Influence of the variation in rural population on farmland preservation in the rapid urbanization area of China

doi:10.1007/s11442-021-1901-5

Abstract

Abstract:

In the past 40 years, cultivated land has faced the continued anthropogenic interference, which has become a significant issue for cultivated land preservation during rapid urbanization. The purpose of this research was to reveal the spatio-temporal evolutionary characteristics of cultivated land and the correlation between rural population variation and farmland change in China. Fifty county-level administrative units in Zhejiang Province were selected as the study area wherein spatio-temporal evolution comparative analysis for every 5 years from 2000 to 2015 was conducted. This study used the pool method to estimate the impacts of the rural population variation, average slope, average elevation, rural residential disposable income, primary industry proportion, and road density on farmland utilization efficiency from the spatial perspective, which is represented by landscape metrics including the mean patch size, edge density, area weighted mean shape index, and area weighted mean patch fractal dimension. This study showed that the cultivated land landscape index continued to rise after 2000 and then started decreasing after 2010, indicating a reduction in human interference after 2010. The spatial variation of rural population of all county-level administrative units decreased from 2000 to 2010, and 62% of them began to increase after 2010. The regression analysis results showed that the spatial variation of rural population was significantly and negatively correlated with the cultivated land landscape while the rural residential disposable income, average slope and primary industry proportion were all significantly and positively related to the cultivated land landscape index. The results implied that the loss of the agricultural labor force and the difficulty of sloping farmlands adapting to mechanized farming were unconducive to farmland utilization efficiency improvement, and the increase in nonagricultural activities in rural areas would increase the difficulty of cultivated land preservation. Our analysis suggests that local governments should improve the production efficiency of fragmented land or strengthen the construction control of housing and facilities in rural areas according to their regional urbanization development situation.

Key words: rural population, farmland, landscape metrics, Zhejiang Province

ZHANG Mingyu, CHEN Qiuxiao, ZHANG Kewei. Influence of the variation in rural population on farmland preservation in the rapid urbanization area of China[J].Journal of Geographical Sciences, 2021, 31(9): 1365-1380.

