Journalof WildlifeManagement 74(5):1141-1153; 2010; DOI: 10.2193/2009-293 111/nu>* ρ ll ■ να τ η,
Toolsand TechnologyArticle '%^% TraditionalVersus Multivariate Methods forIdentifying Jaguar, Puma, and Large Canid Tracks CARLOS DE ANGELO,1 NationalResearch Council of Argentina (CONICET) andAsociación Civil Centrode Invéstigaciones del Bosque Atlântico (CelBA),Yapeyû 23, CP 3370, PuertoIguazú, Misiones, Argentina AGUSTIN PAVIOLO, NationalResearch Council of Argentina (CONICET) andAsociación Civil Centrode Investigacionesdei Bosque Atlântico (CelBA),Yapeyú 23, CP 3370, PuertoIguazú, Misiones, Argentina MARIO S. DI BITETTI, NationalResearch Council of Argentina (CONICET) andAsociación Civil Centrode Investigacionesdel Bosque Atlântico (CelBA),Yapeyú 23, CP 3370, PuertoIguazú, Misiones, Argentina
ABSTRACT The jaguar{Panthern onca) and puma {Puma concolor) are the largest felids of the American Continent and live in sympatry alongmost of their distribution. Their tracks are frequently used for research and management purposes, but tracks are difficult to distinguish fromeach other and can be confusedwith those of big canids. We usedtracks from pumas, jaguars, large dogs, and maned wolves {Chrysocyon brachyurus)to evaluate traditional qualitative and quantitative identification methods and to elaboratemultivariate methods to differentiatebig = canidsversus big felids and puma versus jaguar tracks (n 167tracks from 18 zoos).We testedaccuracy of qualitative classification through an identificationexercise with field-experienced volunteers. Qualitative methods were useful but there was highvariability in accuracyof track identification.Most of the traditional quantitative methods showed an elevatedpercentage of misclassified tracks (>20%). We usedstepwise discriminantfunction analysis to develop3 discriminantmodels: 1 forbig canid versus big felid track identification and 2 alternativemodels for jaguarversus puma track differentiation using 1) bestdiscriminant variables, and 2) size-independentvariables. These modelshad high classificationperformance, with <10% of errorin thevalidation procedures. We used simplerdiscriminant models in the elaborationof identificationkeys to facilitatetrack classification process. We developedan accuratemethod for track identification, capable of distinguishing betweenbig felids (puma and jaguar) and large canids (dog and manedwolf) tracks and between jaguar and puma tracks. Application of our methodwill allow a morereliable use of tracks in pumaand jaguar research and it will help managers using tracks as indicatorsof these felids' presencefor conservation or managementpurposes.
KEY WORDS canids,discriminant function analysis, identification keys, jaguar, Panthern onca, puma, Puma concolor, track differentiation.
Sign surveysare usefulnoninvasive tools to assess and and onlyfew tracks are foundin each event(Fjelline and monitorelusive or rare species (Wemmer et al. 1996, Mansfield1988, Wemmer et al. 1996, Grigioneet al. 1999, Gompperet al. 2006). Spoor countshave been used as Lewisonet al. 2001). Multivariateanalyses have been used indicatorsof presence,relative abundance, and density to reduce subjectivityand improve accuracy in sign estimationof differentspecies (Van Dyke et al. 1986, recognition(Zielinski and Truex 1995, Zalewski 1999, Stander1998, Crooks 2002, Wiltinget al. 2006). Likewise, Harringtonet al. 2008, Steinmetzand Garshelis2008). In manystudies involving endangered species have used sign addition,multivariate analyses of felinetracks have been surveysto obtain basic ecological information(e.g., used formore demanding objectives like sex determination distributionand habitatuse; Perovic and Herran 1998, and individualidentification (Smallwood and Fitzhugh Potvinet al. 2005,Markovchick-Nicholls et al. 2008) and as 1993, Riordan 1998, Sharma et al. 2003, Wiltinget al. preliminaryor complementaryassessment in ecological 2006, Isasi-Cataláand Barreto2008; but see Karanthet al. researchor conservationplans (Schaller and Crawshaw 2003 and Gordonet al. 2007). 1980, Rabinowitz and Nottingha 1986, Soisalo and Jaguars{Panthern onca) live in sympatrywith pumas (Puma Cavalcanti2006, Paviolo et al. 2008). Tracksare not only concolor)along mostof theirdistribution and both species one of themost commonly used signsbut theymay also be are the focusof manyresearch and conservationprograms usefulin identifyingother associated signs such as fecal (Nowelland Jackson 1996, Sanderson et al. 2002, Conroyet samples(Wemmer et al. 1996, Scognamilloet al. 2003, al. 2006, Shaw et al. 2007). These felidsalso sharemost of Shaw et al. 2007, Azevedo 2008). However,one of the theirrange with some large canids, such as pumaswith gray problemsof employingtracks and othersigns is correct wolves (Canis lupus) and coyotes(C. latrans) in North identificationof the species,particularly in areaswhere >2 America,both felids with the maned wolf (Chrysocyon similarspecies are likelyto be foundand wherelittle or no brachyurus)in centralSouth America, and both felidswith informationabout their presence is available. the domesticdog in mostof theirdistribution. Because trackshape is affectedby many factors(like Tracks of pumas and jaguars have been employedfor substratequality or the pace of the animal) it is often research,monitoring, and management(Smallwood and difficultto distinguishtracks of similarspecies, particularly Fitzhugh 1995, Hoogesteijn 2007, Shaw et al. 2007). in areaswhere soil conditionsmake track printing difficult However,it is oftendifficult to differentiatebetween puma and tracksbecause are similarin size and 1 jaguar they shape E-mail:[email protected] and both are frequentlyconfused with big canids' tracks
De Angelo et al. · Large Felid and Canid Track Identification 1141
