Quantifying forest fire impacts in Sabangau peat swamp ... · Shari Lynn Mang Student Number:...

QuantifyingforestfireimpactsinSabangaupeatswamp

forestandtheconsequencesforBorneanorangutan

densityandhomerange

ShariLynnMang

StudentNumber:660051446Supervisor:Dr.FrankvanVeen

UniversityofExeter,CollegeofLifeandEnvironmentalSciencesMasterofScienceDissertation

August2017

TargetJournal:BiologicalConservation

Biologicalconservationisaleadingjournalinconservationbiologyandfocusesonresearchthatinformsand

advances conservation.My research examining how the ranging and density dynamics of orangutans are

impactedbyforestfiresmeetsthejournalsaimsofpublishingresearchfocusedon“theconsequencesofhuman

action for diversity” and articles “that contribute to biological…. dimension of conservation and natural

resourcemanagement”. As Bornean orangutans are an endangered species and forest fires are linked to

humanactivity,myresearchiswellsuitedforthis journal’saudience.Biologicalconservationisalsoawell-

regardedjournal,withthethirdhighestimpactfactorinthefieldofbiodiversityconservation.

TableofContents

Abstract…………………………………….………………………………………….……………………………………………………….11.Introduction………………………………………….…………………………………….……………………………………………22.Methods………………………………………….………………………………………….…………………………………………….4

2.1Studyareaandspecies………….………………………………………….………………………………………..52.2Estimatinghabitatlossduetofire………….………………………………………….……………………..5

2.2.1Data.………….………………………………………….………………………………………………………..52.2.2Landcoverclassification…….………………………………………….………………………………..6

2.3Orangutandensity………….………………………………………….……………………………………………….82.3.1Data………….………………………………………….…………………………………………………………82.3.2Statistics………….………………………………………….…………………………………………………..9

2.4Orangutanhomerange………….………………………………………….……………………………………..102.4.1Data………….………………………………………….……………………………………………………….102.4.2Analysis………….………………………………………….………………………………………………….112.4.3Statistics………….………………………………………….…………………………………………………11

3.Results…………………………………….………………………………………….……………………………………………………113.1Orangutandensityandchangeinforestcover………….…………………………………………..11

3.1.1Changeinforestcoverduetofire..………………………………………….…………………….113.1.2Orangutandensity………….………………………………………….………………………………….153.1.3Changeinorangutandensityandforestcover………….……………………………….....17

3.2Orangutanhomerange………….………………………………………….……………………………………..204.Discussion………….………………………………………….……………………………….……………………………………….22

4.1Changeinforestcoverduetofire.………………………………………….……………………………...234.2Orangutandensityandchangeinforestcoverduetofire……….…………………………..24

4.2.1Overallchangesindensityandforestcover……….………………………………………….244.2.2Variationindensityandforestcoverchangesamongsub-habitats……….………254.2.3Displacementandchangeinorangutandensity……….……………………………………26

4.3Orangutanhomerange………….………………………………………….……………………………………..294.4Long-termeffects………………………………………………………………………………………….....304.5Futureresearch………….………………………………………….………………………………………………….31

5.Conclusions………….………………………………………….……………………………………………………………………..32Acknowledgements………….………………………………………….…………………………………………………………….33References………….………………………………………….……………………………………………………………………………34Appendix1:SupplementaryMethods………….………………………………………….……………………………..43Appendix2:SupplementaryResults………….………………………………………….………………………………..57

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Abstract

Borneo’speatswampforestssupport thehighestdensityofBorneanorangutans,yetareoneof themost

vulnerable ecosystems to fire. Despite the prevalence and destruction of fires in Borneo, there is little

informationontheconsequencestoendangeredorangutans.Here,Iinvestigatedtheimpactsofforestfires

on the world’s largest remaining orangutan population in Sabangau, Central Kalimantan, Indonesia. I

estimatedhabitat lossdue to fire in2006,2010,and2015byclassifying landcover fromLandsat satellite

images.Icoupledthiswithorangutandensitydatafrom2002to2017fromtheBorneoNatureFoundation

(BNF)toevaluatelong-termandfireinducedchangesinpopulationdensity.Toassessshiftsinhomerange

sizeinunburntforestassociatedwiththe2015forestfires,Ievaluatedannualhomerangesfrom2003to2017

for20adultand10adolescentfemalesfromspatial-temporaldataprovidedbyBNF.Theresultsshowedan

830km2declineinforestcoverandanestimatedpopulationincreasefrom5154to8775frompre-fire2006

topost-fire2015.Thepopulationincreaseislinkedtothesignificantincreaseinorangutandensityfrom2002

to2017inthetall-interiorforestandmixed-swampforestinteriorandperimetersub-habitats.Ifoundthat

densitysignificantly increasedpost-fire in themixed-swampforestsub-habitat for9of the11 fireseasons

examined,includingthemajorfireeventsin2006and2015.However,homerangesizedidnotsignificantly

vary after the 2015 fire or between adult and adolescent females. This research shows that despite the

decreaseinforestcoverduetoforestfires,Sabangau’sorangutanpopulationhasincreasedinsizeanddensity.

Displacementofindividualsfromburntareasmaybecontributingintheincreaseddensity,buttheredoesnot

appear tobenegative impacts to thepopulationas it is still increasingand femalesmaintainstablehome

ranges. However, orangutans’ slow life history and long reproductive cyclemay delay the onset of some

consequences. Future burning of Sabangau’s forests should be mitigated to avoid compromised habitat

quality,overcrowding,andabreachofcarryingcapacity.

Keywords:Borneanorangutan,forestfire,Sabangau,peatswampforest,density,homerange

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1.Introduction

WhileBorneo’sforestshavesomeoftheworld’shighestbiodiversityandendemism(Woodruff,2010),Borneo

alsohassomeofthehighestratesofforestdegradation(Miettinenetal.,2011;Sodhietal.,2004)andmost

damagingforestfires(Taylor,2010).Indonesiahasalonghistoryofresourceextraction(Gaveauetal.,2014),

andsincethe1980s,peatswampforestshavebeenincreasinglydegradedbylegalandillegallogging(Tsujino

etal.,2016;Yule,2010),plantationdevelopment(Margonoetal.,2014;MiettinenandLiew,2010),drainage

andlanddevelopment(Yule,2010),andforestfires(Fieldetal.,2009). Indonesiacontainsoverhalfofthe

world’stropicalpeatswampforest(Pageetal.,2006)withalmost68,000km2historicallyfoundinKalimantan

(Posaetal.,2011).However,by2004only47%ofKalimantan’speatswampforestremained,11%ofwhich

wasprotected(Posaetal.,2011).Fortheunique,oftenendemicandendangered,floraandfaunasupported

bypeat swamp forests (Miettinenetal., 2012), thishas causeda severe lossofhabitat (Cochrane,2003),

alteredspeciescompositionandcommunitystructure(Sliketal.,2010),andreducedpopulations(Ancrenaz

etal.2016;Nijmanetal.,2008).

ForestfiresdonotnaturallyoccurinBorneo(Pageetal.,2002;Turetskyetal.,2015)butnowburn

annually(Chisholmetal.2016)largelyduetointentionallysetfires(Simorangkir,2007;Usupetal.,2004)and

reducednatural fire resilience fromyearsofhabitat lossanddegradation (Miettinenetal.,2012;Tacconi,

2016).ThemostsevereeventsarecorrelatedwithextremelystrongElNiño-SouthernOscillation (ElNiño)

episodes(Siegertetal.,2001;Yuliantietal.2012)thatcauseprolongeddrought,exacerbatingforests’reduced

fireresilienceandfacilitatingthespreadandintensityoffires(Chisholmetal.,2016;Fieldetal.,2009;Wooster

etal.,2012).Borneo’s2015fires,whichcoincidedwithastrongElNiñoandextremedrought(Yuliantietal.

2012; Tacconi, 2016), were theworst fires since the 1997-1998 El Niño fires (Chisholm et al., 2016) and

affected1.287millionhaofKalimantan’sforests(Tacconi,2016).

PeatswampforestsaresomeofBorneo’smostvulnerableecosystemstofire(Pageetal.,2009a;Posa

etal.,2011),aslogginganddrainageincreasethedensityofunderstoryspeciesanddeadvegetation(Siegert

etal.,2001),lowerthewatertable,anddryouttheforestfloorandlayersofpeatsoil,generatingabuild-up

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ofextremelyflammabledrysoil(LangnerandSiegert,2009;Turetskyetal.,2015;Wöstenetal.,2006).Peat

firesaredifficulttoextinguishastheypenetratedownthroughpeatlayerswheretheycanburnformonths

(Yule,2010),spreading laterally throughthe forests, ignitingabovegroundfires inareaswithno localheat

source(Chisholmetal.,2016;Usupetal.,2004).Consequently,speciesfarfromignitionsourcesarestillat

riskfromforestfires.This includesBorneanorangutans(Pongopygmaeus),whoarefoundattheirhighest

populationdensityinpeatswampforest(Russonetal.,2001;vanSchaiketal.,1995).

Habitatdegradation,includingforestfires(Chisholmetal.,2016;Drake,2015;Fieldetal.,2009),have

contributedtothe64%declineintheBorneanorangutanpopulation(Ancrenazetal.2016).Orangutans’slow

lifehistory,longinter-birthinterval(GaldikasandAshbury,2013;Leightonetal.,1995;Marshalletal.,2008),

and lowpopulationdensity (Johnsonetal.,2005;Morrogh-Bernardetal.,2003)makethemvulnerable to

stochasticeventssuchasfires(RijksenandMeijaard,1999).Althoughresearchislimitedontheimpactsto

orangutans, theyarehighlysensitive tosomeof thepossibleconsequencesof fires, suchas reduced food

resources (Cant, 1980; Carne et al., 2015; Felton et al., 2003; Husson et al., 2009), degraded ecosystem

structure(Feltonetal.,2003),andrefugeecrowding(RijksenandMeijaard,1999).However,theimpactwill

varywithfireintensity(Pageetal.,2009b),thepopulation’ssizerelativetocarryingcapacity,andecosystem

recoverypotential(Chisholmetal.,2016).Longtermpopulationconsequencesmayarise,asadecreasein

theiralreadylowbirthrate(GaldikasandAshbury,2013;Wichetal.,2008)duetoincreasedcompetitionand

reducedresourceswillmake itdifficult torecover fromthepotential indirectordirect increasedmortality

fromfires(Marshalletal.,2008).

Despitethefrequencyanddevastationofforestfires,there isa lackofresearchonthe impactsto

orangutanpopulations.Toaddressthisknowledgegap,thisresearchaimedtoquantifytheeffectsoffireon

theworld’slargestremainingorangutanpopulationinSabangau,CentralKalimantan,Indonesia.Todothis,I

1) estimated habitat loss due to fire and the associated change in population, 2) assessed the long-term

populationdensitytrendswithafocusonthechangeindensityaftereachfireseason,and3)assessedwhether

female home range size differed before and after a fire in a neighbouring unburnt area. I predicted that

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orangutandensitywouldincreaseandfemalehomerangesizewoulddecreasefollowingafire.Ifocusedon

females’homerangesas femalesarephilopatric (Morrogh-Bernardetal.,2003;SingletonandvanSchaik,

2002)withtemporallystableranges(Galdikas,1988;SingletonandvanSchaik,2001;Wartmannetal.,2010)

andoftenremainintheirestablishedrangeintheeventofdisturbance(vanNoordwijketal.,2012).

2.Methods

2.1Studyareaandspecies

ThisstudyfocusesonSabangauNationalParkinCentralKalimantan,Indonesia(2°19’Sand113°54’E).Thearea

usedfortheorangutandensityandforestcoveranlaysisisdefinedastheregionboundbytheSabangauand

KatinganRivers,whichcoversanareaof6996km2(Figure1).Sabangauisapeatswampforest(PSF)madeup

offoursubhabitats:mixed-swampforest(MSF),low-poleforest(LPF),tall-interiorforest(TIF),andvery-low

canopy(VLC).Thehomerangeanalysisuseda9km2researchplotwithinSabangau’sMSFalongthenorthpart

oftheSabangauRiver.

SabangauisthelargestcontiguouspeatswampforestremaininginKalimantanandsupportsthe

largestorangutanpopulationintheworld(Singletonetal.,2004).Likeotherpeatswampforests,itisrichin

biodiversity,supportingpeatlandspecialistsandmanyotherendangeredspecies(Morrogh-Bernardand

Husson,2002;Hussoneta.,2007).Inadditiontotheorangutansub-speciesP.p.wurmbii,Sabangausupports

Borneanwhite-beardedgibbons(Hylobatesalbibarbis),cloudedleopards(Neogelisnebulosi),andrhinoceros

hornbills(Malacocinclaalbogulare)(Pageetal.,2006).

