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中国沙漠 ›› 2026, Vol. 46 ›› Issue (4): 266-279.DOI: 10.7522/j.issn.1000-694X.2026.00080

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中国旱区农业生态补偿需求的空间分异特征及优化路径

李晨毓1(), 苗伟明1, 曹璇1, 李随红1, 杨洋2   

  1. 1.兰州财经大学 农林经济管理学院,甘肃 兰州 730101
    2.常州大学 吴敬琏经济学院,江苏 常州 213159
  • 收稿日期:2026-03-29 修回日期:2026-05-12 出版日期:2026-07-20 发布日期:2026-08-27
  • 作者简介:李晨毓(1993—),男,甘肃兰州人,博士,副教授。主要从事生态系统服务、生态补偿研究。E-mail: lichy@lzufe.edu.cn
  • 基金资助:
    甘肃省科技计划青年科技基金项目(23JRRA1187);甘肃省教育厅高等学校创新基金项目(2022B-134)

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

摘要:

中国干旱半干旱区是维护国家粮食安全与生态安全的战略核心区域,农业生态补偿是统筹该区域生态保护与农户生计的关键政策工具。本文以中国旱区涉及的153个市级单元为研究对象,构建了涵盖资源环境约束、农业生计依赖、经济支付能力、社会支撑条件的旱区农业生态补偿需求评价体系,运用熵权-TOPSIS、障碍度模型及方差分解等方法,按照西北、华北、东北分区探索了补偿需求的空间分异、核心限制因子及政策优先级等。结果表明:(1)补偿需求呈现三区各自集聚、整体梯度递减的空间格局,西北集聚区规模最大、连片性最强。(2)补偿需求区域差异显著,西北在均值及高值段居首,东北中位数最高,华北整体最低;需求的影响因素方面,华北与西北水资源主导,东北多因子均衡驱动。(3)第一产业增加值占比是限制需求水平的主要因子,人均用水量是需求水平空间分异的主导因素,水资源类指标对空间分异的总贡献度超70%。(4)补偿应侧重新疆西部等高政策优先级区域。据此,提出分区差异化补偿、补偿标准动态调整、多元资金保障及全流程监管等建议,为旱区农业生态补偿制度优化提供科学依据。

关键词: 旱区农业, 生态补偿, 空间格局, 优化路径

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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