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Hystrix It. J. Mamm (n.s.) 16 (2) (2005): 99-112

APPLICATION OF MODELLING TECNIQUES TO MANAGE A POPULATION OF GREY SQUIRRELS

(SCIURUS CAROLINENSIS) IN LOMBARDY, NORTHERNITALY, AND ANALYSIS OF PARAMETERS ESTIMATES

USED IN SIMULATIONS

1CLARA TATTONI, 1DAMIANO G. PREATONI, 1ADRIANO MARTINOLI,2SANDRO BERTOLINO, 1LUCAS A. WAUTERS

1 Dipartimento Ambiente-Salute-Sicurezza, Università degli Studi dell'Insubria,

via J.H. Dunant 3, 21100 Varese (VA), Italy; E-mail: clara.tattoni@uninsubria.it2 DI.VA.P.R.A., Entomologia e Zoologia, Università di Torino

10095 Grugliasco (TO), Italy; E-mail: sandro.bertolino@unito.it

ABSTRACT - Grey squirrel (Sciurus carolinensis), an invasive alien species, is currentlyreplacing the native Eurasian red squirrel (Sciurus vulgaris) in British Isles and north-westItaly. Grey squirrel has recently been reported in the Ticino Park (Lombardy region, NWItaly) and the species is likely to spread in the woodlands connecting Italy to other Europeancountries. We used GRASS Geographical Information System (GIS) and Spatially ExplicitPopulation Dynamics Models (SEPM) as a conservation tool to predict the spread of greysquirrels and to test different management options in the Ticino Regional Park and sur-rounding areas in a 40 years time frame. The integrated approach of SEPM and GIS allowedus to suggest public administration a cost effective action plan to stop the invasion process.We also analyse the parameters used in the model highlighting some missing data in litera-ture: we can address future field study with the aim to improve model performance.

Key words - Geographic Information Systems, grey squirrel, red squirrel, simulation,Spatially Explicit Population Dynamics Models

RIASSUNTO - Modelli per la gestione di una popolazione di Scoiattolo grigio (Sciuruscarolinensis) in Lombardia e stima dei parametri usati nelle simulazioni. La sostituzioneda parte dello Scoiattolo grigio (Sciurus carolinensis), specie alloctona e invasiva, delloScoiattolo rosso (Sciurus vulgaris), specie autoctona Europea, é attualmente in corso nelleIsole Britanniche e nell’Italia nord occidentale. Lo Scoiattolo grigio é stato recentementesegnalato nel Parco Lombardo della Valle del Ticino (Italia nord occidentale) ed é probabileche di diffonda nelle foreste che connettono l’Italia agli altri paesi europei. In questo lavoroil Sistema Informativo Geografico GRASS e i modelli denominati Spatially ExplicitPopulation Dynamics Models sono stati usati come strumento per prevedere la diffusionedello Scoiattolo grigio e per verificare differenti opzioni gestionali all’interno del Parco delTicino e nell’area circostante, per un periodo di tempo di 40 anni. Questo approccio inte-grato ha permesso di formulare un piano di azione efficace da proporre alle autorità compe-tenti per fermare il processo di colonizzazione. Inoltre sono stati valutati criticamente i

INTRODUCTION

The introduction of species from a dif-ferent ecosystem in another environ-ment is claimed to be the second mostimportant reason for loss of biodiversi-ty, after the destruction and fragmenta-tion of natural habitats, leading toextinction or decline of native species(Vitousek et al., 1996; Williamson,1996; IUCN, 2000). Alien speciesinterfere with the native fauna by dif-ferent ecological processes: predation,interspecific competition or acting asvector or reservoir of diseases(Sainsbury et al., 2000; Gurnell et al.,2004). Many introduced species canalso cause direct economic damage tohuman activities (impact on farming,forestry, agriculture, animal husbandry;disease risk), and socio-economicalproblems sum with the ecological one(Shine et al., 2000). A well document-ed case of competition by an invasivealien species is the wide-scale replace-ment of the native Eurasian red squirrel(Sciurus vulgaris) by the introducedgrey squirrel (Sciurus carolinensis) inthe British Isles and in parts of northernItaly. The rapid increase of grey squir-rel's distribution, coincided with a dra-matic decline of the range of the nativered squirrel (Wauters et al., 1997a), atthe point that greys have now almostreplaced reds in Great Britain andIreland (Gurnell and Pepper, 1993) andin a small area in Piedmont region, NW

