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Dominance of particulate organic carbon in top mineral soils in cold regions

Nature Geoscience volume 17, pages 145–150 (2024)Cite this article

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Abstract

The largest stocks of soil organic carbon can be found in cold regions such as Arctic, subarctic and alpine biomes, which are warming faster than the global average. Discriminating between particulate and mineral-associated organic carbon can constrain the uncertainty of projected changes in global soil organic carbon stocks. Yet carbon fractions are not considered when assessing the contribution of cold regions to land carbon–climate feedbacks. Here we synthesize field paired observations of particulate and mineral-associated organic carbon in the mineral layer, along with experimental warming data, to investigate whether the particulate fraction dominates in cold regions and whether this relates to higher soil organic carbon losses with warming than in other (milder) biomes. We show that soil organic carbon in the first 30 cm of mineral soil is dominated or co-dominated by particulate carbon in both permafrost and non-permafrost soils, and in Arctic and alpine ecosystems but not in subarctic environments. Our findings indicate that soil organic carbon is most vulnerable to warming in cold regions compared with milder biomes, with this vulnerability mediated by higher warming-induced losses of particulate carbon. The massive soil carbon accumulation in cold regions appears distributed predominantly in the more vulnerable particulate fraction rather than in the more persistent mineral-associated fraction, supporting the likelihood of a strong, positive land carbon–climate feedback.

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Fig. 1: Distribution of SOC in the POC and MAOC fractions in the mineral layer of cold regions.
Fig. 2: Relationships between SOC and concentrations of POC and MAOC in the top mineral layer of cold regions.
Fig. 3: Effects of environmental drivers on POC and MAOC concentrations in the top mineral layer (first 30 cm) of cold regions.
Fig. 4: Mean effect size of experimental warming on SOC, POC and MAOC in the top mineral layer (first 30 cm) of cold systems versus other biomes.

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Data availability

Data used in this study can be found in the Figshare data repository: https://doi.org/10.6084/m9.figshare.22347175 (ref. 63).

Code availability

The code to carry out the current analyses is available from the corresponding author upon request.

References

  1. Crowther, T. W. et al. The global soil community and its influence on biogeochemistry. Science 365, eaav0550 (2019).

    CAS  PubMed  Google Scholar 

  2. Jackson, R. B. et al. The ecology of soil carbon: pools, vulnerabilities, and biotic and abiotic controls. Annu. Rev. Ecol. Evol. Syst. 48, 419–445 (2017).

    Google Scholar 

  3. Schuur, E. A. G. et al. Permafrost and climate change: carbon cycle feedbacks from the warming arctic. Annu. Rev. Environ. Resour. 47, 343–371 (2022).

    Google Scholar 

  4. Schuur, E. A. G. et al. Climate change and the permafrost carbon feedback. Nature 520, 171–179 (2015).

    CAS  PubMed  ADS  Google Scholar 

  5. 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).

    ADS  Google Scholar 

  6. Carey, J. C. et al. Temperature response of soil respiration largely unaltered with experimental warming. Proc. Natl Acad. Sci. USA 113, 13797–13802 (2016).

    CAS  PubMed  PubMed Central  ADS  Google Scholar 

  7. Koven, C. D., Hugelius, G., Lawrence, D. M. & Wieder, W. R. Higher climatological temperature sensitivity of soil carbon in cold than warm climates. Nat. Clim. Change 7, 817–822 (2017).

    CAS  ADS  Google Scholar 

  8. Rantanen, M. et al. The Arctic has warmed nearly four times faster than the globe since 1979. Commun. Earth Environ. 3, 168 (2022).

    ADS  Google Scholar 

  9. Jansen, E. et al. Past perspectives on the present era of abrupt Arctic climate change. Nat. Clim. Change 10, 714–721 (2020).

    ADS  Google Scholar 

  10. Lavallee, J. M., Soong, J. L. & Cotrufo, M. F. Conceptualizing soil organic matter into particulate and mineral-associated forms to address global change in the 21st century. Glob. Change Biol. 26, 261–273 (2020).

    ADS  Google Scholar 

  11. Sokol, N. W. et al. Global distribution, formation and fate of mineral-associated soil organic matter under a changing climate: a trait-based perspective. Funct. Ecol. 36, 1411–1429 (2022).

