland suggested by the Norwegian

Meteorological Institute (DNMI) Nordic climate map report (Tveito et al 2001) The GS of this study is

defined as the period between 23-April-2012 to 07-Nov-2012 and the WS is defined as the period between 08-

Nov-2012 to 22-April-2013 (based on the current standard normal period 1961-90)

Home rangeUtilization distribution

Variation in ungulate home range size is known to be caused by changes in energy requirements and variation

in food availability (Tufto et al 1996 Kie et al 2010 Moreller et al 2013) With shifting climate causes shifts

in plant phenology and therefore the spatial and temporal distribution of ungulate food (Maringrell et al 2006)

Individuals alter their home ranges to meet their energy requirements to maintain their fitness (Albon et al

1987 White 1997 Festa-Bianchet et al 1998 Forchhammer et al 2001)

The most commonly cited definition of a home range is ldquothat area traversed by the animal during its normal

activities of food gathering mating and caring for youngrdquo (Burt 1943) This has now been expanded to

9 incorporate measures of space use using the utilization distribution (UD van Winkle 1975) which can be

described as the ldquorelative frequency distribution of an animalrsquos occurrence in all four dimensions of space

and timerdquo (Keating and Cherry 2009) Home range is viewed as a constant 2D polygon whereas UDs are

viewed as multiple 3D polygons that take into account the distribution as well as the intensity of animalrsquos

movements and space use within their home range (Kranstauber et al 2012) (see appendix A)

Estimations of each individualrsquos annual and seasonal UDs were found using the Biased Random Bridge (BRB)

kernel approach (Benhamou 2011) from the adehabitatHR package (Calenge 2006) in R It was chosen as it is

considered an improvement on the previously preferred Brownian bridge (BB) method (Horne et al 2007) The

BB is purely a diffusive movement process whereas the BRB is an advective-diffusive movement process BB

does not take into account changes in advection direction (drift) or strength BB assumes an animalrsquos

movement is purely random it moves from a starting point and ends up at the end location randomly By

adding the advection component the BRB takes into account that the animalrsquos movement is biased towards a

certain direction This allows for a more biologically relevant analysis (Benhamou and Corneacutelis 2010)

A grid was created using the minmax XY coordinates of all individuals (plusmn 10 km to increase the extent and

prevent the grid directly touching the XY locations) The resolution of the grid was fixed at a 25 m x 25 m

scale to match the resolution of the relevant habitat maps (Hagner et al 2005) By specifying these criteria the

resolution of the data remains consistent between individuals The diffusion coefficient determines the variance

in the location of the kernels between two locations This was calculated from each individualrsquos dataset using

the BRBD function and added to the BRB model (see Benhamou 2011) The strength and direction of BRB

advection can change between bridges whilst having to remaining constant To remain constant an upper Tmax

and lower Lmin time thresholds were set Successive relocations that exceeded Tmax or under Lmin were

removed from the UD calculations The 50 (UD50) and 95 (UD95) isopleths were then calculated from

the UD using the kernelarea function

Habitat

The scale of analysis was further divided following Johnson (1980) Habitat selection within the landscape

(second order selection) was studied by comparing the UD95 with available habitats in each of the three study

areas of Oumlland (UD95Area) Habitat selection within the home range (third order selection) was studied by

comparing the UD50 with the UD95 (UD50UD95)

12 habitat classes were used in the analysis agricultural land broad leaved forests clear felled areas coastal

coniferous forests freshwater areas moorsgrassland miresmarshes mixed forest sparsely vegetated areas

urban areas and younger forests The proportion of area covered by each of these habitat classes was

determined in the UD50 and UD95 Habitat data was obtained from satellite imagery generated by Svenska

Marktaumlckedata (Hagner et al 2005) The habitat maps were last updated in 2002 and have a resolution of 25

m

Compositional analysis ( habitat used habitat available) (Aebischer 1993) was used in conjunction with

the Jacobrsquos index (D) (eqn1) to quantify habitat selection (Jacobs 1974) Coastal areas were removed as not

10

all home ranges contained them This combined approach allowed identification of habitats that are used

disproportionally to their availability ie in a non-random manner (Beyer et al 2010) This is an indication of

which habitats are important for an individual

119863 = ( 119903minus119901

119903+119901minus2119903119901 ) (eqn1)

r = Proportion of habitat type used

p = Total proportion of habitat available

D = Jacobs index varies from -1 (strong avoidance) to +1 (strong preference) with values close to 0 indicating

the habitat is used in proportion to its availability

Activity

Activity level is measured as the mean daily movement (MDM) by the individual to investigate if individuals

in an areaseason moved more and hence were more active than those in other areasseasons Unfortunately

only two cows were collared in the north and were therefore left out of this analysis Moose were identified as

migratory using a modelling approach (see Bunnefeld et al 2011 for methods) Migratory individuals were

initially removed from the activity analysis (n=4)The reason is that both migratory journeys were completed

during the winter season thus increasing the mean daily distance travelled and potentially biasing the analysis

One individual was also removed due it its collar not returning relocations during the entirety of the WS

Diet analysis

The Ӧland project team conducted histology diet analysis on the rumen content of five individuals that were

shot in the centre and south of the island during the WS of 2013

Survival analysis

The Ӧland project team measured calf survival using the mark-resight method The presenceabsence of a calf

was recorded by tracking the cows at six occasions throughout the year These were at the start of the calving

season (mid-May to early June) twice through the summer before the hunt after the hunt and after winter

Survival trend was estimated using a Kaplan-Meier curve (Kaplan and Meier 1958) The Kaplan-Meier curve

shows the survival function (S (t)) ie the probability of an individual surviving until at least time t (Bewick

et al 2004) The probability of surviving from one period to the next is multiplied together to give the survival

function The S(t) of this study is the probability of an individual surviving from birth to after the hunt

(Method summary see appendix B)

11 Results

Home RangeUtilization Distribution

A total of 51 home ranges were estimated (17 annual 17 within growing season 17 within winter season)

Annual x = 9613 ha GS x = 6345 ha and WS x = 6023 ha (appendix C)

At the UD50 scale the largest annual and seasonal mean home ranges were located in the north Mean annual

and seasonal home ranges in the centre were slightly larger than the south This difference was not significant

(F(113)= 22 p= 87) (ANOVA) There was no significant difference between the seasonal home ranges (x

plusmnSD for GS = 116 plusmn38 for WS = 98 plusmn32 ha) (t(11) = 105 p = 32) or the seasonal home ranges in the centre

(t(8) = 101 p = 34 and the south (t(5) = 87 p = 42) (paired-sample t-test) (Table 1)

At the UD95 scale the largest annual and WS mean home ranges were located in the north The largest GS

mean home ranges were located in the centre Mean annual and seasonal home ranges in the centre were

slightly larger than the south This difference was not significant (F(113) = 59 p = 63) (ANOVA) There

was no significant difference between the seasonal home ranges (x plusmnSD for GS = 635 plusmn225 for WS = 602

plusmn161) (t(11) = 373 p = 71) or the seasonal home ranges in the centre (t(8)= 20 p = 84) or south (t(5) = 34

p = 74) (paired-sample t-test) (Table 1)

Table 1 Seasonal and annual mean UD50 and UD95 BRB kernel area in hectares (1ha = 001km2) for the north centre

and south of Oumlland (smoothing factor (h) =100)

Are

a

Annual UD50 GS UD50 WS UD50

n Mean SD Range n Mean SD Range n Mean SD Range

N 2 209 49 139-279 2 1215 39 67-176 2 1615 106 160-163

C 9 178 56 114-277 9 116 44 48-165 9 943 4 61-173

S 6 160 21 142-177 6 1085 51 65-149 6 933 35 69-125

Annual UD95 GS UD95 WS UD95

N 2 10905 5 1084-1097 2 630 199 349-911 2 809 11 794-824

C 9 997 32 682-1536 9 6531 22 295-945 9 637 17 454-941

S 6 9298 30 605-1088 6 5985 373 442-575 6 5526 20 349-679

12

Activity

MDM rates in the three areas (sedentary individuals) during the GS ranged from 14 ndash31 km day During the

WS ranged they ranged from 11-24 km day (Table 2) Movement rates during the GS were higher than the

WS (x plusmnSD for GS = 202 plusmn043 for WS = 161 plusmn043) but it was not statistically significant (t(11) = 200 p=

07) (paired sample t-test)

Table 2 Seasonal mean daily movement rates (km day) for each area and for both areas (total)

Are

a

GS WS

n Mean SE Range n Mean SE Range

C 8 20 003 14-18 8 20 004 12-24

S 4 22 016 17-31 4 12 02 11-13

Total 12 202 003 14-31 12 16 003 11-24

The seasonal MDM rates of all individuals (migratory and sedentary) were not significantly different (x plusmnSD

for GS = 20 plusmn04 for WS = 18 plusmn061) (t(14) = 139 p= 19) (paired sample t-test)

The WS home range size affects the WS MDM (F(110) = 927 p = 01) (ANOVA) The GS home range size

does not affect the GS MDM (F(110) = 36 p = 56) (ANOVA) When the WS home range outlier was

removed the home range size did not affect the WS MDM (F(111) = 186 p= 19) (ANOVA) The MDM was

lowest in February and highest in April (Table 3) there appeared to be no significant pattern in MDM between

the months (appendix D)

Table 3 Mean daily distance moved (km day) for sedentary individuals

Month Season Distance

April GS 0051

May GS 0044

June GS 0039

July GS 0041

August GS 0042

September GS 0044

October GS 0043

November WS 0043

December WS 0038

January WS 0035

February WS 0028

13 Habitat ndash Proportions

The largest proportion of habitat on the island is agriculture the lowest proportion of habitat (excluding coastal

and freshwater) is urban areas (Fig 2) The largest proportion of habitat in the north was coniferous forests

whilst agricultural areas were the dominant habitat types in the centre and south (Fig 3) The lowest proportion

(excluding coastal and freshwater areas) was urban

Fig 2 Proportion of different types of habitats found on Ӧland

Fig 3 Mean proportion of habitats contained within UD95 in the three areas of Oumlland C = Centre N = North S =

South

14

Habitat - Selection

Generally forest habitat types are the highest ranked whilst sparsely vegetated and urban areas are the lowest

ranked Both the second and third order habitat selection analyses gave significant results in the compositional

analysis (Table 4) In the third order analysis (UD50UD95) the centre displayed significant differences

between habitat types The coniferous forests are significantly preferred to sparsely vegetated areas and the

sparsely vegetated areas are significantly preferred to urban areas In the second order analysis (UD95Area)

significance was observed in the north and centre In the north younger forests are significantly preferred to

miresmarshes clear felled areas are significantly preferred to agriculture and freshwater areas are significantly

preferred to sparsely vegetated areas In the centre clear felled areas are significantly preferred to agricultural

land freshwater areas are significantly preferred to urban areas and grasslandmoors are significantly preferred

to sparsely vegetated areas

Table 4 Summary of second (UD95Area bottom) and third order (UD50UD95 top) ranked habitat preferences between

the three areas according to the compositional analysis (see appendix B)

Rank North Centre South

1 Broad Leaf Younger Coniferous

2 Mixed Broad Leaf Younger

3 MiresMarshes Clear Fell GrasslandMoors

4 Younger Mixed Clear Fell

5 Clear Fell GrasslandMoors Mixed

6 Coniferous MiresMarshes Broad Leaf

7 Freshwater Agriculture Freshwater

8 Agriculture Coniferous Agriculture

9 Sparse Veg Sparse Veg MiresMarshes

10 GrasslandMoors Urban Sparse Veg

11 Urban Freshwater Urban

Rank North Centre South

1 Broad Leaf Mixed Coniferous

2 Mixed Younger Clear Fell

3 GrasslandMoors Broad Leaf Younger

4 Younger Coniferous GrasslandMoors

5 MiresMarshes Clear Fell Agriculture

6 Coniferous Agriculture MiresMarshes

7 Clear Fell MiresMarshes Broad Leaf

8 Agriculture Freshwater Freshwater

9 Urban Urban Sparse Veg

10 Freshwater GrasslandMoors Mixed

11 Sparse Veg Sparse Veg Urban

Indicates significantly preferred to the habitat below (significant deviation from random at P lt05)

15 The Jacobs index revealed that generally the habitats preferred during the GS within the home range (third

order) are younger (0187) and broad leaf forests (0154) The strongest avoidance was for urban areas (-0627)

During the WS only agricultural areas are preferred (0129) and the strongest avoidance was for urban areas (-

0393) (Fig 4)

Fig 4 Third order seasonal habitat preference (UD50UD95) all individuals The index ranges from -1 (total avoidance)

to 1 (strongest preference) Close to 0 indicates used in proportion to its availability

Third order habitat preferencesavoidances by area

North During the GS the strongest preference was for broad leaf (0218) and mixed forests (0161) The

strongest avoidance was for urban (-1) and sparsely vegetated areas (-05) During the WS the strongest

preference was for miresmarshes (0228) The strongest avoidance was for grasslandmoors (-05)

Centre During the GS the strongest preference was for broad leaf (0233) and younger forests (0223) The

strongest avoidance was for urban (-0527) and agricultural land (-0362) During the WS preference was only

shown for agricultural land (0327) The strongest avoidance was for urban areas (-0679) and miresmarshes

(-0638)

South During the GS the strongest preference was for coniferous (0312) and younger forests (0242) The

strongest avoidance was for urban (-0353) and sparsely vegetated areas (-0330) During the WS

grasslandmoors (0106) were the strongest preference The strongest avoidance was for urban (-0666) and

sparsely vegetated areas (-0351)

16

The Jacobs indices revealed that generally the habitats preferred during the GS within the landscape

(UD95Area) are broad leaf (0216) and younger forests (0201) The strongest avoidance was for urban (-

0717) and freshwater areas (-0694) The strongest preference during the WS are coniferous forests (0242)

and the strongest avoidance was for freshwater (-0674) and urban areas (-0648) (Fig 5)

Fig 5 Second order seasonal habitat preference (UD50UD95) all individuals The index ranges from -1 (total avoidance)

to 1 (strongest preference) Close to 0 indicates used in proportion to its availability

Second order habitat preferencesavoidances by area

North During the GS the strongest preference was for broad leaf (0363) and mixed forests (00291) The

strongest avoidance was for sparsely vegetated (-0909) and freshwater areas (-0780) During the WS mixed

(0335) and coniferous forests (0316) were the strongest preference The strongest avoidance was for

freshwater (-0731) and urban areas (-05333)

Centre During the GS the strongest preference for mixed (0394) and younger forests (0286) The strongest

avoidance was for urban (-0733) and sparsely vegetated (-0708) areas During the WS mixed (0404) and

coniferous forests (0255) were the strongest preference The strongest avoidance was for freshwater (-0704)

and sparsely vegetated areas (-0655)

South During the GS the strongest preference for grasslandmoors (0287) and clear fells (0165) The

strongest avoidance was for urban areas (-0678) and mixed forests (-0491) During the WS grasslandmoors

(0425) and coniferous forests (0154) were the strongest preference The strongest avoidance was for urban (-

0876) and freshwater areas (-0587) (appendix E)

17 Diet

Diet analysis of the rumen content sampled from five individuals (C=2 S=3) revealed that almost two thirds

(69) of the diet is comprised of agricultural produce (apple winter rape and sugar beet) (Fig 6)

Fig 6 Diet analysis from the rumen samples of five moose individuals that were culled in 2013

31

2117

9

8

5

22

1 1

1

1

1 00 0

0

0Diet (2610-911 2013 5 individuals)

AppleWinter RapeSugar BeetUndefined WoodSallowBroad-leaf GrassPineAshOakCloverCurrantsUndefined plantElderberryJuniperRaspberry

18

Calf Survival

Of the 18 individuals 13 produced calves in which 7 produced twins giving a total of 20 calves A Kaplan-

Meier estimate was conducted to measure the fraction of calves living up to each period of the study (Fig 7)

The mean survival time is until period 235 (midend of summer) At the start of summer 85 of calves

remained (3 still born) The period between summer and before the hunt survival drops to 30 The survival

at the end of the study (after hunt) drops further to 20 leaving 4 calves surviving (see appendix B)

Fig 7 Kaplan-Meier estimate of moose calf survival during the study period Period 0 (Start of summer) period 1

(midend of summer) period 2 (before hunt) period 3 (after hunt) period 4 (after winter)

19 Discussion

The results of this study emphasised how strikingly different the habitat composition is along the latitudinal

gradient of Oumlland The three areas show contrasting proportions of the key habitat types The starkest

difference is the high proportion of coniferous forests and lack of agriculture in the north compared to the

centre and south The proportion of coniferous forest in the north is almost 5 times greater than in the centre

and south whereas the proportion of agriculture in the centre and south is more than double that in the north

The north is perceived to be composed of the most suitable habitat for moose (Dussault et al 2006) It has the

largest proportions of each forest type and a low proportion of agricultural land This provides suitable forage

and shelter throughout the year The south has a contrasting habitat composition to the north The proportions

of agricultural and sparsely vegetated areas are the highest between the three areas and the proportions of forest

habitats are the lowest The large proportion of sparsely vegetated areas and low proportions of forest habitat

corresponds to the large area of Stora Alvaret This is perceived to be the least suitable area due to a lack of

shelter (coniferous forest) and suitable forage The strong preference for coniferous and younger forest habitats

in the south would suggest that moose exhibit a functional response in habitat selection (Godvik et al 2009)

ie as the proportion of a particular habitat decreases the selection for that habitat increases in this case

coniferous forests which provide shelter and younger forest which provide good forage Similarly in the centre

moose show strong preference for mixed forests a habitat that is of low proportion

In view of the large variation in habitat proportions between the areas it is surprising that there is not a large

variation in the home range sizes or the activity levels annually or seasonally Home ranges are ultimately

chosen to maximise fitness and meet energy requirements by utilizing the available forage Seasonal conditions

change the availability and necessity of resources (food quality shelter) Unlike the GS during the WS

deciduous trees and shrubs are leafless and low-lying shrubs are under snow cover (Dussault et al 2005)

These changes are well known to cause populations to alter their activity and home ranges to meet energy

requirements (Mysterud et al 2001) Populations have been shown to increase or decrease their home ranges

during the two seasons The GS home ranges are often larger than the WS home ranges (Philips et al 1973

Mysterud et al 2001) In some cases they can be found to be almost double the size of the WS home ranges

(Cederlund and Okarma 1988) In other populations the WS home ranges are double the size of the GS home

ranges (Lynch and Morgantini 1984) or sizes do not significantly differ (Cederlund and Sand 1994)

Previous studies on moose find females generally show increased activity from the start on the GS due to

various factors eg reduced ruminating times increased metabolic needs and increased foraging bursts

(Wattles and DeStefano 2013) Increased metabolic needs during this time are a results of pregnancy and

lactation (Georgii 1980) During the height of the GS they usually show reduced activity levels through times

of increased thermal stress (Renecker and Hudson 1989 van Beest et al 2012) During the WS the depth and

the duration of snow cover are well known to affect the activity level (Telfer 1970 Mysterud and Oslashstbye 1999

Bjoslashrneraas et al 2011) During the WS generally home ranges are smaller and activity less due to lower

metabolic needs Moose activity is constrained by rumination during the WS this period is known to be longer

due to the change in diet (Cederlund 1989 Renecker Hudson 1989) This was not the case on Ӧland activity

20

was lowest in February which is a similar result to Cederlundrsquos (1989) paper However Ӧland moose did not

significantly alter their seasonal activity levels The fact that the annual and seasonal activity levels and home

ranges were similar could be a result of the mild winters on Oumlland during the study period (Smhise 2014)

During the study period the average number of snow days was 80 and the mean snow depth was 10cm

(appendix F) (Swedish Meterological and Hydrological Institute- SMHI) These mild conditions do not restrict

the movement of moose or obscure forage Moose are well adapted for movement in deep snow depths of 60-

86cm (Prescott 1968) are needed to truly restrict movement This finding was similar to the Sweanor and

Sandegren (1989) and Cederlund and Sand (1994) where the snow depth at their sites did not reach movement

restricting depths

The survival curve illustrates just how bad the calf survival is on Ӧland Survival falls from 85 at the start to

20 Out of 20 calves only four were alive at the end of the study The sharpest fall in survival was the period

between end of summer and before the hunt so the deaths were not due to hunting Previous calf autopsies

(Malmsten 2014a) have shown that cause of death was starvation mothers possibly either did not have milk

the calf was unable to feed or the mother abandoned the calf Closer field based observations are needed to

attain this knowledge Moose are seasonal polyoestral mammals (Monfort et al 1993) coming into oestrus

during late September early October (Garel et al 2009) (appendix F) The diet of the mother influences the

health of the calf and this period is when sodium is hard to find sodium is a key mineral in moose diets for

features such as reproduction (Belovsky and Jordan 1981) Moose gain sodium mainly through aquatic plants

(MacCracken et al 1993) However the compositional analysis shows that freshwater areas are often ranked

as one of the lowest used habitats and coastal areas were removed as the proportion found in the home ranges

was extremely low The Jacobs Index shows that the moose only prefer freshwater areas in the north UD50

during the WS The north individuals again are those that are showing typical moose habitat selection

It is known that habitat selection is hierarchical with habitats that increase fitness selected for and the effects

of limiting factors are reduced (Rettie and Messier 2000) At the UD95 during the GS moose preferred areas

of good forage (forests) and avoided areas of low forage (freshwater and sparsely vegetated areas) and areas

close to humans (urban) This is consistent with other reports (Laurian et al 2008 Torres et al 2011) Within

the UD50 there is a shift in preferences The good forage areas are again preferred during the GS however

during WS the only preferred habitat is often agricultural land During the WS there could be a steady supply

of supplementary feed available hence the high levels of agricultural produce found in the rumen content

samples and the high preference of agricultural areas This diet is unusual for moose previous studies of

Swedish moose diet have found the GS diet was dominated by birch willow and herbaceous plants and the

WS diet dominated by pine and birch (Cederlund and Nystrom 1981) The diet analysis was conducted during

the WS instead of being dominant pine composed just 2 Birch did not appear however unidentified wood

composed only 9 whereas agricultural produce accounted for 69 Supplementary feed may be perceived

by the moose in the centre and south as a vital forage source during the WS In fact in the centre the

agricultural land is the only preferred habitat at the UD50 It is unknown whether there are salt licks provided

in these areas Selection for a critical habitat is often thought to be a fixed factor The Oumlland population from

21 the three areas are close in proximity however they displayed contrasting preferences This is supported by the

Osko et al (2004) report that found two neighbouring moose populations that had access to the same habitats

displayed contrasting preferences Habitat preferences for populations of the same species are not necessarily

fixed They alter with varying levels of habitat abundance and limiting factors skewing what is preserved to

be critical

The main limitation encountered in this study was with the limited sample There was only data on two

individuals from the north of the island which led it being removed from many of the analysis Similarly due

to a lack of relocations from the collars being turned off at points throughout the year two further individuals

had to be removed from a majority of the analysis This reduced the sample size to 17 or 18 individuals

Similarly only 13 of the individuals from the study produced calves This unfortunately prevented including

survival into models Although the sample size was small it was accurate it was of high resolution over

300000 GPS points In future it would be beneficial to have a more standardised data set An equal sample of

individuals from the three areas would be advised along with ensuring the GPS collars are kept turned on for

the entirety of the growing and winter season to allow comparisons between years It would also be

advantageous to collect coordinates of the feeding sites along with the composition This could then be

compared with high use UD coordinates to look if moose are truly spending a majority of their foraging time

at feeding stations A study on the population densities of moose and the increasing population of roe deer

(Capreolus capreolus) would add the factor of competition into the model

The low calf survival on Ӧland is most likely the result of a combination of factors The lack of suitable habitat

reported in this study in conjunction with Malmstenrsquos (2014a) report on the threat of disease (Anaplasma

phagocytophilum) are probable influences on the calf survival on Ӧland On Ӧland there is an increasing

population of roe deer and large numbers of migratory birds both carriers of ticks and diseases The mild

conditions on Ӧland are advantageous for ticks the carriers of A phagocytophilum Fewer snow days and

shorter periods of snow cover along with dry conditions are favourable for ticks This could probably be one

of the reasons for females to be of lower quality and therefore not being able to ensure calf survival Moose

have to utilise areas where in other populations individuals tend to avoid Finally similar to many studies I

advocate further research using a stronger dataset and longer term monitoring

22

Acknowledgements

I am indebted to NJ Singh and A Allen for all their help and guidance through the whole of this study I

thank SLU for the support provided during this study in terms of data finances and facilities Thank you to

everyone at the Department of Wildlife Fish and Environmental Studies for being so friendly and

supportive I would like to thank L Edenius for driving me around the study area and S Michon and H

Khalil for keeping me sane with fika and training

23 References

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Bewick V Cheek L Ball J (2004) Statistics review 12 Survival analysis Critical Care 8(5)389-394

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Bradshaw RHW Hannon GE Lister AM (2003) A long-term perspective on ungulate-vegetation

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Brandin E (2009) Versions of lsquowildrsquo and the importance of fences in Swedish wildlife tourism involving

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Burt WH (1943) Territoriality and home range concepts as applied to mammals Journal of Mammalogy

24346-352

24

Bunnefeld N Boumlrger L van Moorter B Rolandsen CM Dettki H Solberg EJ Ericsson G(2011) A model-

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Calenge C (2011) Home Range Estimation in R the adehabitatHR package Office national de la classe et de

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Cederlund GN Nystroumlm A (1981) Seasonal differences between moose and roe deer in ability to digest

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Cederlund GN Okarma H (1988) Home range and habitat use of adult female moose Journal of Wildlife

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Cederlund GN (1989) Activity patterns in moose and roe deer in a north boreal forest Holarctic Ecology

1239-45

Cederlund GN Sand H (1994) Home-range size in relation to age and sex in moose American Society of

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Crecircte M Courtois R (1997) Limiting factors might obscure population regulation of moose (Cervidae Alces

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Dussault C Courtois R Ouellet JP Girard I (2005) Space use of moose in relation to food availability

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Dussault C Courtois R Ouellet JP (2006) A habitat suitability index model to assess moose habitat selection

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Ericsson G Wallin K Ball JP Broberg M (2001) Age-related reproductive effort and senescence in free-

ranging moose Alces alces Ecology 821613-1620

Ericsson G Ball JP Danell K (2002) Moose offspring body mass along an altitudinal gradient Journal of

Wildlife Management 55(1)91-97

Ericsson G Malmsten J Neumann W Singh NJ Dali AM Submitted Summer Calf Survival of

Scandinavian Moose along its Southern Distribution Range

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Gaillard JM Festa-Bianchet M Yoccoz NG Loison A Toiumlgo C (2000a) Temporal variation in fitness

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Gaillard JM Festa-Bianchet M Delorme D Jorgenson J (2000b) Body mass and individual fitness in female

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47278-285

Godvik IMR Loe LE Vik JO Veiberg V Langvatn R Mysterud A (2009) Temporal scales trade-offs and

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1031

Hagner O Nilsson M Reese H Egberth M Olsson H (2005) Procedure for classification of forests for

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Hall LS Krausman PR Morrison ML (1997) The habitat concept and a plea for standard terminology

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Horne JS Garton ED Krone SM Lewis JS (2007) Analysing animal movements using Brownian bridges

Ecological Society of America Ecology 882354-2363

Hornok S Kovaacutets D Csoumlrgo T Meli M Goumlnczi E Hadnagy Z Takaacutecs N Farkas R Hofmann-Lehmann R

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Jacobs J (1974) Quantitative measurement of food selection a modification of the forage ratio and Ivlevrsquos

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Jonsson F (2007) rsquoDen oumllaumlndska aringlgstammens foumlrvaltingrsquo Departement of Wildlife Fish and Environmental

Studies SLU Examensarbete I aumlmnet biologi vol 20072

Kaplan EL Meier P (1958) Nonparametric estimation from incomplete observation Journal of the American

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Kie JG Matthiopolos J Fieberg J Powell RA Cagnacci F Mitchell SM Gaillard JM Moorcroft PR (2010)

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27

Malmsten J Wideacuten DG Rydevik G Yon L Hutchings MR Thulin CG Soumlderquist L Aspan A Stuen S

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Malmsten J Soumlderquist L Thulin C Wideacuten DG Yon L Hutchings MR Dalin A (2014b) Reproductive

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Management 39118-123

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Halls LK) pp 91-118 Stackpole Harrisburg Pennsylvania

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success in muskoxen Journal of Zoology 24313-20

30

Appendix A

Introduction

Fig 1 Summary chart of factors affecting the life history and therefore the long term fitness of a population

Fig 2 Summary chart 2

Movement

Habitat

Climate

Topography

Competition

FoodWater

Disease

Die

Survive

Reproduce

Population long term fitness

31 Appendix B

Method and Materials

Fig 1 Summary of processes

32

Fig 2 Examples of classical kernel home range output and Brownian bridge kernel home range (Calenge 2011) The

right image includes the area between relocations ie the movement path in contrast to the classic kernel home range

in the left image

33 Appendix C

Home ranges

Fig 1 Example of a non-migratory (ID006) individuals BRB kernel area From top left annual growing and winter

season UD50 (black contour) and UD95 (red contour)

Fig 2 Example of a migratory (ID012) individuals BRB kernel area From the left annual growing and winter season

UD50 (black contour) and UD95 (red contour)

34

Table 1 Annual and seasonal UD50 and UD95 areas (ha) for all individuals

ID Annual GS WS

UD50 UD95 UD50 UD95 UD50 UD95

ID004 190 924 93 531 173 941

ID005 230 1364 132 945 72 682

ID006 162 1036 89 736 70 611

ID008 277 1536 156 809 78 738

ID009 137 834 48 295 126 653

ID010 114 682 83 448 96 488

ID012 177 963 123 544 76 545

ID014 160 1018 87 575 89 662

ID015 172 858 128 532 109 679

ID016 156 1047 65 455 92 534

ID017 153 1088 149 1043 69 349

ID019 279 1097 176 911 163 824

ID020 139 1084 67 349 160 794

ID022 159 811 131 638 61 454

ID023 187 1061 147 771 72 705

ID024 146 725 165 705 101 458

ID026 142 605 99 442 125 547

ID027 126 567 75 461 48 277

35 Appendix D

Activity

Fig 1 Mean daily movement during the study period GS 23-April-2012 to 07-Nov-2012 WS 08-Nov-2012 to

22-April-2013 (number indicates month)

Fig 2 Mean daily movement in the centre and south during the GS and WS

36

Appendix E

Habitat Proportions

Fig 1 All individualsrsquo seasonal habitat proportions within the UD95

37 Habitat Selection

Table 1 Simplified ranking matrices comparing proportional habitat use within the second order (UD95Area) with

proportions of total available habitat types Mean value on the matrix was replaced by a sign a triple sign represents

significant deviation from random at P lt05 Highlighted habitat is ranked 1st

North A

gri

cult

ure

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 --- --- - +++ --- --- --- +++ +++ --- 8

Broad Leaf +++ 0 +++ + +++ +++ +++ + +++ +++ +++ 1

Clear Fell +++ --- 0 + +++ - - --- +++ +++ --- 7

Coniferous + - - 0 +++ - - --- +++ +++ - 6

Freshwater --- --- --- --- 0 --- --- --- +++ - --- 10

Grassland

Moors +++ --- + + +++ 0 +++ - +++ +++ + 3

MiresMarshes +++ --- + + +++ --- 0 - +++ +++ --- 5

Mixed +++ - +++ +++ +++ + + 0 +++ +++ + 2

Sparse Veg --- --- --- --- --- --- --- --- 0 --- --- 11

Urban --- --- --- --- + --- --- --- +++ 0 --- 9

Younger +++ --- +++ + +++ - +++ - +++ +++ 0 4

Rank Order and

Significance

Broad Leafgt Mixedgt GrasslandMoorsgt Youngergtgtgt MiresMarshesgt Coniferousgt

Clear Fellgtgtgt Agriculturegtgtgt Urbangt Freshwatergtgtgt Sparse Veg

Central

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 --- --- --- + +++ + --- +++ +++ --- 6

Broad Leaf +++ 0 +++ + +++ +++ + - +++ +++ - 3

Clear Fell +++ --- 0 - +++ +++ + --- +++ +++ --- 5

Coniferous +++ - + 0 +++ +++ + --- +++ +++ - 4

Freshwater - --- --- --- 0 +++ - --- +++ +++ --- 8

Grassland

Moors --- --- --- --- --- 0 --- --- +++ - --- 10

MiresMarshes - - - - + +++ 0 - +++ +++ - 7

Mixed +++ + +++ +++ +++ +++ + 0 +++ +++ + 1

Sparse Veg --- --- --- --- --- --- --- --- 0 - --- 11

Urban --- --- --- --- --- + --- --- + 0 --- 9

Younger +++ + +++ + +++ +++ + - +++ +++ 0 2

Rank Order and

Significance

Mixedgt Youngergt Broad Leafgt Coniferousgt Clear Fellgtgtgt Agriculturegt

MiresMarshesgt Freshwatergtgtgt Urbangt GrasslandMoorsgtgtgt Sparse Veg

38

South

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 + - - + - + +++ +++ +++ - 5

Broad Leaf - 0 - - + - - +++ + +++ - 7

Clear Fell + + 0 - + + + +++ + +++ + 2

Coniferous + + + 0 +++ + + +++ + +++ + 1

Freshwater - - - --- 0 - - + + +++ - 8

Grassland

Moors + + - - + 0 + + +++ + - 4

MiresMarshes - + - - + - 0 +++ + +++ - 6

Mixed --- --- --- --- - - --- 0 + + --- 10

Sparse Veg --- - - - - --- - - 0 + - 9

Urban --- --- --- --- --- - --- - - 0 --- 11

Younger + + - - + + + +++ + +++ 0 3

Rank Order

and

Significance

Coniferousgt Clear Fellgt Youngergt GrasslandMoorsgt Agriculturegt MiresMarshesgt Broad Leafgt

Freshwatergt Sparse Veggt Mixedgt Urban

Table 2 Simplified ranking matrices comparing proportional habitat use within the third order (UD50UD95) with

proportions of total available habitat types Mean value on the matrix was replaced by a sign a triple sign represents

significant deviation from random at P lt05 Highlighted habitat is ranked 1st

North

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 --- --- --- - + --- --- + +++ --- 8

Broad Leaf +++ 0 +++ + + + + + +++ +++ + 1

Clear Fell +++ --- 0 + + + - - + +++ - 5

Coniferous +++ - - 0 + + --- --- +++ +++ - 6

Freshwater + - - - 0 +++ - - +++ +++ - 7

GrasslandMoors - - - - --- 0 - - - + - 10

MiresMarshes +++ - + +++ + + 0 - +++ +++ + 3

Mixed +++ - + +++ + + + 0 +++ +++ + 2

Sparse Veg - --- - --- --- + --- --- 0 +++ --- 9

Urban --- --- --- --- --- - --- --- --- 0 --- 11

Younger +++ - + + + + - - +++ +++ 0 4

Rank Order and

Significance

Broad Leafgt Mixedgt MiresMarshesgt Youngergt Clear Fellgt Coniferousgt Freshwatergt

Agriculturegt Sparse Veggt GrasslandMoorsgt Urban

39

Central

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 --- --- + + - - - + +++ --- 7

Broad Leaf +++ 0 + +++ + + + + + +++ - 2

Clear Fell +++ - 0 +++ + + + + + +++ - 3

Coniferous - --- --- 0 + - - --- +++ + --- 8

Freshwater - - - - 0 --- - - --- - - 11

GrasslandMoors + - - + +++ 0 + - + +++ - 5

MiresMarshes + - - + + - 0 + + +++ - 6

Mixed + - - +++ + + - 0 +++ +++ - 4

Sparse Veg - - - --- +++ - - --- 0 +++ - 9

Urban --- --- --- - + --- --- --- --- 0 --- 10

Younger +++ + + +++ + + + + + +++ 0 1

Rank Order and

Significance

Youngergt Broad Leafgt Clear Fellgt Mixedgt GrasslandMoorsgt MiresMarshesgt

Agriculturegt Coniferousgtgtgt Sparse Veggtgtgt Urbangt Freshwater

South

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 - - - - - + - +++ + --- 8

Broad Leaf + 0 - --- + - + - +++ + - 6

Clear Fell + + 0 - + - + - +++ + - 4

Coniferous + +++ + 0 + + +++ + +++ + + 1

Freshwater + - - - 0 - - + + + - 7

GrasslandMoors + + + - + 0 + + + + - 3

MiresMarshes - - - --- + - 0 - + + - 9

Mixed + + + - - - + 0 + + - 5

Sparse Veg --- --- --- --- - - - - 0 + --- 10

Urban - - - - - - - - - 0 - 11

Younger +++ + + - + + + + +++ + 0 2

Rank Order and

Significance

Coniferousgt Youngergt GrasslandMoorsgt Clear Fellgt Mixedgt Broad Leafgt Freshwatergt

Agriculturegt MiresMarshesgt Sparse Veggt Urban

40

Table 3 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the GS according to Jacobs index

Ran

k North Centre South

50 95 50 95 50 95

+ - + - + - + - + - + -

1 Broad

Leaf Urban Broad Leaf Sparse Veg

Broad

Leaf Urban Mixed Urban Coniferous Urban

Grassland

Moors Urban

2 Mixed Sparse Veg Mixed Freshwater Younger Agriculture Younger Sparse Veg Younger Sparse Veg Clear Fell Mixed

3 Mires

Agriculture Grassland

Urban Clear

Fell Coniferous Broad Leaf

Grassland

Moors

Clear Fell Agriculture Coniferous Sparse Veg

Marshes Moors

4 Younger Grassland

Younger Agriculture

Freshwater Coniferous Freshwater

Broad Leaf Mires

Younger Freshwater

Moors Marshes

5 Clear

Fell Freshwater

Mires Coniferous

Sparse Veg Clear Fell Agriculture

Freshwater Agriculture

Marshes

6 Coniferous Clear Fell

Mires

Marshes

Mires

Grassland

Moors

Mires

Marshes Marshes

7 Mixed Mixed Broad Leaf

8 Grassland

Moors

41

Table 4 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the WS according to Jacobs index

Ran

k North Centre South

50 95 50 95 50 95

+ - + - + - + - + - + -

1 Mires

Marshes

Grassland

Moors Mixed Freshwater Agriculture Urban Mixed Freshwater

Grassland

Moors Urban GrasslandMoors Urban

2 Freshwater Mixed Coniferous Urban Mires

Marshes Coniferous Sparse Veg Agriculture

Sparse

Veg Coniferous Freshwater

3 Urban Coniferous Younger Grassland

Moors Freshwater Younger Urban Freshwater

Broad

Leaf Agriculture Mixed

4 Younger Agriculture Sparse Veg Broad

Leaf

Broad

Leaf

Grassland

Moors Mixed Broad Leaf

5 Clear Fell Agriculture Coniferous Agriculture Mires

Marshes Clear Fell

6 Sparse

Veg

Mires

Marshes Mixed

Mires

Marshes

Clear

Fell

Mires

Marshes

7 Broad

Leaf Clear Fell Younger Clear Fell Younger Sparse Veg

8 Clear Fell Younger

9 Sparse

Veg

10 Grassland

Moors

42

Table 5 Second order (UD95Area) individual selectionavoidance for the GS and WS according to the Jacobs index

ID GS WS

Select Avoid Select Avoid

ID004 Younger Sparsely Vegetated MiresMarshes Sparsely Vegetated

ID005 MiresMarshes Sparsely Vegetated Coniferous GrasslandMoors

ID006 Coniferous Sparsely Vegetated Mixed Freshwater

ID008 Mixed Sparsely Vegetated Mixed Freshwater

ID009 Mixed Sparsely Vegetated Mixed GrasslandMoors

ID010 MiresMarshes Freshwater GrasslandMoors Freshwater

ID012 Broad Leaf Sparsely Vegetated Coniferous Urban

ID014 Clear Fell Sparsely Vegetated GrasslandMoors Sparsely Vegetated

ID015 GrasslandMoors Urban GrasslandMoors Freshwater

ID016 GrasslandMoors Freshwater GrasslandMoors Freshwater

ID017 GrasslandMoors Mixed Sparsely Vegetated Mixed

ID019 Mixed Sparsely Vegetated Mixed Urban

ID020 Broad Leaf Sparsely Vegetated Coniferous GrasslandMoors

ID022 MiresMarshes Freshwater MiresMarshes Freshwater

ID023 MiresMarshes GrasslandMoors Mixed Freshwater

ID024 Broadleaf Urban Broad Leaf Urban

ID026 GrasslandMoors Freshwater GrasslandMoors Freshwater

ID027 GrasslandMoors Urban Sparsely Vegetated Freshwater

43 Table 6 Third order (UD50UD95) individual selectionavoidance for the GS and WS according to the Jacobs index

ID GS WS

Select Avoid Select Avoid

ID004 Broad Leaf Mixed GrasslandMoors Freshwater

ID005 Broad Leaf Freshwater Agriculture Freshwater

ID006 Clear Fell Freshwater Agriculture MiresMarshes

ID008 MiresMarshes Freshwater Agriculture Urban

ID009 Freshwater Agriculture Agriculture Freshwater

ID010 Mixed Urban Sparsely Vegetated Urban

ID012 Coniferous GrasslandMoors Freshwater Urban

ID014 Urban Agriculture Freshwater Urban

ID015 Mixed Forest Urban Clear Fell Urban

ID016 Freshwater Urban GrasslandMoors Mixed

ID017 Coniferous Mixed Coniferous Broad Leaf

ID019 Broad Leaf GrasslandMoors Urban GrasslandMoors

ID020 Freshwater Urban Freshwater Agriculture

ID022 MiresMarshes Urban Broad Leaf GrasslandMoors

ID023 Freshwater Mixed Agriculture Freshwater

ID024 Mixed Freshwater Mixed Freshwater

ID026 Mixed MiresMarshes Sparsely Vegetated GrasslandMoors

ID027 Freshwater MiresMarshes GrasslandMoors Broad Leaf

44

Fig 2 North third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)

45

Fig 3 Centre third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)

46

Fig 4 South third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)

47

Fig 5 North second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)

48

Fig 6 Centre second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)

49

Fig 7 South second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)

50

Appendix F

Background

Fig 1 Daily mean snow depth and duration during the study period (Andrew Allen)

Female Moose Reproduction

Moose are seasonal polyoestral mammals (Monfort et al 1993) coming into oestrus during late September

early October (Garel et al 2009) The Swedish moose cow population reaches puberty between the ages 25

and 35 (Sand and Cederlund 1993) during which the reproductive period begins with the onset of ovulation

The age an individual reaches puberty is dependent on their body condition they have to reach a weight

threshold to reach puberty and become reproductive (Sand 1996) If she is over the weight threshold she will

go into oestrus in the autumn If she does not reach the weight threshold then she will go into oestrus the

following autumn if successful she will give birth to individual or twin calves in late May to early June

(Ericsson et al 2001) and therefore reach sexual maturity (Malmsten et al 2014b) Fecundity is related to

both the condition and the age of the cow Cows go through senescence at 12 years of age (Ericsson et al

2001) Providing calves with the required level of nutrition demands high energy and protein resources from

the mother during senescence this becomes harder to achieve leading to decreased levels of parental care

and higher levels of calf mortality

Page 4: Habitat-performance relationships on an island: fitness ...navinderjsingh.weebly.com/uploads/1/1/2/2/11224342/... · Conditions on Öland are milder than those found in other areas

4

Abstract

Moose (Alces alces) the largest among the deer have both high recreational and economic value in

Scandinavia and elsewhere To efficiently manage such a valuable species the key factors affecting their

fitness and performance must be understood Moose generally have high productivity and calf survival in

predator free areas however in recent years populations at the southern edge of their distribution such as on

the predator free island of Ӧland in Sweden there have been reports of low calf survival Individuals are found

to carry Anaplasma phagocytophilum which has been thought to be one of the factors causing the low survival

The aim of this study was to identify what abiotic and biotic factors may also be affecting female moose

performance and their calf survival GPS data from 18 collared moose was used in conjunction with home

range activity diet survival and habitat analysis Moose did not alter the size of their seasonal home ranges

or their activity level Agricultural areas and feeding stations have become the preferred areas in the core home

ranges during the winter season The diet analysis revealed that nearly two thirds of the moosersquos winter diet

contained agricultural produce Moose are having to utilise areas where in other populations individuals tend

to avoid This could probably be one of the reasons for females to be of lower quality and therefore not being

able to ensure calf survival With changing climates and human land use moose continue to be under such

environmental pressures which may therefore jeopardize their future survival and reproduction

Key Words Population dynamics Habitat selection Performance Fitness Climate Survival Alces

alces Sweden Ӧland

Image by Fredrik Stenbacka

5 Introduction

The population size of animals varies in space and time (Turchin 2001) This variation is driven by a

combination of internal as well as external factors that drive changes in survival and reproduction of

individuals (Brown 2011) Internal factors are associated with life history such as sex age body mass and

generation time whereas the external factors include climatic factors (characterised as density independent)

competition food disease (characterised as density dependent) and human influence (appendix A) Long-term

changes in population size therefore determine the long-term fitness of individuals and cohorts in a population

(Albon et al 1987) However little is known about how these factors interact to produce short and long term

variation in demography and population dynamics across space Although difficult understanding causes of

variation of population size is crucial to effective population conservation and management (Lavsund et al

2003 McLoughlin et al 2011) The interplay and relative contribution of the above factors are best shown

from species with short generation times or from long-term monitoring studies

Ungulates are most commonly studied due to their international economic and recreational value large body

sizes and the relative ease of marking handling and capturing them (Forchhammer et al 2002 Bradshaw et

al 2003 Gordon et al 2004 Clutton-Brock and Sheldon 2010) Large herbivores tend to display low fecundity

and high adult survivorship (Gaillard et al 2000a) Past studies have revealed important details about the

factors affecting their population dynamics An ungulate life cycle is usually classified based on defined age

classes new-born weaned young yearlings two-year-olds prime-aged adults and senescent adults (older than

seven years) New-born survival is highly dependent on climatic conditions predation and the level of maternal

care and condition ie quality of milk and reproductive experience (Gaillard et al 2000a Testa 2004 Baringrdsen

et al 2008) Weaned young and yearlings survival tends to be independent of the mothers care and affected

most often by climatic conditions ie severe winters disease and predation (Bartmann et al 1992) Survival

of two-year olds and adults is influenced mainly by predation (Modafferi 1997) Males generally experience a

lower survival rate than females due to the pressure of the rut and male biased hunting (Mysterud et al 2005)

Conditions experienced during a calfrsquos early development not only cause immediate effects on its future

performance but also delayed effects Calf development (weight) affects its future reproductive success

(performance) by effecting adult body size and future calf body size (Albon et al 1987 Lindstroumlm 1999

Forchhammer et al 2002)

The moose (Alces alces) is a large ungulate widely distributed across the northern hemisphere It is the largest

and only solitary member of the deer family (Cervidae) In Sweden it is found throughout the country in boreal

forests with the exception of the island of Gotland (Brandin 2009) Sweden has the largest population of moose

in Europe with approximately 300000-350000 individuals (Singh et al 2014) A part of Swedenrsquos moose

population is influenced to some extent by predators such as brown bears (Ursus arctos) and wolves (Canis

lupus) however in predator free populations individuals are influenced mainly by stochastic environmental

conditions population density traffic and above all hunting (Sӕther 1997) (appendix A) Moose are hunted

all across Scandinavia and the overall value of moose hunting is estimated to be 145 billion SEK per year

6

(158 billion Euro) (Boman et al 2011) Each year in Sweden 90000-100000 individuals are harvested

providing approximately 85 million kilograms of moose meat (Kindberg et al 2009) A common method of

selecting which individuals are to be harvested is to assess the reproductive value of an individual and remove

the lownon-reproductive individuals such as calves bulls and cows without calves (Ball et al 1999 Ericsson

et al 2001) Hunting is biased towards bulls with large trophy antlers often resulting in a skewed sex ratio

(Laurian et al 2000 Harris et al 2002 Milner et al 2007)

Moose are known to have a generally high calf survival noted through studies from predator free areas in both

North America and Europe (Linnell et al 1995 Crecircte and Courtois 1997 Swenson et al 2007) A number of

other factors are nevertheless known to affect the survival during their first summer such as climatic variation

malnutrition abandonment disease and poor maternal investment (Verme and Ullrey 1984 Gaillard et al

2000b Lomas and Bender 2007 Ericsson et al 2002 Herfindal et al 2006 Lenarz et al 2010) Low survival

in single odd years has been attributed to weather and low food quality

During recent years moose populations appear to be under environmental stress across their southern range

ascertained by studies reporting low calf survival from both North America and Sweden (Monteith et al in

press Ericsson et al submitted) A similar situation has been reported recently on the island of Oumlland in

southern Sweden where the harvesting of moose was postponed from 2001 to 2005 by mutual agreement

between hunters This was due to a fear of population collapse due to poor management strategies in previous

years that lead to a suspected unsustainable harvest The four-year harvesting break resulted in a balanced sex

ratio and age distribution (Jonsson 2007) In 2006 however it was brought to the attention of the department

of Pathology and Wildlife Diseases at the Swedish National Veterinary Institute in Uppsala (SVA) that there

was an unusually low number of calves observed on the island Malmsten (2014a) conducted a follow up study

during 2012 and 2013 and found that summer calf survival of individuals from Oumlland was only 318 and

158 respectively When compared to calf survival from two other sites in southern Sweden (Kronoberg and

Soumldermanland) with rates all above 73 for both years this figure was regarded as very worrying and

prompted a need for an in-depth exanimation of the factors determining such low calf survival With this above

rationale in mind this study investigates the habitat performance relationships of female moose on the island

of Oumlland This study also provides a model for examining the factors affecting population dynamics on an

island

7 Materials and Methods

Study area

Ӧland (567333deg N 166667deg E) a Baltic island located in Kalmar county (Fig 1) is Swedenrsquos second largest

island (~140km in length) It can be split broadly into three areas the north (N) centre (C) and south (S) There

are three typical habitats found on the island boreal forests Stora Alvaret and agricultural land The largest

portions of boreal forests are found in the far north the centre and a patch in the far south Forest stands are

dominated by birch (Betula pubescens B pendula) and Scots pine (Pinus sylvestris) with rowan (Sorbus

aucuparia) aspen (Populus tremula) grey alder (Alnus incana) and yew (Taxus baccata) interspersed

throughout with willow sp (Salix spp) in areas near water sources (Sӕther and Heim 1993) The field layer is

made up of primarily bilberry (Vaccinium myrtillus) lowbush cranberry (Vaccinium vitis-idӕa) and heather

(Calluna vulgaris) (Cederlund 1989) The patches of boreal forest in the north centre and south are isolated

from each other by agricultural areas which are distributed throughout the island particularly along the coastal

regions and the island centre The most southerly patch of forest was protected from becoming agricultural

due to its status as a royal hunting ground and an important stopover for migratory birds (Lars Edenius

personal communication April 09 2014) The southern part of Oumlland has the largest expanse of steppe-like

alvar grassland (Stora Alvaret) found in the world (~25500 ha) (Roseacuten 2006) which is found over dry shallow

nutrient-poor grazed soil (Bakker et al 1996) on top of superficial Ordovician limestone (Dengler et al 2006)

Conditions on Oumlland are milder than those found in other areas of Sweden as it is positioned in the ldquorain-

shadowrdquo of mainland Sweden (Prentice 2007) The only predators of moose found on Oumlland are hunters which

were banned from hunting in previous years

Fig 1 Location of Oumlland

8

Capture and Handling

A random sample of adult moose (n = 25) were darted sedated and equipped with GPSGSM neck collars

(Vectronic Aerospace GmbH Berlin Germany) during the winter of 2012 by the Moose Research Group

SLU Movement data were collected from GPS collars dating from 22022012 ndash 24042014 Collars were

fixed to return GPS locations approximately every 30 minutes

Data Screening

The sample contained both males and females (six males 19 females x female age = 95 years range 4-17

years) An initial inspection revealed that one female individual only returned fixed locations for a period of

eight months Locations ceased during the hunting period so the individual was presumed shot and was

removed from the data along with the males

The exact time between each location varied and sometimes no fix could be made The adehabitatLT package

(Calenge 2006) was used to standardise the data and overcome the location fixing errors The function setNA

was used to place NAs where relocations were missing The function sett0 was used to round the timing of

collection obtaining a regular trajectory with 30 minute intervals The final dataset used in the analysis

consisted of 302710 regular GPS data points from a sample size of n=18 individuals two individuals from the

north ten individuals from the centre and six individuals from the south

To address the question and to investigate the influence of climate on the space use patterns of moose the

analysis was performed at two scales The first included all annual movements of moose and the second at a

seasonal scale ie summer and winter The seasonal scales were defined according to the growing season (GS)

and winter season (WS) In Scandinavia the current method used to define the start of season (SOS) is the

period when the daily mean air temperature is above 5degC (GS) Methods of calculating SOS are advancing

with the use of the Normalized Difference vegetation Index (NDVI) becoming more popular The start and

end of the GS and WS were derived using the mean start and end dates for Oumlland suggested by the Norwegian

Meteorological Institute (DNMI) Nordic climate map report (Tveito et al 2001) The GS of this study is

defined as the period between 23-April-2012 to 07-Nov-2012 and the WS is defined as the period between 08-

Nov-2012 to 22-April-2013 (based on the current standard normal period 1961-90)

Home rangeUtilization distribution

Variation in ungulate home range size is known to be caused by changes in energy requirements and variation

in food availability (Tufto et al 1996 Kie et al 2010 Moreller et al 2013) With shifting climate causes shifts

in plant phenology and therefore the spatial and temporal distribution of ungulate food (Maringrell et al 2006)

Individuals alter their home ranges to meet their energy requirements to maintain their fitness (Albon et al

1987 White 1997 Festa-Bianchet et al 1998 Forchhammer et al 2001)

The most commonly cited definition of a home range is ldquothat area traversed by the animal during its normal

activities of food gathering mating and caring for youngrdquo (Burt 1943) This has now been expanded to

9 incorporate measures of space use using the utilization distribution (UD van Winkle 1975) which can be

described as the ldquorelative frequency distribution of an animalrsquos occurrence in all four dimensions of space

and timerdquo (Keating and Cherry 2009) Home range is viewed as a constant 2D polygon whereas UDs are

viewed as multiple 3D polygons that take into account the distribution as well as the intensity of animalrsquos

movements and space use within their home range (Kranstauber et al 2012) (see appendix A)

Estimations of each individualrsquos annual and seasonal UDs were found using the Biased Random Bridge (BRB)

kernel approach (Benhamou 2011) from the adehabitatHR package (Calenge 2006) in R It was chosen as it is

considered an improvement on the previously preferred Brownian bridge (BB) method (Horne et al 2007) The

BB is purely a diffusive movement process whereas the BRB is an advective-diffusive movement process BB

does not take into account changes in advection direction (drift) or strength BB assumes an animalrsquos

movement is purely random it moves from a starting point and ends up at the end location randomly By

adding the advection component the BRB takes into account that the animalrsquos movement is biased towards a

certain direction This allows for a more biologically relevant analysis (Benhamou and Corneacutelis 2010)

A grid was created using the minmax XY coordinates of all individuals (plusmn 10 km to increase the extent and

prevent the grid directly touching the XY locations) The resolution of the grid was fixed at a 25 m x 25 m

scale to match the resolution of the relevant habitat maps (Hagner et al 2005) By specifying these criteria the

resolution of the data remains consistent between individuals The diffusion coefficient determines the variance

in the location of the kernels between two locations This was calculated from each individualrsquos dataset using

the BRBD function and added to the BRB model (see Benhamou 2011) The strength and direction of BRB

advection can change between bridges whilst having to remaining constant To remain constant an upper Tmax

and lower Lmin time thresholds were set Successive relocations that exceeded Tmax or under Lmin were

removed from the UD calculations The 50 (UD50) and 95 (UD95) isopleths were then calculated from

the UD using the kernelarea function

Habitat

The scale of analysis was further divided following Johnson (1980) Habitat selection within the landscape

(second order selection) was studied by comparing the UD95 with available habitats in each of the three study

areas of Oumlland (UD95Area) Habitat selection within the home range (third order selection) was studied by

comparing the UD50 with the UD95 (UD50UD95)

12 habitat classes were used in the analysis agricultural land broad leaved forests clear felled areas coastal

coniferous forests freshwater areas moorsgrassland miresmarshes mixed forest sparsely vegetated areas

urban areas and younger forests The proportion of area covered by each of these habitat classes was

determined in the UD50 and UD95 Habitat data was obtained from satellite imagery generated by Svenska

Marktaumlckedata (Hagner et al 2005) The habitat maps were last updated in 2002 and have a resolution of 25

m

Compositional analysis ( habitat used habitat available) (Aebischer 1993) was used in conjunction with

the Jacobrsquos index (D) (eqn1) to quantify habitat selection (Jacobs 1974) Coastal areas were removed as not

10

all home ranges contained them This combined approach allowed identification of habitats that are used

disproportionally to their availability ie in a non-random manner (Beyer et al 2010) This is an indication of

which habitats are important for an individual

119863 = ( 119903minus119901

119903+119901minus2119903119901 ) (eqn1)

r = Proportion of habitat type used

p = Total proportion of habitat available

D = Jacobs index varies from -1 (strong avoidance) to +1 (strong preference) with values close to 0 indicating

the habitat is used in proportion to its availability

Activity

Activity level is measured as the mean daily movement (MDM) by the individual to investigate if individuals

in an areaseason moved more and hence were more active than those in other areasseasons Unfortunately

only two cows were collared in the north and were therefore left out of this analysis Moose were identified as

migratory using a modelling approach (see Bunnefeld et al 2011 for methods) Migratory individuals were

initially removed from the activity analysis (n=4)The reason is that both migratory journeys were completed

during the winter season thus increasing the mean daily distance travelled and potentially biasing the analysis

One individual was also removed due it its collar not returning relocations during the entirety of the WS

Diet analysis

The Ӧland project team conducted histology diet analysis on the rumen content of five individuals that were

shot in the centre and south of the island during the WS of 2013

Survival analysis

The Ӧland project team measured calf survival using the mark-resight method The presenceabsence of a calf

was recorded by tracking the cows at six occasions throughout the year These were at the start of the calving

season (mid-May to early June) twice through the summer before the hunt after the hunt and after winter

Survival trend was estimated using a Kaplan-Meier curve (Kaplan and Meier 1958) The Kaplan-Meier curve

shows the survival function (S (t)) ie the probability of an individual surviving until at least time t (Bewick

et al 2004) The probability of surviving from one period to the next is multiplied together to give the survival

function The S(t) of this study is the probability of an individual surviving from birth to after the hunt

(Method summary see appendix B)

11 Results

Home RangeUtilization Distribution

A total of 51 home ranges were estimated (17 annual 17 within growing season 17 within winter season)

Annual x = 9613 ha GS x = 6345 ha and WS x = 6023 ha (appendix C)

At the UD50 scale the largest annual and seasonal mean home ranges were located in the north Mean annual

and seasonal home ranges in the centre were slightly larger than the south This difference was not significant

(F(113)= 22 p= 87) (ANOVA) There was no significant difference between the seasonal home ranges (x

plusmnSD for GS = 116 plusmn38 for WS = 98 plusmn32 ha) (t(11) = 105 p = 32) or the seasonal home ranges in the centre

(t(8) = 101 p = 34 and the south (t(5) = 87 p = 42) (paired-sample t-test) (Table 1)

At the UD95 scale the largest annual and WS mean home ranges were located in the north The largest GS

mean home ranges were located in the centre Mean annual and seasonal home ranges in the centre were

slightly larger than the south This difference was not significant (F(113) = 59 p = 63) (ANOVA) There

was no significant difference between the seasonal home ranges (x plusmnSD for GS = 635 plusmn225 for WS = 602

plusmn161) (t(11) = 373 p = 71) or the seasonal home ranges in the centre (t(8)= 20 p = 84) or south (t(5) = 34

p = 74) (paired-sample t-test) (Table 1)

Table 1 Seasonal and annual mean UD50 and UD95 BRB kernel area in hectares (1ha = 001km2) for the north centre

and south of Oumlland (smoothing factor (h) =100)

Are

a

Annual UD50 GS UD50 WS UD50

n Mean SD Range n Mean SD Range n Mean SD Range

N 2 209 49 139-279 2 1215 39 67-176 2 1615 106 160-163

C 9 178 56 114-277 9 116 44 48-165 9 943 4 61-173

S 6 160 21 142-177 6 1085 51 65-149 6 933 35 69-125

Annual UD95 GS UD95 WS UD95

N 2 10905 5 1084-1097 2 630 199 349-911 2 809 11 794-824

C 9 997 32 682-1536 9 6531 22 295-945 9 637 17 454-941

S 6 9298 30 605-1088 6 5985 373 442-575 6 5526 20 349-679

12

Activity

MDM rates in the three areas (sedentary individuals) during the GS ranged from 14 ndash31 km day During the

WS ranged they ranged from 11-24 km day (Table 2) Movement rates during the GS were higher than the

WS (x plusmnSD for GS = 202 plusmn043 for WS = 161 plusmn043) but it was not statistically significant (t(11) = 200 p=

07) (paired sample t-test)

Table 2 Seasonal mean daily movement rates (km day) for each area and for both areas (total)

Are

a

GS WS

n Mean SE Range n Mean SE Range

C 8 20 003 14-18 8 20 004 12-24

S 4 22 016 17-31 4 12 02 11-13

Total 12 202 003 14-31 12 16 003 11-24

The seasonal MDM rates of all individuals (migratory and sedentary) were not significantly different (x plusmnSD

for GS = 20 plusmn04 for WS = 18 plusmn061) (t(14) = 139 p= 19) (paired sample t-test)

The WS home range size affects the WS MDM (F(110) = 927 p = 01) (ANOVA) The GS home range size

does not affect the GS MDM (F(110) = 36 p = 56) (ANOVA) When the WS home range outlier was

removed the home range size did not affect the WS MDM (F(111) = 186 p= 19) (ANOVA) The MDM was

lowest in February and highest in April (Table 3) there appeared to be no significant pattern in MDM between

the months (appendix D)

Table 3 Mean daily distance moved (km day) for sedentary individuals

Month Season Distance

April GS 0051

May GS 0044

June GS 0039

July GS 0041

August GS 0042

September GS 0044

October GS 0043

November WS 0043

December WS 0038

January WS 0035

February WS 0028

13 Habitat ndash Proportions

The largest proportion of habitat on the island is agriculture the lowest proportion of habitat (excluding coastal

and freshwater) is urban areas (Fig 2) The largest proportion of habitat in the north was coniferous forests

whilst agricultural areas were the dominant habitat types in the centre and south (Fig 3) The lowest proportion

(excluding coastal and freshwater areas) was urban

Fig 2 Proportion of different types of habitats found on Ӧland

Fig 3 Mean proportion of habitats contained within UD95 in the three areas of Oumlland C = Centre N = North S =

South

14

Habitat - Selection

Generally forest habitat types are the highest ranked whilst sparsely vegetated and urban areas are the lowest

ranked Both the second and third order habitat selection analyses gave significant results in the compositional

analysis (Table 4) In the third order analysis (UD50UD95) the centre displayed significant differences

between habitat types The coniferous forests are significantly preferred to sparsely vegetated areas and the

sparsely vegetated areas are significantly preferred to urban areas In the second order analysis (UD95Area)

significance was observed in the north and centre In the north younger forests are significantly preferred to

miresmarshes clear felled areas are significantly preferred to agriculture and freshwater areas are significantly

preferred to sparsely vegetated areas In the centre clear felled areas are significantly preferred to agricultural

land freshwater areas are significantly preferred to urban areas and grasslandmoors are significantly preferred

to sparsely vegetated areas

Table 4 Summary of second (UD95Area bottom) and third order (UD50UD95 top) ranked habitat preferences between

the three areas according to the compositional analysis (see appendix B)

Rank North Centre South

1 Broad Leaf Younger Coniferous

2 Mixed Broad Leaf Younger

3 MiresMarshes Clear Fell GrasslandMoors

4 Younger Mixed Clear Fell

5 Clear Fell GrasslandMoors Mixed

6 Coniferous MiresMarshes Broad Leaf

7 Freshwater Agriculture Freshwater

8 Agriculture Coniferous Agriculture

9 Sparse Veg Sparse Veg MiresMarshes

10 GrasslandMoors Urban Sparse Veg

11 Urban Freshwater Urban

Rank North Centre South

1 Broad Leaf Mixed Coniferous

2 Mixed Younger Clear Fell

3 GrasslandMoors Broad Leaf Younger

4 Younger Coniferous GrasslandMoors

5 MiresMarshes Clear Fell Agriculture

6 Coniferous Agriculture MiresMarshes

7 Clear Fell MiresMarshes Broad Leaf

8 Agriculture Freshwater Freshwater

9 Urban Urban Sparse Veg

10 Freshwater GrasslandMoors Mixed

11 Sparse Veg Sparse Veg Urban

Indicates significantly preferred to the habitat below (significant deviation from random at P lt05)

15 The Jacobs index revealed that generally the habitats preferred during the GS within the home range (third

order) are younger (0187) and broad leaf forests (0154) The strongest avoidance was for urban areas (-0627)

During the WS only agricultural areas are preferred (0129) and the strongest avoidance was for urban areas (-

0393) (Fig 4)

Fig 4 Third order seasonal habitat preference (UD50UD95) all individuals The index ranges from -1 (total avoidance)

to 1 (strongest preference) Close to 0 indicates used in proportion to its availability

Third order habitat preferencesavoidances by area

North During the GS the strongest preference was for broad leaf (0218) and mixed forests (0161) The

strongest avoidance was for urban (-1) and sparsely vegetated areas (-05) During the WS the strongest

preference was for miresmarshes (0228) The strongest avoidance was for grasslandmoors (-05)

Centre During the GS the strongest preference was for broad leaf (0233) and younger forests (0223) The

strongest avoidance was for urban (-0527) and agricultural land (-0362) During the WS preference was only

shown for agricultural land (0327) The strongest avoidance was for urban areas (-0679) and miresmarshes

(-0638)

South During the GS the strongest preference was for coniferous (0312) and younger forests (0242) The

strongest avoidance was for urban (-0353) and sparsely vegetated areas (-0330) During the WS

grasslandmoors (0106) were the strongest preference The strongest avoidance was for urban (-0666) and

sparsely vegetated areas (-0351)

16

The Jacobs indices revealed that generally the habitats preferred during the GS within the landscape

(UD95Area) are broad leaf (0216) and younger forests (0201) The strongest avoidance was for urban (-

0717) and freshwater areas (-0694) The strongest preference during the WS are coniferous forests (0242)

and the strongest avoidance was for freshwater (-0674) and urban areas (-0648) (Fig 5)

Fig 5 Second order seasonal habitat preference (UD50UD95) all individuals The index ranges from -1 (total avoidance)

to 1 (strongest preference) Close to 0 indicates used in proportion to its availability

Second order habitat preferencesavoidances by area

North During the GS the strongest preference was for broad leaf (0363) and mixed forests (00291) The

strongest avoidance was for sparsely vegetated (-0909) and freshwater areas (-0780) During the WS mixed

(0335) and coniferous forests (0316) were the strongest preference The strongest avoidance was for

freshwater (-0731) and urban areas (-05333)

Centre During the GS the strongest preference for mixed (0394) and younger forests (0286) The strongest

avoidance was for urban (-0733) and sparsely vegetated (-0708) areas During the WS mixed (0404) and

coniferous forests (0255) were the strongest preference The strongest avoidance was for freshwater (-0704)

and sparsely vegetated areas (-0655)

South During the GS the strongest preference for grasslandmoors (0287) and clear fells (0165) The

strongest avoidance was for urban areas (-0678) and mixed forests (-0491) During the WS grasslandmoors

(0425) and coniferous forests (0154) were the strongest preference The strongest avoidance was for urban (-

0876) and freshwater areas (-0587) (appendix E)

17 Diet

Diet analysis of the rumen content sampled from five individuals (C=2 S=3) revealed that almost two thirds

(69) of the diet is comprised of agricultural produce (apple winter rape and sugar beet) (Fig 6)

Fig 6 Diet analysis from the rumen samples of five moose individuals that were culled in 2013

31

2117

9

8

5

22

1 1

1

1

1 00 0

0

0Diet (2610-911 2013 5 individuals)

AppleWinter RapeSugar BeetUndefined WoodSallowBroad-leaf GrassPineAshOakCloverCurrantsUndefined plantElderberryJuniperRaspberry

18

Calf Survival

Of the 18 individuals 13 produced calves in which 7 produced twins giving a total of 20 calves A Kaplan-

Meier estimate was conducted to measure the fraction of calves living up to each period of the study (Fig 7)

The mean survival time is until period 235 (midend of summer) At the start of summer 85 of calves

remained (3 still born) The period between summer and before the hunt survival drops to 30 The survival

at the end of the study (after hunt) drops further to 20 leaving 4 calves surviving (see appendix B)

Fig 7 Kaplan-Meier estimate of moose calf survival during the study period Period 0 (Start of summer) period 1

(midend of summer) period 2 (before hunt) period 3 (after hunt) period 4 (after winter)

19 Discussion

The results of this study emphasised how strikingly different the habitat composition is along the latitudinal

gradient of Oumlland The three areas show contrasting proportions of the key habitat types The starkest

difference is the high proportion of coniferous forests and lack of agriculture in the north compared to the

centre and south The proportion of coniferous forest in the north is almost 5 times greater than in the centre

and south whereas the proportion of agriculture in the centre and south is more than double that in the north

The north is perceived to be composed of the most suitable habitat for moose (Dussault et al 2006) It has the

largest proportions of each forest type and a low proportion of agricultural land This provides suitable forage

and shelter throughout the year The south has a contrasting habitat composition to the north The proportions

of agricultural and sparsely vegetated areas are the highest between the three areas and the proportions of forest

habitats are the lowest The large proportion of sparsely vegetated areas and low proportions of forest habitat

corresponds to the large area of Stora Alvaret This is perceived to be the least suitable area due to a lack of

shelter (coniferous forest) and suitable forage The strong preference for coniferous and younger forest habitats

in the south would suggest that moose exhibit a functional response in habitat selection (Godvik et al 2009)

ie as the proportion of a particular habitat decreases the selection for that habitat increases in this case

coniferous forests which provide shelter and younger forest which provide good forage Similarly in the centre

moose show strong preference for mixed forests a habitat that is of low proportion

In view of the large variation in habitat proportions between the areas it is surprising that there is not a large

variation in the home range sizes or the activity levels annually or seasonally Home ranges are ultimately

chosen to maximise fitness and meet energy requirements by utilizing the available forage Seasonal conditions

change the availability and necessity of resources (food quality shelter) Unlike the GS during the WS

deciduous trees and shrubs are leafless and low-lying shrubs are under snow cover (Dussault et al 2005)

These changes are well known to cause populations to alter their activity and home ranges to meet energy

requirements (Mysterud et al 2001) Populations have been shown to increase or decrease their home ranges

during the two seasons The GS home ranges are often larger than the WS home ranges (Philips et al 1973

Mysterud et al 2001) In some cases they can be found to be almost double the size of the WS home ranges

(Cederlund and Okarma 1988) In other populations the WS home ranges are double the size of the GS home

ranges (Lynch and Morgantini 1984) or sizes do not significantly differ (Cederlund and Sand 1994)

Previous studies on moose find females generally show increased activity from the start on the GS due to

various factors eg reduced ruminating times increased metabolic needs and increased foraging bursts

(Wattles and DeStefano 2013) Increased metabolic needs during this time are a results of pregnancy and

lactation (Georgii 1980) During the height of the GS they usually show reduced activity levels through times

of increased thermal stress (Renecker and Hudson 1989 van Beest et al 2012) During the WS the depth and

the duration of snow cover are well known to affect the activity level (Telfer 1970 Mysterud and Oslashstbye 1999

Bjoslashrneraas et al 2011) During the WS generally home ranges are smaller and activity less due to lower

metabolic needs Moose activity is constrained by rumination during the WS this period is known to be longer

due to the change in diet (Cederlund 1989 Renecker Hudson 1989) This was not the case on Ӧland activity

20

was lowest in February which is a similar result to Cederlundrsquos (1989) paper However Ӧland moose did not

significantly alter their seasonal activity levels The fact that the annual and seasonal activity levels and home

ranges were similar could be a result of the mild winters on Oumlland during the study period (Smhise 2014)

During the study period the average number of snow days was 80 and the mean snow depth was 10cm

(appendix F) (Swedish Meterological and Hydrological Institute- SMHI) These mild conditions do not restrict

the movement of moose or obscure forage Moose are well adapted for movement in deep snow depths of 60-

86cm (Prescott 1968) are needed to truly restrict movement This finding was similar to the Sweanor and

Sandegren (1989) and Cederlund and Sand (1994) where the snow depth at their sites did not reach movement

restricting depths

The survival curve illustrates just how bad the calf survival is on Ӧland Survival falls from 85 at the start to

20 Out of 20 calves only four were alive at the end of the study The sharpest fall in survival was the period

between end of summer and before the hunt so the deaths were not due to hunting Previous calf autopsies

(Malmsten 2014a) have shown that cause of death was starvation mothers possibly either did not have milk

the calf was unable to feed or the mother abandoned the calf Closer field based observations are needed to

attain this knowledge Moose are seasonal polyoestral mammals (Monfort et al 1993) coming into oestrus

during late September early October (Garel et al 2009) (appendix F) The diet of the mother influences the

health of the calf and this period is when sodium is hard to find sodium is a key mineral in moose diets for

features such as reproduction (Belovsky and Jordan 1981) Moose gain sodium mainly through aquatic plants

(MacCracken et al 1993) However the compositional analysis shows that freshwater areas are often ranked

as one of the lowest used habitats and coastal areas were removed as the proportion found in the home ranges

was extremely low The Jacobs Index shows that the moose only prefer freshwater areas in the north UD50

during the WS The north individuals again are those that are showing typical moose habitat selection

It is known that habitat selection is hierarchical with habitats that increase fitness selected for and the effects

of limiting factors are reduced (Rettie and Messier 2000) At the UD95 during the GS moose preferred areas

of good forage (forests) and avoided areas of low forage (freshwater and sparsely vegetated areas) and areas

close to humans (urban) This is consistent with other reports (Laurian et al 2008 Torres et al 2011) Within

the UD50 there is a shift in preferences The good forage areas are again preferred during the GS however

during WS the only preferred habitat is often agricultural land During the WS there could be a steady supply

of supplementary feed available hence the high levels of agricultural produce found in the rumen content

samples and the high preference of agricultural areas This diet is unusual for moose previous studies of

Swedish moose diet have found the GS diet was dominated by birch willow and herbaceous plants and the

WS diet dominated by pine and birch (Cederlund and Nystrom 1981) The diet analysis was conducted during

the WS instead of being dominant pine composed just 2 Birch did not appear however unidentified wood

composed only 9 whereas agricultural produce accounted for 69 Supplementary feed may be perceived

by the moose in the centre and south as a vital forage source during the WS In fact in the centre the

agricultural land is the only preferred habitat at the UD50 It is unknown whether there are salt licks provided

in these areas Selection for a critical habitat is often thought to be a fixed factor The Oumlland population from

21 the three areas are close in proximity however they displayed contrasting preferences This is supported by the

Osko et al (2004) report that found two neighbouring moose populations that had access to the same habitats

displayed contrasting preferences Habitat preferences for populations of the same species are not necessarily

fixed They alter with varying levels of habitat abundance and limiting factors skewing what is preserved to

be critical

The main limitation encountered in this study was with the limited sample There was only data on two

individuals from the north of the island which led it being removed from many of the analysis Similarly due

to a lack of relocations from the collars being turned off at points throughout the year two further individuals

had to be removed from a majority of the analysis This reduced the sample size to 17 or 18 individuals

Similarly only 13 of the individuals from the study produced calves This unfortunately prevented including

survival into models Although the sample size was small it was accurate it was of high resolution over

300000 GPS points In future it would be beneficial to have a more standardised data set An equal sample of

individuals from the three areas would be advised along with ensuring the GPS collars are kept turned on for

the entirety of the growing and winter season to allow comparisons between years It would also be

advantageous to collect coordinates of the feeding sites along with the composition This could then be

compared with high use UD coordinates to look if moose are truly spending a majority of their foraging time

at feeding stations A study on the population densities of moose and the increasing population of roe deer

(Capreolus capreolus) would add the factor of competition into the model

The low calf survival on Ӧland is most likely the result of a combination of factors The lack of suitable habitat

reported in this study in conjunction with Malmstenrsquos (2014a) report on the threat of disease (Anaplasma

phagocytophilum) are probable influences on the calf survival on Ӧland On Ӧland there is an increasing

population of roe deer and large numbers of migratory birds both carriers of ticks and diseases The mild

conditions on Ӧland are advantageous for ticks the carriers of A phagocytophilum Fewer snow days and

shorter periods of snow cover along with dry conditions are favourable for ticks This could probably be one

of the reasons for females to be of lower quality and therefore not being able to ensure calf survival Moose

have to utilise areas where in other populations individuals tend to avoid Finally similar to many studies I

advocate further research using a stronger dataset and longer term monitoring

22

Acknowledgements

I am indebted to NJ Singh and A Allen for all their help and guidance through the whole of this study I

thank SLU for the support provided during this study in terms of data finances and facilities Thank you to

everyone at the Department of Wildlife Fish and Environmental Studies for being so friendly and

supportive I would like to thank L Edenius for driving me around the study area and S Michon and H

Khalil for keeping me sane with fika and training

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Bradshaw RHW Hannon GE Lister AM (2003) A long-term perspective on ungulate-vegetation

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Bunnefeld N Boumlrger L van Moorter B Rolandsen CM Dettki H Solberg EJ Ericsson G(2011) A model-

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Calenge C (2006) The package adehabitat for the R software a tool for the analysis of space and habitat use

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Calenge C (2011) Home Range Estimation in R the adehabitatHR package Office national de la classe et de

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Cederlund GN Nystroumlm A (1981) Seasonal differences between moose and roe deer in ability to digest

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Cederlund GN (1989) Activity patterns in moose and roe deer in a north boreal forest Holarctic Ecology

1239-45

Cederlund GN Sand H (1994) Home-range size in relation to age and sex in moose American Society of

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Clutton-Brock T Sheldon BC (2010) Individuals and populations the role of long-term individual based

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Cooke SJ Hinch SG Wikelski M Andrews RD Kuchel LJ Wolcott TG Butler PJ (2004) Biotelemerty a

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Crecircte M Courtois R (1997) Limiting factors might obscure population regulation of moose (Cervidae Alces

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Sedetalia) on the island of Ӧland (Sweden) in the context of north and central Europe

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Dussault C Courtois R Ouellet JP Girard I (2005) Space use of moose in relation to food availability

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Dussault C Courtois R Ouellet JP (2006) A habitat suitability index model to assess moose habitat selection

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Ericsson G Wallin K Ball JP Broberg M (2001) Age-related reproductive effort and senescence in free-

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Ericsson G Ball JP Danell K (2002) Moose offspring body mass along an altitudinal gradient Journal of

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Ericsson G Malmsten J Neumann W Singh NJ Dali AM Submitted Summer Calf Survival of

Scandinavian Moose along its Southern Distribution Range

25 Festa-Bianchet M Gaillard JM Jorgenson JT (1998) Mass and density-dependent reproductive success and

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Forchhammer MC Clutton-Brock TH Lindstroumlm J Albon SD (2001) Climate and population density induce

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Forchhammer MC Post E Stenseth NC Boertmann DM (2002) Long-term responses in arctic ungulate

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Gaillard JM Festa-Bianchet M Yoccoz NG (1998) Population dynamics of large herbivores variable

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Gaillard JM Festa-Bianchet M Yoccoz NG Loison A Toiumlgo C (2000a) Temporal variation in fitness

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Gaillard JM Festa-Bianchet M Delorme D Jorgenson J (2000b) Body mass and individual fitness in female

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Gaillard JM Hearingblewhite M Loison A Fuller M Powell R Basille M van Moorter B (2010) Habitat-

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Transactions of the Royal Society B 3652255-2265

Garel M Solberg EJ Sӕther B-E Groslashtan V Tufto J Heim M (2009) Age size and spatiotemporal variation

in ovulation patterns of a seasonal breeder the Norwegian moose (Alces alces) The American

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Georgii B (1980) Home range patterns of female red deer (Cervus elaphus L) in the Alps Oecologia

47278-285

Godvik IMR Loe LE Vik JO Veiberg V Langvatn R Mysterud A (2009) Temporal scales trade-offs and

functional responses in red deer habitat selection Ecology 90699ndash710

Gordon IJ Hester AJ Festa-Bianchet M (2004) Review The management of wild large herbivores to meet

economic conservation and environmental objectives Journal of Applied Ecology 411021-

1031

Hagner O Nilsson M Reese H Egberth M Olsson H (2005) Procedure for classification of forests for

CORINE land cover in Sweden In Oluić M (ed) New strategies for European remote sensing

Millpress Rotterdam pp 523ndash530

Hall LS Krausman PR Morrison ML (1997) The habitat concept and a plea for standard terminology

Wildlife Society Bulletin 25173-182

Harris RB Wall WA Allendorf FW (2002) Genetic consequences of hunting what do we know and what

should we do Wildlife Society Bulletin 30634-643

Herfindal I Saeligther B-E Solberg EJ Andersen R Hoslashgda KA (2006) Population characteristics predict

responses in moose body mass to temporal variation in the environment Journal of Animal

Ecology 75 (5) 1110-1118

Horne JS Garton ED Krone SM Lewis JS (2007) Analysing animal movements using Brownian bridges

Ecological Society of America Ecology 882354-2363

Hornok S Kovaacutets D Csoumlrgo T Meli M Goumlnczi E Hadnagy Z Takaacutecs N Farkas R Hofmann-Lehmann R

(2014) Birds as potential reservoirs of tick-borne pathogens first evidence of bacteraemia

with Rickettsia Helvetica Parasites and Vectors 7128

26

Jacobs J (1974) Quantitative measurement of food selection a modification of the forage ratio and Ivlevrsquos

Electivity Index Oecologia 14(4)413-417

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ungulates Journal of Applied Ecology 451339-1348

Johnson DH (1980) The comparison of usage and availability measurements for evaluating resource

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Jonsson F (2007) rsquoDen oumllaumlndska aringlgstammens foumlrvaltingrsquo Departement of Wildlife Fish and Environmental

Studies SLU Examensarbete I aumlmnet biologi vol 20072

Kaplan EL Meier P (1958) Nonparametric estimation from incomplete observation Journal of the American

Statistical Association 53457-481

Keating KA Cherry S (2009) Modelling utilization distributions in space and time Ecology 90(7)1971-

1980

Kie JG Matthiopolos J Fieberg J Powell RA Cagnacci F Mitchell SM Gaillard JM Moorcroft PR (2010)

The home range concept are traditional estimators still relevant with modern telemetry

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Jaumlgarefoumlrbundet Oumlster-Malma 20092

Kranstauber B Kays R LaPoint SD Wikelski M Safi K (2012) A dynamic Brownian bridge movement

model to estimate utilization distributions for heterogeneous Animal movement Journal of

Animal Ecology 81738-746

Laurian C Ouellet JP Courtois R Breton L St-Onge S (2000) Effects of intensive harvesting on moose

reproduction Journal of Applied Ecology 37515-531

Laurian C Dussault C Ouellet JP Courtois R Poulin M Breton L (2008) Behaviour of moose relative to a

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Lavsund S Nygreacuten T Solberg EJ (2003) Status of moose populations and challenges to moose management

in Fennoscandia Alces 39109-130

Lenarz MS Fieberg J Schrage MW Edwards AJ (2010) Living on the edge viability of moose in

northeastern Minnesota The Journal of Wildlife Management 74(5)1013-1023

Lindstroumlm J (1999) Early development and fitness in birds and mammals Trends in Ecology and Evolution

14343-348

Linnell JDC Aanes R Andersen R (1995) Who killed Bambi The role of predation in the neonatal

mortality of temperate ungulates Wildlife Biology 1209-223

Lomas LA Bender LC (2007) Survival and cause-specific mortality of neonatal mule deer fawns north-

central New Mexico Journal of Wildlife Management 71884ndash894

Lynch GM Morgantini LE (1984) Sex and age differential in seasonal home range size of moose in

northcentral Alberta 1971-1979 Alces 2061-78

MacCracken JG Ballenberghe VV Peek JM (1993) Use of aquatic plants by moose sodium hunger or

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27

Malmsten J Wideacuten DG Rydevik G Yon L Hutchings MR Thulin CG Soumlderquist L Aspan A Stuen S

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University of Agricultural Sciences (SLU) Umearing

Malmsten J Soumlderquist L Thulin C Wideacuten DG Yon L Hutchings MR Dalin A (2014b) Reproductive

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28

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29

Tveito OE Foslashrland EJ Alexandersson H Drebs A Jonsson T Vaarby-Laursen E (2001) Nordic climate

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van Beest FM van Moorter B Milner JM (2012) Temperature-mediated habitat use and selection by a heat

sensitive northern ungulate Animal Behaviour 84(3)723-735

van Winkle W (1975) Comparision of several probabilistic home-range models Journal of Wildlife

Management 39118-123

Verme LJ Ullrey DE (1984) Physiology and nutrition White-tailed deer ecology and management (Ed By

Halls LK) pp 91-118 Stackpole Harrisburg Pennsylvania

Wattles DW DeStefano (2013) Space use and movements of moose in Massachusetts Implications for

conservation of large mammals in a fragmented environment Alces 4965-81

White RG Rowell JE Hauer WE (1997) The role of nutrition body condition and lactation on calving

success in muskoxen Journal of Zoology 24313-20

30

Appendix A

Introduction

Fig 1 Summary chart of factors affecting the life history and therefore the long term fitness of a population

Fig 2 Summary chart 2

Movement

Habitat

Climate

Topography

Competition

FoodWater

Disease

Die

Survive

Reproduce

Population long term fitness

31 Appendix B

Method and Materials

Fig 1 Summary of processes

32

Fig 2 Examples of classical kernel home range output and Brownian bridge kernel home range (Calenge 2011) The

right image includes the area between relocations ie the movement path in contrast to the classic kernel home range

in the left image

33 Appendix C

Home ranges

Fig 1 Example of a non-migratory (ID006) individuals BRB kernel area From top left annual growing and winter

season UD50 (black contour) and UD95 (red contour)

Fig 2 Example of a migratory (ID012) individuals BRB kernel area From the left annual growing and winter season

UD50 (black contour) and UD95 (red contour)

34

Table 1 Annual and seasonal UD50 and UD95 areas (ha) for all individuals

ID Annual GS WS

UD50 UD95 UD50 UD95 UD50 UD95

ID004 190 924 93 531 173 941

ID005 230 1364 132 945 72 682

ID006 162 1036 89 736 70 611

ID008 277 1536 156 809 78 738

ID009 137 834 48 295 126 653

ID010 114 682 83 448 96 488

ID012 177 963 123 544 76 545

ID014 160 1018 87 575 89 662

ID015 172 858 128 532 109 679

ID016 156 1047 65 455 92 534

ID017 153 1088 149 1043 69 349

ID019 279 1097 176 911 163 824

ID020 139 1084 67 349 160 794

ID022 159 811 131 638 61 454

ID023 187 1061 147 771 72 705

ID024 146 725 165 705 101 458

ID026 142 605 99 442 125 547

ID027 126 567 75 461 48 277

35 Appendix D

Activity

Fig 1 Mean daily movement during the study period GS 23-April-2012 to 07-Nov-2012 WS 08-Nov-2012 to

22-April-2013 (number indicates month)

Fig 2 Mean daily movement in the centre and south during the GS and WS

36

Appendix E

Habitat Proportions

Fig 1 All individualsrsquo seasonal habitat proportions within the UD95

37 Habitat Selection

Table 1 Simplified ranking matrices comparing proportional habitat use within the second order (UD95Area) with

proportions of total available habitat types Mean value on the matrix was replaced by a sign a triple sign represents

significant deviation from random at P lt05 Highlighted habitat is ranked 1st

North A

gri

cult

ure

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 --- --- - +++ --- --- --- +++ +++ --- 8

Broad Leaf +++ 0 +++ + +++ +++ +++ + +++ +++ +++ 1

Clear Fell +++ --- 0 + +++ - - --- +++ +++ --- 7

Coniferous + - - 0 +++ - - --- +++ +++ - 6

Freshwater --- --- --- --- 0 --- --- --- +++ - --- 10

Grassland

Moors +++ --- + + +++ 0 +++ - +++ +++ + 3

MiresMarshes +++ --- + + +++ --- 0 - +++ +++ --- 5

Mixed +++ - +++ +++ +++ + + 0 +++ +++ + 2

Sparse Veg --- --- --- --- --- --- --- --- 0 --- --- 11

Urban --- --- --- --- + --- --- --- +++ 0 --- 9

Younger +++ --- +++ + +++ - +++ - +++ +++ 0 4

Rank Order and

Significance

Broad Leafgt Mixedgt GrasslandMoorsgt Youngergtgtgt MiresMarshesgt Coniferousgt

Clear Fellgtgtgt Agriculturegtgtgt Urbangt Freshwatergtgtgt Sparse Veg

Central

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 --- --- --- + +++ + --- +++ +++ --- 6

Broad Leaf +++ 0 +++ + +++ +++ + - +++ +++ - 3

Clear Fell +++ --- 0 - +++ +++ + --- +++ +++ --- 5

Coniferous +++ - + 0 +++ +++ + --- +++ +++ - 4

Freshwater - --- --- --- 0 +++ - --- +++ +++ --- 8

Grassland

Moors --- --- --- --- --- 0 --- --- +++ - --- 10

MiresMarshes - - - - + +++ 0 - +++ +++ - 7

Mixed +++ + +++ +++ +++ +++ + 0 +++ +++ + 1

Sparse Veg --- --- --- --- --- --- --- --- 0 - --- 11

Urban --- --- --- --- --- + --- --- + 0 --- 9

Younger +++ + +++ + +++ +++ + - +++ +++ 0 2

Rank Order and

Significance

Mixedgt Youngergt Broad Leafgt Coniferousgt Clear Fellgtgtgt Agriculturegt

MiresMarshesgt Freshwatergtgtgt Urbangt GrasslandMoorsgtgtgt Sparse Veg

38

South

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 + - - + - + +++ +++ +++ - 5

Broad Leaf - 0 - - + - - +++ + +++ - 7

Clear Fell + + 0 - + + + +++ + +++ + 2

Coniferous + + + 0 +++ + + +++ + +++ + 1

Freshwater - - - --- 0 - - + + +++ - 8

Grassland

Moors + + - - + 0 + + +++ + - 4

MiresMarshes - + - - + - 0 +++ + +++ - 6

Mixed --- --- --- --- - - --- 0 + + --- 10

Sparse Veg --- - - - - --- - - 0 + - 9

Urban --- --- --- --- --- - --- - - 0 --- 11

Younger + + - - + + + +++ + +++ 0 3

Rank Order

and

Significance

Coniferousgt Clear Fellgt Youngergt GrasslandMoorsgt Agriculturegt MiresMarshesgt Broad Leafgt

Freshwatergt Sparse Veggt Mixedgt Urban

Table 2 Simplified ranking matrices comparing proportional habitat use within the third order (UD50UD95) with

proportions of total available habitat types Mean value on the matrix was replaced by a sign a triple sign represents

significant deviation from random at P lt05 Highlighted habitat is ranked 1st

North

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 --- --- --- - + --- --- + +++ --- 8

Broad Leaf +++ 0 +++ + + + + + +++ +++ + 1

Clear Fell +++ --- 0 + + + - - + +++ - 5

Coniferous +++ - - 0 + + --- --- +++ +++ - 6

Freshwater + - - - 0 +++ - - +++ +++ - 7

GrasslandMoors - - - - --- 0 - - - + - 10

MiresMarshes +++ - + +++ + + 0 - +++ +++ + 3

Mixed +++ - + +++ + + + 0 +++ +++ + 2

Sparse Veg - --- - --- --- + --- --- 0 +++ --- 9

Urban --- --- --- --- --- - --- --- --- 0 --- 11

Younger +++ - + + + + - - +++ +++ 0 4

Rank Order and

Significance

Broad Leafgt Mixedgt MiresMarshesgt Youngergt Clear Fellgt Coniferousgt Freshwatergt

Agriculturegt Sparse Veggt GrasslandMoorsgt Urban

39

Central

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 --- --- + + - - - + +++ --- 7

Broad Leaf +++ 0 + +++ + + + + + +++ - 2

Clear Fell +++ - 0 +++ + + + + + +++ - 3

Coniferous - --- --- 0 + - - --- +++ + --- 8

Freshwater - - - - 0 --- - - --- - - 11

GrasslandMoors + - - + +++ 0 + - + +++ - 5

MiresMarshes + - - + + - 0 + + +++ - 6

Mixed + - - +++ + + - 0 +++ +++ - 4

Sparse Veg - - - --- +++ - - --- 0 +++ - 9

Urban --- --- --- - + --- --- --- --- 0 --- 10

Younger +++ + + +++ + + + + + +++ 0 1

Rank Order and

Significance

Youngergt Broad Leafgt Clear Fellgt Mixedgt GrasslandMoorsgt MiresMarshesgt

Agriculturegt Coniferousgtgtgt Sparse Veggtgtgt Urbangt Freshwater

South

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 - - - - - + - +++ + --- 8

Broad Leaf + 0 - --- + - + - +++ + - 6

Clear Fell + + 0 - + - + - +++ + - 4

Coniferous + +++ + 0 + + +++ + +++ + + 1

Freshwater + - - - 0 - - + + + - 7

GrasslandMoors + + + - + 0 + + + + - 3

MiresMarshes - - - --- + - 0 - + + - 9

Mixed + + + - - - + 0 + + - 5

Sparse Veg --- --- --- --- - - - - 0 + --- 10

Urban - - - - - - - - - 0 - 11

Younger +++ + + - + + + + +++ + 0 2

Rank Order and

Significance

Coniferousgt Youngergt GrasslandMoorsgt Clear Fellgt Mixedgt Broad Leafgt Freshwatergt

Agriculturegt MiresMarshesgt Sparse Veggt Urban

40

Table 3 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the GS according to Jacobs index

Ran

k North Centre South

50 95 50 95 50 95

+ - + - + - + - + - + -

1 Broad

Leaf Urban Broad Leaf Sparse Veg

Broad

Leaf Urban Mixed Urban Coniferous Urban

Grassland

Moors Urban

2 Mixed Sparse Veg Mixed Freshwater Younger Agriculture Younger Sparse Veg Younger Sparse Veg Clear Fell Mixed

3 Mires

Agriculture Grassland

Urban Clear

Fell Coniferous Broad Leaf

Grassland

Moors

Clear Fell Agriculture Coniferous Sparse Veg

Marshes Moors

4 Younger Grassland

Younger Agriculture

Freshwater Coniferous Freshwater

Broad Leaf Mires

Younger Freshwater

Moors Marshes

5 Clear

Fell Freshwater

Mires Coniferous

Sparse Veg Clear Fell Agriculture

Freshwater Agriculture

Marshes

6 Coniferous Clear Fell

Mires

Marshes

Mires

Grassland

Moors

Mires

Marshes Marshes

7 Mixed Mixed Broad Leaf

8 Grassland

Moors

41

Table 4 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the WS according to Jacobs index

Ran

k North Centre South

50 95 50 95 50 95

+ - + - + - + - + - + -

1 Mires

Marshes

Grassland

Moors Mixed Freshwater Agriculture Urban Mixed Freshwater

Grassland

Moors Urban GrasslandMoors Urban

2 Freshwater Mixed Coniferous Urban Mires

Marshes Coniferous Sparse Veg Agriculture

Sparse

Veg Coniferous Freshwater

3 Urban Coniferous Younger Grassland

Moors Freshwater Younger Urban Freshwater

Broad

Leaf Agriculture Mixed

4 Younger Agriculture Sparse Veg Broad

Leaf

Broad

Leaf

Grassland

Moors Mixed Broad Leaf

5 Clear Fell Agriculture Coniferous Agriculture Mires

Marshes Clear Fell

6 Sparse

Veg

Mires

Marshes Mixed

Mires

Marshes

Clear

Fell

Mires

Marshes

7 Broad

Leaf Clear Fell Younger Clear Fell Younger Sparse Veg

8 Clear Fell Younger

9 Sparse

Veg

10 Grassland

Moors

42

Table 5 Second order (UD95Area) individual selectionavoidance for the GS and WS according to the Jacobs index

ID GS WS

Select Avoid Select Avoid

ID004 Younger Sparsely Vegetated MiresMarshes Sparsely Vegetated

ID005 MiresMarshes Sparsely Vegetated Coniferous GrasslandMoors

ID006 Coniferous Sparsely Vegetated Mixed Freshwater

ID008 Mixed Sparsely Vegetated Mixed Freshwater

ID009 Mixed Sparsely Vegetated Mixed GrasslandMoors

ID010 MiresMarshes Freshwater GrasslandMoors Freshwater

ID012 Broad Leaf Sparsely Vegetated Coniferous Urban

ID014 Clear Fell Sparsely Vegetated GrasslandMoors Sparsely Vegetated

ID015 GrasslandMoors Urban GrasslandMoors Freshwater

ID016 GrasslandMoors Freshwater GrasslandMoors Freshwater

ID017 GrasslandMoors Mixed Sparsely Vegetated Mixed

ID019 Mixed Sparsely Vegetated Mixed Urban

ID020 Broad Leaf Sparsely Vegetated Coniferous GrasslandMoors

ID022 MiresMarshes Freshwater MiresMarshes Freshwater

ID023 MiresMarshes GrasslandMoors Mixed Freshwater

ID024 Broadleaf Urban Broad Leaf Urban

ID026 GrasslandMoors Freshwater GrasslandMoors Freshwater

ID027 GrasslandMoors Urban Sparsely Vegetated Freshwater

43 Table 6 Third order (UD50UD95) individual selectionavoidance for the GS and WS according to the Jacobs index

ID GS WS

Select Avoid Select Avoid

ID004 Broad Leaf Mixed GrasslandMoors Freshwater

ID005 Broad Leaf Freshwater Agriculture Freshwater

ID006 Clear Fell Freshwater Agriculture MiresMarshes

ID008 MiresMarshes Freshwater Agriculture Urban

ID009 Freshwater Agriculture Agriculture Freshwater

ID010 Mixed Urban Sparsely Vegetated Urban

ID012 Coniferous GrasslandMoors Freshwater Urban

ID014 Urban Agriculture Freshwater Urban

ID015 Mixed Forest Urban Clear Fell Urban

ID016 Freshwater Urban GrasslandMoors Mixed

ID017 Coniferous Mixed Coniferous Broad Leaf

ID019 Broad Leaf GrasslandMoors Urban GrasslandMoors

ID020 Freshwater Urban Freshwater Agriculture

ID022 MiresMarshes Urban Broad Leaf GrasslandMoors

ID023 Freshwater Mixed Agriculture Freshwater

ID024 Mixed Freshwater Mixed Freshwater

ID026 Mixed MiresMarshes Sparsely Vegetated GrasslandMoors

ID027 Freshwater MiresMarshes GrasslandMoors Broad Leaf

44

Fig 2 North third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)

45

Fig 3 Centre third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)

46

Fig 4 South third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)

47

Fig 5 North second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)

48

Fig 6 Centre second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)

49

Fig 7 South second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)

50

Appendix F

Background

Fig 1 Daily mean snow depth and duration during the study period (Andrew Allen)

Female Moose Reproduction

Moose are seasonal polyoestral mammals (Monfort et al 1993) coming into oestrus during late September

early October (Garel et al 2009) The Swedish moose cow population reaches puberty between the ages 25

and 35 (Sand and Cederlund 1993) during which the reproductive period begins with the onset of ovulation

The age an individual reaches puberty is dependent on their body condition they have to reach a weight

threshold to reach puberty and become reproductive (Sand 1996) If she is over the weight threshold she will

go into oestrus in the autumn If she does not reach the weight threshold then she will go into oestrus the

following autumn if successful she will give birth to individual or twin calves in late May to early June

(Ericsson et al 2001) and therefore reach sexual maturity (Malmsten et al 2014b) Fecundity is related to

both the condition and the age of the cow Cows go through senescence at 12 years of age (Ericsson et al

2001) Providing calves with the required level of nutrition demands high energy and protein resources from

the mother during senescence this becomes harder to achieve leading to decreased levels of parental care

and higher levels of calf mortality

Page 5: Habitat-performance relationships on an island: fitness ...navinderjsingh.weebly.com/uploads/1/1/2/2/11224342/... · Conditions on Öland are milder than those found in other areas

5 Introduction

The population size of animals varies in space and time (Turchin 2001) This variation is driven by a

combination of internal as well as external factors that drive changes in survival and reproduction of

individuals (Brown 2011) Internal factors are associated with life history such as sex age body mass and

generation time whereas the external factors include climatic factors (characterised as density independent)

competition food disease (characterised as density dependent) and human influence (appendix A) Long-term

changes in population size therefore determine the long-term fitness of individuals and cohorts in a population

(Albon et al 1987) However little is known about how these factors interact to produce short and long term

variation in demography and population dynamics across space Although difficult understanding causes of

variation of population size is crucial to effective population conservation and management (Lavsund et al

2003 McLoughlin et al 2011) The interplay and relative contribution of the above factors are best shown

from species with short generation times or from long-term monitoring studies

Ungulates are most commonly studied due to their international economic and recreational value large body

sizes and the relative ease of marking handling and capturing them (Forchhammer et al 2002 Bradshaw et

al 2003 Gordon et al 2004 Clutton-Brock and Sheldon 2010) Large herbivores tend to display low fecundity

and high adult survivorship (Gaillard et al 2000a) Past studies have revealed important details about the

factors affecting their population dynamics An ungulate life cycle is usually classified based on defined age

classes new-born weaned young yearlings two-year-olds prime-aged adults and senescent adults (older than

seven years) New-born survival is highly dependent on climatic conditions predation and the level of maternal

care and condition ie quality of milk and reproductive experience (Gaillard et al 2000a Testa 2004 Baringrdsen

et al 2008) Weaned young and yearlings survival tends to be independent of the mothers care and affected

most often by climatic conditions ie severe winters disease and predation (Bartmann et al 1992) Survival

of two-year olds and adults is influenced mainly by predation (Modafferi 1997) Males generally experience a

lower survival rate than females due to the pressure of the rut and male biased hunting (Mysterud et al 2005)

Conditions experienced during a calfrsquos early development not only cause immediate effects on its future

performance but also delayed effects Calf development (weight) affects its future reproductive success

(performance) by effecting adult body size and future calf body size (Albon et al 1987 Lindstroumlm 1999

Forchhammer et al 2002)

The moose (Alces alces) is a large ungulate widely distributed across the northern hemisphere It is the largest

and only solitary member of the deer family (Cervidae) In Sweden it is found throughout the country in boreal

forests with the exception of the island of Gotland (Brandin 2009) Sweden has the largest population of moose

in Europe with approximately 300000-350000 individuals (Singh et al 2014) A part of Swedenrsquos moose

population is influenced to some extent by predators such as brown bears (Ursus arctos) and wolves (Canis

lupus) however in predator free populations individuals are influenced mainly by stochastic environmental

conditions population density traffic and above all hunting (Sӕther 1997) (appendix A) Moose are hunted

all across Scandinavia and the overall value of moose hunting is estimated to be 145 billion SEK per year

6

(158 billion Euro) (Boman et al 2011) Each year in Sweden 90000-100000 individuals are harvested

providing approximately 85 million kilograms of moose meat (Kindberg et al 2009) A common method of

selecting which individuals are to be harvested is to assess the reproductive value of an individual and remove

the lownon-reproductive individuals such as calves bulls and cows without calves (Ball et al 1999 Ericsson

et al 2001) Hunting is biased towards bulls with large trophy antlers often resulting in a skewed sex ratio

(Laurian et al 2000 Harris et al 2002 Milner et al 2007)

Moose are known to have a generally high calf survival noted through studies from predator free areas in both

North America and Europe (Linnell et al 1995 Crecircte and Courtois 1997 Swenson et al 2007) A number of

other factors are nevertheless known to affect the survival during their first summer such as climatic variation

malnutrition abandonment disease and poor maternal investment (Verme and Ullrey 1984 Gaillard et al

2000b Lomas and Bender 2007 Ericsson et al 2002 Herfindal et al 2006 Lenarz et al 2010) Low survival

in single odd years has been attributed to weather and low food quality

During recent years moose populations appear to be under environmental stress across their southern range

ascertained by studies reporting low calf survival from both North America and Sweden (Monteith et al in

press Ericsson et al submitted) A similar situation has been reported recently on the island of Oumlland in

southern Sweden where the harvesting of moose was postponed from 2001 to 2005 by mutual agreement

between hunters This was due to a fear of population collapse due to poor management strategies in previous

years that lead to a suspected unsustainable harvest The four-year harvesting break resulted in a balanced sex

ratio and age distribution (Jonsson 2007) In 2006 however it was brought to the attention of the department

of Pathology and Wildlife Diseases at the Swedish National Veterinary Institute in Uppsala (SVA) that there

was an unusually low number of calves observed on the island Malmsten (2014a) conducted a follow up study

during 2012 and 2013 and found that summer calf survival of individuals from Oumlland was only 318 and

158 respectively When compared to calf survival from two other sites in southern Sweden (Kronoberg and

Soumldermanland) with rates all above 73 for both years this figure was regarded as very worrying and

prompted a need for an in-depth exanimation of the factors determining such low calf survival With this above

rationale in mind this study investigates the habitat performance relationships of female moose on the island

of Oumlland This study also provides a model for examining the factors affecting population dynamics on an

island

7 Materials and Methods

Study area

Ӧland (567333deg N 166667deg E) a Baltic island located in Kalmar county (Fig 1) is Swedenrsquos second largest

island (~140km in length) It can be split broadly into three areas the north (N) centre (C) and south (S) There

are three typical habitats found on the island boreal forests Stora Alvaret and agricultural land The largest

portions of boreal forests are found in the far north the centre and a patch in the far south Forest stands are

dominated by birch (Betula pubescens B pendula) and Scots pine (Pinus sylvestris) with rowan (Sorbus

aucuparia) aspen (Populus tremula) grey alder (Alnus incana) and yew (Taxus baccata) interspersed

throughout with willow sp (Salix spp) in areas near water sources (Sӕther and Heim 1993) The field layer is

made up of primarily bilberry (Vaccinium myrtillus) lowbush cranberry (Vaccinium vitis-idӕa) and heather

(Calluna vulgaris) (Cederlund 1989) The patches of boreal forest in the north centre and south are isolated

from each other by agricultural areas which are distributed throughout the island particularly along the coastal

regions and the island centre The most southerly patch of forest was protected from becoming agricultural

due to its status as a royal hunting ground and an important stopover for migratory birds (Lars Edenius

personal communication April 09 2014) The southern part of Oumlland has the largest expanse of steppe-like

alvar grassland (Stora Alvaret) found in the world (~25500 ha) (Roseacuten 2006) which is found over dry shallow

nutrient-poor grazed soil (Bakker et al 1996) on top of superficial Ordovician limestone (Dengler et al 2006)

Conditions on Oumlland are milder than those found in other areas of Sweden as it is positioned in the ldquorain-

shadowrdquo of mainland Sweden (Prentice 2007) The only predators of moose found on Oumlland are hunters which

were banned from hunting in previous years

Fig 1 Location of Oumlland

8

Capture and Handling

A random sample of adult moose (n = 25) were darted sedated and equipped with GPSGSM neck collars

(Vectronic Aerospace GmbH Berlin Germany) during the winter of 2012 by the Moose Research Group

SLU Movement data were collected from GPS collars dating from 22022012 ndash 24042014 Collars were

fixed to return GPS locations approximately every 30 minutes

Data Screening

The sample contained both males and females (six males 19 females x female age = 95 years range 4-17

years) An initial inspection revealed that one female individual only returned fixed locations for a period of

eight months Locations ceased during the hunting period so the individual was presumed shot and was

removed from the data along with the males

The exact time between each location varied and sometimes no fix could be made The adehabitatLT package

(Calenge 2006) was used to standardise the data and overcome the location fixing errors The function setNA

was used to place NAs where relocations were missing The function sett0 was used to round the timing of

collection obtaining a regular trajectory with 30 minute intervals The final dataset used in the analysis

consisted of 302710 regular GPS data points from a sample size of n=18 individuals two individuals from the

north ten individuals from the centre and six individuals from the south

To address the question and to investigate the influence of climate on the space use patterns of moose the

analysis was performed at two scales The first included all annual movements of moose and the second at a

seasonal scale ie summer and winter The seasonal scales were defined according to the growing season (GS)

and winter season (WS) In Scandinavia the current method used to define the start of season (SOS) is the

period when the daily mean air temperature is above 5degC (GS) Methods of calculating SOS are advancing

with the use of the Normalized Difference vegetation Index (NDVI) becoming more popular The start and

end of the GS and WS were derived using the mean start and end dates for Oumlland suggested by the Norwegian

Meteorological Institute (DNMI) Nordic climate map report (Tveito et al 2001) The GS of this study is

defined as the period between 23-April-2012 to 07-Nov-2012 and the WS is defined as the period between 08-

Nov-2012 to 22-April-2013 (based on the current standard normal period 1961-90)

Home rangeUtilization distribution

Variation in ungulate home range size is known to be caused by changes in energy requirements and variation

in food availability (Tufto et al 1996 Kie et al 2010 Moreller et al 2013) With shifting climate causes shifts

in plant phenology and therefore the spatial and temporal distribution of ungulate food (Maringrell et al 2006)

Individuals alter their home ranges to meet their energy requirements to maintain their fitness (Albon et al

1987 White 1997 Festa-Bianchet et al 1998 Forchhammer et al 2001)

The most commonly cited definition of a home range is ldquothat area traversed by the animal during its normal

activities of food gathering mating and caring for youngrdquo (Burt 1943) This has now been expanded to

9 incorporate measures of space use using the utilization distribution (UD van Winkle 1975) which can be

described as the ldquorelative frequency distribution of an animalrsquos occurrence in all four dimensions of space

and timerdquo (Keating and Cherry 2009) Home range is viewed as a constant 2D polygon whereas UDs are

viewed as multiple 3D polygons that take into account the distribution as well as the intensity of animalrsquos

movements and space use within their home range (Kranstauber et al 2012) (see appendix A)

Estimations of each individualrsquos annual and seasonal UDs were found using the Biased Random Bridge (BRB)

kernel approach (Benhamou 2011) from the adehabitatHR package (Calenge 2006) in R It was chosen as it is

considered an improvement on the previously preferred Brownian bridge (BB) method (Horne et al 2007) The

BB is purely a diffusive movement process whereas the BRB is an advective-diffusive movement process BB

does not take into account changes in advection direction (drift) or strength BB assumes an animalrsquos

movement is purely random it moves from a starting point and ends up at the end location randomly By

adding the advection component the BRB takes into account that the animalrsquos movement is biased towards a

certain direction This allows for a more biologically relevant analysis (Benhamou and Corneacutelis 2010)

A grid was created using the minmax XY coordinates of all individuals (plusmn 10 km to increase the extent and

prevent the grid directly touching the XY locations) The resolution of the grid was fixed at a 25 m x 25 m

scale to match the resolution of the relevant habitat maps (Hagner et al 2005) By specifying these criteria the

resolution of the data remains consistent between individuals The diffusion coefficient determines the variance

in the location of the kernels between two locations This was calculated from each individualrsquos dataset using

the BRBD function and added to the BRB model (see Benhamou 2011) The strength and direction of BRB

advection can change between bridges whilst having to remaining constant To remain constant an upper Tmax

and lower Lmin time thresholds were set Successive relocations that exceeded Tmax or under Lmin were

removed from the UD calculations The 50 (UD50) and 95 (UD95) isopleths were then calculated from

the UD using the kernelarea function

Habitat

The scale of analysis was further divided following Johnson (1980) Habitat selection within the landscape

(second order selection) was studied by comparing the UD95 with available habitats in each of the three study

areas of Oumlland (UD95Area) Habitat selection within the home range (third order selection) was studied by

comparing the UD50 with the UD95 (UD50UD95)

12 habitat classes were used in the analysis agricultural land broad leaved forests clear felled areas coastal

coniferous forests freshwater areas moorsgrassland miresmarshes mixed forest sparsely vegetated areas

urban areas and younger forests The proportion of area covered by each of these habitat classes was

determined in the UD50 and UD95 Habitat data was obtained from satellite imagery generated by Svenska

Marktaumlckedata (Hagner et al 2005) The habitat maps were last updated in 2002 and have a resolution of 25

m

Compositional analysis ( habitat used habitat available) (Aebischer 1993) was used in conjunction with

the Jacobrsquos index (D) (eqn1) to quantify habitat selection (Jacobs 1974) Coastal areas were removed as not

10

all home ranges contained them This combined approach allowed identification of habitats that are used

disproportionally to their availability ie in a non-random manner (Beyer et al 2010) This is an indication of

which habitats are important for an individual

119863 = ( 119903minus119901

119903+119901minus2119903119901 ) (eqn1)

r = Proportion of habitat type used

p = Total proportion of habitat available

D = Jacobs index varies from -1 (strong avoidance) to +1 (strong preference) with values close to 0 indicating

the habitat is used in proportion to its availability

Activity

Activity level is measured as the mean daily movement (MDM) by the individual to investigate if individuals

in an areaseason moved more and hence were more active than those in other areasseasons Unfortunately

only two cows were collared in the north and were therefore left out of this analysis Moose were identified as

migratory using a modelling approach (see Bunnefeld et al 2011 for methods) Migratory individuals were

initially removed from the activity analysis (n=4)The reason is that both migratory journeys were completed

during the winter season thus increasing the mean daily distance travelled and potentially biasing the analysis

One individual was also removed due it its collar not returning relocations during the entirety of the WS

Diet analysis

The Ӧland project team conducted histology diet analysis on the rumen content of five individuals that were

shot in the centre and south of the island during the WS of 2013

Survival analysis

The Ӧland project team measured calf survival using the mark-resight method The presenceabsence of a calf

was recorded by tracking the cows at six occasions throughout the year These were at the start of the calving

season (mid-May to early June) twice through the summer before the hunt after the hunt and after winter

Survival trend was estimated using a Kaplan-Meier curve (Kaplan and Meier 1958) The Kaplan-Meier curve

shows the survival function (S (t)) ie the probability of an individual surviving until at least time t (Bewick

et al 2004) The probability of surviving from one period to the next is multiplied together to give the survival

function The S(t) of this study is the probability of an individual surviving from birth to after the hunt

(Method summary see appendix B)

11 Results

Home RangeUtilization Distribution

A total of 51 home ranges were estimated (17 annual 17 within growing season 17 within winter season)

Annual x = 9613 ha GS x = 6345 ha and WS x = 6023 ha (appendix C)

At the UD50 scale the largest annual and seasonal mean home ranges were located in the north Mean annual

and seasonal home ranges in the centre were slightly larger than the south This difference was not significant

(F(113)= 22 p= 87) (ANOVA) There was no significant difference between the seasonal home ranges (x

plusmnSD for GS = 116 plusmn38 for WS = 98 plusmn32 ha) (t(11) = 105 p = 32) or the seasonal home ranges in the centre

(t(8) = 101 p = 34 and the south (t(5) = 87 p = 42) (paired-sample t-test) (Table 1)

At the UD95 scale the largest annual and WS mean home ranges were located in the north The largest GS

mean home ranges were located in the centre Mean annual and seasonal home ranges in the centre were

slightly larger than the south This difference was not significant (F(113) = 59 p = 63) (ANOVA) There

was no significant difference between the seasonal home ranges (x plusmnSD for GS = 635 plusmn225 for WS = 602

plusmn161) (t(11) = 373 p = 71) or the seasonal home ranges in the centre (t(8)= 20 p = 84) or south (t(5) = 34

p = 74) (paired-sample t-test) (Table 1)

Table 1 Seasonal and annual mean UD50 and UD95 BRB kernel area in hectares (1ha = 001km2) for the north centre

and south of Oumlland (smoothing factor (h) =100)

Are

a

Annual UD50 GS UD50 WS UD50

n Mean SD Range n Mean SD Range n Mean SD Range

N 2 209 49 139-279 2 1215 39 67-176 2 1615 106 160-163

C 9 178 56 114-277 9 116 44 48-165 9 943 4 61-173

S 6 160 21 142-177 6 1085 51 65-149 6 933 35 69-125

Annual UD95 GS UD95 WS UD95

N 2 10905 5 1084-1097 2 630 199 349-911 2 809 11 794-824

C 9 997 32 682-1536 9 6531 22 295-945 9 637 17 454-941

S 6 9298 30 605-1088 6 5985 373 442-575 6 5526 20 349-679

12

Activity

MDM rates in the three areas (sedentary individuals) during the GS ranged from 14 ndash31 km day During the

WS ranged they ranged from 11-24 km day (Table 2) Movement rates during the GS were higher than the

WS (x plusmnSD for GS = 202 plusmn043 for WS = 161 plusmn043) but it was not statistically significant (t(11) = 200 p=

07) (paired sample t-test)

Table 2 Seasonal mean daily movement rates (km day) for each area and for both areas (total)

Are

a

GS WS

n Mean SE Range n Mean SE Range

C 8 20 003 14-18 8 20 004 12-24

S 4 22 016 17-31 4 12 02 11-13

Total 12 202 003 14-31 12 16 003 11-24

The seasonal MDM rates of all individuals (migratory and sedentary) were not significantly different (x plusmnSD

for GS = 20 plusmn04 for WS = 18 plusmn061) (t(14) = 139 p= 19) (paired sample t-test)

The WS home range size affects the WS MDM (F(110) = 927 p = 01) (ANOVA) The GS home range size

does not affect the GS MDM (F(110) = 36 p = 56) (ANOVA) When the WS home range outlier was

removed the home range size did not affect the WS MDM (F(111) = 186 p= 19) (ANOVA) The MDM was

lowest in February and highest in April (Table 3) there appeared to be no significant pattern in MDM between

the months (appendix D)

Table 3 Mean daily distance moved (km day) for sedentary individuals

Month Season Distance

April GS 0051

May GS 0044

June GS 0039

July GS 0041

August GS 0042

September GS 0044

October GS 0043

November WS 0043

December WS 0038

January WS 0035

February WS 0028

13 Habitat ndash Proportions

The largest proportion of habitat on the island is agriculture the lowest proportion of habitat (excluding coastal

and freshwater) is urban areas (Fig 2) The largest proportion of habitat in the north was coniferous forests

whilst agricultural areas were the dominant habitat types in the centre and south (Fig 3) The lowest proportion

(excluding coastal and freshwater areas) was urban

Fig 2 Proportion of different types of habitats found on Ӧland

Fig 3 Mean proportion of habitats contained within UD95 in the three areas of Oumlland C = Centre N = North S =

South

14

Habitat - Selection

Generally forest habitat types are the highest ranked whilst sparsely vegetated and urban areas are the lowest

ranked Both the second and third order habitat selection analyses gave significant results in the compositional

analysis (Table 4) In the third order analysis (UD50UD95) the centre displayed significant differences

between habitat types The coniferous forests are significantly preferred to sparsely vegetated areas and the

sparsely vegetated areas are significantly preferred to urban areas In the second order analysis (UD95Area)

significance was observed in the north and centre In the north younger forests are significantly preferred to

miresmarshes clear felled areas are significantly preferred to agriculture and freshwater areas are significantly

preferred to sparsely vegetated areas In the centre clear felled areas are significantly preferred to agricultural

land freshwater areas are significantly preferred to urban areas and grasslandmoors are significantly preferred

to sparsely vegetated areas

Table 4 Summary of second (UD95Area bottom) and third order (UD50UD95 top) ranked habitat preferences between

the three areas according to the compositional analysis (see appendix B)

Rank North Centre South

1 Broad Leaf Younger Coniferous

2 Mixed Broad Leaf Younger

3 MiresMarshes Clear Fell GrasslandMoors

4 Younger Mixed Clear Fell

5 Clear Fell GrasslandMoors Mixed

6 Coniferous MiresMarshes Broad Leaf

7 Freshwater Agriculture Freshwater

8 Agriculture Coniferous Agriculture

9 Sparse Veg Sparse Veg MiresMarshes

10 GrasslandMoors Urban Sparse Veg

11 Urban Freshwater Urban

Rank North Centre South

1 Broad Leaf Mixed Coniferous

2 Mixed Younger Clear Fell

3 GrasslandMoors Broad Leaf Younger

4 Younger Coniferous GrasslandMoors

5 MiresMarshes Clear Fell Agriculture

6 Coniferous Agriculture MiresMarshes

7 Clear Fell MiresMarshes Broad Leaf

8 Agriculture Freshwater Freshwater

9 Urban Urban Sparse Veg

10 Freshwater GrasslandMoors Mixed

11 Sparse Veg Sparse Veg Urban

Indicates significantly preferred to the habitat below (significant deviation from random at P lt05)

15 The Jacobs index revealed that generally the habitats preferred during the GS within the home range (third

order) are younger (0187) and broad leaf forests (0154) The strongest avoidance was for urban areas (-0627)

During the WS only agricultural areas are preferred (0129) and the strongest avoidance was for urban areas (-

0393) (Fig 4)

Fig 4 Third order seasonal habitat preference (UD50UD95) all individuals The index ranges from -1 (total avoidance)

to 1 (strongest preference) Close to 0 indicates used in proportion to its availability

Third order habitat preferencesavoidances by area

North During the GS the strongest preference was for broad leaf (0218) and mixed forests (0161) The

strongest avoidance was for urban (-1) and sparsely vegetated areas (-05) During the WS the strongest

preference was for miresmarshes (0228) The strongest avoidance was for grasslandmoors (-05)

Centre During the GS the strongest preference was for broad leaf (0233) and younger forests (0223) The

strongest avoidance was for urban (-0527) and agricultural land (-0362) During the WS preference was only

shown for agricultural land (0327) The strongest avoidance was for urban areas (-0679) and miresmarshes

(-0638)

South During the GS the strongest preference was for coniferous (0312) and younger forests (0242) The

strongest avoidance was for urban (-0353) and sparsely vegetated areas (-0330) During the WS

grasslandmoors (0106) were the strongest preference The strongest avoidance was for urban (-0666) and

sparsely vegetated areas (-0351)

16

The Jacobs indices revealed that generally the habitats preferred during the GS within the landscape

(UD95Area) are broad leaf (0216) and younger forests (0201) The strongest avoidance was for urban (-

0717) and freshwater areas (-0694) The strongest preference during the WS are coniferous forests (0242)

and the strongest avoidance was for freshwater (-0674) and urban areas (-0648) (Fig 5)

Fig 5 Second order seasonal habitat preference (UD50UD95) all individuals The index ranges from -1 (total avoidance)

to 1 (strongest preference) Close to 0 indicates used in proportion to its availability

Second order habitat preferencesavoidances by area

North During the GS the strongest preference was for broad leaf (0363) and mixed forests (00291) The

strongest avoidance was for sparsely vegetated (-0909) and freshwater areas (-0780) During the WS mixed

(0335) and coniferous forests (0316) were the strongest preference The strongest avoidance was for

freshwater (-0731) and urban areas (-05333)

Centre During the GS the strongest preference for mixed (0394) and younger forests (0286) The strongest

avoidance was for urban (-0733) and sparsely vegetated (-0708) areas During the WS mixed (0404) and

coniferous forests (0255) were the strongest preference The strongest avoidance was for freshwater (-0704)

and sparsely vegetated areas (-0655)

South During the GS the strongest preference for grasslandmoors (0287) and clear fells (0165) The

strongest avoidance was for urban areas (-0678) and mixed forests (-0491) During the WS grasslandmoors

(0425) and coniferous forests (0154) were the strongest preference The strongest avoidance was for urban (-

0876) and freshwater areas (-0587) (appendix E)

17 Diet

Diet analysis of the rumen content sampled from five individuals (C=2 S=3) revealed that almost two thirds

