Evaluating the Ability of Specialization Indicators to Explain Fishing Preferences

Understanding the predictive ability of recreation specialization to explain behavior is important for wildlife and fisheries management given the widespread use of specialization to capture diversity among outdoor recreationists. Using allocation of days among fishing opportunities in a discrete choice experiment, we studied the extent that specialization predicted preferences for attributes describing the opportunities. Latent class modeling revealed that three groups of anglers optimally captured preference diversity in our sample. To this base model, we sequentially added 11 metrics of angler specialization and used information theory to select the metric that best predicted group membership, namely centrality to lifestyle. Weaker evidence existed for the specialization dimensions "importance of catch," "specialized gear use," and a multidimensional self-classification approach, whereas indices of skill, media use, trophy fish, and harvest orientation were not supported. General specialization constructs such as centrality to lifestyle, therefore, might be best suited for predicting general fishing preferences and subsequent behaviors of anglers.