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Responses of soil organic carbon to climate extremes under warming across global biomes

Nature Climate Change volume 14, pages 98–105 (2024)Cite this article

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Abstract

The impact of more extreme climate conditions under global warming on soil organic carbon (SOC) dynamics remains unquantified. Here we estimate the response of SOC to climate extreme shifts under 1.5 °C warming by combining a space-for-time substitution approach and global SOC measurements (0–30 cm soil). Most extremes (22 out of 33 assessed extreme types) exacerbate SOC loss under warming globally, but their effects vary among ecosystems. Only decreasing duration of cold spells exerts consistent positive effects, and increasing extreme wet days exerts negative effects in all ecosystems. Temperate grasslands and croplands negatively respond to most extremes, while positive responses are dominant in temperate and boreal forests and deserts. In tundra, 21 extremes show neutral effects, but 11 extremes show negative effects with stronger magnitude than in other ecosystems. Our results reveal distinct, biome-specific effects of climate extremes on SOC dynamics, promoting more reliable SOC projection under climate change.

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Fig. 1: Schematic representation of the approach used to quantify the response of SOC to climate extreme and warming scenarios.
Fig. 2: Global responses of SOC to climate change scenarios.
Fig. 3: The dependence of additional ΔSOCE on change levels of climate extremes under warming.
Fig. 4: Influences of environmental variables on SOC changes attributed to climate extreme shifts under warming.
Fig. 5: Global spatial pattern of changes in soil organic carbon attributed to climate extreme shifts under a warmer and more extreme climate.

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Data availability

The 33 climate extreme indices can be accessed at https://doi.org/10.1594/PANGAEA.898014. Global mapping products generated in this study are publicly available and deposited to https://doi.org/10.6084/m9.figshare.22317202. Other data used in this study are the same to those used in ref. 21, which are publicly accessible. The coastline data in all maps can be gained from https://www.naturalearthdata.com/downloads/50m-physical-vectors/50m-coastline/.

Code availability

Code (R scripts)68 used to assess the data and generate the results is deposited at https://doi.org/10.6084/m9.figshare.22317202.

References

  1. Seneviratne., S. I. et al. in Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation (eds Field, C. B. et al.) 109–230 (Cambridge Univ. Press, 2012).

  2. Reichstein, M. et al. Climate extremes and the carbon cycle. Nature 500, 287–295 (2013).

    Article  CAS  Google Scholar 

  3. Frank, D. et al. Effects of climate extremes on the terrestrial carbon cycle: concepts, processes and potential future impacts. Glob. Change Biol. 21, 2861–2880 (2015).

    Article  Google Scholar 

  4. Gampe, D. et al. Increasing impact of warm droughts on northern ecosystem productivity over recent decades. Nat. Clim. Change 11, 772–779 (2021).

    Article  Google Scholar 

  5. Ciais, P. et al. Europe-wide reduction in primary productivity caused by the heat and drought in 2003. Nature 437, 529–533 (2005).

    Article  CAS  Google Scholar 

  6. Zscheischler, J., Mahecha, M. D., Harmeling, S. & Reichstein, M. Detection and attribution of large spatiotemporal extreme events in Earth observation data. Ecol. Inf. 15, 66–73 (2013).

    Article  Google Scholar 

  7. Sippel, S. et al. Drought, heat, and the carbon cycle: a review. Curr. Clim. Change Rep. 4, 266–286 (2018).

    Article  Google Scholar 

  8. Friedlingstein, P. et al. Global carbon budget 2021. Earth Syst. Sci. Data 14, 1917–2005 (2022).

    Article  Google Scholar 

  9. Crowther, T. W. et al. Quantifying global soil carbon losses in response to warming. Nature 540, 104–108 (2016).

    Article  CAS  Google Scholar 

  10. Xiao, L. et al. Younger carbon dominates global soil carbon efflux. Glob. Change Biol. 28, 5587–5599 (2022).

    Article  CAS  Google Scholar 

  11. Smith, M. D., Knapp, A. K. & Collins, S. L. A framework for assessing ecosystem dynamics in response to chronic resource alterations induced by global change. Ecology 90, 3279–3289 (2009).