This content downloaded on Fri, 25 Jan 2013 17:25:26 PM All use subject to JSTOR Terms and Conditions (Smallwoodand Fitzhugh1989, Childs 1998, Shaw et al. foras manyindividuals and zoos as possible,looking for all 2007). For this reason, many authors have described kind of tracks(front, rear, right, and left feet),diverse qualitativetraits to differentiatepuma fromdog tracks substrates,and differentanimal size and behavior(to favor (Smallwoodand Fitzhugh 1989, Shaw et al. 2007; Appendix includingtrack variability caused by animal pace andwt). We A), and to distinguishjaguar from puma tracks (Schaller and collectedall tracksfrom free-walking animals (i.e., the paw Crawshaw1980, Aranda1994, Childs 1998; AppendixA). was notpressed into the substrate by handlers). We obtained Nevertheless,due to thesubjectivity and exceptionsfound in all dog tracksand 78% of tracksfrom zoos fromunprepared applicationof qualitativetraits, some authorsproposed substrates,whereas remaining zoo trackswere from sleekly quantitativeidentification measures (Beiden 1978, Small- preparedsurfaces on. which animals walked freely to yield wood and Fitzhugh1989, Aranda 1994, Childs 1998, Shaw betterprints (mainly in zoos lackingan adequatesurface for et al. 2007; AppendixΒ). However, these quantitative printingtracks). Substrate conditions varied among zoos and criteriawere createdand evaluatedbased on eitherfew among the siteswhere we collecteddog tracks,including knownindividuals or unknownfield tracksclassified by mud,dust, and sand (wetor dry),for all groupsconsidered. qualitativetraits. We triedto collectas manytracks as possiblefrom each In view of these shortcomings,we used a diverseset of individual.However, because we obtainedfew tracks in most tracksfrom definitely known origin with the aim of 1) of the zoos, we triedto select <1 track/footfrom each evaluatingperformance of qualitativeand quantitative individual,in orderto haveall individualsrepresented by the methodologiesdescribed to differentiatetracks of big canids, same numberof tracks.We used 3 methodsfor recording pumas,and jaguars;and 2) developingaccurate and robust tracks:plaster molds, digital photos with a metricrule as size quantitativemultivariate criteria to classifytracks of these reference,and trackcontour in acetatepaper. Multiplicity of groupsand species. zoos, individuals,collectors, and methodsgenerated a variety oftracks of different fromwhich we discarded STUDY AREA qualities, only for furtheranalysis those tracks that had conspicuous Between2004 and 2008, we obtainedtrack records from deformationsprecluding an accuratemeasurement. jaguars,pumas, and manedwolves kept in captivity.Our To givedigital format to collecteddata, we photographed taskwas carriedout in collaborationwith 18 zoos from6 the plastermolds with digitalcameras and scannedtrack countries:Zoo Batán(Batán, Argentina), Zoológico Bosque tracings,including a metricrule. Then, the firstauthor Guarani(Foz do Iguaçu, Brazil), RefugioBiológico Bela digitalizedall tracksusing the splinetool in AutoCAD® Vista (Foz do Iguaçu, Brazil), Zoológico Itaipú Paraguay 2004 (AutoDesk,Inc., Fresno,CA). For digitization and (Hernandarias,Paraguay), Parque Ecológico Urbano de Rio measurement,we scaled tracks accordingto the size- Cuarto(Rio Cuarto,Argentina), Zoológico de la Ciudad de referencemetric rule. Subsequently, we rotatedand placed BuenosAires (Buenos Aires,Argentina), Temaiken (Bue- tracksover a base linedefined by a tangentline between the nos Aires,Argentina), Zoológico de Roque Sáenz Pena outerheel lobes (Smallwoodand Fitzhugh1989; Fig. 1). Tatu (Roque Sáenz Pena, Argentina),Zoológico Carreta We analyzed167 tracks,including plaster molds (n = 98), de Ia Ciudad de (La Cumbre,Argentina), Jardin Zoológico photographs(n = 57), and tracktracings (n = 12) fromthe Córdoba Fe de (Córdoba, Argentina),Zoológico Santa 3 groupsof interest. We randomlyseparated 35 tracksout of Medellín Cari- (Medellín,Colombia), Parque Zoológico the total (10 jaguars,10 pumas,and 15 big canids)to be cuao Las Delicias (Caracas,Venezuela), Parque Zoológico used only for independentvalidation for discriminant Lincoln Park Zoo (Maracay,Venezuela), (Chicago, IL, models and identificationkeys (independentcases). We USA), Sedgwick County Zoo (Wichita, KS, USA), used all other132 tracksin traditionalmethod validation Caldwell Zoo Zoo (Tyler, TX, USA), Philadelphia and formultivariate model and identificationkey develop- and Little Rock Zoo (Philadelphia,PA, USA), (Little ment(46 tracksfrom jaguars, 46 frompumas, 33 fromdogs, Rock,AR, USA). and 7 frommaned wolves). METHODS Evaluation of TraditionalIdentification Methods Sample Collectionand Processing To evaluate accuracy of traditionalqualitative track We collectedtracks from 28 jaguars,29 pumas,and 8 maned identificationwe made a classificationexercise with 67 wolves(mainly ad of bothsexes for all the species,although participantsfrom Argentina, Brazil, and Paraguayin a we also included2 tracksof a juvjaguar and 3 tracksof 2 juv jaguar conservationmeeting (Third Workshopof Collab- pumasof around 1.5 yrold). We usedthe same methodology orativeEffort for Jaguar Monitoring in AtlanticForest, 5-6 to obtainlarge dog tracksfrom urban areas (35 individuals, Oct 2005, PuertoIguazu, Misiones,Argentina). Although most of them straydogs). Authorsand zoo personnel participantsconsidered themselves capable of identifying recordedtracks by followinggeneral recommendations (see tracksof thesecarnivores (jaguars, pumas, and big canids), Wemmeret al. 1996, De Angelo et al. 2008) insteadof we startedthe exerciseby showingexamples of tracksfrom standardizedmethodology, because our main objective was to each groupand by reviewingtraditional qualitative differ- evaluateidentification methods for tracks collected in the entiationcharacters (Appendix A). Fromour track database, fieldby differentpeople, under diverse circumstances, and we randomlyselected 10 photographsof tracksfrom each usingdifferent protocols. For thesame reason, we usedtracks groupand thenasked volunteers to classifytracks into these
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This content downloaded on Fri, 25 Jan 2013 17:25:26 PM All use subject to JSTOR Terms and Conditions Figure 1. Examplesof typicalbig canid, puma, and jaguar tracks.We used measurementsshown in this figurefor the validationof quantitative identificationcriteria and forconstruction of variables used in discriminantanalysis to developa multivariateidentification method for tracks of these species. We collectedsamples from 18 zoos fromArgentina, Brazil, Colombia, Paraguay, United States, and Venezuela,and urbanareas from Argentina, 2004-2008. (a) Heel pad: al: totalwidth, a2: totallength, a3' widthat thethird quarter of the total length (a2 needed),a4' totalarea, a5: totalperimeter, (b) Toes: bl (i to iv): totalwidth, b2 (i to iv): totallength, b3 (i to iv): widthat thefirst third of the total length (b2i-b2iv needed), b4 (i to iv): widthat thesecond third of the totallength (b2i-2biv needed), b5: thehigher distance between toes and the heel pad. (c) Track:cl: totalwidth, c2: totallength. TL1: tangentline created betweenthe base oftoes / and «/, TL2: tangentline created between the base oftoes ii and iv,Angle D: anglebetween the longitudinal axes of i and iv toes, AngleX: inferiorangle formed between TL1 and TL2 lines.