    CAS  Google Scholar 

  12. Benbi, D. K., Boparai, A. K. & Brar, K. Decomposition of particulate organic matter is more sensitive to temperature than the mineral associated organic matter. Soil Biol. Biochem. 70, 183–192 (2014).

    CAS  Google Scholar 

  13. 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).

    CAS  ADS  Google Scholar 

  14. Liu, X. J. A. et al. Soil aggregate-mediated microbial responses to long-term warming. Soil Biol. Biochem. 152, 108055 (2021).

    CAS  Google Scholar 

  15. Zimov, S. A., Schuur, E. A. G. & Iii, F. S. C. Permafrost and the global carbon budget. Science 312, 1612–1613 (2006).

    CAS  PubMed  Google Scholar 

  16. Georgiou, K. et al. Global stocks and capacity of mineral-associated soil organic carbon. Nat. Commun. 13, 3797 (2022).

    CAS  PubMed  PubMed Central  ADS  Google Scholar 

  17. Schuur, E. A. G. & MacK, M. C. Ecological response to permafrost thaw and consequences for local and global ecosystem services. Annu. Rev. Ecol. Evol. Syst. 49, 279–301 (2018).

    Google Scholar 

  18. Liu, F. et al. Divergent changes in particulate and mineral-associated organic carbon upon permafrost thaw. Nat. Commun. 13, 5073 (2022).

    PubMed  PubMed Central  ADS  Google Scholar 

  19. Gentsch, N. et al. Temperature response of permafrost soil carbon is attenuated by mineral protection. Glob. Change Biol. 24, 3401–3415 (2018).

    ADS  Google Scholar 

  20. 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).

    CAS  ADS  Google Scholar 

  21. Joss, H. et al. Cryoturbation impacts iron–organic carbon associations along a permafrost soil chronosequence in northern Alaska. Geoderma 413, 115738 (2022).

    CAS  ADS  Google Scholar 

  22. IPCC Climate Change 2021: The Physical Science Basis (eds Masson-Delmotte, V. et al.) (Cambridge Univ. Press, 2021).

  23. Lehmann, J. & Kleber, M. The contentious nature of soil organic matter. Nature 528, 60–68 (2015).

    CAS  PubMed  ADS  Google Scholar 

  24. Davidson, E. A. & Janssens, I. A. Temperature sensitivity of soil carbon decomposition and feedbacks to climate change. Nature 440, 165–173 (2006).

    CAS  PubMed  ADS  Google Scholar 

  25. Burke, E. J. et al. Quantifying uncertainties of permafrost carbon–climate feedbacks. Biogeosciences 14, 3051–3066 (2017).

    CAS  ADS  Google Scholar 

  26. McGuire, A. D. et al. Dependence of the evolution of carbon dynamics in the northern permafrost region on the trajectory of climate change. Proc. Natl Acad. Sci. USA 115, 3882–3887 (2018).

    PubMed  PubMed Central  ADS  Google Scholar 

  27. Dutta, K., Schuur, E. A. G., Neff, J. C. & Zimov, S. A. Potential carbon release from permafrost soils of Northeastern Siberia. Glob. Change Biol. 12, 2336–2351 (2006).

    ADS  Google Scholar 

  28. Elberling, B. et al. Long-term CO2 production following permafrost thaw. Nat. Clim. Change 3, 890–894 (2013).

    CAS  ADS  Google Scholar 

  29. Miner, K. R. et al. Permafrost carbon emissions in a changing Arctic. Nat. Rev. Earth Environ. 3, 55–67 (2022).

    ADS  Google Scholar 

  30. Turetsky, M. R. et al. Carbon release through abrupt permafrost thaw. Nat. Geosci. 13, 138–143 (2020).

    CAS  ADS  Google Scholar 

  31. Patzner, M. S. et al. Iron mineral dissolution releases iron and associated organic carbon during permafrost thaw. Nat. Commun. 11, 6329 (2020).

    CAS  PubMed  PubMed Central  ADS  Google Scholar 

  32. Prairie, A. M., King, A. E. & Cotrufo, M. F. Restoring particulate and mineral-associated organic carbon through regenerative agriculture. Proc. Natl Acad. Sci. USA 120, 2217481120 (2023).

    Google Scholar 

  33. Ping, C. L. et al. High stocks of soil organic carbon in the North American Arctic region. Nat. Geosci. 1, 615–619 (2008).

