landscape predictors of wolf attacks on bear-hunting dogs in

Landscape predictors of wolf attacks on bear-hunting dogsin Wisconsin USA

Erik R OlsonABD Adrian TrevesB Adrian P WydevenC and Stephen J VenturaB

ANorthland College Department of Natural Resources 1411 Ellis Avenue Ashland WI 54806 USABUniversity of Wisconsin ndash Madison Nelson Institute for Environmental Studies 550N Park Street70 Science Hall Madison WI 53706 USA

C25350 South Garden Avenue Cable WI 54821 USADCorresponding author Email eolsonnorthlandedu

AbstractContext In Europe and the United States wolfndashhuman conflict has increased as wolf populations have recovered and

recolonised human-dominated ecosystems These conflicts may lead to negative attitudes towards wolves and oftencomplicatewolfmanagementWolf attacks onbear-hunting hounds (hereafter hounds) are the second-most common type ofdepredation on domestic animals inWisconsin USA and typically themost costly in terms of compensation per individualanimal Understanding the geospatial patterns inwhich these depredations occur could promote alternative hunting practicesor management strategies that could reduce the number of wolfndashhuman conflicts

AimsWecompared variables differentiating betweenwolf attacks onhounds and non-hounds (eg pets)we constructeda spatial predictive model of wolf attacks on hounds and we explored how the landscape of risk changed over time

Methods We characterised landscape features of hound depredations using logistic regression We applied the spatialmodel to a geographic information system (GIS) to display spatial patterns and to predict areas of risk for wolf attack

Key results Our model correctly classified 84 of sites of past depredations 1999ndash2008 and 78 of nearby random-unaffected sites The model correctly predicted 82 of recent (2009ndash11) depredation sites not used in model constructionthereby validating its predictive power Risk of wolf attack on hounds increased with percentage area of public-access landnearby size of the nearest wolf pack proximity of the nearest wolf pack and decreased with percentage of humandevelopment National and county forest lands had significantly (P lt 0001) more hound depredations than did other land-ownership types whereas private lands had significantly fewer

Conclusions Risk of wolf attacks on hounds had distinctive temporal and spatial signatures with peak risk occurringduring the black bear hound training and hunting seasons and in areas closer to the centre of wolf pack territories with largerwolf packs and more public access land and less developed land

Implications Our analysis can help bear hunters avoid high-risk areas and help wildlife managers protect wildlife andrecreational use of public lands and reduce public costs of predator recovery We present a risk-adjusted compensationequation If wildlife managers choose or are required to provide compensation for hounds attacked by wolves whilehunting on public lands we suggest that managers consider adjusting compensation payments on the basis of the relativelandscape of risk

Additional keywords black bear Canis lupus carnivore coexistence depredation hound humanndashwildlife conflicthunting dogs modelling risk mapping

Received 1 March 2014 accepted 19 Decrmber 2014 published online 20 March 2015

Introduction

Top predators often play an essential role in maintainingecosystem functions and diversity (Berger et al 2001Terborgh and Estes 2010 Ripple et al 2014) Yet restorationof top predators faces obstacles because predators competewith people directly and indirectly for space and resources(Woodroffe and Ginsberg 1998) Hunters concerned withgame scarcity may oppose predator conservation (Chadwick2010 Liberg et al 2011 Treves and Martin 2011) When

hunters lose dogs (Canis familiaris) to predators thecompetition becomes direct and emotional (Naughton-Treveset al 2003 Bisi et al 2010 Lescureux and Linnell 2014)Because humanndashpredator conflicts can increase negativeattitudes towards predators and provide support for opponentsof predator recovery efforts (Lescureux and Linnell 2014)prediction and prevention of conflicts is critical Spatiallyexplicit models can provide resource users and managers withvisual representations of risk (risk maps) that can facilitate

CSIRO PUBLISHING

Wildlife Research 2014 41 584ndash597httpdxdoiorg101071WR14043

Journal compilation CSIRO 2014 wwwpublishcsiroaujournalswr

comprehension of management challenges at a landscape scale(Venette et al 2010 Treves et al 2011) We present a spatialanalysis of wolf attacks on dogs used for hunting large carnivoresin Wisconsin (1999ndash2011)

Domestic dogs have associated with humans for at least15 000 years (Larson et al 2012) and hunters have long useddogs to find and pursue their quarry (Cummin 2001) Across theworld many predators have been or are being hunted with theaid of dogs (eg jackals (Canis spp) coyotes (Canis latrans)wolves (Canis lycaon amp C lupus) bobcats (Lynx rufus) bears(Ursus spp) pumas (Puma concolor) and foxes (Vulpes andUrocyon spp)) In some cultures hunting with dogs contributesto community identity (Chitwood et al 2011) yet some view itas unethical or as incompatible with other hunting methods(Peyton 1989)

Use of dogs for hunting is not without risks multiple dogsmay be injured or killed during the pursuit Globally most dogskilled by wolves are pursuit dogs used for recreational hunting(47ndash87 see Butler et al 2013 corrected for gt53 in FinlandKojola and Kuittinen 2002) In Nicaragua jaguars (Pantheraonca) are known for attacking hunting dogs (Koster 2008) andin Botswana hunting dogs have been killed by lions (Pantheraleo) and foxes (Ikeya 1994) In Europe and the United Stateswolves have attacked dogs Kojola and Kuittinen (2002)reported 43 wolf attacks on dogs in Finland (1996ndash99) andmost of those attacks (54) were associated with dogs usedfor hunting Backeryd (2007) reported 117 hunting dogsattacked by wolves in Sweden and Norway (1995ndash2005) Ruidet al (2009) reported that more than 474 dogs were attackedby wolves in the Great Lakes region of the United States(1974ndash2006) The risk to dogs used in hunting is not arelatively recent phenomenon (Roosevelt 1902) and may varyon the basis of the distance dogs range from their owners orwith dog behaviour (eg baying) or body size (Kojola andKuittinen 2002 Backeryd 2007) In Wisconsin Wydevenet al (2004) demonstrated that the risk varied with a wolfpackrsquos size and history of attacking dogs used for huntingblack bear (Ursus americanus) Similarly Kojola et al (2004)documented that 76 of dog attacks occurred within one wolf-pack territory suggesting that a specific pack could becomehabituated to attacking dogs (see also Kojola and Kuittinen2002) Many researchers have also found that wolf attacks ondogs increase in areas with or during periods of low preydensity (Butler et al 2013)

Negative interactions between wolves and pursuit huntingdogs have been considered a driver of negative attitudes towardwolf conservation (Lescureux and Linnell 2014) Increases innegative attitudes can lead to illegal killing of wolves (Olsonet al 2014 Treves and Bruskotter 2014) or increased supportfor lethal management options or more liberal wolf harvests(Treves et al 2013 Lescureux and Linnell 2014) Thusmitigating wolf attacks on hunting dogs could enhance localsupport of wolf conservation

Currently in the USA black bears can be hunted with dogsin 18 states including Wisconsin In Wisconsin wolves haveattacked dogs during hunting or training seasons since 1985(Treves et al 2002 2009 Wydeven et al 2004 Ruid et al2009) These authors found that verified wolf complaintsgenerally increased from 1976 to 2006 as wolf population and

distribution increased (eg Olson et al 2014) Compensationto property owners for loss of domestic animals also increasedduring this time period (Ruid et al 2009 Treves et al 2009)Wisconsin statutesmandate compensation for wolf depredationsincluding wolf attacks on dogs (hereafter hounds) used forhunting large carnivores (mainly black bears) Depredations onhounds are the second-most common type of wolf damage in thestate and typically the most costly per individual (capped at US$2500 houndndash1 Treves et al 2009) Moreover in Wisconsincompensation for hound depredations accounted for about 37of approximately US$1million total paid in compensationprograms for wolfndashhuman conflicts (1986ndash2010) Thereforedonors to the statersquos compensation fund domestic animalowners those concerned with hound and wolf welfare andother taxpayers have a shared interest in diminishing wolfattacks on hounds

Our goal was to estimate spatial patterns of risk for hunterswho use hounds in Wisconsinrsquos wolf range We first comparedvariables differentiating between hound depredations anddepredations on non-hounds (eg pets bird-hunting dogs) toidentify possible differences between the two types of dogsattacked Second to support efforts to predict and preventwolf attacks on hounds we constructed a spatial predictivemodel and examined how risk may have changed over timeLast we evaluated the role of public access lands in hounddepredations We propose mitigation methods for hunterswho use hounds as well as for managers of wolves seeking tobalance wolf conservation with the needs of people living nearthem

