Aquatic Living Resources, 18(3), 301-311
Marine fisheries and the ecosystems that sustain them are increasingly beset by environmental deterioration, and the problem is particularly acute in coastal zones where human Populations are increasing. In the best of circumstances, fishery managers are faced with the multiple, often conflicting, demands of resource users, politicians, and scientists when considering strategies for resource management. A further challenge is that management decisions must be made against a backdrop of a deteriorating environment and the shifting status of coastal ecosystem integrity. Traditional tools for single-species management may be inadequate in these settings. Furthermore. the necessary empirical data to appropriately parameterize models with vital rates representative of all altered environment are often lacking. Thus, we need approaches that better approximate the complicated dynamics between environmental conditions, fishery impacts, and multi-species interactions. Spatially-explicit, indivickial-based simulation modeling potentially permits this kind of integration, but it has seen limited use in marine resource management. especially with respect to benthic resources. My colleagues and I have used this approach, combined with targeted experimental work, to explore the impacts of nursery habitat deterioration, coastal freshwater management. and fishery activities oil Caribbean spiny lobster populations and sponge community structure in the Florida Keys, Florida (USA). Although not applicable for all resource management situations, our experiences provide all example of the potential use of spatially-explicit, individual-based modeling and targeted empirical science in predicting resource conditions in a dynamic environment.
Original Publication Citation
Butler, M.J. (2005). Benthic fisheries ecology in a changing environment: Unraveling process to achieve prediction. Aquatic Living Resources, 18(3), 301-311. doi: 10.1051/alr:2005034
Butler, Mark J. IV, "Benthic Fisheries Ecology in a Changing Environment: Unraveling Process to Achieve Prediction" (2005). Biological Sciences Faculty Publications. 13.