Coastal SEES (Track 1): Novel Approaches to Understanding Human Use Patterns and Mobility for Coastal Natural Resources Management

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This project will address a critical gap in fisheries science and management by developing better models of fisher location choice in response to management measures such as closed areas and individual fishing quotas. Coastal and marine spatial planning and management is increasingly viewed as the basis with which to allocate access to resources and reduce negative interactions among sectors that are not compatible with long term ecosystem sustainability. Yet, ecological-behavioral models that might assist managers in addressing these needs are rudimentary. This project will evaluate the utility of new classes of behavioral models and entropy statistics, originally developed from terrestrial studies of human activity patterns enabled by advanced technologies for tracking human movements. Assessing traditional methods of predicting human use patterns, introducing and testing new methods, and empirically testing for changes in use patterns due to regulations and ecological conditions are critical for formulating new predictive modeling tools supporting coastal sustainability. While this project focuses on fisheries, the methods will have broader applicability for coastal sustainability, e.g. shipping, coastal wind power, military preparedness, oil production, and other sectors. The project will build upon collaborative networks and partnerships among scientists, academia, government agencies, and others involved in coastal resource management.A unique dataset that includes millions of observations of individual choices of where, when, and what to fish for under a number of regulatory regimes, will be used. Past approaches of modeling and predicting human use patterns (random utility and logit modeling) have, for the most part, utilized data recorded at coarse spatial resolutions (e.g., National Marine Fisheries Service statistical areas) and timespans. In addition to assessing the implications of underlying key assumptions of the past approaches (e.g., spatial aggregation), new methods (entropy models) will be tested for modeling and predicting human-use patterns that have been developed in other research fields that also have high frequency location data (e.g., cellphone usage). Vessel monitoring system (VMS) data that are updated every 60 minutes by satellite provide high fidelity observations of the actual locations of fishing across years. Location choices are determined by ecological conditions (e.g., fish aggregations) and by the incentives created by the regulatory institutions. For example, fishermen engaging in a race to catch fish will likely behave differently than those that have more secure rights to the fish at the beginning of the fishing season as is the case in catch share fisheries. Due to the long time series of VMS data and the changing regulatory institutions in the management of the Gulf of Mexico fisheries during the period of analysis, observational research will estimate how spatial decision making has changed in response to changing regulations.This project is supported under NSF's Coastal SEES (Science, Engineering and Education for Sustainability) program.