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

Author:

Berger Aaron M1ORCID,Deroba Jonathan J2,Bosley Katelyn M1,Goethel Daniel R34ORCID,Langseth Brian J5,Schueller Amy M6,Hanselman Dana H4

Affiliation:

1. Fishery Resource Analysis and Monitoring Division, Northwest Fisheries Science Center, NMFS-NOAA, 2032 S.E. OSU Drive, Newport, OR 97365, USA

2. Population Dynamics Branch, Northeast Fisheries Science Center, NMFS-NOAA, 166 Water St, Woods Hole, MA 02543, USA

3. Sustainable Fisheries Division, Southeast Fisheries Science Center, NMFS-NOAA, 75 Virginia Beach Drive, Miami, FL 33133, USA

4. Auke Bay Laboratories, Alaska Fisheries Science Center, NMFS-NOAA, 17109 Point Lena Loop Road, Juneau, AK 99801, USA

5. Fisheries Research and Monitoring Division, Pacific Islands Fisheries Science Center, NMFS-NOAA, 1845 Wasp Blvd., Bldg. 176, Honolulu, HI 96818, USA

6. Beaufort Laboratory, Southeast Fisheries Science Center, NMFS-NOAA, 101 Pivers Island Road, Beaufort, NC 28516, USA

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.

Funder

NOAA

Office of Science and Technology

NOAA-National Marine Fisheries Service

Stock Assessment Analytical Methods

National Research Council Research Associate Program

Publisher

Oxford University Press (OUP)

Subject

Ecology,Aquatic Science,Ecology, Evolution, Behavior and Systematics,Oceanography

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