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Modeling Enrollment in the Conservation Reserve Program by Using Agents within Spatial Decision Support Systems: An Example from Southern Illinois

Author

Listed:
  • Raja Sengupta

    (Department of Geography, McGill University, 805 Sherbrooke Street W, Montreal, Quebec H3A 2K6, Canada)

  • Christopher Lant

    (Department of Geography (MailCode 4514), Southern Illinois University, Carbondale, IL 62901-4514, USA)

  • Steven Kraft
  • Jeffrey Beaulieu
  • William Peterson
  • Timothy Loftus

    (Water Quality Laboratory, Heidelberg College, 310 E. Market Street, Tiffin, OH 44883-2462, USA)

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.

Suggested Citation

  • Raja Sengupta & Christopher Lant & Steven Kraft & Jeffrey Beaulieu & William Peterson & Timothy Loftus, 2005. "Modeling Enrollment in the Conservation Reserve Program by Using Agents within Spatial Decision Support Systems: An Example from Southern Illinois," Environment and Planning B, , vol. 32(6), pages 821-834, December.
    • Handle: RePEc:sae:envirb:v:32:y:2005:i:6:p:821-834
    DOI: 10.1068/b31193
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    References listed on IDEAS

    as
    1. Berger, Thomas, 2001. "Agent-based spatial models applied to agriculture: a simulation tool for technology diffusion, resource use changes and policy analysis," Agricultural Economics, Blackwell, vol. 25(2-3), pages 245-260, September.
    2. Cain, J. D. & Jinapala, K. & Makin, I. W. & Somaratna, P. G. & Ariyaratna, B. R. & Perera, L. R., 2003. "Participatory decision support for agricultural management. A case study from Sri Lanka," Agricultural Systems, Elsevier, vol. 76(2), pages 457-482, May.
    3. Gerd Gigerenzer & Reinhard Selten (ed.), 2002. "Bounded Rationality: The Adaptive Toolbox," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262571641, December.
    4. repec:ags:agsaem:288652 is not listed on IDEAS
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    Cited by:

    1. An, Li, 2012. "Modeling human decisions in coupled human and natural systems: Review of agent-based models," Ecological Modelling, Elsevier, vol. 229(C), pages 25-36.
    2. Chen, Xiaodong & Lupi, Frank & An, Li & Sheely, Ryan & Viña, Andrés & Liu, Jianguo, 2012. "Agent-based modeling of the effects of social norms on enrollment in payments for ecosystem services," Ecological Modelling, Elsevier, vol. 229(C), pages 16-24.
    3. Kremmydas, Dimitris & Athanasiadis, Ioannis N. & Rozakis, Stelios, 2018. "A review of Agent Based Modeling for agricultural policy evaluation," Agricultural Systems, Elsevier, vol. 164(C), pages 95-106.

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