    CAS  ADS  Google Scholar 

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

    CAS  PubMed  PubMed Central  ADS  Google Scholar 

  35. Ping, C. L., Jastrow, J. D., Jorgenson, M. T., Michaelson, G. J. & Shur, Y. L. Permafrost soils and carbon cycling. Soil 1, 147–171 (2015).

    CAS  ADS  Google Scholar 

  36. Hassink, J. The capacity of soils to preserve organic C and N by their association with clay and silt particles. Plant Soil 191, 77–87 (1997).

    CAS  Google Scholar 

  37. Cotrufo, M. F. & Lavallee, J. M. Soil organic matter formation, persistence, and functioning: a synthesis of current understanding to inform its conservation and regeneration. Adv. Agron. 172, 1–66 (2022).

    Google Scholar 

  38. Prater, I. et al. From fibrous plant residues to mineral-associated organic carbon—the fate of organic matter in Arctic permafrost soils. Biogeosciences 17, 3367–3383 (2020).

    CAS  ADS  Google Scholar 

  39. Rocci, K. S., Lavallee, J. M., Stewart, C. E. & Cotrufo, M. F. Soil organic carbon response to global environmental change depends on its distribution between mineral-associated and particulate organic matter: a meta-analysis. Sci. Total Environ. 793, 148569 (2021).

    CAS  PubMed  ADS  Google Scholar 

  40. Allison, S. D., Wallenstein, M. D. & Bradford, M. A. Soil-carbon response to warming dependent on microbial physiology. Nat. Geosci. 3, 336–340 (2010).

    CAS  ADS  Google Scholar 

  41. Liu, F. et al. Altered microbial structure and function after thermokarst formation. Glob. Change Biol. 27, 823–835 (2021).

    CAS  ADS  Google Scholar 

  42. Abbott, B. W. et al. Biomass offsets little or none of permafrost carbon release from soils, streams, and wildfire: an expert assessment. Environ. Res. Lett. 11, 034014 (2016).

    ADS  Google Scholar 

  43. Tamocai, C. et al. Soil organic carbon pools in the northern circumpolar permafrost region. Glob. Biogeochem. Cycles 23, GB2023 (2009).

    ADS  Google Scholar 

  44. Strauss, J. et al. Deep Yedoma permafrost: a synthesis of depositional characteristics and carbon vulnerability. Earth Sci. Rev. 172, 75–86 (2017).

    CAS  ADS  Google Scholar 

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

    CAS  Google Scholar 

  46. Golchin, A., Oades, J. M., Skjemstad, J. O. & Clarke, P. Soil structure and carbon cycling. Aust. J. Soil Res. 32, 1043–1068 (1994).

    Google Scholar 

  47. Poeplau, C. et al. Isolating organic carbon fractions with varying turnover rates in temperate agricultural soils—a comprehensive method comparison. Soil Biol. Biochem. 125, 10–26 (2018).

    CAS  Google Scholar 

  48. Harris, I., Osborn, T. J., Jones, P. & Lister, D. Version 4 of the CRU TS monthly high-resolution gridded multivariate climate dataset. Sci. Data 7, 109 (2020).

    PubMed  PubMed Central  Google Scholar 

  49. 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).

    Google Scholar 

  50. Bastos, A., Running, S. W., Gouveia, C. & Trigo, R. M. The global NPP dependence on ENSO: La Niña and the extraordinary year of 2011. J. Geophys. Res. Biogeosci. 118, 1247–1255 (2013).

    Google Scholar 

  51. Justice, C. et al. An overview of MODIS Land data processing and product status. Remote Sens. Environ. 83, 3–15 (2002).

    ADS  Google Scholar 

  52. Obu, J. et al. ESA Permafrost Climate Change Initiative (Permafrost_cci): Permafrost Version 2 Data Products (Centre for Environmental Data Analysis, 2022); http://catalogue.ceda.ac.uk/uuid/1f88068e86304b0fbd34456115b6606f

  53. Gelman, A. Scaling regression inputs by dividing by two standard deviations. Stat. Med. 27, 2865–2873 (2008).

    MathSciNet  PubMed  Google Scholar 

  54. Cutler, D. R. et al. Random forests for classification in ecology. Ecology 88, 2783–2792 (2007).

    PubMed  Google Scholar 

  55. Breiman, L. Random forests. Mach. Learn. 45, 5–32 (2001).

    Google Scholar 

  56. Liaw, A. & Wiener, M. Classification and regression by randomForest. R News 2, 18–22 (2002).

    Google Scholar 

  57. R Core Team R: A Language and Environment for Statistical Computing. Version 4.3.1 (R Foundation for Statistical Computing, 2021); https://www.R-project.org/

  58. Fox, S. & Weisberg, J. An R Companion to Applied Regression 3rd edn (Sage, 2019).

  59. Bates, D., Mächler, M., Bolker, B. M. & Walker, S. C. Fitting linear mixed-effects models using lme4. J. Stat. Softw. 67 (2015).

