Climate warming accelerates temporal scaling of grassland soil microbial biodiversity

Abstract

Determining the temporal scaling of biodiversity, typically described as species–time relationships (STRs), in the face of global climate change is a central issue in ecology because it is fundamental to biodiversity preservation and ecosystem management. However, whether and how climate change affects microbial STRs remains unclear, mainly due to the scarcity of long-term experimental data. Here, we examine the STRs and phylogenetic–time relationships (PTRs) of soil bacteria and fungi in a long-term multifactorial global change experiment with warming (+3 °C), half precipitation (−50%), double precipitation (+100%) and clipping (annual plant biomass removal). Soil bacteria and fungi all exhibited strong STRs and PTRs across the 12 experimental conditions. Strikingly, warming accelerated the bacterial and fungal STR and PTR exponents (that is, the w values), yielding significantly (P < 0.001) higher temporal scaling rates. While the STRs and PTRs were significantly shifted by altered precipitation, clipping and their combinations, warming played the predominant role. In addition, comparison with the previous literature revealed that soil bacteria and fungi had considerably higher overall temporal scaling rates (w = 0.39–0.64) than those of plants and animals (w = 0.21–0.38). Our results on warming-enhanced temporal scaling of microbial biodiversity suggest that the strategies of soil biodiversity preservation and ecosystem management may need to be adjusted in a warmer world.

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Fig. 1: STR and PTR of bacteria and fungi under warming (red) and control (blue) treatment conditions.
Fig. 2: Effect size (Cohen’s d) of all single and combined treatments.
Fig. 3: Changes in STR ws and PTR wp in major common phyla under different treatments.
Fig. 4: Comparison of STR and PTR exponents in micro- and macroorganisms.

References

  1. 1.

    Chase, J. M. Stochastic community assembly causes higher biodiversity in more productive environments. Science 328, 1388–1391 (2010).

  2. 2.

    Morlon, H. et al. Spatial patterns of phylogenetic diversity. Ecol. Lett. 14, 141–149 (2011).

  3. 3.

    Rosenzweig, M. L. Species Diversity in Space and Time (Cambridge Univ. Press, 1995).

  4. 4.

    Zhou, J., Kang, S., Schadt, C. W. & Garten, C. T. Jr. Spatial scaling of functional gene diversity across various microbial taxa. Proc. Natl Acad. Sci. USA 105, 7768–7773 (2008).

  5. 5.

    Lawton, J. H. Are there general laws in ecology? Oikos 84, 177–192 (1999).

  6. 6.

    Green, J. & Bohannan, B. J. Spatial scaling of microbial biodiversity. Trends Ecol. Evol. 21, 501–507 (2006).

  7. 7.

    Storch, D., Keil, P. & Jetz, W. Universal species–area and endemics–area relationships at continental scales. Nature 488, 78–81 (2012).

  8. 8.

    Sheik, C. S. et al. Effect of warming and drought on grassland microbial communities. ISME J. 5, 1692–1700 (2011).

  9. 9.

    Guilhaumon, F., Gimenez, O., Gaston, K. J. & Mouillot, D. Taxonomic and regional uncertainty in species–area relationships and the identification of richness hotspots. Proc. Natl Acad. Sci. USA 105, 15458–15463 (2008).

  10. 10.

    Horner-Devine, M. C., Lage, M., Hughes, J. B. & Bohannan, B. J. A taxa–area relationship for bacteria. Nature 432, 750–753 (2004).

  11. 11.

    Shade, A., Caporaso, J. G., Handelsman, J., Knight, R. & Fierer, N. A meta-analysis of changes in bacterial and archaeal communities with time. ISME J. 7, 1493–1506 (2013).

  12. 12.

    Chen, L. X. et al. Comparative metagenomic and metatranscriptomic analyses of microbial communities in acid mine drainage. ISME J. 9, 1579–1592 (2015).

