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.

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

“…The fishers and management administrators need to set management actions based on stock assessment information [1][2][3]. However, most of the world's fish stocks are still unassessed because of data limitations, and a shortage of expertise is a significant constraint in fishery management [3,4]. In affluent nations, the evaluated fish stock's percentage varies between 10% and 50%, whereas in developing countries, the proportion is often 5% to 20% [1,5].…”

“…To address this problem, the length-based Bayesian biomass (LBB) approach was developed [8]. LBB requires simple length frequency (LF) data, and is often the most suitable method for data deficient fish stock [4,[8][9][10][11]. LBB can evaluate growth, mortality, and stock information, and the fishery administrator may utilize this information to manage the fishery resource when LF data is suggestive of an exploited stock [4,8,10,11].…”

“…LBB requires simple length frequency (LF) data, and is often the most suitable method for data deficient fish stock [4,[8][9][10][11]. LBB can evaluate growth, mortality, and stock information, and the fishery administrator may utilize this information to manage the fishery resource when LF data is suggestive of an exploited stock [4,8,10,11]. Additionally, LBB findings may be utilized as inputs for stock assessment techniques that need an independent estimation of biomass as input in comparison to unfished biomass [8,10,11].…”

“…In the Bay of Bengal (BoB) water, several surveys were conducted after 1970 to explore the marine fishery resources, but were paused in 1999 [4]. The BoB is part of the Indian Ocean and is considered one of the most productive ecosystems endowed with a tropical climate and abundant rainfall [12].…”

“…Meen Sandhani started survey research and recorded 344 species of fish, 45 species of shellfish, and 14 species of cephalopods within the shelf sea area of Bangladesh [4,13]. Furthermore, some previous studies reported that around 511 marine fishes, including shrimps, exist within the BoB, Bangladesh [4,14,15]. The marine fisheries' resources are harvested from three different depth zones in the BoB, Bangladesh.…”