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ContentslistsavailableatSciVerseScienceDirect

Ecological

Indicators

j ou rn a l h o m e pa g e :w w w . e l s e v i e r . c o m / l o c a t e / e c o l i n d

Mark-recapture

of

the

endangered

franciscana

dolphin

(Pontoporia

blainvillei)

killed

in

gillnet

fisheries

to

estimate

past

bycatch

from

time

series

of

stranded

carcasses

in

southern

Brazil

J.H.F.

Prado

a,b,∗

,

E.R.

Secchi

b

,

P.G.

Kinas

c

aProgramadePós-Graduac¸ãoemOceanografiaBiológica,InstitutodeOceanografia,UniversidadeFederaldoRioGrande,P.O.Box474,RioGrande,Rio

GrandedoSul96201-900,Brazil

bLaboratóriodeTartarugaseMamíferosMarinhos,InstitutodeOceanografia,UniversidadeFederaldoRioGrande,P.O.Box474,RioGrande,RioGrandedo

Sul96201-900,Brazil

cLaboratóriodeEstatísticaAmbiental,InstitutodeMatemática,EstatísticaeFísica,UniversidadeFederaldoRioGrande,P.O.Box474,RioGrande,Rio

GrandedoSul96201-900,Brazil

a

r

t

i

c

l

e

i

n

f

o

Articlehistory:

Received6February2012

Receivedinrevisedform31January2013 Accepted7March2013 Keywords: Tagrecovery Marinemammals Logisticregression Bayesianinference

a

b

s

t

r

a

c

t

Incidentalfisherymortalityestimatesoffranciscanabasedonstrandingdataarebiaseddownwards,as onlyafractionofthetotalbycatchendsupashore.Weestimatedtheprobabilityofafranciscana inciden-tallykilledbythecoastalgillnetfisheriesinsouthernBraziltowashashoreandusedthisasacorrection factortoback-calculatefishingrelatedmortalityfromadatasetofcarcassescollectedbetween1979and 1998.FromNovember2005toJanuary2009,145franciscanasincidentallykilledinnetsweretaggedand returnedtothesea.Only11ofthetaggedanimalswerefoundduringbeachsurveys.GeneralizedLinear Modelswereusedtomodeltheprobabilityofataggedfranciscanareachingtheshoreasafunctionof thecovariateswaveperiod,winddirectionandintensity,distancefromcoastandthetargetspeciesof thefishery.Thetargetspecieshadasignificanteffectonthestrandingprobability.Thestranding prob-abilityofataggedfranciscanawashigherinthefisherytargetingwhitecroaker(Micropogoniasfurnieri) (median=0.105;95%CI=0.05–0.18)ratherthanweakfish(Cynoscionguatucupa)(0.013;0.0003–0.069). Asthestrandingprobabilityestimateforweakfishwasimprecise(widecredibleinterval)wedecidedto hindcastthenumberoffranciscanasincidentallykilledforwhitecroakerseasononly.Thecorrected esti-mateoffranciscanamortalitywasapproximately10timeshigherthanpreviousestimatesbasedsolelyon strandingdata.Finally,thisnovelmark-recaptureapproachprovidesausefulcorrectionfactortoreduce thebiasinincidentalmortalityestimatesderivedfromstrandingdata.

©2013ElsevierLtd.Allrightsreserved.

1. Introduction

The franciscana, Pontoporia blainvillei, is a small cetacean

endemictothewesternSouthAtlanticOcean.Itscoastal

distribu-tiongreatlyoverlapswithfishingactivities,andbycatchingillnets

isthemainthreattoitsconservation(Secchi,2010).Bycatchin

gillnetfisheriesisobservedthroughoutthefourfranciscana

man-agementareas(FMAsensuSecchietal.,2003a)(e.g.Bertozziand

Zerbini,2002;Kinas,2002;Santosetal.,2002;DiBeneditto,2003; Secchietal.,2003b).However,thehighestbycatchisrecordedin

∗ Correspondingauthorat:ProgramadePós-Graduac¸ãoemOceanografia Biológ-ica,InstitutodeOceanografia,UniversidadeFederaldoRioGrande,P.O.Box474,Rio Grande,RioGrandedoSul96203-900,Brazil.Tel.:+555332336537.

E-mailaddresses:jonatashenriquef@yahoo.com.br(J.H.F.Prado), edu.secchi@furg.br(E.R.Secchi),paulkinas@furg.br(P.G.Kinas).

thecoastalwatersofRioGrandedoSulState(RS),whichtogether

withtheinnershelfofUruguayrepresentFMAIII.