Sabangau experienced selective logging prior to its national park designation in 2004 (Morrogh-

Bernard,2009).However,itisstillatriskfromillegallogging(Tsujinoetal.,2016;Wichetal.,2012;Yule,2010)

anddegradationbyforestfires,particularlyastherehasbeenextensivedrainageofthepeatforconversion

to plantations and logging (Rijksen andMeijaard, 1999). Fires occur annually in Sabangau, but themost

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extensivefiresinrecentyearshavebeenin2006,2010,and2015(Morrogh-Bernard,pers.comm.;Tacconi,

2016;Yuliantietal.,2012).

Figure1:The6996km2Sabangaustudyarea(blackoutline)boundbytheKatinganandSabangauRiversandthe9km2researchplot(redstar)inSabangauNationalPark,CentralKalimantan,Indonesia.2.2Estimatinghabitatlossduetofire

BelowisasummaryofthemainmethodsIusedtoestimatehabitatlossduetofireusingsatelliteimagesand

landcoverclassificationtools.Formorecomprehensivedetailsofthemethods,pleaseseeAppendix1.

2.2.1Data

IusedimagesfromtheLandsatsatelliteseriestoclassifylandcoverbeforeandaftereachfireeventforthe

threeyearsofinterest:2006,2010,and2015.ImagesarefreelyavailablefromtheUnitedStatesGeological

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Survey (USGS) Earth ResourcesObservation and Science (EROS) Data Centre via their Earth Explorerweb

interface(http://earthexplorer.usgs.gov/).

For each year, I examined 8-day composite images of active fires from theModerate Resolution

Imaging Spectroradiometer (MODIS) satellite product MOD14A2 acquired from Earthdata

(https://earthengine.google.com)todeterminethestartandendofeachfireseason.Basedonthisevaluation,

IonlyselectedLandsatimagesfromDecembertotheendofJuly,astherewerenofiresobservedinSabangau

duringthosemonths,whichwassupportedbymonthlyfirehotspotanalysisdonebyYuliantietal. (2012).

Whenpossible,Ipreferentiallyselectedpre-fireimagesatthebeginningofthefireseason(i.e.July)andpost-

fireimagesattheend(i.e.December).TheimagesanddatesIusedforclassificationareinAppendix1,Table

A1.1.

2.2.2Landcoverclassification

Priortoclassification,IradiometricallycorrectedtheimagesinENVI5.4toenabletemporalcomparison(Lu

andWeng,2007;Youngetal.,2017).IthenprojectedtheimagestotheUniversalTransverseMercator(UTM)

project,Zone50South inArcMap10.5,which Iusedfortheremainderof theanalysis. Iusedamaximum

likelihoodsupervisedclassification(MLC)approach(Lietal.,2014;LuandWeng,2007)toclassifytheimages

into nine land cover classes (Table 1). Following the classification, I processed the images to improve the

qualityoftheclassification(Stefanovetal.,2001;LuandWeng,2004)byreducingthenoiseintheimage(Lu

andWeng,2007;Wijedadaetal.,2012)andidentifyingthelandclassescoveredbycloud,cloudshadow,haze,

andnullclassesandconvertedthemtotheappropriateclassification.

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Table1:Descriptionoflandcoverclassesusedintheclassification.Category LandCoverClass Description

Forest Peatswampforest(PSF)

Undisturbedpeatswampforest,oldre-growthwithminimaldisturbancefromfireorlogging;includessomeoldsecondaryforestthatwaspreviouslyloggedandcannotbedistinguishedfromundisturbedpeatswamp

Non-Forest

Burnscar Recentlyburntarea;bareearthwithlittletonovegetation.

Degradedforest

Peatswampforestthathasbeendegradedbyloggingand/orfire.Includesareasofopencanopypeatswampandareasofrecent,minimalvegetationre-growththatexhibitsdistinguishabletextureandreflectancefromprimaryandoldre-growthpeatswampforest.

Sedge Areasofnon-woodyvegetationandtheriversandfloodedpeatcontainedwithinthem.

Water Riversandlakesincludingseasonallyfloodedareas.

NoData

Cloud Cloudthatwasnotremovedbythecloudmask.

Haze Thin,wispycloudthatwasnotremovedbythecloudmask.

CloudShadow Cloudshadowthatwasnotremovedbythecloudmask.

Null SLC-offnodataareasthatwerenotcorrectedbythelocalhistogrammatchingmethod.

To evaluate land cover changeswithin each sub-habitat, I used Ehlmer Smith and Ehlmer Smith’s

(2013) classification and shapefiles which divide Sabangau in four sub-habitats: MSF, LPF, TIF, and VLC

(Appendix1,FigureA1.1).IfurtherdividedMSF(referredtoasMSF-total[MSF-T])intoMSF-interior(MSF-I)

andMSF-perimeter(MSF-P)tocoincidewiththeorangutandensitydata.

AsSabangau isaprotectedarea, Iassumedthatallobservedchanges in forestcoverweredue to

forestfire,however,IacknowledgethatillegalloggingmayoccurinSabangau(Tsujinoetal.,2016;Wichet

al.,2012;Yule,2010).Iftheloggingwasextensiveenough,itmaybeclassifiedasdegradedforestbytheMLC,

but as illegal activityhas slowed in Sabangau (OuTrop,2012), itwould likelybe small relative to thearea

damagedbyfire.

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2.3Orangutandensity

2.3.1Data

Orangutandensitydatafrom2002to2017intheformofnestcountswasprovidedandisownedbySimon

Husson. It was collected monthly for MSF from the 9 km2 research plot along the Sabangau River. Two

transectswereusedforeachMSF-IandMSF-Pthatwere6kmand7kmlong,respectively.DataforTIFwas

gatheredonceayearin2002-2005,2008,2011,2013,and2016andforLPFin2002,2004-2006,2008,2009,

2011,and2013.Theseareasweresurveyedduringthedryseason(JunetoSeptember)fromvariouslocations

each year along two transects each that varied in length from 4 - 5.5 km and 6 – 8 km for TIF and LPF,

respectively.TheydidnotgatherdensitydatafromVLC.

Iconvertedthenestcountstoorangutandensity(individuals/km2)followingthemethodsinMorrogh-

Bernardetal.(2003)andusedtheSabangauspecificparametersprovidedinHussonetal.(2008).

Ifirstcalculatednestdensitiesfromnestcountswiththeformula:

Nd=Nc/(lxw)

WhereNd=nestdensity,Nc=nestcount,l=transectlengthandw=transectwidth(0.042kmforalltransects).

Ithenconvertednestdensitytoorangutandensityusingtherelationship:

D=Nd/(pxrxt)

WhereD=orangutandensity(individuals/km2),p=proportionofnestmakersinthepopulation(0.89),r=rate

ofnestproduction(1.16/individual/day),andt=timeanestremainsvisible(365days)(Hussonetal.,2008;

Morrogh-Bernardetal.,2003).

Togenerateacompletelong-termdensitydataset,Iestimatedorangutandensityforthemissingyears

inTIFandLPF.IfirstcalculatedtheratiosbetweenMSF-IandMSF-PwithbothTIFandLPF.Iusedtheaverage

foreachratio(i.e.LPF:MSF-IandLPF:MSF-P)tomaketwodensityestimatesforeveryyear.Ithencalculated

thedeviancefromthetruedensityinyearswithTIFandLPFobservationsandusedtheratiothatledtothe

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lowest average deviance, which was TIF:MSF-P and LPF:MSF-I, to estimate the missing density values

(Appendix1,TableA1.4).

AstheMSFdatawasgatheredmonthly,Iusedittoevaluatevariationinpre-andpost-fireorangutan

density.Foreachyearfrom2002to2016,IdividedtheMSF-T,MSF-I,andMSF-Pdataintopre-fire,during-

fire,andpost-firecategories.ThefireseasoninBorneovariesannually(LangnerandSiegert,2009),butusing

theMODISsatelliteproductMOD14A2(Section2.2.1)IfoundSabangau’sfiresoccurredfromAugusttothe

endofNovember.ThisagreeswithYuliantietal.(2012)whofoundAugust,September,andOctobertohave

thehighest incidenceof fires inCentralKalimantan.Accordingly, Iassigned ‘during-fire’asAugustthrough

November,‘pre-fire’asDecemberthepreviousyearthroughJuly,and‘post-fire’asDecemberthroughJuly

thefollowingyear.

2.3.2Statistics

IperformedallstatisticalanalysisinSPSS(version24).Aftertestingorangutandensitydatafornormality,Iran

alinearregressionforeachsub-habitattotesttheinfluenceoftimeonorangutandensity.Ialsousedalinear

regressiontodeterminewhetherdensitywasaffectedbyhabitattypeovertime;Ifollowedthiswithaone-

wayANOVAandTukeyHSDposthoctodeterminewheresignificantvariationoccurred.

Asdensity increasedover time, I used the linearequation tode-trend thedataby calculating the

residualdensityforMSF-P,MSF-I,andMSF-T.Fortheseregions,Iperformedalinearregressiontodetermine

whetherorangutandensitywasinfluencedbyforestcover,ascalculatedfromtheMLCforpre-andpost-fire

2006,2010,and2015.Iusedapairedt-testtoevaluatevariationbetweenpre-andpost-fireorangutandensity

ineachMSFsub-habitat from2002 to2016.Although there isa linear increase indensity throughout the

study,Iusedthemeasuredorangutandensityforpairedt-testanalysis;thelong-termdensityincreaseshould

minimallyinfluencethe8-monthpre-andpost-fireperiodsasorangutans’havealong-lifehistoryandinter-

birthinterval(Leightonetal.,1995;Marshalletal.,2008).

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2.4Orangutanhomerange

2.4.1Data

Todetermineorangutanhome range size, I used followdataprovidedandownedbyDr.HelenMorrogh-

Bernard of the Borneo Nature Foundation (BNF) that was collected from September 2003 toMay 2017.

Surveysweredoneinthe9km2researchplotalongtheSabangauRiver.Observersusedoneof12N-Sor12E-

Wtransectstolocateanorangutanandthenfollowedtheindividual,recordingtheirlocationonaGPSevery

30minutesforfollowsbetween2003and2011,andevery5minutesfrom2011onward.Observerstracked

anindividualforamaximumoftenconsecutivedaysoruntillost.Thenumberofsurveysdoneeachyearis

variable,withamaximumof259in2005andaminimumof57in2010.ToconverttheGPSdatafrompoint

datatodecimaldegrees,IusedExpertGPS6.0.

Thedataincludes10adolescentfemales(ADF)and20adultfemales(AF),2ofwhichwerefollowed

fromadolescenceintoadulthood.Iseparatedindividualsbyage-classfortheanalysisashomerangesizevaries

amongorangutanage-sexclasses(Galdikas,1988;Morrogh-Bernard,2009;SingletonandvanSchaik,2001).

ADFaredistinguishedfromAFinthattheformerarenon-sexuallyactiveandliveindependentoftheirmother,

whilethelatteraresexuallyactiveandoftenaccompaniedbyaninfant(Morrogh-Bernard,2009).

I used theaforementionedMOD14A2 images (Section2.2.1) todateSabangau’s2015 fire season,

whichIdeterminedtobefromAugust5thtoNovember8th,2015.Basedonthis,Iclassifiedeachorangutan

followaspre-fire(September9th,2003–August4th,2015),during-fire(August5th–November8th,2015),or

post-fire(November9th,2015–May18th,2017).Nofiresburnedinsidetheresearchplot(Morrogh-Bernard,

pers.comm.),buttwooccurredeastandsouthwestofthestudysite,bothlessthan1kmaway.

Iestimated individuals’ residencestatusbycalculating theirpresence index (Kj), as thenumberof

monthstheyweresighteddividedbythelengthofthestudy(SingletonandvanSchaik,2001). Icalculated

annualKj(JanuarytoDecember)tocapturechangesinresidencyovertime.For2015,Icalculatedannual,pre-

fire, during-fire, and post-fire Kj values.Using the Kj score, I classified individuals as Frequent (Kj ≥ 50%),

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Regular(25%≤Kj<50%),Occasional(4%≤Kj<25%),orRare(Kj≤4%)(Appendix1,TableA1.5).Iconsidered

FrequentandRegularindividualstoberesidentsofthepopulation.

2.4.2Analysis

ThedatawasprojectedintotheUniversalTransverseMercator(UTM)WorldGeodeticSystem(WSG)198450

South coordinate projection in ArcMap 10.5. I estimated individuals’ annual home range size using the

minimumconvexpolygonmethod(MCP)(Boyleetal.,2009;Hayne,1949).MCPlinkstheoutmostpointsto

generateavectorpolygonandiscommonlyusedtoestimateorangutanhomerange(Campbell-Smithetal.,

2011;Morrogh-Bernard,2009;SingletonandvanSchaik,2001;Wartmannetal.,2010).Togetanaccurate

estimateofhomerangesize,Ionlyanalyzedresidentsofthepopulationastheyhadthemostdataandshould

havestablehomeranges(Morrogh-Bernard,2009).

