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

Abstract

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 (Lmean/Lopt) and between the mean length at first capture and the mean length, which maximizes catch and biomass (Lc/Lc_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 L95th/Linf 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.

Stock Assessment of Six Sciaenidae Species in the Bay of Bengal, Bangladesh Water Using a Length-Based Bayesian Biomass (LBB) Method

“…The length-based Bayesian Biomass estimation approach (LBB) was developed to analyze the LF data from the commercial fisheries [5,23,25]. For species that grow throughout their lives, such as the most economically important fish and invertebrates, the LBB model is appropriate with only length-frequency data required [25].…”

“…Equation (3) assumes the selection curves for fishing gears, to avoid catching extremely young fish. Equations ( 1)-( 3) can be combined and rearranged to create Equations ( 4) and (5), which can determine L in f , L c , M K , F K , and at the same time α (alpha). Equation ( 6) was used to predict the L opt (size of fish at which cohort biomass reaches the greatest) using the provided L in f and M K [31].…”

“…Likewise, at least some large fish species are still present, as is indicated when the 95th percentile length and asymptotic length L 95th /L inf ratio are close to one (>0.9). Table 2 shows the stock status based on the estimated value of B/B MSY [3,5,24,25,33]. The estimated outputs of LBB can directly be used in the data-limited stocks management.…”

“…Effective fish stock assessments can provide the condition of fish stocks and the effect on these stocks of the actions being contemplated [1], which will facilitate the sustainable use of the fisheries resources [2,3]. However, for the data poor fisheries, fish stock assessment is a challenging task, and only about 12% of the world's fisheries are correctly managed as a consequence of stock assessments [3][4][5]. Due to a lack of data for estimating abundance and fishing mortality of the stocks, the majority of commercially harvested fish and shellfish stocks in the world do not have a proper stock assessment [6,7].…”

“…The surplus production model is one of them, where the maximum sustainable yield (MSY) was estimated using time series of catch and effort/abundance index data [12,21,22]. Length-based Bayesian Biomass (LBB) method is another one, where the stock status of single fisheries were estimated using only the length frequency (LF) data [3,5,[22][23][24][25].…”