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
caProgramadePós-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
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
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
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
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
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
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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