中国村域贫困地理格局及其分异机理

doi:10.11821/dlxb202104009

地理学报 ›› 2021, Vol. 76 ›› Issue (4): 903-920.doi: 10.11821/dlxb202104009

中国村域贫困地理格局及其分异机理

周扬¹^,²^,³(), 李寻欢¹^,²^,³, 童春阳¹^,²^,³, 黄晗¹^,²^,³

1.中国科学院地理科学与资源研究所中国科学院区域可持续发展分析与模拟重点实验室,北京 100101
2.中国科学院精准扶贫评估研究中心,北京 100101
3.中国科学院大学,北京 100049

收稿日期:2020-01-05 修回日期:2020-10-19 出版日期:2021-04-25 发布日期:2021-06-25
作者简介:周扬(1984-), 男, 贵州普安人, 副研究员, 硕士生导师, 主要从事农村贫困与乡村振兴研究。E-mail: zhouyang@igsnrr.ac.cn
基金资助:
国家自然科学基金项目(41871183);国家自然科学基金项目(41601172);中国科学院战略性先导科技专项(XDA23070301);中国博士后科学基金项目(2016M591105)

The geographical pattern and differentiational mechanism of rural poverty in China

ZHOU Yang¹^,²^,³(), LI Xunhuan¹^,²^,³, TONG Chunyang¹^,²^,³, HUANG Han¹^,²^,³

1. Key Laboratory of Regional Sustainable Development Modeling, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China
2. Center for Assessment and Research on Targeted Poverty Alleviation, CAS, Beijing 100101, China
3. University of Chinese Academy of Sciences, Beijing 100049, China

Received:2020-01-05 Revised:2020-10-19 Published:2021-04-25 Online:2021-06-25
Supported by:
National Natural Science Foundation of China(41871183);National Natural Science Foundation of China(41601172);Strategic Priority Research Program of the Chinese Academy of Sciences(XDA23070301);China Postdoctoral Science Foundation(2016M591105)

摘要/Abstract

摘要：

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。

关键词: 贫困村, 空间格局, 地理要素, 地理探测器, 贫困地理学, 乡村振兴

Abstract:

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.

Key words: poverty-stricken village, spatial heterogeneity, geographic factor, geodetector, poverty geography, rural revitalization

周扬, 李寻欢, 童春阳, 黄晗. 中国村域贫困地理格局及其分异机理[J]. 地理学报, 2021, 76(4): 903-920.

ZHOU Yang, LI Xunhuan, TONG Chunyang, HUANG Han. The geographical pattern and differentiational mechanism of rural poverty in China[J]. Acta Geographica Sinica, 2021, 76(4): 903-920.

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系统类型	影响要素	指标	指标释义与计算方法
环境系统	地形条件	X1: 海拔(m)	提取贫困村的高程值
		X2: 坡度(°)	提取贫困村的坡度值
		X3: 地形起伏度(m)	提取贫困村的地形起伏度
	气候变化	X4: 气温变化量(℃)	2015年平均气温-2000年平均气温
		X5: 降水变化量(mm)	2015年降水量-2000年降水量
	自然灾害	X6: 地质灾害发生次数(次)	村域内发生地质灾害次数
		X7: 地质灾害造成财产威胁(元)	村域内发生地质灾害造成财产威胁的总和
	生态脆弱性	X8: 归一化植被指数	提取贫困村的NDVI值
		X9: 土壤中度侵蚀及以上的面积(km²)	土壤中度/强度/极强度/剧烈侵蚀的面积
		X10: 植被净初级生产力(gC/km²)	提取贫困村的NPP值
	资源禀赋	X11: 人均耕地面积(km²/人)	贫困村所在网格内的耕地面积/人口
		X12: 年降水量(mm)	提取贫困村的年降水量
社会系统	人口条件	X13: 人口增长速度(%)	(2015年人口-2000年人口)/2000年人口总量
		X14: 人口外流率(%)	(农村户籍人口-农村常住人口)/农村户籍人口
		X15: 劳动力数量(人/户)	贫困村户均家庭劳动力数量
	公共服务	X16: 教育资源可达性(km)	到学校(幼儿园、大中小学)的最短距离
		X17: 医疗资源可达性(km)	到卫生室、卫生院、医院、诊所的最短距离
经济系统	区位条件	X18: 到县域交通干线的最短距离(km)	贫困村到县道/省道的最短距离
		X19: 交通通达度(min)	贫困村到县政府驻点的通行时间
	农业生产条件	X20: 农田生产潜力(kg/hm²)	贫困村内土地的粮食生产潜力
	经济发展水平	Y: 每公里栅格单元人均GDP(元/(km²·人))	2015年每公里栅格单元的GDP/人口

影响因子	q值	影响因子	q值	影响因子	q值	影响因子	q值
X1	0.055^**	X6	0.000	X11	0.005^**	X16	0.021^**
X2	0.010^**	X7	0.000	X12	0.022^**	X17	0.011^**
X3	0.012^**	X8	0.004^**	X13	0.016^**	X18	0.013^**
X4	0.016^**	X9	0.007^**	X14	0.012^**	X19	0.022^**
X5	0.014^**	X10	0.011^**	X15	0.028^**	X20	0.009^**

q值	X1	X2	X3	X4	X5	X9	X10	X12	X13	X14	X15	X16	X17	X18	X19	X20
X1	0.06
X2	0.06	0.01
X3	0.06	0.01	0.01
X4	0.10	0.02	0.03	0.02
X5	0.07	0.03	0.03	0.06	0.01
X9	0.06	0.02	0.02	0.03	0.02	0.01
X10	0.07	0.03	0.04	0.05	0.04	0.02	0.01
X12	0.08	0.04	0.04	0.07	0.05	0.03	0.04	0.02
X13	0.08	0.14	0.14	0.10	0.09	0.13	0.09	0.15	0.02
X14	0.09	0.03	0.04	0.05	0.04	0.03	0.05	0.05	0.09	0.01
X15	0.07	0.04	0.04	0.07	0.05	0.04	0.05	0.06	0.15	0.06	0.03
X16	0.07	0.03	0.04	0.04	0.04	0.02	0.03	0.03	0.06	0.04	0.03	0.02
X17	0.06	0.02	0.02	0.04	0.03	0.02	0.03	0.04	0.06	0.04	0.04	0.02	0.01
X18	0.07	0.02	0.02	0.04	0.03	0.02	0.03	0.03	0.06	0.04	0.04	0.04	0.02	0.01
X19	0.06	0.03	0.03	0.04	0.03	0.03	0.04	0.04	0.04	0.05	0.04	0.02	0.02	0.02	0.02
X20	0.06	0.01	0.02	0.03	0.04	0.02	0.04	0.04	0.13	0.04	0.04	0.03	0.02	0.02	0.03	0.01

中国村域贫困地理格局及其分异机理

The geographical pattern and differentiational mechanism of rural poverty in China

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