3 categoriesduring a slide presentationof photographsof dent-sample/-tests. We maintainedas preselectedvariables the tracks.Finally, we markedthe achievementof each only those that showed significantdifferences between volunteerby the percentage of correctly classified tracks, and groupsin univariatetests. We also checkedthese variables contrastedtheir performance with 67 randomlysimulated forredundancy by usingPearson correlations. From groups classifications. of highlycorrelated variables (r > 0.8), we selectedonly the We selected4 categoricalvariables proposed for differen- variable that showed the largest univariatedifference tiationof big canidsfrom felids (i.e., claw marks,shape of betweengroups (the highestt value).When >2 correlated heel-padfront area, shape of heel-pad base, and shapeof the variablesshowed similar univariate differentiation capability, innerside of outer toes; AppendixA), and we assessed we selectedthe variablethat featuredmore simplicityfor percentageof correctlyclassified tracks by each feature.We precisemeasurement (Zielinski and Truex 1995). used 33 dog, 46 puma, and 46 jaguar tracksto validate We combinedpreselected variables and a setof tracks from existentquantitative classification criteria (Appendix B). We each group(original training cases) in discriminantfunction also included7 manedwolf tracks to assesswhether they analysis(DFA). We createdmodels to differentiate1) big wereclassified in the same groupas dog tracks.For each canid tracksfrom those of big felids,and 2) puma tracks criterion,we observed the number of correctlyand from those of jaguars. To constructeach model, we lambda misclassifiedtracks. Following the statementby Aranda conductedstepwise variable selection using Wilks' the minimumnumber of less correlated (1994) thatany of the toes could be usedin his criterion,we criterion,choosing used all toes in each trackto testit. variablesbut ensuringthe highestgroup differentiation = = (min.partial Ζ7 to enter 3.84; max.partial F to remove Constructionand Validationof MultivariateModels 2.71; SPSS 2008, Steinmetzand Garshelis2008). We We createda seriesof measurementsand combinationsof validatedmodels by percentageof originaltraining cases measurementsfor representingquantitatively each of the correctlyclassified, percentage of cross-validatedcases describedqualitative traits for track differentiation (Appen- correctlyclassified (leave- one-out classification),and per- dix A). We also incorporatedexisting quantitative criteria centageof independentcases (tracksnot used for model (AppendixB) as theywere originallydescribed and with development)correctly classified (SPSS 2008, Steinmetz somemodifications (e.g., see VarA2and VarB3in Appendix and Garshelis2008). Additionally,we evaluatedmodel C). This procedureresulted in 155 measurementsand performanceby estimatingprobabilities of groupmember- variablesthat included linear, angular, and areadimensions, shipfor all cases,both for misclassified and correctlyclassi- proportionalvariables composed by ratios among >2 fiedtraining and independenttracks (see Stockburger1998). measurements,and shapevariables as describedby Lewison Jaguarsare biggerthan pumas and bodysize is correlated et al. (2001). To reducethe totalnumber of variables,we withtrack size (Crawshaw 1995, Sunquist and Sunquist 2002); randomlyselected 20 tracksfrom each group (jaguars, therefore,absolute size provesto be usefulin trackdifferen- pumas,and big canids)and assessedvariable performance in tiation(Childs 1998, Brown and Lopez Gonzalez 2001). trackdifferentiation using box-plotgraphs and indepen- However,both species show high variation in size alongtheir
De Angelo et al. · Large Felid and Canid Track Identification 1143
This content downloaded on Fri, 25 Jan 2013 17:25:26 PM All use subject to JSTOR Terms and Conditions distributionand their size ranges overlap extensively (Iriarte et Table 1. Classificationaccuracy of traditionalquantitative methods describedto differentiate canids versus felids tracks al. 1990, Sunquistand Sunquist2002). Most of ourjaguar big big (mainly - describedfor dog vs. pumatracks) and pumaversus jaguar tracks. We made trackswere bigger than puma tracks (pad width for pumas: χ our evaluation tracksfrom 18 zoos of = = = using Argentina,Brazil, Colombia, 5.06 cm,SD 0.79,η 46; andfor jaguars: χ 7.14 cm,SD Paraguay,United States, and Venezuela,and urbanareas from Argentina, = = = = 1.05, η = 46). Inclusionof all tracksin modeltraining 2004-2008 (dog η = 33, manedwolf η 7, pumaη 46,jaguar η 46). See of criteriain B. causedclassification errors only with the biggestpuma and description Appendix smallestjaguar tracks due to an overratedimportance of size in % of misclassifiedtracks size tracks are track classification.These intermediate Criterion Dog Maned wolf Puma Jaguar the most difficulttracks to even for commonly identify, Beiden(1978)a 45 ο 24 4 experts.Accordingly, we selectedthe 50th percentile contain- Smallwoodand Fitzhugh ing smallerjaguar tracks and the 50thpercentile containing (1989)a 21 14 17 9 tracksas tracksfor versus Shaw et al. (2007)b 0 0 biggerpuma model-training puma 87 0 discriminantmodels to reduce the relative of Aranda(1994)c'd jaguar importance Childs (1998)ac>e 15 18 size-relatedvariables. In addition,we produceda modelwith a Criteriondescribed to differentiate vs. tracks. all trackswithout including absolute measurements related b dog puma Criteriondescribed to characterizepuma tracks. withtrack size. c only Criteriondescribed to distinguishpuma vs. jaguartracks. Fromthe finalvariables used in discriminantmodels, we d Criterionevaluated foreach toe of the tracks. e independently print selectedeasier-to-measure variables to make simplerdis- Criteriondescribed for rear tracks and evaluatedonly with 17 jaguarand 13 tracks,because of thecollected tracks did nothave accurate criminantmodels. We used thesesimpler models as stepsto puma many informationin thisaspect. constructtrack identification keys (Steinmetz and Garshelis 2008). We determinedthe rangesfor step decisions by the Smallwoodand Fitzhugh(1989) presentedbetter reliability functiondiscriminant scores (DS) thatrepresented 90-99% in dog and pumatrack differentiation, but showeda higher ofposterior probabilities of group membership (Stockburger errorwith maned wolf and jaguar tracksthan the method 1998). We startedeach key with the easiest-to-measure described Beiden (1978; Table 1). All and variablesand the model,and thenwe used more