Introduction

Species that live in low densities need largeareas and are very mobile are particularly

threatened by habitat loss and fragmentation(eg Noss et al 1996 Herrmann 1998 Klar 2007)Theoretical models on island food chain ecologypredict that predators especially larger carni-vores are more prone to extinction (Cohen and

[177]

Acta Theriologica 55 (2) 177ndash192 2010

PL ISSN 0001-7051 doi 104098jat0001-70511142009

Habitat suitability corridors and dispersal barriers for large

carnivores in Poland

Maren HUCK Wsup3odzimierz JEcircDRZEJEWSKI Tomasz BOROWIK

Masup3gorzata MIpoundOSZ-CIELMA Krzysztof SCHMIDT Bogumisup3a JEcircDRZEJEWSKA

Sabina NOWAK and Robert W MYSpoundAJEK

Huck M Jecircdrzejewski W Borowik T Misup3osz-Cielma M Schmidt KJecircdrzejewska B Nowak S and Myssup3ajek R W 2010 Habitat suitabil-ity corridors and dispersal barriers for large carnivores in Poland ActaTheriologica 55 177ndash192

Carnivores are often particularly sensitive to landscape fragmentationEcological corridors may help to connect local populations ensuring gene flowand retaining viable meta-populations We aimed to establish habitat suit-ability models for two large carnivores in Poland the grey wolf Canis lupusLinnaeus 1758 and the Eurasian lynx Lynx lynx Linnaeus 1758 based onecological niche factor analysis (ENFA) Secondly we calculated least costpaths (LCPs) based on cost values obtained from ENFA Thirdly we deter-mined structures that might act as barriers thus diminishing the value of thecorridor unless appropriate conservation measures are taken We comparedsome of the results with actual dispersal data of four lynx in eastern PolandResults indicate that both species are highly marginalised Less habitat thatis currently available in Poland is suitable for lynx than for wolves Wedetermined a total of 76 LCPs Comparison of these theoretical corridors withactual dispersal routes suggests that the traits of calculated LCPs are mostlywithin the range of those of real routes We highlight a variety of features thatmight act as barriers such as major roads (including planned highways) ur-banized areas and large un-forested areas We give suggestions where concertedconservation efforts (eg wildlife passages) might be particularly well-directed

Mammal Research Institute Polish Academy of Sciences Waszkiewicza 1 17-230 Biasup3owieiquestaPoland e-mail maren_huckhotmailcom (MH WJ TB MM-C KS BJ) Association for NatureldquoWolfrdquo Twardorzeczka 229 34-229 Lipowa Poland (SN RWM)

Key words Canis lupus Lynx lynx least cost path analysis ecological nichefactor analysis green bridges roads

Newman 1991 Crooks 2002) Ecological corri-dors can help to connect local populations sothat individuals can disperse freely betweenpopulations (Beier and Noss 1998) This ensuresgene flow which will minimize negative effectsdue to isolation inbreeding and random demo-graphic processes (Taylor et al 1993 Gilbert et

al 1998 Frankham et al 2004) The effective-ness of corridors beyond the increase in area hasbeen shown experimentally on a relatively largescale (52 ha) by studying movements of butter-flies pollen and bird-dispersed seeds (Tewksburyet al 2002) Hence retaining or restoring con-nectivity is often of high conservation priority(Clevenger and Waltho 2000 Kusak et al 2009)The western limit of the contiguous East-Euro-pean ranges of two large European carnivoresthe Eurasian lynx Lynx lynx Linnaeus 1758 andthe wolf Canis lupus Linnaeus 1758 are in Po-land The Polish populations are therefore cru-cial as a source for dispersal to the fragmentedwestern European populations eg in Germanyand functional corridors are essential

Designing corridors for a species or group ofspecies consists of at least two steps when basedon computer models the determination of fric-tion or cost values associated with different hab-itat types and the actual determination ofroutes that minimize the costs the least costpaths (LCP Schadt et al 2002 Adriaensen et al2003 Nikolakaki 2004 Ray et al 2005 Epps et

al 2007) The use of habitat suitability valuesbased on species occurrence data rests on the as-sumption that proportional occurrence of a spe-cies and permeability of a habitat type for thespecies are correlated This supposition is diffi-cult to test However it is likely that modelsbased on data of resident animals will be conser-vative in the sense that habitat types preferen-tially occupied by residents will also be suitablefor dispersing animals but that dispersing ani-mals might use a broader range of habitats asin the case of the Iberian lynx Lynx pardinus

Temminck 1827 (Palomares et al 2000) Itseems reasonable to assume that the shift inhabitat use by dispersing individuals ratherstems from necessity than from changes in ac-tive selection This assumption is supported bythe fact that in the Iberian lynx dispersing in-

dividuals used some habitats according to theiravailability whereas the same habitats wereavoided by adult residents (Palomares et al2000) The use of data from resident individualsmight therefore be sufficient for the purposeof establishing possible dispersal corridors ormight even be more adequate if data from dis-persing individuals would rather reflect whatanimals are forced to use (because of the lack ofconnectivity) instead of what they prefer

After establishing least cost paths as proxiesfor corridors a third very important step shouldbe employed ie the determination of barriersor only marginally suitable areas along theroute For forest species such (partial) barriersmight consist of highways or large open areas(Trombulak and Frissell 2000 Kaczensky et al2003 Zimmermann et al 2005) An LCP is notyet a functioning corridor One important differ-ence between LCPs and final lsquocorridorsrsquo is thatgiven a start and ending point exactly one LCPwill be calculated regardless of the final costseven if it will actually not be suitable That LCPmight be better than all alternative routes butwill still only be as good as the weakest piece inthe chain Only when potential barriers areidentified it will be possible to employ conserva-tion efforts that are likely to be effective For ex-ample highways can be a major cause of deathfor wildlife (Seiler and Helldin 2006 Lovari et

al 2007) Where corridors cross highways andother large roads it would be advisable to buildgreen bridges or other crossing structures to re-duce the number of traffic accidents that are notonly lethal for animals but might also lead todeath or severe injuries to people and usuallycause considerable damage to properties (Seilerand Helldin 2006) A report by the English De-partment for Environment Food and Rural Af-fairs estimates annual costs caused by deer-trafficaccident related damage of 105 million poundswhich does not even include additional costssuch as lost work time (Wilson 2003) The colli-sion with deer causes annually between 7ndash32human fatalities in England alone with addi-tional 750ndash3200 injuries (Wilson 2003) The ef-fectiveness of wildlife passages has been shownfor both large and small species (Pfister et al2002 Kusak et al 2009) but it depends crucially

178 M Huck et al

Newman 1991 Crooks 2002) Ecological corri-dors can help to connect local populations sothat individuals can disperse freely betweenpopulations (Beier and Noss 1998) This ensuresgene flow which will minimize negative effectsdue to isolation inbreeding and random demo-graphic processes (Taylor et al 1993 Gilbert et

al 1998 Frankham et al 2004) The effective-ness of corridors beyond the increase in area hasbeen shown experimentally on a relatively largescale (52 ha) by studying movements of butter-flies pollen and bird-dispersed seeds (Tewksburyet al 2002) Hence retaining or restoring con-nectivity is often of high conservation priority(Clevenger and Waltho 2000 Kusak et al 2009)The western limit of the contiguous East-Euro-pean ranges of two large European carnivoresthe Eurasian lynx Lynx lynx Linnaeus 1758 andthe wolf Canis lupus Linnaeus 1758 are in Po-land The Polish populations are therefore cru-cial as a source for dispersal to the fragmentedwestern European populations eg in Germanyand functional corridors are essential

