FINALREPORT20April2017Fortheprojectentitled:PotentialjaguarhabitatandstructuralconnectivityinandsurroundingtheNorthwesternRecoveryUnitSubmittedto:WilburforceFoundationBy:DavidM.Theobald,PhD–SeniorScientistVincentLandau–GraduateDegreePrograminEcology,ColoradoStateUniversityMeredithMcClure,PhD–LeadScientistBrettG.Dickson,PhD–ChiefScientist

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BackgroundThegoalofthisworkwastomaphabitatandconnectivityforjaguars(Pantheraonca)insouthernArizonaandtheNorthwesternRecoveryUnit(NRU)studyarea.Todothis,wefollowedthegeneralapproachoutlinedbySandersonandFisher(2011;2013)butupdateditusingfiner-grainedspatialdataandagradient-based(ratherthanbinaryhabitat/non-habitat)modelusingthesameobservationaldataonjaguars.BriefreviewofmodelinDraftRecoveryPlanThemodelintheUSFWSdraftrecoveryplanwasgeneratedbySandersonandFisher(2011;2013),andupdatedbyStoneretal.(2015),whichinturnisbasedgenerallyonapotentialjaguarhabitatmodelforArizona(Hattenetal.2005).SandersonandFisherdevelopedjaguarhabitatsuitabilityandconnectivitymapsat1-km2resolutionbasedonguidancefromthetechnicalsubgroupoftheJaguarRecoveryTeamintheNorthwesternRecoveryUnit(USFWSJaguarhomepage:https://www.fws.gov/southwest/es/arizona/Jaguar.htm).Thebinary(habitat/non-habitat)modelwasbasedonlandscapecharacteristicsatsitesof~200jaguarobservations(http://jaguardata.info/),andformsthebasisfortheDraftRecoveryPlan(postedDecember20,2016),whichiscurrentlyinreview(commentsdueMarch20,2017).Thelandscapevariablesusedtomodelhabitatincluded:percenttreecover(T),distancetowater(W),degreeofhumaninfluence(HII),terrainruggedness(R),andhabitatcovertypeweight(X)(Table1).TheformulausedwasdevelopedbySandersonandFisher(2013;model11-13):

Habitat=(T+R)*W*HII*X,wheretreecover(T)was1if1%<cover

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Arizona,Chihuahua,Sinaloa,andSonora;andwereobservedwithinthelastcentury(i.e.,since1917).WeconsideredeachoftheexplanatoryvariablesincludedinSandersonandFisher’s(2013)model,anddescribebelowthedevelopmentofourrevisedhabitatmodel,inwhichwe:(a)leveragedmorerecentlyavailablelandscapedataat30-mresolution(a1000-foldincreaseinresolution);(b)estimatedcontinuousratherthanbinaryhabitatsuitability;and(c)re-examinedthemodellogictoevaluatepotentialhabitatuse(orquality)asafunctionofavailabilitywithinthestudyarea.WealsorevisedthestudyareaforwhichthismodelwasdevelopedtoextendbeyondthedefinedNRU,becausewewereusingrefineddataandagradient-basedmodel,wewantedtobeabletoexaminethesupportofthismodifiedmodeltosupportrefinementofamapofsuitablehabitatextent(Figures1&2).WederivedthismodelinGoogleEarthEngine(GEE),apowerfulcloudcomputingplatformforefficientlyprocessingandintegratinglargedatasets,andprovideGEE-generatedmapsofdatainputsandmodeloutputs.

Figure1.Thestudyareaforthisworkisthefullextentshownhere,whichcontainstheNorthwesternJaguarRecoveryUnit,withanextensiontothenorth(notshadedbutboundedbyInterstates40and25betweenFlagstaff,AZandAlbuquerque,NM).Notethatinputlayersforourmodelwerewall-to-wallinthevisibleextent,andwedidnotuseanyadditionalboundariestocliporremoveotherareas(e.g.,theBajaorareasoutsideoftheNRU).

