Repetitive capture of marine fishes: implications for estimating number and mortality of releases. (12th November 2020)

• Record Type: Journal Article
• Authors: Runde, Brendan J; Buckel, Jeffrey A; Shertzer, Kyle W; Bacheler, Nathan M; Rudershausen, Paul J; Sauls, Beverly
• Editors: Poos, Jan Jaap
• Is Part Of: ICES journal of marine science. Volume 77:Number 7/8(2020)
• Page Start: 2905
• Page End: 2917
• Publication Date: 2020-11-12
• Subjects: discards -- stock assessment -- survival -- tagging; Ocean -- Periodicals; Fisheries -- Periodicals; Fishes -- Periodicals; Marine biology -- Bibliography -- Periodicals; 551.4605
• DOI: 10.1093/icesjms/fsaa166
• Languages: English
• ISSNs: 1054-3139

Abstract

Abstract: In some fisheries, releases are a high percentage of total catch. Recent tagging data of marine fishes have revealed that recapture of the same individual multiple times occurs frequently. We investigated the magnitude of this phenomenon and its effect on survival using previously collected mark-recapture data of four reef-associated species. We used Cox proportional hazard regression models to examine whether survival varied with release number. For three of four species, survival was significantly higher after the second, third, and/or fourth release as compared to the first release, perhaps resulting from selection for robust individuals. Repetitive recapture implies that the estimated number of unique released fish is biased. Increased survival following later releases as compared to the initial release suggests that the number of dead discards may be similarly overestimated. We analysed the sensitivity of stock assessment results to reduced estimates of dead discards using two of our species that had recently been assessed. We found that reduced estimates of dead discards had a modest effect on assessment results but could nonetheless affect the perception of fishery status. Our findings highlight the need to revise current practices for estimating live and dead discards, either internal or external to stock assessment models.