Marine Fishery Management Agent-Based Modeling

Fisheries in the United States not only provide seafood for us to enjoy and contribute significantly to the American economy, they also help us to sustain ecological balance and protect our ocean resources. Fishery management agencies in the United States conduct stock assessments to discover the changes in the abundance of fishery stocks in response to changes in the environment and effects of commercial and recreational fishing. Efficient stock assessment enables maintenance of healthy fisheries without permanently damaging the marine ecosystem. In order to forecast the future trend of fisheries, predicting fish migration patterns in response to the environmental factors is important. We present an agent-based model which through emergence, predicts migration patterns of Mackerel by exploiting their biological characteristics. We generalized the agent-based model proposed by SEASIM [ 4 ] by employing an optimal temperature of Mackerel for fish movement in response to environmental data. The experimental results suggested that integration of bio-energetics and an energy budget for each agent was necessary for improving the accuracy of the Mackerel spatial dynamics in the simulation