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Warming drives ecological community changes linked to host-associated microbiome dysbiosis


Anthropogenic climate warming affects many biological systems, ranging in scale from microbiomes to biomes. In many animals, warming-related fitness depression appears more closely linked to changes in ecological community interactions than to direct thermal stress. This biotic community framework is commonly applied to warming studies at the scale of ecosystems but is rarely applied at the scale of microbiomes. Here, we used replicated bromeliad microecosystems to show warming effects on tadpole gut microbiome dysbiosis mediated through biotic community interactions. Warming shifted environmental bacteria and arthropod community composition, with linkages to changes in microbial recruitment that promoted dysbiosis and stunted tadpole growth. Tadpole growth was more strongly associated with cascading effects of warming on gut dysbiosis than with direct warming effects or indirect effects on food resources. These results suggest that assessing warming effects on animal health requires an ecological community perspective on microbiome structure and function.

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Fig. 1: Bromeliad set-up and main experimental findings.
Fig. 2: Piecewise SEMs.

Data availability

Sequence data that support the findings of this study have been deposited in the NCBI Sequence Read Archive with the accession code PRJNA613682. Other data that support the findings of this study are available from the corresponding author upon reasonable request.


  1. 1.

    Ockendon, N. et al. Mechanisms underpinning climatic impacts on natural populations: altered species interactions are more important than direct effects. Glob. Change Biol. 20, 2221–2229 (2014).

    Google Scholar 

  2. 2.

    Cahill, A. E. et al. How does climate change cause extinction? Proc. R. Soc. B 280, 20121890 (2013).

    Google Scholar 

  3. 3.

    Penuelas, J., Filella, I. & Comas, P. Changed plant and animal life cycles from 1952 to 2000 in the Mediterranean region. Glob. Change Biol. 8, 531–544 (2002).

    Google Scholar 

  4. 4.

    Parmesan, C. et al. Poleward shifts in geographical ranges of butterfly species associated with regional warming. Nature 399, 579–583 (1999).

    CAS  Google Scholar 

  5. 5.

    Freeman, B. G., Yaw, J. A. L., Sunday, J. M. & Hargreaves, A. L. Expanding, shifting and shrinking: the impact of global warming on species’ elevational distributions. Glob. Ecol. Biogeogr. 27, 1268–1276 (2018).

    Google Scholar 

  6. 6.

    Draper, A. M. & Weissburg, M. J. Impacts of global warming and elevated CO2 on sensory behavior in predator–prey interactions: a review and synthesis. Front. Ecol. Evol. 7, 72 (2019).

    Google Scholar 

  7. 7.

    Romero, G. Q. et al. Global predation pressure redistribution under future climate change. Nat. Clim. Change 8, 1087–1091 (2018).

    Google Scholar 

  8. 8.

    Hudson, P. J., Cattadori, I. M., Boag, B. & Dobson, A. P. Climate disruption and parasite–host dynamics: patterns and processes associated with warming and the frequency of extreme climatic events. J. Helminthol. 80, 175–182 (2006).

    CAS  Google Scholar 

  9. 9.

    Robinson, C. J., Bohannan, B. J. M. & Young, V. B. From structure to function: the ecology of host-associated microbial communities. Microbiol. Mol. Biol. Rev. 74, 453–476 (2010).

    CAS  Google Scholar 

  10. 10.

    Longo, A. V. & Zamudio, K. R. Temperature variation, bacterial diversity and fungal infection dynamics in the amphibian skin. Mol. Ecol. 26, 4787–4797 (2017).

    Google Scholar 

  11. 11.

    Longo, A. V., Savage, A. E., Hewson, I. & Zamudio, K. R. Seasonal and ontogenetic variation of skin microbial communities and relationships to natural disease dynamics in declining amphibians. R. Soc. Open Sci. 2, 140377 (2015).

    Google Scholar 

  12. 12.