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Figure2.The48reliablelocationsofobservedjaguars(asblackdots)usedinthisstudy,drawnontopoftheNorthwesternRecoveryUnitforreference.Allofthe48locationswereusedinourmodel.TreecanopycoverOurassumptionintherevisedmodelwasthathabitatusebyjaguarincreasedwithincreasedpercentcanopycover.Toexaminethis,weusedtreecanopycover(TCC)datafromtheGlobalLandCoverFacility’sLandsatTreeCoverContinuousFields(www.landcover.org;Sextonetal.2013)andcalculatedtheaveragecanopycover(0-100%)for2005and2010tominimizesomeabruptchangesinTCCthatappearedasstripesinthedatathatappearatdifferentlocationsineachofthedatasets(i.e.attheedgeofLandsattiles).TheaverageTCCwas12.48%.WeexaminedthefulldistributionofTCCwithintheNorthwesternJaguarRecoveryUnitpolygontorepresenttheavailabilityofdifferentpercentcoverclasses,andwethencalculated,at5%

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increments,anodds-ratiooftheproportionofthenumberofobservationpointstotheproportionofthenumberoflandscaperastercellscoveredbyagivenTCCincrementtocomparehabitatusetoavailability.TCCincrementclassesthatareuseddisproportionatelytotheiravailabilityinthelandscapeareassumedtobepreferredbyjaguars;likewise,TCCclassesthatareusedlessfrequentlythanexpectedbasedontheiravailabilityareassumedtobeavoided.Wethenfitasimpleexponentialmodeltotheseobservedoddsratios,whichyieldedthefollowingrelationship:

y=0.0487e(0.0386xTCC),whereyistherelativeprobabilityofjaguaruseofarastercellwithpercentcoverTCC.OurmodelhadanR2of0.768,suggestingagoodfittothedata(Figure3).

Figure3.Anexponentialmodelassumingthathabitatuseincreaseswithincreasingtreecanopycover,fittoobservations.TopographicpositionTopographicpositionindicateswhereaparticularlocationliesrelativetosurroundingslopes(e.g.,ridgeversusvalley).Wecalculatedatopographicpositionindex(TPI)usinga30-mresolutiondigitalelevationmodel(DEM)fromtheShuttleRadarTopographyMissionv4(Jarvisetal.2008).Weusedamulti-scaleTPIinwhichtopographicpositionwasderivedusingan810and2430mradiineighborhood,andthencombinedbyaveragingthevalues(Theobaldetal.2015).TPIalsoallowsvalleybottomstobedistinguishedfromridgetops,whichpresumablyofferverydifferentdegreesofexposure/coverforjaguar.Weconsideredcalculatingaterrainruggednessindex,butthisindexiscalculatedusinga3x3windowofneighbors,itisverysensitivetotheDEMresolutionused,anditdoesnotdistinguishexposedridgesfromnarrow

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valleybottoms.Therefore,wefeltitwasinappropriateforestimatingtheinfluenceoftopographyonjaguarhabitatsuitabilityatfine-grainedscales.Wecalculatedtheodds-ratioofTPIvaluesatobservedlocationsagainstthedistributionofTPIvalues(at10-mTPIintervals)acrosstheNRU,andthenfitapolynomialmodeltoestimatetherelationship:

y=0.00008TPI+0.00007TPI2+0.0169,whereyistherelativeprobabilityofjaguaruseofarastercellwithtopographicpositionTPI.OurmodelhadanR2of0.794,suggestingagoodfittothedata(Figure4).ForTPIvaluesoutsidetherangeoftopographicpositionswherejaguarobservationsoccurred(i.e.<-130and>130),wesethabitatsuitabilityvaluesat0.1.

Figure4.Asecond-orderpolynomialmodeloftopographicpositionindexvaluesfittoobservations.DistancefromwaterWedidnotincludedistancefromwaterasaconstraintonjaguarhabitatsuitabilityforthreereasons.First,thepoorqualityofhydrologicdataandthevariabilityandperiodicityofwaterindesertenvironmentsmakeitdifficulttoadequatelyandaccuratelyrepresentavailabilityofwateracrossthestudyarealandscape.TheSandersonandFisher(2013)modelrepresented“water”byidentifyingpotentialstreams/riversusingHydroSHEDdata,butdetailswerenotprovidedintheirreport.Wededucefromsomeunpublishedgraphicsthatthestreamswere