Designing corridors for a species or group ofspecies consists of at least two steps when basedon computer models the determination of fric-tion or cost values associated with different hab-itat types and the actual determination ofroutes that minimize the costs the least costpaths (LCP Schadt et al 2002 Adriaensen et al2003 Nikolakaki 2004 Ray et al 2005 Epps et

al 2007) The use of habitat suitability valuesbased on species occurrence data rests on the as-sumption that proportional occurrence of a spe-cies and permeability of a habitat type for thespecies are correlated This supposition is diffi-cult to test However it is likely that modelsbased on data of resident animals will be conser-vative in the sense that habitat types preferen-tially occupied by residents will also be suitablefor dispersing animals but that dispersing ani-mals might use a broader range of habitats asin the case of the Iberian lynx Lynx pardinus

Temminck 1827 (Palomares et al 2000) Itseems reasonable to assume that the shift inhabitat use by dispersing individuals ratherstems from necessity than from changes in ac-tive selection This assumption is supported bythe fact that in the Iberian lynx dispersing in-

dividuals used some habitats according to theiravailability whereas the same habitats wereavoided by adult residents (Palomares et al2000) The use of data from resident individualsmight therefore be sufficient for the purposeof establishing possible dispersal corridors ormight even be more adequate if data from dis-persing individuals would rather reflect whatanimals are forced to use (because of the lack ofconnectivity) instead of what they prefer

After establishing least cost paths as proxiesfor corridors a third very important step shouldbe employed ie the determination of barriersor only marginally suitable areas along theroute For forest species such (partial) barriersmight consist of highways or large open areas(Trombulak and Frissell 2000 Kaczensky et al2003 Zimmermann et al 2005) An LCP is notyet a functioning corridor One important differ-ence between LCPs and final lsquocorridorsrsquo is thatgiven a start and ending point exactly one LCPwill be calculated regardless of the final costseven if it will actually not be suitable That LCPmight be better than all alternative routes butwill still only be as good as the weakest piece inthe chain Only when potential barriers areidentified it will be possible to employ conserva-tion efforts that are likely to be effective For ex-ample highways can be a major cause of deathfor wildlife (Seiler and Helldin 2006 Lovari et

al 2007) Where corridors cross highways andother large roads it would be advisable to buildgreen bridges or other crossing structures to re-duce the number of traffic accidents that are notonly lethal for animals but might also lead todeath or severe injuries to people and usuallycause considerable damage to properties (Seilerand Helldin 2006) A report by the English De-partment for Environment Food and Rural Af-fairs estimates annual costs caused by deer-trafficaccident related damage of 105 million poundswhich does not even include additional costssuch as lost work time (Wilson 2003) The colli-sion with deer causes annually between 7ndash32human fatalities in England alone with addi-tional 750ndash3200 injuries (Wilson 2003) The ef-fectiveness of wildlife passages has been shownfor both large and small species (Pfister et al2002 Kusak et al 2009) but it depends crucially

178 M Huck et al

on the location (Clevenger and Waltho 2000Pfister et al 2002)

The aim of this study was threefold Firstlywe wanted to establish habitat suitability mod-els for two large carnivores the grey wolf andthe Eurasian lynx based on ecological niche fac-tor analysis (ENFA see Methods) and comparethe results in terms of available suitable habi-tat marginalisation and specialisation betweenthe species Secondly we aimed to determineleast cost paths based on the values obtainedfrom ENFA that can be considered core parts ofpotentially suitable corridors connecting localpopulations of these species Thirdly we wantedto identify structures that might act as barriersdiminishing the value of the corridors unless ap-propriate conservation measures are taken Wegive suggestions where concerted conservationefforts might be well-directed

Methods

Habitat suitability analysis

We calculated habitat suitability maps for lynx and wolfin entire Poland using the ENFA incorporated in the pro-gram BIOMAPPER 40 (Hirzel et al 2002a b) ENFA is aprincipal component analysis based method It comparesthe distribution of the localities where the focal species wasobserved to a reference set describing the whole studyarea The first of the extracted factors maximizes the mar-ginality of the species the global marginality taking alleco-geographical variables into account is a measure of thedifference between the optimum of the species and themean available habitat within the study area A high mar-ginality (values close to 1) occurs if the species lives in avery particular subset of habitat types relative to the refer-ence area The other factors describe the specialisation ofthe species which is given by the ratio of the ecologicalvariance in average habitat to that observed for the focalspecies The global tolerance of the species (the inverse ofthe global specialisation) indicates how specialised a spe-cies is with respect to those parameters that were used forthe analysis Values close to 1 stand for euryoecious (broadniche) and values close to zero for stenoecious (narrowniche) species

In contrast to a study that determined effects of habitattypes on permeability for wolves alone (M Huck and co-workers unpubl) we used more detailed habitat maps sincelynx are known to be more specific in their microhabitat se-lection than wolves (Podgoacuterski et al 2008) The species oc-currence maps consisted of wolf and lynx records collectedduring the National Wolf and Lynx Census between 2000and 2006 (Jecircdrzejewski et al 2004 2005 Niedziasup3kowska et

al 2006) The wolf data set represented 15 670 observationevents the lynx data set 2947 These observations consistprimarily of tracks direct sights howling (for wolves) preyremains and road kills so that location errors are negligi-ble All forests in Poland are divided into small forest dis-tricts and sub-compartments that are regularly checked byforestry personnel Those areas that might have beensubject to less intense monitoring by forestry staff weresearched in concentrated actions by the organizers of thecensus The data are therefore likely to represent speciesoccurences without systematic bias

We used a CORINE land cover map (copy EEA Copenha-gen 2000 httpdataserviceeeaeuropaeudataservice) andgrouped a variety of habitat types together resulting in thefollowing eight habitat types that we converted into sepa-rate raster maps with a grid cell size of 1 km2 (details in Ta-ble 1) DECIDUOUS CONIFEROUS and MIXED forest PASTURE

