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Differences in Precipitation Regime Shape Microbial Community Composition and Functional Potential in Namib Desert Soils

  • Soil Microbiology
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Abstract

Precipitation is one of the major constraints influencing the diversity, structure, and activity of soil microbial communities in desert ecosystems. However, the effect of changes in precipitation on soil microbial communities in arid soil microbiomes remains unresolved. In this study, using 16S rRNA gene high-throughput sequencing and shotgun metagenome sequencing, we explored changes in taxonomic composition and functional potential across two zones in the Namib Desert with contrasting precipitation regime. We found that precipitation regime had no effect on taxonomic and functional alpha-diversity, but that microbial community composition and functional potential (beta-diversity) changed with increased precipitation. For instance, Acidobacteriota and ‘resistance to antibiotics and toxic compounds’ related genes were relatively more abundant in the high-rainfall zone. These changes were largely due to a small set of microbial taxa, some of which were present in low abundance (i.e. members of the rare biosphere). Overall, these results indicate that key climatic factors (i.e. precipitation) shape the taxonomic and functional attributes of the arid soil microbiome. This research provides insight into how changes in precipitation patterns associated with global climate change may impact microbial community structure and function in desert soils.

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Availability of Data and Material

The metagenome sequence data and 16S amplicon sequence data are available on NCBI (http://www.ncbi.nlm.nih.gov/PRJNA592367).

Code Availability

There are no unreported custom computer code or algorithms used to generate results in this paper.

References

  1. Makhalanyane TP, Valverde A, Gunnigle E et al (2015) Microbial ecology of hot desert edaphic systems. FEMS Microbiol Rev 39:203–221. https://doi.org/10.1093/femsre/fuu011

    Article  CAS  PubMed  Google Scholar 

  2. Heulin T, De Luca G, Barakat M, et al (2017) Bacterial adaptation to hot and dry deserts. in: adaptation of microbial life to environmental extremes. 75–98

  3. León-Sobrino C, Ramond J, Maggs-Kölling G, Cowan DA (2019) Nutrient acquisition, rather than stress response over diel cycles, drives microbial transcription in a hyper-arid namib desert soil. Front Microbiol 10:1–11. https://doi.org/10.3389/fmicb.2019.01054

    Article  Google Scholar 

  4. Jansson JK, Hofmockel K (2020) Soil microbiomes and climate change. Nat Rev Microbiol 18:35–46. https://doi.org/10.1038/s41579-019-0265-7

    Article  CAS  PubMed  Google Scholar 

  5. Durant SM, Pettorelli N, Bashir S et al (2012) edited by Jennifer Sills Forgotten Biodiversity in Desert Ecosystems. Science (80- ) 336:1–2

    Article  Google Scholar 

  6. Quoreshi AM, Suleiman MK, Kumar V et al (2019) Untangling the bacterial community composition and structure in selected Kuwait desert soils. Appl Soil Ecol 138:1–9. https://doi.org/10.1016/j.apsoil.2019.02.006

    Article  Google Scholar 

  7. Zheng Q, Hu Y, Zhang S et al (2019) Soil multifunctionality is affected by the soil environment and by microbial community composition and diversity. Soil Biol Biochem 136:107521. https://doi.org/10.1016/j.soilbio.2019.107521

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Fierer N, Leff JW, Adams BJ et al (2012) Cross-biome metagenomic analyses of soil microbial communities and their functional attributes. Proc Natl Acad Sci 109:21390–21395. https://doi.org/10.1073/pnas.1215210110

    Article  PubMed  PubMed Central  Google Scholar 

  9. Noronha MF, Lacerda Júnior GV, Gilbert JA, de Oliveira VM (2017) Taxonomic and functional patterns across soil microbial communities of global biomes. Sci Total Environ 609:1064–1074. https://doi.org/10.1016/j.scitotenv.2017.07.159

    Article  CAS  PubMed  Google Scholar 

  10. She W, Bai Y, Zhang Y et al (2018) Resource Availability Drives Responses of Soil Microbial Communities to Short-term Precipitation and Nitrogen Addition in a Desert Shrubland. Front Microbiol 9:1–14. https://doi.org/10.3389/fmicb.2018.00186

    Article  Google Scholar 

  11. Andrew DR, Fitak RR, Munguia-Vega A et al (2012) Abiotic factors shape microbial diversity in sonoran desert soils. Appl Environ Microbiol 78:7527–7537. https://doi.org/10.1128/aem.01459-12

