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Simulation models in farming systems research: potential and challenges

posted 6 Jun 2012, 01:38 by Giuseppe Feola   [ updated 18 Jan 2014, 13:50 ]

Feola, G., Sattler, C., Saysel, A.K. Simulation models in farming systems research: potential and challenges. In: Darnhofer, I., Gibbon, D., Dedieu, B. (Eds.), The farming systems approaches into the 21st century: The new dynamic. Springer.


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Abstract

Integrated simulation models can be useful tools in farming system research. This chapter reviews three commonly used approaches, i.e. linear programming, system dynamics and agent-based models. Applications of each approach are presented and strengths and drawbacks discussed. We argue that, despite some challenges, mainly related to the integration of different approaches, model validation and the representation of human agents, integrated simulation models contribute important insights to the analysis of farming systems. They help unravelling the complex and dynamic interactions and feedbacks among bio-physical, socio-economic, and institutional components across scales and levels in farming systems. In addition, they can provide a platform for integrative research, and can support transdisciplinary research by functioning as learning platforms in participatory processes.

Keywords: Simulation models - Farming Systems - System Dynamics - Linear Programming - Agent-based Modelling - Learning - Participation