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County Ecosystem Health Assessment Based on the VORS Model: A Case Study of 183 Counties in Sichuan Province, China

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  • Rong He

    (Sichuan Academy of Environmental Policy and Planning, No. 1 Keyuan South Road, High-Tech Zone, Chengdu 610041, China)

  • Xintong Huang

    (College of Environment and Ecology, Chongqing University, 83 Shabei Street, Shapingba District, Chongqing 400045, China)

  • Xiaoying Ye

    (Guangdong Provincial Academy of Environmental Science, 335 Dongfeng Road, Yuexiu District, Guangzhou 510030, China)

  • Zhe Pan

    (Sichuan Academy of Environmental Policy and Planning, No. 1 Keyuan South Road, High-Tech Zone, Chengdu 610041, China)

  • Heng Wang

    (Sichuan Academy of Environmental Policy and Planning, No. 1 Keyuan South Road, High-Tech Zone, Chengdu 610041, China)

  • Bin Luo

    (Sichuan Academy of Environmental Policy and Planning, No. 1 Keyuan South Road, High-Tech Zone, Chengdu 610041, China)

  • Dongmei Liu

    (Sichuan Academy of Environmental Policy and Planning, No. 1 Keyuan South Road, High-Tech Zone, Chengdu 610041, China)

  • Xinxin Hu

    (Shanghai Environment and Energy Exchange, Zhongshan North 1st Road, Hongkou District, Shanghai 200800, China)

Abstract

The scientific assessment of the health level of county ecosystems is the basis for formulating county-based sustainable development strategies. In this paper, we take the county areas of Sichuan Province as the evaluation objects and combine the SDGs (the Sustainable Development Goals) to establish a county ecosystem health evaluation index system based on the VORS (Vigor–Organization–Resilience–Service) model. On this basis, we used the entropy weight method, the Moran index method, and the obstacle degree model to analyze the ecosystem health level, spatial distribution characteristics, and obstacles of 183 counties in Sichuan Province. The main results were as follows: (1) A total of 80.87% of the counties in Sichuan Province were at sub-healthy and healthy levels, concentrated in the southeastern part of Sichuan, and 19.13% of the counties were at an unhealthy level, mainly in the Aba, Ganzi, and Liangshan areas. (2) The health levels of county ecosystems in Sichuan Province had high spatial autocorrelation characteristics. The H–H (High–High) agglomeration area and the L–L (Low–Low) agglomeration area had significant agglomeration characteristics, which were distributed in the Cheng-Mian area and the northwestern Sichuan area, respectively. (3) The key indicators restricting the healthy development of urban ecosystems in Sichuan counties are economic vitality, economic resilience, and quality of life, all of which belong to the economic subsystems, with obstacles reaching 17.25%, 16.68%, and 13.52%, respectively. This study can provide theoretical and methodological support for research into ecosystem health evaluations at the county level, and provide a decision-making basis for promoting the health of county ecosystems and coordinating regional development in Sichuan Province.

Suggested Citation

  • Rong He & Xintong Huang & Xiaoying Ye & Zhe Pan & Heng Wang & Bin Luo & Dongmei Liu & Xinxin Hu, 2022. "County Ecosystem Health Assessment Based on the VORS Model: A Case Study of 183 Counties in Sichuan Province, China," Sustainability, MDPI, vol. 14(18), pages 1-17, September.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:18:p:11565-:d:915529
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    References listed on IDEAS

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    1. Yan Wu & Yingmei Wu & Chen Li & Binpin Gao & Kejun Zheng & Mengjiao Wang & Yuhong Deng & Xin Fan, 2022. "Spatial Relationships and Impact Effects between Urbanization and Ecosystem Health in Urban Agglomerations along the Belt and Road: A Case Study of the Guangdong-Hong Kong-Macao Greater Bay Area," IJERPH, MDPI, vol. 19(23), pages 1-20, November.

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