2.4.3Statistics

IperformedallstatisticalanalysisinSPSS(version24).AshomerangesizewasnormallydistributedforAFand

ADF,Iusedalinearregressiontodeterminewhetherthenumberoffollowsinfluencedanindividuals’annual

homerangesize.Ialsousedalinearregressiontoexaminewhetherhomerangesizewithineachage-class

variedovertime.Iusedagenerallinearmodel(GLM)totestwhetherhomerangesizevariedpre-topost-fire

andbetweenage-classes.Only4residentAF(Feb,Gracia,Indah,andIndy)weresampledpre-andpost-fire

2015, so Iuseda sign test todetermine if theiraveragehomerangesizevariedbeforeandafter the fire.

3.Results

3.1Orangutandensityandchangeinforestcover

3.1.1Changeinforestcoverduetofire

BasedontheMLC,2006hadthegreatestdecreaseinforestcoverat562.2km2followedby2015(510.3km2)

then2010(277.3km2)(Figures3,4,5;Appendix2,TableA2.1).Betweenfireevents,forestcoverincreased

butnevertopreviouslevels,leadingtoa14.8%decreaseinforestcoverbetweenpre-fire2006andpost-fire

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2015.Asaresult,thepercentoftheSabangauclassifiedaspeatswampforestdeclinedfrom80.4%to68.5%,

withtheremainderbeingpredominantlyclassifiedasdegradedforestandburnscars.Burninganddegradation

wereconcentratedaroundtheforestperipheryandalongrivers,sedge,anddevelopedarea.Althoughthe

percentincreaseinburnscarareawashigherin2006(282.4%)thanin2015(99.7%),thepost-fireburntareas

weresimilar(2006=897.4km2;2015=843.9km2)duetoextensiveburnscarspre-fire2015.Whileburnscars

oftenreplacedareasclassifiedaspeatswampforest, theyalsooccurred in regionspreviouslyclassifiedas

degraded.Frompost-fire2006topre-fire2010,sedgeexpanded(9.9km2to95.0km2)predominantly into

areaspreviouslyclassifiedasburnscarordegradedforest.However,therewasanoveralldecreasefrom62.4

km2to11.2km2bypost-fire2015withsedgebeingreplacedbyburnscarsanddegradedregions.

Figure3:LandcoverclassificationforSabangaupre-fire2006(07-06-2006)andpost-fire2006(04-07-2007)basedontheoutputfromtheMLC.Theblackstarrepresentsthe9km2researchplot.

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Based on the sub-habitat division provided by Ehlmer Smith and Ehlmer Smith (2013), MSF-T

constitutes53.8%(3761.2km2)ofthetotalstudyarea,2137.2km2ofwhichisMSF-I.LPFisthenextlargest

sub-habitatat1907.0km2followedbyTIF(1044.6km2)andVLC(283.0km2).Figure6showstheproportionof

eachsub-habitatclassifiedasforestbytheMLCforeachperiod.Theremainderofeachsub-habitatconsists

ofnon-forestclasses,predominantlyburnscarsanddegradedforestwithminimalareaclassifiedassedgeand

water(Appendix2,TableA2.2).Withineachsub-habitat,MSF-Phadthegreatestpercentdecreaseinforest

covereveryyear(2006:28.9%;2010:13.3%;2015:22.0%)leadingtoanoveralldecreaseof44.9%bypost-fire

2015.TogetherwithhighannualforestcoverlossesinMSF-I(2006:14.7%;2010:7.4%;2015:14.8%),MSF-T

forestcoverdeclinedby29.9%.Theremainingsub-habitatshadmuchlowerannualandtotalchange;overall,

forestcoverinTIFandVLCdeclined5.9%and3.1%,respectively,andforestcoverinLPFincreasedby0.3%.

Figure6:Theproportionofeachsub-habitatthatwasclassifiedasforestinSabangauforpre-andpost-firein2006,2010,and2015.ValuesarebasedonlandcoverclassificationbytheMLC.

Frompre-fire2006topost-fire2015,theproportionofSabangau’stotalforestcoverwithinMSF-P

and MSP-I decreased due to their greater forest loss relative to the other sub-habitats (Figure 7). This

proportionincreasedinLPF,TIF,andVLC,withthelargestincreaseinLPFfrom0.31to0.37,representinga

15

17.7%increase.MSF-Psawthelargestdecline,from0.16to0.10,representinga35.3%decrease.Whilethe

proportionoftotalforestcoverdeclinedinMSF-I,itstillconstitutesthesecondhighestproportionat0.27in

post-fire2015.

Figure7:TheproportionofSabangau’sforestcoverineachsub-habitatforpre-andpost-firein2006,2010,and2015.ValuesarebasedonlandcoverclassificationbytheMLC.3.1.2Orangutandensity

Bothtimeandsub-habitatexplainasignificantamountofvariationinorangutandensity(R2=0.907,F(4,59)=

143.981,p< 0.001),with a significant difference between all sub-habitat pairs (MSF-P andMSF-I, F(3,60)=

53.595,p=0.005;allotherpairs:F(3,60)=53.595,p<0.001)exceptforMSF-IandLPF(F(3,60)=53.595,p=0.051)

(Figure8).Aswell,thelinearregressionshowedasignificantincreaseinorangutandensityfrom2002to2017

inallsub-habitatsexceptLPF(MSF-P:R2=0.812,F(1,129)=558.840,p<0.001;MSF-I:R2=0.715,F(1,129)=323.525,

p<0.001;TIF:R2=0.890,F(1,14)=113.101,p<0.001;LPF:R2=0.235,F(1,14)=4.298,p=0.057).

16

Figure 8: Annual orangutan density in each sub-habitat from 2002 to 2017.MSF-P andMSF-I are yearlyaveragesbasedonmonthlymeasurements.LPFandTIFaresingleannualmeasurements,withfilledcirclesbeing fieldobservationsandopen trianglesbeingestimatesbasedon the ratiosTIF:MSF-PandLPF:MSP-I.(MSF-PandMSF-I:n=4in2017;n=6in2015;n=8in2003,2007,2009,2011,and2016;n=9in2002,2004,2005,2006,2008,2010,2012,2013,and2014.LPFandTIF:fieldobservations:n=8;estimates:n=8)

TIFhad thehighestdensity through theentire studyaswellas thegreatest rateof change (0.118

individuals/km2/year). MSF-P andMSF-I experienced similar rates of change in density (0.066 and 0.072

individuals/km2/year,respectively),withMSF-Pmaintainingahigherdensitythroughout.Apartfrom2002and

2003,LPFhadthelowestorangutandensityandshowedlittleincreaseovertime(0.029individuals/km2/year).

Theresidualdensity for theMSFsub-habitatsshowsanoscillationwithinthe increasingtrends for

thesesub-habitats(Figure9;Appendix2,FigureA2.1).Thesingletrough,fromlate2008tolate2011,isflanked

bytwopeaks,themostrecentofwhichmaybeshowingthestartofadownwardtrend.Thispatternismost

prominentinMSF-I,withmorevariationintheresidualdensityinMSF-P.

17

Figure9:ResidualorangutandensityforMSF-TfromJanuary2002toMay2017(n=131).3.1.3Changeinorangutandensityandforestcover

Bycombiningtheorangutandensitydatawithestimatesofforestcover,IestimatedSabangau’sorangutan

populationpre-fire2006as5154individuals;bypost-fire2015,Iestimatethepopulationincreasedby3612

to8775individuals(Appendix2,FigureA2.2,TableA2.3).However,thisestimateexcludesindividualsinVLC,

astherewasnodensitydataforthissub-habitat.

Thechangeinpopulationandforestcoverisnotevenlydistributedthroughoutthesub-habitats.Over

thestudy,MSF-Phad the largestdecrease in the forestcover (24.2%)andpopulation (16.6%) (Figure10).

AlthoughtherewasadecreaseinforestcoverinMSF-I(17.6%)andTIF(5.7%),thepopulationincreasedin

bothby46.8%and96.3%,respectively.LPFwastheonlyareatoincreaseinforestcover(0.3%)andhadthe

greatestincreaseinpopulationat216.7%.

18

Figure10:Percentchangeinforestcoverandorangutanpopulationfrompre-fire2006topost-fire2015withineachsub-habitat.

Theunequalchangeinforestcoverandorangutandensityamongthesub-habitatsshiftedtherelative

distributionofSabangau’stotalforestcoverandorangutanpopulation(Appendix2,FigureA2.3).Although

LPFexperiencedasmall increase inforestcover,thischangecoupledwithdecreasedforestcover inother

areas,causeda17.7%increaseintheproportionofSabangau’stotalforestcovercontainedinLPF.Despite

theoverallincreaseinMSF-I’sorangutanpopulation,theproportionofthetotalpopulationthissub-habitat

supportsdecreasedby13.9%,whileitincreasedby86.0%and15.3%inLPFandTIF,respectively.Aswell,by

post-fire2015,MSF-Psupported51.0%lessofSabangau’sorangutanpopulationthanitdidpre-fire2006.

AlthoughthereisasignificantdecreasinglinearrelationshipbetweenorangutandensityinMSF-Tand

Sabangau’stotalforestcover,theamountofvariationindensityexplainedbythemodelislow(R2=0.297,

F(1,74)=31.208,p<0.001)(Figure11).ThisrelationshipholdsforMSF-PandMSF-Iaswell(Appendix2,Figure

A2.4).

19

Figure11:Relationshipbetweenaverageorangutandensity inMSF-TandSabangau’stotalforestcoverforpre-andpost-fire2006,2010,and2015.ForestcovervaluesarebasedonlandcoverclassificationbytheMLC,anderrorbarsrepresent95%confidenceintervals.(n=6for5061km2and5623km2;n=5forallothers)

The paired t-test on orangutan density grouped in 8-month pre- and post-fire periods showed

significantvariationbeforeandafter11fireeventsinMSF-T(Figure12;Appendix2,TableA2.4):2002(t(4)=

-3.062,p=0.038),2003(t(5)=-2.752,p=0.040),2004(t(5)=-8.044,p<0.001),2005(t(5)=4.124,p=0.009),

2006(t(5)=-5.731,p=0.002),2007(t(4)=-3.428,p=0.027),2008(t(4)=10.959,p<0.001),2009(t(4)=-4.824,p

=0.008),2011(t(4)=-10.119,p<0.001),2012(t(5)=-2.980,p=0.031),and2015(t(5)=-4.522,p=0.011).Of

theseevents, density increasedpost-fire in all but 2005and2008.A similarpatternholds true forMSF-P

(Appendix2,FigureA2.5,TableA2.5)andMSF-I (Appendix2,FigureA2.6,TableA2.6)with7and9years,

respectively,havingsignificantvariationbetweenpre-andpost-fireorangutandensity.

20

Figure12:Averagepre-andpost-fireorangutandensityinMSF-Tfrom2002to2016.Errorbarsrepresent95%confidenceintervals.Significantdifferencesareindicatedby*p<0.05;**p<0.01;and***p<0.001.(n=4in2016;n=5in2002,2007,2008,2009,2010,2013,2014,and2015;n=6in2003,2004,2005,2006,2011,and2012)3.2Orangutanhomerange

Whenalladultandadolescentfemalesinthedatasetwereconsidered,therewasasignificantrelationship

between home range size and the number of follows per year (R2 = 0.531; F(1,112) = 126.847; p < 0.001).

Althoughthisrelationshipweakenedwhenonlyregularandfrequentindividualswereconsidered(R2=0.328;

F(1,66)=32.262;p<0.001)andagainwithonlyfrequentindividuals(R2=0.174;F(1,23)=4.851;p=0.038),the

relationshipremainedsignificant(Appendix2,FigureA2.7).Tominimizetheinfluencethenumberoffollows

hadonhomerangesize,Iusedonlyfrequentandregularindividuals(i.e.residents)fortheanalysis.

Basedonthelinearregression,homerangesizedoesnotsignificantlyvaryfrom2003topre-fire2015

forAF(R2=0.020;F(1,34)=0.680;p=0.415)orADF(R2=0.150;F(1,17)=2.992;p=0.102)(Appendix2,Figure

A2.8).TheGLMcontainingthevariablesage-classandpre-andpost-fire2015didnotexplainasignificant

proportionofthevariationinrangesize(R2=0.301;F(3,15)=2.148;p=0.137).Theaveragehomerangesizefor

21

AFpre-firewas1.38km2(SD=0.43)andpost-firewas1.04km2(SD=0.17);forADFitwas0.90km2(SD=0.55)

and0.73km2(SD=0.39)pre-andpost-fire,respectively(Figure13).

