Evaluation of traditional and bootstrapped methods for assessing data-poor fisheries: a case study on tropical seabob shrimp ( Xiphopenaeus kroyeri ) with an improved length-based mortality estimation method

• Published in: PeerJ (San Francisco, CA) Vol. 12; p. e18397
• Main Authors: de Barros, Matheus, Oliveira-Filho, Ronaldo, Aschenbrenner, Alexandre, Hostim-Silva, Mauricio, Chiquieri, Julien, Schwamborn, Ralf
• Format: Journal Article
• Language: English
• Published: San Diego PeerJ. Ltd 14-11-2024; PeerJ, Inc; PeerJ Inc
• Subjects: Age; Algorithms; Analysis; Aquaculture, Fisheries and Fish Science; Case studies; Crustacean; Crustaceans; Developing countries; Ecology; ELEFAN; Estimates; Fish industry; Fisheries; Fishing; Health aspects; LDCs; Length-frequency analysis; Marine Biology; Methods; Mortality; Natural Resource Management; Optimization techniques; Parameter estimation; Pauly D; Penaeidae; Population Biology; Population studies; Powell-Wetheral; Stock assessment; Stock evaluation; Xiphopenaeus kroyeri; Brazil
• ISSN: 2167-8359; 2167-8359
• DOI: 10.7717/peerj.18397

Background Unrealistic model assumptions or improper quantitative methods reduce the reliability of data-limited fisheries assessments. Here, we evaluate how traditional length-based methods perform in estimating growth and mortality parameters in comparison with unconstrained bootstrapped methods, based on a virtual population and a case study of seabob shrimp (Xiphopenaeus kroyeri, Heller, 1862). Methods Size data were obtained for 5,725 seabob shrimp caught in four distinct fishing grounds in the Southwestern Atlantic. Also, a synthetic population with known parameter values was simulated. These datasets were analyzed using different length-based methods: the traditional Powell-Wetheral plot method and novel bootstrapped methods. Results Analysis with bootstrapped ELEFAN (fishboot package) resulted in considerably lower estimates for asymptotic size (L.sub.[infinity] ), instantaneous growth rate (K), total mortalities (Z) and Z/K values compared to traditional methods. These parameters were highly influenced by L.sub.[infinity] estimates, which exhibited median values far below maximum lengths for all samples. Contrastingly, traditional methods (PW method and L.sub.max approach) resulted in much larger L.sub.[infinity] estimates, with average bias >70%. This caused multiplicative errors when estimating both Z and Z/K, with an astonishing average bias of roughly 200%, with deleterious consequences for stock assessment and management. We also present an improved version of the length-converted catch-curve method (the iLCCC) that allows for populations with L.sub.[infinity] > L.sub.max and propagates the uncertainty in growth parameters into mortality estimates. Our results highlight the importance of unbiased growth estimates to robustly evaluate mortality rates, with significant implications for length-based assessments of data-poor stocks. Thus, we underscore the call for standardized, unconstrained use of fishboot routines.