The majority of the world's marine and diadromous fish stocks lack adequate data for conventional stock assessment methods. Such stocks, known as “data-limited", can also occur in regions with long-term surveys (e.g., northeast Atlantic). Until recently, fisheries science has been unable to inform decision-makers on their status and potential, as the assessments of data-limited species and stocks still need sufficient data and to be based on robust calibration, statistical design, and data-handling. The number of stocks in need and the timetables of policy-makers around the world make it vital to improve methodologies. The global fisheries science community is innovating methodologies to take advantage of the available data to assess data-limited stocks. This session will provide an international forum where the latest advancements in data-limited method development and application are presented and discussed.
While there is an impressive selection of data-limited assessment strategies, , it is imperative to develop innovative and practical approaches for identifying and assessing data-limited fisheries and species complexes to provide effective scientific advice to fisheries managers. Theme session N will highlight approaches that have the potential to be practical in their implementation and effective in their application.
The objectives of this session are to:
- Discuss improvements in monitoring and data collection methods for data-limited species, including fish with complex life history and non-targeted species
- Showcase advancements in single and multispecies data-limited assessment methods
- Quantify uncertainties in stock assessment methods and identify key challenges to method development and application to provide effective advice
Research, perspectives, and real-world experiences that relate to overcoming challenges in assessing and managing data-limited stocks are solicited, as well as submissions on the following topics:
- Survey design and data collection methods for data-limited fisheries
- New and innovative use of models to assess data-limited stocks or species complexes
- Methods to determine and use life history traits to assess stock status
- Stock identification techniques to identify cryptic species or determine composition of mixed stock catches
- Use of meta-analysis or similar species to inform data-limited models
- Development of data-limited stock harvest levels and adaptive management plans
- Management strategy evaluation of data-limited approaches
- Quantifying uncertainties in assessment practices with a special focus on communicating advice