Figure13:Averagehomerangesize(km2)pre-andpost-fire2015forresidentadultandadolescentfemale.Homerangesizedoesnotsignificantlyvarypre-topost-fireforAF(p=0.415)orADF(p=0.102).(AFPre-fire:n=7;AFPost-fire:n=4;ADFpre-fire:n=5;ADFpost-fire:n=3)

AlthougheachAFwithpaireddatahadasmalleraveragehomerangeafterthefire(Appendix2,Table

A2.7),thesigntest(alpha=0.0625)indicatedthechangeforthegroupwasnotsignificant(p=0.125)(Mpre-fire

=1.56±0.18SD;Mpost-fire=1.04±0.17SD).Figure14illustratesthevariationinFeb’sannualhomerangesize

from2010to2017.VariationintheannualhomerangesizeforGracia,Indy,andIndahareshowinAppendix

2,FigureA2.9,A2.10,andA2.11,respectively.

22

Figure14:AnnualhomerangesizebasedontheminimumconvexpolygonforFeb(residentadult female)from2010to2017.(n=numberoffollows/year:2010:n=22;2011:n=22;2012:n=31;2013:n=50;2014:n=18;2015pre-fire:n=15;2016:n=14;2017:n=9)

4.Discussion

Borneanorangutansare increasinglyatriskfromforest fireseven inprotectedareassuchasSabangau,as

previous degradation reduced the region’s resilience, making it vulnerable to fires from the surrounding

developingarea(Cochrane,2003;Siegertetal.,2001;VanEijketal.,2009).Whilethereissubstantialresearch

ontheimpactsoffiresonecosystemstructure(ClearyandPriadjati,2005;CochraneandSchulze,1999;Sliket

al., 2010, 2008; Slik and Eichhorn, 2003), little focuses on the consequences for forest dwelling species.

Hitherto,therelationshipsbetweenfireinducedforestcoverchangesandorangutanpopulationdynamicshas

beenunclear.

Overall,IfoundthatSabangauforestcoverdeclinedby830.3km2frompre-fire2006topost-fire2015.

Despitetheforestcoverdecline,Sabangau’sorangutanpopulationisestimatedtohaveincreasedby3621to

8775 individuals over the same period. This increase in population is driven by a significant increase in

23

orangutandensityinMSF-P,MSF-I,andLPFwiththegreatestpopulationincreaseinLPFandTIF.Myprediction

that density would increase after a fire was supported most strongly when looking at MSF-T as density

increased significantly for 9outof 15 fire seasons; however, therewasmore variation in thedirectionof

changewhenexaminingMSF-PandMSF-Iseparately.Althoughfemalehomerangesizediddecreasepost-fire

aspredicted,thischangewasnotsignificant.

4.1Changeinforestcoverduetofire

Basedonthelandcoverclassification,MSF-PandMSF-Ihadthegreatestdeclineinforestcover,whileLPF’s

forestcover increasedslightlyoverthestudy.Landclearingactivitiesandtheirassociatedfires inthearea

surroundingSabangauandalongrivers’edgesmakeperipheralforestmorevulnerabletothespreadoffires

(Cochrane,2003).Thisexplains theconcentrationof firesanddegradation to the forestedge, causing the

higher loss in MSF-T compared to the other sub-habitats. As well, it appears that previously burnt and

degradedareasaremorevulnerabletofire,whichisconsistentwithpreviousresearch(Siegertetal.,2001;

VanEijketal.,2009)asnumerousburnscarswere inareaspreviouslyclassifiedasdegradedforest.Areas

adjacenttodegradedforestaremoresusceptibletofires(Lestarietal.,2016),whichIobservedasthefires

oftenexpandedoutfrompreviouslydegradedareas.

Aspoorimagequalitycausedsomepost-fireimagestobeselectedmonthsafterthefiresended,it’s

likelythatsomeburntareasexperiencedsomeregrowthorwereconvertedtosedgegrasses(VanEijketal.,

2009)leadingthemtobeclassifiedasdegradedorsedge.Combinedwiththefacethatfiresoftenoccurredin

degradedareas,burnscarareaitselfdoesnotnecessarilyrepresenttheextentofdamagetoprimaryforest

fromthatfireseason;thechangeinforestcoverisabettermetricforannualdamagefromfires.AsSabangau

isstillsubjecttoillegallogging(Tsujinoetal.,2016;Wichetal.,2012;Yule,2010),changeinforestcovermay

includelossesattributedtologging,butthis is likelysmallcomparedtotheareaaffectedbyfires(OuTrop,

2012). Comparing imagery that identifies fire hotspots, such as MODIS satellite product MOD14A2, to

24

classified Landsat images would help differentiate forest fire impacts from other types of degradation.

However,thetypeofdegradationdoesnotaltertheoutcomesofmyassessmentontheimpactstoorangutans

asit’sbasedonchangeinforestcovernottheintensityofforestdegradation.

4.2Orangutandensityandchangeinforestcoverduetofire

4.2.1Overallchangesindensityandforestcover

Average annual orangutan density increased inMSF-P,MSF-I, and TIF since 2002. Several factorsmay be

influencingthisincrease,oneofwhichisthedecreaseinforestcoverasseenbytherelationshipbetweenMSF

orangutandensityandforestcover.Thereductioninsuitablehabitatbyfiresmaycompressthepopulation

andincreasedensity(Marshalletal.,2008;Speharetal.,2010).However,forallMSFsub-habitats,forestcover

explainedalowamountofvariationinorangutandensityindicatingthatotherfactorsareinfluencingthelong-

termdensityincrease.

Thedensity increaseovertimemaybe linkedtothecessationof32yearsofselective loggingthat

occurredpriortoSabangau’snationalparkdesignationin2004(Morrogh-Bernardetal.,2011).Astheforest

structurerecovers,theecosystemisbetterabletosupportlargerorangutanpopulations(Morrogh-Bernard

etal.,2003)duetoimprovedhabitatqualityandfoodavailability(Ancrenazetal.,2010;Davies,1986)allowing

individualstorepopulatethearea(Knopetal.,2004).Slightdegradationinecosystemstructureandhabitat

quality in older regrowth cannot always be distinguished from primary peat swamp forest in land cover

classification(Wijedadaetal.,2012),sotherelationshipbetweenorangutandensityand improvedhabitat

qualityinoldregrowthisnotcontainedwithintherelationshipwithforestcoverchange.AlthoughIdidnot

measureforestcoverpriorto2006,Margonoetal.’s(2014)datashowsthatthetrendfordecreasingforest

coverextendsfrom2000to2015,astherewas255.8km2moreprimaryforest in2000thanpre-fire2006.

Thus,thedensityincreasefrom2002to2006mayalsobeinfluencedbythecorrespondingdeclineinforest

cover.

25

TheoscillationinMSFdensitymaybeinfluencedbyvariationinresourceavailability.Asorangutan

densityiscorrelatedwithfruitavailability(Carneetal.,2015;Hussonetal.,2008),thisoscillatingpatternmay

reflect annual variation in food resources and abiotic factors such as drought (Fredriksson et al., 2007;

Kanamorietal.,2017), leadingtovariationinbirthanddeathratesaswellasimmigrationandemigration.

Migrationismorelikelyresponsiblefortheobservedoscillationindensityaschangesinbirthratewilllagthe

triggering factors due to orangutans’ long inter-birth interval. Other population pressures such as illegal

huntingcouldalsoplayarole(Abrametal.,2015;Meijaardetal.,2012).

4.2.2Variationindensityandforestcoverchangesamongsub-habitats

Thespatialdistributionofforestfiresandorangutandensityofeachsub-habitatwillinfluencethelong-term

effectsoffiresonSabangau’sorangutanpopulation.FirespredominantlyoccurredinMSF-P,meaninghigh

orangutan density habitat was mainly affected. Although MSF-P’s population decreased over the study,

individualswerenotnecessarykilledbythefirebutmayhavemigratedtoothersub-habitatsinSabangau.The

overalldecreaseinforestcoverandincreaseinpopulationinMSF-ImaysuggestthatMSF-Ireceivedaninflux

ofdisplacedindividuals,likelyfromneighbouringMSF-P.Thismovementofindividualsmayalsoaccountfor

the increaseddensity post-fire inMSF-I, but not inMSF-P, such as in 2010 and2012. Similarly, the217%

increaseinLPF’spopulationmaybeinfluencedbymigrationofdisplacedindividuals.However,otherfactors

suchasseasonalityandvariationinresourceavailability(Kanamorietal.,2017;SingletonandvanSchaik,2001)

andmovementofrovingmaleswithlessstablehomeranges(Morrogh-Bernardetal.,2011;Spillmannetal.,

2017)cannotbeexcludedasfactorspossiblyinfluencingchangesindensity.

AlargelossofforestcoverfromMSFcoupledwithminimalburninginLPFresultedinasubstantial

decreaseintheproportionofSabangau’stotalforestcovercontainedinMSFswhilethisfactorincreasedin

LPF.The lowdensity inLPFthroughoutthestudysuggeststhatSabangau’sorangutanpopulationsizemay

becomelimitedifLPFcontinuestoincreasinglyrepresentSabangau’stotalforestcover.Thelowerorangutan

density in LPF compared to the other sub-habitats is due to low tree species diversity and lower canopy

heterogeneity(Pageetal.1997;Pageetal.,1999),makingitlessdiverseandapoorerhabitatfororangutans.

26

Assuch,itisnotthetotalforestlostbyfireinSabangauthatwillprimarilyinfluencetheorangutanpopulation,

butthespatialdistributionoffiresinthesub-habitatsasthiswillimpactthenumberofindividualsdisplaced,

thequalityoftheremaininghabitat,andtheoveralldensitythatSabangaucansupport.

4.2.3Displacementandchangeinorangutandensity

Whiledisplacementof individuals tounaffected areashasnot been studiedpost-fire, it’s known tooccur

adjacenttologgedsites(Davies,1986;Hussonetal.,2008;Russonetal.,2001)asloggingreducesorangutan

density(Feltonetal.,2003;Hussonetal.,2008;MejaardandWich,2014;ReijksenandMeijaard,1999;van

Schaik andRao, 1997). Since fires and logging cause similar changes in ecosystem structure and resource

availability(Sliketal.,2002),asimilarresponsebyorangutansafterfirecanreasonablybeexpected,which

mayaccountforchangesindensitypost-fire. InMSF-T,densityfrequentlyincreasedpost-fire,withgreater

variabilityinMSF-PandMSF-I.ThedensitydecreaseinMSF-Pafterfiresin2010and2012correspondedto

increases inMSF-I,whichmay indicatemigrationof individuals fromthe former to the latter.However, in

2005,2008,and2016densitydecreasedinbothsub-habitats.It’spossiblethatindividualsmigratedtoLPF,TIF

orVLC,but as therewasnomonthlydataprovided for these sub-habitats, the likelihoodof thisover the

influenceofotherenvironmentalfactorscannotbestated.

Asorangutansaregeneralist frugivores (Galdikas, 1988),decreaseddensity indisturbed regions is

linkedtoareductioninfruittrees(Rijksen&Meijaard,1999),astheirdensityispositivelycorrelatedwiththe

amountoffoodavailable(Hussonetal.,2008).However,orangutanshavebeendocumentedtoexhibithigh

dietaryflexibilityinmodifiedlandscapes(Campbell-Smithetal.,2011b)astheyareadaptedtoperiodsoflow

fruitavailability(vanSchaiketal.,2008)throughrelianceonfallbackfoods,suchasleaves,seeds,bark,and

invertebrates(Morrogh-Bernardetal.,2008;Russonetal.,2008;vanSchaikandRao,1997).Populationsthat

donotnaturallyexperiencesuchdramaticfluctuationsinfruitabundance,suchasthoseinnon-mastingpeat

swamp forests like Sabangau (Cannon et al., 2007),maybemorenegatively impactedby prolonged food

shortages(vanSchaiketal.,2008).Aswell,firewilllikelydegradethequalityandquantityofthosefallback

resources(Sliketal.,2002;LeightonandWirawan,1986;VanEijketal.,2009),unlikeselectiveloggingthat

27

preservessomeintacttreesfororangutanstofallbackon(Feltonetal.,2003).Consequently,aregionmaybe

unabletosupportitspreviousorangutanpopulationiffiresdestroysubstantialprimaryandfallbackfoods,

whichcouldcausethedisplacementofindividualsfromburnttounburntareaseitherwithinorbetweensub-

habitats.

