Journal of Resources and Ecology ›› 2021, Vol. 12 ›› Issue (2): 280-291.DOI: 10.5814/j.issn.1674-764x.2021.02.014
• Ecosystem Services and Ecological Risks of Land Resource • Previous Articles Next Articles
KUANG Lihua, YE Yingcong, GUO Xi, XIE Wen, ZHAO Xiaomin*()
Received:
2020-10-15
Accepted:
2020-12-26
Online:
2021-03-30
Published:
2021-05-30
Contact:
ZHAO Xiaomin
Supported by:
KUANG Lihua, YE Yingcong, GUO Xi, XIE Wen, ZHAO Xiaomin. Spatiotemporal Variation of Cultivated Land Security and Its Drivers: The Case of Yingtan City, China[J]. Journal of Resources and Ecology, 2021, 12(2): 280-291.
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URL: http://www.jorae.cn/EN/10.5814/j.issn.1674-764x.2021.02.014
Fig. 1 Elevation and administrative divisions of Yingtan City Note: 1. Chengqu; 2. Bailu; 3. Tongjia; 4. Xiabu; 5. Guixi subdistrict Community; 6. Binjiang; 7. Baitian; 8. Erkou; 9. Hetan; 10. Hongtan; 11. Jintan; 12. Leixi; 13. Lengshui; 14. Liukou; 15. Longhushan; 16. Luohe; 17. Pengwan; 18. Shangqing; 19. Sili; 20. Tangwan; 21. Wenfang; 22. Tianlu; 23. Zhangping; 24. Zhiguang; 25. Zhoufang; 26. Chuntao; 27. Dengbu; 28. Huaqiao; 29. Huangzhuang; 30. Huangxi; 31. Jinjiang; 32. Liujiazhan; 33. Maqun; 34. Pingding; 35. Yangxi; 36. Zhongtong; 37. Honghu.
Criteria layer | Indicator layer | Indicator description | Weight | |
---|---|---|---|---|
Quantitative security | Cultivated land retention (n1) | The area of cultivated land in the year / the area of cultivated land in 2015 | 0.3254 | |
Per capita cultivated area (n2) | Cultivated land area / population (ha per person) | 0.3186 | ||
Cultivated land supplement coefficient (n3) | Increased area of cultivated land in the same year / reduced area of cultivated land | 0.3560 | ||
Qualitative security | Natural qualities | Effective soil thickness (n4) | Reflecting the depth of soil effective tillage | 0.0817 |
Soil texture (n5) | Reflecting soil physical properties | 0.0686 | ||
Soil pH (n6) | Reflecting the acidity and alkalinity of cultivated soil | 0.0883 | ||
Soil organic matter (n7) | Reflecting the soil fertility level of cultivated land | 0.1972 | ||
Farming conditions | Irrigation guarantee rate (n8) | Reflecting the ability of irrigation and water conservancy | 0.1750 | |
Drainage condition (n9) | Reflecting the ability of arable land to drain water | 0.1051 | ||
Plot flatness (n10) | Reflecting the steepness of the cultivated land surface | 0.0431 | ||
Road density (n11) | Reflecting road accessibility, Road length / spot area (m ha‒1) | 0.1606 | ||
Cultivated land concentration (n12) | The concentration of cultivated land in space | 0.0804 | ||
Ecological security | Forest coverage (n13) | Forest area / total land area | 0.3381 | |
Proportion of soil erosion area of cultivated land (n14) | Soil erosion area / total cultivated area | 0.1362 | ||
Fertilizer load per unit area (n15) | Fertilizer application rate / cultivated area (kg ha‒1) | 0.1957 | ||
Pesticide load per unit area (n16) | Pesticide application rate / cultivated area (kg ha‒1) | 0.1587 | ||
Heavy metal pollution (n17) | Reflecting the degree of damage by heavy metals | 0.1713 |
Table 1 Detailed structure of the comprehensive index system designed to evaluate cultivated land security
Criteria layer | Indicator layer | Indicator description | Weight | |
---|---|---|---|---|
Quantitative security | Cultivated land retention (n1) | The area of cultivated land in the year / the area of cultivated land in 2015 | 0.3254 | |
Per capita cultivated area (n2) | Cultivated land area / population (ha per person) | 0.3186 | ||
Cultivated land supplement coefficient (n3) | Increased area of cultivated land in the same year / reduced area of cultivated land | 0.3560 | ||