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Aslam SN, Dumbrell AJ, Sabir JS et al (2016) Soil compartment is a major determinant of the impact of simulated rainfall on desert microbiota. Environ Microbiol 18:5048–5062. https://doi.org/10.1111/1462-2920.13474

    Article  CAS  PubMed  Google Scholar 

  13. Neilson JW, Califf K, Cardona C et al (2017) Significant Impacts of Increasing Aridity on the Arid Soil Microbiome. mSystems 2:1–15

    Article  Google Scholar 

  14. Frossard A, Ramond J, Seely M, Cowan DA (2015) Water regime history drives responses of soil Namib Desert microbial communities to wetting events. Sci Rep 5:1–13. https://doi.org/10.1038/srep12263

    Article  CAS  Google Scholar 

  15. Pointing SB, Belnap J (2012) Microbial colonization and controls in dryland systems. Nat Rev Microbiol 10:551–562. https://doi.org/10.1038/nrmicro2831

    Article  CAS  PubMed  Google Scholar 

  16. Eckardt FD, Soderberg K, Coop LJ et al (2012) The nature of moisture at Gobabeb, in the central Namib Desert. J Arid Environ 93:7–19. https://doi.org/10.1016/j.jaridenv.2012.01.011

    Article  Google Scholar 

  17. Scola V, Ramond JB, Frossard A et al (2018) Namib Desert soil microbial community diversity, assembly, and function along a natural xeric gradient. Microb Ecol 75:193–203. https://doi.org/10.1007/s00248-017-1009-8

    Article  CAS  PubMed  Google Scholar 

  18. Wassenaar TD, Henschel JR, Pfaffenthaler MM et al (2013) Ensuring the future of the Namib’s biodiversity: Ecological restoration as a key management response to a mining boom. J Arid Environ 93:126–135. https://doi.org/10.1016/j.jaridenv.2012.05.012

    Article  Google Scholar 

  19. Bachar A, Al-Ashhab A, Soares MIM et al (2010) Soil microbial abundance and diversity along a low precipitation gradient. Microb Ecol 60:453–461. https://doi.org/10.1007/s00248-010-9727-1

    Article  PubMed  Google Scholar 

  20. Angel R, Soares MIM, Ungar ED, Gillor O (2010) Biogeography of soil archaea and bacteria along a steep precipitation gradient. ISME J 4:553–563. https://doi.org/10.1038/ismej.2009.136

    Article  PubMed  Google Scholar 

  21. Crits-Christoph A, Robinson CK, Barnum T et al (2013) Colonization patterns of soil microbial communities in the Atacama Desert. Microbiome 1:1–13

    Article  Google Scholar 

  22. Fetzer I, Johst K, Schäwe R et al (2015) The extent of functional redundancy changes as species ’ roles shift in different environments. Proc Natl Acad Sci 112:14888–14893. https://doi.org/10.1073/pnas.1505587112

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Lu X, Wang L, Pan M et al (2016) A multi-scale analysis of Namibian rainfall over the recent decade – comparing TMPA satellite estimates and ground observations. J Hydrol 8:59–68

    Google Scholar 

  24. Bray RH, Kurtz LT (1945) Determination of total, organic, and available forms of phosphorus in soils. Soil Sci 59:39–46. https://doi.org/10.1097/00010694-194501000-00006

    Article  CAS  Google Scholar 

  25. Andrews S (2010) Fastqc: A quality control tool for high throughput sequence data. http://www.bioinformatics.babraham.ac.uk/projects/fastqc

  26. Schmieder R, Edwards R (2012) Insights into antibiotic resistance through metagenomic approaches. Future Microbiol 7:73–89. https://doi.org/10.2217/fmb.11.135

    Article  CAS  PubMed  Google Scholar 

  27. Bankevich A, Nurk S, Antipov D et al (2012) SPAdes: a new genome assembly algorithm and its applications to single-cell sequencing. J Comput Biol 19:455–477. https://doi.org/10.1089/cmb.2012.0021

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Mikheenko A, Prjibelski A, Saveliev V et al (2018) Versatile genome assembly evaluation with QUAST-LG. Bioinformatics 34:i142–i150. https://doi.org/10.1093/bioinformatics/bty266

