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Increased artificial illumination delays urban autumnal foliar senescence

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Abstract

Rapid urbanization has driven widespread increases in artificial light at night, intensifying energy use, light pollution, and sustainability challenges. However, its ecological impacts, particularly on vegetation phenological transitions, remain poorly understood. Using 62,994 site-year in situ records and satellite observations across 452 cities from 2001 to 2022, we show that elevated levels of artificial light at night are associated with delayed dates of foliar senescence in urban areas. This delaying effect is spatially heterogeneous and nonlinear, being most pronounced at low light intensities ( < 15 nW cm–2 sr–1) and decreasing or saturating at higher levels. Regional variability in effects of artificial light at night is primarily shaped by urban socioeconomic factors and vegetation traits. Mechanistically, the delaying effect may result from enhanced carbon assimilation and altered climatic responses. We further improve the phenological modeling by incorporating the effects of artificial light at night and project overall later foliar senescence dates than currently predicted. Collectively, our findings highlight a previously underrecognized pathway by which urbanization alters vegetation phenology, with implications for forecasting ecosystem dynamics under continued urban growth and climate change.

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Data availability

All data used in this study are freely available from the following sources: In situ DFS data can be accessed from https://doi.org/10.5281/zenodo.17925641 and http://www.pep725.eu/. Satellite-derived DFS data is available from https://lpdaac.usgs.gov/products/mcd12q2v061/. NPP-VIIRS-like nighttime light data is available from https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/YGIVCD. DMSP-OLS nighttime light data is available from https://eogdata.mines.edu/products/dmsp/. NPP-VIIRS nighttime light data is available from https://eogdata.mines.edu/products/vnl/. H-NTL-v2 data is available from https://doi.org/10.5281/zenodo.17925641. Global urban boundaries data is available from https://data-starcloud.pcl.ac.cn/iearthdata/map?id=14. Six-hourly temperature data is available from https://catalogue.ceda.ac.uk/uuid/aed8e269513f446fb1b5d2512bb387ad/. Monthly climatic data is available from https://www.climatologylab.org/terraclimate.html. HDI, GDP, Per capita GDP data is available from https://datadryad.org/dataset/doi:10.5061/dryad.dk1j0. Aboveground biomass is available from https://zenodo.org/records/13331493. Tree density is available from https://elischolar.library.yale.edu/yale_fes_data/1/. Canopy height is available from https://webmap.ornl.gov/ogc/dataset.jsp?ds_id=1665. GPP, ET, FPAR data are available from https://lpdaac.usgs.gov/products/. Vcmax data is available from https://www.nesdc.org.cn/sdo/detail?id=612f42ee7e28172cbed3d80f. SIF is available from https://globalecology.unh.edu/data/GOSIF.html. Future temperatures, Per capita GPP data were from the CMIP6 models (https://esgf-node.llnl.gov/projects/esgf-llnl/). Source data are provided with this paper.

Code availability

All data analyses and modeling were performed using Python (v3.8.10). The code is stored in a publicly available Zenodo repository https://doi.org/10.5281/zenodo.17925641.

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Acknowledgements

This study was supported by National Natural Science Foundation of China grant (42125101, W2412014). W.Q. was supported by National Natural Science Foundation of China grant (42401029). J.P. was supported by the Spanish Government grants TED2021-132627 B–I00 and PID2022-140808NB-I00, funded by MCIN, AEI/10.13039/ 501100011033 European Union Next Generation EU/PRTR, and the Fundación Ramón Areces grant CIVP20A6621.

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Author notes

  1. These authors contributed equally: Yang Chen, Wendi Qu.

Authors and Affiliations

  1. The Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China

    Yang Chen & Chaoyang Wu

  2. University of the Chinese Academy of Sciences, Beijing, China

    Yang Chen & Chaoyang Wu

  3. School of Ecology and Nature Conservation, Beijing Forestry University, Beijing, China

    Wendi Qu

  4. Department of Environmental Systems Science, Institute of Integrative Biology, ETH Zurich, Zurich, Switzerland

    Constantin M. Zohner

  5. CSIC, Global Ecology Unit CREAF-CSIC-UAB, Barcelona, Catalonia, Spain

    Josep Peñuelas

  6. CREAF, Cerdanyola del Valles, Barcelona, Catalonia, Spain

    Josep Peñuelas

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  1. Yang Chen
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  2. Wendi Qu
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  3. Constantin M. Zohner
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  4. Josep Peñuelas
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  5. Chaoyang Wu
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Contributions

C.W. designed the research. Y.C. and W.Q. wrote the first draft of the manuscript. Y.C. performed the analyses and visualization. W.Q. processed ground-based phenology datasets. C.M.Z. and J.P. discussed the design, methods and results and substantially revised the manuscript with intensive suggestions.

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Correspondence to
Chaoyang Wu.

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Nature Communications thanks Phillipe Wernette and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. A peer review file is available.

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Chen, Y., Qu, W., Zohner, C.M. et al. Increased artificial illumination delays urban autumnal foliar senescence.
Nat Commun (2026). https://doi.org/10.1038/s41467-025-68246-7

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