Abstract for: Exploring the Effects of Offshore Wind Farm Spatial Exclusion on Fishing Vessel Behavior: An Agent-Based Model Using AIS Data from the Norwegian North

Offshore wind farms in the North Sea are expanding rapidly, but they overlap with fishing grounds. When areas are restricted, fishing vessels lose access to places they have used for years. This forces them to change their routes, travel farther, and fish in smaller areas. How vessel behavior changes under different levels of restriction is not well understood. We built a spatial agent-based model that simulates a real fishing vessel operating near the Sønnavind A wind farm site in Norway. The model uses actual vessel tracking data from Global Fishing Watch to define fishing grounds, trip patterns, and cell quality. We ran five scenarios, restricting 0% to 100% of the wind farm area, and compared how the vessel's behavior changed across each level. As more area is restricted, the vessel's fishing efficiency drops. It takes more trips but catches less per trip — trip count rises while fishing hours per trip fall. The vessel also uses fewer fishing cells. These effects are small at low restriction but grow sharply beyond higher exclusion. The model shows that spatial exclusion does not just reduce fishing time — it changes how the vessel operates. Trips become shorter and less productive, and effort concentrates into a smaller area. These patterns match concerns raised by Norwegian fishers about losing access to grounds. However, the model does not capture how vessels might adapt over time or how competition from other displaced vessels could change outcomes. To provide assistance in writing and coding for the simulation.