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Hyatt D, Chen G-L, LoCascio PF et al (2010) Prodigal: prokaryotic gene recognition and translation initiation site identification. BMC Bioinformatics 11:119. https://doi.org/10.1186/1471-2105-11-119

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Meyer F, Paarmann D, D’Souza M et al (2008) The metagenomics RAST server – a public resource for the automatic phylogenetic and functional analysis of metagenomes. BMC Bioinformatics 9:386. https://doi.org/10.1186/1471-2105-9-386

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Finn RD, Bateman A, Clements J et al (2014) Pfam: the protein families database. Nucleic Acids Res 42:D222–D230. https://doi.org/10.1093/nar/gkt1223

    Article  CAS  PubMed  Google Scholar 

  32. Jones P, Binns D, Chang H-Y et al (2014) InterProScan 5: genome-scale protein function classification. Bioinformatics 30:1236–1240. https://doi.org/10.1093/bioinformatics/btu031

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. An L, Pookhao N, Jiang H, Xu J (2014) Statistical approach of functional profiling for a microbial community. PLoS ONE 9:1–11. https://doi.org/10.1371/journal.pone.0106588

    Article  CAS  Google Scholar 

  34. Martin M (2011) Cutadapt removes adapter sequences from high-throughput sequence reads. EMBnet.journal 17:10–12

    Article  Google Scholar 

  35. Callahan BJ, Mcmurdie PJ, Rosen MJ et al (2016) DADA2: High resolution sample inference from Illumina amplicon data. Nat Methods 13:581–583. https://doi.org/10.1038/nmeth.3869.DADA2

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. R Core Team (2013) A language and environment for statistical computing. R Found Stat Comput

  37. McMurdie PJ, Holmes S (2013) Phyloseq: An R Package for Reproducible Interactive Analysis and Graphics of Microbiome Census Data. PLoS One 8. https://doi.org/10.1371/journal.pone.0061217

  38. Lahti L, Shetty S, Blake T, Salojarvi J (2019) Tools for microbiome analysis in R. Microbiome package version. Bioconductor

  39. Wickham H, Averick M, Bryan J et al (2019) Welcome to the Tidyverse Tidyverse package. J Open Source Softw 4:1–6. https://doi.org/10.21105/joss.01686

    Article  Google Scholar 

  40. Oksanen J, Kindt R, Legendre P et al (2007) The vegan package. Community Ecol Packag 10:631–637

    Google Scholar 

  41. Foster ZSL, Sharpton TJ, Grünwald NJ (2017) Metacoder: An R package for visualization and manipulation of community taxonomic diversity data. PLoS Comput Biol 13:1–15. https://doi.org/10.1371/journal.pcbi.1005404

    Article  CAS  Google Scholar 

  42. Kembel S, Cowan P, Helmus M et al (2010) Picante: R tools for integrating phylogenies and ecology. Bioinformatics 26:1463–1464

    Article  CAS  PubMed  Google Scholar 

  43. Love MI, Huber W, Anders S (2014) Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol 15:550. https://doi.org/10.1186/s13059-014-0550-8

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Westcott SL, Schloss PD (2017) OptiClust, an Improved Method for Assigning Amplicon-Based Sequence Data to Operational Taxonomic Units. mSphere 2:e00073-e117. https://doi.org/10.1128/mSphereDirect.00073-17

    Article  PubMed  PubMed Central  Google Scholar 

  45. Schloss PD, Westcott SL, Ryabin T et al (2009) Introducing mothur: open-source, platform-independent, community-supported software for describing and comparing microbial communities. Appl Environ Microbiol 75:7537–7541. https://doi.org/10.1128/AEM.01541-09

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. Parks DH, Tyson GW, Hugenholtz P, Beiko RG (2014) STAMP: statistical analysis of taxonomic and functional profiles. Bioinformatics 30:3123–3124. https://doi.org/10.1093/bioinformatics/btu494

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. Welch B (1938) The significance of the difference between two means when the population variances are unequal. Biometrika 29:350–362

    Article  Google Scholar 

  48. Welch B (1947) No TitleThe generalisation of students problem when several different population variances are involved. Biometrika 34:23–35

    Google Scholar 

  49. Benjamini Y, Hochberg Y (1995) Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing. J R Stat Soc Ser B 57:289–300

