Ph.D. candidate University of California, Davis Seattle, California, United States
Abstract: Successful conservation and natural resource management often require significant investments in monitoring programs to allow management actions to respond adaptively to changes in the ecosystem. However, financial and scientific resources for these programs are often limited and must be allocated between competing priorities. This problem is particularly acute for fisheries management, where harvest limits are regularly updated to track changes in the population’s abundance. We developed a bioeconomic model to identify the optimal strategy for investing in monitoring information for fisheries management and tested the effect of the manager’s objective and the population’s biology on the economic value of monitoring information. Based on these findings, we identified a set of factors that can be used to prioritize scarce monitoring resources like fisheries independent surveys and model-based stock assessments. Of these factors, the time scale of the population's dynamics was especially important. Populations with lower growth and mortality rates were monitored less frequently under the optimal policy. The abundance of these populations changed more slowly over time, allowing management actions (the harvest limit) to adapt in a timely manner, even when observations were made infrequently. These results suggest that adaptive management strategies are most efficient when designed to match the time scale of the underlying biological processes.