    Article  Google Scholar 

  12. Sippel, S., Zscheischler, J. & Reichstein, M. Ecosystem impacts of climate extremes crucially depend on the timing. Proc. Natl Acad. Sci. USA 113, 5768–5770 (2016).

    Article  CAS  Google Scholar 

  13. Lugato, E. et al. Soil erosion is unlikely to drive a future carbon sink in Europe. Sci. Adv. 4, eaau3523 (2018).

    Article  CAS  Google Scholar 

  14. Van Oost, K. et al. The impact of agricultural soil erosion on the global carbon cycle. Science 318, 626–629 (2007).

    Article  Google Scholar 

  15. Anderegg, W. R. et al. Pervasive drought legacies in forest ecosystems and their implications for carbon cycle models. Science 349, 528–532 (2015).

    Article  CAS  Google Scholar 

  16. Anjileli, H. et al. Extreme heat events heighten soil respiration. Sci. Rep. 11, 6632 (2021).

    Article  CAS  Google Scholar 

  17. Bardgett, R. D. & Caruso, T. Soil microbial community responses to climate extremes: resistance, resilience and transitions to alternative states. Philos. Trans. R. Soc. Lond. B 375, 20190112 (2020).

    Article  CAS  Google Scholar 

  18. Deng, L. et al. Drought effects on soil carbon and nitrogen dynamics in global natural ecosystems. Earth Sci. Rev. 214, 103501 (2021).

  19. Diffenbaugh, N. S. et al. Quantifying the influence of global warming on unprecedented extreme climate events. Proc. Natl Acad. Sci. USA 114, 4881–4886 (2017).

    Article  CAS  Google Scholar 

  20. Fischer, E. M., Sippel, S. & Knutti, R. Increasing probability of record-shattering climate extremes. Nat. Clim. Change 11, 689–695 (2021).

    Article  Google Scholar 

  21. Wang, M. et al. Global soil profiles indicate depth-dependent soil carbon losses under a warmer climate. Nat. Commun. 13, 5514 (2022).

    Article  CAS  Google Scholar 

  22. Karl, T. R., Nicholls, N. & Ghazi, A. in Weather and Climate Extremes: Changes, Variations and a Perspective from the Insurance Industry (eds Karl, T. R. et al.) 3–7 (Springer Netherlands, 1999).

  23. Mistry, M. A high-resolution global gridded historical dataset of climate extreme indices. Data 4, 41 (2019).

  24. Karl, T. R., Nicholls, N. & Ghazi, A. Clivar/GCOS/WMO workshop on indices and indicators for climate extremes workshop summary. Weather Clim. Extremes 42, 3–7 (1999).

    Article  Google Scholar 

  25. Kim, Y.-H., Min, S.-K., Zhang, X., Sillmann, J. & Sandstad, M. Evaluation of the CMIP6 multi-model ensemble for climate extreme indices. Weather. Clim. Extremes 29, 100269 (2020).

    Article  Google Scholar 

  26. Zscheischler, J. et al. Future climate risk from compound events. Nat. Clim. Change 8, 469–477 (2018).

    Article  Google Scholar 

  27. Bardgett, R. D. & Caruso, T. Soil microbial community responses to climate extremes: resistance, resilience and transitions to alternative states. Philos. Trans. R. Soc. B 375, 20190112 (2020).

    Article  CAS  Google Scholar 

  28. Bennett, A. C. et al. Resistance of African tropical forests to an extreme climate anomaly. Proc. Natl Acad. Sci. USA 118, e2003169118 (2021).

