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Managing uncertainty in soil carbon feedbacks to climate change

Abstract

Planetary warming may be exacerbated if it accelerates loss of soil carbon to the atmosphere. This carbon-cycle–climate feedback is included in climate projections. Yet, despite ancillary data supporting a positive feedback, there is limited evidence for soil carbon loss under warming. The low confidence engendered in feedback projections is reduced further by the common representation in models of an outdated knowledge of soil carbon turnover. 'Model-knowledge integration' — representing in models an advanced understanding of soil carbon stabilization — is the first step to build confidence. This will inform experiments that further increase confidence by resolving competing mechanisms that most influence projected soil-carbon stocks. Improving feedback projections is an imperative for establishing greenhouse gas emission targets that limit climate change.

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Figure 1: Soil C stocks are the net result of outputs and inputs of plant C, but most warming research focuses only on outputs, making stock responses highly uncertain.
Figure 2: Timescale of organismal responses to warming, with the potential that initial increases in microbial activity are exacerbated or mitigated through physiological, population and community-level responses as the warming perturbation continues.
Figure 3: The dual role of soil microbes as the agents of both soil C decomposition and stabilization.
Figure 4: Proposed activities to address low confidence in the projected magnitude of carbon–climate feedbacks.

References

  1. 1

    Conant, R. T. et al. Temperature and soil organic matter decomposition rates — synthesis of current knowledge and a way forward. Glob. Change Biol. 17, 3392–3404 (2011).

    Google Scholar 

  2. 2

    Lu, M. et al. Responses of ecosystem carbon cycle to experimental warming: a meta-analysis. Ecology 94, 726–738 (2013).

    Google Scholar 

  3. 3

    Dorrepaal, E. et al. Carbon respiration from subsurface peat accelerated by climate warming in the subarctic. Nature 460, 616–619 (2013).

    Google Scholar 

  4. 4

    Frey, S. D., Lee, J., Melillo, J. M. & Six, J. The temperature response of soil microbial efficiency and its feedback to climate. Nature Clim. Change 3, 395–398 (2013).

    CAS  Google Scholar 

  5. 5

    Karhu, K. et al. Temperature sensitivity of soil respiration rates enhanced by microbial community response. Nature 513, 81–84 (2014).

    CAS  Google Scholar 

  6. 6

    Melillo, J. M. et al. Soil warming, carbon–nitrogen interactions, and forest carbon budgets. Proc. Natl Acad. Sci. USA 108, 9508–9512 (2011).

    CAS  Google Scholar 

  7. 7

    Zhou, J. et al. Microbial mediation of carbon-cycle feedbacks to climate warming. Nature Clim. Change 2, 106–110 (2012).

    CAS  Google Scholar 

  8. 8

    Friedlingstein, P. et al. Uncertainties in CMIP5 climate projections due to carbon cycle feedbacks. J Clim. 27, 511–526 (2014).

    Google Scholar 

  9. 9

    Arora, V. K. et al. Carbon-concentration and carbon-climate feedbacks in CMIP5 Earth System Models. J Clim. 26, 5289–5314 (2013).

    Google Scholar 

  10. 10

    Jones, C. et al. Twenty-first-century compatible CO2 emissions and airborne fraction simulated by CMIP5 Earth system models under four representative concentration pathways. J Clim. 26, 4398–4413 (2013). This study laid out the idea of 'allowable emissions', highlighting the importance of terrestrial carbon cycle uncertainty in projecting allowable greenhouse gas emissions that are compatible with specified climate targets.

    Google Scholar 

  11. 11

    Ciais, P. et al. in Climate Change 2013: The Physical Science Basis (eds Stocker, T. F. et al.) 465–570 (IPCC, Cambridge Univ. Press, 2013).

    Google Scholar 

  12. 12

    Jobbágy, E. G. & Jackson, R. B. The vertical distribution of soil organic carbon and its relation to climate and vegetation. Ecol. Appl. 10, 423–436 (2000).

    Google Scholar 

  13. 13

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

    Google Scholar 

  14. 14

    Denman, K. L. et al. in Climate Change 2007: The Physical Science Basis (eds Solomon, S. et al.) 499–587 (IPCC, Cambridge Univ. Press, 2007).

