Incoherent dimensionality in fisheries management: consequences of misaligned stock assessment and population boundaries. (22nd December 2020)

• Record Type: Journal Article
• Authors: Berger, Aaron M; Deroba, Jonathan J; Bosley, Katelyn M; Goethel, Daniel R; Langseth, Brian J; Schueller, Amy M; Hanselman, Dana H
• Editors: Bartolino, Valerio
• Is Part Of: ICES journal of marine science. Volume 78:Number 1(2021)
• Page Start: 155
• Page End: 171
• Publication Date: 2020-12-22
• Subjects: ecological boundary -- non-stationary dynamics -- risk -- spatial management -- spatial population structure; Ocean -- Periodicals; Fisheries -- Periodicals; Fishes -- Periodicals; Marine biology -- Bibliography -- Periodicals; 551.4605
• DOI: 10.1093/icesjms/fsaa203
• Languages: English
• ISSNs: 1054-3139

Abstract

Abstract: Fisheries policy inherently relies on an explicit definition of management boundaries that delineate the spatial extent over which stocks are assessed and regulations are implemented. However, management boundaries tend to be static and determined by politically negotiated or historically identified population (or multi-species) units, which create a potential disconnect with underlying, dynamic population structure. The consequences of incoherent management and population or stock boundaries were explored through the application of a two-area spatial simulation–estimation framework. Results highlight the importance of aligning management assessment areas with underlying population structure and processes, especially when fishing mortality is disproportionate to vulnerable biomass among management areas, demographic parameters (growth and maturity) are not homogenous within management areas, and connectivity (via recruitment or movement) unknowingly exists among management areas. Bias and risk were greater for assessments that incorrectly span multiple population segments (PSs) compared to assessments that cover a subset of a PS, and these results were exacerbated when there was connectivity between PSs. Directed studies and due consideration of critical PSs, spatially explicit models, and dynamic management options that help align management and population boundaries would likely reduce estimation biases and management risk, as would closely coordinated management that functions across population boundaries.