  60. Kuznetsova, A., Brockhoff, P. B. & Christensen, R. H. B. lmerTest package: tests in linear mixed effects models. J. Stat. Softw. 82, 1–26 (2017).

    Google Scholar 

  61. Stoffel, M. A., Nakagawa, S. & Schielzeth, H. partR2: partitioning R2 in generalized linear mixed models. PeerJ. 9, e11414 (2021).

    PubMed  PubMed Central  Google Scholar 

  62. Wallace, B. C. et al. OpenMEE: intuitive, open-source software for meta-analysis in ecology and evolutionary biology. Methods Ecol. Evol. 8, 941–947 (2016).

    Google Scholar 

  63. García-Palacios, P. & Plaza, C. Dominance of particulate organic carbon in top mineral soils in cold regions. Figshare https://doi.org/10.6084/m9.figshare.22347175 (2023).

Download references

Acknowledgements

We thank all authors who gathered and published the raw data in the original studies that enabled this literature synthesis. P.G.-P. acknowledges support from the Spanish Ministry of Science and Innovation via the I+D+i project PID2020-113021RA-I00 and the TED project TED2021-130908A-C42 (funded by European Union—NextGenerationEU). Work at Lawrence Livermore National Laboratory by N.W.S. was performed under the auspices of the US DOE OBER, under contract DE-AC52-07NA27344 award #SCW1632. M.P. acknowledges financial support by the Comunidad de Madrid and the Spanish National Council of Scientific Researches research grant Atracción de Talento (grant number 2019T1/AMB14503).

Author information

Authors and Affiliations

  1. Instituto de Ciencias Agrarias (ICA), CSIC, Madrid, Spain

    Pablo García-Palacios, Iria Benavente-Ferraces, Miguel de Celis, Juan Carlos García-Gil, Asier Goñi-Urtiaga, Marco Panettieri & César Plaza

  2. Department of Plant and Microbial Biology, University of Zurich, Zurich, Switzerland

    Pablo García-Palacios

  3. The Forest School, Yale School of the Environment, Yale University, New Haven, CT, USA

    Mark A. Bradford

  4. Laboratorio de Biodiversidad y Funcionamiento Ecosistémico. Instituto de Recursos Naturales y Agrobiología de Sevilla (IRNAS), CSIC, Seville, Spain

    Manuel Delgado-Baquerizo

  5. National Institute of Agricultural Technology (INTA), Institute of Soil Science, Hurlingham, Argentina

    Juan J. Gaitán

  6. Department of Technology, National University of Luján, Luján, Argentina

    Juan J. Gaitán

  7. National Research Council of Argentina (CONICET), Buenos Aires, Argentina

    Juan J. Gaitán

  8. Department of Geosciences and Natural Resource Management, University of Copenhagen, Copenhagen, Denmark

    Carsten W. Mueller

  9. Museo Nacional de Ciencias Naturales (MNCN), CSIC, Madrid, Spain

    Ana Rey

  10. Departamento de Sistemas Físicos, Químicos y Naturales, Universidad Pablo de Olavide, Seville, Spain

    Tadeo Sáez-Sandino

  11. Center for Ecosystem Society and Science, Northern Arizona University, Flagstaff, AZ, USA

    Edward A. G. Schuur

  12. Physical and Life Sciences Directorate, Lawrence Livermore National Laboratory, Livermore, CA, USA

    Noah W. Sokol

  13. Mycology and Microbiology Center, University of Tartu, Tartu, Estonia

    Leho Tedersoo

  14. College of Science, King Saud University, Riyadh, Saudi Arabia

    Leho Tedersoo

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  1. Pablo García-Palacios
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Contributions

P.G.-P., M.A.B. and C.P. conceived and designed the research, with inputs from N.W.S.; P.G.-P., I.B.-F., J.C.G.-G., A.G.-U., M.P., A.R. and C.P. conducted the literature synthesis. M.D.-B., C.W.M., T.S.-S., E.A.G.S. and L.T. contributed soil samples. P.G.-P., M.d.C., J.J.G. and C.P. conducted the data analyses. The paper was drafted by P.G.-P., and all authors contributed to the final version.

