Abstract
So far, urban scaling theory has proven that urban area, infrastructure, and economic output have a scaling relation with population. But if we consider ecological space as a part of urban infrastructure, would the same scaling characteristics exist? What is the scaling relationship between ecological spaces and economic social development in different stages of urbanization? This paper is based on this question and explores the trade-off between social economic system and ecosystem in 370 cities of China. The results show that the relationship between population and urban ecological space generally follows the scaling theory in terms of different types of ecological spaces and ecosystem services. For every 10-fold increase in population size, the total area of ecological space and ecosystem services increase by approximately 4 times. The manifestation of ecological space following the scaling laws is the aggregation behavior of better network connectivity. There is a trade-off between urban ecological space and socioeconomic development, with flow equilibrium reached at a population of 2 million and efficiency equilibrium reached at a population of 1 million. Starting from type I and type II megapolis, urban development gradually tends to stabilize, and there may even be a trend of slow decline in urban development potential. In the absence of ecological space, virtual network space can serve as a substitute for ecological space. The driving factors affect scaling behavior of ecological space, including connectivity of ecological space, spatial heterogeneity of natural conditions, and disturbance of economic and social activities. This research can help city to expand ecological space, promoting the added value of urban ecological assets and keeping the urban development potential within the optimal threshold range continuously.
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Data availability
The data that support the findings of this study are openly available from the websites below.
Population density. 1km×1km gridded population density raster data from WorldPop (www.worldpop.org - School of Geography and Environmental Science, University of Southampton; Department of Geography and Geosciences, University of Louisville; Departement de Geographie, Universite de Namur) and Center for International Earth Science Information Network (CIESIN), Columbia University (2018). Global High Resolution Population Denominators Project - Funded by The Bill and Melinda Gates Foundation (OPP1134076). https://doi.org/10.5258/SOTON/WP00674
GDP raster. Chen, J. D. & Gao, M. Global 1 km × 1 km gridded revised real gross domestic product and electricity consumption during 1992–2019 based on calibrated nighttime light data. figshare. Dataset. https://doi.org/10.6084/m9.figshare.17004523.v1 (2021).
NPP-VIIRS-like nighttime light data. Chen, Zuoqi; Yu, Bailang; Yang, Chengshu; Zhou, Yuyu; Yao, Shenjun; Qian, Xingjian; Wang, Congxiao; Wu, Bin; Wu, Jianping, 2020, “An extended time-series (2000-2018) of global NPP-VIIRS-like nighttime light data”, https://doi.org/10.7910/DVN/YGIVCD, Harvard Dataverse, V3, UNF:6:qMXz0adYK5q7pFqKgsCFOQ== [fileUNF]
POI dataset. This dataset is derived from Autonavi Holdings Limited (https://www.autonavi.com). The State Information Center of China, 2017, “Point of Interest data from Amap”, https://doi.org/10.18170/DVN/WSXCNM, open research data platform of Beijing University, V2
LUCC. China Multi-period Land Use Land Cover Remote Sensing Monitoring Dataset (CNLUCC) is obtained by manual visual interpretation with Landsat remote sensing image data as the main information source. The land use types include 6 primary types of cultivated land, forest land, grassland, water, residential land and unused land, and 25 secondary types. Data from Resource and Environment Science and Data Center: http://www.resdc.cn/Datalist1.aspx?FieldTyepID=1,3
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Acknowledgements
We are very grateful to Prof. Lobo Jose for his important suggestions and comments on this paper.
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This work is supported by the National Key Research and Development Program of China (2022YFF1301200), National Natural Science Foundation of China (No. 52070021), and research project of Hainan National Park Research Institute (KY-23ZK02).
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GY Liu was responsible for overall project supervision, conceptualization, project management, and final draft writing, review, and editing; MW Wu contributed to methodology development, conducted validation, and contributed to the writing of early drafts and revision version; F Gonella, WQ Chen, H Li, NY Yan, and Q Yang contributed to the data curation and revision checking.
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Wu, ., Liu, G., Gonella, F. et al. Does a scaling exist in urban ecological infrastructure? A case for sustainability trade-off in China. Environ Sci Pollut Res (2023). https://doi.org/10.1007/s11356-023-29275-1
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DOI: https://doi.org/10.1007/s11356-023-29275-1