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All is fish that comes to the net : metabarcoding for rapid fisheries catch assessment
Monitoring marine resource exploitation is a key activity in fisheries science and biodiversity conservation. Since research surveys are time consuming and costly, fishery-dependent data (i.e., derived directly from fishing vessels) are increasingly credited with a key role in expanding the reach of ocean monitoring. Fishing vessels may be seen as widely ranging data-collecting platforms, which could act as a fleet of sentinels for monitoring marine life, in particular exploited stocks. Here, we investigate the possibility of assessing catch composition of single hauls carried out by trawlers by applying DNA metabarcoding to the dense water draining from fishing nets just after the end of hauling operations (hereafter “slush”). We assess the performance of this approach in portraying β-diversity and examining the quantitative relationship between species abundances in the catch and DNA amount in the slush (read counts generated by amplicon sequencing). We demonstrate that the assemblages identified using DNA in the slush satisfactorily mirror those returned by visual inspection of net content (about 71% of species and 86% of families of fish) and detect a strong relationship between read counts and species abundances in the catch. We therefore argue that this approach could be upscaled to serve as a powerful source of information on the structure of demersal assemblages and the impact of fisheries.
Catch composition, catch per unit effort (CPUE) and species selectivity of fishing gears on multi-species Kaptai Lake in Bangladesh
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 upazilas 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.