Materials and methodsStudy area

Our study area (111 000 km2) represented about three-quartersof the state of Wisconsin (Fig 1) and was within 75 km fromevery known wolf-pack territory in 2009 (Wydeven et al 2009)We used a 75-km buffer because this distance was 25-km greaterthan the maximum distance any dog depredation had beenreported from a known wolf-pack territory in Wisconsin forthe study period The Wisconsin Department of NaturalResources (WDNR) delineated wolf-pack territories using acombination of aerial telemetry snow-track surveys and publicobservations using the techniques described in Wydeven et al(2009) The study area comprised temperate forests interspersedwith wetlands water bodies agricultural land and open areas(Mladenoff et al 1997) Bear hunting with hounds wasrestricted to the northern one-third of the state and opened for4 weeks from early September through early October (WDNR2011a Fig 2) The state-wide training season for hounds wasopen from 1 July to 31 August (WDNR 2011a Fig 2) Huntersused hounds for 13ndash37 of the total bears harvested(1999ndash2010) Hound hunting and training typically occurredon large blocks of public access land (ie land that is openaccess for the general public Dhuey and Kitchell 2006)Public-access lands represented between 38 and 49 of theland base open to bear hunting with hounds (Fig 2)

Wolf populations in Wisconsin have grown steadily sincethe mid-1990rsquos (Wydeven et al 2009) and have begun toestablish in areas with a greater potential for human conflict

Landscape predictors of wolf attacks on hounds Wildlife Research 585

(Mladenoff et al 1995 1999 2009) The WDNR estimated the201011 winter minimum wolf population at between 782 and824 wolves in 202ndash203 packs and 19+ loners (Wydeven et al2011)

Hound depredations

The United States Department of Agriculturersquos WildlifeServices (USDAndashWS) received investigated and verifiedhound depredation complaints since 1995 (Ruid et al 2009)

On the basis of field investigations USDAndashWS agents classifiedreported incidents as confirmed non-wolf unconfirmed orprobable or confirmed wolf threats or depredations (Ruid et al2009) We examined only verified (probable or confirmed) wolfincidents

Using descriptions from verified depredation reports weidentified two separate classes of dog depredation namelyhounds and non-hounds on the basis of breed and activityNon-hounds were attacked by wolves in proximity to theowner or near buildings whereas the subset we call hounds

2009 wolf pack territories

Wisconsin state boundary

Study area

0 25 50 100 Kilometres

Fig 1 Study site (grey) within Wisconsin and within 75 km of any 2009 wolf-pack territory (black polygons)

586 Wildlife Research E Olson et al

were used for hunting carnivores such as black bears coyotesand bobcats Hounds were generally run in groups of up to sixTypically hounds bayed as they pursued quarry and were radio-collared to allow owners to follow them at a distance Commonhound breeds were walker plott hound redbone coonhoundbluetick coonhound coonhound redtick coonhound mountaincur trigg black and tan and their crosses Non-hounds includedcommon pet breeds such as labrador spaniel husky terrier andyorkshire Although beagles are hounds we classified them asnon-hounds because in Wisconsin they are typically used forhunting lagomorphs For one incident where breed was notreported we classified the incident as non-hound because thefield verifier indicated that the dog was a household petAlthough some non-hound breeds are also used for huntingother species of prey we focussed on hounds used for huntingcarnivores because (1) most non-hound hunting dogs behavedifferently and are handled differently (2) only one non-hounddog was known to have been attacked while hunting duringour study period and (3) our results would be more readily

applied by hunters and managers because they would bespecific to a particular type of hunting

We compared temporal distributions (chi-square test) ofverified wolf attacks on the two classes of dogs from 1999 to2010 to verify that classifications based on breed reflecteddifferent patterns We used multi-distance spatial clusteranalysis (999 permutations) in ArcGIS Version 931 (ESRIRedlands California USA) based on Ripleyrsquos K function totest whether the hound or non-hound depredations wereclustered or dispersed across a range of scales (1ndash20-km scalesin 1-km increments) while minimising the study-area sizeeffects (ie reduced study-area edge correction function)

Predicting depredationTo predict the risk of future hound depredation by locationwe modelled landscape predictors of past sites of depredations(Treves et al 2011) Before 2002 the WDNR recordeddepredation locations in Public Land Survey system coordinates


Bear management zone

Public access land within study area

Study area

Fig 2 Wisconsin bear-management zones (AndashD) and public-access lands (includes federal statecounty and private open access lands) Zones A B and D were open for bear hunting with houndswhereas all zones are open to training with hounds typically from 1 July to 31 August Roughly 4649 and 86 of Zones A B and D respectively were in public access


(township range and section) at a resolution of 259 km2 (to thenearest section) We plotted those locations by using the centroidof the section After 2002 the verifiers recorded locations withhigher precision by using global positioning system (GPS)coordinates We discarded five incidents that were duplicates(ie multiple hound owners were affected during one incident)and one incident for which coordinates were corrupted We used101 hound depredations from 28 section-based and 73 GPS-based coordinates (1999ndash2008) to model spatial variation Wereserved 55 more recent depredations (2009ndash11) for modelvalidation

To discriminate high-risk from low-risk sites we compareddepredation sites to randomly chosen sites We assumed thatwolves theoretically had access to virtually all habitat typesexcept perhaps dense urban areas or deep large water bodiesthat infrequently freeze (Wydeven et al 1998 Kohn et al2009) so we excluded the Great Lakes and neighbouringstates (for which wolf data collection differed) We stipulatedthat unaffected site buffers had to be within 5 km of any 2009wolf pack which captures some inter-annual changes in packterritories while ensuring that wolves could be presentWydevenet al (2009) used 5 km as a threshold for defining extra-territorialmovements of wolves inWisconsinWe also required unaffectedbuffers to be separated from affected buffers by 475 km (size of15 radii + 025 km) with no overlap in unaffected buffers(Treves et al 2011) We randomly assigned unaffected sites toa year in the same distribution as observed for the affected sitesto calculate wolf-pack attributes for a given year for unaffectedpoints

Fritts and Paul (1989) acknowledged that some dogdepredations are not likely to be reported Thus we could runthe risk of classifying a site as unaffected when in fact it wasaffected but not reported (Alexander et al 2006) Howeverwe believe that we avoided this common pitfall because of thefollowing (1) Fritts and Paul (1989) referred to Minnesotadepredations that were not compensated and Minnesota doesnot allow hunting of bears with hounds and are likely reportedat a lower rate (Naughton-Treves et al 2003 Ruid et al 2009)(2) decades of press coverage and state outreach relating tocompensation payments for wolf depredations is likely to haveincreased reporting (3) most bear hounds are radio-collaredand therefore easily located and (4) our preliminary analysesindicated that hound depredations were significantly clusteredat multiple spatial scales and thus any unreported depredationswould likely occur relatively close to existing affected sitesMoreover we minimised the impact of misclassification inour unaffected sites by generating 225 unaffected sites forcomparison with the 101 affected sites producing anunbalanced sample Stokland et al (2011)

By using techniques to constrain unaffected sites we believethe resulting model will explain more variation and have higheraccuracy scores as suggested by Chefaoui and Lobo (2008)Furthermore because of our unaffected-site selection ourresults describe the potential distribution of risk to houndswhich would be more meaningful to managers than therealised distribution if we had not constrained unaffected sites(Chefaoui and Lobo 2008) Because our decision to limit co-occurrence among unaffected and affected sites was based onour preliminary analysis we minimised any bias associated with

restricting unaffected-site selection without prior knowledge(Stokland et al 2011)

Wolf-pack attributes were based on the prior winterrsquos territorymapping (Wydeven et al 2009) and included (1) distance togeometric centroid of the nearest wolf-pack territory (m) and(2) the nearest wolf-pack size We used 2009 wolf-pack data todetermine the maximum number of wolf packs within 5 km(WDNR considers single movements gt5 km beyond the clusterof other radio-locations to be extra-territorial movementWydeven et al 2009) 2009 had the highest number of wolfpacks with the greatest geographic spread over the study periodat the time of data collection

We measured percentage area under nine land-cover classes(National Land Cover Database 2001 30-m resolution Homeret al 2007) and used one derived measure distance to the closestforest of any type in kilometres (Treves et al 2011)We estimatedthe density of people houses and seasonal houses per squarekilometre using data from the US Census Bureau (2001) Wecalculated the density of roads (km kmndash2) and streams (km kmndash2)as in Mladenoff et al (1995 1997 2009) We estimated thedensity of livestock premises (per km2) as in Treves et al (2011)We used GIS to measure landscape data within a 3-km radiuscircular buffer (2827 km2) of each incident We chose 3 kmbecause it is an estimate of the maximum attenuation distancesof auditory cues of baying hounds in mixed forestndashopen habitats(Richards and Wiley 1980 Feddersen-Petersen 2000 Coppolaet al 2006) A buffer with an area an order of magnitude largerthan the lowest resolution of our affected sites (259 km2)reduces potential bias from limitations in precision andresolution of the source data Buffers often spanned more thanone geopolitical unit (census block county or township) sowe calculated the area-weighted average densities (ie arealaverages) from each overlapped unit (Treves et al 2011) Wecalculated an areal average for the mean and standard deviationof black-bear harvest by deer-management unit (DMU) sectionof a county (finest resolution) for 1999ndash2009 (data fromWDNReg Dhuey and Olver 2010) which we considered a proxy forbear-hunter effort We also calculated mean and standarddeviation of the density of white-tailed deer (Odocoileusvirginianus) for 1999ndash2009 by DMU which was based on theWDNR sexndashage kill population estimates for each DMU as asurrogate for prey density Last we calculated the percentageof public-access lands within the buffer We define public-access lands as federal state county and Managed ForestLaw (MFL) and Forest Crop Law (FCL) lands with publicaccess MFL and FCL are private forest lands that receive taxbreaks for sustainable forestry management and public accesssome of these lands are closed to public access and were treatedas private lands for this analysis (WDNR 2011b)

