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Progressive decline in soil nitrogen stocks with warming in a Tibetan permafrost ecosystem

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Abstract

Permafrost regions contain a substantial fraction of Earth’s soil nitrogen, which is vulnerable to climate change. The response of this crucial N stock to warming could impact the permafrost–climate feedback by altering plant productivity, microbial decomposition and nitrous oxide emissions. However, the long-term trajectory of soil N stocks in response to warming remains unclear. Here we present results from a ten-year field warming experiment in a permafrost ecosystem on the Tibetan Plateau. We made repeated measurements of soil N stocks to 50 cm depth and assessed 28 N-cycling variables to explore three primary pathways affecting soil N stocks, including N inputs, microbial N transformations and N losses. Our results reveal that, despite no changes being observed during the initial years of the experiment, warmed plots experienced a decline in surface soil N stocks (an average 7.7% reduction relative to control plots) after eight years of warming. This decrease is associated with the enhanced N sequestration in perennial plant biomass, increased ecosystem N leaching and gaseous N losses from soils. Our findings underscore the vulnerability of soil N stocks in permafrost regions to ongoing warming, and suggest that the potential permafrost–climate feedback may be stronger than previously anticipated.

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Fig. 1: Warming effects on total nitrogen stocks and content of the surface soil from 2014 to 2023.
Fig. 2: Responses of ecosystem nitrogen inputs to warming.
Fig. 3: Responses of soil nitrogen-cycling processes to warming.
Fig. 4: Responses of plant nitrogen uptake to warming.
Fig. 5: Warming effects on ecosystem nitrogen losses.
Fig. 6: Schematic depicting the fate of soil nitrogen stocks upon decadal warming in a Tibetan permafrost ecosystem.

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Data availability

Data used in this study are available from the figshare data repository https://doi.org/10.6084/m9.figshare.29468852 (ref. 83). Source data are provided with this paper.

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Acknowledgements

We thank D. Li from the Institute of Subtropical Agriculture, Chinese Academy of Sciences, for his assistance with protein depolymerization determination, and X. Xu from the Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, for his guidance in 15N-labelling experimental design. We also thank Y. Fang from the Institute of Applied Ecology, C. Liu and W. Zhang from the Institute of Atmospheric Physics, Chinese Academy of Sciences, and J. Chang from Zhejiang University for their suggestions during the paper revision. This work was supported by the National Natural Science Foundation of China (32425004 and 32588202), the National Key Research and Development Program of China (2022YFF0801901 and 2022YFF0801902) and the New Cornerstone Science Foundation through the XPLORER PRIZE. C.V. was supported by the project MOMENT (grant number 03F0931A) funded by the German Federal Ministry of Education and Research (BMBF) and the European Research Council Starting Grant COLDSPOT (101163177).

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Authors and Affiliations

  1. State Key Laboratory of Forage Breeding-by-Design and Utilization; Key Laboratory of Vegetation and Environmental Change, Institute of Botany, Chinese Academy of Sciences, Beijing, China

    Bin Wei, Dianye Zhang, Wei Zhou, Yuxuan Bai, Zhihu Zheng, Yuhong Xie, Chunbao Zhao, Feiqi Wang, Luyao Huang, Guibiao Yang, Yunfeng Peng & Yuanhe Yang

  2. China National Botanical Garden, Beijing, China

    Bin Wei, Dianye Zhang, Wei Zhou, Yuxuan Bai, Zhihu Zheng, Yuhong Xie, Chunbao Zhao, Feiqi Wang, Luyao Huang, Guibiao Yang, Yunfeng Peng & Yuanhe Yang

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

    Bin Wei, Wei Zhou, Zhihu Zheng, Yuhong Xie, Chunbao Zhao, Feiqi Wang, Luyao Huang & Yuanhe Yang

  4. Permafrost Research Section, Alfred-Wegener Institute Helmholtz Center for Polar and Marine Research, Potsdam, Germany

    Carolina Voigt

  5. Institute of Soil Science, University of Hamburg, Hamburg, Germany

    Carolina Voigt

  6. Biogeochemistry Research Group, Department of Biological and Environmental Sciences, University of Eastern Finland, Kuopio, Finland