Italy. (Bertolino and Genovesi, 2003).Recently, other grey squirrel popula-tions have been discovered in mixeddeciduous woodland belts along theTicino river (Fornasari et al., 2002).The competition of red and grey squir-rels in northern Italy has serious impli-cations for red squirrel conservation inEurope (Genovesi and Bertolino,2001a, b), because of the vicinity ofFrance and Switzerland (Fig. 1).Political concern about the lack ofaction in many countries has beenexpressed by the Permanent Commis-sion of the Bern Convention, which hasproduced several recommendations (n.57, 77 and 78 of 1997) urging countriesto eradicate alien invasive specieswhere possible. In order to assess therisk of extinction of red squirrel popu-lations, and plan effective managementstrategies for controlling the invasivespecies, it is necessary to know the rateat which replacement will occur, whichmainly depends on landscape structure(connectivity between good habitats)and abundant food supplies (Wauters etal., 1997b). We used an integratedapproach of GRASS GIS with SEPM(Spatially Explicit PopulationDynamics Models) that has been testedon grey squirrels in Britain andPiedmont region, Italy (Rushton et al.,1997; Lurz et al., 2001). The aims ofthis work are: i) evaluate grey squirrelexpansion in the Ticino Regional Parkand surrounding areas, ii) suggest an

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parametri utilizzati nel modello, evidenziando alcuni dati mancanti in letteratura fornendosuggerimenti per studi futuri finalizzati ad accrescere l’accuratezza del modello.

Parole chiave - Geographic Information Systems, Scoiattolo grigio, Scoiattolo rosso, simu-lazione, Spatially Explicit Population Dynamics Models

effective control strategy, iii) evaluatemodel parameters and address futurestudies.

METHODS

1. Study species

The mechanisms of interspecific competi-tion between grey and red squirrels haverecently been understood, at least in part: inbroadleaf woodlands where the two speciesare temporarily syntopic, they show a highniche overlap, both from a trophic and froma spatial point of view. In fact both speciesselect the same tree seed species as foodresource, have similar space use and activ-ity patterns, and eventually grey squirrelsseem to pilfer many of the seeds scatter-hoarded by the congener (Wauters andGurnell, 1999; Wauters et al., 2001a,2002a, b). In deciduous woods grey squir-rels heavily feed on acorns, while red squir-rels feed much less on this often abundantseed supply, resulting in an advantage ofthe introduced species in terms of energyrequirements satisfaction (Kenward andHolm, 1993; Gurnell, 1996a; Kenward etal., 1998; Wauters et al., 2001a, b). Inconifer forests, some degree of niche sepa-ration seems to exist, but red squirrels tendto avoid the habitat patches with the high-est food availability, occupied by greys,being often found at low densities in poorquality patches of exotic spruce species(Gurnell, 1996b; Wauters et al., 2000;Bryce et al., 2002). Overall, interspecificcompetition for primary food resourcesresults for the red squirrel in reduced bodygrowth, juvenile recruitment and reproduc-tive success (Wauters et al., 2001a; Gurnellet al., 2004), which will eventually causedensity to decline and push red squirrels tolocal extinction (Gurnell et al., 2004).Moreover, at least in the UK, grey squirrelsseem to act as vector for a poxvirus whichcauses a lethal disease in red squirrels

(Sainsbury et al., 2000; Tompkins et al.,2002). There are no known competitiveeffects of red squirrels on greys (Rushton etal., 1997; Gurnell et al., 2004).