by puma jaguar simplest trackshad >3.5 cm of widthas described Shaw modelsin each morevariables), to heel-pad by complex step (adding et al. for To differentiate and makethe identification to (2007) puma(Table 1). puma processeasy perform. criterion Aranda We tookall measurements Auto Cad to the nearest jaguar tracks, by (1994; AppendixB) using showed the >80% of 0.01 cm forlinear measurements, 0.01 cm2for areas, and Io highesterror, misclassifying puma toes, all toes were identified forangles. We assessednormality and homoscedasticityof although jaguar correctly (Table 1). The ratioof area to trackarea of reartracks variableswith the Shapiro-Wilkand Levene's test and pad described Childs(1998) had betterclassification applied reciprocal,natural logarithm,square, or cubic by accuracy transformationwhen needed. We used theBox's M statistic (Table 1), but we evaluatedaccuracy for 17 jaguar and 13 tracks and 23% of evaluatedtracks fell into the to test for the homogeneityof covariance matrices. We puma only, undefinedintermediate the totalheel- conductedall statisticalanalyses using SPSS® forWindows range.Considering width betweenrear tracksof statisticalpackage version Rel.11.0.1.2001 (LEAD Tech- pad (AppendixB), ranges and fromzoos = nologies,Inc., Chicago,IL). puma jaguar overlapped(puma range 4.07-5.50 cm;jaguar range = 5.18-8.99 cm)with one puma RESULTS and one jaguarrear track in the overlappingrange (Childs Brownand Gonzalez Reliabilityof PreviouslyDescribed 1998, Lopez 2001; AppendixB). IdentificationMethods Two categoricalfeatures showed the expected pattern with >70% of and tracks but the Volunteerscorrectly classified 61.5 ± 1.4% (x ± SE) of puma dog correctlyclassified, other 2 variablesmisclassified >60% of tracks,a largerpercentage than that obtained by a random categorical dog classification(x = 35.1%, SE = 1.0%, η = 67; Mann- tracks(Fig. 2). Claw markswere absent in 93.5% of puma Whitneytest: Ζ = -9.45, Ρ < 0.001). However,nobody trackswhereas 97% of dog trackspresented claw marks correctlyclassified all tracks,and participantsshowed a wide (Fig. 2A). The frontof the heel pad was flatteror concavein range of identificationaccuracy (37-87%) with higher 84.8% of puma tracksand 72.7% of dog trackspresented variationthan that observed in random classification roundedor pointed shape in thefront of the heel pad. Jaguar (volunteersclassification SD = 11.2%,random classification and puma tracksshowed similar classification percentages SD = 8.1%; F66y66= 1.9,Ρ < 0.02; Sokal and Rohlf1995). using these variables,as did maned wolf and dog tracks Although67% of trackswere correctly identified by >50% (Fig. 2A, B), but no variableallowed differentiationof of volunteers,a group of 10 hard-to-identifytracks 100% of tracksamong these species. Contrary to whatwas (includingcanid, puma, and jaguartracks) were incorrectly expected,63.6% of dog tracksshowed a tri-lobbedheel-pad identifiedby >50% of volunteers. base and 72.7% presenteda roundedinner part of theouter Criteriondescribed by Beiden (1978; AppendixB) showed toes (Fig. 2C, D). In addition,it was sometimesdifficult to >20% of dog and puma tracksmisclassified but had better classify,unambiguously, tracks into the categories defined by performanceidentifying maned wolf tracksas canids and theselast 2 categoricalvariables (i.e., shape of the base ofthe jaguar tracksas felids (Table 1). Criteriondescribed by heel pad and innershape of the outertoes).
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This content downloaded on Fri, 25 Jan 2013 17:25:26 PM All use subject to JSTOR Terms and Conditions Figure 2. Percentageof tracksbearing different characteristics related with 4 categoricalvariables used for canid and felidtrack differentiation. A) Presence orabsence of claw marks; B) shapeof the front of the heel pad; C) shapeof the base of the heel pad; D) shapeof the inner part of the outer toes. We evaluated = = = = tracksfrom pumas (n 46), jaguars(n 46), dogs (n 33), and manedwolves {n 7) thatwe collectedfrom 18 zoos fromArgentina, Brazil, Colombia, Paraguay,United States, and Venezuela,and urbanareas from Argentina, 2004-2008. See a completedescription of thesecharacteristics in Appendix A.
MultivariateModel Constructionand Validation withhigh membership probabilities (>95%; Table 3), with We preselected35 variablesthat showed more differentia- pumas havinglower probabilities than jaguars within the tion capabilitybetween the groupswe analyzed.Stepwise felidgroup (Fig. 3A). DFA startingwith these variables resulted in 3 discriminant To differentiatepuma and jaguar tracks,we selected2 models(Table 2; Fig. 3) constructedby differentcombina- models(models BI, B2; Table 2; Fig. 3B, C). We generated tionsof 10 of thesepreselected variables (see AppendixC). model Bl from a stepwise process startingwith all For big canidversus big felidtrack contrast, we selecteda preselectedvariables, and model B2 only used size- model composedby 3 variablesthat provedto be >98% independentvariables. Model Bl included transformed accuratein all validationprocedures (model Al; Table 2; pad width (VarBl) as a size parameter,so we developed Fig. 3A). Classificationerrors of thismodel occurred with thismodel using only bigger puma tracks (x - 5.67 cm,SD one pumaand onejaguar track that were classified as canid, = 0.65 cm, range = 4.99-7.46 cm, η = 23) and smaller with group probabilitiesof 69% and 88%, respectively jaguartracks (x - 6.35 cm, SD = 0.53 cm,range = 4.99- (Table 3). However,82% of trainingand 83% of indepen- 7.02, η - 23), whereaswe used excludedtracks only for denttracks from felids and canidswere correctlyclassified model validation.Model Bl had highergroup separation
De Angelo et al. · Large Felid and Canid Track Identification 1145
This content downloaded on Fri, 25 Jan 2013 17:25:26 PM All use subject to JSTOR Terms and Conditions Table 2. Parameters,variables incorporated, discriminant functions, and validationresults for discriminant models selected for felid versus canid (Al) and forpuma versus jaguar track differentiation (Bl and B2). To developthese models we collectedsamples from 18 zoos fromArgentina, Brazil, Colombia, Paraguay,United States, and Venezuela,and urbanareas from Argentina, 2004-2008. Validation