    Google Scholar 

  50. Mendes LW, Kuramae EE, Navarrete AA et al (2014) Taxonomical and functional microbial community selection in soybean rhizosphere. ISME J 8:1577–1587. https://doi.org/10.1038/ismej.2014.17

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  51. Csardi G, Nepusz T (2005) The Igraph Software Package for Complex Network Research. InterJ Complex Syst 1695

  52. Gu Z, Eils R, Schlesner M (2016) Complex heatmaps reveal patterns and correlations in multidimensional genomic data. Bioinformatics 32:2847–2849. https://doi.org/10.1093/bioinformatics/btw313

    Article  CAS  PubMed  Google Scholar 

  53. Armstrong A, Valverde A, Ramond J et al (2016) Temporal dynamics of hot desert microbial communities reveal structural and functional responses to water input. Sci Rep 6:1–8. https://doi.org/10.1038/srep34434

    Article  CAS  Google Scholar 

  54. Liang T, Chamecki M, Yu X (2016) Sea salt aerosol deposition in the coastal zone : A large eddy simulation study. Atmos Res 180:119–127. https://doi.org/10.1016/j.atmosres.2016.05.019

    Article  Google Scholar 

  55. Ronca S, Ramond J, Jones BE et al (2015) Namib Desert dune / interdune transects exhibit habitat-specific edaphic bacterial communities. Front Microbiol 6:1–12. https://doi.org/10.3389/fmicb.2015.00845

    Article  Google Scholar 

  56. Valverde A, Makhalanyane TP, Seely MK, Cowan DA (2015) Cyanobacteria drive community composition and functionality in rock-soil interface communities. Mol Ecol 24:812–821. https://doi.org/10.1111/mec.13068

    Article  CAS  PubMed  Google Scholar 

  57. van der Walt A, Johnson RM, Cowan DA et al (2016) Unique microbial phylotypes in namib desert dune and gravel plain fairy circle soils. Appl Environ Microbiol 82:4592–4601. https://doi.org/10.1128/AEM.00844-16.Editor

    Article  PubMed  PubMed Central  Google Scholar 

  58. Gunnigle E, Frossard A, Ramond J et al (2017) Diel-scale temporal dynamics recorded for bacterial groups in Namib Desert soil. Nat Publ Gr 7:1–12. https://doi.org/10.1038/srep40189

    Article  CAS  Google Scholar 

  59. Delgado-Baquerizo M, Oliverio AM, Brewer TE et al (2018) A global atlas of the dominant bacteria found in soil. Science (80- ) 359:320–325

    Article  CAS  Google Scholar 

  60. Zhang H, Liu W, Xiaoming K, et al (2018) Changes in soil microbial community response to precipitation events in a semi-arid steppe of the Xilin River Basin, China. J Arid Land 1–14

  61. Barnard RL, Osborne CA, Firestone MK (2013) Responses of soil bacterial and fungal communities to extreme desiccation and rewetting. ISME J 7:2229–2241. https://doi.org/10.1038/ismej.2013.104

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  62. Maestre FT, Delgado-baquerizo M, Jeffries TC et al (2015) Increasing aridity reduces soil microbial diversity and abundance in global drylands. Proc Natl Acad Sci 112:15684–15689. https://doi.org/10.1073/pnas.1516684112

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  63. Wu K, Xu W, Yang W (2020) Effects of precipitation changes on soil bacterial community composition and diversity in the Junggar desert of Xinjiang, China. PeerJ 8:1–23. https://doi.org/10.7717/peerj.8433

    Article  Google Scholar 

  64. Carrino-Kyker SR, Smemo KA, Burke DJ (2013) Shotgun metagenomic analysis of metabolic diversity and microbial community structure in experimental vernal pools subjected to nitrate pulse. BMC Microbiol 13:78. https://doi.org/10.1186/1471-2180-13-78

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  65. Šťovíček A, Kim M, Or D, Gillor O (2017) Microbial community response to hydration-desiccation cycles in desert soil. Sci Rep 7:1–9. https://doi.org/10.1038/srep45735

    Article  CAS  Google Scholar 

  66. Austin AT, Yahdjian L, Stark JM et al (2004) Water pulses and biogeochemical cycles in arid and semiarid ecosystems. Oecologia 14:221–235. https://doi.org/10.1007/s00442-004-1519-1

