4.6 Article

Incoherent dimensionality in fisheries management: consequences of misaligned stock assessment and population boundaries

Journal

ICES JOURNAL OF MARINE SCIENCE
Volume 78, Issue 1, Pages 155-171

Publisher

OXFORD UNIV PRESS
DOI: 10.1093/icesjms/fsaa203

Keywords

ecological boundary; non-stationary dynamics; risk spatial management; spatial population structure

Funding

  1. Office of Science and Technology, NOAA-National Marine Fisheries Service under the Stock Assessment Analytical Methods grant
  2. National Research Council Research Associate Program (NRC-RAP)

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Fisheries policy relies on explicit management boundaries, but connecting them to underlying population structures and processes is crucial to reduce bias and risk. Studying critical population segments, spatially explicit models, and dynamic management options can help align boundaries and improve management effectiveness.
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.

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