4.7 Article

Stock assessment using length-based Bayesian evaluation method for Trichiurus lepturus in the East China Sea

Journal

FRONTIERS IN MARINE SCIENCE
Volume 9, Issue -, Pages -

Publisher

FRONTIERS MEDIA SA
DOI: 10.3389/fmars.2022.1065954

Keywords

Trichiurus lepturus; LBB model; data-limited method; stock assessment; East China Sea

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Fishery resources assessment is crucial for scientific management and sustainable development of fisheries. This study used length frequency data from 2016 to 2020 to estimate various indicators of the Trichiurus lepturus stock in the East China Sea. The analysis revealed overfishing and heavy fishing pressure on the stock, highlighting the need for conservation measures.
Fishery resources assessment is the basis of scientific management and sustainable development of fisheries. Trichiurus lepturus, one of the major commercial fishes in the East China Sea, is of great significance to study its stocks status. Based on length frequency data of T. lepturus collected in the East China Sea from 2016 to 2020, we estimated asymptotic length, optimal length at first capture, relative mortality, and relative biomass of the stock using length-based Bayesian biomass estimation (LBB). The analysis shows a high exploitation rate and low biomass suggesting that the stock of T. lepturus has been overfished and is currently under heavy fishing pressure. Although the number of fishing vessels decreased by 29% from 2016 to 2020, the fishing horsepower decreased by only 9%, indicating that the fishing pressure on fishery resources is still high. To recover the stock, we consider the reduction of fishing intensity and enforcing of size-at-first-capture regulations to be imperative. In addition to reducing fishing boats and horsepower, it is essential to increase the escape proportion of juvenile fish by increasing the mesh size, and reduce the proportion of juvenile fish in the catch. The result in this study can provide informative reference for fishery stock assessment T. lepturus in the East China Sea under the data-limited conditions.

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