Stock Assessment of 19 Perciformes in the Beibu Gulf, China, Using a Length-Based Bayesian Biomass Method

The Beibu Gulf in China is rich in fish resources. However, only a small number of commercially developed fish stocks have been specifically assessed owing to limited data and expertise. In this study, 19 perciform fish populations in the Beibu Gulf were assessed using a length-based Bayesian biomass (LBB) estimator method, which is a new approach to evaluate a fishery's status using length frequency (LF) data. The results showed that only 21% of the evaluated stocks were healthy and 79% were overfished. In particular, 26 and 21% of the assessed species had collapsed and were grossly overfished, respectively. Only 11 and 21% of the assessed species were slightly overfished and overfished, respectively. The ratios between the mean and optimum length (L-mean/L-opt) and between the mean length at first capture and the mean length, which maximizes catch and biomass (L-c/L-c_opt), were below one in 14 out of the 19 stocks, suggesting a truncated length structure and fishing of undersized individuals. The ratio of the 95th percentile length to asymptotic length L-95th/L-inf was close to one (>0.9) in 10 of 19 stocks, suggesting that at least some large fish were still present. Our research confirmed that the fishery resources in the Beibu Gulf were seriously overfished and provided evidence that LBB was an efficient method to evaluate the fishery resources. Fishery managers need to take specific measures to restore fishery resources.

Automated summary

The study reveals that there is a serious issue of overfishing in the Beibu Gulf, with 79% of assessed fish stocks being overfished. A high proportion of species were found to have collapsed or were severely overfished in the assessment. The length-based Bayesian biomass (LBB) estimator method was shown to be an efficient tool for evaluating fishery resources in the region.