The management of exploited fish and invertebrate stocks in the future needs to be robust to ongoing and further anticipated global shifts in climate and ecosystem function. This theme session will shed light on how and when system-level processes such as predation or climate change should be included in the models used to provide quantitative scientific advice for management procedures.
Ecosystem-based fisheries management (EBFM) calls for the incorporation of external factors into fisheries management procedures. This has been achieved in stock assessments by incorporating time-variant parameters or parameters estimated from multi-species or ecosystem models, and in management frameworks by informing buffers with ecosystem models. However, the use of ecosystem-based models for quantitative scientific fisheries management advice is still in its infancy. New methods are needed for developing these models, adapting them to a wider variety of data quality scenarios, and using them for simulation testing.
Simulation approaches like management strategy evaluation (MSE) allow practitioners to test hypotheses about how EBFM should be implemented. They are also critical tools for communicating tradeoffs and analyzing the risks associated with management decisions, and are considered to be a best practice in fisheries management. In addition to the challenge of balancing realism with tractability, practitioners using MSE for EBFM questions face new challenges: possible misspecification, structural uncertainty, and the need for addressing complex tradeoffs between ecosystem components. The uncertainty, risks and trade-offs associated with management of ecological systems of varying data availability need to be quantified and evaluated to provide the best possible scientific advice.
We invite contributions on the following topics:
- Methods for incorporating ecosystem processes in closed-loop simulations such as management strategy evaluation
- The development of multispecies models to inform EBFM
- Ecosystem-based simulation and assessment frameworks suitable for data-poor systems
- Evaluation and communication of tradeoffs related to ecosystem function or processes (e.g., incorporating ecosystem components in the tradeoffs presented for decision makers)