2. Study area and data collection

The Ticino Regional Park (Lombardyregion), covers about 900 km2 along theeast bank of the Ticino river, from LakeMaggiore to its confluence with the Poriver at Pavia (Fig. 1). Our study areaenclosed the park area plus a 40 km bufferzone, extended in all directions from thepark boundaries.The distribution of grey (and red) squirrelsin the park was investigated using 21 tran-sects of 15 hair-tubes each, placed in vari-ous parts of the park (Gurnell et al., 2001;Fornasari et al., 2002).To predict grey squirrel range expansion,we obtained land cover data for Piedmontand Lombardy regions in digitised formatat 250 m spatial resolution, and furtherlyrefined the base dataset (CORINE Landcover; Commission of the EuropeanCommunities, 1993) adding data derivedfrom two other sources: the TicinoRegional Park forestry map (10 m spatialresolution) for areas inside the park that arenot in the Varese province (Lombardy), andthe vegetation map of the Varese province(10 m spatial resolution, Tosi and Zilio,2002). We produced a final habitat map at250 m spatial resolution where each cellwas characterised by a single habitat type(predominant land cover type, Tab. 1). As aresult of the spatial resolution of the landcover data, some small woodlands (< 3.2ha) suitable for grey squirrels may not havebeen recognised as squirrel habitat, makingmodel predictions of grey squirrel spreadmore conservative by reducing the totalavailable habitat.

3. Modelling approach

The model used for simulating the distribu-

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tion of grey squirrels in the landscape hastwo main components. The first is a geo-graphical information system (GIS) whichstores habitat and animal population infor-mation. GRASS 4.2 (U.S. Army, 1993) andGRASS 5 (GRASS Development Team,2002) were the GIS used to store andretrieve habitat information and the modeloutputs. The GIS undertakes data manipu-lation and abstraction and provides inputfor the second component, which consistsof a program simulating the populationdynamics of grey squirrels and their inter-actions and dispersal within the GIS-heldlandscape. The second component is a pop-ulation dynamics model that predicts thedistribution of squirrels by simulating thelife history processes of births, deaths,home range formation and dispersal inyearly time steps. A detailed description of

the original model, used for investigatingthe spread of the grey squirrel and declineof the red squirrel in East Anglia, England,is given by Rushton et al., 1997. The modelwas applied and fully tested in Piedmont(details are described in Lurz et al., 2001).The population dynamics program waswritten in the programming language C andintegrated with the GIS component in aUNIX-shell environment. GIS capabilitieshave been used to build the habitat mapfrom different sources, the initial distribu-tion of the species and the patterns for con-trol. Suitable habitats were defined accord-ing to the carrying capacity (CC), i.e. thenumber of individuals who can be support-ed by a given area (Odum, 1975). Eachhabitat type received a CC value based onpublished estimates.All the simulation runs started from the sit-

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Figure 1 - a) Postition of the study area relative to the Italian peninsula. b) “Parco Regionaledella Valle del Ticino Lombardo”, solid back line, Piedmont and Lombardy region bounda-ries, grey line. The scalebar is relative to the b) part of the image. In c) the black blocksrepresent the habitat patches in which grey squirrel has been detected inside the boundariesof “Parco Regionale della Valle del Ticino Lombardo”.

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Land cover type Dmax References Dmax ReferencesG.s. R.s.

Riparian forests 1.0 Bertolino et al., 2003 0.3 Bertolino et al., 2003

Oak and oak-hornbeam 5.0 Gurnell 1996a 0.8 Kenward et al., 1998 Kenward et al., 1998 Wauters et al., 2001b

Ostrieti 2.5 Authors’ estimate 0.4 Authors’ estimate

Black locust-oak woodland 1.0 Authors’ estimate 0.2 Wauters et al., 2001b

Black locust or other exotics 0.1 Authors’ estimate 0.1 Authors’ estimate

Mixed broadleaf 5.0 Gurnell, 1991; Koprowski, 1994 1.1 Wauters and Lens, 1995dominated by chestnut Wauters and Gurnell, 1999 Wauters et al., 2001b

Mixed deciduous 2.0 Koprowski, 1994 0.4 Wauters et al., 2001b(CORINE) Gurnell et al., 2001b Authors’ estimate

