Abstract
Marine crustacean capture fisheries have been contributing increasingly more to global aquatic food production in recent decades, helping secure socioeconomic benefits. In the past decade the landings of marine crustaceans rose by more than 67% while expanding spatially and taxonomically, doubling their contribution to global fisheries landings. Although efforts to improve the data collection that informs stock assessments and management decisions have risen to promote sustainability of these fisheries, many stocks remain data-limited and unassessed. For many assessed stocks fishing pressures have declined, but some continue experiencing excessive fishing pressures and remain depleted. Here we review recent progress made to stock assessment methods and management measures applied to both data-limited and -rich crustacean stocks across the globe with particular emphasis on addressing sources of uncertainty. Although an increasing number of assessment methods have been developed to account for various types of uncertainty, evaluation of these methods applied to crustaceans is still limited. Less than one-fifth of the recent assessments accounted for multiple types of uncertainty using flexible methods like integrated population models. And uncertainties associated with crustaceans’ unique biology were not fully accounted for in estimating key demographic parameters in many assessments. Our review also identifies areas of research to address remaining knowledge gaps, including parameter estimation uncertainties associated with spatial stock structure, incorporating dynamic ecosystem effects, and management implications of accounting for uncertainties. These issues are anticipated to play a greater role in the performance of assessment methods adopted for and thus the management of crustacean fisheries under ongoing environmental change.
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Marine crustacean capture fisheries have been contributing increasingly more to global aquatic food production in recent decades, helping secure socioeconomic benefits. In the past decade the landings of marine crustaceans rose by more than 67% while expanding spatially and taxonomically, doubling their contribution to global fisheries landings. Although efforts to improve the data collection that informs stock assessments and management decisions have risen to promote sustainability of these fisheries, many stocks remain data-limited and unassessed. For many assessed stocks fishing pressures have declined, but some continue experiencing excessive fishing pressures and remain depleted. Here we review recent progress made to stock assessment methods and management measures applied to both data-limited and -rich crustacean stocks across the globe with particular emphasis on addressing sources of uncertainty. Although an increasing number of assessment methods have been developed to account for various types of uncertainty, evaluation of these methods applied to crustaceans is still limited. Less than one-fifth of the recent assessments accounted for multiple types of uncertainty using flexible methods like integrated population models. And uncertainties associated with crustaceans’ unique biology were not fully accounted for in estimating key demographic parameters in many assessments. Our review also identifies areas of research to address remaining knowledge gaps, including parameter estimation uncertainties associated with spatial stock structure, incorporating dynamic ecosystem effects, and management implications of accounting for uncertainties. These issues are anticipated to play a greater role in the performance of assessment methods adopted for and thus the management of crustacean fisheries under ongoing environmental change.
https://doi.org/10.32942/X2BD2M
Biodiversity, Ecology and Evolutionary Biology, Environmental Sciences, Marine Biology, Natural Resources and Conservation, Natural Resources Management and Policy, Population Biology
stock assessment, integrated model, size-based method, data-limited stock, management strategy evaluation, Ecosystem-based management
Published: 2025-08-11 05:58
Last Updated: 2025-08-11 05:58
CC BY Attribution 4.0 International
Data and Code Availability Statement:
All data used in this manuscript is publicly available from the databases of FAO FishStat (fao.org/fishery/en/fishstat) and RAM Legacy Stock Assessment (ramlegacy.org).
Language:
English
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