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Cross-biome patterns in soil microbial respiration predictable from evolutionary theory on thermal adaptation

Nature Ecology & Evolution volume 3, pages 223–231 (2019)Cite this article

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Abstract

Climate warming may stimulate microbial metabolism of soil carbon, causing a carbon-cycle–climate feedback whereby carbon is redistributed from the soil to atmospheric CO2. The magnitude of this feedback is uncertain, in part because warming-induced shifts in microbial physiology and/or community composition could retard or accelerate soil carbon losses. Here, we measure microbial respiration rates for soils collected from 22 sites in each of 3 years, at locations spanning boreal to tropical climates. Respiration was measured in the laboratory with standard temperatures, moisture and excess carbon substrate, to allow physiological and community effects to be detected independent of the influence of these abiotic controls. Patterns in respiration for soils collected across the climate gradient are consistent with evolutionary theory on physiological responses that compensate for positive effects of temperature on metabolism. Respiration rates per unit microbial biomass were as much as 2.6 times higher for soils sampled from sites with a mean annual temperature of −2.0 versus 21.7 °C. Subsequent 100-d incubations suggested differences in the plasticity of the thermal response among microbial communities, with communities sampled from sites with higher mean annual temperature having a more plastic response. Our findings are consistent with adaptive metabolic responses to contrasting thermal regimes that are also observed in plants and animals. These results may help build confidence in soil-carbon–climate feedback projections by improving understanding of microbial processes represented in biogeochemical models.

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Fig. 1: Competing assumptions for adaptive responses of soil microbial respiration to changes in thermal climate.
Fig. 2: Estimated effects of spatial variation in thermal climate (observational gradient) on soil microbial respiration rates.
Fig. 3: Estimated effects of experimental variation in thermal climate (incubator gradient)—with substrate supply—on soil microbial respiration rates.
Fig. 4: Estimated effects of experimental variation in thermal climate (incubator gradient)—without substrate supply—on soil microbial respiration rates.

Data availability

Data in the support of these findings and the R code for the statistical models are available via the Dryad Digital Repository (https://doi.org/10.5061/dryad.s87008d).

References

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

    CAS  Google Scholar 

  2. Bradford, M. A. et al. Managing uncertainty in soil carbon feedbacks to climate change. Nat. Clim. Change 6, 751–758 (2016).

    Google Scholar 

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

    Google Scholar 

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

    CAS  Google Scholar 

  5. 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 

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

    CAS  PubMed  Google Scholar 

  7. Romero-Olivares, A. L., Allison, S. D. & Treseder, K. K. Soil microbes and their response to experimental warming over time: a meta-analysis of field studies. Soil Biol. Biochem. 107, 32–40 (2017).

    CAS  Google Scholar 

  8. 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 

  9. Wieder, W. R. et al. Carbon cycle confidence and uncertainty: exploring variation among soil biogeochemical models. Glob. Change Biol. 24, 1563–1579 (2017).

    Google Scholar 

  10. Sulman, B. N. et al. Multiple models and experiments underscore large uncertainty in soil carbon dynamics. Biogeochemistry 141, 109–123 (2018).

    CAS  Google Scholar 

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

    CAS  Google Scholar 

  12. Tang, J. & Riley, W. J. Weaker soil carbon–climate feedbacks resulting from microbial and abiotic interactions. Nat. Clim. Change 5, 56–60 (2015).

    CAS  Google Scholar 

  13. 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. Nat. Clim. Change 4, 1099–1102 (2014).

    CAS  Google Scholar 

  14. Buchkowski, R. W., Bradford, M. A., Grandy, A. S., Schmitz, O. J. & Wieder, W. R. Applying population and community ecology theory to advance understanding of belowground biogeochemistry. Ecol. Lett. 20, 231–245 (2017).

    PubMed  Google Scholar 

  15. 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  Google Scholar 

  16. Hochachka, P. W. & Somero, G. N. Biochemical Adaptation: Mechanism and Process in Physiological Evolution (Oxford Univ. Press, New York, 2002).

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

    CAS  Google Scholar 

  18. Auffret, M. D. et al. The role of microbial community composition in controlling soil respiration responses to temperature. PLoS ONE 11, 0165448 (2016).

