25% of all fisheries are depleted and in need of rebuilding, but economic and institutional barriers prevent reductions in fishing pressure. Management agencies are tasked with developing rebuilding policies that must meet both conservation and economic goals. Matrix models of population demographics have frequently been used optimize natural resource management through targeted mortality policies. While most applications of matrix models to fisheries management have been in pursuit of optimal yield policies, we are interested in how the optimal harvest policy changes when the long term population growth rate is constrained to being positive, resulting in population rebuilding. Here we present a solution to this constrained maximization problem. We then explore these results using an a age-structured, spatially-explicit stochastic model of the red abalone (Haliotis rufescens) population at San Miguel Island, California. California’s red abalone fishery was closed in 1997 after years of unsustainable harvests, and any future harvest policies must be compatible with long-term rebuilding goals for the population. We determine which harvest policy maximizes a utility function that combines population growth and net present value to the fishery over a specified time period.
Results/Conclusions
For biologically relevant parameter sets in our two-stage model, we find that optimal harvest policy to maximize yield while maintaining a positive long-term growth rate involves harvesting a greater proportion of larger individuals. This is analogous to increasing the size limit or changing the selectivity of the fishing gear to target larger fish. We find a similar result in our simulated case study, in which maximizing the combined utility function of population rebuilding and net present value to the fishery over a given time period involves targeting larger individuals for harvest. In many real-world management scenarios, raising size limits may provide relatively low cost approach to rebuilding while maximizing fishery harvests.