Letter | Published:

Mycorrhiza-mediated competition between plants and decomposers drives soil carbon storage

Nature volume 505, pages 543545 (23 January 2014) | Download Citation


Soil contains more carbon than the atmosphere and vegetation combined1. Understanding the mechanisms controlling the accumulation and stability of soil carbon is critical to predicting the Earth’s future climate2,3. Recent studies suggest that decomposition of soil organic matter is often limited by nitrogen availability to microbes4,5,6 and that plants, via their fungal symbionts, compete directly with free-living decomposers for nitrogen6,7. Ectomycorrhizal and ericoid mycorrhizal (EEM) fungi produce nitrogen-degrading enzymes, allowing them greater access to organic nitrogen sources than arbuscular mycorrhizal (AM) fungi8,9,10. This leads to the theoretical prediction that soil carbon storage is greater in ecosystems dominated by EEM fungi than in those dominated by AM fungi11. Using global data sets, we show that soil in ecosystems dominated by EEM-associated plants contains 70% more carbon per unit nitrogen than soil in ecosystems dominated by AM-associated plants. The effect of mycorrhizal type on soil carbon is independent of, and of far larger consequence than, the effects of net primary production, temperature, precipitation and soil clay content. Hence the effect of mycorrhizal type on soil carbon content holds at the global scale. This finding links the functional traits of mycorrhizal fungi to carbon storage at ecosystem-to-global scales, suggesting that plant–decomposer competition for nutrients exerts a fundamental control over the terrestrial carbon cycle.

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  1. 1.

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

  2. 2.

    , & Model estimates of CO2 emissions from soil in response to global warming. Nature 351, 304–306 (1991)

  3. 3.

    , , & Long-term sensitivity of soil carbon turnover to warming. Nature 433, 298–301 (2005)

  4. 4.

    & The implications of exoenzyme activity on microbial carbon and nitrogen limitation in soil: a theoretical model. Soil Biol. Biochem. 35, 549–563 (2003)

  5. 5.

    , , , & Nitrogen alters carbon dynamics during early succession in boreal forest. Soil Biol. Biochem. 42, 1157–1164 (2010)

  6. 6.

    , & Disruption of root carbon transport into forest humus stimulates fungal opportunists at the expense of mycorrhizal fungi. ISME J. 4, 872–881 (2010)

  7. 7.

    & Mycorrhiza and litter decomposition. Science 233, 133 (1971)

  8. 8.

    et al. Boreal forest plants take up organic nitrogen. Nature 392, 914–916 (1998)

  9. 9.

    , & An arbuscular mycorrhizal fungus accelerates decomposition and acquires nitrogen directly from organic material. Nature 413, 297–299 (2001)

  10. 10.

    & Mycorrhizas and nutrient cycling in ecosystems—a journey towards relevance? New Phytol. 157, 475–492 (2003)

  11. 11.

    , , & Organic nutrient uptake by mycorrhizal fungi enhances ecosystem carbon storage: a model-based assessment. Ecol. Lett. 14, 493–502 (2011)

  12. 12.

    & Nitrogen limitation of net primary productivity in terrestrial ecosystems is globally distributed. Ecology 89, 371–379 (2008)

  13. 13.

    & Increasing plant use of organic nitrogen with elevation is reflected in nitrogen uptake rates and ecosystem δ15N. Ecology 92, 883–891 (2011)

  14. 14.

    , & Enzymatic activities of mycelia in mycorrhizal fungal communities. The Fungal Community: its Organization and Role in the Ecosystem 3rd edn, 331–348 (CRC Press, 2005)

  15. 15.

    , , , & Very high resolution interpolated climate surfaces for global land areas. Int. J. Climatol. 25, 1965–1978 (2005)

  16. 16.

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

  17. 17.

    et al. Systematic assessment of terrestrial biogeochemistry in coupled climate-carbon models. Glob. Change Biol. 15, 2462–2484 (2009)

  18. 18.

    , , , & Mineral control of soil organic carbon storage and turnover. Nature 389, 170–173 (1997)

  19. 19.

    & Plant growth-rate dependence of detrital carbon storage in ecosystems. Science 268, 1606–1608 (1995)

  20. 20.

    & Temperature sensitivity of soil carbon decomposition and feedbacks to climate change. Nature 440, 165–173 (2006)

  21. 21.

    et al. Intact amino acid uptake by northern hardwood and conifer trees. Oecologia 160, 129–138 (2009)

  22. 22.

    et al. Arbuscular mycorrhizal fungi increase organic carbon decomposition under elevated CO2. Science 337, 1084–1087 (2012)

  23. 23.

