An assessment of sampling approaches for estimating growth from fishery-dependent biological samples. (6th May 2022)

• Record Type: Journal Article
• Authors: Schemmel, Eva; Bohaboy, Erin C; Kinney, Michael J; O'Malley, Joseph M
• Editors: Poos, Jan Jaap
• Is Part Of: ICES journal of marine science. Volume 79:Number 5(2022)
• Page Start: 1497
• Page End: 1514
• Publication Date: 2022-05-06
• Subjects: age and growth -- fisheries -- fixed otolith sampling -- independent-based model -- population simulations -- proportional otolith sampling -- sampling bias; Ocean -- Periodicals; Fisheries -- Periodicals; Fishes -- Periodicals; Marine biology -- Bibliography -- Periodicals; 551.4605
• DOI: 10.1093/icesjms/fsac075
• Languages: English
• ISSNs: 1054-3139

Abstract

Abstract: Accuracy of fish growth estimates depends greatly on how samples are collected. A total of three common sampling strategies are random, fixed otolith sampling (FOS), and proportional otolith sampling (POS). Random sampling is inefficient and rarely random. While POS has been shown to produce more accurate estimates of growth compared to FOS under ideal conditions, it is unclear how variables such as sample size, fishery selectivity, and fishing mortality influence sampling bias. Simulated age-at-length observations from two tropical deepwater species were used to evaluate the accuracy of von Bertalanffy growth parameter estimates comparing FOS and POS for a fast-growing, short-lived fish ( Prisitipomoides auricilla ) and a slow-growing, long-lived fish ( Etelis coruscans ). A total of 24 scenarios were tested to examine the influence of sample size, minimum size selected in the fishery, fishery exploitation rates, and supplemental sampling on growth parameter estimates. Furthermore, tests were applied to real fishery age–length observations for P. auricilla . POS consistently performed better than FOS, especially when the catch was representative of the population. However, FOS performed better when catch was not representative. This research demonstrates the importance of considering effects of fishery selectivity, fishing mortality, and sample size on sampling strategy and provides a tool to select an appropriate approach.