Likelogging(Feltonetal.,2003;Marshalletal.,2006;vanSchaikandRao,1997),thescaleofhabitat

degradationanddensitydeclinepost-firewillvarywithfireintensityandthedamagetoorangutans’resources

(Blackhametal.,2014;Pageetal.,2009b;Russonetal.,2015;Sliketal.,2008),whichmayaccountforannual

variation inthedensitychangepost-fire.Asmentioned, firewilldestroyfallbackfoods,butthenumberof

resourceslostwillincreasewithfireintensity(Sliketal.,2010).Therefore,themoredamagingthefire,the

moredifficultitwillbefororangutanstomeettheirenergyintakerequirements(Knott,1998;Vogeletal.,

2012),possiblyforcingindividualsoutofthearea.In1982,anextremelystrongElNiñocontributedtohigh

intensityfiresinBorneothatkilledupto60%ofprimatefruittreesand90%oflargelianasandfigsinsome

dipterocarpforestsandseverelydamagedsurvivingvegetation(LeightonandWirawan,1986;Russonetal.,

2015).WhileecosystemdegradationhasnotbeenquantifiedforSabangau,theextensivedroughtandElNiño

eventin2006(Yuliantietal.2012)and2015(Tacconi,2016),respectively,likelycontributedtothehighforest

cover lossandpossiblysubstantiallyreducedfoodresources. Inbothyears,orangutandensitysignificantly

increasedpost-fireinallMSFsub-habitatsexceptforMSF-Iin2006wheretheincreasewasnotsignificant,

which may indicate that individuals were displaced. Examining changes in density and displacement of

individualspost-firecouldbeimprovedbyassessingfireintensityandquantifyingthedegreeofdamageto

theecosystem.

Ifthepopulationintheundisturbedhabitatisatornearcarryingcapacity,aninfluxofindividualsmay

lead to refugee crowding – an overshoot of the carrying capacity in a refuge habitatwhich neighbours a

degradedecosystem(MacKinnon,1971;RijksenandMeijaard,1999),whichincreasesdensityandhomerange

overlap(Carneetal.,2015)causingfoodshortages(Koenig,2002;RijksenandMeijaard,1999)andincreased

relianceonfallbackfoods(Carneetal.,2015).Orangutansaresensitivetochangesindensityandrangeoverlap

28

astheyalreadyliveclosetothelimitsoffoodresourceavailability(Carneetal.,2015).Although,aspreviously

mentioned,theyhavesomenaturaldietaryflexibilitythroughfallbackfoodstoshorttermfluctuationsinfood

resourcesandcarryingcapacity(Leightonetal.,1995),thedegreeoftolerancevariesamongpopulationswith

lessflexibilityamongthoseinforestssuchasSabangauwherefruitavailabilityismoretemporarilystable(van

Schaiketal.,2008).Aswell, compressionof thepopulation,even in theshort term,canhavedetrimental

effectson social cohesionand reproductive success (RijksenandMeijaard,1999).This isdue to increased

agonistic interactions and intraspecific contest competition (Knott et al., 2008), which in turn depresses

fecundityandincreasesmortality(Marshalletal.,2008).Theseimpactsofcrowdingtoorangutans’socialand

reproductive health will likely be exacerbated in lower quality habitat such as LPF that are increasingly

supportingagreaterproportionofthetotalpopulation.Sabangau’sorangutansdonotappeartohavereached

carryingcapacityastheirpopulationisstillincreasing,sotheyarenotlikelyexperiencingrefugeecrowdingat

thisscale.However,spatialvariationinhabitatqualityanddensitymaycauselocalizedimpactsfromrefugee

crowding,theeffectsofwhichwillnotimmediatelybecomeapparentinpopulationdataduetoorangutans’

longlifehistory(Marshalletal.,2008).

Asmentioned, therewillbevariation inorangutans’ responseto firesdependingonthedegreeof

degradation,sospatialvariationinchangestodensityinunburntforestwithineachsub-habitatisexpected

depending on fire intensity and proximity; however, this is not captured by the data as each sub-habitat

representsasingleregioninSabangau.Forthisreason,thechangesindensitymaynottrulyrepresentthe

impactsoffireswithineachsub-habitatandSabangauiffiresdidnotburncloseenoughtothesampledsite

for them to experience density changes as a result. Furthermore, Abram et al. (2015) found Sabangau’s

orangutanpopulationtobeindeclineinrecentyearsduetohumanconflictandkilling,however,thistrendis

notreflectedinourdataset.Thisdiscrepancymaybeduetotheuseofasinglesamplesiteforeachsub-habitat

thatdoesn’tcapturespatialvariationinpopulationpressuresandtheconsequentialchanges inpopulation

density throughout the sub-habitat. However, this analysis provides the best estimate based on the data

available.

29

4.3Orangutanhomerange

Although there is no significant variation in female home range size, the decreasing trend post-fire is as

expected.Thehigherorangutandensitypost-fire inMSF,whichwasmeasured inthesamelocationasthe

followdata,suggeststhatnewindividualsenteredthearea,possiblyfromthetwoadjacentburnsitesboth

lessthan1kmaway.Thisshiftisconsistentwiththeconceptofrefugeecrowdingpreviouslymentioned,as

potentialcrowdingfromrefugeesmaycompressindividuals’homeranges.Eventhoughfemaleshavehighly

stable home ranges (Singleton and van Schaik, 2001), there is some variation in the extent and spatial

orientation of their range (Isbell, 1991),making it reasonable that changes in density and environmental

factorswouldelicitshiftsinhomerange.

Whilethere isnoresearchavailableonthedynamicsoffemalerangesizeafteradisturbancewith

whichtocomparemyresults,femalebehaviourandrangeoverlaptendenciessuggeststhatcontractionisa

likely consequence of crowding. The degree of home range overlap varies depending on the relationship

betweenindividuals,withahigherdegreeofoverlapbetweenkincomparedtonon-kin(Knottetal.,2008;

Singleton and van Schaik, 2002). Although females scramble compete for resources with overlapping

individuals,theyavoidagonisticencountersbyactivelyavoidinginteractionwithotherorangutans(Knottet

al.,2008).Knotetal.(2008)foundthatmostunrelatedfemaledyadsavoideachotherwhenranginginthe

sameareaandencounteredeachothersignificantly less thanexpected.Activeavoidanceofmigrants that

overlaptheirrangemaycausefemalestocoverlessoftheirpreviousrangeleadingtorangesizecontraction.

Additionally,femalesadjusttheextentoftheirhomerangeoverlapbasedonthedensityofindividualsand

resources (Isbell, 1991),meaning the increased density post-fire 2015may have influenced the trend for

smallerhomeranges.Furthermore,comparedtootherpeatswampforestsinBorneo,femalesinSabangau

havesomeofthesmallesthomerangesandhomerangeoverlap(Morrogh-Bernard,2003;Singletonetal.,

2008). This is attributed to the homogeneity in Sabangau’s spatiotemporal pattern of food supply,which

allowsindividualstoacquirethenecessaryresourcesoverasmallerarea(Singletonetal.,2008).Asaresult,

newindividualsemigratingfromtheneighbouringburntforestcouldincreaseoverlaptoadegreeresidents

30

areunaccustomedto,thuscausingthemtocontracttheirranges.Overallthebehaviouroffemalessuggests

it’spossiblethataninfluxofnewindividualscouldreducethehomerangesizeofresidentfemales.Asthere

arenootherstudiestocomparewith,it’sunclearifthelackofsignificanceinfemaleresponsereflectstheir

truebehaviour,orisduetotheweakstatisticalpoweroftheanalysisduetothelowsamplesizeofthedata.

4.4Long-termeffects

DespitetheincreaseinorangutandensityandpopulationinSabangau,ifthepatternofannualfires(Hoscilo

etal.,2011;LangnerandSiegert,2009)anddecreasingforestcovercontinues(Gaveauetal.,2014;Hansenet

al.,2013;Tsujinoetal.,2016),thepopulationmaybecompressedtothepointofexceedingcarryingcapacity

leadingtoapossiblepopulationdecline(Marshalletal.,2008).AnnualfiresinIndonesiaandSabangauwill

likelycontinuetooccur,asthereisaninadequateregulatoryandlegalframeworkinthecountrytoaddress

fires (Nurhidayah, 2013), and legal efforts to reduce deforestation and its associated fires have not been

successful(Buschetal.,2015;Margonoetal.,2014).Aspeatswampforestsareslowtorecoverfromfires

(Chisholmetal.,2016;Pageetal.,2009b;Sliketal.,2008;Yule,2010)andfirestendtooccurinareasthat

werepreviouslyburnt(CochraneandSchulze,1999;Hosciloetal.,2011;Siegertetal.,2001),regeneration

and increased resilience to fires is limited (Page et al., 2009a; Van Eijk et al., 2009). This puts orangutan

populationsnearpreviouslyburntareasatriskforanannualinfluxofmigrantsandlossoftheirownhabitat

as these firespotentiallyexpand toprimary forest.Furthermore, the riskof increasingstrengthofElNiño

eventsduetoclimatechange(Caietal.,2014;Dai,2013)alsoincreasesthelikelihoodofseverefireevents

(Jollyetal.,2015),suchasthosein2006and2015.

Whilecrowdinghasnotyethadanegativeimpactonpopulationgrowth,overtimeovercrowdingand

resourcesharinginconditionsoffoodshortage,evenintheshortterm,canhaveimplicationsonindividuals’

health, survival, and fecundity (Knott, 1998; Knott, 2001; Rijsken & Meijaard, 1999; Vogel et al., 2012).

Decreasedfoodavailabilitycanseverelyreducefatstores,causingahormoneimbalancethatcompromises

31

conception(Knott,1998)andcanlengthentheinter-birthinterval(Knott,2001;Knottetal.,2008),whichif

lengthenedby2yearscancausenegativepopulationgrowth(Tildonetal.,1993).Orangutans’slowlifehistory

and long reproductive cyclemeans thedetriment to thepopulationmaynotbe immediatelyevident; the

populationmayestablishanextinctiondebt (sensuTilmanetal.,1994)and in timeexperiencepopulation

decline(Marshalletal.,2008).AsSabangaudoesnotappeartobeatcarryingcapacity,crowdingmaynot

currentlybehighenoughtosubstantiallyalterreproductivecyclesandsocialcohesion.However,ifdensity

andcrowdingcontinueto increaseandhomerangescontractduetoannualfires,thenegative impactson

populationstabilitycouldbecomerealized.

4.5Futureresearch

I’veshownthatorangutandensityinMSFsub-habitatsoftenvarypre-firetopost-fire,howeveracomplete

understandingoftheimplicationsforSabangau’sorangutanscannotbegaineduntiltheothersub-habitats

areassessedinasmuchdetail.ResearchthatgathersmorefrequentdensitydatafromLPF,TIF,andVLCto

analyze fire impacts would yield a clearer understanding of how Sabangau’s whole population is being

impactedbyfires,andmaygivefurtherinsightintothemovementofindividualsbetweensub-habitats.

There is no research on how variation in fire intensity impacts orangutans’ responses to the

disturbance.It’sevidentthatdegradedhabitatscansupportorangutanstosomedegree,butwithoutspecific

assessment on the damage to ecosystem structure by varying levels of fire intensity and the range of

consequencesontheresidentandneighbouringorangutans,thelossandmovementofindividualscannotbe

accurately estimated. This suggested research coupledwithmy assessment of the relationships between

change in forest cover and fire occurrence with orangutan density would yield a more comprehensive

understandingofthechangesintheorangutanpopulationandwhatthelong-termconsequencesmaybe.

Carryingonfrommyanalysisonchangesinhomerangesize,researchonrangeoverlapandrange

packingwouldbeuseful to furtherassess the impactsof fireonrangingbehaviour.However, thisanalysis

32

requiresdatatobecollectedonallindividualswithequaleffortandnosuchdataiscurrentlyavailable.Future

workwouldbenefitfromindividualsbeingfollowedinasystematicwaythatensuresrandomsamplingofthe

populationandmoreequalityamongtheage-sexclassesovertime.Moreequaleffortmayalsoincreasethe

samplesizeandstatisticalpower,asunder-sampledindividualsthatarecurrentlynon-residentsmaybetrue

residentsofthepopulation.

5.Conclusions

Overall,forestfiresdecreasedforestcoverinSabangauNationalParkfrom2006to2015.Whilethischangein

forestcoverhadsomeeffectonincreasingorangutandensityovertime,theinfluencewaslimited,implying

thereareadditionalcontributingbioticorabioticfactors.Despitethedecreaseinforestcover,theestimated

orangutanpopulationhasincreasedduetoincreaseddensity.Orangutandensityfrequentlyincreasedpost-

firesignifyingthathabitatdegradationmaytriggerthemigrationofindividualsfromburnttounburntrefuge

areas.Femalehomerangesizeinunburnthabitatisnotsignificantlyimpactedbyfire,howevertheincrease

indensitymaycausefemalestocontracttheirhomerangestoavoidinteractionwithunfamiliarindividuals,

as suggested by the tendency for small home ranges post-fire. These changes to orangutan density and

distributioncouldpotentiallyimpedeindividuals’accesstoresourcesleadingtocompromisedwellbeingand

fitness.