    Article  CAS  Google Scholar 

  29. Zhao, M. & Running, S. W. Drought-induced reduction in global terrestrial net primary production from 2000 through 2009. Science 329, 940–943 (2010).

    Article  CAS  Google Scholar 

  30. Tao, F. et al. Microbial carbon use efficiency promotes global soil carbon storage. Nature 618, 981–985 (2023).

    Article  CAS  Google Scholar 

  31. Eckardt, N. A. et al. Climate change challenges, plant science solutions. Plant Cell 35, 24–66 (2023).

    Article  Google Scholar 

  32. Xue, K. et al. Tundra soil carbon is vulnerable to rapid microbial decomposition under climate warming. Nat. Clim. Change 6, 595–600 (2016).

    Article  CAS  Google Scholar 

  33. Plaza, C. et al. Direct observation of permafrost degradation and rapid soil carbon loss in tundra. Nat. Geosci. 12, 627–631 (2019).

    Article  CAS  Google Scholar 

  34. Liu, Q. et al. Drought-induced increase in tree mortality and corresponding decrease in the carbon sink capacity of Canada’s boreal forests from 1970 to 2020. Glob. Change Biol. 29, 2274–2285 (2023).

    Article  CAS  Google Scholar 

  35. Slessarev, E. W. et al. Initial soil organic carbon stocks govern changes in soil carbon: reality or artifact? Glob. Change Biol. 29, 1239–1247 (2023).

    Article  CAS  Google Scholar 

  36. Cotrufo, M. F., Ranalli, M. G., Haddix, M. L., Six, J. & Lugato, E. Soil carbon storage informed by particulate and mineral-associated organic matter. Nat. Geosci. 12, 989–994 (2019).

    Article  CAS  Google Scholar 

  37. Lugato, E., Lavallee, J. M., Haddix, M. L., Panagos, P. & Cotrufo, M. F. Different climate sensitivity of particulate and mineral-associated soil organic matter. Nat. Geosci. 14, 295–300 (2021).

    Article  CAS  Google Scholar 

  38. Du, E. et al. Global patterns of terrestrial nitrogen and phosphorus limitation. Nat. Geosci. 13, 221–226 (2020).

    Article  CAS  Google Scholar 

  39. Wang, H., Richardson, C. J. & Ho, M. Dual controls on carbon loss during drought in peatlands. Nat. Clim. Change 5, 584–587 (2015).

    Article  CAS  Google Scholar 

  40. Bao, T., Jia, G. & Xu, X. Weakening greenhouse gas sink of pristine wetlands under warming. Nat. Clim. Change 13, 462–469 (2023).

    Article  CAS  Google Scholar 

  41. Gauthier, S., Bernier, P., Kuuluvainen, T., Shvidenko, A. Z. & Schepaschenko, D. G. Boreal forest health and global change. Science 349, 819–822 (2015).

    Article  CAS  Google Scholar 

  42. Wang, J., Taylor, A. R. & D’Orangeville, L. Warming-induced tree growth may help offset increasing disturbance across the Canadian boreal forest. Proc. Natl Acad. Sci. USA 120, e2212780120 (2023).

    Article  CAS  Google Scholar 

  43. Jarvis, P. & Linder, S. Constraints to growth of boreal forests. Nature 405, 904–905 (2000).

    Article  CAS  Google Scholar 

  44. Lim, H. et al. Boreal forest biomass accumulation is not increased by two decades of soil warming. Nat. Clim. Change 9, 49–52 (2018).

    Article  Google Scholar 

  45. Wang, P., Huang, K. & Hu, S. Distinct fine-root responses to precipitation changes in herbaceous and woody plants: a meta-analysis. New Phytol. 225, 1491–1499 (2020).

    Article  Google Scholar 

  46. Vereecken, H. et al. Soil hydrology in the Earth system. Nat. Rev. Earth Environ. 3, 573–587 (2022).

    Article  Google Scholar 

  47. García-Palacios, P. et al. Evidence for large microbial-mediated losses of soil carbon under anthropogenic warming. Nat. Rev. Earth Environ. 2, 507–517 (2021).

