ABSTRACT

Urban development in the United States is profoundly changing landscape patterns and biodiversity and is simultaneously affected by these changes. Little is known about the interactions between patterns and processes in human dominated landscapes, however. One of the least understood aspects of urban landscape dynamics is the way in which local interactions of humans and biophysical processes generate the landscape patterns of metropolitan regions. Studying the relationships between these interactions and the resulting urban landscape patterns is critical to plan and manage urban growth in ways that minimize the ecological impacts on ecosystems while sustaining economically and socially viable urban communities. This research project will examine urban landscapes as emergent phenomena that result from local interactions of human agents, real estate markets, built infrastructure, and biophysical factors like land cover, geomorphology, and natural disturbance regimes to develop a theory of urban landscape dynamics. The study will employ complex systems, patch dynamics, hierarchical theory, and an agent-based modeling approach to study coupled human-natural dynamics and empirically test this approach in two different bioregions (Seattle and Phoenix). The models will be developed and used to test hypotheses regarding emergent properties of urban landscapes and to enhance basic understanding of humans-ecological interactions in urban landscapes across scales. Urban landscapes exhibit some fundamental features of complex self-organizing systems. They are highly heterogeneous, spatially nested, and hierarchically structured. The urban spatial structure can be described as a cumulative and aggregate pattern that results from numerous local decisions involving a large number of adaptive agents interacting among themselves and with biophysical factors. These behaviors eventually can lead to different metropolitan patterns. This research will address four questions: (1) How do dynamic landscape systems evolve to generate emergent patterns that are evident in urban landscapes? (2) What nonlinearities, thresholds, discontinuities, and path dependencies explain divergent trajectories of urban landscapes? (3) How do emergent urban landscape patterns influence biodiversity and ecosystem functioning? (4) How can planning integrate this knowledge to develop sustainable urban landscape patterns? The model implementation will be based on a dynamic probabilistic relational model (DPRM) in which parameters and spatial rules are estimated empirically from two longitudinal land-cover and land-use data sets developed for the Seattle and Phoenix metropolitan areas.

The project will have significant theoretical and practical impacts. It will develop a better understanding of complex human-ecological dynamics leading to development patterns such as sprawl, one of the most pressing and controversial problem in the United States. The project will also contribute to advancing biocomplexity science. The findings of this research will have an impact on both the social and natural sciences particularly the study of development patterns, land-use change, ecological resilience, and public policy in urbanizing regions. This project will also employ new computational techniques that are of importance to a broad range of disciplines studying human dynamics, ecology, and artificial intelligence. The findings will also aid planning and management of urban regions by providing simulation tools to assess the ecological impacts and feedback of alternative strategies for urban development and ecological conservation. This project is supported by an award resulting from the FY 2005 special competition in Biocomplexity in the Environment focusing on the Dynamics of Coupled Natural and Human Systems.

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