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Spatially Heterogeneity Response of Critical Ecosystem Service Capacity to Address Regional Development Risks to Rapid Urbanization: The Case of Beijing-Tianjin-Hebei Urban Agglomeration in China

Author

Listed:
  • Kaiping Wang

    (School of Landscape Architecture, Beijing Forestry University, 35 Qinghua East Road, Haidian District, Beijing 100083, China)

  • Weiqi Wang

    (School of Landscape Architecture, Beijing Forestry University, 35 Qinghua East Road, Haidian District, Beijing 100083, China)

  • Niyi Zha

    (School of Landscape Architecture, Beijing Forestry University, 35 Qinghua East Road, Haidian District, Beijing 100083, China)

  • Yue Feng

    (School of Landscape Architecture, Beijing Forestry University, 35 Qinghua East Road, Haidian District, Beijing 100083, China)

  • Chenlan Qiu

    (School of Landscape Architecture, Beijing Forestry University, 35 Qinghua East Road, Haidian District, Beijing 100083, China)

  • Yunlu Zhang

    (School of Landscape Architecture, Beijing Forestry University, 35 Qinghua East Road, Haidian District, Beijing 100083, China)

  • Jia Ma

    (School of Landscape Architecture, Beijing Forestry University, 35 Qinghua East Road, Haidian District, Beijing 100083, China)

  • Rui Zhang

    (School of Landscape Architecture, Beijing Forestry University, 35 Qinghua East Road, Haidian District, Beijing 100083, China)

Abstract

Urban agglomerations have become the new spatial unit of global economic competition. The intense socioeconomic activities attributed to the development of urban agglomerations are bound to cause damage to the ecosystem services of these urban agglomerations. This study adopts the Beijing-Tianjin-Hebei urban agglomeration in China as the research object, analyzes the spatiotemporal evolution of its critical ecosystem service capacity to address regional ++-development risks from 2000–2018, and employs the Moran’s I and geographically weighted regression model to explore the spatial correlation and spatial heterogeneity in the responses of urbanization and ecosystem services. The study indicates that (1) from 2000–2018, the ecosystem services of the Beijing-Tianjin-Hebei urban agglomeration exhibit an increase and then a decline, reaching the highest index in 2015; (2) the ecosystem services reveal obvious spatial heterogeneity with the Yan and Taihang Mountains region as the boundary; (3) built-up area ratio, GDP density, and population density exhibit highly obvious negative correlation driving characteristics on ecosystem services; and (4) the construction land ratio exerts a notable impact on areas with a high ecosystem services, while the spatial response of the effect magnitude of the population and GDP densities is largely influenced by intensive, high-pollution and energy-consuming industries. This article also proposes strategies for the optimization of ecological resources and spatial control, which are dedicated to mitigating the negative impacts of rapid urbanization processes on ecosystem services.

Suggested Citation

  • Kaiping Wang & Weiqi Wang & Niyi Zha & Yue Feng & Chenlan Qiu & Yunlu Zhang & Jia Ma & Rui Zhang, 2022. "Spatially Heterogeneity Response of Critical Ecosystem Service Capacity to Address Regional Development Risks to Rapid Urbanization: The Case of Beijing-Tianjin-Hebei Urban Agglomeration in China," Sustainability, MDPI, vol. 14(12), pages 1-21, June.
  • Handle: RePEc:gam:jsusta:v:14:y:2022:i:12:p:7198-:d:837198
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    References listed on IDEAS

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    1. H. Spencer Banzhaf & James Boyd, 2012. "The Architecture and Measurement of an Ecosystem Services Index," Sustainability, MDPI, vol. 4(4), pages 1-32, March.
    2. Gu, Qiwei & Wang, Hongqi & Zheng, Yinan & Zhu, Jingwen & Li, Xiaoke, 2015. "Ecological footprint analysis for urban agglomeration sustainability in the middle stream of the Yangtze River," Ecological Modelling, Elsevier, vol. 318(C), pages 86-99.
    3. Han, Wenyi & Geng, Yong & Lu, Yangsiyu & Wilson, Jeffrey & Sun, Lu & Satoshi, Onishi & Geldron, Alain & Qian, Yiying, 2018. "Urban metabolism of megacities: A comparative analysis of Shanghai, Tokyo, London and Paris to inform low carbon and sustainable development pathways," Energy, Elsevier, vol. 155(C), pages 887-898.
    4. Häyhä, Tiina & Franzese, Pier Paolo, 2014. "Ecosystem services assessment: A review under an ecological-economic and systems perspective," Ecological Modelling, Elsevier, vol. 289(C), pages 124-132.
    5. Wenbo Cai & Tong Wu & Wei Jiang & Wanting Peng & Yongli Cai, 2020. "Integrating Ecosystem Services Supply–Demand and Spatial Relationships for Intercity Cooperation: A Case Study of the Yangtze River Delta," Sustainability, MDPI, vol. 12(10), pages 1-24, May.
    6. Yiting Chen & Zhanbin Li & Peng Li & Yixin Zhang & Hailiang Liu & Jinjin Pan, 2022. "Impacts and Projections of Land Use and Demographic Changes on Ecosystem Services: A Case Study in the Guanzhong Region, China," Sustainability, MDPI, vol. 14(5), pages 1-20, March.
    7. Li Yao & Xiaolu Li & Qiao Li & Jiankang Wang, 2019. "Temporal and Spatial Changes in Coupling and Coordinating Degree of New Urbanization and Ecological-Environmental Stress in China," Sustainability, MDPI, vol. 11(4), pages 1-16, February.
    8. Shen, Jiashu & Li, Shuangcheng & Liang, Ze & Liu, Laibao & Li, Delong & Wu, Shuyao, 2020. "Exploring the heterogeneity and nonlinearity of trade-offs and synergies among ecosystem services bundles in the Beijing-Tianjin-Hebei urban agglomeration," Ecosystem Services, Elsevier, vol. 43(C).
    9. Jun Hou & Tianlin Qin & Shanshan Liu & Jianwei Wang & Biqiong Dong & Sheng Yan & Hanjiang Nie, 2021. "Analysis and Prediction of Ecosystem Service Values Based on Land Use/Cover Change in the Yiluo River Basin," Sustainability, MDPI, vol. 13(11), pages 1-14, June.
    10. Yushuo Zhang & Xiao Lu & Boyu Liu & Dianting Wu, 2018. "Impacts of Urbanization and Associated Factors on Ecosystem Services in the Beijing-Tianjin-Hebei Urban Agglomeration, China: Implications for Land Use Policy," Sustainability, MDPI, vol. 10(11), pages 1-17, November.
    11. Wei Song & Xiangzheng Deng, 2015. "Effects of Urbanization-Induced Cultivated Land Loss on Ecosystem Services in the North China Plain," Energies, MDPI, vol. 8(6), pages 1-16, June.
    12. Austin, Mike, 2007. "Species distribution models and ecological theory: A critical assessment and some possible new approaches," Ecological Modelling, Elsevier, vol. 200(1), pages 1-19.
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    1. Leizhou Zhu & Yaping Huang, 2022. "A Framework for Analyzing the Family Urbanization of China from a “Culture–Institution” Perspective," Land, MDPI, vol. 11(12), pages 1-15, November.

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