Abstract

China contributes the largest catches to global marine wild-capture fisheries. The majority of them are harvested from China Seas which are highly productive, but are facing heavy fisheries exploitation. The status of exploited fisheries stocks in China Seas have remained largely unknown due to severe data-limited conditions, which hindered their sustainable use and effective management. Although the off-the-shelf use of catch-only methods (COMs) has been cautioned because of their poor estimation performance, such methods have been increasingly applied to infer the status of exploited stocks in China Seas without performance evaluation. In this study, we established an empirical approach to evaluate the performance of a suite of COMs in predicting stock biomass status for the data-limited fisheries in the East China Sea (ECS) from data-rich stocks with similar characteristics in the RAM Legacy Stock Assessment Database (RLSADB). The results confirmed that ensemble approaches performed better than the individual COMs in estimating the mean of stock biomass status for data-rich stocks selected from RLSADB. By contrast, mechanistic COMs demonstrated more accurate estimates when predicting the trend of stock biomass status. The stock status of commercial fisheries in ECS estimated by three mechanistic COMs (Catch-MSY, CMSY, and OCOM) was likely too optimistic for most species. We suggest that China establish its national database and develop and implement regular monitoring programs to satisfy formal statistical stock assessment for its coastal fisheries.

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