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Ecological resilience in China's ten urban agglomerations: evolution and influence under the background of carbon neutrality

Author

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  • Ouyang, Xiao
  • Chen, Jian
  • Wei, Xiao
  • Li, Jiayu

Abstract

Amid global carbon neutrality initiatives, the dynamic interplay between urban decarbonization and ecological resilience remains underexplored, particularly in China’s urban agglomerations where balancing emission reduction and ecosystem stability poses critical challenges. Elucidating how anthropogenic and natural drivers interactively shape ecological resilience under carbon-neutral constraints has emerged as a pivotal scientific frontier for achieving sustainable coexistence between human and natural systems. Therefore, we constructed carbon neutrality index (CNI) and ecological resilience index (ERI) to evaluate the carbon neutrality and ecological resilience of urban agglomeration in China from 2000 to 2020. Using restricted cubic spline analysis to identify the nonlinear thresholds of influence factors, results showed that: (1) Both indices showed positive trends, with CNI increasing from 5.03 to 11.88 and ERI from 0.41 to 0.49, displaying spatial patterns of center-to-periphery gradient. (2) Both anthropogenic and natural factors demonstrated nonlinear impacts on ERI with specific thresholds identified for key variables including CNI (10.75), population density (12,151 individuals), GDP (209,400 CNY), and various environmental parameters. (3) We identified 21,262 km² of maximum potential priority areas requiring ecological restoration. These findings provide scientific guidance for targeted protection and restoration efforts to support sustainable urban agglomeration development within territorial spatial planning frameworks.

Suggested Citation

  • Ouyang, Xiao & Chen, Jian & Wei, Xiao & Li, Jiayu, 2025. "Ecological resilience in China's ten urban agglomerations: evolution and influence under the background of carbon neutrality," Ecological Modelling, Elsevier, vol. 508(C).
  • Handle: RePEc:eee:ecomod:v:508:y:2025:i:c:s030438002500211x
    DOI: 10.1016/j.ecolmodel.2025.111226
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