more natural meadows (NATMEAD) naturally open habitats(very low percentage of total area) and transitional forest(TRANSITIONAL) wetland and inland water bodies (WET)and towns and settlements (HUMAN) Preliminary analysesusing a grid cell size of 250 m2 as well as using coarsergrids (2 and 10 km2) resulted in very similar habitat suit-ability maps as well as in similar patterns of least costpaths (see below) For wolves the variables (except WET)were represented as the proportion of each habitat type inan area of 177 km2 around each grid point The value wasconstrained by the options of the program but was closest tothe 201 km2 average territory size of wolves in Biasup3owieiquestaForest eastern Poland (Jecircdrzejewski et al 2007) For lynxwe chose the proportion of habitat types in a 69 km2 areacorresponding to autumn-winter home range sizes of femalelynx (55 km2 Schmidt et al 1997) By choosing circles cor-responding to average home range sizes we ensured thatthe HSM would represent suitable areas for permanentpopulations (for a similar approach in roe deer see egCoulon et al 2004 Basille et al 2008) However using cir-cles of a smaller (wolves) or larger (lynx) area resulted invirtually the same HSM (data not shown) indicating thatthe maps presented here are robust Data on primary andsecondary roads represented as linear features were ob-tained from the IMAGISreg company Warsaw Because thepresences of primary and secondary roads were highly cor-related we did not distinguish between road types forENFA (lsquoROADrsquo) We did not include prey density becauseJecircdrzejewski et al (2008) estimated that the probability ofwolf occurrence was only lowered by 34 in areas of low un-gulate density in eastern Poland Ungulates are fairly com-mon all over Poland and the combined biomass of roe deerCapreolus capreolus red deer Cervus elaphus and wild boarSus scrofa never falls below 625 kgkm2 (calculated basedon rough census maps for ungulates T Borowik unpubl)using average biomasses for roe deer red deer and wildboar of 20 110 and 80 kg respectively (Jecircdrzejewski et al2008) The lowest ungulate densities tend to occur in theEast where wolf densities are highest (T Borowik unpubl)Furthermore ungulate density is correlated with forestcover a variable that was already included in the analysisFor both species WET ROAD and distance to towns and set-tlements (DISTHUM) were represented as the closest dis-tance to that habitat type We also tried out whether usinghuman population density would improve the model This

Corridors and dispersal barriers 179

variable was correlated with HUMAN had a less negativemarginality value and was therefore not included As aproxy for fragmentation we used the maximal size of contin-uous forest patches (regardless of the forest type) in (thesmallest possible) circle of 9 km2 around each grid cell(WOODAREA) The maximal size of patches was negativelycorrelated with the number of patches but it gave morecontinuous values than ldquonumber of fragments per circlerdquoand was therefore better suited for ENFA For this parame-ter we did not distinguish between forest type because bothspecies prefer any type of forest over all other habitat types(see this study) and using forest sub-types would have re-sulted in relatively small patch sizes regardless whetherthe patch was part of a larger continuous forest or was trulyfragmented We chose the smallest possible circle size inthis case because we were interested in the value for the lo-cation and not an average over a larger area All valueswere Box-Cox transformed to normalise the data AlthoughARABLE was highly negatively correlated with CONIFEROUS

we did not exclude the variable because the difference inthe maps was slight and we were interested in the interpre-tation of all habitat variables by the program The margin-ality (see Results) was above 10 regardless whether ARABLE

was included or not To compare marginality and tolerancevalues of the two species we also ran an ENFA for wolvesusing the habitat data in circles of 69 km2 and for lynx incircles of 177 km2 Resulting maps were quite similar sothat for further analyses we used the maps with the morespecies specific parameters

The number of factors included for the calculation of theHSM was the recommended number following the lsquobrokenstickrsquo method (ie factors with eigenvalues larger than ex-pected from randomly breaking a stick of the same totallength MacArthur 1957) or until at least 80 of the spe-cialisation was explained by the factors which resulted inall cases in using four factors The HSM was validated us-ing a 20-fold cross-validation (Boyce et al 2002 Hirzel et al2006) For representation of the HSM we grouped habitatsuitability values into three categories based on the results

of the cross-validation which shows an area-adjusted cross-validation curve with the habitat suitability value on thex-axis and the predictedexpected ratio (PE-ratio) on they-axis We considered all areas with habitat suitability val-ues corresponding to PE-ratios less than 1 as lsquounsuitablersquo(because less records than predicted are in these areas)PE-ratios of 1ndash3 for wolves and 1ndash5 for lynx as lsquosuitablersquoand PE-ratios over 3 (wolves) and 5 (lynx) as lsquogoodrsquo The sec-ond and third thresholds were chosen according to plateausthat the curves reached before increasing again We chosedifferent threshold values for the species because of the dif-fering overall range of values and because the habitat suit-ability values within these categories were thus more similarIt should be noted however that the representation of theHSM or the chosen thresholds do not affect any of the anal-yses but are just for representational purposes We alsochecked our model by comparing the percentage of wolf andlynx records on unsuitable vs suitable or good areas withinthe range of each species (ie using a buffer with the width ofan average territory size around all records) relative to thepercentage coverage of these areas

Least cost path analysis

We used the values of the marginality factor calculatedby ENFA to derive costs for each habitat type and stand-ardised them by giving the lowest value a cost of 100 andthe highest value a cost of 1 (see Table 1) (Note BecauseWET and ROAD were distances rather than percentage val-ues we changed their signs) To derive a cost map inARCVIEW 33 (ESRIreg) we added the cost grid for habitattypes to the cost grid for roads and then reclassified the val-ues by stretching them between 1 and 100 In this wayroads were not lsquomissedrsquo due to the 1 km2 grid cell size

Moving decisions of animals during dispersal eventswill be based on the actual habitat rather than general suit-ability that will tend to level out differences that might stillbe relevant for habitat selection during dispersal We there-

180 M Huck et al

Table 1 Ecogeographical variables used for ENFA (abbreviations used in the text are written in SMALL CAPS)

Original CORINE code(for habitat types) Detailed Data input Cost wolf Cost lynx

211 213 241 334 ARABLE land 69 or 177 km2 circle 100 100312 CONIFEROUS forest 69 or 177 km2 circle 18 37311 DECIDUOUS forest 69 or 177 km2 circle 1 1Derived variable Distance to HUMAN distance ndash ndashDerived variable Forest size 9 km2 circle ndash ndash111ndash112 121ndash124 131ndash133141ndash142 221ndash222 242

HUMAN 69 or 177 km2 circle 68 72

313 MIXED forest 69 or 177 km2 circle 4 10243 Natural meadows (NATMEAD) 69 or 177 km2 circle 56 65231 PASTURE 69 or 177 km2 circle 36 59Mainsecondary roads ROAD distance 4623 7337321ndash324 331ndash333 TRANSITIONAL (scrub natural open

transitional forest)69 or 177 km2 circle 32 43

411ndash412 421ndash423 511ndash512 Wetland and water bodies (WET) distance 47 64

fore used the Marginality vector of ENFA to assign costs toeach habitat type of the CORINE map instead of convertingthe suitability map directly into a cost map The two costmaps were used to determine LCPs between wolf or lynxpopulations using the program PATHMATRIX (Ray 2005) afree extension to ARCVIEW 33 We chose representativepoints as start and ending point for LCPs We used thepatches of suitable wolf habitat determined in anotherstudy by Jecircdrzejewski et al (2008) to determine relativelycentral true locations of a wolf or lynx record within eachpatch We considered only patches with at least three re-cords The points were then moved so that they lay in areasof highest suitability as predicted by ENFA for both lynxand wolf For each LCP PATHMATRIX provides the Euclid-ean distance between the patches that are connected by thispath the total length of the path and the total cost of thepath Additionally we divided the cost of the path by itslength to obtain the relative cost (in cost-units per meterlsquocpmrsquo)

We also calculated the relative costs for the LCPs deter-mined for wolves using the cost-grid of lynx and vice versathus checking whether the alternative route would also besuitable for the other species If for one species the relativecost for this alternative route was lower we used only thislower-cost route for the final representation of large carni-vore corridors In order to avoid repetitiveness we consid-ered only LCPs connecting neighbouring start and endingpoints By reducing the total number of LCPs conservationefforts can be better focused For all LCPs we calculated thelengths of path segments over non-forested habitat (OPEN)

