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Journal of Desert Research ›› 2026, Vol. 46 ›› Issue (4): 266-279.DOI: 10.7522/j.issn.1000-694X.2026.00080

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Spatial differentiation characteristics and optimization paths of agricultural ecological compensation demand in China's arid regions

Chenyu Li1(), Weiming Miao1, Xuan Cao1, Suihong Li1, Yang Yang2   

  1. 1.School of Agricultural and Forestry Economics and Management,Lanzhou University of Finance and Economics,Lanzhou 730101,China
    2.Wu Jinglian School of Economics,Changzhou University,Changzhou 213159,Jiangsu,China
  • Received:2026-03-29 Revised:2026-05-12 Online:2026-07-20 Published:2026-08-27

Abstract:

China's arid and semi-arid regions represent a strategic core for safeguarding national food security and ecological security. Agricultural ecological compensation is the key policy tool for balancing ecological protection and farmers' livelihoods in these areas. This study examines 153 municipal-level administrative units across China's arid regions and develops an evaluation framework for agricultural ecological compensation demand that integrates four dimensions: resource and environmental constraints, agricultural livelihood dependence, economic payment capacity, and social support conditions. Using the entropy weight-TOPSIS method, obstacle degree model, and variance decomposition analysis, we investigate the spatial differentiation, core limiting factors, and policy priorities of compensation demand, with separate analyses for Northwest, North, and Northeast China. The results show that: (1) Compensation demand forms a spatial pattern of distinct regional clustering with an overall gradient decline, and the Northwest cluster is the largest and most spatially contiguous. (2) Marked regional differences exist in compensation demand: Northwest China has the highest mean value and the largest proportion of high-demand areas, Northeast China shows the highest median value, and North China has the lowest overall demand. In terms of driving factors, water resources dominate demand in North and Northwest China, while multiple factors contribute equally in Northeast China. (3) The share of primary industry in regional GDP is the primary factor limiting overall demand levels, whereas per capita water consumption is the dominant driver of spatial variation. Water resource-related indicators together account for over 70% of the total spatial variance in compensation demand. (4) Compensation resources should be prioritized for high-policy-priority areas such as western Xinjiang. Based on these findings, we propose recommendations including regionally differentiated compensation schemes, dynamic adjustment of compensation standards, diversified funding mechanisms, and whole-process supervision, which provide a scientific basis for optimizing the agricultural ecological compensation system in China's arid regions.

Key words: agriculture of arid regions, ecological compensation, spatial pattern, optimization path

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