Catch-at-age assessment in the face of time-varying selectivity
Author(s) -
Brian C. Linton,
James R. Bence
Publication year - 2010
Publication title -
ices journal of marine science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.348
H-Index - 117
eISSN - 1095-9289
pISSN - 1054-3139
DOI - 10.1093/icesjms/fsq173
Subject(s) - selectivity , selection (genetic algorithm) , population , statistics , model selection , econometrics , computer science , mathematics , biology , demography , machine learning , sociology , catalysis , biochemistry
Linton, B. C., and Bence, J. R. 2011. Catch-at-age assessment in the face of time-varying selectivity. – ICES Journal of Marine Science, 68: . Age-based fishery selectivity represents the relative vulnerability of specific ages of fish to a fishery, whereby age classes that are highly selected tend to be overrepresented in the catch compared with their relative abundance in the population. Statistical catch-at-age analysis (SCAA) results can be sensitive to misspecification of selectivity, which can occur when changes in selectivity over time are not accounted for properly in the assessment model. Four approaches for modelling time-varying selectivity were evaluated within SCAA using Monte Carlo simulations: double-logistic functions with one, two, and all four of the function parameters varying over time, and age-specific selectivity parameters that all varied over time. None of these estimation approaches outperformed the others always. In addition, methods of model selection were compared to identify good estimation models, i.e. those accurately matching the true fish population. The degree of retrospectivity, the best selection method, was based on a retrospective analysis of errors in model estimates as the data time-series for estimation is sequentially shortened. This selection method performed about as well as knowing the correct selectivity model and led to substantial benefits over misspecifying the selectivity model.
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