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探索2015年至2025年中国长江三角洲地区城市规模和城市活力对供需平衡的时空影响。

Exploring the spatiotemporal effects of urban scale and urban vitality on S&D balance in the Yangtze River Delta, China from 2015 to 2025.

作者信息

Wang Ke, Chen Qiuxiao

机构信息

School of Spatial Planning and Design, Hangzhou City University, Hangzhou, 310015, China.

出版信息

Sci Rep. 2025 Jan 3;15(1):648. doi: 10.1038/s41598-024-84546-2.

DOI:10.1038/s41598-024-84546-2
PMID:39753839
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11699126/
Abstract

Analysis of the spatiotemporal trends of urban scale and urban vitality on ecosystem services balance provides an essential basis for regional sustainable development. This study employs the Spatial Durbin Model (SDM), Spatial Autoregressive Model (SAR), and Geographically and Temporally Weighted Regression (GTWR) to effectively capture spatiotemporal associations between urban scale, urban vitality, and ecosystem services supply-demand balance, providing a detailed view of regional variations. The integrated framework combines spatiotemporal analysis, predictive scenario simulation, and importance-performance analysis to quantify and strategize urban impacts on ESs. Results show that urban scale negatively impacts the S&D ratio, while certain urban vitality factors support ecological supply (ESSI) and others enhance ecological demand (ESDI), contributing to a more balanced S&D ratio. Second, the economic priority scenario had the greatest influence on the S&D ratio, reaching - 37.5%. This resulted in Zhejiang Province's S&D value approaching 1 (the lowest S&D value being 2.044). In Anhui, Jiangsu Province, and Shanghai, the ecological priority scenario had the most impact on the S&D ratio, raising the S&D value to 0.58 ~ 1.057. While urban scale and ecological priority scenarios enhance ES supply in northeastern YRD, helping to balance the S&D ratio, urban vitality and economic priority scenarios complement each other in southwestern YRD by driving ES demand, illustrating regional differences in development strategies.

摘要

分析城市规模和城市活力对生态系统服务平衡的时空趋势,为区域可持续发展提供了重要依据。本研究采用空间杜宾模型(SDM)、空间自回归模型(SAR)和地理加权回归(GTWR),有效捕捉城市规模、城市活力与生态系统服务供需平衡之间的时空关联,详细呈现区域差异。该综合框架结合时空分析、预测情景模拟和重要性-绩效分析,以量化城市对生态系统服务的影响并制定相应策略。结果表明,城市规模对供需比有负面影响,而某些城市活力因素支持生态供给(ESSI),其他因素则增强生态需求(ESDI),有助于实现更平衡的供需比。其次,经济优先情景对供需比的影响最大,达到-37.5%。这使得浙江省的供需值接近1(最低供需值为2.044)。在安徽、江苏省和上海,生态优先情景对供需比的影响最大,将供需值提高到0.58至1.057。虽然城市规模和生态优先情景在长三角东北部增强了生态系统服务供给,有助于平衡供需比,但城市活力和经济优先情景在长三角西南部通过推动生态系统服务需求相互补充,体现了发展策略的区域差异。

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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b09e/11699126/7483eda328ef/41598_2024_84546_Fig5a_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b09e/11699126/36e43dd150c1/41598_2024_84546_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b09e/11699126/f9474d920b9d/41598_2024_84546_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b09e/11699126/fc60f4f15cdd/41598_2024_84546_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b09e/11699126/6b5c350e5a14/41598_2024_84546_Fig9_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b09e/11699126/a57849f9ad35/41598_2024_84546_Fig10_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b09e/11699126/68b744754e32/41598_2024_84546_Fig11_HTML.jpg

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