    Kohl, K. D. & Yahn, J. Effects of environmental temperature on the gut microbial communities of tadpoles. Environ. Microbiol. 18, 1561–1565 (2016).

    Google Scholar 

  13. 13.

    Fontaine, S. S., Novarro, A. J. & Kohl, K. D. Environmental temperature alters the digestive performance and gut microbiota of a terrestrial amphibian. J. Exp. Biol. 221, 187559 (2018).

    Google Scholar 

  14. 14.

    Woodhams, D. C. et al. Interacting symbionts and immunity in the amphibian skin mucosome predict disease risk and probiotic effectiveness. PLoS ONE 9, e96375 (2014).

    Google Scholar 

  15. 15.

    Muletz-Wolz, C. R. et al. Inhibition of fungal pathogens across genotypes and temperatures by amphibian skin bacteria. Front. Microbiol. 8, 1551 (2017).

    Google Scholar 

  16. 16.

    Bestion, E. et al. Climate warming reduces gut microbiota diversity in a vertebrate ectotherm. Nat. Ecol. Evol. 1, 0161 (2017).

    Google Scholar 

  17. 17.

    Meyer, E. A., Cramp, R. L., Bernal, M. H. & Franklin, C. E. Changes in cutaneous microbial abundance with sloughing: possible implications for infection and disease in amphibians. Dis. Aquat. Organ. 101, 235–242 (2012).

    Google Scholar 

  18. 18.

    Flury, S. & Gessner, M. O. Experimentally simulated global warming and nitrogen enrichment effects on microbial litter decomposers in a marsh. Appl. Environ. Microbiol. 77, 803–809 (2011).

    CAS  Google Scholar 

  19. 19.

    Belden, L. K. & Harris, R. N. Infectious diseases in wildlife: the community ecology context. Front. Ecol. Environ. 5, 533–539 (2007).

    Google Scholar 

  20. 20.

    Bernabé, T. N. et al. Warming weakens facilitative interactions between decomposers and detritivores, and modifies freshwater ecosystem functioning. Glob. Change Biol. 24, 3170–3186 (2018).

    Google Scholar 

  21. 21.

    Hoekman, D. Turning up the heat: temperature influences the relative importance of top-down and bottom-up effects. Ecology 91, 2819–2825 (2010).

    Google Scholar 

  22. 22.

    Becker, C. G. et al. Low-load pathogen spillover predicts shifts in skin microbiome and survival of a terrestrial-breeding amphibian. Proc. R. Soc. B 286, 20191114 (2019).

    Google Scholar 

  23. 23.

    Jiménez, R. R. & Sommer, S. The amphibian microbiome: natural range of variation, pathogenic dysbiosis, and role in conservation. Biodivers. Conserv. 26, 763–786 (2017).

    Google Scholar 

  24. 24.

    Greenspan, S. E. et al. Arthropod–bacteria interactions influence assembly of aquatic host microbiome and pathogen defense. Proc. R. Soc. B 286, 20190924 (2019).

    CAS  Google Scholar 

  25. 25.

    Walker, W. A. in The Microbiota in Gastrointestinal Pathophysiology: Implications for Human Health, Prebiotics, Probiotics, and Dysbiosis (eds Floch, M. H. et al.) 227–232 (Academic Press, 2016).

  26. 26.

    Zaneveld, J. R., McMinds, R. & Vega Thurber, R. Stress and stability: applying the Anna Karenina principle to animal microbiomes. Nat. Microbiol. 2, 17121 (2017).

    CAS  Google Scholar 

  27. 27.

    Jin Song, S. et al. Engineering the microbiome for animal health and conservation. Exp. Biol. Med. 244, 494–504 (2019).

    CAS  Google Scholar 

  28. 28.

    Kriss, M., Hazleton, K. Z., Nusbacher, N. M., Martin, C. G. & Lozupone, C. A. Low diversity gut microbiota dysbiosis: drivers, functional implications and recovery. Curr. Opin. Microbiol. 44, 34–40 (2018).

