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Dynamics of small mammal communities along an elevational gradient

Journal: Canadian Journal of Zoology

Manuscript ID cjz-2018-0201.R2

Manuscript Type: Article

Date Submitted by the Author: 03-Oct-2018

Complete List of Authors: Benedek, Ana Maria; Lucian Blaga University of Sibiu, Faculty of Sciences, Applied Ecology Research CenterSirbu, Ioan; Lucian Blaga University of Sibiu, Faculty of Sciences, Applied Ecology Research Center

Is your manuscript invited for consideration in a Special

Issue?:Not applicable (regular submission)

Keyword: community dynamics, elevational gradient, multivariate analysis, rodents, shrews, Rodentia, Soricidae

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Dynamics of small mammal communities along an elevational gradient

A. M. Benedeka, I. Sîrbua

aLucian Blaga University of Sibiu, Faculty of Sciences, Applied Ecology Research Center, 5-7

Raţiu Street, 550012 Sibiu, Romania. ana.benedek@ulbsibiu.ro, ioan.n.sirbu@ulbsibiu.ro

Corresponding author:

A.M. Benedek

Lucian Blaga University of Sibiu

Faculty of Sciences

Applied Ecology Research Center

5-7 Raţiu Street, 550012 Sibiu

Romania

Telephone: 0040 269 216 642

Mobile: 0040 744 538 278

Fax: 0040 269 216 617

E-mail address: ana.benedek@ulbsibiu.ro, benedek_ana@yahoo.com

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Dynamics of small mammal communities along an elevational gradient

A. M. Benedeka, I. Sîrbua

Abstract

Elevation is one of the most important natural gradients that is strongly shaping communities

across relatively small areas. However, few studies have followed the temporal dynamics of

elevational patterns, even in organisms for which population and community fluctuations have

been extensively studied, such as rodents. Here we report the multiannual dynamics of small

mammal communities along an elevational gradient in the Southern Carpathians. During a five-

year survey, we conducted live-trapping in forested and shrubby habitats, at elevations between

820 m and 2040 m. We used partial constrained multivariate analysis and mixed effects models

to test the effect of elevation, year, and their interaction. Community metrics differed

significantly between even and odd years and temporal changes had stronger effect on small

mammal communities than elevation. The two-year pattern of dynamics was especially marked

in Apodemus flavicollis (Melchior, 1834). Species abundance was predicted not only by year

and elevation, but also by their interaction. The dominant rodent species, Myodes glareolus

(Schreber, 1780) and A. flavicollis, showed opposite annual patterns in relation to elevation,

possibly as a strategy to avoid competition. Failure to consider the fluctuations in montane small

mammal communities may lead to wrong assessment of species’ state and distribution.

Key words: community dynamics, elevational gradient, multivariate analysis, rodents, shrews,

Rodentia, Soricidae

Introduction

Understanding the patterns and driving forces of the spatio-temporal population and

community dynamics is one of the main goals of ecology, and small mammals, especially

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microtine rodents, have long been model species (Hansson and Henttonen 1985; Krebs 1996;

Lambin et al. 1998; Bierman et al. 2006). One of the most complex spatial gradients is

elevation. Many of the recent studies on small mammals in montane areas focus either on the

changes in the communities along the elevational gradient (McCain 2005; Rowe et al. 2015), or

on their temporal dynamics. Studies on elevational patterns are conducted especially in tropical

zones (Willig and Presley 2016), where changes in environmental conditions along this gradient

are greatest (Dreiss et al. 2015). However, few studies combine the two viewpoints.

Several multiannual studies were conducted in the Northern Carpathians, but these

aimed mainly to evaluate the effect of habitat characteristics and forest management on small

mammal community structure (Bryja et al. 2002; Suchomel et al. 2014; Krojerová-Prokešová et

al. 2016). Data from long term studies on small mammals in Central Europe come mainly from

lowlands of Poland, the Białowieża National Park (Pucek et al. 1993; Stenseth et al. 2002b) and

Crabapple Island (Grüm and Bujalska 2000; Bujalska and Grüm 2008), where forests are

dominated by oak and other broadleaf trees. In the Southern Carpathians data on small

mammals are scarce and mainly faunistical (Gurzău et al. 2008; Murariu et al. 2009; Nae et al.

