Time-varying natural mortality in fisheries stock assessment models: identifying a default approach

2015 
Center for the Advancement of Population Assessment Methodology, 8901 La Jolla ShoresDrive,La Jolla, CA 92037, USA*Corresponding author: tel: +1 206 543 4270; fax: +1 206 685 7471; e-mail: kfjohns@uw.eduJohnson,K.F.,Monnahan,C.C.,McGilliard,C.R.,Vert-pre,K.A.,Anderson,S.C.,Cunningham,C.J.,Hurtado-Ferro,F.,Licandeo,R.R.,Muradian,M.L.,Ono,K.,Szuwalski,C.S.,Valero,J.L.,Whitten,A.R.,andPunt,A.E.Time-varyingnaturalmortalityinfisheriesstockassessmentmodels:identifyingadefaultapproach. – ICESJournalofMarineScience,doi:10.1093/icesjms/fsu055.Received4 September 2013; revised 1 March 2014; accepted 3 March 2014.A typical assumption used in most fishery stock assessments is that natural mortality (M) is constant across time and age. However, M is rarelyconstant in reality as a result of the combined impacts of exploitation history, predation, environmental factors, and physiological trade-offs.Misspecification or poor estimation of M can lead to bias in quantities estimated using stock assessment methods, potentially resulting inbiasedestimatesoffisheryreferencepointsandcatchlimits,withthemagnitudeofbiasbeinginfluencedbylifehistoryandtrendsinfishingmor-tality. Monte Carlo simulations were used to evaluate the ability of statistical age-structured population models to estimate spawning-stockbiomass,fishingmortality,andtotalallowablecatchwhenthetrueMwasage-invariant,buttime-varying.Configurationsofthestockassessmentmethod,implementedinStockSynthesis,includedasingleage-andtime-invariantMparameter,specifiedatoneofthethreelevels(high,medium,andlow)oranestimatedM.Themin–max(i.e.mostrobust)approachtospecifyingMwhenitisthoughttovaryacrosstimewastoestimateM.The least robust approach for most scenarios examined was to fix M at a high value, suggesting that the consequences of misspecifying M areasymmetric.Keywords: model misspecification, natural mortality,population models, reference points, simulation, Stock Synthesis, time-varying.
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