Abstract

This work demonstrates the correction of gear-selectivity and retention effects in estimation of growth in fish populations. The selectivity bias can be removed from length-at-age and length increment data. To correct for bias, a maximum-likelihood estimator that incorporates gear selectivity, a size-dependent retention function and several stochastic growth models are provided. The estimator allows the use of joint samples collected by fishing gears with different selectivity, which increases sample size and data representativeness, and thus improves accuracy of population parameter estimates. Data collected from retained tiger flathead caught by Danish seine gear were used for numerical analysis of the selectivity bias. Stock assessment implications of bias in growth estimation are discussed.

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