Beech 2.0 Gurnell, 1991 0.4 Cagnin et al., 2000Wauters and Lens, 1995

Maple-ash-lime 5.0 Authors’ estimate 1.1 Authors’ estimate

Conifers and mixed 1.5 Gurnell, 1991; 1996a 1.3 Wauters and Lens, 1995broadleaf Gurnell et al., 2001b

Scots pine 0.3 Smith and Gurnell, 1997 0.5 Authors’ estimateAuthors’ estimate

Norway spruce 0.2 Smith and Gurnell, 1997 0.35 Wauters et al., 2000

Poplar plantations 0.3 Bertolino et al., 2003 0.1 Wauters et al., 1997a, b

Pastures (CORINE) 0.2 Authors’ estimate 0.1 Authors’ estimate

Alder 0.1 Authors’ estimate 0.1 Authors’ estimate

Mixed agriculture 0.013 Bertolino et al., 2003 0.005 Bertolino et al., 2003 Lurz et al., 2001

Maize, wheat 0.013 Bertolino et al., 2003 0.005 Bertolino et al., 2003 Lurz et al., 2001

Permanent grassland 0.013 Authors’ estimate 0.005 Authors’ estimate

Vineyards, orchardsand hazelnuts 1.0 Authors’ estimate 0.2 Authors’ estimate

Urban areas 0.013 Authors’ estimate 0.013 Wauters and Gurnell, 1999Koprowski, 1994

Urban parks 1.0 Authors’ estimate 0.02 Authors’ estimate

Table 1 - Habitat description and squirrel maximum densities (Dmax, ind./ha) derived fromliterature, for the digitised land cover classes. Unsuitable habitats are: Cliffs, rock slides andriverbeds, Scrub, Herbaceous vegetation, Rice fields, Water bodies, Sterile land, Scrub,newly planted areas and uncultivated grassland, and Infrastructure. They all received a valueof zero in the model; G. s. = grey squirrel; R.s. = red squirrel.

uation known for year 2001 and forecastedsquirrel population dynamics for the fol-lowing 40 years. As the model is a stochas-tic one, we ran it 10 times over for each setof inputs for 40 year time span. So for eachscenario we ran the models 400 times over-all. Results presented are averages of thosemultiple runs. A detailed description of allthe runs can be find in Tattoni et al., 2005.

4. Parameter estimation

An individual based model requires a goodestimate of all the parameters used into themodel itself in order to produce a reliableoutput.The main drawback of these models is thata sound knowledge of both life-historyparameters and habitat preferences isrequired and, thus, SEPM can only be usedfor species for which detailed data of popu-lation parameters in different habitat types

are available (Rushton et al., 1997 and2000). Many studies on the populationdynamics of red and grey squirrels haveproduced reliable estimates of these life-history traits under variable environmental(habitat) conditions.Two main kind of parameters are needed torun simulations: individual linked parame-

ters (such as fertility, litter size, etc.) com-monly referred as life history parameters(Tab. 2) and ecological parameters, such ascarrying capacity in different habitat types(Tab. 3).For some habitat types no published datawere available so we provided an estimatebased on comparison with similar habitatsand field experience. Over a total of 29habitat types present on the study area, wehave been able to find literature estimatesof CC for red squirrel in 21 habitat classesand in 20 for grey squirrel. Red squirrel lit-erature reports CC estimates in Scots pine(Pinus sylvestris) forests, while the sameestimate is not available for grey squirrel(Tab. 1). This tree species is absent in northAmerica, so the behaviour of the greysquirrel in this kind of forest is not known.The other habitats with unavailable CC inliterature for both species are mainlyanthropic habitats (orchards, urban areas,

urban parks, pastures, permanent grass-land). We proposed a very low CC insteadof a null value because these habitats canbe used by squirrels of both species tomove through. A null CC implies that in thesimulation any squirrel dies when passingover these habitats: we considered thisoption unrealistic.

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Poor year Good year Mast year

Paramete R.s. G.s. R.s. G.s. R.s. G.s.