We used the stepwise modelling approach modified fromTreves et al (2011) and Murtaugh (2009) To discriminateaffected from unaffected sites we used a model selectionapproach that included two steps We first conductedunivariate logistic regressions in JMP Version 8 (SASInstitute Cary North Carolina USA) to screen and identifypotential predictors We used the following two criteria beforeconsidering a predictor for the subsequent multivariate analysis(1) univariate significance at P lt 005 and (2) lack of collinearity(|r| 07) with a stronger predictor For multivariate modelling


(second step) variables entered the model in an order ofdecreasing area under the receiver operator characteristiccurve (AUC) from univariate analysis which is a measureof discriminating ability (McPherson et al 2004 Stoklandet al 2011) We kept candidate predictors if (1) betacoefficients standard error excluded zero (2) significancewas P lt 0025 (Whittingham et al 2006) (3) Bayesianinformation criterion (DBIC) improved by two and (4) DAUCincreased by 1 Newly retained predictors in the modelhad their interactions with prior predictors tested The use of aconservative criteria such as BIC reduces over-fitting models(Burnham and Anderson 2004) If a variable did not meet eachof these criteria variables collinear with that variable thatalso passed univariate tests were then tested

We verified the final logistic model using classificationmatrices (Fielding and Bell 1997) odds-ratio evaluation(Vaughan and Ormerod 2005) phi-correlation coefficient (ndash1to 1 1 being perfect ndash1 being worse than at random Sing et al2005) and a binomial exact test to determine significance Weused multiple metrics to assess the model because each metrichas its own strengths and weaknesses and we chose to usemultiple metrics as a way to avoid the pitfalls of any onemetric and for comparison purposes with other models Weused receiver operating characteristic (ROC) information inR 2131 (R Development Core Team httpwwwRprojectorgaccessedOctober 2011) to determine the optimal predictivethreshold for the logistic model while minimising Type II error(using the ROCR Package Sing et al 2005 eg Olson et al2012)

We compared our final model with two previously publishedmodels for livestock depredations one from Wisconsin (Treveset al 2011) and one from Michigan (Edge et al 2011) todetermine whether the two types of depredation could beadequately predicted under one model and because these arethe two most recently published models for the region regardingdepredations of any kind We validated the final model againstmore recent hound depredations (2009ndash2011 n= 55)

We mapped risk of depredation across our study area usingthe best-fit logistic regression on 2011 wolf-distribution dataThe resulting map had a resolution of 30m (the resolution ofland-cover data) To examine changes in risk since 1991 wemapped risk every 5 years using that yearrsquos wolf-distributiondata but keeping land-cover variables constant We classifiedrisk using six equal intervals but excluding values lt031(effectively unaffected areas)

The previous analysis indicated that public-access landswere a predominant predictor of risk Large blocks of public-access lands are commonly used by bear hunters using houndsand represent suitable habitat for wolves (Mladenoff et al1995 1997) Therefore we repeated our modelling methods togenerate the following two additional models (1) for siteslocated on public-access lands (n= 185 83 affected and 102unaffected) and (2) for sites with 75 of their area withina 3-km radius in public access (n= 114 67 affected 47unaffected) We also compared the proportion of alldepredations (1999ndash2008) across different land-managementtypes (ie federal state county private open-access andprivate) by using chi-square tests and analysis of means forproportions

Results

Between 1999 and 2010 USDAndashWS verified 214 incidentsof wolf depredation on domestic dogs in Wisconsin Houndincidents constituted 70 of the total domestic-dog incidentsHound breeds walker plott hound redbone coonhound andbluetick coonhound were the four most frequently depredateddog breeds with frequencies of 25 23 8 and 7respectively ( of all dog depredations) Other hound breedsattacked included trigg hound mountain cur redtick coonhoundblack and tan coonhound and an unspecified coonhound breedLabrador spaniel husky and beagle breeds were the four mostfrequently depredated non-hound breeds with frequencies of6 3 2 and 2 respectively Other non-hound breedsattacked included hybrid dogs (non-hunting dogs) Germanwirehair German shorthair terrier German sheparddachshund yorkshire St Bernard labrador hybrid ShebaInu miniature doberman great dane boxer hybrid goldenretriever English hunting Chesapeake blue heeler pit bullAmerican samoyed and Gordon setter Seasonal variation indepredations revealed the influence of the hound training andblack-bear hunting seasons (Fig 3) and a significantly differenttemporal pattern between the two classes of dogs (c2 = 1191P 0001 df = 3) Hound depredations were significantlyclustered across all spatial scales whereas non-hounddepredations were slightly clustered at the 1ndash2-km scale butneither clustered nor dispersed significantly at any spatial scalegt2 km (999 confidence envelope P 0001 for both) Thusthe two classes of depredations on dogs displayed differentspatial and temporal patterns which corroborated ourclassification by dog breed Although roughly three timesmore depredations resulted in mortalities than injuries (185mortalities vs 62 injuries) injuries were significantly morecommon among the non-hound dogs (45 of incidents) thanamong the hounds (12 comparison of proportions Z= 48P 0001)

A minority of wolf packs attacked dogs (between 54and 136 of wolf packs annually using WDNR wolf-packestimates 2001ndash2010) Of those wolf packs implicated(n= 78) 52 of packs were involved in one dog depredationOnly 12 of the implicated wolf packs had five or more dogdepredations and some of those packs depredated non-hound

0

Jan

Feb Mar Apr

May Ju

n Jul

Aug Sep OctNov Dec

10

20

30

40

50

60

70

Num

ber

of d

epre

datio

ns

Other dog

Bear dog

Fig 3 Monthly variation in verified dog-depredation incidents inWisconsin from 1999 to 2010


dogs or hounds more so than expected (c2 = 279 df = 8P lt 0001)

Predicting depredation

Twenty predictors were retained for multivariate analysis(Table 1) Percentage of public-access land had the highestAUC value and met other criteria so it was the first variableincluded in the multivariate model Our methods produced asingle model (Table 2 n= 326 c2 = 149 df = 4 P lt 0001R2 = 037 no lack of fit c2 = 254 P = 0997) as follows

P ethAffectedTHORN frac141=eth1thorn e28502 37354Pubthorn 286717Devlthorn 000006167DCen 03151NPSTHORN

eth1THORNwhere Pub = percentage of public-access land within a 3-kmradius Devl= percentage of developed-land cover within a3-km radius DCen = distance to geometric centre of thenearest wolf-pack territory andNPS= the nearest wolf-pack size

By using the ROCR package we identified the thresholdbetween affected and unaffected sites as P(Affected)031This threshold also matches the probability of randomlyselecting an affected site from the total sample (031 101affected out of a total of 326) Prevalence of affected sites hasbeen used as a threshold (Stokland et al 2011) which reinforcesthe validity of our threshold Given that threshold our modeldiscriminated past sites of wolf attack on hounds (1999ndash2008)with an 84 sensitivity (85 of 101 affected sites identifiedcorrectly) 78 specificity (175 of 225 unaffected sites

identified correctly) 186 odds-ratio 058 phi-correlationcoefficient and significantly better than chance (assumingP(Affected) = 69 binomial exact P lt 0001)

The model predicted hound depredations better than didprior livestock-depredation models (Table 2) justifying theneed for a model specific to hound depredations Modelvalidation with recent data (n = 55) by using Eqn 1 identified45 (82) sites correctly as affected (P = 002) We then appliedthe model to the 2011 wolf-pack data and produced a riskmap (Fig 4)

We compared the classification errors (n= 26) to the entiredataset (n=156) Based on the information gleaned fromWildlifeServicersquos field verifier reports there was a significantly higherproportion of false negatives (24) than true positives (7df = 1 c2 = 7 P= 0008) associated with the use of hounds tohunt species other than black bears (eg coyote bobcatraccoon) This suggests that the risk map may be moreeffective for hunters hunting black bears with hounds than forhunters hunting other species with hounds Classification errorswere also more common for depredations on private lands (38for false negatives 12 for true positives) and private lands instate forestry programs (19 for false negatives 10 for truepositives df = 4 c2 = 167 P = 0002) Depredations deemedprobable wolf-related incidents by field verifiers also had agreater proportion of classification errors (19) than didconfirmed depredations (5 df = 1 c2 = 71 P= 0008) Wealso identified one classification error where a hound wasdepredated at a private residence while neither hunting nortraining (ie effectively a pet dog depredation)

In addition to the risk map based on 2011 wolf-pack data wegenerated risk maps for 1991 1996 2001 and 2006 (Fig 5)

