PROGRESS IN GEOGRAPHY ›› 2016, Vol. 35 ›› Issue (2): 214-222.doi: 10.18306/dlkxjz.2016.02.008

• Articles | Vulnerability and Disaster • Previous Articles     Next Articles

Quantitative inference method for the relationship between social and ecological vulnerabilities

Ning LI1,2,3,*(), Zhengtao ZHANG1,3, Xiaolin HAO1,3   

  1. 1. State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, Beijing 100875, China
    2. Key Laboratory of environmental Change and Natural Disaster, MOE, Beijing Normal University, Beijing 100875, China
    3. Academy of Disaster Reduction and Emergency Management, Beijing Normal University, Beijing 100875, China
  • Received:2015-08-01 Accepted:2015-11-01 Online:2016-02-10 Published:2016-02-10
  • Contact: Ning LI
  • Supported by:
    National Basic Program of China (973 Program), No.2012CB955402;National Natural Science Foundation of China, No.41171401;the Fundamental Research Funds for the Central Universities, No.310421101


This study systematically analyzed the results of current integrated method for social-ecological vulnerability research and found that the comprehensive index method can represent the overall level of social and ecological vulnerabilities using indicators of the two particular aspects of vulnerability in certain time period. But such method cannot reflect the degree of interaction and direction of influence of indicators. Correlation analysis can indicate a quantitative relationship between indicators, but is unable to identify causality. Least square method can generate variable coefficient of explanatory indicators when the indicators have changed, but due to the subjectivity in selecting indicators as explanatory variables or explained variables, the direction of influence between variables still cannot be determined. Given these problems, this article explores the feasibility of using instrumental variable (IV) method to reveal interactions between social and ecological vulnerabilities. By application in a case study at the country level in China , the result shows that the IV method can reveal the direction of influence between indicators of social vulnerability and ecological vulnerability, which overcomes the problem identified above. From 1980s to 2000s, the impact of ecological vulnerability on social vulnerability (NPPISoVI) decreased, the corresponding significant impact provinces decreased from 5 to 2; the impact of social vulnerability on ecological vulnerability (SoVINPPI) increased, and the corresponding significant impact provinces increased from 1 to 7. A quantitative method that indicates the direction of influence is expected to explain how social vulnerability and ecological vulnerability interact and affect one another.

Key words: social vulnerability, ecological vulnerability, interaction, instrumental variable estimation