Management Strategy Evaluation Allowing the Light on the Hill to Illuminate More Than One Species

Management strategy evaluation (MSE) is a simulation approach that serves as a light on the hill (Smith, 1994) to test options for marine management, monitoring, and assessment against simulated ecosystem and fishery dynamics, including uncertainty in ecological and fishery processes and observations. MSE has become a key method to evaluate trade-offs between management objectives and to communicate with decision makers. Here we describe how and why MSE is continuing to grow from a single species approach to one relevant to multi-species and ecosystem based management. In particular, different ecosystem modeling approaches can fit within the MSE process to meet particular natural resource management needs. We present four case studies that illustrate how MSE is expanding to include ecosystem considerations and ecosystem models as 'operating models' (i.e., virtual test worlds), to simulate monitoring, assessment, and harvest control rules, and to evaluate tradeoffs via performance metrics. We highlight United States case studies related to fisheries regulations and climate, which support NOAA's policy goals related to the Ecosystem Based Fishery Roadmap and Climate Science Strategy but vary in the complexity of population, ecosystem, and assessment representation. We emphasize methods, tool development, and lessons learned that are relevant beyond the United States, and the additional benefits relative to single-species MSE approaches.

Automated summary

Management strategy evaluation (MSE) is a simulation approach that has become a key method to evaluate trade-offs between management objectives and to communicate with decision makers in the field of marine management. It is evolving from a single species approach to one relevant to multi-species and ecosystem based management. By incorporating ecosystem models as 'operating models', MSE can simulate monitoring, assessment, and harvest control rules to evaluate tradeoffs via performance metrics.