  13. 13.

    van der Gast, C. J., Ager, D. & Lilley, A. K. Temporal scaling of bacterial taxa is influenced by both stochastic and deterministic ecological factors. Environ. Microbiol. 10, 1411–1418 (2008).

  14. 14.

    Deng, Y. et al. Spatial scaling of forest soil microbial communities across a temperature gradient. Environ. Microbiol. 20, 3504–3513 (2018).

  15. 15.

    Preston, F. W. Time and space and the variation of species. Ecology 41, 611–627 (1960).

  16. 16.

    Adler, P. B. & Lauenroth, W. K. The power of time: spatiotemporal scaling of species diversity. Ecol. Lett. 6, 749–756 (2003).

  17. 17.

    White, E P. et al. A comparison of the species–time relationship across ecosystems and taxonomic groups. Oikos 112, 185–195 (2006).

  18. 18.

    Carey, S., Ostling, A., Harte, J. & del Moral, R. Impact of curve construction and community dynamics on the species–time relationship. Ecology 88, 2145–2153 (2007).

  19. 19.

    Swenson, N. G. et al. Species–time–area and phylogenetic–time–area relationships in tropical tree communities. Ecol. Evol. 3, 1173–1183 (2013).

  20. 20.

    Devictor, V. et al. Spatial mismatch and congruence between taxonomic, phylogenetic and functional diversity: the need for integrative conservation strategies in a changing world. Ecol. Lett. 13, 1030–1040 (2010).

  21. 21.

    Winter, M. et al. Plant extinctions and introductions lead to phylogenetic and taxonomic homogenization of the European flora. Proc. Natl Acad. Sci. USA 106, 21721–21725 (2009).

  22. 22.

    Srivastava, D. S., Cadotte, M. W., MacDonald, A. A. M., Marushia, R. G. & Mirotchnick, N. Phylogenetic diversity and the functioning of ecosystems. Ecol. Lett. 15, 637–648 (2012).

  23. 23.

    Jabot, F. & Chave, J. Inferring the parameters of the neutral theory of biodiversity using phylogenetic information and implications for tropical forests. Ecol. Lett. 12, 239–248 (2009).

  24. 24.

    IPCC Climate Change 2013: The Physical Science Basis—Findings and Lessons Learned (eds. Stocker, T. F. et al.) (Cambridge Univ. Press, 2013).

  25. 25.

    Bellard, C., Bertelsmeier, C., Leadley, P., Thuiller, W. & Courchamp, F. Impacts of climate change on the future of biodiversity. Ecol. Lett. 15, 365–377 (2012).

  26. 26.

    Moss, R. H. et al. The next generation of scenarios for climate change research and assessment. Nature 463, 747–756 (2010).

  27. 27.

    Bebber, D. P., Ramotowski, M. A. T. & Gurr, S. J. Crop pests and pathogens move polewards in a warming world. Nat. Clim. Change 3, 985–988 (2013).

  28. 28.

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

  29. 29.

    Brown, J. H., Gillooly, J. F., Allen, A. P., Savage, V. M. & West, G. B. Toward a metabolic theory of ecology. Ecology 85, 1771–1789 (2004).

  30. 30.

    Zhou, J. et al. Temperature mediates continental-scale diversity of microbes in forest soils. Nat. Commun. 7, 12083 (2016).

  31. 31.

    Zhao, L. et al. Soil organic carbon and total nitrogen pools in permafrost zones of the Qinghai-Tibetan Plateau. Sci. Rep. 8, 3656 (2018).

  32. 32.

    Guo, X. et al. Climate warming leads to divergent succession of grassland microbial communities. Nat. Clim. Change 8, 813–818 (2018).

  33. 33.

    Zhou, J. et al. Stochasticity, succession, and environmental perturbations in a fluidic ecosystem. Proc. Natl Acad. Sci. USA 111, E836–E845 (2014).

  34. 34.

