Spatio-temporal responses of ecological resilience to urbanization in five Great Lakes Regions (GLRs) in China and implications for building resilient GLRs

Abstract

Great Lakes Regions (GLRs) in China often confront landscape fragmentation, wetland degradation, and ecological resilience (ER) losses owing to extensive and intensive urbanization. In GLRs, however, the ER responses to urbanization remain unclear. This study explored the spatiotemporal evolution of ER and urbanization in five GLRs in China to analyze the ER dynamic patterns along center−lakeside−periphery gradient. The Spatial Durbin Model (SDM) and Panel Threshold Model (PTM) were combined to reveal the spillover and threshold effects of urbanization in five GLRs. The results indicate that the ER in five GLRs declined with a rate of 21 % from 2000 to 2020. There was a clear “center-periphery” contraction trend with low ER areas primarily spreading to human activity-concentrated regions such as lakesides, riversides, and road networks. Driven by economic and land urbanization, the average urbanization level increased from 0.06 to 0.13, where lakesides, riversides, and road networks were key areas undergoing expansion. The urbanization showed a noticeable negative spatial spillover effect on ER. Away from central lakes, the negative impacts on ER exhibited a two-phase decrease with the threshold of 81 km. This study contributes to the understanding of human-environment interactions by examining the ecological resilience response process of GLRs under the impact of urbanization. Based on a multidimensional “center−lakeside−periphery” analytical model, this study provides a strategic framework for ecological construction in GLRs in China, promoting sustainable development and adaptive capacity in vulnerable areas.

Keywords

Ecological resilience / Urbanization / Spatial durbin model / Panel threshold model / Great Lakes Region

CRediT authorship contribution statement

Tongning Li: Writing - review & editing, Writing - original draft, Visualization, Formal analysis, Data curation, Conceptualization. Guoen Wei: Writing - original draft, Funding acquisition, Conceptualization. Minghui Xu: Methodology. Daozheng Li: Software. Weifeng Deng: Data curation. Yaobin Liu: Funding acquisition, Conceptualization. Bao-Jie He: Writing - original draft.

Declaration of competing interests

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgements

This research was supported by the National Natural Science Foundation of China (Grants No. 42301226, 42271209 and 42471199), the Fundamental Research Funds for the Central Universities (Grant No. 2024CDJXY014), the Natural Science Foundation of Jiangxi Province (Grant No. 20242BAB25170), Special Funds for Water Resources in Jiangxi Province (Science and Technology Projects) (Grant No. 202425YBKT16) and the Young Talent Cultivation and Innovation Fund Project of Nanchang University (Grant No. XX202506030028).

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