    Article  Google Scholar 

  48. Ridder, N. N. et al. Global hotspots for the occurrence of compound events. Nat. Commun. 11, 5956 (2020).

    Article  CAS  Google Scholar 

  49. Xu, L., Wang, A., Wang, D. & Wang, H. Hot spots of climate extremes in the future. J. Geophys Res. Atmos. 124, 3035–3049 (2019).

    Article  Google Scholar 

  50. Tschumi, E. & Zscheischler, J. Countrywide climate features during recorded climate-related disasters. Climatic Change 158, 593–609 (2020).

    Article  Google Scholar 

  51. Batjes, N. H., Ribeiro, E. & van Oostrum, A. Standardised soil profile data to support global mapping and modelling (WoSIS snapshot 2019). Earth Syst. Sci. Data 12, 299–320 (2020).

    Article  Google Scholar 

  52. Mishra, U. et al. Spatial heterogeneity and environmental predictors of permafrost region soil organic carbon stocks. Sci. Adv. 7, eaaz5236 (2021).

    Article  CAS  Google Scholar 

  53. Fick, S. E. & Hijmans, R. J. WorldClim 2: new 1-km spatial resolution climate surfaces for global land areas. Int. J. Climatol. 37, 4302–4315 (2017).

    Article  Google Scholar 

  54. Olson, D. M. et al. Terrestrial ecoregions of the world: a new map of life on Earth: a new global map of terrestrial ecoregions provides an innovative tool for conserving biodiversity. Bioscience 51, 933–938 (2001).

    Article  Google Scholar 

  55. Channan, S., Collins, K. & Emanuel, W. Global Mosaics of the Standard MODIS Land Cover Type Data (Univ. of Maryland & Pacific Northwest National Laboratory, 2014).

  56. Meybeck, M., Green, P. & Vörösmarty, C. A new typology for mountains and other relief classes: an application to global continental water resources and population distribution. Mt. Res. Dev. 21, 34–45 (2001).

    Article  Google Scholar 

  57. Alexander, L. V. Global observed long-term changes in temperature and precipitation extremes: a review of progress and limitations in IPCC assessments and beyond. Weather Clim. Extremes 11, 4–16 (2016).

    Article  Google Scholar 

  58. Rodell, M. et al. The global land data assimilation system. Bull. Am. Meteorol. Soc. 85, 381–394 (2004).

    Article  Google Scholar 

  59. Alexander, L. V. & Perkins, S. E. On the measurement of heat waves. J. Clim. 26, 4500–4517 (2013).

    Article  Google Scholar 

  60. Sheridan, S. C. & Lee, C. C. Temporal trends in absolute and relative extreme temperature events across North America. J Geophys. Res. Atmos. 123, 11889–11898 (2018).

  61. Vicente-Serrano, S. M., Beguería, S. & López-Moreno, J. I. A multiscalar drought index sensitive to global warming: the standardized precipitation evapotranspiration index. J. Clim. 23, 1696–1718 (2010).

    Article  Google Scholar 

  62. Schwalm, C. R. et al. Global patterns of drought recovery. Nature 548, 202–205 (2017).

    Article  CAS  Google Scholar 

  63. Chen, H., Wang, S., Zhu, J. & Zhang, B. Projected changes in abrupt shifts between dry and wet extremes over China through an ensemble of regional climate model simulations. J. Geophys. Res. Atmos. 125, e2020JD033894 (2020).

  64. IPCC Special Report on Global Warming of 1.5 °C (eds Masson-Delmotte, V. et al.) (WMO, 2018).

  65. Bevacqua, E., Zappa, G., Lehner, F. & Zscheischler, J. Precipitation trends determine future occurrences of compound hot–dry events. Nat. Clim. Change 12, 350–355 (2022).