    Google Scholar 

  15. 15

    Giardina, C. P., Litton, C. M., Crow, S. E. & Asner, G. P. Warming-related increases in soil CO2 efflux are explained by increased below-ground carbon flux. Nature Clim. Change 4, 822–827 (2014). This study across an elevation gradient in a tropical forest showed that the positive relationship between temperature and soil respiration rates occurred not through expected direct warming effects on soil-C decomposition but because of higher plant C inputs belowground.

    CAS  Google Scholar 

  16. 16

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

    CAS  Google Scholar 

  17. 17

    Davidson, D. A., Savage, K. E. & Finzi, A. C. A big-microsite framework for soil carbon modeling. Glob. Change Biol. 20, 3610–3620 (2014). This opinion piece proposed a modular model structure to represent the complexity of processes influencing soil C turnover, bringing representations of soil C turnover in line with those of photosynthesis in ecosystem and global models.

    Google Scholar 

  18. 18

    Wieder, W. R., Grandy, A. S., Kallenbach, C. M. & Bonan, G. B. Integrating microbial physiology and physio-chemical principles in soils with the MIcrobial–MIneral Carbon Stabilization (MIMICS) model. Biogeosci. 11, 1147–1185 (2014).

    Google Scholar 

  19. 19

    Wieder, W. R., Bonan, G. B. & Allison, S. D. Global soil carbon projections are improved by modelling microbial processes. Nature Clim. Change 3, 909–912 (2013).

    CAS  Google Scholar 

  20. 20

    Jenkinson, D. S., Adams, D. E. & Wild, A. Model estimates of CO2 emissions from soil in response to global warming. Nature 351, 304–306 (1991).

    CAS  Google Scholar 

  21. 21

    Todd-Brown, K. E. O., Hopkins, F. M., Kivlin, S. N., Talbot, J. M. & Allison, S. D. A framework for representing microbial decomposition in coupled climate models. Biogeochem. 109, 19–33 (2012).

    Google Scholar 

  22. 22

    Castellano, M. J., Mueller, K. E., Olk, D. C., Sawyer, J. E. & Six, J. Integrating plant litter quality, soil organic matter stabilization, and the carbon saturation concept. Glob. Change Biol. 21, 3200–3209 (2015). This opinion laid out a new conceptual model that integrates advances in understanding of how microbial physiology controls soil C cycling, with established physico-chemical principles that dictate whether physiological responses influence soil C stocks.

    Google Scholar 

  23. 23

    Cotrufo, M. F., Wallenstein, M. D., Boot, C. M., Denef, K. & Paul, E. 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).

    Google Scholar 

  24. 24

    Friedlingstein, P. et al. Climate-carbon cycle feedback analysis: results from the C4MIP model intercomparison. J. Clim. 19, 3337–3353 (2006).

    Google Scholar 

  25. 25

    Cox, P. M. et al. Sensitivity of tropical carbon to climate change constrained by carbon dioxide variability. Nature 494, 341–344 (2013).

    CAS  Google Scholar 

  26. 26

    Exbrayat, J.-F., Pitman, A. J. & Abramowitz, G. Response of microbial decomposition to spin-up explains CMIP5 soil carbon range until 2100. Geosci. Model Dev. 7, 3481–3504 (2014).

    Google Scholar 

  27. 27

    Todd-Brown, K. E. O. et al. Causes of variation in soil carbon simulations from CMIP5 Earth system models and comparison with observations. Biogeosci. 10, 1717–1736 (2013).

    Google Scholar 

  28. 28

    Hawkins, E. & Sutton, R. The potential to narrow uncertainty in regional climate predictions. Bull. Am. Meteorol. Soc. 90, 1095–1107 (2009). This study identified sources of uncertainty in physical climate projections: revealing that at decadal timescales model uncertainty is a dominant uncertainty source at regional and global scales, and highlighting the large gains in certainty possible by refining climate models.

    Google Scholar 

  29. 29

    Knutti, R. & Sedláček, J. Robustness and uncertainties in the new CMIP5 climate model projections. Nature Clim. Change 3, 369–373 (2013). This study showed that model spread (that is, uncertainty) in physical-based climate projections changed little from the fourth to fifth assessment report of the IPCC, yet the authors argued that confidence in these projections should be substantially greater given major advances in representing mechanistic understanding.

    Google Scholar 

  30. 30

    Melillo, J. M. et al. Soil warming and carbon-cycle feedbacks to the climate system. Science 298, 2173–2176 (2002).

    CAS  Google Scholar 

  31. 31

    Kirschbaum, M. U. F. The temperature dependence of organic-matter decomposition — still a topic of debate. Soil Biol. Biochem. 38, 2510–2518 (2006).