Data on franciscanamortality have been systematically

col-lectedfrombeachsurveyssincethelate1970s(e.g.Pinedoand

Polacheck,1999), whengillnetfishery operationsstartedin the

coastalregionofsouthernBrazil(Reisetal.,1994).Between1979

and1998,1076deadfranciscanaswerefoundwashedashoreon

thecoastofRS(PinedoandPolacheck,1999).Intheearly1990sthe

coastalgillnetfleetbegantobesystematicallymonitored

(volun-tarilyrecordeddatabyfishermenthroughspecificlogbooks)with

thepurposeofestimatingmoreaccuratelytheincidental

mortal-ityoffranciscanas(e.g.Secchietal.,1997,2004;KinasandSecchi,

1998).Bycatchestimates fromfisheries, monitoredvia logbook

records,are appreciablyhigher thanestimates frombeach

sur-veys,suggestingthatonlyafractionofthefranciscanasincidentally

caughtingillnetsarewashedashore(Secchietal.,1997).Logbook

monitoringofthegillnetfleetfromRSprovidedanestimated

mor-talityof946(CI=467–1525)franciscanasin1999and719(CI=CI:

1470-160X/$–seefrontmatter©2013ElsevierLtd.Allrightsreserved. http://dx.doi.org/10.1016/j.ecolind.2013.03.005

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248–1413)in2000(Secchietal.,2004).Theseestimatesare

consid-erablyhigherthanthosereportedbyPinedoandPolacheck(1999)

forearlieryearsbasedonstrandings.

Williamsetal.(2011)observedthatabout2%ofcarcassesof

dolphinsdyinginthenorthernGulfofMexicoarerecoveredas

strandings.SimilarvalueswerefoundbyEpperlyetal.(1996).These

authorsuseddataonseaturtlestrandingratesinNorthCarolinaas

anindicatorofthetotalnumberofturtleskilledbyfisheriesand

estimatedthatonly7–13%ofanimalscaughtinfisherieswashed

ashoreinwinter.Hartetal.(2006)analyzedthespatiotemporal

patternofseaturtlesstrandingsinthisregionandconcludedthat

strandingratesvaryseasonallyduetogeographicaland

environ-mentalvariablessuchaswinddirectionandstrengthanddistance

fromshore.

While franciscana stranding data have been collected since

thelate1970s, themagnitudeof incidentalmortalityremained

unknownuntilthemid1990s,asthere wasnodirect

monitor-ingofthegillnetfleetinsouthernRSduringthatperiod(Pinedo

andPolacheck,1999).Therefore,franciscanafishing-related

mor-talityestimates,duringthisperiod,reliedoncountsofbeached

carcassesonly(e.g.Pinedoetal.,1989;PinedoandPolacheck,1999).

Althoughitwasacknowledgedthatthesedatalikely

underesti-matedthetruebycatchrate(Secchietal.,1997,2004),noattempt

hadbeenmadetocorrectforthisbias.Thisstudypresentsanovel

approachtoestimatetheprobabilitythatafranciscanakilledinthe

coastalfisheriesinsouthernBrazilwillendupashoreand

deter-mineswhichvariablesaffectthis probability.Thisprobabilityis

thenusedascorrectionfactortoback-calculatethelikelynumber

offranciscanasincidentallykilledforthoseyearswithoutlogbook

monitoring,usingdataonthenumberofcarcassesfoundashore.

Theapproachusedherepresentsanovelmethodologytoutilize

strandingdatatoassessthemagnitudeofcetaceanandotherlarge

vertebrateshuman-derivedmortalityforperiodswhendatafrom

directfisheriesmonitoringarenotavailable.

2. Materialsandmethods

2.1. Studyarea

TheStateofRioGrandedoSul(RS)ischaracterizedbyastraight

coastoriented northeast/southwest and presenting a relatively

widecontinental shelf (60–122nm atthe180misobath)and a

smoothslope.Thisregionhasaseasonallyvariablewindregime

(Piolaetal.,2005),withnortheastwindspredominatinginsummer

andgeneratingasouthwardflowofcoastalwaters,andsouthwest

windsinwinter,withcoastalwatersflowingnorthward(Mölleret

al.,2008).Thetidalinfluenceisminimal,withmeanamplitudeof

0.47m.

2.2. Mark-recapturedata

ThemonitoredcoastalgillnetfleetisbasedinRioGrande

(south-ernRioGrandedo SulState)and comprisesabout140boats.It

operatesbetweenMostardas(31◦ 13S)and Chuí(33◦ 45S), in

waterdepthsfrom5to150m(Fig.1).However,65%oftheboats

fishinwatersof35morless.Thisfleetisconsideredthemost

rep-resentativeinvolumeofcatchforcoastalgillnetfisheriesinRio

Grandedo SulState(Reisetal., 1994)and alsoresponsible for

ahighnumber ofincidentallycaughtfranciscanas(Secchietal.,

2004).Thetwomaintargetspeciesofthefisheryarewhitecroaker

(Micropogoniasfurnieri)inspringandsummer(OctobertoMarch)

andstripedweakfish(Cynoscionguatucupa)inautumnandwinter

(ApriltoSeptember)(Secchietal.,1997;Ferreira,2009).