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References 51

[1]	Chen C R, 2019. Untitled land, occupational choice, and agricultural productivity. American Economic Journal: Macroeconomics, 9(4): 91-121.
[2]	Chien S S, 2015. Local farmland loss and preservation in China: A perspective of quota territorialization. Land Use Policy, 49: 65-74. doi: 10.1016/j.landusepol.2015.07.010
[3]	Gao C L, Cheng L, 2020. Tourism-driven rural spatial restructuring in the metropolitan fringe: An empirical observation. Land Use Policy, 95: 104609. doi: 10.1016/j.landusepol.2020.104609
[4]	Gao J, Wu B, 2017. Revitalizing traditional villages through rural tourism: A case study of Yuanjia Village, Shaanxi Province, China. Tourism Management, 63: 223-233. doi: 10.1016/j.tourman.2017.04.003
[5]	Han H B, Zhang X Y, 2020. Exploring environmental efficiency and total factor productivity of cultivated land use in China. Science of The Total Environment, 726: 138434. doi: 10.1016/j.scitotenv.2020.138434
[6]	Hao P, Sliuzas R, Geertman S, 2011. The development and redevelopment of urban villages in Shenzhen. Habitat International, 35(2): 214-224. doi: 10.1016/j.habitatint.2010.09.001
[7]	Jiang G H, Zhang R J, Ma W Q et al., 2017 Cultivated land productivity potential improvement in land consolidation schemes in Shenyang, China: Assessment and policy implications. Land Use Policy, 68: 80-88. doi: 10.1016/j.landusepol.2017.07.001
[8]	Jiang L, Guo S, Wang G et al., 2020a. Changes in agricultural land requirements for food provision in China 2003-2011: A comparison between urban and rural residents. Science of the Total Environment, 725: 138293. doi: 10.1016/j.scitotenv.2020.138293
[9]	Jiang P H, Li M C, Liang C, 2020b. Dynamic response of agricultural productivity to landscape structure changes and its policy implications of Chinese farmland conservation. Resources Conservation and Recycling, 156: 104724. doi: 10.1016/j.resconrec.2020.104724
[10]	Jiang P H, Li M C, Lv J C, 2019. The causes of farmland landscape structural changes in different geographical environments. Science of The Total Environment, 685: 667-680. doi: 10.1016/j.scitotenv.2019.05.383
[11]	Li Y H, Westlund H, Liu Y S, 2019. Why some rural areas decline while some others not: An overview of rural evolution in the world. Journal of Rural Studies, 68: 135-143. doi: 10.1016/j.jrurstud.2019.03.003
[12]	Li Y R, Liu Y S, Long H L et al., 2014. Community-based rural residential land consolidation and allocation can help to revitalize hollowed villages in traditional agricultural areas of China: Evidence from Dancheng County, Henan Province. Land Use Policy, 39: 188-198. doi: 10.1016/j.landusepol.2014.02.016
[13]	Liang X Y, Li Y B, Ran C H et al., 2020. Study on the transformed farmland landscape in rural areas of southwest China: A case study of Chongqing. Journal of Rural Studies, 76: 272-285. doi: 10.1016/j.jrurstud.2020.04.017
[14]	Lin S N, Li Z G, 2019. City profile: Wenzhou - A model city of transitional China. Cities, 95: 102393. doi: 10.1016/j.cities.2019.102393
[15]	Liu J, Jin X B, Xu W Y et al., 2019. Influential factors and classification of cultivated land fragmentation, and implications for future land consolidation: A case study of Jiangsu Province in eastern China. Land Use Policy, 88: 104185. doi: 10.1016/j.landusepol.2019.104185
[16]	Liu L, Xu X, Chen X, 2014. Assessing the impact of urban expansion on potential crop yield in China during 1990-2010. Food Security, (7): 33-43.
[17]	Liu X W, Zhao C L, Song W, 2017. Review of the evolution of cultivated land protection policies in the period following China’s reform and liberalization. Land Use Policy, 67: 660-669. doi: 10.1016/j.landusepol.2017.07.012
[18]	Liu Z, Liu S H, Jin H R et al., 2017. Rural population change in China: Spatial differences, driving forces and policy implications. Journal of Rural Studies, 51: 189-197. doi: 10.1016/j.jrurstud.2017.02.006
[19]	Long H L, Li Y R, Liu Y S et al., 2012. Accelerated restructuring in rural China fueled by ‘increasing vs. decreasing balance’ land-use policy for dealing with hollowed villages. Land Use Policy, 29(1): 11-22. doi: 10.1016/j.landusepol.2011.04.003
[20]	Lu X, Huang X J, Zhong T Y et al., 2011. Review on the research of farmland fragmentation in China. Journal of Natural Resources, 26: 530-540. (in Chinese)
[21]	Mandelbrot B, 1983. The Fractal Geometry of Nature. New York: W. H. Freeman and Co., 460.
[22]	O’Neill R V, Krummel J R, Gardner R H et al., 1988. Indices of landscape pattern. Landscape Ecology, 1: 153-162. doi: 10.1007/BF00162741
[23]	Pei H, Wei Y, Wang X et al., 2014. Method of cultivated land landscape ecological security evaluation and its application. Transactions of the CSAE, China, 30(9): 212-219. (in Chinese)
[24]	Shannon C E, Weaver W, 1962. The Mathematical Theory of Communication. Urbana: University of Illinois Press, IL. I25.
[25]	Skinner W K, Kuhn G R, Joseph A E, 2001. Agricultural land protection in China: A case study of local governance in Zhejiang Province. Land Use Policy, 18(4): 329-340. doi: 10.1016/S0264-8377(01)00026-6
[26]	Sklenicka P, 2016. Classification of farmland ownership fragmentation as a cause of land degradation: A review on typology, consequences, and remedies. Land Use Policy, 57: 694-701. doi: 10.1016/j.landusepol.2016.06.032
