Simulation models in farming systems research: potential and challenges Giuseppe Feola 1 , Claudia Sattler 2 , Ali Kerem Saysel 3 1 Department of Geography and Environmental Science, University of Reading, Whiteknights, PO Box 227, Reading, RG6 6AB, United Kingdom Phone: +44 (0)118 378 7496, Fax: +44 (0)118 975 5865, Email: g.feola@reading.ac.uk 2 Leibniz-Centre for Agricultural Landscape Research (ZALF), Institute of Socioeconomics, Eberswalder Str. 84, 15374 Müncheberg, Germany. Phone: +49 33432 82 398, Fax: +49 33432 82 308, E-mail: csattler@zalf.de 3 Institute of Environmental Sciences, Boğaziçi University, 34342 Bebek İstanbul, Turkey. Phone: +90 212 3597252, Fax: +90 212 2575033, E-mail: ali.saysel@boun.edu.tr Abstract Integrated simulation models are growingly adopted in farming system research. This chapter reviews three commonly used approaches, i.e. linear programming, system dynamics and agent/based models. Exemplary applications of each approach are presented and strengths and drawbacks discussed. The chapter argues that, despite some challenges, mainly related to the integration of different approaches, model validation and the representation of human agents, integrated simulation models are a useful tool in farming system research. 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.