Fecundity 2 1.5 2.8 2.5 3.5 3.5Adult survival 0.55 0.55 0.6 0.6 0.75 0.65Juvenile survival 0.25 0.25 0.3 0.3 0.4 0.4Reproducing females (first litter) (%) 67 87 67 87 67 87Reproudcing females (second litter) (%) 26 42 26 42 26 42

Table 2 - Red (R. s.) and grey (G. s.) squirrel life history parameters in relation to annualchanges in tree seed crops. Fecundity is the average litter size (Bertolino and Genovesi,2003), survival is the percent of individuals surviving to the next year according to two ageclasses and food availability (Gurnell, 1996a). Reproducing females is the percent of adultfemales who reproduce each year once (first litter) or twice (second litter) (Rushton et al.,1997).

Alien species invasiveness is often relatedto their sudden introduction into habitatswhere they have not co-evolved with thebiological community (White, 1997): inter-action with local species in not predictable,the scene becomes then more and morecomplex when more than one alien speciesis present. Our study area is a good exam-ple, since here we can find European andAmerican squirrels in a habitat composedby North American tree species. Wauters etal. (2001b) recently estimated the carryingcapacity for red squirrel in black locust(Robinia pseudoacacia) mixed with oaksforests, while for a black locust mixed withother exotic species there is not an estimateyet. The only natural habitats for which weprovided a personal estimate are alder,hornbeam and maple-ash-lime woodlands.Even with some author’s estimates, werelied on our model outputs. In fact the totalarea covered by the habitats with no CC inliterature is only 18% of the total study area(Tab. 3).

RESULTS

1. Grey squirrel spread

The landscape in and around “ParcoRegionale della valle del TicinoLombardo” is very suitable for squir-rels. If the starting population is not

managed, our results indicate that greysquirrels are likely to spread over awide area over the next 40 years. Themodel predicts approximately 370000individuals (see also Fig. 2 and Fig. 3).Our predictions suggest that it will takemore than twenty years for grey squir-rels to start invading the southern partof the Park and to spread outside thePark boundaries reaching Switzerland(Fig. 2c, d). Squirrels are predicted toshow different patterns of spread:inside the Park dispersion tends tooccur along the wooded riverbank ofTicino river, while outside the spreadhas no preferential direction. Themodel simulations indicate that it willtake up to 15 years to reach carryingcapacity within Ticino Park bound-aries. Dispersal beyond park bound-aries may therefore be slow and therapid implementation of control meas-ures is likely to be successful in slow-ing or even preventing further spread.

2. Grey squirrel control scenarios

We tested the effect of two differentremoval rate, namely 50% and 80% ofthe individuals present at a given timeover three different control scenarios

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Habitat class with CC Habitat types Area km2 % of study estimated by authors area

Natural Alder, maple-ash-lime and scots pine 156.50 1.77Anthropic Orchards, urban parks, pastures 1308.56 14.77Exotic Black locust-oak and black locust and

other exotic species 153.25 1.73Total 1618.31 18.26Total (study area) 8861.63

Table 3 - Surface (km2) of habitat types with a carrying capacity (CC) estimated by authorsfor both red and grey squirrels.

(Tattoni et al., 2005). Squirrel removalstarts in 2005 for each scenario, so forthe first three years of the simulation nosquirrels are removed. From the simu-lation outputs we were able to find thebest compromise between effectivemanagement and number of patches tocontrol. This is confirmed in this sce-nario where an effective control can beachieved on a relatively small area(2600 ha with respect to 4600 ha) if

proper target areas are defined. .Wefind that 80% removal rate results intotal eradication in 30 years. Averageyearly removal is around 50 individualsper year for the first 10 years, droppingto less than ten squirrels per year after-wards (Tattoni et al., 2005). Theseresults show that it is possible to facethe spread of grey squirrels if policymakers and wildlife managers takeimmediate actions to control the alien

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Figure 2 - The spatial spread of grey squirrel population at ten year intervals a) 2011; b)2021; c) 2031; d) 2041.

species and plan a carefully designedcontrol scheme, with selective choiceof target areas, controlling only a smallportion of the landscape. However, forcontrol to be efficient, even on a smallarea, new hair-tube surveys, coveringall woodlands inside the park (andthose just outside the northern border)must be carried out immediately toreveal the present distribution. We alsoproduce a first map for hair tube survey(Fig. 4), and future trapping campaignshould be adjusted on the field accord-ing to the surveys results.

