Length‐Based Stock Assessment of Glossogobius giuris (Tank Goby) in Kaptai Lake, Bangladesh: Implications for Sustainable Fisheries

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Authors: Mohammed Shahidul Alam, Ataher Ali, Anisul Mustafa
Cited by: 0
References: 53

Abstract

ABSTRACT The tank goby ( Glossogobius giuris [ G. giuris ]), a vital indigenous freshwater species in Kaptai Lake, Bangladesh, supports local livelihoods and nutrition but faces escalating fishing pressure due to rising market demand. This study presents the first comprehensive length‐based stock assessment of the species by applying a multimodel approach using TropFishR, Length‐based Bayesian Biomass (LBB), and Length‐Based Spawning Potential Ratio (LB‐SPR) on an 8‐month length‐frequency data set. The LBB analysis estimated an asymptotic length ( L ∞ ) of 17.5 cm, with a length at first capture ( L c50 ) of 6.45 cm, significantly below the optimal capture length ( L c_opt = 9.7 cm) and length at maximum biological yield ( L opt = 12.0 cm), confirming high exploitation of juveniles and recruitment overfishing. Biomass indicators revealed a current‐to‐virgin biomass ratio ( B/B 0 ) of 0.27 and a current‐to‐maximum sustainable yield biomass ratio ( B/B MSY ) of 0.75, classifying the stock as grossly overfished ( B/B 0 < 0.5). The fishing‐to‐natural mortality ratio ( F / M = 1.07) exceeded unity, confirming intense fishing pressure. LB‐SPR complemented these findings, estimating an L c50 of 6.12 cm, well below the length at 50% maturity ( L 50 = 11.85 cm), and a spawning potential ratio (SPR) of 8% (6%–10%), far below the target (40%) and limit (20%) reference points, signaling severe recruitment overfishing. Sensitivity analyses across ±5% parameter variations demonstrated the robustness of both models. These results underscore the urgent need for management actions, including enhanced gear selectivity (e.g., larger mesh sizes) and minimum size limits (9–10 cm), to protect immature fish and restore G. giuris stock sustainability in Kaptai Lake.

Fields of Study & Subjects

Fish Biology and Ecology Studies Marine and fisheries research Fish Ecology and Management Studies

Publication details

Journal / source
Natural Resource Modeling
Volume
39
Issue
1
Publication date
2 January 2026
Language
EN