Predicting fisheries bycatch of protected species in dynamic seascapes

该项目旨在通过利用大数据分析的力量，提高全球预测延绳钓渔业中受保护非目标物种（海鸟、海龟）的偶然捕获（兼捕）发生的时间和地点的能力。利用创新的跨学科技术，该项目预计将产生海洋生态学和渔业海洋学的新知识。预期成果包括新的机构和学科合作，理论进步，以及为管理当局和行业开发新的数字化工具。这将带来重大惠益，例如降低渔业成本，减少决策风险，并在实现国际可持续发展目标方面取得进展。

This project aims to advance global capacity to predict where and when incidental catch (bycatch) of protected non-target species (seabirds, marine turtles) occurs in longline fisheries, by harnessing the power of big data analytics. Using innovative interdisciplinary techniques, this project expects to generate new knowledge in marine ecology and fisheries oceanography. Expected outcomes include new institutional and disciplinary collaborations, advances in theory, and the development of novel digital tools for management authorities and industry. This should provide significant benefits, such as reduced costs to the fishing industry, risk reduction in decision-making, and progress towards international sustainable development goals.