FromNovember2005toJanuary2009,10–20boatswere

mon-itored. Although the study was conducted based onvoluntary

Fig.1. RioGrandecoastalgillnetfleetfishingground(shadedgray)andthestretch ofbeachsurveyedforstrandedcarcasses(darkline).Thediscontinuityofthedark linerepresentsthemouthofthePatosLagoonestuary.

cooperationofthefishermen,itwasassumedthattheywere

rep-resentativeoftheentirefleetsinceboatcharacteristicsandfishing

operationsweresimilaracrossthefleet.Eachboatreceivedasetof

materialscontainingseals,numberedplastictags,toolstoattach

thetagtothecarcass and logbookstoregister foreach fishing

daythedateandfishinglocation,depth,initialandendposition

ofthenet,targetspecies,numberoffranciscanascaught(including

zerointheabsenceofcapture).Incidentallycapturedfranciscanas

weremarked(fishermenwereinstructedtoattachthenumbered

tagbetweentheanimal’slowerjaws–Fig.2),andtheGPS

posi-tionwherethecarcasswasreturnedtoseawasrecorded.Because

duringthefirsttwoyearsofthestudythis informationwasnot

available,thepositionofthereturnedcarcasswasassumedtobe

asthemidpointbetweentheinitialandendpositionsofthenet

set.Themonitoredfishermenwerevisitedonceortwiceaweekin

ordertoassesstheircompliancewiththisstudy.

Systematic beach surveys werecarried out fortnightlyfrom

Lagoa do Peixe(31◦ 26S–051◦ 09W)to Chuí (33◦ 45S–053◦

22W),theborderofBrazilandUruguay,totaling370km

(approx-imately80%ofthelatitudinalextentofthefishinggroundofthe

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monitoredfleet)(Fig.1).Thebeachwassurveyedusing a

four-wheel-drivevehiclewithtwotofourobserversscanningfromthe

washzonetothebaseofthesanddunes.TheGPSlocation,

decom-positionstate(GeraciandLounsbury,2005),bodymeasurements

andthetagnumber(ifpresent)wererecordedforeachstranded

animal.Inordertominimizethechancesofdoublecounting,

car-casseswerespraypaintedandthepositionofstranding,totallength

anddegreeofdecompositionofthespecimenverified.

Thegeographicalcoordinatesofmarkedandrecaptured

fran-ciscanaswereplottedongeo-referencedmapsinSurfer8.0.The

distancesbetweenthereturnpositionofthemarkedfranciscanas

atseaandcoastline(shortestperpendiculardistancefromcoast),

aswellasthedistancebetweenthereturnandstrandingpositions

(driftingdistance)weredeterminedthroughGPSTracKMaker,

Ver-sion1.3.4.DataforwhichdepthandGPSposition,wheremarked

franciscanaswerereturnedatsea,didnotmatchongeo-referenced

maps,wereexcludedprevioustoanalysis.Thiswasdonebecause

lackofmatchingwouldindicateinappropriatedatarecordingby

fishermenandcouldresultinwrongestimatesofthedistanceof

returnedcarcassestoshore.

2.3. Oceanographicdata

Windandwave datawere obtainedthrough theTOMAWAC

numeric model (Benoit et al., 1996; Benoit, 2005), with input

datafromWAVEWATCHIII(WW3)(NationalCenterfor

Environ-mental Prediction – NCEP/NOAA) and wind field of Reanalysis

projects (National Oceanic and Atmospheric Administration –

NOAA,database).Datawereconsideredforthefirstfivedayssince

thefranciscanawasreturnedtoseaandforaspatialresolutionof

4×4km.

2.4. Statisticalmodel

Weassumedthatamarkedfranciscana(yi)(i=1,2,...,n)“found

ashore”(yi=1)ornot(yi=0)ispossiblyaffectedbyasetofuptofive

explanatoryvariables,x1=winddirection(degree),x2=wind

inten-sity(m/s),x3=waveperiod(s),x4=distancefromthecoast(km)and

x5=targetspecies(x5=0forstripedweakfishfisheriesandx5=1

forwhitecroakerfishery).Allvariableswereusedasalinearterm,

exceptwinddirectionthatwasusedasaquadraticterm.Target

specieswastheonlycategoricalvariable.Allquantitative

explana-toryvariableswerecenteredbeforeusedsuchthatXij=(xij− ¯xj),

wherej=1(winddirection),2(windintensity),3(waveperiod)and

4(distance fromthecoast).The advantageofthisis generating

posteriorsampleswithlowerautocorrelationwhichimprovesthe

efficiencyoftheMCMCsampling(McCarthy,2007).Wemodeledyi

asaBernoullidistributionwithwashing-ashoreprobabilityi(Eq.

