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Simulation testing a new multi-stage process to measure the effect of increased sampling effort on effective sample size for age and length data
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2020
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Source: ICES Journal of Marine Science, 77(5), 1728-1737
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Journal Title:ICES Journal of Marine Science
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Description:Ocean management involves monitoring data that are used in biological models, where estimates inform policy choices. However, few science organizations publish results from a recurring, quantitative process to optimize effort spent measuring fish age. We propose that science organizations could predict the likely consequences of changing age-reading effort using four independent and species-specific analyses. Specifically we predict the impact of changing age collections on the variance of expanded age-composition data (“input sample size”, Analysis 1), likely changes in the variance of residuals relative to stock-assessment age-composition estimates (“effective sample size”, Analysis 2), subsequent changes in the variance of stock status estimates (Analysis 3), and likely impacts on management performance (Analysis 4). We propose a bootstrap estimator to conduct Analysis 1 and derive a novel analytic estimator for Analysis 2 when age-composition data are weighted using a Dirichlet-multinomial likelihood. We then provide two simulation studies to evaluate these proposed estimators and show that the bootstrap estimator for Analysis 1 underestimates the likely benefit of increased age reads while the analytic estimator for Analysis 2 is unbiased given a plausible mechanism for model misspecification. We conclude by proposing a formal process to evaluate changes in survey efforts for stock assessment.
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Source:ICES Journal of Marine Science, 77(5), 1728-1737
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Rights Information:Accepted Manuscript
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