    Google Scholar 

  19. Pold, G., Melillo, J. M. & DeAngelis, K. M. Two decades of warming increases diversity of a potentially lignolytic bacterial community. Front. Microbiol. 6, 480 (2015).

    PubMed  PubMed Central  Google Scholar 

  20. Bai, Z. et al. Shifts in microbial trophic strategy explain different temperature sensitivity of CO2 flux under constant and diurnally varying temperature regimes. FEMS Microbiol. Ecol. 93, fix063 (2017).

  21. 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 

  22. Whitaker, J. et al. Microbial community composition explains soil respiration responses to changing carbon inputs along an Andes-to-Amazon elevation gradient. J. Ecol. 102, 1058–1071 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  23. Munafò, M. R. & Davey Smith, G. Repeating experiments is not enough. Nature 553, 399–401 (2018).

    PubMed  Google Scholar 

  24. Bengston, P. & Bengtsson, G. Rapid turnover of DOC in temperate forests accounts for increased CO2 production at elevated temperatures. Ecol. Lett. 10, 783–790 (2007).

    Google Scholar 

  25. Nazaries, L. et al. Shifts in the microbial community structure explain the response of soil respiration to land-use change but not to climate warming. Soil Biol. Biochem. 89, 123–134 (2015).

    CAS  Google Scholar 

  26. Fierer, N., Strickland, M. S., Liptzin, D., Bradford, M. A. & Cleveland, C. C. Global patterns in belowground communities. Ecol. Lett. 12, 1238–1249 (2009).

    PubMed  Google Scholar 

  27. Walker, T. W. N. et al. Microbial temperature sensitivity and biomass change explain soil carbon loss with warming. Nat. Clim. Change 8, 885–889 (2018).

    CAS  Google Scholar 

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

    PubMed  Google Scholar 

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

    CAS  Google Scholar 

  30. Rousk, J. Biomass or growth? How to measure soil food webs to understand structure and function. Soil Biol. Biochem. 102, 45–47 (2016).

    CAS  Google Scholar 

  31. Dacal, M., Bradford, M. A., Plaza, C., Maestre, F. T. & García-Palacios, P. Soil microbial respiration adapts to ambient temperature in global drylands. Nat. Ecol. Evol. https://doi.org/10.1038/s41559-018-0770-5 (2019).

  32. 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  Google Scholar 

  33. Hamdi, S., Moyano, F., Sall, S., Bernoux, M. & Chevallier, T. Synthesis analysis of the temperature sensitivity of soil respiration from laboratory studies in relation to incubation methods and soil conditions. Soil Biol. Biochem. 58, 115–126 (2013).

    CAS  Google Scholar 

  34. Angilletta, M. J. Jr Thermal Adaptation. A Theoretical and Empirical Synthesis (Oxford Univ. Press, New York, 2009).

  35. Bradford, M. A. Thermal adaptation of decomposer communities in warming soils. Front. Microbiol. 4, 333 (2013).

    PubMed  PubMed Central  Google Scholar 

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

    PubMed  Google Scholar 

  37. Tjoelker, M. G., Oleksyn, J., Reich, P. B. & Zytkowiak, R. Coupling of respiration, nitrogen, and sugars underlies convergent temperature acclimation in Pinus banksiana across wide-ranging sites and populations. Glob. Change Biol. 14, 782–797 (2008).

    Google Scholar 

  38. Crowther, T. W. et al. Untangling the fungal niche: the trait-based approach. Front. Microbiol. 5, 579 (2014).

    PubMed  PubMed Central  Google Scholar 

  39. Evans, S. E. & Wallenstein, M. D. Climate change alters ecological strategies of soil bacteria. Ecol. Lett. 17, 155–164 (2014).

    PubMed  Google Scholar 

  40. Blagodatskaya, E., Blagodatsky, S., Khomyakov, N., Myachina, O. & Kuzyakov, Y. Temperature sensitivity and enzymatic mechanisms of soil organic matter decomposition along an altitudinal gradient on Mount Kilimanjaro. Sci. Rep. 6, 22240 (2016).