Table 1 Significant predictors of sites of wolf attack on Hounds(Affected) in Wisconsin 1999ndash2008Black bear-harvest data are from 1999 to 2009 Hounds dogs typically used to hunt carnivores ROC receiver operating curve(discrimination power combining sensitivity and specificity) The same letters after predictors indicate collinearity (|r| gt 07)

Goodness-of-fit (c2) values are for univariate logistic regression n= 326 df = 1 Plt005 Plt001 and Plt0001

Predictor (unit) Affected (mean plusmn sd)(n= 101)

Unaffected (mean plusmn sd)(n= 225)

c2 ROC

Public-access land Pub () 079 plusmn 021 039 plusmn 033 669 83House density (per km2) de 0951 plusmn 1836 4091 plusmn 5165 309 82Human density (per km2) de 0978 plusmn 1833 6199 plusmn 9282 3157 81Developed land Devl () bd 002 plusmn 001 004 plusmn 002 4012 75Seasonal home density (per km2) e 0557 plusmn 1226 1617 plusmn 2272 1477 74Distance to geometric centre of the nearest

wolf-pack territory DCen (m)7036 plusmn 5082 14318 plusmn 14357 234 73

Nearest wolf-pack size NPS (wolves) 465 plusmn 234 318 plusmn 171 298 71Cropland () c 002 plusmn 005 008 plusmn 013 1561 70Livestock premises (per km2) c 0049 plusmn 0082 0121 plusmn 0145 1779 70Number of wolf packs within 5 km (packs) 186 plusmn 081 138 plusmn 061 2911 67Road density (km kmndash2) b 089 plusmn 043 117 plusmn 045 2342 67Bear harvest average (per km2) f 0064 plusmn 0022 0045 plusmn 0028 2432 66Bear harvest standard deviation (per km2) f 0017 plusmn 0005 0014 plusmn 0008 823 63Open water () 002 plusmn 003 005 plusmn 009 1011 62Stream density StrmD (km kmndash2) 058 plusmn 036 075 plusmn 043 1139 61Distance to forest (km) 0004 plusmn 001 004 plusmn 011 884 59Woody wetlands () a 019 plusmn 016 014 plusmn 013 785 58Deciduous forest () 050 plusmn 020 044 plusmn 021 644 58WetlandA () a 023 plusmn 017 019 plusmn 015 506 56

ACombines emergent and woody wetlands


Over the 20 year period as wolf populations increased andexpanded geographically the risk of wolf attack on a houndalso increased in extent (yet may be levelling off in more

recent years Figs 4 5) During this same time period bearharvest using hounds remained within the northern portion ofthe state and generally increased but its spatial distributionremained variable over time (E Olson unpubl data)

Public-access lands

National and county forest lands had more (51 and 53respectively) hound depredations than expected (average 31state lands 32 public-access private forestry lands 31)whereas private lands without public access (13) had fewer(c2 = 49 P lt 0001 analysis of means for proportions P lt 001)When we limited our dataset to only affected and unaffectedsites located on public-access land we developed the followingmodel (n= 185 c2 = 64 df = 3 Plt 0001 R2 = 025 no lack offit c2 = 191 P= 0275)

P ethAffectedTHORN frac14 1=eth1thorn e3898 3884Pubthorn 00000621DCen 0350NPSTHORN

eth2THORN(Pub P lt 005 NPS P lt 0001 DCen P = 0003) Thusareas on public-access land near the centre of a larger wolfpack and with a high proportion of public-access land had ahigher risk

When we limited our dataset to only affected and unaffectedsites with a high percentage (75) of public-access landwithin 3 km we developed the following model (n = 107

Table 2 Multivariate logistic regression model of risk of wolf attackon hounds in Wisconsin 1999ndash2008

Two published models of livestock depredation for the region are includedfor comparison AUC area under the receiver operating characteristic curveBIC Bayesian information criterion (lower values of BIC aremore probable)DBIC the difference in BIC relative to the final model K number ofpredictors + 1 Bold font indicates the final model Log-likelihood valuesare for logistic regression (n= 326) Plt 0001 for all models except null

no significant lack of fit

Model Log likelihood K BIC DBIC AUC

Null 202 1 409 126 50Public-access land Pub 150 2 312 29 83Pub+ developed land Devl 145 3 308 25 84Pub+Devl+ distance

to geometric centreof the nearest wolf-packterritory DCen

137 4 297 14 86

Pub+Devl+DCen+nearestwolf-pack size NPS

127 5 283 0 88

Edge et al (2011)(Michigan livestock risk)

183 4 389 106 72

Treves et al (2011)(Wisconsin livestock risk)

174 5 384 101 76

Risk 2011086ndash10

070ndash085

058ndash069

046ndash057

031ndash045

lt031 within studyarea


Fig 4 Predicted risk of wolf attack on hounds in Wisconsin (30-m resolution P(Affected)gt 031) Unaffectedpixels are grey (82 of the map) and colours indicate probability of a site being classified as affected the top two(070ndash100) middle (058ndash070) and the bottom two (031ndash058) risk-probability classes represent 6 4 and 8of the map respectively (unaffected 0ndash031 represents 82 of the map) Risk map was created using 2011 wolf-pack territories and pack sizes


c2 = 52 df = 5 P lt 0001 R2 = 0353 no lack of fit c2 = 95P = 0623)

P ethAffectedTHORN frac141=eth1thorn e124808 0554NPSthorn 00000386DCenthorn 1932StrmD 01444Deer 9686PubTHORN

eth3THORN

where StrmD = stream density and Deer= average deer density(P lt 005 for all except Dcen which was retained but wasinsignificant)

Discussion

All risk maps should be taken within the context in which theywere developed (Venette et al 2010) Our risk maps representthe probability of a reported incident being classified as a hounddepredation as a function of certain measurable variablesavailable to us We assume that this probability is directlyrelated to the actual risk of depredation and hence thevariation in probability is assumed to be an index of variationin real risk but not the absolute probability of a hounddepredation In other words our risk map can help hunters andmanagers identify which areas may be more risky than others

1991 1996

20062001

Risk086ndash10

070ndash085058ndash069

046ndash057031ndash045lt031 within studyarea


Fig 5 Changes in the predicted risk of wolf attack on hounds in Wisconsin from 1991 to 2006 using Eqn 1 and wolf-pack territory and pack size for eachrespective year (30-m resolution P(affected)gt 031) Unaffected pixels are grey (95 92 88 and 83 of the map for 1991 1996 2001 and 2006respectively) and colours indicate probability of a site being affected


but it does not provide them with the probability of a hounddepredation occurring at that location Thus we recommendthat managers and hunters focus on the relative variation inrisk across the map for guiding landscape-scale decisions

Our models performed well and were significantly betterthan random at predicting future depredations on houndsValidating the model by using more recent data also allowedus to ensure that the model was predictive on external datawhich addresses some of the concerns associated withstepwise regression (Seoane et al 2005)

The positive relationship with the percentage of public-accessland within 3 km (Pub) is understandable because bear hunterstend to use large contiguous blocks of public-access lands torelease their hounds (Dhuey and Kitchell 2006) because bearsand hounds will roam widely during pursuit and bear huntersare likely to want to avoid trespassing on private landsHowever when we restricted the analysis to affected andunaffected locations on or surrounded by a high proportion ofpublic-access land the area of public-access lands remained asignificant predictor We expected the effect of the percentage ofpublic-access lands to lessen in areas already largely dominatedby public-access lands This unexpected result suggests thatlarger more contiguous blocks of public land are risky forhounds likely owing to hound hunters attempting to avoidprivate lands or because such lands could support larger wolfpacks Alternatively reporting rates on private lands could belower if hound owners are trespassing

We observed a negative association between P(Affected) andthe distance to the nearest wolf pack which was also found byTreves et al (2011) for livestock depredations in WisconsinMladenoff et al (1995 2009) found that the density of roadswas the predominant predictor of wolf-pack presence inWisconsin In our analysis road density positively correlatedwith percentage developed land within 3 km thus we suspectthat the significance of percentage developed land in the modelreflects wolf-habitat suitability Alternatively bear hunters couldbe purposefully selecting for areas with less human developmentbut in private ownership

Wydeven et al (2004) reported that larger wolf packs weremore often involved in hound depredations than were smallerpacks Our research supports that finding (Table 2) InWisconsin the areas with the highest risk of attacks to houndsalso represent core habitat areas for wolves (Mladenoff et al1995 2009) such habitat may support packs with higher pupproduction and survival Larger packs involved in houndattacks may also be a manifestation of canid competition withlarger groups more likely to attack smaller canid groups(Merkle et al 2009) Bear hunters who use hounds couldpotentially avoid hunting in areas with wolf packs of four ormore wolves (Wydeven et al 2004)