2010).

Small mammals usually exhibit extensive multiannual and often cyclic variation in

population size (Batzli 1992), but the patterns are largely variable. Well studied and known is

the increase in amplitude and cycle length along the latitudinal gradient towards north in

Scandinavian voles and lemmings (Hansson and Henttonen 1985), but the pattern is opposite in

Central Europe (Tkadlec and Stenseth 2001). Climatic factors are important drivers of

population dynamics, having direct (Hansson and Henttonen 1985) or more often indirect effect,

through primary production (Pucek et al. 1993; Stenseth et al. 2002b). In more seasonal

environments with shortened vegetation periods, population dynamics is less stable (Tkadlec

and Zejda 1998). However, the effect of climate on demography differs among species, habitats

and geographical areas (Ims et al. 2008). Landscape and habitat characteristics may also

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influence population dynamics. Landscape heterogeneity is associated with more stable rodent

populations (Loman 2008).

Myodes glareolus (Schreber, 1780) and Apodemus flavicollis (Melchior, 1834) are the

dominant species in most forests of central and eastern Europe (Pucek et al. 1993; Hille and

Mortelliti 2010), with one or the other being more numerous depending on habitat conditions

and geographic position. The relative abundance of M. glareolus increases towards north and

along the elevational gradient (Torre and Arrizabalaga 2008). These species are also

characteristic of forests in the Southern Carpathians. The dominance of A. flavicollis within the

community extends also in lowland forests, where M. glareolus is scarce and usually limited to

moist habitats with tall herbaceous vegetation (Benedek and Sîrbu 2018). Population dynamics

of these two species have been observed in several long-term studies and different mechanisms

explaining the multiannual fluctuations have been proposed. Apodemus flavicollis seems to be

more vulnerable than M. glareolus to rapid declines in population densities because rapid onset

of breeding and maturation do not allow the formation of a pool of immature females at the end

of breeding season that can replace the mature females that die (Bujalska and Grüm 2008).

Density-dependent winter mortality can also shape rodent abundances, especially in spring

(Pucek et al. 1993). Along with the intrinsic factors, a series of extrinsic factors play an

important role in the determination of dynamics in A. flavicollis and M. glareolus. Massive mast

fruiting allows winter breeding (Löfgren et al. 1996) leading to a rapid population growth in

both species followed by a crash next year (Pucek et al. 1993). Generalist predators regulate and

stabilize population dynamics (Hanski et al. 1991).

Several studies have demonstrated a negative correlation between abundances of A.

flavicollis and M. glareolus, suggesting a competitive relationship, with A. flavicollis exhibiting

higher competitive abilities (Marsh et al. 2001, Hille and Mortelliti 2010). Apodemus flavicollis

is heavier and stronger than M. glareolus and when they meet M. glareolus usually retreats

(Andrezjewski and Olszewski 1963). But M. glareolus may also affect population growth of A.

flavicollis, especially in late spring and early summer (Bujalska and Grüm 2008). However,

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sometimes no quantitative effects of this competition on population dynamics of either species

are observed (Pucek et al. 1993) and there are several mechanisms to avoid competition in these

species: differential microhabitat use (Amori et al. 2015), diet (Hansson 1985), degree of

arboreality (Buesching et al. 2008), temporal activity pattern (Alcheikh 2001).

For five years we conducted surveys in the Retezat Mountains of Romania, aiming to

assess the abundance and composition of small mammal communities in relation to elevation

and year. Because small mammals in montane forest habitats face harsh conditions resulting in

short vegetation period, few resources and low vegetation heterogeneity, we hypothesized that:

1. high elevation communities undergo significant year-to-year changes in total abundance,

species abundance and richness, which are more important than the effect of elevation in

shaping small mammal communities in montane habitats and 2. temporal patterns are better

defined at higher elevations (implying that the effect of the interaction between time and

elevation on the communities is significant). Fluctuations in species abundance follow changes

in the environment, to which species respond more or less differently. Moreover, we expect

some competition between the two dominant rodents and a mechanism to reduce this

competition, so we hypothesized that communities do not fluctuate entirely together (i.e.

changes in species composition are also significant). In addition, we predicted that, because of

its more thermophilous nature, A. flavicollis would fluctuate more intensely.

