Resumen
As one of the largest and most commercially valuable finfish species, Leptomelanosoma indicum (Indian salmon) significantly contributes to Bangladesh?s marine catches. The length-based Bayesian biomass (LBB) method and catch-based Monte Carlo method (CMSY) are among the most recent and powerful methods for predicting the state of fisheries resources from data-limited fisheries. CMSY requires catch and resilience data, as well as quantitative stock status information. For LBB, only length?frequency (LF) data are required. The stock status of L. indicum was estimated using these two independent methods, utilizing twenty-one years of catch?effort and length?frequency data (978 individuals) from commercial fisheries on the Bangladesh coast. Here, a BSM (Bayesian state-space implementation of the Schaefer surplus production model) was also employed. The current study?s findings showed that the B/B0 ratio of currently exploited biomass to unexploited biomass (0.1) was smaller than BMSY/B0 (0.36) and B/BMSY = 0.28 was smaller than the reference value of 1.0, indicating the grossly overfished and depleted condition of the stock. Similar trends in the results were found for B/BMSY = 0.11 (<1.0) from CMSY. In addition, the exploitation rate (F/FMSY = 5.66), biomass (B < BMSY), and fishing status (F > FMSY) further justify the severely overfished conditions of L. indicum stock in the study area. Furthermore, the Lc_opt (optimal length at first capture) was higher than the Lc (length at first capture), indicating that this species is being overfished, and that mesh sizes should be increased for better management. This study provides information on biological reference points (BRPs), and confirms the severely overfished status of L. indicum in the coastal waters of Bangladesh. More specific and prompt management measures are required to recover and sustainably manage this valuable species, and protect the fish stock from commercial extinction.