Comparison with real dispersal data

In order to get a feeling whether the LCPs determinedin this study would be similar to actual dispersal routes byreal animals we compared them with data from four lynx inBiasup3owieiquesta Primeval Forest (Schmidt 1998) For two ofthese lynx (males Nikita and Dymitr) several consecutiveradio locations between the start of dispersal and until thecontact was lost were available while for the other two in-dividuals (female Natasza and male Nikifor) only startand end point were known We calculated LCPs usingPATHMATRIX as described previously For the two lynx withseveral locations we calculated LCPs for each consecutivepair of locations and combined the values because LCPswould otherwise not be comparable due to excursive move-ments by the animals For a fifth male (Masup3y) we knewstart and ending point (ie minimum dispersal distance)but could not calculate a LCP because he emigrated toBelarus Republic which is not covered by CORINE mapsWe used the average of the relative cost for all four lynx tocompare it with the average value of the LCPs For all lynxwe calculated OPEN We also measured by hand the dis-tances the animal would have to cross over non-forestedhabitat when only considering the shortest possible connec-tions between forest patches By dividing the overall sum ofOPEN for each individual along the PATHMATRIX-route bythe sum of the latter estimate (minimal value) we obtaineda measure of the degree by which LCPs overestimated theamount of open landscape that has to be crossed for exam-ple due to the relatively coarse grid size The values for

overestimation for the four lynx was then averaged We de-termined the longest distance that any of the lynx musthave crossed over an open habitat segment This is a con-servative estimate since it is unlikely that animals alwaysfind the shortest connection between forest patches Thevalue was multiplied by the average value of overestima-tion to determine a maximum distance that a lynx might bewilling to cross over open habitat (MAXOPEN) on LCPs cal-culated by PATHMATRIX Unfortunately no published dataon dispersal of wolves in Poland are so far available for de-tailed comparisons

Determination of factors potentially

hindering dispersal

We considered three kinds of features with potentiallyhigh barrier effects major roads (international roads ex-press roads and highways including planned highways)towns and settlements and large open areas without forestpatches We determined locations where LCPs crossed ma-jor roads and large or long-stretched human settlements ortowns Data on roads were obtained from the General Direc-torate of National Roads and Highways (httpwwwgddkiagovpl) At intersections of major roads with corridors (or inthe surrounding area) we propose the building of wildlifepassages To rank these propositions we calculated the areaand number of protected sites in a circle of 201 km2 Weconsidered Natura 2000 sites (Special Areas of Conserva-tion and Special Protected Areas) National Parks Land-scape Parks and Nature Reserves (Ministry of EnvironmentPoland httpnatura2000mosgovpl) Secondly we consid-ered road-corridor intersections as more critical if not onlythe wolf and lynx corridor coincided but also at least one oftwo other corridors based on slightly different cost-grids(data not presented) because this indicates that the pro-posed corridor is likely to be a robust estimate of real trav-elling routes

In ARCMAP 92 (ESRIreg) we determined OPEN For eachLCP we determined those path segments that were (a) lon-ger than the threshold MAXOPEN (see above) but less thandouble that value (b) 2 to 3 times that value and (c) morethan 3 times that value These segments were considered tobe of increasing conservation concern

Results

Habitat suitability and least cost paths

Global marginality and tolerance values cal-culated by the ENFA for lynx and wolves werenearly the same within each species whether us-ing circles of 177 or 69 km2 Lynx were indicatedas more marginalised (19 vs 14 for wolves) andless tolerant (08 vs 09) than wolves (Table 2)This pattern also persisted when using a less de-tailed set of habitat variables (eg not distin-

Corridors and dispersal barriers 181

guishing between forest types) as employed inanother study on wolves (tolerance of lynx 059of wolves 074 M Huck and co-workers unpubl)While the overall pattern of marginalisation val-ues (and thus derived costs) was similar betweenthe species lynx showed a slightly stronger se-lection of deciduous and mixed forest comparedto coniferous forest and a stronger avoidance ofall types of open habitats (Table 1)

The habitat suitability maps of both specieswere similar in that they corresponded mainlyto larger forested areas though they would dif-fer in detail (Fig 1) Habitat suitability classeswere determined depending on the correspond-ing PE-values (see Methods) 0ndash20 unsuitable201ndash36 (wolves) and 201ndash37 (lynx) suitablegt 36 (wolf) and gt 37 (lynx) good Less than halfthe area was indicated as good for lynx than forwolf (lynx 10 639 km2 wolf 26 133 km2 Fig 1)

LCPs for wolves and lynx overlapped by 52The corresponding adaptive Boyce indexes (Boyceet al 2002 Hirzel et al 2006) were 0946 and0879 for wolf and lynx HSMs respectivelyWithin the range of wolf (lynx) occurrences491 (492) were denoted as lsquounsuitablersquo byBIOMAPPER yet only 134 (181) of the actualrecords were recorded in unsuitable areas lend-ing further support to the validity of the model

Generally LCPs based on the lynx-costgridwere more costly than those based on the wolf-costgrid (170 and 116 cpm for lynx and wolf re-spectively) but crossed similar length of openarea segments (Table 3) Twenty-five (out of 53)LCPs for lynx were relatively less costly whenlsquoforcedrsquo along wolf-routes than along the routedetermined by PATHMATRIX Five additionalroutes had the same relative costs for lynx re-gardless whether following the original lynxLCPs or wolf LCPs Only one LCP based on thewolf costgrid was less costly when using theroute that was determined for the correspondinglynx costgrid Since the difference in cost wasonly slight but the path seemed to offer a plausi-ble alternative route we retained it Thus Fig 2represents a total of 76 corridors ie 53 based onthe wolf costgrid and 23 additional ones basedon the lynx costgrid that indicated less relativecosts for lynx

The four radio-tracked lynx dispersed on av-erage 866 km (along path distance) before thecontact was lost A fifth lynx from the study bySchmidt (1998) travelled at least 129 km (straightline distance) The average relative cost basedon the lynx costgrid for these animals was 137(maximum 186) cpm Along the LCPs averagetotal distance crossed through open area during

182 M Huck et al

Table 2 Contribution of the environmental variables to marginality (M1 ranging from ndash1 to +1) specialisation(S1ndashS3 ranging from 0 to 1) and explained information presented for the significant factors of the ecologicalniche factor analysis models for lynx and wolves in Poland a We only present absolute values for all specialisa-tion factors b These variables represent distance-variables therefore the interpretation of values is opposite tothat for the other variables (see text)

VariableLynx Wolf

M1 S1a S2a S3a M1 S1a S2a S3a

ARABLE ndash042 069 051 015 ndash052 061 043 033CONIFER 020 029 039 046 027 024 068 007DECIDUOUS 053 012 013 010 047 007 022 003DISTHUM

b 020b 020 010 036 023b 017 007 016HUMAN ndash016 057 059 015 ndash020 070 001 033MIXED 049 009 009 007 039 013 011 007NATMEAD ndash009 010 041 032 ndash008 004 037 039PASTURE ndash003 006 009 031 012 012 001 023ROAD

b 016b 003 005 000 020b 010 023 010TRANSITIONAL 014 012 008 004 014 010 014 010WET

b 008b 003 005 011 0b 002 028 065WOODAREA 036 015 015 062 035 004 008 033

dispersal was 119 km (average per segment =16 km) with a maximum segment length of 51km continuously in open habitat If one consid-

ers only the shortest possible connections be-tween forest patches that is not following theLCPs then the lynx crossed on average a total of

