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Experimental warming leads to convergent succession of grassland archaeal community

Nature Climate Change volume 13, pages 561–569 (2023)Cite this article

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Abstract

Understanding the temporal succession of ecological communities and the underlying mechanisms in response to climate warming is critical for future climate projections. However, despite its fundamental importance in ecology and evolution, little is known about how the Archaea domain responds to warming. Here we showed that experimental warming of a tallgrass prairie ecosystem significantly altered the community structure of soil archaea and reduced their taxonomic and phylogenetic diversity. In contrast to previous observations in bacteria and fungi, we showed convergent succession of the soil archaeal community between warming and control. Although stochastic processes dominated the archaeal community, their relative importance decreased over time. Furthermore, the warming-induced changes in the archaeal community and soil chemistry had significant impacts on ecosystem functioning. Our results imply that, although the detrimental effects of biodiversity loss on ecosystems could be much severer, the soil archaeal community structure would be more predictable in a warmer world.

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Fig. 1: Effects of experimental warming on archaeal community diversity and succession across 7 yr.
Fig. 2: Ecological processes and community assembly mechanisms associated with the temporal dynamics in the soil archaeal community.
Fig. 3: Variations of ecological processes across different phylogenetic groups.
Fig. 4: Environmental drivers of archaeal community structure and functioning.

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Data availability

The DNA sequences of the archaeal 16S rRNA gene amplicons are available in the National Center for Biotechnology Information (NCBI) Sequence Read Archive under project accession number PRJNA861672. The DNA sequences of the bacterial 16S rRNA gene amplicons are under the project accession number PRJNA331185. Raw shotgun metagenomic sequences are deposited in the European Nucleotide Archive (http://www.ebi.ac.uk/ena) under study no. PRJNA533082. The soil physical and chemical attributes, and plant biomass and richness are downloadable online at http://www.ou.edu/ieg/publications/datasets. Silva 132 Ref NR database is available at https://www.arb-silva.de/documentation/release-132/. The Greengene reference dataset is available from the QIIME GitHub repository https://github.com/biocore/qiime-default-reference/blob/master/qiime_default_reference/gg_13_8_otus/rep_set/97_otus.fasta.gz. Source data are provided with this paper.

Code availability

R scripts for statistical analyses and source data are available on GitHub at https://github.com/yazhang2022/OKwarmingsiteArchaea.

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Acknowledgements

We thank all former and current members of the Institute for Environmental Genomics for their time and energy in maintaining the long-term climate change experiment. This work was supported by the US Department of Energy, Office of Science, Genomic Science Program under Award Number DE-SC0004601 and DE-SC0010715, and the Office of the Vice President for Research at the University of Oklahoma. The data analysis performed by D.N. and N.X. was also partially supported by NSF Grants EF-2025558 and DEB-2129235.

Author information

Authors and Affiliations

  1. Institute for Environmental Genomics and Department of Microbiology and Plant Biology, University of Oklahoma, Norman, OK, USA

    Ya Zhang, Daliang Ning, Linwei Wu, Mengting Maggie Yuan, Xishu Zhou, Yuanliang Hu, Siyang Jian, Zhifeng Yang, Shun Han, Jiajie Feng, Jialiang Kuang, Carolyn R. Cornell, Colin T. Bates, Yupeng Fan, Jonathan P. Michael, Yang Ouyang, Jiajing Guo, Zhipeng Gao, Zheng Shi, Naijia Xiao, Ying Fu, Aifen Zhou, Liyou Wu & Jizhong Zhou

  2. Institute of Ecology, Key Laboratory for Earth Surface Processes of the Ministry of Education, College of Urban and Environmental Sciences, Peking University, Beijing, China

    Linwei Wu

  3. Department of Environmental Science, Policy, and Management, University of California, Berkeley, CA, USA

    Mengting Maggie Yuan

  4. School of Minerals Processing and Bioengineering, Central South University, Changsha, Hunan, China

    Xishu Zhou & Xueduan Liu

  5. State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, China

    Xue Guo & Yunfeng Yang

  6. Hubei Key Laboratory of Edible Wild Plants Conservation and Utilization, College of Life Sciences, Hubei Normal University, Huangshi, China

    Yuanliang Hu

  7. Hunan Agriculture Product Processing Institute, Hunan Academy of Agricultural Sciences, Changsha, Hunan, China

    Jiajing Guo

  8. College of Animal Science and Technology, Hunan Agricultural University, Changsha, Hunan, China

    Zhipeng Gao

  9. Center for Microbial Ecology, Michigan State University, East Lansing, MI, USA

    James M. Tiedje

  10. School of Civil Engineering and Environmental Sciences, University of Oklahoma, Norman, OK, USA

    Jizhong Zhou

  11. School of Computer Science, University of Oklahoma, Norman, OK, USA

    Jizhong Zhou

  12. Earth and Environmental Sciences, Lawrence Berkeley National Laboratory, Berkeley, CA, USA

    Jizhong Zhou

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  1. Ya Zhang
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Contributions

All authors contributed intellectual input and assistance to this study. The original concepts were conceived by Y.Z. and J.Z. Field management was carried out by Y.Z., Linwei Wu, M.M.Y., X.Z., X.G., S.J., Z.Y., S.H., J.F., J.K., C.R.C., C.T.B., Y. Fan, J.P.M., Y.O., Y. Fu, D.N., Z.S., N.X., A.Z. and Liyou Wu. Sample collection, soil chemical and microbial characterization were carried out by Y.H., M.M.Y., Linwei Wu, J.G. and Z.G. Data analyses were done by Y.Z. and D.N. with assistance from Linwei Wu and J.Z. All data analysis and integration were guided by J.Z. The manuscript was prepared by Y.Z., D.N., X.L., Y.Y., J.M.T. and J.Z.