    Dan Kou

  7. Soil and Crop Sciences Section, School of Integrative Plant Science, Cornell University, Ithaca, NY, USA

    Yiqi Luo

  8. CSIC, Global Ecology Unit CREAF-CSIC-UAB, Barcelona, Spain

    Josep Peñuelas

  9. CREAF, Cerdanyola del Vallès, Spain

    Josep Peñuelas

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  1. Bin Wei
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Contributions

Y.Y. and B.W. designed the research. B.W., W.Z., Y.B., Z.Z., Y.X., C.Z., F.W. and L.H. performed the experiments. B.W. analysed the data. B.W. and Y.Y. wrote the paper with inputs from D.Z., C.V., Y.B., G.Y., D.K., Y.P., Y.L. and J.P.

Corresponding author

Correspondence to Yuanhe Yang.

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The authors declare no competing interests.

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Nature Geoscience thanks Birgit Wild, Petr Capek and Kate Buckeridge for their contribution to the peer review of this work. Primary handling editors: Xujia Jiang and Carolina Ortiz Guerrero, in collaboration with the Nature Geoscience team.

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Extended data

Extended Data Fig. 1 Overview of the study site and design of the warming experiment.

a, The field warming experiment was established within a 50 × 50 m fenced area in June 2013 (photo credit: Bin Wei). b, Design of open-top chamber warming devices. The manipulative warming experiment followed a paired design and comprised ten 4 × 4 m blocks. In each block, a hexagonal open-top chamber and a 0.8 × 1.2 m plot were diagonally arranged as the warming and control plot, respectively. The warming device elevated topsoil temperature by an average of 1.3 °C over the past decade. See Supplementary Fig. 1 for details.

Extended Data Fig. 2 A schematic diagram of ecosystem nitrogen cycle and 28 nitrogen-cycling parameters measured in this study.

The N cycle usually consists of an external (that is, atmospheric N deposition, biological N2 fixation, ecosystem N leaching and gaseous losses) and an internal cycle (that is, litter N return, microbial N transformation and plant N uptake). Yellowish-brown, reddish-brown, green and blue arrows denote biological N2 fixation, microbial N transformation, plant N uptake, N leaching and gaseous emissions, respectively. Abbreviations: \({{\rm{NH}}}_{4}^{+}-{\rm{N}}\), ammonium; \({{\rm{NO}}}_{3}^{-}-{\rm{N}}\), nitrate; NO, nitric oxide; N2O, nitrous oxide; N2, dinitrogen gas.

Extended Data Fig. 3 Warming effects on total nitrogen stocks and content in 10-30 cm soils from 2014 to 2023.

a,b, Total N stocks (a) and content (b) in 10-30 cm soil. In a,b, data are visualized as split violin plots with the outline denoting the kernel density estimation of the underlying distributions, and dashed lines denoting the average in control and warming plots (n = 10 biologically independent samples). These comparisons were conducted using the paired-samples t-tests (two sided).

Source data

Extended Data Fig. 4 Warming effects on total nitrogen stocks and content in 30-50 cm soils from 2018 to 2023.

a,b, total N stocks (a) and content (b) in 30-50 cm soil. In a,b, data are visualized as split violin plots with the outline denoting the kernel density estimation of the underlying distributions, and dashed lines denote the average in control and warming plots (n = 10 biologically independent samples). Paired-samples t-tests (two sided) were performed to compare the difference in soil N stocks and content between warming and control plots. Deeper soil samples (that is, 30-40 and 40-50 cm) were collected from 2018 onwards.

Source data

Extended Data Fig. 5 Warming effects on topsoil bioavailable nitrogen and microbial biomass nitrogen.

a-d, The content of \({{\rm{NO}}}_{4}^{+}-{\rm{N}}\) (a), \({{\rm{NO}}}_{3}^{-}-{\rm{N}}\) (b), dissolved organic N (c) and microbial biomass N (d) in the top 10 cm soil. In a-d, data are shown as the mean ± s.d. (n = 10 biologically independent samples). Each diamond represents the content of soil variables in control and warming plots. Paired-samples t-tests (two sided) were performed to compare differences in these topsoil variables between warming and control treatment. Soil abiotic and biotic parameters in the top 10 cm were determined in 2021. Abbreviations: \({{\rm{NH}}}_{4}^{+}-{\rm{N}}\), ammonium; \({{\rm{NO}}}_{3}^{-}-{\rm{N}}\), nitrate.

