A spatial individual behaviour-based model approach of the yellowfin tuna fishery in the eastern Pacific Ocean

A spatial individual-based model of the yellowfin tuna fishery in the eastern Pacific Ocean is presented. Schools of fish and individual fishing vessels are represented with artificial neural networks. These representations are intended to model behaviour decisions of movement in space. Schools of fish search continually for comfort and tuna vessels search for the tuna schools during a fishing trip. Two scenarios are considered: one with no fishing regulation and another with area closure during the last quarter of the year. This model is focused on spatial dynamics of fishing effort. Effort redistribution when regulations are implemented is not well understood and this modelling approach can help fishery managers to envisage some regulation effects in the fishery.