Journal of Geographical Sciences >
Farmland use behavior and its influencing factors from the perspective of population migration
Ma Libang (1984‒), Professor, specialized in rural settlement and its spatial reconstruction. E-mail: malb0613@163.com |
Received date: 2023-02-20
Accepted date: 2023-09-07
Online published: 2024-04-24
Supported by
National Natural Science Foundation of China(42271222)
Natural Science Foundation of Gansu Province(22JR5RA130)
Science and Technology Program of Gansu Province(22JR5RA136)
Due to rapid socio-economic development and urban-rural integration, the rural population is increasingly moving away from the primary industry, leading to a noticeable transformation of rural farmland use. This paper analyzed the changes in farmland use and the mechanisms in 213 villages of Longxi county, China in 2020, using multiple linear regression models, based on the aforementioned situation. Analysis revealed main findings: (1) Male and young and middle-aged emigration levels are concentrated in areas with higher and lower values, the emigration of talent is more evenly distributed. Overall, male emigration rates were high in all directions and low in the central area, whereas the young and middle-aged emigration rates exhibited a pattern of high loss in the north and south extremes, and low loss in the central area. The emigration of talent demonstrated a pattern of low losses to the east and high losses to the west of the G30 national highway. (2) Primary farmland use behavior was self-cultivation, then abandonment and finally transfer, with over 60% of the total area in 179 villages used for self-cultivation compared to less than 5% in 164 villages allocated for transfer, while less than 30% of the area in 179 villages was abandoned. (3) Significant differences were observed in the factors that influenced various farmland use behaviors, emigration of male, young and middle-aged and talent were the common influencing factors observed among all three types of farmland uses. The loss of males, young and middle-aged had a significant association with reduced self-cultivation while the emigration of talent led to an increase in self-cultivation use. Increased emigration of all three population constituencies significantly increased farmland transfer and abandonment. The conclusions carry significant theoretical and practical implications for enhancing the coordination of rural human-land relationships and improvement of the understanding of the relationship between population migration and farmland use.
Key words: population migration; farming use; farmland transfer; farmland abandonment
MA Libang , ZONG Yanling , WANG Xiang , SHI Zhihao , ZHANG Wenbo . Farmland use behavior and its influencing factors from the perspective of population migration[J]. Journal of Geographical Sciences, 2024 , 34(3) : 439 -458 . DOI: 10.1007/s11442-024-2212-4
Figure 1 Theoretical framework |
Figure 2 Location of the study area (Longxi county, Dingxi city, Gansu province, China) |
Figure 3 Variable selection |
Figure 4 Population migration characteristics of Longxi county, Gansu province, China |
Figure 5 Farmland use status |
Table 1 Analysis of factors influencing the decision-making behavior toward self-cultivation |
Factor | Model (l) | Model (2) | Model (3) | Model (4) | Model (5) |
---|---|---|---|---|---|
Male emigration | -0.242*** | -0.217*** | -0.192*** | -0.157** | -0.154** |
Young and middle-aged emigration | -0.197*** | -0.151** | -0.141** | -0.115* | -0.105* |
Educated people emigration | 0.113** | 0.084* | 0.078 | 0.088* | 0.082* |
Surplus labor | 0.170*** | 0.153*** | 0.146*** | 0.147*** | |
Non-farm income | 0.140** | 0.094 | 0.099* | ||
Farmland fragmentation | -0.259*** | -0.262*** | |||
Distance to the nearest road | -0.095* | ||||
_cons | 0.989*** | 0.936*** | 0.801*** | 0.833*** | 0.848*** |
N | 213 | 213 | 213 | 213 | 213 |
Note:*, **, *** indicate significance at the 10%, 5% and 1% levels, respectively. |
Table 2 Analysis of the factors influencing the decision-making behavior toward farmland transfer |
Factor | Model (l) | Model (2) | Model (3) | Model (4) | Model (5) |
---|---|---|---|---|---|
Male emigration | 0.050** | 0.050** | 0.050** | 0.050** | 0.038* |
Young and middle-aged emigration | 0.065*** | 0.065*** | 0.065*** | 0.065*** | 0.065*** |
Talent emigration | 0.023* | 0.022* | 0.022* | 0.022* | 0.028** |
Surplus labor | -0.012 | -0.012 | -0.012 | -0.008 | |
Non-farm income | 0.001 | 0.001 | 0.001 | ||
Farmland fragmentation | -0.001 | 0.003 | |||
Distance to the nearest road | 0.019** | ||||
_cons | -0.013* | -0.021 | -0.002 | -0.002 | -0.019 |
N | 213 | 213 | 213 | 213 | 213 |
Note: *, **, *** indicate significance at the 10%, 5% and 1% levels, respectively. |
Table 3 Analysis of the factors influencing the decision-making behavior toward farmland abandonment |
Factor | Model (l) | Model (2). | Model (3) | Model (4) | Model (5) |
---|---|---|---|---|---|
Male emigration | 0.170*** | 0.159** | 0.158** | 0.146** | 0.125* |
Young and middle-aged emigration | 0.140** | 0.142** | 0.131** | 0.136** | 0.140** |
Talent emigration | 0.140*** | 0.118** | 0.111** | 0.097* | 0.101* |
Surplus labor | -0.215*** | -0.208*** | -0.207*** | 0.201*** | |
Non-farm income | 0.134* | 0.131* | 0.128* | ||
Farmland fragmentation | 0.034 | 0.053 | |||
Distance to the nearest road | -0.057 | ||||
_cons | -0.051 | 0.150* | 0.139* | 0.120 | 0.143* |
N | 213 | 213 | 213 | 213 | 213 |
Note: *, **, *** indicate significance at the 10%, 5%, and 1% levels, respectively. |
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