Document Type

Article

Department/Program

Virginia Institute of Marine Science

Publication Date

2022

Journal

Fish and Fisheries

First Page

1

Last Page

16

Abstract

Fishery management frequently involves precautionary buffering for scientific uncertainty. For example, a precautionary buffer that scales with scientific uncertainty is used to calculate the acceptable biological catch downward from the overfishing limit in the US federal fishery management system. However, there is little empirical guidance to suggest how large buffers for scientific uncertainty should be. One important component of uncertainty is variation among different assessments of the same stock in estimates of management-relevant quantities. We analysed commercially exploited marine fish and invertebrate stocks around the world and developed Bayesian hierarchical models to quantify inter-assessment variation in terminal year biomass and fishing mortality estimates, reference points, relative biomass and fishing mortality estimates, and overfishing limits. There was little evidence of inter-assessment bias; stock assessment estimates in the terminal year of the assessment were not consistently higher or lower than estimates of the same quantities in future years. However, there was a tendency for extreme values from the terminal year to be pulled closer to the mean in future years. Inter-assessment variation in all estimates differed across regions, and a longer inter-assessment interval generally resulted in greater variation. Inter-assessment uncertainty was greatest for estimates of the overfishing limit, with coefficients of variation ranging from 17% in Europe (non-EU) to 107% for Pacific Ocean pelagic stocks. Because inter-assessment variation is only one component of scientific uncertainty, we suggest that these uncertainty estimates may provide a basis for determining the minimum size of precautionary buffers.

DOI

DOI: 10.1111/faf.12714

Creative Commons License

Creative Commons Attribution 4.0 International License
This work is licensed under a Creative Commons Attribution 4.0 International License.

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