An Evaluation of the Robustness of Length-Based Stock Assessment Approaches for Sustainable Fisheries Management in Data and Capacity Limited Situations

To ensure sustainability, the Ecosystem Approach to Fisheries (EAF) requires the evaluation of the impacts of fisheries beyond the main targeted species, to include those on bycaught, endangered, threatened and protected populations and keystone species. However, traditional stock assessments require extensive datasets that are often unavailable for data-limited fisheries, particularly in small-scale settings or in the Global South. This study evaluates the robustness of length-based approaches for fish stock assessment by comparing simple indicators and quantitative methods using an age-structured Operating Model. Simulations were conducted for a range of scenarios, for a range of life-history types and recruitment and natural mortality dynamics. Results reveal that while length-based approaches can effectively track trends in fishing mortality, performance varies significantly depending on species-specific life histories and assumptions about key parameters. Simple indicators often matched or outperformed complex methods, particularly when assumptions about equilibrium conditions or natural mortality were violated. The study highlights the limitations of length-based methods for classifying stock status relative to reference points, but demonstrates their utility when used with historical reference periods or as part of empirical harvest control rules. The findings provide practical guidance for applying length-based approaches in data-limited fisheries management, ensuring sustainability in data- and capacity-limited situations.

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Publication Details

Journal
Sustainability
Published
2025-05-23
DOI
https://doi.org/10.3390/su17114791
Citations
5
Primary Topic
Marine and fisheries research
Type
article
Field-Weighted Citation Impact
5.53
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article

An Evaluation of the Robustness of Length-Based Stock Assessment Approaches for Sustainable Fisheries Management in Data and Capacity Limited Situations

Laurence T. Kell, Rishi Sharma
5 citations
Sustainability
Marine and fisheries research
5.53
article

An Evaluation of the Robustness of Length-Based Stock Assessment Approaches for Sustainable Fisheries Management in Data and Capacity Limited Situations

Laurence T. Kell, Rishi Sharma
article en
5 citations

Abstract

To ensure sustainability, the Ecosystem Approach to Fisheries (EAF) requires the evaluation of the impacts of fisheries beyond the main targeted species, to include those on bycaught, endangered, threatened and protected populations and keystone species. However, traditional stock assessments require extensive datasets that are often unavailable for data-limited fisheries, particularly in small-scale settings or in the Global South. This study evaluates the robustness of length-based approaches for fish stock assessment by comparing simple indicators and quantitative methods using an age-structured Operating Model. Simulations were conducted for a range of scenarios, for a range of life-history types and recruitment and natural mortality dynamics. Results reveal that while length-based approaches can effectively track trends in fishing mortality, performance varies significantly depending on species-specific life histories and assumptions about key parameters. Simple indicators often matched or outperformed complex methods, particularly when assumptions about equilibrium conditions or natural mortality were violated. The study highlights the limitations of length-based methods for classifying stock status relative to reference points, but demonstrates their utility when used with historical reference periods or as part of empirical harvest control rules. The findings provide practical guidance for applying length-based approaches in data-limited fisheries management, ensuring sustainability in data- and capacity-limited situations.

SustainabilityVol. 17(11)
Food and Agriculture Organization of the United Nations (IT), Imperial College London (GB)
Openalex Percentile: Top 4%
Marine and fisheries research
5.53
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