(1)) yi∼Bern(i) h(i)=log



 1−i



=ˇ0+ˇ1Xi1+···+ˇ4Xi4+ˇ5xi5, (1)

where ˇ0 to ˇ5 are regression parameters to be estimated:

ˇ0=baselineeffectforstripedweakfish,ˇ0+ˇ5=baselineeffectfor

whitecroaker.

TheBernoullidistributionistheBinomialdistributionwithonly

onereplicate.Sinceeachindividualstrandingis,infact,asingle

replicate,withacase-specificstrandingprobabilityforeachevent

i=1,2,...,n,withyieither0or1,theBernoulliistheadequate

distributiontochoosehere.

Weadopteda weaklyinformativenormalprior(mean0and

varianceequal1× 106)forallcoefficients.Theposterior

distribu-tionsoftheregressionparameterswereobtainedbytheMarkov

Table1

Twentyoneproposedmodels.

Model1 Winddirection

Model2 Windintensity

Model3 Waveperiod

Model4 Distancefromthecoast

Model5 Targetspecies

Model6 Winddirection+windintensity

Model7 Winddirection+waveperiod

Model8 Winddirection+distancefromthecoast Model9 Winddirection+targetspecies

Model10 Windintensity+waveperiod

Model11 Windintensity+distancefromthecoast Model12 Windintensity+targetspecies Model13 Waveperiod+distancefromthecoast Model14 Waveperiod+targetspecies

Model15 Winddirection+windintensity+waveperiod Model16 Winddirection+windintensity+distancefromthecoast Model17 Winddirection+waveperiod+distancefromthecoast Model18 Windintensity+waveperiod+distancefromthecoast Model19 Winddirection+windintensity+waveperiod+distance

fromthecoast

Model20 Winddirection+windintensity+waveperiod+target species

Model21 Winddirection×distancefromthecoasta

Model22 Windintensity× distancefromthecoasta

aInteraction.

chain Monte Carlo (MCMC) method implemented in OpenBugs

(Spiegelhalteretal.,2004).Atotalof100,000sampleswere

sim-ulatedtogeneratetheposteriordistributionforeachparameter,of

which10,000sampleswerediscardedasburn-in.

Twenty-one ecologically plausible models were proposed

(Table1).Thefitofthesemodelswascomparedusingthedeviance

informationcriterion(DIC),theBayesianequivalentofAIC(Eq.(2)),

(Spiegelhalteretal.,2002).

DIC=D + 2pd (2)

whereD isposteriordistributiondevianceandpdistheeffective

numberofestimatedparameters.Themodelselectionwasbased

ontheDICvalue,whichindicatesthegoodnessoffit,and

parsi-mony(McCarthy,2007).ModelswithlowerDICvalues andless

than2unitsdifferenthavesimilarlevelofsupportandwere

con-sideredplausiblemodels(Spiegelhalteretal.,2002).Nevertheless,

thosemodelswhichthecredibleintervalsincludedzerowerenot

consideredplausiblemodels(McCarthy,2007).

Afterselecting“thebestmodel”theposteriordistributionfor

“theprobabilityoffranciscanasincidentallykilledinthecoastal

gill-netfisheriesoffRioGrandeto“washashore”wasobtainedapplying

theinverselogitfunctionasshowninEq.(3)

P(|data)=11+e−h(), (3)

whereh () istheposteriorlinearpredictorwithallquantitative

variatessetatthemean(i.e.,X1,X2,X3andX4allequaltozero)and

x5=0orx5=1forthetargetspecies,stripedweakfishandwhite

croaker,respectively.

Finally,theposteriordistributionfor“thenumberoffranciscanas

incidentallycaught”(Nc)wasobtainedbyEq.(4)

Nc=



Ns P(ˆ|data)



, (4)

whereNsisthenumberofstrandedfranciscanasreportedinPinedo

andPolacheck(1999).

WeusedthemeanoftheposteriordistributionasaBayes

esti-matorforˇ0 toˇ5 andthemedianforP(



|data)and(Nc)dueto

strongasymmetryintheposteriordistributions.Forallinferences

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Fig. 3.Distribution of franciscanas incidentally caught and marked during spring/summer(circle)andautumn/winter(triangle)insouthernRioGrandedoSul statecoast.Straightlineconnectthespotswheretaggedfranciscanaswerereleased andstranded.

Allanalysesandvisualizationswereperformedusingthefree

softwareR(RDevelopmentCoreTeam,2008)andOpenBUGSvia

librariesR2WinBUGSandBRugs(Sturtzetal.,2005).

3. Results

Thenumberofincidentallycaughtandmarkedfranciscanaswas

145in114gillnetsetsduringthestudyperiod(November2005to

January2009)(Fig.3).Ofthese,67weremarkedinspring(n=58

inwhitecroakerfishery;n=9instripedweakfishfishery),25in

summer(n=24inwhitecroakerfishery;n=1instripedweakfish

fishery),18inautumn(allinthestripedweakfishfishery)and36

inwinter(n=3inwhitecroakerfishery;n=32instripedweakfish

fishery).Elevenoutof145markedfranciscanaswererecapturedon

thebeach(teninspringandoneinwinter)(Fig.3).Allrecaptured

franciscanashadbeenthrownbacktosealessthan30kmoffshore

and72%ofthosehadbeendiscardedlessthan15kmfromthecoast

(Table2).