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representedat~1kmresolution,andtheaccumulatedupstreamwatershedareaexceededathresholdof~500km2(K.Fisher,pers.comm.March2017).Althoughthisisfairlycommonpractice,estimatingthepresenceofastreambasedonwatershedareaalonedoesnotincorporateinformationaboutprecipitationorevapotranspiration,andintheNRUregion,largerpotentialflowaccumulationvaluesdonottranslatewelltoactualpresenceofreliablewatersources.Thisisbecausetheregionencompassesmanysmallmountainstreamswithephemeralwaterthatoccurinareaswithrelativelylittleupstreamwatershedarea,ascomparedtolargerupstreamwatershedareasthatoccurwherealluvialwasheshavewaterveryinfrequently.Moreover,springs,stocktanks,cienégas,andotherlocalfeaturesarelikelyimportantwaterresourcesforjaguarandtheirprey,andmightcontributesignificantlytospatialpatternsofwateravailability,butthesesourcesareverydifficulttoreliablymap.Second,iftheassumptionthatdistancetowaterisaproxyforpresenceofriparianareasandhigherdensityofhabitat,thentheTPIindexalreadyrepresentsvalleybottomsinamuchmorediscerningway.Finally,becauseofthedispersedpatternofthehydrologicnetwork,mostofthelandscapeiswithin10-kmdistanceofthemodeledstreams,andsothisfactordoeslittletonarrowjaguarhabitatsuitabilityintheuniquegeographyofthisregion.HumaninfluenceWecalculatedahigherresolutionandmorerobustmeasureofhumaninfluencethanthatusedbySandersonandFisher(2013).Thedegreeofhumanmodification(H,Theobald2010,2013)integratesmeasuresofboththefootprintextentandrelativeintensityofmanyformsofhumaninfluenceonthelandscapeinacomprehensiveandparsimoniousway.Valuesareonaratioscaleandrangefrom0.0(nohumanmodification)to1.0(highlyhumanmodified).Hwasmappedusing30--90-mresolutiondata,includinglandcoverdata(30m)fromtheNationalLandCoverDataset2011,globallandcoverforMexico(30m;Chenetal.2015),globalhumansettlementdata(300m;Pesaresietal.2015),VIIRSnight-timelights(400m),andadetailed2016roadmapfromOpenStreetMap(withadjustedweightfornumberoflanes).Therefore,HimprovesonSandersonandFisher’s(2013)humaninfluencemeasurewithmuchhigherresolution,morecontemporarydatasets,andexplicitincorporationofbothintensityandfootprintofhumandisturbance.ThemeanHvalueatsitesofjaguarobservationswasquitelow:0.055(median=0.02,SD=0.10).BecausetheHvalueswerequitelowandthedistributionwasskewedwithmanylowvaluesattheobservedlocations,wedecidedtotransformHintoanaturalnessvalue(N)thatreflectsanassumptionthathighjaguarhabitatsuitabilityisinverselyrelatedtothepresenceofhumanmodification.Weusedanexponentialfunction:

N=(1-H)2

thatassumeshabitatuseisrelatedto“naturalness,”whichistheinverseofHbutdeclinesexponentially(Figure5).

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Figure5.Anexponentialmodeltransformingthedegreeofhumanmodificationtoanaturalnessvalue.ElevationSandersonandFisher(2013)removedhabitatthatexceeded2000minelevation:"[b]ecauseonly20eventsoccurredabove2000m,theJRTtechnicalsubgroupdecidedtomaskoutareasabove2000m.”Wedecidedthatanelevationalthresholdwasnotsubstantiated,because20observationeventsabove2000msubstantiatesomejaguaruse(20eventsoutofn=102or203,dependingonevidencetypesselectedinSandersonandFisher(2013)is10-20%).Moreover,ahistogramofelevation(Figure6)intheNRUshowsthathigherelevationlocationsarefairlyrare,suggestingthatanyuseathigherelevations(>1500m)mayactuallyshowpreferentialuse,afteraccountingforlowavailabilityofhigh-elevationareas.WealsonotethatTPI,whichisanindexofrelativeelevation,capturessomeoftheseeffects.

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Figure6.Ahistogramofelevation(x-axisinmeters)intheJaguarNorthwesternRecoveryUnitarea.HighhabitatsuitabilityandcoresWecalculatedhabitatsuitability(S)astheproductofthethreevariables,representingthehabitatqualityrelatedtotreecanopy(TCC),topographicposition(TPI),andhumanmodification(N):

S=TCC*TPI*N.

Weusedtheproductofthevariablesbecauseitismorerobusttothedistributionsunderlyingeachvariablethanaddition(Tofallis2014).Foreachpixel,wethencalculatedtheaverageSvaluewithina100km2circulararea(i.e.,5,641-mradius),whichwasidentifiedbytheJaguarRecoveryTeamastheminimumareaneededtosupportajaguar,andhasalsobeenusedastheminimumpatchsizeforcorridormodeling(Stoneretal.2015).Wethenidentified“cores"ofhighhabitatsuitabilitybyapplyingtwoarbitrarybutstandardthresholds(S75,S90)wherecellswithSvaluesexceedingthe75thand90thpercentileofSformedcontiguouspatchesatleast100km2inarea.NotethatSandersonandFisher(2013)appliedasafinalstepa“habitatweight”inordertoestimateoveralljaguardensityintheNRU.WedidnotperformthisstepbecauseourgoalwastomappotentiallysuitablehabitatandstructuralconnectivitywithinandsurroundingtheNRU,ratherthantoestimatedensity.