Corridors and dispersal barriers 183

(b) Wolf

unsuitable

suitable

good

species range

0 50 100 km

(a) Lynx

Fig 1 Habitat suitability map based on Ecological Niche Factor Analysis and occurrence of lynx and wolves in Poland

184 M Huck et al

Table 3 Summary of potential barriers to the dispersal of lynx and wolves in Poland Av-erage length (in km) and number of LCP-segments crossing open (non-forested) habitatsfor paths based on lynx and wolf costgrids as well as the combined corridors and numberof major roads crossing potential corridors As a reference the total length (in km) andnumber of LCPs is given in the last line a Note that the combined column is not the sumof lynx+wolf It does not include those lynx LCPs that had a relatively higher cost thanthe corresponding wolf LCP

FeatureLynx Wolf Combineda

Length Count Length Count Length Count

All 28 608 24 463 26 742

Open habitat4ndash8 km 54 96 51 65 52 1008ndash12 km 96 14 99 5 103 8gt 12 km 168 3 183 5 174 7

No of roads crossing ndash 56 ndash 49 ndash 56

Corridors 7529 53 6784 53 8063 76

0 50 100 km

52 No

20 Eo

lowhigh

mediumhigh

LCPsAdditional lynx LCPsMajor roadsPlanned highways

lowmediumhigh

Green bridges (priority)

for existing highways for planned highways

Green belts throughurbanized area (priority)

Fig 2 Least cost paths for wolves and lynx major roads and proposed green bridges in Poland

56 km open habitat while the longest distancethe lynx must have traversed across a singlepatch of open habitat was at least 19 km Hencethe potential overestimate of LCPs compared tothe shortest routes possible was 21-fold (11956)If 19 km of open habitat is the upper limit ofwhat a lynx is willing to cross (for a similarthreshold see Zimmermann et al 2005) and con-sidering the overestimation by the program bymultiplying this value with 21 we used athreshold of 399 km ie if corridors pass open ar-eas over four or more kilometres this is likely toact as a barrier for dispersal

Potential barriers

Essentially all corridors showed long sectionsthat were not covered by forest (Fig 3) Seven of

these sections were more than 12 km long 100between 4 and 8 km long and 8 further of inter-mediate length (Table 3 average length of sec-tions 4 km = 63 km)

At 56 locations major roads crossed the pro-posed corridors (Table 3) For these road-corridorintersections we propose the location of wildlifepassages (Fig 2) The locations do not always liedirectly on the LCP since actual corridors willusually be of several 100 m width and thecoarse grid might on some occasions lead tosub-optimal routes that were corrected by eyeFurthermore the responsible agencies mightadapt the location to a certain degree due totheir specific knowledge of the actual site InAppendix we also propose a priority list for thewildlife passages 31 of which are considered tobe of high priority because of either the vicinity

Corridors and dispersal barriers 185

0 50 100 km

52 No

20 Eo

Open habitat segmentsMost costly LCPsLCPs 4-8 gt 8-12 gt 12 km

Fig 3 Segments of un-forested habitat along least cost paths for wolves and lynx in Poland

184 M Huck et al

Table 3 Summary of potential barriers to the dispersal of lynx and wolves in Poland Av-erage length (in km) and number of LCP-segments crossing open (non-forested) habitatsfor paths based on lynx and wolf costgrids as well as the combined corridors and numberof major roads crossing potential corridors As a reference the total length (in km) andnumber of LCPs is given in the last line a Note that the combined column is not the sumof lynx+wolf It does not include those lynx LCPs that had a relatively higher cost thanthe corresponding wolf LCP

FeatureLynx Wolf Combineda

Length Count Length Count Length Count

All 28 608 24 463 26 742

Open habitat4ndash8 km 54 96 51 65 52 1008ndash12 km 96 14 99 5 103 8gt 12 km 168 3 183 5 174 7

No of roads crossing ndash 56 ndash 49 ndash 56

Corridors 7529 53 6784 53 8063 76

0 50 100 km

52 No

20 Eo

lowhigh

mediumhigh

LCPsAdditional lynx LCPsMajor roadsPlanned highways

lowmediumhigh

Green bridges (priority)

for existing highways for planned highways

Green belts throughurbanized area (priority)

Fig 2 Least cost paths for wolves and lynx major roads and proposed green bridges in Poland

56 km open habitat while the longest distancethe lynx must have traversed across a singlepatch of open habitat was at least 19 km Hencethe potential overestimate of LCPs compared tothe shortest routes possible was 21-fold (11956)If 19 km of open habitat is the upper limit ofwhat a lynx is willing to cross (for a similarthreshold see Zimmermann et al 2005) and con-sidering the overestimation by the program bymultiplying this value with 21 we used athreshold of 399 km ie if corridors pass open ar-eas over four or more kilometres this is likely toact as a barrier for dispersal

Potential barriers

Essentially all corridors showed long sectionsthat were not covered by forest (Fig 3) Seven of

these sections were more than 12 km long 100between 4 and 8 km long and 8 further of inter-mediate length (Table 3 average length of sec-tions 4 km = 63 km)

At 56 locations major roads crossed the pro-posed corridors (Table 3) For these road-corridorintersections we propose the location of wildlifepassages (Fig 2) The locations do not always liedirectly on the LCP since actual corridors willusually be of several 100 m width and thecoarse grid might on some occasions lead tosub-optimal routes that were corrected by eyeFurthermore the responsible agencies mightadapt the location to a certain degree due totheir specific knowledge of the actual site InAppendix we also propose a priority list for thewildlife passages 31 of which are considered tobe of high priority because of either the vicinity

Corridors and dispersal barriers 185

0 50 100 km

52 No

20 Eo

Open habitat segmentsMost costly LCPsLCPs 4-8 gt 8-12 gt 12 km

Fig 3 Segments of un-forested habitat along least cost paths for wolves and lynx in Poland

56 km open habitat while the longest distancethe lynx must have traversed across a singlepatch of open habitat was at least 19 km Hencethe potential overestimate of LCPs compared tothe shortest routes possible was 21-fold (11956)If 19 km of open habitat is the upper limit ofwhat a lynx is willing to cross (for a similarthreshold see Zimmermann et al 2005) and con-sidering the overestimation by the program bymultiplying this value with 21 we used athreshold of 399 km ie if corridors pass open ar-eas over four or more kilometres this is likely toact as a barrier for dispersal

Potential barriers

Essentially all corridors showed long sectionsthat were not covered by forest (Fig 3) Seven of

these sections were more than 12 km long 100between 4 and 8 km long and 8 further of inter-mediate length (Table 3 average length of sec-tions 4 km = 63 km)

At 56 locations major roads crossed the pro-posed corridors (Table 3) For these road-corridorintersections we propose the location of wildlifepassages (Fig 2) The locations do not always liedirectly on the LCP since actual corridors willusually be of several 100 m width and thecoarse grid might on some occasions lead tosub-optimal routes that were corrected by eyeFurthermore the responsible agencies mightadapt the location to a certain degree due totheir specific knowledge of the actual site InAppendix we also propose a priority list for thewildlife passages 31 of which are considered tobe of high priority because of either the vicinity