Duringthestudyperiod,566untaggedstrandedfranciscanas

wererecordedalong11,623kmofsurveyedbeach.Thestranding

rates(numberoffranciscanasper100kmofbeachsurveyed)were

Table2

Numberofmarked(M)andrecaptured(R)franciscanasbyseasonanddistancefrom coastofdiscardinglocations.

Distancefrom coast(km)

Spring Summer Autumn Winter

M R M R M R M R <10 37 5 11 − 5 − 8 1 11–15 13 2 1 − 1 − 4 − 16–20 4 1 5 − 3 − 2 − 21–25 3 − − − 0 − 2 − 26–30 4 2 2 − 0 − 4 − >30 6 − 6 − 9 − 15 − Total 65 10 25 − 18 − 35 1

higherinspring(n=436;14.16)andsummer(n=99;3.68)thanin

autumn(n=15;0.45)andwinter(n=16;0.64).

Although the mean distance to coast from where marked

bycaught franciscanas were returned to the sea was 10.75km

(SD=9.61),themeandriftingdistancewas34.56km(SD=31.56)

(Fig.3).

TheDICvaluesareshownforthefivebestofthetwenty-two

developedmodels(Table3).ThedifferencesamongtheDIC

val-uesbetweenallmodelswerenotlarge(0.4–4.1),especiallywhen

consideringthebesttwomodels,forwhichthedifferenceswere

lessthan0.5,suggestingthattheyarevirtuallyindistinguishable.

Forthesetwobestmodelsthecoefficients’credibleintervalsdidnot

encompasszero,suggestingthatthereisarelationshipbetween

theirrespectivecovariateandthewashingashoreprobabilityof

afranciscana(Table3).Withincreaseindistancefromthecoast

(Model4;DIC=94.2)thestrandingprobabilitydecreases(Fig.4).

Thepositivevaluesofthecredibleintervalsforcoefficient(ˇ5)of

Model5(DIC=93.8)suggeststhatthewashingashore

probabil-ityofataggedcarcassishigherforthefisherytargetingonwhite

croakerthanonstripedweakfish.Forthethreeremainingmodels

(1,DIC=97.9;2, DIC=95.5and 3, DIC=96.8)thecredible

inter-valsoftheircoefficientsencompasszero,whichmeansthatthere

isnoclearrelationshipbetweentheirrespectivevariableandthe

probabilityofataggedcarcasswashingashore.

Asamongthebestmodels,Model5(targetspecies)was

cho-sentoestimatetheprobabilityofafranciscanaincidentallykilled

incoastalgillnetfisheriesoffRioGrandewashingashore.Sincethe

onlyinformationavailableinPinedoandPolacheck(1999)isthe

datewheneachfranciscanawasfoundashore,thetargetspecies

couldbedeterminedbasedonfishingseasons(date).Thus,byusing

dateofstrandingasaproxyfortargetspecies,itwouldbepossible

toback-calculate,atleastroughly,thenumberoffranciscanas

inci-dentallykilledbasedonthenumberofstrandedcarcassesfound

duringthecroakerseason.

Table3

DICsvaluesforthefivelogisticregressionmodelsandthecoefficientestimateforthem.ˇ1(winddirection),ˇ2(windintensity),ˇ3(waveperiod),ˇ4(distancefromcoast),

ˇ5(targetspecies:whitecroakercategory).

Models Mean(standarddeviation) DIC

[Cr.I.] ˇ0 ˇ1 ˇ2 ˇ3 ˇ4 ˇ5 Model1 −2.32(0.40) −0.00009(0.0001) [−3.15;−1.57] [−0.0003;0.00007] 97.9 Model2 −2.71(0.36) 0.41(0.24) [−3.47;−2.07] [−0.05;0.90] 95.5 Model3 −2.61(0.33) 0.27(0.30) [−3.30;−2.01] [−0.34;0.83] 96.8 Model4 −3.01(0.49) −0.05(0.03) [−4.10;−2.19] [−0.12;−0.005] 94.2 Model5 −4.53(1.34) 2.37(1.38) [−7.85;−2.60] [0.28;5.70] 93.8

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Fig.4. Probabilityofafranciscanastrandingaccordingtodistancefromcoastat positionwhereitwasmarkedandreturnedtosea.Thiscurvewasgeneratedfromthe medianoftheposteriorprobabilitydistributionoffranciscanastrandingfordifferent distancestocoast.Thedashedlinesindicate95%credibleintervals.

