This award is funded under the American Recovery and Reinvestment Act of 2009 (Public Law 111-5).
Fishing and fishery management is typically a complex system of human activities in which the properties of the system are not obvious from the properties of its components. For example, the race for fish by rational individuals likely would result in an irrational consequence for the entire fishery?fishery collapse. This project adopts agent-based modeling (ABM), an emerging technique for studying complex systems, as an alternative tool for modeling the management of pelagic fisheries, using Hawaii?s longline fishery as a case study. ABM is expected to better incorporate the heterogeneity of individual fishers (e.g., different cost structure, risk attitude, fishing preference, etc.) and their fishing decisions/activities (e.g., responses to change in regulatory policies). Model development will be guided using the strategy of pattern oriented modeling (POM). In particular, the project will explore the utility of POM in testing the credibility of alternative theories concerning fishing decisions and activities such as revenue targeting, profit maximization and adaptive learning in Hawaii?s longline fishery. While POM has a record of success in ecology, the proposed application to socioeconomic systems such as fishing and fishery management is unprecedented. The developed model will be used to evaluate alternative fishery policies with respect to their impacts on both the fishing communities (productivity of vessels, trip choice, remuneration arrangement, etc.) and the conservation of endangered marine species (e.g., sea turtles).
This research will contribute academically and practically toward the formulation of ecosystem-based responsible fishery management for Hawaii?s longline fishery and fishery in general. It will provide vital information in regards to improving the conservation of endangered sea turtles, assessing the broad impacts of policy reforms on fishery, and facilitating the decision making of fishery managers.
