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Vulnerability Assessment and Optimization Countermeasures of the Human–Land Coupling System of the China–Mongolia–Russia Cross-Border Transportation Corridor

Author

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  • Xinyuan Wang

    (Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
    College of Resource and Environment, University of Chinese Academy of Sciences, Beijing 100049, China)

  • Hao Cheng

    (Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China)

  • Fujia Li

    (Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China)

  • Dashtseren Avirmed

    (Institute of Geography and Geo-ecology, Mongolian Academy of Sciences, Ulaanbaatar 15170, Mongolia)

  • Bair Tsydypov

    (Baikal Institute of Nature Management, Siberian Branch, Russian Academy of Sciences, Ulan-Ude 670047, Russia)

  • Menghan Zhang

    (Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
    College of Resource and Environment, University of Chinese Academy of Sciences, Beijing 100049, China)

Abstract

In recent years, the conflicts of the human–land coupling system (HLS) in the cross-border transportation corridor areas have become increasingly severe, especially in the China–Mongolia–Russia Cross-Border Transportation Corridor (CMRTC). The vulnerability assessment of the HLS-CMRTC is the key scientific issue for regional sustainable development. Based on the nearly 20 years of a scientific expedition, we set the CMRTC as the study area, constructed the vulnerability assessment index system and quantitative model, assessed the vulnerability of the HLS-CMRTC, revealed the key influencing factors, divided vulnerability risk prevention zones, and proposed the targeted optimization countermeasures. This study found that: (1) The overall vulnerability pattern of the HLS-CMRTC showed a vulnerability level gradually increasing from south to north. (2) Permafrost instability risk, land desertification, temperature increase, and backward social development were key influences. (3) Vulnerability risk prevention zones were divided into four priority and two general zones. The targeted optimization countermeasures were proposed, such as establishing an ecological security barrier, carrying out collaborative ecological risk monitoring, and early warning. The conclusions could provide a decision-making basis for the study area to reduce the vulnerability of the HLS. They could also provide reference and scientific support for achieving sustainable development of the economy and environment in similar regions of the world.

Suggested Citation

  • Xinyuan Wang & Hao Cheng & Fujia Li & Dashtseren Avirmed & Bair Tsydypov & Menghan Zhang, 2023. "Vulnerability Assessment and Optimization Countermeasures of the Human–Land Coupling System of the China–Mongolia–Russia Cross-Border Transportation Corridor," Sustainability, MDPI, vol. 15(16), pages 1-19, August.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:16:p:12606-:d:1221152
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    References listed on IDEAS

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    1. Hanlong Gu & Chongyang Huan & Fengjiao Yang, 2023. "Spatiotemporal Dynamics of Ecological Vulnerability and Its Influencing Factors in Shenyang City of China: Based on SRP Model," IJERPH, MDPI, vol. 20(2), pages 1-26, January.
    2. Yue Chen & Kangning Xiong & Xiaodong Ren & Cai Cheng, 2021. "Vulnerability Comparison between Karst and Non-Karst Nature Reserves—With a Special Reference to Guizhou Province, China," Sustainability, MDPI, vol. 13(5), pages 1-12, February.
    3. Alexey Bilgaev & Erzhena Sadykova & Fujia Li & Anna Mikheeva & Suocheng Dong, 2021. "Socio-Economic Factor Impact on the Republic of Buryatia (Russia) Green Economic Development Transition," IJERPH, MDPI, vol. 18(20), pages 1-17, October.
    4. Dong Li & Chongyang Huan & Jun Yang & Hanlong Gu, 2022. "Temporal and Spatial Distribution Changes, Driving Force Analysis and Simulation Prediction of Ecological Vulnerability in Liaoning Province, China," Land, MDPI, vol. 11(7), pages 1-25, July.
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