Wilks' lambda (λ) Original Cross- Independent Groups Model and associatedχ2 Discriminantfunction'1 cases validation cases Felidsvs. canids ΑΙ λ = 0.280 DS = 10.711 X VarAl + 1.563 X VarA3 + 0.047 98.5% 98.5% 100.0% - χ23= 163.1* X AngleX 16.126 = = Jaguarsvs. pumas Bl λ 0.206 DS 5.412 X VarBl + 2.806 X VarB2 + 10.865 100% 93.5% 100.0% - χ24= 63.97* X VarB4 + 0.342 X VarB5 8.936 X VarB7 - 0.261 X VarB8 - 0.942 X VarB9 - 15.765 B2 λ = 0.282 DS = 4.052 X VarB2 + 7.710 X VarB4 + 0.207 96.7% 94.6% 95.0% - - χ24= 110.19* X VarB5 3.525 X VarB7 0.072 X VarB8 - 1.672 X VarB9 - 7.659 a Functionused to calculatethe discriminantscore (DS) to classifytracks. See AppendixC forvariable descriptions. b Independentvalidation in modelBl consistsof independentcases plus excludedcases. * Ρ < 0.001. - - (i.e., lower Wilks' lambda) and highervalues in the 3 DS 6.528 X VarBl + 0.077 X VarB8 14.627 validationmethods than model B2 (Table 2). No original, Bl. DS < -2.40: puma. excluded,or independenttracks were misclassified and 90% B2. DS > 1.95: jaguar. of tracks were classifiedwith >95% of membership B3. DS = -2.40-1.93: go to stepC. probabilities(Table 3; Fig. 3B). Model Bl incorporated7 variablesthat needed 19 measurements(Table 2). Step C: Calculatediscriminant score using: Model B2 6 variables(19 incorporated size-independent DS = 5.890 X VarBl - 8.088 X VarB7 + 0.024 measurements Table model B2 had needed; 2). Although X VarB8 - 9.830 lowerperformance than model Bl (Table 2), it misclassified only1 jaguarand 3 pumatracks, but with medium to high Cl. DS < -1.90: puma. groupprobabilities (58-95%; Table 3; Fig. 3C). C2. DS > 1.80: jaguar. We constructed3 identificationkeys: one forthe contrast C3. DS - -1.90-1.80: go to stepD. betweencanids and felidsand 2 for from identifyingpuma D: Calculatediscriminant score jaguar tracks (with and without size-relatedvariables, Step using: respectively). DS = 6.539 X VarBl + 10.222 X VarB4 - 10.762 - - - X VarB7 0.039 X VarB8 6.029 Key1. Big canidversus big felidtrack identification. Dl. DS < -1.00: A: CalculateVarAl (see C) puma. Step Appendix > Al. <0.41: canid. D2. DS 1.55: jaguar. DS - use discriminantmodel Bl. A2. >0.67: felid. D3. -1.00-1.55: A3. 0.41-0.67: go to stepB. Phis key used total heel-padwidth in the firststep but becauseit was a one-variable-size-relatedstep, we selected Step B: Calculatediscriminant score using: an extremerange (the chosenvalues represent>99% of = - DS 12.532 X VarAl + 1.962 X VarA3 12.458 ιmembership probabilities in one-variablediscriminant ] The 4 variables Bl. DS < -1.60: canid. model). key required (13 measurements), and 41% of 4% of and 25% of B2. DS > 0.01: felid. ! training, excluded, ] tracksremained unidentified and the B3. DS = -1.60-0.01: use discriminantmodel Al. independent required use of discriminantmodel Bl forfurther discrimination. This key used 2 variablesincorporated in 2 steps (6 - Key3. Puma versusjaguar track identification without measurementsneeded to completethe key).This keyfailed usingtrack size. to classify19% of trainingtracks and 20% of independent tracks,which then required use ofdiscriminant model Al to Step A: Calculate heel pad:track area ratio (VarB8; attaina finalclassification. Childs 1998) Al. <24.5%: 2.- Puma versus trackidentification puma. Key jaguar using A2. >50%: tracksize. jaguar. A3. 24.5-50%: go to stepB. StepA: Measurethe heel-pad width (measurement al) Step B: Calculatediscriminant score using: Al. <4.5 cm: puma. - A2. >7.9 cm:jaguar. DS = 3.989 X VarB7 0.094 X VarB8 + 3.156 - A3. 4.5-7.9 cm: go to stepB. X VarB9 2.142 Step B: Calculatediscriminant score using: Bl. DS > 1.75: puma.
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This content downloaded on Fri, 25 Jan 2013 17:25:26 PM All use subject to JSTOR Terms and Conditions B2. DS < -2.26: jaguar. B3. DS = -2.26-1.75: go to stepC. Step C: Calculatediscriminant score using:
DS = 7.885 X VarB4 - 4.043 X VarB7 + 0.077 X VarB8 - 2.487 X VarB9 - 4.477
Cl. DS < -1.40: puma. C2. DS > 1.50: jaguar. C3. DS = -1.40-1.50: use discriminantmodel B2.
The key required4 size-independentvariables (17 mea- surements),and 53% of trainingand 55% of independent tracks remainedunidentified and required the use of discriminantmodel B2 forfurther discrimination. DISCUSSION Described Methods forJaguar and Puma Track Identification Althoughnot a real field-trackrecognition situation, the identificationexercise showed that qualitativetraits are useful for track distinction.At the same time, it also revealedambiguity and subjectivityin criteriaapplication resultingin high variationin classificationaccuracy. All participantswere trained togetherin track recognition beforethe exercise;however, variation in the performance amongvolunteers was higherthan that observed in random classifications.Although volunteers (mainly biologists and parkrangers) had experiencein fieldwork,not all of them had the same expertisein track recognition.Previous experiencein identifyingtracks is probablythe mainreason forthis variability in participants'classification rate. Several authorshave mentionedthe relevanceof fieldexpertise in sign identification(Wemmer et al. 1996, Standeret al. 1997, Childs 199.8,Shaw et al. 2007), but the frequent assumptionthat people with fieldexperience possess sign recognitionskills does not alwayshold true(Lynam 2002). Existing quantitativeunivariate criteria showed low accuracyin trackclassification. The techniqueby Beiden (1978) had a high misclassificationrate (>20%) and criterionby Smallwoodand Fitzhugh(1989), thoughmore accurate,also misclassifiednearly 20% of puma and dog tracks.Likewise, for jaguar and puma trackrecognition we obtainedlow classificationrates with criterionby Aranda
of tracksalong discriminant models (vertical axis) obtainedto differentiate A) canid versusfelid tracks,B) puma versusjaguar tracksusing size- dependentvariables, and C) puma versusjaguar tracks using size- independentvariables. We includedboth trainingand independenttracks = = = in thegraphs (jaguar η = 56; puma η 56; dog η 44; manedwolf η 11). Horizontalcontinuous line indicates the limit among groups predicted by the model,and horizontaldashed lines indicatethe centroidvalue for each group.VarAl: widthat the thirdquarter of the heel pad, dividedby the totalheel-pad width. VarB5: actualarea of theheel pad dividedby the squaredarea of the track(total track width X totaltrack length) expressed as percentage.We collectedsamples from 18 zoos fromArgentina, Brazil, Figure 3. Distributionof tracksalong the variablewith the highest Colombia,Paraguay, United States, and Venezuela,and urbanareas from differentiationability between groups (horizontal axis), against distribution Argentina,2004-2008.