Qualitative security | Natural qualities | Effective soil thickness (n4) | Reflecting the depth of soil effective tillage | 0.0817 |
Soil texture (n5) | Reflecting soil physical properties | 0.0686 | ||
Soil pH (n6) | Reflecting the acidity and alkalinity of cultivated soil | 0.0883 | ||
Soil organic matter (n7) | Reflecting the soil fertility level of cultivated land | 0.1972 | ||
Farming conditions | Irrigation guarantee rate (n8) | Reflecting the ability of irrigation and water conservancy | 0.1750 | |
Drainage condition (n9) | Reflecting the ability of arable land to drain water | 0.1051 | ||
Plot flatness (n10) | Reflecting the steepness of the cultivated land surface | 0.0431 | ||
Road density (n11) | Reflecting road accessibility, Road length / spot area (m ha‒1) | 0.1606 | ||
Cultivated land concentration (n12) | The concentration of cultivated land in space | 0.0804 | ||
Ecological security | Forest coverage (n13) | Forest area / total land area | 0.3381 | |
Proportion of soil erosion area of cultivated land (n14) | Soil erosion area / total cultivated area | 0.1362 | ||
Fertilizer load per unit area (n15) | Fertilizer application rate / cultivated area (kg ha‒1) | 0.1957 | ||
Pesticide load per unit area (n16) | Pesticide application rate / cultivated area (kg ha‒1) | 0.1587 | ||
Heavy metal pollution (n17) | Reflecting the degree of damage by heavy metals | 0.1713 |
Feature class | Driver | Instruction | Predicted influence direction |
---|---|---|---|
Natural factors | The effective accumulated temperature (X1) | Sum of the average temperature>10 ℃ per year | + |
Precipitation (X2) | Unit: mm | + | |
Socio-economic factors | Per capita income of farmers (X3) | Changes in farmers’ income levels | + |
Agricultural mechanization level (X4) | Unit: ha per agricultural machine | + | |
Policy factors | Investment in environmental governance as a proportion of GDP (X5) | Environmental governance investment / GDP | + |
Protection of cultivated land (X6) | Increased area of cultivated land / reduced area of cultivated land | + | |
Input of agricultural technicians (X7) | Unit: ha per person | + |
Table 2 Preliminary selection of the drivers of changes in cultivated land security
Feature class | Driver | Instruction | Predicted influence direction |
---|---|---|---|
Natural factors | The effective accumulated temperature (X1) | Sum of the average temperature>10 ℃ per year | + |
Precipitation (X2) | Unit: mm | + | |
Socio-economic factors | Per capita income of farmers (X3) | Changes in farmers’ income levels | + |
Agricultural mechanization level (X4) | Unit: ha per agricultural machine | + | |
Policy factors | Investment in environmental governance as a proportion of GDP (X5) | Environmental governance investment / GDP | + |
Protection of cultivated land (X6) | Increased area of cultivated land / reduced area of cultivated land | + | |
Input of agricultural technicians (X7) | Unit: ha per person | + |
Security state | 1995 | 2005 | 2015 |
---|---|---|---|
Generally secure | 8.01 | 6.14 | 5.95 |
Critically secure | 91.32 | 48.96 | 60.72 |
Generally dangerous | 0.67 | 37.55 | 27.38 |
Highly dangerous | 0 | 7.36 | 5.95 |
Table 3 The state of cultivated land security in Yingtan City from 1995 to 2015, expressed as a proportion of its total area in 1995, 2005, and 2015. (%)
Security state | 1995 | 2005 | 2015 |
---|---|---|---|
Generally secure | 8.01 | 6.14 | 5.95 |
Critically secure | 91.32 | 48.96 | 60.72 |
Generally dangerous | 0.67 | 37.55 | 27.38 |
Highly dangerous | 0 | 7.36 | 5.95 |
Fig. 2 Spatial distribution of values for the quantitative security (a-c), qualitative security (d-f), and ecological security (g-i) indexes of cultivated land in Yingtan City, China, in 1995, 2005, and 2015.