[27]	Sklenicka P, Salek M, 2008. Ownership and soil quality as sources of agricultural land fragmentation in highly fragmented ownership patterns. Landscape Ecology, 23: 299-311. doi: 10.1007/s10980-007-9185-4
[28]	Song W, 2014. Decoupling cultivated land loss by construction occupation from economic growth in Beijing. Habitat International, 43: 198-205. doi: 10.1016/j.habitatint.2014.03.002
[29]	Tischendorf L, 2001. Can landscape indices predict ecological processes consistently? Landscape Ecology, 16: 235-254. doi: 10.1023/A:1011112719782
[30]	Wang H, Tao R, Wang L L et al., 2010. Farmland preservation and land development rights trading in Zhejiang, China. Habitat International, 34(4): 454-463. doi: 10.1016/j.habitatint.2009.12.004
[31]	Wang X, Xin L, Tan M et al., 2020. Impact of spatiotemporal change of cultivated land on food-water relations in China during 1990-2015. Science of The Total Environment, 716: 137119. doi: 10.1016/j.scitotenv.2020.137119
[32]	Wang Y H, Li X B, Xin L J et al., 2020. Farmland marginalization and its drivers in mountainous areas of China. Science of The Total Environment, 719: 135132. doi: 10.1016/j.scitotenv.2019.135132
[33]	Wu Y Z, Shan L P, Guo Z et al., 2017. Cultivated land protection policies in China facing 2030: Dynamic balance system versus basic farmland zoning. Habitat International, 69: 126-138. doi: 10.1016/j.habitatint.2017.09.002
[34]	Xiang D, Chen J K, Tripe D et al., 2019. Family firms, sustainable innovation and financing cost: Evidence from Chinese hi-tech small and medium-sized enterprises. Technological Forecasting and Social Change, 144: 499-511. doi: 10.1016/j.techfore.2018.02.021
[35]	Xiao R, Liu Y, Huang X, 2018. Exploring the driving forces of farmland loss under rapid urbanization using binary logistic regression and spatial regression: A case study of Shanghai and Hangzhou Bay. Ecological Indicators, 95: 455-467. doi: 10.1016/j.ecolind.2018.07.057
[36]	Xu H G, Huang X Y, Zhang Q F, 2018. Tourism development and local borders in ancient villages in China. Journal of Destination Marketing & Management, 9: 330-339.
[37]	Yan F, Zhang S, Kuang W et al., 2016. Comparison of cultivated landscape changes under different management modes: A case study in Sanjiang Plain. Sustainability, 8(10): 16. doi: 10.3390/su8010016
[38]	Yang H, Li X B, 2000. Cultivated land and food supply in China. Land Use Policy, 17(2): 73-88. doi: 10.1016/S0264-8377(00)00008-9
[39]	Ye J Z, 2015. Land transfer and the pursuit of agricultural modernization in China. Journal of Agrarian Change, 15(3): 314-337. doi: 10.1111/joac.2015.15.issue-3
[40]	York A M, Shrestha M, Boone C G et al., 2011. Land fragmentation under rapid urbanization: A cross-site analysis of southwestern cities. Urban Ecosystems, 14(3): 429-455. doi: 10.1007/s11252-011-0157-8
[41]	Yu D, Wang D Y, Lin W B et al., 2018. Decreased landscape ecological security of peri-urban cultivated land following rapid urbanization: An impediment to sustainable agriculture. Sustainability, 10: 394. doi: 10.3390/su10020394
[42]	Yu M, Yang Y J, Chen F et al., 2019. Response of agricultural multifunctionality to farmland loss under rapidly urbanizing processes in Yangtze River Delta, China. Science of The Total Environment, 666: 1-11. doi: 10.1016/j.scitotenv.2019.02.226
[43]	Yu X W, Zhuo Y, Liu H et al., 2020. Degree of desertification based on normalized landscape index of sandy lands in Inner Mongolia, China. Global Ecology and Conservation, 23: e01132. doi: 10.1016/j.gecco.2020.e01132
[44]	Zeng H, Yu X F, Zhang J F, 2019. Urban village demolition, migrant workers' rental costs and housing choices: Evidence from Hangzhou, China. Cities, 94: 70-79. doi: 10.1016/j.cities.2019.05.029
[45]	Zhang R J, Jiang G H, Zhang Q, 2019. Does urbanization always lead to rural hollowing? Assessing the spatio-temporal variations in this relationship at the county level in China 2000-2015. Journal of Cleaner Production, 220: 9-22. doi: 10.1016/j.jclepro.2019.02.148
[46]	Zhang T, Zhu Y, Lin L Y, 2017. The residential location choices of returned migrant workers in the context of local urbanization: A case study of Yongcheng City in Henan Province. Economic Geography, 37(4): 84-91. (in Chinese)
[47]	Zhang X Y, Cai Z L, Li G E et al., 2020. Assessment of determinants of cultivated land fragmentation and its impacts on rural income. Science of Surveying and Mapping, 45: 134-141. (in Chinese)
[48]	Zhong T Y, Huang X J, Zhang X Y et al., 2011. Temporal and spatial variability of agricultural land loss in relation to policy and accessibility in a low hilly region of southeast China. Land Use Policy, 28: 762-769. doi: 10.1016/j.landusepol.2011.01.004
[49]	Zhou J H, Yan Z, Wang Y, 2013. Improving quality and safety of aquatic products: A case study of self-inspection behavior from export-oriented aquatic enterprises in Zhejiang Province, China. Food Control, 33(2): 528-535. doi: 10.1016/j.foodcont.2013.03.019
[50]	Zhou Z X, Li J, 2015. The correlation analysis on the landscape pattern index and hydrological processes in the Yanhe watershed, China. Journal of Hydrology, 524: 417-426. doi: 10.1016/j.jhydrol.2015.02.028
[51]	Zhu Y, 2015. In situ urbanization in China: Processes, contributing factors, and policy implications. Background paper for the World Migration Report 2015: Migrants and Cities: New Partnerships to Manage Mobility. IOM, Geneva.