Currently Sabangau’s orangutan population is increasing despite fires decreasing forest cover.

However,thereisasriskthatcontinualforestdegradationbyfirewillincreasethepopulationdensitybeyond

carrying capacityand that someof these impactshavenot yetbeen realizeddue toorangutans’ slow life

history.Assuch,it’sessentialthateffortbemadetoreduceintentionallysetfiresintheareasurroundingand

withinSabangautoensurethattheorangutanpopulationcontinuestoincrease.

33

Acknowledgements

Iwouldliketothankmysupervisors,Dr.FrankvanVeenandDr.HelenMorrogh-Bernard,fortheirguidance

andfeedbackthroughoutthisprojectandSaraEshpeterandBernieRipollCapillafortheirinvaluableadvice

onmylandcoverclassificationmethods.Theorangutandensitydataandfollowdatausedtoevaluatehome

range were collected by the Borneo Nature foundation (BNF) team as part of the BNF/CIMTROP multi-

disciplinaryresearchprojectinthenorthernSabangauForest,CentralKalimantan,Indonesia.

34

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Appendix1:SupplementaryMethods

43

1.Estimatinghabitatlossduetofire

1.1Data

IusedimagesfromtheLandsatsatelliteseriestoclassifylandcoverbeforeandaftereachfireeventforthe

threeyearsofinterest,2006,2010,and2015.ImagesarefreelyavailablefromtheUnitedStatesGeological

Survey (USGS) Earth ResourcesObservation and Science (EROS) Data Centre via their Earth Explorerweb

interface(http://earthexplorer.usgs.gov/).TheanalysisusedimagesfromseveralLandsatsensors,including

ThematicMapper(TM),EnhancedThematicMapperPlus(ETM+),andOperationalLandImagerandThermal

InfraredSensor(OLI/TIRS),allofwhichhavearesolutionof30X30m.

Ilimitedthesearchforimagesforthepath/row:118/62tothosetakenduringthedaywithlessthan

30%cloudcover.IavoidedLandsat7imageswiththeScanLineCorrector(SLC)-offunlesstheimagesfromthe

othersatelliteswereinsufficient;thisoccurredforthe2006post-fireand2010post-fireimages(TableA1.1).

Foreachyear,Iexamined8-daycompositeimagesofactivefiresinSabangaufromtheModerateResolution

Imaging Spectroradiometer (MODIS) satellite product MOD14A2 acquired from Earthdata

(https://earthengine.google.com)todeterminethestartandendofeachfireseason.Basedonthisevaluation,

IonlyselectedLandsatimagesfromDecembertotheendofJuly,astherewerenofiresobservedduringthose

months,whichwassupportedbymonthlyfirehotspotanalysisdonebyYuliantietal.(2012).Whenpossible,

Ipreferentiallyselectedpre-fireimagesatthebeginningofthefireseason(i.e.July)andpost-fireimagesat

theend(i.e.December).However,poorimagequalityduetoheavycloudcoverlimitedthenumberofusable

images,causingsometobeselectedseveralmonthsbeforeorafterthefire.Duetoalackofusableimages,

the2015pre-fire image is fromAugust3rd,2015;however,as it is stilloutsideof thatyear’s fireseason, I

deemeditacceptable.Additionally, Iusedtwoimagestocompletetheclassificationfor2015post-fireand

2006pre-fireassubstantialareawascoveredbycloud.


44

TableA1.1:Satelliteimagesusedforlandcoverclassification.

Category DateAcquired SatelliteSensor Spatial

Resolution(m)Bandsusedforclassification¶

ClassificationUse

2006Pre-Fire07-06-2006 Landsat5TM 30X30 2,3,4,5,7 Primary09-07-2006 Landsat5TM 30X30 2,3,4,5,7 Fillgaps

2006Post-Fire 04-07-2007‡ Landsat7ETM+ 30X30 2,3,4,5,7 Primary

2010Pre-Fire 10-02-2010 Landsat5TM 30X30 2,3,4,5,7 Primary

2010Post-Fire13-06-2011∫ Landsat7ETM+ 30X30 2,3,4,5,7 Primary12-05-2011¥ Landsat7ETM+ 30X30 2,3,4,5,7 Fillgaps

2015Pre-Fire 03-08-2015 Landsat8OLI/TIRS 30X30 3,4,5,6,7 Primary

2015Post-Fire 14-03-2016 Landsat8OLI/TIRS 30X30 3,4,5,6,7 Primary‡gapfilledwithLandsat7ETM+imagefrom05-08-2007usinglocalhistogrammatching∫gapfilledwithLandsat7ETM+imagefrom12-05-2011usinglocalhistogrammatching¥gapfilledwithLandsat7ETM+imagefrom13-06-2011usinglocalhistogrammatching¶Thecorrespondingspectralwavelengthforeachbandare:Landsat5TMandLandsat7ETM+:band2=green,band3=red,band4=nearinfrared,band5=shortwaveinfrared-1,band7=shortwaveinfrared-2;Landsat8OLI/TIRS:band3=green,band4=red,band4=nearinfrared,band6=shortwaveinfrared-1,band7=shortwaveinfrared-21.2Pre-processing

RadiometriccorrectionofLandsatimagesisrequiredwhenmappingchangesinhabitatandwhencomparing

multispectral images temporally (Lu andWeng, 2007) as itminimizes the effects of differences in sensor

calibration,sun-earthdistance,andsunelevation(Youngetal.,2017).Todothis,Iconvertedtherawdigital

values (DN) to top of atmosphere (TOA) reflectance (Hansen et al., 2008; Potapov et al., 2012) using the

radiometric calibration tool in ENVI 5.4. To reduce reflectance variation between images dates due to

atmosphericconditions,IusedENVI5.4todoadarkobjectsubtractionatmosphericcorrection(Chavez,1988).

TheLandsat7ETM+imageswithSLC-offneededtohavetheareaswithnodatacorrectedpriorto

classificationasabout25%ofthedatawasmissingfromtheimage(Triggetal.,2006;Wulderetal.,2008).I

didthisusinglocalhistogrammatchingthroughtheLandsatGapFillextensioninENVI5.4(Storeyetal.,2005),

whichusesdatafromasecondEMT+imagetakenatasimilartimetoestimatethevaluesofthemissingpixels.

AllimageswereprojectedtotheUniversalTransverseMercator(UTM)projection,Zone50Southin

ArcMap10.5,whichIusedfortheremainderoftheanalysis.Toremovecloudandshadow,Igeneratedcloud

masksfromeachimages’qualityassessment(QA)bandandappliedthemtothemultispectralimagesinorder

toimproveclassificationquality(Xieetal.,2008).IclippedtheimagestotheSabangaustudyareawithinthe


45

boundaryoftheSabangauandKatinganRivers.Toexcludethedevelopmentalongtheperipheryoftheforest,

Idelimitedthestudyareabasedonprimaryforestdatafrom2000(Margonoetal.,2014)retrievedfromGlobal

Forest Watch (http://www.globalforestwatch.org). As orangutans do not occupy sedge grass (Morrogh-

Bernard,pers.comm.),Iremovedthesedgepatchesborderingtheriversasthissimplifiedtheclassification.

1.3Landcoverclassification

Iusedamaximumlikelihoodsupervisedclassification(MLC)approachtoclassifythe images intonine land

coverclasses(TableA1.2),asMLCisacommonandaccuratemethodforclassifyingforests(Jiaetal.,2014;Li

etal.,2014;LuandWeng,2007;RawatandKumar,2015).Ibasedthelandcoverclassesonpreviousstudies

ofpeatswampforest (Hosciloetal.,2011;Wijedadaetal.,2012),visualstudyofthesatellite images,and

communicationabouttheecosystemwithDr.Morrogh-BernardofBNF.

TableA1.2:Descriptionoflandcoverclassesusedfortheclassification.Category LandCoverClass Description

Forest Peatswampforest(PSF)

Undisturbedpeatswampforest,oldre-growthwithminimaldisturbancefromfireorlogging;includessomeoldsecondaryforestthatwaspreviouslyloggedandcannotbedistinguishedfromundisturbedpeatswamp

Non-Forest

Burnscar Recentlyburnedarea;bareearthwithlittletonovegetation.

Degradedforest

Peatswampforestthathasbeendegradedbyloggingand/orfire.Includesareasofopencanopypeatswampandareasofrecent,minimalvegetationre-growththatexhibitsdistinguishabletextureandreflectancefromprimaryandoldre-growthpeatswampforest.

SedgeAreasofnon-woodyvegetationandtheriversandfloodedpeatcontainedwithinthem.

Water Riversandlakesincludingseasonallyfloodedareas.

NoData

Cloud Cloudthatwasnotremovedbythecloudmask.

Haze Thin,wispycloudthatwasnotremovedbythecloudmask.

CloudShadow Cloudshadowthatwasnotremovedbythecloudmask.

Null SLC-offareasthatwerenotproperlyfilledbythelocalhistogrammatchingmethod.

Idigitizedtrainingpolygonsbasedonvisualanalysis infalsecolour(shortwaveinfrared-1(SWIR-1),

nearinfrared(NIR),andred)foreachimageseparately.Theareaoftrainingpolygonsandnumberofpixels

usedvariedbyyeardependingonthecoverageofeachclassandthesimilarityinpixelvaluesbetweenclasses


46

(TableA1.3).Toreducethe impactofatmosphericdisturbancesontheclassification (LangnerandSiegert,

2009),Iusedaspectralsubsetofbandsthatincludedbands2,3,4,5,and7forLandsat5and7imagesand

bands3,4,5,6,and7forLandsat8images.Thissubsetcoversthegreentoshortwaveinfraredspectrum,

whichcontainsthemostrelevantinformationfordetectingburnscarsandvegetation(LangnerandSiegert,

2009).Irepeatedtheprocessofcreatingtrainingpolygonsandrunningtheclassificationuntil,basedonvisual

inspectionoftheclassifiedimage,therewasahighlevelofaccuracyintheclassification.

TableA1.3:NumberofpolygonsandpixelsineachlandcoverclassusedfortrainingtheMLC.

¶Coveredanareaof4180km2asitwasusedtofillgapsduetocloudcover.‡Coveredanareaof919km2asitwasusedtofillgapsduetocloudcover.

Beforeclassifyingtheimagesusedtofilldatagapsfromcloudcoverin2006pre-fireand2010post-

fire,Iclippedtheimagestothecorrespondedareaintheprimaryimagethatrequiredfilling.Ithenclipped

thisareaoutoftheprimaryimage,classifiedthemindependently,andmergedthempost-classification.

1.4Post-processing

Per-pixel classification methods such as MLC can cause a ‘salt and pepper’ effect from isolated pixel

classification errors and requires post-classification processing to reduce the noise (Lu andWeng, 2007;

ImageDate No.of: Burnscar DegradedForest

Peatswampforest

Sedge Water Cloud Haze CloudShadow Null

07-06-2006Polygons 135 125 94 29 3 40 N/A 22 N/APixels 13524 31534 40959 1442 354 597 N/A 1517 N/A

09-07-2006¶Polygons 140 141 94 47 N/A 39 N/A 21 N/APixels 7220 13557 5280 2460 N/A 1001 N/A 887 N/A

04-07-2007Polygons 312 163 93 57 5 24 N/A 18 34Pixels 22496 10525 32026 1108 507 568 N/A 482 3706

10-02-2010Polygons 148 93 54 41 4 4 N/A N/A N/APixels 22598 22933 246851 3455 669 138 N/A N/A N/A

13-06-2011Polygons 266 214 88 48 4 40 N/A 22 38Pixels 15838 9434 33274 1184 510 1382 N/A 1022 4148

12-05-2011‡Polygons 100 102 23 16 N/A 9 N/A 12 10Pixels 1769 4064 4737 383 N/A 222 N/A 337 1072

03-08-2015Polygons 316 284 85 8 19 19 11 19 N/APixels 10889 12666 34805 105 708 222 471 342 N/A

14-03-2016Polygons 659 477 74 184 5 79 N/A 41 N/APixels 23782 12302 97733 3294 720 3437 N/A 1226 N/A


47

Wijedadaetal.,2012)andimprovethequalityoftheclassification(Stefanovetal.,2001;LuandWeng,2004).

IcarriedthisoutusingArcMap10.5’smajorityfilter,boundaryclean,andnibbletools.

