中国村域贫困地理格局及其分异机理

贫困与地理环境之间的关系是贫困地理学理论研究的核心。本文以贫困地域系统和区域多维贫困为理论基础,构建了村域贫困化的理论分析框架,以2013年底中国精准扶贫识别的12.4万个贫困村为研究对象,运用空间自相关、核密度分析和地理探测器等方法,刻画了新时期中国贫困村的空间地理格局,定量探测了贫困村地域分异的主导因子,揭示了村域贫困化与地理环境之间的相互作用机理。结果表明：① 贫困化与地理致贫因子相互作用、相互影响,空间上两者的作用路径和表现形式复杂多样。总体上,可从自然和人文2类要素和环境、经济、社会3个维度来综合识别村域致贫因子。地理环境在贫困化过程中发挥着基础性作用,经济要素是重要的致贫因子,社会要素具有贫困放大效应。② 贫困村分布具有明显的空间集聚性特征。全国贫困村空间分布与胡焕庸线和地势三级阶梯所形成的基础地理格局具有高度一致性,村域贫困化具有明显的垂直分异特征和坡度分异特征,在空间上有1个一级核心区、5个二级核心区、7个三级核心区。③ 地形、资源禀赋、劳动力状况、交通条件和公共服务是中国村域贫困化空间分异的主导因子,且省际间各因子驱动大小差异明显。交互探测结果表明,双因子交互驱动力强于单因子作用,交互作用类型以非线性增强为主。

The geographical pattern and differentiational mechanism of rural poverty in China

Poverty eradication is a worldwide concern. Regional impoverishment has been considered to be closely related to the geographical environment. Therefore, the relationship between poverty and geographical environment has become the core content of poverty geography. Based on the theoretical basis of regional multidimensional poverty and impoverished areal system, this study constructed a "poverty-environment-economy-society" analytical framework to examine the nexus between poverty and geo-environment. On this basis, taking 124000 poverty-stricken villages as the research object, this study used the methods of spatial autocorrelation, kernel density analysis and geographical detector to depict the spatial geographical pattern of China's poverty-stricken villages in the new era, quantitatively detect the leading factors of the regional differentiation of poverty-stricken villages, and reveal the interaction mechanism between the village impoverishment and the geographical environment. The main conclusions can be drawn in the following three aspects. First of all, poverty and the geo-environment interact with each other, and the paths and manifestations of the interaction between the two are complex and diverse. In general, factors leading to village poverty can be detected from the two categories of nature and humanities and the three dimensions of environment, economy, and society. Environmental factors play a fundamental role in the evolution of poverty, economic factors are the most direct and important contributor to impoverishment, and social factors have a magnifying effect on poverty. Secondly, the distribution of poor villages in China has obvious spatial agglomeration characteristics. The spatial distribution pattern of poverty-stricken villages across the country is consistent with the basic geographic pattern depicted by the Hu Huanyong Line and the three-level topography, with obvious vertical and slope differentiation characteristics. The poor villages in China are spatially distributed with one first-level core area, five second-level core areas and seven third-level core areas. Last but not least, the spatial distribution pattern of poor villages in China is the result of the interaction of multiple factors. Topography, natural resources endowment, labors, transportation and public services were identified as the main contributors to spatial differentiation of poor villages in China. Interaction detection results indicated that the driving force between two-factor interaction is stronger than that of a single factor, and the interaction types are non-linear enhancement except for topographic factors and location. Facing the 2030 UN Sustainable Development Goals, China needs to establish the long-term mechanism to effectively link up poverty reduction, rural revitalization, ecological civilization construction, territorial space optimization and urban-rural integrated development, so as to stimulate the endogenous development momentum of poverty-stricken areas and promote regional sustainable development.