Landscape indicator	Unit	Correlation with human interference	Weight
MPS	ha	Negative	0.4624
ED	km/ha	Positive	0.1762
AWMSI	-	Negative	0.2806
AWMPFD	-	Negative	0.0808

Control variables	Year	Min.	Max.	Mean	Standard deviation
Average slope (°)	2005, 2010, 2015	2.10	25.53	15.69	6.33
Average elevation (m)	2005, 2010, 2015	7.58	875.69	293.26	214.38
Primary industry proportion (%)	2015	0.02	0.15	0.08	0.04
	2010	0.02	0.20	0.09	0.04
	2005	0.03	0.29	0.12	0.06
Road density (km/km²)	2015	0.46	2.78	1.13	0.47
	2010	0.43	2.67	1.02	0.42
	2005	0.22	0.99	0.51	0.20
Per capita rural residential disposable income (RMB yuan)	2015	12973.00	29177.00	20483.08	5508.01
	2010	6010.00	15513.00	10273.64	3118.16
	2005	2966.00	8542.00	5758.98	1788.75

Indicator	Amount	Min.	Max.	Mean	Standard deviation
RPSV in stage 1	50	-0.804	0.246	-0.468	0.271
RPSV in stage 2	50	-0.918	-0.293	-0.673	0.138
RPSV in stage 3	50	-0.854	0.986	0.185	0.596
CLI in stage 1	50	0.057	0.743	0.483	0.164
CLI in stage 2	50	0.099	0.781	0.503	0.173
CLI in stage 3	49	0.000	0.759	0.461	0.185

Test method	Related models	Test results
F test	FE model and POOL model	F (46,94)=1.302, P=0.140
BP test	RE model and POOL model	χ²(1)=0.548, P=0.459
Hausman test	FE model and RE model	χ²(4)=4.586, P=0.332

Variables	POOL model	FE model	RE model
Intercept	0.117 (1.952*)	0.341 (3.600***)	0.109 (1.775*)
RPSV	-0.075 (-2.687***)	-0.061 (-1.882*)	-0.073 (-2.655***)
RDI	0.000 (1.873*)	0.000 (0.508)	0.000 (1.699*)
AS	0.016 (4.216***)	0.050 (1.043)	0.016 (4.065***)
AE	0.000 (0.544)	0.583 (0.957)	0.000 (0.428)
RD	-0.022 (-0.625)	0.000 (0.000***)	-0.012 (-0.354)
PIP	0.420 (1.851*)	0.000 (0.000***)	0.421 (1.738*)
R²	0.544	0.069	0.503
Adjust R²	0.525	-0.446	0.482
Test	F (6140)=27.842, P=0.000	F (4,94)=1.750, P=0.145	χ²(6)=141.826, P=0.000