    Article  Google Scholar 

  66. Strayer, D. et al. Long-term ecological studies: an illustrated account of their design, operation, and importance to ecology. Occasional Publ. Inst. Ecosyst. Stud. 2, 1–38 (1986).

    Google Scholar 

  67. FAO, IIASA, ISRIC, ISS-CAS & JRC Harmonized World Soil Database version 1.2 (FAO & IIASA, 2012).

  68. Wang, M. & Luo, Z. Changes in soil organic carbon in response to climate extremes under warming across globe biomes. figshare https://doi.org/10.6084/m9.figshare.22317202.v1 (2023).

Download references

Acknowledgements

This research has been financially supported by the National Natural Science Foundation of China (grant number 32241036, 32171639) and the National Key Research Program of the Ministry of Science and Technology of China (grant number 2021YFE0114500). Contributions of U.M. were supported through a US Department of Energy grant to the Sandia National Laboratories, which is a multi-mission laboratory managed and operated by National Technology and Engineering Solutions of Sandia LLC, a wholly owned subsidiary of Honeywell International Inc. for the US Department of Energy’s National Nuclear Security Administration under contract DE-NA-0003525.

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Authors and Affiliations

  1. Key Laboratory of Agricultural Remote Sensing and Information Technology (Zhejiang Province), College of Environmental and Resource Sciences, Zhejiang University, Hangzhou, China

    Mingming Wang, Shuai Zhang, Xiaowei Guo & Zhongkui Luo

  2. Key Laboratory of Environment Remediation and Ecological Health, Ministry of Education, Zhejiang University, Hangzhou, China

    Mingming Wang, Shuai Zhang, Xiaowei Guo & Zhongkui Luo

  3. College of Agriculture, Nanjing Agricultural University, Nanjing, China

    Liujun Xiao

  4. State Key Laboratory of Vegetation and Environmental Change, Institute of Botany, Chinese Academy of Sciences, Beijing, China

    Yuanhe Yang

  5. School of Integrative Plant Science, Cornell University, Ithaca, NY, USA

    Yiqi Luo

  6. Computational Biology and Biophysics, Sandia National Laboratories, Livermore, CA, USA

    Umakant Mishra

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Contributions

Z.L. conceived the study; M.W. and Z.L. led data assessment; Y.Y. and U.M. contributed to permafrost data; Z.L. and M.W. interpreted the results with the contribution of all authors; Z.L. and M.W. led the writing of the manuscript and all authors improved the manuscript.

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Correspondence to Zhongkui Luo.

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Nature Climate Change thanks Emanuele Lugato and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Extended data

Extended Data Fig. 1 The response of soil organic carbon to climate change scenarios.

Error bars show 95% confidence interval, centred on the mean with the sample size shows Supplementary Data 1. Detailed descriptions of climate extreme indices (CEIs) and climate scenarios are shown in Supplementary Table 1.

Extended Data Fig. 2 The additional changes in soil organic carbon induced by climate extremes under a warmer and more extreme climate.

The dependence of additional changes in soil organic carbon (ΔSOCE) on the change levels of climate extremes under a warmer and more extreme climate. Grey grids indicate that the estimated dependence is statistically insignificant (P > 0.05). TS forests, tropical/subtropical forests; Med/Mon shrublands, Mediterranean/montane shrublands; TS grasslands/savannas, tropical/subtropical grasslands/savannas. Detailed descriptions of CEIs are shown in Supplementary Table 1.

Extended Data Fig. 3 The comparison of soil organic carbon changes induced by changes in extreme dry magnitude using our approach with file drought experimental results.

Comparison of soil organic carbon changes induced by changes in extreme dry magnitude (EDM). Deng et al. (2021) synthesized the data from field experiments. Biomes are grouped into tundra, shrublands, grasslands, and forests. Dots with bars show the mean effect sizes with 95% confidence intervals, and numbers besides them are sample sizes used to calculate the mean effect size. The actual drought levels (that is, the reduction of precipitation) in field drought experiments were normalized to annual mean precipitation. The change level in our estimation which is close most to the experimental change level was targeted to conduct the comparison.

