Assessing the impacts of the changes in farming systems on food security and environmental sustainability of a Chinese rural region under different policy scenarios: an agent-based model

  • Chengcheng Yuan
  • Liming LiuEmail author
  • Xiaoxing Qi
  • Yonghu Fu
  • Jinwei Ye


Since China has undergone a series of economic reforms and implemented opening up policies, its farming systems have significantly changed and have dramatically influenced the society, economy, and environment of China. To assess the comprehensive impacts of these changes on food security and environmental sustainability, and establish effective and environment-friendly subsidy policies, this research constructed an agent-based model (ABM). Daligang Town, which is located in the two-season rice region of Southern China, was selected as the case study site. Four different policy scenarios, i.e., “sharply increasing” (SI), “no-increase” (NI), “adjusted-method” (AM), and “trend” (TD) scenarios were investigated from 2015 to 2029. The validation result shows that the relative prediction errors between the simulated and actual values annually ranged from −20 to 20%, indicating the reliability of the proposed model. The scenario analysis revealed that the four scenarios generated different variations in cropping systems, rice yield, and fertilizer and pesticide inputs when the purchase price of rice and the non-agricultural income were assumed to increase annually by 0.1 RMB per kg and 10% per person, respectively. Among the four different policy scenarios in Daligang, the TD scenario was considered the best, because it had a relatively high rice yield, fairly minimal use of fertilizers and pesticides, and a lower level of subsidy. Despite its limitations, ABM could be considered a useful tool in analyzing, exploring, and discussing the comprehensive effects of the changes in farming system on food security and environmental sustainability.


ABM Environmental sustainability Farming systems Food security Southern China 



We gratefully acknowledge the funding support from the National Nature Science Foundation of China (41130526).


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Copyright information

© Springer International Publishing Switzerland 2017

Authors and Affiliations

  • Chengcheng Yuan
    • 1
    • 2
  • Liming Liu
    • 1
    Email author
  • Xiaoxing Qi
    • 3
  • Yonghu Fu
    • 1
  • Jinwei Ye
    • 1
  1. 1.Department of Land Resources ManagementChina Agricultural UniversityBeijingChina
  2. 2.China Land Surveying and Planning InstituteBeijingChina
  3. 3.School of GovernmentSun Yat-sen UniversityGuangzhouChina

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