    CAS  Google Scholar 

  32. 32

    Torn, M. S., Vitousek, P. M. & Trumbore, S. E. The influence of nutrient availability on soil organic matter turnover estimated by incubations and radiocarbon modeling. Ecosystems 8, 352–372 (2005).

    CAS  Google Scholar 

  33. 33

    Lehmann, J. et al. Spatial complexity of soil organic matter forms at nanometre scales. Nature Geosci. 1, 238–242 (2008).

    CAS  Google Scholar 

  34. 34

    Vogel, C. et al. Submicron structures provide preferential spots for carbon and nitrogen sequestration in soils. Nature Commun. 5, 2947 (2014). This empirical study showed that decomposition of plant C inputs into more stable soil C fractions occurred preferentially via association with mineral surfaces already clustered with organic matter, changing ideas about how soil clay content relates to the potential of soils to sequester C.

    Google Scholar 

  35. 35

    Strickland, M. S., DeVore, J. L., Maerz, J. C. & Bradford, M. A. Grass invasion of a hardwood forest is associated with declines in belowground carbon pools. Glob. Change Biol. 16, 1338–1350 (2010).

    Google Scholar 

  36. 36

    Bradford, M. A., Keiser, A. D., Davies, C. A., Mersmann, C. A. & Strickland, M. S. Empirical evidence that soil carbon formation from plant inputs is positively related to microbial growth. Biogeochem. 113, 271–281 (2013).

    CAS  Google Scholar 

  37. 37

    Clemmensen, K. E. et al. Roots and associated fungi drive long-term carbon sequestration in boreal forest. Science 339, 1615–1618 (2013).

    CAS  Google Scholar 

  38. 38

    Keiluweit, M. et al. Mineral protection of soil carbon counteracted by root exudates. Nature Clim. Change 5, 588–595 (2015). This empirical study showed that plant-root inputs could directly liberate soil C from protective associations with minerals, bypassing the presumed direct microbial role in decomposing this 'stable' soil C fraction.

    CAS  Google Scholar 

  39. 39

    Liang, C. & Balser, T. C. Warming and nitrogen deposition lessen microbial residue contribution to soil carbon pool. Nature Commun. 3, 1222 (2012).

    Google Scholar 

  40. 40

    Neff, J. C. et al. Variable effects of nitrogen additions on the stability and turnover of soil carbon. Nature 419, 915–917 (2002).

    CAS  Google Scholar 

  41. 41

    Torn, M. S. et al. A call for international soil experiment networks for studying, predicting, and managing global change impacts. SOIL 1, 575–582 (2015).

    Google Scholar 

  42. 42

    Sistla, S. A. et al. Long-term warming restructures Arctic tundra without changing net soil carbon storage. Nature 497, 615–618 (2013).

    CAS  Google Scholar 

  43. 43

    Gifford, R. M. & Roderick, M. L. Soil carbon stocks and bulk density: spatial or cumulative mass coordinates as a basis of expression? Glob. Change Biol. 9, 1507–1514 (2003). This study showed how conventional soil sampling procedures might fail to measure real changes in soil C stocks with time, and the authors proposed that a mass-dependent method be broadly adopted to address these issues.

    Google Scholar 

  44. 44

    Hopkins, D. W. et al. Soil organic carbon contents in long-term experimental grassland plots in the UK (Palace Leas and Park Grass) have not changed consistently in recent decades. Glob. Change Biol. 15, 1739–1754 (2009).

    Google Scholar 

  45. 45

    Schmitz, O. J. et al. Animating the carbon cycle. Ecosystems 17, 344–359 (2014).

    CAS  Google Scholar 

  46. 46

    Reich, P. B. The carbon dioxide exchange. Science 329, 774–775 (2010).

    CAS  Google Scholar 

  47. 47

    Bradford, M. A. et al. Thermal adaptation of soil microbial respiration to elevated temperature. Ecol. Lett. 11, 1316–1327 (2008).

    Google Scholar 

  48. 48

    Hagerty, S. B. et al. Accelerated microbial turnover but constant growth efficiency with warming in soil. Nature Clim. Change 4, 903–906 (2014).

    CAS  Google Scholar 

  49. 49

    Crowther, T. W. & Bradford, M. A. Thermal acclimation in widespread heterotrophic soil microbes. Ecol. Lett. 16, 469–477 (2013).