    Google Scholar 

  29. 29.

    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).

  30. 30.

    Sabagh, L. T., Ferreira, G. L., Branco, C. W. C., Rocha, C. F. D. & Dias, N. Y. N. Larval diet in bromeliad pools: a case study of tadpoles of two species in the genus Scinax (Hylidae). Copeia 2012, 683–689 (2012).

    Google Scholar 

  31. 31.

    Angilletta, M. J., Niewiarowski, P. H. & Navas, C. A. The evolution of thermal physiology in ectotherms. J. Therm. Biol. 27, 249–268 (2002).

    Google Scholar 

  32. 32.

    Becker, C. G., Longo, A. V., Haddad, C. F. B. & Zamudio, K. R. Land cover and forest connectivity alter the interactions among host, pathogen and skin microbiome. Proc. R. Soc. B 284, 20170582 (2017).

    Google Scholar 

  33. 33.

    Fukami, T. & Nakajima, M. Community assembly: alternative stable states or alternative transient states? Ecol. Lett. 14, 973–984 (2011).

    Google Scholar 

  34. 34.

    Wang, J. et al. Phylogenetic beta diversity in bacterial assemblages across ecosystems: deterministic versus stochastic processes. ISME J. 7, 1310–1321 (2013).

    CAS  Google Scholar 

  35. 35.

    Longo, A. V. & Zamudio, K. R. Environmental fluctuations and host skin bacteria shift survival advantage between frogs and their fungal pathogen. ISME J. 11, 349–361 (2017).

    Google Scholar 

  36. 36.

    Friedman, B. A. & Dugan, P. R. Identification of Zoogloea species and the relationship to zoogloeal matrix and floc formation. J. Bacteriol. 95, 1903–1909 (1968).

    CAS  Google Scholar 

  37. 37.

    Gao, N. et al. Both widespread PEP-CTERM proteins and exopolysaccharides are required for floc formation of Zoogloea resiniphila and other activated sludge bacteria. Environ. Microbiol. 20, 1677–1692 (2018).

    CAS  Google Scholar 

  38. 38.

    Merritt, R. W., Dadd, R. H. & Walker, E. D. Feeding behavior, natural food, and nutritional relationships of larval mosquitos. Annu. Rev. Entomol. 37, 349–376 (1992).

    CAS  Google Scholar 

  39. 39.

    Moghadam, F. S. & Zimmer, M. Effects of warming and nutrient enrichment on how grazing pressure affects leaf litter–colonizing bacteria. J. Environ. Qual. 43, 851–858 (2014).

    Google Scholar 

  40. 40.

    Zander, A., Bersier, L. & Gray, S. M. Effects of temperature variability on community structure in a natural microbial food web. Glob. Change Biol. 23, 56–67 (2017).

    Google Scholar 

  41. 41.

    Aguirre, A. A. & Tabor, G. M. Global factors driving emerging infectious diseases: Impact on wildlife populations. Ann. NY Acad. Sci. 1149, 1–3 (2008).

    Google Scholar 

  42. 42.

    Greenspan, S. E. et al. Infection increases vulnerability to climate change via effects on host thermal tolerance. Sci. Rep. 7, 9349 (2017).

    Google Scholar 

  43. 43.

    Neely, W. J. et al. Synergistic effects of warming and disease linked to high mortality in cool-adapted terrestrial frogs. Biol. Conserv. 245, 108521 (2020).

    Google Scholar 

  44. 44.

    Raffel, T. R. et al. Disease and thermal acclimation in a more variable and unpredictable climate. Nat. Clim. Change 3, 146–151 (2013).

    Google Scholar 

  45. 45.

    Raffel, T. R., Halstead, N. T., Mcmahon, T. A., Davis, A. K. & Rohr, J. R. Temperature variability and moisture synergistically interact to exacerbate an epizootic disease. Proc. R. Soc. B 282, 20142039 (2015).

