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"This study addresses a central puzzle facing the Human Dimensions of Global Change research community: How can we understand the influence of environmental policies on human behavior when little or no information is available on the condition of forest resources? This dissertation capitalized on new research tools, methods and approaches to overcome the 'no information about the resource' problem. Specifically, I combine (1)forest mensuration techniques, (2)Global Positioning Systems, (3)Geographic Information Systems (GIS), (4)spatial statistics, (5)remote sensing, and (6)institutional analysis to analyze forest vegetation patterns. I provide explanation of these patterns by considering the incentive structures driving human decision-making and activity and do this through two studies in very different empirical settings.
"Both studies apply applicable theory related to human behavior and action. Both examine the incentive structures individuals face as they undertake daily activities related to forest resources. The first study, set in East Chitwan, Nepal, identifies spatial patterns in georeferenced forest inventory data and links these to patterns predicted by optimal foraging subject to institutional constraints. The second study compares forest management in one state and one national forest in Indiana, U.S.A. In this effort, I identify spatio-temporal patterns in the forest vegetation captured by a time series of Landsat multispectral images. The combination of natural forest regrowth and property manager actions in response to incentives and constraints explain these patterns.
"Substantively, both studies identify change in forest resources associated with combinations of the physical, human community and institutional 'landscapes' in their regions. In both cases, geographic attributes of institutions (e.g. laws, rules) are found to influence the type and location of human actions. Methodologically, the two studies provide examples of how to control for natural influences carefully, and how to link theory on human behavior with spatial statistics, institutional analysis, GIS and remote sensing toward understanding human-environment relationships. By applying one of the two approaches outlined in the studies, a researcher can overcome the 'no information on forest condition' problem in any empirical context." |
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