(69) of the diet is comprised of agricultural produce (apple winter rape and sugar beet) (Fig 6)

Fig 6 Diet analysis from the rumen samples of five moose individuals that were culled in 2013

31

2117

9

8

5

22

1 1

1

1

1 00 0

0

0Diet (2610-911 2013 5 individuals)

AppleWinter RapeSugar BeetUndefined WoodSallowBroad-leaf GrassPineAshOakCloverCurrantsUndefined plantElderberryJuniperRaspberry

18

Calf Survival

Of the 18 individuals 13 produced calves in which 7 produced twins giving a total of 20 calves A Kaplan-

Meier estimate was conducted to measure the fraction of calves living up to each period of the study (Fig 7)

The mean survival time is until period 235 (midend of summer) At the start of summer 85 of calves

remained (3 still born) The period between summer and before the hunt survival drops to 30 The survival

at the end of the study (after hunt) drops further to 20 leaving 4 calves surviving (see appendix B)

Fig 7 Kaplan-Meier estimate of moose calf survival during the study period Period 0 (Start of summer) period 1

(midend of summer) period 2 (before hunt) period 3 (after hunt) period 4 (after winter)

19 Discussion

The results of this study emphasised how strikingly different the habitat composition is along the latitudinal

gradient of Oumlland The three areas show contrasting proportions of the key habitat types The starkest

difference is the high proportion of coniferous forests and lack of agriculture in the north compared to the

centre and south The proportion of coniferous forest in the north is almost 5 times greater than in the centre

and south whereas the proportion of agriculture in the centre and south is more than double that in the north

The north is perceived to be composed of the most suitable habitat for moose (Dussault et al 2006) It has the

largest proportions of each forest type and a low proportion of agricultural land This provides suitable forage

and shelter throughout the year The south has a contrasting habitat composition to the north The proportions

of agricultural and sparsely vegetated areas are the highest between the three areas and the proportions of forest

habitats are the lowest The large proportion of sparsely vegetated areas and low proportions of forest habitat

corresponds to the large area of Stora Alvaret This is perceived to be the least suitable area due to a lack of

shelter (coniferous forest) and suitable forage The strong preference for coniferous and younger forest habitats

in the south would suggest that moose exhibit a functional response in habitat selection (Godvik et al 2009)

ie as the proportion of a particular habitat decreases the selection for that habitat increases in this case

coniferous forests which provide shelter and younger forest which provide good forage Similarly in the centre

moose show strong preference for mixed forests a habitat that is of low proportion

In view of the large variation in habitat proportions between the areas it is surprising that there is not a large

variation in the home range sizes or the activity levels annually or seasonally Home ranges are ultimately

chosen to maximise fitness and meet energy requirements by utilizing the available forage Seasonal conditions

change the availability and necessity of resources (food quality shelter) Unlike the GS during the WS

deciduous trees and shrubs are leafless and low-lying shrubs are under snow cover (Dussault et al 2005)

These changes are well known to cause populations to alter their activity and home ranges to meet energy

requirements (Mysterud et al 2001) Populations have been shown to increase or decrease their home ranges

during the two seasons The GS home ranges are often larger than the WS home ranges (Philips et al 1973

Mysterud et al 2001) In some cases they can be found to be almost double the size of the WS home ranges

(Cederlund and Okarma 1988) In other populations the WS home ranges are double the size of the GS home

ranges (Lynch and Morgantini 1984) or sizes do not significantly differ (Cederlund and Sand 1994)

Previous studies on moose find females generally show increased activity from the start on the GS due to

various factors eg reduced ruminating times increased metabolic needs and increased foraging bursts

(Wattles and DeStefano 2013) Increased metabolic needs during this time are a results of pregnancy and

lactation (Georgii 1980) During the height of the GS they usually show reduced activity levels through times

of increased thermal stress (Renecker and Hudson 1989 van Beest et al 2012) During the WS the depth and

the duration of snow cover are well known to affect the activity level (Telfer 1970 Mysterud and Oslashstbye 1999

Bjoslashrneraas et al 2011) During the WS generally home ranges are smaller and activity less due to lower

metabolic needs Moose activity is constrained by rumination during the WS this period is known to be longer

due to the change in diet (Cederlund 1989 Renecker Hudson 1989) This was not the case on Ӧland activity

20

was lowest in February which is a similar result to Cederlundrsquos (1989) paper However Ӧland moose did not

significantly alter their seasonal activity levels The fact that the annual and seasonal activity levels and home

ranges were similar could be a result of the mild winters on Oumlland during the study period (Smhise 2014)

During the study period the average number of snow days was 80 and the mean snow depth was 10cm

(appendix F) (Swedish Meterological and Hydrological Institute- SMHI) These mild conditions do not restrict

the movement of moose or obscure forage Moose are well adapted for movement in deep snow depths of 60-

86cm (Prescott 1968) are needed to truly restrict movement This finding was similar to the Sweanor and

Sandegren (1989) and Cederlund and Sand (1994) where the snow depth at their sites did not reach movement

restricting depths

The survival curve illustrates just how bad the calf survival is on Ӧland Survival falls from 85 at the start to

20 Out of 20 calves only four were alive at the end of the study The sharpest fall in survival was the period

between end of summer and before the hunt so the deaths were not due to hunting Previous calf autopsies

(Malmsten 2014a) have shown that cause of death was starvation mothers possibly either did not have milk

the calf was unable to feed or the mother abandoned the calf Closer field based observations are needed to

attain this knowledge Moose are seasonal polyoestral mammals (Monfort et al 1993) coming into oestrus

during late September early October (Garel et al 2009) (appendix F) The diet of the mother influences the

health of the calf and this period is when sodium is hard to find sodium is a key mineral in moose diets for

features such as reproduction (Belovsky and Jordan 1981) Moose gain sodium mainly through aquatic plants

(MacCracken et al 1993) However the compositional analysis shows that freshwater areas are often ranked

as one of the lowest used habitats and coastal areas were removed as the proportion found in the home ranges

was extremely low The Jacobs Index shows that the moose only prefer freshwater areas in the north UD50

during the WS The north individuals again are those that are showing typical moose habitat selection

It is known that habitat selection is hierarchical with habitats that increase fitness selected for and the effects

of limiting factors are reduced (Rettie and Messier 2000) At the UD95 during the GS moose preferred areas

of good forage (forests) and avoided areas of low forage (freshwater and sparsely vegetated areas) and areas

close to humans (urban) This is consistent with other reports (Laurian et al 2008 Torres et al 2011) Within

the UD50 there is a shift in preferences The good forage areas are again preferred during the GS however

during WS the only preferred habitat is often agricultural land During the WS there could be a steady supply

of supplementary feed available hence the high levels of agricultural produce found in the rumen content

samples and the high preference of agricultural areas This diet is unusual for moose previous studies of

Swedish moose diet have found the GS diet was dominated by birch willow and herbaceous plants and the

WS diet dominated by pine and birch (Cederlund and Nystrom 1981) The diet analysis was conducted during

the WS instead of being dominant pine composed just 2 Birch did not appear however unidentified wood

composed only 9 whereas agricultural produce accounted for 69 Supplementary feed may be perceived

by the moose in the centre and south as a vital forage source during the WS In fact in the centre the

agricultural land is the only preferred habitat at the UD50 It is unknown whether there are salt licks provided

in these areas Selection for a critical habitat is often thought to be a fixed factor The Oumlland population from

21 the three areas are close in proximity however they displayed contrasting preferences This is supported by the

Osko et al (2004) report that found two neighbouring moose populations that had access to the same habitats

displayed contrasting preferences Habitat preferences for populations of the same species are not necessarily

fixed They alter with varying levels of habitat abundance and limiting factors skewing what is preserved to

be critical

The main limitation encountered in this study was with the limited sample There was only data on two

individuals from the north of the island which led it being removed from many of the analysis Similarly due

to a lack of relocations from the collars being turned off at points throughout the year two further individuals

had to be removed from a majority of the analysis This reduced the sample size to 17 or 18 individuals

Similarly only 13 of the individuals from the study produced calves This unfortunately prevented including

survival into models Although the sample size was small it was accurate it was of high resolution over

300000 GPS points In future it would be beneficial to have a more standardised data set An equal sample of

individuals from the three areas would be advised along with ensuring the GPS collars are kept turned on for

the entirety of the growing and winter season to allow comparisons between years It would also be

advantageous to collect coordinates of the feeding sites along with the composition This could then be

compared with high use UD coordinates to look if moose are truly spending a majority of their foraging time

at feeding stations A study on the population densities of moose and the increasing population of roe deer

(Capreolus capreolus) would add the factor of competition into the model

The low calf survival on Ӧland is most likely the result of a combination of factors The lack of suitable habitat

reported in this study in conjunction with Malmstenrsquos (2014a) report on the threat of disease (Anaplasma

phagocytophilum) are probable influences on the calf survival on Ӧland On Ӧland there is an increasing

population of roe deer and large numbers of migratory birds both carriers of ticks and diseases The mild

conditions on Ӧland are advantageous for ticks the carriers of A phagocytophilum Fewer snow days and

shorter periods of snow cover along with dry conditions are favourable for ticks This could probably be one

of the reasons for females to be of lower quality and therefore not being able to ensure calf survival Moose

have to utilise areas where in other populations individuals tend to avoid Finally similar to many studies I

advocate further research using a stronger dataset and longer term monitoring

22

Acknowledgements

I am indebted to NJ Singh and A Allen for all their help and guidance through the whole of this study I

thank SLU for the support provided during this study in terms of data finances and facilities Thank you to

everyone at the Department of Wildlife Fish and Environmental Studies for being so friendly and

supportive I would like to thank L Edenius for driving me around the study area and S Michon and H

Khalil for keeping me sane with fika and training

23 References

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success in muskoxen Journal of Zoology 24313-20

30

Appendix A

Introduction

Fig 1 Summary chart of factors affecting the life history and therefore the long term fitness of a population

Fig 2 Summary chart 2

Movement

Habitat

Climate

Topography

Competition

FoodWater

Disease

Die

Survive

Reproduce

Population long term fitness

31 Appendix B

Method and Materials

Fig 1 Summary of processes

32

Fig 2 Examples of classical kernel home range output and Brownian bridge kernel home range (Calenge 2011) The

right image includes the area between relocations ie the movement path in contrast to the classic kernel home range

in the left image

33 Appendix C

Home ranges

Fig 1 Example of a non-migratory (ID006) individuals BRB kernel area From top left annual growing and winter

season UD50 (black contour) and UD95 (red contour)

Fig 2 Example of a migratory (ID012) individuals BRB kernel area From the left annual growing and winter season

UD50 (black contour) and UD95 (red contour)

34

Table 1 Annual and seasonal UD50 and UD95 areas (ha) for all individuals

ID Annual GS WS

UD50 UD95 UD50 UD95 UD50 UD95

ID004 190 924 93 531 173 941

ID005 230 1364 132 945 72 682

ID006 162 1036 89 736 70 611

ID008 277 1536 156 809 78 738

ID009 137 834 48 295 126 653

ID010 114 682 83 448 96 488

ID012 177 963 123 544 76 545

ID014 160 1018 87 575 89 662

ID015 172 858 128 532 109 679

ID016 156 1047 65 455 92 534

ID017 153 1088 149 1043 69 349

ID019 279 1097 176 911 163 824

ID020 139 1084 67 349 160 794

ID022 159 811 131 638 61 454

ID023 187 1061 147 771 72 705

ID024 146 725 165 705 101 458

ID026 142 605 99 442 125 547

ID027 126 567 75 461 48 277

35 Appendix D

Activity

Fig 1 Mean daily movement during the study period GS 23-April-2012 to 07-Nov-2012 WS 08-Nov-2012 to

22-April-2013 (number indicates month)

Fig 2 Mean daily movement in the centre and south during the GS and WS

36

Appendix E

Habitat Proportions

Fig 1 All individualsrsquo seasonal habitat proportions within the UD95

37 Habitat Selection

Table 1 Simplified ranking matrices comparing proportional habitat use within the second order (UD95Area) with

proportions of total available habitat types Mean value on the matrix was replaced by a sign a triple sign represents

significant deviation from random at P lt05 Highlighted habitat is ranked 1st

North A

gri

cult

ure

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 --- --- - +++ --- --- --- +++ +++ --- 8

Broad Leaf +++ 0 +++ + +++ +++ +++ + +++ +++ +++ 1

Clear Fell +++ --- 0 + +++ - - --- +++ +++ --- 7

Coniferous + - - 0 +++ - - --- +++ +++ - 6

Freshwater --- --- --- --- 0 --- --- --- +++ - --- 10

Grassland

Moors +++ --- + + +++ 0 +++ - +++ +++ + 3

MiresMarshes +++ --- + + +++ --- 0 - +++ +++ --- 5

Mixed +++ - +++ +++ +++ + + 0 +++ +++ + 2

Sparse Veg --- --- --- --- --- --- --- --- 0 --- --- 11

Urban --- --- --- --- + --- --- --- +++ 0 --- 9

Younger +++ --- +++ + +++ - +++ - +++ +++ 0 4

Rank Order and

Significance

Broad Leafgt Mixedgt GrasslandMoorsgt Youngergtgtgt MiresMarshesgt Coniferousgt

Clear Fellgtgtgt Agriculturegtgtgt Urbangt Freshwatergtgtgt Sparse Veg

Central

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 --- --- --- + +++ + --- +++ +++ --- 6

Broad Leaf +++ 0 +++ + +++ +++ + - +++ +++ - 3

Clear Fell +++ --- 0 - +++ +++ + --- +++ +++ --- 5

Coniferous +++ - + 0 +++ +++ + --- +++ +++ - 4

Freshwater - --- --- --- 0 +++ - --- +++ +++ --- 8

Grassland

Moors --- --- --- --- --- 0 --- --- +++ - --- 10

MiresMarshes - - - - + +++ 0 - +++ +++ - 7

Mixed +++ + +++ +++ +++ +++ + 0 +++ +++ + 1

Sparse Veg --- --- --- --- --- --- --- --- 0 - --- 11

Urban --- --- --- --- --- + --- --- + 0 --- 9

Younger +++ + +++ + +++ +++ + - +++ +++ 0 2

Rank Order and

Significance

Mixedgt Youngergt Broad Leafgt Coniferousgt Clear Fellgtgtgt Agriculturegt

MiresMarshesgt Freshwatergtgtgt Urbangt GrasslandMoorsgtgtgt Sparse Veg

38

South

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 + - - + - + +++ +++ +++ - 5

Broad Leaf - 0 - - + - - +++ + +++ - 7

Clear Fell + + 0 - + + + +++ + +++ + 2

Coniferous + + + 0 +++ + + +++ + +++ + 1

Freshwater - - - --- 0 - - + + +++ - 8

Grassland

Moors + + - - + 0 + + +++ + - 4

MiresMarshes - + - - + - 0 +++ + +++ - 6

Mixed --- --- --- --- - - --- 0 + + --- 10

Sparse Veg --- - - - - --- - - 0 + - 9

Urban --- --- --- --- --- - --- - - 0 --- 11

Younger + + - - + + + +++ + +++ 0 3

Rank Order

and

Significance

Coniferousgt Clear Fellgt Youngergt GrasslandMoorsgt Agriculturegt MiresMarshesgt Broad Leafgt

Freshwatergt Sparse Veggt Mixedgt Urban

Table 2 Simplified ranking matrices comparing proportional habitat use within the third order (UD50UD95) with

proportions of total available habitat types Mean value on the matrix was replaced by a sign a triple sign represents

significant deviation from random at P lt05 Highlighted habitat is ranked 1st

North

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 --- --- --- - + --- --- + +++ --- 8

Broad Leaf +++ 0 +++ + + + + + +++ +++ + 1

Clear Fell +++ --- 0 + + + - - + +++ - 5

Coniferous +++ - - 0 + + --- --- +++ +++ - 6

Freshwater + - - - 0 +++ - - +++ +++ - 7

GrasslandMoors - - - - --- 0 - - - + - 10

MiresMarshes +++ - + +++ + + 0 - +++ +++ + 3

Mixed +++ - + +++ + + + 0 +++ +++ + 2

Sparse Veg - --- - --- --- + --- --- 0 +++ --- 9

Urban --- --- --- --- --- - --- --- --- 0 --- 11

Younger +++ - + + + + - - +++ +++ 0 4

Rank Order and

Significance

Broad Leafgt Mixedgt MiresMarshesgt Youngergt Clear Fellgt Coniferousgt Freshwatergt

Agriculturegt Sparse Veggt GrasslandMoorsgt Urban

39

Central

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 --- --- + + - - - + +++ --- 7

Broad Leaf +++ 0 + +++ + + + + + +++ - 2

Clear Fell +++ - 0 +++ + + + + + +++ - 3

Coniferous - --- --- 0 + - - --- +++ + --- 8

Freshwater - - - - 0 --- - - --- - - 11

GrasslandMoors + - - + +++ 0 + - + +++ - 5

MiresMarshes + - - + + - 0 + + +++ - 6

Mixed + - - +++ + + - 0 +++ +++ - 4

Sparse Veg - - - --- +++ - - --- 0 +++ - 9

Urban --- --- --- - + --- --- --- --- 0 --- 10

Younger +++ + + +++ + + + + + +++ 0 1

Rank Order and

Significance

Youngergt Broad Leafgt Clear Fellgt Mixedgt GrasslandMoorsgt MiresMarshesgt

Agriculturegt Coniferousgtgtgt Sparse Veggtgtgt Urbangt Freshwater

South

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 - - - - - + - +++ + --- 8

Broad Leaf + 0 - --- + - + - +++ + - 6

Clear Fell + + 0 - + - + - +++ + - 4

Coniferous + +++ + 0 + + +++ + +++ + + 1

Freshwater + - - - 0 - - + + + - 7

GrasslandMoors + + + - + 0 + + + + - 3

MiresMarshes - - - --- + - 0 - + + - 9

Mixed + + + - - - + 0 + + - 5

Sparse Veg --- --- --- --- - - - - 0 + --- 10

Urban - - - - - - - - - 0 - 11

Younger +++ + + - + + + + +++ + 0 2

Rank Order and

Significance

Coniferousgt Youngergt GrasslandMoorsgt Clear Fellgt Mixedgt Broad Leafgt Freshwatergt

Agriculturegt MiresMarshesgt Sparse Veggt Urban

40

Table 3 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the GS according to Jacobs index

Ran

k North Centre South

50 95 50 95 50 95

+ - + - + - + - + - + -

1 Broad

Leaf Urban Broad Leaf Sparse Veg

Broad

Leaf Urban Mixed Urban Coniferous Urban

Grassland

Moors Urban

2 Mixed Sparse Veg Mixed Freshwater Younger Agriculture Younger Sparse Veg Younger Sparse Veg Clear Fell Mixed

3 Mires

Agriculture Grassland

Urban Clear

Fell Coniferous Broad Leaf

Grassland

Moors

Clear Fell Agriculture Coniferous Sparse Veg

Marshes Moors

4 Younger Grassland

Younger Agriculture

Freshwater Coniferous Freshwater

Broad Leaf Mires

Younger Freshwater

Moors Marshes

5 Clear

Fell Freshwater

Mires Coniferous

Sparse Veg Clear Fell Agriculture

Freshwater Agriculture

Marshes

6 Coniferous Clear Fell

Mires

Marshes

Mires

Grassland

Moors

Mires

Marshes Marshes

7 Mixed Mixed Broad Leaf

8 Grassland

Moors

41

Table 4 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the WS according to Jacobs index

Ran

k North Centre South

50 95 50 95 50 95

+ - + - + - + - + - + -

1 Mires

Marshes

Grassland

Moors Mixed Freshwater Agriculture Urban Mixed Freshwater

Grassland

Moors Urban GrasslandMoors Urban

2 Freshwater Mixed Coniferous Urban Mires

Marshes Coniferous Sparse Veg Agriculture

Sparse

Veg Coniferous Freshwater

3 Urban Coniferous Younger Grassland

Moors Freshwater Younger Urban Freshwater

Broad

Leaf Agriculture Mixed

4 Younger Agriculture Sparse Veg Broad

Leaf

Broad

Leaf

Grassland

Moors Mixed Broad Leaf

5 Clear Fell Agriculture Coniferous Agriculture Mires

Marshes Clear Fell

6 Sparse

Veg

Mires

Marshes Mixed

Mires

Marshes

Clear

Fell

Mires

Marshes

7 Broad

Leaf Clear Fell Younger Clear Fell Younger Sparse Veg

8 Clear Fell Younger

9 Sparse

Veg

10 Grassland

Moors

42

Table 5 Second order (UD95Area) individual selectionavoidance for the GS and WS according to the Jacobs index

ID GS WS

Select Avoid Select Avoid

ID004 Younger Sparsely Vegetated MiresMarshes Sparsely Vegetated

ID005 MiresMarshes Sparsely Vegetated Coniferous GrasslandMoors

ID006 Coniferous Sparsely Vegetated Mixed Freshwater

ID008 Mixed Sparsely Vegetated Mixed Freshwater

ID009 Mixed Sparsely Vegetated Mixed GrasslandMoors

ID010 MiresMarshes Freshwater GrasslandMoors Freshwater

ID012 Broad Leaf Sparsely Vegetated Coniferous Urban

ID014 Clear Fell Sparsely Vegetated GrasslandMoors Sparsely Vegetated

ID015 GrasslandMoors Urban GrasslandMoors Freshwater

ID016 GrasslandMoors Freshwater GrasslandMoors Freshwater

ID017 GrasslandMoors Mixed Sparsely Vegetated Mixed

ID019 Mixed Sparsely Vegetated Mixed Urban

ID020 Broad Leaf Sparsely Vegetated Coniferous GrasslandMoors

ID022 MiresMarshes Freshwater MiresMarshes Freshwater

ID023 MiresMarshes GrasslandMoors Mixed Freshwater

ID024 Broadleaf Urban Broad Leaf Urban

ID026 GrasslandMoors Freshwater GrasslandMoors Freshwater

ID027 GrasslandMoors Urban Sparsely Vegetated Freshwater

43 Table 6 Third order (UD50UD95) individual selectionavoidance for the GS and WS according to the Jacobs index

ID GS WS

Select Avoid Select Avoid

ID004 Broad Leaf Mixed GrasslandMoors Freshwater

ID005 Broad Leaf Freshwater Agriculture Freshwater

ID006 Clear Fell Freshwater Agriculture MiresMarshes

ID008 MiresMarshes Freshwater Agriculture Urban

ID009 Freshwater Agriculture Agriculture Freshwater

ID010 Mixed Urban Sparsely Vegetated Urban

ID012 Coniferous GrasslandMoors Freshwater Urban

ID014 Urban Agriculture Freshwater Urban

ID015 Mixed Forest Urban Clear Fell Urban

ID016 Freshwater Urban GrasslandMoors Mixed

ID017 Coniferous Mixed Coniferous Broad Leaf

ID019 Broad Leaf GrasslandMoors Urban GrasslandMoors

ID020 Freshwater Urban Freshwater Agriculture

ID022 MiresMarshes Urban Broad Leaf GrasslandMoors

ID023 Freshwater Mixed Agriculture Freshwater

ID024 Mixed Freshwater Mixed Freshwater

ID026 Mixed MiresMarshes Sparsely Vegetated GrasslandMoors

ID027 Freshwater MiresMarshes GrasslandMoors Broad Leaf

44

Fig 2 North third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)

45

Fig 3 Centre third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)

46

Fig 4 South third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)

47

Fig 5 North second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)

48

Fig 6 Centre second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)

49

Fig 7 South second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)

50

Appendix F

Background

Fig 1 Daily mean snow depth and duration during the study period (Andrew Allen)

Female Moose Reproduction

Moose are seasonal polyoestral mammals (Monfort et al 1993) coming into oestrus during late September

early October (Garel et al 2009) The Swedish moose cow population reaches puberty between the ages 25

and 35 (Sand and Cederlund 1993) during which the reproductive period begins with the onset of ovulation

The age an individual reaches puberty is dependent on their body condition they have to reach a weight

threshold to reach puberty and become reproductive (Sand 1996) If she is over the weight threshold she will

go into oestrus in the autumn If she does not reach the weight threshold then she will go into oestrus the

following autumn if successful she will give birth to individual or twin calves in late May to early June

(Ericsson et al 2001) and therefore reach sexual maturity (Malmsten et al 2014b) Fecundity is related to

both the condition and the age of the cow Cows go through senescence at 12 years of age (Ericsson et al

2001) Providing calves with the required level of nutrition demands high energy and protein resources from

the mother during senescence this becomes harder to achieve leading to decreased levels of parental care

and higher levels of calf mortality

Page 6: Habitat-performance relationships on an island: fitness ...navinderjsingh.weebly.com/uploads/1/1/2/2/11224342/... · Conditions on Öland are milder than those found in other areas

6

(158 billion Euro) (Boman et al 2011) Each year in Sweden 90000-100000 individuals are harvested

providing approximately 85 million kilograms of moose meat (Kindberg et al 2009) A common method of

selecting which individuals are to be harvested is to assess the reproductive value of an individual and remove

the lownon-reproductive individuals such as calves bulls and cows without calves (Ball et al 1999 Ericsson

et al 2001) Hunting is biased towards bulls with large trophy antlers often resulting in a skewed sex ratio

(Laurian et al 2000 Harris et al 2002 Milner et al 2007)

Moose are known to have a generally high calf survival noted through studies from predator free areas in both

North America and Europe (Linnell et al 1995 Crecircte and Courtois 1997 Swenson et al 2007) A number of

other factors are nevertheless known to affect the survival during their first summer such as climatic variation

malnutrition abandonment disease and poor maternal investment (Verme and Ullrey 1984 Gaillard et al

2000b Lomas and Bender 2007 Ericsson et al 2002 Herfindal et al 2006 Lenarz et al 2010) Low survival

in single odd years has been attributed to weather and low food quality

During recent years moose populations appear to be under environmental stress across their southern range

ascertained by studies reporting low calf survival from both North America and Sweden (Monteith et al in

press Ericsson et al submitted) A similar situation has been reported recently on the island of Oumlland in

southern Sweden where the harvesting of moose was postponed from 2001 to 2005 by mutual agreement

between hunters This was due to a fear of population collapse due to poor management strategies in previous

years that lead to a suspected unsustainable harvest The four-year harvesting break resulted in a balanced sex

ratio and age distribution (Jonsson 2007) In 2006 however it was brought to the attention of the department

of Pathology and Wildlife Diseases at the Swedish National Veterinary Institute in Uppsala (SVA) that there

was an unusually low number of calves observed on the island Malmsten (2014a) conducted a follow up study

during 2012 and 2013 and found that summer calf survival of individuals from Oumlland was only 318 and

158 respectively When compared to calf survival from two other sites in southern Sweden (Kronoberg and

Soumldermanland) with rates all above 73 for both years this figure was regarded as very worrying and

prompted a need for an in-depth exanimation of the factors determining such low calf survival With this above

rationale in mind this study investigates the habitat performance relationships of female moose on the island

of Oumlland This study also provides a model for examining the factors affecting population dynamics on an

island

7 Materials and Methods

Study area

Ӧland (567333deg N 166667deg E) a Baltic island located in Kalmar county (Fig 1) is Swedenrsquos second largest

island (~140km in length) It can be split broadly into three areas the north (N) centre (C) and south (S) There

are three typical habitats found on the island boreal forests Stora Alvaret and agricultural land The largest

portions of boreal forests are found in the far north the centre and a patch in the far south Forest stands are

dominated by birch (Betula pubescens B pendula) and Scots pine (Pinus sylvestris) with rowan (Sorbus

aucuparia) aspen (Populus tremula) grey alder (Alnus incana) and yew (Taxus baccata) interspersed

throughout with willow sp (Salix spp) in areas near water sources (Sӕther and Heim 1993) The field layer is

made up of primarily bilberry (Vaccinium myrtillus) lowbush cranberry (Vaccinium vitis-idӕa) and heather

(Calluna vulgaris) (Cederlund 1989) The patches of boreal forest in the north centre and south are isolated

from each other by agricultural areas which are distributed throughout the island particularly along the coastal

regions and the island centre The most southerly patch of forest was protected from becoming agricultural

due to its status as a royal hunting ground and an important stopover for migratory birds (Lars Edenius

personal communication April 09 2014) The southern part of Oumlland has the largest expanse of steppe-like

alvar grassland (Stora Alvaret) found in the world (~25500 ha) (Roseacuten 2006) which is found over dry shallow

nutrient-poor grazed soil (Bakker et al 1996) on top of superficial Ordovician limestone (Dengler et al 2006)

Conditions on Oumlland are milder than those found in other areas of Sweden as it is positioned in the ldquorain-

shadowrdquo of mainland Sweden (Prentice 2007) The only predators of moose found on Oumlland are hunters which

were banned from hunting in previous years

Fig 1 Location of Oumlland

8

Capture and Handling

A random sample of adult moose (n = 25) were darted sedated and equipped with GPSGSM neck collars

(Vectronic Aerospace GmbH Berlin Germany) during the winter of 2012 by the Moose Research Group

SLU Movement data were collected from GPS collars dating from 22022012 ndash 24042014 Collars were

fixed to return GPS locations approximately every 30 minutes

Data Screening

The sample contained both males and females (six males 19 females x female age = 95 years range 4-17

years) An initial inspection revealed that one female individual only returned fixed locations for a period of

eight months Locations ceased during the hunting period so the individual was presumed shot and was

removed from the data along with the males

The exact time between each location varied and sometimes no fix could be made The adehabitatLT package

(Calenge 2006) was used to standardise the data and overcome the location fixing errors The function setNA

was used to place NAs where relocations were missing The function sett0 was used to round the timing of

collection obtaining a regular trajectory with 30 minute intervals The final dataset used in the analysis

consisted of 302710 regular GPS data points from a sample size of n=18 individuals two individuals from the

north ten individuals from the centre and six individuals from the south

To address the question and to investigate the influence of climate on the space use patterns of moose the

analysis was performed at two scales The first included all annual movements of moose and the second at a

seasonal scale ie summer and winter The seasonal scales were defined according to the growing season (GS)

and winter season (WS) In Scandinavia the current method used to define the start of season (SOS) is the

period when the daily mean air temperature is above 5degC (GS) Methods of calculating SOS are advancing

with the use of the Normalized Difference vegetation Index (NDVI) becoming more popular The start and

end of the GS and WS were derived using the mean start and end dates for Oumlland suggested by the Norwegian

Meteorological Institute (DNMI) Nordic climate map report (Tveito et al 2001) The GS of this study is

defined as the period between 23-April-2012 to 07-Nov-2012 and the WS is defined as the period between 08-

Nov-2012 to 22-April-2013 (based on the current standard normal period 1961-90)

Home rangeUtilization distribution

Variation in ungulate home range size is known to be caused by changes in energy requirements and variation

in food availability (Tufto et al 1996 Kie et al 2010 Moreller et al 2013) With shifting climate causes shifts

in plant phenology and therefore the spatial and temporal distribution of ungulate food (Maringrell et al 2006)

Individuals alter their home ranges to meet their energy requirements to maintain their fitness (Albon et al

1987 White 1997 Festa-Bianchet et al 1998 Forchhammer et al 2001)

The most commonly cited definition of a home range is ldquothat area traversed by the animal during its normal

activities of food gathering mating and caring for youngrdquo (Burt 1943) This has now been expanded to

9 incorporate measures of space use using the utilization distribution (UD van Winkle 1975) which can be

described as the ldquorelative frequency distribution of an animalrsquos occurrence in all four dimensions of space

and timerdquo (Keating and Cherry 2009) Home range is viewed as a constant 2D polygon whereas UDs are

viewed as multiple 3D polygons that take into account the distribution as well as the intensity of animalrsquos

movements and space use within their home range (Kranstauber et al 2012) (see appendix A)

Estimations of each individualrsquos annual and seasonal UDs were found using the Biased Random Bridge (BRB)

kernel approach (Benhamou 2011) from the adehabitatHR package (Calenge 2006) in R It was chosen as it is

considered an improvement on the previously preferred Brownian bridge (BB) method (Horne et al 2007) The

BB is purely a diffusive movement process whereas the BRB is an advective-diffusive movement process BB

does not take into account changes in advection direction (drift) or strength BB assumes an animalrsquos

movement is purely random it moves from a starting point and ends up at the end location randomly By

adding the advection component the BRB takes into account that the animalrsquos movement is biased towards a

certain direction This allows for a more biologically relevant analysis (Benhamou and Corneacutelis 2010)

A grid was created using the minmax XY coordinates of all individuals (plusmn 10 km to increase the extent and

prevent the grid directly touching the XY locations) The resolution of the grid was fixed at a 25 m x 25 m

scale to match the resolution of the relevant habitat maps (Hagner et al 2005) By specifying these criteria the

resolution of the data remains consistent between individuals The diffusion coefficient determines the variance

in the location of the kernels between two locations This was calculated from each individualrsquos dataset using

the BRBD function and added to the BRB model (see Benhamou 2011) The strength and direction of BRB

advection can change between bridges whilst having to remaining constant To remain constant an upper Tmax

and lower Lmin time thresholds were set Successive relocations that exceeded Tmax or under Lmin were

removed from the UD calculations The 50 (UD50) and 95 (UD95) isopleths were then calculated from

the UD using the kernelarea function

Habitat

The scale of analysis was further divided following Johnson (1980) Habitat selection within the landscape

(second order selection) was studied by comparing the UD95 with available habitats in each of the three study

areas of Oumlland (UD95Area) Habitat selection within the home range (third order selection) was studied by

comparing the UD50 with the UD95 (UD50UD95)

12 habitat classes were used in the analysis agricultural land broad leaved forests clear felled areas coastal

coniferous forests freshwater areas moorsgrassland miresmarshes mixed forest sparsely vegetated areas

urban areas and younger forests The proportion of area covered by each of these habitat classes was

determined in the UD50 and UD95 Habitat data was obtained from satellite imagery generated by Svenska

Marktaumlckedata (Hagner et al 2005) The habitat maps were last updated in 2002 and have a resolution of 25

m

Compositional analysis ( habitat used habitat available) (Aebischer 1993) was used in conjunction with

the Jacobrsquos index (D) (eqn1) to quantify habitat selection (Jacobs 1974) Coastal areas were removed as not

10

all home ranges contained them This combined approach allowed identification of habitats that are used

disproportionally to their availability ie in a non-random manner (Beyer et al 2010) This is an indication of

which habitats are important for an individual

119863 = ( 119903minus119901

119903+119901minus2119903119901 ) (eqn1)

r = Proportion of habitat type used

p = Total proportion of habitat available

D = Jacobs index varies from -1 (strong avoidance) to +1 (strong preference) with values close to 0 indicating

the habitat is used in proportion to its availability

Activity

Activity level is measured as the mean daily movement (MDM) by the individual to investigate if individuals

in an areaseason moved more and hence were more active than those in other areasseasons Unfortunately

only two cows were collared in the north and were therefore left out of this analysis Moose were identified as

migratory using a modelling approach (see Bunnefeld et al 2011 for methods) Migratory individuals were

initially removed from the activity analysis (n=4)The reason is that both migratory journeys were completed

during the winter season thus increasing the mean daily distance travelled and potentially biasing the analysis

One individual was also removed due it its collar not returning relocations during the entirety of the WS

Diet analysis

The Ӧland project team conducted histology diet analysis on the rumen content of five individuals that were

shot in the centre and south of the island during the WS of 2013

Survival analysis

The Ӧland project team measured calf survival using the mark-resight method The presenceabsence of a calf

was recorded by tracking the cows at six occasions throughout the year These were at the start of the calving

season (mid-May to early June) twice through the summer before the hunt after the hunt and after winter

Survival trend was estimated using a Kaplan-Meier curve (Kaplan and Meier 1958) The Kaplan-Meier curve

shows the survival function (S (t)) ie the probability of an individual surviving until at least time t (Bewick

et al 2004) The probability of surviving from one period to the next is multiplied together to give the survival

function The S(t) of this study is the probability of an individual surviving from birth to after the hunt

(Method summary see appendix B)

11 Results

Home RangeUtilization Distribution

A total of 51 home ranges were estimated (17 annual 17 within growing season 17 within winter season)

Annual x = 9613 ha GS x = 6345 ha and WS x = 6023 ha (appendix C)

At the UD50 scale the largest annual and seasonal mean home ranges were located in the north Mean annual

and seasonal home ranges in the centre were slightly larger than the south This difference was not significant

(F(113)= 22 p= 87) (ANOVA) There was no significant difference between the seasonal home ranges (x

plusmnSD for GS = 116 plusmn38 for WS = 98 plusmn32 ha) (t(11) = 105 p = 32) or the seasonal home ranges in the centre

(t(8) = 101 p = 34 and the south (t(5) = 87 p = 42) (paired-sample t-test) (Table 1)

At the UD95 scale the largest annual and WS mean home ranges were located in the north The largest GS

mean home ranges were located in the centre Mean annual and seasonal home ranges in the centre were

slightly larger than the south This difference was not significant (F(113) = 59 p = 63) (ANOVA) There

was no significant difference between the seasonal home ranges (x plusmnSD for GS = 635 plusmn225 for WS = 602

plusmn161) (t(11) = 373 p = 71) or the seasonal home ranges in the centre (t(8)= 20 p = 84) or south (t(5) = 34

p = 74) (paired-sample t-test) (Table 1)

Table 1 Seasonal and annual mean UD50 and UD95 BRB kernel area in hectares (1ha = 001km2) for the north centre

and south of Oumlland (smoothing factor (h) =100)

Are

a

Annual UD50 GS UD50 WS UD50

n Mean SD Range n Mean SD Range n Mean SD Range

N 2 209 49 139-279 2 1215 39 67-176 2 1615 106 160-163

C 9 178 56 114-277 9 116 44 48-165 9 943 4 61-173

S 6 160 21 142-177 6 1085 51 65-149 6 933 35 69-125

Annual UD95 GS UD95 WS UD95

N 2 10905 5 1084-1097 2 630 199 349-911 2 809 11 794-824

C 9 997 32 682-1536 9 6531 22 295-945 9 637 17 454-941

S 6 9298 30 605-1088 6 5985 373 442-575 6 5526 20 349-679

12

Activity

MDM rates in the three areas (sedentary individuals) during the GS ranged from 14 ndash31 km day During the

WS ranged they ranged from 11-24 km day (Table 2) Movement rates during the GS were higher than the

WS (x plusmnSD for GS = 202 plusmn043 for WS = 161 plusmn043) but it was not statistically significant (t(11) = 200 p=

07) (paired sample t-test)

Table 2 Seasonal mean daily movement rates (km day) for each area and for both areas (total)

Are

a

GS WS

n Mean SE Range n Mean SE Range

C 8 20 003 14-18 8 20 004 12-24

S 4 22 016 17-31 4 12 02 11-13

Total 12 202 003 14-31 12 16 003 11-24

The seasonal MDM rates of all individuals (migratory and sedentary) were not significantly different (x plusmnSD

for GS = 20 plusmn04 for WS = 18 plusmn061) (t(14) = 139 p= 19) (paired sample t-test)

The WS home range size affects the WS MDM (F(110) = 927 p = 01) (ANOVA) The GS home range size

does not affect the GS MDM (F(110) = 36 p = 56) (ANOVA) When the WS home range outlier was

removed the home range size did not affect the WS MDM (F(111) = 186 p= 19) (ANOVA) The MDM was

lowest in February and highest in April (Table 3) there appeared to be no significant pattern in MDM between

the months (appendix D)

Table 3 Mean daily distance moved (km day) for sedentary individuals

Month Season Distance

April GS 0051

May GS 0044

June GS 0039

July GS 0041

August GS 0042

September GS 0044

October GS 0043

November WS 0043

December WS 0038

January WS 0035

February WS 0028

13 Habitat ndash Proportions

The largest proportion of habitat on the island is agriculture the lowest proportion of habitat (excluding coastal

and freshwater) is urban areas (Fig 2) The largest proportion of habitat in the north was coniferous forests

whilst agricultural areas were the dominant habitat types in the centre and south (Fig 3) The lowest proportion

(excluding coastal and freshwater areas) was urban

Fig 2 Proportion of different types of habitats found on Ӧland

Fig 3 Mean proportion of habitats contained within UD95 in the three areas of Oumlland C = Centre N = North S =

South

14

Habitat - Selection

Generally forest habitat types are the highest ranked whilst sparsely vegetated and urban areas are the lowest

ranked Both the second and third order habitat selection analyses gave significant results in the compositional

analysis (Table 4) In the third order analysis (UD50UD95) the centre displayed significant differences

between habitat types The coniferous forests are significantly preferred to sparsely vegetated areas and the

sparsely vegetated areas are significantly preferred to urban areas In the second order analysis (UD95Area)

significance was observed in the north and centre In the north younger forests are significantly preferred to

miresmarshes clear felled areas are significantly preferred to agriculture and freshwater areas are significantly

preferred to sparsely vegetated areas In the centre clear felled areas are significantly preferred to agricultural

land freshwater areas are significantly preferred to urban areas and grasslandmoors are significantly preferred

to sparsely vegetated areas

Table 4 Summary of second (UD95Area bottom) and third order (UD50UD95 top) ranked habitat preferences between

the three areas according to the compositional analysis (see appendix B)

Rank North Centre South

1 Broad Leaf Younger Coniferous

2 Mixed Broad Leaf Younger

3 MiresMarshes Clear Fell GrasslandMoors

4 Younger Mixed Clear Fell

5 Clear Fell GrasslandMoors Mixed

6 Coniferous MiresMarshes Broad Leaf

7 Freshwater Agriculture Freshwater

8 Agriculture Coniferous Agriculture

9 Sparse Veg Sparse Veg MiresMarshes

10 GrasslandMoors Urban Sparse Veg

11 Urban Freshwater Urban

Rank North Centre South

1 Broad Leaf Mixed Coniferous

2 Mixed Younger Clear Fell

3 GrasslandMoors Broad Leaf Younger

4 Younger Coniferous GrasslandMoors

5 MiresMarshes Clear Fell Agriculture

6 Coniferous Agriculture MiresMarshes

7 Clear Fell MiresMarshes Broad Leaf

8 Agriculture Freshwater Freshwater

9 Urban Urban Sparse Veg

10 Freshwater GrasslandMoors Mixed

11 Sparse Veg Sparse Veg Urban

Indicates significantly preferred to the habitat below (significant deviation from random at P lt05)

15 The Jacobs index revealed that generally the habitats preferred during the GS within the home range (third

order) are younger (0187) and broad leaf forests (0154) The strongest avoidance was for urban areas (-0627)

During the WS only agricultural areas are preferred (0129) and the strongest avoidance was for urban areas (-

0393) (Fig 4)

Fig 4 Third order seasonal habitat preference (UD50UD95) all individuals The index ranges from -1 (total avoidance)

to 1 (strongest preference) Close to 0 indicates used in proportion to its availability

Third order habitat preferencesavoidances by area

North During the GS the strongest preference was for broad leaf (0218) and mixed forests (0161) The

strongest avoidance was for urban (-1) and sparsely vegetated areas (-05) During the WS the strongest

preference was for miresmarshes (0228) The strongest avoidance was for grasslandmoors (-05)

Centre During the GS the strongest preference was for broad leaf (0233) and younger forests (0223) The

strongest avoidance was for urban (-0527) and agricultural land (-0362) During the WS preference was only

shown for agricultural land (0327) The strongest avoidance was for urban areas (-0679) and miresmarshes

(-0638)

South During the GS the strongest preference was for coniferous (0312) and younger forests (0242) The

strongest avoidance was for urban (-0353) and sparsely vegetated areas (-0330) During the WS

grasslandmoors (0106) were the strongest preference The strongest avoidance was for urban (-0666) and

sparsely vegetated areas (-0351)

16

The Jacobs indices revealed that generally the habitats preferred during the GS within the landscape

(UD95Area) are broad leaf (0216) and younger forests (0201) The strongest avoidance was for urban (-

0717) and freshwater areas (-0694) The strongest preference during the WS are coniferous forests (0242)

and the strongest avoidance was for freshwater (-0674) and urban areas (-0648) (Fig 5)

Fig 5 Second order seasonal habitat preference (UD50UD95) all individuals The index ranges from -1 (total avoidance)

to 1 (strongest preference) Close to 0 indicates used in proportion to its availability

Second order habitat preferencesavoidances by area

North During the GS the strongest preference was for broad leaf (0363) and mixed forests (00291) The

strongest avoidance was for sparsely vegetated (-0909) and freshwater areas (-0780) During the WS mixed

(0335) and coniferous forests (0316) were the strongest preference The strongest avoidance was for

freshwater (-0731) and urban areas (-05333)

Centre During the GS the strongest preference for mixed (0394) and younger forests (0286) The strongest

avoidance was for urban (-0733) and sparsely vegetated (-0708) areas During the WS mixed (0404) and

coniferous forests (0255) were the strongest preference The strongest avoidance was for freshwater (-0704)

and sparsely vegetated areas (-0655)

South During the GS the strongest preference for grasslandmoors (0287) and clear fells (0165) The

strongest avoidance was for urban areas (-0678) and mixed forests (-0491) During the WS grasslandmoors

(0425) and coniferous forests (0154) were the strongest preference The strongest avoidance was for urban (-

0876) and freshwater areas (-0587) (appendix E)

17 Diet

Diet analysis of the rumen content sampled from five individuals (C=2 S=3) revealed that almost two thirds

(69) of the diet is comprised of agricultural produce (apple winter rape and sugar beet) (Fig 6)

Fig 6 Diet analysis from the rumen samples of five moose individuals that were culled in 2013

31

2117

9

8

5

22

1 1

1

1

1 00 0

0

0Diet (2610-911 2013 5 individuals)

AppleWinter RapeSugar BeetUndefined WoodSallowBroad-leaf GrassPineAshOakCloverCurrantsUndefined plantElderberryJuniperRaspberry

18

Calf Survival

Of the 18 individuals 13 produced calves in which 7 produced twins giving a total of 20 calves A Kaplan-

Meier estimate was conducted to measure the fraction of calves living up to each period of the study (Fig 7)

The mean survival time is until period 235 (midend of summer) At the start of summer 85 of calves

remained (3 still born) The period between summer and before the hunt survival drops to 30 The survival

at the end of the study (after hunt) drops further to 20 leaving 4 calves surviving (see appendix B)

Fig 7 Kaplan-Meier estimate of moose calf survival during the study period Period 0 (Start of summer) period 1

(midend of summer) period 2 (before hunt) period 3 (after hunt) period 4 (after winter)

19 Discussion

The results of this study emphasised how strikingly different the habitat composition is along the latitudinal

gradient of Oumlland The three areas show contrasting proportions of the key habitat types The starkest

difference is the high proportion of coniferous forests and lack of agriculture in the north compared to the

centre and south The proportion of coniferous forest in the north is almost 5 times greater than in the centre

and south whereas the proportion of agriculture in the centre and south is more than double that in the north

The north is perceived to be composed of the most suitable habitat for moose (Dussault et al 2006) It has the

largest proportions of each forest type and a low proportion of agricultural land This provides suitable forage

and shelter throughout the year The south has a contrasting habitat composition to the north The proportions

of agricultural and sparsely vegetated areas are the highest between the three areas and the proportions of forest

habitats are the lowest The large proportion of sparsely vegetated areas and low proportions of forest habitat

corresponds to the large area of Stora Alvaret This is perceived to be the least suitable area due to a lack of

shelter (coniferous forest) and suitable forage The strong preference for coniferous and younger forest habitats

in the south would suggest that moose exhibit a functional response in habitat selection (Godvik et al 2009)

ie as the proportion of a particular habitat decreases the selection for that habitat increases in this case

coniferous forests which provide shelter and younger forest which provide good forage Similarly in the centre

moose show strong preference for mixed forests a habitat that is of low proportion

In view of the large variation in habitat proportions between the areas it is surprising that there is not a large

variation in the home range sizes or the activity levels annually or seasonally Home ranges are ultimately

chosen to maximise fitness and meet energy requirements by utilizing the available forage Seasonal conditions

change the availability and necessity of resources (food quality shelter) Unlike the GS during the WS

deciduous trees and shrubs are leafless and low-lying shrubs are under snow cover (Dussault et al 2005)

These changes are well known to cause populations to alter their activity and home ranges to meet energy

requirements (Mysterud et al 2001) Populations have been shown to increase or decrease their home ranges

during the two seasons The GS home ranges are often larger than the WS home ranges (Philips et al 1973

Mysterud et al 2001) In some cases they can be found to be almost double the size of the WS home ranges

(Cederlund and Okarma 1988) In other populations the WS home ranges are double the size of the GS home

ranges (Lynch and Morgantini 1984) or sizes do not significantly differ (Cederlund and Sand 1994)

Previous studies on moose find females generally show increased activity from the start on the GS due to

various factors eg reduced ruminating times increased metabolic needs and increased foraging bursts

(Wattles and DeStefano 2013) Increased metabolic needs during this time are a results of pregnancy and

lactation (Georgii 1980) During the height of the GS they usually show reduced activity levels through times

of increased thermal stress (Renecker and Hudson 1989 van Beest et al 2012) During the WS the depth and

the duration of snow cover are well known to affect the activity level (Telfer 1970 Mysterud and Oslashstbye 1999

Bjoslashrneraas et al 2011) During the WS generally home ranges are smaller and activity less due to lower

metabolic needs Moose activity is constrained by rumination during the WS this period is known to be longer

due to the change in diet (Cederlund 1989 Renecker Hudson 1989) This was not the case on Ӧland activity

20

was lowest in February which is a similar result to Cederlundrsquos (1989) paper However Ӧland moose did not

significantly alter their seasonal activity levels The fact that the annual and seasonal activity levels and home

ranges were similar could be a result of the mild winters on Oumlland during the study period (Smhise 2014)

During the study period the average number of snow days was 80 and the mean snow depth was 10cm

(appendix F) (Swedish Meterological and Hydrological Institute- SMHI) These mild conditions do not restrict

the movement of moose or obscure forage Moose are well adapted for movement in deep snow depths of 60-

86cm (Prescott 1968) are needed to truly restrict movement This finding was similar to the Sweanor and

Sandegren (1989) and Cederlund and Sand (1994) where the snow depth at their sites did not reach movement

restricting depths

The survival curve illustrates just how bad the calf survival is on Ӧland Survival falls from 85 at the start to

20 Out of 20 calves only four were alive at the end of the study The sharpest fall in survival was the period

between end of summer and before the hunt so the deaths were not due to hunting Previous calf autopsies

(Malmsten 2014a) have shown that cause of death was starvation mothers possibly either did not have milk

the calf was unable to feed or the mother abandoned the calf Closer field based observations are needed to

attain this knowledge Moose are seasonal polyoestral mammals (Monfort et al 1993) coming into oestrus

during late September early October (Garel et al 2009) (appendix F) The diet of the mother influences the

health of the calf and this period is when sodium is hard to find sodium is a key mineral in moose diets for

features such as reproduction (Belovsky and Jordan 1981) Moose gain sodium mainly through aquatic plants

(MacCracken et al 1993) However the compositional analysis shows that freshwater areas are often ranked

as one of the lowest used habitats and coastal areas were removed as the proportion found in the home ranges

was extremely low The Jacobs Index shows that the moose only prefer freshwater areas in the north UD50

during the WS The north individuals again are those that are showing typical moose habitat selection

It is known that habitat selection is hierarchical with habitats that increase fitness selected for and the effects

of limiting factors are reduced (Rettie and Messier 2000) At the UD95 during the GS moose preferred areas

of good forage (forests) and avoided areas of low forage (freshwater and sparsely vegetated areas) and areas

close to humans (urban) This is consistent with other reports (Laurian et al 2008 Torres et al 2011) Within

the UD50 there is a shift in preferences The good forage areas are again preferred during the GS however

during WS the only preferred habitat is often agricultural land During the WS there could be a steady supply

of supplementary feed available hence the high levels of agricultural produce found in the rumen content

samples and the high preference of agricultural areas This diet is unusual for moose previous studies of

Swedish moose diet have found the GS diet was dominated by birch willow and herbaceous plants and the

WS diet dominated by pine and birch (Cederlund and Nystrom 1981) The diet analysis was conducted during

the WS instead of being dominant pine composed just 2 Birch did not appear however unidentified wood

composed only 9 whereas agricultural produce accounted for 69 Supplementary feed may be perceived

by the moose in the centre and south as a vital forage source during the WS In fact in the centre the

agricultural land is the only preferred habitat at the UD50 It is unknown whether there are salt licks provided

in these areas Selection for a critical habitat is often thought to be a fixed factor The Oumlland population from

21 the three areas are close in proximity however they displayed contrasting preferences This is supported by the

Osko et al (2004) report that found two neighbouring moose populations that had access to the same habitats

displayed contrasting preferences Habitat preferences for populations of the same species are not necessarily

fixed They alter with varying levels of habitat abundance and limiting factors skewing what is preserved to

be critical

The main limitation encountered in this study was with the limited sample There was only data on two

individuals from the north of the island which led it being removed from many of the analysis Similarly due

to a lack of relocations from the collars being turned off at points throughout the year two further individuals

had to be removed from a majority of the analysis This reduced the sample size to 17 or 18 individuals

Similarly only 13 of the individuals from the study produced calves This unfortunately prevented including

survival into models Although the sample size was small it was accurate it was of high resolution over

300000 GPS points In future it would be beneficial to have a more standardised data set An equal sample of

individuals from the three areas would be advised along with ensuring the GPS collars are kept turned on for

the entirety of the growing and winter season to allow comparisons between years It would also be

advantageous to collect coordinates of the feeding sites along with the composition This could then be

compared with high use UD coordinates to look if moose are truly spending a majority of their foraging time

at feeding stations A study on the population densities of moose and the increasing population of roe deer

(Capreolus capreolus) would add the factor of competition into the model

The low calf survival on Ӧland is most likely the result of a combination of factors The lack of suitable habitat

reported in this study in conjunction with Malmstenrsquos (2014a) report on the threat of disease (Anaplasma

phagocytophilum) are probable influences on the calf survival on Ӧland On Ӧland there is an increasing

population of roe deer and large numbers of migratory birds both carriers of ticks and diseases The mild

conditions on Ӧland are advantageous for ticks the carriers of A phagocytophilum Fewer snow days and

shorter periods of snow cover along with dry conditions are favourable for ticks This could probably be one

of the reasons for females to be of lower quality and therefore not being able to ensure calf survival Moose

have to utilise areas where in other populations individuals tend to avoid Finally similar to many studies I

advocate further research using a stronger dataset and longer term monitoring

22

Acknowledgements

I am indebted to NJ Singh and A Allen for all their help and guidance through the whole of this study I

thank SLU for the support provided during this study in terms of data finances and facilities Thank you to

everyone at the Department of Wildlife Fish and Environmental Studies for being so friendly and

supportive I would like to thank L Edenius for driving me around the study area and S Michon and H

Khalil for keeping me sane with fika and training

23 References

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Bradshaw RHW Hannon GE Lister AM (2003) A long-term perspective on ungulate-vegetation

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Ericsson G Malmsten J Neumann W Singh NJ Dali AM Submitted Summer Calf Survival of

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Tveito OE Foslashrland EJ Alexandersson H Drebs A Jonsson T Vaarby-Laursen E (2001) Nordic climate

maps Norway CICERO

Udina IG Danilkin AA Boeskorov GG (2002) Genetic diversity of moose (Alces ales L) in Eurasia

Russian Journal of Genetics 38951-957

van Beest FM van Moorter B Milner JM (2012) Temperature-mediated habitat use and selection by a heat

sensitive northern ungulate Animal Behaviour 84(3)723-735

van Winkle W (1975) Comparision of several probabilistic home-range models Journal of Wildlife

Management 39118-123

Verme LJ Ullrey DE (1984) Physiology and nutrition White-tailed deer ecology and management (Ed By

Halls LK) pp 91-118 Stackpole Harrisburg Pennsylvania

Wattles DW DeStefano (2013) Space use and movements of moose in Massachusetts Implications for

conservation of large mammals in a fragmented environment Alces 4965-81

White RG Rowell JE Hauer WE (1997) The role of nutrition body condition and lactation on calving

success in muskoxen Journal of Zoology 24313-20

30

Appendix A

Introduction

Fig 1 Summary chart of factors affecting the life history and therefore the long term fitness of a population

Fig 2 Summary chart 2

Movement

Habitat

Climate

Topography

Competition

FoodWater

Disease

Die

Survive

Reproduce

Population long term fitness

31 Appendix B

Method and Materials

Fig 1 Summary of processes

32

Fig 2 Examples of classical kernel home range output and Brownian bridge kernel home range (Calenge 2011) The

right image includes the area between relocations ie the movement path in contrast to the classic kernel home range

in the left image

33 Appendix C

Home ranges

Fig 1 Example of a non-migratory (ID006) individuals BRB kernel area From top left annual growing and winter

season UD50 (black contour) and UD95 (red contour)

Fig 2 Example of a migratory (ID012) individuals BRB kernel area From the left annual growing and winter season

UD50 (black contour) and UD95 (red contour)

34

Table 1 Annual and seasonal UD50 and UD95 areas (ha) for all individuals

ID Annual GS WS

UD50 UD95 UD50 UD95 UD50 UD95

ID004 190 924 93 531 173 941

ID005 230 1364 132 945 72 682

ID006 162 1036 89 736 70 611

ID008 277 1536 156 809 78 738

ID009 137 834 48 295 126 653

ID010 114 682 83 448 96 488

ID012 177 963 123 544 76 545

ID014 160 1018 87 575 89 662

ID015 172 858 128 532 109 679

ID016 156 1047 65 455 92 534

ID017 153 1088 149 1043 69 349

ID019 279 1097 176 911 163 824

ID020 139 1084 67 349 160 794

ID022 159 811 131 638 61 454

ID023 187 1061 147 771 72 705

ID024 146 725 165 705 101 458

ID026 142 605 99 442 125 547

ID027 126 567 75 461 48 277

35 Appendix D

Activity

Fig 1 Mean daily movement during the study period GS 23-April-2012 to 07-Nov-2012 WS 08-Nov-2012 to

22-April-2013 (number indicates month)

Fig 2 Mean daily movement in the centre and south during the GS and WS

36

Appendix E

Habitat Proportions

Fig 1 All individualsrsquo seasonal habitat proportions within the UD95

37 Habitat Selection

Table 1 Simplified ranking matrices comparing proportional habitat use within the second order (UD95Area) with

proportions of total available habitat types Mean value on the matrix was replaced by a sign a triple sign represents

significant deviation from random at P lt05 Highlighted habitat is ranked 1st

North A

gri

cult

ure

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 --- --- - +++ --- --- --- +++ +++ --- 8

Broad Leaf +++ 0 +++ + +++ +++ +++ + +++ +++ +++ 1

Clear Fell +++ --- 0 + +++ - - --- +++ +++ --- 7

Coniferous + - - 0 +++ - - --- +++ +++ - 6

Freshwater --- --- --- --- 0 --- --- --- +++ - --- 10

Grassland

Moors +++ --- + + +++ 0 +++ - +++ +++ + 3

MiresMarshes +++ --- + + +++ --- 0 - +++ +++ --- 5

Mixed +++ - +++ +++ +++ + + 0 +++ +++ + 2

Sparse Veg --- --- --- --- --- --- --- --- 0 --- --- 11

Urban --- --- --- --- + --- --- --- +++ 0 --- 9

Younger +++ --- +++ + +++ - +++ - +++ +++ 0 4

Rank Order and

Significance

Broad Leafgt Mixedgt GrasslandMoorsgt Youngergtgtgt MiresMarshesgt Coniferousgt

Clear Fellgtgtgt Agriculturegtgtgt Urbangt Freshwatergtgtgt Sparse Veg

Central

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 --- --- --- + +++ + --- +++ +++ --- 6

Broad Leaf +++ 0 +++ + +++ +++ + - +++ +++ - 3

Clear Fell +++ --- 0 - +++ +++ + --- +++ +++ --- 5

Coniferous +++ - + 0 +++ +++ + --- +++ +++ - 4

Freshwater - --- --- --- 0 +++ - --- +++ +++ --- 8

Grassland

Moors --- --- --- --- --- 0 --- --- +++ - --- 10

MiresMarshes - - - - + +++ 0 - +++ +++ - 7

Mixed +++ + +++ +++ +++ +++ + 0 +++ +++ + 1

Sparse Veg --- --- --- --- --- --- --- --- 0 - --- 11

Urban --- --- --- --- --- + --- --- + 0 --- 9

Younger +++ + +++ + +++ +++ + - +++ +++ 0 2

Rank Order and

Significance

Mixedgt Youngergt Broad Leafgt Coniferousgt Clear Fellgtgtgt Agriculturegt

MiresMarshesgt Freshwatergtgtgt Urbangt GrasslandMoorsgtgtgt Sparse Veg

38

South

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 + - - + - + +++ +++ +++ - 5

Broad Leaf - 0 - - + - - +++ + +++ - 7

Clear Fell + + 0 - + + + +++ + +++ + 2

Coniferous + + + 0 +++ + + +++ + +++ + 1

Freshwater - - - --- 0 - - + + +++ - 8

Grassland

Moors + + - - + 0 + + +++ + - 4

MiresMarshes - + - - + - 0 +++ + +++ - 6

Mixed --- --- --- --- - - --- 0 + + --- 10

Sparse Veg --- - - - - --- - - 0 + - 9

Urban --- --- --- --- --- - --- - - 0 --- 11

Younger + + - - + + + +++ + +++ 0 3

Rank Order

and

Significance

Coniferousgt Clear Fellgt Youngergt GrasslandMoorsgt Agriculturegt MiresMarshesgt Broad Leafgt

Freshwatergt Sparse Veggt Mixedgt Urban

Table 2 Simplified ranking matrices comparing proportional habitat use within the third order (UD50UD95) with

proportions of total available habitat types Mean value on the matrix was replaced by a sign a triple sign represents

significant deviation from random at P lt05 Highlighted habitat is ranked 1st

North

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 --- --- --- - + --- --- + +++ --- 8

Broad Leaf +++ 0 +++ + + + + + +++ +++ + 1

Clear Fell +++ --- 0 + + + - - + +++ - 5

Coniferous +++ - - 0 + + --- --- +++ +++ - 6

Freshwater + - - - 0 +++ - - +++ +++ - 7

GrasslandMoors - - - - --- 0 - - - + - 10

MiresMarshes +++ - + +++ + + 0 - +++ +++ + 3

Mixed +++ - + +++ + + + 0 +++ +++ + 2

Sparse Veg - --- - --- --- + --- --- 0 +++ --- 9

Urban --- --- --- --- --- - --- --- --- 0 --- 11

Younger +++ - + + + + - - +++ +++ 0 4

Rank Order and

Significance

Broad Leafgt Mixedgt MiresMarshesgt Youngergt Clear Fellgt Coniferousgt Freshwatergt

Agriculturegt Sparse Veggt GrasslandMoorsgt Urban

39

Central

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 --- --- + + - - - + +++ --- 7

Broad Leaf +++ 0 + +++ + + + + + +++ - 2

Clear Fell +++ - 0 +++ + + + + + +++ - 3

Coniferous - --- --- 0 + - - --- +++ + --- 8

Freshwater - - - - 0 --- - - --- - - 11

GrasslandMoors + - - + +++ 0 + - + +++ - 5

MiresMarshes + - - + + - 0 + + +++ - 6

Mixed + - - +++ + + - 0 +++ +++ - 4

Sparse Veg - - - --- +++ - - --- 0 +++ - 9

Urban --- --- --- - + --- --- --- --- 0 --- 10

Younger +++ + + +++ + + + + + +++ 0 1

Rank Order and

Significance

Youngergt Broad Leafgt Clear Fellgt Mixedgt GrasslandMoorsgt MiresMarshesgt

Agriculturegt Coniferousgtgtgt Sparse Veggtgtgt Urbangt Freshwater

South

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 - - - - - + - +++ + --- 8

Broad Leaf + 0 - --- + - + - +++ + - 6

Clear Fell + + 0 - + - + - +++ + - 4

Coniferous + +++ + 0 + + +++ + +++ + + 1

Freshwater + - - - 0 - - + + + - 7

GrasslandMoors + + + - + 0 + + + + - 3

MiresMarshes - - - --- + - 0 - + + - 9

Mixed + + + - - - + 0 + + - 5

Sparse Veg --- --- --- --- - - - - 0 + --- 10

Urban - - - - - - - - - 0 - 11

Younger +++ + + - + + + + +++ + 0 2

Rank Order and

Significance

Coniferousgt Youngergt GrasslandMoorsgt Clear Fellgt Mixedgt Broad Leafgt Freshwatergt

Agriculturegt MiresMarshesgt Sparse Veggt Urban

40

Table 3 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the GS according to Jacobs index

Ran

k North Centre South

50 95 50 95 50 95

+ - + - + - + - + - + -

1 Broad

Leaf Urban Broad Leaf Sparse Veg

Broad

Leaf Urban Mixed Urban Coniferous Urban

Grassland

Moors Urban

2 Mixed Sparse Veg Mixed Freshwater Younger Agriculture Younger Sparse Veg Younger Sparse Veg Clear Fell Mixed

3 Mires

Agriculture Grassland

Urban Clear

Fell Coniferous Broad Leaf

Grassland

Moors

Clear Fell Agriculture Coniferous Sparse Veg

Marshes Moors

4 Younger Grassland

Younger Agriculture

Freshwater Coniferous Freshwater

Broad Leaf Mires

Younger Freshwater

Moors Marshes

5 Clear

Fell Freshwater

Mires Coniferous

Sparse Veg Clear Fell Agriculture

Freshwater Agriculture

Marshes

6 Coniferous Clear Fell

Mires

Marshes

Mires

Grassland

Moors

Mires

Marshes Marshes

7 Mixed Mixed Broad Leaf

8 Grassland

Moors

41

Table 4 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the WS according to Jacobs index

Ran

k North Centre South

50 95 50 95 50 95

+ - + - + - + - + - + -

1 Mires

Marshes

Grassland

Moors Mixed Freshwater Agriculture Urban Mixed Freshwater

Grassland

Moors Urban GrasslandMoors Urban

2 Freshwater Mixed Coniferous Urban Mires

Marshes Coniferous Sparse Veg Agriculture

Sparse

Veg Coniferous Freshwater

3 Urban Coniferous Younger Grassland

Moors Freshwater Younger Urban Freshwater

Broad

Leaf Agriculture Mixed

4 Younger Agriculture Sparse Veg Broad

Leaf

Broad

Leaf

Grassland

Moors Mixed Broad Leaf

5 Clear Fell Agriculture Coniferous Agriculture Mires

Marshes Clear Fell

6 Sparse

Veg

Mires

Marshes Mixed

Mires

Marshes

Clear

Fell

Mires

Marshes

7 Broad

Leaf Clear Fell Younger Clear Fell Younger Sparse Veg

8 Clear Fell Younger

9 Sparse

Veg

10 Grassland

Moors

42

Table 5 Second order (UD95Area) individual selectionavoidance for the GS and WS according to the Jacobs index

ID GS WS

Select Avoid Select Avoid

ID004 Younger Sparsely Vegetated MiresMarshes Sparsely Vegetated

ID005 MiresMarshes Sparsely Vegetated Coniferous GrasslandMoors

ID006 Coniferous Sparsely Vegetated Mixed Freshwater

ID008 Mixed Sparsely Vegetated Mixed Freshwater

ID009 Mixed Sparsely Vegetated Mixed GrasslandMoors

ID010 MiresMarshes Freshwater GrasslandMoors Freshwater

ID012 Broad Leaf Sparsely Vegetated Coniferous Urban

ID014 Clear Fell Sparsely Vegetated GrasslandMoors Sparsely Vegetated

ID015 GrasslandMoors Urban GrasslandMoors Freshwater

ID016 GrasslandMoors Freshwater GrasslandMoors Freshwater

ID017 GrasslandMoors Mixed Sparsely Vegetated Mixed

ID019 Mixed Sparsely Vegetated Mixed Urban

ID020 Broad Leaf Sparsely Vegetated Coniferous GrasslandMoors

ID022 MiresMarshes Freshwater MiresMarshes Freshwater

ID023 MiresMarshes GrasslandMoors Mixed Freshwater

ID024 Broadleaf Urban Broad Leaf Urban

ID026 GrasslandMoors Freshwater GrasslandMoors Freshwater

ID027 GrasslandMoors Urban Sparsely Vegetated Freshwater

43 Table 6 Third order (UD50UD95) individual selectionavoidance for the GS and WS according to the Jacobs index

ID GS WS

Select Avoid Select Avoid

ID004 Broad Leaf Mixed GrasslandMoors Freshwater

ID005 Broad Leaf Freshwater Agriculture Freshwater

ID006 Clear Fell Freshwater Agriculture MiresMarshes

ID008 MiresMarshes Freshwater Agriculture Urban

ID009 Freshwater Agriculture Agriculture Freshwater

ID010 Mixed Urban Sparsely Vegetated Urban

ID012 Coniferous GrasslandMoors Freshwater Urban

ID014 Urban Agriculture Freshwater Urban

ID015 Mixed Forest Urban Clear Fell Urban

ID016 Freshwater Urban GrasslandMoors Mixed

ID017 Coniferous Mixed Coniferous Broad Leaf

ID019 Broad Leaf GrasslandMoors Urban GrasslandMoors

ID020 Freshwater Urban Freshwater Agriculture

ID022 MiresMarshes Urban Broad Leaf GrasslandMoors

ID023 Freshwater Mixed Agriculture Freshwater

ID024 Mixed Freshwater Mixed Freshwater

ID026 Mixed MiresMarshes Sparsely Vegetated GrasslandMoors

ID027 Freshwater MiresMarshes GrasslandMoors Broad Leaf

44

Fig 2 North third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)

45

Fig 3 Centre third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)

46

Fig 4 South third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)

47

Fig 5 North second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)

48

Fig 6 Centre second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)

49

Fig 7 South second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)

50

Appendix F

Background

Fig 1 Daily mean snow depth and duration during the study period (Andrew Allen)

Female Moose Reproduction

Moose are seasonal polyoestral mammals (Monfort et al 1993) coming into oestrus during late September

early October (Garel et al 2009) The Swedish moose cow population reaches puberty between the ages 25

and 35 (Sand and Cederlund 1993) during which the reproductive period begins with the onset of ovulation

The age an individual reaches puberty is dependent on their body condition they have to reach a weight

threshold to reach puberty and become reproductive (Sand 1996) If she is over the weight threshold she will

go into oestrus in the autumn If she does not reach the weight threshold then she will go into oestrus the

following autumn if successful she will give birth to individual or twin calves in late May to early June

(Ericsson et al 2001) and therefore reach sexual maturity (Malmsten et al 2014b) Fecundity is related to

both the condition and the age of the cow Cows go through senescence at 12 years of age (Ericsson et al

2001) Providing calves with the required level of nutrition demands high energy and protein resources from

the mother during senescence this becomes harder to achieve leading to decreased levels of parental care

and higher levels of calf mortality

Page 7: Habitat-performance relationships on an island: fitness ...navinderjsingh.weebly.com/uploads/1/1/2/2/11224342/... · Conditions on Öland are milder than those found in other areas

7 Materials and Methods

Study area

Ӧland (567333deg N 166667deg E) a Baltic island located in Kalmar county (Fig 1) is Swedenrsquos second largest

island (~140km in length) It can be split broadly into three areas the north (N) centre (C) and south (S) There

are three typical habitats found on the island boreal forests Stora Alvaret and agricultural land The largest

portions of boreal forests are found in the far north the centre and a patch in the far south Forest stands are

dominated by birch (Betula pubescens B pendula) and Scots pine (Pinus sylvestris) with rowan (Sorbus

aucuparia) aspen (Populus tremula) grey alder (Alnus incana) and yew (Taxus baccata) interspersed

throughout with willow sp (Salix spp) in areas near water sources (Sӕther and Heim 1993) The field layer is

made up of primarily bilberry (Vaccinium myrtillus) lowbush cranberry (Vaccinium vitis-idӕa) and heather

(Calluna vulgaris) (Cederlund 1989) The patches of boreal forest in the north centre and south are isolated

from each other by agricultural areas which are distributed throughout the island particularly along the coastal

regions and the island centre The most southerly patch of forest was protected from becoming agricultural

due to its status as a royal hunting ground and an important stopover for migratory birds (Lars Edenius

personal communication April 09 2014) The southern part of Oumlland has the largest expanse of steppe-like

alvar grassland (Stora Alvaret) found in the world (~25500 ha) (Roseacuten 2006) which is found over dry shallow

nutrient-poor grazed soil (Bakker et al 1996) on top of superficial Ordovician limestone (Dengler et al 2006)

Conditions on Oumlland are milder than those found in other areas of Sweden as it is positioned in the ldquorain-

shadowrdquo of mainland Sweden (Prentice 2007) The only predators of moose found on Oumlland are hunters which

were banned from hunting in previous years

Fig 1 Location of Oumlland

8

Capture and Handling

A random sample of adult moose (n = 25) were darted sedated and equipped with GPSGSM neck collars

(Vectronic Aerospace GmbH Berlin Germany) during the winter of 2012 by the Moose Research Group

SLU Movement data were collected from GPS collars dating from 22022012 ndash 24042014 Collars were

fixed to return GPS locations approximately every 30 minutes

Data Screening

The sample contained both males and females (six males 19 females x female age = 95 years range 4-17

years) An initial inspection revealed that one female individual only returned fixed locations for a period of

eight months Locations ceased during the hunting period so the individual was presumed shot and was

removed from the data along with the males

The exact time between each location varied and sometimes no fix could be made The adehabitatLT package

(Calenge 2006) was used to standardise the data and overcome the location fixing errors The function setNA

was used to place NAs where relocations were missing The function sett0 was used to round the timing of

collection obtaining a regular trajectory with 30 minute intervals The final dataset used in the analysis

consisted of 302710 regular GPS data points from a sample size of n=18 individuals two individuals from the

north ten individuals from the centre and six individuals from the south

To address the question and to investigate the influence of climate on the space use patterns of moose the

analysis was performed at two scales The first included all annual movements of moose and the second at a

seasonal scale ie summer and winter The seasonal scales were defined according to the growing season (GS)

and winter season (WS) In Scandinavia the current method used to define the start of season (SOS) is the

period when the daily mean air temperature is above 5degC (GS) Methods of calculating SOS are advancing

with the use of the Normalized Difference vegetation Index (NDVI) becoming more popular The start and

end of the GS and WS were derived using the mean start and end dates for Oumlland suggested by the Norwegian

Meteorological Institute (DNMI) Nordic climate map report (Tveito et al 2001) The GS of this study is

defined as the period between 23-April-2012 to 07-Nov-2012 and the WS is defined as the period between 08-

Nov-2012 to 22-April-2013 (based on the current standard normal period 1961-90)

Home rangeUtilization distribution

Variation in ungulate home range size is known to be caused by changes in energy requirements and variation

in food availability (Tufto et al 1996 Kie et al 2010 Moreller et al 2013) With shifting climate causes shifts

in plant phenology and therefore the spatial and temporal distribution of ungulate food (Maringrell et al 2006)

Individuals alter their home ranges to meet their energy requirements to maintain their fitness (Albon et al

1987 White 1997 Festa-Bianchet et al 1998 Forchhammer et al 2001)

The most commonly cited definition of a home range is ldquothat area traversed by the animal during its normal

activities of food gathering mating and caring for youngrdquo (Burt 1943) This has now been expanded to

9 incorporate measures of space use using the utilization distribution (UD van Winkle 1975) which can be

described as the ldquorelative frequency distribution of an animalrsquos occurrence in all four dimensions of space

and timerdquo (Keating and Cherry 2009) Home range is viewed as a constant 2D polygon whereas UDs are

viewed as multiple 3D polygons that take into account the distribution as well as the intensity of animalrsquos

movements and space use within their home range (Kranstauber et al 2012) (see appendix A)

Estimations of each individualrsquos annual and seasonal UDs were found using the Biased Random Bridge (BRB)

kernel approach (Benhamou 2011) from the adehabitatHR package (Calenge 2006) in R It was chosen as it is

considered an improvement on the previously preferred Brownian bridge (BB) method (Horne et al 2007) The

BB is purely a diffusive movement process whereas the BRB is an advective-diffusive movement process BB

does not take into account changes in advection direction (drift) or strength BB assumes an animalrsquos

movement is purely random it moves from a starting point and ends up at the end location randomly By

adding the advection component the BRB takes into account that the animalrsquos movement is biased towards a

certain direction This allows for a more biologically relevant analysis (Benhamou and Corneacutelis 2010)

A grid was created using the minmax XY coordinates of all individuals (plusmn 10 km to increase the extent and

prevent the grid directly touching the XY locations) The resolution of the grid was fixed at a 25 m x 25 m

scale to match the resolution of the relevant habitat maps (Hagner et al 2005) By specifying these criteria the

resolution of the data remains consistent between individuals The diffusion coefficient determines the variance

in the location of the kernels between two locations This was calculated from each individualrsquos dataset using

the BRBD function and added to the BRB model (see Benhamou 2011) The strength and direction of BRB

advection can change between bridges whilst having to remaining constant To remain constant an upper Tmax

and lower Lmin time thresholds were set Successive relocations that exceeded Tmax or under Lmin were

removed from the UD calculations The 50 (UD50) and 95 (UD95) isopleths were then calculated from

the UD using the kernelarea function

Habitat

The scale of analysis was further divided following Johnson (1980) Habitat selection within the landscape

(second order selection) was studied by comparing the UD95 with available habitats in each of the three study

areas of Oumlland (UD95Area) Habitat selection within the home range (third order selection) was studied by

comparing the UD50 with the UD95 (UD50UD95)

12 habitat classes were used in the analysis agricultural land broad leaved forests clear felled areas coastal

coniferous forests freshwater areas moorsgrassland miresmarshes mixed forest sparsely vegetated areas

urban areas and younger forests The proportion of area covered by each of these habitat classes was

determined in the UD50 and UD95 Habitat data was obtained from satellite imagery generated by Svenska

Marktaumlckedata (Hagner et al 2005) The habitat maps were last updated in 2002 and have a resolution of 25

m

Compositional analysis ( habitat used habitat available) (Aebischer 1993) was used in conjunction with

the Jacobrsquos index (D) (eqn1) to quantify habitat selection (Jacobs 1974) Coastal areas were removed as not

10

all home ranges contained them This combined approach allowed identification of habitats that are used

disproportionally to their availability ie in a non-random manner (Beyer et al 2010) This is an indication of

which habitats are important for an individual

119863 = ( 119903minus119901

119903+119901minus2119903119901 ) (eqn1)

r = Proportion of habitat type used

p = Total proportion of habitat available

D = Jacobs index varies from -1 (strong avoidance) to +1 (strong preference) with values close to 0 indicating

the habitat is used in proportion to its availability

Activity

Activity level is measured as the mean daily movement (MDM) by the individual to investigate if individuals

in an areaseason moved more and hence were more active than those in other areasseasons Unfortunately

only two cows were collared in the north and were therefore left out of this analysis Moose were identified as

migratory using a modelling approach (see Bunnefeld et al 2011 for methods) Migratory individuals were

initially removed from the activity analysis (n=4)The reason is that both migratory journeys were completed

during the winter season thus increasing the mean daily distance travelled and potentially biasing the analysis

One individual was also removed due it its collar not returning relocations during the entirety of the WS

Diet analysis

The Ӧland project team conducted histology diet analysis on the rumen content of five individuals that were

shot in the centre and south of the island during the WS of 2013

Survival analysis

The Ӧland project team measured calf survival using the mark-resight method The presenceabsence of a calf

was recorded by tracking the cows at six occasions throughout the year These were at the start of the calving

season (mid-May to early June) twice through the summer before the hunt after the hunt and after winter

Survival trend was estimated using a Kaplan-Meier curve (Kaplan and Meier 1958) The Kaplan-Meier curve

shows the survival function (S (t)) ie the probability of an individual surviving until at least time t (Bewick

et al 2004) The probability of surviving from one period to the next is multiplied together to give the survival

function The S(t) of this study is the probability of an individual surviving from birth to after the hunt

(Method summary see appendix B)

11 Results

Home RangeUtilization Distribution

A total of 51 home ranges were estimated (17 annual 17 within growing season 17 within winter season)

Annual x = 9613 ha GS x = 6345 ha and WS x = 6023 ha (appendix C)

At the UD50 scale the largest annual and seasonal mean home ranges were located in the north Mean annual

and seasonal home ranges in the centre were slightly larger than the south This difference was not significant

(F(113)= 22 p= 87) (ANOVA) There was no significant difference between the seasonal home ranges (x

plusmnSD for GS = 116 plusmn38 for WS = 98 plusmn32 ha) (t(11) = 105 p = 32) or the seasonal home ranges in the centre

(t(8) = 101 p = 34 and the south (t(5) = 87 p = 42) (paired-sample t-test) (Table 1)

At the UD95 scale the largest annual and WS mean home ranges were located in the north The largest GS

mean home ranges were located in the centre Mean annual and seasonal home ranges in the centre were

slightly larger than the south This difference was not significant (F(113) = 59 p = 63) (ANOVA) There

was no significant difference between the seasonal home ranges (x plusmnSD for GS = 635 plusmn225 for WS = 602

plusmn161) (t(11) = 373 p = 71) or the seasonal home ranges in the centre (t(8)= 20 p = 84) or south (t(5) = 34

p = 74) (paired-sample t-test) (Table 1)

Table 1 Seasonal and annual mean UD50 and UD95 BRB kernel area in hectares (1ha = 001km2) for the north centre

and south of Oumlland (smoothing factor (h) =100)

Are

a

Annual UD50 GS UD50 WS UD50

n Mean SD Range n Mean SD Range n Mean SD Range

N 2 209 49 139-279 2 1215 39 67-176 2 1615 106 160-163

C 9 178 56 114-277 9 116 44 48-165 9 943 4 61-173

S 6 160 21 142-177 6 1085 51 65-149 6 933 35 69-125

Annual UD95 GS UD95 WS UD95

N 2 10905 5 1084-1097 2 630 199 349-911 2 809 11 794-824

C 9 997 32 682-1536 9 6531 22 295-945 9 637 17 454-941

S 6 9298 30 605-1088 6 5985 373 442-575 6 5526 20 349-679

12

Activity

MDM rates in the three areas (sedentary individuals) during the GS ranged from 14 ndash31 km day During the

WS ranged they ranged from 11-24 km day (Table 2) Movement rates during the GS were higher than the

WS (x plusmnSD for GS = 202 plusmn043 for WS = 161 plusmn043) but it was not statistically significant (t(11) = 200 p=

07) (paired sample t-test)

Table 2 Seasonal mean daily movement rates (km day) for each area and for both areas (total)

Are

a

GS WS

n Mean SE Range n Mean SE Range

C 8 20 003 14-18 8 20 004 12-24

S 4 22 016 17-31 4 12 02 11-13

Total 12 202 003 14-31 12 16 003 11-24

The seasonal MDM rates of all individuals (migratory and sedentary) were not significantly different (x plusmnSD

for GS = 20 plusmn04 for WS = 18 plusmn061) (t(14) = 139 p= 19) (paired sample t-test)

The WS home range size affects the WS MDM (F(110) = 927 p = 01) (ANOVA) The GS home range size

does not affect the GS MDM (F(110) = 36 p = 56) (ANOVA) When the WS home range outlier was

removed the home range size did not affect the WS MDM (F(111) = 186 p= 19) (ANOVA) The MDM was

lowest in February and highest in April (Table 3) there appeared to be no significant pattern in MDM between

the months (appendix D)

Table 3 Mean daily distance moved (km day) for sedentary individuals

Month Season Distance

April GS 0051

May GS 0044

June GS 0039

July GS 0041

August GS 0042

September GS 0044

October GS 0043

November WS 0043

December WS 0038

January WS 0035

February WS 0028

13 Habitat ndash Proportions

The largest proportion of habitat on the island is agriculture the lowest proportion of habitat (excluding coastal

and freshwater) is urban areas (Fig 2) The largest proportion of habitat in the north was coniferous forests

whilst agricultural areas were the dominant habitat types in the centre and south (Fig 3) The lowest proportion

(excluding coastal and freshwater areas) was urban

Fig 2 Proportion of different types of habitats found on Ӧland

Fig 3 Mean proportion of habitats contained within UD95 in the three areas of Oumlland C = Centre N = North S =

South

14

Habitat - Selection

Generally forest habitat types are the highest ranked whilst sparsely vegetated and urban areas are the lowest

ranked Both the second and third order habitat selection analyses gave significant results in the compositional

analysis (Table 4) In the third order analysis (UD50UD95) the centre displayed significant differences

between habitat types The coniferous forests are significantly preferred to sparsely vegetated areas and the

sparsely vegetated areas are significantly preferred to urban areas In the second order analysis (UD95Area)

significance was observed in the north and centre In the north younger forests are significantly preferred to

miresmarshes clear felled areas are significantly preferred to agriculture and freshwater areas are significantly

preferred to sparsely vegetated areas In the centre clear felled areas are significantly preferred to agricultural

land freshwater areas are significantly preferred to urban areas and grasslandmoors are significantly preferred

to sparsely vegetated areas

Table 4 Summary of second (UD95Area bottom) and third order (UD50UD95 top) ranked habitat preferences between

the three areas according to the compositional analysis (see appendix B)

Rank North Centre South

1 Broad Leaf Younger Coniferous

2 Mixed Broad Leaf Younger

3 MiresMarshes Clear Fell GrasslandMoors

4 Younger Mixed Clear Fell

5 Clear Fell GrasslandMoors Mixed

6 Coniferous MiresMarshes Broad Leaf

7 Freshwater Agriculture Freshwater

8 Agriculture Coniferous Agriculture

9 Sparse Veg Sparse Veg MiresMarshes

10 GrasslandMoors Urban Sparse Veg

11 Urban Freshwater Urban

Rank North Centre South

1 Broad Leaf Mixed Coniferous

2 Mixed Younger Clear Fell

3 GrasslandMoors Broad Leaf Younger

4 Younger Coniferous GrasslandMoors

5 MiresMarshes Clear Fell Agriculture

6 Coniferous Agriculture MiresMarshes

7 Clear Fell MiresMarshes Broad Leaf

8 Agriculture Freshwater Freshwater

9 Urban Urban Sparse Veg

10 Freshwater GrasslandMoors Mixed

11 Sparse Veg Sparse Veg Urban

Indicates significantly preferred to the habitat below (significant deviation from random at P lt05)

15 The Jacobs index revealed that generally the habitats preferred during the GS within the home range (third

order) are younger (0187) and broad leaf forests (0154) The strongest avoidance was for urban areas (-0627)

During the WS only agricultural areas are preferred (0129) and the strongest avoidance was for urban areas (-

0393) (Fig 4)

Fig 4 Third order seasonal habitat preference (UD50UD95) all individuals The index ranges from -1 (total avoidance)

to 1 (strongest preference) Close to 0 indicates used in proportion to its availability

Third order habitat preferencesavoidances by area

North During the GS the strongest preference was for broad leaf (0218) and mixed forests (0161) The

strongest avoidance was for urban (-1) and sparsely vegetated areas (-05) During the WS the strongest

preference was for miresmarshes (0228) The strongest avoidance was for grasslandmoors (-05)

Centre During the GS the strongest preference was for broad leaf (0233) and younger forests (0223) The

strongest avoidance was for urban (-0527) and agricultural land (-0362) During the WS preference was only

shown for agricultural land (0327) The strongest avoidance was for urban areas (-0679) and miresmarshes

(-0638)

South During the GS the strongest preference was for coniferous (0312) and younger forests (0242) The

strongest avoidance was for urban (-0353) and sparsely vegetated areas (-0330) During the WS

grasslandmoors (0106) were the strongest preference The strongest avoidance was for urban (-0666) and

sparsely vegetated areas (-0351)

16

The Jacobs indices revealed that generally the habitats preferred during the GS within the landscape

(UD95Area) are broad leaf (0216) and younger forests (0201) The strongest avoidance was for urban (-

0717) and freshwater areas (-0694) The strongest preference during the WS are coniferous forests (0242)

and the strongest avoidance was for freshwater (-0674) and urban areas (-0648) (Fig 5)

Fig 5 Second order seasonal habitat preference (UD50UD95) all individuals The index ranges from -1 (total avoidance)

to 1 (strongest preference) Close to 0 indicates used in proportion to its availability

Second order habitat preferencesavoidances by area

North During the GS the strongest preference was for broad leaf (0363) and mixed forests (00291) The

strongest avoidance was for sparsely vegetated (-0909) and freshwater areas (-0780) During the WS mixed

(0335) and coniferous forests (0316) were the strongest preference The strongest avoidance was for

freshwater (-0731) and urban areas (-05333)

Centre During the GS the strongest preference for mixed (0394) and younger forests (0286) The strongest

avoidance was for urban (-0733) and sparsely vegetated (-0708) areas During the WS mixed (0404) and

coniferous forests (0255) were the strongest preference The strongest avoidance was for freshwater (-0704)

and sparsely vegetated areas (-0655)

South During the GS the strongest preference for grasslandmoors (0287) and clear fells (0165) The

strongest avoidance was for urban areas (-0678) and mixed forests (-0491) During the WS grasslandmoors

(0425) and coniferous forests (0154) were the strongest preference The strongest avoidance was for urban (-

0876) and freshwater areas (-0587) (appendix E)

17 Diet

Diet analysis of the rumen content sampled from five individuals (C=2 S=3) revealed that almost two thirds

(69) of the diet is comprised of agricultural produce (apple winter rape and sugar beet) (Fig 6)

Fig 6 Diet analysis from the rumen samples of five moose individuals that were culled in 2013

31

2117

9

8

5

22

1 1

1

1

1 00 0

0

0Diet (2610-911 2013 5 individuals)

AppleWinter RapeSugar BeetUndefined WoodSallowBroad-leaf GrassPineAshOakCloverCurrantsUndefined plantElderberryJuniperRaspberry

18

Calf Survival

Of the 18 individuals 13 produced calves in which 7 produced twins giving a total of 20 calves A Kaplan-

Meier estimate was conducted to measure the fraction of calves living up to each period of the study (Fig 7)

The mean survival time is until period 235 (midend of summer) At the start of summer 85 of calves

remained (3 still born) The period between summer and before the hunt survival drops to 30 The survival

at the end of the study (after hunt) drops further to 20 leaving 4 calves surviving (see appendix B)

Fig 7 Kaplan-Meier estimate of moose calf survival during the study period Period 0 (Start of summer) period 1

(midend of summer) period 2 (before hunt) period 3 (after hunt) period 4 (after winter)

19 Discussion

The results of this study emphasised how strikingly different the habitat composition is along the latitudinal

gradient of Oumlland The three areas show contrasting proportions of the key habitat types The starkest

difference is the high proportion of coniferous forests and lack of agriculture in the north compared to the

centre and south The proportion of coniferous forest in the north is almost 5 times greater than in the centre

and south whereas the proportion of agriculture in the centre and south is more than double that in the north

The north is perceived to be composed of the most suitable habitat for moose (Dussault et al 2006) It has the

largest proportions of each forest type and a low proportion of agricultural land This provides suitable forage

and shelter throughout the year The south has a contrasting habitat composition to the north The proportions

of agricultural and sparsely vegetated areas are the highest between the three areas and the proportions of forest

habitats are the lowest The large proportion of sparsely vegetated areas and low proportions of forest habitat

corresponds to the large area of Stora Alvaret This is perceived to be the least suitable area due to a lack of

shelter (coniferous forest) and suitable forage The strong preference for coniferous and younger forest habitats

in the south would suggest that moose exhibit a functional response in habitat selection (Godvik et al 2009)

ie as the proportion of a particular habitat decreases the selection for that habitat increases in this case

coniferous forests which provide shelter and younger forest which provide good forage Similarly in the centre

moose show strong preference for mixed forests a habitat that is of low proportion

In view of the large variation in habitat proportions between the areas it is surprising that there is not a large

variation in the home range sizes or the activity levels annually or seasonally Home ranges are ultimately

chosen to maximise fitness and meet energy requirements by utilizing the available forage Seasonal conditions

change the availability and necessity of resources (food quality shelter) Unlike the GS during the WS

deciduous trees and shrubs are leafless and low-lying shrubs are under snow cover (Dussault et al 2005)

These changes are well known to cause populations to alter their activity and home ranges to meet energy

requirements (Mysterud et al 2001) Populations have been shown to increase or decrease their home ranges

during the two seasons The GS home ranges are often larger than the WS home ranges (Philips et al 1973

Mysterud et al 2001) In some cases they can be found to be almost double the size of the WS home ranges

(Cederlund and Okarma 1988) In other populations the WS home ranges are double the size of the GS home

ranges (Lynch and Morgantini 1984) or sizes do not significantly differ (Cederlund and Sand 1994)

Previous studies on moose find females generally show increased activity from the start on the GS due to

various factors eg reduced ruminating times increased metabolic needs and increased foraging bursts

(Wattles and DeStefano 2013) Increased metabolic needs during this time are a results of pregnancy and

lactation (Georgii 1980) During the height of the GS they usually show reduced activity levels through times

of increased thermal stress (Renecker and Hudson 1989 van Beest et al 2012) During the WS the depth and

the duration of snow cover are well known to affect the activity level (Telfer 1970 Mysterud and Oslashstbye 1999

Bjoslashrneraas et al 2011) During the WS generally home ranges are smaller and activity less due to lower

metabolic needs Moose activity is constrained by rumination during the WS this period is known to be longer

due to the change in diet (Cederlund 1989 Renecker Hudson 1989) This was not the case on Ӧland activity

20

was lowest in February which is a similar result to Cederlundrsquos (1989) paper However Ӧland moose did not

significantly alter their seasonal activity levels The fact that the annual and seasonal activity levels and home

ranges were similar could be a result of the mild winters on Oumlland during the study period (Smhise 2014)

During the study period the average number of snow days was 80 and the mean snow depth was 10cm

(appendix F) (Swedish Meterological and Hydrological Institute- SMHI) These mild conditions do not restrict

the movement of moose or obscure forage Moose are well adapted for movement in deep snow depths of 60-

86cm (Prescott 1968) are needed to truly restrict movement This finding was similar to the Sweanor and

Sandegren (1989) and Cederlund and Sand (1994) where the snow depth at their sites did not reach movement

restricting depths

The survival curve illustrates just how bad the calf survival is on Ӧland Survival falls from 85 at the start to

20 Out of 20 calves only four were alive at the end of the study The sharpest fall in survival was the period

between end of summer and before the hunt so the deaths were not due to hunting Previous calf autopsies

(Malmsten 2014a) have shown that cause of death was starvation mothers possibly either did not have milk

the calf was unable to feed or the mother abandoned the calf Closer field based observations are needed to

attain this knowledge Moose are seasonal polyoestral mammals (Monfort et al 1993) coming into oestrus

during late September early October (Garel et al 2009) (appendix F) The diet of the mother influences the

health of the calf and this period is when sodium is hard to find sodium is a key mineral in moose diets for

features such as reproduction (Belovsky and Jordan 1981) Moose gain sodium mainly through aquatic plants

(MacCracken et al 1993) However the compositional analysis shows that freshwater areas are often ranked

as one of the lowest used habitats and coastal areas were removed as the proportion found in the home ranges

was extremely low The Jacobs Index shows that the moose only prefer freshwater areas in the north UD50

during the WS The north individuals again are those that are showing typical moose habitat selection

It is known that habitat selection is hierarchical with habitats that increase fitness selected for and the effects

of limiting factors are reduced (Rettie and Messier 2000) At the UD95 during the GS moose preferred areas

of good forage (forests) and avoided areas of low forage (freshwater and sparsely vegetated areas) and areas

close to humans (urban) This is consistent with other reports (Laurian et al 2008 Torres et al 2011) Within

the UD50 there is a shift in preferences The good forage areas are again preferred during the GS however

during WS the only preferred habitat is often agricultural land During the WS there could be a steady supply

of supplementary feed available hence the high levels of agricultural produce found in the rumen content

samples and the high preference of agricultural areas This diet is unusual for moose previous studies of

Swedish moose diet have found the GS diet was dominated by birch willow and herbaceous plants and the

WS diet dominated by pine and birch (Cederlund and Nystrom 1981) The diet analysis was conducted during

the WS instead of being dominant pine composed just 2 Birch did not appear however unidentified wood

composed only 9 whereas agricultural produce accounted for 69 Supplementary feed may be perceived

by the moose in the centre and south as a vital forage source during the WS In fact in the centre the

agricultural land is the only preferred habitat at the UD50 It is unknown whether there are salt licks provided

in these areas Selection for a critical habitat is often thought to be a fixed factor The Oumlland population from

21 the three areas are close in proximity however they displayed contrasting preferences This is supported by the

Osko et al (2004) report that found two neighbouring moose populations that had access to the same habitats

displayed contrasting preferences Habitat preferences for populations of the same species are not necessarily

fixed They alter with varying levels of habitat abundance and limiting factors skewing what is preserved to

be critical

The main limitation encountered in this study was with the limited sample There was only data on two

individuals from the north of the island which led it being removed from many of the analysis Similarly due

to a lack of relocations from the collars being turned off at points throughout the year two further individuals

had to be removed from a majority of the analysis This reduced the sample size to 17 or 18 individuals

Similarly only 13 of the individuals from the study produced calves This unfortunately prevented including

survival into models Although the sample size was small it was accurate it was of high resolution over

300000 GPS points In future it would be beneficial to have a more standardised data set An equal sample of

individuals from the three areas would be advised along with ensuring the GPS collars are kept turned on for

the entirety of the growing and winter season to allow comparisons between years It would also be

advantageous to collect coordinates of the feeding sites along with the composition This could then be

compared with high use UD coordinates to look if moose are truly spending a majority of their foraging time

at feeding stations A study on the population densities of moose and the increasing population of roe deer

(Capreolus capreolus) would add the factor of competition into the model

The low calf survival on Ӧland is most likely the result of a combination of factors The lack of suitable habitat

reported in this study in conjunction with Malmstenrsquos (2014a) report on the threat of disease (Anaplasma

phagocytophilum) are probable influences on the calf survival on Ӧland On Ӧland there is an increasing

population of roe deer and large numbers of migratory birds both carriers of ticks and diseases The mild

conditions on Ӧland are advantageous for ticks the carriers of A phagocytophilum Fewer snow days and

shorter periods of snow cover along with dry conditions are favourable for ticks This could probably be one

of the reasons for females to be of lower quality and therefore not being able to ensure calf survival Moose

have to utilise areas where in other populations individuals tend to avoid Finally similar to many studies I

advocate further research using a stronger dataset and longer term monitoring

22

Acknowledgements

I am indebted to NJ Singh and A Allen for all their help and guidance through the whole of this study I

thank SLU for the support provided during this study in terms of data finances and facilities Thank you to

everyone at the Department of Wildlife Fish and Environmental Studies for being so friendly and

supportive I would like to thank L Edenius for driving me around the study area and S Michon and H

Khalil for keeping me sane with fika and training

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Bradshaw RHW Hannon GE Lister AM (2003) A long-term perspective on ungulate-vegetation

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Ericsson G Wallin K Ball JP Broberg M (2001) Age-related reproductive effort and senescence in free-

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Ericsson G Malmsten J Neumann W Singh NJ Dali AM Submitted Summer Calf Survival of

Scandinavian Moose along its Southern Distribution Range

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Gaillard JM Festa-Bianchet M Yoccoz NG Loison A Toiumlgo C (2000a) Temporal variation in fitness

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Hagner O Nilsson M Reese H Egberth M Olsson H (2005) Procedure for classification of forests for

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northeastern Minnesota The Journal of Wildlife Management 74(5)1013-1023

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Linnell JDC Aanes R Andersen R (1995) Who killed Bambi The role of predation in the neonatal

mortality of temperate ungulates Wildlife Biology 1209-223

Lomas LA Bender LC (2007) Survival and cause-specific mortality of neonatal mule deer fawns north-

central New Mexico Journal of Wildlife Management 71884ndash894

Lynch GM Morgantini LE (1984) Sex and age differential in seasonal home range size of moose in

northcentral Alberta 1971-1979 Alces 2061-78

MacCracken JG Ballenberghe VV Peek JM (1993) Use of aquatic plants by moose sodium hunger or

foraging efficiency Canadian Journal of Zoology 71(12)2345-2351

27

Malmsten J Wideacuten DG Rydevik G Yon L Hutchings MR Thulin CG Soumlderquist L Aspan A Stuen S

Dalin AM (2013) Temporal and spatial variation in Anaplasma phagocytophilum infection in

Swedish moose (Alces alces) Epidemiology and Infection 1421205-1213

Malmsten J (2014a) lsquoReproduction and health of moose in southern Swedenrsquo Doctoral thesis Swedish

University of Agricultural Sciences (SLU) Umearing

Malmsten J Soumlderquist L Thulin C Wideacuten DG Yon L Hutchings MR Dalin A (2014b) Reproductive

characteristics in female Swedish moose (Alces alces) with emphasis on puberty timing of

oestrus and mating Acta Veterinaria Scandinavica 5623

Marsh DM Hanlon TJ (2004) Observer gender and observation bias in animal behaviour research

experimental tests with red-backed salamanders Animal Behaviour 681425-1433

Maringrell A Hofgaard A Danell K (2006) Nutrient dynamics of reindeer forage species along snowmelt

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McLoughlin PD Vander Wal E Lowe SJ Patterson BR Murray DL (2011) Seasonal shifts in habitat

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12(8) 654-663

Milner JM Nilsen EB and Andreassen HP (2007) Demographic side effects of selective hunting in ungulates

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Monfort SL Schwartz CC Wasser SK (1993) Monitoring reproduction in captive moose using urinary and

faecal steroid metabolites The Journal of Wildlife Management 57400-407

Monteith KL Klaver R Hersey K Holland A Thomas T Kauffman M In press Effects of climate and

plant phenology on recruitment of moose at the southern extent of their range

Morales JM Moorcroft PR Matthiopoulos J Frair JL Kie JG Powell RA Merrill EH Haydon DT (2010)

Building the bridge between animal movement and population dynamics Philosophical

Transactions of the Royal Society B 3652289-230

Morellet N Bonenfant C Boumlrger L Ossi F Cagnacci F Heurich M Kjellander P Linnell JDC Nicoloso S

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28

Prentice HC Jonsson BO Sykes MT Ihse M Kindstroumlm M (2007) Fragmented grasslands on the Baltic

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Computing Vienna Austria URL httpwwwR-projectorg

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University Press

29

Tveito OE Foslashrland EJ Alexandersson H Drebs A Jonsson T Vaarby-Laursen E (2001) Nordic climate

maps Norway CICERO

Udina IG Danilkin AA Boeskorov GG (2002) Genetic diversity of moose (Alces ales L) in Eurasia

Russian Journal of Genetics 38951-957

van Beest FM van Moorter B Milner JM (2012) Temperature-mediated habitat use and selection by a heat

sensitive northern ungulate Animal Behaviour 84(3)723-735

van Winkle W (1975) Comparision of several probabilistic home-range models Journal of Wildlife

Management 39118-123

Verme LJ Ullrey DE (1984) Physiology and nutrition White-tailed deer ecology and management (Ed By

Halls LK) pp 91-118 Stackpole Harrisburg Pennsylvania

Wattles DW DeStefano (2013) Space use and movements of moose in Massachusetts Implications for

conservation of large mammals in a fragmented environment Alces 4965-81

White RG Rowell JE Hauer WE (1997) The role of nutrition body condition and lactation on calving

success in muskoxen Journal of Zoology 24313-20

30

Appendix A

Introduction

Fig 1 Summary chart of factors affecting the life history and therefore the long term fitness of a population

Fig 2 Summary chart 2

Movement

Habitat

Climate

Topography

Competition

FoodWater

Disease

Die

Survive

Reproduce

Population long term fitness

31 Appendix B

Method and Materials

Fig 1 Summary of processes

32

Fig 2 Examples of classical kernel home range output and Brownian bridge kernel home range (Calenge 2011) The

right image includes the area between relocations ie the movement path in contrast to the classic kernel home range

in the left image

33 Appendix C

Home ranges

Fig 1 Example of a non-migratory (ID006) individuals BRB kernel area From top left annual growing and winter

season UD50 (black contour) and UD95 (red contour)

Fig 2 Example of a migratory (ID012) individuals BRB kernel area From the left annual growing and winter season

UD50 (black contour) and UD95 (red contour)

34

Table 1 Annual and seasonal UD50 and UD95 areas (ha) for all individuals

ID Annual GS WS

UD50 UD95 UD50 UD95 UD50 UD95

ID004 190 924 93 531 173 941

ID005 230 1364 132 945 72 682

ID006 162 1036 89 736 70 611

ID008 277 1536 156 809 78 738

ID009 137 834 48 295 126 653

ID010 114 682 83 448 96 488

ID012 177 963 123 544 76 545

ID014 160 1018 87 575 89 662

ID015 172 858 128 532 109 679

ID016 156 1047 65 455 92 534

ID017 153 1088 149 1043 69 349

ID019 279 1097 176 911 163 824

ID020 139 1084 67 349 160 794

ID022 159 811 131 638 61 454

ID023 187 1061 147 771 72 705

ID024 146 725 165 705 101 458

ID026 142 605 99 442 125 547

ID027 126 567 75 461 48 277

35 Appendix D

Activity

Fig 1 Mean daily movement during the study period GS 23-April-2012 to 07-Nov-2012 WS 08-Nov-2012 to

22-April-2013 (number indicates month)

Fig 2 Mean daily movement in the centre and south during the GS and WS

36

Appendix E

Habitat Proportions

Fig 1 All individualsrsquo seasonal habitat proportions within the UD95

37 Habitat Selection

Table 1 Simplified ranking matrices comparing proportional habitat use within the second order (UD95Area) with

proportions of total available habitat types Mean value on the matrix was replaced by a sign a triple sign represents

significant deviation from random at P lt05 Highlighted habitat is ranked 1st

North A

gri

cult

ure

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 --- --- - +++ --- --- --- +++ +++ --- 8

Broad Leaf +++ 0 +++ + +++ +++ +++ + +++ +++ +++ 1

Clear Fell +++ --- 0 + +++ - - --- +++ +++ --- 7

Coniferous + - - 0 +++ - - --- +++ +++ - 6

Freshwater --- --- --- --- 0 --- --- --- +++ - --- 10

Grassland

Moors +++ --- + + +++ 0 +++ - +++ +++ + 3

MiresMarshes +++ --- + + +++ --- 0 - +++ +++ --- 5

Mixed +++ - +++ +++ +++ + + 0 +++ +++ + 2

Sparse Veg --- --- --- --- --- --- --- --- 0 --- --- 11

Urban --- --- --- --- + --- --- --- +++ 0 --- 9

Younger +++ --- +++ + +++ - +++ - +++ +++ 0 4

Rank Order and

Significance

Broad Leafgt Mixedgt GrasslandMoorsgt Youngergtgtgt MiresMarshesgt Coniferousgt

Clear Fellgtgtgt Agriculturegtgtgt Urbangt Freshwatergtgtgt Sparse Veg

Central

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 --- --- --- + +++ + --- +++ +++ --- 6

Broad Leaf +++ 0 +++ + +++ +++ + - +++ +++ - 3

Clear Fell +++ --- 0 - +++ +++ + --- +++ +++ --- 5

Coniferous +++ - + 0 +++ +++ + --- +++ +++ - 4

Freshwater - --- --- --- 0 +++ - --- +++ +++ --- 8

Grassland

Moors --- --- --- --- --- 0 --- --- +++ - --- 10

MiresMarshes - - - - + +++ 0 - +++ +++ - 7

Mixed +++ + +++ +++ +++ +++ + 0 +++ +++ + 1

Sparse Veg --- --- --- --- --- --- --- --- 0 - --- 11

Urban --- --- --- --- --- + --- --- + 0 --- 9

Younger +++ + +++ + +++ +++ + - +++ +++ 0 2

Rank Order and

Significance

Mixedgt Youngergt Broad Leafgt Coniferousgt Clear Fellgtgtgt Agriculturegt

MiresMarshesgt Freshwatergtgtgt Urbangt GrasslandMoorsgtgtgt Sparse Veg

38

South

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 + - - + - + +++ +++ +++ - 5

Broad Leaf - 0 - - + - - +++ + +++ - 7

Clear Fell + + 0 - + + + +++ + +++ + 2

Coniferous + + + 0 +++ + + +++ + +++ + 1

Freshwater - - - --- 0 - - + + +++ - 8

Grassland

Moors + + - - + 0 + + +++ + - 4

MiresMarshes - + - - + - 0 +++ + +++ - 6

Mixed --- --- --- --- - - --- 0 + + --- 10

Sparse Veg --- - - - - --- - - 0 + - 9

Urban --- --- --- --- --- - --- - - 0 --- 11

Younger + + - - + + + +++ + +++ 0 3

Rank Order

and

Significance

Coniferousgt Clear Fellgt Youngergt GrasslandMoorsgt Agriculturegt MiresMarshesgt Broad Leafgt

Freshwatergt Sparse Veggt Mixedgt Urban

Table 2 Simplified ranking matrices comparing proportional habitat use within the third order (UD50UD95) with

proportions of total available habitat types Mean value on the matrix was replaced by a sign a triple sign represents

significant deviation from random at P lt05 Highlighted habitat is ranked 1st

North

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 --- --- --- - + --- --- + +++ --- 8

Broad Leaf +++ 0 +++ + + + + + +++ +++ + 1

Clear Fell +++ --- 0 + + + - - + +++ - 5

Coniferous +++ - - 0 + + --- --- +++ +++ - 6

Freshwater + - - - 0 +++ - - +++ +++ - 7

GrasslandMoors - - - - --- 0 - - - + - 10

MiresMarshes +++ - + +++ + + 0 - +++ +++ + 3

Mixed +++ - + +++ + + + 0 +++ +++ + 2

Sparse Veg - --- - --- --- + --- --- 0 +++ --- 9

Urban --- --- --- --- --- - --- --- --- 0 --- 11

Younger +++ - + + + + - - +++ +++ 0 4

Rank Order and

Significance

Broad Leafgt Mixedgt MiresMarshesgt Youngergt Clear Fellgt Coniferousgt Freshwatergt

Agriculturegt Sparse Veggt GrasslandMoorsgt Urban

39

Central

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 --- --- + + - - - + +++ --- 7

Broad Leaf +++ 0 + +++ + + + + + +++ - 2

Clear Fell +++ - 0 +++ + + + + + +++ - 3

Coniferous - --- --- 0 + - - --- +++ + --- 8

Freshwater - - - - 0 --- - - --- - - 11

GrasslandMoors + - - + +++ 0 + - + +++ - 5

MiresMarshes + - - + + - 0 + + +++ - 6

Mixed + - - +++ + + - 0 +++ +++ - 4

Sparse Veg - - - --- +++ - - --- 0 +++ - 9

Urban --- --- --- - + --- --- --- --- 0 --- 10

Younger +++ + + +++ + + + + + +++ 0 1

Rank Order and

Significance

Youngergt Broad Leafgt Clear Fellgt Mixedgt GrasslandMoorsgt MiresMarshesgt

Agriculturegt Coniferousgtgtgt Sparse Veggtgtgt Urbangt Freshwater

South

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 - - - - - + - +++ + --- 8

Broad Leaf + 0 - --- + - + - +++ + - 6

Clear Fell + + 0 - + - + - +++ + - 4

Coniferous + +++ + 0 + + +++ + +++ + + 1

Freshwater + - - - 0 - - + + + - 7

GrasslandMoors + + + - + 0 + + + + - 3

MiresMarshes - - - --- + - 0 - + + - 9

Mixed + + + - - - + 0 + + - 5

Sparse Veg --- --- --- --- - - - - 0 + --- 10

Urban - - - - - - - - - 0 - 11

Younger +++ + + - + + + + +++ + 0 2

Rank Order and

Significance

Coniferousgt Youngergt GrasslandMoorsgt Clear Fellgt Mixedgt Broad Leafgt Freshwatergt

Agriculturegt MiresMarshesgt Sparse Veggt Urban

40

Table 3 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the GS according to Jacobs index

Ran

k North Centre South

50 95 50 95 50 95

+ - + - + - + - + - + -

1 Broad

Leaf Urban Broad Leaf Sparse Veg

Broad

Leaf Urban Mixed Urban Coniferous Urban

Grassland

Moors Urban

2 Mixed Sparse Veg Mixed Freshwater Younger Agriculture Younger Sparse Veg Younger Sparse Veg Clear Fell Mixed

3 Mires

Agriculture Grassland

Urban Clear

Fell Coniferous Broad Leaf

Grassland

Moors

Clear Fell Agriculture Coniferous Sparse Veg

Marshes Moors

4 Younger Grassland

Younger Agriculture

Freshwater Coniferous Freshwater

Broad Leaf Mires

Younger Freshwater

Moors Marshes

5 Clear

Fell Freshwater

Mires Coniferous

Sparse Veg Clear Fell Agriculture

Freshwater Agriculture

Marshes

6 Coniferous Clear Fell

Mires

Marshes

Mires

Grassland

Moors

Mires

Marshes Marshes

7 Mixed Mixed Broad Leaf

8 Grassland

Moors

41

Table 4 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the WS according to Jacobs index

Ran

k North Centre South

50 95 50 95 50 95

+ - + - + - + - + - + -

1 Mires

Marshes

Grassland

Moors Mixed Freshwater Agriculture Urban Mixed Freshwater

Grassland

Moors Urban GrasslandMoors Urban

2 Freshwater Mixed Coniferous Urban Mires

Marshes Coniferous Sparse Veg Agriculture

Sparse

Veg Coniferous Freshwater

3 Urban Coniferous Younger Grassland

Moors Freshwater Younger Urban Freshwater

Broad

Leaf Agriculture Mixed

4 Younger Agriculture Sparse Veg Broad

Leaf

Broad

Leaf

Grassland

Moors Mixed Broad Leaf

5 Clear Fell Agriculture Coniferous Agriculture Mires

Marshes Clear Fell

6 Sparse

Veg

Mires

Marshes Mixed

Mires

Marshes

Clear

Fell

Mires

Marshes

7 Broad

Leaf Clear Fell Younger Clear Fell Younger Sparse Veg

8 Clear Fell Younger

9 Sparse

Veg

10 Grassland

Moors

42

Table 5 Second order (UD95Area) individual selectionavoidance for the GS and WS according to the Jacobs index

ID GS WS

Select Avoid Select Avoid

ID004 Younger Sparsely Vegetated MiresMarshes Sparsely Vegetated

ID005 MiresMarshes Sparsely Vegetated Coniferous GrasslandMoors

ID006 Coniferous Sparsely Vegetated Mixed Freshwater

ID008 Mixed Sparsely Vegetated Mixed Freshwater

ID009 Mixed Sparsely Vegetated Mixed GrasslandMoors

ID010 MiresMarshes Freshwater GrasslandMoors Freshwater

ID012 Broad Leaf Sparsely Vegetated Coniferous Urban

ID014 Clear Fell Sparsely Vegetated GrasslandMoors Sparsely Vegetated

ID015 GrasslandMoors Urban GrasslandMoors Freshwater

ID016 GrasslandMoors Freshwater GrasslandMoors Freshwater

ID017 GrasslandMoors Mixed Sparsely Vegetated Mixed

ID019 Mixed Sparsely Vegetated Mixed Urban

ID020 Broad Leaf Sparsely Vegetated Coniferous GrasslandMoors

ID022 MiresMarshes Freshwater MiresMarshes Freshwater

ID023 MiresMarshes GrasslandMoors Mixed Freshwater

ID024 Broadleaf Urban Broad Leaf Urban

ID026 GrasslandMoors Freshwater GrasslandMoors Freshwater

ID027 GrasslandMoors Urban Sparsely Vegetated Freshwater

43 Table 6 Third order (UD50UD95) individual selectionavoidance for the GS and WS according to the Jacobs index

ID GS WS

Select Avoid Select Avoid

ID004 Broad Leaf Mixed GrasslandMoors Freshwater

ID005 Broad Leaf Freshwater Agriculture Freshwater

ID006 Clear Fell Freshwater Agriculture MiresMarshes

ID008 MiresMarshes Freshwater Agriculture Urban

ID009 Freshwater Agriculture Agriculture Freshwater

ID010 Mixed Urban Sparsely Vegetated Urban

ID012 Coniferous GrasslandMoors Freshwater Urban

ID014 Urban Agriculture Freshwater Urban

ID015 Mixed Forest Urban Clear Fell Urban

ID016 Freshwater Urban GrasslandMoors Mixed

ID017 Coniferous Mixed Coniferous Broad Leaf

ID019 Broad Leaf GrasslandMoors Urban GrasslandMoors

ID020 Freshwater Urban Freshwater Agriculture

ID022 MiresMarshes Urban Broad Leaf GrasslandMoors

ID023 Freshwater Mixed Agriculture Freshwater

ID024 Mixed Freshwater Mixed Freshwater

ID026 Mixed MiresMarshes Sparsely Vegetated GrasslandMoors

ID027 Freshwater MiresMarshes GrasslandMoors Broad Leaf

44

Fig 2 North third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)

45

Fig 3 Centre third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)

46

Fig 4 South third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)

47

Fig 5 North second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)

48

Fig 6 Centre second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)

49

Fig 7 South second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)

50

Appendix F

Background

Fig 1 Daily mean snow depth and duration during the study period (Andrew Allen)

Female Moose Reproduction

Moose are seasonal polyoestral mammals (Monfort et al 1993) coming into oestrus during late September

early October (Garel et al 2009) The Swedish moose cow population reaches puberty between the ages 25

and 35 (Sand and Cederlund 1993) during which the reproductive period begins with the onset of ovulation

The age an individual reaches puberty is dependent on their body condition they have to reach a weight

threshold to reach puberty and become reproductive (Sand 1996) If she is over the weight threshold she will

go into oestrus in the autumn If she does not reach the weight threshold then she will go into oestrus the

following autumn if successful she will give birth to individual or twin calves in late May to early June

(Ericsson et al 2001) and therefore reach sexual maturity (Malmsten et al 2014b) Fecundity is related to

both the condition and the age of the cow Cows go through senescence at 12 years of age (Ericsson et al

2001) Providing calves with the required level of nutrition demands high energy and protein resources from

the mother during senescence this becomes harder to achieve leading to decreased levels of parental care

and higher levels of calf mortality

Page 8: Habitat-performance relationships on an island: fitness ...navinderjsingh.weebly.com/uploads/1/1/2/2/11224342/... · Conditions on Öland are milder than those found in other areas

8

Capture and Handling

A random sample of adult moose (n = 25) were darted sedated and equipped with GPSGSM neck collars

(Vectronic Aerospace GmbH Berlin Germany) during the winter of 2012 by the Moose Research Group

SLU Movement data were collected from GPS collars dating from 22022012 ndash 24042014 Collars were

fixed to return GPS locations approximately every 30 minutes

Data Screening

The sample contained both males and females (six males 19 females x female age = 95 years range 4-17

years) An initial inspection revealed that one female individual only returned fixed locations for a period of

eight months Locations ceased during the hunting period so the individual was presumed shot and was

removed from the data along with the males

The exact time between each location varied and sometimes no fix could be made The adehabitatLT package

(Calenge 2006) was used to standardise the data and overcome the location fixing errors The function setNA

was used to place NAs where relocations were missing The function sett0 was used to round the timing of

collection obtaining a regular trajectory with 30 minute intervals The final dataset used in the analysis

consisted of 302710 regular GPS data points from a sample size of n=18 individuals two individuals from the

north ten individuals from the centre and six individuals from the south

To address the question and to investigate the influence of climate on the space use patterns of moose the

analysis was performed at two scales The first included all annual movements of moose and the second at a

seasonal scale ie summer and winter The seasonal scales were defined according to the growing season (GS)

and winter season (WS) In Scandinavia the current method used to define the start of season (SOS) is the

period when the daily mean air temperature is above 5degC (GS) Methods of calculating SOS are advancing

with the use of the Normalized Difference vegetation Index (NDVI) becoming more popular The start and

end of the GS and WS were derived using the mean start and end dates for Oumlland suggested by the Norwegian

Meteorological Institute (DNMI) Nordic climate map report (Tveito et al 2001) The GS of this study is

defined as the period between 23-April-2012 to 07-Nov-2012 and the WS is defined as the period between 08-

Nov-2012 to 22-April-2013 (based on the current standard normal period 1961-90)

Home rangeUtilization distribution

Variation in ungulate home range size is known to be caused by changes in energy requirements and variation

in food availability (Tufto et al 1996 Kie et al 2010 Moreller et al 2013) With shifting climate causes shifts

in plant phenology and therefore the spatial and temporal distribution of ungulate food (Maringrell et al 2006)

Individuals alter their home ranges to meet their energy requirements to maintain their fitness (Albon et al

1987 White 1997 Festa-Bianchet et al 1998 Forchhammer et al 2001)

The most commonly cited definition of a home range is ldquothat area traversed by the animal during its normal

activities of food gathering mating and caring for youngrdquo (Burt 1943) This has now been expanded to

9 incorporate measures of space use using the utilization distribution (UD van Winkle 1975) which can be

described as the ldquorelative frequency distribution of an animalrsquos occurrence in all four dimensions of space

and timerdquo (Keating and Cherry 2009) Home range is viewed as a constant 2D polygon whereas UDs are

viewed as multiple 3D polygons that take into account the distribution as well as the intensity of animalrsquos

movements and space use within their home range (Kranstauber et al 2012) (see appendix A)

Estimations of each individualrsquos annual and seasonal UDs were found using the Biased Random Bridge (BRB)

kernel approach (Benhamou 2011) from the adehabitatHR package (Calenge 2006) in R It was chosen as it is

considered an improvement on the previously preferred Brownian bridge (BB) method (Horne et al 2007) The

BB is purely a diffusive movement process whereas the BRB is an advective-diffusive movement process BB

does not take into account changes in advection direction (drift) or strength BB assumes an animalrsquos

movement is purely random it moves from a starting point and ends up at the end location randomly By

adding the advection component the BRB takes into account that the animalrsquos movement is biased towards a

certain direction This allows for a more biologically relevant analysis (Benhamou and Corneacutelis 2010)

A grid was created using the minmax XY coordinates of all individuals (plusmn 10 km to increase the extent and

prevent the grid directly touching the XY locations) The resolution of the grid was fixed at a 25 m x 25 m

scale to match the resolution of the relevant habitat maps (Hagner et al 2005) By specifying these criteria the

resolution of the data remains consistent between individuals The diffusion coefficient determines the variance

in the location of the kernels between two locations This was calculated from each individualrsquos dataset using

the BRBD function and added to the BRB model (see Benhamou 2011) The strength and direction of BRB

advection can change between bridges whilst having to remaining constant To remain constant an upper Tmax

and lower Lmin time thresholds were set Successive relocations that exceeded Tmax or under Lmin were

removed from the UD calculations The 50 (UD50) and 95 (UD95) isopleths were then calculated from

the UD using the kernelarea function

Habitat

The scale of analysis was further divided following Johnson (1980) Habitat selection within the landscape

(second order selection) was studied by comparing the UD95 with available habitats in each of the three study

areas of Oumlland (UD95Area) Habitat selection within the home range (third order selection) was studied by

comparing the UD50 with the UD95 (UD50UD95)

12 habitat classes were used in the analysis agricultural land broad leaved forests clear felled areas coastal

coniferous forests freshwater areas moorsgrassland miresmarshes mixed forest sparsely vegetated areas

urban areas and younger forests The proportion of area covered by each of these habitat classes was

determined in the UD50 and UD95 Habitat data was obtained from satellite imagery generated by Svenska

Marktaumlckedata (Hagner et al 2005) The habitat maps were last updated in 2002 and have a resolution of 25

m

Compositional analysis ( habitat used habitat available) (Aebischer 1993) was used in conjunction with

the Jacobrsquos index (D) (eqn1) to quantify habitat selection (Jacobs 1974) Coastal areas were removed as not