Corridors and dispersal barriers 185

0 50 100 km

52 No

20 Eo

Open habitat segmentsMost costly LCPsLCPs 4-8 gt 8-12 gt 12 km

Fig 3 Segments of un-forested habitat along least cost paths for wolves and lynx in Poland

to large protected areas or because the corridoris likely to be a main migration axis

At three locations the corridors lead throughurbanized areas (two in Gdantildesk North Polandand one around Bielsko-Biasup3a South PolandFig 2) Particularly in the southern region thecorridor necessarily passes through human set-tlements or cities which should be kept in mindin any future city and landscape planning

Discussion

Habitat suitability and least cost paths

The values given by the ENFA marginalityfactors indicate habitat preferences and avoid-ances of wolf and lynx that correspond well tofindings by other studies (as far as the variablesare comparable) even those using differentmethodology (Zimmerman 2004 Basille et al2008 Jecircdrzejewski et al 2008) the preferencefor forest habitats and the avoidance of agricul-tural and otherwise strongly human influencedland One major difference to some of the othermodels was that we did not include slope oraltitude although in other studies this was oftena significant explanatory variable (Zimmerman2004 Jecircdrzejewski et al 2005 Basille et al2008) In Poland however and probably inmany other areas slope and altitude in themountainous areas are negatively correlatedwith the degree of human land-use Thus thepreference for slopes or high altitude for somepopulations might rather reflect avoidance ofhumans and may lead to nonsensical results ifapplied to populations that live in flat terrain(compare for example discussion of the problemin Jecircdrzejewski et al 2004 2005) The broadpreferences of the two species are similar butthe results from the ENFA confirm that theEuropean lynx is in many respects more spe-cialised than the wolf Because of the relativelybroad scale of the study it was not possible toanalyse habitat preferences in more detail other-wise the difference between the species mighthave become even more pronounced For ex-ample Podgoacuterski et al (2008) found that lynxstrongly prefer more structured forests (in-

cluding more fallen trees undergrowth etc) Inthis sense the presented HSM for lynx mightrepresent a rather optimistic view on habitatavailable for permanent lynx populations Onthe other hand the species occurrences depictedin Fig 1 indicate that both lynx and wolf do alsooccur in areas that are classified as less thangood with 18 and 13 of lynx and wolf occur-rences respectively recorded on lsquounsuitablersquohabitat However it should be kept in mind thatsome of these represent road kills ephemeralsightings of apparently dispersing animals or are-introduced population (central part of Fig 1a)and furthermore even ldquoavoidedrdquo habitats suchas human settlements or arable land will befrequented to a certain (low) extent by bothspecies Overall the HSMs for both species werevery similar not only using the approach de-scribed in this study but also compared to earlierstudies (Jecircdrzejewski et al 2008 M Huck andco-workers unpubl) This enhances the con-fidence that we have presented a suitable modelon which management decisions can be basedParticularly areas suitable for lynx will also besuitable for wolves but only to a lesser extentvice versa

As the HSMs the least cost paths for bothspecies were similar They overlapped lsquoonlyrsquo to52 but considering that paths only one kilo-metre apart are lsquonon-overlappingrsquo the valuepoints to a rather close similarity Likewisewhen comparing the costs of alternative routes(ie the routes calculated originally with the lynxand the wolf costgrid respectively but deter-mining the costs with the species-specific val-ues) it is evident that relative costs do not differto a great extent and for lynx the wolf route wasoften even cheaper in terms of costs per meterpath length This suggests that the differentLCPs are indeed alternatives

Although costs calculated by PATHMATRIX

are an abstract measure not easily related toreal costs like energy expenditure or mortalityrisk the differing absolute and relative costs forthe two species indicate that dispersal might bemore difficult for lynx than for wolves Particu-larly lynx seem to be more averse to crossnon-forested habitats The assumed correlationbetween cost values based on occurrence data

186 M Huck et al

and true permeability for the individual migrantis supported by a study on Swiss lynx that usedagricultural and other open areas least and gen-erally seemed to avoid them during dispersal(Zimmerman 2004) Obviously animals do notusually know in advance about potential risksthey may encounter along the entire length of aspecific route and decision lsquoerrorsrsquo are also ex-pected because animals may have evolved in aquite different (not anthropogenically influ-enced) environment (Fahrig 2007) This leadFahrig (2007) to conclude that LCPs should notbe used as a substitute for analyses of actualmovement paths and risks While this is theoret-ically a sound advice it is in practice not alwaysa good solution to demand actual movementdata before any management solutions are con-sidered The review and analysis of Fahrig(2007) is based on studies done on insects am-phibians small birds and rodents ndash all specieswith low dispersal distances whose movementscan be comparatively easily monitored Formany large species that occur in low densities orare difficult to capture and monitor such dataon dispersal movements are often simply notavailable for a specific site Given these notori-ous difficulties modelling has to be employed inorder to develop in time conservation strategiesthat at least try to keep up with ongoing habitatdestruction and fragmentation If available realdispersal data should be used to evaluate anycomputer models

Real dispersal data

The comparison with the real lynx datasetshowed the values of our analysis to be similarto those that lynx truly experience when emi-grating The length of some paths connectingneighbouring suitable areas was larger than thelongest observed migration distance of the fourradio-tracked lynx in eastern Poland (Schmidt1998 this study) However these observed dis-tances are minimal values because in most casesthe contact to the animal was lost before it prob-ably reached the end of its dispersal and the129 km traversed by lynx Masup3y represent thestraight-line distance while the actual along-path distance was probably much longer The oc-

currence of ephemeral sightings of lynx in un-suitable habitats further suggests that lynx canundertake quite long dispersals For wolvesthat have been observed to cover more than 700km the corridor lengths lie well within recordeddispersal distances (review in Mech and Boitani2003) Likewise the relative costs for the fourlynx was slightly lower (137 vs 170 cpm) butone individual lsquopaidrsquo even 186 cpm Thus theproposed corridors should be manageable for theanimals when certain issues (see below) havebeen addressed Since lynx are less tolerantthan wolves and probably also less tolerant thanmost ungulates (red deer roe deer wild boar)the suggested corridors should be suitable for avariety of species not only the two carnivores

Management recommendations

We present 76 LCP that might be further de-veloped into working corridors However wewould like to stress that these LCPs representonly a subset of corridors that are necessaryto promote biodiversity in Poland Other ap-proaches might find additional areas of high pri-ority to be conserved as corridors For examplein 2005 W Jecircdrzejewski and co-workers pro-posed a corridor network for Poland based on ex-pert knowledge that tried to include as manyareas of forest or marshland as possible but wasnot tailored for specific species (Jecircdrzejewski et

al 2009) While the overall patterns are quitesimilar the discrepancies should be viewed ascomplementary rather than competitive Givenspecific start and ending points the proposedLCPs are the most likely routes chosen bywolves or lynx (and probably other species) forthis connection but this does not prove that ani-mals will actually use them for example be-cause of sub-optimal decisions (Fahrig 2007)Furthermore the LCPs are still far from opti-mal a point that is sometimes not emphasizedsufficiently Motorways have to be crossed hu-man settlements cannot always be avoided andlarge stretches of open habitat might hindermovements These open areas might act as bar-riers not only in that the animals are wary tocross them and might rather return than at-tempt the crossing but also because they pose

