A prototype agent based fishery management model of Hawaii's longline fishery

The recent advent of agent-based modeling (ABM) and the availability of software platforms for its implementation offer a powerful alternative to model the spatio-temporal behaviors of a fishery with the consideration of heterogeneity and interactivity. This paper describes a prototype agent-based fishery management model of Hawaii's longline fishery. The model simulates the daily fishing activities of 120 Hawaii longline vessels of diverse characteristics. Following the strategy of pattern oriented modeling (POM), we use the spatio-temporal distribution pattern of fishing efforts to calibrate the model. While POM has a record of success in ecology, the present application to socioeconomic systems such as fishing and fishery management is almost unprecedented. We also use the calibrated model to evaluate three alternative fishery regulatory policies in Hawaii's longline fishery: 1) no regulation; 2) annual cap of 17 turtle interactions; and 3) close the north central area year round, with respect to their impacts on fishing productivity and by-catch of protected sea turtle. The prototype model, constructed using 1999 data, appears to be able to capture the responses of the fishery to these alternative regulations reasonably well, suggesting its potential as a management tool for policy evaluation in Hawaii's longline fishery.