Modeling enrollment in the Conservation Reserve Program by using agents within spatial decision support systems: an example from southern Illinois

Authored by R Sengupta, C Lant, S Kraft, J Beaulieu, W Peterson, T Loftus

Date Published: 2005-11

DOI: 10.1068/b31193

Sponsors: Illinois Council on Food and Agricultural Research United States National Science Foundation (NSF)

Platforms: C++

Model Documentation: Other Narrative

Model Code URLs: Model code not found

Abstract

Existing models of agricultural decisionmaking based on economic optimization often fall short of capturing the complex dynamics of land-use choices at both individual parcel and watershed-level scales. The complexity arises from an interplay of several factors, as explained by Herbert Simon's model of bounded rationality, the theory of diffusion of innovations through spatial contagion, the role of personal environmental values and local culture, and simple historical momentum. This complexity can be captured using `artificial life agents' that model land-use choice for individual parcels by considering characteristics and personal beliefs of the owner or operator, physical traits of the land, and information obtained via social networks. Agents are therefore able to consider holistically a large number of factors affecting land-use choice. The creation of agent-based models of human behavior described herein is based upon empirical data on the acceptance of Conservation Reserve Program for the Cache River watershed of southern Illinois (USA). These models are interfaced with a geographic information system to produce a spatial decision support system capable of anticipating the effects of policies that affect land-use decisionmaking on a real landscape and their economic performance.

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