Journal of Resources and Ecology >
Farmland Abandonment Research Progress: Influencing Factors and Simulation Model
First author: SONG Wei, E-mail: songw@igsnrr.ac.cn
Received date: 2018-05-22
Accepted date: 2018-12-08
Online published: 2019-07-30
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).
Copyright
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.
SONG Wei , ZHANG Ying . Farmland Abandonment Research Progress: Influencing Factors and Simulation Model[J]. Journal of Resources and Ecology, 2019 , 10(4) : 345 -352 . DOI: 10.5814/j.issn.1674-764X.2019.04.001
Table 1 Main models for the simulation and prediction of farmland abandonment |
Model category | Model name | Applied regions | Quantitative prediction | Spatial distribution/ Abandonment risk | Reference sources |
---|---|---|---|---|---|
Spatial statistical/ quantitative models | Logit model of probability | South Chile | ‒ | + | Díaz et al., 2011 |
Spatial statistical model | Switzerland mountainous areas | ‒ | + | Gellrich and Zimmermann, 2007 | |
PROBAT | ‒ | ‒ | + | Silber and Wytrzens, 2006 | |
Spatial statistical model | Switzerland mountainous areas | ‒ | + | Gellrich et al., 2007b | |
Logistic regression model and Area Under Curve statistics | Slovakia | ‒ | + | Pazur et al., 2014 | |
Multivariate statistical models | Switzerland mountainous areas | ‒ | + | Gellrich et al., 2007a | |
System dynamics models | Dyna-CLUE | Switzerland | + | + | Price et al., 2015 |
FORE-SCE | Pyrenees | + | + | Vacquie et al., 2015 | |
CAPRI and Dyna-CLUE | European Union | + | + | Renwick et al., 2013 |
Note: “+” and “‒” indicate whether the model has a specific function or not, respectively. |
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