De Angelo et al. · Large Felid and Canid Track Identification 1147
This content downloaded on Fri, 25 Jan 2013 17:25:26 PM All use subject to JSTOR Terms and Conditions Table 3. Discriminantscore ranges and theirapproximately associated probability for each discriminantmodel that we developedto differentiatetracks of canids,pumas, and jaguars. Number of misclassifiedand well-classifiedtraining and independenttracks are shown for each range.To developthese models, we collectedsamples from 18 zoos fromArgentina, Brazil, Colombia, Paraguay, United States, and Venezuela,and urbanareas from Argentina, 2004-2008. ^ .j ^ Misclassifiedtracks Well-classifiedtracks Centroid Group Model Groups value Discriminantscore probability3 Training Excluded Independent Training Excluded Independent Al Canids -2.411 <-2.000 >99% canid 0 0 26 10 -2.000 to -1.086 80-99% canid 1 0-13 3 -1.085 to -0.739 55-79% canid 1 0 1 2 -0.738 to -0.623 Undetermined0 0 0 0 0 Felids 1.048 -0.624 to -0.277 55-79% felid 0 0 8 1 -0.278 to 0.650 80-99% felid 0 0 26 6 >0.650 >99% felid 0 0 56 13 Bl Pumas -1.920 <-1.2 > 99% puma 0 0 0 18 22 8 -0.769 to -0.361 80-99% puma 0 0 0 3 0 1 -0.360 to -0.052 55-79% puma 0 0 0 2 11 -0.051 to 0.051 Undetermined13 0 0 0 0 0 0 Jaguars 1.92 0.052 to 0.360 55-79% jaguar 0 0 0 0 0 0 0.361 to 0.769 80-99% jaguar 0 0 0 6 2 0 >1.2 >99% jaguar 0 0 0 17 21 10 B2 Pumas -1.579 <- 1.450 > 99% puma 0 0 26 4 -1.450 to -0.439 80-99% puma 1 0 14 3 -0.438 to -0.064 55-79% puma 0 0 3 2 -0.063 to 0.063 Undeterminedb 1 0 1 0 Jaguars 1.579 0.064 to 0.438 55-79% jaguar 0 14 1 0.439 to 1.450 80-99% jaguar 2 0 15 3 > 1.450 >99% jaguar 0 0 25 6 a Rangesof approx.group membership probabilities estimated using a posterioriprobabilities calculated by SPSS forall cases (Stockburger1998, SPSS 2008). b Although50% probabilitydetermines the limitbetween 2 groups,we consideredthat the differencein valuesaround 50% is too scarceto be used as criterionfor unknown track classification.
(1994), which misclassifiedmost puma tracktoes. Heel towardincluding only well-defined tracks (easiest to identify padrtrackarea ratioshowed better results for distinguishing in the field;Lynam 2002, Sharmaet al. 2003). However, reartracks, but we onlyevaluated a fewtracks and it is not whenusing zoo tracks(or tracksfrom dogs in urbanareas) alwayspossible to determinerear and fronttracks under insteadof fieldtracks, we are possiblyintroducing a bias fieldconditions. Heel-pad widthof reartracks presents the relatedto differencesbetween natural substrates and zoo same limitationand dependson regionalsize variationof substrates.Additionally, we wouldexpect differences in paw thesespecies. Well-defined ranges in a specificregion could characteristicsand pace of animalswalking inside zoo cages probablyrender this criterion locally useful for preliminary or dogs in urbanareas versus animals walking freely in field trackidentification in the field. areas. Geographicvariation in animalsand soil condition Only2 categoricalvariables were suitable for discriminat- may also influencethe misclassificationrate of these ing big canid frombig felidtracks. Nevertheless, none of methods.All of these methodswere originallydeveloped thesevariables demonstrated a 100% classificationrate and in a restrictedregion (i.e., criteriaby Beiden and by Smallwood and in of the United sometimestracks could not be includedwith certainty in the Fizthugh part States, criteria Arandain of and criteria Childs categoriesdefined by these variables. Subjectivity in variable by part Mexico, by in the Brazilian we assessmentcould introduceimportant biases in track Pantanal; Appendix B), though evaluatedthese methods with tracks from animals of classification.Smallwood and Fitzhugh(1989) foundsimilar many zoos from6 countries. and the low resultsin theirexploratory evaluation, and we agreewith the Nevertheless, despite all of these traitswere as assessmentby those authorsthat presence and absenceof accuracy, quantitative preselected variablesfor the multivariate and of them claw marksand the frontof the heel pad were the most analysis many wereused in finaldiscriminant models usefulcategorical variables. (AppendixC). A likelyexplanation for misclassifications using previously MultivariateTrack ClassificationMethod described and is thatwe quantitative categoricaltechniques All discriminantmodels had statisticallysignificant group selecteda setof tracks with different fromdifferent qualities differentiationcapabilities, and independenttrack classifi- and insteadof individuals,zoos, substrates, usingonly high- cationhad >95% discriminationaccuracy in all models.As tracks collected in quality standardizedand controlled mentionedabove, the set of tracks used for construction and conditions.Most of these methodswere tested originally validationof models includedhigh variabilitybecause it with a few knowntracks from zoos or with only mostly incorporatedtracks from males and females,from rear, trackscollected in the field and this (see AppendixB), front,right and left foot, as well as tracksfrom many could not the of practice only present problem possible substratesand of various qualities. Thus, the high misidentificationof the field butalso track, introducea bias discriminantrates we achievedwith our models suggest
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This content downloaded on Fri, 25 Jan 2013 17:25:26 PM All use subject to JSTOR Terms and Conditions that theyare robust,and theycould be used to classify confidencein final decisions. Substratetype and track unknowntracks in fieldstudies. qualityshould also be consideredin decisions;results from However,all modelshad >1 misclassifiedtrack in cross- low-quality tracks should be takenwith caution. validationclassification, and occasionallyin originalcases Animalage could also influencetrack classification when reclassification,which emphasized the importance of taking using key 2 and model Bl, which are size-dependent. into accountgroup membership probabilities when using However,at the age of puma and jaguar dispersal(around thesemodels (Stockburger 1998; Table 3). Most trackswere 1.5-2 yrold; Sunquistand Sunquist2002), mostjuveniles correctlyclassified in all modelswith probabilities >90%, reacha size similarto an adultanimal, particularly their paw and mosterrors occurred in tracksclassified as belongingto size (Crawshaw1995, Shaw et al. 2007). Juveniletracks an incorrectgroup with low or mediumprobabilities. includedin ouranalysis were correctly classified by key 2 and The bigcanid versus big felid discriminant model (Al) and modelBl. Consideringthe wide rangeof tracksize thatwe identificationkey (key 1) used size-independentvariables; analyzedand