Journal of Resources and Ecology ›› 2019, Vol. 10 ›› Issue (4): 345-352.DOI: 10.5814/j.issn.1674-764X.2019.04.001

Special Issue: 中国耕地资源与粮食安全

• Water and Soil Resources •     Next Articles

Farmland Abandonment Research Progress: Influencing Factors and Simulation Model

SONG Wei1(), ZHANG Ying2,*()   

  1. 1. Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
    2. Chinese Academy of Surveying & Mapping, Beijing 100830, China;
  • Received:2018-05-22 Accepted:2018-12-08 Online:2019-07-30 Published:2019-07-30
  • Contact: ZHANG Ying
  • About author:

    First author: SONG Wei, E-mail: songw@igsnrr.ac.cn

  • Supported by:
    National Natural Science Foundation of China (41501192);The Strategic Priority Research Program of Chinese Academy of Sciences (XDA20040201);Key Laboratory of Earth Observation and Geospatial Information Science of NASG (201807).

Abstract:

Farmland abandonment is a global problem and considered one of the most important areas in land use change research. Farmland abandonment research currently focuses on understanding the factors that affect farmland abandonment and developing scientific models to simulate farmland abandonment. The study reviewed the natural and political factors driving farmland abandonment and summarized the main models for farmland abandonment simulation together with their advantages and disadvantages. We discuss the main ecological effects of farmland abandonment and propose farmland abandonment research directions. The study found that: (1) the influence of labor cost change and ageing labor force on farmland abandonment needs further investigation, (2) simulation models for farmland abandonment must include the decision-making mechanism of individual farmers and focus on macro large-scale abandonment prediction models, and (3) the influence of farmland abandonment on landscape culture must be investigated in detail.

Key words: farmland abandonment, driving factors, model simulation, eco-environmental effects, research progress