Estimation of Stock Status Using the LBB and CMSY Methods for the Indian Salmon Leptomelanosoma indicum (Shaw, 1804) in the Bay of Bengal, Bangladesh

Author:

Al-Mamun Md. AbdullahORCID,Shamsuzzaman Md. MostafaORCID,Schneider PetraORCID,Mozumder Mohammad Mojibul HoqueORCID,Liu Qun

Abstract

As one of the largest and most commercially valuable finfish species, Leptomelanosomaindicum (Indian salmon) significantly contributes to Bangladesh’s marine catches. The length-based Bayesian biomass (LBB) method and catch-based Monte Carlo method (CMSY) are among the most recent and powerful methods for predicting the state of fisheries resources from data-limited fisheries. CMSY requires catch and resilience data, as well as quantitative stock status information. For LBB, only length–frequency (LF) data are required. The stock status of L. indicum was estimated using these two independent methods, utilizing twenty-one years of catch–effort and length–frequency data (978 individuals) from commercial fisheries on the Bangladesh coast. Here, a BSM (Bayesian state-space implementation of the Schaefer surplus production model) was also employed. The current study’s findings showed that the B/B0 ratio of currently exploited biomass to unexploited biomass (0.1) was smaller than BMSY/B0 (0.36) and B/BMSY = 0.28 was smaller than the reference value of 1.0, indicating the grossly overfished and depleted condition of the stock. Similar trends in the results were found for B/BMSY = 0.11 (<1.0) from CMSY. In addition, the exploitation rate (F/FMSY = 5.66), biomass (B < BMSY), and fishing status (F > FMSY) further justify the severely overfished conditions of L. indicum stock in the study area. Furthermore, the Lc_opt (optimal length at first capture) was higher than the Lc (length at first capture), indicating that this species is being overfished, and that mesh sizes should be increased for better management. This study provides information on biological reference points (BRPs), and confirms the severely overfished status of L. indicum in the coastal waters of Bangladesh. More specific and prompt management measures are required to recover and sustainably manage this valuable species, and protect the fish stock from commercial extinction.

Publisher

MDPI AG

Subject

Ocean Engineering,Water Science and Technology,Civil and Structural Engineering

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3