NSF Award Abstract - #0083511

AWSFL008-DS3

Biocomplexity Research: Agent-Based Models of Land Use Decisions and Emergent
Land Use Patterns

Abstract

The primary goal of this project is to explain long-term, complex change processes in human-bioecological systems-especially forested regions. We will develop agent-based models to examine how land-use decisions made at one level (a household) affect outcomes at that level and at several higher and lower levels in a hierarchically nested set of systems. We develop two agent-based models to explain land-use patterns in the frontier and post-frontier Midwest of the United States and the frontier of the Brazilian Amazon. The first model will address two major puzzles: (1) Why did the descendants of the initial settlers in nineteenth-century Indiana cut down timber at such a massive and seemingly uneconomic rate that they eventually denuded the land, causing massive erosion and soil loss, and leading to substantial farm abandonment? and (2) Why have forests regrown so extensively on privately owned land when so many public policies are based on the assumption that fragmented, privately owned parcels are destined never to have significant forest regrowth? The second model will explain the spatial and temporal patterns of deforestation in the Amazon over the last three decades. The assumptions we make in the two models will be empirically tested and grounded by rigorous laboratory experiments. The patterns of land use at any point in time and the processes of change also will be tested against a rich set of data derived from ground-truthed satellite data, aerial photographs, land surveys, census data, household interviews, forest mensuration undertaken in a sample of forest patches, and archival data regarding timber and agricultural prices, input costs, and land values. After further development and testing, both models will be used to extrapolate into the future and assess how diverse public policies are likely to affect land use in general and forest change in particular in these regions. The project will involve three important capstone activities: a Workshop on Agent-Based Models of Biocomplexity, a synthesis volume to be derived from the Workshop, and a Summer Institute.

The study will have multiple impacts. By achieving an empirically validated understanding of land-use decisions of individual households under different policy regimes, the study will produce useful tools for evaluating alternative public policies. Ascertaining how public inducements, taxation, and constraints affect rates of forest change contributes to the worldwide effort to find effective methods for stimulating reforestation and thereby sequestering carbon to offset carbon released into the atmosphere. The study also addresses fundamental questions related to the appropriate model of human behavior to use when examining a combination of investment decisions in complex, dynamic environments. Thus, the study is relevant for achieving an empirically validated foundation for an array of decision situations beyond those of land use and deforestation. Tools from multiple social, biological, and physical science disciplines will be combined and expanded in unique ways and disseminated in publications, workshops, and training institutes. This research activity was funded as part of the FY2000 Biocomplexity Special Competition.