In 2010 the WDNR instituted an email warning system withmaps displaying 12ndash16-km buffers around sites of recenthound depredations to enable bear hunters to avoid thoseareas (httpdnrwigovtopicwildlifehabitatwolfmapshtmltabx2 accessed October 2012) In regard to livestockKarlsson and Johansson (2010) suggested that farmspreviously depredated are at a 55 times higher risk forsubsequent depredation Wydeven et al (2004) reported thatin Wisconsin repeat incidents of dog depredation are even

more predictable than with livestock This and the results ofour spatial analysis of hound depredations (ie significantclustering of hound depredations across multiple spatial scales)support the creation and avoidance of caution areas and riskmaps (Fig 4) Additionally bear hunters could take moreproactive measures when running hounds in areas of high risksuch as deterrent devices or closer supervision of their houndsbecause wolves tend to avoid humans (Karlsson et al 2007)To support that step we need additional research on non-lethaltechniques to prevent attacks or mortalities on hounds andother hunting dogs (eg protection collars McManus et al2014) However whereas the intent of warning systems andrisk maps is to enable hunters who use hounds to avoid riskyareas compensation schemes (up to US$2500 houndndash1) couldencourage hunters to engage in more risky behaviour

When we considered only sites with a high proportion(75) of public-access lands both stream density andaverage deer density predicted risk suggesting that houndsrunning in areas with a lower stream and a higher deer densityface greater risk Mladenoff et al (1997) found that deer densitywas positively correlated with wolf density and negatively withwolf-pack territory size Perhaps wolves are more likely todefend a territory with a high prey density however wecannot rule out that more bears use such areas or houndbehaviour changes in such areas Also if wolf packs withhigher deer densities have smaller territories (Mladenoff et al1997) then the probability of encountering a wolf within theterritory would be likely to increase suggesting that wolf packswith large territories are less likely to encounter and attackhounds Alternatively when wolves prey on dogs as a foodsource low prey availability may be a factor in increased dogattacks (Butler et al 2013) whereas when predation is mainlydue to interference competition as occurs in Wisconsin preyavailability is apparently less of a factor The interactionsamong humans wolves and deer are highly complex anddifficult to interpret with much certainty Thus we urge futureresearchers to investigate the role of prey density experimentallyin wolfndashhuman conflicts We found a negative relationshipwith stream density which is somewhat counter to whatwould be expected because streams provide habitat for beaversCastor canadensis an important food item for wolves inWisconsin (Mandernack 1983) Reduced risk in areas with ahigher stream density may be due to higher levels of humandevelopments that tend to occur on waterways or perhaps highstream density reduces the abilities of hounds to chase bearsand thus reduces encounters with wolves Assuming landscapefeatures and other predictors had not changed dramatically weexamined how risk may have changed over time as the wolfpopulation and distribution increased and we observed ashifting and expanding area of risk as wolves recolonised thestate (Figs 4 5) It appears that between 2001 and 2011 wolvesestablished packs on most large blocks of public-access landswithin our study area which suggests that the percentage ofarea at risk for hound depredation has begun to level off Thuswe suspect that the extent of the area of risk for hounds withinour study area will not increase dramatically (unless changesin bear-hunting and training regulations or wolf managementoccur) Newly colonised areas are likely to be more marginalwolf habitat and thus support smaller packs and contain less


public lands for hunting with hounds However as wolf-packsizes and land uses change over time we might see changes inthe level of risk within that extent

These techniques can be used to assess the relative risk forother-pursuit hounds (eg moose- hare- or boar-huntinghounds) however quarry dog and wolf behaviour as well ashunter technique will likely vary with quarry land coverdevelopment density and other factors Thus we suggest thatfuture researchers examine the spatial and temporal patterns ofrisk for other types of hunting dogs to provide a foundationfor comparison

Wolf hunting with dogs

Our findings may also apply to the controversial hunting ofwolves using dogs in Wisconsin In April 2012 the Governorof Wisconsin signed legislation which mandated that Wisconsinwould be thefirst state in theUSA in recent times to allowhuntingof wolves using dogs In 2013 35 wolves were harvested usinghounds in Wisconsin (D MacFarland pers comm) Lescureuxand Linnell (2014) suggested that in some cases hunting largecarnivores with dogs can helpmitigate conflicts between humansand wolves We have demonstrated that wolves represent animportant aspect of risk faced by bear-hunting hounds Huntingbears with hounds increases the number of dogs attacked bywolves (eg Fig 3) and our review of a subset of depredationverification reports suggests that these incidents were provoked(vs unprovoked Quigley and Herrero 2005) in the sense thatdogs were actively entering wolf territories and would havebeen perceived by the wolves as competitors (Butler et al2013) Depredations on other domestic animals (petslivestock) are likely to be independent of depredations on dogsused for hunting carnivores and are more likely to be associatedwith predation versus competitive killing (Butler et al 2013)Thus counter to Lescureux and Linnell (2014) hunting withpursuit dogs is likely to have an additive effect to wolfndashhumanconflicts (ie increasing the number of wolfndashhuman conflicts ina given year)

Keeping risk in perspective

Between 1999 and 2011 a total of 157 incidents of depredationson hounds (including those depredated during training) wasverified whereas roughly 13 150 bears were harvested usinghounds Summarising this pooled data there was roughly oneincident of hound depredation for every 84 black bearsharvested using hounds Because hounds are typicallydeployed multiple times (eg hound training and unsuccessfulhunts) prior to a successful harvest this is a conservative indexof the real risk to hounds but does put risk into perspectiveAdditionally our research only reflects one of many risk factorsfor hounds From conversations with hunters and veterinariansmany hounds are also injured or killed by bears There are noformal reporting systems on these other risk factors so the fullextent and distribution of these risks is not well known Futureresearch could examine other risk factors facing hounds to putwolf attacks in perspective Last our research focused on thelandscape scale however fine-scale and behavioural factors arelikely to be just as useful in predicting risk of attack andhunters and managers should not disregard local indicators of

risk (eg fresh wolf tracks site of repeated or recent depredationwolf-pack rendezvous sites behaviour of hounds) For examplethere is early evidence that bear baiting attracts both wolvesand bears to bait sites (Palacios and Mech 2011 L Hill perscomm E Olson pers obs) and it has been suggested thatthe length of the bear baiting season in Wisconsin (15 April toearly October) also increases the likelihood of encounterbetween wolves and hounds (Bump et al 2013) which seemslikely because a majority of hound depredations occur duringthe hound-training season in Wisconsin Thus reducing thelength of the baiting season as in Michigan (where baitingbegins in mid-August) may be a way to reduce wolfndashhoundconflicts

Compensation and risk

Dorrance (1983 322) proposed that lands lsquoshould be classifiedinto areas with a low or high probability of wildlife depredation[conflict]rsquo which can then be used to determine the propermanagement response Here we have documented thathunting with hounds can extend humanndashwildlife conflict ontopublic lands Although we generally agree with Dorrance (1983)that the location of a depredation should influence the policyresponse it is not clear under the public-trust doctrine (Smith2011) what the appropriate response should be by wildlifeagencies under these circumstances Managers shouldapproach depredations differently on public lands versusprivate lands especially recreational activity in whichdomestic animals are voluntarily placed at risk Bruskotteret al (2011) discussed the responsibility of the government tomanage wildlife under the public-trust doctrine similarlyDorrance (1983 323) wrote lsquowildlife is a legitimate resourceon public lands and users must accept the possibility of wildlifeconflictsrsquo In Wisconsin higher-risk areas for wolf attacks onhounds also coincide with core wolf habitat (Fig 4 Mladenoffet al 1995 2009) and management applied to wolvesattacking livestock on private land (Ruid et al 2009) may notbe appropriate in these core habitat areas As Dorrance (1983)suggested this means establishing a more realistic set ofexpectations when wildlife damage to property occurs withinpublic lands

Wisconsin state statutes currently require compensation forhounds attacked by wolves as long as the hounds are not usedfor hunting or training on wolves However indemnification islikely to remove incentives for hunters tomove from traditional orpreferred hunting grounds to avoid high-risk areas If managerschoose or are required to provide compensation for houndsattacked by wolves while hunting on public lands managersshould consider weighting compensation payments based on therisk level at the point of depredation (Dorrance 1983) Areas thatare known to be risky could have reduced compensationpayments whereas areas of low risk could remain stablewhich would provide an incentive for hunters to avoid riskyareas This could be done by applying the followingcompensation-adjustment equation

Cadj frac14 eth1 PethAffectedTHORNTHORN C

where Cadj= the adjusted compensation payment C= the apriori estimated compensation payment and P(Affected) = the


relative probability of being affected which could be extractedfrom the riskmapbyusing theGPScoordinates of thedepredationincident or could be calculated using the model equationpresented earlier (Eqn 1) Risk-weighted compensation mightreinforce avoidance of risky areas which might minimise futuredepredations and remove incentives for risky behaviours ndash

essential elements of a sound compensation scheme (Dorrance1983)

As part of the bill establishing the wolf as a game species inWisconsin compensation for hounds attacked by wolves will befunded through license and permit fees associated with thewolf harvest In addition compensation would receive fundingpriority over other wolf management-related activities thusreducing funding for both compensation payments and wolfmanagement The rules regarding compensation payments ofmissing calves for livestock producers have already beenadjusted to deal with the reduced funds available howevercompensation for hounds typically the most costly perindividual depredated has not been adjusted Reducing thecompensation payment for depredated hounds in areas of highrisk could shift stakeholder activity to less risky areas or shiftgreater responsibility onto owners who choose to hunt withdogs in risky areas Agencies that choose or are required topay for depredations on hunting dogs should consideradjusting payments based on landscape risk factors (Dorrance1983)

