Agent-based modeling of deforestation in southern Yucatán, Mexico, and reforestation in the Midwest United States

Steven M. Manson, Tom Evans

Research output: Contribution to journalArticle

91 Scopus citations

Abstract

We combine mixed-methods research with integrated agent-based modeling to understand land change and economic decision making in the United States and Mexico. This work demonstrates how sustainability science benefits from combining integrated agent-based modeling (which blends methods from the social, ecological, and information sciences) and mixed-methods research (which interleaves multiple approaches ranging from qualitative field research to quantitative laboratory experiments and interpretation of remotely sensed imagery). We test assumptions of utility-maximizing behavior in household-level landscape management in south-central Indiana, linking parcel data, land cover derived from aerial photography, and findings from laboratory experiments. We examine the role of uncertainty and limited information, preferences, differential demographic attributes, and past experience and future time horizons. We also use evolutionary programming to represent bounded rationality in agriculturalist households in the southern Yucatán of Mexico. This approach captures realistic rule of thumb strategies while identifying social and environmental factors in a manner similar to econometric models. These case studies highlight the role of computational models of decision making in land-change contexts and advance our understanding of decision making in general.

Original languageEnglish (US)
Pages (from-to)20678-20683
Number of pages6
JournalProceedings of the National Academy of Sciences of the United States of America
Volume104
Issue number52
DOIs
StatePublished - Dec 26 2007

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Keywords

  • Agent-based model
  • Bounded rationality
  • Decision making
  • Land change
  • Landscape management

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