Source data

Extended Data Fig. 6 The relative contribution of three potential pathways to the observed declines in soil nitrogen stocks.

See Supplementary Table 2 for model details.

Source data

Extended Data Fig. 7 Warming effects on cumulative amount of nitrogen losses during the initial 8 years of experiment based on the DeNitrification–DeComposition model.

The green, purple and red areas indicate the primary pathways of N losses included plant N uptake, N leaching and gaseous N emissions from 2014 to 2021. The gaseous N refers to N2O, N2, nitric oxide and ammonia in the DNDC model.

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Extended Data Fig. 8 Locations of collected studies and soil nitrogen response to warming across the permafrost-affected regions.

a, Soil N response was collected in 38 datasets from 29 warming experiments at Arctic, subarctic and Tibetan alpine sites. Panel a adapted with permission from ref. 84, Elsevier. b, Mean soil N response to warming (Hedges’s SMD) for all sites, Arctic, subarctic and Tibetan alpine regions. In b, data were visualized as violin plots with outer shape denoting the kernel density estimation of underlying distributions. The white circle in the violin represents the metaregression model estimates, and the error bar denotes 95% confidence interval. The effect of warming was statistically significant if the 95% confidence interval did not overlap zero. Bubble sizes reflect the weight of the observation in the metaregression model. The sample size (n) for each region is indicated in the parenthesis. Abbreviations: Hedges’s SMD; the Hedges’ standardized mean difference. See Supplementary Table 4 for details.

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Extended Data Fig. 9 Context-dependencies in the soil nitrogen response to warming.

a-d, Mean annual temperature (a), mean annual precipitation (b), soil pH (c) and soil C:N ratio (d) across Arctic, subarctic and Alpine regions. e-h, The single-factor metaregression modes were used to test the association of soil N Hedges’s SMD with these context-specific environmental conditions. In a-d, data are shown as the median values. In e-h, metaregression results are presented as the mean model estimate (solid line) and 95% confidence intervals grey area. Qm refer to the Q value of importance of the environmental and soil variables. Bubble sizes reflect weight of the observation in the metaregression, with larger bubbles denoting greater weights. In h, hollow point is the outlier identified through Boxplot Procedures and thus excluded from the fitting. Abbreviations: C:N ratios, carbon: nitrogen ratios; Hedges’s SMD; the Hedges’ standardized mean difference.

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Extended Data Fig. 10 Trajectories of soil nitrogen stocks under two future climate change scenarios from 2024 to 2100.

The DNDC model was performed under two Shared Socioeconomic Pathway 1-2.6 (SSP1-2.6, low-carbon emissions) and SSP5-8.5 (high-carbon emissions) scenarios to simulate the dynamics of soil N stocks in the top 50 cm (detailed in Supplementary Text Note 5). Green and red lines are multi-model means under SSP1-2.6 and SSP5-8.5 scenarios, and shaded areas represent the standard deviation, calculated from modeling results using meteorological data from three General Circulation Models (that is, EC-Earth3-Veg-LR, ACCESS-CM2 and NorESM2-LM). Green and red donut charts denote that the relative proportions of plant uptake, N leaching and gaseous N emissions to total ecosystem N losses under SSP1-2.6 and SSP5-8.5 scenarios, respectively.

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Supplementary information

Supplementary Information

Supplementary Notes 1–14, Tables 1–7, Figs. 1–19, Appendix and References. 1–72.

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Extended Data Figs. 3–10

Statistical source data.

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Wei, B., Zhang, D., Voigt, C. et al. Progressive decline in soil nitrogen stocks with warming in a Tibetan permafrost ecosystem. Nat. Geosci. (2025). https://doi.org/10.1038/s41561-025-01786-1

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