    CAS  Google Scholar 

  41. Strickland, M. S., Keiser, A. D. & Bradford, M. A. Climate history shapes contemporary leaf litter decomposition. Biogeochemistry 122, 165–174 (2015).

    Google Scholar 

  42. Eilers, K. G., Lauber, C. L., Knight, R. & Fierer, N. Shifts in bacterial community structure associated with inputs of low molecular weight carbon compounds to soil. Soil Biol. Biochem. 42, 896–903 (2010).

    CAS  Google Scholar 

  43. Johnston, A. S. A. & Sibly, R. M. The influence of soil communities on the temperature sensitivity of soil respiration. Nat. Ecol. Evol. 2, 1597–1602 (2018).

    PubMed  Google Scholar 

  44. 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 

  45. Min, K., Lehmeier, C. A., Ballantyne, F. & Billings, S. A. Carbon availability modifies temperature responses of heterotrophic microbial respiration, carbon uptake affinity, and stable carbon isotope discrimination. Front. Microbiol. 7, 2083 (2016).

    PubMed  PubMed Central  Google Scholar 

  46. Schindlbacher, A., Schnecker, J., Takriti, M., Borken, W. & Wanek, W. Microbial physiology and soil CO2 efflux after 9 years of soil warming in a temperate forest—no indications for thermal adaptations. Glob. Change Biol. 21, 4265–4277 (2015).

    Google Scholar 

  47. Melillo, J. M. et al. Long-term pattern and magnitude of soil carbon feedback to the climate system in a warming world. Science 358, 101–104 (2017).

    CAS  Google Scholar 

  48. Wu, C. S. et al. Heterotrophic respiration does not acclimate to continuous warming in a subtropical forest. Sci. Rep. 6, 21561 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  49. 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 

  50. Georgiou, K., Abramoff, R. Z., Harte, J., Riley, W. J. & Torn, M. S. Microbial community-level regulation explains soil carbon responses to long-term litter manipulations. Nat. Commun. 8, 1223 (2017).

    PubMed  PubMed Central  Google Scholar 

  51. Crowther, T. W. et al. Predicting the responsiveness of soil biodiversity to deforestation: a cross-biome study. Glob. Change Biol. 20, 2983–2994 (2014).

    Google Scholar 

  52. Ratkowsky, D. A., Lowry, R. K., McMeekin, T. A., Stokes, A. N. & Chandler, R. E. Model for bacterial culture growth rate throughout the entire biokinetic temperature range. J. Bacteriol. 154, 1222–1226 (1983).

    CAS  PubMed  PubMed Central  Google Scholar 

  53. Paul, E. A., Morris, S. J. & Böhm, S. in Assessment Methods for Soil Carbon (eds Lal, R. Kimble, J. M., Follett, R. F. & Stewart, B. A.) 193–205 (CRC Press, Boca Raton, 2001).

  54. Bradford, M. A., Watts, B. W. & Davies, C. A. Thermal adaptation of heterotrophic soil respiration in laboratory microcosms. Glob. Change Biol. 16, 1576–1588 (2010).

    Google Scholar 

  55. Smets, W. et al. A method for simultaneous measurement of soil bacterial abundances and community composition via 16S rRNA gene sequencing. Soil Biol. Biochem. 96, 145–151 (2016).

    CAS  Google Scholar 

  56. Wardle, D. A. & Ghani, A. Why is the strength of relationships between pairs of methods for estimating soil microbial biomass often so variable? Soil Biol. Biochem. 27, 821–828 (1995).

    CAS  Google Scholar 

  57. Bradford, M. A. et al. Decreased mass specific respiration under experimental warming is robust to the microbial biomass method employed. Ecol. Lett. 12, E15–E18 (2009).

    Google Scholar 

  58. Anderson, J. P. E. & Domsch, K. H. A physiological method for the quantitative measurement of microbial biomass in soils. Soil Biol. Biochem. 10, 215–221 (1978).

    CAS  Google Scholar 

  59. Findlay, R. & Dobbs, F. in Current Methods in Aquatic Microbial Ecology (ed. Kemp, P. F.) 271–284 (Lewis Publications, Boca Raton, 1993).

