Simple Adaptive Rules Describe Fishing Behaviour Better than Perfect Rationality in the US West Coast Groundfish Fishery

Most bio-economic models in fisheries assume perfectly rational profit-maximizing behaviour by fishing vessels. Here we investigate this assumption empirically. Using a flexible agent-based model of fishing vessels called POSEIDON, we compared predicted fishing patterns to observed patterns in logbook data, that resulted from a wide range of stylized decision-making processes in the U.S. west coast dover sole-thomyhead-sablefish (DTS) fishery, which is managed with tradable quotas (ITQs). We found that observed vessel behaviour was best predicted in the model by simple decision algorithms whereby vessels chose between exploring new fishing grounds and revisiting previous ones based on their and other vessels' past successes. In contrast, when the model assumed that vessels were perfect profit maximizers, the model substantially overestimated their profits and utilization of quota of rare, constraining species that carry high quota costs, such as yelloweye rockfish. Our results suggest that bounded rationality is an important driver of vessel behaviour in this fishery.