Corridors and dispersal barriers 187

actual risks eg due to the higher visibility Fur-thermore if animals are forced to use for exam-ple pastures the degree of predation and thushuman-wildlife conflict will increase While notall of these barriers can be abolished measure-ments can be taken to mitigate the adverse ef-fects as far as possible Our proposed sites forcrossing structures (Fig 2 Appendix) should beregarded as rough hints rather than exact loca-tions Proper evaluation based on the combinedknowledge of both transportation and environ-mental experts should be used to carefully judgetechnical possibilities for wildlife passages andthe needs of all sides before deciding on the ac-tual site We have only presented a limited num-ber of recommendations for the location ofcrossing structures This does not imply that fur-ther structures for example as presented inother studies (Jecircdrzejewski et al 2009) mightnot be also necessary firstly we included onlymajor roads but other roads with a high trafficvolume might pose even higher risks thanmotorways (Seiler and Helldin 2006) Secondlywe indicate only one structure per LCP-majorroad intersection More structures might beneeded for example if the actual corridor isvery wide with long stretches of road intersect-ing it The building of wildlife passages shouldalso be accompanied by monitoring the use andacceptance of the structure by animals in orderto evaluate the effectiveness (eg Clevenger andWaltho 2000 Pfister et al 2002 Kusak et al2009) A total of 39 passages for larger mammalshave already been built in Poland (by 2008Jecircdrzejewski et al 2009) thus some experiencealready exists In the country ecological connec-tivity is protected by a number of laws and regu-lations giving legal basis for the implementationof the suggested measures (Jecircdrzejewski et al2009)

At three sites Polish forest wildlife corridorspass necessarily through urban areas While itcan be argued that animals might be able toavoid the path through Gdantildesk (which wouldhowever result in very long open-habitat dis-tances) the long stretched urbanised area in theSouth of Poland along the Carpathians seems tobe a critical barrier to wolf dispersal (M Huckand co-workers unpubl) that cannot be avoided

(central part of the southern border in Fig 2)Here the construction or extension of ldquogreenlungrdquo belts within settlement might not onlybenefit the human population but also enhancegene flow between animal populations In Fig 3we have indicated the seven most costly LCPsThe high costs make it unlikely that these LCPsthough the relatively least costly connections be-tween the given locations will be actually usedby animals at least under current conditions

Unless some actions are taken some of thecorridors will not fulfil their aim to promotegene flow between populations Land-ownersshould be encouraged to afforest some of theirland particularly in the indicated areas Fur-thermore considering the apparent preferenceof deciduous and mixed forest by both species amore natural forest management should be em-ployed Reforestation will not only enhance theconnectivity between wildlife populations but itmight also serve human interests in various di-rect and indirect ways eg by enhancing the mi-croclimate acting as wind-breakers and thusreducing erosion of arable land by offering rec-reational areas and for the aesthetic value ofless uniform habitats (Secretariat of the Con-vention on Biological Diversity 2001)

Concluding we strongly suggest that al-though our proposed corridors are likely to givea good indication of rough routes fine scaleanalyses are carried out on local levels when ac-tually planning any specific conservation activ-ity Our study shows that the determination ofLCPs as surrogates for corridors should be fol-lowed by the identification of potential barriersbecause otherwise they might not fulfil their ob-jective Combining the knowledge of expertssuch as biologists foresters and road plannerswill lead to the most successful results We sug-gest that any conservation measures should beaccompanied by scientific research studying theeffectiveness of the measure both in terms oftravel rates and in terms of gene-flow before andafter the measurement was taking effect Thiswill provide a powerful tool how to optimize ef-forts to enhance connectivity between wildlifepopulation in a cost-effective way

Acknowledgements We would like to thank J Cromsigt forvaluable hints regarding ARCVIEW M Huck was supported

188 M Huck et al

in the frames of the European Union project ldquoTransferof Knowledge in Biodiversity Research and ConservationBIORESCrdquo under the Marie Curie Host Fellowships for theTransfer of Knowledge (ToK-DEV) in the 6th FrameworkProgramme (Contract No MTKD-CT-2005-029957) We thankthe General Directorate of the State Forests and the De-partment of Nature Conservation of the Ministry of Envi-ronment for their cooperation during the National Wolf andLynx Censuses The European Nature Heritage Fund Euro-natur (Germany) provided funding for the wolf census SNamp RWM were supported by the International Fund for Ani-mal Welfare (IFAW) and the Wolves and Humans Founda-tion Anonymous referees provided helpful suggestions

References

Adriaensen F Chardon J P De Blust G Swinnen EVillalba S Gulinck H and Matthysen E 2003 The ap-plication of least-cost modelling as a functional land-scape model Landscape and Urban Planning 64 233ndash247doi 101016S0169-2046(02)00242-6

Basille M Calenge C Marboutin Eacute Andersen R andGaillard J-M 2008 Assessing habitat selection usingmultivariate statistics Some refinements of the ecological-niche factor analysis Ecological Modelling 211 233ndash240doi 101016jecolmodel200709006

Beier P and Noss R F 1998 Do habitat corridors provideconnectivity Conservation Biology 12 1241ndash1252 doi101046j1523-1739199898036x

Boyce M S Vernier P R Nielsen S E and SchmiegelowF K A 2002 Evaluating resource selection functionsEcological Modelling 157 281ndash300 doi 101016S0304-3800(02)00200-4

Clevenger A P and Waltho N 2000 Factors influencingthe effectiveness of wildlife underpasses in Banff Na-tional Park Alberta Canada Conservation Biology 1447ndash56 doi 101046j1523-1739200000099-085x

Cohen J E and Newman C M 1991 Community area andfood-chain length theoretical predictions The AmericanNaturalist 138 1542ndash1554 doi 1023072462559

Coulon A Cosson J Angibault J Cargnelutti B GalanM Morellet N Petit E Aulagnier S and Hewison AJ M 2004 Landscape connectivity influences gene flowin a roe deer population inhabiting a fragmented land-scape an individual-based approach Molecular Ecology13 2841ndash2850 doi 101111j1365-294X200402253x

Crooks K R 2002 Relative sensitivities of mammalian car-nivores to habitat fragmentation Conservation Biology16 488ndash502 doi 101046j1523-1739200200386x

Epps C W Wehausen J D Bleich V C Torres S G andBrashares J S 2007 Optimizing dispersal and corridormodels using landscape genetics Journal of Applied Ecol-ogy 44 714ndash724 doi 101111j1365-2664200701325x

Fahrig L 2007 Non-optimal animal movement in human-altered landscapes Functional Ecology 21 1003ndash1015doi 101111j1365-2435200701326x

Frankham R Ballou J D and Briscoe D A 2004 A primerof conservation genetics Cambridge University PressCambridge

Gilbert F Gonzalez A and Evans-Freke I 1998 Corridorsmaintain species richness in the fragmented landscapesof a microecosystem Proceedings of the Royal Society ofLondon Series B 265 577ndash582 doi 101098rspb19980333

Herrmann M 1998 Verinselung der Lebensraumlume vonCarnivoren ndash Von der Inseloumlkologie zur planerischenUmsetzung Naturschutz und Landschaftspflege inBrandenburg 45ndash49

Hirzel A H Hausser J Chessel D and Perrin N 2002aBiomapper 40 Lab for Conservation Biology Lausanne

