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Anthropogenically-driven escalating impact of soil-based compound dry-hot extremes on vegetation productivity

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Abstract

Compound dry-hot extremes exert stronger environmental impacts than individual dry or hot extremes. While evidence for increasing meteorological compound dry-hot extremes (defined using surface air temperature and vapor pressure deficit or precipitation) is growing, the impacts and evolving risks of soil-based compound dry-hot extremes remain poorly understood. Using homogenized soil temperature observations and observationally constrained soil moisture dataset for China, we show that the adverse effects of soil-based compound dry-hot extremes on vegetation productivity are more severe than their meteorological counterparts. From 1980 to 2017, the frequency and coverage area of soil-based compound dry-hot extremes in China increased by 3.0 days and 141.9(times)104 km2, respectively, with the most pronounced increases occurring in northern China. These increases are primarily attributed to anthropogenic soil warming. Under a fossil-fueled development scenario, the mean frequency of such extremes is projected to increase by 13.3 days by the end of the twenty-first century relative to the 1981–2010 baseline, potentially reducing China’s terrestrial vegetation gross primary production by approximately 0.025 Pg C a−1. Our findings highlight an anthropogenic escalation of soil-based compound dry-hot extremes and their growing threats to terrestrial carbon sinks and food security.

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Data availability

All data supporting the findings are publicly available. The gridded daily soil temperature data are available at https://www.scidb.cn/en/detail?dataSetId=765528002485288960&version=V3. The GLEAM4 dataset (soil moisture, surface sensible and latent heat fluxes) is from https://www.gleam.eu/. The GPP, SIF, and NPP data can be downloaded from https://daac.ornl.gov/VEGETATION/guides/FluxSat_GPP_FPAR.html, https://doi.org/10.6084/m9.figshare.6387494, and https://acdisc.gsfc.nasa.gov/data/CMS/MICASA_FLUX_D.1, respectively. The CN05.1 data can be secured through https://ccrc.iap.ac.cn/resource/detail?id=228. The global daily SPEI dataset is available at https://doi.org/10.5281/zenodo.8060268. The ERA5 reanalysis data is available at https://www.ecmwf.int/en/forecasts/dataset/ecmwf-reanalysis-v5. The land-use/land-cover dataset is available at https://zenodo.org/records/4417810. The model simulation data can be downloaded from https://pcmdi.llnl.gov/CMIP6/. The raw data to reproduce the figures of the paper are available at https://doi.org/10.6084/m9.figshare.2841542068.

Code availability

The codes supporting this study are available at https://doi.org/10.6084/m9.figshare.2841542068.

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Acknowledgements

Our sincere gratitude goes to the researchers and institutions responsible for the development, compilation, and public release of the datasets employed in this study. Their efforts in advancing open data sharing have laid a critical foundation for this work. This work was supported by the National Natural Science Foundation of China (42522102, 42275040) and the Programme of Kezhen-Bingwei Excellent Young Scientists of the Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences (2022RC006).

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Authors and Affiliations

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

    Yani Liang, Jun Wang, Huanjiong Wang, Huijuan Cui & Quansheng Ge

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

    Yani Liang & Quansheng Ge

  3. College of Water Sciences, Beijing Normal University, Beijing, China

    Zengchao Hao

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  1. Yani Liang
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Contributions

J.W. and Q.G. conceived and designed the study. Y.L. and J.W. performed the analyses. J.W. and Y.L. wrote the draft. J.W., Q.G., Z.H., H.W., and H.C. reviewed, revised, and edited the manuscript. All authors contributed to interpreting the results.

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Jun Wang or Quansheng Ge.

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Nature Communications thanks Wanjuan Song, Duminda Vidana 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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Liang, Y., Wang, J., Hao, Z. et al. Anthropogenically-driven escalating impact of soil-based compound dry-hot extremes on vegetation productivity.
Nat Commun (2026). https://doi.org/10.1038/s41467-026-68878-3

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