Dynamic trends and driving forces of land use intensification of cultivated land in China

doi:10.1007/s11442-015-1152-4

Abstract

Abstract:

The aim of this study is to establish several important factors representing land use intensification in cultivated land (denoted by CII), using a multi-dimensional approach to achieve realistic and practical cultivated land use policies in China. For this reason, the theoretical framework was first built to explain the changes of land use intensification in the cultivated land, and then the variables and index were further developed for the purpose of characterizing the dynamic trends and driving forces of the land use intensification in the cultivated land at the provincial level. The study results indicate that the extent of CII significantly increased during the period of 1996 to 2008, due to the extensive use of fertilizers, machinery and pesticide, increased labor and capital input, and intensified land use. Moreover, the principal component regression results show that the productivity of cultivated land, economic benefits of cultivated land, labor productivity, and land use conversion are the main factors affecting the village development. The first three factors play a positive role, while the last one has a negative effect on the land use intensification in the cultivated land. According to these results, the main policies for sustainable intensification in cultivated land are proposed. First, the sustainable pathways for intensification should be adopted to reduce the unsustainable uses of chemical fertilizer, agricultural chemicals, etc. Second, the conditions for agricultural production should be further improved to increase the cultivated land productivity. Third, it is very necessary and helpful for improving labor productivity and land use efficiency from the viewpoint of accelerated the cultivated land circulation. The last step is to positively affect the production activities of peasants by means of reforming the subsidy standards.

Key words: cultivated land, land use intensification, spatial pattern, factors, China

Guogang WANG, Yansui LIU, Yurui LI, Yangfen CHEN. Dynamic trends and driving forces of land use intensification of cultivated land in China[J].Journal of Geographical Sciences, 2015, 25(1): 45-57.

Figures/Tables 8

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Evaluation index	Metering method	Index description	Effect
Labor input (V₁)	Labor / Cropland area	Labor input level	+
Fertilizer input (V₂)	Fertilizer pure quantity / Cropland area	Fertilizer input intensity	+
Pesticide input (V₃)	Pesticide usage / Cropland area	Pesticide input intensity	+
Mechanical input (V₄)	Mechanical power / Cropland area	Mechanical use level	+
Agricultural expenditure per unit area of cropland (V₅)	Agricultural expenditure / Cropland area	Capital input level	+
Multiple crop index (V₆)	Total cropping area / Cropland area	Cropland use intensity	+
Relative abandoning index % (V₇)	Note^①(①Calculation method of cropland abandoning index: in which AAI is the cropland abandoning index, MCI is the multiple crop index, and i and j respectively represent the region and year. The MCI_i_max indicates the maximum multiple crop index value in Region i. The cropland abandoning index mainly reflects the intensive utilization of cropland in quantity. The greater the AAI value is, the higher the cropland abandoning degree will be, otherwise it will be lower.)	Cropland intensive utilization degree	-
Cropland change rate (V₈)	(Cropland end area - base area) / Cropland end area	Cropland transition degree	-
Effective irrigated area proportion (V₉)	Effective irrigated area / Cropland area	Irrigation fundamental infrastructure status	+

Factors	Rotated value		Variables
Factors	λ	Cumulative variance (%)	V₁	V₂	V₃	V₄	V₅	V₆	V₇	V₈	V₉
1	2.24	24.85	0.57	0.87	0.79	-0.08	0.04	0.64	-0.05	-0.03	0.3
2	1.94	46.41	0.18	-0.07	0.4	0.89	0.04	0.47	0.01	-0.04	0.86
3	1.52	63.32	0.68	0.03	0.25	0.12	-0.92	0.35	0.03	-0.09	-0.06
4	1.08	75.33	-0.12	-0.12	0.04	-0.1	-0.07	-0.21	0.99	-0.05	0.11
5	1.05	87.00	0.17	-0.07	0.03	-0.02	0.2	0.13	-0.05	0.98	-0.02

Variables	Y	X₁	X₂	X₃	X₄	X₅	X₆	X₇	X₈	X₉
Y	1
X₁	0.605^**	1
X₂	0.147^*	0.317^**	1
X₃	-0.125^*	-0.477^**	-0.178^**	1
X₄	0.408^**	-0.017	0.148^**	0.545^**	1
X₅	0.529^**	-0.276^**	-0.1	0.689^**	0.625^**	1
X₆	0.643^**	0.160^**	0.049	0.275^**	0.563^**	0.038	1
X₇	-0.469^**	-0.358^**	-0.323^**	0.347^**	-0.058	0.107	-0.052	1
X₈	0.01	-0.403^**	-0.367^**	0.516^**	0.390^**	0.343^**	0.233^**	0.454^**	1
X₉	0.580^**	0.764^**	0.262^**	-0.182^**	0.210^**	-0.106	0.458^**	-0.151^**	0.046	1

Factors	X₁	X₄	X₅	X₆	X₇	X₉
1	0.925	0.055	-0.13	0.188	-0.148	0.913
2	-0.134	0.758	0.963	0.072	0.025	0.016
3	-0.015	0.568	-0.046	0.962	-0.018	0.306
4	-0.242	-0.078	0.075	-0.005	0.985	0.011

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