    Xu, X., Sherry, R. A., Niu, S., Li, D. & Luo, Y. Net primary productivity and rain‐use efficiency as affected by warming, altered precipitation, and clipping in a mixed‐grass prairie. Glob. Change Biol. 19, 2753–2764 (2013).

  35. 35.

    Shi, Z. et al. Successional change in species composition alters climate sensitivity of grassland productivity. Glob. Change Biol. 24, 4993–5003 (2018).

  36. 36.

    Xu, X. et al. Unchanged carbon balance driven by equivalent responses of production and respiration to climate change in a mixed-grass prairie. Glob. Change Biol. 22, 1857–1866 (2016).

  37. 37.

    Bardgett, R. D., Bowman, W. D., Kaufmann, R. & Schmidt, S. K. A temporal approach to linking aboveground and belowground ecology. Trends Ecol. Evol. 20, 634–641 (2005).

  38. 38.

    Tscherko, D., Hammesfahr, U., Zeltner, G., Kandeler, E. & Böcker, R. Plant succession and rhizosphere microbial communities in a recently deglaciated alpine terrain. Basic Appl. Ecol. 6, 367–383 (2005).

  39. 39.

    Shaw, M. R. et al. Grassland responses to global environmental changes suppressed by elevated CO2. Science 298, 1987–1990 (2002).

  40. 40.

    Zhou, X., Sherry, R. A., An, Y., Wallace, L. L. & Luo, Y. Main and interactive effects of warming, clipping, and doubled precipitation on soil CO2 efflux in a grassland ecosystem. Global Biogeochem. Cycles 20 https://doi.org/10.1029/2005GB002526 (2006).

  41. 41.

    Zavaleta, E. S., Shaw, M. R., Chiariello, N. R., Mooney, H. A. & Field, C. B. Additive effects of simulated climate changes, elevated CO2, and nitrogen deposition on grassland diversity. Proc. Natl Acad. Sci. USA 100, 7650–7654 (2003).

  42. 42.

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

  43. 43.

    Fierer, N., Bradford, M. A. & Jackson, R. B. Toward an ecological classification of soil bacteria. Ecology 88, 1354–1364 (2007).

  44. 44.

    Blois, J. L., Williams, J. W., Fitzpatrick, M. C., Jackson, S. T. & Ferrier, S. Space can substitute for time in predicting climate-change effects on biodiversity. Proc. Natl Acad. Sci. USA 110, 9374–9379 (2013).

  45. 45.

    Li, D., Zhou, X., Wu, L., Zhou, J. & Luo, Y. Contrasting responses of heterotrophic and autotrophic respiration to experimental warming in a winter annual-dominated prairie. Glob. Change Biol. 19, 3553–3564 (2013).

  46. 46.

    Yahdjian, L. & Sala, O. E. A rainout shelter design for intercepting different amounts of rainfall. Oecologia 133, 95–101 (2002).

  47. 47.

    Zhou, J., Bruns, M. A. & Tiedje, J. M. DNA recovery from soils of diverse composition. Appl. Environ. Microbiol. 62, 316–322 (1996).

  48. 48.

    Wu, L. et al. Phasing amplicon sequencing on Illumina Miseq for robust environmental microbial community analysis. BMC Microbiol. 15, 125 (2015).

  49. 49.

    Peiffer, J. A. et al. Diversity and heritability of the maize rhizosphere microbiome under field conditions. Proc. Natl Acad. Sci. USA 110, 6548–6553 (2013).

  50. 50.

    Caporaso, J. G. et al. Ultra-high-throughput microbial community analysis on the Illumina HiSeq and MiSeq platforms. ISME J. 6, 1621–1624 (2012).

  51. 51.

    Giardine, B. et al. Galaxy: a platform for interactive large-scale genome analysis. Genome Res. 15, 1451–1455 (2005).

  52. 52.

