Biomass limit reference points are sensitive to estimation method, time‐series length and stock development

Biomass limit reference points are widely used in fisheries management and defines the biomass threshold below which stock productivity (i.e. recruitment) is likely to be impaired. Scientifically sound and transparent methods for estimating biomass thresholds are therefore needed together with ways...

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Bibliographic Details
Published in:Fish and Fisheries
Main Authors: van Deurs, Mikael, Brooks, Mollie Elizabeth, Lindegren, Martin, Henriksen, Ole, Rindorf, Anna
Format: Article in Journal/Newspaper
Language:English
Published: 2021
Subjects:
Online Access:https://orbit.dtu.dk/en/publications/5f29d99b-0a9c-42f4-9d14-e0a9bac9743e
https://doi.org/10.1111/faf.12503
https://backend.orbit.dtu.dk/ws/files/222463481/van_Deurs_et_al._2020_FaF.pdf
Description
Summary:Biomass limit reference points are widely used in fisheries management and defines the biomass threshold below which stock productivity (i.e. recruitment) is likely to be impaired. Scientifically sound and transparent methods for estimating biomass thresholds are therefore needed together with ways of quantifying uncertainties. The main focus of the study was placed on two methods currently applied to several small-bodied pelagic species in the Northeast Atlantic. These methods have not formerly been described in the scientific literature and are in the present study being compared to some already described methods, of which, one is broadly applied outside the Northeast Atlantic. Using a combination of data simulations and data from 51 small-bodied pelagic fish stocks, we analyzed the sensitivity of estimated biomass thresholds to (i) the choice of method, (ii) time-series length, and (iii) stock development (e.g. rebuilding or declining). It was demonstrated that estimated biomass thresholds are associated with considerable uncertainty not previously quantified. Furthermore, the level of the estimated threshold and the amount of uncertainty depended on choice of method, time-series length, and stock development trends. Hence, this study contributes to improving the quality of future biomass limit reference points by providing guidance regarding choice of method and how to demonstrate stock-specific uncertainties.