Exploring the regional differences of ecosystem health and its driving factors in China

Jianhua He; Zhenzhen Pan; Dianfeng Liu; Xiaona Guo

doi:10.1016/j.scitotenv.2019.03.465

Exploring the regional differences of ecosystem health and its driving factors in China

Sci Total Environ. 2019 Jul 10:673:553-564. doi: 10.1016/j.scitotenv.2019.03.465. Epub 2019 Apr 2.

Authors

Jianhua He¹, Zhenzhen Pan², Dianfeng Liu³, Xiaona Guo⁴

Affiliations

¹ Wuhan University, School of Resource & Environment Science, 129 Luoyu Road, Wuhan, China; Wuhan University, School of Resource & Environment Science, Key Laboratory of Geographic Information Systems, Ministry Education, 129 Luoyu Road, Wuhan, China. Electronic address: hjianh@whu.edu.cn.
² Wuhan University, School of Resource & Environment Science, 129 Luoyu Road, Wuhan, China. Electronic address: panzhenzhen@whu.edu.cn.
³ Wuhan University, School of Resource & Environment Science, 129 Luoyu Road, Wuhan, China; Wuhan University, School of Resource & Environment Science, Key Laboratory of Geographic Information Systems, Ministry Education, 129 Luoyu Road, Wuhan, China. Electronic address: liudianfeng@whu.edu.cn.
⁴ East China Normal University, School of Geographic Sciences, 500 Dongchuan Road, Shanghai, China.

PMID: 30999096
DOI: 10.1016/j.scitotenv.2019.03.465

Abstract

A better understanding of regional differences in ecosystem health and its driving factors is conducive to ecosystem management and restoration. Although various studies on ecosystem health have been carried out in different regions, few studies have been devoted to the insightful exploration of the spatial heterogeneity of ecosystem health and its driving forces at a national scale. In this study, we used an evaluation framework in terms of vigor, organization, resilience, and ecosystem service functions to assess the ecosystem health level in China from 2000 to 2015. Then, spatial agglomeration and regional differences in ecosystem health were examined using the spatial autocorrelation method and K-means clustering analysis, and the factors driving the regional differences of ecosystem health were explored based on the geographical detector model. Our results showed the following: (1) the ecosystem health level in China spatially increases from the northwest to the southeast, exhibiting significant global spatial autocorrelation and local spatial agglomeration; (2) eleven zones with three types were identified to indicate the regional differences of ecosystem health; (3) In terms of the driving factors, the moisture index and land use intensity contributed 24.5% and 20.7% to the variation in ecosystem health at the national scale. The ecosystem health changes were influenced by the interaction of meteorological and socio-economic factors in most regions with high ecosystem health types. Socio-economic factors act as a bridge that linked and reinforced the other factors in most regions with low and medium ecosystem health types. Ecologically protected factors were found to exert a remarkable impact in the southwestern region and the Loess Plateau region. Our findings can provide more effective and detailed decision-making support for ecosystem conservation and management in China.

Keywords: China; Driving factors; Ecosystem health; Ecosystem health zones; Geographical detector model; Regional differences.