Advancing the Management of Global Data-Limited Fisheries

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The status and future of 90% of global fish species is uncertain. Limited data and scientific capacity mean that most remain unassessed and are classified as data-limited. These fish populations are vital for global food security and biodiversity. In most cases it is unknown whether proposed management approaches are sustainable. This is one of the most critical issues facing global marine conservation and ocean sustainability today. There are at least three scientific obstructions to progress: lack of a scientifically rigorous framework for risk-based management, insufficient scientific capacity and, few management approaches tailored to the developing-world data-limited problem. More generally there is a lack of clear management guidance for these fisheries. Over the last five years, a UBC project has established a scientifically rigorous approach for identifying sustainable management of data-limited fisheries. The data-limited methods toolkit (DLMtool) is free open-source software that uses Management Strategy Evaluation (MSE) simulation techniques and supercomputing technology to find robust fishery management solutions. Since its release in 2015, DLMtool has informed management in over 30 fisheries in North America, providing benefits in scientific rigor, transparency and accountability. In partnership with the UN Food and Agricultural Organization (FAO) DLMtool workshops have trained more than 25 national scientists from over 15 countries. Aim: Leveraging existing FAO-DLMtool projects, I propose a 5-year PhD research program to address the critical problems of developing-world data-limited fisheries by developing case studies, testing new approaches and building capacity through collaboration with regional scientists. There are 4 short-term objectives: 1. Use an existing FAO-DLMtool training program to build a research network, collate data and construct case studies in South-East Asia, East Africa, South American and Central America. 2. Identify critical research gaps and develop and test new statistical approaches for managing fisheries. 3. Make all new methods and models publicly available in a DLMtool release and publish an impact report. 4. Establish a working management protocol(s) to transition data-limited fisheries from unmanaged to sustainably managed. The long term objective is to jump-start the process of establishing sustainable fishery management in developing world fisheries by providing a blueprint for moving out of the data-limited situation. The HQP arising from this research program will be experts in two cutting edge and rapidly expanding fields of marine science: MSE and data-limited fisheries. They will also be placed at the heart of an international collaborative program connected through the most influential organization for global food security and environmental sustainability the UN FAO.