Fishery-dependent data increasingly include fine-scale resolution of the spatial and temporal behavior of individual fishing vessels. Here, I discuss how empirical economic models can be used to analyze these data and inform the design and evaluation of marine spatial management. First, empirical economic models can isolate the causal drivers of fishing decisions and inform managers about what will happen after a policy change such as the formation of a new marine reserve. The main approach in fisheries economics is to use a statistical model of fishing-ground choice as a function of the profitability of each alternative. I highlight key findings from this literature and ways in which recent methodological developments can address emerging issues in spatial management. Second, the decisions of individual fishermen can reveal information about the spatial biophysical characteristics of an ecosystem. To illustrate this point, I present a Monte Carlo simulated-data experiment in which individual spatial fishing choices are statistically analyzed. The experiment shows how the information embedded in individual fishermen's choices can isolate the spatiotemporal pattern of fish abundance. This pattern, in turn, can be used to quantify the environment dependence of fishery resources. Harnessing fishery-dependent data in this way can in principle show how environmental variables affect fisheries without direct observation of fish abundance or a specific model of stock dynamics.
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