Hirzel A H Hausser J Chessel D and Perrin N 2002bEcological-niche factor analysis how to compute habitat-suitability maps without absence data Ecology 832027ndash2036 doi 1018900012-9658(2002)083[2027ENFAHT]20CO2

Hirzel A H Le Lay G Helfer V Randin C and Guisan A2006 Evaluating the ability of habitat suitability mod-els to predict species presences Ecological Modelling199 142ndash152 doi 101016jecolmodel200605017

Jecircdrzejewski W Jecircdrzejewska B Zawadzka B BorowikT Nowak S and Myssup3ajek R W 2008 Habitat suitabil-ity model for Polish wolves based on long-term nationalcensus Animal Conservation 11 377ndash390 doi 101111j1469-1795200800193x

Jecircdrzejewski W Niedziasup3kowska M Myssup3ajek R WNowak S and Jecircdrzejewska B 2005 Habitat selectionby wolves Canis lupus in the uplands and mountains ofsouthern Poland Acta Theriologica 50 417ndash428

Jecircdrzejewski W Niedziasup3kowska M Nowak S and Jecircd-rzejewska B 2004 Habitat variables associated withwolf (Canis lupus) distribution and abundance in north-ern Poland Diversity and Distributions 10 225ndash233doi 101111j1366-9516200400073x

Jecircdrzejewski W Nowak S Kurek R Myssup3ajek R WStachura K Zawadzka B and Pchasup3ek M 2009 Ani-mals and roads ndash Methods of mitigating the negativeimpact of roads on wildlife Mammal Research InstitutePolish Academy of Sciences Biasup3owieiquesta

Jecircdrzejewski W Schmidt K Theuerkauf J JecircdrzejewskaB and Kowalczyk R 2007 Territory size of wolvesCanis lupus linking local (Biasup3owieiquesta Primeval ForestPoland) and Holarctic-scale patterns Ecography 3066ndash76 doi 101111j0906-7590200704826x

Kaczensky P Knauer F Krze B Jonozovic M Adamic Mand Gossow H 2003 The impact of high speed high vol-ume traffic axes on brown bears in Slovenia BiologicalConservation 111 191ndash204 doi 101016S0006-3207(02)00273-2

Klar N 2007 Der Wildkatze koumlnnte geholfen werden ndash DasBeispiel eines Wildkorridorsystems fuumlr Rheinland-Pfalz [In Lebensraumlume schaffen H Leitschuh-Fechtand P Holm eds] Haupt Berne Basel 115ndash129

Kusak J Huber D Gomeregraveiaelig T Schwaderer G and GuvicaG 2009 The permeability of highway in Gorski Kotar(Croatia) for large mammals European Journal of Wild-life Research 55 7ndash21 doi 101007s10344- 008-0208-5

Lovari S Sforzi A Scala C and Fico R 2007 Mortality pa-rameters of the wolf in Italy does the wolf keep himself

Corridors and dispersal barriers 189

from the door Journal of Zoology London 272 117ndash124doi 101111j1469-7998200600260x

MacArthur R H 1957 On the relative abundance of birdspecies Proceedings of the National Academy of Sci-ences USA 43 293ndash295 doi 101073pnas433293

Mech L D and Boitani L (eds) 2003 Wolves ndash behaviorecology and conservation University of Chicago PressChicago

Niedziasup3kowska M Jecircdrzejewski W Myssup3ajek R W NowakS Jecircdrzejewska B and Schmidt K 2006 Environmen-tal correlates of Eurasian lynx occurrence in Poland ndashlarge scale census and GIS mapping Biological Conser-vation 133 63ndash69 doi 101016jbiocon200605022

Nikolakaki P 2004 A GIS site-selection process for habitatcreation estimating connectivity of habitat patchesLandscape and Urban Planning 68 77ndash94 doi 101016S0169-2046(03)00167-1

Noss R F Quigley H B Hornocker M G Merrill T andPaquet P C 1996 Conservation biology and carnivoreconservation in the Rocky Mountains ConservationBiology 10 949ndash963 doi 101046j1523-1739199610040949x

Palomares F Delibes M Ferreras P Fedriani J MCalzada J and Revilla E 2000 Iberian lynx in a frag-mented landscape predispersal dispersal and post-dispersal habitats Conservation Biology 14 809ndash818doi 101046j1523-1739200098539x

Pfister H P Keller V Heynen D and Holzgang O 2002Wildtieroumlkologische Grundlagen im Strassenbau Strasseund Verkehr 3 101ndash108

Podgoacuterski T Schmidt K Kowalczyk R and Gulczyntildeska A2008 Microhabitat selection by Eurasian lynx and itsimplications for species conservation Acta Theriologica53 97ndash110

Ray N 2005 PATHMATRIX a geographical informationsystem tool to compute effective distances among sam-ples Molecular Ecology Notes 5 177ndash180 doi 101111j1471-8286200400843x

Ray N Lehmann A and Joly P 2005 Modeling spatial dis-tribution of amphibian populations a GIS approach basedon habitat matrix permeability Biodiversity and Con-servation 11 2143ndash2165 doi 101023A102139027698

Schadt S Knauer F Kaczensky P Revilla E Wiegand Tand Trepl L 2002 Rule-based assessment of suitable

habitat and patch connectivity for the Eurasian lynx inGermany Ecological Applications 12 1469ndash1483 doi101046j1365-2664200200700x

Schmidt K 1998 Maternal behaviour and juvenile dispersalin the Eurasian lynx Acta Theriologica 43 391ndash408

Schmidt K Jecircdrzejewski W and Okarma H 1997 Spatialorganization and social relations in the Eurasian lynxpopulation in Biasup3owieiquesta Primeval Forest Poland ActaTheriologica 42 289ndash312

Secretariat of the Convention on Biological Diversity 2001The Value of Forest Ecosystems SCBD Montreal

Seiler A and Helldin J-O 2006 Mortality in wildlife due totransportation [In The ecology of transportation man-aging mobility for the environment J Davenport and JL Davenport eds] Springer Dordrecht 165ndash190

Taylor P D Fahrig L Henein K and Gray M 1993 Con-nectivity is a vital element of landscape structure OIKOS68 571ndash573

Tewksbury J J Levey D J Haddad N M Sargent SOrrock J L Weldon A Danielson B J Brinkerhoff JDamschen E I and Townsend P 2002 Corridors affectplants animals and their interactions in fragmentedlandscapes Proceedings of the National Academy of Sci-ences USA 99 12923ndash12926 doi 101073pnas202242699

Trombulak S C and Frissell C A 2000 Review of ecologi-cal effects of roads on terrestrial and aquatic communi-ties Conservation Biology 14 18ndash30 doi 101046j1523-1739200099084x

Wilson C J 2003 Estimating the cost of road traffic acci-dents caused by deer in England Defra National Wild-life Management Team

Zimmerman F 2004 Conservation of the Eurasian lynx(Lynx lynx) in a fragmented landscape ndash habitat modelsdispersal and potential distribution PhD thesis Uni-versity of Lausanne Lausanne 1ndash179

Zimmermann F Breitenmoser-Wuumlrsten C and BreitenmoserU 2005 Natal dispersal of Eurasian lynx (Lynx lynx) inSwitzerland Journal of Zoology London 267 381ndash395doi 101017S0952836905007545

Received 18 December 2009 accepted 22 February 2010

Associate editor was Andrzej Zalewski

190 M Huck et al

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