10

all home ranges contained them This combined approach allowed identification of habitats that are used

disproportionally to their availability ie in a non-random manner (Beyer et al 2010) This is an indication of

which habitats are important for an individual

119863 = ( 119903minus119901

119903+119901minus2119903119901 ) (eqn1)

r = Proportion of habitat type used

p = Total proportion of habitat available

D = Jacobs index varies from -1 (strong avoidance) to +1 (strong preference) with values close to 0 indicating

the habitat is used in proportion to its availability

Activity

Activity level is measured as the mean daily movement (MDM) by the individual to investigate if individuals

in an areaseason moved more and hence were more active than those in other areasseasons Unfortunately

only two cows were collared in the north and were therefore left out of this analysis Moose were identified as

migratory using a modelling approach (see Bunnefeld et al 2011 for methods) Migratory individuals were

initially removed from the activity analysis (n=4)The reason is that both migratory journeys were completed

during the winter season thus increasing the mean daily distance travelled and potentially biasing the analysis

One individual was also removed due it its collar not returning relocations during the entirety of the WS

Diet analysis

The Ӧland project team conducted histology diet analysis on the rumen content of five individuals that were

shot in the centre and south of the island during the WS of 2013

Survival analysis

The Ӧland project team measured calf survival using the mark-resight method The presenceabsence of a calf

was recorded by tracking the cows at six occasions throughout the year These were at the start of the calving

season (mid-May to early June) twice through the summer before the hunt after the hunt and after winter

Survival trend was estimated using a Kaplan-Meier curve (Kaplan and Meier 1958) The Kaplan-Meier curve

shows the survival function (S (t)) ie the probability of an individual surviving until at least time t (Bewick

et al 2004) The probability of surviving from one period to the next is multiplied together to give the survival

function The S(t) of this study is the probability of an individual surviving from birth to after the hunt

(Method summary see appendix B)

11 Results

Home RangeUtilization Distribution

A total of 51 home ranges were estimated (17 annual 17 within growing season 17 within winter season)

Annual x = 9613 ha GS x = 6345 ha and WS x = 6023 ha (appendix C)

At the UD50 scale the largest annual and seasonal mean home ranges were located in the north Mean annual

and seasonal home ranges in the centre were slightly larger than the south This difference was not significant

(F(113)= 22 p= 87) (ANOVA) There was no significant difference between the seasonal home ranges (x

plusmnSD for GS = 116 plusmn38 for WS = 98 plusmn32 ha) (t(11) = 105 p = 32) or the seasonal home ranges in the centre

(t(8) = 101 p = 34 and the south (t(5) = 87 p = 42) (paired-sample t-test) (Table 1)

At the UD95 scale the largest annual and WS mean home ranges were located in the north The largest GS

mean home ranges were located in the centre Mean annual and seasonal home ranges in the centre were

slightly larger than the south This difference was not significant (F(113) = 59 p = 63) (ANOVA) There

was no significant difference between the seasonal home ranges (x plusmnSD for GS = 635 plusmn225 for WS = 602

plusmn161) (t(11) = 373 p = 71) or the seasonal home ranges in the centre (t(8)= 20 p = 84) or south (t(5) = 34

p = 74) (paired-sample t-test) (Table 1)

Table 1 Seasonal and annual mean UD50 and UD95 BRB kernel area in hectares (1ha = 001km2) for the north centre

and south of Oumlland (smoothing factor (h) =100)

Are

a

Annual UD50 GS UD50 WS UD50

n Mean SD Range n Mean SD Range n Mean SD Range

N 2 209 49 139-279 2 1215 39 67-176 2 1615 106 160-163

C 9 178 56 114-277 9 116 44 48-165 9 943 4 61-173

S 6 160 21 142-177 6 1085 51 65-149 6 933 35 69-125

Annual UD95 GS UD95 WS UD95

N 2 10905 5 1084-1097 2 630 199 349-911 2 809 11 794-824

C 9 997 32 682-1536 9 6531 22 295-945 9 637 17 454-941

S 6 9298 30 605-1088 6 5985 373 442-575 6 5526 20 349-679

12

Activity

MDM rates in the three areas (sedentary individuals) during the GS ranged from 14 ndash31 km day During the

WS ranged they ranged from 11-24 km day (Table 2) Movement rates during the GS were higher than the

WS (x plusmnSD for GS = 202 plusmn043 for WS = 161 plusmn043) but it was not statistically significant (t(11) = 200 p=

07) (paired sample t-test)

Table 2 Seasonal mean daily movement rates (km day) for each area and for both areas (total)

Are

a

GS WS

n Mean SE Range n Mean SE Range

C 8 20 003 14-18 8 20 004 12-24

S 4 22 016 17-31 4 12 02 11-13

Total 12 202 003 14-31 12 16 003 11-24

The seasonal MDM rates of all individuals (migratory and sedentary) were not significantly different (x plusmnSD

for GS = 20 plusmn04 for WS = 18 plusmn061) (t(14) = 139 p= 19) (paired sample t-test)

The WS home range size affects the WS MDM (F(110) = 927 p = 01) (ANOVA) The GS home range size

does not affect the GS MDM (F(110) = 36 p = 56) (ANOVA) When the WS home range outlier was

removed the home range size did not affect the WS MDM (F(111) = 186 p= 19) (ANOVA) The MDM was

lowest in February and highest in April (Table 3) there appeared to be no significant pattern in MDM between

the months (appendix D)

Table 3 Mean daily distance moved (km day) for sedentary individuals

Month Season Distance

April GS 0051

May GS 0044

June GS 0039

July GS 0041

August GS 0042

September GS 0044

October GS 0043

November WS 0043

December WS 0038

January WS 0035

February WS 0028

13 Habitat ndash Proportions

The largest proportion of habitat on the island is agriculture the lowest proportion of habitat (excluding coastal

and freshwater) is urban areas (Fig 2) The largest proportion of habitat in the north was coniferous forests

whilst agricultural areas were the dominant habitat types in the centre and south (Fig 3) The lowest proportion

(excluding coastal and freshwater areas) was urban

Fig 2 Proportion of different types of habitats found on Ӧland

Fig 3 Mean proportion of habitats contained within UD95 in the three areas of Oumlland C = Centre N = North S =

South

14

Habitat - Selection

Generally forest habitat types are the highest ranked whilst sparsely vegetated and urban areas are the lowest

ranked Both the second and third order habitat selection analyses gave significant results in the compositional

analysis (Table 4) In the third order analysis (UD50UD95) the centre displayed significant differences

between habitat types The coniferous forests are significantly preferred to sparsely vegetated areas and the

sparsely vegetated areas are significantly preferred to urban areas In the second order analysis (UD95Area)

significance was observed in the north and centre In the north younger forests are significantly preferred to

miresmarshes clear felled areas are significantly preferred to agriculture and freshwater areas are significantly

preferred to sparsely vegetated areas In the centre clear felled areas are significantly preferred to agricultural

land freshwater areas are significantly preferred to urban areas and grasslandmoors are significantly preferred

to sparsely vegetated areas

Table 4 Summary of second (UD95Area bottom) and third order (UD50UD95 top) ranked habitat preferences between

the three areas according to the compositional analysis (see appendix B)

Rank North Centre South

1 Broad Leaf Younger Coniferous

2 Mixed Broad Leaf Younger

3 MiresMarshes Clear Fell GrasslandMoors

4 Younger Mixed Clear Fell

5 Clear Fell GrasslandMoors Mixed

6 Coniferous MiresMarshes Broad Leaf

7 Freshwater Agriculture Freshwater

8 Agriculture Coniferous Agriculture

9 Sparse Veg Sparse Veg MiresMarshes

10 GrasslandMoors Urban Sparse Veg

11 Urban Freshwater Urban

Rank North Centre South

1 Broad Leaf Mixed Coniferous

2 Mixed Younger Clear Fell

3 GrasslandMoors Broad Leaf Younger

4 Younger Coniferous GrasslandMoors

5 MiresMarshes Clear Fell Agriculture

6 Coniferous Agriculture MiresMarshes

7 Clear Fell MiresMarshes Broad Leaf

8 Agriculture Freshwater Freshwater

9 Urban Urban Sparse Veg

10 Freshwater GrasslandMoors Mixed

11 Sparse Veg Sparse Veg Urban

Indicates significantly preferred to the habitat below (significant deviation from random at P lt05)

15 The Jacobs index revealed that generally the habitats preferred during the GS within the home range (third

order) are younger (0187) and broad leaf forests (0154) The strongest avoidance was for urban areas (-0627)

During the WS only agricultural areas are preferred (0129) and the strongest avoidance was for urban areas (-

0393) (Fig 4)

Fig 4 Third order seasonal habitat preference (UD50UD95) all individuals The index ranges from -1 (total avoidance)

to 1 (strongest preference) Close to 0 indicates used in proportion to its availability

Third order habitat preferencesavoidances by area

North During the GS the strongest preference was for broad leaf (0218) and mixed forests (0161) The

strongest avoidance was for urban (-1) and sparsely vegetated areas (-05) During the WS the strongest

preference was for miresmarshes (0228) The strongest avoidance was for grasslandmoors (-05)

Centre During the GS the strongest preference was for broad leaf (0233) and younger forests (0223) The

strongest avoidance was for urban (-0527) and agricultural land (-0362) During the WS preference was only

shown for agricultural land (0327) The strongest avoidance was for urban areas (-0679) and miresmarshes

(-0638)

South During the GS the strongest preference was for coniferous (0312) and younger forests (0242) The

strongest avoidance was for urban (-0353) and sparsely vegetated areas (-0330) During the WS

grasslandmoors (0106) were the strongest preference The strongest avoidance was for urban (-0666) and

sparsely vegetated areas (-0351)

16

The Jacobs indices revealed that generally the habitats preferred during the GS within the landscape

(UD95Area) are broad leaf (0216) and younger forests (0201) The strongest avoidance was for urban (-

0717) and freshwater areas (-0694) The strongest preference during the WS are coniferous forests (0242)

and the strongest avoidance was for freshwater (-0674) and urban areas (-0648) (Fig 5)

Fig 5 Second order seasonal habitat preference (UD50UD95) all individuals The index ranges from -1 (total avoidance)

to 1 (strongest preference) Close to 0 indicates used in proportion to its availability

Second order habitat preferencesavoidances by area

North During the GS the strongest preference was for broad leaf (0363) and mixed forests (00291) The

strongest avoidance was for sparsely vegetated (-0909) and freshwater areas (-0780) During the WS mixed

(0335) and coniferous forests (0316) were the strongest preference The strongest avoidance was for

freshwater (-0731) and urban areas (-05333)

Centre During the GS the strongest preference for mixed (0394) and younger forests (0286) The strongest

avoidance was for urban (-0733) and sparsely vegetated (-0708) areas During the WS mixed (0404) and

coniferous forests (0255) were the strongest preference The strongest avoidance was for freshwater (-0704)

and sparsely vegetated areas (-0655)

South During the GS the strongest preference for grasslandmoors (0287) and clear fells (0165) The

strongest avoidance was for urban areas (-0678) and mixed forests (-0491) During the WS grasslandmoors

(0425) and coniferous forests (0154) were the strongest preference The strongest avoidance was for urban (-

0876) and freshwater areas (-0587) (appendix E)

17 Diet

Diet analysis of the rumen content sampled from five individuals (C=2 S=3) revealed that almost two thirds

(69) of the diet is comprised of agricultural produce (apple winter rape and sugar beet) (Fig 6)

Fig 6 Diet analysis from the rumen samples of five moose individuals that were culled in 2013

31

2117

9

8

5

22

1 1

1

1

1 00 0

0

0Diet (2610-911 2013 5 individuals)

AppleWinter RapeSugar BeetUndefined WoodSallowBroad-leaf GrassPineAshOakCloverCurrantsUndefined plantElderberryJuniperRaspberry

18

Calf Survival

Of the 18 individuals 13 produced calves in which 7 produced twins giving a total of 20 calves A Kaplan-

Meier estimate was conducted to measure the fraction of calves living up to each period of the study (Fig 7)

The mean survival time is until period 235 (midend of summer) At the start of summer 85 of calves

remained (3 still born) The period between summer and before the hunt survival drops to 30 The survival

at the end of the study (after hunt) drops further to 20 leaving 4 calves surviving (see appendix B)

Fig 7 Kaplan-Meier estimate of moose calf survival during the study period Period 0 (Start of summer) period 1

(midend of summer) period 2 (before hunt) period 3 (after hunt) period 4 (after winter)

19 Discussion

The results of this study emphasised how strikingly different the habitat composition is along the latitudinal

gradient of Oumlland The three areas show contrasting proportions of the key habitat types The starkest

difference is the high proportion of coniferous forests and lack of agriculture in the north compared to the

centre and south The proportion of coniferous forest in the north is almost 5 times greater than in the centre

and south whereas the proportion of agriculture in the centre and south is more than double that in the north

The north is perceived to be composed of the most suitable habitat for moose (Dussault et al 2006) It has the

largest proportions of each forest type and a low proportion of agricultural land This provides suitable forage

and shelter throughout the year The south has a contrasting habitat composition to the north The proportions

of agricultural and sparsely vegetated areas are the highest between the three areas and the proportions of forest

habitats are the lowest The large proportion of sparsely vegetated areas and low proportions of forest habitat

corresponds to the large area of Stora Alvaret This is perceived to be the least suitable area due to a lack of

shelter (coniferous forest) and suitable forage The strong preference for coniferous and younger forest habitats

in the south would suggest that moose exhibit a functional response in habitat selection (Godvik et al 2009)

ie as the proportion of a particular habitat decreases the selection for that habitat increases in this case

coniferous forests which provide shelter and younger forest which provide good forage Similarly in the centre

moose show strong preference for mixed forests a habitat that is of low proportion

In view of the large variation in habitat proportions between the areas it is surprising that there is not a large

variation in the home range sizes or the activity levels annually or seasonally Home ranges are ultimately

chosen to maximise fitness and meet energy requirements by utilizing the available forage Seasonal conditions

change the availability and necessity of resources (food quality shelter) Unlike the GS during the WS

deciduous trees and shrubs are leafless and low-lying shrubs are under snow cover (Dussault et al 2005)

These changes are well known to cause populations to alter their activity and home ranges to meet energy

requirements (Mysterud et al 2001) Populations have been shown to increase or decrease their home ranges

during the two seasons The GS home ranges are often larger than the WS home ranges (Philips et al 1973

Mysterud et al 2001) In some cases they can be found to be almost double the size of the WS home ranges

(Cederlund and Okarma 1988) In other populations the WS home ranges are double the size of the GS home

ranges (Lynch and Morgantini 1984) or sizes do not significantly differ (Cederlund and Sand 1994)

Previous studies on moose find females generally show increased activity from the start on the GS due to

various factors eg reduced ruminating times increased metabolic needs and increased foraging bursts

(Wattles and DeStefano 2013) Increased metabolic needs during this time are a results of pregnancy and

lactation (Georgii 1980) During the height of the GS they usually show reduced activity levels through times

of increased thermal stress (Renecker and Hudson 1989 van Beest et al 2012) During the WS the depth and

the duration of snow cover are well known to affect the activity level (Telfer 1970 Mysterud and Oslashstbye 1999

Bjoslashrneraas et al 2011) During the WS generally home ranges are smaller and activity less due to lower

metabolic needs Moose activity is constrained by rumination during the WS this period is known to be longer

due to the change in diet (Cederlund 1989 Renecker Hudson 1989) This was not the case on Ӧland activity

20

was lowest in February which is a similar result to Cederlundrsquos (1989) paper However Ӧland moose did not

significantly alter their seasonal activity levels The fact that the annual and seasonal activity levels and home

ranges were similar could be a result of the mild winters on Oumlland during the study period (Smhise 2014)

During the study period the average number of snow days was 80 and the mean snow depth was 10cm

(appendix F) (Swedish Meterological and Hydrological Institute- SMHI) These mild conditions do not restrict

the movement of moose or obscure forage Moose are well adapted for movement in deep snow depths of 60-

86cm (Prescott 1968) are needed to truly restrict movement This finding was similar to the Sweanor and

Sandegren (1989) and Cederlund and Sand (1994) where the snow depth at their sites did not reach movement

restricting depths

The survival curve illustrates just how bad the calf survival is on Ӧland Survival falls from 85 at the start to

20 Out of 20 calves only four were alive at the end of the study The sharpest fall in survival was the period

between end of summer and before the hunt so the deaths were not due to hunting Previous calf autopsies

(Malmsten 2014a) have shown that cause of death was starvation mothers possibly either did not have milk

the calf was unable to feed or the mother abandoned the calf Closer field based observations are needed to

attain this knowledge Moose are seasonal polyoestral mammals (Monfort et al 1993) coming into oestrus

during late September early October (Garel et al 2009) (appendix F) The diet of the mother influences the

health of the calf and this period is when sodium is hard to find sodium is a key mineral in moose diets for

features such as reproduction (Belovsky and Jordan 1981) Moose gain sodium mainly through aquatic plants

(MacCracken et al 1993) However the compositional analysis shows that freshwater areas are often ranked

as one of the lowest used habitats and coastal areas were removed as the proportion found in the home ranges

was extremely low The Jacobs Index shows that the moose only prefer freshwater areas in the north UD50

during the WS The north individuals again are those that are showing typical moose habitat selection

It is known that habitat selection is hierarchical with habitats that increase fitness selected for and the effects

of limiting factors are reduced (Rettie and Messier 2000) At the UD95 during the GS moose preferred areas

of good forage (forests) and avoided areas of low forage (freshwater and sparsely vegetated areas) and areas

close to humans (urban) This is consistent with other reports (Laurian et al 2008 Torres et al 2011) Within

the UD50 there is a shift in preferences The good forage areas are again preferred during the GS however

during WS the only preferred habitat is often agricultural land During the WS there could be a steady supply

of supplementary feed available hence the high levels of agricultural produce found in the rumen content

samples and the high preference of agricultural areas This diet is unusual for moose previous studies of

Swedish moose diet have found the GS diet was dominated by birch willow and herbaceous plants and the

WS diet dominated by pine and birch (Cederlund and Nystrom 1981) The diet analysis was conducted during

the WS instead of being dominant pine composed just 2 Birch did not appear however unidentified wood

composed only 9 whereas agricultural produce accounted for 69 Supplementary feed may be perceived

by the moose in the centre and south as a vital forage source during the WS In fact in the centre the

agricultural land is the only preferred habitat at the UD50 It is unknown whether there are salt licks provided

in these areas Selection for a critical habitat is often thought to be a fixed factor The Oumlland population from

21 the three areas are close in proximity however they displayed contrasting preferences This is supported by the

Osko et al (2004) report that found two neighbouring moose populations that had access to the same habitats

displayed contrasting preferences Habitat preferences for populations of the same species are not necessarily

fixed They alter with varying levels of habitat abundance and limiting factors skewing what is preserved to

be critical

The main limitation encountered in this study was with the limited sample There was only data on two

individuals from the north of the island which led it being removed from many of the analysis Similarly due

to a lack of relocations from the collars being turned off at points throughout the year two further individuals

had to be removed from a majority of the analysis This reduced the sample size to 17 or 18 individuals

Similarly only 13 of the individuals from the study produced calves This unfortunately prevented including

survival into models Although the sample size was small it was accurate it was of high resolution over

300000 GPS points In future it would be beneficial to have a more standardised data set An equal sample of

individuals from the three areas would be advised along with ensuring the GPS collars are kept turned on for

the entirety of the growing and winter season to allow comparisons between years It would also be

advantageous to collect coordinates of the feeding sites along with the composition This could then be

compared with high use UD coordinates to look if moose are truly spending a majority of their foraging time

at feeding stations A study on the population densities of moose and the increasing population of roe deer

(Capreolus capreolus) would add the factor of competition into the model

The low calf survival on Ӧland is most likely the result of a combination of factors The lack of suitable habitat

reported in this study in conjunction with Malmstenrsquos (2014a) report on the threat of disease (Anaplasma

phagocytophilum) are probable influences on the calf survival on Ӧland On Ӧland there is an increasing

population of roe deer and large numbers of migratory birds both carriers of ticks and diseases The mild

conditions on Ӧland are advantageous for ticks the carriers of A phagocytophilum Fewer snow days and

shorter periods of snow cover along with dry conditions are favourable for ticks This could probably be one

of the reasons for females to be of lower quality and therefore not being able to ensure calf survival Moose

have to utilise areas where in other populations individuals tend to avoid Finally similar to many studies I

advocate further research using a stronger dataset and longer term monitoring

22

Acknowledgements

I am indebted to NJ Singh and A Allen for all their help and guidance through the whole of this study I

thank SLU for the support provided during this study in terms of data finances and facilities Thank you to

everyone at the Department of Wildlife Fish and Environmental Studies for being so friendly and

supportive I would like to thank L Edenius for driving me around the study area and S Michon and H

Khalil for keeping me sane with fika and training

23 References

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Bradshaw RHW Hannon GE Lister AM (2003) A long-term perspective on ungulate-vegetation

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24

Bunnefeld N Boumlrger L van Moorter B Rolandsen CM Dettki H Solberg EJ Ericsson G(2011) A model-

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Cooke SJ Hinch SG Wikelski M Andrews RD Kuchel LJ Wolcott TG Butler PJ (2004) Biotelemerty a

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Ericsson G Wallin K Ball JP Broberg M (2001) Age-related reproductive effort and senescence in free-

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Ericsson G Malmsten J Neumann W Singh NJ Dali AM Submitted Summer Calf Survival of

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25 Festa-Bianchet M Gaillard JM Jorgenson JT (1998) Mass and density-dependent reproductive success and

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Gaillard JM Festa-Bianchet M Yoccoz NG (1998) Population dynamics of large herbivores variable

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Systematics 31367-393

Gaillard JM Festa-Bianchet M Delorme D Jorgenson J (2000b) Body mass and individual fitness in female

ungulate bigger is not always better Proceedings Biological Sciences 267471-477

Gaillard JM Hearingblewhite M Loison A Fuller M Powell R Basille M van Moorter B (2010) Habitat-

performance relationships finding the right metric at a given Spatial scale Philosophical

Transactions of the Royal Society B 3652255-2265

Garel M Solberg EJ Sӕther B-E Groslashtan V Tufto J Heim M (2009) Age size and spatiotemporal variation

in ovulation patterns of a seasonal breeder the Norwegian moose (Alces alces) The American

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Georgii B (1980) Home range patterns of female red deer (Cervus elaphus L) in the Alps Oecologia

47278-285

Godvik IMR Loe LE Vik JO Veiberg V Langvatn R Mysterud A (2009) Temporal scales trade-offs and

functional responses in red deer habitat selection Ecology 90699ndash710

Gordon IJ Hester AJ Festa-Bianchet M (2004) Review The management of wild large herbivores to meet

economic conservation and environmental objectives Journal of Applied Ecology 411021-

1031

Hagner O Nilsson M Reese H Egberth M Olsson H (2005) Procedure for classification of forests for

CORINE land cover in Sweden In Oluić M (ed) New strategies for European remote sensing

Millpress Rotterdam pp 523ndash530

Hall LS Krausman PR Morrison ML (1997) The habitat concept and a plea for standard terminology

Wildlife Society Bulletin 25173-182

Harris RB Wall WA Allendorf FW (2002) Genetic consequences of hunting what do we know and what

should we do Wildlife Society Bulletin 30634-643

Herfindal I Saeligther B-E Solberg EJ Andersen R Hoslashgda KA (2006) Population characteristics predict

responses in moose body mass to temporal variation in the environment Journal of Animal

Ecology 75 (5) 1110-1118

Horne JS Garton ED Krone SM Lewis JS (2007) Analysing animal movements using Brownian bridges

Ecological Society of America Ecology 882354-2363

Hornok S Kovaacutets D Csoumlrgo T Meli M Goumlnczi E Hadnagy Z Takaacutecs N Farkas R Hofmann-Lehmann R

(2014) Birds as potential reservoirs of tick-borne pathogens first evidence of bacteraemia

with Rickettsia Helvetica Parasites and Vectors 7128

26

Jacobs J (1974) Quantitative measurement of food selection a modification of the forage ratio and Ivlevrsquos

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ungulates Journal of Applied Ecology 451339-1348

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preference Ecology 6165-71

Jonsson F (2007) rsquoDen oumllaumlndska aringlgstammens foumlrvaltingrsquo Departement of Wildlife Fish and Environmental

Studies SLU Examensarbete I aumlmnet biologi vol 20072

Kaplan EL Meier P (1958) Nonparametric estimation from incomplete observation Journal of the American

Statistical Association 53457-481

Keating KA Cherry S (2009) Modelling utilization distributions in space and time Ecology 90(7)1971-

1980

Kie JG Matthiopolos J Fieberg J Powell RA Cagnacci F Mitchell SM Gaillard JM Moorcroft PR (2010)

The home range concept are traditional estimators still relevant with modern telemetry

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Viltoumlvervakningen 20072008 (Annual wildlife surveillance report) Viltforum Svenska

Jaumlgarefoumlrbundet Oumlster-Malma 20092

Kranstauber B Kays R LaPoint SD Wikelski M Safi K (2012) A dynamic Brownian bridge movement

model to estimate utilization distributions for heterogeneous Animal movement Journal of

Animal Ecology 81738-746

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Laurian C Dussault C Ouellet JP Courtois R Poulin M Breton L (2008) Behaviour of moose relative to a

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Lavsund S Nygreacuten T Solberg EJ (2003) Status of moose populations and challenges to moose management

in Fennoscandia Alces 39109-130

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14343-348

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mortality of temperate ungulates Wildlife Biology 1209-223

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Lynch GM Morgantini LE (1984) Sex and age differential in seasonal home range size of moose in

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MacCracken JG Ballenberghe VV Peek JM (1993) Use of aquatic plants by moose sodium hunger or

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27

Malmsten J Wideacuten DG Rydevik G Yon L Hutchings MR Thulin CG Soumlderquist L Aspan A Stuen S

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Malmsten J (2014a) lsquoReproduction and health of moose in southern Swedenrsquo Doctoral thesis Swedish

University of Agricultural Sciences (SLU) Umearing

Malmsten J Soumlderquist L Thulin C Wideacuten DG Yon L Hutchings MR Dalin A (2014b) Reproductive

characteristics in female Swedish moose (Alces alces) with emphasis on puberty timing of

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Marsh DM Hanlon TJ (2004) Observer gender and observation bias in animal behaviour research

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28

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29

Tveito OE Foslashrland EJ Alexandersson H Drebs A Jonsson T Vaarby-Laursen E (2001) Nordic climate

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van Beest FM van Moorter B Milner JM (2012) Temperature-mediated habitat use and selection by a heat

sensitive northern ungulate Animal Behaviour 84(3)723-735

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Management 39118-123

Verme LJ Ullrey DE (1984) Physiology and nutrition White-tailed deer ecology and management (Ed By

Halls LK) pp 91-118 Stackpole Harrisburg Pennsylvania

Wattles DW DeStefano (2013) Space use and movements of moose in Massachusetts Implications for

conservation of large mammals in a fragmented environment Alces 4965-81

White RG Rowell JE Hauer WE (1997) The role of nutrition body condition and lactation on calving

success in muskoxen Journal of Zoology 24313-20

30

Appendix A

Introduction

Fig 1 Summary chart of factors affecting the life history and therefore the long term fitness of a population

Fig 2 Summary chart 2

Movement

Habitat

Climate

Topography

Competition

FoodWater

Disease

Die

Survive

Reproduce

Population long term fitness

31 Appendix B

Method and Materials

Fig 1 Summary of processes

32

Fig 2 Examples of classical kernel home range output and Brownian bridge kernel home range (Calenge 2011) The

right image includes the area between relocations ie the movement path in contrast to the classic kernel home range

in the left image

33 Appendix C

Home ranges

Fig 1 Example of a non-migratory (ID006) individuals BRB kernel area From top left annual growing and winter

season UD50 (black contour) and UD95 (red contour)

Fig 2 Example of a migratory (ID012) individuals BRB kernel area From the left annual growing and winter season

UD50 (black contour) and UD95 (red contour)

34

Table 1 Annual and seasonal UD50 and UD95 areas (ha) for all individuals

ID Annual GS WS

UD50 UD95 UD50 UD95 UD50 UD95

ID004 190 924 93 531 173 941

ID005 230 1364 132 945 72 682

ID006 162 1036 89 736 70 611

ID008 277 1536 156 809 78 738

ID009 137 834 48 295 126 653

ID010 114 682 83 448 96 488

ID012 177 963 123 544 76 545

ID014 160 1018 87 575 89 662

ID015 172 858 128 532 109 679

ID016 156 1047 65 455 92 534

ID017 153 1088 149 1043 69 349

ID019 279 1097 176 911 163 824

ID020 139 1084 67 349 160 794

ID022 159 811 131 638 61 454

ID023 187 1061 147 771 72 705

ID024 146 725 165 705 101 458

ID026 142 605 99 442 125 547

ID027 126 567 75 461 48 277

35 Appendix D

Activity

Fig 1 Mean daily movement during the study period GS 23-April-2012 to 07-Nov-2012 WS 08-Nov-2012 to

22-April-2013 (number indicates month)

Fig 2 Mean daily movement in the centre and south during the GS and WS

36

Appendix E

Habitat Proportions

Fig 1 All individualsrsquo seasonal habitat proportions within the UD95

37 Habitat Selection

Table 1 Simplified ranking matrices comparing proportional habitat use within the second order (UD95Area) with

proportions of total available habitat types Mean value on the matrix was replaced by a sign a triple sign represents

significant deviation from random at P lt05 Highlighted habitat is ranked 1st

North A

gri

cult

ure

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 --- --- - +++ --- --- --- +++ +++ --- 8

Broad Leaf +++ 0 +++ + +++ +++ +++ + +++ +++ +++ 1

Clear Fell +++ --- 0 + +++ - - --- +++ +++ --- 7

Coniferous + - - 0 +++ - - --- +++ +++ - 6

Freshwater --- --- --- --- 0 --- --- --- +++ - --- 10

Grassland

Moors +++ --- + + +++ 0 +++ - +++ +++ + 3

MiresMarshes +++ --- + + +++ --- 0 - +++ +++ --- 5

Mixed +++ - +++ +++ +++ + + 0 +++ +++ + 2

Sparse Veg --- --- --- --- --- --- --- --- 0 --- --- 11

Urban --- --- --- --- + --- --- --- +++ 0 --- 9

Younger +++ --- +++ + +++ - +++ - +++ +++ 0 4

Rank Order and

Significance

Broad Leafgt Mixedgt GrasslandMoorsgt Youngergtgtgt MiresMarshesgt Coniferousgt

Clear Fellgtgtgt Agriculturegtgtgt Urbangt Freshwatergtgtgt Sparse Veg

Central

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 --- --- --- + +++ + --- +++ +++ --- 6

Broad Leaf +++ 0 +++ + +++ +++ + - +++ +++ - 3

Clear Fell +++ --- 0 - +++ +++ + --- +++ +++ --- 5

Coniferous +++ - + 0 +++ +++ + --- +++ +++ - 4

Freshwater - --- --- --- 0 +++ - --- +++ +++ --- 8

Grassland

Moors --- --- --- --- --- 0 --- --- +++ - --- 10

MiresMarshes - - - - + +++ 0 - +++ +++ - 7

Mixed +++ + +++ +++ +++ +++ + 0 +++ +++ + 1

Sparse Veg --- --- --- --- --- --- --- --- 0 - --- 11

Urban --- --- --- --- --- + --- --- + 0 --- 9

Younger +++ + +++ + +++ +++ + - +++ +++ 0 2

Rank Order and

Significance

Mixedgt Youngergt Broad Leafgt Coniferousgt Clear Fellgtgtgt Agriculturegt

MiresMarshesgt Freshwatergtgtgt Urbangt GrasslandMoorsgtgtgt Sparse Veg

38

South

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 + - - + - + +++ +++ +++ - 5

Broad Leaf - 0 - - + - - +++ + +++ - 7

Clear Fell + + 0 - + + + +++ + +++ + 2

Coniferous + + + 0 +++ + + +++ + +++ + 1

Freshwater - - - --- 0 - - + + +++ - 8

Grassland

Moors + + - - + 0 + + +++ + - 4

MiresMarshes - + - - + - 0 +++ + +++ - 6

Mixed --- --- --- --- - - --- 0 + + --- 10

Sparse Veg --- - - - - --- - - 0 + - 9

Urban --- --- --- --- --- - --- - - 0 --- 11

Younger + + - - + + + +++ + +++ 0 3

Rank Order

and

Significance

Coniferousgt Clear Fellgt Youngergt GrasslandMoorsgt Agriculturegt MiresMarshesgt Broad Leafgt

Freshwatergt Sparse Veggt Mixedgt Urban

Table 2 Simplified ranking matrices comparing proportional habitat use within the third order (UD50UD95) with

proportions of total available habitat types Mean value on the matrix was replaced by a sign a triple sign represents

significant deviation from random at P lt05 Highlighted habitat is ranked 1st

North

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 --- --- --- - + --- --- + +++ --- 8

Broad Leaf +++ 0 +++ + + + + + +++ +++ + 1

Clear Fell +++ --- 0 + + + - - + +++ - 5

Coniferous +++ - - 0 + + --- --- +++ +++ - 6

Freshwater + - - - 0 +++ - - +++ +++ - 7

GrasslandMoors - - - - --- 0 - - - + - 10

MiresMarshes +++ - + +++ + + 0 - +++ +++ + 3

Mixed +++ - + +++ + + + 0 +++ +++ + 2

Sparse Veg - --- - --- --- + --- --- 0 +++ --- 9

Urban --- --- --- --- --- - --- --- --- 0 --- 11

Younger +++ - + + + + - - +++ +++ 0 4

Rank Order and

Significance

Broad Leafgt Mixedgt MiresMarshesgt Youngergt Clear Fellgt Coniferousgt Freshwatergt

Agriculturegt Sparse Veggt GrasslandMoorsgt Urban

39

Central

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 --- --- + + - - - + +++ --- 7

Broad Leaf +++ 0 + +++ + + + + + +++ - 2

Clear Fell +++ - 0 +++ + + + + + +++ - 3

Coniferous - --- --- 0 + - - --- +++ + --- 8

Freshwater - - - - 0 --- - - --- - - 11

GrasslandMoors + - - + +++ 0 + - + +++ - 5

MiresMarshes + - - + + - 0 + + +++ - 6

Mixed + - - +++ + + - 0 +++ +++ - 4

Sparse Veg - - - --- +++ - - --- 0 +++ - 9

Urban --- --- --- - + --- --- --- --- 0 --- 10

Younger +++ + + +++ + + + + + +++ 0 1

Rank Order and

Significance

Youngergt Broad Leafgt Clear Fellgt Mixedgt GrasslandMoorsgt MiresMarshesgt

Agriculturegt Coniferousgtgtgt Sparse Veggtgtgt Urbangt Freshwater

South

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 - - - - - + - +++ + --- 8

Broad Leaf + 0 - --- + - + - +++ + - 6

Clear Fell + + 0 - + - + - +++ + - 4

Coniferous + +++ + 0 + + +++ + +++ + + 1

Freshwater + - - - 0 - - + + + - 7

GrasslandMoors + + + - + 0 + + + + - 3

MiresMarshes - - - --- + - 0 - + + - 9

Mixed + + + - - - + 0 + + - 5

Sparse Veg --- --- --- --- - - - - 0 + --- 10

Urban - - - - - - - - - 0 - 11

Younger +++ + + - + + + + +++ + 0 2

Rank Order and

Significance

Coniferousgt Youngergt GrasslandMoorsgt Clear Fellgt Mixedgt Broad Leafgt Freshwatergt

Agriculturegt MiresMarshesgt Sparse Veggt Urban

40

Table 3 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the GS according to Jacobs index

Ran

k North Centre South

50 95 50 95 50 95

+ - + - + - + - + - + -

1 Broad

Leaf Urban Broad Leaf Sparse Veg

Broad

Leaf Urban Mixed Urban Coniferous Urban

Grassland

Moors Urban

2 Mixed Sparse Veg Mixed Freshwater Younger Agriculture Younger Sparse Veg Younger Sparse Veg Clear Fell Mixed

3 Mires

Agriculture Grassland

Urban Clear

Fell Coniferous Broad Leaf

Grassland

Moors

Clear Fell Agriculture Coniferous Sparse Veg

Marshes Moors

4 Younger Grassland

Younger Agriculture

Freshwater Coniferous Freshwater

Broad Leaf Mires

Younger Freshwater

Moors Marshes

5 Clear

Fell Freshwater

Mires Coniferous

Sparse Veg Clear Fell Agriculture

Freshwater Agriculture

Marshes

6 Coniferous Clear Fell

Mires

Marshes

Mires

Grassland

Moors

Mires

Marshes Marshes

7 Mixed Mixed Broad Leaf

8 Grassland

Moors

41

Table 4 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the WS according to Jacobs index

Ran

k North Centre South

50 95 50 95 50 95

+ - + - + - + - + - + -

1 Mires

Marshes

Grassland

Moors Mixed Freshwater Agriculture Urban Mixed Freshwater

Grassland

Moors Urban GrasslandMoors Urban

2 Freshwater Mixed Coniferous Urban Mires

Marshes Coniferous Sparse Veg Agriculture

Sparse

Veg Coniferous Freshwater

3 Urban Coniferous Younger Grassland

Moors Freshwater Younger Urban Freshwater

Broad

Leaf Agriculture Mixed

4 Younger Agriculture Sparse Veg Broad

Leaf

Broad

Leaf

Grassland

Moors Mixed Broad Leaf

5 Clear Fell Agriculture Coniferous Agriculture Mires

Marshes Clear Fell

6 Sparse

Veg

Mires

Marshes Mixed

Mires

Marshes

Clear

Fell

Mires

Marshes

7 Broad

Leaf Clear Fell Younger Clear Fell Younger Sparse Veg

8 Clear Fell Younger

9 Sparse

Veg

10 Grassland

Moors

42

Table 5 Second order (UD95Area) individual selectionavoidance for the GS and WS according to the Jacobs index

ID GS WS

Select Avoid Select Avoid

ID004 Younger Sparsely Vegetated MiresMarshes Sparsely Vegetated

ID005 MiresMarshes Sparsely Vegetated Coniferous GrasslandMoors

ID006 Coniferous Sparsely Vegetated Mixed Freshwater

ID008 Mixed Sparsely Vegetated Mixed Freshwater

ID009 Mixed Sparsely Vegetated Mixed GrasslandMoors

ID010 MiresMarshes Freshwater GrasslandMoors Freshwater

ID012 Broad Leaf Sparsely Vegetated Coniferous Urban

ID014 Clear Fell Sparsely Vegetated GrasslandMoors Sparsely Vegetated

ID015 GrasslandMoors Urban GrasslandMoors Freshwater

ID016 GrasslandMoors Freshwater GrasslandMoors Freshwater

ID017 GrasslandMoors Mixed Sparsely Vegetated Mixed

ID019 Mixed Sparsely Vegetated Mixed Urban

ID020 Broad Leaf Sparsely Vegetated Coniferous GrasslandMoors

ID022 MiresMarshes Freshwater MiresMarshes Freshwater

ID023 MiresMarshes GrasslandMoors Mixed Freshwater

ID024 Broadleaf Urban Broad Leaf Urban

ID026 GrasslandMoors Freshwater GrasslandMoors Freshwater

ID027 GrasslandMoors Urban Sparsely Vegetated Freshwater

43 Table 6 Third order (UD50UD95) individual selectionavoidance for the GS and WS according to the Jacobs index

ID GS WS

Select Avoid Select Avoid

ID004 Broad Leaf Mixed GrasslandMoors Freshwater

ID005 Broad Leaf Freshwater Agriculture Freshwater

ID006 Clear Fell Freshwater Agriculture MiresMarshes

ID008 MiresMarshes Freshwater Agriculture Urban

ID009 Freshwater Agriculture Agriculture Freshwater

ID010 Mixed Urban Sparsely Vegetated Urban

ID012 Coniferous GrasslandMoors Freshwater Urban

ID014 Urban Agriculture Freshwater Urban

ID015 Mixed Forest Urban Clear Fell Urban

ID016 Freshwater Urban GrasslandMoors Mixed

ID017 Coniferous Mixed Coniferous Broad Leaf

ID019 Broad Leaf GrasslandMoors Urban GrasslandMoors

ID020 Freshwater Urban Freshwater Agriculture

ID022 MiresMarshes Urban Broad Leaf GrasslandMoors

ID023 Freshwater Mixed Agriculture Freshwater

ID024 Mixed Freshwater Mixed Freshwater

ID026 Mixed MiresMarshes Sparsely Vegetated GrasslandMoors

ID027 Freshwater MiresMarshes GrasslandMoors Broad Leaf

44

Fig 2 North third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)

45

Fig 3 Centre third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)

46

Fig 4 South third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)

47

Fig 5 North second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)

48

Fig 6 Centre second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)

49

Fig 7 South second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)

50

Appendix F

Background

Fig 1 Daily mean snow depth and duration during the study period (Andrew Allen)

Female Moose Reproduction

Moose are seasonal polyoestral mammals (Monfort et al 1993) coming into oestrus during late September

early October (Garel et al 2009) The Swedish moose cow population reaches puberty between the ages 25

and 35 (Sand and Cederlund 1993) during which the reproductive period begins with the onset of ovulation

The age an individual reaches puberty is dependent on their body condition they have to reach a weight

threshold to reach puberty and become reproductive (Sand 1996) If she is over the weight threshold she will

go into oestrus in the autumn If she does not reach the weight threshold then she will go into oestrus the

following autumn if successful she will give birth to individual or twin calves in late May to early June

(Ericsson et al 2001) and therefore reach sexual maturity (Malmsten et al 2014b) Fecundity is related to

both the condition and the age of the cow Cows go through senescence at 12 years of age (Ericsson et al

2001) Providing calves with the required level of nutrition demands high energy and protein resources from

the mother during senescence this becomes harder to achieve leading to decreased levels of parental care

and higher levels of calf mortality

Page 9: Habitat-performance relationships on an island: fitness ...navinderjsingh.weebly.com/uploads/1/1/2/2/11224342/... · Conditions on Öland are milder than those found in other areas

9 incorporate measures of space use using the utilization distribution (UD van Winkle 1975) which can be

described as the ldquorelative frequency distribution of an animalrsquos occurrence in all four dimensions of space

and timerdquo (Keating and Cherry 2009) Home range is viewed as a constant 2D polygon whereas UDs are

viewed as multiple 3D polygons that take into account the distribution as well as the intensity of animalrsquos

movements and space use within their home range (Kranstauber et al 2012) (see appendix A)

Estimations of each individualrsquos annual and seasonal UDs were found using the Biased Random Bridge (BRB)

kernel approach (Benhamou 2011) from the adehabitatHR package (Calenge 2006) in R It was chosen as it is

considered an improvement on the previously preferred Brownian bridge (BB) method (Horne et al 2007) The

BB is purely a diffusive movement process whereas the BRB is an advective-diffusive movement process BB

does not take into account changes in advection direction (drift) or strength BB assumes an animalrsquos

movement is purely random it moves from a starting point and ends up at the end location randomly By

adding the advection component the BRB takes into account that the animalrsquos movement is biased towards a

certain direction This allows for a more biologically relevant analysis (Benhamou and Corneacutelis 2010)

A grid was created using the minmax XY coordinates of all individuals (plusmn 10 km to increase the extent and

prevent the grid directly touching the XY locations) The resolution of the grid was fixed at a 25 m x 25 m

scale to match the resolution of the relevant habitat maps (Hagner et al 2005) By specifying these criteria the

resolution of the data remains consistent between individuals The diffusion coefficient determines the variance

in the location of the kernels between two locations This was calculated from each individualrsquos dataset using

the BRBD function and added to the BRB model (see Benhamou 2011) The strength and direction of BRB

advection can change between bridges whilst having to remaining constant To remain constant an upper Tmax

and lower Lmin time thresholds were set Successive relocations that exceeded Tmax or under Lmin were

removed from the UD calculations The 50 (UD50) and 95 (UD95) isopleths were then calculated from

the UD using the kernelarea function

Habitat

The scale of analysis was further divided following Johnson (1980) Habitat selection within the landscape

(second order selection) was studied by comparing the UD95 with available habitats in each of the three study

areas of Oumlland (UD95Area) Habitat selection within the home range (third order selection) was studied by

comparing the UD50 with the UD95 (UD50UD95)

12 habitat classes were used in the analysis agricultural land broad leaved forests clear felled areas coastal

coniferous forests freshwater areas moorsgrassland miresmarshes mixed forest sparsely vegetated areas

urban areas and younger forests The proportion of area covered by each of these habitat classes was

determined in the UD50 and UD95 Habitat data was obtained from satellite imagery generated by Svenska

Marktaumlckedata (Hagner et al 2005) The habitat maps were last updated in 2002 and have a resolution of 25

m

Compositional analysis ( habitat used habitat available) (Aebischer 1993) was used in conjunction with

the Jacobrsquos index (D) (eqn1) to quantify habitat selection (Jacobs 1974) Coastal areas were removed as not

10

all home ranges contained them This combined approach allowed identification of habitats that are used

disproportionally to their availability ie in a non-random manner (Beyer et al 2010) This is an indication of

which habitats are important for an individual

119863 = ( 119903minus119901

119903+119901minus2119903119901 ) (eqn1)

r = Proportion of habitat type used

p = Total proportion of habitat available

D = Jacobs index varies from -1 (strong avoidance) to +1 (strong preference) with values close to 0 indicating

the habitat is used in proportion to its availability

Activity

Activity level is measured as the mean daily movement (MDM) by the individual to investigate if individuals

in an areaseason moved more and hence were more active than those in other areasseasons Unfortunately

only two cows were collared in the north and were therefore left out of this analysis Moose were identified as

migratory using a modelling approach (see Bunnefeld et al 2011 for methods) Migratory individuals were

initially removed from the activity analysis (n=4)The reason is that both migratory journeys were completed

during the winter season thus increasing the mean daily distance travelled and potentially biasing the analysis

One individual was also removed due it its collar not returning relocations during the entirety of the WS

Diet analysis

The Ӧland project team conducted histology diet analysis on the rumen content of five individuals that were

shot in the centre and south of the island during the WS of 2013

Survival analysis

The Ӧland project team measured calf survival using the mark-resight method The presenceabsence of a calf

was recorded by tracking the cows at six occasions throughout the year These were at the start of the calving

season (mid-May to early June) twice through the summer before the hunt after the hunt and after winter

Survival trend was estimated using a Kaplan-Meier curve (Kaplan and Meier 1958) The Kaplan-Meier curve

shows the survival function (S (t)) ie the probability of an individual surviving until at least time t (Bewick

et al 2004) The probability of surviving from one period to the next is multiplied together to give the survival

function The S(t) of this study is the probability of an individual surviving from birth to after the hunt

(Method summary see appendix B)

11 Results

Home RangeUtilization Distribution

A total of 51 home ranges were estimated (17 annual 17 within growing season 17 within winter season)

Annual x = 9613 ha GS x = 6345 ha and WS x = 6023 ha (appendix C)

At the UD50 scale the largest annual and seasonal mean home ranges were located in the north Mean annual

and seasonal home ranges in the centre were slightly larger than the south This difference was not significant

(F(113)= 22 p= 87) (ANOVA) There was no significant difference between the seasonal home ranges (x

plusmnSD for GS = 116 plusmn38 for WS = 98 plusmn32 ha) (t(11) = 105 p = 32) or the seasonal home ranges in the centre

(t(8) = 101 p = 34 and the south (t(5) = 87 p = 42) (paired-sample t-test) (Table 1)

At the UD95 scale the largest annual and WS mean home ranges were located in the north The largest GS

mean home ranges were located in the centre Mean annual and seasonal home ranges in the centre were

slightly larger than the south This difference was not significant (F(113) = 59 p = 63) (ANOVA) There

was no significant difference between the seasonal home ranges (x plusmnSD for GS = 635 plusmn225 for WS = 602

plusmn161) (t(11) = 373 p = 71) or the seasonal home ranges in the centre (t(8)= 20 p = 84) or south (t(5) = 34

p = 74) (paired-sample t-test) (Table 1)

Table 1 Seasonal and annual mean UD50 and UD95 BRB kernel area in hectares (1ha = 001km2) for the north centre

and south of Oumlland (smoothing factor (h) =100)

Are

a

Annual UD50 GS UD50 WS UD50

n Mean SD Range n Mean SD Range n Mean SD Range

N 2 209 49 139-279 2 1215 39 67-176 2 1615 106 160-163

C 9 178 56 114-277 9 116 44 48-165 9 943 4 61-173

S 6 160 21 142-177 6 1085 51 65-149 6 933 35 69-125

Annual UD95 GS UD95 WS UD95

N 2 10905 5 1084-1097 2 630 199 349-911 2 809 11 794-824

C 9 997 32 682-1536 9 6531 22 295-945 9 637 17 454-941

S 6 9298 30 605-1088 6 5985 373 442-575 6 5526 20 349-679

12

Activity

MDM rates in the three areas (sedentary individuals) during the GS ranged from 14 ndash31 km day During the

WS ranged they ranged from 11-24 km day (Table 2) Movement rates during the GS were higher than the

WS (x plusmnSD for GS = 202 plusmn043 for WS = 161 plusmn043) but it was not statistically significant (t(11) = 200 p=

07) (paired sample t-test)

Table 2 Seasonal mean daily movement rates (km day) for each area and for both areas (total)

Are

a

GS WS

n Mean SE Range n Mean SE Range

C 8 20 003 14-18 8 20 004 12-24

S 4 22 016 17-31 4 12 02 11-13

Total 12 202 003 14-31 12 16 003 11-24

The seasonal MDM rates of all individuals (migratory and sedentary) were not significantly different (x plusmnSD

for GS = 20 plusmn04 for WS = 18 plusmn061) (t(14) = 139 p= 19) (paired sample t-test)

The WS home range size affects the WS MDM (F(110) = 927 p = 01) (ANOVA) The GS home range size

does not affect the GS MDM (F(110) = 36 p = 56) (ANOVA) When the WS home range outlier was

removed the home range size did not affect the WS MDM (F(111) = 186 p= 19) (ANOVA) The MDM was

lowest in February and highest in April (Table 3) there appeared to be no significant pattern in MDM between

the months (appendix D)

Table 3 Mean daily distance moved (km day) for sedentary individuals

Month Season Distance

April GS 0051

May GS 0044

June GS 0039

July GS 0041

August GS 0042

September GS 0044

October GS 0043

November WS 0043

December WS 0038

January WS 0035

February WS 0028

13 Habitat ndash Proportions

The largest proportion of habitat on the island is agriculture the lowest proportion of habitat (excluding coastal

and freshwater) is urban areas (Fig 2) The largest proportion of habitat in the north was coniferous forests

whilst agricultural areas were the dominant habitat types in the centre and south (Fig 3) The lowest proportion

(excluding coastal and freshwater areas) was urban

Fig 2 Proportion of different types of habitats found on Ӧland

Fig 3 Mean proportion of habitats contained within UD95 in the three areas of Oumlland C = Centre N = North S =

South

14

Habitat - Selection

Generally forest habitat types are the highest ranked whilst sparsely vegetated and urban areas are the lowest

ranked Both the second and third order habitat selection analyses gave significant results in the compositional

analysis (Table 4) In the third order analysis (UD50UD95) the centre displayed significant differences

between habitat types The coniferous forests are significantly preferred to sparsely vegetated areas and the

sparsely vegetated areas are significantly preferred to urban areas In the second order analysis (UD95Area)

significance was observed in the north and centre In the north younger forests are significantly preferred to

miresmarshes clear felled areas are significantly preferred to agriculture and freshwater areas are significantly

preferred to sparsely vegetated areas In the centre clear felled areas are significantly preferred to agricultural

land freshwater areas are significantly preferred to urban areas and grasslandmoors are significantly preferred

to sparsely vegetated areas

Table 4 Summary of second (UD95Area bottom) and third order (UD50UD95 top) ranked habitat preferences between

the three areas according to the compositional analysis (see appendix B)

Rank North Centre South

1 Broad Leaf Younger Coniferous

2 Mixed Broad Leaf Younger

3 MiresMarshes Clear Fell GrasslandMoors

4 Younger Mixed Clear Fell

5 Clear Fell GrasslandMoors Mixed

6 Coniferous MiresMarshes Broad Leaf

7 Freshwater Agriculture Freshwater

8 Agriculture Coniferous Agriculture

9 Sparse Veg Sparse Veg MiresMarshes

10 GrasslandMoors Urban Sparse Veg

11 Urban Freshwater Urban

Rank North Centre South

1 Broad Leaf Mixed Coniferous

2 Mixed Younger Clear Fell

3 GrasslandMoors Broad Leaf Younger

4 Younger Coniferous GrasslandMoors

5 MiresMarshes Clear Fell Agriculture

6 Coniferous Agriculture MiresMarshes

7 Clear Fell MiresMarshes Broad Leaf

8 Agriculture Freshwater Freshwater

9 Urban Urban Sparse Veg

10 Freshwater GrasslandMoors Mixed

11 Sparse Veg Sparse Veg Urban

Indicates significantly preferred to the habitat below (significant deviation from random at P lt05)

15 The Jacobs index revealed that generally the habitats preferred during the GS within the home range (third

order) are younger (0187) and broad leaf forests (0154) The strongest avoidance was for urban areas (-0627)

During the WS only agricultural areas are preferred (0129) and the strongest avoidance was for urban areas (-

0393) (Fig 4)

Fig 4 Third order seasonal habitat preference (UD50UD95) all individuals The index ranges from -1 (total avoidance)

to 1 (strongest preference) Close to 0 indicates used in proportion to its availability

Third order habitat preferencesavoidances by area

North During the GS the strongest preference was for broad leaf (0218) and mixed forests (0161) The

strongest avoidance was for urban (-1) and sparsely vegetated areas (-05) During the WS the strongest

preference was for miresmarshes (0228) The strongest avoidance was for grasslandmoors (-05)

Centre During the GS the strongest preference was for broad leaf (0233) and younger forests (0223) The

strongest avoidance was for urban (-0527) and agricultural land (-0362) During the WS preference was only

shown for agricultural land (0327) The strongest avoidance was for urban areas (-0679) and miresmarshes

(-0638)

South During the GS the strongest preference was for coniferous (0312) and younger forests (0242) The

strongest avoidance was for urban (-0353) and sparsely vegetated areas (-0330) During the WS

grasslandmoors (0106) were the strongest preference The strongest avoidance was for urban (-0666) and

sparsely vegetated areas (-0351)

16

The Jacobs indices revealed that generally the habitats preferred during the GS within the landscape

(UD95Area) are broad leaf (0216) and younger forests (0201) The strongest avoidance was for urban (-

0717) and freshwater areas (-0694) The strongest preference during the WS are coniferous forests (0242)

and the strongest avoidance was for freshwater (-0674) and urban areas (-0648) (Fig 5)

Fig 5 Second order seasonal habitat preference (UD50UD95) all individuals The index ranges from -1 (total avoidance)

to 1 (strongest preference) Close to 0 indicates used in proportion to its availability

Second order habitat preferencesavoidances by area

North During the GS the strongest preference was for broad leaf (0363) and mixed forests (00291) The

strongest avoidance was for sparsely vegetated (-0909) and freshwater areas (-0780) During the WS mixed

(0335) and coniferous forests (0316) were the strongest preference The strongest avoidance was for

freshwater (-0731) and urban areas (-05333)

Centre During the GS the strongest preference for mixed (0394) and younger forests (0286) The strongest

avoidance was for urban (-0733) and sparsely vegetated (-0708) areas During the WS mixed (0404) and

coniferous forests (0255) were the strongest preference The strongest avoidance was for freshwater (-0704)

and sparsely vegetated areas (-0655)

South During the GS the strongest preference for grasslandmoors (0287) and clear fells (0165) The

strongest avoidance was for urban areas (-0678) and mixed forests (-0491) During the WS grasslandmoors

(0425) and coniferous forests (0154) were the strongest preference The strongest avoidance was for urban (-

0876) and freshwater areas (-0587) (appendix E)

17 Diet

Diet analysis of the rumen content sampled from five individuals (C=2 S=3) revealed that almost two thirds

(69) of the diet is comprised of agricultural produce (apple winter rape and sugar beet) (Fig 6)

Fig 6 Diet analysis from the rumen samples of five moose individuals that were culled in 2013

31

2117

9

8

5

22

1 1

1

1

1 00 0

0

0Diet (2610-911 2013 5 individuals)

AppleWinter RapeSugar BeetUndefined WoodSallowBroad-leaf GrassPineAshOakCloverCurrantsUndefined plantElderberryJuniperRaspberry

18

Calf Survival

Of the 18 individuals 13 produced calves in which 7 produced twins giving a total of 20 calves A Kaplan-

Meier estimate was conducted to measure the fraction of calves living up to each period of the study (Fig 7)

The mean survival time is until period 235 (midend of summer) At the start of summer 85 of calves

remained (3 still born) The period between summer and before the hunt survival drops to 30 The survival

at the end of the study (after hunt) drops further to 20 leaving 4 calves surviving (see appendix B)

Fig 7 Kaplan-Meier estimate of moose calf survival during the study period Period 0 (Start of summer) period 1

(midend of summer) period 2 (before hunt) period 3 (after hunt) period 4 (after winter)

19 Discussion

The results of this study emphasised how strikingly different the habitat composition is along the latitudinal

gradient of Oumlland The three areas show contrasting proportions of the key habitat types The starkest

difference is the high proportion of coniferous forests and lack of agriculture in the north compared to the

centre and south The proportion of coniferous forest in the north is almost 5 times greater than in the centre

and south whereas the proportion of agriculture in the centre and south is more than double that in the north

The north is perceived to be composed of the most suitable habitat for moose (Dussault et al 2006) It has the

largest proportions of each forest type and a low proportion of agricultural land This provides suitable forage

and shelter throughout the year The south has a contrasting habitat composition to the north The proportions

of agricultural and sparsely vegetated areas are the highest between the three areas and the proportions of forest

habitats are the lowest The large proportion of sparsely vegetated areas and low proportions of forest habitat

corresponds to the large area of Stora Alvaret This is perceived to be the least suitable area due to a lack of

shelter (coniferous forest) and suitable forage The strong preference for coniferous and younger forest habitats

in the south would suggest that moose exhibit a functional response in habitat selection (Godvik et al 2009)

ie as the proportion of a particular habitat decreases the selection for that habitat increases in this case

coniferous forests which provide shelter and younger forest which provide good forage Similarly in the centre

moose show strong preference for mixed forests a habitat that is of low proportion

In view of the large variation in habitat proportions between the areas it is surprising that there is not a large

variation in the home range sizes or the activity levels annually or seasonally Home ranges are ultimately

chosen to maximise fitness and meet energy requirements by utilizing the available forage Seasonal conditions

change the availability and necessity of resources (food quality shelter) Unlike the GS during the WS

deciduous trees and shrubs are leafless and low-lying shrubs are under snow cover (Dussault et al 2005)

These changes are well known to cause populations to alter their activity and home ranges to meet energy

requirements (Mysterud et al 2001) Populations have been shown to increase or decrease their home ranges

during the two seasons The GS home ranges are often larger than the WS home ranges (Philips et al 1973

Mysterud et al 2001) In some cases they can be found to be almost double the size of the WS home ranges

(Cederlund and Okarma 1988) In other populations the WS home ranges are double the size of the GS home

ranges (Lynch and Morgantini 1984) or sizes do not significantly differ (Cederlund and Sand 1994)

Previous studies on moose find females generally show increased activity from the start on the GS due to

various factors eg reduced ruminating times increased metabolic needs and increased foraging bursts

(Wattles and DeStefano 2013) Increased metabolic needs during this time are a results of pregnancy and

lactation (Georgii 1980) During the height of the GS they usually show reduced activity levels through times

of increased thermal stress (Renecker and Hudson 1989 van Beest et al 2012) During the WS the depth and

the duration of snow cover are well known to affect the activity level (Telfer 1970 Mysterud and Oslashstbye 1999

Bjoslashrneraas et al 2011) During the WS generally home ranges are smaller and activity less due to lower

metabolic needs Moose activity is constrained by rumination during the WS this period is known to be longer

due to the change in diet (Cederlund 1989 Renecker Hudson 1989) This was not the case on Ӧland activity

20

was lowest in February which is a similar result to Cederlundrsquos (1989) paper However Ӧland moose did not

significantly alter their seasonal activity levels The fact that the annual and seasonal activity levels and home

ranges were similar could be a result of the mild winters on Oumlland during the study period (Smhise 2014)

During the study period the average number of snow days was 80 and the mean snow depth was 10cm

(appendix F) (Swedish Meterological and Hydrological Institute- SMHI) These mild conditions do not restrict

the movement of moose or obscure forage Moose are well adapted for movement in deep snow depths of 60-

86cm (Prescott 1968) are needed to truly restrict movement This finding was similar to the Sweanor and

Sandegren (1989) and Cederlund and Sand (1994) where the snow depth at their sites did not reach movement

restricting depths

The survival curve illustrates just how bad the calf survival is on Ӧland Survival falls from 85 at the start to

20 Out of 20 calves only four were alive at the end of the study The sharpest fall in survival was the period

between end of summer and before the hunt so the deaths were not due to hunting Previous calf autopsies

(Malmsten 2014a) have shown that cause of death was starvation mothers possibly either did not have milk

the calf was unable to feed or the mother abandoned the calf Closer field based observations are needed to

attain this knowledge Moose are seasonal polyoestral mammals (Monfort et al 1993) coming into oestrus

during late September early October (Garel et al 2009) (appendix F) The diet of the mother influences the

health of the calf and this period is when sodium is hard to find sodium is a key mineral in moose diets for

features such as reproduction (Belovsky and Jordan 1981) Moose gain sodium mainly through aquatic plants

(MacCracken et al 1993) However the compositional analysis shows that freshwater areas are often ranked

as one of the lowest used habitats and coastal areas were removed as the proportion found in the home ranges

was extremely low The Jacobs Index shows that the moose only prefer freshwater areas in the north UD50

during the WS The north individuals again are those that are showing typical moose habitat selection

It is known that habitat selection is hierarchical with habitats that increase fitness selected for and the effects

of limiting factors are reduced (Rettie and Messier 2000) At the UD95 during the GS moose preferred areas

of good forage (forests) and avoided areas of low forage (freshwater and sparsely vegetated areas) and areas

close to humans (urban) This is consistent with other reports (Laurian et al 2008 Torres et al 2011) Within

the UD50 there is a shift in preferences The good forage areas are again preferred during the GS however

during WS the only preferred habitat is often agricultural land During the WS there could be a steady supply

of supplementary feed available hence the high levels of agricultural produce found in the rumen content

samples and the high preference of agricultural areas This diet is unusual for moose previous studies of

Swedish moose diet have found the GS diet was dominated by birch willow and herbaceous plants and the

WS diet dominated by pine and birch (Cederlund and Nystrom 1981) The diet analysis was conducted during

the WS instead of being dominant pine composed just 2 Birch did not appear however unidentified wood

composed only 9 whereas agricultural produce accounted for 69 Supplementary feed may be perceived

by the moose in the centre and south as a vital forage source during the WS In fact in the centre the

agricultural land is the only preferred habitat at the UD50 It is unknown whether there are salt licks provided

in these areas Selection for a critical habitat is often thought to be a fixed factor The Oumlland population from

21 the three areas are close in proximity however they displayed contrasting preferences This is supported by the

Osko et al (2004) report that found two neighbouring moose populations that had access to the same habitats

displayed contrasting preferences Habitat preferences for populations of the same species are not necessarily

fixed They alter with varying levels of habitat abundance and limiting factors skewing what is preserved to

be critical

The main limitation encountered in this study was with the limited sample There was only data on two

individuals from the north of the island which led it being removed from many of the analysis Similarly due

to a lack of relocations from the collars being turned off at points throughout the year two further individuals

had to be removed from a majority of the analysis This reduced the sample size to 17 or 18 individuals

Similarly only 13 of the individuals from the study produced calves This unfortunately prevented including

survival into models Although the sample size was small it was accurate it was of high resolution over

300000 GPS points In future it would be beneficial to have a more standardised data set An equal sample of

individuals from the three areas would be advised along with ensuring the GPS collars are kept turned on for

the entirety of the growing and winter season to allow comparisons between years It would also be

advantageous to collect coordinates of the feeding sites along with the composition This could then be

compared with high use UD coordinates to look if moose are truly spending a majority of their foraging time

at feeding stations A study on the population densities of moose and the increasing population of roe deer

(Capreolus capreolus) would add the factor of competition into the model

The low calf survival on Ӧland is most likely the result of a combination of factors The lack of suitable habitat

reported in this study in conjunction with Malmstenrsquos (2014a) report on the threat of disease (Anaplasma

phagocytophilum) are probable influences on the calf survival on Ӧland On Ӧland there is an increasing

population of roe deer and large numbers of migratory birds both carriers of ticks and diseases The mild

conditions on Ӧland are advantageous for ticks the carriers of A phagocytophilum Fewer snow days and

shorter periods of snow cover along with dry conditions are favourable for ticks This could probably be one

of the reasons for females to be of lower quality and therefore not being able to ensure calf survival Moose

have to utilise areas where in other populations individuals tend to avoid Finally similar to many studies I

advocate further research using a stronger dataset and longer term monitoring

22

Acknowledgements

I am indebted to NJ Singh and A Allen for all their help and guidance through the whole of this study I

thank SLU for the support provided during this study in terms of data finances and facilities Thank you to

everyone at the Department of Wildlife Fish and Environmental Studies for being so friendly and

supportive I would like to thank L Edenius for driving me around the study area and S Michon and H

Khalil for keeping me sane with fika and training

23 References

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tracking data Ecology 741313ndash1325

Albon SD Clutton-Brock TH Guinness FE (1987) Early development and population dynamics in red deer

II density-independent effects and cohort variation Journal of Animal Ecology 5669-81

Bakker JP Bakker ES Roseacuten E Verweij GL Bekker RM (1996) Soil seed bank composition along a

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Ball JP Ericsson G Wallin K (1999) Climate change moose and their human predators Ecological

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Bartmann RM White GC Carpenter LH (1992) Compensatory mortality in a Colorado mule deer

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Baringrdsen BJ Fauchald P Tveraa T Langeland K Yoccoz NG Ims RA (2008) Experimental evidence of

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Belovsky GE Jordan PA (1981) Sodium dynamics and adaptations of moose population American Society

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Benhamou S Corneacutelis D (2010) Incorporating movement behaviour and barriers to improve kernel home

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Benhamou S (2011) Dynamics approach to space and habitat use based on biased random bridges PLOS

One 61-8

Bewick V Cheek L Ball J (2004) Statistics review 12 Survival analysis Critical Care 8(5)389-394

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Bischof R Loe LE Meisingset EL Zimmermann B Van Moorter B Mysterud A (2012) A migratory

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Erikson R Astrup R (2011) Moose Alces alces habitat use at multiple temporal scales in a

human altered landscape Wildlife Biology 1744-54

Boman M Matsson L Ericsson G Kristroumlm B (2011) Moose hunting values in Sweden now and two

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530

Bradshaw RHW Hannon GE Lister AM (2003) A long-term perspective on ungulate-vegetation

interactions Forest Ecology and Management 181267-280

Brandin E (2009) Versions of lsquowildrsquo and the importance of fences in Swedish wildlife tourism involving

moose Current Issues in Tourism 12413-427

Burt WH (1943) Territoriality and home range concepts as applied to mammals Journal of Mammalogy

24346-352

24

Bunnefeld N Boumlrger L van Moorter B Rolandsen CM Dettki H Solberg EJ Ericsson G(2011) A model-

driven approach to quantify migration patterns individual regional and yearly differences

Journal of Animal Ecology 80466-476

Brown G (2011) Patterns and causes of demographic variation in a harvested moose population evidence for

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Calenge C (2006) The package adehabitat for the R software a tool for the analysis of space and habitat use

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Calenge C (2011) Home Range Estimation in R the adehabitatHR package Office national de la classe et de

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Cederlund GN Nystroumlm A (1981) Seasonal differences between moose and roe deer in ability to digest

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Cederlund GN Okarma H (1988) Home range and habitat use of adult female moose Journal of Wildlife

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Cederlund GN (1989) Activity patterns in moose and roe deer in a north boreal forest Holarctic Ecology

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Cederlund GN Sand H (1994) Home-range size in relation to age and sex in moose American Society of

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Clutton-Brock T Sheldon BC (2010) Individuals and populations the role of long-term individual based

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Cooke SJ Hinch SG Wikelski M Andrews RD Kuchel LJ Wolcott TG Butler PJ (2004) Biotelemerty a

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Crecircte M Courtois R (1997) Limiting factors might obscure population regulation of moose (Cervidae Alces

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Sedetalia) on the island of Ӧland (Sweden) in the context of north and central Europe

Phytocoenologia 36343-391

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Dussault C Courtois R Ouellet JP (2006) A habitat suitability index model to assess moose habitat selection

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Ericsson G Wallin K Ball JP Broberg M (2001) Age-related reproductive effort and senescence in free-

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Ericsson G Ball JP Danell K (2002) Moose offspring body mass along an altitudinal gradient Journal of

Wildlife Management 55(1)91-97

Ericsson G Malmsten J Neumann W Singh NJ Dali AM Submitted Summer Calf Survival of

Scandinavian Moose along its Southern Distribution Range

25 Festa-Bianchet M Gaillard JM Jorgenson JT (1998) Mass and density-dependent reproductive success and

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Gaillard JM Festa-Bianchet M Yoccoz NG Loison A Toiumlgo C (2000a) Temporal variation in fitness

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Gaillard JM Festa-Bianchet M Delorme D Jorgenson J (2000b) Body mass and individual fitness in female

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Transactions of the Royal Society B 3652255-2265

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Gordon IJ Hester AJ Festa-Bianchet M (2004) Review The management of wild large herbivores to meet

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1031

Hagner O Nilsson M Reese H Egberth M Olsson H (2005) Procedure for classification of forests for

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Horne JS Garton ED Krone SM Lewis JS (2007) Analysing animal movements using Brownian bridges

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Hornok S Kovaacutets D Csoumlrgo T Meli M Goumlnczi E Hadnagy Z Takaacutecs N Farkas R Hofmann-Lehmann R

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Kaplan EL Meier P (1958) Nonparametric estimation from incomplete observation Journal of the American

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Kie JG Matthiopolos J Fieberg J Powell RA Cagnacci F Mitchell SM Gaillard JM Moorcroft PR (2010)

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Kranstauber B Kays R LaPoint SD Wikelski M Safi K (2012) A dynamic Brownian bridge movement

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27

Malmsten J Wideacuten DG Rydevik G Yon L Hutchings MR Thulin CG Soumlderquist L Aspan A Stuen S

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Malmsten J Soumlderquist L Thulin C Wideacuten DG Yon L Hutchings MR Dalin A (2014b) Reproductive

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28

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29

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30

Appendix A

Introduction

Fig 1 Summary chart of factors affecting the life history and therefore the long term fitness of a population

Fig 2 Summary chart 2

Movement

Habitat

Climate

Topography

Competition

FoodWater

Disease

Die

Survive

Reproduce

Population long term fitness

31 Appendix B

Method and Materials

Fig 1 Summary of processes

32

Fig 2 Examples of classical kernel home range output and Brownian bridge kernel home range (Calenge 2011) The

right image includes the area between relocations ie the movement path in contrast to the classic kernel home range

in the left image

33 Appendix C

Home ranges

Fig 1 Example of a non-migratory (ID006) individuals BRB kernel area From top left annual growing and winter

season UD50 (black contour) and UD95 (red contour)

Fig 2 Example of a migratory (ID012) individuals BRB kernel area From the left annual growing and winter season

UD50 (black contour) and UD95 (red contour)

34

Table 1 Annual and seasonal UD50 and UD95 areas (ha) for all individuals

ID Annual GS WS

UD50 UD95 UD50 UD95 UD50 UD95

ID004 190 924 93 531 173 941

ID005 230 1364 132 945 72 682

ID006 162 1036 89 736 70 611

ID008 277 1536 156 809 78 738

ID009 137 834 48 295 126 653

ID010 114 682 83 448 96 488

ID012 177 963 123 544 76 545

ID014 160 1018 87 575 89 662

ID015 172 858 128 532 109 679

ID016 156 1047 65 455 92 534

ID017 153 1088 149 1043 69 349

ID019 279 1097 176 911 163 824

ID020 139 1084 67 349 160 794

ID022 159 811 131 638 61 454

ID023 187 1061 147 771 72 705

ID024 146 725 165 705 101 458

ID026 142 605 99 442 125 547

ID027 126 567 75 461 48 277

35 Appendix D

Activity

Fig 1 Mean daily movement during the study period GS 23-April-2012 to 07-Nov-2012 WS 08-Nov-2012 to

22-April-2013 (number indicates month)

Fig 2 Mean daily movement in the centre and south during the GS and WS

36

Appendix E

Habitat Proportions

Fig 1 All individualsrsquo seasonal habitat proportions within the UD95

37 Habitat Selection

Table 1 Simplified ranking matrices comparing proportional habitat use within the second order (UD95Area) with

proportions of total available habitat types Mean value on the matrix was replaced by a sign a triple sign represents

significant deviation from random at P lt05 Highlighted habitat is ranked 1st

North A

gri

cult

ure

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 --- --- - +++ --- --- --- +++ +++ --- 8

Broad Leaf +++ 0 +++ + +++ +++ +++ + +++ +++ +++ 1

Clear Fell +++ --- 0 + +++ - - --- +++ +++ --- 7

Coniferous + - - 0 +++ - - --- +++ +++ - 6

Freshwater --- --- --- --- 0 --- --- --- +++ - --- 10

Grassland

Moors +++ --- + + +++ 0 +++ - +++ +++ + 3

MiresMarshes +++ --- + + +++ --- 0 - +++ +++ --- 5

Mixed +++ - +++ +++ +++ + + 0 +++ +++ + 2

Sparse Veg --- --- --- --- --- --- --- --- 0 --- --- 11

Urban --- --- --- --- + --- --- --- +++ 0 --- 9

Younger +++ --- +++ + +++ - +++ - +++ +++ 0 4

Rank Order and

Significance

Broad Leafgt Mixedgt GrasslandMoorsgt Youngergtgtgt MiresMarshesgt Coniferousgt

Clear Fellgtgtgt Agriculturegtgtgt Urbangt Freshwatergtgtgt Sparse Veg

Central

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 --- --- --- + +++ + --- +++ +++ --- 6

Broad Leaf +++ 0 +++ + +++ +++ + - +++ +++ - 3

Clear Fell +++ --- 0 - +++ +++ + --- +++ +++ --- 5

Coniferous +++ - + 0 +++ +++ + --- +++ +++ - 4

Freshwater - --- --- --- 0 +++ - --- +++ +++ --- 8

Grassland

Moors --- --- --- --- --- 0 --- --- +++ - --- 10

MiresMarshes - - - - + +++ 0 - +++ +++ - 7

Mixed +++ + +++ +++ +++ +++ + 0 +++ +++ + 1

Sparse Veg --- --- --- --- --- --- --- --- 0 - --- 11

Urban --- --- --- --- --- + --- --- + 0 --- 9

Younger +++ + +++ + +++ +++ + - +++ +++ 0 2

Rank Order and

Significance

Mixedgt Youngergt Broad Leafgt Coniferousgt Clear Fellgtgtgt Agriculturegt

MiresMarshesgt Freshwatergtgtgt Urbangt GrasslandMoorsgtgtgt Sparse Veg

38

South

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 + - - + - + +++ +++ +++ - 5

Broad Leaf - 0 - - + - - +++ + +++ - 7

Clear Fell + + 0 - + + + +++ + +++ + 2

Coniferous + + + 0 +++ + + +++ + +++ + 1

Freshwater - - - --- 0 - - + + +++ - 8

Grassland

Moors + + - - + 0 + + +++ + - 4

MiresMarshes - + - - + - 0 +++ + +++ - 6

Mixed --- --- --- --- - - --- 0 + + --- 10

Sparse Veg --- - - - - --- - - 0 + - 9

Urban --- --- --- --- --- - --- - - 0 --- 11

Younger + + - - + + + +++ + +++ 0 3

Rank Order

and

Significance

Coniferousgt Clear Fellgt Youngergt GrasslandMoorsgt Agriculturegt MiresMarshesgt Broad Leafgt

Freshwatergt Sparse Veggt Mixedgt Urban

Table 2 Simplified ranking matrices comparing proportional habitat use within the third order (UD50UD95) with

proportions of total available habitat types Mean value on the matrix was replaced by a sign a triple sign represents

significant deviation from random at P lt05 Highlighted habitat is ranked 1st

North

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 --- --- --- - + --- --- + +++ --- 8

Broad Leaf +++ 0 +++ + + + + + +++ +++ + 1

Clear Fell +++ --- 0 + + + - - + +++ - 5

Coniferous +++ - - 0 + + --- --- +++ +++ - 6

Freshwater + - - - 0 +++ - - +++ +++ - 7

GrasslandMoors - - - - --- 0 - - - + - 10

MiresMarshes +++ - + +++ + + 0 - +++ +++ + 3

Mixed +++ - + +++ + + + 0 +++ +++ + 2

Sparse Veg - --- - --- --- + --- --- 0 +++ --- 9

Urban --- --- --- --- --- - --- --- --- 0 --- 11

Younger +++ - + + + + - - +++ +++ 0 4

Rank Order and

Significance

Broad Leafgt Mixedgt MiresMarshesgt Youngergt Clear Fellgt Coniferousgt Freshwatergt

Agriculturegt Sparse Veggt GrasslandMoorsgt Urban

39

Central

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 --- --- + + - - - + +++ --- 7

Broad Leaf +++ 0 + +++ + + + + + +++ - 2

Clear Fell +++ - 0 +++ + + + + + +++ - 3

Coniferous - --- --- 0 + - - --- +++ + --- 8

Freshwater - - - - 0 --- - - --- - - 11

GrasslandMoors + - - + +++ 0 + - + +++ - 5

MiresMarshes + - - + + - 0 + + +++ - 6

Mixed + - - +++ + + - 0 +++ +++ - 4

Sparse Veg - - - --- +++ - - --- 0 +++ - 9

Urban --- --- --- - + --- --- --- --- 0 --- 10

Younger +++ + + +++ + + + + + +++ 0 1

Rank Order and

Significance

Youngergt Broad Leafgt Clear Fellgt Mixedgt GrasslandMoorsgt MiresMarshesgt

Agriculturegt Coniferousgtgtgt Sparse Veggtgtgt Urbangt Freshwater

South

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 - - - - - + - +++ + --- 8

Broad Leaf + 0 - --- + - + - +++ + - 6

Clear Fell + + 0 - + - + - +++ + - 4

Coniferous + +++ + 0 + + +++ + +++ + + 1

Freshwater + - - - 0 - - + + + - 7

GrasslandMoors + + + - + 0 + + + + - 3

MiresMarshes - - - --- + - 0 - + + - 9

Mixed + + + - - - + 0 + + - 5

Sparse Veg --- --- --- --- - - - - 0 + --- 10

Urban - - - - - - - - - 0 - 11

Younger +++ + + - + + + + +++ + 0 2

Rank Order and

Significance

Coniferousgt Youngergt GrasslandMoorsgt Clear Fellgt Mixedgt Broad Leafgt Freshwatergt

Agriculturegt MiresMarshesgt Sparse Veggt Urban

40

Table 3 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the GS according to Jacobs index

Ran

k North Centre South

50 95 50 95 50 95

+ - + - + - + - + - + -

1 Broad

Leaf Urban Broad Leaf Sparse Veg

Broad

Leaf Urban Mixed Urban Coniferous Urban

Grassland

Moors Urban

2 Mixed Sparse Veg Mixed Freshwater Younger Agriculture Younger Sparse Veg Younger Sparse Veg Clear Fell Mixed

3 Mires

Agriculture Grassland

Urban Clear

Fell Coniferous Broad Leaf

Grassland

Moors

Clear Fell Agriculture Coniferous Sparse Veg

Marshes Moors

4 Younger Grassland

Younger Agriculture

Freshwater Coniferous Freshwater

Broad Leaf Mires

Younger Freshwater

Moors Marshes

5 Clear

Fell Freshwater

Mires Coniferous

Sparse Veg Clear Fell Agriculture

Freshwater Agriculture

Marshes

6 Coniferous Clear Fell

Mires

Marshes

Mires

Grassland

Moors

Mires

Marshes Marshes

7 Mixed Mixed Broad Leaf

8 Grassland

Moors

41

Table 4 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the WS according to Jacobs index

Ran

k North Centre South

50 95 50 95 50 95

+ - + - + - + - + - + -

1 Mires

Marshes

Grassland

Moors Mixed Freshwater Agriculture Urban Mixed Freshwater

Grassland

Moors Urban GrasslandMoors Urban

2 Freshwater Mixed Coniferous Urban Mires

Marshes Coniferous Sparse Veg Agriculture

Sparse

Veg Coniferous Freshwater

3 Urban Coniferous Younger Grassland

Moors Freshwater Younger Urban Freshwater

Broad

Leaf Agriculture Mixed

4 Younger Agriculture Sparse Veg Broad

Leaf

Broad

Leaf

Grassland

Moors Mixed Broad Leaf

5 Clear Fell Agriculture Coniferous Agriculture Mires

Marshes Clear Fell

6 Sparse

Veg

Mires

Marshes Mixed

Mires

Marshes

Clear

Fell

Mires

Marshes

7 Broad

Leaf Clear Fell Younger Clear Fell Younger Sparse Veg

8 Clear Fell Younger

9 Sparse

Veg

10 Grassland

Moors

42

Table 5 Second order (UD95Area) individual selectionavoidance for the GS and WS according to the Jacobs index

ID GS WS

Select Avoid Select Avoid

ID004 Younger Sparsely Vegetated MiresMarshes Sparsely Vegetated

ID005 MiresMarshes Sparsely Vegetated Coniferous GrasslandMoors

ID006 Coniferous Sparsely Vegetated Mixed Freshwater

ID008 Mixed Sparsely Vegetated Mixed Freshwater

ID009 Mixed Sparsely Vegetated Mixed GrasslandMoors

ID010 MiresMarshes Freshwater GrasslandMoors Freshwater

ID012 Broad Leaf Sparsely Vegetated Coniferous Urban

ID014 Clear Fell Sparsely Vegetated GrasslandMoors Sparsely Vegetated

ID015 GrasslandMoors Urban GrasslandMoors Freshwater

ID016 GrasslandMoors Freshwater GrasslandMoors Freshwater

ID017 GrasslandMoors Mixed Sparsely Vegetated Mixed

ID019 Mixed Sparsely Vegetated Mixed Urban

ID020 Broad Leaf Sparsely Vegetated Coniferous GrasslandMoors

ID022 MiresMarshes Freshwater MiresMarshes Freshwater

ID023 MiresMarshes GrasslandMoors Mixed Freshwater

ID024 Broadleaf Urban Broad Leaf Urban

ID026 GrasslandMoors Freshwater GrasslandMoors Freshwater

ID027 GrasslandMoors Urban Sparsely Vegetated Freshwater

43 Table 6 Third order (UD50UD95) individual selectionavoidance for the GS and WS according to the Jacobs index

ID GS WS

Select Avoid Select Avoid

ID004 Broad Leaf Mixed GrasslandMoors Freshwater

ID005 Broad Leaf Freshwater Agriculture Freshwater

ID006 Clear Fell Freshwater Agriculture MiresMarshes

ID008 MiresMarshes Freshwater Agriculture Urban

ID009 Freshwater Agriculture Agriculture Freshwater

ID010 Mixed Urban Sparsely Vegetated Urban

ID012 Coniferous GrasslandMoors Freshwater Urban

ID014 Urban Agriculture Freshwater Urban

ID015 Mixed Forest Urban Clear Fell Urban

ID016 Freshwater Urban GrasslandMoors Mixed

ID017 Coniferous Mixed Coniferous Broad Leaf

ID019 Broad Leaf GrasslandMoors Urban GrasslandMoors

ID020 Freshwater Urban Freshwater Agriculture

ID022 MiresMarshes Urban Broad Leaf GrasslandMoors

ID023 Freshwater Mixed Agriculture Freshwater

ID024 Mixed Freshwater Mixed Freshwater

ID026 Mixed MiresMarshes Sparsely Vegetated GrasslandMoors

ID027 Freshwater MiresMarshes GrasslandMoors Broad Leaf

44

Fig 2 North third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)

45

Fig 3 Centre third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)

46

Fig 4 South third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)

47

Fig 5 North second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)

48

Fig 6 Centre second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)

49

Fig 7 South second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)

50

Appendix F

Background

Fig 1 Daily mean snow depth and duration during the study period (Andrew Allen)

Female Moose Reproduction

Moose are seasonal polyoestral mammals (Monfort et al 1993) coming into oestrus during late September

early October (Garel et al 2009) The Swedish moose cow population reaches puberty between the ages 25

and 35 (Sand and Cederlund 1993) during which the reproductive period begins with the onset of ovulation

The age an individual reaches puberty is dependent on their body condition they have to reach a weight

threshold to reach puberty and become reproductive (Sand 1996) If she is over the weight threshold she will

go into oestrus in the autumn If she does not reach the weight threshold then she will go into oestrus the

following autumn if successful she will give birth to individual or twin calves in late May to early June

(Ericsson et al 2001) and therefore reach sexual maturity (Malmsten et al 2014b) Fecundity is related to

both the condition and the age of the cow Cows go through senescence at 12 years of age (Ericsson et al

2001) Providing calves with the required level of nutrition demands high energy and protein resources from

the mother during senescence this becomes harder to achieve leading to decreased levels of parental care

and higher levels of calf mortality

Page 10: Habitat-performance relationships on an island: fitness ...navinderjsingh.weebly.com/uploads/1/1/2/2/11224342/... · Conditions on Öland are milder than those found in other areas

10

all home ranges contained them This combined approach allowed identification of habitats that are used

disproportionally to their availability ie in a non-random manner (Beyer et al 2010) This is an indication of

which habitats are important for an individual

119863 = ( 119903minus119901

119903+119901minus2119903119901 ) (eqn1)

r = Proportion of habitat type used

p = Total proportion of habitat available

D = Jacobs index varies from -1 (strong avoidance) to +1 (strong preference) with values close to 0 indicating

the habitat is used in proportion to its availability

Activity

Activity level is measured as the mean daily movement (MDM) by the individual to investigate if individuals

in an areaseason moved more and hence were more active than those in other areasseasons Unfortunately

only two cows were collared in the north and were therefore left out of this analysis Moose were identified as

migratory using a modelling approach (see Bunnefeld et al 2011 for methods) Migratory individuals were

initially removed from the activity analysis (n=4)The reason is that both migratory journeys were completed

during the winter season thus increasing the mean daily distance travelled and potentially biasing the analysis

One individual was also removed due it its collar not returning relocations during the entirety of the WS

Diet analysis

The Ӧland project team conducted histology diet analysis on the rumen content of five individuals that were

shot in the centre and south of the island during the WS of 2013

Survival analysis

The Ӧland project team measured calf survival using the mark-resight method The presenceabsence of a calf

was recorded by tracking the cows at six occasions throughout the year These were at the start of the calving

season (mid-May to early June) twice through the summer before the hunt after the hunt and after winter

Survival trend was estimated using a Kaplan-Meier curve (Kaplan and Meier 1958) The Kaplan-Meier curve

shows the survival function (S (t)) ie the probability of an individual surviving until at least time t (Bewick

et al 2004) The probability of surviving from one period to the next is multiplied together to give the survival

function The S(t) of this study is the probability of an individual surviving from birth to after the hunt

(Method summary see appendix B)

11 Results

Home RangeUtilization Distribution

A total of 51 home ranges were estimated (17 annual 17 within growing season 17 within winter season)

Annual x = 9613 ha GS x = 6345 ha and WS x = 6023 ha (appendix C)

At the UD50 scale the largest annual and seasonal mean home ranges were located in the north Mean annual

and seasonal home ranges in the centre were slightly larger than the south This difference was not significant

(F(113)= 22 p= 87) (ANOVA) There was no significant difference between the seasonal home ranges (x

plusmnSD for GS = 116 plusmn38 for WS = 98 plusmn32 ha) (t(11) = 105 p = 32) or the seasonal home ranges in the centre

(t(8) = 101 p = 34 and the south (t(5) = 87 p = 42) (paired-sample t-test) (Table 1)

At the UD95 scale the largest annual and WS mean home ranges were located in the north The largest GS

mean home ranges were located in the centre Mean annual and seasonal home ranges in the centre were

slightly larger than the south This difference was not significant (F(113) = 59 p = 63) (ANOVA) There

was no significant difference between the seasonal home ranges (x plusmnSD for GS = 635 plusmn225 for WS = 602

plusmn161) (t(11) = 373 p = 71) or the seasonal home ranges in the centre (t(8)= 20 p = 84) or south (t(5) = 34

p = 74) (paired-sample t-test) (Table 1)

Table 1 Seasonal and annual mean UD50 and UD95 BRB kernel area in hectares (1ha = 001km2) for the north centre

and south of Oumlland (smoothing factor (h) =100)

Are

a

Annual UD50 GS UD50 WS UD50

n Mean SD Range n Mean SD Range n Mean SD Range

N 2 209 49 139-279 2 1215 39 67-176 2 1615 106 160-163

C 9 178 56 114-277 9 116 44 48-165 9 943 4 61-173

S 6 160 21 142-177 6 1085 51 65-149 6 933 35 69-125

Annual UD95 GS UD95 WS UD95

N 2 10905 5 1084-1097 2 630 199 349-911 2 809 11 794-824

C 9 997 32 682-1536 9 6531 22 295-945 9 637 17 454-941

S 6 9298 30 605-1088 6 5985 373 442-575 6 5526 20 349-679

12

Activity

MDM rates in the three areas (sedentary individuals) during the GS ranged from 14 ndash31 km day During the

WS ranged they ranged from 11-24 km day (Table 2) Movement rates during the GS were higher than the

WS (x plusmnSD for GS = 202 plusmn043 for WS = 161 plusmn043) but it was not statistically significant (t(11) = 200 p=

07) (paired sample t-test)

Table 2 Seasonal mean daily movement rates (km day) for each area and for both areas (total)

Are

a

GS WS

n Mean SE Range n Mean SE Range

C 8 20 003 14-18 8 20 004 12-24

S 4 22 016 17-31 4 12 02 11-13

Total 12 202 003 14-31 12 16 003 11-24

The seasonal MDM rates of all individuals (migratory and sedentary) were not significantly different (x plusmnSD

for GS = 20 plusmn04 for WS = 18 plusmn061) (t(14) = 139 p= 19) (paired sample t-test)

The WS home range size affects the WS MDM (F(110) = 927 p = 01) (ANOVA) The GS home range size

does not affect the GS MDM (F(110) = 36 p = 56) (ANOVA) When the WS home range outlier was

removed the home range size did not affect the WS MDM (F(111) = 186 p= 19) (ANOVA) The MDM was

lowest in February and highest in April (Table 3) there appeared to be no significant pattern in MDM between

the months (appendix D)

Table 3 Mean daily distance moved (km day) for sedentary individuals

Month Season Distance

April GS 0051

May GS 0044

June GS 0039

July GS 0041

August GS 0042

September GS 0044

October GS 0043

November WS 0043

December WS 0038

January WS 0035

February WS 0028

13 Habitat ndash Proportions

The largest proportion of habitat on the island is agriculture the lowest proportion of habitat (excluding coastal

and freshwater) is urban areas (Fig 2) The largest proportion of habitat in the north was coniferous forests

whilst agricultural areas were the dominant habitat types in the centre and south (Fig 3) The lowest proportion

(excluding coastal and freshwater areas) was urban

Fig 2 Proportion of different types of habitats found on Ӧland

Fig 3 Mean proportion of habitats contained within UD95 in the three areas of Oumlland C = Centre N = North S =

South

14

Habitat - Selection

Generally forest habitat types are the highest ranked whilst sparsely vegetated and urban areas are the lowest

ranked Both the second and third order habitat selection analyses gave significant results in the compositional

analysis (Table 4) In the third order analysis (UD50UD95) the centre displayed significant differences

between habitat types The coniferous forests are significantly preferred to sparsely vegetated areas and the

sparsely vegetated areas are significantly preferred to urban areas In the second order analysis (UD95Area)

significance was observed in the north and centre In the north younger forests are significantly preferred to

miresmarshes clear felled areas are significantly preferred to agriculture and freshwater areas are significantly

preferred to sparsely vegetated areas In the centre clear felled areas are significantly preferred to agricultural

land freshwater areas are significantly preferred to urban areas and grasslandmoors are significantly preferred

to sparsely vegetated areas

Table 4 Summary of second (UD95Area bottom) and third order (UD50UD95 top) ranked habitat preferences between

the three areas according to the compositional analysis (see appendix B)

Rank North Centre South

1 Broad Leaf Younger Coniferous

2 Mixed Broad Leaf Younger

3 MiresMarshes Clear Fell GrasslandMoors

4 Younger Mixed Clear Fell

5 Clear Fell GrasslandMoors Mixed

6 Coniferous MiresMarshes Broad Leaf

7 Freshwater Agriculture Freshwater

8 Agriculture Coniferous Agriculture

9 Sparse Veg Sparse Veg MiresMarshes

10 GrasslandMoors Urban Sparse Veg

11 Urban Freshwater Urban

Rank North Centre South

1 Broad Leaf Mixed Coniferous

2 Mixed Younger Clear Fell

3 GrasslandMoors Broad Leaf Younger

4 Younger Coniferous GrasslandMoors

5 MiresMarshes Clear Fell Agriculture

6 Coniferous Agriculture MiresMarshes

7 Clear Fell MiresMarshes Broad Leaf

8 Agriculture Freshwater Freshwater

9 Urban Urban Sparse Veg

10 Freshwater GrasslandMoors Mixed

11 Sparse Veg Sparse Veg Urban

Indicates significantly preferred to the habitat below (significant deviation from random at P lt05)

15 The Jacobs index revealed that generally the habitats preferred during the GS within the home range (third

order) are younger (0187) and broad leaf forests (0154) The strongest avoidance was for urban areas (-0627)

During the WS only agricultural areas are preferred (0129) and the strongest avoidance was for urban areas (-

0393) (Fig 4)

Fig 4 Third order seasonal habitat preference (UD50UD95) all individuals The index ranges from -1 (total avoidance)

to 1 (strongest preference) Close to 0 indicates used in proportion to its availability

Third order habitat preferencesavoidances by area

North During the GS the strongest preference was for broad leaf (0218) and mixed forests (0161) The

strongest avoidance was for urban (-1) and sparsely vegetated areas (-05) During the WS the strongest

preference was for miresmarshes (0228) The strongest avoidance was for grasslandmoors (-05)

Centre During the GS the strongest preference was for broad leaf (0233) and younger forests (0223) The

strongest avoidance was for urban (-0527) and agricultural land (-0362) During the WS preference was only

shown for agricultural land (0327) The strongest avoidance was for urban areas (-0679) and miresmarshes

(-0638)

South During the GS the strongest preference was for coniferous (0312) and younger forests (0242) The

strongest avoidance was for urban (-0353) and sparsely vegetated areas (-0330) During the WS

grasslandmoors (0106) were the strongest preference The strongest avoidance was for urban (-0666) and

sparsely vegetated areas (-0351)

16

The Jacobs indices revealed that generally the habitats preferred during the GS within the landscape

(UD95Area) are broad leaf (0216) and younger forests (0201) The strongest avoidance was for urban (-

0717) and freshwater areas (-0694) The strongest preference during the WS are coniferous forests (0242)

and the strongest avoidance was for freshwater (-0674) and urban areas (-0648) (Fig 5)

Fig 5 Second order seasonal habitat preference (UD50UD95) all individuals The index ranges from -1 (total avoidance)

to 1 (strongest preference) Close to 0 indicates used in proportion to its availability

Second order habitat preferencesavoidances by area

North During the GS the strongest preference was for broad leaf (0363) and mixed forests (00291) The

strongest avoidance was for sparsely vegetated (-0909) and freshwater areas (-0780) During the WS mixed

(0335) and coniferous forests (0316) were the strongest preference The strongest avoidance was for

freshwater (-0731) and urban areas (-05333)

Centre During the GS the strongest preference for mixed (0394) and younger forests (0286) The strongest

avoidance was for urban (-0733) and sparsely vegetated (-0708) areas During the WS mixed (0404) and

coniferous forests (0255) were the strongest preference The strongest avoidance was for freshwater (-0704)

and sparsely vegetated areas (-0655)

South During the GS the strongest preference for grasslandmoors (0287) and clear fells (0165) The

strongest avoidance was for urban areas (-0678) and mixed forests (-0491) During the WS grasslandmoors

(0425) and coniferous forests (0154) were the strongest preference The strongest avoidance was for urban (-

0876) and freshwater areas (-0587) (appendix E)

17 Diet

Diet analysis of the rumen content sampled from five individuals (C=2 S=3) revealed that almost two thirds

(69) of the diet is comprised of agricultural produce (apple winter rape and sugar beet) (Fig 6)

Fig 6 Diet analysis from the rumen samples of five moose individuals that were culled in 2013

31

2117

9

8

5

22

1 1

1

1

1 00 0

0

0Diet (2610-911 2013 5 individuals)

AppleWinter RapeSugar BeetUndefined WoodSallowBroad-leaf GrassPineAshOakCloverCurrantsUndefined plantElderberryJuniperRaspberry

18

Calf Survival

Of the 18 individuals 13 produced calves in which 7 produced twins giving a total of 20 calves A Kaplan-

Meier estimate was conducted to measure the fraction of calves living up to each period of the study (Fig 7)

The mean survival time is until period 235 (midend of summer) At the start of summer 85 of calves

remained (3 still born) The period between summer and before the hunt survival drops to 30 The survival

at the end of the study (after hunt) drops further to 20 leaving 4 calves surviving (see appendix B)

Fig 7 Kaplan-Meier estimate of moose calf survival during the study period Period 0 (Start of summer) period 1

(midend of summer) period 2 (before hunt) period 3 (after hunt) period 4 (after winter)

19 Discussion

The results of this study emphasised how strikingly different the habitat composition is along the latitudinal

gradient of Oumlland The three areas show contrasting proportions of the key habitat types The starkest

difference is the high proportion of coniferous forests and lack of agriculture in the north compared to the

centre and south The proportion of coniferous forest in the north is almost 5 times greater than in the centre

and south whereas the proportion of agriculture in the centre and south is more than double that in the north

The north is perceived to be composed of the most suitable habitat for moose (Dussault et al 2006) It has the

largest proportions of each forest type and a low proportion of agricultural land This provides suitable forage

and shelter throughout the year The south has a contrasting habitat composition to the north The proportions

of agricultural and sparsely vegetated areas are the highest between the three areas and the proportions of forest

habitats are the lowest The large proportion of sparsely vegetated areas and low proportions of forest habitat

corresponds to the large area of Stora Alvaret This is perceived to be the least suitable area due to a lack of

shelter (coniferous forest) and suitable forage The strong preference for coniferous and younger forest habitats

in the south would suggest that moose exhibit a functional response in habitat selection (Godvik et al 2009)

ie as the proportion of a particular habitat decreases the selection for that habitat increases in this case

coniferous forests which provide shelter and younger forest which provide good forage Similarly in the centre

moose show strong preference for mixed forests a habitat that is of low proportion

In view of the large variation in habitat proportions between the areas it is surprising that there is not a large

variation in the home range sizes or the activity levels annually or seasonally Home ranges are ultimately

chosen to maximise fitness and meet energy requirements by utilizing the available forage Seasonal conditions

change the availability and necessity of resources (food quality shelter) Unlike the GS during the WS

deciduous trees and shrubs are leafless and low-lying shrubs are under snow cover (Dussault et al 2005)

These changes are well known to cause populations to alter their activity and home ranges to meet energy

requirements (Mysterud et al 2001) Populations have been shown to increase or decrease their home ranges

during the two seasons The GS home ranges are often larger than the WS home ranges (Philips et al 1973

Mysterud et al 2001) In some cases they can be found to be almost double the size of the WS home ranges

(Cederlund and Okarma 1988) In other populations the WS home ranges are double the size of the GS home

ranges (Lynch and Morgantini 1984) or sizes do not significantly differ (Cederlund and Sand 1994)

Previous studies on moose find females generally show increased activity from the start on the GS due to

various factors eg reduced ruminating times increased metabolic needs and increased foraging bursts

(Wattles and DeStefano 2013) Increased metabolic needs during this time are a results of pregnancy and

lactation (Georgii 1980) During the height of the GS they usually show reduced activity levels through times

of increased thermal stress (Renecker and Hudson 1989 van Beest et al 2012) During the WS the depth and

the duration of snow cover are well known to affect the activity level (Telfer 1970 Mysterud and Oslashstbye 1999

Bjoslashrneraas et al 2011) During the WS generally home ranges are smaller and activity less due to lower

metabolic needs Moose activity is constrained by rumination during the WS this period is known to be longer

due to the change in diet (Cederlund 1989 Renecker Hudson 1989) This was not the case on Ӧland activity

20

was lowest in February which is a similar result to Cederlundrsquos (1989) paper However Ӧland moose did not

significantly alter their seasonal activity levels The fact that the annual and seasonal activity levels and home

ranges were similar could be a result of the mild winters on Oumlland during the study period (Smhise 2014)

During the study period the average number of snow days was 80 and the mean snow depth was 10cm

(appendix F) (Swedish Meterological and Hydrological Institute- SMHI) These mild conditions do not restrict

the movement of moose or obscure forage Moose are well adapted for movement in deep snow depths of 60-

86cm (Prescott 1968) are needed to truly restrict movement This finding was similar to the Sweanor and

Sandegren (1989) and Cederlund and Sand (1994) where the snow depth at their sites did not reach movement

restricting depths

The survival curve illustrates just how bad the calf survival is on Ӧland Survival falls from 85 at the start to

20 Out of 20 calves only four were alive at the end of the study The sharpest fall in survival was the period

between end of summer and before the hunt so the deaths were not due to hunting Previous calf autopsies

(Malmsten 2014a) have shown that cause of death was starvation mothers possibly either did not have milk

the calf was unable to feed or the mother abandoned the calf Closer field based observations are needed to

attain this knowledge Moose are seasonal polyoestral mammals (Monfort et al 1993) coming into oestrus

during late September early October (Garel et al 2009) (appendix F) The diet of the mother influences the

health of the calf and this period is when sodium is hard to find sodium is a key mineral in moose diets for

features such as reproduction (Belovsky and Jordan 1981) Moose gain sodium mainly through aquatic plants

(MacCracken et al 1993) However the compositional analysis shows that freshwater areas are often ranked

as one of the lowest used habitats and coastal areas were removed as the proportion found in the home ranges

was extremely low The Jacobs Index shows that the moose only prefer freshwater areas in the north UD50

during the WS The north individuals again are those that are showing typical moose habitat selection

It is known that habitat selection is hierarchical with habitats that increase fitness selected for and the effects

of limiting factors are reduced (Rettie and Messier 2000) At the UD95 during the GS moose preferred areas

of good forage (forests) and avoided areas of low forage (freshwater and sparsely vegetated areas) and areas

close to humans (urban) This is consistent with other reports (Laurian et al 2008 Torres et al 2011) Within

the UD50 there is a shift in preferences The good forage areas are again preferred during the GS however

during WS the only preferred habitat is often agricultural land During the WS there could be a steady supply

of supplementary feed available hence the high levels of agricultural produce found in the rumen content

samples and the high preference of agricultural areas This diet is unusual for moose previous studies of

Swedish moose diet have found the GS diet was dominated by birch willow and herbaceous plants and the

WS diet dominated by pine and birch (Cederlund and Nystrom 1981) The diet analysis was conducted during

the WS instead of being dominant pine composed just 2 Birch did not appear however unidentified wood

composed only 9 whereas agricultural produce accounted for 69 Supplementary feed may be perceived

by the moose in the centre and south as a vital forage source during the WS In fact in the centre the

agricultural land is the only preferred habitat at the UD50 It is unknown whether there are salt licks provided

in these areas Selection for a critical habitat is often thought to be a fixed factor The Oumlland population from

21 the three areas are close in proximity however they displayed contrasting preferences This is supported by the

Osko et al (2004) report that found two neighbouring moose populations that had access to the same habitats

displayed contrasting preferences Habitat preferences for populations of the same species are not necessarily

fixed They alter with varying levels of habitat abundance and limiting factors skewing what is preserved to

be critical

The main limitation encountered in this study was with the limited sample There was only data on two

individuals from the north of the island which led it being removed from many of the analysis Similarly due

to a lack of relocations from the collars being turned off at points throughout the year two further individuals

had to be removed from a majority of the analysis This reduced the sample size to 17 or 18 individuals

Similarly only 13 of the individuals from the study produced calves This unfortunately prevented including

survival into models Although the sample size was small it was accurate it was of high resolution over

300000 GPS points In future it would be beneficial to have a more standardised data set An equal sample of

individuals from the three areas would be advised along with ensuring the GPS collars are kept turned on for

the entirety of the growing and winter season to allow comparisons between years It would also be

advantageous to collect coordinates of the feeding sites along with the composition This could then be

compared with high use UD coordinates to look if moose are truly spending a majority of their foraging time

at feeding stations A study on the population densities of moose and the increasing population of roe deer

(Capreolus capreolus) would add the factor of competition into the model

The low calf survival on Ӧland is most likely the result of a combination of factors The lack of suitable habitat

reported in this study in conjunction with Malmstenrsquos (2014a) report on the threat of disease (Anaplasma

phagocytophilum) are probable influences on the calf survival on Ӧland On Ӧland there is an increasing

population of roe deer and large numbers of migratory birds both carriers of ticks and diseases The mild

conditions on Ӧland are advantageous for ticks the carriers of A phagocytophilum Fewer snow days and

shorter periods of snow cover along with dry conditions are favourable for ticks This could probably be one

of the reasons for females to be of lower quality and therefore not being able to ensure calf survival Moose

have to utilise areas where in other populations individuals tend to avoid Finally similar to many studies I

advocate further research using a stronger dataset and longer term monitoring

22

Acknowledgements

I am indebted to NJ Singh and A Allen for all their help and guidance through the whole of this study I

thank SLU for the support provided during this study in terms of data finances and facilities Thank you to

everyone at the Department of Wildlife Fish and Environmental Studies for being so friendly and

supportive I would like to thank L Edenius for driving me around the study area and S Michon and H

Khalil for keeping me sane with fika and training

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Forchhammer MC Post E Stenseth NC Boertmann DM (2002) Long-term responses in arctic ungulate

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Gaillard JM Festa-Bianchet M Yoccoz NG (1998) Population dynamics of large herbivores variable

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Gaillard JM Festa-Bianchet M Yoccoz NG Loison A Toiumlgo C (2000a) Temporal variation in fitness

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Gaillard JM Festa-Bianchet M Delorme D Jorgenson J (2000b) Body mass and individual fitness in female

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Gaillard JM Hearingblewhite M Loison A Fuller M Powell R Basille M van Moorter B (2010) Habitat-

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Transactions of the Royal Society B 3652255-2265

Garel M Solberg EJ Sӕther B-E Groslashtan V Tufto J Heim M (2009) Age size and spatiotemporal variation

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Georgii B (1980) Home range patterns of female red deer (Cervus elaphus L) in the Alps Oecologia

47278-285

Godvik IMR Loe LE Vik JO Veiberg V Langvatn R Mysterud A (2009) Temporal scales trade-offs and

functional responses in red deer habitat selection Ecology 90699ndash710

Gordon IJ Hester AJ Festa-Bianchet M (2004) Review The management of wild large herbivores to meet

economic conservation and environmental objectives Journal of Applied Ecology 411021-

1031

Hagner O Nilsson M Reese H Egberth M Olsson H (2005) Procedure for classification of forests for

CORINE land cover in Sweden In Oluić M (ed) New strategies for European remote sensing

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Hall LS Krausman PR Morrison ML (1997) The habitat concept and a plea for standard terminology

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should we do Wildlife Society Bulletin 30634-643

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responses in moose body mass to temporal variation in the environment Journal of Animal

Ecology 75 (5) 1110-1118

Horne JS Garton ED Krone SM Lewis JS (2007) Analysing animal movements using Brownian bridges

Ecological Society of America Ecology 882354-2363

Hornok S Kovaacutets D Csoumlrgo T Meli M Goumlnczi E Hadnagy Z Takaacutecs N Farkas R Hofmann-Lehmann R

(2014) Birds as potential reservoirs of tick-borne pathogens first evidence of bacteraemia

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26

Jacobs J (1974) Quantitative measurement of food selection a modification of the forage ratio and Ivlevrsquos

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Johnson DH (1980) The comparison of usage and availability measurements for evaluating resource

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Jonsson F (2007) rsquoDen oumllaumlndska aringlgstammens foumlrvaltingrsquo Departement of Wildlife Fish and Environmental

Studies SLU Examensarbete I aumlmnet biologi vol 20072

Kaplan EL Meier P (1958) Nonparametric estimation from incomplete observation Journal of the American

Statistical Association 53457-481

Keating KA Cherry S (2009) Modelling utilization distributions in space and time Ecology 90(7)1971-

1980

Kie JG Matthiopolos J Fieberg J Powell RA Cagnacci F Mitchell SM Gaillard JM Moorcroft PR (2010)

The home range concept are traditional estimators still relevant with modern telemetry

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Jaumlgarefoumlrbundet Oumlster-Malma 20092

Kranstauber B Kays R LaPoint SD Wikelski M Safi K (2012) A dynamic Brownian bridge movement

model to estimate utilization distributions for heterogeneous Animal movement Journal of

Animal Ecology 81738-746

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Lavsund S Nygreacuten T Solberg EJ (2003) Status of moose populations and challenges to moose management

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MacCracken JG Ballenberghe VV Peek JM (1993) Use of aquatic plants by moose sodium hunger or

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27

Malmsten J Wideacuten DG Rydevik G Yon L Hutchings MR Thulin CG Soumlderquist L Aspan A Stuen S

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Malmsten J Soumlderquist L Thulin C Wideacuten DG Yon L Hutchings MR Dalin A (2014b) Reproductive

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28

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29

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Wattles DW DeStefano (2013) Space use and movements of moose in Massachusetts Implications for

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success in muskoxen Journal of Zoology 24313-20

30

Appendix A

Introduction

Fig 1 Summary chart of factors affecting the life history and therefore the long term fitness of a population

Fig 2 Summary chart 2

Movement

Habitat

Climate

Topography

Competition

FoodWater

Disease

Die

Survive

Reproduce

Population long term fitness

31 Appendix B

Method and Materials

Fig 1 Summary of processes

32

Fig 2 Examples of classical kernel home range output and Brownian bridge kernel home range (Calenge 2011) The

right image includes the area between relocations ie the movement path in contrast to the classic kernel home range

in the left image

33 Appendix C

Home ranges

Fig 1 Example of a non-migratory (ID006) individuals BRB kernel area From top left annual growing and winter

season UD50 (black contour) and UD95 (red contour)

Fig 2 Example of a migratory (ID012) individuals BRB kernel area From the left annual growing and winter season

UD50 (black contour) and UD95 (red contour)

34

Table 1 Annual and seasonal UD50 and UD95 areas (ha) for all individuals

ID Annual GS WS

UD50 UD95 UD50 UD95 UD50 UD95

ID004 190 924 93 531 173 941

ID005 230 1364 132 945 72 682

ID006 162 1036 89 736 70 611

ID008 277 1536 156 809 78 738

ID009 137 834 48 295 126 653

ID010 114 682 83 448 96 488

ID012 177 963 123 544 76 545

ID014 160 1018 87 575 89 662

ID015 172 858 128 532 109 679

ID016 156 1047 65 455 92 534

ID017 153 1088 149 1043 69 349

ID019 279 1097 176 911 163 824

ID020 139 1084 67 349 160 794

ID022 159 811 131 638 61 454

ID023 187 1061 147 771 72 705

ID024 146 725 165 705 101 458

ID026 142 605 99 442 125 547

ID027 126 567 75 461 48 277

35 Appendix D

Activity

Fig 1 Mean daily movement during the study period GS 23-April-2012 to 07-Nov-2012 WS 08-Nov-2012 to

22-April-2013 (number indicates month)

Fig 2 Mean daily movement in the centre and south during the GS and WS

36

Appendix E

Habitat Proportions

Fig 1 All individualsrsquo seasonal habitat proportions within the UD95

37 Habitat Selection

Table 1 Simplified ranking matrices comparing proportional habitat use within the second order (UD95Area) with

proportions of total available habitat types Mean value on the matrix was replaced by a sign a triple sign represents

significant deviation from random at P lt05 Highlighted habitat is ranked 1st

North A

gri

cult

ure

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 --- --- - +++ --- --- --- +++ +++ --- 8

Broad Leaf +++ 0 +++ + +++ +++ +++ + +++ +++ +++ 1

Clear Fell +++ --- 0 + +++ - - --- +++ +++ --- 7

Coniferous + - - 0 +++ - - --- +++ +++ - 6

Freshwater --- --- --- --- 0 --- --- --- +++ - --- 10

Grassland

Moors +++ --- + + +++ 0 +++ - +++ +++ + 3

MiresMarshes +++ --- + + +++ --- 0 - +++ +++ --- 5

Mixed +++ - +++ +++ +++ + + 0 +++ +++ + 2

Sparse Veg --- --- --- --- --- --- --- --- 0 --- --- 11

Urban --- --- --- --- + --- --- --- +++ 0 --- 9

Younger +++ --- +++ + +++ - +++ - +++ +++ 0 4

Rank Order and

Significance

Broad Leafgt Mixedgt GrasslandMoorsgt Youngergtgtgt MiresMarshesgt Coniferousgt

Clear Fellgtgtgt Agriculturegtgtgt Urbangt Freshwatergtgtgt Sparse Veg

Central

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 --- --- --- + +++ + --- +++ +++ --- 6

Broad Leaf +++ 0 +++ + +++ +++ + - +++ +++ - 3

Clear Fell +++ --- 0 - +++ +++ + --- +++ +++ --- 5

Coniferous +++ - + 0 +++ +++ + --- +++ +++ - 4

Freshwater - --- --- --- 0 +++ - --- +++ +++ --- 8

Grassland

Moors --- --- --- --- --- 0 --- --- +++ - --- 10

MiresMarshes - - - - + +++ 0 - +++ +++ - 7

Mixed +++ + +++ +++ +++ +++ + 0 +++ +++ + 1

Sparse Veg --- --- --- --- --- --- --- --- 0 - --- 11

Urban --- --- --- --- --- + --- --- + 0 --- 9

Younger +++ + +++ + +++ +++ + - +++ +++ 0 2

Rank Order and

Significance

Mixedgt Youngergt Broad Leafgt Coniferousgt Clear Fellgtgtgt Agriculturegt

MiresMarshesgt Freshwatergtgtgt Urbangt GrasslandMoorsgtgtgt Sparse Veg

38

South

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 + - - + - + +++ +++ +++ - 5

Broad Leaf - 0 - - + - - +++ + +++ - 7

Clear Fell + + 0 - + + + +++ + +++ + 2

Coniferous + + + 0 +++ + + +++ + +++ + 1

Freshwater - - - --- 0 - - + + +++ - 8

Grassland

Moors + + - - + 0 + + +++ + - 4

MiresMarshes - + - - + - 0 +++ + +++ - 6

Mixed --- --- --- --- - - --- 0 + + --- 10

Sparse Veg --- - - - - --- - - 0 + - 9

Urban --- --- --- --- --- - --- - - 0 --- 11

Younger + + - - + + + +++ + +++ 0 3

Rank Order

and

Significance

Coniferousgt Clear Fellgt Youngergt GrasslandMoorsgt Agriculturegt MiresMarshesgt Broad Leafgt

Freshwatergt Sparse Veggt Mixedgt Urban

Table 2 Simplified ranking matrices comparing proportional habitat use within the third order (UD50UD95) with

proportions of total available habitat types Mean value on the matrix was replaced by a sign a triple sign represents

significant deviation from random at P lt05 Highlighted habitat is ranked 1st

North

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 --- --- --- - + --- --- + +++ --- 8

Broad Leaf +++ 0 +++ + + + + + +++ +++ + 1

Clear Fell +++ --- 0 + + + - - + +++ - 5

Coniferous +++ - - 0 + + --- --- +++ +++ - 6

Freshwater + - - - 0 +++ - - +++ +++ - 7

GrasslandMoors - - - - --- 0 - - - + - 10

MiresMarshes +++ - + +++ + + 0 - +++ +++ + 3

Mixed +++ - + +++ + + + 0 +++ +++ + 2

Sparse Veg - --- - --- --- + --- --- 0 +++ --- 9

Urban --- --- --- --- --- - --- --- --- 0 --- 11

Younger +++ - + + + + - - +++ +++ 0 4

Rank Order and

Significance

Broad Leafgt Mixedgt MiresMarshesgt Youngergt Clear Fellgt Coniferousgt Freshwatergt

Agriculturegt Sparse Veggt GrasslandMoorsgt Urban

39

Central

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 --- --- + + - - - + +++ --- 7

Broad Leaf +++ 0 + +++ + + + + + +++ - 2

Clear Fell +++ - 0 +++ + + + + + +++ - 3

Coniferous - --- --- 0 + - - --- +++ + --- 8

Freshwater - - - - 0 --- - - --- - - 11

GrasslandMoors + - - + +++ 0 + - + +++ - 5

MiresMarshes + - - + + - 0 + + +++ - 6

Mixed + - - +++ + + - 0 +++ +++ - 4

Sparse Veg - - - --- +++ - - --- 0 +++ - 9

Urban --- --- --- - + --- --- --- --- 0 --- 10

Younger +++ + + +++ + + + + + +++ 0 1

Rank Order and

Significance

Youngergt Broad Leafgt Clear Fellgt Mixedgt GrasslandMoorsgt MiresMarshesgt

Agriculturegt Coniferousgtgtgt Sparse Veggtgtgt Urbangt Freshwater

South

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 - - - - - + - +++ + --- 8

Broad Leaf + 0 - --- + - + - +++ + - 6

Clear Fell + + 0 - + - + - +++ + - 4

Coniferous + +++ + 0 + + +++ + +++ + + 1

Freshwater + - - - 0 - - + + + - 7

GrasslandMoors + + + - + 0 + + + + - 3

MiresMarshes - - - --- + - 0 - + + - 9

Mixed + + + - - - + 0 + + - 5

Sparse Veg --- --- --- --- - - - - 0 + --- 10

Urban - - - - - - - - - 0 - 11

Younger +++ + + - + + + + +++ + 0 2

Rank Order and

Significance

Coniferousgt Youngergt GrasslandMoorsgt Clear Fellgt Mixedgt Broad Leafgt Freshwatergt

Agriculturegt MiresMarshesgt Sparse Veggt Urban

40

Table 3 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the GS according to Jacobs index

Ran

k North Centre South

50 95 50 95 50 95

+ - + - + - + - + - + -

1 Broad

Leaf Urban Broad Leaf Sparse Veg

Broad

Leaf Urban Mixed Urban Coniferous Urban

Grassland

Moors Urban

2 Mixed Sparse Veg Mixed Freshwater Younger Agriculture Younger Sparse Veg Younger Sparse Veg Clear Fell Mixed

3 Mires

Agriculture Grassland

Urban Clear

Fell Coniferous Broad Leaf

Grassland

Moors

Clear Fell Agriculture Coniferous Sparse Veg

Marshes Moors

4 Younger Grassland

Younger Agriculture

Freshwater Coniferous Freshwater

Broad Leaf Mires

Younger Freshwater

Moors Marshes

5 Clear

Fell Freshwater

Mires Coniferous

Sparse Veg Clear Fell Agriculture

Freshwater Agriculture

Marshes

6 Coniferous Clear Fell

Mires

Marshes

Mires

Grassland

Moors

Mires

Marshes Marshes

7 Mixed Mixed Broad Leaf

8 Grassland

Moors

41

Table 4 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the WS according to Jacobs index

Ran

k North Centre South

50 95 50 95 50 95

+ - + - + - + - + - + -

1 Mires

Marshes

Grassland

Moors Mixed Freshwater Agriculture Urban Mixed Freshwater

Grassland

Moors Urban GrasslandMoors Urban

2 Freshwater Mixed Coniferous Urban Mires

Marshes Coniferous Sparse Veg Agriculture

Sparse

Veg Coniferous Freshwater

3 Urban Coniferous Younger Grassland

Moors Freshwater Younger Urban Freshwater

Broad

Leaf Agriculture Mixed

4 Younger Agriculture Sparse Veg Broad

Leaf

Broad

Leaf

Grassland

Moors Mixed Broad Leaf

5 Clear Fell Agriculture Coniferous Agriculture Mires

Marshes Clear Fell

6 Sparse

Veg

Mires

Marshes Mixed

Mires

Marshes

Clear

Fell

Mires

Marshes

7 Broad

Leaf Clear Fell Younger Clear Fell Younger Sparse Veg

8 Clear Fell Younger

9 Sparse

Veg

10 Grassland

Moors

42

Table 5 Second order (UD95Area) individual selectionavoidance for the GS and WS according to the Jacobs index

ID GS WS

Select Avoid Select Avoid

ID004 Younger Sparsely Vegetated MiresMarshes Sparsely Vegetated

ID005 MiresMarshes Sparsely Vegetated Coniferous GrasslandMoors

ID006 Coniferous Sparsely Vegetated Mixed Freshwater

ID008 Mixed Sparsely Vegetated Mixed Freshwater

ID009 Mixed Sparsely Vegetated Mixed GrasslandMoors

ID010 MiresMarshes Freshwater GrasslandMoors Freshwater

ID012 Broad Leaf Sparsely Vegetated Coniferous Urban

ID014 Clear Fell Sparsely Vegetated GrasslandMoors Sparsely Vegetated

ID015 GrasslandMoors Urban GrasslandMoors Freshwater

ID016 GrasslandMoors Freshwater GrasslandMoors Freshwater

ID017 GrasslandMoors Mixed Sparsely Vegetated Mixed

ID019 Mixed Sparsely Vegetated Mixed Urban

ID020 Broad Leaf Sparsely Vegetated Coniferous GrasslandMoors

ID022 MiresMarshes Freshwater MiresMarshes Freshwater

ID023 MiresMarshes GrasslandMoors Mixed Freshwater

ID024 Broadleaf Urban Broad Leaf Urban

ID026 GrasslandMoors Freshwater GrasslandMoors Freshwater

ID027 GrasslandMoors Urban Sparsely Vegetated Freshwater

43 Table 6 Third order (UD50UD95) individual selectionavoidance for the GS and WS according to the Jacobs index

ID GS WS

Select Avoid Select Avoid

ID004 Broad Leaf Mixed GrasslandMoors Freshwater

ID005 Broad Leaf Freshwater Agriculture Freshwater

ID006 Clear Fell Freshwater Agriculture MiresMarshes

ID008 MiresMarshes Freshwater Agriculture Urban

ID009 Freshwater Agriculture Agriculture Freshwater

ID010 Mixed Urban Sparsely Vegetated Urban

ID012 Coniferous GrasslandMoors Freshwater Urban

ID014 Urban Agriculture Freshwater Urban

ID015 Mixed Forest Urban Clear Fell Urban

ID016 Freshwater Urban GrasslandMoors Mixed

ID017 Coniferous Mixed Coniferous Broad Leaf

ID019 Broad Leaf GrasslandMoors Urban GrasslandMoors

ID020 Freshwater Urban Freshwater Agriculture

ID022 MiresMarshes Urban Broad Leaf GrasslandMoors

ID023 Freshwater Mixed Agriculture Freshwater

ID024 Mixed Freshwater Mixed Freshwater

ID026 Mixed MiresMarshes Sparsely Vegetated GrasslandMoors

ID027 Freshwater MiresMarshes GrasslandMoors Broad Leaf

44

Fig 2 North third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)

45

Fig 3 Centre third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)

46

Fig 4 South third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)

47

Fig 5 North second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)

48

Fig 6 Centre second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)

49

Fig 7 South second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)

50

Appendix F

Background

Fig 1 Daily mean snow depth and duration during the study period (Andrew Allen)