Furtherpost-processingwasdoneto identify the landclassesmaskedbyareasof ‘nodata’,which

includedcloud,cloudshadow,haze,andnullclasses.Inareaswithextensivehomogeneityandsmallnodata

clusters,examiningtheoriginalsatelliteimagewassufficienttodeterminethecorrectlandcoverclass.For

moreheterogeneousareasandthosewithdensernodataclusters,IusedtheNIRspectralbandtodistinguish

burn scars and healthy and degraded vegetation from each other, asNIR can penetrate thin cloud cover

(Marshaketal.,2000)andhasthehighestpowertodiscriminatebetweenburnedandunburnedareas(Pleniou

andKoutsias,2013;Schepersetal.,2014).Additionally,Iusedsecondaryimagesforthosethathadthemto

identifythecorrectclass.

To evaluate land cover changeswithin each sub-habitat, I used Ehlmer Smith and Ehlmer Smith’s

(2013)classificationandshapefileswhichdivideSabanagauinfoursub-habitats–mixed-swampforest(MSF),

low-poleforest(LPF),tall-interiorforest(TIF)andvery-lowcanopy(VLC)(FigureA1.1).IfurtherdividedMSF

(referredtoasMSF-total[MSF-T])intoMSF-interior(MSF-I)andMSF-perimeter(MSF-P)tocoincidewiththe

orangutandensitydata.MSF-Pextends2kmintotheforestfromtheedgeofriversandtheforestborder,and

MSF-I constitutes the remaining interior area. Lastly, I clipped the classified images to the sub-habitat

shapefilesthensummedtheareaofeachlandcoverclassineachsub-habitat.


48

FigureA1.1:Sub-habitatswithintheSabangaustudyarea.Theblackstarrepresentsthe9km2researchplot.

AsSabangau isaprotectedarea, Iassumedthatallobservedchanges in forestcoverweredue to

forestfire,however,IacknowledgethatillegalloggingmayoccurinSabangau(Tsujinoetal.,2016;Wichet

al.,2012;Yule,2010).Iftheloggingwasextensiveenough,itmaybeclassifiedasdegradedforestbytheMLC,

but as illegal activityhas slowed in Sabangau (OuTrop,2012), itwould likelybe small relative to thearea

damagedbyfire.


49

2.OrangutandensityTable A1.4: Annual orangutan density for each sub-habitat in Sabangau. Values forMSF-P andMSF-I areaveragesofmonthlyfieldobservations.ValuesforLPFandTIFareeithersingleannualfieldobservationsorestimatesbasedontheratiosLPF:MSF-IandTIF:MSF-P.Year MSF-P MSF-I LPF TIF2002 1.06 0.51 0.72 1.732003 0.99 0.62 0.81 1.56‡2004 1.26 0.88 0.55 1.642005 1.40 0.96 0.40 1.592006 1.34 0.80 0.51∫ 2.052007 1.51 0.76 0.48∫ 2.37‡2008 1.45 0.80 0.32 1.992009 1.30 0.71 0.46∫ 2.822010 1.51 0.76 0.48∫ 2.36‡2011 1.42 0.93 0.25 2.632012 1.70 1.13 0.72∫ 2.67‡2013 1.73 1.32 0.41 2.672014 1.91 1.29 0.83∫ 2.99‡2015 1.84 1.38 0.88∫ 2.89‡2016 2.12 1.81 1.25 3.32‡2017 2.11 1.78 1.14∫ 3.30‡

∫EstimateddensitybasedontheaverageoftheratioLPF:MSF-I‡EstimateddensitybasedontheaverageoftheratioTIF:MSF-P


50

3.Orangutanhomerange

TableA1.5:Kjscoresforadultandadolescentfemalesobservedinthe9km2researchplotfrom2003to2017.Adultfemales(AF)aresexuallyactive,whileadolescentfemales(ADF)arenon-sexuallyactive.IndividualswithastatusofFrequentandRegularareresidentsofthepopulation.Kjscoresfor2015arecalculatedfortheyearaswellaspre-fire,during-fire,andpost-fire.Year Name Age-SexClass Kj Status¶

2003

Cleopatra AF 50 Frequent(resident)Feb ADF 100 Frequent(resident)Indah AF 50 Frequent(resident)Chopin ADF 25 Regular(resident)

No.ResidentsAF 2

ADF 2

2004

Cleopatra AF 50.0 Frequent(resident)Feb ADF 83.3 Frequent(resident)Indah AF 75.0 Frequent(resident)Teresia AF 25.0 Regular(resident)Potret AF 8.3 OccasionalViola AF 8.3 Occasional

No.Residents AF 3

ADF 1

2005

Cleopatra AF 58.3 Frequent(resident)Feb ADF 100.0 Frequent(resident)Indah AF 58.3 Frequent(resident)Viola AF 50.0 Frequent(resident)Indy ADF 25.0 Regular(resident)Gracia AF 8.3 OccasionalPotret AF 8.3 OccasionalTeresia AF 8.3 OccasionalWillow AF 8.3 Occasional

No.Residents AF 3

ADF 2

2006

Feb ADF 50.0 Frequent(resident)Indah AF 75.0 Frequent(resident)Indy ADF 33.3 Regular(resident)Cleopatra AF 16.7 OccasionalLeony AF 8.3 OccasionalNLF030206 AF 8.3 OccasionalViola AF 8.3 OccasionalWillow AF 8.3 Occasional

No.Residents AF 1


51

ADF 2

2007

Feb ADF 75.0 Frequent(resident)Cleopatra AF 25.0 Regular(resident)Indah AF 41.7 Regular(resident)Indy ADF 41.7 Regular(resident)

No.Residents AF 2

ADF 2

2008

Indy ADF 58.3 Frequent(resident)Cleopatra AF 33.3 Regular(resident)Feb ADF 33.3 Regular(resident)Indah AF 33.3 Regular(resident)Teresia AF 25.0 Regular(resident)Viola AF 33.3 Regular(resident)Potret AF 8.3 OccasionalWillow AF 16.7 Occasional

No.Residents AF 4

ADF 2

2009

Indy ADF 58.3 Frequent(resident)Feb ADF 33.3 Regular(resident)Indah AF 41.7 Regular(resident)Aya AF 8.3 OccasionalBarita AF 8.3 OccasionalCleopatra AF 16.7 OccasionalEosah AF 8.3 OccasionalFossey AF 8.3 OccasionalSAF130909 ADF 8.3 OccasionalTeresia AF 8.3 OccasionalViola AF 8.3 OccasionalWillow AF 8.3 Occasional

No.Residents AF 1

ADF 2

2010

Feb AF 33.3 Regular(resident)Indy ADF 25.0 Regular(resident)Barita AF 8.3 OccasionalGracia AF 8.3 OccasionalTeresia AF 8.3 Occasional

No.Residents AF 1

ADF 1

2011 Indy ADF 50.0 Frequent(resident)Feb AF 41.7 Regular(resident)


52

Teresia AF 25.0 Regular(resident)Barita AF 8.3 OccasionalCleopatra AF 8.3 OccasionalIndah AF 16.7 OccasionalViola AF 8.3 Occasional

No.Residents AF 2

ADF 1

2012

Feb AF 75.0 Frequent(resident)Indy AF 58.3 Frequent(resident)Gracia AF 25.0 Regular(resident)Indah AF 41.7 Regular(resident)Teresia AF 33.3 Regular(resident)Viola AF 25.0 Regular(resident)Barita AF 8.3 OccasionalCleo3 AF 8.3 OccasionalSAF041112 ADF 8.3 OccasionalU16_Fem_Adult AF 8.3 Occasional

No.Residents AF 6

ADF 0

2013

Feb AF 66.7 Frequent(resident)Indy AF 83.3 Frequent(resident)Teresia AF 75.0 Frequent(resident)Gracia AF 33.3 Regular(resident)Cleopatra AF 16.7 OccasionalGeorgia ADF 16.7 OccasionalIndah AF 8.3 OccasionalSAF110913 ADF 8.3 OccasionalTimi ADF 16.7 OccasionalWillow AF 8.3 OccasionalYana AF 8.3 Occasional

No.Residents AF 4

ADF 0

2014

Indy AF 83.3 Frequent(resident)Feb AF 41.7 Regular(resident)Georgia ADF 25.0 Regular(resident)Gracia AF 33.3 Regular(resident)Indah AF 33.3 Regular(resident)Teresia AF 41.7 Regular(resident)Timi ADF 33.3 Regular(resident)Cleopatra AF 16.7 Occasional


53

Isabella ADF 16.7 OccasionalLipstik AF 8.3 Occasional

No.Residents AF 5

ADF 2

2015

Feb AF 58.3 Frequent(resident)Georgia ADF 33.3 Regular(resident)Gracia AF 33.3 Regular(resident)Indah AF 25.0 Regular(resident)Indy AF 41.7 Regular(resident)Isabella ADF 25.0 Regular(resident)Teresia AF 25.0 Regular(resident)Timi ADF 25.0 Regular(resident)

No.Residents AF 5

ADF 3

2015Pre-Fire

Feb AF 41.7 Regular(resident)Georgia ADF 25.0 Regular(resident)Indy AF 33.3 Regular(resident)Timi ADF 25.0 Regular(resident)Gracia AF 8.3 OccasionalIndah AF 16.7 OccasionalIsabella ADF 8.3 OccasionalTeresia AF 16.7 Occasional

No.Residents AF 2

ADF 2

2015During-Fire

Feb AF 8.3 OccasionalGeorgia ADF 8.3 OccasionalGracia AF 16.7 OccasionalIndah AF 8.3 OccasionalIndy AF 8.3 OccasionalIsabella ADF 16.7 OccasionalTeresia AF 8.3 Occasional

No.Residents AF 0

ADF 0

2015Post-Fire

Feb AF 8.3 OccasionalGracia ADF 8.3 Occasional

No.Residents AF 0

ADF 0

2016

Feb AF 41.7 Regular(resident)Georgia ADF 25.0 Regular(resident)Gracia AF 33.3 Regular(resident)Gretel ADF 33.3 Regular(resident)


54

Indah AF 33.3 Regular(resident)Indy AF 41.7 Regular(resident)Juno AF 16.7 OccasionalTeresia AF 16.7 OccasionalTimi ADF 16.7 Occasional

No.Residents AF 4

ADF 2

2017*

Feb AF 60.0 Frequent(resident)Georgia ADF 60.0 Frequent(resident)Gretel ADF 40.0 Regular(resident)Juno AF 20.0 OccasionalTimi ADF 20.0 Occasional

No.Residents AF 1

ADF 2

*Kjisbasedona5-monthstudyperiod.¶Frequent:Kj≥50%;Regular:25%≤Kj<50%;Occasional:4%≤Kj<25%;Rare:Kj≤4%


55

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Appendix2:SupplementaryResults

57

1.ChangeinforestcoverduetofireTableA2.1:Thearea(km2)ofeachlandcoverclassandthepercentchangeineachduetothe2006,2010,and2015firesinSabangau.ValuesarebasedonthelandcoverclassificationusingtheMLC

2006 2010 2015 Overall

Pre-fire Post-fire %Change Pre-fire Post-fire %Change Pre-fire Post-fire %Change %Change

