The effective management and conservation of fish population is achieved by understanding the behavior of anglers and creating appropriate incentives for sustainability. However, it is often difficult to predict the behavior of anglers in recreational fisheries because multiple factors influence them. Here, a model that links fish population dynamics to anglers’ behavioral dynamics was built. The anglers’ decision model takes the discrete choice approach, in which, anglers first decide whether they go fishing or not based on distance to fishing sites and expected catch of fish. Then, if they decide to go fishing, they determine the location to go fishing based on the distance and expected catch. The biological models are in the form of vector autoregressive models. These two models are linked by incorporating the relative abundance of fish predicted by the biological models as the expected catch in the angler’s decision model. The coupled model predicts that under the level of fluctuation in fish abundance experienced in the past 35 years, the number of trips taken by anglers fluctuates noticeably. This fluctuation is magnified as the cost of travel decreases because the anglers can travel long distance to seek better fishing conditions. The model demonstrates the importance of incorporating anglers’ decision processes in understanding the changes in a fishing effort level. The model in this study can be used for improving management and conservation of fish and potentially other populations.