Female Moose Reproduction

Moose are seasonal polyoestral mammals (Monfort et al 1993) coming into oestrus during late September

early October (Garel et al 2009) The Swedish moose cow population reaches puberty between the ages 25

and 35 (Sand and Cederlund 1993) during which the reproductive period begins with the onset of ovulation

The age an individual reaches puberty is dependent on their body condition they have to reach a weight

threshold to reach puberty and become reproductive (Sand 1996) If she is over the weight threshold she will

go into oestrus in the autumn If she does not reach the weight threshold then she will go into oestrus the

following autumn if successful she will give birth to individual or twin calves in late May to early June

(Ericsson et al 2001) and therefore reach sexual maturity (Malmsten et al 2014b) Fecundity is related to

both the condition and the age of the cow Cows go through senescence at 12 years of age (Ericsson et al

2001) Providing calves with the required level of nutrition demands high energy and protein resources from

the mother during senescence this becomes harder to achieve leading to decreased levels of parental care

and higher levels of calf mortality

Page 11: Habitat-performance relationships on an island: fitness ...navinderjsingh.weebly.com/uploads/1/1/2/2/11224342/... · Conditions on Öland are milder than those found in other areas

11 Results

Home RangeUtilization Distribution

A total of 51 home ranges were estimated (17 annual 17 within growing season 17 within winter season)

Annual x = 9613 ha GS x = 6345 ha and WS x = 6023 ha (appendix C)

At the UD50 scale the largest annual and seasonal mean home ranges were located in the north Mean annual

and seasonal home ranges in the centre were slightly larger than the south This difference was not significant

(F(113)= 22 p= 87) (ANOVA) There was no significant difference between the seasonal home ranges (x

plusmnSD for GS = 116 plusmn38 for WS = 98 plusmn32 ha) (t(11) = 105 p = 32) or the seasonal home ranges in the centre

(t(8) = 101 p = 34 and the south (t(5) = 87 p = 42) (paired-sample t-test) (Table 1)

At the UD95 scale the largest annual and WS mean home ranges were located in the north The largest GS

mean home ranges were located in the centre Mean annual and seasonal home ranges in the centre were

slightly larger than the south This difference was not significant (F(113) = 59 p = 63) (ANOVA) There

was no significant difference between the seasonal home ranges (x plusmnSD for GS = 635 plusmn225 for WS = 602

plusmn161) (t(11) = 373 p = 71) or the seasonal home ranges in the centre (t(8)= 20 p = 84) or south (t(5) = 34

p = 74) (paired-sample t-test) (Table 1)

Table 1 Seasonal and annual mean UD50 and UD95 BRB kernel area in hectares (1ha = 001km2) for the north centre

and south of Oumlland (smoothing factor (h) =100)

Are

a

Annual UD50 GS UD50 WS UD50

n Mean SD Range n Mean SD Range n Mean SD Range

N 2 209 49 139-279 2 1215 39 67-176 2 1615 106 160-163

C 9 178 56 114-277 9 116 44 48-165 9 943 4 61-173

S 6 160 21 142-177 6 1085 51 65-149 6 933 35 69-125

Annual UD95 GS UD95 WS UD95

N 2 10905 5 1084-1097 2 630 199 349-911 2 809 11 794-824

C 9 997 32 682-1536 9 6531 22 295-945 9 637 17 454-941

S 6 9298 30 605-1088 6 5985 373 442-575 6 5526 20 349-679

12

Activity

MDM rates in the three areas (sedentary individuals) during the GS ranged from 14 ndash31 km day During the

WS ranged they ranged from 11-24 km day (Table 2) Movement rates during the GS were higher than the

WS (x plusmnSD for GS = 202 plusmn043 for WS = 161 plusmn043) but it was not statistically significant (t(11) = 200 p=

07) (paired sample t-test)

Table 2 Seasonal mean daily movement rates (km day) for each area and for both areas (total)

Are

a

GS WS

n Mean SE Range n Mean SE Range

C 8 20 003 14-18 8 20 004 12-24

S 4 22 016 17-31 4 12 02 11-13

Total 12 202 003 14-31 12 16 003 11-24

The seasonal MDM rates of all individuals (migratory and sedentary) were not significantly different (x plusmnSD

for GS = 20 plusmn04 for WS = 18 plusmn061) (t(14) = 139 p= 19) (paired sample t-test)

The WS home range size affects the WS MDM (F(110) = 927 p = 01) (ANOVA) The GS home range size

does not affect the GS MDM (F(110) = 36 p = 56) (ANOVA) When the WS home range outlier was

removed the home range size did not affect the WS MDM (F(111) = 186 p= 19) (ANOVA) The MDM was

lowest in February and highest in April (Table 3) there appeared to be no significant pattern in MDM between

the months (appendix D)

Table 3 Mean daily distance moved (km day) for sedentary individuals

Month Season Distance

April GS 0051

May GS 0044

June GS 0039

July GS 0041

August GS 0042

September GS 0044

October GS 0043

November WS 0043

December WS 0038

January WS 0035

February WS 0028

13 Habitat ndash Proportions

The largest proportion of habitat on the island is agriculture the lowest proportion of habitat (excluding coastal

and freshwater) is urban areas (Fig 2) The largest proportion of habitat in the north was coniferous forests

whilst agricultural areas were the dominant habitat types in the centre and south (Fig 3) The lowest proportion

(excluding coastal and freshwater areas) was urban

Fig 2 Proportion of different types of habitats found on Ӧland

Fig 3 Mean proportion of habitats contained within UD95 in the three areas of Oumlland C = Centre N = North S =

South

14

Habitat - Selection

Generally forest habitat types are the highest ranked whilst sparsely vegetated and urban areas are the lowest

ranked Both the second and third order habitat selection analyses gave significant results in the compositional

analysis (Table 4) In the third order analysis (UD50UD95) the centre displayed significant differences

between habitat types The coniferous forests are significantly preferred to sparsely vegetated areas and the

sparsely vegetated areas are significantly preferred to urban areas In the second order analysis (UD95Area)

significance was observed in the north and centre In the north younger forests are significantly preferred to

miresmarshes clear felled areas are significantly preferred to agriculture and freshwater areas are significantly

preferred to sparsely vegetated areas In the centre clear felled areas are significantly preferred to agricultural

land freshwater areas are significantly preferred to urban areas and grasslandmoors are significantly preferred

to sparsely vegetated areas

Table 4 Summary of second (UD95Area bottom) and third order (UD50UD95 top) ranked habitat preferences between

the three areas according to the compositional analysis (see appendix B)

Rank North Centre South

1 Broad Leaf Younger Coniferous

2 Mixed Broad Leaf Younger

3 MiresMarshes Clear Fell GrasslandMoors

4 Younger Mixed Clear Fell

5 Clear Fell GrasslandMoors Mixed

6 Coniferous MiresMarshes Broad Leaf

7 Freshwater Agriculture Freshwater

8 Agriculture Coniferous Agriculture

9 Sparse Veg Sparse Veg MiresMarshes

10 GrasslandMoors Urban Sparse Veg

11 Urban Freshwater Urban

Rank North Centre South

1 Broad Leaf Mixed Coniferous

2 Mixed Younger Clear Fell

3 GrasslandMoors Broad Leaf Younger

4 Younger Coniferous GrasslandMoors

5 MiresMarshes Clear Fell Agriculture

6 Coniferous Agriculture MiresMarshes

7 Clear Fell MiresMarshes Broad Leaf

8 Agriculture Freshwater Freshwater

9 Urban Urban Sparse Veg

10 Freshwater GrasslandMoors Mixed

11 Sparse Veg Sparse Veg Urban

Indicates significantly preferred to the habitat below (significant deviation from random at P lt05)

15 The Jacobs index revealed that generally the habitats preferred during the GS within the home range (third

order) are younger (0187) and broad leaf forests (0154) The strongest avoidance was for urban areas (-0627)

During the WS only agricultural areas are preferred (0129) and the strongest avoidance was for urban areas (-

0393) (Fig 4)

Fig 4 Third order seasonal habitat preference (UD50UD95) all individuals The index ranges from -1 (total avoidance)

to 1 (strongest preference) Close to 0 indicates used in proportion to its availability

Third order habitat preferencesavoidances by area

North During the GS the strongest preference was for broad leaf (0218) and mixed forests (0161) The

strongest avoidance was for urban (-1) and sparsely vegetated areas (-05) During the WS the strongest

preference was for miresmarshes (0228) The strongest avoidance was for grasslandmoors (-05)

Centre During the GS the strongest preference was for broad leaf (0233) and younger forests (0223) The

strongest avoidance was for urban (-0527) and agricultural land (-0362) During the WS preference was only

shown for agricultural land (0327) The strongest avoidance was for urban areas (-0679) and miresmarshes

(-0638)

South During the GS the strongest preference was for coniferous (0312) and younger forests (0242) The

strongest avoidance was for urban (-0353) and sparsely vegetated areas (-0330) During the WS

grasslandmoors (0106) were the strongest preference The strongest avoidance was for urban (-0666) and

sparsely vegetated areas (-0351)

16

The Jacobs indices revealed that generally the habitats preferred during the GS within the landscape

(UD95Area) are broad leaf (0216) and younger forests (0201) The strongest avoidance was for urban (-

0717) and freshwater areas (-0694) The strongest preference during the WS are coniferous forests (0242)

and the strongest avoidance was for freshwater (-0674) and urban areas (-0648) (Fig 5)

Fig 5 Second order seasonal habitat preference (UD50UD95) all individuals The index ranges from -1 (total avoidance)

to 1 (strongest preference) Close to 0 indicates used in proportion to its availability

Second order habitat preferencesavoidances by area

North During the GS the strongest preference was for broad leaf (0363) and mixed forests (00291) The

strongest avoidance was for sparsely vegetated (-0909) and freshwater areas (-0780) During the WS mixed

(0335) and coniferous forests (0316) were the strongest preference The strongest avoidance was for

freshwater (-0731) and urban areas (-05333)

Centre During the GS the strongest preference for mixed (0394) and younger forests (0286) The strongest

avoidance was for urban (-0733) and sparsely vegetated (-0708) areas During the WS mixed (0404) and

coniferous forests (0255) were the strongest preference The strongest avoidance was for freshwater (-0704)

and sparsely vegetated areas (-0655)

South During the GS the strongest preference for grasslandmoors (0287) and clear fells (0165) The

strongest avoidance was for urban areas (-0678) and mixed forests (-0491) During the WS grasslandmoors

(0425) and coniferous forests (0154) were the strongest preference The strongest avoidance was for urban (-

0876) and freshwater areas (-0587) (appendix E)

17 Diet

Diet analysis of the rumen content sampled from five individuals (C=2 S=3) revealed that almost two thirds

(69) of the diet is comprised of agricultural produce (apple winter rape and sugar beet) (Fig 6)

Fig 6 Diet analysis from the rumen samples of five moose individuals that were culled in 2013

31

2117

9

8

5

22

1 1

1

1

1 00 0

0

0Diet (2610-911 2013 5 individuals)

AppleWinter RapeSugar BeetUndefined WoodSallowBroad-leaf GrassPineAshOakCloverCurrantsUndefined plantElderberryJuniperRaspberry

18

Calf Survival

Of the 18 individuals 13 produced calves in which 7 produced twins giving a total of 20 calves A Kaplan-

Meier estimate was conducted to measure the fraction of calves living up to each period of the study (Fig 7)

The mean survival time is until period 235 (midend of summer) At the start of summer 85 of calves

remained (3 still born) The period between summer and before the hunt survival drops to 30 The survival

at the end of the study (after hunt) drops further to 20 leaving 4 calves surviving (see appendix B)

Fig 7 Kaplan-Meier estimate of moose calf survival during the study period Period 0 (Start of summer) period 1

(midend of summer) period 2 (before hunt) period 3 (after hunt) period 4 (after winter)

19 Discussion

The results of this study emphasised how strikingly different the habitat composition is along the latitudinal

gradient of Oumlland The three areas show contrasting proportions of the key habitat types The starkest

difference is the high proportion of coniferous forests and lack of agriculture in the north compared to the

centre and south The proportion of coniferous forest in the north is almost 5 times greater than in the centre

and south whereas the proportion of agriculture in the centre and south is more than double that in the north

The north is perceived to be composed of the most suitable habitat for moose (Dussault et al 2006) It has the

largest proportions of each forest type and a low proportion of agricultural land This provides suitable forage

and shelter throughout the year The south has a contrasting habitat composition to the north The proportions

of agricultural and sparsely vegetated areas are the highest between the three areas and the proportions of forest

habitats are the lowest The large proportion of sparsely vegetated areas and low proportions of forest habitat

corresponds to the large area of Stora Alvaret This is perceived to be the least suitable area due to a lack of

shelter (coniferous forest) and suitable forage The strong preference for coniferous and younger forest habitats

in the south would suggest that moose exhibit a functional response in habitat selection (Godvik et al 2009)

ie as the proportion of a particular habitat decreases the selection for that habitat increases in this case

coniferous forests which provide shelter and younger forest which provide good forage Similarly in the centre

moose show strong preference for mixed forests a habitat that is of low proportion

In view of the large variation in habitat proportions between the areas it is surprising that there is not a large

variation in the home range sizes or the activity levels annually or seasonally Home ranges are ultimately

chosen to maximise fitness and meet energy requirements by utilizing the available forage Seasonal conditions

change the availability and necessity of resources (food quality shelter) Unlike the GS during the WS

deciduous trees and shrubs are leafless and low-lying shrubs are under snow cover (Dussault et al 2005)

These changes are well known to cause populations to alter their activity and home ranges to meet energy

requirements (Mysterud et al 2001) Populations have been shown to increase or decrease their home ranges

during the two seasons The GS home ranges are often larger than the WS home ranges (Philips et al 1973

Mysterud et al 2001) In some cases they can be found to be almost double the size of the WS home ranges

(Cederlund and Okarma 1988) In other populations the WS home ranges are double the size of the GS home

ranges (Lynch and Morgantini 1984) or sizes do not significantly differ (Cederlund and Sand 1994)

Previous studies on moose find females generally show increased activity from the start on the GS due to

various factors eg reduced ruminating times increased metabolic needs and increased foraging bursts

(Wattles and DeStefano 2013) Increased metabolic needs during this time are a results of pregnancy and

lactation (Georgii 1980) During the height of the GS they usually show reduced activity levels through times

of increased thermal stress (Renecker and Hudson 1989 van Beest et al 2012) During the WS the depth and

the duration of snow cover are well known to affect the activity level (Telfer 1970 Mysterud and Oslashstbye 1999

Bjoslashrneraas et al 2011) During the WS generally home ranges are smaller and activity less due to lower

metabolic needs Moose activity is constrained by rumination during the WS this period is known to be longer

due to the change in diet (Cederlund 1989 Renecker Hudson 1989) This was not the case on Ӧland activity

20

was lowest in February which is a similar result to Cederlundrsquos (1989) paper However Ӧland moose did not

significantly alter their seasonal activity levels The fact that the annual and seasonal activity levels and home

ranges were similar could be a result of the mild winters on Oumlland during the study period (Smhise 2014)

During the study period the average number of snow days was 80 and the mean snow depth was 10cm

(appendix F) (Swedish Meterological and Hydrological Institute- SMHI) These mild conditions do not restrict

the movement of moose or obscure forage Moose are well adapted for movement in deep snow depths of 60-

86cm (Prescott 1968) are needed to truly restrict movement This finding was similar to the Sweanor and

Sandegren (1989) and Cederlund and Sand (1994) where the snow depth at their sites did not reach movement

restricting depths

The survival curve illustrates just how bad the calf survival is on Ӧland Survival falls from 85 at the start to

20 Out of 20 calves only four were alive at the end of the study The sharpest fall in survival was the period

between end of summer and before the hunt so the deaths were not due to hunting Previous calf autopsies

(Malmsten 2014a) have shown that cause of death was starvation mothers possibly either did not have milk

the calf was unable to feed or the mother abandoned the calf Closer field based observations are needed to

attain this knowledge Moose are seasonal polyoestral mammals (Monfort et al 1993) coming into oestrus

during late September early October (Garel et al 2009) (appendix F) The diet of the mother influences the

health of the calf and this period is when sodium is hard to find sodium is a key mineral in moose diets for

features such as reproduction (Belovsky and Jordan 1981) Moose gain sodium mainly through aquatic plants

(MacCracken et al 1993) However the compositional analysis shows that freshwater areas are often ranked

as one of the lowest used habitats and coastal areas were removed as the proportion found in the home ranges

was extremely low The Jacobs Index shows that the moose only prefer freshwater areas in the north UD50

during the WS The north individuals again are those that are showing typical moose habitat selection

It is known that habitat selection is hierarchical with habitats that increase fitness selected for and the effects

of limiting factors are reduced (Rettie and Messier 2000) At the UD95 during the GS moose preferred areas

of good forage (forests) and avoided areas of low forage (freshwater and sparsely vegetated areas) and areas

close to humans (urban) This is consistent with other reports (Laurian et al 2008 Torres et al 2011) Within

the UD50 there is a shift in preferences The good forage areas are again preferred during the GS however

during WS the only preferred habitat is often agricultural land During the WS there could be a steady supply

of supplementary feed available hence the high levels of agricultural produce found in the rumen content

samples and the high preference of agricultural areas This diet is unusual for moose previous studies of

Swedish moose diet have found the GS diet was dominated by birch willow and herbaceous plants and the

WS diet dominated by pine and birch (Cederlund and Nystrom 1981) The diet analysis was conducted during

the WS instead of being dominant pine composed just 2 Birch did not appear however unidentified wood

composed only 9 whereas agricultural produce accounted for 69 Supplementary feed may be perceived

by the moose in the centre and south as a vital forage source during the WS In fact in the centre the

agricultural land is the only preferred habitat at the UD50 It is unknown whether there are salt licks provided

in these areas Selection for a critical habitat is often thought to be a fixed factor The Oumlland population from

21 the three areas are close in proximity however they displayed contrasting preferences This is supported by the

Osko et al (2004) report that found two neighbouring moose populations that had access to the same habitats

displayed contrasting preferences Habitat preferences for populations of the same species are not necessarily

fixed They alter with varying levels of habitat abundance and limiting factors skewing what is preserved to

be critical

The main limitation encountered in this study was with the limited sample There was only data on two

individuals from the north of the island which led it being removed from many of the analysis Similarly due

to a lack of relocations from the collars being turned off at points throughout the year two further individuals

had to be removed from a majority of the analysis This reduced the sample size to 17 or 18 individuals

Similarly only 13 of the individuals from the study produced calves This unfortunately prevented including

survival into models Although the sample size was small it was accurate it was of high resolution over

300000 GPS points In future it would be beneficial to have a more standardised data set An equal sample of

individuals from the three areas would be advised along with ensuring the GPS collars are kept turned on for

the entirety of the growing and winter season to allow comparisons between years It would also be

advantageous to collect coordinates of the feeding sites along with the composition This could then be

compared with high use UD coordinates to look if moose are truly spending a majority of their foraging time

at feeding stations A study on the population densities of moose and the increasing population of roe deer

(Capreolus capreolus) would add the factor of competition into the model

The low calf survival on Ӧland is most likely the result of a combination of factors The lack of suitable habitat

reported in this study in conjunction with Malmstenrsquos (2014a) report on the threat of disease (Anaplasma

phagocytophilum) are probable influences on the calf survival on Ӧland On Ӧland there is an increasing

population of roe deer and large numbers of migratory birds both carriers of ticks and diseases The mild

conditions on Ӧland are advantageous for ticks the carriers of A phagocytophilum Fewer snow days and

shorter periods of snow cover along with dry conditions are favourable for ticks This could probably be one

of the reasons for females to be of lower quality and therefore not being able to ensure calf survival Moose

have to utilise areas where in other populations individuals tend to avoid Finally similar to many studies I

advocate further research using a stronger dataset and longer term monitoring

22

Acknowledgements

I am indebted to NJ Singh and A Allen for all their help and guidance through the whole of this study I

thank SLU for the support provided during this study in terms of data finances and facilities Thank you to

everyone at the Department of Wildlife Fish and Environmental Studies for being so friendly and

supportive I would like to thank L Edenius for driving me around the study area and S Michon and H

Khalil for keeping me sane with fika and training

23 References

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Bradshaw RHW Hannon GE Lister AM (2003) A long-term perspective on ungulate-vegetation

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Burt WH (1943) Territoriality and home range concepts as applied to mammals Journal of Mammalogy

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24

Bunnefeld N Boumlrger L van Moorter B Rolandsen CM Dettki H Solberg EJ Ericsson G(2011) A model-

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Calenge C (2006) The package adehabitat for the R software a tool for the analysis of space and habitat use

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Calenge C (2011) Home Range Estimation in R the adehabitatHR package Office national de la classe et de

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Cederlund GN Nystroumlm A (1981) Seasonal differences between moose and roe deer in ability to digest

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Cederlund GN Okarma H (1988) Home range and habitat use of adult female moose Journal of Wildlife

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Cederlund GN (1989) Activity patterns in moose and roe deer in a north boreal forest Holarctic Ecology

1239-45

Cederlund GN Sand H (1994) Home-range size in relation to age and sex in moose American Society of

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Clutton-Brock T Sheldon BC (2010) Individuals and populations the role of long-term individual based

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Cooke SJ Hinch SG Wikelski M Andrews RD Kuchel LJ Wolcott TG Butler PJ (2004) Biotelemerty a

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Crecircte M Courtois R (1997) Limiting factors might obscure population regulation of moose (Cervidae Alces

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Sedetalia) on the island of Ӧland (Sweden) in the context of north and central Europe

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Dussault C Courtois R Ouellet JP Girard I (2005) Space use of moose in relation to food availability

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Ericsson G Wallin K Ball JP Broberg M (2001) Age-related reproductive effort and senescence in free-

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Ericsson G Ball JP Danell K (2002) Moose offspring body mass along an altitudinal gradient Journal of

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Ericsson G Malmsten J Neumann W Singh NJ Dali AM Submitted Summer Calf Survival of

Scandinavian Moose along its Southern Distribution Range

25 Festa-Bianchet M Gaillard JM Jorgenson JT (1998) Mass and density-dependent reproductive success and

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Forchhammer MC Post E Stenseth NC Boertmann DM (2002) Long-term responses in arctic ungulate

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Gaillard JM Festa-Bianchet M Yoccoz NG (1998) Population dynamics of large herbivores variable

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Gaillard JM Festa-Bianchet M Yoccoz NG Loison A Toiumlgo C (2000a) Temporal variation in fitness

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Gaillard JM Festa-Bianchet M Delorme D Jorgenson J (2000b) Body mass and individual fitness in female

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Gaillard JM Hearingblewhite M Loison A Fuller M Powell R Basille M van Moorter B (2010) Habitat-

performance relationships finding the right metric at a given Spatial scale Philosophical

Transactions of the Royal Society B 3652255-2265

Garel M Solberg EJ Sӕther B-E Groslashtan V Tufto J Heim M (2009) Age size and spatiotemporal variation

in ovulation patterns of a seasonal breeder the Norwegian moose (Alces alces) The American

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Georgii B (1980) Home range patterns of female red deer (Cervus elaphus L) in the Alps Oecologia

47278-285

Godvik IMR Loe LE Vik JO Veiberg V Langvatn R Mysterud A (2009) Temporal scales trade-offs and

functional responses in red deer habitat selection Ecology 90699ndash710

Gordon IJ Hester AJ Festa-Bianchet M (2004) Review The management of wild large herbivores to meet

economic conservation and environmental objectives Journal of Applied Ecology 411021-

1031

Hagner O Nilsson M Reese H Egberth M Olsson H (2005) Procedure for classification of forests for

CORINE land cover in Sweden In Oluić M (ed) New strategies for European remote sensing

Millpress Rotterdam pp 523ndash530

Hall LS Krausman PR Morrison ML (1997) The habitat concept and a plea for standard terminology

Wildlife Society Bulletin 25173-182

Harris RB Wall WA Allendorf FW (2002) Genetic consequences of hunting what do we know and what

should we do Wildlife Society Bulletin 30634-643

Herfindal I Saeligther B-E Solberg EJ Andersen R Hoslashgda KA (2006) Population characteristics predict

responses in moose body mass to temporal variation in the environment Journal of Animal

Ecology 75 (5) 1110-1118

Horne JS Garton ED Krone SM Lewis JS (2007) Analysing animal movements using Brownian bridges

Ecological Society of America Ecology 882354-2363

Hornok S Kovaacutets D Csoumlrgo T Meli M Goumlnczi E Hadnagy Z Takaacutecs N Farkas R Hofmann-Lehmann R

(2014) Birds as potential reservoirs of tick-borne pathogens first evidence of bacteraemia

with Rickettsia Helvetica Parasites and Vectors 7128

26

Jacobs J (1974) Quantitative measurement of food selection a modification of the forage ratio and Ivlevrsquos

Electivity Index Oecologia 14(4)413-417

Jenkins KJ Manly FJ (2008) A double-observer method for reducing bias in faecal pellet surveys of forest

ungulates Journal of Applied Ecology 451339-1348

Johnson DH (1980) The comparison of usage and availability measurements for evaluating resource

preference Ecology 6165-71

Jonsson F (2007) rsquoDen oumllaumlndska aringlgstammens foumlrvaltingrsquo Departement of Wildlife Fish and Environmental

Studies SLU Examensarbete I aumlmnet biologi vol 20072

Kaplan EL Meier P (1958) Nonparametric estimation from incomplete observation Journal of the American

Statistical Association 53457-481

Keating KA Cherry S (2009) Modelling utilization distributions in space and time Ecology 90(7)1971-

1980

Kie JG Matthiopolos J Fieberg J Powell RA Cagnacci F Mitchell SM Gaillard JM Moorcroft PR (2010)

The home range concept are traditional estimators still relevant with modern telemetry

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Jaumlgarefoumlrbundet Oumlster-Malma 20092

Kranstauber B Kays R LaPoint SD Wikelski M Safi K (2012) A dynamic Brownian bridge movement

model to estimate utilization distributions for heterogeneous Animal movement Journal of

Animal Ecology 81738-746

Laurian C Ouellet JP Courtois R Breton L St-Onge S (2000) Effects of intensive harvesting on moose

reproduction Journal of Applied Ecology 37515-531

Laurian C Dussault C Ouellet JP Courtois R Poulin M Breton L (2008) Behaviour of moose relative to a

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Lavsund S Nygreacuten T Solberg EJ (2003) Status of moose populations and challenges to moose management

in Fennoscandia Alces 39109-130

Lenarz MS Fieberg J Schrage MW Edwards AJ (2010) Living on the edge viability of moose in

northeastern Minnesota The Journal of Wildlife Management 74(5)1013-1023

Lindstroumlm J (1999) Early development and fitness in birds and mammals Trends in Ecology and Evolution

14343-348

Linnell JDC Aanes R Andersen R (1995) Who killed Bambi The role of predation in the neonatal

mortality of temperate ungulates Wildlife Biology 1209-223

Lomas LA Bender LC (2007) Survival and cause-specific mortality of neonatal mule deer fawns north-

central New Mexico Journal of Wildlife Management 71884ndash894

Lynch GM Morgantini LE (1984) Sex and age differential in seasonal home range size of moose in

northcentral Alberta 1971-1979 Alces 2061-78

MacCracken JG Ballenberghe VV Peek JM (1993) Use of aquatic plants by moose sodium hunger or

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27

Malmsten J Wideacuten DG Rydevik G Yon L Hutchings MR Thulin CG Soumlderquist L Aspan A Stuen S

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University of Agricultural Sciences (SLU) Umearing

Malmsten J Soumlderquist L Thulin C Wideacuten DG Yon L Hutchings MR Dalin A (2014b) Reproductive

characteristics in female Swedish moose (Alces alces) with emphasis on puberty timing of

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28

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29

Tveito OE Foslashrland EJ Alexandersson H Drebs A Jonsson T Vaarby-Laursen E (2001) Nordic climate

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van Beest FM van Moorter B Milner JM (2012) Temperature-mediated habitat use and selection by a heat

sensitive northern ungulate Animal Behaviour 84(3)723-735

van Winkle W (1975) Comparision of several probabilistic home-range models Journal of Wildlife

Management 39118-123

Verme LJ Ullrey DE (1984) Physiology and nutrition White-tailed deer ecology and management (Ed By

Halls LK) pp 91-118 Stackpole Harrisburg Pennsylvania

Wattles DW DeStefano (2013) Space use and movements of moose in Massachusetts Implications for

conservation of large mammals in a fragmented environment Alces 4965-81

White RG Rowell JE Hauer WE (1997) The role of nutrition body condition and lactation on calving

success in muskoxen Journal of Zoology 24313-20

30

Appendix A

Introduction

Fig 1 Summary chart of factors affecting the life history and therefore the long term fitness of a population

Fig 2 Summary chart 2

Movement

Habitat

Climate

Topography

Competition

FoodWater

Disease

Die

Survive

Reproduce

Population long term fitness

31 Appendix B

Method and Materials

Fig 1 Summary of processes

32

Fig 2 Examples of classical kernel home range output and Brownian bridge kernel home range (Calenge 2011) The

right image includes the area between relocations ie the movement path in contrast to the classic kernel home range

in the left image

33 Appendix C

Home ranges

Fig 1 Example of a non-migratory (ID006) individuals BRB kernel area From top left annual growing and winter

season UD50 (black contour) and UD95 (red contour)

Fig 2 Example of a migratory (ID012) individuals BRB kernel area From the left annual growing and winter season

UD50 (black contour) and UD95 (red contour)

34

Table 1 Annual and seasonal UD50 and UD95 areas (ha) for all individuals

ID Annual GS WS

UD50 UD95 UD50 UD95 UD50 UD95

ID004 190 924 93 531 173 941

ID005 230 1364 132 945 72 682

ID006 162 1036 89 736 70 611

ID008 277 1536 156 809 78 738

ID009 137 834 48 295 126 653

ID010 114 682 83 448 96 488

ID012 177 963 123 544 76 545

ID014 160 1018 87 575 89 662

ID015 172 858 128 532 109 679

ID016 156 1047 65 455 92 534

ID017 153 1088 149 1043 69 349

ID019 279 1097 176 911 163 824

ID020 139 1084 67 349 160 794

ID022 159 811 131 638 61 454

ID023 187 1061 147 771 72 705

ID024 146 725 165 705 101 458

ID026 142 605 99 442 125 547

ID027 126 567 75 461 48 277

35 Appendix D

Activity

Fig 1 Mean daily movement during the study period GS 23-April-2012 to 07-Nov-2012 WS 08-Nov-2012 to

22-April-2013 (number indicates month)

Fig 2 Mean daily movement in the centre and south during the GS and WS

36

Appendix E

Habitat Proportions

Fig 1 All individualsrsquo seasonal habitat proportions within the UD95

37 Habitat Selection

Table 1 Simplified ranking matrices comparing proportional habitat use within the second order (UD95Area) with

proportions of total available habitat types Mean value on the matrix was replaced by a sign a triple sign represents

significant deviation from random at P lt05 Highlighted habitat is ranked 1st

North A

gri

cult

ure

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 --- --- - +++ --- --- --- +++ +++ --- 8

Broad Leaf +++ 0 +++ + +++ +++ +++ + +++ +++ +++ 1

Clear Fell +++ --- 0 + +++ - - --- +++ +++ --- 7

Coniferous + - - 0 +++ - - --- +++ +++ - 6

Freshwater --- --- --- --- 0 --- --- --- +++ - --- 10

Grassland

Moors +++ --- + + +++ 0 +++ - +++ +++ + 3

MiresMarshes +++ --- + + +++ --- 0 - +++ +++ --- 5

Mixed +++ - +++ +++ +++ + + 0 +++ +++ + 2

Sparse Veg --- --- --- --- --- --- --- --- 0 --- --- 11

Urban --- --- --- --- + --- --- --- +++ 0 --- 9

Younger +++ --- +++ + +++ - +++ - +++ +++ 0 4

Rank Order and

Significance

Broad Leafgt Mixedgt GrasslandMoorsgt Youngergtgtgt MiresMarshesgt Coniferousgt

Clear Fellgtgtgt Agriculturegtgtgt Urbangt Freshwatergtgtgt Sparse Veg

Central

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 --- --- --- + +++ + --- +++ +++ --- 6

Broad Leaf +++ 0 +++ + +++ +++ + - +++ +++ - 3

Clear Fell +++ --- 0 - +++ +++ + --- +++ +++ --- 5

Coniferous +++ - + 0 +++ +++ + --- +++ +++ - 4

Freshwater - --- --- --- 0 +++ - --- +++ +++ --- 8

Grassland

Moors --- --- --- --- --- 0 --- --- +++ - --- 10

MiresMarshes - - - - + +++ 0 - +++ +++ - 7

Mixed +++ + +++ +++ +++ +++ + 0 +++ +++ + 1

Sparse Veg --- --- --- --- --- --- --- --- 0 - --- 11

Urban --- --- --- --- --- + --- --- + 0 --- 9

Younger +++ + +++ + +++ +++ + - +++ +++ 0 2

Rank Order and

Significance

Mixedgt Youngergt Broad Leafgt Coniferousgt Clear Fellgtgtgt Agriculturegt

MiresMarshesgt Freshwatergtgtgt Urbangt GrasslandMoorsgtgtgt Sparse Veg

38

South

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 + - - + - + +++ +++ +++ - 5

Broad Leaf - 0 - - + - - +++ + +++ - 7

Clear Fell + + 0 - + + + +++ + +++ + 2

Coniferous + + + 0 +++ + + +++ + +++ + 1

Freshwater - - - --- 0 - - + + +++ - 8

Grassland

Moors + + - - + 0 + + +++ + - 4

MiresMarshes - + - - + - 0 +++ + +++ - 6

Mixed --- --- --- --- - - --- 0 + + --- 10

Sparse Veg --- - - - - --- - - 0 + - 9

Urban --- --- --- --- --- - --- - - 0 --- 11

Younger + + - - + + + +++ + +++ 0 3

Rank Order

and

Significance

Coniferousgt Clear Fellgt Youngergt GrasslandMoorsgt Agriculturegt MiresMarshesgt Broad Leafgt

Freshwatergt Sparse Veggt Mixedgt Urban

Table 2 Simplified ranking matrices comparing proportional habitat use within the third order (UD50UD95) with

proportions of total available habitat types Mean value on the matrix was replaced by a sign a triple sign represents

significant deviation from random at P lt05 Highlighted habitat is ranked 1st

North

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 --- --- --- - + --- --- + +++ --- 8

Broad Leaf +++ 0 +++ + + + + + +++ +++ + 1

Clear Fell +++ --- 0 + + + - - + +++ - 5

Coniferous +++ - - 0 + + --- --- +++ +++ - 6

Freshwater + - - - 0 +++ - - +++ +++ - 7

GrasslandMoors - - - - --- 0 - - - + - 10

MiresMarshes +++ - + +++ + + 0 - +++ +++ + 3

Mixed +++ - + +++ + + + 0 +++ +++ + 2

Sparse Veg - --- - --- --- + --- --- 0 +++ --- 9

Urban --- --- --- --- --- - --- --- --- 0 --- 11

Younger +++ - + + + + - - +++ +++ 0 4

Rank Order and

Significance

Broad Leafgt Mixedgt MiresMarshesgt Youngergt Clear Fellgt Coniferousgt Freshwatergt

Agriculturegt Sparse Veggt GrasslandMoorsgt Urban

39

Central

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 --- --- + + - - - + +++ --- 7

Broad Leaf +++ 0 + +++ + + + + + +++ - 2

Clear Fell +++ - 0 +++ + + + + + +++ - 3

Coniferous - --- --- 0 + - - --- +++ + --- 8

Freshwater - - - - 0 --- - - --- - - 11

GrasslandMoors + - - + +++ 0 + - + +++ - 5

MiresMarshes + - - + + - 0 + + +++ - 6

Mixed + - - +++ + + - 0 +++ +++ - 4

Sparse Veg - - - --- +++ - - --- 0 +++ - 9

Urban --- --- --- - + --- --- --- --- 0 --- 10

Younger +++ + + +++ + + + + + +++ 0 1

Rank Order and

Significance

Youngergt Broad Leafgt Clear Fellgt Mixedgt GrasslandMoorsgt MiresMarshesgt

Agriculturegt Coniferousgtgtgt Sparse Veggtgtgt Urbangt Freshwater

South

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 - - - - - + - +++ + --- 8

Broad Leaf + 0 - --- + - + - +++ + - 6

Clear Fell + + 0 - + - + - +++ + - 4

Coniferous + +++ + 0 + + +++ + +++ + + 1

Freshwater + - - - 0 - - + + + - 7

GrasslandMoors + + + - + 0 + + + + - 3

MiresMarshes - - - --- + - 0 - + + - 9

Mixed + + + - - - + 0 + + - 5

Sparse Veg --- --- --- --- - - - - 0 + --- 10

Urban - - - - - - - - - 0 - 11

Younger +++ + + - + + + + +++ + 0 2

Rank Order and

Significance

Coniferousgt Youngergt GrasslandMoorsgt Clear Fellgt Mixedgt Broad Leafgt Freshwatergt

Agriculturegt MiresMarshesgt Sparse Veggt Urban

40

Table 3 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the GS according to Jacobs index

Ran

k North Centre South

50 95 50 95 50 95

+ - + - + - + - + - + -

1 Broad

Leaf Urban Broad Leaf Sparse Veg

Broad

Leaf Urban Mixed Urban Coniferous Urban

Grassland

Moors Urban

2 Mixed Sparse Veg Mixed Freshwater Younger Agriculture Younger Sparse Veg Younger Sparse Veg Clear Fell Mixed

3 Mires

Agriculture Grassland

Urban Clear

Fell Coniferous Broad Leaf

Grassland

Moors

Clear Fell Agriculture Coniferous Sparse Veg

Marshes Moors

4 Younger Grassland

Younger Agriculture

Freshwater Coniferous Freshwater

Broad Leaf Mires

Younger Freshwater

Moors Marshes

5 Clear

Fell Freshwater

Mires Coniferous

Sparse Veg Clear Fell Agriculture

Freshwater Agriculture

Marshes

6 Coniferous Clear Fell

Mires

Marshes

Mires

Grassland

Moors

Mires

Marshes Marshes

7 Mixed Mixed Broad Leaf

8 Grassland

Moors

41

Table 4 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the WS according to Jacobs index

Ran

k North Centre South

50 95 50 95 50 95

+ - + - + - + - + - + -

1 Mires

Marshes

Grassland

Moors Mixed Freshwater Agriculture Urban Mixed Freshwater

Grassland

Moors Urban GrasslandMoors Urban

2 Freshwater Mixed Coniferous Urban Mires

Marshes Coniferous Sparse Veg Agriculture

Sparse

Veg Coniferous Freshwater

3 Urban Coniferous Younger Grassland

Moors Freshwater Younger Urban Freshwater

Broad

Leaf Agriculture Mixed

4 Younger Agriculture Sparse Veg Broad

Leaf

Broad

Leaf

Grassland

Moors Mixed Broad Leaf

5 Clear Fell Agriculture Coniferous Agriculture Mires

Marshes Clear Fell

6 Sparse

Veg

Mires

Marshes Mixed

Mires

Marshes

Clear

Fell

Mires

Marshes

7 Broad

Leaf Clear Fell Younger Clear Fell Younger Sparse Veg

8 Clear Fell Younger

9 Sparse

Veg

10 Grassland

Moors

42

Table 5 Second order (UD95Area) individual selectionavoidance for the GS and WS according to the Jacobs index

ID GS WS

Select Avoid Select Avoid

ID004 Younger Sparsely Vegetated MiresMarshes Sparsely Vegetated

ID005 MiresMarshes Sparsely Vegetated Coniferous GrasslandMoors

ID006 Coniferous Sparsely Vegetated Mixed Freshwater

ID008 Mixed Sparsely Vegetated Mixed Freshwater

ID009 Mixed Sparsely Vegetated Mixed GrasslandMoors

ID010 MiresMarshes Freshwater GrasslandMoors Freshwater

ID012 Broad Leaf Sparsely Vegetated Coniferous Urban

ID014 Clear Fell Sparsely Vegetated GrasslandMoors Sparsely Vegetated

ID015 GrasslandMoors Urban GrasslandMoors Freshwater

ID016 GrasslandMoors Freshwater GrasslandMoors Freshwater

ID017 GrasslandMoors Mixed Sparsely Vegetated Mixed

ID019 Mixed Sparsely Vegetated Mixed Urban

ID020 Broad Leaf Sparsely Vegetated Coniferous GrasslandMoors

ID022 MiresMarshes Freshwater MiresMarshes Freshwater

ID023 MiresMarshes GrasslandMoors Mixed Freshwater

ID024 Broadleaf Urban Broad Leaf Urban

ID026 GrasslandMoors Freshwater GrasslandMoors Freshwater

ID027 GrasslandMoors Urban Sparsely Vegetated Freshwater

43 Table 6 Third order (UD50UD95) individual selectionavoidance for the GS and WS according to the Jacobs index

ID GS WS

Select Avoid Select Avoid

ID004 Broad Leaf Mixed GrasslandMoors Freshwater

ID005 Broad Leaf Freshwater Agriculture Freshwater

ID006 Clear Fell Freshwater Agriculture MiresMarshes

ID008 MiresMarshes Freshwater Agriculture Urban

ID009 Freshwater Agriculture Agriculture Freshwater

ID010 Mixed Urban Sparsely Vegetated Urban

ID012 Coniferous GrasslandMoors Freshwater Urban

ID014 Urban Agriculture Freshwater Urban

ID015 Mixed Forest Urban Clear Fell Urban

ID016 Freshwater Urban GrasslandMoors Mixed

ID017 Coniferous Mixed Coniferous Broad Leaf

ID019 Broad Leaf GrasslandMoors Urban GrasslandMoors

ID020 Freshwater Urban Freshwater Agriculture

ID022 MiresMarshes Urban Broad Leaf GrasslandMoors

ID023 Freshwater Mixed Agriculture Freshwater

ID024 Mixed Freshwater Mixed Freshwater

ID026 Mixed MiresMarshes Sparsely Vegetated GrasslandMoors

ID027 Freshwater MiresMarshes GrasslandMoors Broad Leaf

44

Fig 2 North third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)

45

Fig 3 Centre third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)

46

Fig 4 South third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)

47

Fig 5 North second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)

48

Fig 6 Centre second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)

49

Fig 7 South second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)

50

Appendix F

Background

Fig 1 Daily mean snow depth and duration during the study period (Andrew Allen)

Female Moose Reproduction

Moose are seasonal polyoestral mammals (Monfort et al 1993) coming into oestrus during late September

early October (Garel et al 2009) The Swedish moose cow population reaches puberty between the ages 25

and 35 (Sand and Cederlund 1993) during which the reproductive period begins with the onset of ovulation

The age an individual reaches puberty is dependent on their body condition they have to reach a weight

threshold to reach puberty and become reproductive (Sand 1996) If she is over the weight threshold she will

go into oestrus in the autumn If she does not reach the weight threshold then she will go into oestrus the

following autumn if successful she will give birth to individual or twin calves in late May to early June

(Ericsson et al 2001) and therefore reach sexual maturity (Malmsten et al 2014b) Fecundity is related to

both the condition and the age of the cow Cows go through senescence at 12 years of age (Ericsson et al

2001) Providing calves with the required level of nutrition demands high energy and protein resources from

the mother during senescence this becomes harder to achieve leading to decreased levels of parental care

and higher levels of calf mortality

Page 12: Habitat-performance relationships on an island: fitness ...navinderjsingh.weebly.com/uploads/1/1/2/2/11224342/... · Conditions on Öland are milder than those found in other areas

12

Activity

MDM rates in the three areas (sedentary individuals) during the GS ranged from 14 ndash31 km day During the

WS ranged they ranged from 11-24 km day (Table 2) Movement rates during the GS were higher than the

WS (x plusmnSD for GS = 202 plusmn043 for WS = 161 plusmn043) but it was not statistically significant (t(11) = 200 p=

07) (paired sample t-test)

Table 2 Seasonal mean daily movement rates (km day) for each area and for both areas (total)

Are

a

GS WS

n Mean SE Range n Mean SE Range

C 8 20 003 14-18 8 20 004 12-24

S 4 22 016 17-31 4 12 02 11-13

Total 12 202 003 14-31 12 16 003 11-24

The seasonal MDM rates of all individuals (migratory and sedentary) were not significantly different (x plusmnSD

for GS = 20 plusmn04 for WS = 18 plusmn061) (t(14) = 139 p= 19) (paired sample t-test)

The WS home range size affects the WS MDM (F(110) = 927 p = 01) (ANOVA) The GS home range size

does not affect the GS MDM (F(110) = 36 p = 56) (ANOVA) When the WS home range outlier was

removed the home range size did not affect the WS MDM (F(111) = 186 p= 19) (ANOVA) The MDM was

lowest in February and highest in April (Table 3) there appeared to be no significant pattern in MDM between

the months (appendix D)

Table 3 Mean daily distance moved (km day) for sedentary individuals

Month Season Distance

April GS 0051

May GS 0044

June GS 0039

July GS 0041

August GS 0042

September GS 0044

October GS 0043

November WS 0043

December WS 0038

January WS 0035

February WS 0028

13 Habitat ndash Proportions

The largest proportion of habitat on the island is agriculture the lowest proportion of habitat (excluding coastal

and freshwater) is urban areas (Fig 2) The largest proportion of habitat in the north was coniferous forests

whilst agricultural areas were the dominant habitat types in the centre and south (Fig 3) The lowest proportion

(excluding coastal and freshwater areas) was urban

Fig 2 Proportion of different types of habitats found on Ӧland

Fig 3 Mean proportion of habitats contained within UD95 in the three areas of Oumlland C = Centre N = North S =

South

14

Habitat - Selection

Generally forest habitat types are the highest ranked whilst sparsely vegetated and urban areas are the lowest

ranked Both the second and third order habitat selection analyses gave significant results in the compositional

analysis (Table 4) In the third order analysis (UD50UD95) the centre displayed significant differences

between habitat types The coniferous forests are significantly preferred to sparsely vegetated areas and the

sparsely vegetated areas are significantly preferred to urban areas In the second order analysis (UD95Area)

significance was observed in the north and centre In the north younger forests are significantly preferred to

miresmarshes clear felled areas are significantly preferred to agriculture and freshwater areas are significantly

preferred to sparsely vegetated areas In the centre clear felled areas are significantly preferred to agricultural

land freshwater areas are significantly preferred to urban areas and grasslandmoors are significantly preferred

to sparsely vegetated areas

Table 4 Summary of second (UD95Area bottom) and third order (UD50UD95 top) ranked habitat preferences between

the three areas according to the compositional analysis (see appendix B)

Rank North Centre South

1 Broad Leaf Younger Coniferous

2 Mixed Broad Leaf Younger

3 MiresMarshes Clear Fell GrasslandMoors

4 Younger Mixed Clear Fell

5 Clear Fell GrasslandMoors Mixed

6 Coniferous MiresMarshes Broad Leaf

7 Freshwater Agriculture Freshwater

8 Agriculture Coniferous Agriculture

9 Sparse Veg Sparse Veg MiresMarshes

10 GrasslandMoors Urban Sparse Veg

11 Urban Freshwater Urban

Rank North Centre South

1 Broad Leaf Mixed Coniferous

2 Mixed Younger Clear Fell

3 GrasslandMoors Broad Leaf Younger

4 Younger Coniferous GrasslandMoors

5 MiresMarshes Clear Fell Agriculture

6 Coniferous Agriculture MiresMarshes

7 Clear Fell MiresMarshes Broad Leaf

8 Agriculture Freshwater Freshwater

9 Urban Urban Sparse Veg

10 Freshwater GrasslandMoors Mixed

11 Sparse Veg Sparse Veg Urban

Indicates significantly preferred to the habitat below (significant deviation from random at P lt05)

15 The Jacobs index revealed that generally the habitats preferred during the GS within the home range (third

order) are younger (0187) and broad leaf forests (0154) The strongest avoidance was for urban areas (-0627)

During the WS only agricultural areas are preferred (0129) and the strongest avoidance was for urban areas (-

0393) (Fig 4)

Fig 4 Third order seasonal habitat preference (UD50UD95) all individuals The index ranges from -1 (total avoidance)

to 1 (strongest preference) Close to 0 indicates used in proportion to its availability

Third order habitat preferencesavoidances by area

North During the GS the strongest preference was for broad leaf (0218) and mixed forests (0161) The

strongest avoidance was for urban (-1) and sparsely vegetated areas (-05) During the WS the strongest

preference was for miresmarshes (0228) The strongest avoidance was for grasslandmoors (-05)

Centre During the GS the strongest preference was for broad leaf (0233) and younger forests (0223) The

strongest avoidance was for urban (-0527) and agricultural land (-0362) During the WS preference was only

shown for agricultural land (0327) The strongest avoidance was for urban areas (-0679) and miresmarshes

(-0638)

South During the GS the strongest preference was for coniferous (0312) and younger forests (0242) The

strongest avoidance was for urban (-0353) and sparsely vegetated areas (-0330) During the WS

grasslandmoors (0106) were the strongest preference The strongest avoidance was for urban (-0666) and

sparsely vegetated areas (-0351)

16

The Jacobs indices revealed that generally the habitats preferred during the GS within the landscape

(UD95Area) are broad leaf (0216) and younger forests (0201) The strongest avoidance was for urban (-

0717) and freshwater areas (-0694) The strongest preference during the WS are coniferous forests (0242)

and the strongest avoidance was for freshwater (-0674) and urban areas (-0648) (Fig 5)

Fig 5 Second order seasonal habitat preference (UD50UD95) all individuals The index ranges from -1 (total avoidance)

to 1 (strongest preference) Close to 0 indicates used in proportion to its availability

Second order habitat preferencesavoidances by area

North During the GS the strongest preference was for broad leaf (0363) and mixed forests (00291) The

strongest avoidance was for sparsely vegetated (-0909) and freshwater areas (-0780) During the WS mixed

(0335) and coniferous forests (0316) were the strongest preference The strongest avoidance was for

freshwater (-0731) and urban areas (-05333)

Centre During the GS the strongest preference for mixed (0394) and younger forests (0286) The strongest

avoidance was for urban (-0733) and sparsely vegetated (-0708) areas During the WS mixed (0404) and

coniferous forests (0255) were the strongest preference The strongest avoidance was for freshwater (-0704)

and sparsely vegetated areas (-0655)

South During the GS the strongest preference for grasslandmoors (0287) and clear fells (0165) The

strongest avoidance was for urban areas (-0678) and mixed forests (-0491) During the WS grasslandmoors

(0425) and coniferous forests (0154) were the strongest preference The strongest avoidance was for urban (-

0876) and freshwater areas (-0587) (appendix E)

17 Diet

Diet analysis of the rumen content sampled from five individuals (C=2 S=3) revealed that almost two thirds

(69) of the diet is comprised of agricultural produce (apple winter rape and sugar beet) (Fig 6)

Fig 6 Diet analysis from the rumen samples of five moose individuals that were culled in 2013

31

2117

9

8

5

22

1 1

1

1

1 00 0

0

0Diet (2610-911 2013 5 individuals)

AppleWinter RapeSugar BeetUndefined WoodSallowBroad-leaf GrassPineAshOakCloverCurrantsUndefined plantElderberryJuniperRaspberry

18

Calf Survival

Of the 18 individuals 13 produced calves in which 7 produced twins giving a total of 20 calves A Kaplan-

Meier estimate was conducted to measure the fraction of calves living up to each period of the study (Fig 7)

The mean survival time is until period 235 (midend of summer) At the start of summer 85 of calves

remained (3 still born) The period between summer and before the hunt survival drops to 30 The survival

at the end of the study (after hunt) drops further to 20 leaving 4 calves surviving (see appendix B)

Fig 7 Kaplan-Meier estimate of moose calf survival during the study period Period 0 (Start of summer) period 1

(midend of summer) period 2 (before hunt) period 3 (after hunt) period 4 (after winter)

19 Discussion

The results of this study emphasised how strikingly different the habitat composition is along the latitudinal

gradient of Oumlland The three areas show contrasting proportions of the key habitat types The starkest

difference is the high proportion of coniferous forests and lack of agriculture in the north compared to the

centre and south The proportion of coniferous forest in the north is almost 5 times greater than in the centre

and south whereas the proportion of agriculture in the centre and south is more than double that in the north

The north is perceived to be composed of the most suitable habitat for moose (Dussault et al 2006) It has the

largest proportions of each forest type and a low proportion of agricultural land This provides suitable forage

and shelter throughout the year The south has a contrasting habitat composition to the north The proportions

of agricultural and sparsely vegetated areas are the highest between the three areas and the proportions of forest

habitats are the lowest The large proportion of sparsely vegetated areas and low proportions of forest habitat

corresponds to the large area of Stora Alvaret This is perceived to be the least suitable area due to a lack of

shelter (coniferous forest) and suitable forage The strong preference for coniferous and younger forest habitats

in the south would suggest that moose exhibit a functional response in habitat selection (Godvik et al 2009)

ie as the proportion of a particular habitat decreases the selection for that habitat increases in this case

coniferous forests which provide shelter and younger forest which provide good forage Similarly in the centre

moose show strong preference for mixed forests a habitat that is of low proportion

In view of the large variation in habitat proportions between the areas it is surprising that there is not a large

variation in the home range sizes or the activity levels annually or seasonally Home ranges are ultimately

chosen to maximise fitness and meet energy requirements by utilizing the available forage Seasonal conditions

change the availability and necessity of resources (food quality shelter) Unlike the GS during the WS

deciduous trees and shrubs are leafless and low-lying shrubs are under snow cover (Dussault et al 2005)

These changes are well known to cause populations to alter their activity and home ranges to meet energy

requirements (Mysterud et al 2001) Populations have been shown to increase or decrease their home ranges

during the two seasons The GS home ranges are often larger than the WS home ranges (Philips et al 1973

Mysterud et al 2001) In some cases they can be found to be almost double the size of the WS home ranges

(Cederlund and Okarma 1988) In other populations the WS home ranges are double the size of the GS home

ranges (Lynch and Morgantini 1984) or sizes do not significantly differ (Cederlund and Sand 1994)

Previous studies on moose find females generally show increased activity from the start on the GS due to

various factors eg reduced ruminating times increased metabolic needs and increased foraging bursts

(Wattles and DeStefano 2013) Increased metabolic needs during this time are a results of pregnancy and

lactation (Georgii 1980) During the height of the GS they usually show reduced activity levels through times

of increased thermal stress (Renecker and Hudson 1989 van Beest et al 2012) During the WS the depth and

the duration of snow cover are well known to affect the activity level (Telfer 1970 Mysterud and Oslashstbye 1999

Bjoslashrneraas et al 2011) During the WS generally home ranges are smaller and activity less due to lower

metabolic needs Moose activity is constrained by rumination during the WS this period is known to be longer

due to the change in diet (Cederlund 1989 Renecker Hudson 1989) This was not the case on Ӧland activity

20

was lowest in February which is a similar result to Cederlundrsquos (1989) paper However Ӧland moose did not

significantly alter their seasonal activity levels The fact that the annual and seasonal activity levels and home

ranges were similar could be a result of the mild winters on Oumlland during the study period (Smhise 2014)

During the study period the average number of snow days was 80 and the mean snow depth was 10cm

(appendix F) (Swedish Meterological and Hydrological Institute- SMHI) These mild conditions do not restrict

the movement of moose or obscure forage Moose are well adapted for movement in deep snow depths of 60-

86cm (Prescott 1968) are needed to truly restrict movement This finding was similar to the Sweanor and

Sandegren (1989) and Cederlund and Sand (1994) where the snow depth at their sites did not reach movement

restricting depths

The survival curve illustrates just how bad the calf survival is on Ӧland Survival falls from 85 at the start to

20 Out of 20 calves only four were alive at the end of the study The sharpest fall in survival was the period

between end of summer and before the hunt so the deaths were not due to hunting Previous calf autopsies

(Malmsten 2014a) have shown that cause of death was starvation mothers possibly either did not have milk

the calf was unable to feed or the mother abandoned the calf Closer field based observations are needed to

attain this knowledge Moose are seasonal polyoestral mammals (Monfort et al 1993) coming into oestrus

during late September early October (Garel et al 2009) (appendix F) The diet of the mother influences the

health of the calf and this period is when sodium is hard to find sodium is a key mineral in moose diets for

features such as reproduction (Belovsky and Jordan 1981) Moose gain sodium mainly through aquatic plants

(MacCracken et al 1993) However the compositional analysis shows that freshwater areas are often ranked

as one of the lowest used habitats and coastal areas were removed as the proportion found in the home ranges

was extremely low The Jacobs Index shows that the moose only prefer freshwater areas in the north UD50

during the WS The north individuals again are those that are showing typical moose habitat selection

It is known that habitat selection is hierarchical with habitats that increase fitness selected for and the effects

of limiting factors are reduced (Rettie and Messier 2000) At the UD95 during the GS moose preferred areas

of good forage (forests) and avoided areas of low forage (freshwater and sparsely vegetated areas) and areas

close to humans (urban) This is consistent with other reports (Laurian et al 2008 Torres et al 2011) Within

the UD50 there is a shift in preferences The good forage areas are again preferred during the GS however

during WS the only preferred habitat is often agricultural land During the WS there could be a steady supply

of supplementary feed available hence the high levels of agricultural produce found in the rumen content

samples and the high preference of agricultural areas This diet is unusual for moose previous studies of

Swedish moose diet have found the GS diet was dominated by birch willow and herbaceous plants and the

WS diet dominated by pine and birch (Cederlund and Nystrom 1981) The diet analysis was conducted during

the WS instead of being dominant pine composed just 2 Birch did not appear however unidentified wood

composed only 9 whereas agricultural produce accounted for 69 Supplementary feed may be perceived

by the moose in the centre and south as a vital forage source during the WS In fact in the centre the

agricultural land is the only preferred habitat at the UD50 It is unknown whether there are salt licks provided

in these areas Selection for a critical habitat is often thought to be a fixed factor The Oumlland population from

21 the three areas are close in proximity however they displayed contrasting preferences This is supported by the

Osko et al (2004) report that found two neighbouring moose populations that had access to the same habitats

displayed contrasting preferences Habitat preferences for populations of the same species are not necessarily

fixed They alter with varying levels of habitat abundance and limiting factors skewing what is preserved to

be critical

The main limitation encountered in this study was with the limited sample There was only data on two

individuals from the north of the island which led it being removed from many of the analysis Similarly due

to a lack of relocations from the collars being turned off at points throughout the year two further individuals

had to be removed from a majority of the analysis This reduced the sample size to 17 or 18 individuals

Similarly only 13 of the individuals from the study produced calves This unfortunately prevented including

survival into models Although the sample size was small it was accurate it was of high resolution over

300000 GPS points In future it would be beneficial to have a more standardised data set An equal sample of

individuals from the three areas would be advised along with ensuring the GPS collars are kept turned on for

the entirety of the growing and winter season to allow comparisons between years It would also be

advantageous to collect coordinates of the feeding sites along with the composition This could then be

compared with high use UD coordinates to look if moose are truly spending a majority of their foraging time

at feeding stations A study on the population densities of moose and the increasing population of roe deer

(Capreolus capreolus) would add the factor of competition into the model

The low calf survival on Ӧland is most likely the result of a combination of factors The lack of suitable habitat

reported in this study in conjunction with Malmstenrsquos (2014a) report on the threat of disease (Anaplasma

phagocytophilum) are probable influences on the calf survival on Ӧland On Ӧland there is an increasing

population of roe deer and large numbers of migratory birds both carriers of ticks and diseases The mild

conditions on Ӧland are advantageous for ticks the carriers of A phagocytophilum Fewer snow days and

shorter periods of snow cover along with dry conditions are favourable for ticks This could probably be one

of the reasons for females to be of lower quality and therefore not being able to ensure calf survival Moose

have to utilise areas where in other populations individuals tend to avoid Finally similar to many studies I

advocate further research using a stronger dataset and longer term monitoring

22

Acknowledgements

I am indebted to NJ Singh and A Allen for all their help and guidance through the whole of this study I

thank SLU for the support provided during this study in terms of data finances and facilities Thank you to

everyone at the Department of Wildlife Fish and Environmental Studies for being so friendly and

supportive I would like to thank L Edenius for driving me around the study area and S Michon and H

Khalil for keeping me sane with fika and training

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Bradshaw RHW Hannon GE Lister AM (2003) A long-term perspective on ungulate-vegetation

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Calenge C (2011) Home Range Estimation in R the adehabitatHR package Office national de la classe et de

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1239-45

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Cooke SJ Hinch SG Wikelski M Andrews RD Kuchel LJ Wolcott TG Butler PJ (2004) Biotelemerty a

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Sedetalia) on the island of Ӧland (Sweden) in the context of north and central Europe

Phytocoenologia 36343-391

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Dussault C Courtois R Ouellet JP (2006) A habitat suitability index model to assess moose habitat selection

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Ericsson G Ball JP Danell K (2002) Moose offspring body mass along an altitudinal gradient Journal of

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Ericsson G Malmsten J Neumann W Singh NJ Dali AM Submitted Summer Calf Survival of

Scandinavian Moose along its Southern Distribution Range

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Gaillard JM Festa-Bianchet M Yoccoz NG Loison A Toiumlgo C (2000a) Temporal variation in fitness

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47278-285

Godvik IMR Loe LE Vik JO Veiberg V Langvatn R Mysterud A (2009) Temporal scales trade-offs and

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Hagner O Nilsson M Reese H Egberth M Olsson H (2005) Procedure for classification of forests for

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Malmsten J Wideacuten DG Rydevik G Yon L Hutchings MR Thulin CG Soumlderquist L Aspan A Stuen S

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Malmsten J (2014a) lsquoReproduction and health of moose in southern Swedenrsquo Doctoral thesis Swedish

University of Agricultural Sciences (SLU) Umearing

Malmsten J Soumlderquist L Thulin C Wideacuten DG Yon L Hutchings MR Dalin A (2014b) Reproductive

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faecal steroid metabolites The Journal of Wildlife Management 57400-407

Monteith KL Klaver R Hersey K Holland A Thomas T Kauffman M In press Effects of climate and

plant phenology on recruitment of moose at the southern extent of their range

Morales JM Moorcroft PR Matthiopoulos J Frair JL Kie JG Powell RA Merrill EH Haydon DT (2010)

Building the bridge between animal movement and population dynamics Philosophical

Transactions of the Royal Society B 3652289-230

Morellet N Bonenfant C Boumlrger L Ossi F Cagnacci F Heurich M Kjellander P Linnell JDC Nicoloso S

Sustr P Urbano F Mysterud A (2013) Seasonality weather and climate affect home range

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30

Appendix A

Introduction

Fig 1 Summary chart of factors affecting the life history and therefore the long term fitness of a population

Fig 2 Summary chart 2

Movement

Habitat

Climate

Topography

Competition

FoodWater

Disease

Die

Survive

Reproduce

Population long term fitness

31 Appendix B

Method and Materials

Fig 1 Summary of processes

32

Fig 2 Examples of classical kernel home range output and Brownian bridge kernel home range (Calenge 2011) The

right image includes the area between relocations ie the movement path in contrast to the classic kernel home range

in the left image

33 Appendix C

Home ranges

Fig 1 Example of a non-migratory (ID006) individuals BRB kernel area From top left annual growing and winter

season UD50 (black contour) and UD95 (red contour)

Fig 2 Example of a migratory (ID012) individuals BRB kernel area From the left annual growing and winter season

UD50 (black contour) and UD95 (red contour)

34

Table 1 Annual and seasonal UD50 and UD95 areas (ha) for all individuals

ID Annual GS WS

UD50 UD95 UD50 UD95 UD50 UD95

ID004 190 924 93 531 173 941

ID005 230 1364 132 945 72 682

ID006 162 1036 89 736 70 611

ID008 277 1536 156 809 78 738

ID009 137 834 48 295 126 653

ID010 114 682 83 448 96 488

ID012 177 963 123 544 76 545

ID014 160 1018 87 575 89 662

ID015 172 858 128 532 109 679

ID016 156 1047 65 455 92 534

ID017 153 1088 149 1043 69 349

ID019 279 1097 176 911 163 824

ID020 139 1084 67 349 160 794

ID022 159 811 131 638 61 454

ID023 187 1061 147 771 72 705

ID024 146 725 165 705 101 458

ID026 142 605 99 442 125 547

ID027 126 567 75 461 48 277

35 Appendix D

Activity

Fig 1 Mean daily movement during the study period GS 23-April-2012 to 07-Nov-2012 WS 08-Nov-2012 to

22-April-2013 (number indicates month)

Fig 2 Mean daily movement in the centre and south during the GS and WS

36

Appendix E

Habitat Proportions

Fig 1 All individualsrsquo seasonal habitat proportions within the UD95

37 Habitat Selection

Table 1 Simplified ranking matrices comparing proportional habitat use within the second order (UD95Area) with

proportions of total available habitat types Mean value on the matrix was replaced by a sign a triple sign represents

significant deviation from random at P lt05 Highlighted habitat is ranked 1st

North A

gri

cult

ure

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 --- --- - +++ --- --- --- +++ +++ --- 8

Broad Leaf +++ 0 +++ + +++ +++ +++ + +++ +++ +++ 1

Clear Fell +++ --- 0 + +++ - - --- +++ +++ --- 7

Coniferous + - - 0 +++ - - --- +++ +++ - 6

Freshwater --- --- --- --- 0 --- --- --- +++ - --- 10

Grassland

Moors +++ --- + + +++ 0 +++ - +++ +++ + 3

MiresMarshes +++ --- + + +++ --- 0 - +++ +++ --- 5

Mixed +++ - +++ +++ +++ + + 0 +++ +++ + 2

Sparse Veg --- --- --- --- --- --- --- --- 0 --- --- 11

Urban --- --- --- --- + --- --- --- +++ 0 --- 9

Younger +++ --- +++ + +++ - +++ - +++ +++ 0 4

Rank Order and

Significance

Broad Leafgt Mixedgt GrasslandMoorsgt Youngergtgtgt MiresMarshesgt Coniferousgt

Clear Fellgtgtgt Agriculturegtgtgt Urbangt Freshwatergtgtgt Sparse Veg

Central

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 --- --- --- + +++ + --- +++ +++ --- 6

Broad Leaf +++ 0 +++ + +++ +++ + - +++ +++ - 3

Clear Fell +++ --- 0 - +++ +++ + --- +++ +++ --- 5

Coniferous +++ - + 0 +++ +++ + --- +++ +++ - 4

Freshwater - --- --- --- 0 +++ - --- +++ +++ --- 8

Grassland

Moors --- --- --- --- --- 0 --- --- +++ - --- 10

MiresMarshes - - - - + +++ 0 - +++ +++ - 7

Mixed +++ + +++ +++ +++ +++ + 0 +++ +++ + 1

Sparse Veg --- --- --- --- --- --- --- --- 0 - --- 11

Urban --- --- --- --- --- + --- --- + 0 --- 9

Younger +++ + +++ + +++ +++ + - +++ +++ 0 2

Rank Order and

Significance

Mixedgt Youngergt Broad Leafgt Coniferousgt Clear Fellgtgtgt Agriculturegt

MiresMarshesgt Freshwatergtgtgt Urbangt GrasslandMoorsgtgtgt Sparse Veg

38

South

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 + - - + - + +++ +++ +++ - 5

Broad Leaf - 0 - - + - - +++ + +++ - 7

Clear Fell + + 0 - + + + +++ + +++ + 2

Coniferous + + + 0 +++ + + +++ + +++ + 1

Freshwater - - - --- 0 - - + + +++ - 8

Grassland

Moors + + - - + 0 + + +++ + - 4

MiresMarshes - + - - + - 0 +++ + +++ - 6

Mixed --- --- --- --- - - --- 0 + + --- 10

Sparse Veg --- - - - - --- - - 0 + - 9

Urban --- --- --- --- --- - --- - - 0 --- 11

Younger + + - - + + + +++ + +++ 0 3

Rank Order

and

Significance

Coniferousgt Clear Fellgt Youngergt GrasslandMoorsgt Agriculturegt MiresMarshesgt Broad Leafgt

Freshwatergt Sparse Veggt Mixedgt Urban

Table 2 Simplified ranking matrices comparing proportional habitat use within the third order (UD50UD95) with

proportions of total available habitat types Mean value on the matrix was replaced by a sign a triple sign represents

significant deviation from random at P lt05 Highlighted habitat is ranked 1st

North

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 --- --- --- - + --- --- + +++ --- 8

Broad Leaf +++ 0 +++ + + + + + +++ +++ + 1

Clear Fell +++ --- 0 + + + - - + +++ - 5

Coniferous +++ - - 0 + + --- --- +++ +++ - 6

Freshwater + - - - 0 +++ - - +++ +++ - 7

GrasslandMoors - - - - --- 0 - - - + - 10

MiresMarshes +++ - + +++ + + 0 - +++ +++ + 3

Mixed +++ - + +++ + + + 0 +++ +++ + 2

Sparse Veg - --- - --- --- + --- --- 0 +++ --- 9

Urban --- --- --- --- --- - --- --- --- 0 --- 11

Younger +++ - + + + + - - +++ +++ 0 4

Rank Order and

Significance

Broad Leafgt Mixedgt MiresMarshesgt Youngergt Clear Fellgt Coniferousgt Freshwatergt

Agriculturegt Sparse Veggt GrasslandMoorsgt Urban

39

Central

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 --- --- + + - - - + +++ --- 7

Broad Leaf +++ 0 + +++ + + + + + +++ - 2

Clear Fell +++ - 0 +++ + + + + + +++ - 3

Coniferous - --- --- 0 + - - --- +++ + --- 8

Freshwater - - - - 0 --- - - --- - - 11

GrasslandMoors + - - + +++ 0 + - + +++ - 5

MiresMarshes + - - + + - 0 + + +++ - 6

Mixed + - - +++ + + - 0 +++ +++ - 4

Sparse Veg - - - --- +++ - - --- 0 +++ - 9

Urban --- --- --- - + --- --- --- --- 0 --- 10

Younger +++ + + +++ + + + + + +++ 0 1

Rank Order and

Significance

Youngergt Broad Leafgt Clear Fellgt Mixedgt GrasslandMoorsgt MiresMarshesgt

Agriculturegt Coniferousgtgtgt Sparse Veggtgtgt Urbangt Freshwater

South

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 - - - - - + - +++ + --- 8

Broad Leaf + 0 - --- + - + - +++ + - 6

Clear Fell + + 0 - + - + - +++ + - 4

Coniferous + +++ + 0 + + +++ + +++ + + 1

Freshwater + - - - 0 - - + + + - 7

GrasslandMoors + + + - + 0 + + + + - 3

MiresMarshes - - - --- + - 0 - + + - 9

Mixed + + + - - - + 0 + + - 5

Sparse Veg --- --- --- --- - - - - 0 + --- 10

Urban - - - - - - - - - 0 - 11

Younger +++ + + - + + + + +++ + 0 2

Rank Order and

Significance

Coniferousgt Youngergt GrasslandMoorsgt Clear Fellgt Mixedgt Broad Leafgt Freshwatergt

Agriculturegt MiresMarshesgt Sparse Veggt Urban

40

Table 3 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the GS according to Jacobs index

Ran

k North Centre South

50 95 50 95 50 95

+ - + - + - + - + - + -

1 Broad

Leaf Urban Broad Leaf Sparse Veg

Broad

Leaf Urban Mixed Urban Coniferous Urban

Grassland

Moors Urban

2 Mixed Sparse Veg Mixed Freshwater Younger Agriculture Younger Sparse Veg Younger Sparse Veg Clear Fell Mixed

3 Mires

Agriculture Grassland

Urban Clear

Fell Coniferous Broad Leaf

Grassland

Moors

Clear Fell Agriculture Coniferous Sparse Veg

Marshes Moors

4 Younger Grassland

Younger Agriculture

Freshwater Coniferous Freshwater

Broad Leaf Mires

Younger Freshwater

Moors Marshes

5 Clear

Fell Freshwater

Mires Coniferous

Sparse Veg Clear Fell Agriculture

Freshwater Agriculture

Marshes

6 Coniferous Clear Fell

Mires

Marshes

Mires

Grassland

Moors

Mires

Marshes Marshes

7 Mixed Mixed Broad Leaf

8 Grassland

Moors

41

Table 4 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the WS according to Jacobs index

Ran

k North Centre South

50 95 50 95 50 95

+ - + - + - + - + - + -

1 Mires

Marshes

Grassland

Moors Mixed Freshwater Agriculture Urban Mixed Freshwater

Grassland

Moors Urban GrasslandMoors Urban

2 Freshwater Mixed Coniferous Urban Mires

Marshes Coniferous Sparse Veg Agriculture

Sparse

Veg Coniferous Freshwater

3 Urban Coniferous Younger Grassland

Moors Freshwater Younger Urban Freshwater

Broad

Leaf Agriculture Mixed

4 Younger Agriculture Sparse Veg Broad

Leaf

Broad

Leaf

Grassland

Moors Mixed Broad Leaf

5 Clear Fell Agriculture Coniferous Agriculture Mires

Marshes Clear Fell

6 Sparse

Veg

Mires

Marshes Mixed

Mires

Marshes

Clear

Fell

Mires

Marshes

7 Broad

Leaf Clear Fell Younger Clear Fell Younger Sparse Veg

8 Clear Fell Younger

9 Sparse

Veg

10 Grassland

Moors

42

Table 5 Second order (UD95Area) individual selectionavoidance for the GS and WS according to the Jacobs index

ID GS WS

Select Avoid Select Avoid

ID004 Younger Sparsely Vegetated MiresMarshes Sparsely Vegetated

ID005 MiresMarshes Sparsely Vegetated Coniferous GrasslandMoors

ID006 Coniferous Sparsely Vegetated Mixed Freshwater

ID008 Mixed Sparsely Vegetated Mixed Freshwater

ID009 Mixed Sparsely Vegetated Mixed GrasslandMoors

ID010 MiresMarshes Freshwater GrasslandMoors Freshwater

ID012 Broad Leaf Sparsely Vegetated Coniferous Urban

ID014 Clear Fell Sparsely Vegetated GrasslandMoors Sparsely Vegetated

ID015 GrasslandMoors Urban GrasslandMoors Freshwater

ID016 GrasslandMoors Freshwater GrasslandMoors Freshwater

ID017 GrasslandMoors Mixed Sparsely Vegetated Mixed

ID019 Mixed Sparsely Vegetated Mixed Urban

ID020 Broad Leaf Sparsely Vegetated Coniferous GrasslandMoors

ID022 MiresMarshes Freshwater MiresMarshes Freshwater

ID023 MiresMarshes GrasslandMoors Mixed Freshwater

ID024 Broadleaf Urban Broad Leaf Urban

ID026 GrasslandMoors Freshwater GrasslandMoors Freshwater

ID027 GrasslandMoors Urban Sparsely Vegetated Freshwater

43 Table 6 Third order (UD50UD95) individual selectionavoidance for the GS and WS according to the Jacobs index

ID GS WS

Select Avoid Select Avoid

ID004 Broad Leaf Mixed GrasslandMoors Freshwater

ID005 Broad Leaf Freshwater Agriculture Freshwater

ID006 Clear Fell Freshwater Agriculture MiresMarshes

ID008 MiresMarshes Freshwater Agriculture Urban

ID009 Freshwater Agriculture Agriculture Freshwater

ID010 Mixed Urban Sparsely Vegetated Urban

ID012 Coniferous GrasslandMoors Freshwater Urban

ID014 Urban Agriculture Freshwater Urban

ID015 Mixed Forest Urban Clear Fell Urban

ID016 Freshwater Urban GrasslandMoors Mixed

ID017 Coniferous Mixed Coniferous Broad Leaf

ID019 Broad Leaf GrasslandMoors Urban GrasslandMoors

ID020 Freshwater Urban Freshwater Agriculture

ID022 MiresMarshes Urban Broad Leaf GrasslandMoors

ID023 Freshwater Mixed Agriculture Freshwater

ID024 Mixed Freshwater Mixed Freshwater

ID026 Mixed MiresMarshes Sparsely Vegetated GrasslandMoors

ID027 Freshwater MiresMarshes GrasslandMoors Broad Leaf

44

Fig 2 North third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)

45

Fig 3 Centre third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)

46

Fig 4 South third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)

47

Fig 5 North second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)

48

Fig 6 Centre second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)

49

Fig 7 South second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)

50

Appendix F

Background

Fig 1 Daily mean snow depth and duration during the study period (Andrew Allen)

Female Moose Reproduction

Moose are seasonal polyoestral mammals (Monfort et al 1993) coming into oestrus during late September

early October (Garel et al 2009) The Swedish moose cow population reaches puberty between the ages 25

and 35 (Sand and Cederlund 1993) during which the reproductive period begins with the onset of ovulation

The age an individual reaches puberty is dependent on their body condition they have to reach a weight

threshold to reach puberty and become reproductive (Sand 1996) If she is over the weight threshold she will

go into oestrus in the autumn If she does not reach the weight threshold then she will go into oestrus the

following autumn if successful she will give birth to individual or twin calves in late May to early June

(Ericsson et al 2001) and therefore reach sexual maturity (Malmsten et al 2014b) Fecundity is related to

both the condition and the age of the cow Cows go through senescence at 12 years of age (Ericsson et al

2001) Providing calves with the required level of nutrition demands high energy and protein resources from

the mother during senescence this becomes harder to achieve leading to decreased levels of parental care

and higher levels of calf mortality

Page 13: Habitat-performance relationships on an island: fitness ...navinderjsingh.weebly.com/uploads/1/1/2/2/11224342/... · Conditions on Öland are milder than those found in other areas

13 Habitat ndash Proportions

The largest proportion of habitat on the island is agriculture the lowest proportion of habitat (excluding coastal

and freshwater) is urban areas (Fig 2) The largest proportion of habitat in the north was coniferous forests

whilst agricultural areas were the dominant habitat types in the centre and south (Fig 3) The lowest proportion

(excluding coastal and freshwater areas) was urban

Fig 2 Proportion of different types of habitats found on Ӧland

Fig 3 Mean proportion of habitats contained within UD95 in the three areas of Oumlland C = Centre N = North S =

South

14

Habitat - Selection

Generally forest habitat types are the highest ranked whilst sparsely vegetated and urban areas are the lowest

ranked Both the second and third order habitat selection analyses gave significant results in the compositional

analysis (Table 4) In the third order analysis (UD50UD95) the centre displayed significant differences

between habitat types The coniferous forests are significantly preferred to sparsely vegetated areas and the

sparsely vegetated areas are significantly preferred to urban areas In the second order analysis (UD95Area)

significance was observed in the north and centre In the north younger forests are significantly preferred to

miresmarshes clear felled areas are significantly preferred to agriculture and freshwater areas are significantly

preferred to sparsely vegetated areas In the centre clear felled areas are significantly preferred to agricultural

land freshwater areas are significantly preferred to urban areas and grasslandmoors are significantly preferred

to sparsely vegetated areas

Table 4 Summary of second (UD95Area bottom) and third order (UD50UD95 top) ranked habitat preferences between

the three areas according to the compositional analysis (see appendix B)

Rank North Centre South

1 Broad Leaf Younger Coniferous

2 Mixed Broad Leaf Younger

3 MiresMarshes Clear Fell GrasslandMoors

4 Younger Mixed Clear Fell

5 Clear Fell GrasslandMoors Mixed

6 Coniferous MiresMarshes Broad Leaf

7 Freshwater Agriculture Freshwater

8 Agriculture Coniferous Agriculture

9 Sparse Veg Sparse Veg MiresMarshes

10 GrasslandMoors Urban Sparse Veg

11 Urban Freshwater Urban

Rank North Centre South

1 Broad Leaf Mixed Coniferous

2 Mixed Younger Clear Fell

3 GrasslandMoors Broad Leaf Younger

4 Younger Coniferous GrasslandMoors

5 MiresMarshes Clear Fell Agriculture

6 Coniferous Agriculture MiresMarshes

7 Clear Fell MiresMarshes Broad Leaf

8 Agriculture Freshwater Freshwater

9 Urban Urban Sparse Veg

10 Freshwater GrasslandMoors Mixed

11 Sparse Veg Sparse Veg Urban

Indicates significantly preferred to the habitat below (significant deviation from random at P lt05)

15 The Jacobs index revealed that generally the habitats preferred during the GS within the home range (third

order) are younger (0187) and broad leaf forests (0154) The strongest avoidance was for urban areas (-0627)

During the WS only agricultural areas are preferred (0129) and the strongest avoidance was for urban areas (-

0393) (Fig 4)

Fig 4 Third order seasonal habitat preference (UD50UD95) all individuals The index ranges from -1 (total avoidance)

to 1 (strongest preference) Close to 0 indicates used in proportion to its availability

Third order habitat preferencesavoidances by area

North During the GS the strongest preference was for broad leaf (0218) and mixed forests (0161) The

strongest avoidance was for urban (-1) and sparsely vegetated areas (-05) During the WS the strongest

preference was for miresmarshes (0228) The strongest avoidance was for grasslandmoors (-05)

Centre During the GS the strongest preference was for broad leaf (0233) and younger forests (0223) The

strongest avoidance was for urban (-0527) and agricultural land (-0362) During the WS preference was only

shown for agricultural land (0327) The strongest avoidance was for urban areas (-0679) and miresmarshes

(-0638)

South During the GS the strongest preference was for coniferous (0312) and younger forests (0242) The

strongest avoidance was for urban (-0353) and sparsely vegetated areas (-0330) During the WS

grasslandmoors (0106) were the strongest preference The strongest avoidance was for urban (-0666) and

sparsely vegetated areas (-0351)

16

The Jacobs indices revealed that generally the habitats preferred during the GS within the landscape

(UD95Area) are broad leaf (0216) and younger forests (0201) The strongest avoidance was for urban (-

0717) and freshwater areas (-0694) The strongest preference during the WS are coniferous forests (0242)

and the strongest avoidance was for freshwater (-0674) and urban areas (-0648) (Fig 5)

Fig 5 Second order seasonal habitat preference (UD50UD95) all individuals The index ranges from -1 (total avoidance)

to 1 (strongest preference) Close to 0 indicates used in proportion to its availability

Second order habitat preferencesavoidances by area

North During the GS the strongest preference was for broad leaf (0363) and mixed forests (00291) The

strongest avoidance was for sparsely vegetated (-0909) and freshwater areas (-0780) During the WS mixed

(0335) and coniferous forests (0316) were the strongest preference The strongest avoidance was for

freshwater (-0731) and urban areas (-05333)

Centre During the GS the strongest preference for mixed (0394) and younger forests (0286) The strongest

avoidance was for urban (-0733) and sparsely vegetated (-0708) areas During the WS mixed (0404) and

coniferous forests (0255) were the strongest preference The strongest avoidance was for freshwater (-0704)

and sparsely vegetated areas (-0655)

South During the GS the strongest preference for grasslandmoors (0287) and clear fells (0165) The

strongest avoidance was for urban areas (-0678) and mixed forests (-0491) During the WS grasslandmoors

(0425) and coniferous forests (0154) were the strongest preference The strongest avoidance was for urban (-

0876) and freshwater areas (-0587) (appendix E)

17 Diet

Diet analysis of the rumen content sampled from five individuals (C=2 S=3) revealed that almost two thirds

(69) of the diet is comprised of agricultural produce (apple winter rape and sugar beet) (Fig 6)

Fig 6 Diet analysis from the rumen samples of five moose individuals that were culled in 2013

31

2117

9

8

5

22

1 1

1

1

1 00 0

0

0Diet (2610-911 2013 5 individuals)

AppleWinter RapeSugar BeetUndefined WoodSallowBroad-leaf GrassPineAshOakCloverCurrantsUndefined plantElderberryJuniperRaspberry

18

Calf Survival

Of the 18 individuals 13 produced calves in which 7 produced twins giving a total of 20 calves A Kaplan-

Meier estimate was conducted to measure the fraction of calves living up to each period of the study (Fig 7)

The mean survival time is until period 235 (midend of summer) At the start of summer 85 of calves

remained (3 still born) The period between summer and before the hunt survival drops to 30 The survival

at the end of the study (after hunt) drops further to 20 leaving 4 calves surviving (see appendix B)

Fig 7 Kaplan-Meier estimate of moose calf survival during the study period Period 0 (Start of summer) period 1

(midend of summer) period 2 (before hunt) period 3 (after hunt) period 4 (after winter)

19 Discussion

The results of this study emphasised how strikingly different the habitat composition is along the latitudinal

gradient of Oumlland The three areas show contrasting proportions of the key habitat types The starkest

difference is the high proportion of coniferous forests and lack of agriculture in the north compared to the

centre and south The proportion of coniferous forest in the north is almost 5 times greater than in the centre

and south whereas the proportion of agriculture in the centre and south is more than double that in the north

The north is perceived to be composed of the most suitable habitat for moose (Dussault et al 2006) It has the

largest proportions of each forest type and a low proportion of agricultural land This provides suitable forage

and shelter throughout the year The south has a contrasting habitat composition to the north The proportions

of agricultural and sparsely vegetated areas are the highest between the three areas and the proportions of forest

habitats are the lowest The large proportion of sparsely vegetated areas and low proportions of forest habitat

corresponds to the large area of Stora Alvaret This is perceived to be the least suitable area due to a lack of

shelter (coniferous forest) and suitable forage The strong preference for coniferous and younger forest habitats

in the south would suggest that moose exhibit a functional response in habitat selection (Godvik et al 2009)

ie as the proportion of a particular habitat decreases the selection for that habitat increases in this case

coniferous forests which provide shelter and younger forest which provide good forage Similarly in the centre

moose show strong preference for mixed forests a habitat that is of low proportion

In view of the large variation in habitat proportions between the areas it is surprising that there is not a large

variation in the home range sizes or the activity levels annually or seasonally Home ranges are ultimately

chosen to maximise fitness and meet energy requirements by utilizing the available forage Seasonal conditions

change the availability and necessity of resources (food quality shelter) Unlike the GS during the WS

deciduous trees and shrubs are leafless and low-lying shrubs are under snow cover (Dussault et al 2005)

These changes are well known to cause populations to alter their activity and home ranges to meet energy

requirements (Mysterud et al 2001) Populations have been shown to increase or decrease their home ranges

during the two seasons The GS home ranges are often larger than the WS home ranges (Philips et al 1973

Mysterud et al 2001) In some cases they can be found to be almost double the size of the WS home ranges

(Cederlund and Okarma 1988) In other populations the WS home ranges are double the size of the GS home

ranges (Lynch and Morgantini 1984) or sizes do not significantly differ (Cederlund and Sand 1994)

Previous studies on moose find females generally show increased activity from the start on the GS due to

various factors eg reduced ruminating times increased metabolic needs and increased foraging bursts

(Wattles and DeStefano 2013) Increased metabolic needs during this time are a results of pregnancy and

lactation (Georgii 1980) During the height of the GS they usually show reduced activity levels through times

of increased thermal stress (Renecker and Hudson 1989 van Beest et al 2012) During the WS the depth and

the duration of snow cover are well known to affect the activity level (Telfer 1970 Mysterud and Oslashstbye 1999

Bjoslashrneraas et al 2011) During the WS generally home ranges are smaller and activity less due to lower

metabolic needs Moose activity is constrained by rumination during the WS this period is known to be longer

due to the change in diet (Cederlund 1989 Renecker Hudson 1989) This was not the case on Ӧland activity

20

was lowest in February which is a similar result to Cederlundrsquos (1989) paper However Ӧland moose did not

significantly alter their seasonal activity levels The fact that the annual and seasonal activity levels and home

ranges were similar could be a result of the mild winters on Oumlland during the study period (Smhise 2014)

During the study period the average number of snow days was 80 and the mean snow depth was 10cm

(appendix F) (Swedish Meterological and Hydrological Institute- SMHI) These mild conditions do not restrict

the movement of moose or obscure forage Moose are well adapted for movement in deep snow depths of 60-

86cm (Prescott 1968) are needed to truly restrict movement This finding was similar to the Sweanor and

Sandegren (1989) and Cederlund and Sand (1994) where the snow depth at their sites did not reach movement

restricting depths

The survival curve illustrates just how bad the calf survival is on Ӧland Survival falls from 85 at the start to

20 Out of 20 calves only four were alive at the end of the study The sharpest fall in survival was the period

between end of summer and before the hunt so the deaths were not due to hunting Previous calf autopsies

(Malmsten 2014a) have shown that cause of death was starvation mothers possibly either did not have milk

the calf was unable to feed or the mother abandoned the calf Closer field based observations are needed to

attain this knowledge Moose are seasonal polyoestral mammals (Monfort et al 1993) coming into oestrus

during late September early October (Garel et al 2009) (appendix F) The diet of the mother influences the

health of the calf and this period is when sodium is hard to find sodium is a key mineral in moose diets for

features such as reproduction (Belovsky and Jordan 1981) Moose gain sodium mainly through aquatic plants

(MacCracken et al 1993) However the compositional analysis shows that freshwater areas are often ranked

as one of the lowest used habitats and coastal areas were removed as the proportion found in the home ranges

was extremely low The Jacobs Index shows that the moose only prefer freshwater areas in the north UD50

during the WS The north individuals again are those that are showing typical moose habitat selection

It is known that habitat selection is hierarchical with habitats that increase fitness selected for and the effects

of limiting factors are reduced (Rettie and Messier 2000) At the UD95 during the GS moose preferred areas

of good forage (forests) and avoided areas of low forage (freshwater and sparsely vegetated areas) and areas

close to humans (urban) This is consistent with other reports (Laurian et al 2008 Torres et al 2011) Within

the UD50 there is a shift in preferences The good forage areas are again preferred during the GS however

during WS the only preferred habitat is often agricultural land During the WS there could be a steady supply

of supplementary feed available hence the high levels of agricultural produce found in the rumen content

samples and the high preference of agricultural areas This diet is unusual for moose previous studies of

Swedish moose diet have found the GS diet was dominated by birch willow and herbaceous plants and the

WS diet dominated by pine and birch (Cederlund and Nystrom 1981) The diet analysis was conducted during

the WS instead of being dominant pine composed just 2 Birch did not appear however unidentified wood

composed only 9 whereas agricultural produce accounted for 69 Supplementary feed may be perceived

by the moose in the centre and south as a vital forage source during the WS In fact in the centre the

agricultural land is the only preferred habitat at the UD50 It is unknown whether there are salt licks provided

in these areas Selection for a critical habitat is often thought to be a fixed factor The Oumlland population from

21 the three areas are close in proximity however they displayed contrasting preferences This is supported by the

Osko et al (2004) report that found two neighbouring moose populations that had access to the same habitats

displayed contrasting preferences Habitat preferences for populations of the same species are not necessarily

fixed They alter with varying levels of habitat abundance and limiting factors skewing what is preserved to

be critical

The main limitation encountered in this study was with the limited sample There was only data on two

individuals from the north of the island which led it being removed from many of the analysis Similarly due

to a lack of relocations from the collars being turned off at points throughout the year two further individuals

had to be removed from a majority of the analysis This reduced the sample size to 17 or 18 individuals

Similarly only 13 of the individuals from the study produced calves This unfortunately prevented including

survival into models Although the sample size was small it was accurate it was of high resolution over

300000 GPS points In future it would be beneficial to have a more standardised data set An equal sample of

individuals from the three areas would be advised along with ensuring the GPS collars are kept turned on for

the entirety of the growing and winter season to allow comparisons between years It would also be

advantageous to collect coordinates of the feeding sites along with the composition This could then be

compared with high use UD coordinates to look if moose are truly spending a majority of their foraging time

at feeding stations A study on the population densities of moose and the increasing population of roe deer

(Capreolus capreolus) would add the factor of competition into the model

The low calf survival on Ӧland is most likely the result of a combination of factors The lack of suitable habitat

reported in this study in conjunction with Malmstenrsquos (2014a) report on the threat of disease (Anaplasma

phagocytophilum) are probable influences on the calf survival on Ӧland On Ӧland there is an increasing

population of roe deer and large numbers of migratory birds both carriers of ticks and diseases The mild

conditions on Ӧland are advantageous for ticks the carriers of A phagocytophilum Fewer snow days and

shorter periods of snow cover along with dry conditions are favourable for ticks This could probably be one

of the reasons for females to be of lower quality and therefore not being able to ensure calf survival Moose

have to utilise areas where in other populations individuals tend to avoid Finally similar to many studies I

advocate further research using a stronger dataset and longer term monitoring

22

Acknowledgements

I am indebted to NJ Singh and A Allen for all their help and guidance through the whole of this study I

thank SLU for the support provided during this study in terms of data finances and facilities Thank you to

everyone at the Department of Wildlife Fish and Environmental Studies for being so friendly and

supportive I would like to thank L Edenius for driving me around the study area and S Michon and H

Khalil for keeping me sane with fika and training

23 References

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Bradshaw RHW Hannon GE Lister AM (2003) A long-term perspective on ungulate-vegetation

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Brandin E (2009) Versions of lsquowildrsquo and the importance of fences in Swedish wildlife tourism involving

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24346-352

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Bunnefeld N Boumlrger L van Moorter B Rolandsen CM Dettki H Solberg EJ Ericsson G(2011) A model-

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Crecircte M Courtois R (1997) Limiting factors might obscure population regulation of moose (Cervidae Alces

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ranging moose Alces alces Ecology 821613-1620

Ericsson G Ball JP Danell K (2002) Moose offspring body mass along an altitudinal gradient Journal of

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Ericsson G Malmsten J Neumann W Singh NJ Dali AM Submitted Summer Calf Survival of

Scandinavian Moose along its Southern Distribution Range

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success in muskoxen Journal of Zoology 24313-20

30

Appendix A

Introduction

Fig 1 Summary chart of factors affecting the life history and therefore the long term fitness of a population

Fig 2 Summary chart 2

Movement

Habitat

Climate

Topography

Competition

FoodWater

Disease

Die

Survive

Reproduce

Population long term fitness

31 Appendix B

Method and Materials

Fig 1 Summary of processes

32

Fig 2 Examples of classical kernel home range output and Brownian bridge kernel home range (Calenge 2011) The

right image includes the area between relocations ie the movement path in contrast to the classic kernel home range

in the left image

33 Appendix C

Home ranges

Fig 1 Example of a non-migratory (ID006) individuals BRB kernel area From top left annual growing and winter

season UD50 (black contour) and UD95 (red contour)

Fig 2 Example of a migratory (ID012) individuals BRB kernel area From the left annual growing and winter season

UD50 (black contour) and UD95 (red contour)

34

Table 1 Annual and seasonal UD50 and UD95 areas (ha) for all individuals

ID Annual GS WS

UD50 UD95 UD50 UD95 UD50 UD95

ID004 190 924 93 531 173 941

ID005 230 1364 132 945 72 682

ID006 162 1036 89 736 70 611

ID008 277 1536 156 809 78 738

ID009 137 834 48 295 126 653

ID010 114 682 83 448 96 488

ID012 177 963 123 544 76 545

ID014 160 1018 87 575 89 662

ID015 172 858 128 532 109 679

ID016 156 1047 65 455 92 534

ID017 153 1088 149 1043 69 349

ID019 279 1097 176 911 163 824

ID020 139 1084 67 349 160 794

ID022 159 811 131 638 61 454

ID023 187 1061 147 771 72 705

ID024 146 725 165 705 101 458

ID026 142 605 99 442 125 547

ID027 126 567 75 461 48 277

35 Appendix D

Activity

Fig 1 Mean daily movement during the study period GS 23-April-2012 to 07-Nov-2012 WS 08-Nov-2012 to

22-April-2013 (number indicates month)

Fig 2 Mean daily movement in the centre and south during the GS and WS

36

Appendix E

Habitat Proportions

Fig 1 All individualsrsquo seasonal habitat proportions within the UD95

37 Habitat Selection

Table 1 Simplified ranking matrices comparing proportional habitat use within the second order (UD95Area) with

proportions of total available habitat types Mean value on the matrix was replaced by a sign a triple sign represents

significant deviation from random at P lt05 Highlighted habitat is ranked 1st

North A

gri

cult

ure

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 --- --- - +++ --- --- --- +++ +++ --- 8

Broad Leaf +++ 0 +++ + +++ +++ +++ + +++ +++ +++ 1

Clear Fell +++ --- 0 + +++ - - --- +++ +++ --- 7

Coniferous + - - 0 +++ - - --- +++ +++ - 6

Freshwater --- --- --- --- 0 --- --- --- +++ - --- 10

Grassland

Moors +++ --- + + +++ 0 +++ - +++ +++ + 3

MiresMarshes +++ --- + + +++ --- 0 - +++ +++ --- 5

Mixed +++ - +++ +++ +++ + + 0 +++ +++ + 2

Sparse Veg --- --- --- --- --- --- --- --- 0 --- --- 11

Urban --- --- --- --- + --- --- --- +++ 0 --- 9

Younger +++ --- +++ + +++ - +++ - +++ +++ 0 4

Rank Order and

Significance

Broad Leafgt Mixedgt GrasslandMoorsgt Youngergtgtgt MiresMarshesgt Coniferousgt

Clear Fellgtgtgt Agriculturegtgtgt Urbangt Freshwatergtgtgt Sparse Veg

Central

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 --- --- --- + +++ + --- +++ +++ --- 6

Broad Leaf +++ 0 +++ + +++ +++ + - +++ +++ - 3

Clear Fell +++ --- 0 - +++ +++ + --- +++ +++ --- 5

Coniferous +++ - + 0 +++ +++ + --- +++ +++ - 4

Freshwater - --- --- --- 0 +++ - --- +++ +++ --- 8

Grassland

Moors --- --- --- --- --- 0 --- --- +++ - --- 10

MiresMarshes - - - - + +++ 0 - +++ +++ - 7

Mixed +++ + +++ +++ +++ +++ + 0 +++ +++ + 1

Sparse Veg --- --- --- --- --- --- --- --- 0 - --- 11

Urban --- --- --- --- --- + --- --- + 0 --- 9

Younger +++ + +++ + +++ +++ + - +++ +++ 0 2

Rank Order and

Significance

Mixedgt Youngergt Broad Leafgt Coniferousgt Clear Fellgtgtgt Agriculturegt

MiresMarshesgt Freshwatergtgtgt Urbangt GrasslandMoorsgtgtgt Sparse Veg

38

South

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 + - - + - + +++ +++ +++ - 5

Broad Leaf - 0 - - + - - +++ + +++ - 7

Clear Fell + + 0 - + + + +++ + +++ + 2

Coniferous + + + 0 +++ + + +++ + +++ + 1

Freshwater - - - --- 0 - - + + +++ - 8

Grassland

Moors + + - - + 0 + + +++ + - 4

MiresMarshes - + - - + - 0 +++ + +++ - 6

Mixed --- --- --- --- - - --- 0 + + --- 10

Sparse Veg --- - - - - --- - - 0 + - 9

Urban --- --- --- --- --- - --- - - 0 --- 11

Younger + + - - + + + +++ + +++ 0 3

Rank Order

and

Significance

Coniferousgt Clear Fellgt Youngergt GrasslandMoorsgt Agriculturegt MiresMarshesgt Broad Leafgt

Freshwatergt Sparse Veggt Mixedgt Urban

Table 2 Simplified ranking matrices comparing proportional habitat use within the third order (UD50UD95) with

proportions of total available habitat types Mean value on the matrix was replaced by a sign a triple sign represents

significant deviation from random at P lt05 Highlighted habitat is ranked 1st

North

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 --- --- --- - + --- --- + +++ --- 8

Broad Leaf +++ 0 +++ + + + + + +++ +++ + 1

Clear Fell +++ --- 0 + + + - - + +++ - 5

Coniferous +++ - - 0 + + --- --- +++ +++ - 6

Freshwater + - - - 0 +++ - - +++ +++ - 7

GrasslandMoors - - - - --- 0 - - - + - 10

MiresMarshes +++ - + +++ + + 0 - +++ +++ + 3

Mixed +++ - + +++ + + + 0 +++ +++ + 2

Sparse Veg - --- - --- --- + --- --- 0 +++ --- 9

Urban --- --- --- --- --- - --- --- --- 0 --- 11

Younger +++ - + + + + - - +++ +++ 0 4

Rank Order and

Significance

Broad Leafgt Mixedgt MiresMarshesgt Youngergt Clear Fellgt Coniferousgt Freshwatergt

Agriculturegt Sparse Veggt GrasslandMoorsgt Urban

39

Central

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 --- --- + + - - - + +++ --- 7

Broad Leaf +++ 0 + +++ + + + + + +++ - 2

Clear Fell +++ - 0 +++ + + + + + +++ - 3

Coniferous - --- --- 0 + - - --- +++ + --- 8

Freshwater - - - - 0 --- - - --- - - 11

GrasslandMoors + - - + +++ 0 + - + +++ - 5

MiresMarshes + - - + + - 0 + + +++ - 6

Mixed + - - +++ + + - 0 +++ +++ - 4

Sparse Veg - - - --- +++ - - --- 0 +++ - 9

Urban --- --- --- - + --- --- --- --- 0 --- 10

Younger +++ + + +++ + + + + + +++ 0 1

Rank Order and

Significance

Youngergt Broad Leafgt Clear Fellgt Mixedgt GrasslandMoorsgt MiresMarshesgt

Agriculturegt Coniferousgtgtgt Sparse Veggtgtgt Urbangt Freshwater

South

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 - - - - - + - +++ + --- 8

Broad Leaf + 0 - --- + - + - +++ + - 6

Clear Fell + + 0 - + - + - +++ + - 4

Coniferous + +++ + 0 + + +++ + +++ + + 1

Freshwater + - - - 0 - - + + + - 7

GrasslandMoors + + + - + 0 + + + + - 3

MiresMarshes - - - --- + - 0 - + + - 9

Mixed + + + - - - + 0 + + - 5

Sparse Veg --- --- --- --- - - - - 0 + --- 10

Urban - - - - - - - - - 0 - 11

Younger +++ + + - + + + + +++ + 0 2

Rank Order and

Significance

Coniferousgt Youngergt GrasslandMoorsgt Clear Fellgt Mixedgt Broad Leafgt Freshwatergt

Agriculturegt MiresMarshesgt Sparse Veggt Urban

40

Table 3 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the GS according to Jacobs index

Ran

k North Centre South

50 95 50 95 50 95

+ - + - + - + - + - + -

1 Broad

Leaf Urban Broad Leaf Sparse Veg

Broad

Leaf Urban Mixed Urban Coniferous Urban

Grassland

Moors Urban

2 Mixed Sparse Veg Mixed Freshwater Younger Agriculture Younger Sparse Veg Younger Sparse Veg Clear Fell Mixed

3 Mires

Agriculture Grassland

Urban Clear

Fell Coniferous Broad Leaf

Grassland

Moors

Clear Fell Agriculture Coniferous Sparse Veg

Marshes Moors

4 Younger Grassland

Younger Agriculture

Freshwater Coniferous Freshwater

Broad Leaf Mires

Younger Freshwater

Moors Marshes

5 Clear

Fell Freshwater

Mires Coniferous

Sparse Veg Clear Fell Agriculture

Freshwater Agriculture

Marshes

6 Coniferous Clear Fell

Mires

Marshes

Mires

Grassland

Moors

Mires

Marshes Marshes

7 Mixed Mixed Broad Leaf

8 Grassland

Moors

41

Table 4 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the WS according to Jacobs index

Ran

k North Centre South

50 95 50 95 50 95

+ - + - + - + - + - + -

1 Mires

Marshes

Grassland

Moors Mixed Freshwater Agriculture Urban Mixed Freshwater

Grassland

Moors Urban GrasslandMoors Urban

2 Freshwater Mixed Coniferous Urban Mires

Marshes Coniferous Sparse Veg Agriculture

Sparse

Veg Coniferous Freshwater

3 Urban Coniferous Younger Grassland

Moors Freshwater Younger Urban Freshwater

Broad

Leaf Agriculture Mixed

4 Younger Agriculture Sparse Veg Broad

Leaf

Broad

Leaf

Grassland

Moors Mixed Broad Leaf

5 Clear Fell Agriculture Coniferous Agriculture Mires

Marshes Clear Fell

6 Sparse

Veg

Mires

Marshes Mixed

Mires

Marshes

Clear

Fell

Mires

Marshes

7 Broad

Leaf Clear Fell Younger Clear Fell Younger Sparse Veg

8 Clear Fell Younger

9 Sparse

Veg

10 Grassland

Moors

42

Table 5 Second order (UD95Area) individual selectionavoidance for the GS and WS according to the Jacobs index

ID GS WS

Select Avoid Select Avoid

ID004 Younger Sparsely Vegetated MiresMarshes Sparsely Vegetated

ID005 MiresMarshes Sparsely Vegetated Coniferous GrasslandMoors

ID006 Coniferous Sparsely Vegetated Mixed Freshwater

ID008 Mixed Sparsely Vegetated Mixed Freshwater

ID009 Mixed Sparsely Vegetated Mixed GrasslandMoors

ID010 MiresMarshes Freshwater GrasslandMoors Freshwater

ID012 Broad Leaf Sparsely Vegetated Coniferous Urban

ID014 Clear Fell Sparsely Vegetated GrasslandMoors Sparsely Vegetated

ID015 GrasslandMoors Urban GrasslandMoors Freshwater

ID016 GrasslandMoors Freshwater GrasslandMoors Freshwater

ID017 GrasslandMoors Mixed Sparsely Vegetated Mixed

ID019 Mixed Sparsely Vegetated Mixed Urban

ID020 Broad Leaf Sparsely Vegetated Coniferous GrasslandMoors

ID022 MiresMarshes Freshwater MiresMarshes Freshwater

ID023 MiresMarshes GrasslandMoors Mixed Freshwater

ID024 Broadleaf Urban Broad Leaf Urban

ID026 GrasslandMoors Freshwater GrasslandMoors Freshwater

ID027 GrasslandMoors Urban Sparsely Vegetated Freshwater

43 Table 6 Third order (UD50UD95) individual selectionavoidance for the GS and WS according to the Jacobs index

ID GS WS

Select Avoid Select Avoid

ID004 Broad Leaf Mixed GrasslandMoors Freshwater

ID005 Broad Leaf Freshwater Agriculture Freshwater

ID006 Clear Fell Freshwater Agriculture MiresMarshes

ID008 MiresMarshes Freshwater Agriculture Urban

ID009 Freshwater Agriculture Agriculture Freshwater

ID010 Mixed Urban Sparsely Vegetated Urban

ID012 Coniferous GrasslandMoors Freshwater Urban

ID014 Urban Agriculture Freshwater Urban

ID015 Mixed Forest Urban Clear Fell Urban

ID016 Freshwater Urban GrasslandMoors Mixed

ID017 Coniferous Mixed Coniferous Broad Leaf

ID019 Broad Leaf GrasslandMoors Urban GrasslandMoors

ID020 Freshwater Urban Freshwater Agriculture

ID022 MiresMarshes Urban Broad Leaf GrasslandMoors

ID023 Freshwater Mixed Agriculture Freshwater

ID024 Mixed Freshwater Mixed Freshwater

ID026 Mixed MiresMarshes Sparsely Vegetated GrasslandMoors

ID027 Freshwater MiresMarshes GrasslandMoors Broad Leaf

44

Fig 2 North third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)

45

Fig 3 Centre third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)

46

Fig 4 South third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)

47

Fig 5 North second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)

48

Fig 6 Centre second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)

49

Fig 7 South second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)

50

Appendix F

Background

Fig 1 Daily mean snow depth and duration during the study period (Andrew Allen)

Female Moose Reproduction

Moose are seasonal polyoestral mammals (Monfort et al 1993) coming into oestrus during late September

early October (Garel et al 2009) The Swedish moose cow population reaches puberty between the ages 25

and 35 (Sand and Cederlund 1993) during which the reproductive period begins with the onset of ovulation

The age an individual reaches puberty is dependent on their body condition they have to reach a weight

threshold to reach puberty and become reproductive (Sand 1996) If she is over the weight threshold she will

go into oestrus in the autumn If she does not reach the weight threshold then she will go into oestrus the

following autumn if successful she will give birth to individual or twin calves in late May to early June

(Ericsson et al 2001) and therefore reach sexual maturity (Malmsten et al 2014b) Fecundity is related to

both the condition and the age of the cow Cows go through senescence at 12 years of age (Ericsson et al

2001) Providing calves with the required level of nutrition demands high energy and protein resources from

the mother during senescence this becomes harder to achieve leading to decreased levels of parental care

and higher levels of calf mortality

Page 14: Habitat-performance relationships on an island: fitness ...navinderjsingh.weebly.com/uploads/1/1/2/2/11224342/... · Conditions on Öland are milder than those found in other areas

14

Habitat - Selection

Generally forest habitat types are the highest ranked whilst sparsely vegetated and urban areas are the lowest

ranked Both the second and third order habitat selection analyses gave significant results in the compositional

analysis (Table 4) In the third order analysis (UD50UD95) the centre displayed significant differences

between habitat types The coniferous forests are significantly preferred to sparsely vegetated areas and the

sparsely vegetated areas are significantly preferred to urban areas In the second order analysis (UD95Area)

significance was observed in the north and centre In the north younger forests are significantly preferred to

miresmarshes clear felled areas are significantly preferred to agriculture and freshwater areas are significantly

preferred to sparsely vegetated areas In the centre clear felled areas are significantly preferred to agricultural

land freshwater areas are significantly preferred to urban areas and grasslandmoors are significantly preferred

to sparsely vegetated areas

Table 4 Summary of second (UD95Area bottom) and third order (UD50UD95 top) ranked habitat preferences between

the three areas according to the compositional analysis (see appendix B)

Rank North Centre South

1 Broad Leaf Younger Coniferous

2 Mixed Broad Leaf Younger

3 MiresMarshes Clear Fell GrasslandMoors

4 Younger Mixed Clear Fell

5 Clear Fell GrasslandMoors Mixed

6 Coniferous MiresMarshes Broad Leaf

7 Freshwater Agriculture Freshwater

8 Agriculture Coniferous Agriculture

9 Sparse Veg Sparse Veg MiresMarshes

10 GrasslandMoors Urban Sparse Veg

11 Urban Freshwater Urban

Rank North Centre South

1 Broad Leaf Mixed Coniferous

2 Mixed Younger Clear Fell

3 GrasslandMoors Broad Leaf Younger

4 Younger Coniferous GrasslandMoors

5 MiresMarshes Clear Fell Agriculture

6 Coniferous Agriculture MiresMarshes

7 Clear Fell MiresMarshes Broad Leaf

8 Agriculture Freshwater Freshwater

9 Urban Urban Sparse Veg

10 Freshwater GrasslandMoors Mixed

11 Sparse Veg Sparse Veg Urban

Indicates significantly preferred to the habitat below (significant deviation from random at P lt05)

15 The Jacobs index revealed that generally the habitats preferred during the GS within the home range (third

order) are younger (0187) and broad leaf forests (0154) The strongest avoidance was for urban areas (-0627)

During the WS only agricultural areas are preferred (0129) and the strongest avoidance was for urban areas (-

0393) (Fig 4)

Fig 4 Third order seasonal habitat preference (UD50UD95) all individuals The index ranges from -1 (total avoidance)

to 1 (strongest preference) Close to 0 indicates used in proportion to its availability

Third order habitat preferencesavoidances by area

North During the GS the strongest preference was for broad leaf (0218) and mixed forests (0161) The

strongest avoidance was for urban (-1) and sparsely vegetated areas (-05) During the WS the strongest

preference was for miresmarshes (0228) The strongest avoidance was for grasslandmoors (-05)

Centre During the GS the strongest preference was for broad leaf (0233) and younger forests (0223) The

strongest avoidance was for urban (-0527) and agricultural land (-0362) During the WS preference was only

shown for agricultural land (0327) The strongest avoidance was for urban areas (-0679) and miresmarshes

(-0638)

South During the GS the strongest preference was for coniferous (0312) and younger forests (0242) The

strongest avoidance was for urban (-0353) and sparsely vegetated areas (-0330) During the WS

grasslandmoors (0106) were the strongest preference The strongest avoidance was for urban (-0666) and

sparsely vegetated areas (-0351)

16

The Jacobs indices revealed that generally the habitats preferred during the GS within the landscape

(UD95Area) are broad leaf (0216) and younger forests (0201) The strongest avoidance was for urban (-

0717) and freshwater areas (-0694) The strongest preference during the WS are coniferous forests (0242)

and the strongest avoidance was for freshwater (-0674) and urban areas (-0648) (Fig 5)

Fig 5 Second order seasonal habitat preference (UD50UD95) all individuals The index ranges from -1 (total avoidance)

to 1 (strongest preference) Close to 0 indicates used in proportion to its availability

Second order habitat preferencesavoidances by area

North During the GS the strongest preference was for broad leaf (0363) and mixed forests (00291) The

strongest avoidance was for sparsely vegetated (-0909) and freshwater areas (-0780) During the WS mixed

(0335) and coniferous forests (0316) were the strongest preference The strongest avoidance was for

freshwater (-0731) and urban areas (-05333)

Centre During the GS the strongest preference for mixed (0394) and younger forests (0286) The strongest

avoidance was for urban (-0733) and sparsely vegetated (-0708) areas During the WS mixed (0404) and

coniferous forests (0255) were the strongest preference The strongest avoidance was for freshwater (-0704)

and sparsely vegetated areas (-0655)

South During the GS the strongest preference for grasslandmoors (0287) and clear fells (0165) The

strongest avoidance was for urban areas (-0678) and mixed forests (-0491) During the WS grasslandmoors

(0425) and coniferous forests (0154) were the strongest preference The strongest avoidance was for urban (-

0876) and freshwater areas (-0587) (appendix E)

17 Diet

Diet analysis of the rumen content sampled from five individuals (C=2 S=3) revealed that almost two thirds

(69) of the diet is comprised of agricultural produce (apple winter rape and sugar beet) (Fig 6)

Fig 6 Diet analysis from the rumen samples of five moose individuals that were culled in 2013

31

2117

9

8

5

22

1 1

1

1

1 00 0

0

0Diet (2610-911 2013 5 individuals)

AppleWinter RapeSugar BeetUndefined WoodSallowBroad-leaf GrassPineAshOakCloverCurrantsUndefined plantElderberryJuniperRaspberry

18

Calf Survival

Of the 18 individuals 13 produced calves in which 7 produced twins giving a total of 20 calves A Kaplan-

Meier estimate was conducted to measure the fraction of calves living up to each period of the study (Fig 7)

The mean survival time is until period 235 (midend of summer) At the start of summer 85 of calves

remained (3 still born) The period between summer and before the hunt survival drops to 30 The survival

at the end of the study (after hunt) drops further to 20 leaving 4 calves surviving (see appendix B)

Fig 7 Kaplan-Meier estimate of moose calf survival during the study period Period 0 (Start of summer) period 1

(midend of summer) period 2 (before hunt) period 3 (after hunt) period 4 (after winter)

19 Discussion

The results of this study emphasised how strikingly different the habitat composition is along the latitudinal

gradient of Oumlland The three areas show contrasting proportions of the key habitat types The starkest

difference is the high proportion of coniferous forests and lack of agriculture in the north compared to the

centre and south The proportion of coniferous forest in the north is almost 5 times greater than in the centre

and south whereas the proportion of agriculture in the centre and south is more than double that in the north

The north is perceived to be composed of the most suitable habitat for moose (Dussault et al 2006) It has the

largest proportions of each forest type and a low proportion of agricultural land This provides suitable forage

and shelter throughout the year The south has a contrasting habitat composition to the north The proportions

of agricultural and sparsely vegetated areas are the highest between the three areas and the proportions of forest

habitats are the lowest The large proportion of sparsely vegetated areas and low proportions of forest habitat

corresponds to the large area of Stora Alvaret This is perceived to be the least suitable area due to a lack of

shelter (coniferous forest) and suitable forage The strong preference for coniferous and younger forest habitats

in the south would suggest that moose exhibit a functional response in habitat selection (Godvik et al 2009)

ie as the proportion of a particular habitat decreases the selection for that habitat increases in this case

coniferous forests which provide shelter and younger forest which provide good forage Similarly in the centre

moose show strong preference for mixed forests a habitat that is of low proportion

In view of the large variation in habitat proportions between the areas it is surprising that there is not a large

variation in the home range sizes or the activity levels annually or seasonally Home ranges are ultimately

chosen to maximise fitness and meet energy requirements by utilizing the available forage Seasonal conditions

change the availability and necessity of resources (food quality shelter) Unlike the GS during the WS

deciduous trees and shrubs are leafless and low-lying shrubs are under snow cover (Dussault et al 2005)

These changes are well known to cause populations to alter their activity and home ranges to meet energy

requirements (Mysterud et al 2001) Populations have been shown to increase or decrease their home ranges

during the two seasons The GS home ranges are often larger than the WS home ranges (Philips et al 1973

Mysterud et al 2001) In some cases they can be found to be almost double the size of the WS home ranges

(Cederlund and Okarma 1988) In other populations the WS home ranges are double the size of the GS home

ranges (Lynch and Morgantini 1984) or sizes do not significantly differ (Cederlund and Sand 1994)

Previous studies on moose find females generally show increased activity from the start on the GS due to

various factors eg reduced ruminating times increased metabolic needs and increased foraging bursts

(Wattles and DeStefano 2013) Increased metabolic needs during this time are a results of pregnancy and

lactation (Georgii 1980) During the height of the GS they usually show reduced activity levels through times

of increased thermal stress (Renecker and Hudson 1989 van Beest et al 2012) During the WS the depth and

the duration of snow cover are well known to affect the activity level (Telfer 1970 Mysterud and Oslashstbye 1999

Bjoslashrneraas et al 2011) During the WS generally home ranges are smaller and activity less due to lower

metabolic needs Moose activity is constrained by rumination during the WS this period is known to be longer

due to the change in diet (Cederlund 1989 Renecker Hudson 1989) This was not the case on Ӧland activity

20

was lowest in February which is a similar result to Cederlundrsquos (1989) paper However Ӧland moose did not

significantly alter their seasonal activity levels The fact that the annual and seasonal activity levels and home

ranges were similar could be a result of the mild winters on Oumlland during the study period (Smhise 2014)

During the study period the average number of snow days was 80 and the mean snow depth was 10cm

(appendix F) (Swedish Meterological and Hydrological Institute- SMHI) These mild conditions do not restrict

the movement of moose or obscure forage Moose are well adapted for movement in deep snow depths of 60-

86cm (Prescott 1968) are needed to truly restrict movement This finding was similar to the Sweanor and

Sandegren (1989) and Cederlund and Sand (1994) where the snow depth at their sites did not reach movement

restricting depths

The survival curve illustrates just how bad the calf survival is on Ӧland Survival falls from 85 at the start to

20 Out of 20 calves only four were alive at the end of the study The sharpest fall in survival was the period

between end of summer and before the hunt so the deaths were not due to hunting Previous calf autopsies

(Malmsten 2014a) have shown that cause of death was starvation mothers possibly either did not have milk

the calf was unable to feed or the mother abandoned the calf Closer field based observations are needed to

attain this knowledge Moose are seasonal polyoestral mammals (Monfort et al 1993) coming into oestrus

during late September early October (Garel et al 2009) (appendix F) The diet of the mother influences the

health of the calf and this period is when sodium is hard to find sodium is a key mineral in moose diets for

features such as reproduction (Belovsky and Jordan 1981) Moose gain sodium mainly through aquatic plants

(MacCracken et al 1993) However the compositional analysis shows that freshwater areas are often ranked

as one of the lowest used habitats and coastal areas were removed as the proportion found in the home ranges

was extremely low The Jacobs Index shows that the moose only prefer freshwater areas in the north UD50

during the WS The north individuals again are those that are showing typical moose habitat selection

It is known that habitat selection is hierarchical with habitats that increase fitness selected for and the effects

of limiting factors are reduced (Rettie and Messier 2000) At the UD95 during the GS moose preferred areas

of good forage (forests) and avoided areas of low forage (freshwater and sparsely vegetated areas) and areas

close to humans (urban) This is consistent with other reports (Laurian et al 2008 Torres et al 2011) Within

the UD50 there is a shift in preferences The good forage areas are again preferred during the GS however

during WS the only preferred habitat is often agricultural land During the WS there could be a steady supply

of supplementary feed available hence the high levels of agricultural produce found in the rumen content

samples and the high preference of agricultural areas This diet is unusual for moose previous studies of

Swedish moose diet have found the GS diet was dominated by birch willow and herbaceous plants and the

WS diet dominated by pine and birch (Cederlund and Nystrom 1981) The diet analysis was conducted during

the WS instead of being dominant pine composed just 2 Birch did not appear however unidentified wood

composed only 9 whereas agricultural produce accounted for 69 Supplementary feed may be perceived

by the moose in the centre and south as a vital forage source during the WS In fact in the centre the

agricultural land is the only preferred habitat at the UD50 It is unknown whether there are salt licks provided

in these areas Selection for a critical habitat is often thought to be a fixed factor The Oumlland population from

21 the three areas are close in proximity however they displayed contrasting preferences This is supported by the

Osko et al (2004) report that found two neighbouring moose populations that had access to the same habitats

displayed contrasting preferences Habitat preferences for populations of the same species are not necessarily

fixed They alter with varying levels of habitat abundance and limiting factors skewing what is preserved to

be critical

The main limitation encountered in this study was with the limited sample There was only data on two

individuals from the north of the island which led it being removed from many of the analysis Similarly due

to a lack of relocations from the collars being turned off at points throughout the year two further individuals

had to be removed from a majority of the analysis This reduced the sample size to 17 or 18 individuals

Similarly only 13 of the individuals from the study produced calves This unfortunately prevented including

survival into models Although the sample size was small it was accurate it was of high resolution over

300000 GPS points In future it would be beneficial to have a more standardised data set An equal sample of

individuals from the three areas would be advised along with ensuring the GPS collars are kept turned on for

the entirety of the growing and winter season to allow comparisons between years It would also be

advantageous to collect coordinates of the feeding sites along with the composition This could then be

compared with high use UD coordinates to look if moose are truly spending a majority of their foraging time

at feeding stations A study on the population densities of moose and the increasing population of roe deer

(Capreolus capreolus) would add the factor of competition into the model

The low calf survival on Ӧland is most likely the result of a combination of factors The lack of suitable habitat

reported in this study in conjunction with Malmstenrsquos (2014a) report on the threat of disease (Anaplasma

phagocytophilum) are probable influences on the calf survival on Ӧland On Ӧland there is an increasing

population of roe deer and large numbers of migratory birds both carriers of ticks and diseases The mild

conditions on Ӧland are advantageous for ticks the carriers of A phagocytophilum Fewer snow days and

shorter periods of snow cover along with dry conditions are favourable for ticks This could probably be one

of the reasons for females to be of lower quality and therefore not being able to ensure calf survival Moose

have to utilise areas where in other populations individuals tend to avoid Finally similar to many studies I

advocate further research using a stronger dataset and longer term monitoring

22

Acknowledgements

I am indebted to NJ Singh and A Allen for all their help and guidance through the whole of this study I

thank SLU for the support provided during this study in terms of data finances and facilities Thank you to

everyone at the Department of Wildlife Fish and Environmental Studies for being so friendly and

supportive I would like to thank L Edenius for driving me around the study area and S Michon and H

Khalil for keeping me sane with fika and training

23 References

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success in muskoxen Journal of Zoology 24313-20

30

Appendix A

Introduction

Fig 1 Summary chart of factors affecting the life history and therefore the long term fitness of a population

Fig 2 Summary chart 2

Movement

Habitat

Climate

Topography

Competition

FoodWater

Disease

Die

Survive

Reproduce

Population long term fitness

31 Appendix B

Method and Materials

Fig 1 Summary of processes

32

Fig 2 Examples of classical kernel home range output and Brownian bridge kernel home range (Calenge 2011) The

right image includes the area between relocations ie the movement path in contrast to the classic kernel home range

in the left image

33 Appendix C

Home ranges

Fig 1 Example of a non-migratory (ID006) individuals BRB kernel area From top left annual growing and winter

season UD50 (black contour) and UD95 (red contour)

Fig 2 Example of a migratory (ID012) individuals BRB kernel area From the left annual growing and winter season