Extended Data Fig. 4 The performance of random forest model.

The performance of random forest model on predicting soil organic carbon responses attributed to eight climate extremes under a warmer and more extreme climate. Detailed descriptions of climate extreme indices (CEIs) are shown in Supplementary Table 1.

Extended Data Fig. 5 The distribution of global wetlands and the location of soils with organic carbon stock of >300 Mg C ha–1 (0–30 cm) used in this study.

The wetland map data is obtained from http://www.wwfus.org/science/data.cfm.

Extended Data Fig. 6 The partial depended relationship of soil organic carbon changes with background climate extreme conditions.

The relationship of soil organic carbon changes (that is, ΔSOCE) with background climate extreme conditions. Partial dependence of ΔSOCE induced by a typical CEI on corresponding background CEI. Detailed descriptions of the eight CEIs are shown in Supplementary Table 1.

Extended Data Fig. 7 The global spatial pattern of absolute changes in soil organic carbon stock under a warmer and more extreme climate.

Global spatial pattern of absolute changes in soil organic carbon stock attributed to climate extreme shifts under a warmer and more extreme climate. a-h, eight climate extremes including heat wave magnitude (a) and frequency (b), cold wave magnitude (c) and frequency (d), extreme dry magnitude (e) and frequency (f), extreme wet magnitude (g) and frequency (h).

Extended Data Fig. 8 The uncertainty of soil organic carbon relative changes under a warmer and more extreme climate.

Uncertainty of soil organic carbon changes attributed to climate extreme shifts (ΔSOCE) under a warmer and more extreme climate. ΔSOCE is defined as the difference between percentage responses of SOC to W + E and that to W, which can also be explained as the additional changes in SOC induced by climate extremes. a-h, eight climate extremes including heat wave magnitude (a) and frequency (b), cold wave magnitude (c) and frequecy (d), extreme dry magnitude (e) and frequency (f), extreme wet magnitude (g) and frequency (h).

Extended Data Fig. 9 The uncertainty of soil organic carbon absolute changes attributed to climate extreme shifts (ΔSOCE, Mg C ha−1) under a warmer and more extreme climate.

The standard error was estimated based on 500 estimates of the random forest model. a-h, eight climate extremes including heat wave magnitude (a) and frequency (b), cold wave magnitude (c) and frequecy (d), extreme dry magnitude (e) and frequency (f), extreme wet magnitude (g) and frequency (h).

Extended Data Fig. 10 The latitudinal pattern of changes in soil organic under 1.5 °C warming plus the specified climate change shifts.

Latitudinal pattern of changes in soil organic carbon attributed to climate extremes (that is, ΔSOCE) under 1.5 °C warming plus the specified climate change shifts. ΔSOCE is defined as the difference between percentage responses of SOC to W + E and that to W, which can also be explained as the additional changes in SOC induced by climate extremes. a-h, eight climate extremes including heat wave magnitude (a) and frequency (b), cold wave magnitude (c) and frequecy (d), extreme dry magnitude (e) and frequency (f), extreme wet magnitude (g) and frequency (h). Black and green lines indicate the median and global average. Dashed lines show zero change, which is blocked by green lines in e and f.

Supplementary information

Supplementary Information

Supplementary Figs. 1–6 and Tables 1–6.

Supplementary Data 1

The detailed statistical results showed in Extended Data Fig. 1 and Supplementary Figs. 3, 4 and 5.

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Wang, M., Zhang, S., Guo, X. et al. Responses of soil organic carbon to climate extremes under warming across global biomes. Nat. Clim. Chang. 14, 98–105 (2024). https://doi.org/10.1038/s41558-023-01874-3

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