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Identification of Key Areas and Early-Warning Points for Ecological Protection and Restoration in the Yellow River Source Area Based on Ecological Security Pattern

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  • Shiru Wang

    (Department of Geological Engineering, Qinghai University, Xining 810016, China
    Provincial Key Laboratory of Cenozoic Resources and Environment on the Northern Rim of the Qinghai—Tibet Plateau, Qinghai University, Xining 810016, China)

  • Qian Song

    (Department of Geological Engineering, Qinghai University, Xining 810016, China
    Provincial Key Laboratory of Cenozoic Resources and Environment on the Northern Rim of the Qinghai—Tibet Plateau, Qinghai University, Xining 810016, China)

  • Jianyun Zhao

    (Department of Geological Engineering, Qinghai University, Xining 810016, China
    Provincial Key Laboratory of Cenozoic Resources and Environment on the Northern Rim of the Qinghai—Tibet Plateau, Qinghai University, Xining 810016, China)

  • Zhibo Lu

    (Department of Geological Engineering, Qinghai University, Xining 810016, China
    Provincial Key Laboratory of Cenozoic Resources and Environment on the Northern Rim of the Qinghai—Tibet Plateau, Qinghai University, Xining 810016, China)

  • Haoxiang Zhang

    (Department of Geological Engineering, Qinghai University, Xining 810016, China
    Provincial Key Laboratory of Cenozoic Resources and Environment on the Northern Rim of the Qinghai—Tibet Plateau, Qinghai University, Xining 810016, China)

Abstract

The Yellow River Source Area is located in the ecological protection and restoration area of the Sanjiangyuan in China, which has been deteriorating as a result of human-caused overgrazing and the grassland destruction caused by plateau rats and rabbits, as well as the influence of other natural factors. The Yellow River Source Area is an important area that implements ecological restoration and protection in the Three Rivers Source Region, where the ecologically vulnerable areas that are of great significance to the implementation of ecological restoration in national land space should be identified and the early warning should be extended. This measure can help us identify potential ecological problems and take timely and targeted protection measures to ensure the health and sustainable development of the ecosystem in the Yellow River Source Area. Therefore, an in-depth understanding of the ecological vulnerability of the Yellow River Source Area and the establishment of an early warning mechanism are of vital importance for the protection and restoration of the ecology of the national space in the Yellow River Source Area. Aiming to comprehensively delimit ecological restoration areas in the Yellow River Source Area and provide an early warning, this study applies the MSPA method to identify ecological source areas and uses a patch importance index to identify the importance of ecological source areas, along with extracting potential ecological corridors by using the MCR model, screening important ecological corridors by using the gravity model as a criterion, and simulating land cover changes in 2030 under the limitations of ecological security pattern by using the PLUS model. The results show that: (1) 154 potential ecological corridors were extracted based on the MCR model, with a total length of 7891.90. (2) The total area of the landscape types in the Yellow River Source Area was 12,301 based on MSPA analysis, including the 6899.57 of core area. (3) Based on the PLUS model, the area of farmland and forest in the study area will decrease, while the grassland area will increase. According to the studies, the grassland in the study area expands in a circular pattern towards the surrounding wetland and water area, threatening the ecological sources and corridors. In summary, the study delimits one protection zone in the ecological source land and two core ecological restoration zones and points out the early warning points in the ecological protection space. The delimitation and instruction provide specific spatial guidance for the protection and restoration of ecosystems in order to promote ecological sustainability.

Suggested Citation

  • Shiru Wang & Qian Song & Jianyun Zhao & Zhibo Lu & Haoxiang Zhang, 2023. "Identification of Key Areas and Early-Warning Points for Ecological Protection and Restoration in the Yellow River Source Area Based on Ecological Security Pattern," Land, MDPI, vol. 12(8), pages 1-20, August.
    • Handle: RePEc:gam:jlands:v:12:y:2023:i:8:p:1643-:d:1221804
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    References listed on IDEAS

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    1. Shaokun Zhou & Yuhong Song & Yijiao Li & Jing Wang & Lan Zhang, 2022. "Construction of Ecological Security Pattern for Plateau Lake Based on MSPA–MCR Model: A Case Study of Dianchi Lake Area," Sustainability, MDPI, vol. 14(21), pages 1-17, November.
    2. Jiulin Li & Jiangang Xu & Jinlong Chu, 2019. "The Construction of a Regional Ecological Security Pattern Based on Circuit Theory," Sustainability, MDPI, vol. 11(22), pages 1-17, November.
    3. Lingbin Yan & Lifei Yu & Mingtai An & Haijun Su & He Li & Congjun Yuan, 2019. "Explanation of the Patterns, Spatial Relationships, and Node Functions of Biodiversity and Island: An Example of Nature Reserves in Guizhou, Southwest China," Sustainability, MDPI, vol. 11(22), pages 1-16, November.
    4. Xiufeng Cao & Zhaoshun Liu & Shujie Li & Zhenjun Gao, 2022. "Integrating the Ecological Security Pattern and the PLUS Model to Assess the Effects of Regional Ecological Restoration: A Case Study of Hefei City, Anhui Province," IJERPH, MDPI, vol. 19(11), pages 1-19, May.
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    2. Zhongxu Wang & Shengbo Chen & Junqiang Xu & Chao Ren & Yafeng Yu & Zibo Wang & Lei Wang & Yucheng Xu, 2024. "Integrating Ecosystem Service Assessment, Human Activity Impacts, and Priority Conservation Area Delineation into Ecological Management Frameworks," Sustainability, MDPI, vol. 16(24), pages 1-21, December.
    3. Yuchi Cai & Hong Li & Wancong Li, 2024. "Optimization of a “Social-Ecological” System Pattern from the Perspective of Ecosystem Service Supply and Demand: A Case Study of Jilin Province," Land, MDPI, vol. 13(10), pages 1-31, October.

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