    & Mycorrhizae alter quality and quantity of carbon allocated below ground. Nature 369, 58–60 (1994)

  24. 24.

    et al. Mycorrhizal fungal diversity determines plant biodiversity, ecosystem variability and productivity. Nature 396, 69–72 (1998)

  25. 25.

    & Differential effects of sugar maple, red oak, and hemlock tannins on carbon and nitrogen cycling in temperate forest soils. Oecologia 155, 583–592 (2008)

  26. 26.

    et al. Persistence of soil organic matter as an ecosystem property. Nature 478, 49–56 (2011)

  27. 27.

    , , , & The Microbial Efficiency-Matrix Stabilization (MEMS) framework integrates plant litter decomposition with soil organic matter stabilization: do labile plant inputs form stable soil organic matter? Glob. Change Biol. 19, 988–995 (2013)

  28. 28.

    , , & The temperature response of soil microbial efficiency and its feedback to climate. Nature Clim. Change 3, 395–398 (2013)

  29. 29.

    , , & & the R Development Core Team nlme: Linear and Nonlinear Mixed Effects Models R package version 3. 1–109, (2013)

  30. 30.

    , , , & Relation between soil order and sorption of dissolved organic carbon in temperate subsoils. Soil Sci. Soc. Am. J. 76, 1027–1037 (2012)

  31. 31.

    & 2002. in Methods of Soil Analysis, Part 4: Physical Methods (eds & ) 201–203 (Soil Society of America, 2002)

  32. 32.

    & 2002. in Methods of Soil Analysis, Part 4: Physical Methods (eds & ) 255–293 (Soil Society of America, 2002)

  33. 33.

    Communities and Ecosystems 2nd edn, 111–191 (Macmillan, 1975)

  34. 34.

    AICcmodavg: Model selection and Multimodel Inference based on (Q)AIC(c) R package version 1.31,. (2013)

  35. 35.

    Least squares percentage regression. J. Mod. Appl. Stat. Methods 7, 526–534 (2008)

  36. 36.

    R2 measures based on wald and likelihood ratio joint significance tests. Am. Stat. 44, 250–253 (1990)

  37. 37.

    lmmfit: Goodness-of-Fit-Measures for Linear Mixed Models with One-Level-Grouping R package version 1.0,. (2011)

  38. 38.

    & An {R} Companion to Applied Regression 2nd edn (Sage Publications, 2011)

  39. 39.

    , & A protocol for data exploration to avoid common statistical problems. Methods Ecol. Evol. 1, 3–14 (2010)

  40. 40.

    The VGAM package for categorical data analysis. J. Stat. Softw. 32, 1–34 (2010)

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We thank L. Nave and the International Soil Carbon Network for access to their database. C. Hawkes provided feedback during data collection and initial analyses of C storage. C. Iversen, J. Powers and M. Vadeboncouer provided unpublished data that contributed to this analysis. D. Jacquier provided the Australian soil database and E. Carlston helped to extract data from the Australian soil database. C. Shaw provided the Siltanen soil carbon database and the Forest Ecosystem Carbon Database of Canadian soils. T. Baisden provided scans of the California Soil-Vegetation Survey. E. Brzostek, N. Fowler, P. Groffman, E. Hobbie, B. Schlesinger and B. Waring provided feedback on earlier versions of this manuscript. The Center for Tropical Forest Science (CTFS) and Smithsonian Institution Geo-observatories (SIGEO) provided funding for the collection and analysis of soil profile data at large forest dynamics plots, and we thank the many collaborators, field assistants and laboratory technicians who assisted in the collection and analysis of soil profile data. This work benefited from extensive data contributions to the International Soil Carbon Network from both the USDA Natural Resources Conservation Service, National Cooperative Soil Survey, and the US Geological Survey. C.A. was supported by a fellowship from the University of Texas at Austin and by the National Science Foundation Graduate Research Fellowship Program (grant DGE-1110007). A.C.F. was supported by NSF grant number DEB 07-43564 and DOE grants 10-DOE-1053 and DE-SC0006916. Any opinions, findings and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation.

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  1. Department of Integrative Biology, Graduate Program in Ecology, Evolution and Behavior, University of Texas at Austin, Austin, Texas 78712, USA

    • Colin Averill
  2. Smithsonian Tropical Research Institute, Apartado 0843-03092, Balboa, Ancon, Republic of Panama

    • Benjamin L. Turner
  3. Department of Biology, Boston University, Boston, Masachusetts 02215, USA

    • Adrien C. Finzi


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C.A. and B.L.T. collected the data. C.A. performed all statistical analyses. C.A. and A.C.F. conceptualized the work and wrote the manuscript. All authors contributed to revisions.

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The authors declare no competing financial interests.

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Correspondence to Colin Averill.

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