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ConnectivitymodelWeestimatedconnectivityusingcircuittheorymodels.WemodeledconnectivityusingCircuitscape(McRaeetal.2013)whichborrowsconceptsfromelectroniccircuittheorytoestimateecologicalflow(e.g.,movementofindividuals,geneflow;McRae2006,McRaeetal.2008)amongcoreareas,ortheprobabilityofmovementfromasourcetoadestinationpassingthrougharastercellgivenitsresistancetomovement.Specifically,circuittheorymodelsareusefulforidentifying‘pinchpoints’,orbottlenecks,whereflowishighlyconstrainedasitpassesthroughlimitednaturalareasembeddedinmodifiedorotherwisehighlyresistantlandscapes.Thesepinchpointsarelikelytorepresentimportantconservationopportunities,whereimposingabarriertomovementwouldcausedisproportionatelossofconnectivity.Weestimatedresistancebasedondegreeofhumanmodificationtoidentifypinchpointswherenaturalareas,regardlessofothercharacteristics(i.e.,canopycover,topography)aremostconstrainedbyhumaninfluence.Werescaleddegreeofhumanmodification(H)torangefrom0to1,thenappliedaPower(10)transformationandconvertedtointegervaluesusingamultiplicationfactorof10,000,asCircuitscapehasdifficultysolvingnetworkswithnarrowrangesofvalues.Weidentifiedcentroidsofeach75thpercentilecoreareaassourcenodesforCircuitscapemodels.Useofcentroidsassourcenodesratherthancompletecorepolygonsnotonlyspeedsimplementation,butalsoallowsestimationofcurrentflowwithincoreareasratherthantreatingthemasuniformlyzero-resistancepatches(e.g.,Dicksonetal.2016).DesignationofS75coresresultedindelineationofoneverylargecoreinthecenterofthestudyarea(seeResultsbelow).Inthecaseofthiscore,we‘shrunk’coreedgesinwardby900mtoseparateitintotwodiscretepatchesatitsnarrowestpoint,thenidentifiedthecentroidofeachofthetworesultingpatches.Useofmultiplepointstorepresentthenorthandsouthportionsofthislarge,centralcoreresultedinbetterdistributionofcurrentflowthroughoutitsarea.WeimplementedCircuitscapeinone-to-allmode,inwhichonenodeatatimeischargedwithcurrentandallothernodesaregrounded,iteratingandsummingoverallnodes(McRaeetal.2013).Thismodeallowsestimationofecologicalflowfromeachpotentialsourcetoallpotentialdestinationsinthelandscape,whichwesuggestismostrealisticforrepresentingnataldispersalprocesses.Circuitscapeiscomputationallyintensive,andspeedandmemoryrequirementsincreaseexponentiallywithnumberofrastercellsinthelandscapeandnumberofnodesconnected.Inordertoachievereasonablecomputationtime(daysratherthanmonths),wereducedtheanalysisresolutionto540-mandlimitedconnectionsamongnodestothose<100kmapart.ResultsWecalculatedandmappedoverall,continuousjaguarhabitatsuitability(Figure7)andareaswithsuitabilityexceedingthe50th,75th,and90thpercentiles.Fromthe75thand95thpercentilesofhabitatsuitability,weextracted“cores”thatwereatleast100km2inarea(Figure8).WethencalculatedpotentialconnectivityusingCircuitscapetocalculatecurrentflowbetween75thpercentilecores(Figures9&10).Wealsocalculatedpotentialconnectivityusing

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Circuitscapeathigherresolution(90m)foralimitedportionofthestudyareacenteredontheArizona/Sonoranborder(Figure11).

Figure7.Potentialnorthernjaguaroverallhabitatsuitability(left)calculatedasafunctionoftreecanopycover,topographicpositionindex,andnaturalness(complementtothedegreeofhumanmodification),witha100km2averagingwindow.Therangeofhabitatsuitabilityqualityisshownusingalinearstretchrangingfrombrightyellow(high)tored(moderate)toblue(low).Wealsoidentified(right)highsuitabilityhabitatexceeding50th(green),75th(yellow),and90th(red)percentiles.