    Google Scholar 

  46. 46.

    Greenspan, S. E. et al. White blood cell profiles in amphibians help to explain disease susceptibility following temperature shifts. Dev. Comp. Immunol. 77, 280–286 (2017).

    CAS  Google Scholar 

  47. 47.

    Dézerald, O. et al. Food-web structure in relation to environmental gradients and predator–prey ratios in tank-bromeliad ecosystems. PLoS ONE 8, e71735 (2013).

    Google Scholar 

  48. 48.

    Kitching, R. L. Food Webs and Container Habitats: The Natural History and Ecology of Phytotelmata (Cambridge Univ. Press, 2000).

  49. 49.

    Richardson, B. A. The bromeliad microcosm and the assessment of faunal diversity in a Neotropical forest. Biotropica 31, 321–336 (1999).

    Google Scholar 

  50. 50.

    Leroy, C. et al. What drives detrital decomposition in Neotropical tank bromeliads? Hydrobiologia 802, 85–95 (2017).

    Google Scholar 

  51. 51.

    Giongo, A. et al. Seasonal physiological parameters and phytotelmata bacterial diversity of two bromeliad species (Aechmea gamosepala and Vriesea platynema) from the Atlantic Forest of Southern Brazil. Diversity 11, 111 (2019).

    CAS  Google Scholar 

  52. 52.

    Frank, J. H. & Lounibos, L. P. Insects and allies associated with bromeliads: a review. Terr. Arthropod Rev. 1, 125–153 (2009).

    CAS  Google Scholar 

  53. 53.

    Ruano-Fajardo, G., Toledo, L. F. & Mott, T. Jumping into a trap: high prevalence of chytrid fungus in the preferred microhabitats of a bromeliad-specialist frog. Dis. Aquat. Organ. 121, 223–232 (2016).

    Google Scholar 

  54. 54.

    Gomez-Hoyos, D. A. et al. Phytotelmata selection by anurans and implications for their conservation at Las Tablas Protected Zone, Costa Rica. Alytes 35, 1–11 (2018).

    Google Scholar 

  55. 55.

    Haddad, C. F. B. et al. Guia dos Anfíbios da Mata Atlântica: Diversidade e Biologia (Anolis Books, 2013).

  56. 56.

    Gosner, K. L. A simplified table for staging anuran embryos and larvae with notes on identification. Herpetologica 16, 183–190 (1960).

    Google Scholar 

  57. 57.

    Oksanen, J. et al. vegan: community ecology package. R package version 2.4-1 (2016).

  58. 58.

    R Core Team. R: A Language and Environment for Statistical Computing (R Foundation for Statistical Computing, 2018).

  59. 59.

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

    CAS  Google Scholar 

  60. 60.

    Caporaso, J. G. et al. EMP 16S Illumina Amplicon Protocol (, 2018).

  61. 61.

    Kozich, J. J., Westcott, S. L., Baxter, N. T., Highlander, S. K. & Schloss, P. D. Development of a dual-index sequencing strategy and curation pipeline for analyzing amplicon sequence data on the MiSeq Illumina sequencing platform. Appl. Environ. Microbiol. 79, 5112–5120 (2013).

    CAS  Google Scholar 

  62. 62.

    Bolyen, E. et al. Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2. Nat. Biotechnol. 37, 848–857 (2019).

    Google Scholar 

  63. 63.

    Caporaso, J. G. et al. QIIME allows analysis of high-throughput community sequencing data. Nat. Methods 7, 335–336 (2010).

    CAS  Google Scholar 

  64. 64.

    Amir, A. et al. Deblur rapidly resolves single-nucleotide community sequence patterns. mSystems 2, e00191–16 (2017).

    Google Scholar 

  65. 65.

    Katoh, K., Misawa, K., Kuma, K. & Miyata, T. MAFFT: a novel method for rapid multiple sequence alignment based on fast Fourier transform. Nucleic Acids Res. 30, 3059–3066 (2002).

