Inference of Age Compositions in a Sample of Fish from Fish Length Data

Fish ages are critical information in fish stock assessments because they are required for age-structure models such as virtual population analysis and stochastic catch-at-age models, whose outputs include recruitment strengths, a spawning stock size (abundance or biomass), and the projection of a fish population size in future. However, most countries other than the developed countries have not identified ages of fish caught by fisheries or surveys in a consistent manner for a long time (e.g.,>20 years). Instead, data about fish body sizes (e.g., lengths) have been well available because of ease of measurement. To infer age compositions of fish in a target group using fish length data, we intended to improve the length frequency analysis (LFA), which Schnute and Fournier had introduced in 1980. Our study was different in two ways from the Schnute and Fournier's method. First we calculated not only point estimates of age compositions but also the uncertainty in those estimates. Second, we modified LFA based on the von Bertalanffy growth model (vB-based model) to allow both individual-to-individual and cohort-to-cohort variability in estimates of parameters in the vB-based model. For illustration, we used data about lengths of Korean mackerel Scomber japonicas caught by purse-seine fisheries from 2000-2016.

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