thereduction of the relative importance of size thus,their application apparently does not have limitations made by excludingextreme-sized tracks, we feelconfident due to regionalsize variation.In addition,correct classifica- thatkey 2 and modelBl shouldbe usefulwith dispersing tionof both domestic dogs and manedwolf tracks as canids subadults'tracks. Key 3 and model B2, which are size- suggestsapplication of discriminantmodel Al and identifi- independent,could be an alternativemethod to avoid cationkey 1 to differentiatebig felid tracks from those of any potentialproblems related with track size. Nevertheless,we largecanid. We made a preliminaryanalysis with 6 coyote suggestnot usingany of the keysand modelswith tracks and 8 graywolf tracks obtained from field guides of North <3.5-4 cm of pad width,to avoid confusionwith younger Americanmammals (Childs 1998, Murie 1998, Paul and animalsand smallercanid or felidspecies not consideredin Gibson2005, Reid 2006) andin all casesthe classification key our analysis.Tracks of kittensor predispersalpumas and andAl modelcorrectly classified these tracks as canids(most jaguarswill oftenbe foundwith their mother's tracks, thus of themwith >95% membershipprobabilities). However, facilitatingtheir track recognition (Shaw et al. 2007). thismethod should be furtherevaluated with more tracks Our multivariateanalyses present >2 mainlimitations in fromthese canid species where they could live in sympatry comparisonwith qualitativeor univariatequantitative withpumas or jaguars. methods.First, some measurementsare difficultto get, In the comparisonof puma versusjaguar models,we theprocess of obtainingthem is time-consuming,and track incorporatedheel-pad width in model Bl as a variable digitalizationis needed(i.e., totalarea and perimeterof the directlyrelated with tracksize as used by manyauthors heel pad). Second,variable construction and discriminant (Fjellineand Mansfield1988, Zielinskiand Truex 1995, functioncomputation require mathematical skills. Howev- Childs1998, Sharma et al. 2003). By excludingextreme-size er, advancedtechnology and softwareare availablefor easy tracksfrom training sets, we reducedthe relative importance and precise image digitalizationand for automatic of track size, therebyimproving overlapping- size track calculations.Moreover, the digitalizationprocess is facil- classificationand overallclassification success. The smallest itatedby new methodsfor trackcollection (e.g., digital jaguartracks we used in the analysishad 4.99 cm and the photographsor track-tracing and image scanner),and biggestpuma tracks had 7.46 cm totalheel-pad width. Both identificationkeys simplify the measurementand identifi- Model ofthese tracks were correctly classified by model Bl. cationprocesses. We also incorporatedthe keys and models B2 used a similarcombination of variables but the exclusion in a spreadsheetfile uploaded as an online supplemental of the heel pad diminishedits classificationaccuracy. materialrelated to this articleat
De Angelo et al. · Large Felid and Canid Track Identification 1149
This content downloaded on Fri, 25 Jan 2013 17:25:26 PM All use subject to JSTOR Terms and Conditions (Zielinskiand Truex 1995, Lynam 2002, Sharma et al. use, withoutthe need to relyon the opinionof expertsin 2003). Besides, findinggood-quality tracks or complete trackidentification. Secondly, tracks could be used with tracksets is difficultin someareas due to substratecondition moreconfidence as a complementarysource of information and animalbehavior (Sharma et al. 2003), and manysurveys forresearch (e.g., helpingin camera-traplocalization) and employvolunteers or studentswith low expertisein track conservationplans (e.g., detectingthe use of biological recognition(e.g., Smallwoodand Fitzhugh1995, Wydeven corridors).Finally, tracks are often additionalevidence et al. 2004, Danielsenet al. 2005, Markovchick-Nichollset collected for identifyingpredators in human-predator al. 2008, De Angelo2009). conflicts(Leite et al. 2002, Hoogesteijn2007, Shaw et al. Multivariatetrack recognition using discriminantfunc- 2007). Tracks may not only help identifythe speciesin tionscould be usefulto solveproblems related with poor- attacksto livestockor humans,but also determinepresence quality tracks and observersubjectivity, and has been ofpotentially dangerous animals in urbanizedor recreational successfullyused to differentiatetracks of American martens areas. Managementactions may differdepending on the (Martesamericana) from tracks of fishers(M. pennantr, predatorspecies (puma, jaguar, or big canid); thus,correct Zielinskiand Truex 1995); thoseof mink(Mustela vison) trackidentification in thesecases is extremelyimportant. fromthose of polecats(Mustela putorius; Harrington et al. 2008); claw marksof Asiaticblack bears (Ursus thibetanus) ACKNOWLEDGMENTS fromthose of sunbears (He/arc tos ma/ay anus; Steinmetz and We thankProyecto Yaguareté volunteers for their partic- Garshelis2008); and also forgender discrimination of tiger ipationin the classificationexercise and samplecollection. tracks(Panther a tigris;Sharma et al. 2003). Followinga We are gratefulto M. Avalos,P. Brandolin,G. Boaglio,E. similar approach,we developed a robust multivariate Catalá, L. Chiyo,A. Colmán,P. Cruz,W. de Moraes,Y. classificationmethod to recognizepuma and jaguar tracks Di Blanco, J. Earnhardt,C. Ferrari,M. Guevara, M. with confidence.Because we used tracks collected by Mealla, S. Moro, Ν. Perez, V. Quiroga,M. Ramirez,R. differentpeople in an unstandardizedway, our method Rivero,C. Schloss,A. Sestelo,D. Villarreal,and all zoos' mightbe used to identifytracks obtained in the fieldfrom authoritiesand personnelfor helpingin trackacquisition differentsources and methodsof collection.Additionally, and processing.G. De Angelo and C. De Angelogave us selectedvariables and discriminantmodels may help to technicalassistance in softwaremanagement. L. Fitzhugh, developmore accurate techniques for track differentiation in R. Steinmetz,and Y. Jhalaassisted with bibliography. We standardizedtrack surveys in the future(e.g., when using are thankfulto J. Earnhardt,C. Boiero, E. Gese, S. smoothedplots; Wemmer et al. 1996). For example,a more Smallwood,D. Hanseder,and an anonymousreviewer for detailedanalysis using more tracks from each individualwill commentsand suggestionsfor improving this manuscript. improveability for species differentiation, and independent Financialsupport for this project was providedby National classificationof front and rear tracks may help to ResearchCouncil of Argentina(CONICET), Fundación differentiatepuma and jaguar tracks with more confidence. Vida SilvestreArgentina, Education for Nature Program of This approachcould help to developsimilar methods for the World WildlifeFund (WWF), WWF-International, male and female track identificationof these species WWF- Switzerland,and LincolnPark Zoo. (Sharma et al. 2003), or for identifyingother sympatric felidor canidspecies as well. LITERATURE CITED To applyour methods in unknowntrack samples from the Aranda, M. 1994. Differentiationof jaguar and puma footprints:a fieldwe suggestresearchers 1) use keysand modelsin tracks diagnosticanalysis. Acta Zoológica Mexicana (η.s.) 63:75-78. [In with>4 cm of startwith identification Spanish.] heel-padwidth; 2) F. C. C. 2008. Food habitsand livestock of to trackswith confidence while the Azevedo, depredation sympatric keys distinguish using jaguars and pumas in the Iguaçu National Park area, South Brazil. minimumnumber of variables and mathematicalcalculation; Biotropica40:494-500. 