Corresponding author

Correspondence to Jizhong Zhou.

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The authors declare no competing interests.

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Nature Climate Change thanks Federica D’Alò and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Extended data

Extended Data Fig. 1 Effects of experimental warming on archaeal community composition under unwarmed and warmed conditions at the order level.

Cumulative richness is expressed as the number of operational taxonomic units (OTUs).

Extended Data Fig. 2 The succession of soil archaea communities under unwarmed and warmed treatments by detrended correspondence analysis (DCA).

Individual samples from warmed and unwarmed plots within each year are shown in (a) and the centroids of four replicates from each treatment within each year are shown in (b). The analysis was performed based on Sorensen dissimilarity metric. Warmed samples are clustered together with control samples in year 0 (2009) and separated from control samples in the following seven years (2010–2016).

Source data

Extended Data Fig. 3 Temporal changes in community differences between warming and control conditions for archaea and fungi.

The first year is 2009 (year 0). Considering the repeated-measures design, the warming-versus-control dissimilarity values at each block were fitted to the linear mixed-effects (LMMs) models with a fixed effect of time and a random intercept and slope effect among different pairs of plots (blocks). The slopes are presented as a coefficient in fixed effect ± standard error in random effect. The r2 values are calculated (details in Methods), reflecting the variance explained by the whole LMM model. p values were based on permutation tests (two-sided). The lines showed the fixed effects of the LMM.

Source data

Extended Data Fig. 4 Temporal changes in community differences between warming and control conditions for orders Nitrososphaerales and Methanomassiliicoccales.

The analysis was performed based on unweighted UniFrac metrics. Considering the repeated-measures design, the warming-versus-control dissimilarity values at each block were fitted to LMMs with a fixed effect of time and a random intercept and slope effect among different pairs of plots (blocks). The slopes are presented as a coefficient in fixed effect ± standard error in random effect. The r2 values are calculated (details in Methods), reflecting the variance explained by the whole LMM model. p values were based on permutation tests (two-sided). The lines showed the fixed effects of the LMM.

Source data

Extended Data Fig. 5 Constrained ordination analysis of archaeal communities.

(a) Canonical correspondence analyses (CCA) of soil archaea community and environmental attributes. Tested environmental attributes include soil nitrate (NO3−), ammonium (NH4+), total nitrogen (TN), total organic C (TOC), pH, Precipitation of sampling month (Prcp_SM), temperature, moisutre drought index, C3 and C4 aboveground biomass, plant richness, and total biomass. The insert table shows the significance of each environmental variable in explaining the variations of archaeal community (one-way ANOVA test). (b) CCA-based variation partitioning analysis (VPA) showed the relative proportions of archaeal community variations that can be explained by different types of environmental factors. The numbers within the circles showed the variation explained by each group of environmental factors alone. The numbers between the circles showed the interactions of the two factors on either side and number in the center of the interactions of all three factors.

Extended Data Fig. 6 Constrained ordination analysis of the order Nitrososphaerales.

(a) CCA of the Nitrososphaerales group and environmental attributes. The tested environmental attributes and other properties are the same as in Extended Data Fig. 5 (one-way ANOVA test). Significant tests (P < 0.05) are shown in bold red. (b) CCA-based VPA showed the relative proportions of variations in the Nitrososphaerales group that can be explained by different types of environmental factors. The numbers within the circles showed the variation explained by each group of environmental factors alone. The numbers between the circles showed the interactions of the two factors on either side and number in the center of the interactions of all three factors.

Extended Data Fig. 7 Warming-induced changes of different bins.

Warming-induced difference between warming and control is expressed in percentages for the three dominating ecological processes—homogeneous selection (HoS), dispersal limitation (DL), and drift and others (DR).

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Extended Data Fig. 8 Relationships between archaeal community structure and environmental variables and ecosystem processes under control.

Archaeal community structures, which include taxonomical composition by 16 S rRNA genes and functional gene composition by GeoChip and EcoFUN-MAP, were tested against time, soil and plant variables and ecosystem C fluxes. All the other properties are the same as Fig. 4a.

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Zhang, Y., Ning, D., Wu, L. et al. Experimental warming leads to convergent succession of grassland archaeal community. Nat. Clim. Chang. 13, 561–569 (2023). https://doi.org/10.1038/s41558-023-01664-x

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