Conclusions

Risk of hound depredation had a distinctive temporal and spatialsignature with the peak risk occurring during the black-bearhound-training and -hunting seasons and in areas closer to thecentre of wolf-pack territories with larger wolf packs and morepublic-access land and less developed land Risk maps providevisual representations of risk that can help stakeholders andmanagers develop management policies that are adaptive andsensitive to spatiotemporal patterns of risk Although relativelyrare mitigating incidents of wolf attack on hunting dogs arecritical for the long-term conservation of wolves (Butler et al2013) especially in Wisconsin and Fennoscandia (Lescureuxand Linnell 2014) We urge hunters to attempt to avoid riskyareas or take added precautions in these areasWe propose a risk-weighted compensation scheme designed to reduce incentivesfor risky behaviour and minimise future conflict We suggestthat wolf attacks on hunting dogs are most likely to be the resultof competitive killing (vs predatory killing) and appear to havean additive effect on the number of wolfndashhuman conflicts (ieadditional source of conflict) In Wisconsin as in many otherstates and countries wolves are now a part of the landscape andwith this comes responsibility for both the government (underthe public-trust doctrine) and the private individual to mitigateconflicts with wolves

Acknowledgements

We thank USDAndashWS wildlife specialists that investigated wolfdepredations We also thank C Ane K Martin and the Land InformationComputer Graphics Facility at UWndashMadison B Dhuey J WiedenhoeftD MacFarland and R Jurewicz of the WDNR We thank T Van Deelen forproviding a thorough review of earlier versions of this manuscript Thisresearch was funded principally by a NSFndashIGERT CHANGE Fellowship

to ERO and supported by the Nelson Institute for Environmental Studiesand the Derse Foundation

References

Alexander SM Logan T B and Paquet P C (2006) Spatio-temporal co-occurrence of cougars (Felis concolor) wolves (Canis lupus) and theirprey during winter a comparison of two analytical methods Journal ofBiogeography 33 2001ndash2012 doi101111j1365-2699200601564x

Backeryd J (2007) lsquoWolf Attacks on Dogs in Scandinavia 1995ndash2005WillWolves in Scandinavia Go Extinct if Dog Owners Are Allowed to Killa Wolf Attacking a Dog Nr 175rsquo (Sveriges Lantbruks UniversitetUppsala Sweden)

Berger L L Stacey P B Bellis L and Johnson M P (2001)A mammalian predatorndashprey imbalance grizzly bear and wolfextinction affect avian neotropical migrants Ecological Applications11 947ndash960

Bisi J Liukkonen T Mykra S Pohja-Mykra M and Kurki S (2010)The good bad wolfndashwolf evaluation reveals the roots of the Finnishwolf conflict European Journal of Wildlife Research 56 771ndash779doi101007s10344-010-0374-0

Bruskotter J T Enzler S A and Treves A (2011) Rescuing wolves frompolitics wildlife as a public trust resource Science 333 1828ndash1829doi101126science1207803

Bump JKMurawski CMKartano LMBeyerD E Jr andRoell B J(2013) Bear-baiting may exacerbate wolf-hunting dog conflict PLoSONE 8 e61708 doi101371journalpone0061708

Burnham K P and Anderson D R (2004) Multimodel inferenceunderstanding AIC and BIC in model selection Sociological Methodsamp Research 33 261ndash304 doi1011770049124104268644

Butler J RA Linnell J D CMorrant D AthreyaV LescureuxN andMcKeown A (2013) Dog eat dog cat eat dog social-ecologicaldimensions of dog predation by wild carnivores In lsquoFree-RangingDogs and Wildlife Conservationrsquo (Ed M E Gompper) pp 117ndash143(Oxford University Press Oxford UK)

Chadwick D H (2010) Wolf wars National Geographic 217 34ndash55Chefaoui R M and Lobo J M (2008) Assessing the effects of pseudo-

absences on predictive distribution model performance EcologicalModelling 210 478ndash486 doi101016jecolmodel200708010

Chitwood M C Peterson M N and Deperno C S (2011) Assessing doghunter identity in coastal North Carolina Human Dimensions of Wildlife16 128ndash141 doi101080108712092011551448

Coppola C L Enns R M and Grandin T (2006) Noise in the animalshelter environment building design and the effects of daily noiseexposure Journal of Applied Animal Welfare Science 9 1ndash7doi101207s15327604jaws0901_1

Cummins J (2001) lsquoThe Hound and the Hawk the Art of MedievalHuntingrsquo (St Martinrsquos Press New York New York USA)

Dhuey B and Kitchell J (2006) lsquoBlack Bear Hunter Questionnairersquo(Wisconsin Department of Natural Resources Madison WI)

Dhuey B and Olver L (2010) Wisconsin black bear harvest reportWisconsin Department of Natural Resources Madison WI

Dorrance M J (1983) A philosophy of problem wildlife managementWildlife Society Bulletin 11 319ndash324

Edge J L Beyer D E Jr Belant J L JordanM J and Roell B J (2011)Adapting a predictive spatial model for wolf Canis spp predation onlivestock in the Upper Peninsula Michigan USA Wildlife Biology 171ndash10 doi10298110-043

Feddersen-Petersen D U (2000) Vocalization of European wolves (Canislupus lupus L) and various dog breeds (Canis lupus ffam) Archiv FuumlrTierzucht Archives of Animal Breeding 43 387ndash397

FieldingAH andBell J F (1997) A review ofmethods for the assessmentof prediction errors in conservation presenceabsence modelsEnvironmental Conservation 24 38ndash49 doi101017S0376892997000088


Fritts S H and Paul W J (1989) Interactions of wolves and dogs inMinnesota Wildlife Society Bulletin 17 121ndash123

Homer C Dewitz J Fry J Coan M Hossain N Larson C Herold NMcKerrow A VanDriel J N and Wickham J (2007) Completionof the 2001 National Land Cover Database for the conterminousUnited States Photogrammetric Engineering and Remote Sensing 73337ndash341

Ikeya K (1994) Hunting with dogs among the San in the central KalahariAfrican Study Monographs 15 119ndash134

Karlsson J and Johansson O (2010) Predictability of repeated carnivoreattacks on livestock favours reactive use of mitigation measures Journalof Applied Ecology 47 166ndash171 doi101111j1365-2664200901747x

Karlsson J ErikssonM and Liberg O (2007) At what distance do wolvesmove away from an approaching human Canadian Journal of Zoology85 1193ndash1197 doi101139Z07-099

Kohn B E Anderson E M and Thiel R P (2009) Wolves roads andhighway development In lsquoRecovery of Gray Wolves in the Great LakesRegion of the United States an Endangered Species Success Storyrsquo (EdsAPWydevenTRVanDeelenandE JHeske) pp 217ndash232 (SpringerNew York)

Kojola I and Kuittinen J (2002) Wolf attacks on dogs in FinlandWildlifeSociety Bulletin 30 498ndash501

Kojola I Ronkainen S Hakala A Heikkinen S and Kokko S (2004)Interactions between wolves Canis lupus and dogs C familiaris inFinland Wildlife Biology 10 101ndash105

Koster J M (2008) Hunting with dogs in Nicaragua an optimal foragingapproach Current Anthropology 49 935ndash944 doi101086592021

Larson G Karlsson E K Perri AWebsterM T Ho S YW Peters JStahl P W Piper P J Lingaas F Fredholm M Comstock K EModiano J F Schelling C Agoulnik A I Leegwater P A DobneyK Vigne J-D Vila C Andersson L and Lindblad-Toh K (2012)Rethinking dog domestication by integrating genetics archaeology andbiogeography Proceedings of the National Academy of Sciences USA109 8878ndash8883

Lescureux N and Linnell J D C (2014) Warring brothers the complexinteractions between wolves (Canis lupus) and dogs (Canis familiaris)in a conservation context Biological Conservation 171 232ndash245doi101016jbiocon201401032

Liberg O Chapron G Wabakken P Pedersen H C Hobbs N T andSand H (2011) Shoot shovel and shut up cryptic poaching slowsrestoration of a large carnivore in Europe Proceedings of the RoyalSociety B 279 910ndash915

MandernackBA (1983) Foodhabits ofwolves inWisconsinMScThesisUniversity of Wisconsin Eau Claire Eau Claire WI

McManus J S Dickman A J Gaynor D Smuts D H and MacDonaldD W (2014) Dead or alive Comparing costs and benefits of lethaland non-lethal human-wildlife conflict mitigation on livestock farmsOryx doi101017S0030605313001610

McPherson J A Jetz W and Rogers D J (2004) The effects of speciesrsquorange size on the accuracy of distribution models ecologicalphenomenon or statistical artifact Journal of Applied Ecology 41811ndash823 doi101111j0021-8901200400943x