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Figure8.Corehabitatareas>100squarekilometersinarea(shownasblackoutlineandfilledpolygons),identifiedusing90thpercentile(left)and75thpercentile(right).TheNorthwesternRecoveryUnitisdrawnaswellforreference(ingrey).Wefound219and346“cores”atthe90thand75thpercentile,respectively.NotethatwedidnotartificiallyremovepotentialhabitatareasfromtheBajaSur,buttheseareaswereremovedbecausetheydidnotcontain100km2coreareas.AlsonotethatmanyoftheidentifiedcoresliealongoroutsidetheeasternedgeoftheNRUboundaries.

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Figure9.PotentialconnectivitymodeledusingCircuitscapefromthecentroidsof75thpercentilesuitablehabitatcores.Areasofhighercurrentflow(connectivity)areshowninyellow,moderateinred/blue,andlowindarkblue/grey.Coresareshowninblack,andcorecentroidsareshownasturquoisepoints.

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Figure10.Azoom-inofanareaontheUS-Mexicanborder.Areasofhighercurrentflow(connectivity)areshowninyellow,moderateinred/blue,andlowindarkblue/grey.Coresfrom75thpercentilehabitatsuitabilityareshowninblack,andcorecentroidsareshownasturquoisepoints.

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Figure11.ConnectivityresultsforsouthernArizonaandnorthernSonorausingahigherresolution(90m)Circuitscapemodelrun.USInterstate10isvisibleatthetopoftheimageasagreylinewindingeast-west,andMexicanFederalHighway2isvisibleinthemiddleoftheimageasablackeast-westline.Areasofhighercurrentflow(connectivity)areshowninyellow,moderateinred/blue,andlowindarkblue/grey.Coresfrom75thpercentilehabitatsuitabilityareshowninblack,andcorecentroidsareshownasturquoisepoints.

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DiscussionWemappedpotentialjaguarhabitatandstructuralconnectivityroughlyfollowingtheguidanceandlogicdevelopedbytheTechnicalSubgroupoftheJaguarRecoveryTeamasreportedinSandersonandFisher(2013),butalsoupdatedandrefinedthisapproach.Ourrefinedmodelusesmuchfiner-graineddata(30mvs.1000m)andrepresentsgradientsofhabitatqualityratherthanasimplebinaryhabitatmodel.Ourmodelsuggeststhatjaguarsshowpreferenceforgreatertreecover,valleysandridgelines,andlowerhumanmodification.Areasofhighestsuitabilityisvariable,withalargecentralportionalongtheSierraMadre,and90thpercentilecoresareamorevariableanddisconnected,especiallyinnorthernportionofstudyarea,whereas75thandparticularly50thpercentilecoresaremoreconnected.Allbut7observedlocationsfellwithinthe50thpercentile,suggestingthattheseregionsaregenerallytraversableandused,andmayalsoindicatethepotentialformovementbetween90thpercentilecores.Wenotethattheobservationlocationsarequiteadhocandthereisnoformalstatisticaldesignthatallowsstronginferenceastoareaswithlittleorfewobservations,aswellaslikelybeingbiasedtohumanaccessibilityConnectivitymodelresultssuggesthighlevelsofconnectivityamongnortherncoresandamongsoutherncores,butlittlenorth-southconnectivity(Figure9).Thismaytosomeextentbeanartifactofrepresentingthesinglelargecorespanningthecentralportionofthestudyareaascentroidsofnorthernandsouthernsub-cores,dividedataverynarrownaturalbreakpoint.Thesetwosub-corecentroidsarefarapart,andnoothercoresexistintheareabetweenthem,resultinginapparentlylittleconnectivity.However,thisportionofthelargecentralcorealsoappearstohaverelativelylowsuitability(Figure7)andismore‘permeable’comparedtoitsnorthernandsouthernextremes,soitislikelythatconnectivityhereis,infact,relativelylowaswell.Thefarsouthernportionofthestudyareaappearstohavemoreconstrictedpinchpointsamongcoresthaninthenorth.Inthenorth,currentflowgenerallyspreadssmoothlyoutfromcorecentroids,withsomelocal-scale‘funneling’ofcurrentaroundhighlydevelopedplacesoracrossroads.Inthesouth,however,flowamongadjacentcorestendstobeconstrainedtomuchmoredistinct,linearroutesbetweenmoreextensivelymodifiedareasofthelandscape.Theseremainingpathsofferimportantconservationopportunities.RelativelyfewareasofhighpotentialconnectivityacrosstheU.S.-Mexicoborderappeartoexist.EastofNogales,ourmodelsuggestshighpotentialflowbetweentwocoresinrelativelycloseproximityoneithersideoftheborder.ProvisionsforjaguarinthisareamaybecriticalfortheircontinuedabilitytomoveacrosstheborderifUSbordersecuritymeasurescontinuetoescalate.MaintainingconnectivityfromthesetwocorestonearbycoresoneachsidesoftheborderwillalsobeneededtoensurecontinuedgeneflowthroughouttheNRUviadispersalmovements.Overall,wefoundreasonableconcordancebetweenourmodelsofpotentiallysuitablehabitatandconnectivitywithknownobservations--boththoseusedinourmodel,aswellasthe

