Edited by Randy Gimblett

The purpose of this volume is to help form a set of coherent, cross-referenced perspectives on incorporating the spatial representation and analytical power provided by those employing the use of Geographic Information Systems with those developing agent-based technologies to dynamically simulate evolutionary and nonlinear phenomena. This volume is broadly focused on spatially-explicit simulation modeling as an essential component of decision-making in natural resource management. In recent years a strong need has arisen to improve the detail, realism and validity of such models. This is due in part to the very real gap between the many models constructed for research purposes and the practical needs of decision-makers. As the alternatives available in resolving resource problems become expensive, and the resources themselves become increasingly scarce, such models become vital tools in the direct and indirect management of natural resources.

Discussed in this volume is the use of the individual-based perspective in modeling, and arising directly from this, the ability to include intelligent agents as entities within spatially-explicit simulation models. The advantage of the individual-based perspective is that it allows global phenomena to emerge as a result of interactions between individuals and other aspects of the environment, analogous to the physical world hose complexities are captured in a realistic modeling the participation of humans in their environment, and thus the disturbances and changes induced by human activities that are central to many problems in natural resource management.

This volume is a collection of papers representing those developing and applying these technologies to address resource management problems or to aid in the understanding of ecological phenomena. Chapters are both technically driven for the audience interested in algorithm and system development as well as application oriented for those readers exploring the use of intelligent agents for modeling both social and ecological processes and the policy and management implications resulting from such simulations.

About the Editors

H. Randy Gimblett, Professor, School of Renewable Natural Resources, The University of Arizona. His research interests are in Spatial Dynamic Ecosystem Modeling, Geographic Information Systems, Human Cognition and Environmental Perception, Landscape Simulation and Recreation Behavior Modeling. He has worked in numerous National Forests, Parks and Natural Area settings in the United States, Canada, Mexico, and Australia.