  60. Grandy, A. S., Strickland, M. S., Lauber, C., Bradford, M. A. & Fierer, N. The influence of microbial communities, management, and soil texture on soil organic matter chemistry. Geoderma 150, 278–286 (2009).

    CAS  Google Scholar 

  61. Bradford, M. A. et al. A test of the hierarchical model of litter decomposition. Nat. Ecol. Evol. 1, 1836–1845 (2017).

    PubMed  Google Scholar 

  62. Jaśienski, M. & Bazzaz, F. A. The fallacy of ratios and the testability of models in biology. Oikos 84, 321–326 (1999).

    Google Scholar 

  63. Hobbs, N. T., Andren, H., Persson, J., Aronsson, M. & Chapron, G. Native predators reduce harvest of reindeer by Sámi pastoralists. Ecol. App. 22, 1640–1654 (2012).

    Google Scholar 

  64. Bolker, B. M. et al. Generalized linear mixed models: a practical guide for ecology and evolution. Trends Ecol. Evol. 24, 127–135 (2009).

    PubMed  Google Scholar 

  65. Gelman, A. & Hill, J. Data Analysis Using Regression and Multilevel/Hierarchical Models (Cambridge Univ. Press, Cambridge, 2007).

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

    PubMed  Google Scholar 

  67. Luke, S. G. Evaluating significance in linear mixed-effects models in R. Behav. Res. 49, 1494–1502 (2017).

    Google Scholar 

  68. Baayen, R. H., Davidson, D. J. & Bates, D. M. Mixed-effects modeling with crossed random effects for subjects and items. J. Mem. Lang. 59, 390–412 (2008).

    Google Scholar 

  69. Nakagawa, S. & Schielzeth, H. A general and simple method for obtaining R 2 from generalized linear mixed-effects models. Methods Ecol. Evol. 4, 133–142 (2013).

    Google Scholar 

  70. Bradford, M. A., Berg, B., Maynard, D. S., Wieder, W. R. & Wood, S. A. Understanding the dominant controls on litter decomposition. J. Ecol. 104, 229–238 (2016).

    CAS  Google Scholar 

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Acknowledgements

Research was supported by the US National Science Foundation with grants to M.A.B., R.L.M. and N.F. (DEB-1457614, -1021098, -1021222 and -1021112). This work was made possible by the generosity of researchers at the 11 locations who collected and packaged soils—in particular, A. Keiser, I. Halm, S. Bailey, M. Schulze, S. VanderWulp, P. O’Neal, T. Van Slyke, K. Chowanski, J. Love, A. Barker Plotkin, S. Cantrell and C. Giardina. Thanks also to J. Nelson for the PLFA analyses, and the Bradford laboratory group and M. Dacal for comments on an earlier version of the manuscript.

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Authors and Affiliations

  1. School of Forestry and Environmental Studies, Yale University, New Haven, CT, USA

    Mark A. Bradford, Emily E. Oldfield & Stephen A. Wood

  2. Department of Plant and Soil Science, University of Kentucky, Lexington, KY, USA

    Rebecca L. McCulley

  3. Institute of Integrative Biology, ETH Zurich, Zürich, Switzerland

    Thomas. W. Crowther

  4. The Nature Conservancy, Arlington, VA, USA

    Stephen A. Wood

  5. Department of Ecology and Evolutionary Biology, University of Colorado, Boulder, CO, USA

    Noah Fierer

  6. Cooperative Institute for Research in Environmental Sciences, University of Colorado, Boulder, CO, USA

    Noah Fierer

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Contributions

M.A.B., R.L.M. and N.F. co-designed the study and wrote the application for the grant that funded the work. M.A.B., R.L.M., E.E.O. and T.W.C. collected the data and performed the laboratory work. S.A.W. and M.A.B. carried out the statistical analyses. All authors contributed to interpreting the data and writing the paper.

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Correspondence to Mark A. Bradford.

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Bradford, M.A., McCulley, R.L., Crowther, T.W. et al. Cross-biome patterns in soil microbial respiration predictable from evolutionary theory on thermal adaptation. Nat Ecol Evol 3, 223–231 (2019). https://doi.org/10.1038/s41559-018-0771-4

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