Study area and methods

Landscape description

The present paper is based on the analysis of a data set obtained during annual surveys

conducted between 2002 and 2006 in the Retezat Mountains National Park, the oldest

(established in 1935) protected area in Romania, and in some adjacent logged areas. The study

area is situated in the Southern Carpathians, between 45°56.190' to 46°02.759' N and 24°27.460'

to 24°46.040' E. The trapping sites, situated in forests and subalpine shrublands between 820

and 2080 m, were chosen for the best spatial coverage, being located along four valleys in

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different parts of the massif and covering most of the range of elevation in the Park. Beech

(Fagus sylvatica L.) forests, mostly with sparse herbaceous layer and understory dominate at the

lowest elevations. Mixed forest habitats, composed of differing proportions of beech and

Norway spruce (Picea abies (L.) H. Karst) with scattered silver fir (Abies alba L.) and sycamore

(Acer pseudoplatanus L.), often have rich understory and herbaceous layer. Canopy cover of

beech in mixed forests is sometimes reduced because of harvesting of older trees. Norway

spruce forests dominate at high elevations and vary in shrub and herbaceous layer cover. Their

canopy cover is either dense or absent (after clear-cutting). At timberline, mountain-ash (Sorbus

aucuparia L.) and stone pine (Pinus cembra L.) are interspersed among dwarf spruce trees.

Above the timberline, shrubby mugo pine (Pinus mugo Turra) may cover parts of the subalpine

meadows.

Small mammal trapping

We live-trapped small mammals using artisanal wooden box-traps (18 x 10 x 8 cm)

(supplementary Fig. S1)1 in summer (mid June to early July) and autumn (September) from

2002 to 2006. In 2006 trapping was conducted only in autumn. Transects included 30 to 40

traps placed at intervals of 15 m. We used sunflower seeds and apple slices as bait but we did

not prebait the traps. We checked the traps in early morning and at dusk for two nights. Because

some traps were non-functional (closed by strong wind, disturbed by animals or stolen), we

used a third night when needed to compensate for these, so our trapping effort ranged between

40 and 80 trap-nights per transect. Traps were set in transects within the forest at minimum 100

m from the forest edge. Transects were established in homogenous habitats; ecotones were

avoided. Transects were set along the contour lines, to exclude the within-transect effect of

elevation. Trapping sites were established along each valley at more than 250 m difference in

elevation. In heterogeneous sites, with two or three habitat types (e.g. mixed forest on one slope

of the valley and spruce forest on the other), we set one transect in each forest, to get an image

on the whole community in that site. Sites comprised one to three transects and in all we

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surveyed 37 forest and shrubby habitats in 27 sites. In sites with more than one transects, these

were set at least 200 m apart, but no more than 50 m in elevation, and were spatially

independent, their position depending on the site morphology. Position of transects was the

same in successive samplings. Habitats were randomly surveyed between one and six times,

resulting in a total of 73 transects. Each year we covered most of the elevational range (except

in 2006 when we did not survey the subalpine shrubs) and habitat types. Trapping details in

each year are given in Table 1. Despite the unbalancedness of the design, our data set is

representative for the elevational-temporal space that we have explored.

We identified captured animals to species based on morphological traits, marked them

by fur clipping, and then released each at its trapping site. From the specimens which had

intermediate traits between A. flavicollis and Apodemus sylvaticus (Linnaeus, 1758) we sampled

ear tissue for molecular identification (de Mendonça and Benedek 2013). Recaptures were not

considered in the analyses.