    Google Scholar 

  50. 50

    Crowther, T. W. et al. Biotic interactions mediate soil microbial feedbacks to climate change. Proc. Natl Acad. Sci. USA 112, 7033–7038 (2015).

    CAS  Google Scholar 

  51. 51

    Mahecha, M. D. et al. Global convergence in the temperature sensitivity of respiration at ecosystem level. Science 329, 838–840 (2010).

    CAS  Google Scholar 

  52. 52

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

    CAS  Google Scholar 

  53. 53

    Allison, S. D. Modeling adaptation of carbon use efficiency in microbial communities. Front. Microbiol. 5, e571 (2014).

    Google Scholar 

  54. 54

    Todd-Brown, K. E. O. et al. Changes in soil organic carbon storage predicted by Earth system models during the 21st century. Biogeosci. 11, 2341–2356 (2014).

    CAS  Google Scholar 

  55. 55

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

    CAS  Google Scholar 

  56. 56

    Carvalhais, N. et al. Global covariation of carbon turnover times with climate in terrestrial ecosystems. Nature 514, 213–217 (2014).

    CAS  Google Scholar 

  57. 57

    Davidson, E. A., Samanta, S., Caramori, S. S. & Savage, K. The Dual Arrhenius and Michaelis-Menten kinetics model for decomposition of soil organic matter at hourly to seasonal time scales. Glob. Change Biol. 18, 371–384 (2012).

    Google Scholar 

  58. 58

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

    CAS  Google Scholar 

  59. 59

    Bradford, M. A. Thermal adaptation of decomposer communities in warming soils. Front. Microbiol. 4, e333 (2013).

    Google Scholar 

  60. 60

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

    CAS  Google Scholar 

  61. 61

    Miltner, A., Bombach, P., Schmidt-Brücken, B. & Kästner, M. SOM genesis: microbial biomass as a significant source. Biogeochem. 111, 41–55 (2012).

    CAS  Google Scholar 

  62. 62

    Liang, C. & Balser, T. C. Microbial production of recalcitrant organic matter in global soils: implications for productivity and climate policy. Nature Rev. Microbiol. 9, 75–77 (2010).

    Google Scholar 

  63. 63

    Ahrens, B., Braakhekke, M. C., Guggenberger, G., Schrumpf, M. & Reichstein, M. Contribution of sorption, DOC transport and microbial interactions to the 14C age of a soil organic carbon profile: insights from a calibrated process model. Soil Biol. Biochem. 88, 390–402 (2015).

    CAS  Google Scholar 

  64. 64

    Grandy, A. S. & Neff, J. C. Molecular C dynamics downstream: the biochemical decomposition sequence and its impact on soil organic matter structure and function. Sci. Total Environ. 404, 297–307 (2008).

    CAS  Google Scholar 

  65. 65

    Tang, J. & Riley, W. J. Weaker soil carbon–climate feedbacks resulting from microbial and abiotic interactions. Nature Clim. Change 5, 56–60 (2015). This study showed that use of a dynamic, as opposed to the conventional static, model structure to represent spatiotemporal dependencies in temperature, microbial and mineral surface interactions, predicted weaker but more variable soil-C–climate feedbacks.

    CAS  Google Scholar 

  66. 66

    Dungait, J. A. J., Hopkins, D. W., Gregory, A. S. & Whitmore, A. P. Soil organic matter turnover is governed by accessibility not recalcitrance. Glob. Change Biol. 18, 1781–1796 (2012).

    Google Scholar 

  67. 67

    Doetterl, S. et al. Soil carbon storage controlled by interactions between geochemistry and climate. Nature Geosci. 8, 780–783 (2015).

    CAS  Google Scholar 

  68. 68

    Marschner, B. et al. How relevant is recalcitrance for the stabilization of organic matter in soils? J. Plant. Nutr. Soil. Sci. 171, 91–110 (2008).

    CAS  Google Scholar 

  69. 69

    Crowther, T. W. et al. Environmental stress response limits microbial necromass contributions to soil organic carbon. Soil Biol. Biochem. 85, 153–161 (2015).

    CAS  Google Scholar 

  70. 70

    Högberg, P. & Read, D. J. Towards a more plant physiological perspective on soil ecology. Trends Ecol. Evol. 21, 548–554 (2006).

