A Bayesian Methodology for Estimating the Impacts of Improved Coastal Ocean Information on the Marine Recreational Fishing Industry

Abstract

The study develops a model of recreational fish catch probabilities, based on angler fishing strategies, that is conditional on uncertain information about the coastal ocean environment. We calculate expected catch based on a hypothetical Baseline Data Set and hypothetical data from an Integrated Ocean Observation System (IOOS) to demonstrate potential benefits from IOOS. The role of Bayesian probabilities in Random Utility Models of recreational fishing is identified. The study discusses the types of information that will be required by recreational anglers in the Gulf of Mexico. Results have implications for the construction of ocean observation systems for recreational fishermen.