Data analysis

In the multivariate approach, we used in separate analyses, as response variables, species

abundance and species composition in each transect. We accounted for the unequal trapping

effort among transects by using as measure of species abundance a capture index, i.e. the

number of trapped animals (excluding recaptures) per 100 functional trap-nights. Species

composition is given by the relative abundances of species, i.e. their proportions within the

assemblage. We excluded from the multivariate analyses rare species, i.e. trapped in less than

six transects.

Temporal variables were included, together with elevation, as explanatory variables in

the univariate and multivariate models. Because we did not expect a trend in our response data,

both season and year were considered as categorical variables. Since odd and even years were

similar in respect of species responses, we grouped together the even (2002, 2004, and 2006)

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and odd (2003 and 2005) years to test a two-year pattern in community changes, indicating a

possible cyclicity.

The variation of small mammal communities in relation to elevation and time (season

and year) was analyzed using Canoco 5 software (ter Braak and Šmilauer 2012). An indirect

gradient analysis, the detrended correspondence analysis (DCA), was first performed to

establish the length of the gradients and to summarize the variation in the small mammal

community. Because the length of the first gradient was less than four we were able to use the

linear redundancy analysis (RDA). This method enabled us to consider both species

composition, by standardizing species data by site total, and species abundance (not

standardizing response data), and to include also the empty samples.

We tested the significance of temporal (seasonal and annual) variations in the species

abundance and composition, and the effect of elevation, using a partial RDA with sampling site

(when testing time) and time (when testing elevation) as covariates. In partial ordinations we

focus on the influence of the variables of prime interest after having accounted for the effect of

the covariates (ter Braak and Šmilauer 2012). Significance of ordination axes was tested by the

Monte-Carlo permutation test with 999 unrestricted permutations per each test. We also tested

the temporal changes in the elevational patterns. We focused only on the interactions between

year and elevation, thus we first partialled out their main effects (Šmilauer and Lepš 2014),

introducing sampling site (which includes both elevation and habitat characteristics) and time

(year and season) in the partial-RDA as covariates. In these analyses we considered elevation as

ordinal variable with three levels: 1 – ≤ 1200 m (24 transects in 15 habitats), 2 – 1200 m to 1600

m (34 transects in 13 habitats), and 3 – ≥ 1600 m (15 transects in 9 habitats).

We used the variation partitioning procedure to assess and compare the explanatory

importance of the elevation and time (year and season). Variation partitioning disentangles the

unique and shared contributions that two or more groups of explanatory variables representing

some distinct, interpretable phenomena, have on the variation in the response data (Šmilauer

and Lepš 2014).

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In the univariate models we included as response variables total abundance, i.e. the sum

of capture indices for all the species in a trap line, and species richness, expressed by the

number of trapped species. We used mixed effects models in nlme package (Pinheiro and Bates

2018) in R (R Core Development Team 2018). We included site as random effect when we

modeled temporal variations and year and season when modeling the elevational patterns. For

the comparison of mixed models (with and without random effects) we used the Likelihood

Ratio test (LR test). The explained variation for the best model was expressed by Nagelkerke’s

R squared (Nagelkerke 1991), computed in the MuMIn package (Bartoń 2018). To obtain a

normal distribution of residuals in the univariate models, we transformed the response data.

Because square-root-transformation deals best with zero values, we chose it over the log-

transformation. For consistency, we square-root-transformed response data also in the

multivariate analyses.

Results

Trapping results

Over 5 years we captured 488 small mammals of 12 species - 5 shrews (93 individuals) and 7

rodents (395 individuals): common shrew – Sorex araneus Linnaeus, 1758, pygmy shrew –

Sorex minutus Linnaeus, 1766, alpine shrew – Sorex alpinus Schintz, 1837, water shrew –

Neomys fodiens (Pennant, 1771), Miller’s water shrew – Neomys anomalus Cabrera, 1907, hazel

dormouse – Muscardinus avellanarius (Linnaeus, 1758), edible dormouse – Glis glis (Linnaeus,

1766), bank vole – Myodes glareolus, snow vole – Chionomys nivalis (Martins, 1842), field

vole – Microtus agrestis (Linnaeus, 1761), pine vole – Microtus subterraneus (de Selys-

Longchamps, 1836), and yellow-necked mouse – Apodemus flavicollis. Based on molecular

identification we concluded that only A. flavicollis was present in our study area; none of the

samples gave positive results for the A. sylvaticus primers.

