Fishers' tales—Impact of artisanal fisheries on threatened sharks and rays in the Bay of Bengal, Bangladesh

Abstract

Funder: Bangladesh Fisheries Research Institute; Id: http://dx.doi.org/10.13039/501100008229Funder: Save Our Seas Foundation; Id: http://dx.doi.org/10.13039/501100007665Funder: National Geographic Photo Ark ZSL EDGEFunder: Natural Environment Research Council; Id: http://dx.doi.org/10.13039/501100000270Funder: Bangabandhu Overseas Scholarship 2019, University of Dhaka, BangladeshAbstract: Increasing fishing pressure has negatively impacted elasmobranch populations globally. Despite high levels of historical and current fishing pressure, the Bay of Bengal region remains data‐poor. Focusing on Bangladesh, we conducted a socio‐ecological study to characterize elasmobranch fisheries and evaluate their impact on threatened species. The results demonstrate that several globally threatened elasmobranch species are frequently captured, and some of them have experienced substantial population declines (e.g., wedgefishes, sawfishes, large carcharhinid sharks) over the past decade. A decrease in elasmobranch diversity, abundance, and size of caught specimens was also reported, which was attributed to increased fishing intensity, destructive practices (e.g., bottom trawling), and an accessible elasmobranch market. While catch and trade of more than 90 elasmobranchs are regulated under Bangladesh's law, non‐compliance is widespread. Likely causes include a dearth of awareness, practical alternative livelihoods, and technical facilities, and the complex nature of the fisheries. Encouraging and facilitating the engagement of fishers in science (data collection), local governance (policy‐making), and field implementation (bycatch mitigation) is vital. These interventions must be rooted in sustainable approaches and co‐designed with fishers, with appropriate training available. Development of this work through enhanced engagement with fishers has the potential to transform the elasmobranch fishery situation in Bangladesh and could be used as a model for data‐poor regions

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