Work

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

Year: 2021

Type: article

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.

Source: Journal of Marine Science and Engineering

DOI: 10.3390/jmse9101137

Authors: Partho Protim Barman, Qun Liu, Md. Abdullah Al-Mamun, Petra Schneider, Mohammad Mojibul Hoque Mozumder

Institutions: Sylhet Agricultural University, Ocean University of China, Department of Fisheries of the Government of the People's Republic of Bangladesh, Hochschule Magdeburg-Stendal, University of Helsinki

Language: English

Topic: Marine and fisheries research

Subfield: Aquatic Science

Field: Agricultural and Biological Sciences

Domain: Life Sciences

SDG: Life below water

Open Access status: gold

Estimated APC paid: $1,944