Six species had fewer than six occurrences, either because the trapping method was not

suitable (G. glis), or because they are characteristic of open habitats such as meadows (M.

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agrestis, M. subterraneus) or rocky fields (C. nivalis), or restricted to the proximity of waters

(N. fodiens, N. anomalus), thus they were not included in the multivariate analyses.

The dominant species were two forest rodents, A. flavicollis (40.2% of all captured

individuals, SE = 2.2%) and M. glareolus (36.5%, SE = 2.2%), and one shrew, S. araneus

(16.4%, SE = 1.7%). Species richness varied between zero and five captured species, but in

most habitats we found only one or two species, either A. flavicollis and M. glareolus, or M.

glareolus and S. araneus (Fig. 1). Nine transects were empty, most in odd years. In odd years

we also had very low abundances of A. flavicollis, which was trapped only at low elevations,

unlike in even years, when it was captured up to the subalpine shrubs (Table 1). In Table 2 we

present the abundance of the small mammal species in three habitats along Buta Valley,

surveyed five or six times.

Species abundance and composition

The elevational pattern of species abundance explained 9.4% of the partial variation

(pseudo-F = 6.9, p = 0.001). Responses of both dominant rodent species were significant and

negative, i.e. their abundances decreased with elevation. However, the relative abundance of M.

glareolus was independent of elevation and S. araneus was better represented in communities at

high elevations; only for A. flavicollis relative abundance also decreased with elevation (pseudo-

F = 3.1, p = 0.027, explained partial variation 5.4%).

Year-to-year changes explained most of the variation, both in species abundance, 45.4%

(pseudo-F = 6.4, p = 0.001), and in species composition, 32.3% (pseudo-F = 2.9, p = 0.006).

Responses of species abundance and composition to year were similar except for M. glareolus,

which reached the highest abundance in 2002 (Fig. 2 A) and relative abundance in 2005 (Fig. 2

B). Variations in the species parameters had a strong two-year temporal pattern. The separation

between odd and even years explained 26.4% in the species abundance (pseudo-F = 12.2, p =

0.001). All species increased in abundance in even years, but the response was significant only

for A. flavicollis and M. glareolus. The explained variation in species composition was 21.7%

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(pseudo-F = 7.5, p = 0.002). In even years only A. flavicollis had a significant increase in

relative abundance, whereas in odd years M. glareolus, S. alpinus and S. araneus comprised a

higher proportion in the community.

In the variation partitioning, time (year and season) explained 39.4% of the variation in

species abundance (pseudo-F = 8.1, p = 0.001) and 31.8% in species composition (pseudo-F =

5.6, p = 0.001), whereas the effect of elevation was not significant. Similar results were

obtained for species composition.

The interaction between elevation and odd and even years explained 8% of the partial

variation in the species abundances (pseudo-F = 2.6, p = 0.047). In odd years M. glareolus

increased in abundance along the elevational gradient, whereas A. flavicollis and the three

shrews had opposite patterns (Fig. 3).

Total abundance

Highest abundances were recorded in 2002 (mean = 37.4 individuals/100 trap-nights, SD =

23.2) and the lowest in 2003 (mean = 6.2 individuals/100 trap-nights, SD = 5.7) and 2005 (mean

= 7.2 individuals/100 trap-nights, SD = 7.1). Year-to-year fluctuations of total abundance and

the additional effect of season (LR = 8.22, p = 0.004, R2 = 0.54) were significant. The total

abundance increased from summer (mean = 12.2 individuals/100 trap-nights, SD = 16.2) to

autumn (mean = 18.9 individuals/100 trap-nights, SD = 22.5).

Total abundance decreased with elevation and the interaction between elevation and

year had an additional significant effect (LR = 26.19, p = 0.001, R2 = 0.44).

