Rahman B M Shahinur, Rahman Md Khaled, Ali Azhar, Lima Rabina Akther, Mia Md Lipon, Mahmud Yahia
Bangladesh Fisheries Research Institute, Riverine Sub-station, Rangamati, 4500, Bangladesh.
Bangladesh Fisheries Research Institute, Freshwater Sub-station, Saidpur, 5310, Bangladesh.
Heliyon. 2024 May 13;10(10):e31173. doi: 10.1016/j.heliyon.2024.e31173. eCollection 2024 May 30.
Kaptai Lake, the largest artificial reservoir in Southeast Asia, is home to a diverse fish fauna that supports thousands of livelihoods and is distinguished by multi-species and multi-gear fisheries. In Kaptai Lake, the gear-based catch composition, catch rate and distribution pattern are little known. From August 2020 to April 2021, a nine-month study was conducted in five using direct catch assessment surveys and fishing effort surveys from four fishing gears, namely seine nets, gill nets, lift nets, and push nets. A total of 49 morpho-species from 22 families were found, with three species from the Clupeidae accounting for 93.63 % of the catch in all gear combined. The total catch composition and CPUE were higher in seine nets (75.07 %, 13.86 ± 1.8 kg/gear/trip respectively) and lower in lift nets (4.97 %, 1.01 ± 0.21 kg/gear/trip) and showed significant differences among gears, except sampling sites whereas CPUE was higher in Naniarchar for seine nets (17.29 ± 8.89 kg/gear/trip) and lower in Langadu for lift nets (0.62 ± 0.25 kg/gear/trip). Seine nets captured more species, and the number of species increased significantly as CPUE increased. Our study assessed four gears that targeted different fish species with little overlap in leading species; seine nets and gill nets primarily targeted Clupeidae (96.53 % and 41.69 %, respectively), whereas lift nets and push nets primarily targeted Cyprinidae and Palaemonidae (38.93 % and 99.37 % respectively). The observed abundance and variety of fish species captured in gill nets suggest a significant overlap in the selectivity of this fishing method with that of lift nets. Due to the varying contributions of sites and gears, the nMDS ordination pattern reveals a weak spatial variation in catch composition. According to the SIMPER results, Bagridae, Gobiidae, and Ambassidae were the most significant contributors to site grouping patterns across all gears. Furthermore, the findings indicate that the catch composition does not follow the typical pattern of spatial variation. By implementing measures to eliminate or decrease the usage of small mesh nets, there is expected to be a corresponding decrease in the capture of small fish. Additionally, this action will help mitigate the issue of overlapping selectivity among the current fishing gears. Our findings provide baseline data on the potential efficacy of gear limitation and suggest a gear-based management strategy.
卡普泰湖是东南亚最大的人工水库，拥有丰富多样的鱼类种群，支撑着数千人的生计，以多物种和多渔具渔业而闻名。在卡普泰湖，基于渔具的渔获物组成、渔获率和分布模式鲜为人知。2020年8月至2021年4月，进行了为期九个月的研究，在五个地点使用直接渔获评估调查和来自四种渔具（即围网、刺网、抬网和推网）的捕捞努力调查。共发现了来自22个科的49个形态物种，鲱科的三个物种占所有渔具合并渔获量的93.63%。围网的总渔获物组成和CPUE较高（分别为75.07%，13.86±1.8千克/渔具/航次），抬网较低（4.97%，1.01±0.21千克/渔具/航次），并且除采样地点外，各渔具之间存在显著差异，而围网在纳尼亚查尔的CPUE较高（17.29±8.89千克/渔具/航次），抬网在朗加杜较低（0.62±0.25千克/渔具/航次）。围网捕获的物种更多，物种数量随着CPUE的增加而显著增加。我们的研究评估了四种针对不同鱼类物种且主要物种重叠较少的渔具；围网和刺网主要针对鲱科（分别为96.53%和41.69%），而抬网和推网主要针对鲤科和对虾科（分别为38.93%和99.37%）。在刺网中观察到的鱼类物种丰富度和多样性表明，这种捕捞方法与抬网的选择性存在显著重叠。由于地点和渔具的贡献不同，nMDS排序模式显示渔获物组成的空间变化较弱。根据SIMPER结果，鲿科、虾虎科和双边鱼科是所有渔具中对地点分组模式贡献最大的科。此外，研究结果表明渔获物组成并不遵循典型的空间变化模式。通过采取措施消除或减少小网目的使用，预计小鱼的捕获量将相应减少。此外，这一行动将有助于缓解当前渔具之间选择性重叠的问题。我们的研究结果提供了关于渔具限制潜在效果的基线数据，并提出了基于渔具的管理策略。