    Google Scholar 

  71. 71

    van Hees, P. A. W., Jones, D. L., Finlay, R., Godbold, D. L. & Lundström, U. S. The carbon we do not see-the impact of low molecular weight compounds on carbon dynamics and respiration in forest soils: a review. Soil Biol. Biochem. 37, 1–13 (2005).

    CAS  Google Scholar 

  72. 72

    Pittelkow, C. M. et al. Productivity limits and potentials of the principles of conservation agriculture. Nature 517, 365–368 (2015).

    CAS  Google Scholar 

  73. 73

    Koven, C. D., Lawrence, D. M. & Riley, W. J. Permafrost carbon−climate feedback is sensitive to deep soil carbon decomposability but not deep soil nitrogen dynamics. Proc. Natl Acad. Sci. USA 112, 3752–3757 (2015).

    CAS  Google Scholar 

  74. 74

    Collins, M. et al. in Climate Change 2013: The Physical Science Basis (eds Stocker, T. F. et al.) 1029–1136 (IPCC, Cambridge Univ. Press, 2013).

    Google Scholar 

  75. 75

    Sierra, C. A., Müller, M. & Trumbore, S. E. Models of soil organic matter decomposition: the SoilR package, version 1.0. Geosci. Model Dev. Discuss. 5, 1045–1060 (2012).

    Google Scholar 

  76. 76

    Xia, J., Luo, Y., Wang, Y.-P. & Hararuk, O. Traceable components of terrestrial carbon storage capacity in biogeochemical models. Glob. Change Biol. 19, 2104–2116 (2013).

    Google Scholar 

  77. 77

    Flato, G. et al. in Climate Change 2013: The Physical Science Basis (eds Stocker, T. F. et al.) 741–866 (IPCC, Cambridge Univ. Press, 2013).

    Google Scholar 

  78. 78

    Stocker, T. F. et al. in Climate Change 2013: The Physical Science Basis (eds Stocker, T. F. et al.) 33–115 (IPCC, Cambridge Univ. Press, 2013).

    Google Scholar 

  79. 79

    Wenzel, S., Cox, P. M., Eyring, V. & Friedlingstein, P. Emergent constraints on climate-carbon cycle feedbacks in the CMIP5 Earth system models. J. Geophys. Res. 119, 794–807 (2014).

    CAS  Google Scholar 

  80. 80

    Luo, Y. et al. Towards more realistic projections of soil carbon dynamics by Earth System Models. Glob. Biogeochem. Cycles 29, 40–56 (2015).

    Google Scholar 

  81. 81

    Luo, Y., Keenan, T. F. & Smith, M. Predictability of the terrestrial carbon cycle. Glob. Change Biol. 21, 1737–1751 (2015).

    Google Scholar 

  82. 82

    Reich, P. B. et al. Nitrogen limitation constrains sustainability of ecosystem response to CO2 . Nature 440, 922–925 (2006).

    CAS  Google Scholar 

  83. 83

    Wieder, W. R., Cleveland, C. C., Smith, W. K. & Todd-Brown, K. Future productivity and carbon storage limited by terrestrial nutrient availability. Nature Geosci. 8, 441–444 (2015).

    CAS  Google Scholar 

  84. 84

    Zhang, Q., Wang, Y. P., Matear, R. J., Pitman, A. J. & Dai, Y. J. Nitrogen and phosphorous limitations significantly reduce future allowable CO2 emissions. Geophys. Res. Lett. 41, 632–637 (2014).

    CAS  Google Scholar 

  85. 85

    Hararuk, O., Smith, M. J. & Luo, Y. Microbial models with data-driven parameters predict stronger soil carbon responses to climate change. Glob. Change Biol. 21, 2439–2453 (2015).

    Google Scholar 

  86. 86

    Sulman, B. N., Phillips, R. P., Oishi, A. C., Shevliakova, E. & Pacala, S. W. Microbe-driven turnover offsets mineral-mediated storage of soil carbon under elevated CO2 . Nature Clim. Change 4, 1099–1102 (2014).

    CAS  Google Scholar 

  87. 87

    Wieder, W. R., Grandy, A. S., Kallenbach, C. M., Taylor, P. G. & Bonan, G. B. Representing life in the Earth system with soil microbial functional traits in the MIMICS model. Geosci. Model Dev. Discuss. 8, 2011–2052 (2015).

    Google Scholar 

  88. 88

    Parton, W. J., Schimel, D. S., Cole, C. V. & Ojima, D. S. Analysis of factors controlling soil organic matter levels in Great Plains grasslands. Soil. Sci. Soc. Am. J. 51, 1173–1179 (1987).

