都市水源区村域社会−生态系统脆弱性空间分异的地理影响模式——以上海市青浦区为例

以上海市青浦区为例，采用数据包络模型、空间自相关模型、多元Logistic回归模型、地理探测器和层次聚类模型分析该区184个行政村社会?生态系统脆弱性的空间差异及地理影响机制。研究表明：① 基于熵权集结交叉的“投入?产出”效率模型对村域社会?生态系统脆弱性评价结果更具可信度和精确性，2018年行政村社会?生态系统脆弱性空间上呈由东向西逐渐降低的变化趋势，脆弱性均值为0.583；② 地理因素对经济发达村域社会?生态系统脆弱性空间分异仍旧具有重要影响。距上海市中心距离、距淀山湖距离、距青浦区中心距离和水域面积成为影响该区社会?生态系统脆弱性的4种主导地理因素，其地理影响力呈现系统结构空间差异和种类属性替代及程度转化；③ 依据地理因素影响力聚类分析将该区社会?生态系统脆弱性地理因素空间耦合模式分为10种，多地理因素耦合模式是主要决定类型，呈现中部多因素主导和两侧单因素主导并存的多元环状地域决定格局；针对不同类型提出调控区域社会?生态系统脆弱性的可行方式。

Geographical Impact Models of Spatial Differentiation for Social-ecosystem Vulnerability in Urban Water Conservation Area:A Case of Qingpu District of Shanghai

This article introduced the ‘input-output’ efficiency theory and constructed the ‘SEE-PSR’ framework for the analysis of social-ecosystem vulnerability in the village area in Qingpu District of Shanghai. The data envelope model, spatial autocorrelation model, multivariate Logistic regression model, geographical detector and hierarchical cluster model were used to analyze the spatial differences of social-ecosystem vulnerability and its geographical impact mechanism in 184 administrative villages in this area. The results were as follows: 1) The ‘input-output’ efficiency model based on entropy weight aggregation crossover was more reliable and accurate for the evaluation results of village social-ecosystem vulnerability. The vulnerability of the social-ecosystems in the administrative villages showed a trend of gradual decline from east to west, with the average value of vulnerability of 0.583, and the vulnerability of social subsystems became an important reason to limit the decrease of the vulnerability of the social-ecosystems in the region. 2) Geographic factors still had an important impact on the spatial differentiation of social-ecosystem vulnerability in developed villages. The distance from the center of Shanghai, the distance from the Dianshan Lake, the distance from the center of Qingpu District and the area of water area were the four dominant geographical factors affecting the vulnerability of social-ecosystem in this area. The geographical influence presented the spatial difference of system structure, the substitution of type attribute and the transformation of degree. 3) According to the cluster analysis of the influence of geographical factors, the spatial coupling types of social-ecosystem vulnerability factors were divided into 10 types. The multi-geographic factor coupling influence classes were the main decision type, which presented the multi-cyclic regional decision patterns which were dominated by the central multi-factor and co-exist by the single factor on both sides. According to different types, a feasible way to regulate the vulnerability of regional socio-ecological systems was proposed. The results of this study can provide scientific references for urban suburban rural space reconstruction and regional sustainable development with ‘strict protection and vigorous development’ conflict.rban suburban rural space reconstruction and regional sustainable development with ‘strict protection and vigorous development’ conflict.rban suburban rural space reconstruction and regional sustainable development with ‘strict protection and vigorous development’ conflict.