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Correspondence to Pablo García-Palacios.

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Nature Geoscience thanks Yuanhe Yang and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Primary Handling Editor: Xujia Jiang, in collaboration with the Nature Geoscience team.

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Extended data

Extended Data Fig. 1 Global distribution of the study sites.

Global distribution of the study sites included in the observational meta-analysis addressing the distribution of soil organic carbon in particulate (POC) and mineral-associated (MAOC) fractions in cold systems (n = 134).

Extended Data Fig. 2 Linear mixed-effects modelling on POC and MAOC.

Difference in soil organic carbon concentration in POC vs. MAOC in the mineral layer of cold regions and its interactions with soil depth, permafrost, and biome type (Arctic, Subarctic, and Alpine). Main and interactions effects of C fraction (POC vs. MAOC) controlling for climate (MAT and MAP), net primary productivity (NPP), and soil properties (pH and clay + silt %). The variance explained by the fixed effect predictors and random effects relative to the total variance (R2) was 33% and 12%, respectively (n = 309). C fraction concentrations were natural-logarithm transformed. Dots and lines represent coefficients and 95% confidence intervals in the linear mixed effects model with C fraction (POC vs. MAOC) as a binary variable. MAT, mean annual temperature; MAP, mean annual precipitation. The panel corresponds to the first 30 cm of mineral soil. P values for two-tailed tests.

Extended Data Fig. 3 POC and MAOC by fractionation method.

Distribution of soil organic carbon in the POC and MAOC fractions in the mineral layer of cold regions separated by (a) size, (b) density, and (c) combination of size and density methods. Panels represent (left) overall fraction distribution or separated by (right) soil depth. Results from paired Wilcoxon signed-rank tests. POC = particulate organic C; MAOC = mineral-associated organic C. Box plots represent 1st and 3rd quartiles (box), medians (central horizontal line), largest value smaller than 1.5 times the interquartile range (upper vertical line), and smallest value larger than 1.5 times the interquartile range (lower vertical line). n = 87, 48 and 24 for both fractions in a, b and c, respectively. n = 80, 35 and 18 in a, b and c, respectively, in the first 30 cm of mineral soil. n = 7, 13 and 5 in a, b and c, respectively, in >30 cm. P values for two-tailed tests.

Extended Data Fig. 4 Random forest: environmental drivers versus POC and MAOC.

Random forest analysis to identify the relative importance of the different environmental drivers predicting soil organic carbon concentration in POC vs. MAOC in the mineral layer of cold regions. The relative importance is estimated on the basis of the increase in mean-square error (%IncMSE). This analysis was performed using data from the first 30 cm of mineral soil. POC random forest: R2 = 0.45 and MSE = 0.762 (n = 128), MAOC random forest: R2 = 0.36 and MSE = 0.519 (n = 127).

Extended Data Fig. 5 Active layer thickness versus fMAOC.

Relationship between active layer thickness and proportion of MAOC relative to SOC (fMAOC). Line and shading represent linear regression and 95% confidence intervals (fMAOC = 0.33 + 0.0014 × Active layer thickness, n = 133, R2 = 0.09, P = 0.031). The panel corresponds to the first 30 cm of mineral soil.

Extended Data Fig. 6 PRISMA-flowchart: observational meta-analysis.

PRISMA-flowchart of assessment of eligible studies in the observational meta-analysis of soil carbon fractions distribution in cold systems.

Extended Data Fig. 7 PRISMA-flowchart: experimental meta-analysis.

PRISMA-flowchart of assessment of eligible studies in the meta-analysis of experimental warming effects on soil carbon fractions.

Extended Data Table 1 Random-effects models of experimental warming
Full size table
Extended Data Table 2 Study selection criteria
Full size table

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García-Palacios, P., Bradford, M.A., Benavente-Ferraces, I. et al. Dominance of particulate organic carbon in top mineral soils in cold regions. Nat. Geosci. 17, 145–150 (2024). https://doi.org/10.1038/s41561-023-01354-5

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