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

Abstract

Six most abundant and commercially valuable croakers (Sciaenidae) stocks in the coastal water of Bangladesh were evaluated using a length-based Bayesian Biomass (LBB) approach. The ratios B/B0 (current relative biomass) were smaller than the BMSY/B0 in five of the six stocks. For the six estimated populations, two (Otolithes ruber and Pterotolithus maculatus) are grossly overfished, one (Otolithoides pama) is overfished, two (Johnius belangerii and Panna heterolepis) are slightly overfished, and only donkey croaker (Pennahia anea) is in the healthy (B/B0 > BMSY/B0) status. Furthermore, the optimal length at first capture (Lc_opt) was higher than the length at first capture (Lc) in four populations, indicating growth overfishing, suggesting that increasing mesh size would benefit the catch and biomass. Findings from the present study confirm the declining trend of fisheries resources, particularly the croaker species in the BoB, Bangladesh coastal water. Management strategies (such as effort control, choosing the appropriate mesh size, total allowable catch limit, identify and enhance protection of the feeding, breeding, and nursery ground, etc.) should be taken for the sustainable management and recovery of the country’s marine fishing resources, particularly the valuable croaker species.

Evaluation of Yellow Sea anchovy (Engraulis japonicus) fishery for management strategies using a data-limited management toolkit

“…However, coastal provinces still need to clarify the areas under their jurisdiction, which will not only enhance the authenticity of fishery data collection, but also facilitate the practical implementation of fishery management measures with less uncertainties. In order to mitigate the effects of limited data, accumulations of more fishery data and improved data quality have great significance in fishery management of developing countries, for example similar proposals have been suggested in Bangladesh [ 43 ]. Further it is important for the collection of informative data for specific fishery, which will help meet management objectives using minimum data and suitable for data-limited fisheries [ 44 ].…”

Stock Assessment of Chub Mackerel (Scomber japonicus) in the Northwest Pacific Ocean Based on Catch and Resilience Data

“…As a method of identifying the chub mackerel stock state using the CMSY model, the state of the fishery resource was defined based on the stock biomass in the last year of the analysis period compared to the B MSY used in several recent studies [11,12,21,22]. Depending on the rate of stock biomass to B MSY , the resource state is defined: collapsed, grossly overfished, overfished, slightly overfished, or healthy (Table 2).…”

“…Depending on the rate of stock biomass to B MSY , the resource state is defined: collapsed, grossly overfished, overfished, slightly overfished, or healthy (Table 2). Source: [11,12,21,22].…”

Complete mitogenome and intra-family comparative mitogenomics showed distinct position of Pama Croaker Otolithoides pama

“…These fishes are highly sought-after in both domestic and international markets. Around 86% of the total harvested croakers are dried and exported to various Asian countries, including Singapore, Japan, China and South Korea 9 . Among the different croaker fishes, the pama croaker Otolothoides pama stands out as one of the commercially important species in Bangladesh meeting 33.33% of total marine fish demand of Dhaka city 10 .…”

“…This migratory fish species is commonly found in estuaries and the BoB, with a seasonal migration to inland rivers, especially the Meghna River, during the monsoon for breeding purposes 14 . Although the IUCN Red List of Bangladesh (2000) does not list O. pama as a threatened species, its population has experienced a decline in recent years in its natural habitat, the BoB, primarily due to overfishing 9 . Despite its significance, research on O. pama has been relatively limited to its proximity analysis, reproductive pattern, growth pattern, otolith shape analysis, food and feeding habits, stock analysis, and barcoding of the cox1 gene for species identification, especially in countries such as Bangladesh, India, and Myanmar 13 , 15 – 21 .…”