Accordingtoposteriormedians,thestrandingprobabilityinthe

whitecroakerfishery(median=0.105;CI=[0.05;0.18])isaboutten

timeshigherthaninthestripedweakfishfishery(median=0.013;

CI=[0.0003;0.069]).

Theposteriordistributionfor incidentalmortalityof

francis-canasconditionedonthenumberofstrandedcarcassesrecorded

inPinedoandPolacheck(1999)between1979and1998(except

from1989to1991)wasobtainedwithequation4.However,the

lackof precision(wide credibleinterval)associated tothevery

lowstrandingprobabilityestimateforthestripedweakfish

fish-eryismagnifiedwhenestimatingincidentalmortality.Hence,we

decidedtohindcastthenumberoffranciscanasincidentallykilled

forwhitecroakerseasononly.Theincidentalmortalityestimates

of franciscana obtained in this study for white croaker season

between1979and1998(except1989–1991)(Median=9409;CI

[5553–18,546])wasapproximately10timeshigherthanestimates

obtainedinPinedoandPolacheck(1999)forthesameseasonand

period(992strandedindividuals).

Thecorrectedincidentalmortalityestimatefromstranded

fran-ciscanas from1979 to2007 indicatesa much higher mortality

thanthatreportedfromstrandings(Fig.5).Despitesomeyear-to

yearvariation,thecorrectedestimatessuggestaslighttemporal

increase.

4. Discussion

Directindependentonboardmonitoringoffisheriesisessential

toproduceaccurateestimatesofmarinemammalbycatchrates.

However,thisrequiresthata largerepresentativeproportionof

afleetsfishingeffortisobservedandsuchmonitoringprograms

areinherently costlyand requireeitherthe voluntary

coopera-tionoffishermenordirectlegislation mandatingthatobservers

arecompulsory.Whiledatafromstrandingprogramscanbeused

toestimatebycatchrates,thelevelofbiasintheestimates

pro-ducedwillbedirectlyrelatedtotheprobabilitythatacarcasswillbe

beach-cast.Thereforethemethodologypresentedinthisstudy

pro-videsanovelframeworkforestimatingthisbias,therebyproviding

a cost-effective technique to improve bycatch estimates from

Fig.5. Incidentalmortalityestimateforfranciscanasobtainedinthisstudyfrom stranded carcasses reported in Pinedo and Polacheck (1999) for the period 1979–1998andreportedby LaboratóriodeTartarugaseMamíferos Marinhos (LTMM-FURG)from1999to2007.Theestimatecorrespondsforwhitecroaker sea-sononly.Nodataareavailablefrom1988to1991.Thedashedlinesindicate95% credibleintervals.

strandingdata,whendirectfisheriesmonitoringisnotpossible.The

seasonal differences in thenumber of franciscanas incidentally

caughtandmarkedislikelyaresultofthedistancethatgillnetsare

setfromshoreinthedifferentfisheries.Duringthewhitecroaker

fishery, gillnetsaresetclosetoshore,predominantly indepths

oflessthan35m(Secchietal.,1997,2004;Ferreiraetal.,2010),

whichcoincideswiththedistributionpatternoffranciscana(Secchi

andOtt,2000;Secchietal.,2001;Danilewiczetal.,2009,2010; Ferreiraetal.,2010).However,duringthestripedweakfishfishery,

thegillnetfleetoperatesmostlyfartherfromthecoast,indepths

greaterthan35m(Secchietal.,1997,2004;Ferreiraetal.,2010),

wherefranciscanasarelessabundant(SecchiandOtt,2000;Secchi

etal.,2001;Danilewiczetal.,2009,2010;Ferreiraetal.,2010).The

higherprobabilityoffranciscanabycatchinsummer/springthanin

autumn/winterislikelyrelatedtothehigherfishingeffortcloserto

shore(Secchietal.,1997;Ferreira,2009;Ferreiraetal.,2010).

Ouranalysesshowthattheprobabilityofafranciscanacarcass

washingashoreismuchhigherinthewhitecroakerfishery,which

isdrivenbythefactthatthisfisheryoperatesmuchclosertothe

coastthanstriped weakfish fishery.Intuitively, objectsreleased

closertoshorehaveahigherprobabilityofreachingtheshorethan

thosereleasedfarfromthecoast.Distantcarcasseshavealower

probabilityofstrandingbecausetheyaremorelikelytodecompose,

sinkorbeeatenbysharksorbecausethedurationof

stranding-favorableconditionsmaynotbesufficienttocarrythemtoshore.

Perrinetal.(2010)estimatedthatdeadcoastalcommonbottlenose

dolphins(Tursiopstruncatus)were50timesmorelikelytostrand

thantheiroffshoreconspecifics,andthislikelihoodwasprobably

duetoscavengingbypredators(sharks),sinkingduring

decomposi-tion,andtheinfluenceofwindandcurrents.Likewise,Normanetal.