3) use complete discriminantmodels (Table 2) when Beiden,R. C. 1978. How to recognizepanther tracks. Proceedings of the identification do not the and Annual Conferenceof SoutheasternAssociation of Fish and Wildlife keys classify track; 4) compare 32:112-115. the resultantdiscriminant score with our classification Agencies Brown,D. E., and C. A. Lopez Gonzalez.2001. Borderlandjaguars: tigres results(Table 3) to get an estimateof confidencelimits. de la frontera.University of Utah Press,Salt Lake City,USA. In addition,we recommendusing model B2 in areaswhere Childs,J. L. 1998. Trackingthe felids of theborderlands. Printing Corner are width>7 or aresmall Press,El Paso, Texas,USA. pumas large(heel-pad cm) jaguars M. P. H. and M. R. 2006. width<5.50 orwhen there is no information Conroy, J., Beier, Quigley, Vaughan. Improving (heel-pad cm) the use of sciencein conservation:lessons from the Florida panther. on tracksize (as in photographsobtained without a scaleof Journalof WildlifeManagement 70:1-7. reference). Crawshaw,P. G., Jr.1995. Comparativeecology of ocelot Felis pardalis and jaguar Panthernonca in a protectedsubtropical forest in Brazil and MANAGEMENT IMPLICATIONS Argentina.Dissertation, Universitv of Florida,Gainesville, USA. Crooks, K. R. 2002. Relativesensitivities of mammaliancarnivores to Our multivariateclassification method has >3 main habitatfragmentation. Conservation Biology 16:488-502. applicationsin jaguarand puma conservationand manage- Danielsen,F., N. Burgess,and A. Balmford.2005. 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This content downloaded on Fri, 25 Jan 2013 17:25:26 PM All use subject to JSTOR Terms and Conditions onca)y el puma {Puma concolor).Dissertation, Universidad de Buenos Potvin,M. J.,T. D. Drummer,J. A. Vucetich,D. E. Beyer,Jr., R. O. Aires,Buenos Aires, Argentina. [In Spanish.] Peterson,and J. H. Hammill.2005. Monitoringand habitatanalysis for De Angelo,C, A. Paviolo,Y. Di Blanco,and M. Di Bitetti.2008. Guia de wolvesin upperMichigan. Journal of WildlifeManagement 69:1660- huellasde los mamíferosde Misionesy otrasáreas del Subtrópicode 1669. Argentina.Ediciones dei Subtrópico, San Miguel de Tucumán, Rabinowitz,Α., and B. G. Nottingham,Jr. 1986. Ecologyand behaviourof Argentina.[In Spanish.] thejaguar {Panthern onca) in Belize,Central America. Journal of Zoology Fjelline,D., and T. M. Mansfield.1988. Method to standardizethe 210:149-159. procedurefor measuring mountain lion tracks.Pages 49-51 in R. H. Reid,F. 2006. Petersonfield guide to mammalsof North America. Fourth Smith,editor. The Third Mountain Lion Workshop.The Wildlife edition.Houghton Mifflin, New York,New York,USA. Societyand ArizonaGame and Fish Department,Prescott, USA. Riordan,P. 1998. Unsupervisedrecognition of individualtigers and snow Gompper,M. E., R. W. Kays,J. C. Ray,S. D. Lapoint,D. A. Bogan,and J. leopardsfrom their footprints. Animal Conservation 1:253-262. R. Cryan.2006. A comparisonof noninvasivetechniques to survey Sanderson,E. W., K. H. Redford,C. L. B. Chetkiewicz,R. A. Medellin, carnivorecommunities in northeasternNorth America. Wildlife Society A. R. Rabinowitz,J. G. Robinson,and A. B. Taber. 2002. Planningto Bulletin34:1142-1151. save a species:the jaguar as a model.Conservation Biology 16:58-72. Gordon, C, A. M. Stewart,and E. Meijaard. 2007. Correspondence Schaller,G. B., and P. G. Crawshaw,Jr. 1980. Movement pattern of jaguar. regarding'Clouded leopards,the secretivetop-carnivore of South-East Biotropica12:161-168. Asian rainforests:their distribution, status and conservationneeds in Scognamillo,D., I. E. Maxit,M. Sunquist,and J. Polisar. 2003. Coexistence Sabah,Malaysia. BMC Ecology7:5. ofjaguar {Panther a onca) and puma {Puma concolor) in a mosaiclandscape in Grigione,M. M., P. Burman,V. C. Bleich, and B. M. Pierce. 1999. theVenezuelan llanos. Journal of Zoology259:269-279. Identifyingindividual mountain lions Felts concolorby their tracks: Sharma,S., Y. Jhala,and V. B. Sawarkar.2003. Genderdiscrimination of refinementof an innovativetechnique. Biological Conservation 88:25-32. tigersby usingtheir pugmarks. Wildlife Society Bulletin 31:258-264. Harrington,L. Α., A. L. Harrington,and D. W. Macdonald. 2008. Shaw,H. G., P. Beier,M. Culver,and M. M. Grigione.2007. Puma held Distinguishingtracks of minkMustela vison and polecatM. putorius. guide.The CougarNetwork, Concord, Massachusetts, USA. EuropeanJournal of WildlifeResearch 54:367-371. Smallwood,K. S., and E. L. Fitzhugh.1989. Differentiatingmountain lion Hoogesteijn,R. 2007.Manual on theproblem of depredation caused by jaguars and dog tracks.Pages 15-18 in R. H. Smith,editor. Proceedings of - and pumason cattleranches. Jaguar Conservation Program Wildlife Mountain Lion Workshop,third. The WildlifeSociety and Arizona ConservationSociety,
1151 De Angelo et al. · Large Felid and Canid Track Identification
This content downloaded on Fri, 25 Jan 2013 17:25:26 PM All use subject to JSTOR Terms and Conditions consinDepartment of NaturalResources,
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This content downloaded on Fri, 25 Jan 2013 17:25:26 PM All use subject to JSTOR Terms and Conditions - pumas,and jaguars, collected from 18 zoos fromArgentina, VarB3. Averageof the firstthird width divided by Brazil,Colombia, Paraguay, United States, and Venezuela, second thirdwidth of each toe (modifiedfrom Aranda and urbanareas from Argentina, 2004-2008. We included 1994): the listof evaluated measurements and variablesin complete VarB3 = [(b3i / b4i) + (b3ii / b4ii) + (b3iii / b4iii) + theOnline Material2 SI and Table SI) Supplemental (Fig. (b3iv/ b4iv)] / 4 uploadedas onlinesupplemental material of thisarticle at -
De Angelo et al. · Large Felid and Canid Track Identification 1153
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