Stock Assessment for Seven Fish Species Using the LBB Method from the Northeastern Tip of the Bay of Bengal, Bangladesh

Abstract

Assessment of fish stock status is generally required for fisheries management, which is difficult when the data are limited. The length-based Bayesian Biomass (LBB) approach is a powerful and new method, where only the length-frequency data are used for estimating the status of fisheries resources. Here, we applied the LBB method to assess the status of seven commercially valuable marine fishes from the northern tip of the Bay of Bengal (BoB), Bangladesh. These species were Lepturacanthus savala, Pampus argenteus, Nemipterus japonicas, Nemipterus randalli, Ilisha filigera, Saurida tumbil, and Upeneus sulphurous. The current relative biomass (B/B0) ratios were smaller than the BMSY/B0 in five stocks, except for N. japonicas and N. randalli, and this indicates that, of the seven populations assessed, two are grossly overfished, three are overfished, and two are healthy stocks. Moreover, the length at first capture (Lc) was lower than the optimal length at first capture (Lc_opt) in all seven populations, which indicates growth overfishing, suggesting that increasing the mesh sizes would be beneficial. The present findings confirm that Bangladesh’s coastal water fishery resources are declining. More specific targeted management measures should be taken to recover the country’s marine fishery resources.