    CAS  Google Scholar 

  66. 66.

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

    Google Scholar 

  67. 67.

    Bokulich, N. A. et al. Optimizing taxonomic classification of marker-gene amplicon sequences with QIIME 2’s q2-feature-classifier plugin. Microbiome 6, 90 (2018).

    Google Scholar 

  68. 68.

    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).

    CAS  Google Scholar 

  69. 69.

    McDonald, D. et al. An improved Greengenes taxonomy with explicit ranks for ecological and evolutionary analyses of bacteria and archaea. ISME J. 6, 610–618 (2012).

    CAS  Google Scholar 

  70. 70.

    Bokulich, N. A. et al. Quality-filtering vastly improves diversity estimates from Illumina amplicon sequencing. Nat. Methods 10, 57–59 (2013).

    CAS  Google Scholar 

  71. 71.

    Faith, D. P. Conservation evaluation and phylogenetic diversity. Biol. Conserv. 61, 1–10 (1992).

    Google Scholar 

  72. 72.

    Lozupone, C. & Knight, R. UniFrac: a new phylogenetic method for comparing microbial communities. Appl. Environ. Microbiol. 71, 8228–8235 (2005).

    CAS  Google Scholar 

  73. 73.

    Lozupone, C. A., Hamady, M., Kelley, S. T. & Knight, R. Quantitative and qualitative β diversity measures lead to different insights into factors that structure microbial communities. Appl. Environ. Microbiol. 73, 1576–1585 (2007).

    CAS  Google Scholar 

  74. 74.

    Lozupone, C., Lladser, M. E., Knights, D., Stombaugh, J. & Knight, R. UniFrac: an effective distance metric for microbial community comparison. ISME J. 5, 169–172 (2011).

    Google Scholar 

  75. 75.

    Lefcheck, J. S. piecewiseSEM: Piecewise structural equation modelling in R for ecology. Methods Ecol. Evol. 7, 573–579 (2016).

    Google Scholar 

  76. 76.

    Deegan, J. On the occurrence of standardized regression coefficients greater than one. Educ. Psychol. Meas. 38, 873–888 (1978).

    Google Scholar 

  77. 77.

    JMP v.14.0.0 (SAS Institute, 2019).

  78. 78.

    Warnes, G. et al. gplots: various R programming tools for plotting data. R package version (2019).

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We thank R. Bell, T. Bernabe, M. Bletz, T. Jenkinson, R. Martins, D. Medina, W. Neely and R. Salla Jacob. São Paulo Research Foundation (FAPESP) provided grants to M.L.L. (grant no. 2017/26162-8), L.P.R. (grant nos. 2018/23622-0 and 2016/25358-3), L.F.T. (grant nos. 2016/25358-3 and 2019/18335-5), C.F.B.H. (grant no. 2013/50741-7) and G.Q.R. (grant nos. 2017/09052-4 and 2018/12225-0). National Council for Scientific and Technological Development (CNPq) provided research fellowships to L.F.T. (grant no. 300896/2016-6), C.F.B.H. (grant no. 306623/2018-8) and G.Q.R. The Royal Society provided a Newton Advanced Fellowship to G.Q.R. (grant no. NAF\R2\180791).

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C.G.B. and S.E.G. designed the study. All authors carried out the study. C.G.B., S.E.G. and G.Q.R. analysed the data. S.E.G. drafted the manuscript. All authors critically revised the manuscript.

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Correspondence to Sasha E. Greenspan.

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The authors declare no competing interests.

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Peer review information Nature Climate Change thanks Obed Hernandez-Gomez and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Greenspan, S.E., Migliorini, G.H., Lyra, M.L. et al. Warming drives ecological community changes linked to host-associated microbiome dysbiosis. Nat. Clim. Chang. 10, 1057–1061 (2020).

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