周侃, 樊杰, 孙勇. 长江经济带农村相对贫困格局及区域承载力约束机理[J]. 农业工程学报, 2021, 37(11): 249-258. DOI: 10.11975/j.issn.1002-6819.2021.11.028
    引用本文: 周侃, 樊杰, 孙勇. 长江经济带农村相对贫困格局及区域承载力约束机理[J]. 农业工程学报, 2021, 37(11): 249-258. DOI: 10.11975/j.issn.1002-6819.2021.11.028
    Zhou Kan, Fan Jie, Sun Yong. Spatial pattern of rural relative poverty and constraint mechanism of regional carrying capacity in the Yangtze River Economic Belt[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2021, 37(11): 249-258. DOI: 10.11975/j.issn.1002-6819.2021.11.028
    Citation: Zhou Kan, Fan Jie, Sun Yong. Spatial pattern of rural relative poverty and constraint mechanism of regional carrying capacity in the Yangtze River Economic Belt[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2021, 37(11): 249-258. DOI: 10.11975/j.issn.1002-6819.2021.11.028

    长江经济带农村相对贫困格局及区域承载力约束机理

    Spatial pattern of rural relative poverty and constraint mechanism of regional carrying capacity in the Yangtze River Economic Belt

    • 摘要: 随着中国反贫困重点由消除绝对贫困转变为全面实施乡村振兴、系统解决相对贫困,亟需定量揭示农村相对贫困与区域承载力之间的作用关系,为同步制定缓解相对贫困和增加区域承载力的干预措施提供科学依据。该研究以长江经济带为例,通过农村相对贫困区界定及变化类型识别,从流域、县域及主体功能区多尺度解析2010年以来农村相对贫困区的时空演化过程,建立由土地资源、水资源、环境、生态、灾害和交通6个要素构成的区域承载力指标体系,定量评价农村相对贫困受区域承载力的约束程度及致贫作用。结果表明:长江经济带农村相对贫困空间格局呈总体稳定、局部收缩态势,且以重点生态功能区为主,稳定分布于乌蒙山区、武陵山区、罗霄山区、滇桂黔石漠化区以及滇西边境山区,已消除农村相对贫困的县域主要位于城市群地区或中心城市外围;逻辑斯蒂回归模型估计结果表明,交通、生态和灾害承载力是导致长江经济带农村相对贫困的重要因素,这3类要素约束程度每提升1个等级,发生相对贫困的概率将提高120.85%、30.59%、42.43%,城市化地区、农产品主产区致贫概率仅为生态功能区的19.87%、66.00%。建议基于区域承载力约束程度和地域功能类型,瞄准农民生计资本和区域综合效益增值设计差异化的反贫困政策体系,探索实现农民可持续生计和农村相对贫困区可持续发展的“个体+区域”互动融合发展模式。

       

      Abstract: Rural poverty was a persistent problem in human society, and a common challenge faced by the whole world, where China is no exception. Many untiring efforts have been made to completely eliminate absolute poverty in China to achieve the goal of poverty reduction 10 years ahead of schedule in the United Nations 2030 Agenda for Sustainable Development. After that, the anti-poverty focus has changed into rural relative poverty since 2020. It is necessary to continuously narrow the development gap between urban and rural areas, thereby promoting the rationed sharing of development achievements. It is highly urgent to quantitatively determine the relationship between rural relative poverty and regional carrying capacity, thereby providing a scientific basis for the simultaneous formulation of intervention measures. Taking the Yangtze River Economic Belt (YREB) as the case area, this study aims to explore the spatial pattern of rural relative poverty and the constraint mechanism of regional carrying capacity. Multi-source databases were established using 1 070 county-level administrative units, including the rural social economy, resources, environment, road traffic, and major function zones. The areas of rural relative poverty were defined to identify the change types. The spatio-temporal evolution of rural relative poverty areas since 2010 was then determined from the multi-scale of the river basin, county, and major function zones. At the same time, an index system of regional carrying capacity was established to quantitatively evaluate the level of relative poverty restricted by regional carrying capacity in rural areas of YREB. Six elements were composed of land resources, water resources, environment, ecology, disaster, and transportation. Furthermore, the hierarchical clustering and binary logistic regression model were used to clarify the poverty-causing effect and the constraint level of regional carrying capacity. The results showed that: 1) The number and population size of rural relative poverty areas in the YREB decreased from 353 and 133.666 million in 2010 to 237 and 89.922 million in 2018, indicating that the precise poverty alleviation strategy was achieved to effectively reduce poverty. 2) The spatial pattern of rural relative poverty areas was generally stable and partially shrinking. Key ecological function zones were focused mainly on stable distribution in Wumeng Mountain, Wuling Mountain, Luoxiao Mountain, Yunnan-Guangxi-Guizhou rocky desertification areas, and western Yunnan Border Mountain. The counties without rural relative poverty were located mainly in the urban agglomeration areas or the periphery of central cities. 3) Ordinal logistic regression model showed that transportation, ecology and disaster carrying capacity were the important factors leading to rural relative poverty in the YREB. The probability of rural relative poverty increased by 120.85%, 30.59%, and 42.43%, when the constraint level of three factors increased by one grade. The probability of poverty in urbanized areas and main agricultural production zones was only 19.87% and 66.00% of that in ecological function zones. 4) There was an obvious conjugacy relation among the carrying capacities of each factor in the rural relative poverty areas, showing the characteristics of global transportation dominance and comprehensive constraints of local ecology, disasters, and land resources carrying capacity. It was suggested to design a differentiated anti-poverty policy system using the constraint degree of regional carrying capacity and the type of regional function, thereby realizing the two-way promotion of sustainable development ability on the regional scale, particularly on the individual ability of sustainable livelihood with farmers as the main body.

       

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