Simulation models in Farming Systems Research: potential and challenges
Simulation models in Farming Systems Research: potential and challenges
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农业系统研究中的仿真模型：潜力与挑战
DOI：
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发表时间：
2012
期刊：
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通讯作者：
A. K. Saysel
中科院分区：
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作者：
G. Feola;C. Sattler;A. K. Saysel
综合仿真模型是农业系统研究的有效工具。本章回顾了三种常用的方法，即线性规划、系统动力学和基于agent的模型。介绍了每种方法的应用，并讨论了它们的优缺点。我们认为，尽管存在一些挑战，主要涉及不同方法的集成、模型验证和人类代理的表示，但集成仿真模型为农业系统的分析提供了重要的见解。它们有助于揭示农业系统中不同规模和层次的生物物理、社会经济和制度组成部分之间复杂而动态的相互作用和反馈。此外，它们可以为综合研究提供平台，并可以通过在参与式过程中充当学习平台来支持跨学科研究。
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.