(2004)suggestedthatalthoughDall’sporpoises(Phocoenoidesdalli)

aremoreabundantthanharbourporpoises(Phocoenaphocoena)in

thesoutheasternBeringSea(Mooreetal.,2002),strandingsare

lessfrequentduetotheirpreferencefordeeperwaters.Hartetal.

(2006),usingdriftbottlereturndata,alsosuggestedthatonlythose

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Table4

Estimatesoffranciscanasincidentallykilledobtainedafterusingthecorrection fac-tor(Method1),estimatesreportedinFerreira(2009)(Method2)andestimateson strandedcarcassescountedduringsystematicbeachsurveys.Forallmethodsthe estimatescorrespondedforwhitecroakerseasononly.

Year Method1 Method2 Method3

Median(CI) Mean(CI)

1997 702(414–1383) 354(129–782) 74 1998 711(419–1402) 919(553–1445) 75 1999 740(436–6277) 1035(512–1865) 78 2000 1356(800–2673) 495(178–1108) 143 2001 38(22–74) 249(84–588) 4 2002 1356(800–2673) 607(223–1360) 143 2003 436(257–860) 194(71–428) 46 2004 2428(1433–4786) – 256 2005 1640(968–4179) 681(258–1476) 173 2006 2115(1248–4169) 551(299–933) 223 2007 1138(671–2243) 174(85–321) 120

Althoughwindintensityand directiononacross-shelfocean

circulationhavebeensuggestedasimportantaspectsofcarcass

transportatsea(e.g.BibbyandLloyd,1977;DeGangeetal.,1994;

Epperlyetal.,1996;Normanetal.,2004;Hartetal.,2006;O’Hara andMorgan,2006;Chaloupkaetal.,2008;Peltieretal.,2011),these

variablesandwaveperiodtoowerenotimportantindetermining

franciscanastrandingprobabilityinthewaytheyweremodeledin

ourstudy.

Inordertoapplythecorrectionfactorestimatedinthisworkto

thetimeseriesdataofstrandedfranciscanaanumberof

assump-tionswere madethat(1) thenumberof carcassesthat washed

ashoreinthestudyyeararerepresentativeofpreviousyears,(2)the

patternsobservedinourmark-recaptureexperimentreflect

envi-ronmentalphenomenathathavenotchangedsignificantlyoverthe

past30years,and(3)thespatialandtemporaldistributionofthe

RioGrandegillnetfishinghasnotchangedsignificantlyoverthe

years.Thislatterassumptionisprobablymetasthemaintarget

specieshasremainedconstantandthereisnoevidencethattheir

distributionhaschanged(Haimovicietal.,1996).

Although mortality estimates described in Ferreira (2009),

obtainedfromreportedbycatch(voluntaryrecordeddataby

fisher-menthroughspecificlogbooks)providedbyafractionofthecoastal

gillnetfleetbetween1997and2007(Method2)were

consider-ablylowerthanestimatesobtainedinthisstudy(Method1),with

theexceptionoftheyears1998,1999and2001,thetwoestimates

aremoresimilarthanthoseproducedusingstrandingdataalone

(Method3)(Table4).Therefore,strandingdataalone(Method3)

considerablyunderestimatemortality(Table4).Itisnotclear,

how-ever,which method(Method1orMethod2)islessbiased(see

aboveexplanation).

For1998,1999and2001mortalityestimateswerelowerthan

thosecalculatedfromlogbooksandthislikelyreflectslowerbeach

survey effort in these years (Table 4). There are several other

potentialsourcesofbias:(i)themortalityestimatesfromlogbooks

representonly fishing mortality,while ourestimates represent

naturalandnon-naturalmortality.Secchi(2006)showedthatthe

agestructure of franciscanas killedin coastal gillnetfleetswas

slightdifferentfromthosestrandedonthecoastand suggested

that strandedanimalsrepresent a mixture of both natural and

non-naturalmortality.However,asthenaturalmortalityoflarge

mammalsissmall(Caughley,1977–lowerthan0.01incetaceans;

e.g.Taylor,2007)and knowing thatothernon-naturalcause of

mortality,suchas,ingestionofdebris,chemicalcontaminationand

habitatlossareunlikelyintheregionitisreasonabletoassume

thatthevastmajorityofthecarcassesfoundonthebeachwere

killedinfisheries.(ii)estimatesmadefromlogbooksdependon

thehonestyanddiligencewithwhichthelogbooksarecompleted.

Usually,voluntaryreportsofbycatcharebiaseddownwards(e.g.