Fig. 3 Spatial distribution of values for the comprehensive index of cultivated land security (a-c) and areas with different security levels (d-f) in Yingtan City, China, in 1995, 2005, and 2015. Note: The meaning of the numbers in maps is the same as that of the numbers in Fig. 1.
Variable | The first period (1995-2005) | The second period (2005-2015) | ||||
---|---|---|---|---|---|---|
Coefficient | Std. Error | P | Coefficient | Std. Error | P | |
Constant | 0.307 | 0.066 | <0.01 | ‒0.873 | 0.228 | <0.01 |
l | 0.816 | 0.009 | <0.01 | 0.941 | 0.007 | <0.01 |
The effective accumulated temperature (X1) | ‒0.001 | 0.001 | 0.720 | ‒0.025 | 0.004 | <0.01 |
Precipitation (X2) | ‒0.001 | 0.001 | <0.01 | 1.007 | 0.256 | <0.01 |
Per capita income of farmers (X3) | 0.001 | 0.001 | <0.01 | 0.002 | 0.007 | 0.795 |
Agricultural mechanization level (X4) | 0.001 | 0.002 | 0.921 | 0.036 | 0.018 | 0.046 |
Investment in environmental governance as a proportion of GDP (X5) | 0.357 | 0.034 | <0.01 | 0.073 | 0.019 | <0.01 |
Protection of cultivated land (X6) | 0.003 | 0.001 | <0.01 | 0.001 | 0.002 | <0.01 |
Input of agricultural technicians (X7) | 0.001 | 0.001 | <0.01 | 0.001 | 0.001 | 0.803 |
Table 4 Driving factors of cultivated land security in Yingtan City from 1995 to 2015 based on the SEM
Variable | The first period (1995-2005) | The second period (2005-2015) | ||||
---|---|---|---|---|---|---|
Coefficient | Std. Error | P | Coefficient | Std. Error | P | |
Constant | 0.307 | 0.066 | <0.01 | ‒0.873 | 0.228 | <0.01 |
l | 0.816 | 0.009 | <0.01 | 0.941 | 0.007 | <0.01 |
The effective accumulated temperature (X1) | ‒0.001 | 0.001 | 0.720 | ‒0.025 | 0.004 | <0.01 |
Precipitation (X2) | ‒0.001 | 0.001 | <0.01 | 1.007 | 0.256 | <0.01 |
Per capita income of farmers (X3) | 0.001 | 0.001 | <0.01 | 0.002 | 0.007 | 0.795 |
Agricultural mechanization level (X4) | 0.001 | 0.002 | 0.921 | 0.036 | 0.018 | 0.046 |
Investment in environmental governance as a proportion of GDP (X5) | 0.357 | 0.034 | <0.01 | 0.073 | 0.019 | <0.01 |
Protection of cultivated land (X6) | 0.003 | 0.001 | <0.01 | 0.001 | 0.002 | <0.01 |
Input of agricultural technicians (X7) | 0.001 | 0.001 | <0.01 | 0.001 | 0.001 | 0.803 |
Variable | The first period (1995-2005) | The second period (2005-2015) | ||||
---|---|---|---|---|---|---|
OLS | SLM | SEM | OLS | SLM | SEM | |
Constant | 0.235*** | 0.049*** | 0.307*** | ‒0.618*** | 0.013 | ‒0.873*** |
