Stock Assessment of Exploited Sardine Populations from Northeastern Bay of Bengal Water, Bangladesh Using the Length-Based Bayesian Biomass (LBB) Method

Abstract

Stock assessment is necessary to understand the status of fishery stocks. However, for the data-poor fishery, it is very challenging to assess the stock status. The length-based Bayesian biomass (LBB) technique is one of the most powerful methods to assess the data-poor fisheries resources that need simple length frequency (LF) data. Addressing the present gap, this study aimed to assess the stock status of three sardines (Sardinella fimbriata, Dussumieria acuta, and D. elopsoides) in the Bay of Bengal (BoB), Bangladesh using the LBB method. The estimated relative biomass for S. fimbriata was B/B0 < BMSY/B0, indicating the overfished biomass, while the assessed B/B0 > BMSY/B0 for D. acuta and D. elopsoides indicates healthy biomass. Additionally, for S. fimbriata, the length at first landing was smaller than the optimum length at first landing (Lc < Lc_opt), indicating an overfishing status, but a safe fishing status was assessed for D. acuta and D. elopsoides (Lc > Lc_opt). Therefore, increasing the mesh size of fishing gears may help to ensure the long-term viability of sardine populations in the BoB, Bangladesh.