Management strategy evaluation of fishery stocks in Haizhou Bay based on Data-Limited Methods

Data-limited stock assessment with Data-Limited Methods (DLMs) is capable of evaluating and managing data-limited fisheries and widely used in the world. Fisheries in China are at high risk of overfishing but meanwhile subject to limited data, which makes DLMs the optimal scientific advisory tools to support management. However, DLMs are rarely studied and implemented in China. In order to examine the effectiveness of DLMs in China, the present study conducts management strategy evaluation (MSE) with four data-limited management procedures (MPs) on silvery pomfret (Pampus argenteus), small yellow croaker (Larimichthys polyactis), greenling (Hexagrammos otakii), and lizardfish (Saurida elongate) from Haizhou Bay. According to the results, MPs based on DLMs are proved to be sustainable fisheries management methods by effectively enhancing the spawning stock biomass of overfished stocks while maintaining a considerable level of yield. The length-based MPs (matlenlim and minlenLopt) outperformed the effort-based MPs (CurE and CurE75) with better trade-offs between yields and overfishing. The results also suggest that, with the implementation of DLMs, the overfished status of silvery pomfret and greenling can be improved, and the lizardfish stock can be better exploited. DLMs with the small yellow croaker stock are subject to fluctuation and uncertainty. In general, DLMs have broad application prospect in China.