Combining Samples from Multiple Gears Helps to Avoid Fishy Growth Curves

Kyle L. Wilson, Bryan G. Matthias, Andrew B. Barbour, Robert N.M. Ahrens, Travis Tuten, Micheal S. Allen

Research output: Contribution to journalArticlepeer-review

21 Scopus citations

Abstract

Size-at-age information is critical in estimating growth parameters (e.g., the von Bertalanffy growth function [VBGF]) that are used to assess fish populations. Due to gear selectivity, single sampling methods rarely sample all ages or all sizes equally well. Most growth estimates rely on samples from a single gear or a haphazard combination of gears, potentially leading to biased and imprecise growth parameter estimates. We evaluated the efficacy of combining samples from two gears with different size selectivity to estimate VBGF parameters; we then applied that approach to a case study on the Lochloosa Lake (Florida) population of Black Crappies Pomoxis nigromaculatus. Simulated age- and size-structured populations were randomly sampled with two gears characterized by different size-selectivity curves (one gear was selective for smaller fish; the other was selective for larger fish). Maximum likelihood VBGF estimates obtained for each gear separately were compared with estimates from a combined VBGF fitted to data from both gears. In every simulated scenario, a combined-gear approach reduced bias and increased precision for estimating the VBGF, but the gear-specific proportions that improved VBGF estimates depended on size selectivity. The VBGF estimates for the Black Crappie population showed that the combined-gear method yielded intermediate parameter values relative to single-gear approaches based on (1) trawl sampling (fishery-independent survey) and (2) angler harvest (as determined from carcass collections; fishery-dependent data). Furthermore, the combined-gear approach had greater precision in individual parameter estimates and much less variance than single-gear approaches when estimating the VBGF. Combining data from two gears can increase sample representativeness, leading to improvements in VBGF estimation. Such approaches can reduce uncertainty in VBGF estimation and can provide insight into key demographic processes occurring in fish populations for which ontogeny and gear selectivity lead to imperfect sampling. Received January 22, 2015; accepted July 30, 2015

Original languageEnglish (US)
Pages (from-to)1121-1131
Number of pages11
JournalNorth American Journal of Fisheries Management
Volume35
Issue number6
DOIs
StatePublished - Nov 2 2015

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