X1 | ‒0.041*** | ‒0.001 | ‒0.001 | ‒0.043*** | ‒0.026 | ‒0.025*** |
X2 | ‒0.206*** | ‒0.001*** | ‒0.001*** | 0.650*** | 0.007 | 1.007*** |
X3 | 0.026*** | 0.001 | 0.001*** | 0.065*** | 0.006 | 0.002 |
X4 | ‒0.076*** | ‒0.002*** | 0.001 | 0.031*** | 0.008 | 0.036** |
X5 | 0.192*** | 0.083*** | 0.357*** | 0.071*** | 0.013** | 0.073*** |
X6 | 0.081*** | 0.002*** | 0.003*** | 0.015*** | ‒0.001 | 0.001*** |
X7 | 0.002*** | 0.001*** | 0.001*** | 0.003*** | 0.001 | 0.001 |
l | 0.816*** | 0.941*** | ||||
W_Y | 0.798*** | 0.925*** | ||||
Lagrange multiplier (lag) | 18841.548*** | 46087.474*** | ||||
Robust LM (lag) | 249.744*** | 256.640*** | ||||
Lagrange multiplier (error) | 19681.217*** | 53157.894*** | ||||
Robust LM (error) | 10894.13*** | 7327.059*** | ||||
Log likelihood | ‒4587.287 | ‒2049.645 | ‒2004.538 | 1186.945 | 3950.090 | 4056.011 |
Akaike info criterion | 9192.574 | 4119.289 | 4026.716 | ‒2355.890 | ‒7880.172 | ‒7994.020 |
Schwarz criterion | 9265.655 | 4200.490 | 4099.797 | ‒2283.502 | ‒7799.744 | ‒7921.640 |
Table S1 Statistical results for the driver analysis of changes in the cultivated land security in Yingtan City (Jiangxi Province, China) from 1995 to 2015
Variable | The first period (1995-2005) | The second period (2005-2015) | ||||
---|---|---|---|---|---|---|
OLS | SLM | SEM | OLS | SLM | SEM | |
Constant | 0.235*** | 0.049*** | 0.307*** | ‒0.618*** | 0.013 | ‒0.873*** |
X1 | ‒0.041*** | ‒0.001 | ‒0.001 | ‒0.043*** | ‒0.026 | ‒0.025*** |
X2 | ‒0.206*** | ‒0.001*** | ‒0.001*** | 0.650*** | 0.007 | 1.007*** |
X3 | 0.026*** | 0.001 | 0.001*** | 0.065*** | 0.006 | 0.002 |
X4 | ‒0.076*** | ‒0.002*** | 0.001 | 0.031*** | 0.008 | 0.036** |
X5 | 0.192*** | 0.083*** | 0.357*** | 0.071*** | 0.013** | 0.073*** |
X6 | 0.081*** | 0.002*** | 0.003*** | 0.015*** | ‒0.001 | 0.001*** |
X7 | 0.002*** | 0.001*** | 0.001*** | 0.003*** | 0.001 | 0.001 |
l | 0.816*** | 0.941*** | ||||
W_Y | 0.798*** | 0.925*** | ||||
Lagrange multiplier (lag) | 18841.548*** | 46087.474*** | ||||
Robust LM (lag) | 249.744*** | 256.640*** | ||||
Lagrange multiplier (error) | 19681.217*** | 53157.894*** | ||||
Robust LM (error) | 10894.13*** | 7327.059*** | ||||
Log likelihood | ‒4587.287 | ‒2049.645 | ‒2004.538 | 1186.945 | 3950.090 | 4056.011 |
Akaike info criterion | 9192.574 | 4119.289 | 4026.716 | ‒2355.890 | ‒7880.172 | ‒7994.020 |
Schwarz criterion | 9265.655 | 4200.490 | 4099.797 | ‒2283.502 | ‒7799.744 | ‒7921.640 |
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