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A Step-By-Step Approach to Building Land Management Scenarios Based on Multiple Viewpoints on Multi-Agent System Simulations

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Abstract

A multi-agent system was developed to simulate strategies of natural resource management in the Causse Méjan, a limestone plateau dominated by a rare grassland-dominated ecosystem endangered by pine invasion. To stimulate the emergence of alternative long-term management strategies for the sheep farms and the woodlands, contrasting dynamic viewpoints on land resources were designed at different space scales. To begin with, they were individually used to validate the model with each type of main stakeholders (foresters, farmers and the National Park of Cévennes rangers), to improve it and to propose individual scenarios of natural resource management. Once the model improved, the set of viewpoints made it possible to assess the impact of the individual scenarios on the main productive (sheep stocking rate, timber growth) and environmental (endangered species, landscape value) stakes on any spatial entity considered as relevant by any stakeholder. As the different opinions were collectively viewed and confronted, the need to agree to a compromise was highlighted and led to new scenarios based on more collective management of the pine woodlands. The results of these alternative scenarios were collectively evaluated anew and it was then possible to select a set of feasible scenarios stemming from current actors? perceptions and practices and to suggest alternative sylvopastoral management based on innovative practices. The paper underlines the usefulness of the representation of viewpoints in that it allowed for scenario description and impact assessment of the compared management strategies. It also shows how the step-by-step approach contributed to improve decision-making by National Park managers.

Suggested Citation

  • Michel Etienne & Christophe Le Page & Mathilde Cohen, 2003. "A Step-By-Step Approach to Building Land Management Scenarios Based on Multiple Viewpoints on Multi-Agent System Simulations," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 6(2), pages 1-2.
  • Handle: RePEc:jas:jasssj:2003-11-1
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    Cited by:

    1. Nicola Lettieri, 2016. "Computational Social Science, the Evolution of Policy Design and Rule Making in Smart Societies," Future Internet, MDPI, vol. 8(2), pages 1-17, May.
    2. Asseng, S. & Dray, A. & Perez, P. & Su, X., 2010. "Rainfall–human–spatial interactions in a salinity-prone agricultural region of the Western Australian wheat-belt," Ecological Modelling, Elsevier, vol. 221(5), pages 812-824.
    3. Riccardo Boero & Flaminio Squazzoni, 2005. "Does Empirical Embeddedness Matter? Methodological Issues on Agent-Based Models for Analytical Social Science," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 8(4), pages 1-6.
    4. Tanatorn Tanantong & Monchai Parnkow, 2022. "A Survey of Automatic Text Classification Based on Thai Social Media Data," International Journal of Knowledge and Systems Science (IJKSS), IGI Global, vol. 13(1), pages 1-25, January.
    5. 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.
    6. Flaminio Squazzoni, 2010. "The impact of agent-based models in the social sciences after 15 years of incursions," History of Economic Ideas, Fabrizio Serra Editore, Pisa - Roma, vol. 18(2), pages 197-234.
    7. Lucie Clavel & Marie-Hélène Charron & Olivier Therond & Delphine Leenhardt, 2012. "A Modelling Solution for Developing and Evaluating Agricultural Land-Use Scenarios in Water Scarcity Contexts," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 26(9), pages 2625-2641, July.
    8. Minh Nguyen-Duc & Alexis Drogoul, 2007. "Using Computational Agents to Design Participatory Social Simulations," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 10(4), pages 1-5.
    9. Kelley, Hugh & Evans, Tom, 2011. "The relative influences of land-owner and landscape heterogeneity in an agent-based model of land-use," Ecological Economics, Elsevier, vol. 70(6), pages 1075-1087, April.
    10. Olivier Barreteau & G. Abrami, 2007. "Variable time scales, agent-based models, and role-playing games: The PIEPLUE river basin management game," Post-Print hal-00453892, HAL.

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