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additionalpointsnotusedinourmodelsuchasthosefoundinArizona(Figure12).Notethatwedidnotincorporatetheseadditionalpointsdirectlyinthemodelbecausewewereunabletoobtaintheprecisex,ylocationsinthedownloadedobservationdataset,althoughthepointsareclearlyviewableinthemapsontheJaguarData.infowebsite.OurmodelalsosuggeststhattheexistingNRUdefinitiondoesnotincorporatesomepotentiallysuitableandconnectedhabitatpresentedinourresults,bothtotheeastinMexico,aswellastothenorthinsouthernArizona.Thesefindingsprovidepreliminarysupportforconsideringanextensionoftheboundariesofthejaguarrecoveryunitintotheseareaswithsuitable,connectedpotentialhabitat.IntendedusesandcaveatsWeintendtheseresultstobeusefulinunderstandingpotentialsuitablehabitatthatincludesstructuralconnectivityforjaguarextendingbeyondtheNRUboundaries(uptoroughly300km).AnotherkeydistinctionbetweenourmodelandthatofSandersonandFisher(2013)isthatwedidnotimposeanyfactorthatdepictsthecurrentestimateddensityofjaguarsassociatedwithdifferentecoregionalareas(i.e.,“habitatweights”).Also,weobservethat4oftheobservedjaguarlocationsarenotlocatedintheNRU(ascomparedto7outsideoftheS50habitat).Thestructuralconnectivitymapsareintendedtoprovidegeneralguidanceforpotentialjaguarconnectivitybetweencorehabitatareas,buthaveonlypreliminaryutilityinidentifyingspecificpotentialhighwaycrossingsataveryfine-scaleoratthesite-planninglevel(e.g.,wheremovementwouldoccurwithin<3kmstretch).Itisimportanttoconsiderthattheobservationaldata,whilequiteusefulingeneratinggeneralsuitabilitymodels,areobtainedonanadhocbasis–andthereforedonotrepresentacarefullystructuredstudydesign.Duetothenatureofthedataused,modelresultsmaybeaffectedbysamplingbias,especiallybecausewewereunabletoincorporateabsencedata.Moreappropriatedata,particularlyastratifiedsampleofpresence-absence(HirzelandGuisan2002),wouldbeideal,butsuchdatadoesnotexistforthestudyarea.Finally,wemappedpotentialjaguarhabitatandstructuralconnectivityonthebasisofrelativelylimitedobservationsthatwereavailable,andwehopetoupdateandfurtherrefinethemodelwithadditionalobservations.

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Figure12.Ourmodelofpotentialsuitablehabitatdoesareasonablejobpredictinghabitatcomparedtothelocationsofknownjaguarobservations.Pointsusedinthemodelareshownasblackdots,andadditional(‘validation’)observationsnotincludedinthemodelareshownincyan.Therangeofhabitatsuitabilityqualityisshownrangingfromhighsuitabilityhabitatat50thpercentile(green),75th(yellow),and90th(red).NotethathabitatonBajaCaliforniawastoolowandsmalltobeconsideredhabitat“cores”at75thand90thpercentile.

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AcknowledgementsWegreatlyappreciatefundingprovidedtoconductthisworkbyWilburforceFoundation,sharingofdataandmodelingmethodsbyK.FisherandE.SandersonoftheWildlifeConservationSociety,andbroaderdiscussionsofjaguarconservationwithMAlanen,JCBravo,andLNorman.ReferencesChen,J,JChen,ALiao,etal.2015.Globallandcovermappingat30mresolution:APOK-based

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