UD50 (black contour) and UD95 (red contour)

34

Table 1 Annual and seasonal UD50 and UD95 areas (ha) for all individuals

ID Annual GS WS

UD50 UD95 UD50 UD95 UD50 UD95

ID004 190 924 93 531 173 941

ID005 230 1364 132 945 72 682

ID006 162 1036 89 736 70 611

ID008 277 1536 156 809 78 738

ID009 137 834 48 295 126 653

ID010 114 682 83 448 96 488

ID012 177 963 123 544 76 545

ID014 160 1018 87 575 89 662

ID015 172 858 128 532 109 679

ID016 156 1047 65 455 92 534

ID017 153 1088 149 1043 69 349

ID019 279 1097 176 911 163 824

ID020 139 1084 67 349 160 794

ID022 159 811 131 638 61 454

ID023 187 1061 147 771 72 705

ID024 146 725 165 705 101 458

ID026 142 605 99 442 125 547

ID027 126 567 75 461 48 277

35 Appendix D

Activity

Fig 1 Mean daily movement during the study period GS 23-April-2012 to 07-Nov-2012 WS 08-Nov-2012 to

22-April-2013 (number indicates month)

Fig 2 Mean daily movement in the centre and south during the GS and WS

36

Appendix E

Habitat Proportions

Fig 1 All individualsrsquo seasonal habitat proportions within the UD95

37 Habitat Selection

Table 1 Simplified ranking matrices comparing proportional habitat use within the second order (UD95Area) with

proportions of total available habitat types Mean value on the matrix was replaced by a sign a triple sign represents

significant deviation from random at P lt05 Highlighted habitat is ranked 1st

North A

gri

cult

ure

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 --- --- - +++ --- --- --- +++ +++ --- 8

Broad Leaf +++ 0 +++ + +++ +++ +++ + +++ +++ +++ 1

Clear Fell +++ --- 0 + +++ - - --- +++ +++ --- 7

Coniferous + - - 0 +++ - - --- +++ +++ - 6

Freshwater --- --- --- --- 0 --- --- --- +++ - --- 10

Grassland

Moors +++ --- + + +++ 0 +++ - +++ +++ + 3

MiresMarshes +++ --- + + +++ --- 0 - +++ +++ --- 5

Mixed +++ - +++ +++ +++ + + 0 +++ +++ + 2

Sparse Veg --- --- --- --- --- --- --- --- 0 --- --- 11

Urban --- --- --- --- + --- --- --- +++ 0 --- 9

Younger +++ --- +++ + +++ - +++ - +++ +++ 0 4

Rank Order and

Significance

Broad Leafgt Mixedgt GrasslandMoorsgt Youngergtgtgt MiresMarshesgt Coniferousgt

Clear Fellgtgtgt Agriculturegtgtgt Urbangt Freshwatergtgtgt Sparse Veg

Central

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 --- --- --- + +++ + --- +++ +++ --- 6

Broad Leaf +++ 0 +++ + +++ +++ + - +++ +++ - 3

Clear Fell +++ --- 0 - +++ +++ + --- +++ +++ --- 5

Coniferous +++ - + 0 +++ +++ + --- +++ +++ - 4

Freshwater - --- --- --- 0 +++ - --- +++ +++ --- 8

Grassland

Moors --- --- --- --- --- 0 --- --- +++ - --- 10

MiresMarshes - - - - + +++ 0 - +++ +++ - 7

Mixed +++ + +++ +++ +++ +++ + 0 +++ +++ + 1

Sparse Veg --- --- --- --- --- --- --- --- 0 - --- 11

Urban --- --- --- --- --- + --- --- + 0 --- 9

Younger +++ + +++ + +++ +++ + - +++ +++ 0 2

Rank Order and

Significance

Mixedgt Youngergt Broad Leafgt Coniferousgt Clear Fellgtgtgt Agriculturegt

MiresMarshesgt Freshwatergtgtgt Urbangt GrasslandMoorsgtgtgt Sparse Veg

38

South

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 + - - + - + +++ +++ +++ - 5

Broad Leaf - 0 - - + - - +++ + +++ - 7

Clear Fell + + 0 - + + + +++ + +++ + 2

Coniferous + + + 0 +++ + + +++ + +++ + 1

Freshwater - - - --- 0 - - + + +++ - 8

Grassland

Moors + + - - + 0 + + +++ + - 4

MiresMarshes - + - - + - 0 +++ + +++ - 6

Mixed --- --- --- --- - - --- 0 + + --- 10

Sparse Veg --- - - - - --- - - 0 + - 9

Urban --- --- --- --- --- - --- - - 0 --- 11

Younger + + - - + + + +++ + +++ 0 3

Rank Order

and

Significance

Coniferousgt Clear Fellgt Youngergt GrasslandMoorsgt Agriculturegt MiresMarshesgt Broad Leafgt

Freshwatergt Sparse Veggt Mixedgt Urban

Table 2 Simplified ranking matrices comparing proportional habitat use within the third order (UD50UD95) with

proportions of total available habitat types Mean value on the matrix was replaced by a sign a triple sign represents

significant deviation from random at P lt05 Highlighted habitat is ranked 1st

North

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 --- --- --- - + --- --- + +++ --- 8

Broad Leaf +++ 0 +++ + + + + + +++ +++ + 1

Clear Fell +++ --- 0 + + + - - + +++ - 5

Coniferous +++ - - 0 + + --- --- +++ +++ - 6

Freshwater + - - - 0 +++ - - +++ +++ - 7

GrasslandMoors - - - - --- 0 - - - + - 10

MiresMarshes +++ - + +++ + + 0 - +++ +++ + 3

Mixed +++ - + +++ + + + 0 +++ +++ + 2

Sparse Veg - --- - --- --- + --- --- 0 +++ --- 9

Urban --- --- --- --- --- - --- --- --- 0 --- 11

Younger +++ - + + + + - - +++ +++ 0 4

Rank Order and

Significance

Broad Leafgt Mixedgt MiresMarshesgt Youngergt Clear Fellgt Coniferousgt Freshwatergt

Agriculturegt Sparse Veggt GrasslandMoorsgt Urban

39

Central

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 --- --- + + - - - + +++ --- 7

Broad Leaf +++ 0 + +++ + + + + + +++ - 2

Clear Fell +++ - 0 +++ + + + + + +++ - 3

Coniferous - --- --- 0 + - - --- +++ + --- 8

Freshwater - - - - 0 --- - - --- - - 11

GrasslandMoors + - - + +++ 0 + - + +++ - 5

MiresMarshes + - - + + - 0 + + +++ - 6

Mixed + - - +++ + + - 0 +++ +++ - 4

Sparse Veg - - - --- +++ - - --- 0 +++ - 9

Urban --- --- --- - + --- --- --- --- 0 --- 10

Younger +++ + + +++ + + + + + +++ 0 1

Rank Order and

Significance

Youngergt Broad Leafgt Clear Fellgt Mixedgt GrasslandMoorsgt MiresMarshesgt

Agriculturegt Coniferousgtgtgt Sparse Veggtgtgt Urbangt Freshwater

South

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 - - - - - + - +++ + --- 8

Broad Leaf + 0 - --- + - + - +++ + - 6

Clear Fell + + 0 - + - + - +++ + - 4

Coniferous + +++ + 0 + + +++ + +++ + + 1

Freshwater + - - - 0 - - + + + - 7

GrasslandMoors + + + - + 0 + + + + - 3

MiresMarshes - - - --- + - 0 - + + - 9

Mixed + + + - - - + 0 + + - 5

Sparse Veg --- --- --- --- - - - - 0 + --- 10

Urban - - - - - - - - - 0 - 11

Younger +++ + + - + + + + +++ + 0 2

Rank Order and

Significance

Coniferousgt Youngergt GrasslandMoorsgt Clear Fellgt Mixedgt Broad Leafgt Freshwatergt

Agriculturegt MiresMarshesgt Sparse Veggt Urban

40

Table 3 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the GS according to Jacobs index

Ran

k North Centre South

50 95 50 95 50 95

+ - + - + - + - + - + -

1 Broad

Leaf Urban Broad Leaf Sparse Veg

Broad

Leaf Urban Mixed Urban Coniferous Urban

Grassland

Moors Urban

2 Mixed Sparse Veg Mixed Freshwater Younger Agriculture Younger Sparse Veg Younger Sparse Veg Clear Fell Mixed

3 Mires

Agriculture Grassland

Urban Clear

Fell Coniferous Broad Leaf

Grassland

Moors

Clear Fell Agriculture Coniferous Sparse Veg

Marshes Moors

4 Younger Grassland

Younger Agriculture

Freshwater Coniferous Freshwater

Broad Leaf Mires

Younger Freshwater

Moors Marshes

5 Clear

Fell Freshwater

Mires Coniferous

Sparse Veg Clear Fell Agriculture

Freshwater Agriculture

Marshes

6 Coniferous Clear Fell

Mires

Marshes

Mires

Grassland

Moors

Mires

Marshes Marshes

7 Mixed Mixed Broad Leaf

8 Grassland

Moors

41

Table 4 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the WS according to Jacobs index

Ran

k North Centre South

50 95 50 95 50 95

+ - + - + - + - + - + -

1 Mires

Marshes

Grassland

Moors Mixed Freshwater Agriculture Urban Mixed Freshwater

Grassland

Moors Urban GrasslandMoors Urban

2 Freshwater Mixed Coniferous Urban Mires

Marshes Coniferous Sparse Veg Agriculture

Sparse

Veg Coniferous Freshwater

3 Urban Coniferous Younger Grassland

Moors Freshwater Younger Urban Freshwater

Broad

Leaf Agriculture Mixed

4 Younger Agriculture Sparse Veg Broad

Leaf

Broad

Leaf

Grassland

Moors Mixed Broad Leaf

5 Clear Fell Agriculture Coniferous Agriculture Mires

Marshes Clear Fell

6 Sparse

Veg

Mires

Marshes Mixed

Mires

Marshes

Clear

Fell

Mires

Marshes

7 Broad

Leaf Clear Fell Younger Clear Fell Younger Sparse Veg

8 Clear Fell Younger

9 Sparse

Veg

10 Grassland

Moors

42

Table 5 Second order (UD95Area) individual selectionavoidance for the GS and WS according to the Jacobs index

ID GS WS

Select Avoid Select Avoid

ID004 Younger Sparsely Vegetated MiresMarshes Sparsely Vegetated

ID005 MiresMarshes Sparsely Vegetated Coniferous GrasslandMoors

ID006 Coniferous Sparsely Vegetated Mixed Freshwater

ID008 Mixed Sparsely Vegetated Mixed Freshwater

ID009 Mixed Sparsely Vegetated Mixed GrasslandMoors

ID010 MiresMarshes Freshwater GrasslandMoors Freshwater

ID012 Broad Leaf Sparsely Vegetated Coniferous Urban

ID014 Clear Fell Sparsely Vegetated GrasslandMoors Sparsely Vegetated

ID015 GrasslandMoors Urban GrasslandMoors Freshwater

ID016 GrasslandMoors Freshwater GrasslandMoors Freshwater

ID017 GrasslandMoors Mixed Sparsely Vegetated Mixed

ID019 Mixed Sparsely Vegetated Mixed Urban

ID020 Broad Leaf Sparsely Vegetated Coniferous GrasslandMoors

ID022 MiresMarshes Freshwater MiresMarshes Freshwater

ID023 MiresMarshes GrasslandMoors Mixed Freshwater

ID024 Broadleaf Urban Broad Leaf Urban

ID026 GrasslandMoors Freshwater GrasslandMoors Freshwater

ID027 GrasslandMoors Urban Sparsely Vegetated Freshwater

43 Table 6 Third order (UD50UD95) individual selectionavoidance for the GS and WS according to the Jacobs index

ID GS WS

Select Avoid Select Avoid

ID004 Broad Leaf Mixed GrasslandMoors Freshwater

ID005 Broad Leaf Freshwater Agriculture Freshwater

ID006 Clear Fell Freshwater Agriculture MiresMarshes

ID008 MiresMarshes Freshwater Agriculture Urban

ID009 Freshwater Agriculture Agriculture Freshwater

ID010 Mixed Urban Sparsely Vegetated Urban

ID012 Coniferous GrasslandMoors Freshwater Urban

ID014 Urban Agriculture Freshwater Urban

ID015 Mixed Forest Urban Clear Fell Urban

ID016 Freshwater Urban GrasslandMoors Mixed

ID017 Coniferous Mixed Coniferous Broad Leaf

ID019 Broad Leaf GrasslandMoors Urban GrasslandMoors

ID020 Freshwater Urban Freshwater Agriculture

ID022 MiresMarshes Urban Broad Leaf GrasslandMoors

ID023 Freshwater Mixed Agriculture Freshwater

ID024 Mixed Freshwater Mixed Freshwater

ID026 Mixed MiresMarshes Sparsely Vegetated GrasslandMoors

ID027 Freshwater MiresMarshes GrasslandMoors Broad Leaf

44

Fig 2 North third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)

45

Fig 3 Centre third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)

46

Fig 4 South third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)

47

Fig 5 North second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)

48

Fig 6 Centre second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)

49

Fig 7 South second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)

50

Appendix F

Background

Fig 1 Daily mean snow depth and duration during the study period (Andrew Allen)

Female Moose Reproduction

Moose are seasonal polyoestral mammals (Monfort et al 1993) coming into oestrus during late September

early October (Garel et al 2009) The Swedish moose cow population reaches puberty between the ages 25

and 35 (Sand and Cederlund 1993) during which the reproductive period begins with the onset of ovulation

The age an individual reaches puberty is dependent on their body condition they have to reach a weight

threshold to reach puberty and become reproductive (Sand 1996) If she is over the weight threshold she will

go into oestrus in the autumn If she does not reach the weight threshold then she will go into oestrus the

following autumn if successful she will give birth to individual or twin calves in late May to early June

(Ericsson et al 2001) and therefore reach sexual maturity (Malmsten et al 2014b) Fecundity is related to

both the condition and the age of the cow Cows go through senescence at 12 years of age (Ericsson et al

2001) Providing calves with the required level of nutrition demands high energy and protein resources from

the mother during senescence this becomes harder to achieve leading to decreased levels of parental care

and higher levels of calf mortality

Page 15: Habitat-performance relationships on an island: fitness ...navinderjsingh.weebly.com/uploads/1/1/2/2/11224342/... · Conditions on Öland are milder than those found in other areas

15 The Jacobs index revealed that generally the habitats preferred during the GS within the home range (third

order) are younger (0187) and broad leaf forests (0154) The strongest avoidance was for urban areas (-0627)

During the WS only agricultural areas are preferred (0129) and the strongest avoidance was for urban areas (-

0393) (Fig 4)

Fig 4 Third order seasonal habitat preference (UD50UD95) all individuals The index ranges from -1 (total avoidance)

to 1 (strongest preference) Close to 0 indicates used in proportion to its availability

Third order habitat preferencesavoidances by area

North During the GS the strongest preference was for broad leaf (0218) and mixed forests (0161) The

strongest avoidance was for urban (-1) and sparsely vegetated areas (-05) During the WS the strongest

preference was for miresmarshes (0228) The strongest avoidance was for grasslandmoors (-05)

Centre During the GS the strongest preference was for broad leaf (0233) and younger forests (0223) The

strongest avoidance was for urban (-0527) and agricultural land (-0362) During the WS preference was only

shown for agricultural land (0327) The strongest avoidance was for urban areas (-0679) and miresmarshes

(-0638)

South During the GS the strongest preference was for coniferous (0312) and younger forests (0242) The

strongest avoidance was for urban (-0353) and sparsely vegetated areas (-0330) During the WS

grasslandmoors (0106) were the strongest preference The strongest avoidance was for urban (-0666) and

sparsely vegetated areas (-0351)

16

The Jacobs indices revealed that generally the habitats preferred during the GS within the landscape

(UD95Area) are broad leaf (0216) and younger forests (0201) The strongest avoidance was for urban (-

0717) and freshwater areas (-0694) The strongest preference during the WS are coniferous forests (0242)

and the strongest avoidance was for freshwater (-0674) and urban areas (-0648) (Fig 5)

Fig 5 Second order seasonal habitat preference (UD50UD95) all individuals The index ranges from -1 (total avoidance)

to 1 (strongest preference) Close to 0 indicates used in proportion to its availability

Second order habitat preferencesavoidances by area

North During the GS the strongest preference was for broad leaf (0363) and mixed forests (00291) The

strongest avoidance was for sparsely vegetated (-0909) and freshwater areas (-0780) During the WS mixed

(0335) and coniferous forests (0316) were the strongest preference The strongest avoidance was for

freshwater (-0731) and urban areas (-05333)

Centre During the GS the strongest preference for mixed (0394) and younger forests (0286) The strongest

avoidance was for urban (-0733) and sparsely vegetated (-0708) areas During the WS mixed (0404) and

coniferous forests (0255) were the strongest preference The strongest avoidance was for freshwater (-0704)

and sparsely vegetated areas (-0655)

South During the GS the strongest preference for grasslandmoors (0287) and clear fells (0165) The

strongest avoidance was for urban areas (-0678) and mixed forests (-0491) During the WS grasslandmoors

(0425) and coniferous forests (0154) were the strongest preference The strongest avoidance was for urban (-

0876) and freshwater areas (-0587) (appendix E)

17 Diet

Diet analysis of the rumen content sampled from five individuals (C=2 S=3) revealed that almost two thirds

(69) of the diet is comprised of agricultural produce (apple winter rape and sugar beet) (Fig 6)

Fig 6 Diet analysis from the rumen samples of five moose individuals that were culled in 2013

31

2117

9

8

5

22

1 1

1

1

1 00 0

0

0Diet (2610-911 2013 5 individuals)

AppleWinter RapeSugar BeetUndefined WoodSallowBroad-leaf GrassPineAshOakCloverCurrantsUndefined plantElderberryJuniperRaspberry

18

Calf Survival

Of the 18 individuals 13 produced calves in which 7 produced twins giving a total of 20 calves A Kaplan-

Meier estimate was conducted to measure the fraction of calves living up to each period of the study (Fig 7)

The mean survival time is until period 235 (midend of summer) At the start of summer 85 of calves

remained (3 still born) The period between summer and before the hunt survival drops to 30 The survival

at the end of the study (after hunt) drops further to 20 leaving 4 calves surviving (see appendix B)

Fig 7 Kaplan-Meier estimate of moose calf survival during the study period Period 0 (Start of summer) period 1

(midend of summer) period 2 (before hunt) period 3 (after hunt) period 4 (after winter)

19 Discussion

The results of this study emphasised how strikingly different the habitat composition is along the latitudinal

gradient of Oumlland The three areas show contrasting proportions of the key habitat types The starkest

difference is the high proportion of coniferous forests and lack of agriculture in the north compared to the

centre and south The proportion of coniferous forest in the north is almost 5 times greater than in the centre

and south whereas the proportion of agriculture in the centre and south is more than double that in the north

The north is perceived to be composed of the most suitable habitat for moose (Dussault et al 2006) It has the

largest proportions of each forest type and a low proportion of agricultural land This provides suitable forage

and shelter throughout the year The south has a contrasting habitat composition to the north The proportions

of agricultural and sparsely vegetated areas are the highest between the three areas and the proportions of forest

habitats are the lowest The large proportion of sparsely vegetated areas and low proportions of forest habitat

corresponds to the large area of Stora Alvaret This is perceived to be the least suitable area due to a lack of

shelter (coniferous forest) and suitable forage The strong preference for coniferous and younger forest habitats

in the south would suggest that moose exhibit a functional response in habitat selection (Godvik et al 2009)

ie as the proportion of a particular habitat decreases the selection for that habitat increases in this case

coniferous forests which provide shelter and younger forest which provide good forage Similarly in the centre

moose show strong preference for mixed forests a habitat that is of low proportion

In view of the large variation in habitat proportions between the areas it is surprising that there is not a large

variation in the home range sizes or the activity levels annually or seasonally Home ranges are ultimately

chosen to maximise fitness and meet energy requirements by utilizing the available forage Seasonal conditions

change the availability and necessity of resources (food quality shelter) Unlike the GS during the WS

deciduous trees and shrubs are leafless and low-lying shrubs are under snow cover (Dussault et al 2005)

These changes are well known to cause populations to alter their activity and home ranges to meet energy

requirements (Mysterud et al 2001) Populations have been shown to increase or decrease their home ranges

during the two seasons The GS home ranges are often larger than the WS home ranges (Philips et al 1973

Mysterud et al 2001) In some cases they can be found to be almost double the size of the WS home ranges

(Cederlund and Okarma 1988) In other populations the WS home ranges are double the size of the GS home

ranges (Lynch and Morgantini 1984) or sizes do not significantly differ (Cederlund and Sand 1994)

Previous studies on moose find females generally show increased activity from the start on the GS due to

various factors eg reduced ruminating times increased metabolic needs and increased foraging bursts

(Wattles and DeStefano 2013) Increased metabolic needs during this time are a results of pregnancy and

lactation (Georgii 1980) During the height of the GS they usually show reduced activity levels through times

of increased thermal stress (Renecker and Hudson 1989 van Beest et al 2012) During the WS the depth and

the duration of snow cover are well known to affect the activity level (Telfer 1970 Mysterud and Oslashstbye 1999

Bjoslashrneraas et al 2011) During the WS generally home ranges are smaller and activity less due to lower

metabolic needs Moose activity is constrained by rumination during the WS this period is known to be longer

due to the change in diet (Cederlund 1989 Renecker Hudson 1989) This was not the case on Ӧland activity

20

was lowest in February which is a similar result to Cederlundrsquos (1989) paper However Ӧland moose did not

significantly alter their seasonal activity levels The fact that the annual and seasonal activity levels and home

ranges were similar could be a result of the mild winters on Oumlland during the study period (Smhise 2014)

During the study period the average number of snow days was 80 and the mean snow depth was 10cm

(appendix F) (Swedish Meterological and Hydrological Institute- SMHI) These mild conditions do not restrict

the movement of moose or obscure forage Moose are well adapted for movement in deep snow depths of 60-

86cm (Prescott 1968) are needed to truly restrict movement This finding was similar to the Sweanor and

Sandegren (1989) and Cederlund and Sand (1994) where the snow depth at their sites did not reach movement

restricting depths

The survival curve illustrates just how bad the calf survival is on Ӧland Survival falls from 85 at the start to

20 Out of 20 calves only four were alive at the end of the study The sharpest fall in survival was the period

between end of summer and before the hunt so the deaths were not due to hunting Previous calf autopsies

(Malmsten 2014a) have shown that cause of death was starvation mothers possibly either did not have milk

the calf was unable to feed or the mother abandoned the calf Closer field based observations are needed to

attain this knowledge Moose are seasonal polyoestral mammals (Monfort et al 1993) coming into oestrus

during late September early October (Garel et al 2009) (appendix F) The diet of the mother influences the

health of the calf and this period is when sodium is hard to find sodium is a key mineral in moose diets for

features such as reproduction (Belovsky and Jordan 1981) Moose gain sodium mainly through aquatic plants

(MacCracken et al 1993) However the compositional analysis shows that freshwater areas are often ranked

as one of the lowest used habitats and coastal areas were removed as the proportion found in the home ranges

was extremely low The Jacobs Index shows that the moose only prefer freshwater areas in the north UD50

during the WS The north individuals again are those that are showing typical moose habitat selection

It is known that habitat selection is hierarchical with habitats that increase fitness selected for and the effects

of limiting factors are reduced (Rettie and Messier 2000) At the UD95 during the GS moose preferred areas

of good forage (forests) and avoided areas of low forage (freshwater and sparsely vegetated areas) and areas

close to humans (urban) This is consistent with other reports (Laurian et al 2008 Torres et al 2011) Within

the UD50 there is a shift in preferences The good forage areas are again preferred during the GS however

during WS the only preferred habitat is often agricultural land During the WS there could be a steady supply

of supplementary feed available hence the high levels of agricultural produce found in the rumen content

samples and the high preference of agricultural areas This diet is unusual for moose previous studies of

Swedish moose diet have found the GS diet was dominated by birch willow and herbaceous plants and the

WS diet dominated by pine and birch (Cederlund and Nystrom 1981) The diet analysis was conducted during

the WS instead of being dominant pine composed just 2 Birch did not appear however unidentified wood

composed only 9 whereas agricultural produce accounted for 69 Supplementary feed may be perceived

by the moose in the centre and south as a vital forage source during the WS In fact in the centre the

agricultural land is the only preferred habitat at the UD50 It is unknown whether there are salt licks provided

in these areas Selection for a critical habitat is often thought to be a fixed factor The Oumlland population from

21 the three areas are close in proximity however they displayed contrasting preferences This is supported by the

Osko et al (2004) report that found two neighbouring moose populations that had access to the same habitats

displayed contrasting preferences Habitat preferences for populations of the same species are not necessarily

fixed They alter with varying levels of habitat abundance and limiting factors skewing what is preserved to

be critical

The main limitation encountered in this study was with the limited sample There was only data on two

individuals from the north of the island which led it being removed from many of the analysis Similarly due

to a lack of relocations from the collars being turned off at points throughout the year two further individuals

had to be removed from a majority of the analysis This reduced the sample size to 17 or 18 individuals

Similarly only 13 of the individuals from the study produced calves This unfortunately prevented including

survival into models Although the sample size was small it was accurate it was of high resolution over

300000 GPS points In future it would be beneficial to have a more standardised data set An equal sample of

individuals from the three areas would be advised along with ensuring the GPS collars are kept turned on for

the entirety of the growing and winter season to allow comparisons between years It would also be

advantageous to collect coordinates of the feeding sites along with the composition This could then be

compared with high use UD coordinates to look if moose are truly spending a majority of their foraging time

at feeding stations A study on the population densities of moose and the increasing population of roe deer

(Capreolus capreolus) would add the factor of competition into the model

The low calf survival on Ӧland is most likely the result of a combination of factors The lack of suitable habitat

reported in this study in conjunction with Malmstenrsquos (2014a) report on the threat of disease (Anaplasma

phagocytophilum) are probable influences on the calf survival on Ӧland On Ӧland there is an increasing

population of roe deer and large numbers of migratory birds both carriers of ticks and diseases The mild

conditions on Ӧland are advantageous for ticks the carriers of A phagocytophilum Fewer snow days and

shorter periods of snow cover along with dry conditions are favourable for ticks This could probably be one

of the reasons for females to be of lower quality and therefore not being able to ensure calf survival Moose

have to utilise areas where in other populations individuals tend to avoid Finally similar to many studies I

advocate further research using a stronger dataset and longer term monitoring

22

Acknowledgements

I am indebted to NJ Singh and A Allen for all their help and guidance through the whole of this study I

thank SLU for the support provided during this study in terms of data finances and facilities Thank you to

everyone at the Department of Wildlife Fish and Environmental Studies for being so friendly and

supportive I would like to thank L Edenius for driving me around the study area and S Michon and H

Khalil for keeping me sane with fika and training

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Hagner O Nilsson M Reese H Egberth M Olsson H (2005) Procedure for classification of forests for

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Horne JS Garton ED Krone SM Lewis JS (2007) Analysing animal movements using Brownian bridges

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Hornok S Kovaacutets D Csoumlrgo T Meli M Goumlnczi E Hadnagy Z Takaacutecs N Farkas R Hofmann-Lehmann R

(2014) Birds as potential reservoirs of tick-borne pathogens first evidence of bacteraemia

with Rickettsia Helvetica Parasites and Vectors 7128

26

Jacobs J (1974) Quantitative measurement of food selection a modification of the forage ratio and Ivlevrsquos

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Jonsson F (2007) rsquoDen oumllaumlndska aringlgstammens foumlrvaltingrsquo Departement of Wildlife Fish and Environmental

Studies SLU Examensarbete I aumlmnet biologi vol 20072

Kaplan EL Meier P (1958) Nonparametric estimation from incomplete observation Journal of the American

Statistical Association 53457-481

Keating KA Cherry S (2009) Modelling utilization distributions in space and time Ecology 90(7)1971-

1980

Kie JG Matthiopolos J Fieberg J Powell RA Cagnacci F Mitchell SM Gaillard JM Moorcroft PR (2010)

The home range concept are traditional estimators still relevant with modern telemetry

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Jaumlgarefoumlrbundet Oumlster-Malma 20092

Kranstauber B Kays R LaPoint SD Wikelski M Safi K (2012) A dynamic Brownian bridge movement

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Animal Ecology 81738-746

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Laurian C Dussault C Ouellet JP Courtois R Poulin M Breton L (2008) Behaviour of moose relative to a

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Lavsund S Nygreacuten T Solberg EJ (2003) Status of moose populations and challenges to moose management

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Lenarz MS Fieberg J Schrage MW Edwards AJ (2010) Living on the edge viability of moose in

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14343-348

Linnell JDC Aanes R Andersen R (1995) Who killed Bambi The role of predation in the neonatal

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MacCracken JG Ballenberghe VV Peek JM (1993) Use of aquatic plants by moose sodium hunger or

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27

Malmsten J Wideacuten DG Rydevik G Yon L Hutchings MR Thulin CG Soumlderquist L Aspan A Stuen S

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Malmsten J Soumlderquist L Thulin C Wideacuten DG Yon L Hutchings MR Dalin A (2014b) Reproductive

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Marsh DM Hanlon TJ (2004) Observer gender and observation bias in animal behaviour research

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28

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29

Tveito OE Foslashrland EJ Alexandersson H Drebs A Jonsson T Vaarby-Laursen E (2001) Nordic climate

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Russian Journal of Genetics 38951-957

van Beest FM van Moorter B Milner JM (2012) Temperature-mediated habitat use and selection by a heat

sensitive northern ungulate Animal Behaviour 84(3)723-735

van Winkle W (1975) Comparision of several probabilistic home-range models Journal of Wildlife

Management 39118-123

Verme LJ Ullrey DE (1984) Physiology and nutrition White-tailed deer ecology and management (Ed By

Halls LK) pp 91-118 Stackpole Harrisburg Pennsylvania

Wattles DW DeStefano (2013) Space use and movements of moose in Massachusetts Implications for

conservation of large mammals in a fragmented environment Alces 4965-81

White RG Rowell JE Hauer WE (1997) The role of nutrition body condition and lactation on calving

success in muskoxen Journal of Zoology 24313-20

30

Appendix A

Introduction

Fig 1 Summary chart of factors affecting the life history and therefore the long term fitness of a population

Fig 2 Summary chart 2

Movement

Habitat

Climate

Topography

Competition

FoodWater

Disease

Die

Survive

Reproduce

Population long term fitness

31 Appendix B

Method and Materials

Fig 1 Summary of processes

32

Fig 2 Examples of classical kernel home range output and Brownian bridge kernel home range (Calenge 2011) The

right image includes the area between relocations ie the movement path in contrast to the classic kernel home range

in the left image

33 Appendix C

Home ranges

Fig 1 Example of a non-migratory (ID006) individuals BRB kernel area From top left annual growing and winter

season UD50 (black contour) and UD95 (red contour)

Fig 2 Example of a migratory (ID012) individuals BRB kernel area From the left annual growing and winter season

UD50 (black contour) and UD95 (red contour)

34

Table 1 Annual and seasonal UD50 and UD95 areas (ha) for all individuals

ID Annual GS WS

UD50 UD95 UD50 UD95 UD50 UD95

ID004 190 924 93 531 173 941

ID005 230 1364 132 945 72 682

ID006 162 1036 89 736 70 611

ID008 277 1536 156 809 78 738

ID009 137 834 48 295 126 653

ID010 114 682 83 448 96 488

ID012 177 963 123 544 76 545

ID014 160 1018 87 575 89 662

ID015 172 858 128 532 109 679

ID016 156 1047 65 455 92 534

ID017 153 1088 149 1043 69 349

ID019 279 1097 176 911 163 824

ID020 139 1084 67 349 160 794

ID022 159 811 131 638 61 454

ID023 187 1061 147 771 72 705

ID024 146 725 165 705 101 458

ID026 142 605 99 442 125 547

ID027 126 567 75 461 48 277

35 Appendix D

Activity

Fig 1 Mean daily movement during the study period GS 23-April-2012 to 07-Nov-2012 WS 08-Nov-2012 to

22-April-2013 (number indicates month)

Fig 2 Mean daily movement in the centre and south during the GS and WS

36

Appendix E

Habitat Proportions

Fig 1 All individualsrsquo seasonal habitat proportions within the UD95

37 Habitat Selection

Table 1 Simplified ranking matrices comparing proportional habitat use within the second order (UD95Area) with

proportions of total available habitat types Mean value on the matrix was replaced by a sign a triple sign represents

significant deviation from random at P lt05 Highlighted habitat is ranked 1st

North A

gri

cult

ure

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 --- --- - +++ --- --- --- +++ +++ --- 8

Broad Leaf +++ 0 +++ + +++ +++ +++ + +++ +++ +++ 1

Clear Fell +++ --- 0 + +++ - - --- +++ +++ --- 7

Coniferous + - - 0 +++ - - --- +++ +++ - 6

Freshwater --- --- --- --- 0 --- --- --- +++ - --- 10

Grassland

Moors +++ --- + + +++ 0 +++ - +++ +++ + 3

MiresMarshes +++ --- + + +++ --- 0 - +++ +++ --- 5

Mixed +++ - +++ +++ +++ + + 0 +++ +++ + 2

Sparse Veg --- --- --- --- --- --- --- --- 0 --- --- 11

Urban --- --- --- --- + --- --- --- +++ 0 --- 9

Younger +++ --- +++ + +++ - +++ - +++ +++ 0 4

Rank Order and

Significance

Broad Leafgt Mixedgt GrasslandMoorsgt Youngergtgtgt MiresMarshesgt Coniferousgt

Clear Fellgtgtgt Agriculturegtgtgt Urbangt Freshwatergtgtgt Sparse Veg

Central

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 --- --- --- + +++ + --- +++ +++ --- 6

Broad Leaf +++ 0 +++ + +++ +++ + - +++ +++ - 3

Clear Fell +++ --- 0 - +++ +++ + --- +++ +++ --- 5

Coniferous +++ - + 0 +++ +++ + --- +++ +++ - 4

Freshwater - --- --- --- 0 +++ - --- +++ +++ --- 8

Grassland

Moors --- --- --- --- --- 0 --- --- +++ - --- 10

MiresMarshes - - - - + +++ 0 - +++ +++ - 7

Mixed +++ + +++ +++ +++ +++ + 0 +++ +++ + 1

Sparse Veg --- --- --- --- --- --- --- --- 0 - --- 11

Urban --- --- --- --- --- + --- --- + 0 --- 9

Younger +++ + +++ + +++ +++ + - +++ +++ 0 2

Rank Order and

Significance

Mixedgt Youngergt Broad Leafgt Coniferousgt Clear Fellgtgtgt Agriculturegt

MiresMarshesgt Freshwatergtgtgt Urbangt GrasslandMoorsgtgtgt Sparse Veg

38

South

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 + - - + - + +++ +++ +++ - 5

Broad Leaf - 0 - - + - - +++ + +++ - 7

Clear Fell + + 0 - + + + +++ + +++ + 2

Coniferous + + + 0 +++ + + +++ + +++ + 1

Freshwater - - - --- 0 - - + + +++ - 8

Grassland

Moors + + - - + 0 + + +++ + - 4

MiresMarshes - + - - + - 0 +++ + +++ - 6

Mixed --- --- --- --- - - --- 0 + + --- 10

Sparse Veg --- - - - - --- - - 0 + - 9

Urban --- --- --- --- --- - --- - - 0 --- 11

Younger + + - - + + + +++ + +++ 0 3

Rank Order

and

Significance

Coniferousgt Clear Fellgt Youngergt GrasslandMoorsgt Agriculturegt MiresMarshesgt Broad Leafgt

Freshwatergt Sparse Veggt Mixedgt Urban

Table 2 Simplified ranking matrices comparing proportional habitat use within the third order (UD50UD95) with

proportions of total available habitat types Mean value on the matrix was replaced by a sign a triple sign represents

significant deviation from random at P lt05 Highlighted habitat is ranked 1st

North

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 --- --- --- - + --- --- + +++ --- 8

Broad Leaf +++ 0 +++ + + + + + +++ +++ + 1

Clear Fell +++ --- 0 + + + - - + +++ - 5

Coniferous +++ - - 0 + + --- --- +++ +++ - 6

Freshwater + - - - 0 +++ - - +++ +++ - 7

GrasslandMoors - - - - --- 0 - - - + - 10

MiresMarshes +++ - + +++ + + 0 - +++ +++ + 3

Mixed +++ - + +++ + + + 0 +++ +++ + 2

Sparse Veg - --- - --- --- + --- --- 0 +++ --- 9

Urban --- --- --- --- --- - --- --- --- 0 --- 11

Younger +++ - + + + + - - +++ +++ 0 4

Rank Order and

Significance

Broad Leafgt Mixedgt MiresMarshesgt Youngergt Clear Fellgt Coniferousgt Freshwatergt

Agriculturegt Sparse Veggt GrasslandMoorsgt Urban

39

Central

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 --- --- + + - - - + +++ --- 7

Broad Leaf +++ 0 + +++ + + + + + +++ - 2

Clear Fell +++ - 0 +++ + + + + + +++ - 3

Coniferous - --- --- 0 + - - --- +++ + --- 8

Freshwater - - - - 0 --- - - --- - - 11

GrasslandMoors + - - + +++ 0 + - + +++ - 5

MiresMarshes + - - + + - 0 + + +++ - 6

Mixed + - - +++ + + - 0 +++ +++ - 4

Sparse Veg - - - --- +++ - - --- 0 +++ - 9

Urban --- --- --- - + --- --- --- --- 0 --- 10

Younger +++ + + +++ + + + + + +++ 0 1

Rank Order and

Significance

Youngergt Broad Leafgt Clear Fellgt Mixedgt GrasslandMoorsgt MiresMarshesgt

Agriculturegt Coniferousgtgtgt Sparse Veggtgtgt Urbangt Freshwater

South

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 - - - - - + - +++ + --- 8

Broad Leaf + 0 - --- + - + - +++ + - 6

Clear Fell + + 0 - + - + - +++ + - 4

Coniferous + +++ + 0 + + +++ + +++ + + 1

Freshwater + - - - 0 - - + + + - 7

GrasslandMoors + + + - + 0 + + + + - 3

MiresMarshes - - - --- + - 0 - + + - 9

Mixed + + + - - - + 0 + + - 5

Sparse Veg --- --- --- --- - - - - 0 + --- 10

Urban - - - - - - - - - 0 - 11

Younger +++ + + - + + + + +++ + 0 2

Rank Order and

Significance

Coniferousgt Youngergt GrasslandMoorsgt Clear Fellgt Mixedgt Broad Leafgt Freshwatergt

Agriculturegt MiresMarshesgt Sparse Veggt Urban

40

Table 3 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the GS according to Jacobs index

Ran

k North Centre South

50 95 50 95 50 95

+ - + - + - + - + - + -

1 Broad

Leaf Urban Broad Leaf Sparse Veg

Broad

Leaf Urban Mixed Urban Coniferous Urban

Grassland

Moors Urban

2 Mixed Sparse Veg Mixed Freshwater Younger Agriculture Younger Sparse Veg Younger Sparse Veg Clear Fell Mixed

3 Mires

Agriculture Grassland

Urban Clear

Fell Coniferous Broad Leaf

Grassland

Moors

Clear Fell Agriculture Coniferous Sparse Veg

Marshes Moors

4 Younger Grassland

Younger Agriculture

Freshwater Coniferous Freshwater

Broad Leaf Mires

Younger Freshwater

Moors Marshes

5 Clear

Fell Freshwater

Mires Coniferous

Sparse Veg Clear Fell Agriculture

Freshwater Agriculture

Marshes

6 Coniferous Clear Fell

Mires

Marshes

Mires

Grassland

Moors

Mires

Marshes Marshes

7 Mixed Mixed Broad Leaf

8 Grassland

Moors

41

Table 4 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the WS according to Jacobs index

Ran

k North Centre South

50 95 50 95 50 95

+ - + - + - + - + - + -

1 Mires

Marshes

Grassland

Moors Mixed Freshwater Agriculture Urban Mixed Freshwater

Grassland

Moors Urban GrasslandMoors Urban

2 Freshwater Mixed Coniferous Urban Mires

Marshes Coniferous Sparse Veg Agriculture

Sparse

Veg Coniferous Freshwater

3 Urban Coniferous Younger Grassland

Moors Freshwater Younger Urban Freshwater

Broad

Leaf Agriculture Mixed

4 Younger Agriculture Sparse Veg Broad

Leaf

Broad

Leaf

Grassland

Moors Mixed Broad Leaf

5 Clear Fell Agriculture Coniferous Agriculture Mires

Marshes Clear Fell

6 Sparse

Veg

Mires

Marshes Mixed

Mires

Marshes

Clear

Fell

Mires

Marshes

7 Broad

Leaf Clear Fell Younger Clear Fell Younger Sparse Veg

8 Clear Fell Younger

9 Sparse

Veg

10 Grassland

Moors

42

Table 5 Second order (UD95Area) individual selectionavoidance for the GS and WS according to the Jacobs index

ID GS WS

Select Avoid Select Avoid

ID004 Younger Sparsely Vegetated MiresMarshes Sparsely Vegetated

ID005 MiresMarshes Sparsely Vegetated Coniferous GrasslandMoors

ID006 Coniferous Sparsely Vegetated Mixed Freshwater

ID008 Mixed Sparsely Vegetated Mixed Freshwater

ID009 Mixed Sparsely Vegetated Mixed GrasslandMoors

ID010 MiresMarshes Freshwater GrasslandMoors Freshwater

ID012 Broad Leaf Sparsely Vegetated Coniferous Urban

ID014 Clear Fell Sparsely Vegetated GrasslandMoors Sparsely Vegetated

ID015 GrasslandMoors Urban GrasslandMoors Freshwater

ID016 GrasslandMoors Freshwater GrasslandMoors Freshwater

ID017 GrasslandMoors Mixed Sparsely Vegetated Mixed

ID019 Mixed Sparsely Vegetated Mixed Urban

ID020 Broad Leaf Sparsely Vegetated Coniferous GrasslandMoors

ID022 MiresMarshes Freshwater MiresMarshes Freshwater

ID023 MiresMarshes GrasslandMoors Mixed Freshwater

ID024 Broadleaf Urban Broad Leaf Urban

ID026 GrasslandMoors Freshwater GrasslandMoors Freshwater

ID027 GrasslandMoors Urban Sparsely Vegetated Freshwater

43 Table 6 Third order (UD50UD95) individual selectionavoidance for the GS and WS according to the Jacobs index

ID GS WS

Select Avoid Select Avoid

ID004 Broad Leaf Mixed GrasslandMoors Freshwater

ID005 Broad Leaf Freshwater Agriculture Freshwater

ID006 Clear Fell Freshwater Agriculture MiresMarshes

ID008 MiresMarshes Freshwater Agriculture Urban

ID009 Freshwater Agriculture Agriculture Freshwater

ID010 Mixed Urban Sparsely Vegetated Urban

ID012 Coniferous GrasslandMoors Freshwater Urban

ID014 Urban Agriculture Freshwater Urban

ID015 Mixed Forest Urban Clear Fell Urban

ID016 Freshwater Urban GrasslandMoors Mixed

ID017 Coniferous Mixed Coniferous Broad Leaf

ID019 Broad Leaf GrasslandMoors Urban GrasslandMoors

ID020 Freshwater Urban Freshwater Agriculture

ID022 MiresMarshes Urban Broad Leaf GrasslandMoors

ID023 Freshwater Mixed Agriculture Freshwater

ID024 Mixed Freshwater Mixed Freshwater

ID026 Mixed MiresMarshes Sparsely Vegetated GrasslandMoors

ID027 Freshwater MiresMarshes GrasslandMoors Broad Leaf

44

Fig 2 North third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)

45

Fig 3 Centre third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)

46

Fig 4 South third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)

47

Fig 5 North second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)

48

Fig 6 Centre second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)

49

Fig 7 South second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)

50

Appendix F

Background

Fig 1 Daily mean snow depth and duration during the study period (Andrew Allen)

Female Moose Reproduction

Moose are seasonal polyoestral mammals (Monfort et al 1993) coming into oestrus during late September

early October (Garel et al 2009) The Swedish moose cow population reaches puberty between the ages 25

and 35 (Sand and Cederlund 1993) during which the reproductive period begins with the onset of ovulation

The age an individual reaches puberty is dependent on their body condition they have to reach a weight

threshold to reach puberty and become reproductive (Sand 1996) If she is over the weight threshold she will

go into oestrus in the autumn If she does not reach the weight threshold then she will go into oestrus the

following autumn if successful she will give birth to individual or twin calves in late May to early June

(Ericsson et al 2001) and therefore reach sexual maturity (Malmsten et al 2014b) Fecundity is related to

both the condition and the age of the cow Cows go through senescence at 12 years of age (Ericsson et al

2001) Providing calves with the required level of nutrition demands high energy and protein resources from

the mother during senescence this becomes harder to achieve leading to decreased levels of parental care

and higher levels of calf mortality

Page 16: Habitat-performance relationships on an island: fitness ...navinderjsingh.weebly.com/uploads/1/1/2/2/11224342/... · Conditions on Öland are milder than those found in other areas

16

The Jacobs indices revealed that generally the habitats preferred during the GS within the landscape

(UD95Area) are broad leaf (0216) and younger forests (0201) The strongest avoidance was for urban (-

0717) and freshwater areas (-0694) The strongest preference during the WS are coniferous forests (0242)

and the strongest avoidance was for freshwater (-0674) and urban areas (-0648) (Fig 5)

Fig 5 Second order seasonal habitat preference (UD50UD95) all individuals The index ranges from -1 (total avoidance)

to 1 (strongest preference) Close to 0 indicates used in proportion to its availability

Second order habitat preferencesavoidances by area

North During the GS the strongest preference was for broad leaf (0363) and mixed forests (00291) The

strongest avoidance was for sparsely vegetated (-0909) and freshwater areas (-0780) During the WS mixed

(0335) and coniferous forests (0316) were the strongest preference The strongest avoidance was for

freshwater (-0731) and urban areas (-05333)

Centre During the GS the strongest preference for mixed (0394) and younger forests (0286) The strongest

avoidance was for urban (-0733) and sparsely vegetated (-0708) areas During the WS mixed (0404) and

coniferous forests (0255) were the strongest preference The strongest avoidance was for freshwater (-0704)

and sparsely vegetated areas (-0655)

South During the GS the strongest preference for grasslandmoors (0287) and clear fells (0165) The

strongest avoidance was for urban areas (-0678) and mixed forests (-0491) During the WS grasslandmoors

(0425) and coniferous forests (0154) were the strongest preference The strongest avoidance was for urban (-

0876) and freshwater areas (-0587) (appendix E)

17 Diet

Diet analysis of the rumen content sampled from five individuals (C=2 S=3) revealed that almost two thirds

(69) of the diet is comprised of agricultural produce (apple winter rape and sugar beet) (Fig 6)

Fig 6 Diet analysis from the rumen samples of five moose individuals that were culled in 2013

31

2117

9

8

5

22

1 1

1

1

1 00 0

0

0Diet (2610-911 2013 5 individuals)

AppleWinter RapeSugar BeetUndefined WoodSallowBroad-leaf GrassPineAshOakCloverCurrantsUndefined plantElderberryJuniperRaspberry

18

Calf Survival

Of the 18 individuals 13 produced calves in which 7 produced twins giving a total of 20 calves A Kaplan-

Meier estimate was conducted to measure the fraction of calves living up to each period of the study (Fig 7)

The mean survival time is until period 235 (midend of summer) At the start of summer 85 of calves

remained (3 still born) The period between summer and before the hunt survival drops to 30 The survival

at the end of the study (after hunt) drops further to 20 leaving 4 calves surviving (see appendix B)

Fig 7 Kaplan-Meier estimate of moose calf survival during the study period Period 0 (Start of summer) period 1

(midend of summer) period 2 (before hunt) period 3 (after hunt) period 4 (after winter)

19 Discussion

The results of this study emphasised how strikingly different the habitat composition is along the latitudinal

gradient of Oumlland The three areas show contrasting proportions of the key habitat types The starkest

difference is the high proportion of coniferous forests and lack of agriculture in the north compared to the

centre and south The proportion of coniferous forest in the north is almost 5 times greater than in the centre

and south whereas the proportion of agriculture in the centre and south is more than double that in the north

The north is perceived to be composed of the most suitable habitat for moose (Dussault et al 2006) It has the

largest proportions of each forest type and a low proportion of agricultural land This provides suitable forage

and shelter throughout the year The south has a contrasting habitat composition to the north The proportions

of agricultural and sparsely vegetated areas are the highest between the three areas and the proportions of forest

habitats are the lowest The large proportion of sparsely vegetated areas and low proportions of forest habitat

corresponds to the large area of Stora Alvaret This is perceived to be the least suitable area due to a lack of

shelter (coniferous forest) and suitable forage The strong preference for coniferous and younger forest habitats

in the south would suggest that moose exhibit a functional response in habitat selection (Godvik et al 2009)

ie as the proportion of a particular habitat decreases the selection for that habitat increases in this case

coniferous forests which provide shelter and younger forest which provide good forage Similarly in the centre

moose show strong preference for mixed forests a habitat that is of low proportion

In view of the large variation in habitat proportions between the areas it is surprising that there is not a large

variation in the home range sizes or the activity levels annually or seasonally Home ranges are ultimately

chosen to maximise fitness and meet energy requirements by utilizing the available forage Seasonal conditions

change the availability and necessity of resources (food quality shelter) Unlike the GS during the WS

deciduous trees and shrubs are leafless and low-lying shrubs are under snow cover (Dussault et al 2005)

These changes are well known to cause populations to alter their activity and home ranges to meet energy

requirements (Mysterud et al 2001) Populations have been shown to increase or decrease their home ranges

during the two seasons The GS home ranges are often larger than the WS home ranges (Philips et al 1973

Mysterud et al 2001) In some cases they can be found to be almost double the size of the WS home ranges

(Cederlund and Okarma 1988) In other populations the WS home ranges are double the size of the GS home

ranges (Lynch and Morgantini 1984) or sizes do not significantly differ (Cederlund and Sand 1994)

Previous studies on moose find females generally show increased activity from the start on the GS due to

various factors eg reduced ruminating times increased metabolic needs and increased foraging bursts

(Wattles and DeStefano 2013) Increased metabolic needs during this time are a results of pregnancy and

lactation (Georgii 1980) During the height of the GS they usually show reduced activity levels through times

of increased thermal stress (Renecker and Hudson 1989 van Beest et al 2012) During the WS the depth and

the duration of snow cover are well known to affect the activity level (Telfer 1970 Mysterud and Oslashstbye 1999

Bjoslashrneraas et al 2011) During the WS generally home ranges are smaller and activity less due to lower

metabolic needs Moose activity is constrained by rumination during the WS this period is known to be longer

due to the change in diet (Cederlund 1989 Renecker Hudson 1989) This was not the case on Ӧland activity

20

was lowest in February which is a similar result to Cederlundrsquos (1989) paper However Ӧland moose did not

significantly alter their seasonal activity levels The fact that the annual and seasonal activity levels and home

ranges were similar could be a result of the mild winters on Oumlland during the study period (Smhise 2014)

During the study period the average number of snow days was 80 and the mean snow depth was 10cm

(appendix F) (Swedish Meterological and Hydrological Institute- SMHI) These mild conditions do not restrict

the movement of moose or obscure forage Moose are well adapted for movement in deep snow depths of 60-

86cm (Prescott 1968) are needed to truly restrict movement This finding was similar to the Sweanor and

Sandegren (1989) and Cederlund and Sand (1994) where the snow depth at their sites did not reach movement

restricting depths

The survival curve illustrates just how bad the calf survival is on Ӧland Survival falls from 85 at the start to

20 Out of 20 calves only four were alive at the end of the study The sharpest fall in survival was the period

between end of summer and before the hunt so the deaths were not due to hunting Previous calf autopsies

(Malmsten 2014a) have shown that cause of death was starvation mothers possibly either did not have milk

the calf was unable to feed or the mother abandoned the calf Closer field based observations are needed to

attain this knowledge Moose are seasonal polyoestral mammals (Monfort et al 1993) coming into oestrus

during late September early October (Garel et al 2009) (appendix F) The diet of the mother influences the

health of the calf and this period is when sodium is hard to find sodium is a key mineral in moose diets for

features such as reproduction (Belovsky and Jordan 1981) Moose gain sodium mainly through aquatic plants

(MacCracken et al 1993) However the compositional analysis shows that freshwater areas are often ranked

as one of the lowest used habitats and coastal areas were removed as the proportion found in the home ranges

was extremely low The Jacobs Index shows that the moose only prefer freshwater areas in the north UD50

during the WS The north individuals again are those that are showing typical moose habitat selection

It is known that habitat selection is hierarchical with habitats that increase fitness selected for and the effects

of limiting factors are reduced (Rettie and Messier 2000) At the UD95 during the GS moose preferred areas

of good forage (forests) and avoided areas of low forage (freshwater and sparsely vegetated areas) and areas

close to humans (urban) This is consistent with other reports (Laurian et al 2008 Torres et al 2011) Within

the UD50 there is a shift in preferences The good forage areas are again preferred during the GS however

during WS the only preferred habitat is often agricultural land During the WS there could be a steady supply

of supplementary feed available hence the high levels of agricultural produce found in the rumen content

samples and the high preference of agricultural areas This diet is unusual for moose previous studies of

Swedish moose diet have found the GS diet was dominated by birch willow and herbaceous plants and the

WS diet dominated by pine and birch (Cederlund and Nystrom 1981) The diet analysis was conducted during

the WS instead of being dominant pine composed just 2 Birch did not appear however unidentified wood

composed only 9 whereas agricultural produce accounted for 69 Supplementary feed may be perceived

by the moose in the centre and south as a vital forage source during the WS In fact in the centre the

agricultural land is the only preferred habitat at the UD50 It is unknown whether there are salt licks provided

in these areas Selection for a critical habitat is often thought to be a fixed factor The Oumlland population from

21 the three areas are close in proximity however they displayed contrasting preferences This is supported by the

Osko et al (2004) report that found two neighbouring moose populations that had access to the same habitats

displayed contrasting preferences Habitat preferences for populations of the same species are not necessarily

fixed They alter with varying levels of habitat abundance and limiting factors skewing what is preserved to

be critical

The main limitation encountered in this study was with the limited sample There was only data on two

individuals from the north of the island which led it being removed from many of the analysis Similarly due

to a lack of relocations from the collars being turned off at points throughout the year two further individuals

had to be removed from a majority of the analysis This reduced the sample size to 17 or 18 individuals

Similarly only 13 of the individuals from the study produced calves This unfortunately prevented including

survival into models Although the sample size was small it was accurate it was of high resolution over

300000 GPS points In future it would be beneficial to have a more standardised data set An equal sample of

individuals from the three areas would be advised along with ensuring the GPS collars are kept turned on for

the entirety of the growing and winter season to allow comparisons between years It would also be

advantageous to collect coordinates of the feeding sites along with the composition This could then be

compared with high use UD coordinates to look if moose are truly spending a majority of their foraging time

at feeding stations A study on the population densities of moose and the increasing population of roe deer

(Capreolus capreolus) would add the factor of competition into the model

The low calf survival on Ӧland is most likely the result of a combination of factors The lack of suitable habitat

reported in this study in conjunction with Malmstenrsquos (2014a) report on the threat of disease (Anaplasma

phagocytophilum) are probable influences on the calf survival on Ӧland On Ӧland there is an increasing

population of roe deer and large numbers of migratory birds both carriers of ticks and diseases The mild

conditions on Ӧland are advantageous for ticks the carriers of A phagocytophilum Fewer snow days and

shorter periods of snow cover along with dry conditions are favourable for ticks This could probably be one

of the reasons for females to be of lower quality and therefore not being able to ensure calf survival Moose

have to utilise areas where in other populations individuals tend to avoid Finally similar to many studies I

advocate further research using a stronger dataset and longer term monitoring

22

Acknowledgements

I am indebted to NJ Singh and A Allen for all their help and guidance through the whole of this study I

thank SLU for the support provided during this study in terms of data finances and facilities Thank you to

everyone at the Department of Wildlife Fish and Environmental Studies for being so friendly and

supportive I would like to thank L Edenius for driving me around the study area and S Michon and H

Khalil for keeping me sane with fika and training

23 References

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Bewick V Cheek L Ball J (2004) Statistics review 12 Survival analysis Critical Care 8(5)389-394

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Bischof R Loe LE Meisingset EL Zimmermann B Van Moorter B Mysterud A (2012) A migratory

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Bradshaw RHW Hannon GE Lister AM (2003) A long-term perspective on ungulate-vegetation

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Brandin E (2009) Versions of lsquowildrsquo and the importance of fences in Swedish wildlife tourism involving

moose Current Issues in Tourism 12413-427

Burt WH (1943) Territoriality and home range concepts as applied to mammals Journal of Mammalogy

24346-352

24

Bunnefeld N Boumlrger L van Moorter B Rolandsen CM Dettki H Solberg EJ Ericsson G(2011) A model-

driven approach to quantify migration patterns individual regional and yearly differences

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Calenge C (2006) The package adehabitat for the R software a tool for the analysis of space and habitat use

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Calenge C (2011) Home Range Estimation in R the adehabitatHR package Office national de la classe et de

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Cederlund GN Nystroumlm A (1981) Seasonal differences between moose and roe deer in ability to digest

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Cederlund GN Okarma H (1988) Home range and habitat use of adult female moose Journal of Wildlife

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Cederlund GN (1989) Activity patterns in moose and roe deer in a north boreal forest Holarctic Ecology

1239-45

Cederlund GN Sand H (1994) Home-range size in relation to age and sex in moose American Society of

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Clutton-Brock T Sheldon BC (2010) Individuals and populations the role of long-term individual based

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Cooke SJ Hinch SG Wikelski M Andrews RD Kuchel LJ Wolcott TG Butler PJ (2004) Biotelemerty a

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Crecircte M Courtois R (1997) Limiting factors might obscure population regulation of moose (Cervidae Alces

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Dengler J Loumlbel L Loumlbel W (2006) The basiphilous dry grasslands of shallow skeletal soils (Alysso-

Sedetalia) on the island of Ӧland (Sweden) in the context of north and central Europe

Phytocoenologia 36343-391

Dussault C Courtois R Ouellet JP Girard I (2005) Space use of moose in relation to food availability

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Dussault C Courtois R Ouellet JP (2006) A habitat suitability index model to assess moose habitat selection

at multiple spatial scales Canadian Journal of Forest Research 361097-1107

Ericsson G Wallin K Ball JP Broberg M (2001) Age-related reproductive effort and senescence in free-

ranging moose Alces alces Ecology 821613-1620

Ericsson G Ball JP Danell K (2002) Moose offspring body mass along an altitudinal gradient Journal of

Wildlife Management 55(1)91-97

Ericsson G Malmsten J Neumann W Singh NJ Dali AM Submitted Summer Calf Survival of

Scandinavian Moose along its Southern Distribution Range

25 Festa-Bianchet M Gaillard JM Jorgenson JT (1998) Mass and density-dependent reproductive success and

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Gaillard JM Festa-Bianchet M Delorme D Jorgenson J (2000b) Body mass and individual fitness in female

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Kaplan EL Meier P (1958) Nonparametric estimation from incomplete observation Journal of the American

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success in muskoxen Journal of Zoology 24313-20

30

Appendix A

Introduction

Fig 1 Summary chart of factors affecting the life history and therefore the long term fitness of a population

Fig 2 Summary chart 2

Movement

Habitat

Climate

Topography

Competition

FoodWater

Disease

Die

Survive

Reproduce

Population long term fitness

31 Appendix B

Method and Materials

Fig 1 Summary of processes

32

Fig 2 Examples of classical kernel home range output and Brownian bridge kernel home range (Calenge 2011) The

right image includes the area between relocations ie the movement path in contrast to the classic kernel home range

in the left image

33 Appendix C

Home ranges

Fig 1 Example of a non-migratory (ID006) individuals BRB kernel area From top left annual growing and winter

season UD50 (black contour) and UD95 (red contour)

Fig 2 Example of a migratory (ID012) individuals BRB kernel area From the left annual growing and winter season

UD50 (black contour) and UD95 (red contour)

34

Table 1 Annual and seasonal UD50 and UD95 areas (ha) for all individuals

ID Annual GS WS

UD50 UD95 UD50 UD95 UD50 UD95

ID004 190 924 93 531 173 941

ID005 230 1364 132 945 72 682

ID006 162 1036 89 736 70 611

ID008 277 1536 156 809 78 738

ID009 137 834 48 295 126 653

ID010 114 682 83 448 96 488

ID012 177 963 123 544 76 545

ID014 160 1018 87 575 89 662

ID015 172 858 128 532 109 679

ID016 156 1047 65 455 92 534

ID017 153 1088 149 1043 69 349

ID019 279 1097 176 911 163 824

ID020 139 1084 67 349 160 794

ID022 159 811 131 638 61 454

ID023 187 1061 147 771 72 705

ID024 146 725 165 705 101 458

ID026 142 605 99 442 125 547

ID027 126 567 75 461 48 277

35 Appendix D

Activity

Fig 1 Mean daily movement during the study period GS 23-April-2012 to 07-Nov-2012 WS 08-Nov-2012 to

22-April-2013 (number indicates month)

Fig 2 Mean daily movement in the centre and south during the GS and WS

36

Appendix E

Habitat Proportions

Fig 1 All individualsrsquo seasonal habitat proportions within the UD95

37 Habitat Selection

Table 1 Simplified ranking matrices comparing proportional habitat use within the second order (UD95Area) with

proportions of total available habitat types Mean value on the matrix was replaced by a sign a triple sign represents

significant deviation from random at P lt05 Highlighted habitat is ranked 1st

North A

gri

cult

ure

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 --- --- - +++ --- --- --- +++ +++ --- 8

Broad Leaf +++ 0 +++ + +++ +++ +++ + +++ +++ +++ 1

Clear Fell +++ --- 0 + +++ - - --- +++ +++ --- 7

Coniferous + - - 0 +++ - - --- +++ +++ - 6

Freshwater --- --- --- --- 0 --- --- --- +++ - --- 10

Grassland

Moors +++ --- + + +++ 0 +++ - +++ +++ + 3

MiresMarshes +++ --- + + +++ --- 0 - +++ +++ --- 5

Mixed +++ - +++ +++ +++ + + 0 +++ +++ + 2

Sparse Veg --- --- --- --- --- --- --- --- 0 --- --- 11

Urban --- --- --- --- + --- --- --- +++ 0 --- 9

Younger +++ --- +++ + +++ - +++ - +++ +++ 0 4

Rank Order and

Significance

Broad Leafgt Mixedgt GrasslandMoorsgt Youngergtgtgt MiresMarshesgt Coniferousgt

Clear Fellgtgtgt Agriculturegtgtgt Urbangt Freshwatergtgtgt Sparse Veg

Central

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 --- --- --- + +++ + --- +++ +++ --- 6

Broad Leaf +++ 0 +++ + +++ +++ + - +++ +++ - 3

Clear Fell +++ --- 0 - +++ +++ + --- +++ +++ --- 5

Coniferous +++ - + 0 +++ +++ + --- +++ +++ - 4

Freshwater - --- --- --- 0 +++ - --- +++ +++ --- 8

Grassland

Moors --- --- --- --- --- 0 --- --- +++ - --- 10

MiresMarshes - - - - + +++ 0 - +++ +++ - 7

Mixed +++ + +++ +++ +++ +++ + 0 +++ +++ + 1

Sparse Veg --- --- --- --- --- --- --- --- 0 - --- 11

Urban --- --- --- --- --- + --- --- + 0 --- 9

Younger +++ + +++ + +++ +++ + - +++ +++ 0 2

Rank Order and

Significance

Mixedgt Youngergt Broad Leafgt Coniferousgt Clear Fellgtgtgt Agriculturegt

MiresMarshesgt Freshwatergtgtgt Urbangt GrasslandMoorsgtgtgt Sparse Veg

38

South

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 + - - + - + +++ +++ +++ - 5

Broad Leaf - 0 - - + - - +++ + +++ - 7

Clear Fell + + 0 - + + + +++ + +++ + 2

Coniferous + + + 0 +++ + + +++ + +++ + 1

Freshwater - - - --- 0 - - + + +++ - 8

Grassland

Moors + + - - + 0 + + +++ + - 4

MiresMarshes - + - - + - 0 +++ + +++ - 6

Mixed --- --- --- --- - - --- 0 + + --- 10

Sparse Veg --- - - - - --- - - 0 + - 9

Urban --- --- --- --- --- - --- - - 0 --- 11

Younger + + - - + + + +++ + +++ 0 3

Rank Order

and

Significance

Coniferousgt Clear Fellgt Youngergt GrasslandMoorsgt Agriculturegt MiresMarshesgt Broad Leafgt

Freshwatergt Sparse Veggt Mixedgt Urban

Table 2 Simplified ranking matrices comparing proportional habitat use within the third order (UD50UD95) with

proportions of total available habitat types Mean value on the matrix was replaced by a sign a triple sign represents

significant deviation from random at P lt05 Highlighted habitat is ranked 1st

North

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 --- --- --- - + --- --- + +++ --- 8

Broad Leaf +++ 0 +++ + + + + + +++ +++ + 1

Clear Fell +++ --- 0 + + + - - + +++ - 5

Coniferous +++ - - 0 + + --- --- +++ +++ - 6

Freshwater + - - - 0 +++ - - +++ +++ - 7

GrasslandMoors - - - - --- 0 - - - + - 10

MiresMarshes +++ - + +++ + + 0 - +++ +++ + 3

Mixed +++ - + +++ + + + 0 +++ +++ + 2

Sparse Veg - --- - --- --- + --- --- 0 +++ --- 9

Urban --- --- --- --- --- - --- --- --- 0 --- 11

Younger +++ - + + + + - - +++ +++ 0 4

Rank Order and

Significance

Broad Leafgt Mixedgt MiresMarshesgt Youngergt Clear Fellgt Coniferousgt Freshwatergt

Agriculturegt Sparse Veggt GrasslandMoorsgt Urban

39

Central

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 --- --- + + - - - + +++ --- 7

Broad Leaf +++ 0 + +++ + + + + + +++ - 2

Clear Fell +++ - 0 +++ + + + + + +++ - 3

Coniferous - --- --- 0 + - - --- +++ + --- 8

Freshwater - - - - 0 --- - - --- - - 11

GrasslandMoors + - - + +++ 0 + - + +++ - 5

MiresMarshes + - - + + - 0 + + +++ - 6

Mixed + - - +++ + + - 0 +++ +++ - 4

Sparse Veg - - - --- +++ - - --- 0 +++ - 9

Urban --- --- --- - + --- --- --- --- 0 --- 10

Younger +++ + + +++ + + + + + +++ 0 1

Rank Order and

Significance

Youngergt Broad Leafgt Clear Fellgt Mixedgt GrasslandMoorsgt MiresMarshesgt

Agriculturegt Coniferousgtgtgt Sparse Veggtgtgt Urbangt Freshwater

South

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 - - - - - + - +++ + --- 8

Broad Leaf + 0 - --- + - + - +++ + - 6

Clear Fell + + 0 - + - + - +++ + - 4

Coniferous + +++ + 0 + + +++ + +++ + + 1

Freshwater + - - - 0 - - + + + - 7

GrasslandMoors + + + - + 0 + + + + - 3

MiresMarshes - - - --- + - 0 - + + - 9

Mixed + + + - - - + 0 + + - 5

Sparse Veg --- --- --- --- - - - - 0 + --- 10

Urban - - - - - - - - - 0 - 11

Younger +++ + + - + + + + +++ + 0 2

Rank Order and

Significance

Coniferousgt Youngergt GrasslandMoorsgt Clear Fellgt Mixedgt Broad Leafgt Freshwatergt

Agriculturegt MiresMarshesgt Sparse Veggt Urban

40

Table 3 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the GS according to Jacobs index

Ran

k North Centre South

50 95 50 95 50 95

+ - + - + - + - + - + -

1 Broad

Leaf Urban Broad Leaf Sparse Veg

Broad

Leaf Urban Mixed Urban Coniferous Urban

Grassland

Moors Urban

2 Mixed Sparse Veg Mixed Freshwater Younger Agriculture Younger Sparse Veg Younger Sparse Veg Clear Fell Mixed

3 Mires

Agriculture Grassland

Urban Clear

Fell Coniferous Broad Leaf

Grassland

Moors

Clear Fell Agriculture Coniferous Sparse Veg

Marshes Moors

4 Younger Grassland

Younger Agriculture

Freshwater Coniferous Freshwater

Broad Leaf Mires

Younger Freshwater

Moors Marshes

5 Clear

Fell Freshwater

Mires Coniferous

Sparse Veg Clear Fell Agriculture

Freshwater Agriculture

Marshes

6 Coniferous Clear Fell

Mires

Marshes

Mires

Grassland

Moors

Mires

Marshes Marshes

7 Mixed Mixed Broad Leaf

8 Grassland

Moors

41

Table 4 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the WS according to Jacobs index

Ran

k North Centre South

50 95 50 95 50 95

+ - + - + - + - + - + -

1 Mires

Marshes

Grassland

Moors Mixed Freshwater Agriculture Urban Mixed Freshwater

Grassland

Moors Urban GrasslandMoors Urban

2 Freshwater Mixed Coniferous Urban Mires

Marshes Coniferous Sparse Veg Agriculture

Sparse

Veg Coniferous Freshwater

3 Urban Coniferous Younger Grassland

Moors Freshwater Younger Urban Freshwater

Broad

Leaf Agriculture Mixed

4 Younger Agriculture Sparse Veg Broad

Leaf

Broad

Leaf

Grassland

Moors Mixed Broad Leaf

5 Clear Fell Agriculture Coniferous Agriculture Mires

Marshes Clear Fell

6 Sparse

Veg

Mires

Marshes Mixed

Mires

Marshes

Clear

Fell

Mires

Marshes

7 Broad

Leaf Clear Fell Younger Clear Fell Younger Sparse Veg

8 Clear Fell Younger

9 Sparse

Veg

10 Grassland

Moors

42

Table 5 Second order (UD95Area) individual selectionavoidance for the GS and WS according to the Jacobs index

ID GS WS

Select Avoid Select Avoid

ID004 Younger Sparsely Vegetated MiresMarshes Sparsely Vegetated

ID005 MiresMarshes Sparsely Vegetated Coniferous GrasslandMoors

ID006 Coniferous Sparsely Vegetated Mixed Freshwater

ID008 Mixed Sparsely Vegetated Mixed Freshwater

ID009 Mixed Sparsely Vegetated Mixed GrasslandMoors

ID010 MiresMarshes Freshwater GrasslandMoors Freshwater

ID012 Broad Leaf Sparsely Vegetated Coniferous Urban

ID014 Clear Fell Sparsely Vegetated GrasslandMoors Sparsely Vegetated

ID015 GrasslandMoors Urban GrasslandMoors Freshwater

ID016 GrasslandMoors Freshwater GrasslandMoors Freshwater

ID017 GrasslandMoors Mixed Sparsely Vegetated Mixed

ID019 Mixed Sparsely Vegetated Mixed Urban

ID020 Broad Leaf Sparsely Vegetated Coniferous GrasslandMoors

ID022 MiresMarshes Freshwater MiresMarshes Freshwater

ID023 MiresMarshes GrasslandMoors Mixed Freshwater

ID024 Broadleaf Urban Broad Leaf Urban

ID026 GrasslandMoors Freshwater GrasslandMoors Freshwater

ID027 GrasslandMoors Urban Sparsely Vegetated Freshwater

43 Table 6 Third order (UD50UD95) individual selectionavoidance for the GS and WS according to the Jacobs index

ID GS WS

Select Avoid Select Avoid

ID004 Broad Leaf Mixed GrasslandMoors Freshwater

ID005 Broad Leaf Freshwater Agriculture Freshwater

ID006 Clear Fell Freshwater Agriculture MiresMarshes

ID008 MiresMarshes Freshwater Agriculture Urban

ID009 Freshwater Agriculture Agriculture Freshwater

ID010 Mixed Urban Sparsely Vegetated Urban

ID012 Coniferous GrasslandMoors Freshwater Urban

ID014 Urban Agriculture Freshwater Urban

ID015 Mixed Forest Urban Clear Fell Urban

ID016 Freshwater Urban GrasslandMoors Mixed

ID017 Coniferous Mixed Coniferous Broad Leaf

ID019 Broad Leaf GrasslandMoors Urban GrasslandMoors

ID020 Freshwater Urban Freshwater Agriculture

ID022 MiresMarshes Urban Broad Leaf GrasslandMoors

ID023 Freshwater Mixed Agriculture Freshwater

ID024 Mixed Freshwater Mixed Freshwater

ID026 Mixed MiresMarshes Sparsely Vegetated GrasslandMoors

ID027 Freshwater MiresMarshes GrasslandMoors Broad Leaf

44

Fig 2 North third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)

45

Fig 3 Centre third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)

46

Fig 4 South third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)

47

Fig 5 North second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)

48

Fig 6 Centre second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)

49

Fig 7 South second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)

50

Appendix F

Background

Fig 1 Daily mean snow depth and duration during the study period (Andrew Allen)

Female Moose Reproduction

Moose are seasonal polyoestral mammals (Monfort et al 1993) coming into oestrus during late September

early October (Garel et al 2009) The Swedish moose cow population reaches puberty between the ages 25

and 35 (Sand and Cederlund 1993) during which the reproductive period begins with the onset of ovulation

The age an individual reaches puberty is dependent on their body condition they have to reach a weight

threshold to reach puberty and become reproductive (Sand 1996) If she is over the weight threshold she will

go into oestrus in the autumn If she does not reach the weight threshold then she will go into oestrus the

following autumn if successful she will give birth to individual or twin calves in late May to early June

(Ericsson et al 2001) and therefore reach sexual maturity (Malmsten et al 2014b) Fecundity is related to

both the condition and the age of the cow Cows go through senescence at 12 years of age (Ericsson et al

2001) Providing calves with the required level of nutrition demands high energy and protein resources from

the mother during senescence this becomes harder to achieve leading to decreased levels of parental care

and higher levels of calf mortality

Page 17: Habitat-performance relationships on an island: fitness ...navinderjsingh.weebly.com/uploads/1/1/2/2/11224342/... · Conditions on Öland are milder than those found in other areas

17 Diet

Diet analysis of the rumen content sampled from five individuals (C=2 S=3) revealed that almost two thirds

(69) of the diet is comprised of agricultural produce (apple winter rape and sugar beet) (Fig 6)

Fig 6 Diet analysis from the rumen samples of five moose individuals that were culled in 2013

31

2117

9

8

5

22

1 1

1

1

1 00 0

0

0Diet (2610-911 2013 5 individuals)

AppleWinter RapeSugar BeetUndefined WoodSallowBroad-leaf GrassPineAshOakCloverCurrantsUndefined plantElderberryJuniperRaspberry

18

Calf Survival

Of the 18 individuals 13 produced calves in which 7 produced twins giving a total of 20 calves A Kaplan-

Meier estimate was conducted to measure the fraction of calves living up to each period of the study (Fig 7)

The mean survival time is until period 235 (midend of summer) At the start of summer 85 of calves

remained (3 still born) The period between summer and before the hunt survival drops to 30 The survival

at the end of the study (after hunt) drops further to 20 leaving 4 calves surviving (see appendix B)

Fig 7 Kaplan-Meier estimate of moose calf survival during the study period Period 0 (Start of summer) period 1

(midend of summer) period 2 (before hunt) period 3 (after hunt) period 4 (after winter)

19 Discussion

The results of this study emphasised how strikingly different the habitat composition is along the latitudinal

gradient of Oumlland The three areas show contrasting proportions of the key habitat types The starkest

difference is the high proportion of coniferous forests and lack of agriculture in the north compared to the

centre and south The proportion of coniferous forest in the north is almost 5 times greater than in the centre

and south whereas the proportion of agriculture in the centre and south is more than double that in the north

The north is perceived to be composed of the most suitable habitat for moose (Dussault et al 2006) It has the

largest proportions of each forest type and a low proportion of agricultural land This provides suitable forage

and shelter throughout the year The south has a contrasting habitat composition to the north The proportions

of agricultural and sparsely vegetated areas are the highest between the three areas and the proportions of forest

habitats are the lowest The large proportion of sparsely vegetated areas and low proportions of forest habitat

corresponds to the large area of Stora Alvaret This is perceived to be the least suitable area due to a lack of

shelter (coniferous forest) and suitable forage The strong preference for coniferous and younger forest habitats

in the south would suggest that moose exhibit a functional response in habitat selection (Godvik et al 2009)

ie as the proportion of a particular habitat decreases the selection for that habitat increases in this case

coniferous forests which provide shelter and younger forest which provide good forage Similarly in the centre

moose show strong preference for mixed forests a habitat that is of low proportion

In view of the large variation in habitat proportions between the areas it is surprising that there is not a large

variation in the home range sizes or the activity levels annually or seasonally Home ranges are ultimately

chosen to maximise fitness and meet energy requirements by utilizing the available forage Seasonal conditions

change the availability and necessity of resources (food quality shelter) Unlike the GS during the WS

deciduous trees and shrubs are leafless and low-lying shrubs are under snow cover (Dussault et al 2005)

These changes are well known to cause populations to alter their activity and home ranges to meet energy

requirements (Mysterud et al 2001) Populations have been shown to increase or decrease their home ranges

during the two seasons The GS home ranges are often larger than the WS home ranges (Philips et al 1973

Mysterud et al 2001) In some cases they can be found to be almost double the size of the WS home ranges

(Cederlund and Okarma 1988) In other populations the WS home ranges are double the size of the GS home

ranges (Lynch and Morgantini 1984) or sizes do not significantly differ (Cederlund and Sand 1994)

Previous studies on moose find females generally show increased activity from the start on the GS due to

various factors eg reduced ruminating times increased metabolic needs and increased foraging bursts

(Wattles and DeStefano 2013) Increased metabolic needs during this time are a results of pregnancy and

lactation (Georgii 1980) During the height of the GS they usually show reduced activity levels through times

of increased thermal stress (Renecker and Hudson 1989 van Beest et al 2012) During the WS the depth and

the duration of snow cover are well known to affect the activity level (Telfer 1970 Mysterud and Oslashstbye 1999

Bjoslashrneraas et al 2011) During the WS generally home ranges are smaller and activity less due to lower

metabolic needs Moose activity is constrained by rumination during the WS this period is known to be longer

due to the change in diet (Cederlund 1989 Renecker Hudson 1989) This was not the case on Ӧland activity

20

was lowest in February which is a similar result to Cederlundrsquos (1989) paper However Ӧland moose did not

significantly alter their seasonal activity levels The fact that the annual and seasonal activity levels and home

ranges were similar could be a result of the mild winters on Oumlland during the study period (Smhise 2014)

During the study period the average number of snow days was 80 and the mean snow depth was 10cm

(appendix F) (Swedish Meterological and Hydrological Institute- SMHI) These mild conditions do not restrict

the movement of moose or obscure forage Moose are well adapted for movement in deep snow depths of 60-

86cm (Prescott 1968) are needed to truly restrict movement This finding was similar to the Sweanor and

Sandegren (1989) and Cederlund and Sand (1994) where the snow depth at their sites did not reach movement

restricting depths

The survival curve illustrates just how bad the calf survival is on Ӧland Survival falls from 85 at the start to

20 Out of 20 calves only four were alive at the end of the study The sharpest fall in survival was the period

between end of summer and before the hunt so the deaths were not due to hunting Previous calf autopsies

(Malmsten 2014a) have shown that cause of death was starvation mothers possibly either did not have milk

the calf was unable to feed or the mother abandoned the calf Closer field based observations are needed to

attain this knowledge Moose are seasonal polyoestral mammals (Monfort et al 1993) coming into oestrus

during late September early October (Garel et al 2009) (appendix F) The diet of the mother influences the

health of the calf and this period is when sodium is hard to find sodium is a key mineral in moose diets for

features such as reproduction (Belovsky and Jordan 1981) Moose gain sodium mainly through aquatic plants

(MacCracken et al 1993) However the compositional analysis shows that freshwater areas are often ranked

as one of the lowest used habitats and coastal areas were removed as the proportion found in the home ranges

was extremely low The Jacobs Index shows that the moose only prefer freshwater areas in the north UD50

during the WS The north individuals again are those that are showing typical moose habitat selection

It is known that habitat selection is hierarchical with habitats that increase fitness selected for and the effects

of limiting factors are reduced (Rettie and Messier 2000) At the UD95 during the GS moose preferred areas

of good forage (forests) and avoided areas of low forage (freshwater and sparsely vegetated areas) and areas

close to humans (urban) This is consistent with other reports (Laurian et al 2008 Torres et al 2011) Within

the UD50 there is a shift in preferences The good forage areas are again preferred during the GS however

during WS the only preferred habitat is often agricultural land During the WS there could be a steady supply

of supplementary feed available hence the high levels of agricultural produce found in the rumen content

samples and the high preference of agricultural areas This diet is unusual for moose previous studies of

Swedish moose diet have found the GS diet was dominated by birch willow and herbaceous plants and the

WS diet dominated by pine and birch (Cederlund and Nystrom 1981) The diet analysis was conducted during

the WS instead of being dominant pine composed just 2 Birch did not appear however unidentified wood

composed only 9 whereas agricultural produce accounted for 69 Supplementary feed may be perceived

by the moose in the centre and south as a vital forage source during the WS In fact in the centre the

agricultural land is the only preferred habitat at the UD50 It is unknown whether there are salt licks provided

in these areas Selection for a critical habitat is often thought to be a fixed factor The Oumlland population from

21 the three areas are close in proximity however they displayed contrasting preferences This is supported by the

Osko et al (2004) report that found two neighbouring moose populations that had access to the same habitats

displayed contrasting preferences Habitat preferences for populations of the same species are not necessarily

fixed They alter with varying levels of habitat abundance and limiting factors skewing what is preserved to

be critical

The main limitation encountered in this study was with the limited sample There was only data on two

individuals from the north of the island which led it being removed from many of the analysis Similarly due

to a lack of relocations from the collars being turned off at points throughout the year two further individuals

had to be removed from a majority of the analysis This reduced the sample size to 17 or 18 individuals

Similarly only 13 of the individuals from the study produced calves This unfortunately prevented including

survival into models Although the sample size was small it was accurate it was of high resolution over

300000 GPS points In future it would be beneficial to have a more standardised data set An equal sample of

individuals from the three areas would be advised along with ensuring the GPS collars are kept turned on for

the entirety of the growing and winter season to allow comparisons between years It would also be

advantageous to collect coordinates of the feeding sites along with the composition This could then be

compared with high use UD coordinates to look if moose are truly spending a majority of their foraging time

at feeding stations A study on the population densities of moose and the increasing population of roe deer

(Capreolus capreolus) would add the factor of competition into the model

The low calf survival on Ӧland is most likely the result of a combination of factors The lack of suitable habitat

reported in this study in conjunction with Malmstenrsquos (2014a) report on the threat of disease (Anaplasma

phagocytophilum) are probable influences on the calf survival on Ӧland On Ӧland there is an increasing

population of roe deer and large numbers of migratory birds both carriers of ticks and diseases The mild

conditions on Ӧland are advantageous for ticks the carriers of A phagocytophilum Fewer snow days and

shorter periods of snow cover along with dry conditions are favourable for ticks This could probably be one

of the reasons for females to be of lower quality and therefore not being able to ensure calf survival Moose

have to utilise areas where in other populations individuals tend to avoid Finally similar to many studies I

advocate further research using a stronger dataset and longer term monitoring

22

Acknowledgements

I am indebted to NJ Singh and A Allen for all their help and guidance through the whole of this study I

thank SLU for the support provided during this study in terms of data finances and facilities Thank you to

everyone at the Department of Wildlife Fish and Environmental Studies for being so friendly and

supportive I would like to thank L Edenius for driving me around the study area and S Michon and H

Khalil for keeping me sane with fika and training

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Bjoslashrneraas K Solberg EJ Herfindal I Van Moorter B Rolandsen CM Tremblay JP Skarpe C Sӕther B-E

Erikson R Astrup R (2011) Moose Alces alces habitat use at multiple temporal scales in a

human altered landscape Wildlife Biology 1744-54

Boman M Matsson L Ericsson G Kristroumlm B (2011) Moose hunting values in Sweden now and two

decades ago the Swedish hunters revisited Environmental and Resource Economics 50515-

530

Bradshaw RHW Hannon GE Lister AM (2003) A long-term perspective on ungulate-vegetation

interactions Forest Ecology and Management 181267-280

Brandin E (2009) Versions of lsquowildrsquo and the importance of fences in Swedish wildlife tourism involving

moose Current Issues in Tourism 12413-427

Burt WH (1943) Territoriality and home range concepts as applied to mammals Journal of Mammalogy

24346-352

24

Bunnefeld N Boumlrger L van Moorter B Rolandsen CM Dettki H Solberg EJ Ericsson G(2011) A model-

driven approach to quantify migration patterns individual regional and yearly differences

Journal of Animal Ecology 80466-476

Brown G (2011) Patterns and causes of demographic variation in a harvested moose population evidence for

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Calenge C (2006) The package adehabitat for the R software a tool for the analysis of space and habitat use

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Calenge C (2011) Home Range Estimation in R the adehabitatHR package Office national de la classe et de

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Cederlund GN Okarma H (1988) Home range and habitat use of adult female moose Journal of Wildlife

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Cederlund GN (1989) Activity patterns in moose and roe deer in a north boreal forest Holarctic Ecology

1239-45

Cederlund GN Sand H (1994) Home-range size in relation to age and sex in moose American Society of

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25(10)562-573

Cooke SJ Hinch SG Wikelski M Andrews RD Kuchel LJ Wolcott TG Butler PJ (2004) Biotelemerty a

mechanistic approach to ecology Trends in Ecology and Evolution 19334-343

Crecircte M Courtois R (1997) Limiting factors might obscure population regulation of moose (Cervidae Alces

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Sedetalia) on the island of Ӧland (Sweden) in the context of north and central Europe

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Dussault C Courtois R Ouellet JP (2006) A habitat suitability index model to assess moose habitat selection

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Hornok S Kovaacutets D Csoumlrgo T Meli M Goumlnczi E Hadnagy Z Takaacutecs N Farkas R Hofmann-Lehmann R

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Kie JG Matthiopolos J Fieberg J Powell RA Cagnacci F Mitchell SM Gaillard JM Moorcroft PR (2010)

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Kranstauber B Kays R LaPoint SD Wikelski M Safi K (2012) A dynamic Brownian bridge movement

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30

Appendix A

Introduction

Fig 1 Summary chart of factors affecting the life history and therefore the long term fitness of a population

Fig 2 Summary chart 2

Movement

Habitat

Climate

Topography

Competition

FoodWater

Disease

Die

Survive

Reproduce

Population long term fitness

31 Appendix B

Method and Materials

Fig 1 Summary of processes

32

Fig 2 Examples of classical kernel home range output and Brownian bridge kernel home range (Calenge 2011) The

right image includes the area between relocations ie the movement path in contrast to the classic kernel home range

in the left image

33 Appendix C

Home ranges

Fig 1 Example of a non-migratory (ID006) individuals BRB kernel area From top left annual growing and winter

season UD50 (black contour) and UD95 (red contour)

Fig 2 Example of a migratory (ID012) individuals BRB kernel area From the left annual growing and winter season

UD50 (black contour) and UD95 (red contour)

34

Table 1 Annual and seasonal UD50 and UD95 areas (ha) for all individuals

ID Annual GS WS

UD50 UD95 UD50 UD95 UD50 UD95

ID004 190 924 93 531 173 941

ID005 230 1364 132 945 72 682

ID006 162 1036 89 736 70 611

ID008 277 1536 156 809 78 738

ID009 137 834 48 295 126 653

ID010 114 682 83 448 96 488

ID012 177 963 123 544 76 545

ID014 160 1018 87 575 89 662

ID015 172 858 128 532 109 679

ID016 156 1047 65 455 92 534

ID017 153 1088 149 1043 69 349

ID019 279 1097 176 911 163 824

ID020 139 1084 67 349 160 794

ID022 159 811 131 638 61 454

ID023 187 1061 147 771 72 705

ID024 146 725 165 705 101 458

ID026 142 605 99 442 125 547

ID027 126 567 75 461 48 277

35 Appendix D

Activity

Fig 1 Mean daily movement during the study period GS 23-April-2012 to 07-Nov-2012 WS 08-Nov-2012 to

22-April-2013 (number indicates month)

Fig 2 Mean daily movement in the centre and south during the GS and WS

36

Appendix E

Habitat Proportions

Fig 1 All individualsrsquo seasonal habitat proportions within the UD95

37 Habitat Selection

Table 1 Simplified ranking matrices comparing proportional habitat use within the second order (UD95Area) with

proportions of total available habitat types Mean value on the matrix was replaced by a sign a triple sign represents

significant deviation from random at P lt05 Highlighted habitat is ranked 1st

North A

gri

cult

ure

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 --- --- - +++ --- --- --- +++ +++ --- 8

Broad Leaf +++ 0 +++ + +++ +++ +++ + +++ +++ +++ 1

Clear Fell +++ --- 0 + +++ - - --- +++ +++ --- 7

Coniferous + - - 0 +++ - - --- +++ +++ - 6

Freshwater --- --- --- --- 0 --- --- --- +++ - --- 10

Grassland

Moors +++ --- + + +++ 0 +++ - +++ +++ + 3

MiresMarshes +++ --- + + +++ --- 0 - +++ +++ --- 5

Mixed +++ - +++ +++ +++ + + 0 +++ +++ + 2

Sparse Veg --- --- --- --- --- --- --- --- 0 --- --- 11

Urban --- --- --- --- + --- --- --- +++ 0 --- 9

Younger +++ --- +++ + +++ - +++ - +++ +++ 0 4

Rank Order and

Significance

Broad Leafgt Mixedgt GrasslandMoorsgt Youngergtgtgt MiresMarshesgt Coniferousgt

Clear Fellgtgtgt Agriculturegtgtgt Urbangt Freshwatergtgtgt Sparse Veg

Central

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 --- --- --- + +++ + --- +++ +++ --- 6

Broad Leaf +++ 0 +++ + +++ +++ + - +++ +++ - 3

Clear Fell +++ --- 0 - +++ +++ + --- +++ +++ --- 5

Coniferous +++ - + 0 +++ +++ + --- +++ +++ - 4

Freshwater - --- --- --- 0 +++ - --- +++ +++ --- 8

Grassland

Moors --- --- --- --- --- 0 --- --- +++ - --- 10

MiresMarshes - - - - + +++ 0 - +++ +++ - 7

Mixed +++ + +++ +++ +++ +++ + 0 +++ +++ + 1

Sparse Veg --- --- --- --- --- --- --- --- 0 - --- 11

Urban --- --- --- --- --- + --- --- + 0 --- 9

Younger +++ + +++ + +++ +++ + - +++ +++ 0 2

Rank Order and

Significance

Mixedgt Youngergt Broad Leafgt Coniferousgt Clear Fellgtgtgt Agriculturegt

MiresMarshesgt Freshwatergtgtgt Urbangt GrasslandMoorsgtgtgt Sparse Veg

38

South

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 + - - + - + +++ +++ +++ - 5

Broad Leaf - 0 - - + - - +++ + +++ - 7

Clear Fell + + 0 - + + + +++ + +++ + 2

Coniferous + + + 0 +++ + + +++ + +++ + 1

Freshwater - - - --- 0 - - + + +++ - 8

Grassland

Moors + + - - + 0 + + +++ + - 4

MiresMarshes - + - - + - 0 +++ + +++ - 6

Mixed --- --- --- --- - - --- 0 + + --- 10

Sparse Veg --- - - - - --- - - 0 + - 9

Urban --- --- --- --- --- - --- - - 0 --- 11

Younger + + - - + + + +++ + +++ 0 3

Rank Order

and

Significance

Coniferousgt Clear Fellgt Youngergt GrasslandMoorsgt Agriculturegt MiresMarshesgt Broad Leafgt

Freshwatergt Sparse Veggt Mixedgt Urban

Table 2 Simplified ranking matrices comparing proportional habitat use within the third order (UD50UD95) with

proportions of total available habitat types Mean value on the matrix was replaced by a sign a triple sign represents

significant deviation from random at P lt05 Highlighted habitat is ranked 1st

North

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 --- --- --- - + --- --- + +++ --- 8

Broad Leaf +++ 0 +++ + + + + + +++ +++ + 1

Clear Fell +++ --- 0 + + + - - + +++ - 5

Coniferous +++ - - 0 + + --- --- +++ +++ - 6

Freshwater + - - - 0 +++ - - +++ +++ - 7

GrasslandMoors - - - - --- 0 - - - + - 10

MiresMarshes +++ - + +++ + + 0 - +++ +++ + 3

Mixed +++ - + +++ + + + 0 +++ +++ + 2

Sparse Veg - --- - --- --- + --- --- 0 +++ --- 9

Urban --- --- --- --- --- - --- --- --- 0 --- 11

Younger +++ - + + + + - - +++ +++ 0 4

Rank Order and

Significance

Broad Leafgt Mixedgt MiresMarshesgt Youngergt Clear Fellgt Coniferousgt Freshwatergt

Agriculturegt Sparse Veggt GrasslandMoorsgt Urban

39

Central

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 --- --- + + - - - + +++ --- 7

Broad Leaf +++ 0 + +++ + + + + + +++ - 2

Clear Fell +++ - 0 +++ + + + + + +++ - 3

Coniferous - --- --- 0 + - - --- +++ + --- 8

Freshwater - - - - 0 --- - - --- - - 11

GrasslandMoors + - - + +++ 0 + - + +++ - 5

MiresMarshes + - - + + - 0 + + +++ - 6

Mixed + - - +++ + + - 0 +++ +++ - 4

Sparse Veg - - - --- +++ - - --- 0 +++ - 9

Urban --- --- --- - + --- --- --- --- 0 --- 10

Younger +++ + + +++ + + + + + +++ 0 1

Rank Order and

Significance

Youngergt Broad Leafgt Clear Fellgt Mixedgt GrasslandMoorsgt MiresMarshesgt

Agriculturegt Coniferousgtgtgt Sparse Veggtgtgt Urbangt Freshwater

South

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 - - - - - + - +++ + --- 8

Broad Leaf + 0 - --- + - + - +++ + - 6

Clear Fell + + 0 - + - + - +++ + - 4

Coniferous + +++ + 0 + + +++ + +++ + + 1

Freshwater + - - - 0 - - + + + - 7

GrasslandMoors + + + - + 0 + + + + - 3

MiresMarshes - - - --- + - 0 - + + - 9

Mixed + + + - - - + 0 + + - 5

Sparse Veg --- --- --- --- - - - - 0 + --- 10

Urban - - - - - - - - - 0 - 11

Younger +++ + + - + + + + +++ + 0 2

Rank Order and

Significance

Coniferousgt Youngergt GrasslandMoorsgt Clear Fellgt Mixedgt Broad Leafgt Freshwatergt

Agriculturegt MiresMarshesgt Sparse Veggt Urban

40

Table 3 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the GS according to Jacobs index

Ran

k North Centre South

50 95 50 95 50 95

+ - + - + - + - + - + -

1 Broad

Leaf Urban Broad Leaf Sparse Veg

Broad

Leaf Urban Mixed Urban Coniferous Urban

Grassland

Moors Urban

2 Mixed Sparse Veg Mixed Freshwater Younger Agriculture Younger Sparse Veg Younger Sparse Veg Clear Fell Mixed

3 Mires

Agriculture Grassland

Urban Clear

Fell Coniferous Broad Leaf

Grassland

Moors

Clear Fell Agriculture Coniferous Sparse Veg

Marshes Moors

4 Younger Grassland

Younger Agriculture

Freshwater Coniferous Freshwater

Broad Leaf Mires

Younger Freshwater

Moors Marshes

5 Clear

Fell Freshwater

Mires Coniferous

Sparse Veg Clear Fell Agriculture

Freshwater Agriculture

Marshes

6 Coniferous Clear Fell

Mires

Marshes

Mires

Grassland

Moors

Mires

Marshes Marshes

7 Mixed Mixed Broad Leaf

8 Grassland

Moors

41

Table 4 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the WS according to Jacobs index

Ran

k North Centre South

50 95 50 95 50 95

+ - + - + - + - + - + -

1 Mires

Marshes

Grassland

Moors Mixed Freshwater Agriculture Urban Mixed Freshwater

Grassland

Moors Urban GrasslandMoors Urban

2 Freshwater Mixed Coniferous Urban Mires

Marshes Coniferous Sparse Veg Agriculture

Sparse

Veg Coniferous Freshwater

3 Urban Coniferous Younger Grassland

Moors Freshwater Younger Urban Freshwater

Broad

Leaf Agriculture Mixed

4 Younger Agriculture Sparse Veg Broad

Leaf

Broad

Leaf

Grassland

Moors Mixed Broad Leaf

5 Clear Fell Agriculture Coniferous Agriculture Mires

Marshes Clear Fell

6 Sparse

Veg

Mires

Marshes Mixed

Mires

Marshes

Clear

Fell

Mires

Marshes

7 Broad

Leaf Clear Fell Younger Clear Fell Younger Sparse Veg

8 Clear Fell Younger

9 Sparse

Veg

10 Grassland

Moors

42

Table 5 Second order (UD95Area) individual selectionavoidance for the GS and WS according to the Jacobs index

ID GS WS

Select Avoid Select Avoid

ID004 Younger Sparsely Vegetated MiresMarshes Sparsely Vegetated

ID005 MiresMarshes Sparsely Vegetated Coniferous GrasslandMoors

ID006 Coniferous Sparsely Vegetated Mixed Freshwater

ID008 Mixed Sparsely Vegetated Mixed Freshwater

ID009 Mixed Sparsely Vegetated Mixed GrasslandMoors

ID010 MiresMarshes Freshwater GrasslandMoors Freshwater

ID012 Broad Leaf Sparsely Vegetated Coniferous Urban

ID014 Clear Fell Sparsely Vegetated GrasslandMoors Sparsely Vegetated

ID015 GrasslandMoors Urban GrasslandMoors Freshwater

ID016 GrasslandMoors Freshwater GrasslandMoors Freshwater

ID017 GrasslandMoors Mixed Sparsely Vegetated Mixed

ID019 Mixed Sparsely Vegetated Mixed Urban

ID020 Broad Leaf Sparsely Vegetated Coniferous GrasslandMoors

ID022 MiresMarshes Freshwater MiresMarshes Freshwater

ID023 MiresMarshes GrasslandMoors Mixed Freshwater

ID024 Broadleaf Urban Broad Leaf Urban

ID026 GrasslandMoors Freshwater GrasslandMoors Freshwater

ID027 GrasslandMoors Urban Sparsely Vegetated Freshwater

43 Table 6 Third order (UD50UD95) individual selectionavoidance for the GS and WS according to the Jacobs index

ID GS WS

Select Avoid Select Avoid

ID004 Broad Leaf Mixed GrasslandMoors Freshwater

ID005 Broad Leaf Freshwater Agriculture Freshwater

ID006 Clear Fell Freshwater Agriculture MiresMarshes

ID008 MiresMarshes Freshwater Agriculture Urban

ID009 Freshwater Agriculture Agriculture Freshwater

ID010 Mixed Urban Sparsely Vegetated Urban

ID012 Coniferous GrasslandMoors Freshwater Urban

ID014 Urban Agriculture Freshwater Urban

ID015 Mixed Forest Urban Clear Fell Urban

ID016 Freshwater Urban GrasslandMoors Mixed

ID017 Coniferous Mixed Coniferous Broad Leaf

ID019 Broad Leaf GrasslandMoors Urban GrasslandMoors

ID020 Freshwater Urban Freshwater Agriculture

ID022 MiresMarshes Urban Broad Leaf GrasslandMoors

ID023 Freshwater Mixed Agriculture Freshwater

ID024 Mixed Freshwater Mixed Freshwater

ID026 Mixed MiresMarshes Sparsely Vegetated GrasslandMoors

ID027 Freshwater MiresMarshes GrasslandMoors Broad Leaf

44

Fig 2 North third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)

45

Fig 3 Centre third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)

46

Fig 4 South third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)

47

Fig 5 North second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)

48

Fig 6 Centre second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)

49

Fig 7 South second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)

50

Appendix F

Background

Fig 1 Daily mean snow depth and duration during the study period (Andrew Allen)

Female Moose Reproduction

Moose are seasonal polyoestral mammals (Monfort et al 1993) coming into oestrus during late September

early October (Garel et al 2009) The Swedish moose cow population reaches puberty between the ages 25

and 35 (Sand and Cederlund 1993) during which the reproductive period begins with the onset of ovulation

The age an individual reaches puberty is dependent on their body condition they have to reach a weight

threshold to reach puberty and become reproductive (Sand 1996) If she is over the weight threshold she will

go into oestrus in the autumn If she does not reach the weight threshold then she will go into oestrus the

following autumn if successful she will give birth to individual or twin calves in late May to early June

(Ericsson et al 2001) and therefore reach sexual maturity (Malmsten et al 2014b) Fecundity is related to

both the condition and the age of the cow Cows go through senescence at 12 years of age (Ericsson et al

2001) Providing calves with the required level of nutrition demands high energy and protein resources from

the mother during senescence this becomes harder to achieve leading to decreased levels of parental care

and higher levels of calf mortality

Page 18: Habitat-performance relationships on an island: fitness ...navinderjsingh.weebly.com/uploads/1/1/2/2/11224342/... · Conditions on Öland are milder than those found in other areas

18

Calf Survival

Of the 18 individuals 13 produced calves in which 7 produced twins giving a total of 20 calves A Kaplan-

Meier estimate was conducted to measure the fraction of calves living up to each period of the study (Fig 7)

The mean survival time is until period 235 (midend of summer) At the start of summer 85 of calves

remained (3 still born) The period between summer and before the hunt survival drops to 30 The survival

at the end of the study (after hunt) drops further to 20 leaving 4 calves surviving (see appendix B)

Fig 7 Kaplan-Meier estimate of moose calf survival during the study period Period 0 (Start of summer) period 1

(midend of summer) period 2 (before hunt) period 3 (after hunt) period 4 (after winter)

19 Discussion

The results of this study emphasised how strikingly different the habitat composition is along the latitudinal

gradient of Oumlland The three areas show contrasting proportions of the key habitat types The starkest

difference is the high proportion of coniferous forests and lack of agriculture in the north compared to the

centre and south The proportion of coniferous forest in the north is almost 5 times greater than in the centre

and south whereas the proportion of agriculture in the centre and south is more than double that in the north

The north is perceived to be composed of the most suitable habitat for moose (Dussault et al 2006) It has the

largest proportions of each forest type and a low proportion of agricultural land This provides suitable forage

and shelter throughout the year The south has a contrasting habitat composition to the north The proportions

of agricultural and sparsely vegetated areas are the highest between the three areas and the proportions of forest

habitats are the lowest The large proportion of sparsely vegetated areas and low proportions of forest habitat

corresponds to the large area of Stora Alvaret This is perceived to be the least suitable area due to a lack of

shelter (coniferous forest) and suitable forage The strong preference for coniferous and younger forest habitats

in the south would suggest that moose exhibit a functional response in habitat selection (Godvik et al 2009)

ie as the proportion of a particular habitat decreases the selection for that habitat increases in this case

coniferous forests which provide shelter and younger forest which provide good forage Similarly in the centre

moose show strong preference for mixed forests a habitat that is of low proportion

In view of the large variation in habitat proportions between the areas it is surprising that there is not a large

variation in the home range sizes or the activity levels annually or seasonally Home ranges are ultimately

chosen to maximise fitness and meet energy requirements by utilizing the available forage Seasonal conditions

change the availability and necessity of resources (food quality shelter) Unlike the GS during the WS

deciduous trees and shrubs are leafless and low-lying shrubs are under snow cover (Dussault et al 2005)

These changes are well known to cause populations to alter their activity and home ranges to meet energy

requirements (Mysterud et al 2001) Populations have been shown to increase or decrease their home ranges

during the two seasons The GS home ranges are often larger than the WS home ranges (Philips et al 1973

Mysterud et al 2001) In some cases they can be found to be almost double the size of the WS home ranges

(Cederlund and Okarma 1988) In other populations the WS home ranges are double the size of the GS home

ranges (Lynch and Morgantini 1984) or sizes do not significantly differ (Cederlund and Sand 1994)

Previous studies on moose find females generally show increased activity from the start on the GS due to

various factors eg reduced ruminating times increased metabolic needs and increased foraging bursts

(Wattles and DeStefano 2013) Increased metabolic needs during this time are a results of pregnancy and

lactation (Georgii 1980) During the height of the GS they usually show reduced activity levels through times

of increased thermal stress (Renecker and Hudson 1989 van Beest et al 2012) During the WS the depth and

the duration of snow cover are well known to affect the activity level (Telfer 1970 Mysterud and Oslashstbye 1999

Bjoslashrneraas et al 2011) During the WS generally home ranges are smaller and activity less due to lower

metabolic needs Moose activity is constrained by rumination during the WS this period is known to be longer

due to the change in diet (Cederlund 1989 Renecker Hudson 1989) This was not the case on Ӧland activity

20

was lowest in February which is a similar result to Cederlundrsquos (1989) paper However Ӧland moose did not

significantly alter their seasonal activity levels The fact that the annual and seasonal activity levels and home

ranges were similar could be a result of the mild winters on Oumlland during the study period (Smhise 2014)

During the study period the average number of snow days was 80 and the mean snow depth was 10cm

(appendix F) (Swedish Meterological and Hydrological Institute- SMHI) These mild conditions do not restrict

the movement of moose or obscure forage Moose are well adapted for movement in deep snow depths of 60-

86cm (Prescott 1968) are needed to truly restrict movement This finding was similar to the Sweanor and

Sandegren (1989) and Cederlund and Sand (1994) where the snow depth at their sites did not reach movement

restricting depths

The survival curve illustrates just how bad the calf survival is on Ӧland Survival falls from 85 at the start to

20 Out of 20 calves only four were alive at the end of the study The sharpest fall in survival was the period

between end of summer and before the hunt so the deaths were not due to hunting Previous calf autopsies

(Malmsten 2014a) have shown that cause of death was starvation mothers possibly either did not have milk

the calf was unable to feed or the mother abandoned the calf Closer field based observations are needed to

attain this knowledge Moose are seasonal polyoestral mammals (Monfort et al 1993) coming into oestrus

during late September early October (Garel et al 2009) (appendix F) The diet of the mother influences the

health of the calf and this period is when sodium is hard to find sodium is a key mineral in moose diets for

features such as reproduction (Belovsky and Jordan 1981) Moose gain sodium mainly through aquatic plants

(MacCracken et al 1993) However the compositional analysis shows that freshwater areas are often ranked

as one of the lowest used habitats and coastal areas were removed as the proportion found in the home ranges

was extremely low The Jacobs Index shows that the moose only prefer freshwater areas in the north UD50

during the WS The north individuals again are those that are showing typical moose habitat selection

It is known that habitat selection is hierarchical with habitats that increase fitness selected for and the effects

of limiting factors are reduced (Rettie and Messier 2000) At the UD95 during the GS moose preferred areas

of good forage (forests) and avoided areas of low forage (freshwater and sparsely vegetated areas) and areas

close to humans (urban) This is consistent with other reports (Laurian et al 2008 Torres et al 2011) Within

the UD50 there is a shift in preferences The good forage areas are again preferred during the GS however

during WS the only preferred habitat is often agricultural land During the WS there could be a steady supply

of supplementary feed available hence the high levels of agricultural produce found in the rumen content

samples and the high preference of agricultural areas This diet is unusual for moose previous studies of

Swedish moose diet have found the GS diet was dominated by birch willow and herbaceous plants and the

WS diet dominated by pine and birch (Cederlund and Nystrom 1981) The diet analysis was conducted during

the WS instead of being dominant pine composed just 2 Birch did not appear however unidentified wood

composed only 9 whereas agricultural produce accounted for 69 Supplementary feed may be perceived

by the moose in the centre and south as a vital forage source during the WS In fact in the centre the

agricultural land is the only preferred habitat at the UD50 It is unknown whether there are salt licks provided

in these areas Selection for a critical habitat is often thought to be a fixed factor The Oumlland population from

21 the three areas are close in proximity however they displayed contrasting preferences This is supported by the

Osko et al (2004) report that found two neighbouring moose populations that had access to the same habitats

displayed contrasting preferences Habitat preferences for populations of the same species are not necessarily

fixed They alter with varying levels of habitat abundance and limiting factors skewing what is preserved to

be critical

The main limitation encountered in this study was with the limited sample There was only data on two

individuals from the north of the island which led it being removed from many of the analysis Similarly due

to a lack of relocations from the collars being turned off at points throughout the year two further individuals

had to be removed from a majority of the analysis This reduced the sample size to 17 or 18 individuals

Similarly only 13 of the individuals from the study produced calves This unfortunately prevented including

survival into models Although the sample size was small it was accurate it was of high resolution over

300000 GPS points In future it would be beneficial to have a more standardised data set An equal sample of

individuals from the three areas would be advised along with ensuring the GPS collars are kept turned on for

the entirety of the growing and winter season to allow comparisons between years It would also be

advantageous to collect coordinates of the feeding sites along with the composition This could then be

compared with high use UD coordinates to look if moose are truly spending a majority of their foraging time

at feeding stations A study on the population densities of moose and the increasing population of roe deer

(Capreolus capreolus) would add the factor of competition into the model

The low calf survival on Ӧland is most likely the result of a combination of factors The lack of suitable habitat

reported in this study in conjunction with Malmstenrsquos (2014a) report on the threat of disease (Anaplasma

phagocytophilum) are probable influences on the calf survival on Ӧland On Ӧland there is an increasing

population of roe deer and large numbers of migratory birds both carriers of ticks and diseases The mild

conditions on Ӧland are advantageous for ticks the carriers of A phagocytophilum Fewer snow days and

shorter periods of snow cover along with dry conditions are favourable for ticks This could probably be one

of the reasons for females to be of lower quality and therefore not being able to ensure calf survival Moose

have to utilise areas where in other populations individuals tend to avoid Finally similar to many studies I

advocate further research using a stronger dataset and longer term monitoring

22

Acknowledgements

I am indebted to NJ Singh and A Allen for all their help and guidance through the whole of this study I

thank SLU for the support provided during this study in terms of data finances and facilities Thank you to

everyone at the Department of Wildlife Fish and Environmental Studies for being so friendly and

supportive I would like to thank L Edenius for driving me around the study area and S Michon and H

Khalil for keeping me sane with fika and training

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Renecker LA Hudson RJ (1989) Seasonal activity budgets of moose in Aspen-dominated boreal forests The

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29

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30

Appendix A

Introduction

Fig 1 Summary chart of factors affecting the life history and therefore the long term fitness of a population

Fig 2 Summary chart 2

Movement

Habitat

Climate

Topography

Competition

FoodWater

Disease

Die

Survive

Reproduce

Population long term fitness

31 Appendix B

Method and Materials

Fig 1 Summary of processes

32

Fig 2 Examples of classical kernel home range output and Brownian bridge kernel home range (Calenge 2011) The

right image includes the area between relocations ie the movement path in contrast to the classic kernel home range

in the left image

33 Appendix C

Home ranges

Fig 1 Example of a non-migratory (ID006) individuals BRB kernel area From top left annual growing and winter

season UD50 (black contour) and UD95 (red contour)

Fig 2 Example of a migratory (ID012) individuals BRB kernel area From the left annual growing and winter season

UD50 (black contour) and UD95 (red contour)

34

Table 1 Annual and seasonal UD50 and UD95 areas (ha) for all individuals

ID Annual GS WS

UD50 UD95 UD50 UD95 UD50 UD95

ID004 190 924 93 531 173 941

ID005 230 1364 132 945 72 682

ID006 162 1036 89 736 70 611

ID008 277 1536 156 809 78 738

ID009 137 834 48 295 126 653

ID010 114 682 83 448 96 488

ID012 177 963 123 544 76 545

ID014 160 1018 87 575 89 662

ID015 172 858 128 532 109 679

ID016 156 1047 65 455 92 534

ID017 153 1088 149 1043 69 349

ID019 279 1097 176 911 163 824

ID020 139 1084 67 349 160 794

ID022 159 811 131 638 61 454

ID023 187 1061 147 771 72 705

ID024 146 725 165 705 101 458

ID026 142 605 99 442 125 547

ID027 126 567 75 461 48 277

35 Appendix D

Activity

Fig 1 Mean daily movement during the study period GS 23-April-2012 to 07-Nov-2012 WS 08-Nov-2012 to

22-April-2013 (number indicates month)

Fig 2 Mean daily movement in the centre and south during the GS and WS

36

Appendix E

Habitat Proportions

Fig 1 All individualsrsquo seasonal habitat proportions within the UD95

37 Habitat Selection

Table 1 Simplified ranking matrices comparing proportional habitat use within the second order (UD95Area) with

proportions of total available habitat types Mean value on the matrix was replaced by a sign a triple sign represents

significant deviation from random at P lt05 Highlighted habitat is ranked 1st

North A

gri

cult

ure

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 --- --- - +++ --- --- --- +++ +++ --- 8

Broad Leaf +++ 0 +++ + +++ +++ +++ + +++ +++ +++ 1

Clear Fell +++ --- 0 + +++ - - --- +++ +++ --- 7

Coniferous + - - 0 +++ - - --- +++ +++ - 6

Freshwater --- --- --- --- 0 --- --- --- +++ - --- 10

Grassland

Moors +++ --- + + +++ 0 +++ - +++ +++ + 3

MiresMarshes +++ --- + + +++ --- 0 - +++ +++ --- 5

Mixed +++ - +++ +++ +++ + + 0 +++ +++ + 2

Sparse Veg --- --- --- --- --- --- --- --- 0 --- --- 11

Urban --- --- --- --- + --- --- --- +++ 0 --- 9

Younger +++ --- +++ + +++ - +++ - +++ +++ 0 4

Rank Order and

Significance

Broad Leafgt Mixedgt GrasslandMoorsgt Youngergtgtgt MiresMarshesgt Coniferousgt

Clear Fellgtgtgt Agriculturegtgtgt Urbangt Freshwatergtgtgt Sparse Veg

Central

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 --- --- --- + +++ + --- +++ +++ --- 6

Broad Leaf +++ 0 +++ + +++ +++ + - +++ +++ - 3

Clear Fell +++ --- 0 - +++ +++ + --- +++ +++ --- 5

Coniferous +++ - + 0 +++ +++ + --- +++ +++ - 4

Freshwater - --- --- --- 0 +++ - --- +++ +++ --- 8

Grassland

Moors --- --- --- --- --- 0 --- --- +++ - --- 10

MiresMarshes - - - - + +++ 0 - +++ +++ - 7

Mixed +++ + +++ +++ +++ +++ + 0 +++ +++ + 1

Sparse Veg --- --- --- --- --- --- --- --- 0 - --- 11

Urban --- --- --- --- --- + --- --- + 0 --- 9

Younger +++ + +++ + +++ +++ + - +++ +++ 0 2

Rank Order and

Significance

Mixedgt Youngergt Broad Leafgt Coniferousgt Clear Fellgtgtgt Agriculturegt

MiresMarshesgt Freshwatergtgtgt Urbangt GrasslandMoorsgtgtgt Sparse Veg

38

South

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 + - - + - + +++ +++ +++ - 5

Broad Leaf - 0 - - + - - +++ + +++ - 7

Clear Fell + + 0 - + + + +++ + +++ + 2

Coniferous + + + 0 +++ + + +++ + +++ + 1

Freshwater - - - --- 0 - - + + +++ - 8

Grassland

Moors + + - - + 0 + + +++ + - 4

MiresMarshes - + - - + - 0 +++ + +++ - 6

Mixed --- --- --- --- - - --- 0 + + --- 10

Sparse Veg --- - - - - --- - - 0 + - 9

Urban --- --- --- --- --- - --- - - 0 --- 11

Younger + + - - + + + +++ + +++ 0 3

Rank Order

and

Significance

Coniferousgt Clear Fellgt Youngergt GrasslandMoorsgt Agriculturegt MiresMarshesgt Broad Leafgt

Freshwatergt Sparse Veggt Mixedgt Urban

Table 2 Simplified ranking matrices comparing proportional habitat use within the third order (UD50UD95) with

proportions of total available habitat types Mean value on the matrix was replaced by a sign a triple sign represents

significant deviation from random at P lt05 Highlighted habitat is ranked 1st

North

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 --- --- --- - + --- --- + +++ --- 8

Broad Leaf +++ 0 +++ + + + + + +++ +++ + 1

Clear Fell +++ --- 0 + + + - - + +++ - 5

Coniferous +++ - - 0 + + --- --- +++ +++ - 6

Freshwater + - - - 0 +++ - - +++ +++ - 7

GrasslandMoors - - - - --- 0 - - - + - 10

MiresMarshes +++ - + +++ + + 0 - +++ +++ + 3

Mixed +++ - + +++ + + + 0 +++ +++ + 2

Sparse Veg - --- - --- --- + --- --- 0 +++ --- 9

Urban --- --- --- --- --- - --- --- --- 0 --- 11

Younger +++ - + + + + - - +++ +++ 0 4

Rank Order and

Significance

Broad Leafgt Mixedgt MiresMarshesgt Youngergt Clear Fellgt Coniferousgt Freshwatergt

Agriculturegt Sparse Veggt GrasslandMoorsgt Urban

39

Central

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 --- --- + + - - - + +++ --- 7

Broad Leaf +++ 0 + +++ + + + + + +++ - 2

Clear Fell +++ - 0 +++ + + + + + +++ - 3

Coniferous - --- --- 0 + - - --- +++ + --- 8

Freshwater - - - - 0 --- - - --- - - 11

GrasslandMoors + - - + +++ 0 + - + +++ - 5

MiresMarshes + - - + + - 0 + + +++ - 6

Mixed + - - +++ + + - 0 +++ +++ - 4

Sparse Veg - - - --- +++ - - --- 0 +++ - 9

Urban --- --- --- - + --- --- --- --- 0 --- 10

Younger +++ + + +++ + + + + + +++ 0 1

Rank Order and

Significance

Youngergt Broad Leafgt Clear Fellgt Mixedgt GrasslandMoorsgt MiresMarshesgt

Agriculturegt Coniferousgtgtgt Sparse Veggtgtgt Urbangt Freshwater

South

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 - - - - - + - +++ + --- 8

Broad Leaf + 0 - --- + - + - +++ + - 6

Clear Fell + + 0 - + - + - +++ + - 4

Coniferous + +++ + 0 + + +++ + +++ + + 1

Freshwater + - - - 0 - - + + + - 7

GrasslandMoors + + + - + 0 + + + + - 3

MiresMarshes - - - --- + - 0 - + + - 9

Mixed + + + - - - + 0 + + - 5

Sparse Veg --- --- --- --- - - - - 0 + --- 10

Urban - - - - - - - - - 0 - 11

Younger +++ + + - + + + + +++ + 0 2

Rank Order and

Significance

Coniferousgt Youngergt GrasslandMoorsgt Clear Fellgt Mixedgt Broad Leafgt Freshwatergt

Agriculturegt MiresMarshesgt Sparse Veggt Urban

40

Table 3 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the GS according to Jacobs index

Ran

k North Centre South

50 95 50 95 50 95

+ - + - + - + - + - + -

1 Broad

Leaf Urban Broad Leaf Sparse Veg

Broad

Leaf Urban Mixed Urban Coniferous Urban

Grassland

Moors Urban

2 Mixed Sparse Veg Mixed Freshwater Younger Agriculture Younger Sparse Veg Younger Sparse Veg Clear Fell Mixed

3 Mires

Agriculture Grassland

Urban Clear

Fell Coniferous Broad Leaf

Grassland

Moors

Clear Fell Agriculture Coniferous Sparse Veg

Marshes Moors

4 Younger Grassland

Younger Agriculture

Freshwater Coniferous Freshwater

Broad Leaf Mires

Younger Freshwater

Moors Marshes

5 Clear

Fell Freshwater

Mires Coniferous

Sparse Veg Clear Fell Agriculture

Freshwater Agriculture

Marshes

6 Coniferous Clear Fell

Mires

Marshes

Mires

Grassland

Moors

Mires

Marshes Marshes

7 Mixed Mixed Broad Leaf

8 Grassland

Moors

41

Table 4 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the WS according to Jacobs index

Ran

k North Centre South

50 95 50 95 50 95

+ - + - + - + - + - + -

1 Mires

Marshes

Grassland

Moors Mixed Freshwater Agriculture Urban Mixed Freshwater

Grassland

Moors Urban GrasslandMoors Urban

2 Freshwater Mixed Coniferous Urban Mires

Marshes Coniferous Sparse Veg Agriculture

Sparse

Veg Coniferous Freshwater

3 Urban Coniferous Younger Grassland

Moors Freshwater Younger Urban Freshwater

Broad

Leaf Agriculture Mixed

4 Younger Agriculture Sparse Veg Broad

Leaf

Broad

Leaf

Grassland

Moors Mixed Broad Leaf

5 Clear Fell Agriculture Coniferous Agriculture Mires

Marshes Clear Fell

6 Sparse

Veg

Mires

Marshes Mixed

Mires

Marshes

Clear

Fell

Mires

Marshes

7 Broad

Leaf Clear Fell Younger Clear Fell Younger Sparse Veg

8 Clear Fell Younger

9 Sparse

Veg

10 Grassland

Moors

42

Table 5 Second order (UD95Area) individual selectionavoidance for the GS and WS according to the Jacobs index

ID GS WS

Select Avoid Select Avoid

ID004 Younger Sparsely Vegetated MiresMarshes Sparsely Vegetated

ID005 MiresMarshes Sparsely Vegetated Coniferous GrasslandMoors

ID006 Coniferous Sparsely Vegetated Mixed Freshwater

ID008 Mixed Sparsely Vegetated Mixed Freshwater

ID009 Mixed Sparsely Vegetated Mixed GrasslandMoors

ID010 MiresMarshes Freshwater GrasslandMoors Freshwater

ID012 Broad Leaf Sparsely Vegetated Coniferous Urban

ID014 Clear Fell Sparsely Vegetated GrasslandMoors Sparsely Vegetated

ID015 GrasslandMoors Urban GrasslandMoors Freshwater

ID016 GrasslandMoors Freshwater GrasslandMoors Freshwater

ID017 GrasslandMoors Mixed Sparsely Vegetated Mixed

ID019 Mixed Sparsely Vegetated Mixed Urban

ID020 Broad Leaf Sparsely Vegetated Coniferous GrasslandMoors

ID022 MiresMarshes Freshwater MiresMarshes Freshwater

ID023 MiresMarshes GrasslandMoors Mixed Freshwater

ID024 Broadleaf Urban Broad Leaf Urban

ID026 GrasslandMoors Freshwater GrasslandMoors Freshwater

ID027 GrasslandMoors Urban Sparsely Vegetated Freshwater

43 Table 6 Third order (UD50UD95) individual selectionavoidance for the GS and WS according to the Jacobs index

ID GS WS

Select Avoid Select Avoid

ID004 Broad Leaf Mixed GrasslandMoors Freshwater

ID005 Broad Leaf Freshwater Agriculture Freshwater

ID006 Clear Fell Freshwater Agriculture MiresMarshes

ID008 MiresMarshes Freshwater Agriculture Urban

ID009 Freshwater Agriculture Agriculture Freshwater

ID010 Mixed Urban Sparsely Vegetated Urban

ID012 Coniferous GrasslandMoors Freshwater Urban

ID014 Urban Agriculture Freshwater Urban

ID015 Mixed Forest Urban Clear Fell Urban

ID016 Freshwater Urban GrasslandMoors Mixed

ID017 Coniferous Mixed Coniferous Broad Leaf

ID019 Broad Leaf GrasslandMoors Urban GrasslandMoors

ID020 Freshwater Urban Freshwater Agriculture

ID022 MiresMarshes Urban Broad Leaf GrasslandMoors

ID023 Freshwater Mixed Agriculture Freshwater

ID024 Mixed Freshwater Mixed Freshwater

ID026 Mixed MiresMarshes Sparsely Vegetated GrasslandMoors

ID027 Freshwater MiresMarshes GrasslandMoors Broad Leaf

44

Fig 2 North third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)