Hamer et al., 2008), do not account for drop-outs (Bravington and Bisack, 1996)and depend onthe fishers who report their

catchesbeingrepresentativeofthefishery.(iii)afractionofthe

gillnetfleetfromtheneighboringstateofSantaCatarinastarted

operating in the coastal region of Rio Grande do Sul state in

theearly2000s. Astheseboatshavenotbeenmonitored,

fran-ciscanas incidentallycapturedby this fleet hasbeenaccounted

foronlythroughbeachsurveys.iv)taggedfranciscanasmay

dis-appearfromthebeachduetoscavengers,decomposition,wave

action,burialbysandoramarkedcarcassestagmayhavebeen

unattachedbeforedetection.Researchersusingrecovery

experi-mentstoestimatethetotalmortalityofseabirdsandmarineotters

fromoil spillsarguedthat those factors influence tagrecovery

rates(BibbyandLloyd,1977;DeGangeetal.,1994;PiattandFord,

1996).Toimprove theaccuracyoffranciscanastranding

proba-bilityestimates,furthermark-recaptureexperiments,usingmore

than one tag, as wellas experiments to determine the

persis-tenceanddetectionprobabilityofbeachcastcarcassesshouldbe

conducted.

Thetwomethodsconsideredhere,ofestimatingbycatchfrom

logbookdataorviamark-recapturecorrectionofcountsof

beach-castcarcasses,each haveinherentlimitations. Whilewedo not

knowwhichestimateislessbiased,webelievethatthe

methodol-ogywehavedevelopedprovidesabetterestimateofbycatchwhen

datafromdirectmonitoringofthegillnetfishingfleetis

unavail-able. Based oncurrent abundanceestimates (Danilewicz et al.,

2010),thecorrectedmortalityestimatecanbeusedasaninput

parameter in logistic population models (Pella and Tomlinson,

1969)toback-calculatethepopulationinordertoestimatestock

sizepriortotheestablishmentofthegillnetfisheriesintheearly

1980s(Reisetal.,1994).Thisratiobetweenthecurrentandinitial

populationsizeisacrucialindicatorofpopulationstatus(e.g.Wade

etal.,2007).

5. Conclusions

Although data on stranding records are a useful source of

informationaboutanthropogenicimpactsonmarinemega-fauna

populations, careful interpretation of such data is needed. As

demonstratedinthisandotherstudies(e.g.Epperlyetal.,1996;

Perrinetal.,2010;Williamsetal.,2011),theproportionof

ani-malskilledoffshorethatendupbeachcastissmall.Otherimportant

aspectprovidedbyourresultsisthatthisproportioncanvaryalong

theyear.Despitethelackofprecisionintheestimateoffranciscana

strandingprobabilityforstripedweakfish,thenumberofanimals

markedduringthisfisherywasreasonable(n=54).Thefactthat

onlyonetaggedfranciscanawasrecoveredonthebeachisastrong

evidencethatanimalsincidentallycaughtduringthisfishingseason

rarelyendupashore.Thisisrelevantconsideringthatthenumberof

franciscanakilledinthestripedweakfishisrelativelyhigh(Secchi

etal.,2004).Thus,effortsshouldfocusonthestripedweakfish

fish-erybecauseoftheverylowstrandingprobability(about10%of

thewhitecroakerstrandingprobabilityaccordingtomediansof

posteriordistributions)and associatedstrongamplifyingimpact

onincidentalmortalityestimate.Itwouldalsobehelpfulif

sea-sonalvariabilityinprobabilityofstrandingcouldbequantitatively

addressedandincorporatedintorevisedbycatchestimates.

Ourfindingsthatafewthousandfranciscanamaybekilledin

nearshoregillnetfisherieseveryyearinsouthernBrazilisareason

forconcern.Ifoneconsiderstheupperconfidenceinterval(18,546)

ofthemostrecentabundanceestimateforthisarea(Danilewicz

etal.,2010)andtakesintoaccountthelowintrinsicpotentialfor

populationincreaseofabout2–3%ayear(Secchi,2006,2010),even

thelowestcurrentestimatesofbycatchareunsustainableandthe

(7)

Acknowledgements

WewouldliketoacknowledgetoallmembersofLaboratóriode

TartarugasMarinhaseMamíferosMarinhos/UniversidadeFederal

doRioGrande(LTMM/FURG)especiallytoLiliaFidelixdaSilveira

andEmanuelCarvalhoFerreirawhoinvolvedinthefieldworkand

CristianoDapperwhostartedthetaggingandrecoveryexperiment.

FishermenfromRioGrandeforhelpingtotaggedfranciscanaand

collectdataoffranciscanacapture.ThisstudywaspartofaMaster

ThesisofJ.H.F.P.,whichwassupportedbygrantsfromCAPES

(42004012001P-4). Thanks to the financial support from Yaqu

PachaandFundac¸ãoOBoticáriodeProtec¸ãoàNatureza.Wethank

WilliamPerrin,RandallReeves,StevenDawsonandAliceMacKay

forreviewingtheirhelpfulcommentsonthemanuscript.The

Con-selhoNacionalparaDesenvolvimentoCientíficoeTecnológicoof

theBrazilianGovernment(CNPq)grantedfellowshiptoE.R.S.(PQ

307843/2011-4).

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