Management Strategy Evaluation for the Hilsa (Tenualosa ilisha) Fishery in the Bay of Bengal, Bangladesh
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Suman Barua [1] ; Qun Liu [2]
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[1] College of Fisheries, Ocean University of China, Qingdao, China; Department of Fisheries, Ministry of Fisheries and Livestock, Dhaka, Bangladesh
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[2] College of Fisheries, Ocean University of China, Qingdao, China
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- Localización: Thalassas: An international journal of marine sciences, ISSN 0212-5919, Vol. 41, Nº. 1, 2025
- Idioma: inglés
- Texto completo no disponible (Saber más ...)
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Resumen
The Hilsa shad, Tenualosa ilisha (Hamilton, 1822) is a national fsh of Bangladesh. Overexploitation and the presence of an immature size group have been documented in the catch composition. Some efectively practiced precautionary management measures such as lower catch limit, fshing ban during peak breeding season and juvenile stage have been initiated without considering associated uncertainties. This study attempts to evaluate the existing measures and quantify the management performance for better understanding and implementation of management strategies, with a holistic projection-based management approach like management strategy evaluation (MSE) using a newly developed data-limited management toolkit (DLMtool) for the hilsa fshery in Bangladesh. According to the fndings, eight management procedures (MPs) such as AVC_MLL, FMSyref, FMSYref75, FMSYref50, LBSPR, minlenLopt1, matlenlim, and CCI, assessed by DLMtool performed well. Consequently, TAC (Total Allowable Catch) of suggested two MPs indicates a fairly wide diference compared to the hilsa catch in 2022. The engaged fshing mortality in 2022 was almost double than referenced fshing mortality of 0.25, which recommended limiting the fshing efort at a considerable level. The spawning potential ratio (SPR) was calculated as 0.37 and the estimated minimum size of hilsa to capture should be >28.22 cm TL (Total Length). As a primary study on MSE for hilsa fshery, research in numerous areas, including improvement of overall data collection for populating OM (Operating Model), uncertainty quantifcation, and model improvement, is still necessary for sustainable management using this holistic approach.