45

Fig 3 Centre third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)

46

Fig 4 South third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)

47

Fig 5 North second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)

48

Fig 6 Centre second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)

49

Fig 7 South second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)

50

Appendix F

Background

Fig 1 Daily mean snow depth and duration during the study period (Andrew Allen)

Female Moose Reproduction

Moose are seasonal polyoestral mammals (Monfort et al 1993) coming into oestrus during late September

early October (Garel et al 2009) The Swedish moose cow population reaches puberty between the ages 25

and 35 (Sand and Cederlund 1993) during which the reproductive period begins with the onset of ovulation

The age an individual reaches puberty is dependent on their body condition they have to reach a weight

threshold to reach puberty and become reproductive (Sand 1996) If she is over the weight threshold she will

go into oestrus in the autumn If she does not reach the weight threshold then she will go into oestrus the

following autumn if successful she will give birth to individual or twin calves in late May to early June

(Ericsson et al 2001) and therefore reach sexual maturity (Malmsten et al 2014b) Fecundity is related to

both the condition and the age of the cow Cows go through senescence at 12 years of age (Ericsson et al

2001) Providing calves with the required level of nutrition demands high energy and protein resources from

the mother during senescence this becomes harder to achieve leading to decreased levels of parental care

and higher levels of calf mortality

Page 19: Habitat-performance relationships on an island: fitness ...navinderjsingh.weebly.com/uploads/1/1/2/2/11224342/... · Conditions on Öland are milder than those found in other areas

19 Discussion

The results of this study emphasised how strikingly different the habitat composition is along the latitudinal

gradient of Oumlland The three areas show contrasting proportions of the key habitat types The starkest

difference is the high proportion of coniferous forests and lack of agriculture in the north compared to the

centre and south The proportion of coniferous forest in the north is almost 5 times greater than in the centre

and south whereas the proportion of agriculture in the centre and south is more than double that in the north

The north is perceived to be composed of the most suitable habitat for moose (Dussault et al 2006) It has the

largest proportions of each forest type and a low proportion of agricultural land This provides suitable forage

and shelter throughout the year The south has a contrasting habitat composition to the north The proportions

of agricultural and sparsely vegetated areas are the highest between the three areas and the proportions of forest

habitats are the lowest The large proportion of sparsely vegetated areas and low proportions of forest habitat

corresponds to the large area of Stora Alvaret This is perceived to be the least suitable area due to a lack of

shelter (coniferous forest) and suitable forage The strong preference for coniferous and younger forest habitats

in the south would suggest that moose exhibit a functional response in habitat selection (Godvik et al 2009)

ie as the proportion of a particular habitat decreases the selection for that habitat increases in this case

coniferous forests which provide shelter and younger forest which provide good forage Similarly in the centre

moose show strong preference for mixed forests a habitat that is of low proportion

In view of the large variation in habitat proportions between the areas it is surprising that there is not a large

variation in the home range sizes or the activity levels annually or seasonally Home ranges are ultimately

chosen to maximise fitness and meet energy requirements by utilizing the available forage Seasonal conditions

change the availability and necessity of resources (food quality shelter) Unlike the GS during the WS

deciduous trees and shrubs are leafless and low-lying shrubs are under snow cover (Dussault et al 2005)

These changes are well known to cause populations to alter their activity and home ranges to meet energy

requirements (Mysterud et al 2001) Populations have been shown to increase or decrease their home ranges

during the two seasons The GS home ranges are often larger than the WS home ranges (Philips et al 1973

Mysterud et al 2001) In some cases they can be found to be almost double the size of the WS home ranges

(Cederlund and Okarma 1988) In other populations the WS home ranges are double the size of the GS home

ranges (Lynch and Morgantini 1984) or sizes do not significantly differ (Cederlund and Sand 1994)

Previous studies on moose find females generally show increased activity from the start on the GS due to

various factors eg reduced ruminating times increased metabolic needs and increased foraging bursts

(Wattles and DeStefano 2013) Increased metabolic needs during this time are a results of pregnancy and

lactation (Georgii 1980) During the height of the GS they usually show reduced activity levels through times

of increased thermal stress (Renecker and Hudson 1989 van Beest et al 2012) During the WS the depth and

the duration of snow cover are well known to affect the activity level (Telfer 1970 Mysterud and Oslashstbye 1999

Bjoslashrneraas et al 2011) During the WS generally home ranges are smaller and activity less due to lower

metabolic needs Moose activity is constrained by rumination during the WS this period is known to be longer

due to the change in diet (Cederlund 1989 Renecker Hudson 1989) This was not the case on Ӧland activity

20

was lowest in February which is a similar result to Cederlundrsquos (1989) paper However Ӧland moose did not

significantly alter their seasonal activity levels The fact that the annual and seasonal activity levels and home

ranges were similar could be a result of the mild winters on Oumlland during the study period (Smhise 2014)

During the study period the average number of snow days was 80 and the mean snow depth was 10cm

(appendix F) (Swedish Meterological and Hydrological Institute- SMHI) These mild conditions do not restrict

the movement of moose or obscure forage Moose are well adapted for movement in deep snow depths of 60-

86cm (Prescott 1968) are needed to truly restrict movement This finding was similar to the Sweanor and

Sandegren (1989) and Cederlund and Sand (1994) where the snow depth at their sites did not reach movement

restricting depths

The survival curve illustrates just how bad the calf survival is on Ӧland Survival falls from 85 at the start to

20 Out of 20 calves only four were alive at the end of the study The sharpest fall in survival was the period

between end of summer and before the hunt so the deaths were not due to hunting Previous calf autopsies

(Malmsten 2014a) have shown that cause of death was starvation mothers possibly either did not have milk

the calf was unable to feed or the mother abandoned the calf Closer field based observations are needed to

attain this knowledge Moose are seasonal polyoestral mammals (Monfort et al 1993) coming into oestrus

during late September early October (Garel et al 2009) (appendix F) The diet of the mother influences the

health of the calf and this period is when sodium is hard to find sodium is a key mineral in moose diets for

features such as reproduction (Belovsky and Jordan 1981) Moose gain sodium mainly through aquatic plants

(MacCracken et al 1993) However the compositional analysis shows that freshwater areas are often ranked

as one of the lowest used habitats and coastal areas were removed as the proportion found in the home ranges

was extremely low The Jacobs Index shows that the moose only prefer freshwater areas in the north UD50

during the WS The north individuals again are those that are showing typical moose habitat selection

It is known that habitat selection is hierarchical with habitats that increase fitness selected for and the effects

of limiting factors are reduced (Rettie and Messier 2000) At the UD95 during the GS moose preferred areas

of good forage (forests) and avoided areas of low forage (freshwater and sparsely vegetated areas) and areas

close to humans (urban) This is consistent with other reports (Laurian et al 2008 Torres et al 2011) Within

the UD50 there is a shift in preferences The good forage areas are again preferred during the GS however

during WS the only preferred habitat is often agricultural land During the WS there could be a steady supply

of supplementary feed available hence the high levels of agricultural produce found in the rumen content

samples and the high preference of agricultural areas This diet is unusual for moose previous studies of

Swedish moose diet have found the GS diet was dominated by birch willow and herbaceous plants and the

WS diet dominated by pine and birch (Cederlund and Nystrom 1981) The diet analysis was conducted during

the WS instead of being dominant pine composed just 2 Birch did not appear however unidentified wood

composed only 9 whereas agricultural produce accounted for 69 Supplementary feed may be perceived

by the moose in the centre and south as a vital forage source during the WS In fact in the centre the

agricultural land is the only preferred habitat at the UD50 It is unknown whether there are salt licks provided

in these areas Selection for a critical habitat is often thought to be a fixed factor The Oumlland population from

21 the three areas are close in proximity however they displayed contrasting preferences This is supported by the

Osko et al (2004) report that found two neighbouring moose populations that had access to the same habitats

displayed contrasting preferences Habitat preferences for populations of the same species are not necessarily

fixed They alter with varying levels of habitat abundance and limiting factors skewing what is preserved to

be critical

The main limitation encountered in this study was with the limited sample There was only data on two

individuals from the north of the island which led it being removed from many of the analysis Similarly due

to a lack of relocations from the collars being turned off at points throughout the year two further individuals

had to be removed from a majority of the analysis This reduced the sample size to 17 or 18 individuals

Similarly only 13 of the individuals from the study produced calves This unfortunately prevented including

survival into models Although the sample size was small it was accurate it was of high resolution over

300000 GPS points In future it would be beneficial to have a more standardised data set An equal sample of

individuals from the three areas would be advised along with ensuring the GPS collars are kept turned on for

the entirety of the growing and winter season to allow comparisons between years It would also be

advantageous to collect coordinates of the feeding sites along with the composition This could then be

compared with high use UD coordinates to look if moose are truly spending a majority of their foraging time

at feeding stations A study on the population densities of moose and the increasing population of roe deer

(Capreolus capreolus) would add the factor of competition into the model

The low calf survival on Ӧland is most likely the result of a combination of factors The lack of suitable habitat

reported in this study in conjunction with Malmstenrsquos (2014a) report on the threat of disease (Anaplasma

phagocytophilum) are probable influences on the calf survival on Ӧland On Ӧland there is an increasing

population of roe deer and large numbers of migratory birds both carriers of ticks and diseases The mild

conditions on Ӧland are advantageous for ticks the carriers of A phagocytophilum Fewer snow days and

shorter periods of snow cover along with dry conditions are favourable for ticks This could probably be one

of the reasons for females to be of lower quality and therefore not being able to ensure calf survival Moose

have to utilise areas where in other populations individuals tend to avoid Finally similar to many studies I

advocate further research using a stronger dataset and longer term monitoring

22

Acknowledgements

I am indebted to NJ Singh and A Allen for all their help and guidance through the whole of this study I

thank SLU for the support provided during this study in terms of data finances and facilities Thank you to

everyone at the Department of Wildlife Fish and Environmental Studies for being so friendly and

supportive I would like to thank L Edenius for driving me around the study area and S Michon and H

Khalil for keeping me sane with fika and training

23 References

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success in muskoxen Journal of Zoology 24313-20

30

Appendix A

Introduction

Fig 1 Summary chart of factors affecting the life history and therefore the long term fitness of a population

Fig 2 Summary chart 2

Movement

Habitat

Climate

Topography

Competition

FoodWater

Disease

Die

Survive

Reproduce

Population long term fitness

31 Appendix B

Method and Materials

Fig 1 Summary of processes

32

Fig 2 Examples of classical kernel home range output and Brownian bridge kernel home range (Calenge 2011) The

right image includes the area between relocations ie the movement path in contrast to the classic kernel home range

in the left image

33 Appendix C

Home ranges

Fig 1 Example of a non-migratory (ID006) individuals BRB kernel area From top left annual growing and winter

season UD50 (black contour) and UD95 (red contour)

Fig 2 Example of a migratory (ID012) individuals BRB kernel area From the left annual growing and winter season

UD50 (black contour) and UD95 (red contour)

34

Table 1 Annual and seasonal UD50 and UD95 areas (ha) for all individuals

ID Annual GS WS

UD50 UD95 UD50 UD95 UD50 UD95

ID004 190 924 93 531 173 941

ID005 230 1364 132 945 72 682

ID006 162 1036 89 736 70 611

ID008 277 1536 156 809 78 738

ID009 137 834 48 295 126 653

ID010 114 682 83 448 96 488

ID012 177 963 123 544 76 545

ID014 160 1018 87 575 89 662

ID015 172 858 128 532 109 679

ID016 156 1047 65 455 92 534

ID017 153 1088 149 1043 69 349

ID019 279 1097 176 911 163 824

ID020 139 1084 67 349 160 794

ID022 159 811 131 638 61 454

ID023 187 1061 147 771 72 705

ID024 146 725 165 705 101 458

ID026 142 605 99 442 125 547

ID027 126 567 75 461 48 277

35 Appendix D

Activity

Fig 1 Mean daily movement during the study period GS 23-April-2012 to 07-Nov-2012 WS 08-Nov-2012 to

22-April-2013 (number indicates month)

Fig 2 Mean daily movement in the centre and south during the GS and WS

36

Appendix E

Habitat Proportions

Fig 1 All individualsrsquo seasonal habitat proportions within the UD95

37 Habitat Selection

Table 1 Simplified ranking matrices comparing proportional habitat use within the second order (UD95Area) with

proportions of total available habitat types Mean value on the matrix was replaced by a sign a triple sign represents

significant deviation from random at P lt05 Highlighted habitat is ranked 1st

North A

gri

cult

ure

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 --- --- - +++ --- --- --- +++ +++ --- 8

Broad Leaf +++ 0 +++ + +++ +++ +++ + +++ +++ +++ 1

Clear Fell +++ --- 0 + +++ - - --- +++ +++ --- 7

Coniferous + - - 0 +++ - - --- +++ +++ - 6

Freshwater --- --- --- --- 0 --- --- --- +++ - --- 10

Grassland

Moors +++ --- + + +++ 0 +++ - +++ +++ + 3

MiresMarshes +++ --- + + +++ --- 0 - +++ +++ --- 5

Mixed +++ - +++ +++ +++ + + 0 +++ +++ + 2

Sparse Veg --- --- --- --- --- --- --- --- 0 --- --- 11

Urban --- --- --- --- + --- --- --- +++ 0 --- 9

Younger +++ --- +++ + +++ - +++ - +++ +++ 0 4

Rank Order and

Significance

Broad Leafgt Mixedgt GrasslandMoorsgt Youngergtgtgt MiresMarshesgt Coniferousgt

Clear Fellgtgtgt Agriculturegtgtgt Urbangt Freshwatergtgtgt Sparse Veg

Central

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 --- --- --- + +++ + --- +++ +++ --- 6

Broad Leaf +++ 0 +++ + +++ +++ + - +++ +++ - 3

Clear Fell +++ --- 0 - +++ +++ + --- +++ +++ --- 5

Coniferous +++ - + 0 +++ +++ + --- +++ +++ - 4

Freshwater - --- --- --- 0 +++ - --- +++ +++ --- 8

Grassland

Moors --- --- --- --- --- 0 --- --- +++ - --- 10

MiresMarshes - - - - + +++ 0 - +++ +++ - 7

Mixed +++ + +++ +++ +++ +++ + 0 +++ +++ + 1

Sparse Veg --- --- --- --- --- --- --- --- 0 - --- 11

Urban --- --- --- --- --- + --- --- + 0 --- 9

Younger +++ + +++ + +++ +++ + - +++ +++ 0 2

Rank Order and

Significance

Mixedgt Youngergt Broad Leafgt Coniferousgt Clear Fellgtgtgt Agriculturegt

MiresMarshesgt Freshwatergtgtgt Urbangt GrasslandMoorsgtgtgt Sparse Veg

38

South

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 + - - + - + +++ +++ +++ - 5

Broad Leaf - 0 - - + - - +++ + +++ - 7

Clear Fell + + 0 - + + + +++ + +++ + 2

Coniferous + + + 0 +++ + + +++ + +++ + 1

Freshwater - - - --- 0 - - + + +++ - 8

Grassland

Moors + + - - + 0 + + +++ + - 4

MiresMarshes - + - - + - 0 +++ + +++ - 6

Mixed --- --- --- --- - - --- 0 + + --- 10

Sparse Veg --- - - - - --- - - 0 + - 9

Urban --- --- --- --- --- - --- - - 0 --- 11

Younger + + - - + + + +++ + +++ 0 3

Rank Order

and

Significance

Coniferousgt Clear Fellgt Youngergt GrasslandMoorsgt Agriculturegt MiresMarshesgt Broad Leafgt

Freshwatergt Sparse Veggt Mixedgt Urban

Table 2 Simplified ranking matrices comparing proportional habitat use within the third order (UD50UD95) with

proportions of total available habitat types Mean value on the matrix was replaced by a sign a triple sign represents

significant deviation from random at P lt05 Highlighted habitat is ranked 1st

North

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 --- --- --- - + --- --- + +++ --- 8

Broad Leaf +++ 0 +++ + + + + + +++ +++ + 1

Clear Fell +++ --- 0 + + + - - + +++ - 5

Coniferous +++ - - 0 + + --- --- +++ +++ - 6

Freshwater + - - - 0 +++ - - +++ +++ - 7

GrasslandMoors - - - - --- 0 - - - + - 10

MiresMarshes +++ - + +++ + + 0 - +++ +++ + 3

Mixed +++ - + +++ + + + 0 +++ +++ + 2

Sparse Veg - --- - --- --- + --- --- 0 +++ --- 9

Urban --- --- --- --- --- - --- --- --- 0 --- 11

Younger +++ - + + + + - - +++ +++ 0 4

Rank Order and

Significance

Broad Leafgt Mixedgt MiresMarshesgt Youngergt Clear Fellgt Coniferousgt Freshwatergt

Agriculturegt Sparse Veggt GrasslandMoorsgt Urban

39

Central

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 --- --- + + - - - + +++ --- 7

Broad Leaf +++ 0 + +++ + + + + + +++ - 2

Clear Fell +++ - 0 +++ + + + + + +++ - 3

Coniferous - --- --- 0 + - - --- +++ + --- 8

Freshwater - - - - 0 --- - - --- - - 11

GrasslandMoors + - - + +++ 0 + - + +++ - 5

MiresMarshes + - - + + - 0 + + +++ - 6

Mixed + - - +++ + + - 0 +++ +++ - 4

Sparse Veg - - - --- +++ - - --- 0 +++ - 9

Urban --- --- --- - + --- --- --- --- 0 --- 10

Younger +++ + + +++ + + + + + +++ 0 1

Rank Order and

Significance

Youngergt Broad Leafgt Clear Fellgt Mixedgt GrasslandMoorsgt MiresMarshesgt

Agriculturegt Coniferousgtgtgt Sparse Veggtgtgt Urbangt Freshwater

South

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 - - - - - + - +++ + --- 8

Broad Leaf + 0 - --- + - + - +++ + - 6

Clear Fell + + 0 - + - + - +++ + - 4

Coniferous + +++ + 0 + + +++ + +++ + + 1

Freshwater + - - - 0 - - + + + - 7

GrasslandMoors + + + - + 0 + + + + - 3

MiresMarshes - - - --- + - 0 - + + - 9

Mixed + + + - - - + 0 + + - 5

Sparse Veg --- --- --- --- - - - - 0 + --- 10

Urban - - - - - - - - - 0 - 11

Younger +++ + + - + + + + +++ + 0 2

Rank Order and

Significance

Coniferousgt Youngergt GrasslandMoorsgt Clear Fellgt Mixedgt Broad Leafgt Freshwatergt

Agriculturegt MiresMarshesgt Sparse Veggt Urban

40

Table 3 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the GS according to Jacobs index

Ran

k North Centre South

50 95 50 95 50 95

+ - + - + - + - + - + -

1 Broad

Leaf Urban Broad Leaf Sparse Veg

Broad

Leaf Urban Mixed Urban Coniferous Urban

Grassland

Moors Urban

2 Mixed Sparse Veg Mixed Freshwater Younger Agriculture Younger Sparse Veg Younger Sparse Veg Clear Fell Mixed

3 Mires

Agriculture Grassland

Urban Clear

Fell Coniferous Broad Leaf

Grassland

Moors

Clear Fell Agriculture Coniferous Sparse Veg

Marshes Moors

4 Younger Grassland

Younger Agriculture

Freshwater Coniferous Freshwater

Broad Leaf Mires

Younger Freshwater

Moors Marshes

5 Clear

Fell Freshwater

Mires Coniferous

Sparse Veg Clear Fell Agriculture

Freshwater Agriculture

Marshes

6 Coniferous Clear Fell

Mires

Marshes

Mires

Grassland

Moors

Mires

Marshes Marshes

7 Mixed Mixed Broad Leaf

8 Grassland

Moors

41

Table 4 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the WS according to Jacobs index

Ran

k North Centre South

50 95 50 95 50 95

+ - + - + - + - + - + -

1 Mires

Marshes

Grassland

Moors Mixed Freshwater Agriculture Urban Mixed Freshwater

Grassland

Moors Urban GrasslandMoors Urban

2 Freshwater Mixed Coniferous Urban Mires

Marshes Coniferous Sparse Veg Agriculture

Sparse

Veg Coniferous Freshwater

3 Urban Coniferous Younger Grassland

Moors Freshwater Younger Urban Freshwater

Broad

Leaf Agriculture Mixed

4 Younger Agriculture Sparse Veg Broad

Leaf

Broad

Leaf

Grassland

Moors Mixed Broad Leaf

5 Clear Fell Agriculture Coniferous Agriculture Mires

Marshes Clear Fell

6 Sparse

Veg

Mires

Marshes Mixed

Mires

Marshes

Clear

Fell

Mires

Marshes

7 Broad

Leaf Clear Fell Younger Clear Fell Younger Sparse Veg

8 Clear Fell Younger

9 Sparse

Veg

10 Grassland

Moors

42

Table 5 Second order (UD95Area) individual selectionavoidance for the GS and WS according to the Jacobs index

ID GS WS

Select Avoid Select Avoid

ID004 Younger Sparsely Vegetated MiresMarshes Sparsely Vegetated

ID005 MiresMarshes Sparsely Vegetated Coniferous GrasslandMoors

ID006 Coniferous Sparsely Vegetated Mixed Freshwater

ID008 Mixed Sparsely Vegetated Mixed Freshwater

ID009 Mixed Sparsely Vegetated Mixed GrasslandMoors

ID010 MiresMarshes Freshwater GrasslandMoors Freshwater

ID012 Broad Leaf Sparsely Vegetated Coniferous Urban

ID014 Clear Fell Sparsely Vegetated GrasslandMoors Sparsely Vegetated

ID015 GrasslandMoors Urban GrasslandMoors Freshwater

ID016 GrasslandMoors Freshwater GrasslandMoors Freshwater

ID017 GrasslandMoors Mixed Sparsely Vegetated Mixed

ID019 Mixed Sparsely Vegetated Mixed Urban

ID020 Broad Leaf Sparsely Vegetated Coniferous GrasslandMoors

ID022 MiresMarshes Freshwater MiresMarshes Freshwater

ID023 MiresMarshes GrasslandMoors Mixed Freshwater

ID024 Broadleaf Urban Broad Leaf Urban

ID026 GrasslandMoors Freshwater GrasslandMoors Freshwater

ID027 GrasslandMoors Urban Sparsely Vegetated Freshwater

43 Table 6 Third order (UD50UD95) individual selectionavoidance for the GS and WS according to the Jacobs index

ID GS WS

Select Avoid Select Avoid

ID004 Broad Leaf Mixed GrasslandMoors Freshwater

ID005 Broad Leaf Freshwater Agriculture Freshwater

ID006 Clear Fell Freshwater Agriculture MiresMarshes

ID008 MiresMarshes Freshwater Agriculture Urban

ID009 Freshwater Agriculture Agriculture Freshwater

ID010 Mixed Urban Sparsely Vegetated Urban

ID012 Coniferous GrasslandMoors Freshwater Urban

ID014 Urban Agriculture Freshwater Urban

ID015 Mixed Forest Urban Clear Fell Urban

ID016 Freshwater Urban GrasslandMoors Mixed

ID017 Coniferous Mixed Coniferous Broad Leaf

ID019 Broad Leaf GrasslandMoors Urban GrasslandMoors

ID020 Freshwater Urban Freshwater Agriculture

ID022 MiresMarshes Urban Broad Leaf GrasslandMoors

ID023 Freshwater Mixed Agriculture Freshwater

ID024 Mixed Freshwater Mixed Freshwater

ID026 Mixed MiresMarshes Sparsely Vegetated GrasslandMoors

ID027 Freshwater MiresMarshes GrasslandMoors Broad Leaf

44

Fig 2 North third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)

45

Fig 3 Centre third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)

46

Fig 4 South third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)

47

Fig 5 North second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)

48

Fig 6 Centre second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)

49

Fig 7 South second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)

50

Appendix F

Background

Fig 1 Daily mean snow depth and duration during the study period (Andrew Allen)

Female Moose Reproduction

Moose are seasonal polyoestral mammals (Monfort et al 1993) coming into oestrus during late September

early October (Garel et al 2009) The Swedish moose cow population reaches puberty between the ages 25

and 35 (Sand and Cederlund 1993) during which the reproductive period begins with the onset of ovulation

The age an individual reaches puberty is dependent on their body condition they have to reach a weight

threshold to reach puberty and become reproductive (Sand 1996) If she is over the weight threshold she will

go into oestrus in the autumn If she does not reach the weight threshold then she will go into oestrus the

following autumn if successful she will give birth to individual or twin calves in late May to early June

(Ericsson et al 2001) and therefore reach sexual maturity (Malmsten et al 2014b) Fecundity is related to

both the condition and the age of the cow Cows go through senescence at 12 years of age (Ericsson et al

2001) Providing calves with the required level of nutrition demands high energy and protein resources from

the mother during senescence this becomes harder to achieve leading to decreased levels of parental care

and higher levels of calf mortality

Page 20: Habitat-performance relationships on an island: fitness ...navinderjsingh.weebly.com/uploads/1/1/2/2/11224342/... · Conditions on Öland are milder than those found in other areas

20

was lowest in February which is a similar result to Cederlundrsquos (1989) paper However Ӧland moose did not

significantly alter their seasonal activity levels The fact that the annual and seasonal activity levels and home

ranges were similar could be a result of the mild winters on Oumlland during the study period (Smhise 2014)

During the study period the average number of snow days was 80 and the mean snow depth was 10cm

(appendix F) (Swedish Meterological and Hydrological Institute- SMHI) These mild conditions do not restrict

the movement of moose or obscure forage Moose are well adapted for movement in deep snow depths of 60-

86cm (Prescott 1968) are needed to truly restrict movement This finding was similar to the Sweanor and

Sandegren (1989) and Cederlund and Sand (1994) where the snow depth at their sites did not reach movement

restricting depths

The survival curve illustrates just how bad the calf survival is on Ӧland Survival falls from 85 at the start to

20 Out of 20 calves only four were alive at the end of the study The sharpest fall in survival was the period

between end of summer and before the hunt so the deaths were not due to hunting Previous calf autopsies

(Malmsten 2014a) have shown that cause of death was starvation mothers possibly either did not have milk

the calf was unable to feed or the mother abandoned the calf Closer field based observations are needed to

attain this knowledge Moose are seasonal polyoestral mammals (Monfort et al 1993) coming into oestrus

during late September early October (Garel et al 2009) (appendix F) The diet of the mother influences the

health of the calf and this period is when sodium is hard to find sodium is a key mineral in moose diets for

features such as reproduction (Belovsky and Jordan 1981) Moose gain sodium mainly through aquatic plants

(MacCracken et al 1993) However the compositional analysis shows that freshwater areas are often ranked

as one of the lowest used habitats and coastal areas were removed as the proportion found in the home ranges

was extremely low The Jacobs Index shows that the moose only prefer freshwater areas in the north UD50

during the WS The north individuals again are those that are showing typical moose habitat selection

It is known that habitat selection is hierarchical with habitats that increase fitness selected for and the effects

of limiting factors are reduced (Rettie and Messier 2000) At the UD95 during the GS moose preferred areas

of good forage (forests) and avoided areas of low forage (freshwater and sparsely vegetated areas) and areas

close to humans (urban) This is consistent with other reports (Laurian et al 2008 Torres et al 2011) Within

the UD50 there is a shift in preferences The good forage areas are again preferred during the GS however

during WS the only preferred habitat is often agricultural land During the WS there could be a steady supply

of supplementary feed available hence the high levels of agricultural produce found in the rumen content

samples and the high preference of agricultural areas This diet is unusual for moose previous studies of

Swedish moose diet have found the GS diet was dominated by birch willow and herbaceous plants and the

WS diet dominated by pine and birch (Cederlund and Nystrom 1981) The diet analysis was conducted during

the WS instead of being dominant pine composed just 2 Birch did not appear however unidentified wood

composed only 9 whereas agricultural produce accounted for 69 Supplementary feed may be perceived

by the moose in the centre and south as a vital forage source during the WS In fact in the centre the

agricultural land is the only preferred habitat at the UD50 It is unknown whether there are salt licks provided

in these areas Selection for a critical habitat is often thought to be a fixed factor The Oumlland population from

21 the three areas are close in proximity however they displayed contrasting preferences This is supported by the

Osko et al (2004) report that found two neighbouring moose populations that had access to the same habitats

displayed contrasting preferences Habitat preferences for populations of the same species are not necessarily

fixed They alter with varying levels of habitat abundance and limiting factors skewing what is preserved to

be critical

The main limitation encountered in this study was with the limited sample There was only data on two

individuals from the north of the island which led it being removed from many of the analysis Similarly due

to a lack of relocations from the collars being turned off at points throughout the year two further individuals

had to be removed from a majority of the analysis This reduced the sample size to 17 or 18 individuals

Similarly only 13 of the individuals from the study produced calves This unfortunately prevented including

survival into models Although the sample size was small it was accurate it was of high resolution over

300000 GPS points In future it would be beneficial to have a more standardised data set An equal sample of

individuals from the three areas would be advised along with ensuring the GPS collars are kept turned on for

the entirety of the growing and winter season to allow comparisons between years It would also be

advantageous to collect coordinates of the feeding sites along with the composition This could then be

compared with high use UD coordinates to look if moose are truly spending a majority of their foraging time

at feeding stations A study on the population densities of moose and the increasing population of roe deer

(Capreolus capreolus) would add the factor of competition into the model

The low calf survival on Ӧland is most likely the result of a combination of factors The lack of suitable habitat

reported in this study in conjunction with Malmstenrsquos (2014a) report on the threat of disease (Anaplasma

phagocytophilum) are probable influences on the calf survival on Ӧland On Ӧland there is an increasing

population of roe deer and large numbers of migratory birds both carriers of ticks and diseases The mild

conditions on Ӧland are advantageous for ticks the carriers of A phagocytophilum Fewer snow days and

shorter periods of snow cover along with dry conditions are favourable for ticks This could probably be one

of the reasons for females to be of lower quality and therefore not being able to ensure calf survival Moose

have to utilise areas where in other populations individuals tend to avoid Finally similar to many studies I

advocate further research using a stronger dataset and longer term monitoring

22

Acknowledgements

I am indebted to NJ Singh and A Allen for all their help and guidance through the whole of this study I

thank SLU for the support provided during this study in terms of data finances and facilities Thank you to

everyone at the Department of Wildlife Fish and Environmental Studies for being so friendly and

supportive I would like to thank L Edenius for driving me around the study area and S Michon and H

Khalil for keeping me sane with fika and training

23 References

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30

Appendix A

Introduction

Fig 1 Summary chart of factors affecting the life history and therefore the long term fitness of a population

Fig 2 Summary chart 2

Movement

Habitat

Climate

Topography

Competition

FoodWater

Disease

Die

Survive

Reproduce

Population long term fitness

31 Appendix B

Method and Materials

Fig 1 Summary of processes

32

Fig 2 Examples of classical kernel home range output and Brownian bridge kernel home range (Calenge 2011) The

right image includes the area between relocations ie the movement path in contrast to the classic kernel home range

in the left image

33 Appendix C

Home ranges

Fig 1 Example of a non-migratory (ID006) individuals BRB kernel area From top left annual growing and winter

season UD50 (black contour) and UD95 (red contour)

Fig 2 Example of a migratory (ID012) individuals BRB kernel area From the left annual growing and winter season

UD50 (black contour) and UD95 (red contour)

34

Table 1 Annual and seasonal UD50 and UD95 areas (ha) for all individuals

ID Annual GS WS

UD50 UD95 UD50 UD95 UD50 UD95

ID004 190 924 93 531 173 941

ID005 230 1364 132 945 72 682

ID006 162 1036 89 736 70 611

ID008 277 1536 156 809 78 738

ID009 137 834 48 295 126 653

ID010 114 682 83 448 96 488

ID012 177 963 123 544 76 545

ID014 160 1018 87 575 89 662

ID015 172 858 128 532 109 679

ID016 156 1047 65 455 92 534

ID017 153 1088 149 1043 69 349

ID019 279 1097 176 911 163 824

ID020 139 1084 67 349 160 794

ID022 159 811 131 638 61 454

ID023 187 1061 147 771 72 705

ID024 146 725 165 705 101 458

ID026 142 605 99 442 125 547

ID027 126 567 75 461 48 277

35 Appendix D

Activity

Fig 1 Mean daily movement during the study period GS 23-April-2012 to 07-Nov-2012 WS 08-Nov-2012 to

22-April-2013 (number indicates month)

Fig 2 Mean daily movement in the centre and south during the GS and WS

36

Appendix E

Habitat Proportions

Fig 1 All individualsrsquo seasonal habitat proportions within the UD95

37 Habitat Selection

Table 1 Simplified ranking matrices comparing proportional habitat use within the second order (UD95Area) with

proportions of total available habitat types Mean value on the matrix was replaced by a sign a triple sign represents

significant deviation from random at P lt05 Highlighted habitat is ranked 1st

North A

gri

cult

ure

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 --- --- - +++ --- --- --- +++ +++ --- 8

Broad Leaf +++ 0 +++ + +++ +++ +++ + +++ +++ +++ 1

Clear Fell +++ --- 0 + +++ - - --- +++ +++ --- 7

Coniferous + - - 0 +++ - - --- +++ +++ - 6

Freshwater --- --- --- --- 0 --- --- --- +++ - --- 10

Grassland

Moors +++ --- + + +++ 0 +++ - +++ +++ + 3

MiresMarshes +++ --- + + +++ --- 0 - +++ +++ --- 5

Mixed +++ - +++ +++ +++ + + 0 +++ +++ + 2

Sparse Veg --- --- --- --- --- --- --- --- 0 --- --- 11

Urban --- --- --- --- + --- --- --- +++ 0 --- 9

Younger +++ --- +++ + +++ - +++ - +++ +++ 0 4

Rank Order and

Significance

Broad Leafgt Mixedgt GrasslandMoorsgt Youngergtgtgt MiresMarshesgt Coniferousgt

Clear Fellgtgtgt Agriculturegtgtgt Urbangt Freshwatergtgtgt Sparse Veg

Central

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 --- --- --- + +++ + --- +++ +++ --- 6

Broad Leaf +++ 0 +++ + +++ +++ + - +++ +++ - 3

Clear Fell +++ --- 0 - +++ +++ + --- +++ +++ --- 5

Coniferous +++ - + 0 +++ +++ + --- +++ +++ - 4

Freshwater - --- --- --- 0 +++ - --- +++ +++ --- 8

Grassland

Moors --- --- --- --- --- 0 --- --- +++ - --- 10

MiresMarshes - - - - + +++ 0 - +++ +++ - 7

Mixed +++ + +++ +++ +++ +++ + 0 +++ +++ + 1

Sparse Veg --- --- --- --- --- --- --- --- 0 - --- 11

Urban --- --- --- --- --- + --- --- + 0 --- 9

Younger +++ + +++ + +++ +++ + - +++ +++ 0 2

Rank Order and

Significance

Mixedgt Youngergt Broad Leafgt Coniferousgt Clear Fellgtgtgt Agriculturegt

MiresMarshesgt Freshwatergtgtgt Urbangt GrasslandMoorsgtgtgt Sparse Veg

38

South

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 + - - + - + +++ +++ +++ - 5

Broad Leaf - 0 - - + - - +++ + +++ - 7

Clear Fell + + 0 - + + + +++ + +++ + 2

Coniferous + + + 0 +++ + + +++ + +++ + 1

Freshwater - - - --- 0 - - + + +++ - 8

Grassland

Moors + + - - + 0 + + +++ + - 4

MiresMarshes - + - - + - 0 +++ + +++ - 6

Mixed --- --- --- --- - - --- 0 + + --- 10

Sparse Veg --- - - - - --- - - 0 + - 9

Urban --- --- --- --- --- - --- - - 0 --- 11

Younger + + - - + + + +++ + +++ 0 3

Rank Order

and

Significance

Coniferousgt Clear Fellgt Youngergt GrasslandMoorsgt Agriculturegt MiresMarshesgt Broad Leafgt

Freshwatergt Sparse Veggt Mixedgt Urban

Table 2 Simplified ranking matrices comparing proportional habitat use within the third order (UD50UD95) with

proportions of total available habitat types Mean value on the matrix was replaced by a sign a triple sign represents

significant deviation from random at P lt05 Highlighted habitat is ranked 1st

North

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 --- --- --- - + --- --- + +++ --- 8

Broad Leaf +++ 0 +++ + + + + + +++ +++ + 1

Clear Fell +++ --- 0 + + + - - + +++ - 5

Coniferous +++ - - 0 + + --- --- +++ +++ - 6

Freshwater + - - - 0 +++ - - +++ +++ - 7

GrasslandMoors - - - - --- 0 - - - + - 10

MiresMarshes +++ - + +++ + + 0 - +++ +++ + 3

Mixed +++ - + +++ + + + 0 +++ +++ + 2

Sparse Veg - --- - --- --- + --- --- 0 +++ --- 9

Urban --- --- --- --- --- - --- --- --- 0 --- 11

Younger +++ - + + + + - - +++ +++ 0 4

Rank Order and

Significance

Broad Leafgt Mixedgt MiresMarshesgt Youngergt Clear Fellgt Coniferousgt Freshwatergt

Agriculturegt Sparse Veggt GrasslandMoorsgt Urban

39

Central

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 --- --- + + - - - + +++ --- 7

Broad Leaf +++ 0 + +++ + + + + + +++ - 2

Clear Fell +++ - 0 +++ + + + + + +++ - 3

Coniferous - --- --- 0 + - - --- +++ + --- 8

Freshwater - - - - 0 --- - - --- - - 11

GrasslandMoors + - - + +++ 0 + - + +++ - 5

MiresMarshes + - - + + - 0 + + +++ - 6

Mixed + - - +++ + + - 0 +++ +++ - 4

Sparse Veg - - - --- +++ - - --- 0 +++ - 9

Urban --- --- --- - + --- --- --- --- 0 --- 10

Younger +++ + + +++ + + + + + +++ 0 1

Rank Order and

Significance

Youngergt Broad Leafgt Clear Fellgt Mixedgt GrasslandMoorsgt MiresMarshesgt

Agriculturegt Coniferousgtgtgt Sparse Veggtgtgt Urbangt Freshwater

South

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 - - - - - + - +++ + --- 8

Broad Leaf + 0 - --- + - + - +++ + - 6

Clear Fell + + 0 - + - + - +++ + - 4

Coniferous + +++ + 0 + + +++ + +++ + + 1

Freshwater + - - - 0 - - + + + - 7

GrasslandMoors + + + - + 0 + + + + - 3

MiresMarshes - - - --- + - 0 - + + - 9

Mixed + + + - - - + 0 + + - 5

Sparse Veg --- --- --- --- - - - - 0 + --- 10

Urban - - - - - - - - - 0 - 11

Younger +++ + + - + + + + +++ + 0 2

Rank Order and

Significance

Coniferousgt Youngergt GrasslandMoorsgt Clear Fellgt Mixedgt Broad Leafgt Freshwatergt

Agriculturegt MiresMarshesgt Sparse Veggt Urban

40

Table 3 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the GS according to Jacobs index

Ran

k North Centre South

50 95 50 95 50 95

+ - + - + - + - + - + -

1 Broad

Leaf Urban Broad Leaf Sparse Veg

Broad

Leaf Urban Mixed Urban Coniferous Urban

Grassland

Moors Urban

2 Mixed Sparse Veg Mixed Freshwater Younger Agriculture Younger Sparse Veg Younger Sparse Veg Clear Fell Mixed

3 Mires

Agriculture Grassland

Urban Clear

Fell Coniferous Broad Leaf

Grassland

Moors

Clear Fell Agriculture Coniferous Sparse Veg

Marshes Moors

4 Younger Grassland

Younger Agriculture

Freshwater Coniferous Freshwater

Broad Leaf Mires

Younger Freshwater

Moors Marshes

5 Clear

Fell Freshwater

Mires Coniferous

Sparse Veg Clear Fell Agriculture

Freshwater Agriculture

Marshes

6 Coniferous Clear Fell

Mires

Marshes

Mires

Grassland

Moors

Mires

Marshes Marshes

7 Mixed Mixed Broad Leaf

8 Grassland

Moors

41

Table 4 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the WS according to Jacobs index

Ran

k North Centre South

50 95 50 95 50 95

+ - + - + - + - + - + -

1 Mires

Marshes

Grassland

Moors Mixed Freshwater Agriculture Urban Mixed Freshwater

Grassland

Moors Urban GrasslandMoors Urban

2 Freshwater Mixed Coniferous Urban Mires

Marshes Coniferous Sparse Veg Agriculture

Sparse

Veg Coniferous Freshwater

3 Urban Coniferous Younger Grassland

Moors Freshwater Younger Urban Freshwater

Broad

Leaf Agriculture Mixed

4 Younger Agriculture Sparse Veg Broad

Leaf

Broad

Leaf

Grassland

Moors Mixed Broad Leaf

5 Clear Fell Agriculture Coniferous Agriculture Mires

Marshes Clear Fell

6 Sparse

Veg

Mires

Marshes Mixed

Mires

Marshes

Clear

Fell

Mires

Marshes

7 Broad

Leaf Clear Fell Younger Clear Fell Younger Sparse Veg

8 Clear Fell Younger

9 Sparse

Veg

10 Grassland

Moors

42

Table 5 Second order (UD95Area) individual selectionavoidance for the GS and WS according to the Jacobs index

ID GS WS

Select Avoid Select Avoid

ID004 Younger Sparsely Vegetated MiresMarshes Sparsely Vegetated

ID005 MiresMarshes Sparsely Vegetated Coniferous GrasslandMoors

ID006 Coniferous Sparsely Vegetated Mixed Freshwater

ID008 Mixed Sparsely Vegetated Mixed Freshwater

ID009 Mixed Sparsely Vegetated Mixed GrasslandMoors

ID010 MiresMarshes Freshwater GrasslandMoors Freshwater

ID012 Broad Leaf Sparsely Vegetated Coniferous Urban

ID014 Clear Fell Sparsely Vegetated GrasslandMoors Sparsely Vegetated

ID015 GrasslandMoors Urban GrasslandMoors Freshwater

ID016 GrasslandMoors Freshwater GrasslandMoors Freshwater

ID017 GrasslandMoors Mixed Sparsely Vegetated Mixed

ID019 Mixed Sparsely Vegetated Mixed Urban

ID020 Broad Leaf Sparsely Vegetated Coniferous GrasslandMoors

ID022 MiresMarshes Freshwater MiresMarshes Freshwater

ID023 MiresMarshes GrasslandMoors Mixed Freshwater

ID024 Broadleaf Urban Broad Leaf Urban

ID026 GrasslandMoors Freshwater GrasslandMoors Freshwater

ID027 GrasslandMoors Urban Sparsely Vegetated Freshwater

43 Table 6 Third order (UD50UD95) individual selectionavoidance for the GS and WS according to the Jacobs index

ID GS WS

Select Avoid Select Avoid

ID004 Broad Leaf Mixed GrasslandMoors Freshwater

ID005 Broad Leaf Freshwater Agriculture Freshwater

ID006 Clear Fell Freshwater Agriculture MiresMarshes

ID008 MiresMarshes Freshwater Agriculture Urban

ID009 Freshwater Agriculture Agriculture Freshwater

ID010 Mixed Urban Sparsely Vegetated Urban

ID012 Coniferous GrasslandMoors Freshwater Urban

ID014 Urban Agriculture Freshwater Urban

ID015 Mixed Forest Urban Clear Fell Urban

ID016 Freshwater Urban GrasslandMoors Mixed

ID017 Coniferous Mixed Coniferous Broad Leaf

ID019 Broad Leaf GrasslandMoors Urban GrasslandMoors

ID020 Freshwater Urban Freshwater Agriculture

ID022 MiresMarshes Urban Broad Leaf GrasslandMoors

ID023 Freshwater Mixed Agriculture Freshwater

ID024 Mixed Freshwater Mixed Freshwater

ID026 Mixed MiresMarshes Sparsely Vegetated GrasslandMoors

ID027 Freshwater MiresMarshes GrasslandMoors Broad Leaf

44

Fig 2 North third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)

45

Fig 3 Centre third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)

46

Fig 4 South third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)

47

Fig 5 North second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)

48

Fig 6 Centre second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)

49

Fig 7 South second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)

50

Appendix F

Background

Fig 1 Daily mean snow depth and duration during the study period (Andrew Allen)

Female Moose Reproduction

Moose are seasonal polyoestral mammals (Monfort et al 1993) coming into oestrus during late September

early October (Garel et al 2009) The Swedish moose cow population reaches puberty between the ages 25

and 35 (Sand and Cederlund 1993) during which the reproductive period begins with the onset of ovulation

The age an individual reaches puberty is dependent on their body condition they have to reach a weight

threshold to reach puberty and become reproductive (Sand 1996) If she is over the weight threshold she will

go into oestrus in the autumn If she does not reach the weight threshold then she will go into oestrus the

following autumn if successful she will give birth to individual or twin calves in late May to early June

(Ericsson et al 2001) and therefore reach sexual maturity (Malmsten et al 2014b) Fecundity is related to

both the condition and the age of the cow Cows go through senescence at 12 years of age (Ericsson et al

2001) Providing calves with the required level of nutrition demands high energy and protein resources from

the mother during senescence this becomes harder to achieve leading to decreased levels of parental care

and higher levels of calf mortality

Page 21: Habitat-performance relationships on an island: fitness ...navinderjsingh.weebly.com/uploads/1/1/2/2/11224342/... · Conditions on Öland are milder than those found in other areas

21 the three areas are close in proximity however they displayed contrasting preferences This is supported by the

Osko et al (2004) report that found two neighbouring moose populations that had access to the same habitats

displayed contrasting preferences Habitat preferences for populations of the same species are not necessarily

fixed They alter with varying levels of habitat abundance and limiting factors skewing what is preserved to

be critical

The main limitation encountered in this study was with the limited sample There was only data on two

individuals from the north of the island which led it being removed from many of the analysis Similarly due

to a lack of relocations from the collars being turned off at points throughout the year two further individuals

had to be removed from a majority of the analysis This reduced the sample size to 17 or 18 individuals

Similarly only 13 of the individuals from the study produced calves This unfortunately prevented including

survival into models Although the sample size was small it was accurate it was of high resolution over

300000 GPS points In future it would be beneficial to have a more standardised data set An equal sample of

individuals from the three areas would be advised along with ensuring the GPS collars are kept turned on for

the entirety of the growing and winter season to allow comparisons between years It would also be

advantageous to collect coordinates of the feeding sites along with the composition This could then be

compared with high use UD coordinates to look if moose are truly spending a majority of their foraging time

at feeding stations A study on the population densities of moose and the increasing population of roe deer

(Capreolus capreolus) would add the factor of competition into the model

The low calf survival on Ӧland is most likely the result of a combination of factors The lack of suitable habitat

reported in this study in conjunction with Malmstenrsquos (2014a) report on the threat of disease (Anaplasma

phagocytophilum) are probable influences on the calf survival on Ӧland On Ӧland there is an increasing

population of roe deer and large numbers of migratory birds both carriers of ticks and diseases The mild

conditions on Ӧland are advantageous for ticks the carriers of A phagocytophilum Fewer snow days and

shorter periods of snow cover along with dry conditions are favourable for ticks This could probably be one

of the reasons for females to be of lower quality and therefore not being able to ensure calf survival Moose

have to utilise areas where in other populations individuals tend to avoid Finally similar to many studies I

advocate further research using a stronger dataset and longer term monitoring

22

Acknowledgements

I am indebted to NJ Singh and A Allen for all their help and guidance through the whole of this study I

thank SLU for the support provided during this study in terms of data finances and facilities Thank you to

everyone at the Department of Wildlife Fish and Environmental Studies for being so friendly and

supportive I would like to thank L Edenius for driving me around the study area and S Michon and H

Khalil for keeping me sane with fika and training

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Gaillard JM Festa-Bianchet M Yoccoz NG Loison A Toiumlgo C (2000a) Temporal variation in fitness

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Systematics 31367-393

Gaillard JM Festa-Bianchet M Delorme D Jorgenson J (2000b) Body mass and individual fitness in female

ungulate bigger is not always better Proceedings Biological Sciences 267471-477

Gaillard JM Hearingblewhite M Loison A Fuller M Powell R Basille M van Moorter B (2010) Habitat-

performance relationships finding the right metric at a given Spatial scale Philosophical

Transactions of the Royal Society B 3652255-2265

Garel M Solberg EJ Sӕther B-E Groslashtan V Tufto J Heim M (2009) Age size and spatiotemporal variation

in ovulation patterns of a seasonal breeder the Norwegian moose (Alces alces) The American

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Georgii B (1980) Home range patterns of female red deer (Cervus elaphus L) in the Alps Oecologia

47278-285

Godvik IMR Loe LE Vik JO Veiberg V Langvatn R Mysterud A (2009) Temporal scales trade-offs and

functional responses in red deer habitat selection Ecology 90699ndash710

Gordon IJ Hester AJ Festa-Bianchet M (2004) Review The management of wild large herbivores to meet

economic conservation and environmental objectives Journal of Applied Ecology 411021-

1031

Hagner O Nilsson M Reese H Egberth M Olsson H (2005) Procedure for classification of forests for

CORINE land cover in Sweden In Oluić M (ed) New strategies for European remote sensing

Millpress Rotterdam pp 523ndash530

Hall LS Krausman PR Morrison ML (1997) The habitat concept and a plea for standard terminology

Wildlife Society Bulletin 25173-182

Harris RB Wall WA Allendorf FW (2002) Genetic consequences of hunting what do we know and what

should we do Wildlife Society Bulletin 30634-643

Herfindal I Saeligther B-E Solberg EJ Andersen R Hoslashgda KA (2006) Population characteristics predict

responses in moose body mass to temporal variation in the environment Journal of Animal

Ecology 75 (5) 1110-1118

Horne JS Garton ED Krone SM Lewis JS (2007) Analysing animal movements using Brownian bridges

Ecological Society of America Ecology 882354-2363

Hornok S Kovaacutets D Csoumlrgo T Meli M Goumlnczi E Hadnagy Z Takaacutecs N Farkas R Hofmann-Lehmann R

(2014) Birds as potential reservoirs of tick-borne pathogens first evidence of bacteraemia

with Rickettsia Helvetica Parasites and Vectors 7128

26

Jacobs J (1974) Quantitative measurement of food selection a modification of the forage ratio and Ivlevrsquos

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Jenkins KJ Manly FJ (2008) A double-observer method for reducing bias in faecal pellet surveys of forest

ungulates Journal of Applied Ecology 451339-1348

Johnson DH (1980) The comparison of usage and availability measurements for evaluating resource

preference Ecology 6165-71

Jonsson F (2007) rsquoDen oumllaumlndska aringlgstammens foumlrvaltingrsquo Departement of Wildlife Fish and Environmental

Studies SLU Examensarbete I aumlmnet biologi vol 20072

Kaplan EL Meier P (1958) Nonparametric estimation from incomplete observation Journal of the American

Statistical Association 53457-481

Keating KA Cherry S (2009) Modelling utilization distributions in space and time Ecology 90(7)1971-

1980

Kie JG Matthiopolos J Fieberg J Powell RA Cagnacci F Mitchell SM Gaillard JM Moorcroft PR (2010)

The home range concept are traditional estimators still relevant with modern telemetry

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Jaumlgarefoumlrbundet Oumlster-Malma 20092

Kranstauber B Kays R LaPoint SD Wikelski M Safi K (2012) A dynamic Brownian bridge movement

model to estimate utilization distributions for heterogeneous Animal movement Journal of

Animal Ecology 81738-746

Laurian C Ouellet JP Courtois R Breton L St-Onge S (2000) Effects of intensive harvesting on moose

reproduction Journal of Applied Ecology 37515-531

Laurian C Dussault C Ouellet JP Courtois R Poulin M Breton L (2008) Behaviour of moose relative to a

road network The Journal of Wildlife Management 72(7)1550-1557

Lavsund S Nygreacuten T Solberg EJ (2003) Status of moose populations and challenges to moose management

in Fennoscandia Alces 39109-130

Lenarz MS Fieberg J Schrage MW Edwards AJ (2010) Living on the edge viability of moose in

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14343-348

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mortality of temperate ungulates Wildlife Biology 1209-223

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Lynch GM Morgantini LE (1984) Sex and age differential in seasonal home range size of moose in

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MacCracken JG Ballenberghe VV Peek JM (1993) Use of aquatic plants by moose sodium hunger or

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27

Malmsten J Wideacuten DG Rydevik G Yon L Hutchings MR Thulin CG Soumlderquist L Aspan A Stuen S

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University of Agricultural Sciences (SLU) Umearing

Malmsten J Soumlderquist L Thulin C Wideacuten DG Yon L Hutchings MR Dalin A (2014b) Reproductive

characteristics in female Swedish moose (Alces alces) with emphasis on puberty timing of

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Marsh DM Hanlon TJ (2004) Observer gender and observation bias in animal behaviour research

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28

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29

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van Beest FM van Moorter B Milner JM (2012) Temperature-mediated habitat use and selection by a heat

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Management 39118-123

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Halls LK) pp 91-118 Stackpole Harrisburg Pennsylvania

Wattles DW DeStefano (2013) Space use and movements of moose in Massachusetts Implications for

conservation of large mammals in a fragmented environment Alces 4965-81

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success in muskoxen Journal of Zoology 24313-20

30

Appendix A

Introduction

Fig 1 Summary chart of factors affecting the life history and therefore the long term fitness of a population

Fig 2 Summary chart 2

Movement

Habitat

Climate

Topography

Competition

FoodWater

Disease

Die

Survive

Reproduce

Population long term fitness

31 Appendix B

Method and Materials

Fig 1 Summary of processes

32

Fig 2 Examples of classical kernel home range output and Brownian bridge kernel home range (Calenge 2011) The

right image includes the area between relocations ie the movement path in contrast to the classic kernel home range

in the left image

33 Appendix C

Home ranges

Fig 1 Example of a non-migratory (ID006) individuals BRB kernel area From top left annual growing and winter

season UD50 (black contour) and UD95 (red contour)

Fig 2 Example of a migratory (ID012) individuals BRB kernel area From the left annual growing and winter season

UD50 (black contour) and UD95 (red contour)

34

Table 1 Annual and seasonal UD50 and UD95 areas (ha) for all individuals

ID Annual GS WS

UD50 UD95 UD50 UD95 UD50 UD95

ID004 190 924 93 531 173 941

ID005 230 1364 132 945 72 682

ID006 162 1036 89 736 70 611

ID008 277 1536 156 809 78 738

ID009 137 834 48 295 126 653

ID010 114 682 83 448 96 488

ID012 177 963 123 544 76 545

ID014 160 1018 87 575 89 662

ID015 172 858 128 532 109 679

ID016 156 1047 65 455 92 534

ID017 153 1088 149 1043 69 349

ID019 279 1097 176 911 163 824

ID020 139 1084 67 349 160 794

ID022 159 811 131 638 61 454

ID023 187 1061 147 771 72 705

ID024 146 725 165 705 101 458

ID026 142 605 99 442 125 547

ID027 126 567 75 461 48 277

35 Appendix D

Activity

Fig 1 Mean daily movement during the study period GS 23-April-2012 to 07-Nov-2012 WS 08-Nov-2012 to

22-April-2013 (number indicates month)

Fig 2 Mean daily movement in the centre and south during the GS and WS

36

Appendix E

Habitat Proportions

Fig 1 All individualsrsquo seasonal habitat proportions within the UD95

37 Habitat Selection

Table 1 Simplified ranking matrices comparing proportional habitat use within the second order (UD95Area) with

proportions of total available habitat types Mean value on the matrix was replaced by a sign a triple sign represents

significant deviation from random at P lt05 Highlighted habitat is ranked 1st

North A

gri

cult

ure

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 --- --- - +++ --- --- --- +++ +++ --- 8

Broad Leaf +++ 0 +++ + +++ +++ +++ + +++ +++ +++ 1

Clear Fell +++ --- 0 + +++ - - --- +++ +++ --- 7

Coniferous + - - 0 +++ - - --- +++ +++ - 6

Freshwater --- --- --- --- 0 --- --- --- +++ - --- 10

Grassland

Moors +++ --- + + +++ 0 +++ - +++ +++ + 3

MiresMarshes +++ --- + + +++ --- 0 - +++ +++ --- 5

Mixed +++ - +++ +++ +++ + + 0 +++ +++ + 2

Sparse Veg --- --- --- --- --- --- --- --- 0 --- --- 11

Urban --- --- --- --- + --- --- --- +++ 0 --- 9

Younger +++ --- +++ + +++ - +++ - +++ +++ 0 4

Rank Order and

Significance

Broad Leafgt Mixedgt GrasslandMoorsgt Youngergtgtgt MiresMarshesgt Coniferousgt

Clear Fellgtgtgt Agriculturegtgtgt Urbangt Freshwatergtgtgt Sparse Veg

Central

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 --- --- --- + +++ + --- +++ +++ --- 6

Broad Leaf +++ 0 +++ + +++ +++ + - +++ +++ - 3

Clear Fell +++ --- 0 - +++ +++ + --- +++ +++ --- 5

Coniferous +++ - + 0 +++ +++ + --- +++ +++ - 4

Freshwater - --- --- --- 0 +++ - --- +++ +++ --- 8

Grassland

Moors --- --- --- --- --- 0 --- --- +++ - --- 10

MiresMarshes - - - - + +++ 0 - +++ +++ - 7

Mixed +++ + +++ +++ +++ +++ + 0 +++ +++ + 1

Sparse Veg --- --- --- --- --- --- --- --- 0 - --- 11

Urban --- --- --- --- --- + --- --- + 0 --- 9

Younger +++ + +++ + +++ +++ + - +++ +++ 0 2

Rank Order and

Significance

Mixedgt Youngergt Broad Leafgt Coniferousgt Clear Fellgtgtgt Agriculturegt

MiresMarshesgt Freshwatergtgtgt Urbangt GrasslandMoorsgtgtgt Sparse Veg

38

South

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 + - - + - + +++ +++ +++ - 5

Broad Leaf - 0 - - + - - +++ + +++ - 7

Clear Fell + + 0 - + + + +++ + +++ + 2

Coniferous + + + 0 +++ + + +++ + +++ + 1

Freshwater - - - --- 0 - - + + +++ - 8

Grassland

Moors + + - - + 0 + + +++ + - 4

MiresMarshes - + - - + - 0 +++ + +++ - 6

Mixed --- --- --- --- - - --- 0 + + --- 10

Sparse Veg --- - - - - --- - - 0 + - 9

Urban --- --- --- --- --- - --- - - 0 --- 11

Younger + + - - + + + +++ + +++ 0 3

Rank Order

and

Significance

Coniferousgt Clear Fellgt Youngergt GrasslandMoorsgt Agriculturegt MiresMarshesgt Broad Leafgt

Freshwatergt Sparse Veggt Mixedgt Urban

Table 2 Simplified ranking matrices comparing proportional habitat use within the third order (UD50UD95) with

proportions of total available habitat types Mean value on the matrix was replaced by a sign a triple sign represents

significant deviation from random at P lt05 Highlighted habitat is ranked 1st

North

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 --- --- --- - + --- --- + +++ --- 8

Broad Leaf +++ 0 +++ + + + + + +++ +++ + 1

Clear Fell +++ --- 0 + + + - - + +++ - 5

Coniferous +++ - - 0 + + --- --- +++ +++ - 6

Freshwater + - - - 0 +++ - - +++ +++ - 7

GrasslandMoors - - - - --- 0 - - - + - 10

MiresMarshes +++ - + +++ + + 0 - +++ +++ + 3

Mixed +++ - + +++ + + + 0 +++ +++ + 2

Sparse Veg - --- - --- --- + --- --- 0 +++ --- 9

Urban --- --- --- --- --- - --- --- --- 0 --- 11

Younger +++ - + + + + - - +++ +++ 0 4

Rank Order and

Significance

Broad Leafgt Mixedgt MiresMarshesgt Youngergt Clear Fellgt Coniferousgt Freshwatergt

Agriculturegt Sparse Veggt GrasslandMoorsgt Urban

39

Central

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 --- --- + + - - - + +++ --- 7

Broad Leaf +++ 0 + +++ + + + + + +++ - 2

Clear Fell +++ - 0 +++ + + + + + +++ - 3

Coniferous - --- --- 0 + - - --- +++ + --- 8

Freshwater - - - - 0 --- - - --- - - 11

GrasslandMoors + - - + +++ 0 + - + +++ - 5

MiresMarshes + - - + + - 0 + + +++ - 6

Mixed + - - +++ + + - 0 +++ +++ - 4

Sparse Veg - - - --- +++ - - --- 0 +++ - 9

Urban --- --- --- - + --- --- --- --- 0 --- 10

Younger +++ + + +++ + + + + + +++ 0 1

Rank Order and

Significance

Youngergt Broad Leafgt Clear Fellgt Mixedgt GrasslandMoorsgt MiresMarshesgt

Agriculturegt Coniferousgtgtgt Sparse Veggtgtgt Urbangt Freshwater

South

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 - - - - - + - +++ + --- 8

Broad Leaf + 0 - --- + - + - +++ + - 6

Clear Fell + + 0 - + - + - +++ + - 4

Coniferous + +++ + 0 + + +++ + +++ + + 1

Freshwater + - - - 0 - - + + + - 7

GrasslandMoors + + + - + 0 + + + + - 3

MiresMarshes - - - --- + - 0 - + + - 9

Mixed + + + - - - + 0 + + - 5

Sparse Veg --- --- --- --- - - - - 0 + --- 10

Urban - - - - - - - - - 0 - 11

Younger +++ + + - + + + + +++ + 0 2

Rank Order and

Significance

Coniferousgt Youngergt GrasslandMoorsgt Clear Fellgt Mixedgt Broad Leafgt Freshwatergt

Agriculturegt MiresMarshesgt Sparse Veggt Urban

40

Table 3 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the GS according to Jacobs index

Ran

k North Centre South

50 95 50 95 50 95

+ - + - + - + - + - + -

1 Broad

Leaf Urban Broad Leaf Sparse Veg

Broad

Leaf Urban Mixed Urban Coniferous Urban

Grassland

Moors Urban

2 Mixed Sparse Veg Mixed Freshwater Younger Agriculture Younger Sparse Veg Younger Sparse Veg Clear Fell Mixed

3 Mires

Agriculture Grassland

Urban Clear

Fell Coniferous Broad Leaf

Grassland

Moors

Clear Fell Agriculture Coniferous Sparse Veg

Marshes Moors

4 Younger Grassland

Younger Agriculture

Freshwater Coniferous Freshwater

Broad Leaf Mires

Younger Freshwater

Moors Marshes

5 Clear

Fell Freshwater

Mires Coniferous

Sparse Veg Clear Fell Agriculture

Freshwater Agriculture

Marshes

6 Coniferous Clear Fell

Mires

Marshes

Mires

Grassland

Moors

Mires

Marshes Marshes

7 Mixed Mixed Broad Leaf

8 Grassland

Moors

41

Table 4 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the WS according to Jacobs index

Ran

k North Centre South

50 95 50 95 50 95

+ - + - + - + - + - + -

1 Mires

Marshes

Grassland

Moors Mixed Freshwater Agriculture Urban Mixed Freshwater

Grassland

Moors Urban GrasslandMoors Urban

2 Freshwater Mixed Coniferous Urban Mires

Marshes Coniferous Sparse Veg Agriculture

Sparse

Veg Coniferous Freshwater

3 Urban Coniferous Younger Grassland

Moors Freshwater Younger Urban Freshwater

Broad

Leaf Agriculture Mixed

4 Younger Agriculture Sparse Veg Broad

Leaf

Broad

Leaf

Grassland

Moors Mixed Broad Leaf

5 Clear Fell Agriculture Coniferous Agriculture Mires

Marshes Clear Fell

6 Sparse

Veg

Mires

Marshes Mixed

Mires

Marshes

Clear

Fell

Mires

Marshes

7 Broad

Leaf Clear Fell Younger Clear Fell Younger Sparse Veg

8 Clear Fell Younger

9 Sparse

Veg

10 Grassland

Moors

42

Table 5 Second order (UD95Area) individual selectionavoidance for the GS and WS according to the Jacobs index

ID GS WS

Select Avoid Select Avoid

ID004 Younger Sparsely Vegetated MiresMarshes Sparsely Vegetated

ID005 MiresMarshes Sparsely Vegetated Coniferous GrasslandMoors

ID006 Coniferous Sparsely Vegetated Mixed Freshwater

ID008 Mixed Sparsely Vegetated Mixed Freshwater

ID009 Mixed Sparsely Vegetated Mixed GrasslandMoors

ID010 MiresMarshes Freshwater GrasslandMoors Freshwater

ID012 Broad Leaf Sparsely Vegetated Coniferous Urban

ID014 Clear Fell Sparsely Vegetated GrasslandMoors Sparsely Vegetated

ID015 GrasslandMoors Urban GrasslandMoors Freshwater

ID016 GrasslandMoors Freshwater GrasslandMoors Freshwater

ID017 GrasslandMoors Mixed Sparsely Vegetated Mixed

ID019 Mixed Sparsely Vegetated Mixed Urban

ID020 Broad Leaf Sparsely Vegetated Coniferous GrasslandMoors

ID022 MiresMarshes Freshwater MiresMarshes Freshwater

ID023 MiresMarshes GrasslandMoors Mixed Freshwater

ID024 Broadleaf Urban Broad Leaf Urban

ID026 GrasslandMoors Freshwater GrasslandMoors Freshwater

ID027 GrasslandMoors Urban Sparsely Vegetated Freshwater

43 Table 6 Third order (UD50UD95) individual selectionavoidance for the GS and WS according to the Jacobs index

ID GS WS

Select Avoid Select Avoid

ID004 Broad Leaf Mixed GrasslandMoors Freshwater

ID005 Broad Leaf Freshwater Agriculture Freshwater

ID006 Clear Fell Freshwater Agriculture MiresMarshes

ID008 MiresMarshes Freshwater Agriculture Urban

ID009 Freshwater Agriculture Agriculture Freshwater

ID010 Mixed Urban Sparsely Vegetated Urban

ID012 Coniferous GrasslandMoors Freshwater Urban

ID014 Urban Agriculture Freshwater Urban

ID015 Mixed Forest Urban Clear Fell Urban

ID016 Freshwater Urban GrasslandMoors Mixed

ID017 Coniferous Mixed Coniferous Broad Leaf

ID019 Broad Leaf GrasslandMoors Urban GrasslandMoors

ID020 Freshwater Urban Freshwater Agriculture

ID022 MiresMarshes Urban Broad Leaf GrasslandMoors

ID023 Freshwater Mixed Agriculture Freshwater

ID024 Mixed Freshwater Mixed Freshwater

ID026 Mixed MiresMarshes Sparsely Vegetated GrasslandMoors

ID027 Freshwater MiresMarshes GrasslandMoors Broad Leaf

44

Fig 2 North third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)

45

Fig 3 Centre third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)

46

Fig 4 South third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)

47

Fig 5 North second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)

48

Fig 6 Centre second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)

49

Fig 7 South second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)

50

Appendix F

Background

Fig 1 Daily mean snow depth and duration during the study period (Andrew Allen)

Female Moose Reproduction

Moose are seasonal polyoestral mammals (Monfort et al 1993) coming into oestrus during late September

early October (Garel et al 2009) The Swedish moose cow population reaches puberty between the ages 25

and 35 (Sand and Cederlund 1993) during which the reproductive period begins with the onset of ovulation

The age an individual reaches puberty is dependent on their body condition they have to reach a weight

threshold to reach puberty and become reproductive (Sand 1996) If she is over the weight threshold she will

go into oestrus in the autumn If she does not reach the weight threshold then she will go into oestrus the

following autumn if successful she will give birth to individual or twin calves in late May to early June

(Ericsson et al 2001) and therefore reach sexual maturity (Malmsten et al 2014b) Fecundity is related to

both the condition and the age of the cow Cows go through senescence at 12 years of age (Ericsson et al

2001) Providing calves with the required level of nutrition demands high energy and protein resources from

the mother during senescence this becomes harder to achieve leading to decreased levels of parental care

and higher levels of calf mortality

Page 22: Habitat-performance relationships on an island: fitness ...navinderjsingh.weebly.com/uploads/1/1/2/2/11224342/... · Conditions on Öland are milder than those found in other areas

22

Acknowledgements

I am indebted to NJ Singh and A Allen for all their help and guidance through the whole of this study I

thank SLU for the support provided during this study in terms of data finances and facilities Thank you to

everyone at the Department of Wildlife Fish and Environmental Studies for being so friendly and

supportive I would like to thank L Edenius for driving me around the study area and S Michon and H

Khalil for keeping me sane with fika and training

23 References

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30

Appendix A

Introduction

Fig 1 Summary chart of factors affecting the life history and therefore the long term fitness of a population

Fig 2 Summary chart 2

Movement

Habitat

Climate

Topography

Competition

FoodWater

Disease

Die

Survive

Reproduce

Population long term fitness

31 Appendix B

Method and Materials

Fig 1 Summary of processes

32

Fig 2 Examples of classical kernel home range output and Brownian bridge kernel home range (Calenge 2011) The

right image includes the area between relocations ie the movement path in contrast to the classic kernel home range

in the left image

33 Appendix C

Home ranges

Fig 1 Example of a non-migratory (ID006) individuals BRB kernel area From top left annual growing and winter

season UD50 (black contour) and UD95 (red contour)

Fig 2 Example of a migratory (ID012) individuals BRB kernel area From the left annual growing and winter season

UD50 (black contour) and UD95 (red contour)

34

Table 1 Annual and seasonal UD50 and UD95 areas (ha) for all individuals

ID Annual GS WS

UD50 UD95 UD50 UD95 UD50 UD95

ID004 190 924 93 531 173 941

ID005 230 1364 132 945 72 682

ID006 162 1036 89 736 70 611

ID008 277 1536 156 809 78 738

ID009 137 834 48 295 126 653

ID010 114 682 83 448 96 488

ID012 177 963 123 544 76 545

ID014 160 1018 87 575 89 662

ID015 172 858 128 532 109 679

ID016 156 1047 65 455 92 534

ID017 153 1088 149 1043 69 349

ID019 279 1097 176 911 163 824

ID020 139 1084 67 349 160 794

ID022 159 811 131 638 61 454

ID023 187 1061 147 771 72 705

ID024 146 725 165 705 101 458

ID026 142 605 99 442 125 547

ID027 126 567 75 461 48 277

35 Appendix D

Activity

Fig 1 Mean daily movement during the study period GS 23-April-2012 to 07-Nov-2012 WS 08-Nov-2012 to

22-April-2013 (number indicates month)

Fig 2 Mean daily movement in the centre and south during the GS and WS

36

Appendix E

Habitat Proportions

Fig 1 All individualsrsquo seasonal habitat proportions within the UD95

37 Habitat Selection

Table 1 Simplified ranking matrices comparing proportional habitat use within the second order (UD95Area) with

proportions of total available habitat types Mean value on the matrix was replaced by a sign a triple sign represents

significant deviation from random at P lt05 Highlighted habitat is ranked 1st

North A

gri

cult

ure

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 --- --- - +++ --- --- --- +++ +++ --- 8

Broad Leaf +++ 0 +++ + +++ +++ +++ + +++ +++ +++ 1

Clear Fell +++ --- 0 + +++ - - --- +++ +++ --- 7

Coniferous + - - 0 +++ - - --- +++ +++ - 6

Freshwater --- --- --- --- 0 --- --- --- +++ - --- 10

Grassland

Moors +++ --- + + +++ 0 +++ - +++ +++ + 3

MiresMarshes +++ --- + + +++ --- 0 - +++ +++ --- 5

Mixed +++ - +++ +++ +++ + + 0 +++ +++ + 2

Sparse Veg --- --- --- --- --- --- --- --- 0 --- --- 11

Urban --- --- --- --- + --- --- --- +++ 0 --- 9

Younger +++ --- +++ + +++ - +++ - +++ +++ 0 4

Rank Order and

Significance

Broad Leafgt Mixedgt GrasslandMoorsgt Youngergtgtgt MiresMarshesgt Coniferousgt

Clear Fellgtgtgt Agriculturegtgtgt Urbangt Freshwatergtgtgt Sparse Veg

Central

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 --- --- --- + +++ + --- +++ +++ --- 6

Broad Leaf +++ 0 +++ + +++ +++ + - +++ +++ - 3

Clear Fell +++ --- 0 - +++ +++ + --- +++ +++ --- 5

Coniferous +++ - + 0 +++ +++ + --- +++ +++ - 4

Freshwater - --- --- --- 0 +++ - --- +++ +++ --- 8

Grassland

Moors --- --- --- --- --- 0 --- --- +++ - --- 10

MiresMarshes - - - - + +++ 0 - +++ +++ - 7

Mixed +++ + +++ +++ +++ +++ + 0 +++ +++ + 1

Sparse Veg --- --- --- --- --- --- --- --- 0 - --- 11

Urban --- --- --- --- --- + --- --- + 0 --- 9

Younger +++ + +++ + +++ +++ + - +++ +++ 0 2

Rank Order and

Significance

Mixedgt Youngergt Broad Leafgt Coniferousgt Clear Fellgtgtgt Agriculturegt

MiresMarshesgt Freshwatergtgtgt Urbangt GrasslandMoorsgtgtgt Sparse Veg

38

South

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 + - - + - + +++ +++ +++ - 5

Broad Leaf - 0 - - + - - +++ + +++ - 7

Clear Fell + + 0 - + + + +++ + +++ + 2

Coniferous + + + 0 +++ + + +++ + +++ + 1

Freshwater - - - --- 0 - - + + +++ - 8

Grassland

Moors + + - - + 0 + + +++ + - 4

MiresMarshes - + - - + - 0 +++ + +++ - 6

Mixed --- --- --- --- - - --- 0 + + --- 10

Sparse Veg --- - - - - --- - - 0 + - 9

Urban --- --- --- --- --- - --- - - 0 --- 11

Younger + + - - + + + +++ + +++ 0 3

Rank Order

and

Significance

Coniferousgt Clear Fellgt Youngergt GrasslandMoorsgt Agriculturegt MiresMarshesgt Broad Leafgt

Freshwatergt Sparse Veggt Mixedgt Urban

Table 2 Simplified ranking matrices comparing proportional habitat use within the third order (UD50UD95) with

proportions of total available habitat types Mean value on the matrix was replaced by a sign a triple sign represents

significant deviation from random at P lt05 Highlighted habitat is ranked 1st

North

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 --- --- --- - + --- --- + +++ --- 8

Broad Leaf +++ 0 +++ + + + + + +++ +++ + 1

Clear Fell +++ --- 0 + + + - - + +++ - 5

Coniferous +++ - - 0 + + --- --- +++ +++ - 6

Freshwater + - - - 0 +++ - - +++ +++ - 7

GrasslandMoors - - - - --- 0 - - - + - 10

MiresMarshes +++ - + +++ + + 0 - +++ +++ + 3

Mixed +++ - + +++ + + + 0 +++ +++ + 2

Sparse Veg - --- - --- --- + --- --- 0 +++ --- 9

Urban --- --- --- --- --- - --- --- --- 0 --- 11

Younger +++ - + + + + - - +++ +++ 0 4

Rank Order and

Significance

Broad Leafgt Mixedgt MiresMarshesgt Youngergt Clear Fellgt Coniferousgt Freshwatergt

Agriculturegt Sparse Veggt GrasslandMoorsgt Urban

39

Central

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 --- --- + + - - - + +++ --- 7

Broad Leaf +++ 0 + +++ + + + + + +++ - 2

Clear Fell +++ - 0 +++ + + + + + +++ - 3

Coniferous - --- --- 0 + - - --- +++ + --- 8

Freshwater - - - - 0 --- - - --- - - 11

GrasslandMoors + - - + +++ 0 + - + +++ - 5

MiresMarshes + - - + + - 0 + + +++ - 6

Mixed + - - +++ + + - 0 +++ +++ - 4

Sparse Veg - - - --- +++ - - --- 0 +++ - 9

Urban --- --- --- - + --- --- --- --- 0 --- 10

Younger +++ + + +++ + + + + + +++ 0 1

Rank Order and

Significance

Youngergt Broad Leafgt Clear Fellgt Mixedgt GrasslandMoorsgt MiresMarshesgt

Agriculturegt Coniferousgtgtgt Sparse Veggtgtgt Urbangt Freshwater

South

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 - - - - - + - +++ + --- 8

Broad Leaf + 0 - --- + - + - +++ + - 6

Clear Fell + + 0 - + - + - +++ + - 4

Coniferous + +++ + 0 + + +++ + +++ + + 1

Freshwater + - - - 0 - - + + + - 7

GrasslandMoors + + + - + 0 + + + + - 3

MiresMarshes - - - --- + - 0 - + + - 9

Mixed + + + - - - + 0 + + - 5

Sparse Veg --- --- --- --- - - - - 0 + --- 10

Urban - - - - - - - - - 0 - 11

Younger +++ + + - + + + + +++ + 0 2

Rank Order and

Significance

Coniferousgt Youngergt GrasslandMoorsgt Clear Fellgt Mixedgt Broad Leafgt Freshwatergt

Agriculturegt MiresMarshesgt Sparse Veggt Urban

40

Table 3 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the GS according to Jacobs index

Ran

k North Centre South

50 95 50 95 50 95

+ - + - + - + - + - + -

1 Broad

Leaf Urban Broad Leaf Sparse Veg

Broad

Leaf Urban Mixed Urban Coniferous Urban

Grassland

Moors Urban

2 Mixed Sparse Veg Mixed Freshwater Younger Agriculture Younger Sparse Veg Younger Sparse Veg Clear Fell Mixed

3 Mires

Agriculture Grassland

Urban Clear

Fell Coniferous Broad Leaf

Grassland

Moors

Clear Fell Agriculture Coniferous Sparse Veg

Marshes Moors

4 Younger Grassland

Younger Agriculture

Freshwater Coniferous Freshwater

Broad Leaf Mires

Younger Freshwater

Moors Marshes

5 Clear

Fell Freshwater

Mires Coniferous

Sparse Veg Clear Fell Agriculture

Freshwater Agriculture

Marshes

6 Coniferous Clear Fell

Mires

Marshes

Mires

Grassland

Moors

Mires

Marshes Marshes

7 Mixed Mixed Broad Leaf

8 Grassland

Moors

41

Table 4 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the WS according to Jacobs index

Ran

k North Centre South

50 95 50 95 50 95

+ - + - + - + - + - + -

1 Mires

Marshes

Grassland

Moors Mixed Freshwater Agriculture Urban Mixed Freshwater

Grassland

Moors Urban GrasslandMoors Urban

2 Freshwater Mixed Coniferous Urban Mires

Marshes Coniferous Sparse Veg Agriculture

Sparse

Veg Coniferous Freshwater

3 Urban Coniferous Younger Grassland

Moors Freshwater Younger Urban Freshwater

Broad

Leaf Agriculture Mixed

4 Younger Agriculture Sparse Veg Broad

Leaf

Broad

Leaf

Grassland

Moors Mixed Broad Leaf

5 Clear Fell Agriculture Coniferous Agriculture Mires

Marshes Clear Fell

6 Sparse

Veg

Mires

Marshes Mixed

Mires

Marshes

Clear

Fell

Mires

Marshes

7 Broad

Leaf Clear Fell Younger Clear Fell Younger Sparse Veg

8 Clear Fell Younger

9 Sparse

Veg

10 Grassland

Moors

42

Table 5 Second order (UD95Area) individual selectionavoidance for the GS and WS according to the Jacobs index

ID GS WS

Select Avoid Select Avoid

ID004 Younger Sparsely Vegetated MiresMarshes Sparsely Vegetated

ID005 MiresMarshes Sparsely Vegetated Coniferous GrasslandMoors

ID006 Coniferous Sparsely Vegetated Mixed Freshwater

ID008 Mixed Sparsely Vegetated Mixed Freshwater

ID009 Mixed Sparsely Vegetated Mixed GrasslandMoors

ID010 MiresMarshes Freshwater GrasslandMoors Freshwater

ID012 Broad Leaf Sparsely Vegetated Coniferous Urban

ID014 Clear Fell Sparsely Vegetated GrasslandMoors Sparsely Vegetated

ID015 GrasslandMoors Urban GrasslandMoors Freshwater

ID016 GrasslandMoors Freshwater GrasslandMoors Freshwater

ID017 GrasslandMoors Mixed Sparsely Vegetated Mixed

ID019 Mixed Sparsely Vegetated Mixed Urban

ID020 Broad Leaf Sparsely Vegetated Coniferous GrasslandMoors

ID022 MiresMarshes Freshwater MiresMarshes Freshwater

ID023 MiresMarshes GrasslandMoors Mixed Freshwater

ID024 Broadleaf Urban Broad Leaf Urban

ID026 GrasslandMoors Freshwater GrasslandMoors Freshwater

ID027 GrasslandMoors Urban Sparsely Vegetated Freshwater

43 Table 6 Third order (UD50UD95) individual selectionavoidance for the GS and WS according to the Jacobs index

ID GS WS

Select Avoid Select Avoid

ID004 Broad Leaf Mixed GrasslandMoors Freshwater

ID005 Broad Leaf Freshwater Agriculture Freshwater

ID006 Clear Fell Freshwater Agriculture MiresMarshes

ID008 MiresMarshes Freshwater Agriculture Urban

ID009 Freshwater Agriculture Agriculture Freshwater

ID010 Mixed Urban Sparsely Vegetated Urban

ID012 Coniferous GrasslandMoors Freshwater Urban

ID014 Urban Agriculture Freshwater Urban

ID015 Mixed Forest Urban Clear Fell Urban

ID016 Freshwater Urban GrasslandMoors Mixed

ID017 Coniferous Mixed Coniferous Broad Leaf

ID019 Broad Leaf GrasslandMoors Urban GrasslandMoors

ID020 Freshwater Urban Freshwater Agriculture

ID022 MiresMarshes Urban Broad Leaf GrasslandMoors

ID023 Freshwater Mixed Agriculture Freshwater

ID024 Mixed Freshwater Mixed Freshwater

ID026 Mixed MiresMarshes Sparsely Vegetated GrasslandMoors

ID027 Freshwater MiresMarshes GrasslandMoors Broad Leaf

44

Fig 2 North third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)

45

Fig 3 Centre third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)

46

Fig 4 South third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)

47

Fig 5 North second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)

48

Fig 6 Centre second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)

49

Fig 7 South second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)

50

Appendix F

Background

Fig 1 Daily mean snow depth and duration during the study period (Andrew Allen)

Female Moose Reproduction

Moose are seasonal polyoestral mammals (Monfort et al 1993) coming into oestrus during late September

early October (Garel et al 2009) The Swedish moose cow population reaches puberty between the ages 25

and 35 (Sand and Cederlund 1993) during which the reproductive period begins with the onset of ovulation

The age an individual reaches puberty is dependent on their body condition they have to reach a weight

threshold to reach puberty and become reproductive (Sand 1996) If she is over the weight threshold she will

go into oestrus in the autumn If she does not reach the weight threshold then she will go into oestrus the

following autumn if successful she will give birth to individual or twin calves in late May to early June

(Ericsson et al 2001) and therefore reach sexual maturity (Malmsten et al 2014b) Fecundity is related to

both the condition and the age of the cow Cows go through senescence at 12 years of age (Ericsson et al

2001) Providing calves with the required level of nutrition demands high energy and protein resources from

the mother during senescence this becomes harder to achieve leading to decreased levels of parental care

and higher levels of calf mortality

Page 23: Habitat-performance relationships on an island: fitness ...navinderjsingh.weebly.com/uploads/1/1/2/2/11224342/... · Conditions on Öland are milder than those found in other areas

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30

Appendix A

Introduction

Fig 1 Summary chart of factors affecting the life history and therefore the long term fitness of a population

Fig 2 Summary chart 2

Movement

Habitat

Climate

Topography

Competition

FoodWater

Disease

Die

Survive

Reproduce

Population long term fitness

31 Appendix B

Method and Materials

Fig 1 Summary of processes

32

Fig 2 Examples of classical kernel home range output and Brownian bridge kernel home range (Calenge 2011) The

right image includes the area between relocations ie the movement path in contrast to the classic kernel home range

in the left image

33 Appendix C

Home ranges

Fig 1 Example of a non-migratory (ID006) individuals BRB kernel area From top left annual growing and winter

season UD50 (black contour) and UD95 (red contour)

Fig 2 Example of a migratory (ID012) individuals BRB kernel area From the left annual growing and winter season

UD50 (black contour) and UD95 (red contour)

34

Table 1 Annual and seasonal UD50 and UD95 areas (ha) for all individuals

ID Annual GS WS

UD50 UD95 UD50 UD95 UD50 UD95

ID004 190 924 93 531 173 941

ID005 230 1364 132 945 72 682

ID006 162 1036 89 736 70 611

ID008 277 1536 156 809 78 738

ID009 137 834 48 295 126 653

ID010 114 682 83 448 96 488

ID012 177 963 123 544 76 545

ID014 160 1018 87 575 89 662

ID015 172 858 128 532 109 679

ID016 156 1047 65 455 92 534

ID017 153 1088 149 1043 69 349

ID019 279 1097 176 911 163 824

ID020 139 1084 67 349 160 794

ID022 159 811 131 638 61 454

ID023 187 1061 147 771 72 705

ID024 146 725 165 705 101 458

ID026 142 605 99 442 125 547

ID027 126 567 75 461 48 277

35 Appendix D

Activity

Fig 1 Mean daily movement during the study period GS 23-April-2012 to 07-Nov-2012 WS 08-Nov-2012 to

22-April-2013 (number indicates month)

Fig 2 Mean daily movement in the centre and south during the GS and WS

36

Appendix E

Habitat Proportions

Fig 1 All individualsrsquo seasonal habitat proportions within the UD95

37 Habitat Selection

Table 1 Simplified ranking matrices comparing proportional habitat use within the second order (UD95Area) with

proportions of total available habitat types Mean value on the matrix was replaced by a sign a triple sign represents

significant deviation from random at P lt05 Highlighted habitat is ranked 1st

North A

gri

cult

ure

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 --- --- - +++ --- --- --- +++ +++ --- 8

Broad Leaf +++ 0 +++ + +++ +++ +++ + +++ +++ +++ 1

Clear Fell +++ --- 0 + +++ - - --- +++ +++ --- 7

Coniferous + - - 0 +++ - - --- +++ +++ - 6

Freshwater --- --- --- --- 0 --- --- --- +++ - --- 10

Grassland

Moors +++ --- + + +++ 0 +++ - +++ +++ + 3

MiresMarshes +++ --- + + +++ --- 0 - +++ +++ --- 5

Mixed +++ - +++ +++ +++ + + 0 +++ +++ + 2

Sparse Veg --- --- --- --- --- --- --- --- 0 --- --- 11

Urban --- --- --- --- + --- --- --- +++ 0 --- 9

Younger +++ --- +++ + +++ - +++ - +++ +++ 0 4

Rank Order and

Significance

Broad Leafgt Mixedgt GrasslandMoorsgt Youngergtgtgt MiresMarshesgt Coniferousgt

Clear Fellgtgtgt Agriculturegtgtgt Urbangt Freshwatergtgtgt Sparse Veg

Central

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 --- --- --- + +++ + --- +++ +++ --- 6

Broad Leaf +++ 0 +++ + +++ +++ + - +++ +++ - 3

Clear Fell +++ --- 0 - +++ +++ + --- +++ +++ --- 5

Coniferous +++ - + 0 +++ +++ + --- +++ +++ - 4

Freshwater - --- --- --- 0 +++ - --- +++ +++ --- 8

Grassland

Moors --- --- --- --- --- 0 --- --- +++ - --- 10

MiresMarshes - - - - + +++ 0 - +++ +++ - 7

Mixed +++ + +++ +++ +++ +++ + 0 +++ +++ + 1

Sparse Veg --- --- --- --- --- --- --- --- 0 - --- 11

Urban --- --- --- --- --- + --- --- + 0 --- 9

Younger +++ + +++ + +++ +++ + - +++ +++ 0 2

Rank Order and

Significance

Mixedgt Youngergt Broad Leafgt Coniferousgt Clear Fellgtgtgt Agriculturegt

MiresMarshesgt Freshwatergtgtgt Urbangt GrasslandMoorsgtgtgt Sparse Veg

38

South

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 + - - + - + +++ +++ +++ - 5

Broad Leaf - 0 - - + - - +++ + +++ - 7

Clear Fell + + 0 - + + + +++ + +++ + 2

Coniferous + + + 0 +++ + + +++ + +++ + 1

Freshwater - - - --- 0 - - + + +++ - 8

Grassland

Moors + + - - + 0 + + +++ + - 4

MiresMarshes - + - - + - 0 +++ + +++ - 6

Mixed --- --- --- --- - - --- 0 + + --- 10

Sparse Veg --- - - - - --- - - 0 + - 9

Urban --- --- --- --- --- - --- - - 0 --- 11

Younger + + - - + + + +++ + +++ 0 3

Rank Order

and

Significance

Coniferousgt Clear Fellgt Youngergt GrasslandMoorsgt Agriculturegt MiresMarshesgt Broad Leafgt

Freshwatergt Sparse Veggt Mixedgt Urban

Table 2 Simplified ranking matrices comparing proportional habitat use within the third order (UD50UD95) with

proportions of total available habitat types Mean value on the matrix was replaced by a sign a triple sign represents

significant deviation from random at P lt05 Highlighted habitat is ranked 1st

North

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 --- --- --- - + --- --- + +++ --- 8

Broad Leaf +++ 0 +++ + + + + + +++ +++ + 1

Clear Fell +++ --- 0 + + + - - + +++ - 5

Coniferous +++ - - 0 + + --- --- +++ +++ - 6

Freshwater + - - - 0 +++ - - +++ +++ - 7

GrasslandMoors - - - - --- 0 - - - + - 10

MiresMarshes +++ - + +++ + + 0 - +++ +++ + 3

Mixed +++ - + +++ + + + 0 +++ +++ + 2

Sparse Veg - --- - --- --- + --- --- 0 +++ --- 9

Urban --- --- --- --- --- - --- --- --- 0 --- 11

Younger +++ - + + + + - - +++ +++ 0 4

Rank Order and

Significance

Broad Leafgt Mixedgt MiresMarshesgt Youngergt Clear Fellgt Coniferousgt Freshwatergt

Agriculturegt Sparse Veggt GrasslandMoorsgt Urban

39

Central

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 --- --- + + - - - + +++ --- 7

Broad Leaf +++ 0 + +++ + + + + + +++ - 2

Clear Fell +++ - 0 +++ + + + + + +++ - 3

Coniferous - --- --- 0 + - - --- +++ + --- 8

Freshwater - - - - 0 --- - - --- - - 11

GrasslandMoors + - - + +++ 0 + - + +++ - 5

MiresMarshes + - - + + - 0 + + +++ - 6

Mixed + - - +++ + + - 0 +++ +++ - 4

Sparse Veg - - - --- +++ - - --- 0 +++ - 9

Urban --- --- --- - + --- --- --- --- 0 --- 10

Younger +++ + + +++ + + + + + +++ 0 1

Rank Order and

Significance

Youngergt Broad Leafgt Clear Fellgt Mixedgt GrasslandMoorsgt MiresMarshesgt

Agriculturegt Coniferousgtgtgt Sparse Veggtgtgt Urbangt Freshwater

South

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 - - - - - + - +++ + --- 8

Broad Leaf + 0 - --- + - + - +++ + - 6

Clear Fell + + 0 - + - + - +++ + - 4

Coniferous + +++ + 0 + + +++ + +++ + + 1

Freshwater + - - - 0 - - + + + - 7

GrasslandMoors + + + - + 0 + + + + - 3

MiresMarshes - - - --- + - 0 - + + - 9

Mixed + + + - - - + 0 + + - 5

Sparse Veg --- --- --- --- - - - - 0 + --- 10

Urban - - - - - - - - - 0 - 11

Younger +++ + + - + + + + +++ + 0 2

Rank Order and

Significance

Coniferousgt Youngergt GrasslandMoorsgt Clear Fellgt Mixedgt Broad Leafgt Freshwatergt

Agriculturegt MiresMarshesgt Sparse Veggt Urban

40

Table 3 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the GS according to Jacobs index

Ran

k North Centre South

50 95 50 95 50 95

+ - + - + - + - + - + -

1 Broad

Leaf Urban Broad Leaf Sparse Veg

Broad

Leaf Urban Mixed Urban Coniferous Urban

Grassland

Moors Urban

2 Mixed Sparse Veg Mixed Freshwater Younger Agriculture Younger Sparse Veg Younger Sparse Veg Clear Fell Mixed

3 Mires

Agriculture Grassland

Urban Clear

Fell Coniferous Broad Leaf

Grassland

Moors

Clear Fell Agriculture Coniferous Sparse Veg

Marshes Moors

4 Younger Grassland

Younger Agriculture

Freshwater Coniferous Freshwater

Broad Leaf Mires

Younger Freshwater

Moors Marshes

5 Clear

Fell Freshwater

Mires Coniferous

Sparse Veg Clear Fell Agriculture

Freshwater Agriculture

Marshes

6 Coniferous Clear Fell

Mires

Marshes

Mires

Grassland

Moors

Mires

Marshes Marshes

7 Mixed Mixed Broad Leaf

8 Grassland

Moors

41

Table 4 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the WS according to Jacobs index

Ran

k North Centre South

50 95 50 95 50 95

+ - + - + - + - + - + -

1 Mires

Marshes

Grassland

Moors Mixed Freshwater Agriculture Urban Mixed Freshwater

Grassland

Moors Urban GrasslandMoors Urban

2 Freshwater Mixed Coniferous Urban Mires

Marshes Coniferous Sparse Veg Agriculture

Sparse

Veg Coniferous Freshwater

3 Urban Coniferous Younger Grassland

Moors Freshwater Younger Urban Freshwater

Broad

Leaf Agriculture Mixed

4 Younger Agriculture Sparse Veg Broad

Leaf

Broad

Leaf

Grassland

Moors Mixed Broad Leaf

5 Clear Fell Agriculture Coniferous Agriculture Mires

Marshes Clear Fell

6 Sparse

Veg

Mires

Marshes Mixed

Mires

Marshes

Clear

Fell

Mires

Marshes

7 Broad

Leaf Clear Fell Younger Clear Fell Younger Sparse Veg

8 Clear Fell Younger

9 Sparse

Veg

10 Grassland

Moors

42

Table 5 Second order (UD95Area) individual selectionavoidance for the GS and WS according to the Jacobs index

ID GS WS

Select Avoid Select Avoid

ID004 Younger Sparsely Vegetated MiresMarshes Sparsely Vegetated

ID005 MiresMarshes Sparsely Vegetated Coniferous GrasslandMoors

ID006 Coniferous Sparsely Vegetated Mixed Freshwater

ID008 Mixed Sparsely Vegetated Mixed Freshwater

ID009 Mixed Sparsely Vegetated Mixed GrasslandMoors

ID010 MiresMarshes Freshwater GrasslandMoors Freshwater

ID012 Broad Leaf Sparsely Vegetated Coniferous Urban

ID014 Clear Fell Sparsely Vegetated GrasslandMoors Sparsely Vegetated

ID015 GrasslandMoors Urban GrasslandMoors Freshwater

ID016 GrasslandMoors Freshwater GrasslandMoors Freshwater

ID017 GrasslandMoors Mixed Sparsely Vegetated Mixed

ID019 Mixed Sparsely Vegetated Mixed Urban

ID020 Broad Leaf Sparsely Vegetated Coniferous GrasslandMoors

ID022 MiresMarshes Freshwater MiresMarshes Freshwater

ID023 MiresMarshes GrasslandMoors Mixed Freshwater

ID024 Broadleaf Urban Broad Leaf Urban

ID026 GrasslandMoors Freshwater GrasslandMoors Freshwater

ID027 GrasslandMoors Urban Sparsely Vegetated Freshwater

43 Table 6 Third order (UD50UD95) individual selectionavoidance for the GS and WS according to the Jacobs index

ID GS WS

Select Avoid Select Avoid

ID004 Broad Leaf Mixed GrasslandMoors Freshwater

ID005 Broad Leaf Freshwater Agriculture Freshwater

ID006 Clear Fell Freshwater Agriculture MiresMarshes

ID008 MiresMarshes Freshwater Agriculture Urban

ID009 Freshwater Agriculture Agriculture Freshwater

ID010 Mixed Urban Sparsely Vegetated Urban

ID012 Coniferous GrasslandMoors Freshwater Urban

ID014 Urban Agriculture Freshwater Urban

ID015 Mixed Forest Urban Clear Fell Urban

ID016 Freshwater Urban GrasslandMoors Mixed

ID017 Coniferous Mixed Coniferous Broad Leaf

ID019 Broad Leaf GrasslandMoors Urban GrasslandMoors

ID020 Freshwater Urban Freshwater Agriculture

ID022 MiresMarshes Urban Broad Leaf GrasslandMoors

ID023 Freshwater Mixed Agriculture Freshwater

ID024 Mixed Freshwater Mixed Freshwater

ID026 Mixed MiresMarshes Sparsely Vegetated GrasslandMoors

ID027 Freshwater MiresMarshes GrasslandMoors Broad Leaf

44

Fig 2 North third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)

45

Fig 3 Centre third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)

46

Fig 4 South third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)

47

Fig 5 North second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)

48

Fig 6 Centre second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)

49

Fig 7 South second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)

50

Appendix F

Background

Fig 1 Daily mean snow depth and duration during the study period (Andrew Allen)

Female Moose Reproduction

Moose are seasonal polyoestral mammals (Monfort et al 1993) coming into oestrus during late September

early October (Garel et al 2009) The Swedish moose cow population reaches puberty between the ages 25

and 35 (Sand and Cederlund 1993) during which the reproductive period begins with the onset of ovulation

The age an individual reaches puberty is dependent on their body condition they have to reach a weight

threshold to reach puberty and become reproductive (Sand 1996) If she is over the weight threshold she will

go into oestrus in the autumn If she does not reach the weight threshold then she will go into oestrus the

following autumn if successful she will give birth to individual or twin calves in late May to early June

(Ericsson et al 2001) and therefore reach sexual maturity (Malmsten et al 2014b) Fecundity is related to

both the condition and the age of the cow Cows go through senescence at 12 years of age (Ericsson et al

2001) Providing calves with the required level of nutrition demands high energy and protein resources from

the mother during senescence this becomes harder to achieve leading to decreased levels of parental care

and higher levels of calf mortality

Page 24: Habitat-performance relationships on an island: fitness ...navinderjsingh.weebly.com/uploads/1/1/2/2/11224342/... · Conditions on Öland are milder than those found in other areas

24

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Calenge C (2006) The package adehabitat for the R software a tool for the analysis of space and habitat use

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Calenge C (2011) Home Range Estimation in R the adehabitatHR package Office national de la classe et de

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Cederlund GN Nystroumlm A (1981) Seasonal differences between moose and roe deer in ability to digest

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Cederlund GN Okarma H (1988) Home range and habitat use of adult female moose Journal of Wildlife

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Cederlund GN (1989) Activity patterns in moose and roe deer in a north boreal forest Holarctic Ecology

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Cederlund GN Sand H (1994) Home-range size in relation to age and sex in moose American Society of

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Clutton-Brock T Sheldon BC (2010) Individuals and populations the role of long-term individual based

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Cooke SJ Hinch SG Wikelski M Andrews RD Kuchel LJ Wolcott TG Butler PJ (2004) Biotelemerty a

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Crecircte M Courtois R (1997) Limiting factors might obscure population regulation of moose (Cervidae Alces

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Ericsson G Malmsten J Neumann W Singh NJ Dali AM Submitted Summer Calf Survival of

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Applied Ecology 2625-33

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University Press

29

Tveito OE Foslashrland EJ Alexandersson H Drebs A Jonsson T Vaarby-Laursen E (2001) Nordic climate

maps Norway CICERO

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Russian Journal of Genetics 38951-957

van Beest FM van Moorter B Milner JM (2012) Temperature-mediated habitat use and selection by a heat

sensitive northern ungulate Animal Behaviour 84(3)723-735

van Winkle W (1975) Comparision of several probabilistic home-range models Journal of Wildlife

Management 39118-123

Verme LJ Ullrey DE (1984) Physiology and nutrition White-tailed deer ecology and management (Ed By

Halls LK) pp 91-118 Stackpole Harrisburg Pennsylvania

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conservation of large mammals in a fragmented environment Alces 4965-81

White RG Rowell JE Hauer WE (1997) The role of nutrition body condition and lactation on calving

success in muskoxen Journal of Zoology 24313-20

30

Appendix A

Introduction

Fig 1 Summary chart of factors affecting the life history and therefore the long term fitness of a population

Fig 2 Summary chart 2

Movement

Habitat

Climate

Topography

Competition

FoodWater

Disease

Die

Survive

Reproduce

Population long term fitness

31 Appendix B

Method and Materials

Fig 1 Summary of processes

32

Fig 2 Examples of classical kernel home range output and Brownian bridge kernel home range (Calenge 2011) The

right image includes the area between relocations ie the movement path in contrast to the classic kernel home range

in the left image

33 Appendix C

Home ranges

Fig 1 Example of a non-migratory (ID006) individuals BRB kernel area From top left annual growing and winter

season UD50 (black contour) and UD95 (red contour)

Fig 2 Example of a migratory (ID012) individuals BRB kernel area From the left annual growing and winter season

UD50 (black contour) and UD95 (red contour)

34

Table 1 Annual and seasonal UD50 and UD95 areas (ha) for all individuals

ID Annual GS WS

UD50 UD95 UD50 UD95 UD50 UD95

ID004 190 924 93 531 173 941

ID005 230 1364 132 945 72 682

ID006 162 1036 89 736 70 611

ID008 277 1536 156 809 78 738

ID009 137 834 48 295 126 653

ID010 114 682 83 448 96 488

ID012 177 963 123 544 76 545

ID014 160 1018 87 575 89 662

ID015 172 858 128 532 109 679

ID016 156 1047 65 455 92 534

ID017 153 1088 149 1043 69 349

ID019 279 1097 176 911 163 824

ID020 139 1084 67 349 160 794

ID022 159 811 131 638 61 454

ID023 187 1061 147 771 72 705

ID024 146 725 165 705 101 458

ID026 142 605 99 442 125 547

ID027 126 567 75 461 48 277

35 Appendix D

Activity

Fig 1 Mean daily movement during the study period GS 23-April-2012 to 07-Nov-2012 WS 08-Nov-2012 to

22-April-2013 (number indicates month)

Fig 2 Mean daily movement in the centre and south during the GS and WS

36

Appendix E

Habitat Proportions

Fig 1 All individualsrsquo seasonal habitat proportions within the UD95

37 Habitat Selection

Table 1 Simplified ranking matrices comparing proportional habitat use within the second order (UD95Area) with

proportions of total available habitat types Mean value on the matrix was replaced by a sign a triple sign represents

significant deviation from random at P lt05 Highlighted habitat is ranked 1st

North A

gri

cult

ure

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 --- --- - +++ --- --- --- +++ +++ --- 8

Broad Leaf +++ 0 +++ + +++ +++ +++ + +++ +++ +++ 1

Clear Fell +++ --- 0 + +++ - - --- +++ +++ --- 7

Coniferous + - - 0 +++ - - --- +++ +++ - 6

Freshwater --- --- --- --- 0 --- --- --- +++ - --- 10

Grassland

Moors +++ --- + + +++ 0 +++ - +++ +++ + 3

MiresMarshes +++ --- + + +++ --- 0 - +++ +++ --- 5

Mixed +++ - +++ +++ +++ + + 0 +++ +++ + 2

Sparse Veg --- --- --- --- --- --- --- --- 0 --- --- 11

Urban --- --- --- --- + --- --- --- +++ 0 --- 9

Younger +++ --- +++ + +++ - +++ - +++ +++ 0 4

Rank Order and

Significance

Broad Leafgt Mixedgt GrasslandMoorsgt Youngergtgtgt MiresMarshesgt Coniferousgt

Clear Fellgtgtgt Agriculturegtgtgt Urbangt Freshwatergtgtgt Sparse Veg

Central

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 --- --- --- + +++ + --- +++ +++ --- 6

Broad Leaf +++ 0 +++ + +++ +++ + - +++ +++ - 3

Clear Fell +++ --- 0 - +++ +++ + --- +++ +++ --- 5

Coniferous +++ - + 0 +++ +++ + --- +++ +++ - 4

Freshwater - --- --- --- 0 +++ - --- +++ +++ --- 8

Grassland

Moors --- --- --- --- --- 0 --- --- +++ - --- 10

MiresMarshes - - - - + +++ 0 - +++ +++ - 7

Mixed +++ + +++ +++ +++ +++ + 0 +++ +++ + 1

Sparse Veg --- --- --- --- --- --- --- --- 0 - --- 11

Urban --- --- --- --- --- + --- --- + 0 --- 9

Younger +++ + +++ + +++ +++ + - +++ +++ 0 2

Rank Order and

Significance

Mixedgt Youngergt Broad Leafgt Coniferousgt Clear Fellgtgtgt Agriculturegt

MiresMarshesgt Freshwatergtgtgt Urbangt GrasslandMoorsgtgtgt Sparse Veg

38

South

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 + - - + - + +++ +++ +++ - 5

Broad Leaf - 0 - - + - - +++ + +++ - 7

Clear Fell + + 0 - + + + +++ + +++ + 2

Coniferous + + + 0 +++ + + +++ + +++ + 1

Freshwater - - - --- 0 - - + + +++ - 8

Grassland

Moors + + - - + 0 + + +++ + - 4

MiresMarshes - + - - + - 0 +++ + +++ - 6

Mixed --- --- --- --- - - --- 0 + + --- 10

Sparse Veg --- - - - - --- - - 0 + - 9

Urban --- --- --- --- --- - --- - - 0 --- 11

Younger + + - - + + + +++ + +++ 0 3

Rank Order

and

Significance

Coniferousgt Clear Fellgt Youngergt GrasslandMoorsgt Agriculturegt MiresMarshesgt Broad Leafgt

Freshwatergt Sparse Veggt Mixedgt Urban

Table 2 Simplified ranking matrices comparing proportional habitat use within the third order (UD50UD95) with

proportions of total available habitat types Mean value on the matrix was replaced by a sign a triple sign represents

significant deviation from random at P lt05 Highlighted habitat is ranked 1st

North

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 --- --- --- - + --- --- + +++ --- 8

Broad Leaf +++ 0 +++ + + + + + +++ +++ + 1

Clear Fell +++ --- 0 + + + - - + +++ - 5

Coniferous +++ - - 0 + + --- --- +++ +++ - 6

Freshwater + - - - 0 +++ - - +++ +++ - 7

GrasslandMoors - - - - --- 0 - - - + - 10

MiresMarshes +++ - + +++ + + 0 - +++ +++ + 3

Mixed +++ - + +++ + + + 0 +++ +++ + 2

Sparse Veg - --- - --- --- + --- --- 0 +++ --- 9

Urban --- --- --- --- --- - --- --- --- 0 --- 11

Younger +++ - + + + + - - +++ +++ 0 4

Rank Order and

Significance

Broad Leafgt Mixedgt MiresMarshesgt Youngergt Clear Fellgt Coniferousgt Freshwatergt

Agriculturegt Sparse Veggt GrasslandMoorsgt Urban

39

Central

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 --- --- + + - - - + +++ --- 7

Broad Leaf +++ 0 + +++ + + + + + +++ - 2

Clear Fell +++ - 0 +++ + + + + + +++ - 3

Coniferous - --- --- 0 + - - --- +++ + --- 8

Freshwater - - - - 0 --- - - --- - - 11

GrasslandMoors + - - + +++ 0 + - + +++ - 5

MiresMarshes + - - + + - 0 + + +++ - 6

Mixed + - - +++ + + - 0 +++ +++ - 4

Sparse Veg - - - --- +++ - - --- 0 +++ - 9

Urban --- --- --- - + --- --- --- --- 0 --- 10

Younger +++ + + +++ + + + + + +++ 0 1

Rank Order and

Significance

Youngergt Broad Leafgt Clear Fellgt Mixedgt GrasslandMoorsgt MiresMarshesgt

Agriculturegt Coniferousgtgtgt Sparse Veggtgtgt Urbangt Freshwater

South

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 - - - - - + - +++ + --- 8

Broad Leaf + 0 - --- + - + - +++ + - 6

Clear Fell + + 0 - + - + - +++ + - 4

Coniferous + +++ + 0 + + +++ + +++ + + 1

Freshwater + - - - 0 - - + + + - 7

GrasslandMoors + + + - + 0 + + + + - 3

MiresMarshes - - - --- + - 0 - + + - 9

Mixed + + + - - - + 0 + + - 5

Sparse Veg --- --- --- --- - - - - 0 + --- 10

Urban - - - - - - - - - 0 - 11

Younger +++ + + - + + + + +++ + 0 2

Rank Order and

Significance

Coniferousgt Youngergt GrasslandMoorsgt Clear Fellgt Mixedgt Broad Leafgt Freshwatergt

Agriculturegt MiresMarshesgt Sparse Veggt Urban

40

Table 3 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the GS according to Jacobs index

Ran

k North Centre South

50 95 50 95 50 95

+ - + - + - + - + - + -

1 Broad

Leaf Urban Broad Leaf Sparse Veg

Broad

Leaf Urban Mixed Urban Coniferous Urban

Grassland

Moors Urban

2 Mixed Sparse Veg Mixed Freshwater Younger Agriculture Younger Sparse Veg Younger Sparse Veg Clear Fell Mixed

3 Mires

Agriculture Grassland

Urban Clear

Fell Coniferous Broad Leaf

Grassland

Moors

Clear Fell Agriculture Coniferous Sparse Veg

Marshes Moors

4 Younger Grassland

Younger Agriculture

Freshwater Coniferous Freshwater

Broad Leaf Mires

Younger Freshwater

Moors Marshes

5 Clear

Fell Freshwater

Mires Coniferous

Sparse Veg Clear Fell Agriculture

Freshwater Agriculture

Marshes

6 Coniferous Clear Fell

Mires

Marshes

Mires

Grassland

Moors

Mires

Marshes Marshes

7 Mixed Mixed Broad Leaf

8 Grassland

Moors

41

Table 4 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the WS according to Jacobs index

Ran

k North Centre South

50 95 50 95 50 95

+ - + - + - + - + - + -

1 Mires

Marshes

Grassland

Moors Mixed Freshwater Agriculture Urban Mixed Freshwater

Grassland

Moors Urban GrasslandMoors Urban

2 Freshwater Mixed Coniferous Urban Mires

Marshes Coniferous Sparse Veg Agriculture

Sparse

Veg Coniferous Freshwater

3 Urban Coniferous Younger Grassland

Moors Freshwater Younger Urban Freshwater

Broad

Leaf Agriculture Mixed

4 Younger Agriculture Sparse Veg Broad

Leaf

Broad

Leaf

Grassland

Moors Mixed Broad Leaf

5 Clear Fell Agriculture Coniferous Agriculture Mires

Marshes Clear Fell

6 Sparse

Veg

Mires

Marshes Mixed

Mires

Marshes

Clear

Fell

Mires

Marshes

7 Broad

Leaf Clear Fell Younger Clear Fell Younger Sparse Veg

8 Clear Fell Younger

9 Sparse

Veg

10 Grassland

Moors

42

Table 5 Second order (UD95Area) individual selectionavoidance for the GS and WS according to the Jacobs index

ID GS WS

Select Avoid Select Avoid

ID004 Younger Sparsely Vegetated MiresMarshes Sparsely Vegetated

ID005 MiresMarshes Sparsely Vegetated Coniferous GrasslandMoors

ID006 Coniferous Sparsely Vegetated Mixed Freshwater

ID008 Mixed Sparsely Vegetated Mixed Freshwater

ID009 Mixed Sparsely Vegetated Mixed GrasslandMoors

ID010 MiresMarshes Freshwater GrasslandMoors Freshwater

ID012 Broad Leaf Sparsely Vegetated Coniferous Urban

ID014 Clear Fell Sparsely Vegetated GrasslandMoors Sparsely Vegetated

ID015 GrasslandMoors Urban GrasslandMoors Freshwater

ID016 GrasslandMoors Freshwater GrasslandMoors Freshwater

ID017 GrasslandMoors Mixed Sparsely Vegetated Mixed

ID019 Mixed Sparsely Vegetated Mixed Urban

ID020 Broad Leaf Sparsely Vegetated Coniferous GrasslandMoors

ID022 MiresMarshes Freshwater MiresMarshes Freshwater

ID023 MiresMarshes GrasslandMoors Mixed Freshwater

ID024 Broadleaf Urban Broad Leaf Urban

ID026 GrasslandMoors Freshwater GrasslandMoors Freshwater

ID027 GrasslandMoors Urban Sparsely Vegetated Freshwater

43 Table 6 Third order (UD50UD95) individual selectionavoidance for the GS and WS according to the Jacobs index

ID GS WS

Select Avoid Select Avoid

ID004 Broad Leaf Mixed GrasslandMoors Freshwater

ID005 Broad Leaf Freshwater Agriculture Freshwater

ID006 Clear Fell Freshwater Agriculture MiresMarshes

ID008 MiresMarshes Freshwater Agriculture Urban

ID009 Freshwater Agriculture Agriculture Freshwater

ID010 Mixed Urban Sparsely Vegetated Urban

ID012 Coniferous GrasslandMoors Freshwater Urban

ID014 Urban Agriculture Freshwater Urban

ID015 Mixed Forest Urban Clear Fell Urban

ID016 Freshwater Urban GrasslandMoors Mixed

ID017 Coniferous Mixed Coniferous Broad Leaf

ID019 Broad Leaf GrasslandMoors Urban GrasslandMoors

ID020 Freshwater Urban Freshwater Agriculture

ID022 MiresMarshes Urban Broad Leaf GrasslandMoors

ID023 Freshwater Mixed Agriculture Freshwater

ID024 Mixed Freshwater Mixed Freshwater

ID026 Mixed MiresMarshes Sparsely Vegetated GrasslandMoors

ID027 Freshwater MiresMarshes GrasslandMoors Broad Leaf

44

Fig 2 North third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)

45

Fig 3 Centre third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)

46

Fig 4 South third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)

47

Fig 5 North second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)

48

Fig 6 Centre second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)

49

Fig 7 South second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)

50

Appendix F

Background

Fig 1 Daily mean snow depth and duration during the study period (Andrew Allen)

Female Moose Reproduction

Moose are seasonal polyoestral mammals (Monfort et al 1993) coming into oestrus during late September

early October (Garel et al 2009) The Swedish moose cow population reaches puberty between the ages 25

and 35 (Sand and Cederlund 1993) during which the reproductive period begins with the onset of ovulation

The age an individual reaches puberty is dependent on their body condition they have to reach a weight

threshold to reach puberty and become reproductive (Sand 1996) If she is over the weight threshold she will

go into oestrus in the autumn If she does not reach the weight threshold then she will go into oestrus the

following autumn if successful she will give birth to individual or twin calves in late May to early June

(Ericsson et al 2001) and therefore reach sexual maturity (Malmsten et al 2014b) Fecundity is related to

both the condition and the age of the cow Cows go through senescence at 12 years of age (Ericsson et al

2001) Providing calves with the required level of nutrition demands high energy and protein resources from

the mother during senescence this becomes harder to achieve leading to decreased levels of parental care

and higher levels of calf mortality

Page 25: Habitat-performance relationships on an island: fitness ...navinderjsingh.weebly.com/uploads/1/1/2/2/11224342/... · Conditions on Öland are milder than those found in other areas

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Forchhammer MC Post E Stenseth NC Boertmann DM (2002) Long-term responses in arctic ungulate

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Gaillard JM Festa-Bianchet M Yoccoz NG (1998) Population dynamics of large herbivores variable

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Gaillard JM Festa-Bianchet M Yoccoz NG Loison A Toiumlgo C (2000a) Temporal variation in fitness

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Gaillard JM Festa-Bianchet M Delorme D Jorgenson J (2000b) Body mass and individual fitness in female

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Gaillard JM Hearingblewhite M Loison A Fuller M Powell R Basille M van Moorter B (2010) Habitat-

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Transactions of the Royal Society B 3652255-2265

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47278-285

Godvik IMR Loe LE Vik JO Veiberg V Langvatn R Mysterud A (2009) Temporal scales trade-offs and

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Gordon IJ Hester AJ Festa-Bianchet M (2004) Review The management of wild large herbivores to meet

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Hagner O Nilsson M Reese H Egberth M Olsson H (2005) Procedure for classification of forests for

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Hall LS Krausman PR Morrison ML (1997) The habitat concept and a plea for standard terminology

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Harris RB Wall WA Allendorf FW (2002) Genetic consequences of hunting what do we know and what

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Herfindal I Saeligther B-E Solberg EJ Andersen R Hoslashgda KA (2006) Population characteristics predict

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Ecology 75 (5) 1110-1118

Horne JS Garton ED Krone SM Lewis JS (2007) Analysing animal movements using Brownian bridges

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Hornok S Kovaacutets D Csoumlrgo T Meli M Goumlnczi E Hadnagy Z Takaacutecs N Farkas R Hofmann-Lehmann R

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Jacobs J (1974) Quantitative measurement of food selection a modification of the forage ratio and Ivlevrsquos

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Kaplan EL Meier P (1958) Nonparametric estimation from incomplete observation Journal of the American

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Kie JG Matthiopolos J Fieberg J Powell RA Cagnacci F Mitchell SM Gaillard JM Moorcroft PR (2010)

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Malmsten J Wideacuten DG Rydevik G Yon L Hutchings MR Thulin CG Soumlderquist L Aspan A Stuen S

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Malmsten J Soumlderquist L Thulin C Wideacuten DG Yon L Hutchings MR Dalin A (2014b) Reproductive

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Prentice HC Jonsson BO Sykes MT Ihse M Kindstroumlm M (2007) Fragmented grasslands on the Baltic

island of Ӧland Plant community composition and land-use history

R Core Team (2003) R A language and environment for statistical computing R Foundation for Statistical

Computing Vienna Austria URL httpwwwR-projectorg

Rettie WJ Messier F (2000) Hierarchical habitat selection by woodland caribou its relationship to limiting

factors Ecography 23(4)466-478

Renecker LA Hudson RJ (1989) Seasonal activity budgets of moose in Aspen-dominated boreal forests The

Journal of Wildlife Management 53(2)296-302

Roseacuten E (2006) Alvar Vegetation of Ӧland ndash Changes Monitoring and Restoration Biology and

Environment Proceedings of the Royal Academy 106387-399

Rutter SM (2007) The integration of GPS vegetation mapping and GIS in ecological and behavioural

studies Revista Brasileira de Zootecnia 3663-70

Sӕther B-E (1997) Environmental stochasticity and population dynamics of large herbivores a search for

mechanisms Trends in Ecology and Evolution 12143-149

Sӕther B-E and Heim M (1993) Ecological correlates of individual variation in age at maturity in female

moose (Alces alces) the effects of environmental variation Journal of Animal Ecology

62482-489

Sand H (1996) Life history strategies in moose (Alces alces) geographical and temporal variation in body

growth and reproduction Dissertation Swedish University of Agricultural Sciences Uppsala

Singh NJ Danell K Edenius L Ericsson G (2014) (Submitted) Tackling the motivation to Monitor success

and sustainability of a participatory monitoring programme

Smhise (2014) Snoumldjup - SMHI | SMHI [online] Available at

httpwwwsmhiseklimatdatameteorologisnosnodjup1213 [Accessed 14 Aug 2014]

Sweanor PY Sandegren F (1989) Winter-range philopatry of seasonally migratory moose Journal of

Applied Ecology 2625-33

Swenson JE Dahle B Busk H Opseth O Johansen T Soumlderberg A Wallin K Cederlund G (2007)

Predation on moose calves by European brown bears The Journal of Wildlife Management

71(6)1993-1997

Telfer ES (1970) Winter habitat selection by moose and white-tailed deer The Journal of Wildlife

Management 34(3)533-559

Testa JW (2004) Population dynamics and life history trade-offs of moose (Alces alces) in south central

Alaska Ecology 851439-1452

Torres RT Carvalho JC Panzacchi M Linnell JDC Fonseca C (2011) Comparative use of forest habitats by

roe deer and moose in a human-modified landscape in southeastern Norway during winter

Ecological Research 26(4)781-789

Tufto J Andersen R Linnell J (1996) Habitat use and ecological correlates of home range size in a small

cervid the roe deer Journal of Animal Ecology 65(6)715-724

Turchin P (2001) Complex population dynamics a theoreticalempirical synthesis New Jersey Princeton

University Press

29

Tveito OE Foslashrland EJ Alexandersson H Drebs A Jonsson T Vaarby-Laursen E (2001) Nordic climate

maps Norway CICERO

Udina IG Danilkin AA Boeskorov GG (2002) Genetic diversity of moose (Alces ales L) in Eurasia

Russian Journal of Genetics 38951-957

van Beest FM van Moorter B Milner JM (2012) Temperature-mediated habitat use and selection by a heat

sensitive northern ungulate Animal Behaviour 84(3)723-735

van Winkle W (1975) Comparision of several probabilistic home-range models Journal of Wildlife

Management 39118-123

Verme LJ Ullrey DE (1984) Physiology and nutrition White-tailed deer ecology and management (Ed By

Halls LK) pp 91-118 Stackpole Harrisburg Pennsylvania

Wattles DW DeStefano (2013) Space use and movements of moose in Massachusetts Implications for

conservation of large mammals in a fragmented environment Alces 4965-81

White RG Rowell JE Hauer WE (1997) The role of nutrition body condition and lactation on calving

success in muskoxen Journal of Zoology 24313-20

30

Appendix A

Introduction

Fig 1 Summary chart of factors affecting the life history and therefore the long term fitness of a population

Fig 2 Summary chart 2

Movement

Habitat

Climate

Topography

Competition

FoodWater

Disease

Die

Survive

Reproduce

Population long term fitness

31 Appendix B

Method and Materials

Fig 1 Summary of processes

32

Fig 2 Examples of classical kernel home range output and Brownian bridge kernel home range (Calenge 2011) The

right image includes the area between relocations ie the movement path in contrast to the classic kernel home range

in the left image

33 Appendix C

Home ranges

Fig 1 Example of a non-migratory (ID006) individuals BRB kernel area From top left annual growing and winter

season UD50 (black contour) and UD95 (red contour)

Fig 2 Example of a migratory (ID012) individuals BRB kernel area From the left annual growing and winter season

UD50 (black contour) and UD95 (red contour)

34

Table 1 Annual and seasonal UD50 and UD95 areas (ha) for all individuals

ID Annual GS WS

UD50 UD95 UD50 UD95 UD50 UD95

ID004 190 924 93 531 173 941

ID005 230 1364 132 945 72 682

ID006 162 1036 89 736 70 611

ID008 277 1536 156 809 78 738

ID009 137 834 48 295 126 653

ID010 114 682 83 448 96 488

ID012 177 963 123 544 76 545

ID014 160 1018 87 575 89 662

ID015 172 858 128 532 109 679

ID016 156 1047 65 455 92 534

ID017 153 1088 149 1043 69 349

ID019 279 1097 176 911 163 824

ID020 139 1084 67 349 160 794

ID022 159 811 131 638 61 454

ID023 187 1061 147 771 72 705

ID024 146 725 165 705 101 458

ID026 142 605 99 442 125 547

ID027 126 567 75 461 48 277

35 Appendix D

Activity

Fig 1 Mean daily movement during the study period GS 23-April-2012 to 07-Nov-2012 WS 08-Nov-2012 to

22-April-2013 (number indicates month)