    Kong, Y. Btrim: a fast, lightweight adapter and quality trimming program for next-generation sequencing technologies. Genomics 98, 152–153 (2011).

  53. 53.

    Magoč, T. & Salzberg, S. L. FLASH: fast length adjustment of short reads to improve genome assemblies. Bioinformatics 27, 2957–2963 (2011).

  54. 54.

    Edgar, R. C. UPARSE: highly accurate OTU sequences from microbial amplicon reads. Nat. Methods 10, 996–998 (2013).

  55. 55.

    DeSantis, T. Z. et al. Greengenes, a chimera-checked 16S rRNA gene database and workbench compatible with ARB. Appl. Environ. Microbiol. 72, 5069–5072 (2006).

  56. 56.

    Wang, Q., Garrity, G. M., Tiedje, J. M. & Cole, J. R. Naive Bayesian classifier for rapid assignment of rRNA sequences into the new bacterial taxonomy. Appl. Environ. Microbiol. 73, 5261–5267 (2007).

  57. 57.

    Price, M. N., Dehal, P. S. & Arkin, A. P. FastTree 2—approximately maximum-likelihood trees for large alignments. PLoS ONE 5, e9490 (2010).

  58. 58.

    Kembel, S. W. et al. Picante: R tools for integrating phylogenies and ecology. Bioinformatics 26, 1463–1464 (2010).

  59. 59.

    Martiny, J. B., Eisen, J. A., Penn, K., Allison, S. D. & Horner-Devine, M. C. Drivers of bacterial β-diversity depend on spatial scale. Proc. Natl Acad. Sci. USA 108, 7850–7854 (2011).

  60. 60.

    Deng, Y. et al. Elevated carbon dioxide accelerates the spatial turnover of soil microbial communities. Glob. Change Biol. 22, 957–964 (2016).

  61. 61.

    R Core Team. R: a language and environment for statistical computing (R Foundation for Statistical Computing, 2013).

  62. 62.

    Stackebrandt, E. et al. Report of the ad hoc committee for the re-evaluation of the species definition in bacteriology. Int. J. Syst. Evol. Microbiol. 52, 1043–1047 (2002).

  63. 63.

    Gevers, D. et al. Re-evaluating prokaryotic species. Nat. Rev. Microbiol. 3, 733–739 (2005).

  64. 64.

    Fierer, N. & Lennon, J. T. The generation and maintenance of diversity in microbial communities. Am. J. Bot. 98, 439–448 (2011).

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Acknowledgements

We thank numerous former laboratory members for their help in maintaining the experimental site. This work is supported by the US Department of Energy, Office of Science, Genomic Science Program under award nos. DE-SC0004601 and DE-SC0010715, the National Science Foundation of China (award no. 41430856) and the Office of the Vice President for Research at the University of Oklahoma. X.G., X.Z. and Q.G. were generously supported by the China Scholarship Council (award no. 201406370046, 201306370141 and 201506210136).

Author information

All authors contributed intellectual input and assistance to this study. The original concept and experimental strategy were developed by J.Z., Y.L. and J.M.T. Field management was carried out by M.Y., J.F., B.F., X.Z., A.Z., L.H., Z.L., Liyou Wu and J.D.V.N. Collection sampling, DNA preparation and MiSeq sequencing analysis were carried out by X.Z., X.G., J.F., M.Y., Y.F. and L.H. Soil chemical analysis was carried out by X.Z., X.G. and M.Y. Various statistical analyses were carried by X.G., Z.S., D.N., Linwei Wu, W.S. and Q.G. Assistance in data interpretation was provided by G.Q., X.L., Z.H. and Y.Y. All data analysis and integration were guided by J.Z. The paper was written by J.Z. and X.G. with help from J.M.T. and D.N. Because of their contributions in terms of site management, and data collection, analysis and/or integration over the last 6 years, X.G., X.Z. and L.H. were listed as co-first authors.

Correspondence to Jizhong Zhou.

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