Evaluating the Efficacy and Consistency of Management Regulations in US Marine Recreational Fisheries

Ensuring sustainability of fisheries by limiting harvest is the central goal of most recreational fisheries management regulations and yet there have been surprisingly few examinations of how effective different regulations are in limiting total harvest within various management contexts.  Through selective removals of certain species of certain sizes, fisheries can cause a cascading effect on growth and mortality rates as well as predatory and competitive interactions with other species.  Despite the complexity of the biological system, we usually use simple regulations to either limit the effectiveness of anglers through such limitations as gear restrictions and bait bans, or limit harvest through bag and size limits.  However, regulations act not only on an individual angler by limiting catch or harvest, but also on the perception of the fishery, which may cause a change in the total number of anglers or the number of return trips per angler.  So while regulations may limit harvest per trip, they may actually increase total harvest due to increased fishing effort.  There are various case studies on the efficacy of many different regulations used in different context, but these are often biased towards reporting on scenarios where management goals were achieved.  In contrast, various simulation studies warn of the unintended consequences of different regulations, either through species interactions or interactions of multiple tactics used simultaneously.  There are very few meta-analyses designed to critically examine how well various regulations work and under what conditions they fail.  We use a two-step analysis to examine how different management regulations have affected catch and effort in various marine recreational fisheries across the coastal United States.  First, we utilize a random forest model to predict catch and effort based on various predictors.  Residuals from the random forest model are then analyzed using a linear mixed effects model to identify fishing regulations that result in increases or decreases in catch and effort both immediately and over time.  This analysis allows us to identify regulations that generally perform poorly and contexts in which various regulations or combinations of regulations have a greater probability of achieving long-term reductions in total harvest.  Through an examination of multiple fisheries in various social, biological and management contexts, future regulations may be chosen based on their probability of success, helping to promote long-term sustainability in fisheries and fish populations.