Fig 2 Mean daily movement in the centre and south during the GS and WS

36

Appendix E

Habitat Proportions

Fig 1 All individualsrsquo seasonal habitat proportions within the UD95

37 Habitat Selection

Table 1 Simplified ranking matrices comparing proportional habitat use within the second order (UD95Area) with

proportions of total available habitat types Mean value on the matrix was replaced by a sign a triple sign represents

significant deviation from random at P lt05 Highlighted habitat is ranked 1st

North A

gri

cult

ure

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 --- --- - +++ --- --- --- +++ +++ --- 8

Broad Leaf +++ 0 +++ + +++ +++ +++ + +++ +++ +++ 1

Clear Fell +++ --- 0 + +++ - - --- +++ +++ --- 7

Coniferous + - - 0 +++ - - --- +++ +++ - 6

Freshwater --- --- --- --- 0 --- --- --- +++ - --- 10

Grassland

Moors +++ --- + + +++ 0 +++ - +++ +++ + 3

MiresMarshes +++ --- + + +++ --- 0 - +++ +++ --- 5

Mixed +++ - +++ +++ +++ + + 0 +++ +++ + 2

Sparse Veg --- --- --- --- --- --- --- --- 0 --- --- 11

Urban --- --- --- --- + --- --- --- +++ 0 --- 9

Younger +++ --- +++ + +++ - +++ - +++ +++ 0 4

Rank Order and

Significance

Broad Leafgt Mixedgt GrasslandMoorsgt Youngergtgtgt MiresMarshesgt Coniferousgt

Clear Fellgtgtgt Agriculturegtgtgt Urbangt Freshwatergtgtgt Sparse Veg

Central

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 --- --- --- + +++ + --- +++ +++ --- 6

Broad Leaf +++ 0 +++ + +++ +++ + - +++ +++ - 3

Clear Fell +++ --- 0 - +++ +++ + --- +++ +++ --- 5

Coniferous +++ - + 0 +++ +++ + --- +++ +++ - 4

Freshwater - --- --- --- 0 +++ - --- +++ +++ --- 8

Grassland

Moors --- --- --- --- --- 0 --- --- +++ - --- 10

MiresMarshes - - - - + +++ 0 - +++ +++ - 7

Mixed +++ + +++ +++ +++ +++ + 0 +++ +++ + 1

Sparse Veg --- --- --- --- --- --- --- --- 0 - --- 11

Urban --- --- --- --- --- + --- --- + 0 --- 9

Younger +++ + +++ + +++ +++ + - +++ +++ 0 2

Rank Order and

Significance

Mixedgt Youngergt Broad Leafgt Coniferousgt Clear Fellgtgtgt Agriculturegt

MiresMarshesgt Freshwatergtgtgt Urbangt GrasslandMoorsgtgtgt Sparse Veg

38

South

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 + - - + - + +++ +++ +++ - 5

Broad Leaf - 0 - - + - - +++ + +++ - 7

Clear Fell + + 0 - + + + +++ + +++ + 2

Coniferous + + + 0 +++ + + +++ + +++ + 1

Freshwater - - - --- 0 - - + + +++ - 8

Grassland

Moors + + - - + 0 + + +++ + - 4

MiresMarshes - + - - + - 0 +++ + +++ - 6

Mixed --- --- --- --- - - --- 0 + + --- 10

Sparse Veg --- - - - - --- - - 0 + - 9

Urban --- --- --- --- --- - --- - - 0 --- 11

Younger + + - - + + + +++ + +++ 0 3

Rank Order

and

Significance

Coniferousgt Clear Fellgt Youngergt GrasslandMoorsgt Agriculturegt MiresMarshesgt Broad Leafgt

Freshwatergt Sparse Veggt Mixedgt Urban

Table 2 Simplified ranking matrices comparing proportional habitat use within the third order (UD50UD95) with

proportions of total available habitat types Mean value on the matrix was replaced by a sign a triple sign represents

significant deviation from random at P lt05 Highlighted habitat is ranked 1st

North

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 --- --- --- - + --- --- + +++ --- 8

Broad Leaf +++ 0 +++ + + + + + +++ +++ + 1

Clear Fell +++ --- 0 + + + - - + +++ - 5

Coniferous +++ - - 0 + + --- --- +++ +++ - 6

Freshwater + - - - 0 +++ - - +++ +++ - 7

GrasslandMoors - - - - --- 0 - - - + - 10

MiresMarshes +++ - + +++ + + 0 - +++ +++ + 3

Mixed +++ - + +++ + + + 0 +++ +++ + 2

Sparse Veg - --- - --- --- + --- --- 0 +++ --- 9

Urban --- --- --- --- --- - --- --- --- 0 --- 11

Younger +++ - + + + + - - +++ +++ 0 4

Rank Order and

Significance

Broad Leafgt Mixedgt MiresMarshesgt Youngergt Clear Fellgt Coniferousgt Freshwatergt

Agriculturegt Sparse Veggt GrasslandMoorsgt Urban

39

Central

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 --- --- + + - - - + +++ --- 7

Broad Leaf +++ 0 + +++ + + + + + +++ - 2

Clear Fell +++ - 0 +++ + + + + + +++ - 3

Coniferous - --- --- 0 + - - --- +++ + --- 8

Freshwater - - - - 0 --- - - --- - - 11

GrasslandMoors + - - + +++ 0 + - + +++ - 5

MiresMarshes + - - + + - 0 + + +++ - 6

Mixed + - - +++ + + - 0 +++ +++ - 4

Sparse Veg - - - --- +++ - - --- 0 +++ - 9

Urban --- --- --- - + --- --- --- --- 0 --- 10

Younger +++ + + +++ + + + + + +++ 0 1

Rank Order and

Significance

Youngergt Broad Leafgt Clear Fellgt Mixedgt GrasslandMoorsgt MiresMarshesgt

Agriculturegt Coniferousgtgtgt Sparse Veggtgtgt Urbangt Freshwater

South

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 - - - - - + - +++ + --- 8

Broad Leaf + 0 - --- + - + - +++ + - 6

Clear Fell + + 0 - + - + - +++ + - 4

Coniferous + +++ + 0 + + +++ + +++ + + 1

Freshwater + - - - 0 - - + + + - 7

GrasslandMoors + + + - + 0 + + + + - 3

MiresMarshes - - - --- + - 0 - + + - 9

Mixed + + + - - - + 0 + + - 5

Sparse Veg --- --- --- --- - - - - 0 + --- 10

Urban - - - - - - - - - 0 - 11

Younger +++ + + - + + + + +++ + 0 2

Rank Order and

Significance

Coniferousgt Youngergt GrasslandMoorsgt Clear Fellgt Mixedgt Broad Leafgt Freshwatergt

Agriculturegt MiresMarshesgt Sparse Veggt Urban

40

Table 3 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the GS according to Jacobs index

Ran

k North Centre South

50 95 50 95 50 95

+ - + - + - + - + - + -

1 Broad

Leaf Urban Broad Leaf Sparse Veg

Broad

Leaf Urban Mixed Urban Coniferous Urban

Grassland

Moors Urban

2 Mixed Sparse Veg Mixed Freshwater Younger Agriculture Younger Sparse Veg Younger Sparse Veg Clear Fell Mixed

3 Mires

Agriculture Grassland

Urban Clear

Fell Coniferous Broad Leaf

Grassland

Moors

Clear Fell Agriculture Coniferous Sparse Veg

Marshes Moors

4 Younger Grassland

Younger Agriculture

Freshwater Coniferous Freshwater

Broad Leaf Mires

Younger Freshwater

Moors Marshes

5 Clear

Fell Freshwater

Mires Coniferous

Sparse Veg Clear Fell Agriculture

Freshwater Agriculture

Marshes

6 Coniferous Clear Fell

Mires

Marshes

Mires

Grassland

Moors

Mires

Marshes Marshes

7 Mixed Mixed Broad Leaf

8 Grassland

Moors

41

Table 4 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the WS according to Jacobs index

Ran

k North Centre South

50 95 50 95 50 95

+ - + - + - + - + - + -

1 Mires

Marshes

Grassland

Moors Mixed Freshwater Agriculture Urban Mixed Freshwater

Grassland

Moors Urban GrasslandMoors Urban

2 Freshwater Mixed Coniferous Urban Mires

Marshes Coniferous Sparse Veg Agriculture

Sparse

Veg Coniferous Freshwater

3 Urban Coniferous Younger Grassland

Moors Freshwater Younger Urban Freshwater

Broad

Leaf Agriculture Mixed

4 Younger Agriculture Sparse Veg Broad

Leaf

Broad

Leaf

Grassland

Moors Mixed Broad Leaf

5 Clear Fell Agriculture Coniferous Agriculture Mires

Marshes Clear Fell

6 Sparse

Veg

Mires

Marshes Mixed

Mires

Marshes

Clear

Fell

Mires

Marshes

7 Broad

Leaf Clear Fell Younger Clear Fell Younger Sparse Veg

8 Clear Fell Younger

9 Sparse

Veg

10 Grassland

Moors

42

Table 5 Second order (UD95Area) individual selectionavoidance for the GS and WS according to the Jacobs index

ID GS WS

Select Avoid Select Avoid

ID004 Younger Sparsely Vegetated MiresMarshes Sparsely Vegetated

ID005 MiresMarshes Sparsely Vegetated Coniferous GrasslandMoors

ID006 Coniferous Sparsely Vegetated Mixed Freshwater

ID008 Mixed Sparsely Vegetated Mixed Freshwater

ID009 Mixed Sparsely Vegetated Mixed GrasslandMoors

ID010 MiresMarshes Freshwater GrasslandMoors Freshwater

ID012 Broad Leaf Sparsely Vegetated Coniferous Urban

ID014 Clear Fell Sparsely Vegetated GrasslandMoors Sparsely Vegetated

ID015 GrasslandMoors Urban GrasslandMoors Freshwater

ID016 GrasslandMoors Freshwater GrasslandMoors Freshwater

ID017 GrasslandMoors Mixed Sparsely Vegetated Mixed

ID019 Mixed Sparsely Vegetated Mixed Urban

ID020 Broad Leaf Sparsely Vegetated Coniferous GrasslandMoors

ID022 MiresMarshes Freshwater MiresMarshes Freshwater

ID023 MiresMarshes GrasslandMoors Mixed Freshwater

ID024 Broadleaf Urban Broad Leaf Urban

ID026 GrasslandMoors Freshwater GrasslandMoors Freshwater

ID027 GrasslandMoors Urban Sparsely Vegetated Freshwater

43 Table 6 Third order (UD50UD95) individual selectionavoidance for the GS and WS according to the Jacobs index

ID GS WS

Select Avoid Select Avoid

ID004 Broad Leaf Mixed GrasslandMoors Freshwater

ID005 Broad Leaf Freshwater Agriculture Freshwater

ID006 Clear Fell Freshwater Agriculture MiresMarshes

ID008 MiresMarshes Freshwater Agriculture Urban

ID009 Freshwater Agriculture Agriculture Freshwater

ID010 Mixed Urban Sparsely Vegetated Urban

ID012 Coniferous GrasslandMoors Freshwater Urban

ID014 Urban Agriculture Freshwater Urban

ID015 Mixed Forest Urban Clear Fell Urban

ID016 Freshwater Urban GrasslandMoors Mixed

ID017 Coniferous Mixed Coniferous Broad Leaf

ID019 Broad Leaf GrasslandMoors Urban GrasslandMoors

ID020 Freshwater Urban Freshwater Agriculture

ID022 MiresMarshes Urban Broad Leaf GrasslandMoors

ID023 Freshwater Mixed Agriculture Freshwater

ID024 Mixed Freshwater Mixed Freshwater

ID026 Mixed MiresMarshes Sparsely Vegetated GrasslandMoors

ID027 Freshwater MiresMarshes GrasslandMoors Broad Leaf

44

Fig 2 North third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)

45

Fig 3 Centre third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)

46

Fig 4 South third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)

47

Fig 5 North second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)

48

Fig 6 Centre second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)

49

Fig 7 South second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)

50

Appendix F

Background

Fig 1 Daily mean snow depth and duration during the study period (Andrew Allen)

Female Moose Reproduction

Moose are seasonal polyoestral mammals (Monfort et al 1993) coming into oestrus during late September

early October (Garel et al 2009) The Swedish moose cow population reaches puberty between the ages 25

and 35 (Sand and Cederlund 1993) during which the reproductive period begins with the onset of ovulation

The age an individual reaches puberty is dependent on their body condition they have to reach a weight

threshold to reach puberty and become reproductive (Sand 1996) If she is over the weight threshold she will

go into oestrus in the autumn If she does not reach the weight threshold then she will go into oestrus the

following autumn if successful she will give birth to individual or twin calves in late May to early June

(Ericsson et al 2001) and therefore reach sexual maturity (Malmsten et al 2014b) Fecundity is related to

both the condition and the age of the cow Cows go through senescence at 12 years of age (Ericsson et al

2001) Providing calves with the required level of nutrition demands high energy and protein resources from

the mother during senescence this becomes harder to achieve leading to decreased levels of parental care

and higher levels of calf mortality

Page 26: Habitat-performance relationships on an island: fitness ...navinderjsingh.weebly.com/uploads/1/1/2/2/11224342/... · Conditions on Öland are milder than those found in other areas

26

Jacobs J (1974) Quantitative measurement of food selection a modification of the forage ratio and Ivlevrsquos

Electivity Index Oecologia 14(4)413-417

Jenkins KJ Manly FJ (2008) A double-observer method for reducing bias in faecal pellet surveys of forest

ungulates Journal of Applied Ecology 451339-1348

Johnson DH (1980) The comparison of usage and availability measurements for evaluating resource

preference Ecology 6165-71

Jonsson F (2007) rsquoDen oumllaumlndska aringlgstammens foumlrvaltingrsquo Departement of Wildlife Fish and Environmental

Studies SLU Examensarbete I aumlmnet biologi vol 20072

Kaplan EL Meier P (1958) Nonparametric estimation from incomplete observation Journal of the American

Statistical Association 53457-481

Keating KA Cherry S (2009) Modelling utilization distributions in space and time Ecology 90(7)1971-

1980

Kie JG Matthiopolos J Fieberg J Powell RA Cagnacci F Mitchell SM Gaillard JM Moorcroft PR (2010)

The home range concept are traditional estimators still relevant with modern telemetry

technology Philosophical Transactions of the Royal Society B 3652221-2231

Kindberg J Holmqvist N Bergqvist G (2009) Hunting bag statistics 2007-2008 [In Swedish] In

Viltoumlvervakningen 20072008 (Annual wildlife surveillance report) Viltforum Svenska

Jaumlgarefoumlrbundet Oumlster-Malma 20092

Kranstauber B Kays R LaPoint SD Wikelski M Safi K (2012) A dynamic Brownian bridge movement

model to estimate utilization distributions for heterogeneous Animal movement Journal of

Animal Ecology 81738-746

Laurian C Ouellet JP Courtois R Breton L St-Onge S (2000) Effects of intensive harvesting on moose

reproduction Journal of Applied Ecology 37515-531

Laurian C Dussault C Ouellet JP Courtois R Poulin M Breton L (2008) Behaviour of moose relative to a

road network The Journal of Wildlife Management 72(7)1550-1557

Lavsund S Nygreacuten T Solberg EJ (2003) Status of moose populations and challenges to moose management

in Fennoscandia Alces 39109-130

Lenarz MS Fieberg J Schrage MW Edwards AJ (2010) Living on the edge viability of moose in

northeastern Minnesota The Journal of Wildlife Management 74(5)1013-1023

Lindstroumlm J (1999) Early development and fitness in birds and mammals Trends in Ecology and Evolution

14343-348

Linnell JDC Aanes R Andersen R (1995) Who killed Bambi The role of predation in the neonatal

mortality of temperate ungulates Wildlife Biology 1209-223

Lomas LA Bender LC (2007) Survival and cause-specific mortality of neonatal mule deer fawns north-

central New Mexico Journal of Wildlife Management 71884ndash894

Lynch GM Morgantini LE (1984) Sex and age differential in seasonal home range size of moose in

northcentral Alberta 1971-1979 Alces 2061-78

MacCracken JG Ballenberghe VV Peek JM (1993) Use of aquatic plants by moose sodium hunger or

foraging efficiency Canadian Journal of Zoology 71(12)2345-2351

27

Malmsten J Wideacuten DG Rydevik G Yon L Hutchings MR Thulin CG Soumlderquist L Aspan A Stuen S

Dalin AM (2013) Temporal and spatial variation in Anaplasma phagocytophilum infection in

Swedish moose (Alces alces) Epidemiology and Infection 1421205-1213

Malmsten J (2014a) lsquoReproduction and health of moose in southern Swedenrsquo Doctoral thesis Swedish

University of Agricultural Sciences (SLU) Umearing

Malmsten J Soumlderquist L Thulin C Wideacuten DG Yon L Hutchings MR Dalin A (2014b) Reproductive

characteristics in female Swedish moose (Alces alces) with emphasis on puberty timing of

oestrus and mating Acta Veterinaria Scandinavica 5623

Marsh DM Hanlon TJ (2004) Observer gender and observation bias in animal behaviour research

experimental tests with red-backed salamanders Animal Behaviour 681425-1433

Maringrell A Hofgaard A Danell K (2006) Nutrient dynamics of reindeer forage species along snowmelt

gradients as different ecological scales Basic and Applied Ecology 713-30

McLoughlin PD Vander Wal E Lowe SJ Patterson BR Murray DL (2011) Seasonal shifts in habitat

selection of a large herbivore and the influence of human activity Basic and Applied Ecology

12(8) 654-663

Milner JM Nilsen EB and Andreassen HP (2007) Demographic side effects of selective hunting in ungulates

and carnivores Conservation Biology 2136-47

Modafferi RD and Becker EF (1997) Survival of radio collared adult moose in lower Susitna River Valley

south-central Alaska The Journal of Wildlife Management 61(2)540-549

Monfort SL Schwartz CC Wasser SK (1993) Monitoring reproduction in captive moose using urinary and

faecal steroid metabolites The Journal of Wildlife Management 57400-407

Monteith KL Klaver R Hersey K Holland A Thomas T Kauffman M In press Effects of climate and

plant phenology on recruitment of moose at the southern extent of their range

Morales JM Moorcroft PR Matthiopoulos J Frair JL Kie JG Powell RA Merrill EH Haydon DT (2010)

Building the bridge between animal movement and population dynamics Philosophical

Transactions of the Royal Society B 3652289-230

Morellet N Bonenfant C Boumlrger L Ossi F Cagnacci F Heurich M Kjellander P Linnell JDC Nicoloso S

Sustr P Urbano F Mysterud A (2013) Seasonality weather and climate affect home range

size in roe deer across a wide latitudinal gradient within Europe 821326-1339

Mysterud A Oslashstbye E (1999) Cover as a habitat element for temperate ungulates effects on habitat selection

and demography Wildlife Society Bulletin 27(2)385-394

Mysterud A Peacuterez-Barberiacutea FJ Gordon IJ (2001) The effect of season sex and feeding style on home range

area versus body mass scaling in temperate ruminants Oecologia 12730-39

Mysterud A Solberg EJ Yoccoz NG (2005) Ageing and reproductive effort in male moose under variable

levels of intrasexual competition Journal of Animal Ecology 74742-754

Osko TJ Hiltz MN Hudson RJ Wasel SM (2004) Moose habitat preferences in response to changing

availably Journal of Wildlife Management 68(3)576-584

Philips RL Berg WE Siniff DB (1973) Moose movement patterns and range use in northern Minnesota The

Journal of Wildlife Management 37(3)266-278

28

Prentice HC Jonsson BO Sykes MT Ihse M Kindstroumlm M (2007) Fragmented grasslands on the Baltic

island of Ӧland Plant community composition and land-use history

R Core Team (2003) R A language and environment for statistical computing R Foundation for Statistical

Computing Vienna Austria URL httpwwwR-projectorg

Rettie WJ Messier F (2000) Hierarchical habitat selection by woodland caribou its relationship to limiting

factors Ecography 23(4)466-478

Renecker LA Hudson RJ (1989) Seasonal activity budgets of moose in Aspen-dominated boreal forests The

Journal of Wildlife Management 53(2)296-302

Roseacuten E (2006) Alvar Vegetation of Ӧland ndash Changes Monitoring and Restoration Biology and

Environment Proceedings of the Royal Academy 106387-399

Rutter SM (2007) The integration of GPS vegetation mapping and GIS in ecological and behavioural

studies Revista Brasileira de Zootecnia 3663-70

Sӕther B-E (1997) Environmental stochasticity and population dynamics of large herbivores a search for

mechanisms Trends in Ecology and Evolution 12143-149

Sӕther B-E and Heim M (1993) Ecological correlates of individual variation in age at maturity in female

moose (Alces alces) the effects of environmental variation Journal of Animal Ecology

62482-489

Sand H (1996) Life history strategies in moose (Alces alces) geographical and temporal variation in body

growth and reproduction Dissertation Swedish University of Agricultural Sciences Uppsala

Singh NJ Danell K Edenius L Ericsson G (2014) (Submitted) Tackling the motivation to Monitor success

and sustainability of a participatory monitoring programme

Smhise (2014) Snoumldjup - SMHI | SMHI [online] Available at

httpwwwsmhiseklimatdatameteorologisnosnodjup1213 [Accessed 14 Aug 2014]

Sweanor PY Sandegren F (1989) Winter-range philopatry of seasonally migratory moose Journal of

Applied Ecology 2625-33

Swenson JE Dahle B Busk H Opseth O Johansen T Soumlderberg A Wallin K Cederlund G (2007)

Predation on moose calves by European brown bears The Journal of Wildlife Management

71(6)1993-1997

Telfer ES (1970) Winter habitat selection by moose and white-tailed deer The Journal of Wildlife

Management 34(3)533-559

Testa JW (2004) Population dynamics and life history trade-offs of moose (Alces alces) in south central

Alaska Ecology 851439-1452

Torres RT Carvalho JC Panzacchi M Linnell JDC Fonseca C (2011) Comparative use of forest habitats by

roe deer and moose in a human-modified landscape in southeastern Norway during winter

Ecological Research 26(4)781-789

Tufto J Andersen R Linnell J (1996) Habitat use and ecological correlates of home range size in a small

cervid the roe deer Journal of Animal Ecology 65(6)715-724

Turchin P (2001) Complex population dynamics a theoreticalempirical synthesis New Jersey Princeton

University Press

29

Tveito OE Foslashrland EJ Alexandersson H Drebs A Jonsson T Vaarby-Laursen E (2001) Nordic climate

maps Norway CICERO

Udina IG Danilkin AA Boeskorov GG (2002) Genetic diversity of moose (Alces ales L) in Eurasia

Russian Journal of Genetics 38951-957

van Beest FM van Moorter B Milner JM (2012) Temperature-mediated habitat use and selection by a heat

sensitive northern ungulate Animal Behaviour 84(3)723-735

van Winkle W (1975) Comparision of several probabilistic home-range models Journal of Wildlife

Management 39118-123

Verme LJ Ullrey DE (1984) Physiology and nutrition White-tailed deer ecology and management (Ed By

Halls LK) pp 91-118 Stackpole Harrisburg Pennsylvania

Wattles DW DeStefano (2013) Space use and movements of moose in Massachusetts Implications for

conservation of large mammals in a fragmented environment Alces 4965-81

White RG Rowell JE Hauer WE (1997) The role of nutrition body condition and lactation on calving

success in muskoxen Journal of Zoology 24313-20

30

Appendix A

Introduction

Fig 1 Summary chart of factors affecting the life history and therefore the long term fitness of a population

Fig 2 Summary chart 2

Movement

Habitat

Climate

Topography

Competition

FoodWater

Disease

Die

Survive

Reproduce

Population long term fitness

31 Appendix B

Method and Materials

Fig 1 Summary of processes

32

Fig 2 Examples of classical kernel home range output and Brownian bridge kernel home range (Calenge 2011) The

right image includes the area between relocations ie the movement path in contrast to the classic kernel home range

in the left image

33 Appendix C

Home ranges

Fig 1 Example of a non-migratory (ID006) individuals BRB kernel area From top left annual growing and winter

season UD50 (black contour) and UD95 (red contour)

Fig 2 Example of a migratory (ID012) individuals BRB kernel area From the left annual growing and winter season

UD50 (black contour) and UD95 (red contour)

34

Table 1 Annual and seasonal UD50 and UD95 areas (ha) for all individuals

ID Annual GS WS

UD50 UD95 UD50 UD95 UD50 UD95

ID004 190 924 93 531 173 941

ID005 230 1364 132 945 72 682

ID006 162 1036 89 736 70 611

ID008 277 1536 156 809 78 738

ID009 137 834 48 295 126 653

ID010 114 682 83 448 96 488

ID012 177 963 123 544 76 545

ID014 160 1018 87 575 89 662

ID015 172 858 128 532 109 679

ID016 156 1047 65 455 92 534

ID017 153 1088 149 1043 69 349

ID019 279 1097 176 911 163 824

ID020 139 1084 67 349 160 794

ID022 159 811 131 638 61 454

ID023 187 1061 147 771 72 705

ID024 146 725 165 705 101 458

ID026 142 605 99 442 125 547

ID027 126 567 75 461 48 277

35 Appendix D

Activity

Fig 1 Mean daily movement during the study period GS 23-April-2012 to 07-Nov-2012 WS 08-Nov-2012 to

22-April-2013 (number indicates month)

Fig 2 Mean daily movement in the centre and south during the GS and WS

36

Appendix E

Habitat Proportions

Fig 1 All individualsrsquo seasonal habitat proportions within the UD95

37 Habitat Selection

Table 1 Simplified ranking matrices comparing proportional habitat use within the second order (UD95Area) with

proportions of total available habitat types Mean value on the matrix was replaced by a sign a triple sign represents

significant deviation from random at P lt05 Highlighted habitat is ranked 1st

North A

gri

cult

ure

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 --- --- - +++ --- --- --- +++ +++ --- 8

Broad Leaf +++ 0 +++ + +++ +++ +++ + +++ +++ +++ 1

Clear Fell +++ --- 0 + +++ - - --- +++ +++ --- 7

Coniferous + - - 0 +++ - - --- +++ +++ - 6

Freshwater --- --- --- --- 0 --- --- --- +++ - --- 10

Grassland

Moors +++ --- + + +++ 0 +++ - +++ +++ + 3

MiresMarshes +++ --- + + +++ --- 0 - +++ +++ --- 5

Mixed +++ - +++ +++ +++ + + 0 +++ +++ + 2

Sparse Veg --- --- --- --- --- --- --- --- 0 --- --- 11

Urban --- --- --- --- + --- --- --- +++ 0 --- 9

Younger +++ --- +++ + +++ - +++ - +++ +++ 0 4

Rank Order and

Significance

Broad Leafgt Mixedgt GrasslandMoorsgt Youngergtgtgt MiresMarshesgt Coniferousgt

Clear Fellgtgtgt Agriculturegtgtgt Urbangt Freshwatergtgtgt Sparse Veg

Central

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 --- --- --- + +++ + --- +++ +++ --- 6

Broad Leaf +++ 0 +++ + +++ +++ + - +++ +++ - 3

Clear Fell +++ --- 0 - +++ +++ + --- +++ +++ --- 5

Coniferous +++ - + 0 +++ +++ + --- +++ +++ - 4

Freshwater - --- --- --- 0 +++ - --- +++ +++ --- 8

Grassland

Moors --- --- --- --- --- 0 --- --- +++ - --- 10

MiresMarshes - - - - + +++ 0 - +++ +++ - 7

Mixed +++ + +++ +++ +++ +++ + 0 +++ +++ + 1

Sparse Veg --- --- --- --- --- --- --- --- 0 - --- 11

Urban --- --- --- --- --- + --- --- + 0 --- 9

Younger +++ + +++ + +++ +++ + - +++ +++ 0 2

Rank Order and

Significance

Mixedgt Youngergt Broad Leafgt Coniferousgt Clear Fellgtgtgt Agriculturegt

MiresMarshesgt Freshwatergtgtgt Urbangt GrasslandMoorsgtgtgt Sparse Veg

38

South

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 + - - + - + +++ +++ +++ - 5

Broad Leaf - 0 - - + - - +++ + +++ - 7

Clear Fell + + 0 - + + + +++ + +++ + 2

Coniferous + + + 0 +++ + + +++ + +++ + 1

Freshwater - - - --- 0 - - + + +++ - 8

Grassland

Moors + + - - + 0 + + +++ + - 4

MiresMarshes - + - - + - 0 +++ + +++ - 6

Mixed --- --- --- --- - - --- 0 + + --- 10

Sparse Veg --- - - - - --- - - 0 + - 9

Urban --- --- --- --- --- - --- - - 0 --- 11

Younger + + - - + + + +++ + +++ 0 3

Rank Order

and

Significance

Coniferousgt Clear Fellgt Youngergt GrasslandMoorsgt Agriculturegt MiresMarshesgt Broad Leafgt

Freshwatergt Sparse Veggt Mixedgt Urban

Table 2 Simplified ranking matrices comparing proportional habitat use within the third order (UD50UD95) with

proportions of total available habitat types Mean value on the matrix was replaced by a sign a triple sign represents

significant deviation from random at P lt05 Highlighted habitat is ranked 1st

North

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 --- --- --- - + --- --- + +++ --- 8

Broad Leaf +++ 0 +++ + + + + + +++ +++ + 1

Clear Fell +++ --- 0 + + + - - + +++ - 5

Coniferous +++ - - 0 + + --- --- +++ +++ - 6

Freshwater + - - - 0 +++ - - +++ +++ - 7

GrasslandMoors - - - - --- 0 - - - + - 10

MiresMarshes +++ - + +++ + + 0 - +++ +++ + 3

Mixed +++ - + +++ + + + 0 +++ +++ + 2

Sparse Veg - --- - --- --- + --- --- 0 +++ --- 9

Urban --- --- --- --- --- - --- --- --- 0 --- 11

Younger +++ - + + + + - - +++ +++ 0 4

Rank Order and

Significance

Broad Leafgt Mixedgt MiresMarshesgt Youngergt Clear Fellgt Coniferousgt Freshwatergt

Agriculturegt Sparse Veggt GrasslandMoorsgt Urban

39

Central

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 --- --- + + - - - + +++ --- 7

Broad Leaf +++ 0 + +++ + + + + + +++ - 2

Clear Fell +++ - 0 +++ + + + + + +++ - 3

Coniferous - --- --- 0 + - - --- +++ + --- 8

Freshwater - - - - 0 --- - - --- - - 11

GrasslandMoors + - - + +++ 0 + - + +++ - 5

MiresMarshes + - - + + - 0 + + +++ - 6

Mixed + - - +++ + + - 0 +++ +++ - 4

Sparse Veg - - - --- +++ - - --- 0 +++ - 9

Urban --- --- --- - + --- --- --- --- 0 --- 10

Younger +++ + + +++ + + + + + +++ 0 1

Rank Order and

Significance

Youngergt Broad Leafgt Clear Fellgt Mixedgt GrasslandMoorsgt MiresMarshesgt

Agriculturegt Coniferousgtgtgt Sparse Veggtgtgt Urbangt Freshwater

South

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 - - - - - + - +++ + --- 8

Broad Leaf + 0 - --- + - + - +++ + - 6

Clear Fell + + 0 - + - + - +++ + - 4

Coniferous + +++ + 0 + + +++ + +++ + + 1

Freshwater + - - - 0 - - + + + - 7

GrasslandMoors + + + - + 0 + + + + - 3

MiresMarshes - - - --- + - 0 - + + - 9

Mixed + + + - - - + 0 + + - 5

Sparse Veg --- --- --- --- - - - - 0 + --- 10

Urban - - - - - - - - - 0 - 11

Younger +++ + + - + + + + +++ + 0 2

Rank Order and

Significance

Coniferousgt Youngergt GrasslandMoorsgt Clear Fellgt Mixedgt Broad Leafgt Freshwatergt

Agriculturegt MiresMarshesgt Sparse Veggt Urban

40

Table 3 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the GS according to Jacobs index

Ran

k North Centre South

50 95 50 95 50 95

+ - + - + - + - + - + -

1 Broad

Leaf Urban Broad Leaf Sparse Veg

Broad

Leaf Urban Mixed Urban Coniferous Urban

Grassland

Moors Urban

2 Mixed Sparse Veg Mixed Freshwater Younger Agriculture Younger Sparse Veg Younger Sparse Veg Clear Fell Mixed

3 Mires

Agriculture Grassland

Urban Clear

Fell Coniferous Broad Leaf

Grassland

Moors

Clear Fell Agriculture Coniferous Sparse Veg

Marshes Moors

4 Younger Grassland

Younger Agriculture

Freshwater Coniferous Freshwater

Broad Leaf Mires

Younger Freshwater

Moors Marshes

5 Clear

Fell Freshwater

Mires Coniferous

Sparse Veg Clear Fell Agriculture

Freshwater Agriculture

Marshes

6 Coniferous Clear Fell

Mires

Marshes

Mires

Grassland

Moors

Mires

Marshes Marshes

7 Mixed Mixed Broad Leaf

8 Grassland

Moors

41

Table 4 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the WS according to Jacobs index

Ran

k North Centre South

50 95 50 95 50 95

+ - + - + - + - + - + -

1 Mires

Marshes

Grassland

Moors Mixed Freshwater Agriculture Urban Mixed Freshwater

Grassland

Moors Urban GrasslandMoors Urban

2 Freshwater Mixed Coniferous Urban Mires

Marshes Coniferous Sparse Veg Agriculture

Sparse

Veg Coniferous Freshwater

3 Urban Coniferous Younger Grassland

Moors Freshwater Younger Urban Freshwater

Broad

Leaf Agriculture Mixed

4 Younger Agriculture Sparse Veg Broad

Leaf

Broad

Leaf

Grassland

Moors Mixed Broad Leaf

5 Clear Fell Agriculture Coniferous Agriculture Mires

Marshes Clear Fell

6 Sparse

Veg

Mires

Marshes Mixed

Mires

Marshes

Clear

Fell

Mires

Marshes

7 Broad

Leaf Clear Fell Younger Clear Fell Younger Sparse Veg

8 Clear Fell Younger

9 Sparse

Veg

10 Grassland

Moors

42

Table 5 Second order (UD95Area) individual selectionavoidance for the GS and WS according to the Jacobs index

ID GS WS

Select Avoid Select Avoid

ID004 Younger Sparsely Vegetated MiresMarshes Sparsely Vegetated

ID005 MiresMarshes Sparsely Vegetated Coniferous GrasslandMoors

ID006 Coniferous Sparsely Vegetated Mixed Freshwater

ID008 Mixed Sparsely Vegetated Mixed Freshwater

ID009 Mixed Sparsely Vegetated Mixed GrasslandMoors

ID010 MiresMarshes Freshwater GrasslandMoors Freshwater

ID012 Broad Leaf Sparsely Vegetated Coniferous Urban

ID014 Clear Fell Sparsely Vegetated GrasslandMoors Sparsely Vegetated

ID015 GrasslandMoors Urban GrasslandMoors Freshwater

ID016 GrasslandMoors Freshwater GrasslandMoors Freshwater

ID017 GrasslandMoors Mixed Sparsely Vegetated Mixed

ID019 Mixed Sparsely Vegetated Mixed Urban

ID020 Broad Leaf Sparsely Vegetated Coniferous GrasslandMoors

ID022 MiresMarshes Freshwater MiresMarshes Freshwater

ID023 MiresMarshes GrasslandMoors Mixed Freshwater

ID024 Broadleaf Urban Broad Leaf Urban

ID026 GrasslandMoors Freshwater GrasslandMoors Freshwater

ID027 GrasslandMoors Urban Sparsely Vegetated Freshwater

43 Table 6 Third order (UD50UD95) individual selectionavoidance for the GS and WS according to the Jacobs index

ID GS WS

Select Avoid Select Avoid

ID004 Broad Leaf Mixed GrasslandMoors Freshwater

ID005 Broad Leaf Freshwater Agriculture Freshwater

ID006 Clear Fell Freshwater Agriculture MiresMarshes

ID008 MiresMarshes Freshwater Agriculture Urban

ID009 Freshwater Agriculture Agriculture Freshwater

ID010 Mixed Urban Sparsely Vegetated Urban

ID012 Coniferous GrasslandMoors Freshwater Urban

ID014 Urban Agriculture Freshwater Urban

ID015 Mixed Forest Urban Clear Fell Urban

ID016 Freshwater Urban GrasslandMoors Mixed

ID017 Coniferous Mixed Coniferous Broad Leaf

ID019 Broad Leaf GrasslandMoors Urban GrasslandMoors

ID020 Freshwater Urban Freshwater Agriculture

ID022 MiresMarshes Urban Broad Leaf GrasslandMoors

ID023 Freshwater Mixed Agriculture Freshwater

ID024 Mixed Freshwater Mixed Freshwater

ID026 Mixed MiresMarshes Sparsely Vegetated GrasslandMoors

ID027 Freshwater MiresMarshes GrasslandMoors Broad Leaf

44

Fig 2 North third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)

45

Fig 3 Centre third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)

46

Fig 4 South third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)

47

Fig 5 North second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)

48

Fig 6 Centre second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)

49

Fig 7 South second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)

50

Appendix F

Background

Fig 1 Daily mean snow depth and duration during the study period (Andrew Allen)

Female Moose Reproduction

Moose are seasonal polyoestral mammals (Monfort et al 1993) coming into oestrus during late September

early October (Garel et al 2009) The Swedish moose cow population reaches puberty between the ages 25

and 35 (Sand and Cederlund 1993) during which the reproductive period begins with the onset of ovulation

The age an individual reaches puberty is dependent on their body condition they have to reach a weight

threshold to reach puberty and become reproductive (Sand 1996) If she is over the weight threshold she will

go into oestrus in the autumn If she does not reach the weight threshold then she will go into oestrus the

following autumn if successful she will give birth to individual or twin calves in late May to early June

(Ericsson et al 2001) and therefore reach sexual maturity (Malmsten et al 2014b) Fecundity is related to

both the condition and the age of the cow Cows go through senescence at 12 years of age (Ericsson et al

2001) Providing calves with the required level of nutrition demands high energy and protein resources from

the mother during senescence this becomes harder to achieve leading to decreased levels of parental care

and higher levels of calf mortality

Page 27: Habitat-performance relationships on an island: fitness ...navinderjsingh.weebly.com/uploads/1/1/2/2/11224342/... · Conditions on Öland are milder than those found in other areas

27

Malmsten J Wideacuten DG Rydevik G Yon L Hutchings MR Thulin CG Soumlderquist L Aspan A Stuen S

Dalin AM (2013) Temporal and spatial variation in Anaplasma phagocytophilum infection in

Swedish moose (Alces alces) Epidemiology and Infection 1421205-1213

Malmsten J (2014a) lsquoReproduction and health of moose in southern Swedenrsquo Doctoral thesis Swedish

University of Agricultural Sciences (SLU) Umearing

Malmsten J Soumlderquist L Thulin C Wideacuten DG Yon L Hutchings MR Dalin A (2014b) Reproductive

characteristics in female Swedish moose (Alces alces) with emphasis on puberty timing of

oestrus and mating Acta Veterinaria Scandinavica 5623

Marsh DM Hanlon TJ (2004) Observer gender and observation bias in animal behaviour research

experimental tests with red-backed salamanders Animal Behaviour 681425-1433

Maringrell A Hofgaard A Danell K (2006) Nutrient dynamics of reindeer forage species along snowmelt

gradients as different ecological scales Basic and Applied Ecology 713-30

McLoughlin PD Vander Wal E Lowe SJ Patterson BR Murray DL (2011) Seasonal shifts in habitat

selection of a large herbivore and the influence of human activity Basic and Applied Ecology

12(8) 654-663

Milner JM Nilsen EB and Andreassen HP (2007) Demographic side effects of selective hunting in ungulates

and carnivores Conservation Biology 2136-47

Modafferi RD and Becker EF (1997) Survival of radio collared adult moose in lower Susitna River Valley

south-central Alaska The Journal of Wildlife Management 61(2)540-549

Monfort SL Schwartz CC Wasser SK (1993) Monitoring reproduction in captive moose using urinary and

faecal steroid metabolites The Journal of Wildlife Management 57400-407

Monteith KL Klaver R Hersey K Holland A Thomas T Kauffman M In press Effects of climate and

plant phenology on recruitment of moose at the southern extent of their range

Morales JM Moorcroft PR Matthiopoulos J Frair JL Kie JG Powell RA Merrill EH Haydon DT (2010)

Building the bridge between animal movement and population dynamics Philosophical

Transactions of the Royal Society B 3652289-230

Morellet N Bonenfant C Boumlrger L Ossi F Cagnacci F Heurich M Kjellander P Linnell JDC Nicoloso S

Sustr P Urbano F Mysterud A (2013) Seasonality weather and climate affect home range

size in roe deer across a wide latitudinal gradient within Europe 821326-1339

Mysterud A Oslashstbye E (1999) Cover as a habitat element for temperate ungulates effects on habitat selection

and demography Wildlife Society Bulletin 27(2)385-394

Mysterud A Peacuterez-Barberiacutea FJ Gordon IJ (2001) The effect of season sex and feeding style on home range

area versus body mass scaling in temperate ruminants Oecologia 12730-39

Mysterud A Solberg EJ Yoccoz NG (2005) Ageing and reproductive effort in male moose under variable

levels of intrasexual competition Journal of Animal Ecology 74742-754

Osko TJ Hiltz MN Hudson RJ Wasel SM (2004) Moose habitat preferences in response to changing

availably Journal of Wildlife Management 68(3)576-584

Philips RL Berg WE Siniff DB (1973) Moose movement patterns and range use in northern Minnesota The

Journal of Wildlife Management 37(3)266-278

28

Prentice HC Jonsson BO Sykes MT Ihse M Kindstroumlm M (2007) Fragmented grasslands on the Baltic

island of Ӧland Plant community composition and land-use history

R Core Team (2003) R A language and environment for statistical computing R Foundation for Statistical

Computing Vienna Austria URL httpwwwR-projectorg

Rettie WJ Messier F (2000) Hierarchical habitat selection by woodland caribou its relationship to limiting

factors Ecography 23(4)466-478

Renecker LA Hudson RJ (1989) Seasonal activity budgets of moose in Aspen-dominated boreal forests The

Journal of Wildlife Management 53(2)296-302

Roseacuten E (2006) Alvar Vegetation of Ӧland ndash Changes Monitoring and Restoration Biology and

Environment Proceedings of the Royal Academy 106387-399

Rutter SM (2007) The integration of GPS vegetation mapping and GIS in ecological and behavioural

studies Revista Brasileira de Zootecnia 3663-70

Sӕther B-E (1997) Environmental stochasticity and population dynamics of large herbivores a search for

mechanisms Trends in Ecology and Evolution 12143-149

Sӕther B-E and Heim M (1993) Ecological correlates of individual variation in age at maturity in female

moose (Alces alces) the effects of environmental variation Journal of Animal Ecology

62482-489

Sand H (1996) Life history strategies in moose (Alces alces) geographical and temporal variation in body

growth and reproduction Dissertation Swedish University of Agricultural Sciences Uppsala

Singh NJ Danell K Edenius L Ericsson G (2014) (Submitted) Tackling the motivation to Monitor success

and sustainability of a participatory monitoring programme

Smhise (2014) Snoumldjup - SMHI | SMHI [online] Available at

httpwwwsmhiseklimatdatameteorologisnosnodjup1213 [Accessed 14 Aug 2014]

Sweanor PY Sandegren F (1989) Winter-range philopatry of seasonally migratory moose Journal of

Applied Ecology 2625-33

Swenson JE Dahle B Busk H Opseth O Johansen T Soumlderberg A Wallin K Cederlund G (2007)

Predation on moose calves by European brown bears The Journal of Wildlife Management

71(6)1993-1997

Telfer ES (1970) Winter habitat selection by moose and white-tailed deer The Journal of Wildlife

Management 34(3)533-559

Testa JW (2004) Population dynamics and life history trade-offs of moose (Alces alces) in south central

Alaska Ecology 851439-1452

Torres RT Carvalho JC Panzacchi M Linnell JDC Fonseca C (2011) Comparative use of forest habitats by

roe deer and moose in a human-modified landscape in southeastern Norway during winter

Ecological Research 26(4)781-789

Tufto J Andersen R Linnell J (1996) Habitat use and ecological correlates of home range size in a small

cervid the roe deer Journal of Animal Ecology 65(6)715-724

Turchin P (2001) Complex population dynamics a theoreticalempirical synthesis New Jersey Princeton

University Press

29

Tveito OE Foslashrland EJ Alexandersson H Drebs A Jonsson T Vaarby-Laursen E (2001) Nordic climate

maps Norway CICERO

Udina IG Danilkin AA Boeskorov GG (2002) Genetic diversity of moose (Alces ales L) in Eurasia

Russian Journal of Genetics 38951-957

van Beest FM van Moorter B Milner JM (2012) Temperature-mediated habitat use and selection by a heat

sensitive northern ungulate Animal Behaviour 84(3)723-735

van Winkle W (1975) Comparision of several probabilistic home-range models Journal of Wildlife

Management 39118-123

Verme LJ Ullrey DE (1984) Physiology and nutrition White-tailed deer ecology and management (Ed By

Halls LK) pp 91-118 Stackpole Harrisburg Pennsylvania

Wattles DW DeStefano (2013) Space use and movements of moose in Massachusetts Implications for

conservation of large mammals in a fragmented environment Alces 4965-81

White RG Rowell JE Hauer WE (1997) The role of nutrition body condition and lactation on calving

success in muskoxen Journal of Zoology 24313-20

30

Appendix A

Introduction

Fig 1 Summary chart of factors affecting the life history and therefore the long term fitness of a population

Fig 2 Summary chart 2

Movement

Habitat

Climate

Topography

Competition

FoodWater

Disease

Die

Survive

Reproduce

Population long term fitness

31 Appendix B

Method and Materials

Fig 1 Summary of processes

32

Fig 2 Examples of classical kernel home range output and Brownian bridge kernel home range (Calenge 2011) The

right image includes the area between relocations ie the movement path in contrast to the classic kernel home range

in the left image

33 Appendix C

Home ranges

Fig 1 Example of a non-migratory (ID006) individuals BRB kernel area From top left annual growing and winter

season UD50 (black contour) and UD95 (red contour)

Fig 2 Example of a migratory (ID012) individuals BRB kernel area From the left annual growing and winter season

UD50 (black contour) and UD95 (red contour)

34

Table 1 Annual and seasonal UD50 and UD95 areas (ha) for all individuals

ID Annual GS WS

UD50 UD95 UD50 UD95 UD50 UD95

ID004 190 924 93 531 173 941

ID005 230 1364 132 945 72 682

ID006 162 1036 89 736 70 611

ID008 277 1536 156 809 78 738

ID009 137 834 48 295 126 653

ID010 114 682 83 448 96 488

ID012 177 963 123 544 76 545

ID014 160 1018 87 575 89 662

ID015 172 858 128 532 109 679

ID016 156 1047 65 455 92 534

ID017 153 1088 149 1043 69 349

ID019 279 1097 176 911 163 824

ID020 139 1084 67 349 160 794

ID022 159 811 131 638 61 454

ID023 187 1061 147 771 72 705

ID024 146 725 165 705 101 458

ID026 142 605 99 442 125 547

ID027 126 567 75 461 48 277

35 Appendix D

Activity

Fig 1 Mean daily movement during the study period GS 23-April-2012 to 07-Nov-2012 WS 08-Nov-2012 to

22-April-2013 (number indicates month)

Fig 2 Mean daily movement in the centre and south during the GS and WS

36

Appendix E

Habitat Proportions

Fig 1 All individualsrsquo seasonal habitat proportions within the UD95

37 Habitat Selection

Table 1 Simplified ranking matrices comparing proportional habitat use within the second order (UD95Area) with

proportions of total available habitat types Mean value on the matrix was replaced by a sign a triple sign represents

significant deviation from random at P lt05 Highlighted habitat is ranked 1st

North A

gri

cult

ure

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 --- --- - +++ --- --- --- +++ +++ --- 8

Broad Leaf +++ 0 +++ + +++ +++ +++ + +++ +++ +++ 1

Clear Fell +++ --- 0 + +++ - - --- +++ +++ --- 7

Coniferous + - - 0 +++ - - --- +++ +++ - 6

Freshwater --- --- --- --- 0 --- --- --- +++ - --- 10

Grassland

Moors +++ --- + + +++ 0 +++ - +++ +++ + 3

MiresMarshes +++ --- + + +++ --- 0 - +++ +++ --- 5

Mixed +++ - +++ +++ +++ + + 0 +++ +++ + 2

Sparse Veg --- --- --- --- --- --- --- --- 0 --- --- 11

Urban --- --- --- --- + --- --- --- +++ 0 --- 9

Younger +++ --- +++ + +++ - +++ - +++ +++ 0 4

Rank Order and

Significance

Broad Leafgt Mixedgt GrasslandMoorsgt Youngergtgtgt MiresMarshesgt Coniferousgt

Clear Fellgtgtgt Agriculturegtgtgt Urbangt Freshwatergtgtgt Sparse Veg

Central

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 --- --- --- + +++ + --- +++ +++ --- 6

Broad Leaf +++ 0 +++ + +++ +++ + - +++ +++ - 3

Clear Fell +++ --- 0 - +++ +++ + --- +++ +++ --- 5

Coniferous +++ - + 0 +++ +++ + --- +++ +++ - 4

Freshwater - --- --- --- 0 +++ - --- +++ +++ --- 8

Grassland

Moors --- --- --- --- --- 0 --- --- +++ - --- 10

MiresMarshes - - - - + +++ 0 - +++ +++ - 7

Mixed +++ + +++ +++ +++ +++ + 0 +++ +++ + 1

Sparse Veg --- --- --- --- --- --- --- --- 0 - --- 11

Urban --- --- --- --- --- + --- --- + 0 --- 9

Younger +++ + +++ + +++ +++ + - +++ +++ 0 2

Rank Order and

Significance

Mixedgt Youngergt Broad Leafgt Coniferousgt Clear Fellgtgtgt Agriculturegt

MiresMarshesgt Freshwatergtgtgt Urbangt GrasslandMoorsgtgtgt Sparse Veg

38

South

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 + - - + - + +++ +++ +++ - 5

Broad Leaf - 0 - - + - - +++ + +++ - 7

Clear Fell + + 0 - + + + +++ + +++ + 2

Coniferous + + + 0 +++ + + +++ + +++ + 1

Freshwater - - - --- 0 - - + + +++ - 8

Grassland

Moors + + - - + 0 + + +++ + - 4

MiresMarshes - + - - + - 0 +++ + +++ - 6

Mixed --- --- --- --- - - --- 0 + + --- 10

Sparse Veg --- - - - - --- - - 0 + - 9

Urban --- --- --- --- --- - --- - - 0 --- 11

Younger + + - - + + + +++ + +++ 0 3

Rank Order

and

Significance

Coniferousgt Clear Fellgt Youngergt GrasslandMoorsgt Agriculturegt MiresMarshesgt Broad Leafgt

Freshwatergt Sparse Veggt Mixedgt Urban

Table 2 Simplified ranking matrices comparing proportional habitat use within the third order (UD50UD95) with

proportions of total available habitat types Mean value on the matrix was replaced by a sign a triple sign represents

significant deviation from random at P lt05 Highlighted habitat is ranked 1st

North

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 --- --- --- - + --- --- + +++ --- 8

Broad Leaf +++ 0 +++ + + + + + +++ +++ + 1

Clear Fell +++ --- 0 + + + - - + +++ - 5

Coniferous +++ - - 0 + + --- --- +++ +++ - 6

Freshwater + - - - 0 +++ - - +++ +++ - 7

GrasslandMoors - - - - --- 0 - - - + - 10

MiresMarshes +++ - + +++ + + 0 - +++ +++ + 3

Mixed +++ - + +++ + + + 0 +++ +++ + 2

Sparse Veg - --- - --- --- + --- --- 0 +++ --- 9

Urban --- --- --- --- --- - --- --- --- 0 --- 11

Younger +++ - + + + + - - +++ +++ 0 4

Rank Order and

Significance

Broad Leafgt Mixedgt MiresMarshesgt Youngergt Clear Fellgt Coniferousgt Freshwatergt

Agriculturegt Sparse Veggt GrasslandMoorsgt Urban

39

Central

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 --- --- + + - - - + +++ --- 7

Broad Leaf +++ 0 + +++ + + + + + +++ - 2

Clear Fell +++ - 0 +++ + + + + + +++ - 3

Coniferous - --- --- 0 + - - --- +++ + --- 8

Freshwater - - - - 0 --- - - --- - - 11

GrasslandMoors + - - + +++ 0 + - + +++ - 5

MiresMarshes + - - + + - 0 + + +++ - 6

Mixed + - - +++ + + - 0 +++ +++ - 4

Sparse Veg - - - --- +++ - - --- 0 +++ - 9

Urban --- --- --- - + --- --- --- --- 0 --- 10

Younger +++ + + +++ + + + + + +++ 0 1

Rank Order and

Significance

Youngergt Broad Leafgt Clear Fellgt Mixedgt GrasslandMoorsgt MiresMarshesgt

Agriculturegt Coniferousgtgtgt Sparse Veggtgtgt Urbangt Freshwater

South

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 - - - - - + - +++ + --- 8

Broad Leaf + 0 - --- + - + - +++ + - 6

Clear Fell + + 0 - + - + - +++ + - 4

Coniferous + +++ + 0 + + +++ + +++ + + 1

Freshwater + - - - 0 - - + + + - 7

GrasslandMoors + + + - + 0 + + + + - 3

MiresMarshes - - - --- + - 0 - + + - 9

Mixed + + + - - - + 0 + + - 5

Sparse Veg --- --- --- --- - - - - 0 + --- 10

Urban - - - - - - - - - 0 - 11

Younger +++ + + - + + + + +++ + 0 2

Rank Order and

Significance

Coniferousgt Youngergt GrasslandMoorsgt Clear Fellgt Mixedgt Broad Leafgt Freshwatergt

Agriculturegt MiresMarshesgt Sparse Veggt Urban

40

Table 3 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the GS according to Jacobs index

Ran

k North Centre South

50 95 50 95 50 95

+ - + - + - + - + - + -

1 Broad

Leaf Urban Broad Leaf Sparse Veg

Broad

Leaf Urban Mixed Urban Coniferous Urban

Grassland

Moors Urban

2 Mixed Sparse Veg Mixed Freshwater Younger Agriculture Younger Sparse Veg Younger Sparse Veg Clear Fell Mixed

3 Mires

Agriculture Grassland

Urban Clear

Fell Coniferous Broad Leaf

Grassland

Moors

Clear Fell Agriculture Coniferous Sparse Veg

Marshes Moors

4 Younger Grassland

Younger Agriculture

Freshwater Coniferous Freshwater

Broad Leaf Mires

Younger Freshwater

Moors Marshes

5 Clear

Fell Freshwater

Mires Coniferous

Sparse Veg Clear Fell Agriculture

Freshwater Agriculture

Marshes

6 Coniferous Clear Fell

Mires

Marshes

Mires

Grassland

Moors

Mires

Marshes Marshes

7 Mixed Mixed Broad Leaf

8 Grassland

Moors

41

Table 4 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the WS according to Jacobs index

Ran

k North Centre South

50 95 50 95 50 95

+ - + - + - + - + - + -

1 Mires

Marshes

Grassland

Moors Mixed Freshwater Agriculture Urban Mixed Freshwater

Grassland

Moors Urban GrasslandMoors Urban

2 Freshwater Mixed Coniferous Urban Mires

Marshes Coniferous Sparse Veg Agriculture

Sparse

Veg Coniferous Freshwater

3 Urban Coniferous Younger Grassland

Moors Freshwater Younger Urban Freshwater

Broad

Leaf Agriculture Mixed

4 Younger Agriculture Sparse Veg Broad

Leaf

Broad

Leaf

Grassland

Moors Mixed Broad Leaf

5 Clear Fell Agriculture Coniferous Agriculture Mires

Marshes Clear Fell

6 Sparse

Veg

Mires

Marshes Mixed

Mires

Marshes

Clear

Fell

Mires

Marshes

7 Broad

Leaf Clear Fell Younger Clear Fell Younger Sparse Veg

8 Clear Fell Younger

9 Sparse

Veg

10 Grassland

Moors

42

Table 5 Second order (UD95Area) individual selectionavoidance for the GS and WS according to the Jacobs index

ID GS WS

Select Avoid Select Avoid

ID004 Younger Sparsely Vegetated MiresMarshes Sparsely Vegetated

ID005 MiresMarshes Sparsely Vegetated Coniferous GrasslandMoors

ID006 Coniferous Sparsely Vegetated Mixed Freshwater

ID008 Mixed Sparsely Vegetated Mixed Freshwater

ID009 Mixed Sparsely Vegetated Mixed GrasslandMoors

ID010 MiresMarshes Freshwater GrasslandMoors Freshwater

ID012 Broad Leaf Sparsely Vegetated Coniferous Urban

ID014 Clear Fell Sparsely Vegetated GrasslandMoors Sparsely Vegetated

ID015 GrasslandMoors Urban GrasslandMoors Freshwater

ID016 GrasslandMoors Freshwater GrasslandMoors Freshwater

ID017 GrasslandMoors Mixed Sparsely Vegetated Mixed

ID019 Mixed Sparsely Vegetated Mixed Urban

ID020 Broad Leaf Sparsely Vegetated Coniferous GrasslandMoors

ID022 MiresMarshes Freshwater MiresMarshes Freshwater

ID023 MiresMarshes GrasslandMoors Mixed Freshwater

ID024 Broadleaf Urban Broad Leaf Urban

ID026 GrasslandMoors Freshwater GrasslandMoors Freshwater

ID027 GrasslandMoors Urban Sparsely Vegetated Freshwater

43 Table 6 Third order (UD50UD95) individual selectionavoidance for the GS and WS according to the Jacobs index

ID GS WS

Select Avoid Select Avoid

ID004 Broad Leaf Mixed GrasslandMoors Freshwater

ID005 Broad Leaf Freshwater Agriculture Freshwater

ID006 Clear Fell Freshwater Agriculture MiresMarshes

ID008 MiresMarshes Freshwater Agriculture Urban

ID009 Freshwater Agriculture Agriculture Freshwater

ID010 Mixed Urban Sparsely Vegetated Urban

ID012 Coniferous GrasslandMoors Freshwater Urban

ID014 Urban Agriculture Freshwater Urban

ID015 Mixed Forest Urban Clear Fell Urban

ID016 Freshwater Urban GrasslandMoors Mixed

ID017 Coniferous Mixed Coniferous Broad Leaf

ID019 Broad Leaf GrasslandMoors Urban GrasslandMoors

ID020 Freshwater Urban Freshwater Agriculture

ID022 MiresMarshes Urban Broad Leaf GrasslandMoors

ID023 Freshwater Mixed Agriculture Freshwater

ID024 Mixed Freshwater Mixed Freshwater

ID026 Mixed MiresMarshes Sparsely Vegetated GrasslandMoors

ID027 Freshwater MiresMarshes GrasslandMoors Broad Leaf

44

Fig 2 North third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)

45

Fig 3 Centre third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)

46

Fig 4 South third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)

47

Fig 5 North second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)

48

Fig 6 Centre second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)

49

Fig 7 South second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)

50

Appendix F

Background

Fig 1 Daily mean snow depth and duration during the study period (Andrew Allen)

Female Moose Reproduction

Moose are seasonal polyoestral mammals (Monfort et al 1993) coming into oestrus during late September

early October (Garel et al 2009) The Swedish moose cow population reaches puberty between the ages 25

and 35 (Sand and Cederlund 1993) during which the reproductive period begins with the onset of ovulation

The age an individual reaches puberty is dependent on their body condition they have to reach a weight

threshold to reach puberty and become reproductive (Sand 1996) If she is over the weight threshold she will

go into oestrus in the autumn If she does not reach the weight threshold then she will go into oestrus the

following autumn if successful she will give birth to individual or twin calves in late May to early June

(Ericsson et al 2001) and therefore reach sexual maturity (Malmsten et al 2014b) Fecundity is related to

both the condition and the age of the cow Cows go through senescence at 12 years of age (Ericsson et al

2001) Providing calves with the required level of nutrition demands high energy and protein resources from

the mother during senescence this becomes harder to achieve leading to decreased levels of parental care

and higher levels of calf mortality

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30

Appendix A

Introduction

Fig 1 Summary chart of factors affecting the life history and therefore the long term fitness of a population

Fig 2 Summary chart 2

Movement

Habitat

Climate

Topography

Competition

FoodWater

Disease

Die

Survive

Reproduce

Population long term fitness

31 Appendix B

Method and Materials

Fig 1 Summary of processes

32

Fig 2 Examples of classical kernel home range output and Brownian bridge kernel home range (Calenge 2011) The

right image includes the area between relocations ie the movement path in contrast to the classic kernel home range

in the left image

33 Appendix C

Home ranges

Fig 1 Example of a non-migratory (ID006) individuals BRB kernel area From top left annual growing and winter

season UD50 (black contour) and UD95 (red contour)

Fig 2 Example of a migratory (ID012) individuals BRB kernel area From the left annual growing and winter season

UD50 (black contour) and UD95 (red contour)

34

Table 1 Annual and seasonal UD50 and UD95 areas (ha) for all individuals

ID Annual GS WS

UD50 UD95 UD50 UD95 UD50 UD95

ID004 190 924 93 531 173 941

ID005 230 1364 132 945 72 682

ID006 162 1036 89 736 70 611

ID008 277 1536 156 809 78 738

ID009 137 834 48 295 126 653

ID010 114 682 83 448 96 488

ID012 177 963 123 544 76 545

ID014 160 1018 87 575 89 662

ID015 172 858 128 532 109 679

ID016 156 1047 65 455 92 534

ID017 153 1088 149 1043 69 349

ID019 279 1097 176 911 163 824

ID020 139 1084 67 349 160 794

ID022 159 811 131 638 61 454

ID023 187 1061 147 771 72 705

ID024 146 725 165 705 101 458

ID026 142 605 99 442 125 547

ID027 126 567 75 461 48 277

35 Appendix D

Activity

Fig 1 Mean daily movement during the study period GS 23-April-2012 to 07-Nov-2012 WS 08-Nov-2012 to

22-April-2013 (number indicates month)

Fig 2 Mean daily movement in the centre and south during the GS and WS

36

Appendix E

Habitat Proportions

Fig 1 All individualsrsquo seasonal habitat proportions within the UD95

37 Habitat Selection

Table 1 Simplified ranking matrices comparing proportional habitat use within the second order (UD95Area) with

proportions of total available habitat types Mean value on the matrix was replaced by a sign a triple sign represents

significant deviation from random at P lt05 Highlighted habitat is ranked 1st

North A

gri

cult

ure

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 --- --- - +++ --- --- --- +++ +++ --- 8

Broad Leaf +++ 0 +++ + +++ +++ +++ + +++ +++ +++ 1

Clear Fell +++ --- 0 + +++ - - --- +++ +++ --- 7

Coniferous + - - 0 +++ - - --- +++ +++ - 6

Freshwater --- --- --- --- 0 --- --- --- +++ - --- 10

Grassland

Moors +++ --- + + +++ 0 +++ - +++ +++ + 3

MiresMarshes +++ --- + + +++ --- 0 - +++ +++ --- 5

Mixed +++ - +++ +++ +++ + + 0 +++ +++ + 2

Sparse Veg --- --- --- --- --- --- --- --- 0 --- --- 11

Urban --- --- --- --- + --- --- --- +++ 0 --- 9

Younger +++ --- +++ + +++ - +++ - +++ +++ 0 4

Rank Order and

Significance

Broad Leafgt Mixedgt GrasslandMoorsgt Youngergtgtgt MiresMarshesgt Coniferousgt

Clear Fellgtgtgt Agriculturegtgtgt Urbangt Freshwatergtgtgt Sparse Veg

Central

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 --- --- --- + +++ + --- +++ +++ --- 6

Broad Leaf +++ 0 +++ + +++ +++ + - +++ +++ - 3

Clear Fell +++ --- 0 - +++ +++ + --- +++ +++ --- 5

Coniferous +++ - + 0 +++ +++ + --- +++ +++ - 4

Freshwater - --- --- --- 0 +++ - --- +++ +++ --- 8

Grassland

Moors --- --- --- --- --- 0 --- --- +++ - --- 10

MiresMarshes - - - - + +++ 0 - +++ +++ - 7

Mixed +++ + +++ +++ +++ +++ + 0 +++ +++ + 1

Sparse Veg --- --- --- --- --- --- --- --- 0 - --- 11

Urban --- --- --- --- --- + --- --- + 0 --- 9

Younger +++ + +++ + +++ +++ + - +++ +++ 0 2

Rank Order and

Significance

Mixedgt Youngergt Broad Leafgt Coniferousgt Clear Fellgtgtgt Agriculturegt

MiresMarshesgt Freshwatergtgtgt Urbangt GrasslandMoorsgtgtgt Sparse Veg

38

South

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 + - - + - + +++ +++ +++ - 5

Broad Leaf - 0 - - + - - +++ + +++ - 7

Clear Fell + + 0 - + + + +++ + +++ + 2

Coniferous + + + 0 +++ + + +++ + +++ + 1

Freshwater - - - --- 0 - - + + +++ - 8

Grassland

Moors + + - - + 0 + + +++ + - 4

MiresMarshes - + - - + - 0 +++ + +++ - 6

Mixed --- --- --- --- - - --- 0 + + --- 10

Sparse Veg --- - - - - --- - - 0 + - 9

Urban --- --- --- --- --- - --- - - 0 --- 11

Younger + + - - + + + +++ + +++ 0 3

Rank Order

and

Significance

Coniferousgt Clear Fellgt Youngergt GrasslandMoorsgt Agriculturegt MiresMarshesgt Broad Leafgt

Freshwatergt Sparse Veggt Mixedgt Urban

Table 2 Simplified ranking matrices comparing proportional habitat use within the third order (UD50UD95) with

proportions of total available habitat types Mean value on the matrix was replaced by a sign a triple sign represents

significant deviation from random at P lt05 Highlighted habitat is ranked 1st

North

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 --- --- --- - + --- --- + +++ --- 8

Broad Leaf +++ 0 +++ + + + + + +++ +++ + 1

Clear Fell +++ --- 0 + + + - - + +++ - 5

Coniferous +++ - - 0 + + --- --- +++ +++ - 6

Freshwater + - - - 0 +++ - - +++ +++ - 7

GrasslandMoors - - - - --- 0 - - - + - 10

MiresMarshes +++ - + +++ + + 0 - +++ +++ + 3

Mixed +++ - + +++ + + + 0 +++ +++ + 2

Sparse Veg - --- - --- --- + --- --- 0 +++ --- 9

Urban --- --- --- --- --- - --- --- --- 0 --- 11

Younger +++ - + + + + - - +++ +++ 0 4

Rank Order and

Significance

Broad Leafgt Mixedgt MiresMarshesgt Youngergt Clear Fellgt Coniferousgt Freshwatergt

Agriculturegt Sparse Veggt GrasslandMoorsgt Urban

39

Central

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

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Ra

nk

Agriculture 0 --- --- + + - - - + +++ --- 7

Broad Leaf +++ 0 + +++ + + + + + +++ - 2

Clear Fell +++ - 0 +++ + + + + + +++ - 3

Coniferous - --- --- 0 + - - --- +++ + --- 8

Freshwater - - - - 0 --- - - --- - - 11

GrasslandMoors + - - + +++ 0 + - + +++ - 5

MiresMarshes + - - + + - 0 + + +++ - 6

Mixed + - - +++ + + - 0 +++ +++ - 4

Sparse Veg - - - --- +++ - - --- 0 +++ - 9

Urban --- --- --- - + --- --- --- --- 0 --- 10

Younger +++ + + +++ + + + + + +++ 0 1

Rank Order and

Significance

Youngergt Broad Leafgt Clear Fellgt Mixedgt GrasslandMoorsgt MiresMarshesgt

Agriculturegt Coniferousgtgtgt Sparse Veggtgtgt Urbangt Freshwater

South

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

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Gra

ssla

nd

Mo

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Mir

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Mar

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Mix

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Veg

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an

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Ra

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Agriculture 0 - - - - - + - +++ + --- 8

Broad Leaf + 0 - --- + - + - +++ + - 6

Clear Fell + + 0 - + - + - +++ + - 4

Coniferous + +++ + 0 + + +++ + +++ + + 1

Freshwater + - - - 0 - - + + + - 7

GrasslandMoors + + + - + 0 + + + + - 3

MiresMarshes - - - --- + - 0 - + + - 9

Mixed + + + - - - + 0 + + - 5

Sparse Veg --- --- --- --- - - - - 0 + --- 10

Urban - - - - - - - - - 0 - 11

Younger +++ + + - + + + + +++ + 0 2

Rank Order and

Significance

Coniferousgt Youngergt GrasslandMoorsgt Clear Fellgt Mixedgt Broad Leafgt Freshwatergt

Agriculturegt MiresMarshesgt Sparse Veggt Urban

40

Table 3 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the GS according to Jacobs index

Ran

k North Centre South

50 95 50 95 50 95

+ - + - + - + - + - + -

1 Broad

Leaf Urban Broad Leaf Sparse Veg

Broad

Leaf Urban Mixed Urban Coniferous Urban

Grassland

Moors Urban

2 Mixed Sparse Veg Mixed Freshwater Younger Agriculture Younger Sparse Veg Younger Sparse Veg Clear Fell Mixed

3 Mires

Agriculture Grassland

Urban Clear

Fell Coniferous Broad Leaf

Grassland

Moors

Clear Fell Agriculture Coniferous Sparse Veg

Marshes Moors

4 Younger Grassland

Younger Agriculture

Freshwater Coniferous Freshwater

Broad Leaf Mires

Younger Freshwater

Moors Marshes

5 Clear

Fell Freshwater

Mires Coniferous

Sparse Veg Clear Fell Agriculture

Freshwater Agriculture

Marshes

6 Coniferous Clear Fell

Mires

Marshes

Mires

Grassland

Moors

Mires

Marshes Marshes

7 Mixed Mixed Broad Leaf

8 Grassland

Moors

41

Table 4 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the WS according to Jacobs index

Ran

k North Centre South

50 95 50 95 50 95

+ - + - + - + - + - + -

1 Mires

Marshes

Grassland

Moors Mixed Freshwater Agriculture Urban Mixed Freshwater

Grassland

Moors Urban GrasslandMoors Urban

2 Freshwater Mixed Coniferous Urban Mires

Marshes Coniferous Sparse Veg Agriculture

Sparse

Veg Coniferous Freshwater

3 Urban Coniferous Younger Grassland

Moors Freshwater Younger Urban Freshwater

Broad

Leaf Agriculture Mixed

4 Younger Agriculture Sparse Veg Broad

Leaf

Broad

Leaf

Grassland

Moors Mixed Broad Leaf

5 Clear Fell Agriculture Coniferous Agriculture Mires

Marshes Clear Fell

6 Sparse

Veg

Mires

Marshes Mixed

Mires

Marshes

Clear

Fell

Mires

Marshes

7 Broad

Leaf Clear Fell Younger Clear Fell Younger Sparse Veg

8 Clear Fell Younger

9 Sparse

Veg

10 Grassland

Moors

42

Table 5 Second order (UD95Area) individual selectionavoidance for the GS and WS according to the Jacobs index

ID GS WS

Select Avoid Select Avoid

ID004 Younger Sparsely Vegetated MiresMarshes Sparsely Vegetated

ID005 MiresMarshes Sparsely Vegetated Coniferous GrasslandMoors

ID006 Coniferous Sparsely Vegetated Mixed Freshwater

ID008 Mixed Sparsely Vegetated Mixed Freshwater

ID009 Mixed Sparsely Vegetated Mixed GrasslandMoors

ID010 MiresMarshes Freshwater GrasslandMoors Freshwater

ID012 Broad Leaf Sparsely Vegetated Coniferous Urban

ID014 Clear Fell Sparsely Vegetated GrasslandMoors Sparsely Vegetated

ID015 GrasslandMoors Urban GrasslandMoors Freshwater

ID016 GrasslandMoors Freshwater GrasslandMoors Freshwater

ID017 GrasslandMoors Mixed Sparsely Vegetated Mixed

ID019 Mixed Sparsely Vegetated Mixed Urban

ID020 Broad Leaf Sparsely Vegetated Coniferous GrasslandMoors

ID022 MiresMarshes Freshwater MiresMarshes Freshwater

ID023 MiresMarshes GrasslandMoors Mixed Freshwater

ID024 Broadleaf Urban Broad Leaf Urban

ID026 GrasslandMoors Freshwater GrasslandMoors Freshwater

ID027 GrasslandMoors Urban Sparsely Vegetated Freshwater

43 Table 6 Third order (UD50UD95) individual selectionavoidance for the GS and WS according to the Jacobs index

ID GS WS

Select Avoid Select Avoid

ID004 Broad Leaf Mixed GrasslandMoors Freshwater

ID005 Broad Leaf Freshwater Agriculture Freshwater

ID006 Clear Fell Freshwater Agriculture MiresMarshes

ID008 MiresMarshes Freshwater Agriculture Urban

ID009 Freshwater Agriculture Agriculture Freshwater

ID010 Mixed Urban Sparsely Vegetated Urban

ID012 Coniferous GrasslandMoors Freshwater Urban

ID014 Urban Agriculture Freshwater Urban

ID015 Mixed Forest Urban Clear Fell Urban

ID016 Freshwater Urban GrasslandMoors Mixed

ID017 Coniferous Mixed Coniferous Broad Leaf

ID019 Broad Leaf GrasslandMoors Urban GrasslandMoors

ID020 Freshwater Urban Freshwater Agriculture

ID022 MiresMarshes Urban Broad Leaf GrasslandMoors

ID023 Freshwater Mixed Agriculture Freshwater

ID024 Mixed Freshwater Mixed Freshwater

ID026 Mixed MiresMarshes Sparsely Vegetated GrasslandMoors

ID027 Freshwater MiresMarshes GrasslandMoors Broad Leaf

44

Fig 2 North third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)

45

Fig 3 Centre third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)

46

Fig 4 South third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)

47

Fig 5 North second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)

48

Fig 6 Centre second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)

49

Fig 7 South second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)

50

Appendix F

Background

Fig 1 Daily mean snow depth and duration during the study period (Andrew Allen)

Female Moose Reproduction

Moose are seasonal polyoestral mammals (Monfort et al 1993) coming into oestrus during late September

early October (Garel et al 2009) The Swedish moose cow population reaches puberty between the ages 25

and 35 (Sand and Cederlund 1993) during which the reproductive period begins with the onset of ovulation

The age an individual reaches puberty is dependent on their body condition they have to reach a weight

threshold to reach puberty and become reproductive (Sand 1996) If she is over the weight threshold she will

go into oestrus in the autumn If she does not reach the weight threshold then she will go into oestrus the

following autumn if successful she will give birth to individual or twin calves in late May to early June

(Ericsson et al 2001) and therefore reach sexual maturity (Malmsten et al 2014b) Fecundity is related to

both the condition and the age of the cow Cows go through senescence at 12 years of age (Ericsson et al

2001) Providing calves with the required level of nutrition demands high energy and protein resources from

the mother during senescence this becomes harder to achieve leading to decreased levels of parental care

and higher levels of calf mortality

Page 29: Habitat-performance relationships on an island: fitness ...navinderjsingh.weebly.com/uploads/1/1/2/2/11224342/... · Conditions on Öland are milder than those found in other areas

29

Tveito OE Foslashrland EJ Alexandersson H Drebs A Jonsson T Vaarby-Laursen E (2001) Nordic climate

maps Norway CICERO

Udina IG Danilkin AA Boeskorov GG (2002) Genetic diversity of moose (Alces ales L) in Eurasia

Russian Journal of Genetics 38951-957

van Beest FM van Moorter B Milner JM (2012) Temperature-mediated habitat use and selection by a heat

sensitive northern ungulate Animal Behaviour 84(3)723-735

van Winkle W (1975) Comparision of several probabilistic home-range models Journal of Wildlife

Management 39118-123

Verme LJ Ullrey DE (1984) Physiology and nutrition White-tailed deer ecology and management (Ed By

Halls LK) pp 91-118 Stackpole Harrisburg Pennsylvania

Wattles DW DeStefano (2013) Space use and movements of moose in Massachusetts Implications for

conservation of large mammals in a fragmented environment Alces 4965-81

White RG Rowell JE Hauer WE (1997) The role of nutrition body condition and lactation on calving

success in muskoxen Journal of Zoology 24313-20

30

Appendix A

Introduction

Fig 1 Summary chart of factors affecting the life history and therefore the long term fitness of a population

Fig 2 Summary chart 2

Movement

Habitat

Climate

Topography

Competition

FoodWater

Disease

Die

Survive

Reproduce

Population long term fitness

31 Appendix B

Method and Materials

Fig 1 Summary of processes

32

Fig 2 Examples of classical kernel home range output and Brownian bridge kernel home range (Calenge 2011) The

right image includes the area between relocations ie the movement path in contrast to the classic kernel home range

in the left image

33 Appendix C

Home ranges

Fig 1 Example of a non-migratory (ID006) individuals BRB kernel area From top left annual growing and winter

season UD50 (black contour) and UD95 (red contour)

Fig 2 Example of a migratory (ID012) individuals BRB kernel area From the left annual growing and winter season

UD50 (black contour) and UD95 (red contour)

34

Table 1 Annual and seasonal UD50 and UD95 areas (ha) for all individuals

ID Annual GS WS

UD50 UD95 UD50 UD95 UD50 UD95

ID004 190 924 93 531 173 941

ID005 230 1364 132 945 72 682

ID006 162 1036 89 736 70 611

ID008 277 1536 156 809 78 738

ID009 137 834 48 295 126 653

ID010 114 682 83 448 96 488

ID012 177 963 123 544 76 545

ID014 160 1018 87 575 89 662

ID015 172 858 128 532 109 679

ID016 156 1047 65 455 92 534

ID017 153 1088 149 1043 69 349

ID019 279 1097 176 911 163 824

ID020 139 1084 67 349 160 794

ID022 159 811 131 638 61 454

ID023 187 1061 147 771 72 705

ID024 146 725 165 705 101 458

ID026 142 605 99 442 125 547

ID027 126 567 75 461 48 277

35 Appendix D

Activity

Fig 1 Mean daily movement during the study period GS 23-April-2012 to 07-Nov-2012 WS 08-Nov-2012 to

22-April-2013 (number indicates month)

Fig 2 Mean daily movement in the centre and south during the GS and WS

36

Appendix E

Habitat Proportions

Fig 1 All individualsrsquo seasonal habitat proportions within the UD95

37 Habitat Selection

Table 1 Simplified ranking matrices comparing proportional habitat use within the second order (UD95Area) with

proportions of total available habitat types Mean value on the matrix was replaced by a sign a triple sign represents

significant deviation from random at P lt05 Highlighted habitat is ranked 1st

North A

gri

cult

ure

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 --- --- - +++ --- --- --- +++ +++ --- 8

Broad Leaf +++ 0 +++ + +++ +++ +++ + +++ +++ +++ 1

Clear Fell +++ --- 0 + +++ - - --- +++ +++ --- 7

Coniferous + - - 0 +++ - - --- +++ +++ - 6

Freshwater --- --- --- --- 0 --- --- --- +++ - --- 10

Grassland

Moors +++ --- + + +++ 0 +++ - +++ +++ + 3

MiresMarshes +++ --- + + +++ --- 0 - +++ +++ --- 5

Mixed +++ - +++ +++ +++ + + 0 +++ +++ + 2

Sparse Veg --- --- --- --- --- --- --- --- 0 --- --- 11

Urban --- --- --- --- + --- --- --- +++ 0 --- 9

Younger +++ --- +++ + +++ - +++ - +++ +++ 0 4

Rank Order and

Significance

Broad Leafgt Mixedgt GrasslandMoorsgt Youngergtgtgt MiresMarshesgt Coniferousgt

Clear Fellgtgtgt Agriculturegtgtgt Urbangt Freshwatergtgtgt Sparse Veg

Central

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 --- --- --- + +++ + --- +++ +++ --- 6

Broad Leaf +++ 0 +++ + +++ +++ + - +++ +++ - 3

Clear Fell +++ --- 0 - +++ +++ + --- +++ +++ --- 5

Coniferous +++ - + 0 +++ +++ + --- +++ +++ - 4

Freshwater - --- --- --- 0 +++ - --- +++ +++ --- 8

Grassland

Moors --- --- --- --- --- 0 --- --- +++ - --- 10

MiresMarshes - - - - + +++ 0 - +++ +++ - 7

Mixed +++ + +++ +++ +++ +++ + 0 +++ +++ + 1

Sparse Veg --- --- --- --- --- --- --- --- 0 - --- 11

Urban --- --- --- --- --- + --- --- + 0 --- 9

Younger +++ + +++ + +++ +++ + - +++ +++ 0 2

Rank Order and

Significance

Mixedgt Youngergt Broad Leafgt Coniferousgt Clear Fellgtgtgt Agriculturegt

MiresMarshesgt Freshwatergtgtgt Urbangt GrasslandMoorsgtgtgt Sparse Veg

38

South

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 + - - + - + +++ +++ +++ - 5

Broad Leaf - 0 - - + - - +++ + +++ - 7

Clear Fell + + 0 - + + + +++ + +++ + 2

Coniferous + + + 0 +++ + + +++ + +++ + 1

Freshwater - - - --- 0 - - + + +++ - 8

Grassland

Moors + + - - + 0 + + +++ + - 4

MiresMarshes - + - - + - 0 +++ + +++ - 6

Mixed --- --- --- --- - - --- 0 + + --- 10

Sparse Veg --- - - - - --- - - 0 + - 9

Urban --- --- --- --- --- - --- - - 0 --- 11

Younger + + - - + + + +++ + +++ 0 3

Rank Order

and

Significance

Coniferousgt Clear Fellgt Youngergt GrasslandMoorsgt Agriculturegt MiresMarshesgt Broad Leafgt

Freshwatergt Sparse Veggt Mixedgt Urban

Table 2 Simplified ranking matrices comparing proportional habitat use within the third order (UD50UD95) with

proportions of total available habitat types Mean value on the matrix was replaced by a sign a triple sign represents

significant deviation from random at P lt05 Highlighted habitat is ranked 1st

North

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 --- --- --- - + --- --- + +++ --- 8

Broad Leaf +++ 0 +++ + + + + + +++ +++ + 1

Clear Fell +++ --- 0 + + + - - + +++ - 5

Coniferous +++ - - 0 + + --- --- +++ +++ - 6

Freshwater + - - - 0 +++ - - +++ +++ - 7

GrasslandMoors - - - - --- 0 - - - + - 10

MiresMarshes +++ - + +++ + + 0 - +++ +++ + 3

Mixed +++ - + +++ + + + 0 +++ +++ + 2

Sparse Veg - --- - --- --- + --- --- 0 +++ --- 9

Urban --- --- --- --- --- - --- --- --- 0 --- 11

Younger +++ - + + + + - - +++ +++ 0 4

Rank Order and

Significance

Broad Leafgt Mixedgt MiresMarshesgt Youngergt Clear Fellgt Coniferousgt Freshwatergt

Agriculturegt Sparse Veggt GrasslandMoorsgt Urban

39

Central

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 --- --- + + - - - + +++ --- 7

Broad Leaf +++ 0 + +++ + + + + + +++ - 2

Clear Fell +++ - 0 +++ + + + + + +++ - 3

Coniferous - --- --- 0 + - - --- +++ + --- 8

Freshwater - - - - 0 --- - - --- - - 11

GrasslandMoors + - - + +++ 0 + - + +++ - 5

MiresMarshes + - - + + - 0 + + +++ - 6

Mixed + - - +++ + + - 0 +++ +++ - 4

Sparse Veg - - - --- +++ - - --- 0 +++ - 9

Urban --- --- --- - + --- --- --- --- 0 --- 10

Younger +++ + + +++ + + + + + +++ 0 1

Rank Order and

Significance

Youngergt Broad Leafgt Clear Fellgt Mixedgt GrasslandMoorsgt MiresMarshesgt

Agriculturegt Coniferousgtgtgt Sparse Veggtgtgt Urbangt Freshwater

South

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 - - - - - + - +++ + --- 8

Broad Leaf + 0 - --- + - + - +++ + - 6

Clear Fell + + 0 - + - + - +++ + - 4

Coniferous + +++ + 0 + + +++ + +++ + + 1

Freshwater + - - - 0 - - + + + - 7

GrasslandMoors + + + - + 0 + + + + - 3

MiresMarshes - - - --- + - 0 - + + - 9

Mixed + + + - - - + 0 + + - 5

Sparse Veg --- --- --- --- - - - - 0 + --- 10

Urban - - - - - - - - - 0 - 11

Younger +++ + + - + + + + +++ + 0 2

Rank Order and

Significance

Coniferousgt Youngergt GrasslandMoorsgt Clear Fellgt Mixedgt Broad Leafgt Freshwatergt

Agriculturegt MiresMarshesgt Sparse Veggt Urban

40

Table 3 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the GS according to Jacobs index

Ran

k North Centre South

50 95 50 95 50 95

+ - + - + - + - + - + -

1 Broad

Leaf Urban Broad Leaf Sparse Veg

Broad

Leaf Urban Mixed Urban Coniferous Urban

Grassland

Moors Urban

2 Mixed Sparse Veg Mixed Freshwater Younger Agriculture Younger Sparse Veg Younger Sparse Veg Clear Fell Mixed

3 Mires

Agriculture Grassland

Urban Clear

Fell Coniferous Broad Leaf

Grassland

Moors

Clear Fell Agriculture Coniferous Sparse Veg

Marshes Moors

4 Younger Grassland

Younger Agriculture

Freshwater Coniferous Freshwater

Broad Leaf Mires

Younger Freshwater

Moors Marshes

5 Clear

Fell Freshwater

Mires Coniferous

Sparse Veg Clear Fell Agriculture

Freshwater Agriculture

Marshes

6 Coniferous Clear Fell

Mires

Marshes

Mires

Grassland

Moors

Mires

Marshes Marshes

7 Mixed Mixed Broad Leaf

8 Grassland

Moors

41

Table 4 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the WS according to Jacobs index

Ran

k North Centre South

50 95 50 95 50 95

+ - + - + - + - + - + -

1 Mires

Marshes

Grassland

Moors Mixed Freshwater Agriculture Urban Mixed Freshwater

Grassland

Moors Urban GrasslandMoors Urban

2 Freshwater Mixed Coniferous Urban Mires

Marshes Coniferous Sparse Veg Agriculture

Sparse

Veg Coniferous Freshwater

3 Urban Coniferous Younger Grassland

Moors Freshwater Younger Urban Freshwater

Broad

Leaf Agriculture Mixed

4 Younger Agriculture Sparse Veg Broad

Leaf

Broad

Leaf

Grassland

Moors Mixed Broad Leaf

5 Clear Fell Agriculture Coniferous Agriculture Mires

Marshes Clear Fell

6 Sparse

Veg

Mires

Marshes Mixed

Mires

Marshes

Clear

Fell

Mires

Marshes

7 Broad

Leaf Clear Fell Younger Clear Fell Younger Sparse Veg

8 Clear Fell Younger

9 Sparse

Veg

10 Grassland

Moors

42

Table 5 Second order (UD95Area) individual selectionavoidance for the GS and WS according to the Jacobs index

ID GS WS

Select Avoid Select Avoid

ID004 Younger Sparsely Vegetated MiresMarshes Sparsely Vegetated

ID005 MiresMarshes Sparsely Vegetated Coniferous GrasslandMoors

ID006 Coniferous Sparsely Vegetated Mixed Freshwater

ID008 Mixed Sparsely Vegetated Mixed Freshwater

ID009 Mixed Sparsely Vegetated Mixed GrasslandMoors

ID010 MiresMarshes Freshwater GrasslandMoors Freshwater

ID012 Broad Leaf Sparsely Vegetated Coniferous Urban

ID014 Clear Fell Sparsely Vegetated GrasslandMoors Sparsely Vegetated

ID015 GrasslandMoors Urban GrasslandMoors Freshwater

ID016 GrasslandMoors Freshwater GrasslandMoors Freshwater

ID017 GrasslandMoors Mixed Sparsely Vegetated Mixed

ID019 Mixed Sparsely Vegetated Mixed Urban

ID020 Broad Leaf Sparsely Vegetated Coniferous GrasslandMoors

ID022 MiresMarshes Freshwater MiresMarshes Freshwater

ID023 MiresMarshes GrasslandMoors Mixed Freshwater

ID024 Broadleaf Urban Broad Leaf Urban

ID026 GrasslandMoors Freshwater GrasslandMoors Freshwater

ID027 GrasslandMoors Urban Sparsely Vegetated Freshwater

43 Table 6 Third order (UD50UD95) individual selectionavoidance for the GS and WS according to the Jacobs index

ID GS WS

Select Avoid Select Avoid

ID004 Broad Leaf Mixed GrasslandMoors Freshwater

ID005 Broad Leaf Freshwater Agriculture Freshwater

ID006 Clear Fell Freshwater Agriculture MiresMarshes

ID008 MiresMarshes Freshwater Agriculture Urban

ID009 Freshwater Agriculture Agriculture Freshwater

ID010 Mixed Urban Sparsely Vegetated Urban

ID012 Coniferous GrasslandMoors Freshwater Urban

ID014 Urban Agriculture Freshwater Urban

ID015 Mixed Forest Urban Clear Fell Urban

ID016 Freshwater Urban GrasslandMoors Mixed

ID017 Coniferous Mixed Coniferous Broad Leaf

ID019 Broad Leaf GrasslandMoors Urban GrasslandMoors

ID020 Freshwater Urban Freshwater Agriculture

ID022 MiresMarshes Urban Broad Leaf GrasslandMoors

ID023 Freshwater Mixed Agriculture Freshwater

ID024 Mixed Freshwater Mixed Freshwater

ID026 Mixed MiresMarshes Sparsely Vegetated GrasslandMoors

ID027 Freshwater MiresMarshes GrasslandMoors Broad Leaf

44

Fig 2 North third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)

45

Fig 3 Centre third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)

46

Fig 4 South third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)

47

Fig 5 North second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)

48

Fig 6 Centre second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)

49

Fig 7 South second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)

50

Appendix F

Background

Fig 1 Daily mean snow depth and duration during the study period (Andrew Allen)

Female Moose Reproduction

Moose are seasonal polyoestral mammals (Monfort et al 1993) coming into oestrus during late September

early October (Garel et al 2009) The Swedish moose cow population reaches puberty between the ages 25

and 35 (Sand and Cederlund 1993) during which the reproductive period begins with the onset of ovulation

The age an individual reaches puberty is dependent on their body condition they have to reach a weight

threshold to reach puberty and become reproductive (Sand 1996) If she is over the weight threshold she will

go into oestrus in the autumn If she does not reach the weight threshold then she will go into oestrus the

following autumn if successful she will give birth to individual or twin calves in late May to early June

(Ericsson et al 2001) and therefore reach sexual maturity (Malmsten et al 2014b) Fecundity is related to

both the condition and the age of the cow Cows go through senescence at 12 years of age (Ericsson et al

2001) Providing calves with the required level of nutrition demands high energy and protein resources from

the mother during senescence this becomes harder to achieve leading to decreased levels of parental care

and higher levels of calf mortality

Page 30: Habitat-performance relationships on an island: fitness ...navinderjsingh.weebly.com/uploads/1/1/2/2/11224342/... · Conditions on Öland are milder than those found in other areas

30

Appendix A

Introduction

Fig 1 Summary chart of factors affecting the life history and therefore the long term fitness of a population

Fig 2 Summary chart 2

Movement

Habitat

Climate

Topography

Competition

FoodWater

Disease

Die

Survive

Reproduce

Population long term fitness

31 Appendix B

Method and Materials

Fig 1 Summary of processes

32

Fig 2 Examples of classical kernel home range output and Brownian bridge kernel home range (Calenge 2011) The

right image includes the area between relocations ie the movement path in contrast to the classic kernel home range

in the left image

33 Appendix C

Home ranges

Fig 1 Example of a non-migratory (ID006) individuals BRB kernel area From top left annual growing and winter

season UD50 (black contour) and UD95 (red contour)

Fig 2 Example of a migratory (ID012) individuals BRB kernel area From the left annual growing and winter season

UD50 (black contour) and UD95 (red contour)

34

Table 1 Annual and seasonal UD50 and UD95 areas (ha) for all individuals

ID Annual GS WS

UD50 UD95 UD50 UD95 UD50 UD95

ID004 190 924 93 531 173 941

ID005 230 1364 132 945 72 682

ID006 162 1036 89 736 70 611

ID008 277 1536 156 809 78 738

ID009 137 834 48 295 126 653

ID010 114 682 83 448 96 488

ID012 177 963 123 544 76 545

ID014 160 1018 87 575 89 662

ID015 172 858 128 532 109 679

ID016 156 1047 65 455 92 534

ID017 153 1088 149 1043 69 349

ID019 279 1097 176 911 163 824

ID020 139 1084 67 349 160 794

ID022 159 811 131 638 61 454

ID023 187 1061 147 771 72 705

ID024 146 725 165 705 101 458

ID026 142 605 99 442 125 547

ID027 126 567 75 461 48 277

35 Appendix D

Activity

Fig 1 Mean daily movement during the study period GS 23-April-2012 to 07-Nov-2012 WS 08-Nov-2012 to

22-April-2013 (number indicates month)

Fig 2 Mean daily movement in the centre and south during the GS and WS

36

Appendix E

Habitat Proportions

Fig 1 All individualsrsquo seasonal habitat proportions within the UD95

37 Habitat Selection

Table 1 Simplified ranking matrices comparing proportional habitat use within the second order (UD95Area) with

proportions of total available habitat types Mean value on the matrix was replaced by a sign a triple sign represents

significant deviation from random at P lt05 Highlighted habitat is ranked 1st

North A

gri

cult

ure

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 --- --- - +++ --- --- --- +++ +++ --- 8

Broad Leaf +++ 0 +++ + +++ +++ +++ + +++ +++ +++ 1

Clear Fell +++ --- 0 + +++ - - --- +++ +++ --- 7

Coniferous + - - 0 +++ - - --- +++ +++ - 6

Freshwater --- --- --- --- 0 --- --- --- +++ - --- 10

Grassland

Moors +++ --- + + +++ 0 +++ - +++ +++ + 3

MiresMarshes +++ --- + + +++ --- 0 - +++ +++ --- 5

Mixed +++ - +++ +++ +++ + + 0 +++ +++ + 2

Sparse Veg --- --- --- --- --- --- --- --- 0 --- --- 11

Urban --- --- --- --- + --- --- --- +++ 0 --- 9

Younger +++ --- +++ + +++ - +++ - +++ +++ 0 4

Rank Order and

Significance

Broad Leafgt Mixedgt GrasslandMoorsgt Youngergtgtgt MiresMarshesgt Coniferousgt

Clear Fellgtgtgt Agriculturegtgtgt Urbangt Freshwatergtgtgt Sparse Veg

Central

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 --- --- --- + +++ + --- +++ +++ --- 6

Broad Leaf +++ 0 +++ + +++ +++ + - +++ +++ - 3

Clear Fell +++ --- 0 - +++ +++ + --- +++ +++ --- 5

Coniferous +++ - + 0 +++ +++ + --- +++ +++ - 4

Freshwater - --- --- --- 0 +++ - --- +++ +++ --- 8

Grassland

Moors --- --- --- --- --- 0 --- --- +++ - --- 10

MiresMarshes - - - - + +++ 0 - +++ +++ - 7

Mixed +++ + +++ +++ +++ +++ + 0 +++ +++ + 1

Sparse Veg --- --- --- --- --- --- --- --- 0 - --- 11

Urban --- --- --- --- --- + --- --- + 0 --- 9

Younger +++ + +++ + +++ +++ + - +++ +++ 0 2

Rank Order and

Significance

Mixedgt Youngergt Broad Leafgt Coniferousgt Clear Fellgtgtgt Agriculturegt

MiresMarshesgt Freshwatergtgtgt Urbangt GrasslandMoorsgtgtgt Sparse Veg

38

South

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 + - - + - + +++ +++ +++ - 5

Broad Leaf - 0 - - + - - +++ + +++ - 7

Clear Fell + + 0 - + + + +++ + +++ + 2

Coniferous + + + 0 +++ + + +++ + +++ + 1

Freshwater - - - --- 0 - - + + +++ - 8

Grassland

Moors + + - - + 0 + + +++ + - 4

MiresMarshes - + - - + - 0 +++ + +++ - 6

Mixed --- --- --- --- - - --- 0 + + --- 10

Sparse Veg --- - - - - --- - - 0 + - 9

Urban --- --- --- --- --- - --- - - 0 --- 11

Younger + + - - + + + +++ + +++ 0 3

Rank Order

and

Significance

Coniferousgt Clear Fellgt Youngergt GrasslandMoorsgt Agriculturegt MiresMarshesgt Broad Leafgt

Freshwatergt Sparse Veggt Mixedgt Urban

Table 2 Simplified ranking matrices comparing proportional habitat use within the third order (UD50UD95) with

proportions of total available habitat types Mean value on the matrix was replaced by a sign a triple sign represents

significant deviation from random at P lt05 Highlighted habitat is ranked 1st

North

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 --- --- --- - + --- --- + +++ --- 8

Broad Leaf +++ 0 +++ + + + + + +++ +++ + 1

Clear Fell +++ --- 0 + + + - - + +++ - 5

Coniferous +++ - - 0 + + --- --- +++ +++ - 6

Freshwater + - - - 0 +++ - - +++ +++ - 7

GrasslandMoors - - - - --- 0 - - - + - 10

MiresMarshes +++ - + +++ + + 0 - +++ +++ + 3

Mixed +++ - + +++ + + + 0 +++ +++ + 2

Sparse Veg - --- - --- --- + --- --- 0 +++ --- 9

Urban --- --- --- --- --- - --- --- --- 0 --- 11

Younger +++ - + + + + - - +++ +++ 0 4

Rank Order and

Significance

Broad Leafgt Mixedgt MiresMarshesgt Youngergt Clear Fellgt Coniferousgt Freshwatergt

Agriculturegt Sparse Veggt GrasslandMoorsgt Urban

39

Central

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 --- --- + + - - - + +++ --- 7

Broad Leaf +++ 0 + +++ + + + + + +++ - 2

Clear Fell +++ - 0 +++ + + + + + +++ - 3

Coniferous - --- --- 0 + - - --- +++ + --- 8

Freshwater - - - - 0 --- - - --- - - 11

GrasslandMoors + - - + +++ 0 + - + +++ - 5

MiresMarshes + - - + + - 0 + + +++ - 6

Mixed + - - +++ + + - 0 +++ +++ - 4

Sparse Veg - - - --- +++ - - --- 0 +++ - 9

Urban --- --- --- - + --- --- --- --- 0 --- 10

Younger +++ + + +++ + + + + + +++ 0 1

Rank Order and

Significance

Youngergt Broad Leafgt Clear Fellgt Mixedgt GrasslandMoorsgt MiresMarshesgt

Agriculturegt Coniferousgtgtgt Sparse Veggtgtgt Urbangt Freshwater

South

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 - - - - - + - +++ + --- 8

Broad Leaf + 0 - --- + - + - +++ + - 6

Clear Fell + + 0 - + - + - +++ + - 4

Coniferous + +++ + 0 + + +++ + +++ + + 1

Freshwater + - - - 0 - - + + + - 7

GrasslandMoors + + + - + 0 + + + + - 3

MiresMarshes - - - --- + - 0 - + + - 9

Mixed + + + - - - + 0 + + - 5

Sparse Veg --- --- --- --- - - - - 0 + --- 10

Urban - - - - - - - - - 0 - 11

Younger +++ + + - + + + + +++ + 0 2

Rank Order and

Significance

Coniferousgt Youngergt GrasslandMoorsgt Clear Fellgt Mixedgt Broad Leafgt Freshwatergt

Agriculturegt MiresMarshesgt Sparse Veggt Urban

40

Table 3 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the GS according to Jacobs index

Ran

k North Centre South

50 95 50 95 50 95

+ - + - + - + - + - + -

1 Broad

Leaf Urban Broad Leaf Sparse Veg

Broad

Leaf Urban Mixed Urban Coniferous Urban

Grassland

Moors Urban

2 Mixed Sparse Veg Mixed Freshwater Younger Agriculture Younger Sparse Veg Younger Sparse Veg Clear Fell Mixed

3 Mires

Agriculture Grassland

Urban Clear

Fell Coniferous Broad Leaf

Grassland

Moors

Clear Fell Agriculture Coniferous Sparse Veg

Marshes Moors

4 Younger Grassland

Younger Agriculture

Freshwater Coniferous Freshwater

Broad Leaf Mires

Younger Freshwater

Moors Marshes

5 Clear

Fell Freshwater

Mires Coniferous

Sparse Veg Clear Fell Agriculture

Freshwater Agriculture

Marshes

6 Coniferous Clear Fell

Mires

Marshes

Mires

Grassland

Moors

Mires

Marshes Marshes

7 Mixed Mixed Broad Leaf

8 Grassland

Moors

41

Table 4 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the WS according to Jacobs index

Ran

k North Centre South

50 95 50 95 50 95

+ - + - + - + - + - + -

1 Mires

Marshes

Grassland

Moors Mixed Freshwater Agriculture Urban Mixed Freshwater

Grassland

Moors Urban GrasslandMoors Urban

2 Freshwater Mixed Coniferous Urban Mires

Marshes Coniferous Sparse Veg Agriculture

Sparse

Veg Coniferous Freshwater

3 Urban Coniferous Younger Grassland

Moors Freshwater Younger Urban Freshwater

Broad

Leaf Agriculture Mixed

4 Younger Agriculture Sparse Veg Broad

Leaf

Broad

Leaf

Grassland

Moors Mixed Broad Leaf

5 Clear Fell Agriculture Coniferous Agriculture Mires

Marshes Clear Fell

6 Sparse

Veg

Mires

Marshes Mixed

Mires

Marshes

Clear

Fell

Mires

Marshes

7 Broad

Leaf Clear Fell Younger Clear Fell Younger Sparse Veg

8 Clear Fell Younger

9 Sparse

Veg

10 Grassland

Moors

42

Table 5 Second order (UD95Area) individual selectionavoidance for the GS and WS according to the Jacobs index

ID GS WS

Select Avoid Select Avoid

ID004 Younger Sparsely Vegetated MiresMarshes Sparsely Vegetated

ID005 MiresMarshes Sparsely Vegetated Coniferous GrasslandMoors

ID006 Coniferous Sparsely Vegetated Mixed Freshwater

ID008 Mixed Sparsely Vegetated Mixed Freshwater

ID009 Mixed Sparsely Vegetated Mixed GrasslandMoors

ID010 MiresMarshes Freshwater GrasslandMoors Freshwater

ID012 Broad Leaf Sparsely Vegetated Coniferous Urban

ID014 Clear Fell Sparsely Vegetated GrasslandMoors Sparsely Vegetated

ID015 GrasslandMoors Urban GrasslandMoors Freshwater

ID016 GrasslandMoors Freshwater GrasslandMoors Freshwater

ID017 GrasslandMoors Mixed Sparsely Vegetated Mixed

ID019 Mixed Sparsely Vegetated Mixed Urban

ID020 Broad Leaf Sparsely Vegetated Coniferous GrasslandMoors

ID022 MiresMarshes Freshwater MiresMarshes Freshwater

ID023 MiresMarshes GrasslandMoors Mixed Freshwater

ID024 Broadleaf Urban Broad Leaf Urban

ID026 GrasslandMoors Freshwater GrasslandMoors Freshwater

ID027 GrasslandMoors Urban Sparsely Vegetated Freshwater

43 Table 6 Third order (UD50UD95) individual selectionavoidance for the GS and WS according to the Jacobs index

ID GS WS

Select Avoid Select Avoid

ID004 Broad Leaf Mixed GrasslandMoors Freshwater

ID005 Broad Leaf Freshwater Agriculture Freshwater

ID006 Clear Fell Freshwater Agriculture MiresMarshes

ID008 MiresMarshes Freshwater Agriculture Urban

ID009 Freshwater Agriculture Agriculture Freshwater

ID010 Mixed Urban Sparsely Vegetated Urban

ID012 Coniferous GrasslandMoors Freshwater Urban

ID014 Urban Agriculture Freshwater Urban

ID015 Mixed Forest Urban Clear Fell Urban

ID016 Freshwater Urban GrasslandMoors Mixed

ID017 Coniferous Mixed Coniferous Broad Leaf

ID019 Broad Leaf GrasslandMoors Urban GrasslandMoors

ID020 Freshwater Urban Freshwater Agriculture

ID022 MiresMarshes Urban Broad Leaf GrasslandMoors

ID023 Freshwater Mixed Agriculture Freshwater

ID024 Mixed Freshwater Mixed Freshwater

ID026 Mixed MiresMarshes Sparsely Vegetated GrasslandMoors

ID027 Freshwater MiresMarshes GrasslandMoors Broad Leaf

44

Fig 2 North third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)

45

Fig 3 Centre third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)

46

Fig 4 South third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)

47

Fig 5 North second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)

48

Fig 6 Centre second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)

49

Fig 7 South second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)

50

Appendix F

Background

Fig 1 Daily mean snow depth and duration during the study period (Andrew Allen)

Female Moose Reproduction

Moose are seasonal polyoestral mammals (Monfort et al 1993) coming into oestrus during late September

early October (Garel et al 2009) The Swedish moose cow population reaches puberty between the ages 25

and 35 (Sand and Cederlund 1993) during which the reproductive period begins with the onset of ovulation

The age an individual reaches puberty is dependent on their body condition they have to reach a weight

threshold to reach puberty and become reproductive (Sand 1996) If she is over the weight threshold she will

go into oestrus in the autumn If she does not reach the weight threshold then she will go into oestrus the

following autumn if successful she will give birth to individual or twin calves in late May to early June

(Ericsson et al 2001) and therefore reach sexual maturity (Malmsten et al 2014b) Fecundity is related to

both the condition and the age of the cow Cows go through senescence at 12 years of age (Ericsson et al

2001) Providing calves with the required level of nutrition demands high energy and protein resources from

the mother during senescence this becomes harder to achieve leading to decreased levels of parental care

and higher levels of calf mortality

Page 31: Habitat-performance relationships on an island: fitness ...navinderjsingh.weebly.com/uploads/1/1/2/2/11224342/... · Conditions on Öland are milder than those found in other areas

31 Appendix B

Method and Materials

Fig 1 Summary of processes

32

Fig 2 Examples of classical kernel home range output and Brownian bridge kernel home range (Calenge 2011) The

right image includes the area between relocations ie the movement path in contrast to the classic kernel home range

in the left image

33 Appendix C

Home ranges

Fig 1 Example of a non-migratory (ID006) individuals BRB kernel area From top left annual growing and winter

season UD50 (black contour) and UD95 (red contour)

Fig 2 Example of a migratory (ID012) individuals BRB kernel area From the left annual growing and winter season

UD50 (black contour) and UD95 (red contour)

34

Table 1 Annual and seasonal UD50 and UD95 areas (ha) for all individuals

ID Annual GS WS

UD50 UD95 UD50 UD95 UD50 UD95

ID004 190 924 93 531 173 941

ID005 230 1364 132 945 72 682

ID006 162 1036 89 736 70 611

ID008 277 1536 156 809 78 738

ID009 137 834 48 295 126 653

ID010 114 682 83 448 96 488

ID012 177 963 123 544 76 545

ID014 160 1018 87 575 89 662

ID015 172 858 128 532 109 679

ID016 156 1047 65 455 92 534

ID017 153 1088 149 1043 69 349

ID019 279 1097 176 911 163 824

ID020 139 1084 67 349 160 794

ID022 159 811 131 638 61 454

ID023 187 1061 147 771 72 705

ID024 146 725 165 705 101 458

ID026 142 605 99 442 125 547

ID027 126 567 75 461 48 277

35 Appendix D

Activity

Fig 1 Mean daily movement during the study period GS 23-April-2012 to 07-Nov-2012 WS 08-Nov-2012 to

22-April-2013 (number indicates month)

Fig 2 Mean daily movement in the centre and south during the GS and WS

36

Appendix E

Habitat Proportions

Fig 1 All individualsrsquo seasonal habitat proportions within the UD95

37 Habitat Selection

Table 1 Simplified ranking matrices comparing proportional habitat use within the second order (UD95Area) with

proportions of total available habitat types Mean value on the matrix was replaced by a sign a triple sign represents

significant deviation from random at P lt05 Highlighted habitat is ranked 1st

North A

gri

cult

ure

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 --- --- - +++ --- --- --- +++ +++ --- 8

Broad Leaf +++ 0 +++ + +++ +++ +++ + +++ +++ +++ 1

Clear Fell +++ --- 0 + +++ - - --- +++ +++ --- 7

Coniferous + - - 0 +++ - - --- +++ +++ - 6

Freshwater --- --- --- --- 0 --- --- --- +++ - --- 10

Grassland

Moors +++ --- + + +++ 0 +++ - +++ +++ + 3

MiresMarshes +++ --- + + +++ --- 0 - +++ +++ --- 5

Mixed +++ - +++ +++ +++ + + 0 +++ +++ + 2

Sparse Veg --- --- --- --- --- --- --- --- 0 --- --- 11

Urban --- --- --- --- + --- --- --- +++ 0 --- 9

Younger +++ --- +++ + +++ - +++ - +++ +++ 0 4

Rank Order and

Significance

Broad Leafgt Mixedgt GrasslandMoorsgt Youngergtgtgt MiresMarshesgt Coniferousgt

Clear Fellgtgtgt Agriculturegtgtgt Urbangt Freshwatergtgtgt Sparse Veg

Central

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 --- --- --- + +++ + --- +++ +++ --- 6

Broad Leaf +++ 0 +++ + +++ +++ + - +++ +++ - 3

Clear Fell +++ --- 0 - +++ +++ + --- +++ +++ --- 5

Coniferous +++ - + 0 +++ +++ + --- +++ +++ - 4

Freshwater - --- --- --- 0 +++ - --- +++ +++ --- 8

Grassland

Moors --- --- --- --- --- 0 --- --- +++ - --- 10

MiresMarshes - - - - + +++ 0 - +++ +++ - 7

Mixed +++ + +++ +++ +++ +++ + 0 +++ +++ + 1

Sparse Veg --- --- --- --- --- --- --- --- 0 - --- 11

Urban --- --- --- --- --- + --- --- + 0 --- 9

Younger +++ + +++ + +++ +++ + - +++ +++ 0 2

Rank Order and

Significance

Mixedgt Youngergt Broad Leafgt Coniferousgt Clear Fellgtgtgt Agriculturegt

MiresMarshesgt Freshwatergtgtgt Urbangt GrasslandMoorsgtgtgt Sparse Veg

38

South

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 + - - + - + +++ +++ +++ - 5

Broad Leaf - 0 - - + - - +++ + +++ - 7

Clear Fell + + 0 - + + + +++ + +++ + 2

Coniferous + + + 0 +++ + + +++ + +++ + 1

Freshwater - - - --- 0 - - + + +++ - 8

Grassland

Moors + + - - + 0 + + +++ + - 4

MiresMarshes - + - - + - 0 +++ + +++ - 6

Mixed --- --- --- --- - - --- 0 + + --- 10

Sparse Veg --- - - - - --- - - 0 + - 9

Urban --- --- --- --- --- - --- - - 0 --- 11

Younger + + - - + + + +++ + +++ 0 3

Rank Order

and

Significance

Coniferousgt Clear Fellgt Youngergt GrasslandMoorsgt Agriculturegt MiresMarshesgt Broad Leafgt

Freshwatergt Sparse Veggt Mixedgt Urban

Table 2 Simplified ranking matrices comparing proportional habitat use within the third order (UD50UD95) with

proportions of total available habitat types Mean value on the matrix was replaced by a sign a triple sign represents

significant deviation from random at P lt05 Highlighted habitat is ranked 1st

North

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 --- --- --- - + --- --- + +++ --- 8

Broad Leaf +++ 0 +++ + + + + + +++ +++ + 1

Clear Fell +++ --- 0 + + + - - + +++ - 5

Coniferous +++ - - 0 + + --- --- +++ +++ - 6

Freshwater + - - - 0 +++ - - +++ +++ - 7

GrasslandMoors - - - - --- 0 - - - + - 10

MiresMarshes +++ - + +++ + + 0 - +++ +++ + 3

Mixed +++ - + +++ + + + 0 +++ +++ + 2

Sparse Veg - --- - --- --- + --- --- 0 +++ --- 9

Urban --- --- --- --- --- - --- --- --- 0 --- 11

Younger +++ - + + + + - - +++ +++ 0 4

Rank Order and

Significance

Broad Leafgt Mixedgt MiresMarshesgt Youngergt Clear Fellgt Coniferousgt Freshwatergt

Agriculturegt Sparse Veggt GrasslandMoorsgt Urban

39

Central

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 --- --- + + - - - + +++ --- 7

Broad Leaf +++ 0 + +++ + + + + + +++ - 2

Clear Fell +++ - 0 +++ + + + + + +++ - 3

Coniferous - --- --- 0 + - - --- +++ + --- 8

Freshwater - - - - 0 --- - - --- - - 11

GrasslandMoors + - - + +++ 0 + - + +++ - 5

MiresMarshes + - - + + - 0 + + +++ - 6

Mixed + - - +++ + + - 0 +++ +++ - 4

Sparse Veg - - - --- +++ - - --- 0 +++ - 9

Urban --- --- --- - + --- --- --- --- 0 --- 10

Younger +++ + + +++ + + + + + +++ 0 1

Rank Order and

Significance

Youngergt Broad Leafgt Clear Fellgt Mixedgt GrasslandMoorsgt MiresMarshesgt

Agriculturegt Coniferousgtgtgt Sparse Veggtgtgt Urbangt Freshwater

South

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 - - - - - + - +++ + --- 8

Broad Leaf + 0 - --- + - + - +++ + - 6

Clear Fell + + 0 - + - + - +++ + - 4

Coniferous + +++ + 0 + + +++ + +++ + + 1

Freshwater + - - - 0 - - + + + - 7

GrasslandMoors + + + - + 0 + + + + - 3

MiresMarshes - - - --- + - 0 - + + - 9

Mixed + + + - - - + 0 + + - 5

Sparse Veg --- --- --- --- - - - - 0 + --- 10

Urban - - - - - - - - - 0 - 11

Younger +++ + + - + + + + +++ + 0 2

Rank Order and

Significance

Coniferousgt Youngergt GrasslandMoorsgt Clear Fellgt Mixedgt Broad Leafgt Freshwatergt

Agriculturegt MiresMarshesgt Sparse Veggt Urban

40

Table 3 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the GS according to Jacobs index

Ran

k North Centre South

50 95 50 95 50 95

+ - + - + - + - + - + -

1 Broad

Leaf Urban Broad Leaf Sparse Veg

Broad

Leaf Urban Mixed Urban Coniferous Urban

Grassland

Moors Urban

2 Mixed Sparse Veg Mixed Freshwater Younger Agriculture Younger Sparse Veg Younger Sparse Veg Clear Fell Mixed

3 Mires

Agriculture Grassland

Urban Clear

Fell Coniferous Broad Leaf

Grassland

Moors

Clear Fell Agriculture Coniferous Sparse Veg

Marshes Moors

4 Younger Grassland

Younger Agriculture

Freshwater Coniferous Freshwater

Broad Leaf Mires

Younger Freshwater

Moors Marshes

5 Clear

Fell Freshwater

Mires Coniferous

Sparse Veg Clear Fell Agriculture

Freshwater Agriculture

Marshes

6 Coniferous Clear Fell

Mires

Marshes

Mires

Grassland

Moors

Mires

Marshes Marshes

7 Mixed Mixed Broad Leaf

8 Grassland

Moors

41

Table 4 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the WS according to Jacobs index

Ran

k North Centre South

50 95 50 95 50 95

+ - + - + - + - + - + -

1 Mires

Marshes

Grassland

Moors Mixed Freshwater Agriculture Urban Mixed Freshwater

Grassland

Moors Urban GrasslandMoors Urban

2 Freshwater Mixed Coniferous Urban Mires

Marshes Coniferous Sparse Veg Agriculture

Sparse

Veg Coniferous Freshwater

3 Urban Coniferous Younger Grassland

Moors Freshwater Younger Urban Freshwater

Broad

Leaf Agriculture Mixed

4 Younger Agriculture Sparse Veg Broad

Leaf

Broad

Leaf

Grassland

Moors Mixed Broad Leaf

5 Clear Fell Agriculture Coniferous Agriculture Mires

Marshes Clear Fell

6 Sparse

Veg

Mires

Marshes Mixed

Mires

Marshes

Clear

Fell

Mires

Marshes

7 Broad

Leaf Clear Fell Younger Clear Fell Younger Sparse Veg

8 Clear Fell Younger

9 Sparse

Veg

10 Grassland

Moors

42

Table 5 Second order (UD95Area) individual selectionavoidance for the GS and WS according to the Jacobs index

ID GS WS

Select Avoid Select Avoid

ID004 Younger Sparsely Vegetated MiresMarshes Sparsely Vegetated

ID005 MiresMarshes Sparsely Vegetated Coniferous GrasslandMoors

ID006 Coniferous Sparsely Vegetated Mixed Freshwater

ID008 Mixed Sparsely Vegetated Mixed Freshwater

ID009 Mixed Sparsely Vegetated Mixed GrasslandMoors

ID010 MiresMarshes Freshwater GrasslandMoors Freshwater

ID012 Broad Leaf Sparsely Vegetated Coniferous Urban

ID014 Clear Fell Sparsely Vegetated GrasslandMoors Sparsely Vegetated

ID015 GrasslandMoors Urban GrasslandMoors Freshwater

ID016 GrasslandMoors Freshwater GrasslandMoors Freshwater

ID017 GrasslandMoors Mixed Sparsely Vegetated Mixed

ID019 Mixed Sparsely Vegetated Mixed Urban

ID020 Broad Leaf Sparsely Vegetated Coniferous GrasslandMoors

ID022 MiresMarshes Freshwater MiresMarshes Freshwater

ID023 MiresMarshes GrasslandMoors Mixed Freshwater

ID024 Broadleaf Urban Broad Leaf Urban

ID026 GrasslandMoors Freshwater GrasslandMoors Freshwater

ID027 GrasslandMoors Urban Sparsely Vegetated Freshwater

43 Table 6 Third order (UD50UD95) individual selectionavoidance for the GS and WS according to the Jacobs index

ID GS WS

Select Avoid Select Avoid

ID004 Broad Leaf Mixed GrasslandMoors Freshwater

ID005 Broad Leaf Freshwater Agriculture Freshwater

ID006 Clear Fell Freshwater Agriculture MiresMarshes

ID008 MiresMarshes Freshwater Agriculture Urban

ID009 Freshwater Agriculture Agriculture Freshwater

ID010 Mixed Urban Sparsely Vegetated Urban

ID012 Coniferous GrasslandMoors Freshwater Urban

ID014 Urban Agriculture Freshwater Urban

ID015 Mixed Forest Urban Clear Fell Urban

ID016 Freshwater Urban GrasslandMoors Mixed

ID017 Coniferous Mixed Coniferous Broad Leaf

ID019 Broad Leaf GrasslandMoors Urban GrasslandMoors

ID020 Freshwater Urban Freshwater Agriculture

ID022 MiresMarshes Urban Broad Leaf GrasslandMoors

ID023 Freshwater Mixed Agriculture Freshwater

ID024 Mixed Freshwater Mixed Freshwater

ID026 Mixed MiresMarshes Sparsely Vegetated GrasslandMoors

ID027 Freshwater MiresMarshes GrasslandMoors Broad Leaf

44

Fig 2 North third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)

45

Fig 3 Centre third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)

46

Fig 4 South third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)

47

Fig 5 North second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)

48

Fig 6 Centre second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)

49

Fig 7 South second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)

50

Appendix F

Background

Fig 1 Daily mean snow depth and duration during the study period (Andrew Allen)

Female Moose Reproduction

Moose are seasonal polyoestral mammals (Monfort et al 1993) coming into oestrus during late September

early October (Garel et al 2009) The Swedish moose cow population reaches puberty between the ages 25

and 35 (Sand and Cederlund 1993) during which the reproductive period begins with the onset of ovulation

The age an individual reaches puberty is dependent on their body condition they have to reach a weight

threshold to reach puberty and become reproductive (Sand 1996) If she is over the weight threshold she will

go into oestrus in the autumn If she does not reach the weight threshold then she will go into oestrus the

following autumn if successful she will give birth to individual or twin calves in late May to early June

(Ericsson et al 2001) and therefore reach sexual maturity (Malmsten et al 2014b) Fecundity is related to

both the condition and the age of the cow Cows go through senescence at 12 years of age (Ericsson et al

2001) Providing calves with the required level of nutrition demands high energy and protein resources from

the mother during senescence this becomes harder to achieve leading to decreased levels of parental care

and higher levels of calf mortality

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32

Fig 2 Examples of classical kernel home range output and Brownian bridge kernel home range (Calenge 2011) The

right image includes the area between relocations ie the movement path in contrast to the classic kernel home range

in the left image

33 Appendix C

Home ranges

Fig 1 Example of a non-migratory (ID006) individuals BRB kernel area From top left annual growing and winter

season UD50 (black contour) and UD95 (red contour)

Fig 2 Example of a migratory (ID012) individuals BRB kernel area From the left annual growing and winter season

UD50 (black contour) and UD95 (red contour)

34

Table 1 Annual and seasonal UD50 and UD95 areas (ha) for all individuals

ID Annual GS WS

UD50 UD95 UD50 UD95 UD50 UD95

ID004 190 924 93 531 173 941

ID005 230 1364 132 945 72 682

ID006 162 1036 89 736 70 611

ID008 277 1536 156 809 78 738

ID009 137 834 48 295 126 653

ID010 114 682 83 448 96 488

ID012 177 963 123 544 76 545

ID014 160 1018 87 575 89 662

ID015 172 858 128 532 109 679

ID016 156 1047 65 455 92 534

ID017 153 1088 149 1043 69 349

ID019 279 1097 176 911 163 824

ID020 139 1084 67 349 160 794

ID022 159 811 131 638 61 454

ID023 187 1061 147 771 72 705

ID024 146 725 165 705 101 458

ID026 142 605 99 442 125 547

ID027 126 567 75 461 48 277

35 Appendix D

Activity

Fig 1 Mean daily movement during the study period GS 23-April-2012 to 07-Nov-2012 WS 08-Nov-2012 to

22-April-2013 (number indicates month)

Fig 2 Mean daily movement in the centre and south during the GS and WS

36

Appendix E

Habitat Proportions

Fig 1 All individualsrsquo seasonal habitat proportions within the UD95

37 Habitat Selection

Table 1 Simplified ranking matrices comparing proportional habitat use within the second order (UD95Area) with

proportions of total available habitat types Mean value on the matrix was replaced by a sign a triple sign represents

significant deviation from random at P lt05 Highlighted habitat is ranked 1st

North A

gri

cult

ure

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 --- --- - +++ --- --- --- +++ +++ --- 8

Broad Leaf +++ 0 +++ + +++ +++ +++ + +++ +++ +++ 1

Clear Fell +++ --- 0 + +++ - - --- +++ +++ --- 7

Coniferous + - - 0 +++ - - --- +++ +++ - 6

Freshwater --- --- --- --- 0 --- --- --- +++ - --- 10

Grassland

Moors +++ --- + + +++ 0 +++ - +++ +++ + 3

MiresMarshes +++ --- + + +++ --- 0 - +++ +++ --- 5

Mixed +++ - +++ +++ +++ + + 0 +++ +++ + 2

Sparse Veg --- --- --- --- --- --- --- --- 0 --- --- 11

Urban --- --- --- --- + --- --- --- +++ 0 --- 9

Younger +++ --- +++ + +++ - +++ - +++ +++ 0 4

Rank Order and

Significance

Broad Leafgt Mixedgt GrasslandMoorsgt Youngergtgtgt MiresMarshesgt Coniferousgt

Clear Fellgtgtgt Agriculturegtgtgt Urbangt Freshwatergtgtgt Sparse Veg

Central

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 --- --- --- + +++ + --- +++ +++ --- 6