3. Competition scenario

We also ran the model with both squir-

rel species to evaluate competition. Redsquirrels start to go extinct in the parkwoodlands from year 2020, as greyscontinue to expand and their numbersincrease (Fig. 3). During the first 10-15years red squirrel population increasesfrom an average density to carryingcapacity. This is an artefact related toinput conditions, defined at an averagedensity for the whole landscape. Redsquirrels reach equilibrium from the10th to 20th year of simulation. The pop-ulation is fluctuating around 280000individuals and the species is spread inall woodland blocks. After the 20th yearof simulation greys begin to be animpacting factor and the predicted21000 grey squirrels are likely to drive

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Figure 3 - Grey and red squirrel population dynamics as predicted by the competition sce-nario. Each line represents average values calculated over 10 simulation runs. Bars indicatestandard deviation.

the red squirrel to extinction within thePark boundaries. Populations of redsquirrels seem to persist longer in thenorthern part of the study area wherethe prealpine mountains are coveredwith conifer forests, and the habitat isslightly more suitable for reds than forgreys. However, reds go extinct in thecentral and most of the southern part ofthe study area within 40 years.

DISCUSSION

Without control, grey squirrels couldinvade Switzerland woodlands withinthe next two decades. Simulating dif-ferent grey squirrel control or removalscenarios suggests that: (i) efficientcontrol is possible and mainly deter-mined by the spatial distribution andwoodland patch size of the 'target' con-

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Figure 4 - Proposed hair tube survey scheme; each transect (bold line) is about 2 km length.Surveys are planned to take place in woodland patches.

trol areas; and (ii) immediate actionsmust be taken, since delay in greysquirrel control will result in the popu-lation increasing and spreading, whichmakes the problems of successful con-tainment more difficult. The coupleduse of SEPM and GIS proved to be auseful tool in conservation as it allowedus to test the effectiveness of differentstrategies, including a 'no action'option, providing wildlife managerswith maps showing the consequencesof each strategy. Control maps analysisallowed us to identify the best cost-effective action control plan to preventthe spread of the invasive grey squir-rels. Those maps, theoretically, couldalready be used on the field to placetraps. However, caution must be used,as model scenarios were based on sur-veys that may underestimate the realrange and current population size ofgrey squirrels. In addition, no informa-tion was available on the presence ofthe species outside the park boundaries,and so we assumed it was absent. Forall these reasons our predictions can beconservative and we suggest a combi-nation of grey squirrel monitoring andpublic participation survey to map greysquirrel presence, which may also helpincrease public awareness. Moreover,future surveys can be used to improvemodel performance and to test the reli-ability of our predictions. A successfulcontainment of further grey squirrelspread will in fact require local co-operation of Park authorities with theRegional Parks and Wildlife Servicesof the Regions of Lombardy andPiedmont. Furthermore, also the Swissauthorities of the Ticino District musttake an active role in counteracting

grey squirrel invasion within the next20-30 years (potentially sooner whendispersing individuals are considered).We also highlight the lack of studies onboth species in some habitat types:future field study may consider toinvestigate species behaviour in blacklocust, alder, hornbeam and maple-ash-lime woodlands.

ACKNOWLEDGEMENTS

The study was financed by the ParcoLombardo della Valle del Ticino toIstituto Oikos, NGO. Steven P. Rushtonand Peter W. W. Lurz of the IRESSchool of Biology, University ofNewcastle upon Tyne collaborated inthe SEPM development. CT stay inNewcastle was granted by a fellowshipfrom the Fondazione FratelliConfalonieri, Milano.

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