A coupled recreational anglers’ decision and fish population dynamics model

• Published in: PLOS ONE
• Main Authors: Fujiwara, Masami, Backstrom, Jesse D., Woodward, Richard T.
• Format: Text
• Language: English
• Published: Public Library of Science 2018
• Subjects: Research Article; Red drum
• Online Access: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6209354/; http://www.ncbi.nlm.nih.gov/pubmed/30379924; https://doi.org/10.1371/journal.pone.0206537

The effective management of fish populations requires understanding of both the biology of the species being managed and the behavior of the humans who harvest those species. For many marine fisheries, recreational harvests represent a significant portion of the total fishing mortality. For such fisheries, therefore, a model that captures the dynamics of angler choices and the fish population would be a valuable tool for fisheries management. In this study, we provide such a model, focusing on red drum and spotted seatrout, which are the two of the main recreational fishing targets in the Gulf of Mexico. The biological models are in the form of vector autoregressive models. The anglers’ decision model takes the discrete choice approach, in which anglers first decide whether to go fishing and then determine the location to fish based on the distance and expected catch of two species of fish if they decide to go fishing. The coupled model predicts that, under the level of fluctuation in the abundance of the two species experienced in the past 35 years, the number of trips that might be taken by anglers fluctuates moderately. This fluctuation is magnified as the cost of travel decreases because the anglers can travel long distance to seek better fishing conditions. On the other hand, as the cost of travel increases, their preference to fish in nearby areas increases regardless of the expected catch in other locations and variation in the trips taken declines. The model demonstrates the importance of incorporating anglers’ decision processes in understanding the changes in a fishing effort level. Although the model in this study still has a room for further improvement, it can be used for more effective management of fish and potentially other populations.