Broad Leaf +++ 0 +++ + +++ +++ + - +++ +++ - 3

Clear Fell +++ --- 0 - +++ +++ + --- +++ +++ --- 5

Coniferous +++ - + 0 +++ +++ + --- +++ +++ - 4

Freshwater - --- --- --- 0 +++ - --- +++ +++ --- 8

Grassland

Moors --- --- --- --- --- 0 --- --- +++ - --- 10

MiresMarshes - - - - + +++ 0 - +++ +++ - 7

Mixed +++ + +++ +++ +++ +++ + 0 +++ +++ + 1

Sparse Veg --- --- --- --- --- --- --- --- 0 - --- 11

Urban --- --- --- --- --- + --- --- + 0 --- 9

Younger +++ + +++ + +++ +++ + - +++ +++ 0 2

Rank Order and

Significance

Mixedgt Youngergt Broad Leafgt Coniferousgt Clear Fellgtgtgt Agriculturegt

MiresMarshesgt Freshwatergtgtgt Urbangt GrasslandMoorsgtgtgt Sparse Veg

38

South

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 + - - + - + +++ +++ +++ - 5

Broad Leaf - 0 - - + - - +++ + +++ - 7

Clear Fell + + 0 - + + + +++ + +++ + 2

Coniferous + + + 0 +++ + + +++ + +++ + 1

Freshwater - - - --- 0 - - + + +++ - 8

Grassland

Moors + + - - + 0 + + +++ + - 4

MiresMarshes - + - - + - 0 +++ + +++ - 6

Mixed --- --- --- --- - - --- 0 + + --- 10

Sparse Veg --- - - - - --- - - 0 + - 9

Urban --- --- --- --- --- - --- - - 0 --- 11

Younger + + - - + + + +++ + +++ 0 3

Rank Order

and

Significance

Coniferousgt Clear Fellgt Youngergt GrasslandMoorsgt Agriculturegt MiresMarshesgt Broad Leafgt

Freshwatergt Sparse Veggt Mixedgt Urban

Table 2 Simplified ranking matrices comparing proportional habitat use within the third order (UD50UD95) with

proportions of total available habitat types Mean value on the matrix was replaced by a sign a triple sign represents

significant deviation from random at P lt05 Highlighted habitat is ranked 1st

North

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 --- --- --- - + --- --- + +++ --- 8

Broad Leaf +++ 0 +++ + + + + + +++ +++ + 1

Clear Fell +++ --- 0 + + + - - + +++ - 5

Coniferous +++ - - 0 + + --- --- +++ +++ - 6

Freshwater + - - - 0 +++ - - +++ +++ - 7

GrasslandMoors - - - - --- 0 - - - + - 10

MiresMarshes +++ - + +++ + + 0 - +++ +++ + 3

Mixed +++ - + +++ + + + 0 +++ +++ + 2

Sparse Veg - --- - --- --- + --- --- 0 +++ --- 9

Urban --- --- --- --- --- - --- --- --- 0 --- 11

Younger +++ - + + + + - - +++ +++ 0 4

Rank Order and

Significance

Broad Leafgt Mixedgt MiresMarshesgt Youngergt Clear Fellgt Coniferousgt Freshwatergt

Agriculturegt Sparse Veggt GrasslandMoorsgt Urban

39

Central

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 --- --- + + - - - + +++ --- 7

Broad Leaf +++ 0 + +++ + + + + + +++ - 2

Clear Fell +++ - 0 +++ + + + + + +++ - 3

Coniferous - --- --- 0 + - - --- +++ + --- 8

Freshwater - - - - 0 --- - - --- - - 11

GrasslandMoors + - - + +++ 0 + - + +++ - 5

MiresMarshes + - - + + - 0 + + +++ - 6

Mixed + - - +++ + + - 0 +++ +++ - 4

Sparse Veg - - - --- +++ - - --- 0 +++ - 9

Urban --- --- --- - + --- --- --- --- 0 --- 10

Younger +++ + + +++ + + + + + +++ 0 1

Rank Order and

Significance

Youngergt Broad Leafgt Clear Fellgt Mixedgt GrasslandMoorsgt MiresMarshesgt

Agriculturegt Coniferousgtgtgt Sparse Veggtgtgt Urbangt Freshwater

South

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 - - - - - + - +++ + --- 8

Broad Leaf + 0 - --- + - + - +++ + - 6

Clear Fell + + 0 - + - + - +++ + - 4

Coniferous + +++ + 0 + + +++ + +++ + + 1

Freshwater + - - - 0 - - + + + - 7

GrasslandMoors + + + - + 0 + + + + - 3

MiresMarshes - - - --- + - 0 - + + - 9

Mixed + + + - - - + 0 + + - 5

Sparse Veg --- --- --- --- - - - - 0 + --- 10

Urban - - - - - - - - - 0 - 11

Younger +++ + + - + + + + +++ + 0 2

Rank Order and

Significance

Coniferousgt Youngergt GrasslandMoorsgt Clear Fellgt Mixedgt Broad Leafgt Freshwatergt

Agriculturegt MiresMarshesgt Sparse Veggt Urban

40

Table 3 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the GS according to Jacobs index

Ran

k North Centre South

50 95 50 95 50 95

+ - + - + - + - + - + -

1 Broad

Leaf Urban Broad Leaf Sparse Veg

Broad

Leaf Urban Mixed Urban Coniferous Urban

Grassland

Moors Urban

2 Mixed Sparse Veg Mixed Freshwater Younger Agriculture Younger Sparse Veg Younger Sparse Veg Clear Fell Mixed

3 Mires

Agriculture Grassland

Urban Clear

Fell Coniferous Broad Leaf

Grassland

Moors

Clear Fell Agriculture Coniferous Sparse Veg

Marshes Moors

4 Younger Grassland

Younger Agriculture

Freshwater Coniferous Freshwater

Broad Leaf Mires

Younger Freshwater

Moors Marshes

5 Clear

Fell Freshwater

Mires Coniferous

Sparse Veg Clear Fell Agriculture

Freshwater Agriculture

Marshes

6 Coniferous Clear Fell

Mires

Marshes

Mires

Grassland

Moors

Mires

Marshes Marshes

7 Mixed Mixed Broad Leaf

8 Grassland

Moors

41

Table 4 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the WS according to Jacobs index

Ran

k North Centre South

50 95 50 95 50 95

+ - + - + - + - + - + -

1 Mires

Marshes

Grassland

Moors Mixed Freshwater Agriculture Urban Mixed Freshwater

Grassland

Moors Urban GrasslandMoors Urban

2 Freshwater Mixed Coniferous Urban Mires

Marshes Coniferous Sparse Veg Agriculture

Sparse

Veg Coniferous Freshwater

3 Urban Coniferous Younger Grassland

Moors Freshwater Younger Urban Freshwater

Broad

Leaf Agriculture Mixed

4 Younger Agriculture Sparse Veg Broad

Leaf

Broad

Leaf

Grassland

Moors Mixed Broad Leaf

5 Clear Fell Agriculture Coniferous Agriculture Mires

Marshes Clear Fell

6 Sparse

Veg

Mires

Marshes Mixed

Mires

Marshes

Clear

Fell

Mires

Marshes

7 Broad

Leaf Clear Fell Younger Clear Fell Younger Sparse Veg

8 Clear Fell Younger

9 Sparse

Veg

10 Grassland

Moors

42

Table 5 Second order (UD95Area) individual selectionavoidance for the GS and WS according to the Jacobs index

ID GS WS

Select Avoid Select Avoid

ID004 Younger Sparsely Vegetated MiresMarshes Sparsely Vegetated

ID005 MiresMarshes Sparsely Vegetated Coniferous GrasslandMoors

ID006 Coniferous Sparsely Vegetated Mixed Freshwater

ID008 Mixed Sparsely Vegetated Mixed Freshwater

ID009 Mixed Sparsely Vegetated Mixed GrasslandMoors

ID010 MiresMarshes Freshwater GrasslandMoors Freshwater

ID012 Broad Leaf Sparsely Vegetated Coniferous Urban

ID014 Clear Fell Sparsely Vegetated GrasslandMoors Sparsely Vegetated

ID015 GrasslandMoors Urban GrasslandMoors Freshwater

ID016 GrasslandMoors Freshwater GrasslandMoors Freshwater

ID017 GrasslandMoors Mixed Sparsely Vegetated Mixed

ID019 Mixed Sparsely Vegetated Mixed Urban

ID020 Broad Leaf Sparsely Vegetated Coniferous GrasslandMoors

ID022 MiresMarshes Freshwater MiresMarshes Freshwater

ID023 MiresMarshes GrasslandMoors Mixed Freshwater

ID024 Broadleaf Urban Broad Leaf Urban

ID026 GrasslandMoors Freshwater GrasslandMoors Freshwater

ID027 GrasslandMoors Urban Sparsely Vegetated Freshwater

43 Table 6 Third order (UD50UD95) individual selectionavoidance for the GS and WS according to the Jacobs index

ID GS WS

Select Avoid Select Avoid

ID004 Broad Leaf Mixed GrasslandMoors Freshwater

ID005 Broad Leaf Freshwater Agriculture Freshwater

ID006 Clear Fell Freshwater Agriculture MiresMarshes

ID008 MiresMarshes Freshwater Agriculture Urban

ID009 Freshwater Agriculture Agriculture Freshwater

ID010 Mixed Urban Sparsely Vegetated Urban

ID012 Coniferous GrasslandMoors Freshwater Urban

ID014 Urban Agriculture Freshwater Urban

ID015 Mixed Forest Urban Clear Fell Urban

ID016 Freshwater Urban GrasslandMoors Mixed

ID017 Coniferous Mixed Coniferous Broad Leaf

ID019 Broad Leaf GrasslandMoors Urban GrasslandMoors

ID020 Freshwater Urban Freshwater Agriculture

ID022 MiresMarshes Urban Broad Leaf GrasslandMoors

ID023 Freshwater Mixed Agriculture Freshwater

ID024 Mixed Freshwater Mixed Freshwater

ID026 Mixed MiresMarshes Sparsely Vegetated GrasslandMoors

ID027 Freshwater MiresMarshes GrasslandMoors Broad Leaf

44

Fig 2 North third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)

45

Fig 3 Centre third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)

46

Fig 4 South third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)

47

Fig 5 North second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)

48

Fig 6 Centre second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)

49

Fig 7 South second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)

50

Appendix F

Background

Fig 1 Daily mean snow depth and duration during the study period (Andrew Allen)

Female Moose Reproduction

Moose are seasonal polyoestral mammals (Monfort et al 1993) coming into oestrus during late September

early October (Garel et al 2009) The Swedish moose cow population reaches puberty between the ages 25

and 35 (Sand and Cederlund 1993) during which the reproductive period begins with the onset of ovulation

The age an individual reaches puberty is dependent on their body condition they have to reach a weight

threshold to reach puberty and become reproductive (Sand 1996) If she is over the weight threshold she will

go into oestrus in the autumn If she does not reach the weight threshold then she will go into oestrus the

following autumn if successful she will give birth to individual or twin calves in late May to early June

(Ericsson et al 2001) and therefore reach sexual maturity (Malmsten et al 2014b) Fecundity is related to

both the condition and the age of the cow Cows go through senescence at 12 years of age (Ericsson et al

2001) Providing calves with the required level of nutrition demands high energy and protein resources from

the mother during senescence this becomes harder to achieve leading to decreased levels of parental care

and higher levels of calf mortality

Page 33: Habitat-performance relationships on an island: fitness ...navinderjsingh.weebly.com/uploads/1/1/2/2/11224342/... · Conditions on Öland are milder than those found in other areas

33 Appendix C

Home ranges

Fig 1 Example of a non-migratory (ID006) individuals BRB kernel area From top left annual growing and winter

season UD50 (black contour) and UD95 (red contour)

Fig 2 Example of a migratory (ID012) individuals BRB kernel area From the left annual growing and winter season

UD50 (black contour) and UD95 (red contour)

34

Table 1 Annual and seasonal UD50 and UD95 areas (ha) for all individuals

ID Annual GS WS

UD50 UD95 UD50 UD95 UD50 UD95

ID004 190 924 93 531 173 941

ID005 230 1364 132 945 72 682

ID006 162 1036 89 736 70 611

ID008 277 1536 156 809 78 738

ID009 137 834 48 295 126 653

ID010 114 682 83 448 96 488

ID012 177 963 123 544 76 545

ID014 160 1018 87 575 89 662

ID015 172 858 128 532 109 679

ID016 156 1047 65 455 92 534

ID017 153 1088 149 1043 69 349

ID019 279 1097 176 911 163 824

ID020 139 1084 67 349 160 794

ID022 159 811 131 638 61 454

ID023 187 1061 147 771 72 705

ID024 146 725 165 705 101 458

ID026 142 605 99 442 125 547

ID027 126 567 75 461 48 277

35 Appendix D

Activity

Fig 1 Mean daily movement during the study period GS 23-April-2012 to 07-Nov-2012 WS 08-Nov-2012 to

22-April-2013 (number indicates month)

Fig 2 Mean daily movement in the centre and south during the GS and WS

36

Appendix E

Habitat Proportions

Fig 1 All individualsrsquo seasonal habitat proportions within the UD95

37 Habitat Selection

Table 1 Simplified ranking matrices comparing proportional habitat use within the second order (UD95Area) with

proportions of total available habitat types Mean value on the matrix was replaced by a sign a triple sign represents

significant deviation from random at P lt05 Highlighted habitat is ranked 1st

North A

gri

cult

ure

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 --- --- - +++ --- --- --- +++ +++ --- 8

Broad Leaf +++ 0 +++ + +++ +++ +++ + +++ +++ +++ 1

Clear Fell +++ --- 0 + +++ - - --- +++ +++ --- 7

Coniferous + - - 0 +++ - - --- +++ +++ - 6

Freshwater --- --- --- --- 0 --- --- --- +++ - --- 10

Grassland

Moors +++ --- + + +++ 0 +++ - +++ +++ + 3

MiresMarshes +++ --- + + +++ --- 0 - +++ +++ --- 5

Mixed +++ - +++ +++ +++ + + 0 +++ +++ + 2

Sparse Veg --- --- --- --- --- --- --- --- 0 --- --- 11

Urban --- --- --- --- + --- --- --- +++ 0 --- 9

Younger +++ --- +++ + +++ - +++ - +++ +++ 0 4

Rank Order and

Significance

Broad Leafgt Mixedgt GrasslandMoorsgt Youngergtgtgt MiresMarshesgt Coniferousgt

Clear Fellgtgtgt Agriculturegtgtgt Urbangt Freshwatergtgtgt Sparse Veg

Central

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 --- --- --- + +++ + --- +++ +++ --- 6

Broad Leaf +++ 0 +++ + +++ +++ + - +++ +++ - 3

Clear Fell +++ --- 0 - +++ +++ + --- +++ +++ --- 5

Coniferous +++ - + 0 +++ +++ + --- +++ +++ - 4

Freshwater - --- --- --- 0 +++ - --- +++ +++ --- 8

Grassland

Moors --- --- --- --- --- 0 --- --- +++ - --- 10

MiresMarshes - - - - + +++ 0 - +++ +++ - 7

Mixed +++ + +++ +++ +++ +++ + 0 +++ +++ + 1

Sparse Veg --- --- --- --- --- --- --- --- 0 - --- 11

Urban --- --- --- --- --- + --- --- + 0 --- 9

Younger +++ + +++ + +++ +++ + - +++ +++ 0 2

Rank Order and

Significance

Mixedgt Youngergt Broad Leafgt Coniferousgt Clear Fellgtgtgt Agriculturegt

MiresMarshesgt Freshwatergtgtgt Urbangt GrasslandMoorsgtgtgt Sparse Veg

38

South

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 + - - + - + +++ +++ +++ - 5

Broad Leaf - 0 - - + - - +++ + +++ - 7

Clear Fell + + 0 - + + + +++ + +++ + 2

Coniferous + + + 0 +++ + + +++ + +++ + 1

Freshwater - - - --- 0 - - + + +++ - 8

Grassland

Moors + + - - + 0 + + +++ + - 4

MiresMarshes - + - - + - 0 +++ + +++ - 6

Mixed --- --- --- --- - - --- 0 + + --- 10

Sparse Veg --- - - - - --- - - 0 + - 9

Urban --- --- --- --- --- - --- - - 0 --- 11

Younger + + - - + + + +++ + +++ 0 3

Rank Order

and

Significance

Coniferousgt Clear Fellgt Youngergt GrasslandMoorsgt Agriculturegt MiresMarshesgt Broad Leafgt

Freshwatergt Sparse Veggt Mixedgt Urban

Table 2 Simplified ranking matrices comparing proportional habitat use within the third order (UD50UD95) with

proportions of total available habitat types Mean value on the matrix was replaced by a sign a triple sign represents

significant deviation from random at P lt05 Highlighted habitat is ranked 1st

North

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 --- --- --- - + --- --- + +++ --- 8

Broad Leaf +++ 0 +++ + + + + + +++ +++ + 1

Clear Fell +++ --- 0 + + + - - + +++ - 5

Coniferous +++ - - 0 + + --- --- +++ +++ - 6

Freshwater + - - - 0 +++ - - +++ +++ - 7

GrasslandMoors - - - - --- 0 - - - + - 10

MiresMarshes +++ - + +++ + + 0 - +++ +++ + 3

Mixed +++ - + +++ + + + 0 +++ +++ + 2

Sparse Veg - --- - --- --- + --- --- 0 +++ --- 9

Urban --- --- --- --- --- - --- --- --- 0 --- 11

Younger +++ - + + + + - - +++ +++ 0 4

Rank Order and

Significance

Broad Leafgt Mixedgt MiresMarshesgt Youngergt Clear Fellgt Coniferousgt Freshwatergt

Agriculturegt Sparse Veggt GrasslandMoorsgt Urban

39

Central

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 --- --- + + - - - + +++ --- 7

Broad Leaf +++ 0 + +++ + + + + + +++ - 2

Clear Fell +++ - 0 +++ + + + + + +++ - 3

Coniferous - --- --- 0 + - - --- +++ + --- 8

Freshwater - - - - 0 --- - - --- - - 11

GrasslandMoors + - - + +++ 0 + - + +++ - 5

MiresMarshes + - - + + - 0 + + +++ - 6

Mixed + - - +++ + + - 0 +++ +++ - 4

Sparse Veg - - - --- +++ - - --- 0 +++ - 9

Urban --- --- --- - + --- --- --- --- 0 --- 10

Younger +++ + + +++ + + + + + +++ 0 1

Rank Order and

Significance

Youngergt Broad Leafgt Clear Fellgt Mixedgt GrasslandMoorsgt MiresMarshesgt

Agriculturegt Coniferousgtgtgt Sparse Veggtgtgt Urbangt Freshwater

South

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 - - - - - + - +++ + --- 8

Broad Leaf + 0 - --- + - + - +++ + - 6

Clear Fell + + 0 - + - + - +++ + - 4

Coniferous + +++ + 0 + + +++ + +++ + + 1

Freshwater + - - - 0 - - + + + - 7

GrasslandMoors + + + - + 0 + + + + - 3

MiresMarshes - - - --- + - 0 - + + - 9

Mixed + + + - - - + 0 + + - 5

Sparse Veg --- --- --- --- - - - - 0 + --- 10

Urban - - - - - - - - - 0 - 11

Younger +++ + + - + + + + +++ + 0 2

Rank Order and

Significance

Coniferousgt Youngergt GrasslandMoorsgt Clear Fellgt Mixedgt Broad Leafgt Freshwatergt

Agriculturegt MiresMarshesgt Sparse Veggt Urban

40

Table 3 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the GS according to Jacobs index

Ran

k North Centre South

50 95 50 95 50 95

+ - + - + - + - + - + -

1 Broad

Leaf Urban Broad Leaf Sparse Veg

Broad

Leaf Urban Mixed Urban Coniferous Urban

Grassland

Moors Urban

2 Mixed Sparse Veg Mixed Freshwater Younger Agriculture Younger Sparse Veg Younger Sparse Veg Clear Fell Mixed

3 Mires

Agriculture Grassland

Urban Clear

Fell Coniferous Broad Leaf

Grassland

Moors

Clear Fell Agriculture Coniferous Sparse Veg

Marshes Moors

4 Younger Grassland

Younger Agriculture

Freshwater Coniferous Freshwater

Broad Leaf Mires

Younger Freshwater

Moors Marshes

5 Clear

Fell Freshwater

Mires Coniferous

Sparse Veg Clear Fell Agriculture

Freshwater Agriculture

Marshes

6 Coniferous Clear Fell

Mires

Marshes

Mires

Grassland

Moors

Mires

Marshes Marshes

7 Mixed Mixed Broad Leaf

8 Grassland

Moors

41

Table 4 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the WS according to Jacobs index

Ran

k North Centre South

50 95 50 95 50 95

+ - + - + - + - + - + -

1 Mires

Marshes

Grassland

Moors Mixed Freshwater Agriculture Urban Mixed Freshwater

Grassland

Moors Urban GrasslandMoors Urban

2 Freshwater Mixed Coniferous Urban Mires

Marshes Coniferous Sparse Veg Agriculture

Sparse

Veg Coniferous Freshwater

3 Urban Coniferous Younger Grassland

Moors Freshwater Younger Urban Freshwater

Broad

Leaf Agriculture Mixed

4 Younger Agriculture Sparse Veg Broad

Leaf

Broad

Leaf

Grassland

Moors Mixed Broad Leaf

5 Clear Fell Agriculture Coniferous Agriculture Mires

Marshes Clear Fell

6 Sparse

Veg

Mires

Marshes Mixed

Mires

Marshes

Clear

Fell

Mires

Marshes

7 Broad

Leaf Clear Fell Younger Clear Fell Younger Sparse Veg

8 Clear Fell Younger

9 Sparse

Veg

10 Grassland

Moors

42

Table 5 Second order (UD95Area) individual selectionavoidance for the GS and WS according to the Jacobs index

ID GS WS

Select Avoid Select Avoid

ID004 Younger Sparsely Vegetated MiresMarshes Sparsely Vegetated

ID005 MiresMarshes Sparsely Vegetated Coniferous GrasslandMoors

ID006 Coniferous Sparsely Vegetated Mixed Freshwater

ID008 Mixed Sparsely Vegetated Mixed Freshwater

ID009 Mixed Sparsely Vegetated Mixed GrasslandMoors

ID010 MiresMarshes Freshwater GrasslandMoors Freshwater

ID012 Broad Leaf Sparsely Vegetated Coniferous Urban

ID014 Clear Fell Sparsely Vegetated GrasslandMoors Sparsely Vegetated

ID015 GrasslandMoors Urban GrasslandMoors Freshwater

ID016 GrasslandMoors Freshwater GrasslandMoors Freshwater

ID017 GrasslandMoors Mixed Sparsely Vegetated Mixed

ID019 Mixed Sparsely Vegetated Mixed Urban

ID020 Broad Leaf Sparsely Vegetated Coniferous GrasslandMoors

ID022 MiresMarshes Freshwater MiresMarshes Freshwater

ID023 MiresMarshes GrasslandMoors Mixed Freshwater

ID024 Broadleaf Urban Broad Leaf Urban

ID026 GrasslandMoors Freshwater GrasslandMoors Freshwater

ID027 GrasslandMoors Urban Sparsely Vegetated Freshwater

43 Table 6 Third order (UD50UD95) individual selectionavoidance for the GS and WS according to the Jacobs index

ID GS WS

Select Avoid Select Avoid

ID004 Broad Leaf Mixed GrasslandMoors Freshwater

ID005 Broad Leaf Freshwater Agriculture Freshwater

ID006 Clear Fell Freshwater Agriculture MiresMarshes

ID008 MiresMarshes Freshwater Agriculture Urban

ID009 Freshwater Agriculture Agriculture Freshwater

ID010 Mixed Urban Sparsely Vegetated Urban

ID012 Coniferous GrasslandMoors Freshwater Urban

ID014 Urban Agriculture Freshwater Urban

ID015 Mixed Forest Urban Clear Fell Urban

ID016 Freshwater Urban GrasslandMoors Mixed

ID017 Coniferous Mixed Coniferous Broad Leaf

ID019 Broad Leaf GrasslandMoors Urban GrasslandMoors

ID020 Freshwater Urban Freshwater Agriculture

ID022 MiresMarshes Urban Broad Leaf GrasslandMoors

ID023 Freshwater Mixed Agriculture Freshwater

ID024 Mixed Freshwater Mixed Freshwater

ID026 Mixed MiresMarshes Sparsely Vegetated GrasslandMoors

ID027 Freshwater MiresMarshes GrasslandMoors Broad Leaf

44

Fig 2 North third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)

45

Fig 3 Centre third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)

46

Fig 4 South third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)

47

Fig 5 North second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)

48

Fig 6 Centre second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)

49

Fig 7 South second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)

50

Appendix F

Background

Fig 1 Daily mean snow depth and duration during the study period (Andrew Allen)

Female Moose Reproduction

Moose are seasonal polyoestral mammals (Monfort et al 1993) coming into oestrus during late September

early October (Garel et al 2009) The Swedish moose cow population reaches puberty between the ages 25

and 35 (Sand and Cederlund 1993) during which the reproductive period begins with the onset of ovulation

The age an individual reaches puberty is dependent on their body condition they have to reach a weight

threshold to reach puberty and become reproductive (Sand 1996) If she is over the weight threshold she will

go into oestrus in the autumn If she does not reach the weight threshold then she will go into oestrus the

following autumn if successful she will give birth to individual or twin calves in late May to early June

(Ericsson et al 2001) and therefore reach sexual maturity (Malmsten et al 2014b) Fecundity is related to

both the condition and the age of the cow Cows go through senescence at 12 years of age (Ericsson et al

2001) Providing calves with the required level of nutrition demands high energy and protein resources from

the mother during senescence this becomes harder to achieve leading to decreased levels of parental care

and higher levels of calf mortality

Page 34: Habitat-performance relationships on an island: fitness ...navinderjsingh.weebly.com/uploads/1/1/2/2/11224342/... · Conditions on Öland are milder than those found in other areas

34

Table 1 Annual and seasonal UD50 and UD95 areas (ha) for all individuals

ID Annual GS WS

UD50 UD95 UD50 UD95 UD50 UD95

ID004 190 924 93 531 173 941

ID005 230 1364 132 945 72 682

ID006 162 1036 89 736 70 611

ID008 277 1536 156 809 78 738

ID009 137 834 48 295 126 653

ID010 114 682 83 448 96 488

ID012 177 963 123 544 76 545

ID014 160 1018 87 575 89 662

ID015 172 858 128 532 109 679

ID016 156 1047 65 455 92 534

ID017 153 1088 149 1043 69 349

ID019 279 1097 176 911 163 824

ID020 139 1084 67 349 160 794

ID022 159 811 131 638 61 454

ID023 187 1061 147 771 72 705

ID024 146 725 165 705 101 458

ID026 142 605 99 442 125 547

ID027 126 567 75 461 48 277

35 Appendix D

Activity

Fig 1 Mean daily movement during the study period GS 23-April-2012 to 07-Nov-2012 WS 08-Nov-2012 to

22-April-2013 (number indicates month)

Fig 2 Mean daily movement in the centre and south during the GS and WS

36

Appendix E

Habitat Proportions

Fig 1 All individualsrsquo seasonal habitat proportions within the UD95

37 Habitat Selection

Table 1 Simplified ranking matrices comparing proportional habitat use within the second order (UD95Area) with

proportions of total available habitat types Mean value on the matrix was replaced by a sign a triple sign represents

significant deviation from random at P lt05 Highlighted habitat is ranked 1st

North A

gri

cult

ure

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 --- --- - +++ --- --- --- +++ +++ --- 8

Broad Leaf +++ 0 +++ + +++ +++ +++ + +++ +++ +++ 1

Clear Fell +++ --- 0 + +++ - - --- +++ +++ --- 7

Coniferous + - - 0 +++ - - --- +++ +++ - 6

Freshwater --- --- --- --- 0 --- --- --- +++ - --- 10

Grassland

Moors +++ --- + + +++ 0 +++ - +++ +++ + 3

MiresMarshes +++ --- + + +++ --- 0 - +++ +++ --- 5

Mixed +++ - +++ +++ +++ + + 0 +++ +++ + 2

Sparse Veg --- --- --- --- --- --- --- --- 0 --- --- 11

Urban --- --- --- --- + --- --- --- +++ 0 --- 9

Younger +++ --- +++ + +++ - +++ - +++ +++ 0 4

Rank Order and

Significance

Broad Leafgt Mixedgt GrasslandMoorsgt Youngergtgtgt MiresMarshesgt Coniferousgt

Clear Fellgtgtgt Agriculturegtgtgt Urbangt Freshwatergtgtgt Sparse Veg

Central

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 --- --- --- + +++ + --- +++ +++ --- 6

Broad Leaf +++ 0 +++ + +++ +++ + - +++ +++ - 3

Clear Fell +++ --- 0 - +++ +++ + --- +++ +++ --- 5

Coniferous +++ - + 0 +++ +++ + --- +++ +++ - 4

Freshwater - --- --- --- 0 +++ - --- +++ +++ --- 8

Grassland

Moors --- --- --- --- --- 0 --- --- +++ - --- 10

MiresMarshes - - - - + +++ 0 - +++ +++ - 7

Mixed +++ + +++ +++ +++ +++ + 0 +++ +++ + 1

Sparse Veg --- --- --- --- --- --- --- --- 0 - --- 11

Urban --- --- --- --- --- + --- --- + 0 --- 9

Younger +++ + +++ + +++ +++ + - +++ +++ 0 2

Rank Order and

Significance

Mixedgt Youngergt Broad Leafgt Coniferousgt Clear Fellgtgtgt Agriculturegt

MiresMarshesgt Freshwatergtgtgt Urbangt GrasslandMoorsgtgtgt Sparse Veg

38

South

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 + - - + - + +++ +++ +++ - 5

Broad Leaf - 0 - - + - - +++ + +++ - 7

Clear Fell + + 0 - + + + +++ + +++ + 2

Coniferous + + + 0 +++ + + +++ + +++ + 1

Freshwater - - - --- 0 - - + + +++ - 8

Grassland

Moors + + - - + 0 + + +++ + - 4

MiresMarshes - + - - + - 0 +++ + +++ - 6

Mixed --- --- --- --- - - --- 0 + + --- 10

Sparse Veg --- - - - - --- - - 0 + - 9

Urban --- --- --- --- --- - --- - - 0 --- 11

Younger + + - - + + + +++ + +++ 0 3

Rank Order

and

Significance

Coniferousgt Clear Fellgt Youngergt GrasslandMoorsgt Agriculturegt MiresMarshesgt Broad Leafgt

Freshwatergt Sparse Veggt Mixedgt Urban

Table 2 Simplified ranking matrices comparing proportional habitat use within the third order (UD50UD95) with

proportions of total available habitat types Mean value on the matrix was replaced by a sign a triple sign represents

significant deviation from random at P lt05 Highlighted habitat is ranked 1st

North

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 --- --- --- - + --- --- + +++ --- 8

Broad Leaf +++ 0 +++ + + + + + +++ +++ + 1

Clear Fell +++ --- 0 + + + - - + +++ - 5

Coniferous +++ - - 0 + + --- --- +++ +++ - 6

Freshwater + - - - 0 +++ - - +++ +++ - 7

GrasslandMoors - - - - --- 0 - - - + - 10

MiresMarshes +++ - + +++ + + 0 - +++ +++ + 3

Mixed +++ - + +++ + + + 0 +++ +++ + 2

Sparse Veg - --- - --- --- + --- --- 0 +++ --- 9

Urban --- --- --- --- --- - --- --- --- 0 --- 11

Younger +++ - + + + + - - +++ +++ 0 4

Rank Order and

Significance

Broad Leafgt Mixedgt MiresMarshesgt Youngergt Clear Fellgt Coniferousgt Freshwatergt

Agriculturegt Sparse Veggt GrasslandMoorsgt Urban

39

Central

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 --- --- + + - - - + +++ --- 7

Broad Leaf +++ 0 + +++ + + + + + +++ - 2

Clear Fell +++ - 0 +++ + + + + + +++ - 3

Coniferous - --- --- 0 + - - --- +++ + --- 8

Freshwater - - - - 0 --- - - --- - - 11

GrasslandMoors + - - + +++ 0 + - + +++ - 5

MiresMarshes + - - + + - 0 + + +++ - 6

Mixed + - - +++ + + - 0 +++ +++ - 4

Sparse Veg - - - --- +++ - - --- 0 +++ - 9

Urban --- --- --- - + --- --- --- --- 0 --- 10

Younger +++ + + +++ + + + + + +++ 0 1

Rank Order and

Significance

Youngergt Broad Leafgt Clear Fellgt Mixedgt GrasslandMoorsgt MiresMarshesgt

Agriculturegt Coniferousgtgtgt Sparse Veggtgtgt Urbangt Freshwater

South

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 - - - - - + - +++ + --- 8

Broad Leaf + 0 - --- + - + - +++ + - 6

Clear Fell + + 0 - + - + - +++ + - 4

Coniferous + +++ + 0 + + +++ + +++ + + 1

Freshwater + - - - 0 - - + + + - 7

GrasslandMoors + + + - + 0 + + + + - 3

MiresMarshes - - - --- + - 0 - + + - 9

Mixed + + + - - - + 0 + + - 5

Sparse Veg --- --- --- --- - - - - 0 + --- 10

Urban - - - - - - - - - 0 - 11

Younger +++ + + - + + + + +++ + 0 2

Rank Order and

Significance

Coniferousgt Youngergt GrasslandMoorsgt Clear Fellgt Mixedgt Broad Leafgt Freshwatergt

Agriculturegt MiresMarshesgt Sparse Veggt Urban

40

Table 3 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the GS according to Jacobs index

Ran

k North Centre South

50 95 50 95 50 95

+ - + - + - + - + - + -

1 Broad

Leaf Urban Broad Leaf Sparse Veg

Broad

Leaf Urban Mixed Urban Coniferous Urban

Grassland

Moors Urban

2 Mixed Sparse Veg Mixed Freshwater Younger Agriculture Younger Sparse Veg Younger Sparse Veg Clear Fell Mixed

3 Mires

Agriculture Grassland

Urban Clear

Fell Coniferous Broad Leaf

Grassland

Moors

Clear Fell Agriculture Coniferous Sparse Veg

Marshes Moors

4 Younger Grassland

Younger Agriculture

Freshwater Coniferous Freshwater

Broad Leaf Mires

Younger Freshwater

Moors Marshes

5 Clear

Fell Freshwater

Mires Coniferous

Sparse Veg Clear Fell Agriculture

Freshwater Agriculture

Marshes

6 Coniferous Clear Fell

Mires

Marshes

Mires

Grassland

Moors

Mires

Marshes Marshes

7 Mixed Mixed Broad Leaf

8 Grassland

Moors

41

Table 4 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the WS according to Jacobs index

Ran

k North Centre South

50 95 50 95 50 95

+ - + - + - + - + - + -

1 Mires

Marshes

Grassland

Moors Mixed Freshwater Agriculture Urban Mixed Freshwater

Grassland

Moors Urban GrasslandMoors Urban

2 Freshwater Mixed Coniferous Urban Mires

Marshes Coniferous Sparse Veg Agriculture

Sparse

Veg Coniferous Freshwater

3 Urban Coniferous Younger Grassland

Moors Freshwater Younger Urban Freshwater

Broad

Leaf Agriculture Mixed

4 Younger Agriculture Sparse Veg Broad

Leaf

Broad

Leaf

Grassland

Moors Mixed Broad Leaf

5 Clear Fell Agriculture Coniferous Agriculture Mires

Marshes Clear Fell

6 Sparse

Veg

Mires

Marshes Mixed

Mires

Marshes

Clear

Fell

Mires

Marshes

7 Broad

Leaf Clear Fell Younger Clear Fell Younger Sparse Veg

8 Clear Fell Younger

9 Sparse

Veg

10 Grassland

Moors

42

Table 5 Second order (UD95Area) individual selectionavoidance for the GS and WS according to the Jacobs index

ID GS WS

Select Avoid Select Avoid

ID004 Younger Sparsely Vegetated MiresMarshes Sparsely Vegetated

ID005 MiresMarshes Sparsely Vegetated Coniferous GrasslandMoors

ID006 Coniferous Sparsely Vegetated Mixed Freshwater

ID008 Mixed Sparsely Vegetated Mixed Freshwater

ID009 Mixed Sparsely Vegetated Mixed GrasslandMoors

ID010 MiresMarshes Freshwater GrasslandMoors Freshwater

ID012 Broad Leaf Sparsely Vegetated Coniferous Urban

ID014 Clear Fell Sparsely Vegetated GrasslandMoors Sparsely Vegetated

ID015 GrasslandMoors Urban GrasslandMoors Freshwater

ID016 GrasslandMoors Freshwater GrasslandMoors Freshwater

ID017 GrasslandMoors Mixed Sparsely Vegetated Mixed

ID019 Mixed Sparsely Vegetated Mixed Urban

ID020 Broad Leaf Sparsely Vegetated Coniferous GrasslandMoors

ID022 MiresMarshes Freshwater MiresMarshes Freshwater

ID023 MiresMarshes GrasslandMoors Mixed Freshwater

ID024 Broadleaf Urban Broad Leaf Urban

ID026 GrasslandMoors Freshwater GrasslandMoors Freshwater

ID027 GrasslandMoors Urban Sparsely Vegetated Freshwater

43 Table 6 Third order (UD50UD95) individual selectionavoidance for the GS and WS according to the Jacobs index

ID GS WS

Select Avoid Select Avoid

ID004 Broad Leaf Mixed GrasslandMoors Freshwater

ID005 Broad Leaf Freshwater Agriculture Freshwater

ID006 Clear Fell Freshwater Agriculture MiresMarshes

ID008 MiresMarshes Freshwater Agriculture Urban

ID009 Freshwater Agriculture Agriculture Freshwater

ID010 Mixed Urban Sparsely Vegetated Urban

ID012 Coniferous GrasslandMoors Freshwater Urban

ID014 Urban Agriculture Freshwater Urban

ID015 Mixed Forest Urban Clear Fell Urban

ID016 Freshwater Urban GrasslandMoors Mixed

ID017 Coniferous Mixed Coniferous Broad Leaf

ID019 Broad Leaf GrasslandMoors Urban GrasslandMoors

ID020 Freshwater Urban Freshwater Agriculture

ID022 MiresMarshes Urban Broad Leaf GrasslandMoors

ID023 Freshwater Mixed Agriculture Freshwater

ID024 Mixed Freshwater Mixed Freshwater

ID026 Mixed MiresMarshes Sparsely Vegetated GrasslandMoors

ID027 Freshwater MiresMarshes GrasslandMoors Broad Leaf

44

Fig 2 North third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)

45

Fig 3 Centre third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)

46

Fig 4 South third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)

47

Fig 5 North second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)

48

Fig 6 Centre second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)

49

Fig 7 South second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)

50

Appendix F

Background

Fig 1 Daily mean snow depth and duration during the study period (Andrew Allen)

Female Moose Reproduction

Moose are seasonal polyoestral mammals (Monfort et al 1993) coming into oestrus during late September

early October (Garel et al 2009) The Swedish moose cow population reaches puberty between the ages 25

and 35 (Sand and Cederlund 1993) during which the reproductive period begins with the onset of ovulation

The age an individual reaches puberty is dependent on their body condition they have to reach a weight

threshold to reach puberty and become reproductive (Sand 1996) If she is over the weight threshold she will

go into oestrus in the autumn If she does not reach the weight threshold then she will go into oestrus the

following autumn if successful she will give birth to individual or twin calves in late May to early June

(Ericsson et al 2001) and therefore reach sexual maturity (Malmsten et al 2014b) Fecundity is related to

both the condition and the age of the cow Cows go through senescence at 12 years of age (Ericsson et al

2001) Providing calves with the required level of nutrition demands high energy and protein resources from

the mother during senescence this becomes harder to achieve leading to decreased levels of parental care

and higher levels of calf mortality

Page 35: Habitat-performance relationships on an island: fitness ...navinderjsingh.weebly.com/uploads/1/1/2/2/11224342/... · Conditions on Öland are milder than those found in other areas

35 Appendix D

Activity

Fig 1 Mean daily movement during the study period GS 23-April-2012 to 07-Nov-2012 WS 08-Nov-2012 to

22-April-2013 (number indicates month)

Fig 2 Mean daily movement in the centre and south during the GS and WS

36

Appendix E

Habitat Proportions

Fig 1 All individualsrsquo seasonal habitat proportions within the UD95

37 Habitat Selection

Table 1 Simplified ranking matrices comparing proportional habitat use within the second order (UD95Area) with

proportions of total available habitat types Mean value on the matrix was replaced by a sign a triple sign represents

significant deviation from random at P lt05 Highlighted habitat is ranked 1st

North A

gri

cult

ure

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 --- --- - +++ --- --- --- +++ +++ --- 8

Broad Leaf +++ 0 +++ + +++ +++ +++ + +++ +++ +++ 1

Clear Fell +++ --- 0 + +++ - - --- +++ +++ --- 7

Coniferous + - - 0 +++ - - --- +++ +++ - 6

Freshwater --- --- --- --- 0 --- --- --- +++ - --- 10

Grassland

Moors +++ --- + + +++ 0 +++ - +++ +++ + 3

MiresMarshes +++ --- + + +++ --- 0 - +++ +++ --- 5

Mixed +++ - +++ +++ +++ + + 0 +++ +++ + 2

Sparse Veg --- --- --- --- --- --- --- --- 0 --- --- 11

Urban --- --- --- --- + --- --- --- +++ 0 --- 9

Younger +++ --- +++ + +++ - +++ - +++ +++ 0 4

Rank Order and

Significance

Broad Leafgt Mixedgt GrasslandMoorsgt Youngergtgtgt MiresMarshesgt Coniferousgt

Clear Fellgtgtgt Agriculturegtgtgt Urbangt Freshwatergtgtgt Sparse Veg

Central

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 --- --- --- + +++ + --- +++ +++ --- 6

Broad Leaf +++ 0 +++ + +++ +++ + - +++ +++ - 3

Clear Fell +++ --- 0 - +++ +++ + --- +++ +++ --- 5

Coniferous +++ - + 0 +++ +++ + --- +++ +++ - 4

Freshwater - --- --- --- 0 +++ - --- +++ +++ --- 8

Grassland

Moors --- --- --- --- --- 0 --- --- +++ - --- 10

MiresMarshes - - - - + +++ 0 - +++ +++ - 7

Mixed +++ + +++ +++ +++ +++ + 0 +++ +++ + 1

Sparse Veg --- --- --- --- --- --- --- --- 0 - --- 11

Urban --- --- --- --- --- + --- --- + 0 --- 9

Younger +++ + +++ + +++ +++ + - +++ +++ 0 2

Rank Order and

Significance

Mixedgt Youngergt Broad Leafgt Coniferousgt Clear Fellgtgtgt Agriculturegt

MiresMarshesgt Freshwatergtgtgt Urbangt GrasslandMoorsgtgtgt Sparse Veg

38

South

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 + - - + - + +++ +++ +++ - 5

Broad Leaf - 0 - - + - - +++ + +++ - 7

Clear Fell + + 0 - + + + +++ + +++ + 2

Coniferous + + + 0 +++ + + +++ + +++ + 1

Freshwater - - - --- 0 - - + + +++ - 8

Grassland

Moors + + - - + 0 + + +++ + - 4

MiresMarshes - + - - + - 0 +++ + +++ - 6

Mixed --- --- --- --- - - --- 0 + + --- 10

Sparse Veg --- - - - - --- - - 0 + - 9

Urban --- --- --- --- --- - --- - - 0 --- 11

Younger + + - - + + + +++ + +++ 0 3

Rank Order

and

Significance

Coniferousgt Clear Fellgt Youngergt GrasslandMoorsgt Agriculturegt MiresMarshesgt Broad Leafgt

Freshwatergt Sparse Veggt Mixedgt Urban

Table 2 Simplified ranking matrices comparing proportional habitat use within the third order (UD50UD95) with

proportions of total available habitat types Mean value on the matrix was replaced by a sign a triple sign represents

significant deviation from random at P lt05 Highlighted habitat is ranked 1st

North

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 --- --- --- - + --- --- + +++ --- 8

Broad Leaf +++ 0 +++ + + + + + +++ +++ + 1

Clear Fell +++ --- 0 + + + - - + +++ - 5

Coniferous +++ - - 0 + + --- --- +++ +++ - 6

Freshwater + - - - 0 +++ - - +++ +++ - 7

GrasslandMoors - - - - --- 0 - - - + - 10

MiresMarshes +++ - + +++ + + 0 - +++ +++ + 3

Mixed +++ - + +++ + + + 0 +++ +++ + 2

Sparse Veg - --- - --- --- + --- --- 0 +++ --- 9

Urban --- --- --- --- --- - --- --- --- 0 --- 11

Younger +++ - + + + + - - +++ +++ 0 4

Rank Order and

Significance

Broad Leafgt Mixedgt MiresMarshesgt Youngergt Clear Fellgt Coniferousgt Freshwatergt

Agriculturegt Sparse Veggt GrasslandMoorsgt Urban

39

Central

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 --- --- + + - - - + +++ --- 7

Broad Leaf +++ 0 + +++ + + + + + +++ - 2

Clear Fell +++ - 0 +++ + + + + + +++ - 3

Coniferous - --- --- 0 + - - --- +++ + --- 8

Freshwater - - - - 0 --- - - --- - - 11

GrasslandMoors + - - + +++ 0 + - + +++ - 5

MiresMarshes + - - + + - 0 + + +++ - 6

Mixed + - - +++ + + - 0 +++ +++ - 4

Sparse Veg - - - --- +++ - - --- 0 +++ - 9

Urban --- --- --- - + --- --- --- --- 0 --- 10

Younger +++ + + +++ + + + + + +++ 0 1

Rank Order and

Significance

Youngergt Broad Leafgt Clear Fellgt Mixedgt GrasslandMoorsgt MiresMarshesgt

Agriculturegt Coniferousgtgtgt Sparse Veggtgtgt Urbangt Freshwater

South

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 - - - - - + - +++ + --- 8

Broad Leaf + 0 - --- + - + - +++ + - 6

Clear Fell + + 0 - + - + - +++ + - 4

Coniferous + +++ + 0 + + +++ + +++ + + 1

Freshwater + - - - 0 - - + + + - 7

GrasslandMoors + + + - + 0 + + + + - 3

MiresMarshes - - - --- + - 0 - + + - 9

Mixed + + + - - - + 0 + + - 5

Sparse Veg --- --- --- --- - - - - 0 + --- 10

Urban - - - - - - - - - 0 - 11

Younger +++ + + - + + + + +++ + 0 2

Rank Order and

Significance

Coniferousgt Youngergt GrasslandMoorsgt Clear Fellgt Mixedgt Broad Leafgt Freshwatergt

Agriculturegt MiresMarshesgt Sparse Veggt Urban

40

Table 3 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the GS according to Jacobs index

Ran

k North Centre South

50 95 50 95 50 95

+ - + - + - + - + - + -

1 Broad

Leaf Urban Broad Leaf Sparse Veg

Broad

Leaf Urban Mixed Urban Coniferous Urban

Grassland

Moors Urban

2 Mixed Sparse Veg Mixed Freshwater Younger Agriculture Younger Sparse Veg Younger Sparse Veg Clear Fell Mixed

3 Mires

Agriculture Grassland

Urban Clear

Fell Coniferous Broad Leaf

Grassland

Moors

Clear Fell Agriculture Coniferous Sparse Veg

Marshes Moors

4 Younger Grassland

Younger Agriculture

Freshwater Coniferous Freshwater

Broad Leaf Mires

Younger Freshwater

Moors Marshes

5 Clear

Fell Freshwater

Mires Coniferous

Sparse Veg Clear Fell Agriculture

Freshwater Agriculture

Marshes

6 Coniferous Clear Fell

Mires

Marshes

Mires

Grassland

Moors

Mires

Marshes Marshes

7 Mixed Mixed Broad Leaf

8 Grassland

Moors

41

Table 4 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the WS according to Jacobs index

Ran

k North Centre South

50 95 50 95 50 95

+ - + - + - + - + - + -

1 Mires

Marshes

Grassland

Moors Mixed Freshwater Agriculture Urban Mixed Freshwater

Grassland

Moors Urban GrasslandMoors Urban

2 Freshwater Mixed Coniferous Urban Mires

Marshes Coniferous Sparse Veg Agriculture

Sparse

Veg Coniferous Freshwater

3 Urban Coniferous Younger Grassland

Moors Freshwater Younger Urban Freshwater

Broad

Leaf Agriculture Mixed

4 Younger Agriculture Sparse Veg Broad

Leaf

Broad

Leaf

Grassland

Moors Mixed Broad Leaf

5 Clear Fell Agriculture Coniferous Agriculture Mires

Marshes Clear Fell

6 Sparse

Veg

Mires

Marshes Mixed

Mires

Marshes

Clear

Fell

Mires

Marshes

7 Broad

Leaf Clear Fell Younger Clear Fell Younger Sparse Veg

8 Clear Fell Younger

9 Sparse

Veg

10 Grassland

Moors

42

Table 5 Second order (UD95Area) individual selectionavoidance for the GS and WS according to the Jacobs index

ID GS WS

Select Avoid Select Avoid

ID004 Younger Sparsely Vegetated MiresMarshes Sparsely Vegetated

ID005 MiresMarshes Sparsely Vegetated Coniferous GrasslandMoors

ID006 Coniferous Sparsely Vegetated Mixed Freshwater

ID008 Mixed Sparsely Vegetated Mixed Freshwater

ID009 Mixed Sparsely Vegetated Mixed GrasslandMoors

ID010 MiresMarshes Freshwater GrasslandMoors Freshwater

ID012 Broad Leaf Sparsely Vegetated Coniferous Urban

ID014 Clear Fell Sparsely Vegetated GrasslandMoors Sparsely Vegetated

ID015 GrasslandMoors Urban GrasslandMoors Freshwater

ID016 GrasslandMoors Freshwater GrasslandMoors Freshwater

ID017 GrasslandMoors Mixed Sparsely Vegetated Mixed

ID019 Mixed Sparsely Vegetated Mixed Urban

ID020 Broad Leaf Sparsely Vegetated Coniferous GrasslandMoors

ID022 MiresMarshes Freshwater MiresMarshes Freshwater

ID023 MiresMarshes GrasslandMoors Mixed Freshwater

ID024 Broadleaf Urban Broad Leaf Urban

ID026 GrasslandMoors Freshwater GrasslandMoors Freshwater

ID027 GrasslandMoors Urban Sparsely Vegetated Freshwater

43 Table 6 Third order (UD50UD95) individual selectionavoidance for the GS and WS according to the Jacobs index

ID GS WS

Select Avoid Select Avoid

ID004 Broad Leaf Mixed GrasslandMoors Freshwater

ID005 Broad Leaf Freshwater Agriculture Freshwater

ID006 Clear Fell Freshwater Agriculture MiresMarshes

ID008 MiresMarshes Freshwater Agriculture Urban

ID009 Freshwater Agriculture Agriculture Freshwater

ID010 Mixed Urban Sparsely Vegetated Urban

ID012 Coniferous GrasslandMoors Freshwater Urban

ID014 Urban Agriculture Freshwater Urban

ID015 Mixed Forest Urban Clear Fell Urban

ID016 Freshwater Urban GrasslandMoors Mixed

ID017 Coniferous Mixed Coniferous Broad Leaf

ID019 Broad Leaf GrasslandMoors Urban GrasslandMoors

ID020 Freshwater Urban Freshwater Agriculture

ID022 MiresMarshes Urban Broad Leaf GrasslandMoors

ID023 Freshwater Mixed Agriculture Freshwater

ID024 Mixed Freshwater Mixed Freshwater

ID026 Mixed MiresMarshes Sparsely Vegetated GrasslandMoors

ID027 Freshwater MiresMarshes GrasslandMoors Broad Leaf

44

Fig 2 North third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)

45

Fig 3 Centre third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)

46

Fig 4 South third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)

47

Fig 5 North second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)

48

Fig 6 Centre second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)

49

Fig 7 South second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)

50

Appendix F

Background

Fig 1 Daily mean snow depth and duration during the study period (Andrew Allen)

Female Moose Reproduction

Moose are seasonal polyoestral mammals (Monfort et al 1993) coming into oestrus during late September

early October (Garel et al 2009) The Swedish moose cow population reaches puberty between the ages 25

and 35 (Sand and Cederlund 1993) during which the reproductive period begins with the onset of ovulation

The age an individual reaches puberty is dependent on their body condition they have to reach a weight

threshold to reach puberty and become reproductive (Sand 1996) If she is over the weight threshold she will

go into oestrus in the autumn If she does not reach the weight threshold then she will go into oestrus the

following autumn if successful she will give birth to individual or twin calves in late May to early June

(Ericsson et al 2001) and therefore reach sexual maturity (Malmsten et al 2014b) Fecundity is related to

both the condition and the age of the cow Cows go through senescence at 12 years of age (Ericsson et al

2001) Providing calves with the required level of nutrition demands high energy and protein resources from

the mother during senescence this becomes harder to achieve leading to decreased levels of parental care

and higher levels of calf mortality

Page 36: Habitat-performance relationships on an island: fitness ...navinderjsingh.weebly.com/uploads/1/1/2/2/11224342/... · Conditions on Öland are milder than those found in other areas

36

Appendix E

Habitat Proportions

Fig 1 All individualsrsquo seasonal habitat proportions within the UD95

37 Habitat Selection

Table 1 Simplified ranking matrices comparing proportional habitat use within the second order (UD95Area) with

proportions of total available habitat types Mean value on the matrix was replaced by a sign a triple sign represents

significant deviation from random at P lt05 Highlighted habitat is ranked 1st

North A

gri

cult

ure

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 --- --- - +++ --- --- --- +++ +++ --- 8

Broad Leaf +++ 0 +++ + +++ +++ +++ + +++ +++ +++ 1

Clear Fell +++ --- 0 + +++ - - --- +++ +++ --- 7

Coniferous + - - 0 +++ - - --- +++ +++ - 6

Freshwater --- --- --- --- 0 --- --- --- +++ - --- 10

Grassland

Moors +++ --- + + +++ 0 +++ - +++ +++ + 3

MiresMarshes +++ --- + + +++ --- 0 - +++ +++ --- 5

Mixed +++ - +++ +++ +++ + + 0 +++ +++ + 2

Sparse Veg --- --- --- --- --- --- --- --- 0 --- --- 11

Urban --- --- --- --- + --- --- --- +++ 0 --- 9

Younger +++ --- +++ + +++ - +++ - +++ +++ 0 4

Rank Order and

Significance

Broad Leafgt Mixedgt GrasslandMoorsgt Youngergtgtgt MiresMarshesgt Coniferousgt

Clear Fellgtgtgt Agriculturegtgtgt Urbangt Freshwatergtgtgt Sparse Veg

Central

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 --- --- --- + +++ + --- +++ +++ --- 6

Broad Leaf +++ 0 +++ + +++ +++ + - +++ +++ - 3

Clear Fell +++ --- 0 - +++ +++ + --- +++ +++ --- 5

Coniferous +++ - + 0 +++ +++ + --- +++ +++ - 4

Freshwater - --- --- --- 0 +++ - --- +++ +++ --- 8

Grassland

Moors --- --- --- --- --- 0 --- --- +++ - --- 10

MiresMarshes - - - - + +++ 0 - +++ +++ - 7

Mixed +++ + +++ +++ +++ +++ + 0 +++ +++ + 1

Sparse Veg --- --- --- --- --- --- --- --- 0 - --- 11

Urban --- --- --- --- --- + --- --- + 0 --- 9

Younger +++ + +++ + +++ +++ + - +++ +++ 0 2

Rank Order and

Significance

Mixedgt Youngergt Broad Leafgt Coniferousgt Clear Fellgtgtgt Agriculturegt

MiresMarshesgt Freshwatergtgtgt Urbangt GrasslandMoorsgtgtgt Sparse Veg

38

South

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 + - - + - + +++ +++ +++ - 5

Broad Leaf - 0 - - + - - +++ + +++ - 7

Clear Fell + + 0 - + + + +++ + +++ + 2

Coniferous + + + 0 +++ + + +++ + +++ + 1

Freshwater - - - --- 0 - - + + +++ - 8

Grassland

Moors + + - - + 0 + + +++ + - 4

MiresMarshes - + - - + - 0 +++ + +++ - 6

Mixed --- --- --- --- - - --- 0 + + --- 10

Sparse Veg --- - - - - --- - - 0 + - 9

Urban --- --- --- --- --- - --- - - 0 --- 11

Younger + + - - + + + +++ + +++ 0 3

Rank Order

and

Significance

Coniferousgt Clear Fellgt Youngergt GrasslandMoorsgt Agriculturegt MiresMarshesgt Broad Leafgt

Freshwatergt Sparse Veggt Mixedgt Urban

Table 2 Simplified ranking matrices comparing proportional habitat use within the third order (UD50UD95) with

proportions of total available habitat types Mean value on the matrix was replaced by a sign a triple sign represents

significant deviation from random at P lt05 Highlighted habitat is ranked 1st

North

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 --- --- --- - + --- --- + +++ --- 8

Broad Leaf +++ 0 +++ + + + + + +++ +++ + 1

Clear Fell +++ --- 0 + + + - - + +++ - 5

Coniferous +++ - - 0 + + --- --- +++ +++ - 6

Freshwater + - - - 0 +++ - - +++ +++ - 7

GrasslandMoors - - - - --- 0 - - - + - 10

MiresMarshes +++ - + +++ + + 0 - +++ +++ + 3

Mixed +++ - + +++ + + + 0 +++ +++ + 2

Sparse Veg - --- - --- --- + --- --- 0 +++ --- 9

Urban --- --- --- --- --- - --- --- --- 0 --- 11

Younger +++ - + + + + - - +++ +++ 0 4

Rank Order and

Significance

Broad Leafgt Mixedgt MiresMarshesgt Youngergt Clear Fellgt Coniferousgt Freshwatergt

Agriculturegt Sparse Veggt GrasslandMoorsgt Urban

39

Central

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 --- --- + + - - - + +++ --- 7

Broad Leaf +++ 0 + +++ + + + + + +++ - 2

Clear Fell +++ - 0 +++ + + + + + +++ - 3

Coniferous - --- --- 0 + - - --- +++ + --- 8

Freshwater - - - - 0 --- - - --- - - 11

GrasslandMoors + - - + +++ 0 + - + +++ - 5

MiresMarshes + - - + + - 0 + + +++ - 6

Mixed + - - +++ + + - 0 +++ +++ - 4

Sparse Veg - - - --- +++ - - --- 0 +++ - 9

Urban --- --- --- - + --- --- --- --- 0 --- 10

Younger +++ + + +++ + + + + + +++ 0 1

Rank Order and

Significance

Youngergt Broad Leafgt Clear Fellgt Mixedgt GrasslandMoorsgt MiresMarshesgt

Agriculturegt Coniferousgtgtgt Sparse Veggtgtgt Urbangt Freshwater

South

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 - - - - - + - +++ + --- 8

Broad Leaf + 0 - --- + - + - +++ + - 6

Clear Fell + + 0 - + - + - +++ + - 4

Coniferous + +++ + 0 + + +++ + +++ + + 1

Freshwater + - - - 0 - - + + + - 7

GrasslandMoors + + + - + 0 + + + + - 3

MiresMarshes - - - --- + - 0 - + + - 9

Mixed + + + - - - + 0 + + - 5

Sparse Veg --- --- --- --- - - - - 0 + --- 10

Urban - - - - - - - - - 0 - 11

Younger +++ + + - + + + + +++ + 0 2

Rank Order and

Significance

Coniferousgt Youngergt GrasslandMoorsgt Clear Fellgt Mixedgt Broad Leafgt Freshwatergt

Agriculturegt MiresMarshesgt Sparse Veggt Urban

40

Table 3 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the GS according to Jacobs index

Ran

k North Centre South

50 95 50 95 50 95

+ - + - + - + - + - + -

1 Broad

Leaf Urban Broad Leaf Sparse Veg

Broad

Leaf Urban Mixed Urban Coniferous Urban

Grassland

Moors Urban

2 Mixed Sparse Veg Mixed Freshwater Younger Agriculture Younger Sparse Veg Younger Sparse Veg Clear Fell Mixed

3 Mires

Agriculture Grassland

Urban Clear

Fell Coniferous Broad Leaf

Grassland

Moors

Clear Fell Agriculture Coniferous Sparse Veg

Marshes Moors

4 Younger Grassland

Younger Agriculture

Freshwater Coniferous Freshwater

Broad Leaf Mires

Younger Freshwater

Moors Marshes

5 Clear

Fell Freshwater

Mires Coniferous

Sparse Veg Clear Fell Agriculture

Freshwater Agriculture

Marshes

6 Coniferous Clear Fell

Mires

Marshes

Mires

Grassland

Moors

Mires

Marshes Marshes

7 Mixed Mixed Broad Leaf

8 Grassland

Moors

41

Table 4 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the WS according to Jacobs index

Ran

k North Centre South

50 95 50 95 50 95

+ - + - + - + - + - + -

1 Mires

Marshes

Grassland

Moors Mixed Freshwater Agriculture Urban Mixed Freshwater

Grassland

Moors Urban GrasslandMoors Urban

2 Freshwater Mixed Coniferous Urban Mires

Marshes Coniferous Sparse Veg Agriculture

Sparse

Veg Coniferous Freshwater

3 Urban Coniferous Younger Grassland

Moors Freshwater Younger Urban Freshwater

Broad

Leaf Agriculture Mixed

4 Younger Agriculture Sparse Veg Broad

Leaf

Broad

Leaf

Grassland

Moors Mixed Broad Leaf

5 Clear Fell Agriculture Coniferous Agriculture Mires

Marshes Clear Fell

6 Sparse

Veg

Mires

Marshes Mixed

Mires

Marshes

Clear

Fell

Mires

Marshes

7 Broad

Leaf Clear Fell Younger Clear Fell Younger Sparse Veg

8 Clear Fell Younger

9 Sparse

Veg

10 Grassland

Moors

42

Table 5 Second order (UD95Area) individual selectionavoidance for the GS and WS according to the Jacobs index

ID GS WS

Select Avoid Select Avoid

ID004 Younger Sparsely Vegetated MiresMarshes Sparsely Vegetated

ID005 MiresMarshes Sparsely Vegetated Coniferous GrasslandMoors

ID006 Coniferous Sparsely Vegetated Mixed Freshwater

ID008 Mixed Sparsely Vegetated Mixed Freshwater

ID009 Mixed Sparsely Vegetated Mixed GrasslandMoors

ID010 MiresMarshes Freshwater GrasslandMoors Freshwater

ID012 Broad Leaf Sparsely Vegetated Coniferous Urban

ID014 Clear Fell Sparsely Vegetated GrasslandMoors Sparsely Vegetated

ID015 GrasslandMoors Urban GrasslandMoors Freshwater

ID016 GrasslandMoors Freshwater GrasslandMoors Freshwater

ID017 GrasslandMoors Mixed Sparsely Vegetated Mixed

ID019 Mixed Sparsely Vegetated Mixed Urban

ID020 Broad Leaf Sparsely Vegetated Coniferous GrasslandMoors

ID022 MiresMarshes Freshwater MiresMarshes Freshwater

ID023 MiresMarshes GrasslandMoors Mixed Freshwater

ID024 Broadleaf Urban Broad Leaf Urban

ID026 GrasslandMoors Freshwater GrasslandMoors Freshwater

ID027 GrasslandMoors Urban Sparsely Vegetated Freshwater

43 Table 6 Third order (UD50UD95) individual selectionavoidance for the GS and WS according to the Jacobs index

ID GS WS

Select Avoid Select Avoid

ID004 Broad Leaf Mixed GrasslandMoors Freshwater

ID005 Broad Leaf Freshwater Agriculture Freshwater

ID006 Clear Fell Freshwater Agriculture MiresMarshes

ID008 MiresMarshes Freshwater Agriculture Urban

ID009 Freshwater Agriculture Agriculture Freshwater

ID010 Mixed Urban Sparsely Vegetated Urban

ID012 Coniferous GrasslandMoors Freshwater Urban

ID014 Urban Agriculture Freshwater Urban

ID015 Mixed Forest Urban Clear Fell Urban

ID016 Freshwater Urban GrasslandMoors Mixed

ID017 Coniferous Mixed Coniferous Broad Leaf

ID019 Broad Leaf GrasslandMoors Urban GrasslandMoors

ID020 Freshwater Urban Freshwater Agriculture

ID022 MiresMarshes Urban Broad Leaf GrasslandMoors

ID023 Freshwater Mixed Agriculture Freshwater

ID024 Mixed Freshwater Mixed Freshwater

ID026 Mixed MiresMarshes Sparsely Vegetated GrasslandMoors

ID027 Freshwater MiresMarshes GrasslandMoors Broad Leaf

44

Fig 2 North third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)

45

Fig 3 Centre third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)

46

Fig 4 South third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)

47

Fig 5 North second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)

48

Fig 6 Centre second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)

49

Fig 7 South second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)

50

Appendix F

Background

Fig 1 Daily mean snow depth and duration during the study period (Andrew Allen)

Female Moose Reproduction

Moose are seasonal polyoestral mammals (Monfort et al 1993) coming into oestrus during late September

early October (Garel et al 2009) The Swedish moose cow population reaches puberty between the ages 25

and 35 (Sand and Cederlund 1993) during which the reproductive period begins with the onset of ovulation

The age an individual reaches puberty is dependent on their body condition they have to reach a weight

threshold to reach puberty and become reproductive (Sand 1996) If she is over the weight threshold she will

go into oestrus in the autumn If she does not reach the weight threshold then she will go into oestrus the

following autumn if successful she will give birth to individual or twin calves in late May to early June

(Ericsson et al 2001) and therefore reach sexual maturity (Malmsten et al 2014b) Fecundity is related to

both the condition and the age of the cow Cows go through senescence at 12 years of age (Ericsson et al

2001) Providing calves with the required level of nutrition demands high energy and protein resources from

the mother during senescence this becomes harder to achieve leading to decreased levels of parental care

and higher levels of calf mortality

Page 37: Habitat-performance relationships on an island: fitness ...navinderjsingh.weebly.com/uploads/1/1/2/2/11224342/... · Conditions on Öland are milder than those found in other areas

37 Habitat Selection

Table 1 Simplified ranking matrices comparing proportional habitat use within the second order (UD95Area) with

proportions of total available habitat types Mean value on the matrix was replaced by a sign a triple sign represents

significant deviation from random at P lt05 Highlighted habitat is ranked 1st

North A

gri

cult

ure

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 --- --- - +++ --- --- --- +++ +++ --- 8

Broad Leaf +++ 0 +++ + +++ +++ +++ + +++ +++ +++ 1

Clear Fell +++ --- 0 + +++ - - --- +++ +++ --- 7

Coniferous + - - 0 +++ - - --- +++ +++ - 6

Freshwater --- --- --- --- 0 --- --- --- +++ - --- 10

Grassland

Moors +++ --- + + +++ 0 +++ - +++ +++ + 3

MiresMarshes +++ --- + + +++ --- 0 - +++ +++ --- 5

Mixed +++ - +++ +++ +++ + + 0 +++ +++ + 2

Sparse Veg --- --- --- --- --- --- --- --- 0 --- --- 11

Urban --- --- --- --- + --- --- --- +++ 0 --- 9

Younger +++ --- +++ + +++ - +++ - +++ +++ 0 4

Rank Order and

Significance

Broad Leafgt Mixedgt GrasslandMoorsgt Youngergtgtgt MiresMarshesgt Coniferousgt

Clear Fellgtgtgt Agriculturegtgtgt Urbangt Freshwatergtgtgt Sparse Veg

Central

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 --- --- --- + +++ + --- +++ +++ --- 6

Broad Leaf +++ 0 +++ + +++ +++ + - +++ +++ - 3

Clear Fell +++ --- 0 - +++ +++ + --- +++ +++ --- 5

Coniferous +++ - + 0 +++ +++ + --- +++ +++ - 4

Freshwater - --- --- --- 0 +++ - --- +++ +++ --- 8

Grassland

Moors --- --- --- --- --- 0 --- --- +++ - --- 10

MiresMarshes - - - - + +++ 0 - +++ +++ - 7

Mixed +++ + +++ +++ +++ +++ + 0 +++ +++ + 1

Sparse Veg --- --- --- --- --- --- --- --- 0 - --- 11

Urban --- --- --- --- --- + --- --- + 0 --- 9

Younger +++ + +++ + +++ +++ + - +++ +++ 0 2

Rank Order and

Significance

Mixedgt Youngergt Broad Leafgt Coniferousgt Clear Fellgtgtgt Agriculturegt

MiresMarshesgt Freshwatergtgtgt Urbangt GrasslandMoorsgtgtgt Sparse Veg

38

South

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 + - - + - + +++ +++ +++ - 5

Broad Leaf - 0 - - + - - +++ + +++ - 7

Clear Fell + + 0 - + + + +++ + +++ + 2

Coniferous + + + 0 +++ + + +++ + +++ + 1

Freshwater - - - --- 0 - - + + +++ - 8

Grassland

Moors + + - - + 0 + + +++ + - 4

MiresMarshes - + - - + - 0 +++ + +++ - 6

Mixed --- --- --- --- - - --- 0 + + --- 10

Sparse Veg --- - - - - --- - - 0 + - 9

Urban --- --- --- --- --- - --- - - 0 --- 11

Younger + + - - + + + +++ + +++ 0 3

Rank Order

and

Significance

Coniferousgt Clear Fellgt Youngergt GrasslandMoorsgt Agriculturegt MiresMarshesgt Broad Leafgt

Freshwatergt Sparse Veggt Mixedgt Urban

Table 2 Simplified ranking matrices comparing proportional habitat use within the third order (UD50UD95) with

proportions of total available habitat types Mean value on the matrix was replaced by a sign a triple sign represents

significant deviation from random at P lt05 Highlighted habitat is ranked 1st

North

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 --- --- --- - + --- --- + +++ --- 8

Broad Leaf +++ 0 +++ + + + + + +++ +++ + 1

Clear Fell +++ --- 0 + + + - - + +++ - 5

Coniferous +++ - - 0 + + --- --- +++ +++ - 6

Freshwater + - - - 0 +++ - - +++ +++ - 7

GrasslandMoors - - - - --- 0 - - - + - 10

MiresMarshes +++ - + +++ + + 0 - +++ +++ + 3

Mixed +++ - + +++ + + + 0 +++ +++ + 2

Sparse Veg - --- - --- --- + --- --- 0 +++ --- 9

Urban --- --- --- --- --- - --- --- --- 0 --- 11

Younger +++ - + + + + - - +++ +++ 0 4

Rank Order and

Significance

Broad Leafgt Mixedgt MiresMarshesgt Youngergt Clear Fellgt Coniferousgt Freshwatergt

Agriculturegt Sparse Veggt GrasslandMoorsgt Urban

39

Central

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 --- --- + + - - - + +++ --- 7

Broad Leaf +++ 0 + +++ + + + + + +++ - 2

Clear Fell +++ - 0 +++ + + + + + +++ - 3

Coniferous - --- --- 0 + - - --- +++ + --- 8

Freshwater - - - - 0 --- - - --- - - 11

GrasslandMoors + - - + +++ 0 + - + +++ - 5

MiresMarshes + - - + + - 0 + + +++ - 6

Mixed + - - +++ + + - 0 +++ +++ - 4

Sparse Veg - - - --- +++ - - --- 0 +++ - 9

Urban --- --- --- - + --- --- --- --- 0 --- 10

Younger +++ + + +++ + + + + + +++ 0 1

Rank Order and

Significance

Youngergt Broad Leafgt Clear Fellgt Mixedgt GrasslandMoorsgt MiresMarshesgt

Agriculturegt Coniferousgtgtgt Sparse Veggtgtgt Urbangt Freshwater

South

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 - - - - - + - +++ + --- 8

Broad Leaf + 0 - --- + - + - +++ + - 6

Clear Fell + + 0 - + - + - +++ + - 4

Coniferous + +++ + 0 + + +++ + +++ + + 1

Freshwater + - - - 0 - - + + + - 7

GrasslandMoors + + + - + 0 + + + + - 3

MiresMarshes - - - --- + - 0 - + + - 9

Mixed + + + - - - + 0 + + - 5

Sparse Veg --- --- --- --- - - - - 0 + --- 10

Urban - - - - - - - - - 0 - 11

Younger +++ + + - + + + + +++ + 0 2

Rank Order and

Significance

Coniferousgt Youngergt GrasslandMoorsgt Clear Fellgt Mixedgt Broad Leafgt Freshwatergt

Agriculturegt MiresMarshesgt Sparse Veggt Urban

40

Table 3 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the GS according to Jacobs index

Ran

k North Centre South

50 95 50 95 50 95

+ - + - + - + - + - + -

1 Broad

Leaf Urban Broad Leaf Sparse Veg

Broad

Leaf Urban Mixed Urban Coniferous Urban

Grassland

Moors Urban

2 Mixed Sparse Veg Mixed Freshwater Younger Agriculture Younger Sparse Veg Younger Sparse Veg Clear Fell Mixed

3 Mires

Agriculture Grassland

Urban Clear

Fell Coniferous Broad Leaf

Grassland

Moors

Clear Fell Agriculture Coniferous Sparse Veg

Marshes Moors

4 Younger Grassland

Younger Agriculture

Freshwater Coniferous Freshwater

Broad Leaf Mires

Younger Freshwater

Moors Marshes

5 Clear

Fell Freshwater

Mires Coniferous

Sparse Veg Clear Fell Agriculture

Freshwater Agriculture

Marshes

6 Coniferous Clear Fell

Mires

Marshes

Mires

Grassland

Moors

Mires

Marshes Marshes

7 Mixed Mixed Broad Leaf

8 Grassland

Moors

41

Table 4 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the WS according to Jacobs index

Ran

k North Centre South

50 95 50 95 50 95

+ - + - + - + - + - + -

1 Mires

Marshes

Grassland

Moors Mixed Freshwater Agriculture Urban Mixed Freshwater

Grassland

Moors Urban GrasslandMoors Urban

2 Freshwater Mixed Coniferous Urban Mires

Marshes Coniferous Sparse Veg Agriculture

Sparse

Veg Coniferous Freshwater

3 Urban Coniferous Younger Grassland

Moors Freshwater Younger Urban Freshwater

Broad

Leaf Agriculture Mixed

4 Younger Agriculture Sparse Veg Broad

Leaf

Broad

Leaf

Grassland

Moors Mixed Broad Leaf

5 Clear Fell Agriculture Coniferous Agriculture Mires

Marshes Clear Fell

6 Sparse

Veg

Mires

Marshes Mixed

Mires

Marshes

Clear

Fell

Mires

Marshes

7 Broad

Leaf Clear Fell Younger Clear Fell Younger Sparse Veg

8 Clear Fell Younger

9 Sparse

Veg

10 Grassland

Moors

42

Table 5 Second order (UD95Area) individual selectionavoidance for the GS and WS according to the Jacobs index

ID GS WS

Select Avoid Select Avoid

ID004 Younger Sparsely Vegetated MiresMarshes Sparsely Vegetated

ID005 MiresMarshes Sparsely Vegetated Coniferous GrasslandMoors

ID006 Coniferous Sparsely Vegetated Mixed Freshwater

ID008 Mixed Sparsely Vegetated Mixed Freshwater

ID009 Mixed Sparsely Vegetated Mixed GrasslandMoors

ID010 MiresMarshes Freshwater GrasslandMoors Freshwater

ID012 Broad Leaf Sparsely Vegetated Coniferous Urban

ID014 Clear Fell Sparsely Vegetated GrasslandMoors Sparsely Vegetated

ID015 GrasslandMoors Urban GrasslandMoors Freshwater

ID016 GrasslandMoors Freshwater GrasslandMoors Freshwater

ID017 GrasslandMoors Mixed Sparsely Vegetated Mixed

ID019 Mixed Sparsely Vegetated Mixed Urban

ID020 Broad Leaf Sparsely Vegetated Coniferous GrasslandMoors

ID022 MiresMarshes Freshwater MiresMarshes Freshwater

ID023 MiresMarshes GrasslandMoors Mixed Freshwater

ID024 Broadleaf Urban Broad Leaf Urban

ID026 GrasslandMoors Freshwater GrasslandMoors Freshwater

ID027 GrasslandMoors Urban Sparsely Vegetated Freshwater

43 Table 6 Third order (UD50UD95) individual selectionavoidance for the GS and WS according to the Jacobs index

ID GS WS

Select Avoid Select Avoid

ID004 Broad Leaf Mixed GrasslandMoors Freshwater

ID005 Broad Leaf Freshwater Agriculture Freshwater

ID006 Clear Fell Freshwater Agriculture MiresMarshes

ID008 MiresMarshes Freshwater Agriculture Urban

ID009 Freshwater Agriculture Agriculture Freshwater

ID010 Mixed Urban Sparsely Vegetated Urban

ID012 Coniferous GrasslandMoors Freshwater Urban

ID014 Urban Agriculture Freshwater Urban

ID015 Mixed Forest Urban Clear Fell Urban

ID016 Freshwater Urban GrasslandMoors Mixed

ID017 Coniferous Mixed Coniferous Broad Leaf

ID019 Broad Leaf GrasslandMoors Urban GrasslandMoors

ID020 Freshwater Urban Freshwater Agriculture

ID022 MiresMarshes Urban Broad Leaf GrasslandMoors

ID023 Freshwater Mixed Agriculture Freshwater

ID024 Mixed Freshwater Mixed Freshwater

ID026 Mixed MiresMarshes Sparsely Vegetated GrasslandMoors

ID027 Freshwater MiresMarshes GrasslandMoors Broad Leaf

44

Fig 2 North third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)

45

Fig 3 Centre third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)

46

Fig 4 South third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)

47

Fig 5 North second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)

48

Fig 6 Centre second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)

49

Fig 7 South second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)

50

Appendix F

Background

Fig 1 Daily mean snow depth and duration during the study period (Andrew Allen)

Female Moose Reproduction

Moose are seasonal polyoestral mammals (Monfort et al 1993) coming into oestrus during late September

early October (Garel et al 2009) The Swedish moose cow population reaches puberty between the ages 25

and 35 (Sand and Cederlund 1993) during which the reproductive period begins with the onset of ovulation

The age an individual reaches puberty is dependent on their body condition they have to reach a weight

threshold to reach puberty and become reproductive (Sand 1996) If she is over the weight threshold she will

go into oestrus in the autumn If she does not reach the weight threshold then she will go into oestrus the

following autumn if successful she will give birth to individual or twin calves in late May to early June

(Ericsson et al 2001) and therefore reach sexual maturity (Malmsten et al 2014b) Fecundity is related to

both the condition and the age of the cow Cows go through senescence at 12 years of age (Ericsson et al

2001) Providing calves with the required level of nutrition demands high energy and protein resources from

the mother during senescence this becomes harder to achieve leading to decreased levels of parental care

and higher levels of calf mortality

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38

South

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 + - - + - + +++ +++ +++ - 5

Broad Leaf - 0 - - + - - +++ + +++ - 7

Clear Fell + + 0 - + + + +++ + +++ + 2

Coniferous + + + 0 +++ + + +++ + +++ + 1

Freshwater - - - --- 0 - - + + +++ - 8

Grassland

Moors + + - - + 0 + + +++ + - 4

MiresMarshes - + - - + - 0 +++ + +++ - 6

Mixed --- --- --- --- - - --- 0 + + --- 10

Sparse Veg --- - - - - --- - - 0 + - 9

Urban --- --- --- --- --- - --- - - 0 --- 11

Younger + + - - + + + +++ + +++ 0 3

Rank Order

and

Significance

Coniferousgt Clear Fellgt Youngergt GrasslandMoorsgt Agriculturegt MiresMarshesgt Broad Leafgt

Freshwatergt Sparse Veggt Mixedgt Urban

Table 2 Simplified ranking matrices comparing proportional habitat use within the third order (UD50UD95) with

proportions of total available habitat types Mean value on the matrix was replaced by a sign a triple sign represents

significant deviation from random at P lt05 Highlighted habitat is ranked 1st

North

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 --- --- --- - + --- --- + +++ --- 8

Broad Leaf +++ 0 +++ + + + + + +++ +++ + 1

Clear Fell +++ --- 0 + + + - - + +++ - 5

Coniferous +++ - - 0 + + --- --- +++ +++ - 6

Freshwater + - - - 0 +++ - - +++ +++ - 7

GrasslandMoors - - - - --- 0 - - - + - 10

MiresMarshes +++ - + +++ + + 0 - +++ +++ + 3

Mixed +++ - + +++ + + + 0 +++ +++ + 2

Sparse Veg - --- - --- --- + --- --- 0 +++ --- 9

Urban --- --- --- --- --- - --- --- --- 0 --- 11

Younger +++ - + + + + - - +++ +++ 0 4

Rank Order and

Significance

Broad Leafgt Mixedgt MiresMarshesgt Youngergt Clear Fellgt Coniferousgt Freshwatergt

Agriculturegt Sparse Veggt GrasslandMoorsgt Urban

39

Central

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 --- --- + + - - - + +++ --- 7

Broad Leaf +++ 0 + +++ + + + + + +++ - 2

Clear Fell +++ - 0 +++ + + + + + +++ - 3

Coniferous - --- --- 0 + - - --- +++ + --- 8

Freshwater - - - - 0 --- - - --- - - 11

GrasslandMoors + - - + +++ 0 + - + +++ - 5

MiresMarshes + - - + + - 0 + + +++ - 6

Mixed + - - +++ + + - 0 +++ +++ - 4

Sparse Veg - - - --- +++ - - --- 0 +++ - 9

Urban --- --- --- - + --- --- --- --- 0 --- 10

Younger +++ + + +++ + + + + + +++ 0 1

Rank Order and

Significance

Youngergt Broad Leafgt Clear Fellgt Mixedgt GrasslandMoorsgt MiresMarshesgt

Agriculturegt Coniferousgtgtgt Sparse Veggtgtgt Urbangt Freshwater

South

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 - - - - - + - +++ + --- 8

Broad Leaf + 0 - --- + - + - +++ + - 6

Clear Fell + + 0 - + - + - +++ + - 4

Coniferous + +++ + 0 + + +++ + +++ + + 1

Freshwater + - - - 0 - - + + + - 7

GrasslandMoors + + + - + 0 + + + + - 3

MiresMarshes - - - --- + - 0 - + + - 9

Mixed + + + - - - + 0 + + - 5

Sparse Veg --- --- --- --- - - - - 0 + --- 10

Urban - - - - - - - - - 0 - 11

Younger +++ + + - + + + + +++ + 0 2

Rank Order and

Significance

Coniferousgt Youngergt GrasslandMoorsgt Clear Fellgt Mixedgt Broad Leafgt Freshwatergt

Agriculturegt MiresMarshesgt Sparse Veggt Urban

40

Table 3 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the GS according to Jacobs index

Ran

k North Centre South

50 95 50 95 50 95

+ - + - + - + - + - + -

1 Broad

Leaf Urban Broad Leaf Sparse Veg

Broad

Leaf Urban Mixed Urban Coniferous Urban

Grassland

Moors Urban

2 Mixed Sparse Veg Mixed Freshwater Younger Agriculture Younger Sparse Veg Younger Sparse Veg Clear Fell Mixed

3 Mires

Agriculture Grassland

Urban Clear

Fell Coniferous Broad Leaf

Grassland

Moors

Clear Fell Agriculture Coniferous Sparse Veg

Marshes Moors

4 Younger Grassland

Younger Agriculture

Freshwater Coniferous Freshwater

Broad Leaf Mires

Younger Freshwater

Moors Marshes

5 Clear

Fell Freshwater

Mires Coniferous

Sparse Veg Clear Fell Agriculture

Freshwater Agriculture

Marshes

6 Coniferous Clear Fell

Mires

Marshes

Mires

Grassland

Moors

Mires

Marshes Marshes

7 Mixed Mixed Broad Leaf

8 Grassland

Moors

41

Table 4 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the WS according to Jacobs index

Ran

k North Centre South

50 95 50 95 50 95

+ - + - + - + - + - + -

1 Mires

Marshes

Grassland

Moors Mixed Freshwater Agriculture Urban Mixed Freshwater

Grassland

Moors Urban GrasslandMoors Urban

2 Freshwater Mixed Coniferous Urban Mires

Marshes Coniferous Sparse Veg Agriculture

Sparse

Veg Coniferous Freshwater

3 Urban Coniferous Younger Grassland

Moors Freshwater Younger Urban Freshwater

Broad

Leaf Agriculture Mixed

4 Younger Agriculture Sparse Veg Broad

Leaf

Broad

Leaf

Grassland

Moors Mixed Broad Leaf

5 Clear Fell Agriculture Coniferous Agriculture Mires

Marshes Clear Fell

6 Sparse

Veg

Mires

Marshes Mixed

Mires

Marshes

Clear

Fell

Mires

Marshes

7 Broad

Leaf Clear Fell Younger Clear Fell Younger Sparse Veg

8 Clear Fell Younger

9 Sparse

Veg

10 Grassland

Moors

42

Table 5 Second order (UD95Area) individual selectionavoidance for the GS and WS according to the Jacobs index

ID GS WS

Select Avoid Select Avoid

ID004 Younger Sparsely Vegetated MiresMarshes Sparsely Vegetated

ID005 MiresMarshes Sparsely Vegetated Coniferous GrasslandMoors

ID006 Coniferous Sparsely Vegetated Mixed Freshwater

ID008 Mixed Sparsely Vegetated Mixed Freshwater

ID009 Mixed Sparsely Vegetated Mixed GrasslandMoors

ID010 MiresMarshes Freshwater GrasslandMoors Freshwater

ID012 Broad Leaf Sparsely Vegetated Coniferous Urban

ID014 Clear Fell Sparsely Vegetated GrasslandMoors Sparsely Vegetated

ID015 GrasslandMoors Urban GrasslandMoors Freshwater

ID016 GrasslandMoors Freshwater GrasslandMoors Freshwater

ID017 GrasslandMoors Mixed Sparsely Vegetated Mixed

ID019 Mixed Sparsely Vegetated Mixed Urban

ID020 Broad Leaf Sparsely Vegetated Coniferous GrasslandMoors

ID022 MiresMarshes Freshwater MiresMarshes Freshwater

ID023 MiresMarshes GrasslandMoors Mixed Freshwater

ID024 Broadleaf Urban Broad Leaf Urban

ID026 GrasslandMoors Freshwater GrasslandMoors Freshwater

ID027 GrasslandMoors Urban Sparsely Vegetated Freshwater

43 Table 6 Third order (UD50UD95) individual selectionavoidance for the GS and WS according to the Jacobs index

ID GS WS

Select Avoid Select Avoid

ID004 Broad Leaf Mixed GrasslandMoors Freshwater

ID005 Broad Leaf Freshwater Agriculture Freshwater

ID006 Clear Fell Freshwater Agriculture MiresMarshes

ID008 MiresMarshes Freshwater Agriculture Urban

ID009 Freshwater Agriculture Agriculture Freshwater

ID010 Mixed Urban Sparsely Vegetated Urban

ID012 Coniferous GrasslandMoors Freshwater Urban

ID014 Urban Agriculture Freshwater Urban

ID015 Mixed Forest Urban Clear Fell Urban

ID016 Freshwater Urban GrasslandMoors Mixed

ID017 Coniferous Mixed Coniferous Broad Leaf

ID019 Broad Leaf GrasslandMoors Urban GrasslandMoors

ID020 Freshwater Urban Freshwater Agriculture

ID022 MiresMarshes Urban Broad Leaf GrasslandMoors

ID023 Freshwater Mixed Agriculture Freshwater

ID024 Mixed Freshwater Mixed Freshwater

ID026 Mixed MiresMarshes Sparsely Vegetated GrasslandMoors

ID027 Freshwater MiresMarshes GrasslandMoors Broad Leaf

44

Fig 2 North third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)

45

Fig 3 Centre third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)

46

Fig 4 South third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)

47

Fig 5 North second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)

48

Fig 6 Centre second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)

49

Fig 7 South second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)

50

Appendix F

Background

Fig 1 Daily mean snow depth and duration during the study period (Andrew Allen)

Female Moose Reproduction

Moose are seasonal polyoestral mammals (Monfort et al 1993) coming into oestrus during late September

early October (Garel et al 2009) The Swedish moose cow population reaches puberty between the ages 25

and 35 (Sand and Cederlund 1993) during which the reproductive period begins with the onset of ovulation

The age an individual reaches puberty is dependent on their body condition they have to reach a weight

threshold to reach puberty and become reproductive (Sand 1996) If she is over the weight threshold she will

go into oestrus in the autumn If she does not reach the weight threshold then she will go into oestrus the

following autumn if successful she will give birth to individual or twin calves in late May to early June

(Ericsson et al 2001) and therefore reach sexual maturity (Malmsten et al 2014b) Fecundity is related to

both the condition and the age of the cow Cows go through senescence at 12 years of age (Ericsson et al

2001) Providing calves with the required level of nutrition demands high energy and protein resources from

the mother during senescence this becomes harder to achieve leading to decreased levels of parental care

and higher levels of calf mortality

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39

Central

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 --- --- + + - - - + +++ --- 7

Broad Leaf +++ 0 + +++ + + + + + +++ - 2

Clear Fell +++ - 0 +++ + + + + + +++ - 3

Coniferous - --- --- 0 + - - --- +++ + --- 8

Freshwater - - - - 0 --- - - --- - - 11

GrasslandMoors + - - + +++ 0 + - + +++ - 5

MiresMarshes + - - + + - 0 + + +++ - 6

Mixed + - - +++ + + - 0 +++ +++ - 4

Sparse Veg - - - --- +++ - - --- 0 +++ - 9

Urban --- --- --- - + --- --- --- --- 0 --- 10

Younger +++ + + +++ + + + + + +++ 0 1

Rank Order and

Significance

Youngergt Broad Leafgt Clear Fellgt Mixedgt GrasslandMoorsgt MiresMarshesgt

Agriculturegt Coniferousgtgtgt Sparse Veggtgtgt Urbangt Freshwater

South

Ag

ricu

ltu

re

Bro

ad L

eaf

Cle

ar F

ell

Co

nif

ero

us

Fre

shw

ater

Gra

ssla

nd

Mo

ors

Mir

es

Mar

shes

Mix

ed

Sp

arse

Veg

Urb

an

Yo

un

ger

Ra

nk

Agriculture 0 - - - - - + - +++ + --- 8

Broad Leaf + 0 - --- + - + - +++ + - 6

Clear Fell + + 0 - + - + - +++ + - 4

Coniferous + +++ + 0 + + +++ + +++ + + 1

Freshwater + - - - 0 - - + + + - 7

GrasslandMoors + + + - + 0 + + + + - 3

MiresMarshes - - - --- + - 0 - + + - 9

Mixed + + + - - - + 0 + + - 5

Sparse Veg --- --- --- --- - - - - 0 + --- 10

Urban - - - - - - - - - 0 - 11

Younger +++ + + - + + + + +++ + 0 2

Rank Order and

Significance

Coniferousgt Youngergt GrasslandMoorsgt Clear Fellgt Mixedgt Broad Leafgt Freshwatergt

Agriculturegt MiresMarshesgt Sparse Veggt Urban

40

Table 3 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the GS according to Jacobs index

Ran

k North Centre South

50 95 50 95 50 95

+ - + - + - + - + - + -

1 Broad

Leaf Urban Broad Leaf Sparse Veg

Broad

Leaf Urban Mixed Urban Coniferous Urban

Grassland

Moors Urban

2 Mixed Sparse Veg Mixed Freshwater Younger Agriculture Younger Sparse Veg Younger Sparse Veg Clear Fell Mixed

3 Mires

Agriculture Grassland

Urban Clear

Fell Coniferous Broad Leaf

Grassland

Moors

Clear Fell Agriculture Coniferous Sparse Veg

Marshes Moors

4 Younger Grassland

Younger Agriculture

Freshwater Coniferous Freshwater

Broad Leaf Mires

Younger Freshwater

Moors Marshes

5 Clear

Fell Freshwater

Mires Coniferous

Sparse Veg Clear Fell Agriculture

Freshwater Agriculture

Marshes

6 Coniferous Clear Fell

Mires

Marshes

Mires

Grassland

Moors

Mires

Marshes Marshes

7 Mixed Mixed Broad Leaf

8 Grassland

Moors

41

Table 4 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the WS according to Jacobs index

Ran

k North Centre South

50 95 50 95 50 95

+ - + - + - + - + - + -

1 Mires

Marshes

Grassland

Moors Mixed Freshwater Agriculture Urban Mixed Freshwater

Grassland

Moors Urban GrasslandMoors Urban

2 Freshwater Mixed Coniferous Urban Mires

Marshes Coniferous Sparse Veg Agriculture

Sparse

Veg Coniferous Freshwater

3 Urban Coniferous Younger Grassland

Moors Freshwater Younger Urban Freshwater

Broad

Leaf Agriculture Mixed

4 Younger Agriculture Sparse Veg Broad

Leaf

Broad

Leaf

Grassland

Moors Mixed Broad Leaf

5 Clear Fell Agriculture Coniferous Agriculture Mires

Marshes Clear Fell

6 Sparse

Veg

Mires

Marshes Mixed

Mires

Marshes

Clear

Fell

Mires

Marshes

7 Broad

Leaf Clear Fell Younger Clear Fell Younger Sparse Veg

8 Clear Fell Younger

9 Sparse

Veg

10 Grassland

Moors

42

Table 5 Second order (UD95Area) individual selectionavoidance for the GS and WS according to the Jacobs index

ID GS WS

Select Avoid Select Avoid

ID004 Younger Sparsely Vegetated MiresMarshes Sparsely Vegetated

ID005 MiresMarshes Sparsely Vegetated Coniferous GrasslandMoors

ID006 Coniferous Sparsely Vegetated Mixed Freshwater

ID008 Mixed Sparsely Vegetated Mixed Freshwater

ID009 Mixed Sparsely Vegetated Mixed GrasslandMoors

ID010 MiresMarshes Freshwater GrasslandMoors Freshwater

ID012 Broad Leaf Sparsely Vegetated Coniferous Urban

ID014 Clear Fell Sparsely Vegetated GrasslandMoors Sparsely Vegetated

ID015 GrasslandMoors Urban GrasslandMoors Freshwater

ID016 GrasslandMoors Freshwater GrasslandMoors Freshwater

ID017 GrasslandMoors Mixed Sparsely Vegetated Mixed

ID019 Mixed Sparsely Vegetated Mixed Urban

ID020 Broad Leaf Sparsely Vegetated Coniferous GrasslandMoors

ID022 MiresMarshes Freshwater MiresMarshes Freshwater

ID023 MiresMarshes GrasslandMoors Mixed Freshwater

ID024 Broadleaf Urban Broad Leaf Urban

ID026 GrasslandMoors Freshwater GrasslandMoors Freshwater

ID027 GrasslandMoors Urban Sparsely Vegetated Freshwater

43 Table 6 Third order (UD50UD95) individual selectionavoidance for the GS and WS according to the Jacobs index

ID GS WS

Select Avoid Select Avoid

ID004 Broad Leaf Mixed GrasslandMoors Freshwater

ID005 Broad Leaf Freshwater Agriculture Freshwater

ID006 Clear Fell Freshwater Agriculture MiresMarshes

ID008 MiresMarshes Freshwater Agriculture Urban

ID009 Freshwater Agriculture Agriculture Freshwater

ID010 Mixed Urban Sparsely Vegetated Urban

ID012 Coniferous GrasslandMoors Freshwater Urban

ID014 Urban Agriculture Freshwater Urban

ID015 Mixed Forest Urban Clear Fell Urban

ID016 Freshwater Urban GrasslandMoors Mixed

ID017 Coniferous Mixed Coniferous Broad Leaf

ID019 Broad Leaf GrasslandMoors Urban GrasslandMoors

ID020 Freshwater Urban Freshwater Agriculture

ID022 MiresMarshes Urban Broad Leaf GrasslandMoors

ID023 Freshwater Mixed Agriculture Freshwater

ID024 Mixed Freshwater Mixed Freshwater

ID026 Mixed MiresMarshes Sparsely Vegetated GrasslandMoors

ID027 Freshwater MiresMarshes GrasslandMoors Broad Leaf

44

Fig 2 North third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)

45

Fig 3 Centre third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)

46

Fig 4 South third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)

47

Fig 5 North second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)

48

Fig 6 Centre second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)

49

Fig 7 South second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)

50

Appendix F

Background

Fig 1 Daily mean snow depth and duration during the study period (Andrew Allen)

Female Moose Reproduction

Moose are seasonal polyoestral mammals (Monfort et al 1993) coming into oestrus during late September

early October (Garel et al 2009) The Swedish moose cow population reaches puberty between the ages 25

and 35 (Sand and Cederlund 1993) during which the reproductive period begins with the onset of ovulation

The age an individual reaches puberty is dependent on their body condition they have to reach a weight

threshold to reach puberty and become reproductive (Sand 1996) If she is over the weight threshold she will

go into oestrus in the autumn If she does not reach the weight threshold then she will go into oestrus the

following autumn if successful she will give birth to individual or twin calves in late May to early June

(Ericsson et al 2001) and therefore reach sexual maturity (Malmsten et al 2014b) Fecundity is related to

both the condition and the age of the cow Cows go through senescence at 12 years of age (Ericsson et al

2001) Providing calves with the required level of nutrition demands high energy and protein resources from

the mother during senescence this becomes harder to achieve leading to decreased levels of parental care

and higher levels of calf mortality

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40

Table 3 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the GS according to Jacobs index

Ran

k North Centre South

50 95 50 95 50 95

+ - + - + - + - + - + -

1 Broad

Leaf Urban Broad Leaf Sparse Veg

Broad

Leaf Urban Mixed Urban Coniferous Urban

Grassland

Moors Urban

2 Mixed Sparse Veg Mixed Freshwater Younger Agriculture Younger Sparse Veg Younger Sparse Veg Clear Fell Mixed

3 Mires

Agriculture Grassland

Urban Clear

Fell Coniferous Broad Leaf

Grassland

Moors

Clear Fell Agriculture Coniferous Sparse Veg

Marshes Moors

4 Younger Grassland

Younger Agriculture

Freshwater Coniferous Freshwater

Broad Leaf Mires

Younger Freshwater

Moors Marshes

5 Clear

Fell Freshwater

Mires Coniferous

Sparse Veg Clear Fell Agriculture

Freshwater Agriculture

Marshes

6 Coniferous Clear Fell

Mires

Marshes

Mires

Grassland

Moors

Mires

Marshes Marshes

7 Mixed Mixed Broad Leaf

8 Grassland

Moors

41

Table 4 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the WS according to Jacobs index

Ran

k North Centre South

50 95 50 95 50 95

+ - + - + - + - + - + -

1 Mires

Marshes

Grassland

Moors Mixed Freshwater Agriculture Urban Mixed Freshwater

Grassland

Moors Urban GrasslandMoors Urban

2 Freshwater Mixed Coniferous Urban Mires

Marshes Coniferous Sparse Veg Agriculture

Sparse

Veg Coniferous Freshwater

3 Urban Coniferous Younger Grassland

Moors Freshwater Younger Urban Freshwater

Broad

Leaf Agriculture Mixed

4 Younger Agriculture Sparse Veg Broad

Leaf

Broad

Leaf

Grassland

Moors Mixed Broad Leaf

5 Clear Fell Agriculture Coniferous Agriculture Mires

Marshes Clear Fell

6 Sparse

Veg

Mires

Marshes Mixed

Mires

Marshes

Clear

Fell

Mires

Marshes

7 Broad

Leaf Clear Fell Younger Clear Fell Younger Sparse Veg

8 Clear Fell Younger

9 Sparse

Veg

10 Grassland

Moors

42

Table 5 Second order (UD95Area) individual selectionavoidance for the GS and WS according to the Jacobs index

ID GS WS

Select Avoid Select Avoid

ID004 Younger Sparsely Vegetated MiresMarshes Sparsely Vegetated

ID005 MiresMarshes Sparsely Vegetated Coniferous GrasslandMoors

ID006 Coniferous Sparsely Vegetated Mixed Freshwater

ID008 Mixed Sparsely Vegetated Mixed Freshwater

ID009 Mixed Sparsely Vegetated Mixed GrasslandMoors

ID010 MiresMarshes Freshwater GrasslandMoors Freshwater

ID012 Broad Leaf Sparsely Vegetated Coniferous Urban

ID014 Clear Fell Sparsely Vegetated GrasslandMoors Sparsely Vegetated

ID015 GrasslandMoors Urban GrasslandMoors Freshwater

ID016 GrasslandMoors Freshwater GrasslandMoors Freshwater

ID017 GrasslandMoors Mixed Sparsely Vegetated Mixed

ID019 Mixed Sparsely Vegetated Mixed Urban

ID020 Broad Leaf Sparsely Vegetated Coniferous GrasslandMoors

ID022 MiresMarshes Freshwater MiresMarshes Freshwater

ID023 MiresMarshes GrasslandMoors Mixed Freshwater

ID024 Broadleaf Urban Broad Leaf Urban

ID026 GrasslandMoors Freshwater GrasslandMoors Freshwater

ID027 GrasslandMoors Urban Sparsely Vegetated Freshwater

43 Table 6 Third order (UD50UD95) individual selectionavoidance for the GS and WS according to the Jacobs index

ID GS WS

Select Avoid Select Avoid

ID004 Broad Leaf Mixed GrasslandMoors Freshwater

ID005 Broad Leaf Freshwater Agriculture Freshwater

ID006 Clear Fell Freshwater Agriculture MiresMarshes

ID008 MiresMarshes Freshwater Agriculture Urban

ID009 Freshwater Agriculture Agriculture Freshwater

ID010 Mixed Urban Sparsely Vegetated Urban

ID012 Coniferous GrasslandMoors Freshwater Urban

ID014 Urban Agriculture Freshwater Urban

ID015 Mixed Forest Urban Clear Fell Urban

ID016 Freshwater Urban GrasslandMoors Mixed

ID017 Coniferous Mixed Coniferous Broad Leaf

ID019 Broad Leaf GrasslandMoors Urban GrasslandMoors

ID020 Freshwater Urban Freshwater Agriculture

ID022 MiresMarshes Urban Broad Leaf GrasslandMoors

ID023 Freshwater Mixed Agriculture Freshwater

ID024 Mixed Freshwater Mixed Freshwater

ID026 Mixed MiresMarshes Sparsely Vegetated GrasslandMoors

ID027 Freshwater MiresMarshes GrasslandMoors Broad Leaf

44

Fig 2 North third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)

45

Fig 3 Centre third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)

46

Fig 4 South third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)

47

Fig 5 North second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)

48

Fig 6 Centre second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)

49

Fig 7 South second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)

50

Appendix F

Background

Fig 1 Daily mean snow depth and duration during the study period (Andrew Allen)

Female Moose Reproduction

Moose are seasonal polyoestral mammals (Monfort et al 1993) coming into oestrus during late September

early October (Garel et al 2009) The Swedish moose cow population reaches puberty between the ages 25

and 35 (Sand and Cederlund 1993) during which the reproductive period begins with the onset of ovulation

The age an individual reaches puberty is dependent on their body condition they have to reach a weight

threshold to reach puberty and become reproductive (Sand 1996) If she is over the weight threshold she will

go into oestrus in the autumn If she does not reach the weight threshold then she will go into oestrus the

following autumn if successful she will give birth to individual or twin calves in late May to early June

(Ericsson et al 2001) and therefore reach sexual maturity (Malmsten et al 2014b) Fecundity is related to

both the condition and the age of the cow Cows go through senescence at 12 years of age (Ericsson et al

2001) Providing calves with the required level of nutrition demands high energy and protein resources from

the mother during senescence this becomes harder to achieve leading to decreased levels of parental care

and higher levels of calf mortality

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41

Table 4 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the WS according to Jacobs index

Ran

k North Centre South

50 95 50 95 50 95

+ - + - + - + - + - + -

1 Mires

Marshes

Grassland

Moors Mixed Freshwater Agriculture Urban Mixed Freshwater

Grassland

Moors Urban GrasslandMoors Urban

2 Freshwater Mixed Coniferous Urban Mires

Marshes Coniferous Sparse Veg Agriculture

Sparse

Veg Coniferous Freshwater

3 Urban Coniferous Younger Grassland

Moors Freshwater Younger Urban Freshwater

Broad

Leaf Agriculture Mixed

4 Younger Agriculture Sparse Veg Broad

Leaf

Broad

Leaf

Grassland

Moors Mixed Broad Leaf

5 Clear Fell Agriculture Coniferous Agriculture Mires

Marshes Clear Fell

6 Sparse

Veg

Mires

Marshes Mixed

Mires

Marshes

Clear

Fell

Mires

Marshes

7 Broad

Leaf Clear Fell Younger Clear Fell Younger Sparse Veg

8 Clear Fell Younger

9 Sparse

Veg

10 Grassland

Moors

42

Table 5 Second order (UD95Area) individual selectionavoidance for the GS and WS according to the Jacobs index

ID GS WS

Select Avoid Select Avoid

ID004 Younger Sparsely Vegetated MiresMarshes Sparsely Vegetated

ID005 MiresMarshes Sparsely Vegetated Coniferous GrasslandMoors

ID006 Coniferous Sparsely Vegetated Mixed Freshwater

ID008 Mixed Sparsely Vegetated Mixed Freshwater

ID009 Mixed Sparsely Vegetated Mixed GrasslandMoors

ID010 MiresMarshes Freshwater GrasslandMoors Freshwater

ID012 Broad Leaf Sparsely Vegetated Coniferous Urban

ID014 Clear Fell Sparsely Vegetated GrasslandMoors Sparsely Vegetated

ID015 GrasslandMoors Urban GrasslandMoors Freshwater

ID016 GrasslandMoors Freshwater GrasslandMoors Freshwater

ID017 GrasslandMoors Mixed Sparsely Vegetated Mixed

ID019 Mixed Sparsely Vegetated Mixed Urban

ID020 Broad Leaf Sparsely Vegetated Coniferous GrasslandMoors

ID022 MiresMarshes Freshwater MiresMarshes Freshwater

ID023 MiresMarshes GrasslandMoors Mixed Freshwater

ID024 Broadleaf Urban Broad Leaf Urban

ID026 GrasslandMoors Freshwater GrasslandMoors Freshwater

ID027 GrasslandMoors Urban Sparsely Vegetated Freshwater

43 Table 6 Third order (UD50UD95) individual selectionavoidance for the GS and WS according to the Jacobs index

ID GS WS

Select Avoid Select Avoid

ID004 Broad Leaf Mixed GrasslandMoors Freshwater

ID005 Broad Leaf Freshwater Agriculture Freshwater

ID006 Clear Fell Freshwater Agriculture MiresMarshes

ID008 MiresMarshes Freshwater Agriculture Urban

ID009 Freshwater Agriculture Agriculture Freshwater

ID010 Mixed Urban Sparsely Vegetated Urban

ID012 Coniferous GrasslandMoors Freshwater Urban

ID014 Urban Agriculture Freshwater Urban

ID015 Mixed Forest Urban Clear Fell Urban

ID016 Freshwater Urban GrasslandMoors Mixed

ID017 Coniferous Mixed Coniferous Broad Leaf

ID019 Broad Leaf GrasslandMoors Urban GrasslandMoors

ID020 Freshwater Urban Freshwater Agriculture

ID022 MiresMarshes Urban Broad Leaf GrasslandMoors

ID023 Freshwater Mixed Agriculture Freshwater

ID024 Mixed Freshwater Mixed Freshwater

ID026 Mixed MiresMarshes Sparsely Vegetated GrasslandMoors

ID027 Freshwater MiresMarshes GrasslandMoors Broad Leaf

44

Fig 2 North third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)

45

Fig 3 Centre third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)

46

Fig 4 South third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)

47

Fig 5 North second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)

48

Fig 6 Centre second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)

49

Fig 7 South second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)

50

Appendix F

Background

Fig 1 Daily mean snow depth and duration during the study period (Andrew Allen)

Female Moose Reproduction

Moose are seasonal polyoestral mammals (Monfort et al 1993) coming into oestrus during late September

early October (Garel et al 2009) The Swedish moose cow population reaches puberty between the ages 25

and 35 (Sand and Cederlund 1993) during which the reproductive period begins with the onset of ovulation

The age an individual reaches puberty is dependent on their body condition they have to reach a weight

threshold to reach puberty and become reproductive (Sand 1996) If she is over the weight threshold she will

go into oestrus in the autumn If she does not reach the weight threshold then she will go into oestrus the

following autumn if successful she will give birth to individual or twin calves in late May to early June

(Ericsson et al 2001) and therefore reach sexual maturity (Malmsten et al 2014b) Fecundity is related to

both the condition and the age of the cow Cows go through senescence at 12 years of age (Ericsson et al

2001) Providing calves with the required level of nutrition demands high energy and protein resources from

the mother during senescence this becomes harder to achieve leading to decreased levels of parental care

and higher levels of calf mortality

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42

Table 5 Second order (UD95Area) individual selectionavoidance for the GS and WS according to the Jacobs index

ID GS WS

Select Avoid Select Avoid

ID004 Younger Sparsely Vegetated MiresMarshes Sparsely Vegetated

ID005 MiresMarshes Sparsely Vegetated Coniferous GrasslandMoors

ID006 Coniferous Sparsely Vegetated Mixed Freshwater

ID008 Mixed Sparsely Vegetated Mixed Freshwater

ID009 Mixed Sparsely Vegetated Mixed GrasslandMoors

ID010 MiresMarshes Freshwater GrasslandMoors Freshwater

ID012 Broad Leaf Sparsely Vegetated Coniferous Urban

ID014 Clear Fell Sparsely Vegetated GrasslandMoors Sparsely Vegetated

ID015 GrasslandMoors Urban GrasslandMoors Freshwater

ID016 GrasslandMoors Freshwater GrasslandMoors Freshwater

ID017 GrasslandMoors Mixed Sparsely Vegetated Mixed

ID019 Mixed Sparsely Vegetated Mixed Urban

ID020 Broad Leaf Sparsely Vegetated Coniferous GrasslandMoors

ID022 MiresMarshes Freshwater MiresMarshes Freshwater

ID023 MiresMarshes GrasslandMoors Mixed Freshwater

ID024 Broadleaf Urban Broad Leaf Urban

ID026 GrasslandMoors Freshwater GrasslandMoors Freshwater

ID027 GrasslandMoors Urban Sparsely Vegetated Freshwater

43 Table 6 Third order (UD50UD95) individual selectionavoidance for the GS and WS according to the Jacobs index

ID GS WS

Select Avoid Select Avoid

ID004 Broad Leaf Mixed GrasslandMoors Freshwater

ID005 Broad Leaf Freshwater Agriculture Freshwater

ID006 Clear Fell Freshwater Agriculture MiresMarshes

ID008 MiresMarshes Freshwater Agriculture Urban

ID009 Freshwater Agriculture Agriculture Freshwater

ID010 Mixed Urban Sparsely Vegetated Urban

ID012 Coniferous GrasslandMoors Freshwater Urban

ID014 Urban Agriculture Freshwater Urban

ID015 Mixed Forest Urban Clear Fell Urban

ID016 Freshwater Urban GrasslandMoors Mixed

ID017 Coniferous Mixed Coniferous Broad Leaf

ID019 Broad Leaf GrasslandMoors Urban GrasslandMoors

ID020 Freshwater Urban Freshwater Agriculture

ID022 MiresMarshes Urban Broad Leaf GrasslandMoors

ID023 Freshwater Mixed Agriculture Freshwater

ID024 Mixed Freshwater Mixed Freshwater

ID026 Mixed MiresMarshes Sparsely Vegetated GrasslandMoors

ID027 Freshwater MiresMarshes GrasslandMoors Broad Leaf

44

Fig 2 North third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)

45

Fig 3 Centre third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)

46

Fig 4 South third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)

47

Fig 5 North second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)

48

Fig 6 Centre second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)

49

Fig 7 South second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)

50

Appendix F

Background

Fig 1 Daily mean snow depth and duration during the study period (Andrew Allen)

Female Moose Reproduction

Moose are seasonal polyoestral mammals (Monfort et al 1993) coming into oestrus during late September

early October (Garel et al 2009) The Swedish moose cow population reaches puberty between the ages 25

and 35 (Sand and Cederlund 1993) during which the reproductive period begins with the onset of ovulation

The age an individual reaches puberty is dependent on their body condition they have to reach a weight

threshold to reach puberty and become reproductive (Sand 1996) If she is over the weight threshold she will

go into oestrus in the autumn If she does not reach the weight threshold then she will go into oestrus the

following autumn if successful she will give birth to individual or twin calves in late May to early June

(Ericsson et al 2001) and therefore reach sexual maturity (Malmsten et al 2014b) Fecundity is related to

both the condition and the age of the cow Cows go through senescence at 12 years of age (Ericsson et al

2001) Providing calves with the required level of nutrition demands high energy and protein resources from

the mother during senescence this becomes harder to achieve leading to decreased levels of parental care

and higher levels of calf mortality

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43 Table 6 Third order (UD50UD95) individual selectionavoidance for the GS and WS according to the Jacobs index

ID GS WS

Select Avoid Select Avoid

ID004 Broad Leaf Mixed GrasslandMoors Freshwater

ID005 Broad Leaf Freshwater Agriculture Freshwater

ID006 Clear Fell Freshwater Agriculture MiresMarshes

ID008 MiresMarshes Freshwater Agriculture Urban

ID009 Freshwater Agriculture Agriculture Freshwater

ID010 Mixed Urban Sparsely Vegetated Urban

ID012 Coniferous GrasslandMoors Freshwater Urban

ID014 Urban Agriculture Freshwater Urban

ID015 Mixed Forest Urban Clear Fell Urban

ID016 Freshwater Urban GrasslandMoors Mixed

ID017 Coniferous Mixed Coniferous Broad Leaf

ID019 Broad Leaf GrasslandMoors Urban GrasslandMoors

ID020 Freshwater Urban Freshwater Agriculture

ID022 MiresMarshes Urban Broad Leaf GrasslandMoors

ID023 Freshwater Mixed Agriculture Freshwater

ID024 Mixed Freshwater Mixed Freshwater

ID026 Mixed MiresMarshes Sparsely Vegetated GrasslandMoors

ID027 Freshwater MiresMarshes GrasslandMoors Broad Leaf

44

Fig 2 North third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)

45

Fig 3 Centre third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)

46

Fig 4 South third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)

47

Fig 5 North second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)

48

Fig 6 Centre second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)

49

Fig 7 South second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)

50

Appendix F

Background

Fig 1 Daily mean snow depth and duration during the study period (Andrew Allen)

Female Moose Reproduction

Moose are seasonal polyoestral mammals (Monfort et al 1993) coming into oestrus during late September

early October (Garel et al 2009) The Swedish moose cow population reaches puberty between the ages 25

and 35 (Sand and Cederlund 1993) during which the reproductive period begins with the onset of ovulation

The age an individual reaches puberty is dependent on their body condition they have to reach a weight

threshold to reach puberty and become reproductive (Sand 1996) If she is over the weight threshold she will

go into oestrus in the autumn If she does not reach the weight threshold then she will go into oestrus the

following autumn if successful she will give birth to individual or twin calves in late May to early June

(Ericsson et al 2001) and therefore reach sexual maturity (Malmsten et al 2014b) Fecundity is related to

both the condition and the age of the cow Cows go through senescence at 12 years of age (Ericsson et al

2001) Providing calves with the required level of nutrition demands high energy and protein resources from

the mother during senescence this becomes harder to achieve leading to decreased levels of parental care

and higher levels of calf mortality

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44

Fig 2 North third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)

45

Fig 3 Centre third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)

46

Fig 4 South third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)

47

Fig 5 North second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)

48

Fig 6 Centre second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)

49

Fig 7 South second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)

50

Appendix F

Background

Fig 1 Daily mean snow depth and duration during the study period (Andrew Allen)

Female Moose Reproduction

Moose are seasonal polyoestral mammals (Monfort et al 1993) coming into oestrus during late September

early October (Garel et al 2009) The Swedish moose cow population reaches puberty between the ages 25

and 35 (Sand and Cederlund 1993) during which the reproductive period begins with the onset of ovulation

The age an individual reaches puberty is dependent on their body condition they have to reach a weight

threshold to reach puberty and become reproductive (Sand 1996) If she is over the weight threshold she will

go into oestrus in the autumn If she does not reach the weight threshold then she will go into oestrus the

following autumn if successful she will give birth to individual or twin calves in late May to early June

(Ericsson et al 2001) and therefore reach sexual maturity (Malmsten et al 2014b) Fecundity is related to

both the condition and the age of the cow Cows go through senescence at 12 years of age (Ericsson et al

2001) Providing calves with the required level of nutrition demands high energy and protein resources from

the mother during senescence this becomes harder to achieve leading to decreased levels of parental care

and higher levels of calf mortality

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45

Fig 3 Centre third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)

46

Fig 4 South third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)

47

Fig 5 North second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)

48

Fig 6 Centre second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)

49

Fig 7 South second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)

50

Appendix F

Background

Fig 1 Daily mean snow depth and duration during the study period (Andrew Allen)

Female Moose Reproduction

Moose are seasonal polyoestral mammals (Monfort et al 1993) coming into oestrus during late September

early October (Garel et al 2009) The Swedish moose cow population reaches puberty between the ages 25

and 35 (Sand and Cederlund 1993) during which the reproductive period begins with the onset of ovulation

The age an individual reaches puberty is dependent on their body condition they have to reach a weight

threshold to reach puberty and become reproductive (Sand 1996) If she is over the weight threshold she will

go into oestrus in the autumn If she does not reach the weight threshold then she will go into oestrus the

following autumn if successful she will give birth to individual or twin calves in late May to early June

(Ericsson et al 2001) and therefore reach sexual maturity (Malmsten et al 2014b) Fecundity is related to

both the condition and the age of the cow Cows go through senescence at 12 years of age (Ericsson et al

2001) Providing calves with the required level of nutrition demands high energy and protein resources from

the mother during senescence this becomes harder to achieve leading to decreased levels of parental care

and higher levels of calf mortality

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46

Fig 4 South third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)

47

Fig 5 North second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)

48

Fig 6 Centre second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)

49

Fig 7 South second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)

50

Appendix F

Background

Fig 1 Daily mean snow depth and duration during the study period (Andrew Allen)

Female Moose Reproduction

Moose are seasonal polyoestral mammals (Monfort et al 1993) coming into oestrus during late September

early October (Garel et al 2009) The Swedish moose cow population reaches puberty between the ages 25

and 35 (Sand and Cederlund 1993) during which the reproductive period begins with the onset of ovulation

The age an individual reaches puberty is dependent on their body condition they have to reach a weight

threshold to reach puberty and become reproductive (Sand 1996) If she is over the weight threshold she will

go into oestrus in the autumn If she does not reach the weight threshold then she will go into oestrus the

following autumn if successful she will give birth to individual or twin calves in late May to early June

(Ericsson et al 2001) and therefore reach sexual maturity (Malmsten et al 2014b) Fecundity is related to

both the condition and the age of the cow Cows go through senescence at 12 years of age (Ericsson et al

2001) Providing calves with the required level of nutrition demands high energy and protein resources from

the mother during senescence this becomes harder to achieve leading to decreased levels of parental care

and higher levels of calf mortality

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47

Fig 5 North second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)

48

Fig 6 Centre second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)

49

Fig 7 South second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)

50

Appendix F

Background

Fig 1 Daily mean snow depth and duration during the study period (Andrew Allen)

Female Moose Reproduction

Moose are seasonal polyoestral mammals (Monfort et al 1993) coming into oestrus during late September

early October (Garel et al 2009) The Swedish moose cow population reaches puberty between the ages 25

and 35 (Sand and Cederlund 1993) during which the reproductive period begins with the onset of ovulation

The age an individual reaches puberty is dependent on their body condition they have to reach a weight

threshold to reach puberty and become reproductive (Sand 1996) If she is over the weight threshold she will

go into oestrus in the autumn If she does not reach the weight threshold then she will go into oestrus the

following autumn if successful she will give birth to individual or twin calves in late May to early June

(Ericsson et al 2001) and therefore reach sexual maturity (Malmsten et al 2014b) Fecundity is related to

both the condition and the age of the cow Cows go through senescence at 12 years of age (Ericsson et al

2001) Providing calves with the required level of nutrition demands high energy and protein resources from

the mother during senescence this becomes harder to achieve leading to decreased levels of parental care

and higher levels of calf mortality

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48

Fig 6 Centre second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)

49

Fig 7 South second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)

50

Appendix F

Background

Fig 1 Daily mean snow depth and duration during the study period (Andrew Allen)

Female Moose Reproduction

Moose are seasonal polyoestral mammals (Monfort et al 1993) coming into oestrus during late September

early October (Garel et al 2009) The Swedish moose cow population reaches puberty between the ages 25

and 35 (Sand and Cederlund 1993) during which the reproductive period begins with the onset of ovulation

The age an individual reaches puberty is dependent on their body condition they have to reach a weight

threshold to reach puberty and become reproductive (Sand 1996) If she is over the weight threshold she will

go into oestrus in the autumn If she does not reach the weight threshold then she will go into oestrus the

following autumn if successful she will give birth to individual or twin calves in late May to early June

(Ericsson et al 2001) and therefore reach sexual maturity (Malmsten et al 2014b) Fecundity is related to

both the condition and the age of the cow Cows go through senescence at 12 years of age (Ericsson et al

2001) Providing calves with the required level of nutrition demands high energy and protein resources from

the mother during senescence this becomes harder to achieve leading to decreased levels of parental care

and higher levels of calf mortality

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49

Fig 7 South second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)

50

Appendix F

Background

Fig 1 Daily mean snow depth and duration during the study period (Andrew Allen)

Female Moose Reproduction

Moose are seasonal polyoestral mammals (Monfort et al 1993) coming into oestrus during late September

early October (Garel et al 2009) The Swedish moose cow population reaches puberty between the ages 25

and 35 (Sand and Cederlund 1993) during which the reproductive period begins with the onset of ovulation

The age an individual reaches puberty is dependent on their body condition they have to reach a weight

threshold to reach puberty and become reproductive (Sand 1996) If she is over the weight threshold she will

go into oestrus in the autumn If she does not reach the weight threshold then she will go into oestrus the

following autumn if successful she will give birth to individual or twin calves in late May to early June

(Ericsson et al 2001) and therefore reach sexual maturity (Malmsten et al 2014b) Fecundity is related to

both the condition and the age of the cow Cows go through senescence at 12 years of age (Ericsson et al

2001) Providing calves with the required level of nutrition demands high energy and protein resources from

the mother during senescence this becomes harder to achieve leading to decreased levels of parental care

and higher levels of calf mortality

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50

Appendix F

Background

Fig 1 Daily mean snow depth and duration during the study period (Andrew Allen)

Female Moose Reproduction

Moose are seasonal polyoestral mammals (Monfort et al 1993) coming into oestrus during late September

early October (Garel et al 2009) The Swedish moose cow population reaches puberty between the ages 25

and 35 (Sand and Cederlund 1993) during which the reproductive period begins with the onset of ovulation

The age an individual reaches puberty is dependent on their body condition they have to reach a weight

threshold to reach puberty and become reproductive (Sand 1996) If she is over the weight threshold she will

go into oestrus in the autumn If she does not reach the weight threshold then she will go into oestrus the

following autumn if successful she will give birth to individual or twin calves in late May to early June

(Ericsson et al 2001) and therefore reach sexual maturity (Malmsten et al 2014b) Fecundity is related to

both the condition and the age of the cow Cows go through senescence at 12 years of age (Ericsson et al

2001) Providing calves with the required level of nutrition demands high energy and protein resources from

the mother during senescence this becomes harder to achieve leading to decreased levels of parental care

and higher levels of calf mortality