4.6 Article

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

Journal

FISH AND FISHERIES
Volume 22, Issue 1, Pages 18-30

Publisher

WILEY
DOI: 10.1111/faf.12503

Keywords

fisheries management; RAM Legacy; small pelagics; statistical uncertainty; stock-recruitment; sustainable exploitation

Categories

Funding

  1. European Maritime and Fisheries Foundation
  2. Ministry of Environment and Food of Denmark [33113-B-19-150]

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This study focuses on two methods for estimating biomass limit reference points for small-bodied pelagic species in the Northeast Atlantic. It demonstrates that estimated BTs are associated with considerable uncertainty, which depends on choice of method, time-series length, and stock development trends. The study contributes to improving the quality of future biomass limit reference points by providing guidance on method selection and demonstrating stock-specific uncertainties.
Biomass limit reference points are widely used in fisheries management and define the biomass threshold (BT) below which stock productivity (i.e. recruitment) is likely to be impaired. Scientifically sound and transparent methods for estimating BTs 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 with 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 analysed the sensitivity of estimated BTs to (a) the choice of method, (b) time-series length and (c) stock development (e.g. rebuilding or declining). It was demonstrated that estimated BTs 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.

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