Merkle J A Stahler D R and Smith D W (2009) Interferencecompetition between gray wolves and coyotes in Yellowstone NationalPark Canadian Journal of Zoology 87 56ndash63 doi101139Z08-136

Mladenoff D J Sickley T A Haight R G and Wydeven A P (1995)A regional landscape analysis and prediction of favorable gray wolfhabitat in the northern Great-Lakes Region Conservation Biology 9279ndash294 doi101046j1523-173919959020279x

Mladenoff D J Haight R G Sickley T A and Wydeven A P (1997)Causes and implications of species restoration in altered ecosystemsBioscience 47 21ndash31 doi1023071313003

Mladenoff D J Sickley T A and Wydeven A P (1999) Predictinggray wolf landscape recolonization logictic regression models vs new

field data Ecological Applications 9 37ndash44 doi1018901051-0761(1999)009[0037PGWLRL]20CO2

Mladenoff D J Clayton M K Pratt S D Sickley T A and WydevenA P (2009) Change in occupied wolf habitat in the NorthernGreat Lakes region In lsquoRecovery of Gray Wolves in the Great LakesRegion of the United States an Endangered Species Success Storyrsquo(Eds A P Wydeven T R Van Deelen and E J Heske) pp 119ndash138(Springer New York)

Murtaugh P A (2009) Performance of several variable-selection methodsapplied to real ecological data Ecology Letters 12 1061ndash1068doi101111j1461-0248200901361x

Naughton-Treves L Grossberg R and Treves A (2003) Paying fortolerance rural citizensrsquo attitudes toward wolf depredation andcompensation Conservation Biology 17 1500ndash1511 doi101111j1523-1739200300060x

Olson E R Ventura S J and Zedler J B (2012) Merging geospatialand field data to predict the distribution and abundance of an exoticmacrophyte in a large Wisconsin reservoir Aquatic Botany 96 31ndash41doi101016jaquabot201109007

Olson E R Stenglein J L Shelley V RissmanA R Browne-Nunez CVoyles Z Wydeven A P and Van Deelen T (2014) Pendulumswings in wolf management led to conflict illegal kills and alegislated wolf hunt Conservation Letters doi101111conl12141

Palacios V and Mech D (2011) Problems with studying wolf predationon small prey in summer via global positioning system collarsEuropean Journal of Wildlife Research 57 149ndash156 doi101007s10344-010-0408-7

Peyton B (1989) A profile of Michigan bear hunters and bear huntingissues Wildlife Society Bulletin 17 463ndash470

Quigley H and Herrero S (2005) Characterization and preventionof attacks on humans In lsquoPeople and Wildlife Conflict andCoexistencersquo (Eds R Woodroffe S Thirgood and A Rabinowitz)pp 27ndash48 (Cambridge University Press Cambridge UK)

Richards D G and Wiley R H (1980) Reverberations and amplitudefluctuations in the propagation of sound in a forest implications foranimal communicationAmericanNaturalist 115 381ndash399 doi101086283568

Ripple W J Estes J A Beschta R L Wilmers C C Ritchie E GHebblewhite M Berger J Elmhagen B Letnic M Nelson M PSchmitz O J Smith D W Wallach A D and Wirsing A J (2014)Status and ecological effects of the worldrsquos largest carnivores Science343 doi101126science1241484

Roosevelt T (1902) lsquoHunting the Grisly and Other Sketches an Accountof the Big Game of the United States and its Chase with Horse Houndand Riflersquo Available at httpwwwreadcentralcombookTheodore-RooseveltRead-Hunting-the-Grisly-and-Other-Sketches-Online [Accessed10 October 2011]

Ruid D B Paul W J Roell B J Wydeven A P Willging R CJurewicz R L and Lonsway D H (2009) Wolfndashhuman conflictsand management in Minnesota Wisconsin and Michigan InlsquoRecovery of Gray Wolves in the Great Lakes Region of theUnited States an Endangered Species Success Storyrsquo (EdsA P Wydeven T R Van Deelen and E J Heske) pp 279ndash295(Springer New York)

Seoane J Bustamante J and Diacuteaz-Delgado R (2005) Effect of expertopinion on the predictive ability of environmental models of birddistribution Conservation Biology 19 512ndash522 doi101111j1523-1739200500364x

Sing T Sander O Beerenwinkel N and Lengauer T (2005) ROCRvisualizing classifier performance in R Bioinformatics 21 3940ndash3941doi101093bioinformaticsbti623

Smith C A (2011) The role of state wildlife professionals under the publictrust doctrine The Journal of Wildlife Management 75 1539ndash1543doi101002jwmg202


Stokland J N Halvorsen R and Stoa B (2011) Species distributionmodeling effect of design and sample size of pseudo-absenceobservations Ecological Modelling 222 1800ndash1809 doi101016jecolmodel201102025

Terborgh J and Estes J A (2010) lsquoTrophic Cascades Predators Preyand the Changing Dynamics of Naturersquo (Island Press Washington DC)

Treves A and Bruskotter J (2014) Tolerance for predatory wildlifeScience 344 476ndash477 doi101126science1252690

Treves A and Martin K A (2011) Hunters as stewards of wolves inWisconsin and the northern Rocky Mountains USA Society amp NaturalResources 24 984ndash994 doi101080089419202011559654

TrevesA JurewiczRRNaughton-TrevesLRoseRAWillgingRCand Wydeven A P (2002) Wolf depredation on domestic animals inWisconsin 1976-2000 Wildlife Society Bulletin 30 231ndash241

Treves A Jurewicz R R Naughton-Treves L andWilcove D S (2009)The price of tolerancewolf damage payments after recoveryBiodiversityand Conservation 18 4003ndash4021 doi101007s10531-009-9695-2

Treves A Martin K A Wydeven A P and Wiedenhoeft J E (2011)Forecasting environmental hazards and the application of risk maps topredator attacks on livestock Bioscience 61 451ndash458 doi101525bio20116167

Treves A Naughton-Treves L and Shelley V (2013) Longitudinalanalysis of attitudes toward wolves Conservation Biology doi101111cobi12009

US Census Bureau (2001) lsquoIntroduction to Census 2000 Data ProductsMSO01-ICDPrsquo (US Department of Commerce Economics andStatistics Administration)

Vaughan I P and Ormerod S J (2005) The continuing challenges oftesting species distribution models Journal of Applied Ecology 42720ndash730 doi101111j1365-2664200501052x

Venette R C Kriticos D J Magarey R D Koch F H Baker R H AWorner S PRaboteauxNNGMcKenneyDWDobesberger E JYemshavnov D de Barro P J HutchinsonW D Fowler G KalarisT M and Pedlar J (2010) Pest risk maps for invasive alien speciesa roadmap for improvement Bioscience 60 349ndash362 doi101525bio20106055

Whittingham M J Stephens P A Bradbury R B and Freckleton R P(2006) Why do we still use stepwise modeling in ecology and behaviorJournal of Animal Ecology 75 1182ndash1189 doi101111j1365-2656200601141x

WDNR (Wisconsin Department of Natural Resources) (2011a) lsquoDogTraining Backtags and More Changing for Wisconsin Bear HuntersrsquoAvailable at httpdnrwigovnewsdnrnews_article_lookupaspid=1826 [Accessed 10 October 2011]

WDNR (Wisconsin Department of Natural Resources) (2011b) lsquoForestTax Lawsrsquo Available at httpdnrwigovforestryftax[Accessed 10October 2011]

Woodroffe R and Ginsberg J R (1998) Edge effects and the extinctionof populations inside protected areas Science 280 2126ndash2128doi101126science28053722126

Wydeven A P Fuller T K Weber W and MacDonald K (1998) Thepotential for wolf recovery in the northeastern United States via dispersalfrom southeastern Canada Wildlife Society Bulletin 26 776ndash784

Wydeven A P Treves A Brost B and Wiedenhoeft J E (2004)Characteristics of wolf packs in Wisconsin identification of traitsinfluencing depredation In lsquoPeople and Predators from Conflict toCoexistencersquo (Eds N Fascione A Delach and M E Smith)pp 28ndash50 (Island Press Washington DC)

Wydeven A P Wiedenhoeft J E Schultz R N Thiel R P JurewiczR L Kohn B E and Van Deelen T R (2009) History populationgrowth and management of wolves in Wisconsin In lsquoRecovery of GrayWolves in the Great Lakes Region of the United States an EndangeredSpecies Success Storyrsquo (Eds A P Wydeven T R Van Deelen andE J Heske) pp 87ndash105 (Springer New York)

Wydeven A PWiedenhoeft J E Schultz R N Thiel R P Bruner J EBoles S R and Windsor M A (2011) Status of the timber wolfin Wisconsin performance report 1 July 2010 through 30 June 2011Wisconsin Endangered Resources report 140Wisconsin Department ofNatural Resources Madison WI


wwwpublishcsiroaujournalswr

comprehension of management challenges at a landscape scale(Venette et al 2010 Treves et al 2011) We present a spatialanalysis of wolf attacks on dogs used for hunting large carnivoresin Wisconsin (1999ndash2011)