Species richness

Similar to the total abundance, species richness was highest (mean = 2.27, SD = 0.9) in 2002

and lowest in 2003 and 2005 (mean = 1.72 , SD = 1.13 for 2003, mean = 1.35, SD = 1.03 for

2005). There were significant differences between even and odd years (LR = 11.58, p < 0.001,

R2 = 0.22).

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Discussion

We surveyed small mammal communities in a montane area along the elevational and temporal

gradients. To the best of our knowledge, our study is the first to focus simultaneously on the

temporal and elevational dynamics of small mammal communities in European mountains,

although several studies have looked at spatio-temporal patterns in small mammals, searching

for evidence of synchrony or asynchrony among the populations across areas of different sizes

(Stenseth et al. 2002a; Bierman et al. 2006).

We seldom captured most species, reflecting their low overall abundances. Ninety-three

percent of captures were represented by only three species: A. flavicollis, M. glareolus, and S.

araneus, and 76.6% were of the two rodents. This is the common structural pattern of small

mammal communities in temperate zones, that is dominated by two species, usually rodents.

Abundances of A. flavicollis and M. glareolus decreased at high elevations. The same pattern

was reported also from low-elevation (between 230 and 1205 m) clear-cuts in Czech Republic

(Krojerová-Prokešová et al. 2016). However, elevation and habitat are at some extent

confounding variables. Increase in elevation is correlated with a turnover in vegetation, with

conifers taking over the place of broadleaf trees, lower diversity and cover of herbaceous layer,

and less deep soil, although at one elevation there can be a diversity of forested habitats, such as

dry or moist, closed-canopy or thinned, etc. Therefore we can not say whether the elevation

itself or the habitat variables have a greater effect on small mammals.

The abundance of S. araneus in the study area was high compared to other areas. In

mixed forests in northern Carpathians this species had constantly low abundances throughout

the nine year study period (Lešo and Kropil 2017). Low abundances of S. araneus were

recorded also in low mountain forests of Moravia, where abundances increased along the

elevational gradient (Dokulilová and Suchomel 2017), unlike in our study area. However, both

studies looked at relatively short gradients. When put together, these data suggest a hump-

shaped curve of S. araneus density distributions, with a mid-elevation peak.

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Year to year fluctuations explained most of the variation in abundance and species

composition of small mammals, whereas summer to autumn changes were less important,

suggesting that recruitment took place in the study area mainly during spring and early summer,

and winter mortality was high. Most small mammal populations in temperate forests exhibit

marked among-year fluctuations (Coppeto et al. 2006; Sollmann et al. 2015). The multiannual

dynamics in rodents is attributed mainly to differences in seed production (Stenseth et al.

2002b). Various tree seeds affect population densities differently (Ogawa et al. 2017), but the

synchrony in mast fruiting (Ascoli et al. 2017), especially in beech and Norway spruce

(Nussbaumer et al. 2016), which dominate montane forests in central Europe, suggests some

common characteristics of the dynamics of small mammal communities across larger areas. In

our study area we found a two-year temporal pattern of the variations in the community and

population parameters. This pattern was especially strong in A. flavicollis, for which not only

abundance and proportion in the assemblage was significantly higher in even years, but also the

maximum elevation of its trapping sites. We observed the same two-year pattern in another

mountain area in the Southern Carpathians, in a mixed forest that we monitored seasonally

between 2000 and 2010 (Benedek and Sîrbu, unpubl. data). We suggest a possible regional-

scale synchrony of patterns in small mammal dynamics, or at least in A. flavicollis populations

in the Southern Carpathians, driven by seed production.

