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Please use this identifier to cite or link to this item: http://ntour.ntou.edu.tw:8080/ir/handle/987654321/39769

Title: Evaluation of virgin recruitment profiling as a diagnostic for selectivity curve structure in integrated stock assessment models
Authors: Sheng-Ping Wang;Mark N. Maunder;Kevin R. Piner;Alexandre Aires-da-Silva;Hui-Hua Lee
Contributors: 國立臺灣海洋大學:環境生物與漁業科學學系
Keywords: Virgin recruitment;Likelihood profile;Stock assessment;Selectivity;Diagnostic;Bigeye tuna
Date: 2014-10
Issue Date: 2016-12-30T06:11:12Z
Publisher: Fisheries Research
Abstract: Abstract:Virgin recruitment (R0), the equilibrium recruitment in the absence of fishing, is an often used parameter in fisheries stock assessment for scaling population size. We describe and evaluate the use of the R0 likelihood component profile to diagnose selectivity misspecification, using simulation analysis for bigeye tuna in the eastern Pacific Ocean. The profile is evaluated under two types of selectivity misspecification: (1) misspecified shape and (2) misspecified temporal variation. The results indicate that length-composition data can provide substantial information on R0 estimation when the model is correctly specified, but can substantially bias estimates of absolute abundance when selectivity is misspecified. Although contradictory profiles for length-composition and abundance index data result from selectivity misspecification, they may not be useful in determining which survey or fishery selectivity is misspecified. The R0 profile selectivity diagnostic is based on the influence of composition data on absolute abundance. However, perhaps a more problematic and difficult to detect issue is the impact of length-composition data on biomass trends. The age-structured production model diagnostic could be applied to identify bias in both absolute biomass and biomass trend caused by age- or length-composition data in the presence of model misspecification.
Relation: 158, pp.(158-164)
URI: http://ntour.ntou.edu.tw:8080/ir/handle/987654321/39769
Appears in Collections:[環境生物與漁業科學學系] 期刊論文

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