Aridity differentially alters the stability of soil bacterial and fungal networks in coastal and inland areas of Australia

Abstract Despite the importance of soil bacterial and fungal communities for ecosystem services and human welfare, how their ecological networks respond to climatic aridity have yet been evaluated. Here, we collected soil samples from 47 sites across 2500 km in coastal and inland areas of eastern Australia with contrasting status of aridity. We found that the diversity of both bacteria and fungi significantly differed between inland and coastal soils. Despite the significant differences in soil nutrient availability and stoichiometry between the inland and coastal regions, aridity was the most important predictor of bacterial and fungal community compositions. Aridity has altered the potential microbial migration rates and further impacted the microbial assembly processes by increasing the importance of stochasticity in bacterial and fungal communities. More importantly, ecological network analysis indicated that aridity enhanced the complexity and stability of the bacterial network but reduced that of the fungal network, possibly due to the contrasting impacts of aridity on the community‐level habitat niche breadth and overlaps. Our work paves the way towards a more comprehensive understanding of how climate changes will alter soil microbial communities, which is integral to predicting their long‐term consequences for ecosystem sustainability and resilience to future disturbances.

[1]  Zhengang Wang,et al.  Soil microbial network complexity predicts ecosystem function along elevation gradients on the Tibetan Plateau , 2022, Soil Biology and Biochemistry.

[2]  B. Griffiths,et al.  Energy flux across multitrophic levels drives ecosystem multifunctionality: Evidence from nematode food webs , 2022, Soil Biology and Biochemistry.

[3]  Jizhong Zhou,et al.  Precipitation balances deterministic and stochastic processes of bacterial community assembly in grassland soils , 2022, Soil Biology and Biochemistry.

[4]  Yong-guan Zhu,et al.  Aridity decreases soil protistan network complexity and stability , 2022, Soil Biology and Biochemistry.

[5]  C. Kaiser,et al.  From diversity to complexity: Microbial networks in soils , 2021, bioRxiv.

[6]  Cara H. Haney,et al.  Drought dampens microbiome development , 2021, Nature Plants.

[7]  Jizhong Zhou,et al.  Climate warming enhances microbial network complexity and stability , 2021, Nature Climate Change.

[8]  Qing‐Lin Chen,et al.  Microbial communities in crop phyllosphere and root endosphere are more resistant than soil microbiota to fertilization , 2021 .

[9]  Michelle E. Afkhami,et al.  Environmental stress destabilizes microbial networks , 2021, The ISME Journal.

[10]  Qing‐Lin Chen,et al.  Fertilization alters protistan consumers and parasites in crop-associated microbiomes. , 2021, Environmental microbiology.

[11]  Yong-guan Zhu,et al.  Deterministic selection dominates microbial community assembly in termite mounds , 2020, Soil Biology and Biochemistry.

[12]  M. Schloter,et al.  Land-use intensity alters networks between biodiversity, ecosystem functions, and services , 2020, Proceedings of the National Academy of Sciences.

[13]  L. F. Toledo,et al.  Warming drives ecological community changes linked to host-associated microbiome dysbiosis , 2020, Nature Climate Change.

[14]  Davey L. Jones,et al.  Soil textural heterogeneity impacts bacterial but not fungal diversity , 2020, Soil Biology and Biochemistry.

[15]  Yunfeng Yang,et al.  Balance between community assembly processes mediates species coexistence in agricultural soil microbiomes across eastern China , 2019, The ISME Journal.

[16]  J. Jansson,et al.  Soil microbiomes and climate change , 2019, Nature Reviews Microbiology.

[17]  Jizhong Zhou,et al.  A general framework for quantitatively assessing ecological stochasticity , 2019, Proceedings of the National Academy of Sciences.

[18]  F. Bengelsdorf,et al.  Different response of bacteria, archaea and fungi to process parameters in nine full‐scale anaerobic digesters , 2019, Microbial biotechnology.

[19]  R. Henrik Nilsson,et al.  The UNITE database for molecular identification of fungi: handling dark taxa and parallel taxonomic classifications , 2018, Nucleic Acids Res..

[20]  J. Prosser,et al.  Soil bacterial networks are less stable under drought than fungal networks , 2018, Nature Communications.

[21]  Falk Hildebrand,et al.  Structure and function of the global topsoil microbiome , 2018, Nature.

[22]  J. Stegen,et al.  Soil pH mediates the balance between stochastic and deterministic assembly of bacteria , 2018, The ISME Journal.

[23]  Akash R. Sastri,et al.  Contrasting the relative importance of species sorting and dispersal limitation in shaping marine bacterial versus protist communities , 2017, The ISME Journal.

[24]  N. Fierer Embracing the unknown: disentangling the complexities of the soil microbiome , 2017, Nature Reviews Microbiology.

[25]  S. Sørensen,et al.  It is elemental: soil nutrient stoichiometry drives bacterial diversity , 2017, Environmental microbiology.

[26]  Shiwei Guo,et al.  Insight into how organic amendments can shape the soil microbiome in long-term field experiments as revealed by network analysis , 2016 .

[27]  Yan He,et al.  Geographic patterns of co-occurrence network topological features for soil microbiota at continental scale in eastern China , 2016, The ISME Journal.

[28]  William A. Walters,et al.  Improved Bacterial 16S rRNA Gene (V4 and V4-5) and Fungal Internal Transcribed Spacer Marker Gene Primers for Microbial Community Surveys , 2015, mSystems.

[29]  K. Foster,et al.  The ecology of the microbiome: Networks, competition, and stability , 2015, Science.

[30]  E. Pebesma,et al.  Classes and Methods for Spatial Data , 2015 .

[31]  Pelin Yilmaz,et al.  The SILVA ribosomal RNA gene database project: improved data processing and web-based tools , 2012, Nucleic Acids Res..

[32]  J. Raes,et al.  Microbial interactions: from networks to models , 2012, Nature Reviews Microbiology.

[33]  L. Meester,et al.  Body size and dispersal mode as key traits determining metacommunity structure of aquatic organisms. , 2012, Ecology letters.

[34]  Noah Fierer,et al.  Using network analysis to explore co-occurrence patterns in soil microbial communities , 2011, The ISME Journal.

[35]  Robert C. Edgar,et al.  BIOINFORMATICS APPLICATIONS NOTE , 2001 .

[36]  William A. Walters,et al.  QIIME allows analysis of high-throughput community sequencing data , 2010, Nature Methods.

[37]  R. Knight,et al.  Pyrosequencing-Based Assessment of Soil pH as a Predictor of Soil Bacterial Community Structure at the Continental Scale , 2009, Applied and Environmental Microbiology.

[38]  P. Legendre,et al.  vegan : Community Ecology Package. R package version 1.8-5 , 2007 .

[39]  Andy Liaw,et al.  Classification and Regression by randomForest , 2007 .

[40]  S. Nee,et al.  Quantifying the roles of immigration and chance in shaping prokaryote community structure. , 2006, Environmental microbiology.

[41]  T. White Amplification and direct sequencing of fungal ribosomal RNA genes for phylogenetics , 1990 .