The effect of time and elevation had a stronger effect on the species abundance than on

species composition. We can infer that in montane forests in our study area small mammals tend

to respond similarly to the changes in the environment but they need to show some

differentiation, hence the slight but significant response of species composition. Several studies

have demonstrated a negative correlation between abundances of A. flavicollis and M. glareolus,

suggesting a competitive relationship between the two species, with A. flavicollis exhibiting

higher competitive abilities (Marsh et al. 2001; Hille and Mortelliti 2010). We did not find such

a negative correlation between the abundances of A. flavicollis and M. glareolus in the study

area and the similarity in their responses suggests that at higher elevations environmental

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limiting factors were more important than antagonistic relationships. Habitat generalists, such as

the two dominant rodents in the study area, are assumed to have divergent dietary or temporal

niches (Sollmann et al. 2015), which enable them to exploit the same wide range of habitat

resources. A. flavicollis appeared to be more sensitive to the limiting factors at high elevations,

probably because of its more thermophilous nature (Marsh et al. 2001); this may explain its

strong variation in density and absence at high elevations in low-density years. In contrast, the

weaker competitor M. glareolus had a more constant presence during the study across the

elevational gradient, suggesting that species that are farther from its optimum (A. flavicollis in

our study area) exhibit greater amplitudes of multiannual variations in abundance.

The multiannual dynamics of species abundance changed along the elevational gradient.

Myodes glareolus and A. flavicollis had completely opposite responses, confirming their

divergent strategies for exploitation of resources. The significant interaction between time and

elevation may become even more relevant in the prospect of the increasing changes in the

climatic conditions. Climate changes causing increased temperatures in our study area might

alter the balance between the two dominant species, in favor of A. flavicollis, which responds

positively to raising summer temperatures (Marsh et al. 2001).

Our analyses are based on a data set that resulted from an exploratory survey. Such data

sets have usually two major drawbacks. First, it is unbalanced data. For this reason we could not

include both site and year as random effects in our univariate models. Second, it is the uneven

and relatively low trapping effort, which may bias abundance estimates. Reduced trapping effort

yields overestimates of abundance when densities are low, so we can presume that in our case

real amplitudes of abundance between years were probably higher.

Although there are many data on patterns of population and community dynamics in

different parts of the world, little is known about how these patterns change with increasing

elevation. A long term study in sites situated along several elevational transects would enable

the evaluation of the potential cyclicity in A. flavicollis at high elevations, and the trends in the

community dynamics, induced by climate change. By increasing the temporal grain of trapping

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(to spring and autumn), we would get more insight into the mechanisms behind the two-year

patterns of population and community temporal fluctuations, to establish the role played by

recruitment and survival. Additional information about masting, predators and their dynamics

along the elevational gradient would help to understand the role played by extrinsic factors in

regulation of population and community dynamics at different elevations.

Our results show the importance of temporal fluctuations in montane communities of

small mammals and their change along the elevational gradient. Ignoring the temporal

dimension may lead to the inability to comprehend the forces and processes that structure

communities. Failure to consider these fluctuations may also lead to unrealistic elevational

models of species richness and wrong assessment of species’ state and distribution.

Footnotes

Supplementary Figure S1 is available with the article through the journal Web site at

http://nrcresearchpress.com/doi/suppl/10.1139/cjz-2018-0201.

Acknowledgements

This paper was written within the project financed by Lucian Blaga University of Sibiu research

grants LBUS-IRG-2017-03. The authors thank Attila D. Sándor, Erika Stanciu, Călin Hodor,

Zoran Acimov, and the Administration of the Retezat National Park for the invitation to take

part in the faunistical inventory program and the students Anamaria Lazăr, Mihai Vasile, Marius

Drugă, Iounț Bordea, Alex Nicoară for their assistance in the field, Philippe Gil de Mendonça

for the molecular analyses of Apodemus samples, Charles J. Krebs and Robert K. Rose for their

comments on the paper and assistance with English usage.

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Table 1. Details of trapping in the five years of survey and the trapping results. The number of

transects in the parentheses are the empty ones. Annual mean and standard deviation of capture

index (expressed as number of individuals per 100 trap-nights) is given for the three dominant

species, for which the maximum elevation of the trapping sites are also shown. For the rest of

the species is given the mean capture index and the number of species (in parentheses).

Year Elevation

range (m)

No of

transects

S. araneus M. glareolus A. flavicollis Others

2002 1190-2020 11 0.37 ± 1.25

(1300 m)

13.08 ± 17.59

(1840 m)

23.1 ± 16.01

(2020 m)

0.97 ±

(5 sp.)