Domestic dogs have associated with humans for at least15 000 years (Larson et al 2012) and hunters have long useddogs to find and pursue their quarry (Cummin 2001) Across theworld many predators have been or are being hunted with theaid of dogs (eg jackals (Canis spp) coyotes (Canis latrans)wolves (Canis lycaon amp C lupus) bobcats (Lynx rufus) bears(Ursus spp) pumas (Puma concolor) and foxes (Vulpes andUrocyon spp)) In some cultures hunting with dogs contributesto community identity (Chitwood et al 2011) yet some view itas unethical or as incompatible with other hunting methods(Peyton 1989)

Use of dogs for hunting is not without risks multiple dogsmay be injured or killed during the pursuit Globally most dogskilled by wolves are pursuit dogs used for recreational hunting(47ndash87 see Butler et al 2013 corrected for gt53 in FinlandKojola and Kuittinen 2002) In Nicaragua jaguars (Pantheraonca) are known for attacking hunting dogs (Koster 2008) andin Botswana hunting dogs have been killed by lions (Pantheraleo) and foxes (Ikeya 1994) In Europe and the United Stateswolves have attacked dogs Kojola and Kuittinen (2002)reported 43 wolf attacks on dogs in Finland (1996ndash99) andmost of those attacks (54) were associated with dogs usedfor hunting Backeryd (2007) reported 117 hunting dogsattacked by wolves in Sweden and Norway (1995ndash2005) Ruidet al (2009) reported that more than 474 dogs were attackedby wolves in the Great Lakes region of the United States(1974ndash2006) The risk to dogs used in hunting is not arelatively recent phenomenon (Roosevelt 1902) and may varyon the basis of the distance dogs range from their owners orwith dog behaviour (eg baying) or body size (Kojola andKuittinen 2002 Backeryd 2007) In Wisconsin Wydevenet al (2004) demonstrated that the risk varied with a wolfpackrsquos size and history of attacking dogs used for huntingblack bear (Ursus americanus) Similarly Kojola et al (2004)documented that 76 of dog attacks occurred within one wolf-pack territory suggesting that a specific pack could becomehabituated to attacking dogs (see also Kojola and Kuittinen2002) Many researchers have also found that wolf attacks ondogs increase in areas with or during periods of low preydensity (Butler et al 2013)

Negative interactions between wolves and pursuit huntingdogs have been considered a driver of negative attitudes towardwolf conservation (Lescureux and Linnell 2014) Increases innegative attitudes can lead to illegal killing of wolves (Olsonet al 2014 Treves and Bruskotter 2014) or increased supportfor lethal management options or more liberal wolf harvests(Treves et al 2013 Lescureux and Linnell 2014) Thusmitigating wolf attacks on hunting dogs could enhance localsupport of wolf conservation

Currently in the USA black bears can be hunted with dogsin 18 states including Wisconsin In Wisconsin wolves haveattacked dogs during hunting or training seasons since 1985(Treves et al 2002 2009 Wydeven et al 2004 Ruid et al2009) These authors found that verified wolf complaintsgenerally increased from 1976 to 2006 as wolf population and

distribution increased (eg Olson et al 2014) Compensationto property owners for loss of domestic animals also increasedduring this time period (Ruid et al 2009 Treves et al 2009)Wisconsin statutesmandate compensation for wolf depredationsincluding wolf attacks on dogs (hereafter hounds) used forhunting large carnivores (mainly black bears) Depredations onhounds are the second-most common type of wolf damage in thestate and typically the most costly per individual (capped at US$2500 houndndash1 Treves et al 2009) Moreover in Wisconsincompensation for hound depredations accounted for about 37of approximately US$1million total paid in compensationprograms for wolfndashhuman conflicts (1986ndash2010) Thereforedonors to the statersquos compensation fund domestic animalowners those concerned with hound and wolf welfare andother taxpayers have a shared interest in diminishing wolfattacks on hounds

Our goal was to estimate spatial patterns of risk for hunterswho use hounds in Wisconsinrsquos wolf range We first comparedvariables differentiating between hound depredations anddepredations on non-hounds (eg pets bird-hunting dogs) toidentify possible differences between the two types of dogsattacked Second to support efforts to predict and preventwolf attacks on hounds we constructed a spatial predictivemodel and examined how risk may have changed over timeLast we evaluated the role of public access lands in hounddepredations We propose mitigation methods for hunterswho use hounds as well as for managers of wolves seeking tobalance wolf conservation with the needs of people living nearthem

Materials and methodsStudy area

Our study area (111 000 km2) represented about three-quartersof the state of Wisconsin (Fig 1) and was within 75 km fromevery known wolf-pack territory in 2009 (Wydeven et al 2009)We used a 75-km buffer because this distance was 25-km greaterthan the maximum distance any dog depredation had beenreported from a known wolf-pack territory in Wisconsin forthe study period The Wisconsin Department of NaturalResources (WDNR) delineated wolf-pack territories using acombination of aerial telemetry snow-track surveys and publicobservations using the techniques described in Wydeven et al(2009) The study area comprised temperate forests interspersedwith wetlands water bodies agricultural land and open areas(Mladenoff et al 1997) Bear hunting with hounds wasrestricted to the northern one-third of the state and opened for4 weeks from early September through early October (WDNR2011a Fig 2) The state-wide training season for hounds wasopen from 1 July to 31 August (WDNR 2011a Fig 2) Huntersused hounds for 13ndash37 of the total bears harvested(1999ndash2010) Hound hunting and training typically occurredon large blocks of public access land (ie land that is openaccess for the general public Dhuey and Kitchell 2006)Public-access lands represented between 38 and 49 of theland base open to bear hunting with hounds (Fig 2)

Wolf populations in Wisconsin have grown steadily sincethe mid-1990rsquos (Wydeven et al 2009) and have begun toestablish in areas with a greater potential for human conflict



Hound depredations






Study area











Study area

















Results



0

Jan

Feb Mar Apr

May Ju

n Jul

Aug Sep OctNov Dec

10

20

30

40

50

60

70

Num

ber

of d

epre

datio

ns

Other dog

Bear dog

















c2 ROC








Public-access lands











137 4 297 14 86


127 5 283 0 88


183 4 389 106 72


174 5 384 101 76

Risk 2011086ndash10

070ndash085

058ndash069

046ndash057

031ndash045







eth3THORN


Discussion


1991 1996

20062001

Risk086ndash10































Conclusions


Acknowledgements



References















































































Hound depredations






Study area











Study area

















Results



0

Jan

Feb Mar Apr

May Ju

n Jul

Aug Sep OctNov Dec

10

20

30

40

50

60

70

Num

ber

of d

epre

datio

ns

Other dog

Bear dog

















c2 ROC








Public-access lands











137 4 297 14 86


127 5 283 0 88


183 4 389 106 72


174 5 384 101 76

Risk 2011086ndash10

070ndash085

058ndash069

046ndash057

031ndash045







eth3THORN


Discussion


1991 1996

20062001

Risk086ndash10































Conclusions


Acknowledgements



References





















































































Study area

















Results



0

Jan

Feb Mar Apr

May Ju

n Jul

Aug Sep OctNov Dec

10

20

30

40

50

60

70

Num

ber

of d

epre

datio

ns

Other dog

Bear dog

















c2 ROC








Public-access lands











137 4 297 14 86


127 5 283 0 88


183 4 389 106 72


174 5 384 101 76

Risk 2011086ndash10

070ndash085

058ndash069

046ndash057

031ndash045







eth3THORN


Discussion


1991 1996

20062001

Risk086ndash10































Conclusions


Acknowledgements



References




























































































Results



0

Jan

Feb Mar Apr

May Ju

n Jul

Aug Sep OctNov Dec

10

20

30

40

50

60

70

Num

ber

of d

epre

datio

ns

Other dog

Bear dog

















c2 ROC








Public-access lands











137 4 297 14 86


127 5 283 0 88


183 4 389 106 72


174 5 384 101 76

Risk 2011086ndash10

070ndash085

058ndash069

046ndash057

031ndash045







eth3THORN


Discussion


1991 1996

20062001

Risk086ndash10































Conclusions


Acknowledgements



References




























































































c2 ROC








Public-access lands











137 4 297 14 86


127 5 283 0 88


183 4 389 106 72


174 5 384 101 76

Risk 2011086ndash10

070ndash085

058ndash069

046ndash057

031ndash045







eth3THORN


Discussion


1991 1996

20062001

Risk086ndash10































Conclusions


Acknowledgements



References
















































































Public-access lands











137 4 297 14 86


127 5 283 0 88


183 4 389 106 72


174 5 384 101 76

Risk 2011086ndash10

070ndash085

058ndash069

046ndash057

031ndash045







eth3THORN


Discussion


1991 1996

20062001

Risk086ndash10































Conclusions


Acknowledgements



References
















































































eth3THORN


Discussion


1991 1996

20062001

Risk086ndash10































Conclusions


Acknowledgements



References







































































































Conclusions


Acknowledgements



References














































































landscape predictors of wolf attacks on bear-hunting dogs in

Documents