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Exploring Complexity in a HumanEnvironment System: An Agent-Based Spatial Model for

Summary: Exploring Complexity in a Human­Environment
System: An Agent-Based Spatial Model for
Multidisciplinary and Multiscale Integration
Li An,* Marc Linderman,* Jiaguo Qi,** Ashton Shortridge,** and Jianguo Liu***
*Department of Fisheries and Wildlife, Michigan State University
**Department of Geography, Michigan State University
***Department of Fisheries and Wildlife and Center for Systems Integration and Sustainability, Michigan State University
Traditional approaches to studying human­environment interactions often ignore individual-level information,
do not account for complexities, or fail to integrate cross-scale or cross-discipline data and methods, thus, in
many situations, resulting in a great loss in predictive or explanatory power. This article reports on the devel-
opment, implementation, validation, and results of an agent-based spatial model that addresses such issues.
Using data from Wolong Nature Reserve for giant pandas (China), the model simulates the impact of the growing
rural population on the forests and panda habitat. The households in Wolong follow a traditional rural lifestyle, in
which fuelwood consumption has been shown to cause panda habitat degradation. By tracking the life history of
individual persons and the dynamics of households, this model equips household agents with ``knowledge'' about
themselves, other agents, and the environment and allows individual agents to interact with each other and the
environment through their activities in accordance with a set of artificial-intelligence rules. The households and
environment coevolve over time and space, resulting in macroscopic human and habitat dynamics. The results
from the model may have value for understanding the roles of socioeconomic and demographic factors, for
identifying particular areas of special concern, and for conservation policy making. In addition to the specific


Source: An, Li - Department of Geography, San Diego State University
Michigan State University, Center for Systems Integration and Sustainability


Collections: Environmental Sciences and Ecology; Geosciences