PSF 5623.3 5061.1 -10.0 5313.8 5036.5 -5.2 5303.3 4793.0 -9.6 -14.7

Burnscar 234.7 897.4 282.4 518.1 700.4 35.2 422.7 843.9 99.7 259.6

Degraded 1071.6 1023.7 -4.5 1058.0 1249.4 18.1 1263.8 1343.4 6.3 25

Sedge 62.4 9.9 -84.2 95.0 5.3 -94.4 0.1 11.2 20769.0 -82.0

Water 3.8 3.7 -2.7 4.6 4.3 -5.7 5.9 3.7 -37.4 -1.7


58

TableA2.2:Thearea(km2)ofeach landcoverclassandthepercentchange ineachduetothe2006,2010,and2015firesforthesub-habitatsofSabangau.ValuesarebasedonlandcoverclassificationbytheMLC. 2006 2010 2015 Overall Pre-fire Post-fire %Change Pre-fire Post-fire %Change Pre-fire Post-fire %Change %ChangeMSF-P PSF 874.9 622.0 -28.9 672.0 582.3 -13.3 618.8 482.5 -22.0 -44.9 Burnscar 115.3 485.5 321.0 325.3 448.2 37.8 271.9 388.5 42.9 236.9 Degraded 569.3 503.2 -11.6 533.9 583.9 9.4 727.4 737.9 1.4 29.6 Sedge 60.7 9.7 -84.0 88.0 5.1 -94.2 0.0 10.9 23773.8 -82.1 River 3.8 3.7 -2.7 4.6 4.3 -5.7 5.9 3.7 -37.4 -1.7MSF-I PSF 1689.5 1441.3 -14.7 1538.2 1424.2 -7.4 1542.0 1314.2 -14.8 -22.2 Burnscar 83.7 335.2 300.7 151.0 149.2 -1.2 119.7 323.4 170.1 286.6 Degraded 362.5 360.6 -0.5 437.7 563.9 28.8 475.6 499.6 5.1 37.8 Sedge 1.5 0.1 -94.2 5.1 0.0 -99.4 0.0 0.0 -69.2 -99.8 River 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0LPF PSF 1770.7 1739.4 -1.8 1830.8 1779.5 -2.8 1859.1 1776.7 -4.4 0.3 Burnscar 26.0 57.2 119.7 28.1 72.4 157.5 10.5 55.5 430.2 113.3 Degraded 110.2 110.4 0.2 46.3 55.1 18.9 37.4 74.4 98.9 -32.5 Sedge 0.0 0.0 0.0 0.7 0.0 -99.0 0.0 0.3 0.0 0.0 River 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0TIF PSF 1009.3 986.6 -2.3 1001.0 978.3 -2.3 1012.5 949.4 -6.2 -5.9 Burnscar 8.4 11.0 30.5 6.1 23.5 286.4 16.4 74.4 354.5 781.7 Degraded 26.7 46.9 75.6 36.6 42.6 16.7 15.7 20.8 32.2 -22.1 Sedge 0.1 0.1 -15.3 0.9 0.0 -96.0 0.0 0.0 0.0 -93.7 River 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0VLC PSF 278.8 271.8 -2.5 271.7 272.1 0.1 271.1 270.1 -0.3 -3.1 Burnscar 1.3 8.5 568.9 7.6 7.1 -6.1 4.3 2.1 -50.3 65.4 Degraded 3.0 2.7 -9.5 3.6 3.8 7.1 7.7 10.7 39.6 262.2 Sedge 0.0 0.0 0.0 0.2 0.1 -72.5 0.0 0.0 0.0 0.0 River 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0


59

2.Orangutandensity

a)

b)

FigureA2.1:Residualorangutandensityfora)MSF-Pandb)MSF-IfromJanuary2002toMay2017(n=131).


60

3.Changeinorangutandensityandforestcover

FigureA2.2:Estimatedorangutanpopulationineachsub-habitatandintotalforpre-andpost-fire2006,2010,and2015.PopulationisestimatedfromthemeasuredandestimatedorangutandensityandtheareaofpeatswampforestasdeterminedbytheMLC.ThetotalvalueexcludesindividualsthatmayoccupyVLCasnodensitymeasurementsweretakenforthatsub-habitat.TableA2.3:Estimatedorangutanpopulationandpercentchangeineachsub-habitatandintotalforpre-andpost-fire2006,2010,and2015.PopulationisestimatedfromthemeasuredandestimatedorangutandensityandtheareaofpeatswampforestasdeterminedbytheMLC.

2006 2010 2015 Overall Pre-fire Post-fire %Change Pre-fire Post-fire %Change Pre-fire Post-fire %Change %Change

MSF-P 1224 940 -23.2 877 825 -5.9 1180 1021 -13.5 -16.6MSF-I 1623 1089 -32.9 1095 1331 21.5 1995 2382 19.4 46.8LPF 701 840 19.7 833 447 -46.4 1537 2221 44.5 216.7TIF 1605 2338 45.6 2827 2569 -9.1 3029 3151 4.0 96.3Total* 5154 5206 1.0 5632 5171 -8.2 7742 8775 13.3 70.3

*ExcludesindividualsthatmayoccupyVLCasnodensitymeasurementweretaken.


61

FigureA2.3:PercentchangeintheproportionofSabangau’stotalforestcoverandpopulationrepresentedwithineachsub-habitatfrompre-fire2006topost-fire2015.


62

There is a significant decreasing linear relationship between average orangutan density and

Sabangau’stotalforestcover inMSF-P(R2=0.330,F(1,74)=36.384,p<0.001)andMSF-I(R2=0.242,F(1,74)=

23.572,p<0.001)(FigureA2.4);however,inboththeamountofvariationindensityexplainedbythemodel

islow.

a)

b)

FigureA2.4:RelationshipbetweenSabangau’stotalforestcoverandaverageorangutandensityina)MSF-Pand b) MSF-I for pre- and post-fire 2006, 2010, and 2015. Forest cover values are based on land coverclassification by the MLC, and error bars represent 95% confidence intervals. The relationship betweenaverageorangutandensityandSabangau’stotalforestcoverisnotsignificantforMSF-P(p<0.001)orMSF-I(p<0.001).(n=6for5061km2and5623km2;n=5forallothers)


63

TableA2.4:Summaryofpairedt-testresultsforvariationinaverageMSF-Torangutandensitybetweenpre-andpost-fireperiodsfor2002to2016.

Year Period N Mean SD T-value DF P-valueDirectionofchange

2002Pre-fire 5 0.71 0.04

-3.062 4 0.038* IncreasePost-fire 5 0.85 0.07

2003Pre-fire 6 0.84 0.07

-2.752 5 0.040* DecreasePost-fire 6 0.99 0.07

2004Pre-fire 6 0.99 0.07


2005Pre-fire 6 1.17 0.04

4.124 5 0.009* DecreasePost-fire 6 1.05 0.05

2006Pre-fire 6 1.05 0.05


2007Pre-fire 5 1.13 0.04


2008Pre-fire 5 1.21 0.03


2009Pre-fire 5 1.01 0.03


2010Pre-fire 5 1.16 0.04

-0.183 4 0.863 NochangePost-fire 5 1.16 0.05

2011Pre-fire 6 1.16 0.04


2012Pre-fire 6 1.43 0.08


2013Pre-fire 5 1.55 0.02

-0.575 4 0.596 IncreasePost-fire 5 1.57 0.06

2014Pre-fire 5 1.57 0.06


2015Pre-fire 5 1.67 0.10


2016Pre-fire 4 1.90 0.02

0.833 3 0.466 DecreasePost-fire 4 1.90 0.04

*Significantvariationbetweenmeanpre-fireandpost-fireorangutandensity


64


significantvariationbeforeandafter7fireeventsinMSF-P:2004(t(5)=-8.088,p<0.001),2006(t(5)=-3.909,p

=0.011),2008(t(4)=9.974,p=0.001),2009(t(4)=-5.403,p=0.006),2010(t(4)=3.046,p=0.038),2011(t(4)=-

6.235,p=0.002),and2015(t(5)=-3.040,p=0.038)(FigureA2.5;TableA2.4).Oftheseevents,densitywas

higherpost-fireinallbut2008and2010.

FigureA2.5:Averagepre-andpost-fireorangutandensityinMSF-Pfrom2002to2016.Errorbarsrepresent95%confidenceintervals.Significantdifferencesareindicatedby*p<0.05;**p<0.01;***p<0.001.(n=4in2016;n=5in2002,2007,2008,2009,2010,2013,2014,and2015;n=6in2003,2004,2005,2006,2011,and2012).


65

TableA2.5:Summaryofpairedt-testresultsforvariationinaverageMSF-Porangutandensitybetweenpre-andpost-fireperiodsfor2002to2016.

Year Period N Mean SD T-value DF P-valueDirectionofChange

2002Pre-fire 5 0.95 0.07


2003Pre-fire 6 0.99 0.15


2004Pre-fire 6 1.16 0.07


2005Pre-fire 6 1.37 0.02


2006Pre-fire 6 1.31 0.07


2007Pre-fire 5 1.45 0.04


2008Pre-fire 5 1.52 0.03


2009Pre-fire 5 1.27 0.05


2010Pre-fire 5 1.52 0.05


2011Pre-fire 6 1.41 0.04


2012Pre-fire 6 1.74 0.13


2013Pre-fire 5 1.74 0.04


2014Pre-fire 5 1.84 0.07


2015Pre-fire 5 1.92 0.15


2016Pre-fire 4 2.11 0.02




66


significantvariationbeforeandafter9fireeventsinMSF-I:2002(t(4)=-9.459,p=0.001),2003(t(5)=-4.437,p

=0.007),2004(t(5)=-6.503,p=0.001),2005(t(5)=5.810,p=0.002),2008(t(4)=8.297,p=0.001),2010(t(4)=-

3.257,p=0.031),2011(t(4)=-5.645,p=0.002),2012(t(5)=-10.596,p<0.001),and2015(t(5)=-7.372,p=0.002)

(FigureA2.6;TableA2.5).Oftheseevents,densitywashigherpost-fireinallbut2005and2008.

FigureA2.6:Averagepre-andpost-fireorangutandensityinMSF-Ifrom2002to2016.Errorbarsrepresent95%confidenceintervals.Significantdifferencesareindicatedby*p<0.05;**p<0.01;***p<0.001.(n=4in2016;n=5in2002,2007,2008,2009,2010,2013,2014,and2015;n=6in2003,2004,2005,2006,2011,and2012).


67

TableA2.6:Summaryofpairedt-testresultsforvariationinaverageMSF-Iorangutandensitybetweenpre-andpost-fireperiodsfor2002to2016.

Year Period N Mean SD T-value DF P-valueDirectionofChange

2002Pre-fire 5 0.43 0.03


2003Pre-fire 6 0.66 0.06


2004Pre-fire 6 0.80 0.08


2005Pre-fire 6 0.94 0.08


2006Pre-fire 6 0.74 0.03


2007Pre-fire 5 0.76 0.07


2008Pre-fire 5 0.84 0.03


2009Pre-fire 5 0.71 0.02


2010Pre-fire 5 0.74 0.03


2011Pre-fire 6 0.87 0.08


2012Pre-fire 6 1.07 0.07


2013Pre-fire 5 1.33 0.03


2014Pre-fire 5 1.26 0.06


2015Pre-fire 5 1.39 0.05


2016Pre-fire 4 1.65 0.05




68

4.Orangutanhomerange

a)

b)

c)

FigureA2.7:Annualhomerangesizeofadultandadolescent femalescomparedtothenumberof followswhenconsideringa)all individuals inthedataset(n=114),b)only individualswithastatusoffrequentorregular(n=68),andc)onlyindividualswithastatusoffrequent(n=25).Therelationshipbetweenthetwovariablesissignificantinallcircumstances(a:p<0.001;b:p<0.001;andc:p=0.038).


69

a)

b)

FigureA2.8:Individuals’annualhomerangesizesfrom2003topre-fire2015fora)adultfemales(n=36)andb)adolescentfemales(n=19).HomerangesizedoesnotsignificantlyvarywithtimeforAF(R2=0.020;F(1,34)=0.680;p=0.415)orADF(R2=0.150;F(1,17)=2.992;p=0.102).


70

TableA2.7:Annualandaveragehomerangesize(km2)forresidentadultfemalesduringpre-andpost-fire2015.Rangesizeisbasedonthemaximumconvexpolygon.

Name Year Status Homerangesize(km2)

Pre-fire2015

Feb

2010 Regular 1.32 2011 Regular 1.38 2012 Frequent 2.55 2013 Frequent 2.13 2014 Regular 1.50 2015 Regular 1.65 Average 1.75 SD 0.49

Gracia2012 Regular 1.54

2013 Regular 1.71 2014 Regular 1.71 Average 1.66 SD 0.10

Indah

2003 Frequent 0.43 2004 Frequent 1.75 2005 Frequent 2.26 2006 Frequent 2.45 2007 Regular 1.21 2008 Regular 1.90 2009 Regular 0.92 2012 Regular 1.16 2014 Regular 0.76 Average 1.43 SD 0.70

Indy

2012 Frequent 1.88 2013 Frequent 1.33 2014 Frequent 1.20 2015 Regular 1.13 Average 1.38 SD 0.34Post-fire2015

Feb2016 Regular 0.45

2017 Frequent 1.67 Average 1.06 SD 0.86 Gracia 2016 Regular 1.27 Indah 2016 Regular 0.91 Indy 2016 Regular 0.92


71

FigureA2.9:AnnualhomerangesizebasedontheminimumconvexpolygonforGracia(residentadultfemale)from2012to2016.(n=numberoffollows/year:2012:n=15;2013:n=29;2014:n=14;2016:n=17)

FigureA2.10:AnnualhomerangesizebasedontheminimumconvexpolygonforIndy(residentadultfemale)from2012to2016.(n=numberoffollows/year:2012:n=41;2013:n=37;2014:n=34;2015pre-fire:n=16;2016:n=33)


72

FigureA2.11:AnnualhomerangesizebasedontheminimumconvexpolygonforIndah(residentadultfemale)from2003to2016.(n=numberoffollows/year:2003:n=14;2004:n=54;2005:n=67;2006:n=44;2007:n=17;2008:n=15;2009:n=10;2012:n=14;2014:n=16;2016:n=15).

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