    CAS  Google Scholar 

  89. 89

    Bonan, G. B., Hartman, M. D., Parton, W. J. & Wieder, W. R. Evaluating litter decomposition in earth system models with long-term litterbag experiments: an example using the Community Land Model version 4 (CLM4). Glob. Change Biol. 19, 957–974 (2013).

    Google Scholar 

  90. 90

    Sinsabaugh, R. L., Manzoni, S., Moorhead, D. L. & Richter, A. Carbon use efficiency of microbial communities: stoichiometry, methodology and modelling. Ecol. Lett. 16, 930–939 (2013).

    Google Scholar 

  91. 91

    Burd, A. B. et al. Terrestrial and marine perspectives on modeling organic matter degradation pathways. Glob. Change Biol. 22, 121–136 (2016).

    Google Scholar 

  92. 92

    Grant, R. F., Humphreys, E. R. & Lafleur, P. M. Ecosystem CO2 and CH4 exchange in a mixed tundra and a fen within a hydrologically diverse Arctic landscape: 1. Modeling versus measurements. J. Geophys. Res-Biogeosci. 120, 1366–1387 (2015).

    CAS  Google Scholar 

  93. 93

    Jones, C. et al. Global climate change and soil carbon stocks; predictions from two contrasting models for the turnover of organic carbon in soil. Glob. Change Biol. 11, 154–166 (2005).

    Google Scholar 

  94. 94

    Manzoni, S. & Porporato, A. Soil carbon and nitrogen mineralization: theory and models across scales. Soil Biol. Biochem. 41, 1355–1379 (2009).

    CAS  Google Scholar 

  95. 95

    German, D. P., Marcelo, K. R. B., Stone, M. M. & Allison, S. D. The Michaelis-Menten kinetics of soil extracellular enzymes in response to temperature: a cross-latitudinal study. Glob. Change Biol. 18, 1468–1479 (2012).

    Google Scholar 

  96. 96

    Tucker, C. L., Bell, J., Pendall, E. & Ogle, K. Does declining carbon-use efficiency explain thermal acclimation of soil respiration with warming? Glob. Change Biol. 19, 252–263 (2013).

    Google Scholar 

  97. 97

    Suseela, V., Conant, R. T., Wallenstein, M. D. & Dukes, J. S. Effects of soil moisture on the temperature sensitivity of heterotrophic respiration vary seasonally in an old-field climate change experiment. Glob. Change Biol. 18, 336–348 (2012).

    Google Scholar 

  98. 98

    Shipley, B., Lechowicz, M. J., Wright, I. & Reich, P. B. Fundamental trade-offs generating the worldwide leaf economics spectrum. Ecology 87, 535–541 (2006).

    Google Scholar 

  99. 99

    Manning, P. et al. Simple measures of climate, soil properties and plant traits predict national-scale grassland soil carbon stocks. J. Appl. Ecol. 52, 1188–1196 (2015).

    CAS  Google Scholar 

  100. 100

    Averill, C., Turner, B. L. & Finzi, A. C. Plant−decomposer competition for nitrogen increases soil carbon storage in ecto- and ericoid-mycorrhizal ecosystems. Nature 505, 543–545 (2014).

    CAS  Google Scholar 

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Acknowledgements

This work was supported by grants from the US National Science Foundation (DEB-1021098 and DEB-1457614). M.A.B. was supported by The Royal Netherlands Academy of Arts and Sciences (Visiting Professors Programme); T.W.C. was supported by the Yale Climate and Energy Institute and a Marie Skłodowska Curie Fellowship; and W.R.W. was supported by grants from the US Department of Agriculture (NIFA 2015-67003-23485) and the US Department of Energy (TES DE-SC0014374). Thanks to W.v.d.P. and F.C. for comments on an earlier draft of this script.

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M.A.B. conceived the overall idea for this manuscript and together with T.W.C. synthesized empirical information, and with W.R.W. modelling knowledge. M.A.B., W.R.W., G.B.B., N.F., P.A.W. and T.W.C. then co-developed the ideas and written material.

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Correspondence to Mark A. Bradford.

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Bradford, M., Wieder, W., Bonan, G. et al. Managing uncertainty in soil carbon feedbacks to climate change. Nature Clim Change 6, 751–758 (2016). https://doi.org/10.1038/nclimate3071

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