2003 920-2040 26 (4) 2.84 ± 3.57

(2040 m)

1.85 ± 2.44

(1650 m)

0.35 ± 1.49

(1050 m)

0.87 ±

(5 sp.)

2004 920-2040 10 (1) 6.38 ± 16.68

(2040 m)

4.33 ± 4.65

(1640 m)

7.52 ± 7.54

(2040 m)

1.0 ±

(3 sp.)

2005 820-2040 20 (4) 1.53 ± 2.57

(1640 m)

4.17 ± 5.6

(1640 m)

0.44 ± 1.15

(1190 m)

0.77 ±

(5 sp.)

2006 820-1640 7 5.77 ± 5.41

(1640 m)

9.61 ± 13.95

(1550 m)

7.41 ± 13.43

(1640 m)

1.39 ±

(3 sp.)

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Table 2. Dynamics of the abundance of small mammal species (capture index) in three of the

forest habitats that were most frequently surveyed, situated along Buta Valley.

Species

Year Season M. glareolus A. flavicollis S. araneus Other

Beech forest 920 m

2003 autumn 3.4 0 10.2 S. minutus - 3.4

2004 summer 1.4 11.0 0 0

summer 0 2.6 0 N. anomalus - 2.62005

autumn 0 4.3 0 0

2006 autumn 0 4.3 4.3 0

Mixed forest 1300 m

2002 summer 58.3 14.6 4.2 M. subterraneus - 2.1

2003 autumn 5.0 0 11.7 M. avellanarius - 1.7

2004 summer 7.2 7.2 0 0

summer 4.2 0 0 02005

autumn 8.7 0 2.9 0

2006 autumn 17.9 0 11.9 M. avellanarius - 3.0

Spruce forest 1550 m

2002 summer 10.0 36.7 0 0

2003 autumn 3.3 0 3.3 S. alpinus - 6.6

2004 summer 3.2 9.7 0 S. minutus - 3.2

summer 0 0 3.0 C. nivalis - 3.02005

autumn 0 0 4.5 M. agrestis - 9.1

2006 autumn 0 0 0 M. agrestis - 2.6

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Fig. 1. Species (triangles) – transects (circles) biplot diagram from DCA (first two axes are

plotted). Color of circles is given by elevation: white – transects below 1200 m, grey – between

1200 m and 1600 m, black – above 1600 m. Only the six most frequent species were included in

the analysis: Afla – Apodemus flavicollis (yellow-necked mouse), Mave – Muscardinus

avellanarius (hazel dormouse), Mgla – Myodes glareolus (bank vole), Salp – Sorex alpinus

(alpine shrew), Sara – S. araneus (common shrew), Smin – S. minutus (pygmy shrew).

Fig. 2. Species-year biplot diagram from RDA in terms of: (A) abundance (with non-

standardized response data) (B) relative abundance (with response data standardized by sample

total).

Fig. 3. Response of the small mammal community in terms of species abundance to the

interaction of elevation (ELEV) and odd and even years.

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Fig. 1. Species (triangles) – transects (circles) biplot diagram from DCA (first two axes are plotted). Color of circles is given by elevation: white – transects below 1200 m, grey – between 1200 m and 1600 m, black – above 1600 m. Only the six most frequent species were included in the analysis: Afla – Apodemus flavicollis (yellow-necked mouse), Mave – Muscardinus avellanarius (hazel dormouse), Mgla – Myodes glareolus (bank vole), Salp – Sorex alpinus (alpine shrew), Sara – S. araneus (common shrew), Smin – S. minutus (pygmy

shrew).

150x131mm (300 x 300 DPI)

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Fig. 2. Species-year biplot diagram from RDA in terms of: (A) abundance (with non-standardized response data) (B) relative abundance (with response data standardized by sample total).

180x77mm (300 x 300 DPI)

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Fig. 3. Response of the small mammal community in terms of species abundance to the interaction of elevation (ELEV) and odd and even years.

150x168mm (300 x 300 DPI)

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