    Article  Google Scholar 

  67. Lee ZM, Poret-Peterson AT, Siefert JL et al (2017) Nutrient stoichiometry shapes microbial community structure in an evaporitic shallow pond. Front Microbiol 8:1–15. https://doi.org/10.3389/fmicb.2017.00949

    Article  Google Scholar 

  68. Rodrigues JLM, Pellizari VH, Mueller R et al (2013) Conversion of the Amazon rainforest to agriculture results in biotic homogenization of soil bacterial communities. Proc Natl Acad Sci 110:988–993. https://doi.org/10.1073/pnas.1220608110

    Article  PubMed  Google Scholar 

  69. Chase JM (2007) Drought mediates the importance of stochastic community assembly. Proc Natl Acad Sci 104:17430–17434

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  70. Langenheder S, Berga M, Östman Ö, Székely AJ (2011) Temporal variation of Β-diversity and assembly mechanisms in a bacterial metacommunity. ISME J 6:1107–1114. https://doi.org/10.1038/ismej.2011.177

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  71. Kielak AM, Barreto CC, Kowalchuk GA et al (2016) The Ecology of Acidobacteria : Moving beyond Genes and Genomes. Front Microbiol 7:1–16. https://doi.org/10.3389/fmicb.2016.00744

    Article  Google Scholar 

  72. Bull A (2011) Actinobacteria of the Extremobiosphere. In: Extremophiles, 1203–1240

  73. Starke R, Bastida F, Abadia J et al (2017) Ecological and functional adaptations to water management in a semiarid agroecosystem: a soil metaproteomics approach. Sci Rep 7:1–16

    Article  CAS  Google Scholar 

  74. Saenz JS, Airo A, Schulze-Makuch D et al (2019) Functional traits co-occurring with mobile genetic elements in the microbiome of the Atacama Desert. Diversity 11:1–20

    Article  Google Scholar 

  75. Le PT, Makhalanyane TP, Guerrero LD et al (2016) Comparative metagenomic analysis reveals mechanisms for stress response in hypoliths from extreme Hyperarid Deserts. Genome Biol Evol 8:2737–2747. https://doi.org/10.1093/gbe/evw189

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  76. Allison SD, Martiny JBH (2008) Resistance, resilience, and redundancy in microbial communities. Proc Natl Acad Sci 105:11512–11519

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  77. Tripathi BM, Moroenyane I, Sherman C et al (2017) Trends in Taxonomic and Functional Composition of Soil Microbiome Along a Precipitation Gradient in Israel. Microb Ecol 74:168–176. https://doi.org/10.1007/s00248-017-0931-0

    Article  PubMed  Google Scholar 

  78. Schimel J, Balser T, Wallenstein M (2007) Microbial stress-response physiology and its implications for ecosystem function. Ecology 88:1386–1394

    Article  PubMed  Google Scholar 

  79. Belov A, Cheptsov V, Vorobyova E (2018) Soil bacterial communities of Sahara and Gibson deserts: Physiological and taxonomical characteristics. AIMS Microbiol 4:685–710. https://doi.org/10.3934/microbiol.2018.4.685

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  80. Keto-Timonen R, Hietala N, Palonen E et al (2016) Cold shock proteins : a minireview with special emphasis on Csp-family of Enteropathogenic Yersinia. Front Microbiol 7:1–7. https://doi.org/10.3389/fmicb.2016.01151

    Article  Google Scholar 

  81. Van Horn DJ, Okie JG, Buelow HN et al (2014) Soil microbial responses to increased moisture and organic resources along a salinity gradient in a Polar Desert. Appl Environ Microbiol 80:3034–3043. https://doi.org/10.1128/AEM.03414-13

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  82. Bertness M, Callaway R (1994) Positive interactions in communities. Trends Ecol Evol 9:191–193

    Article  CAS  PubMed  Google Scholar 

  83. Shade A, Peter H, Allison SD et al (2012) Fundamentals of microbial community resistance and resilience. Front Microbiol 3:1–19. https://doi.org/10.3389/fmicb.2012.00417

    Article  Google Scholar 

  84. Jousset A, Bienhold C, Chatzinotas A et al (2017) Where less may be more: How the rare biosphere pulls ecosystems strings. ISME J 11:853–862. https://doi.org/10.1038/ismej.2016.174

    Article  PubMed  PubMed Central  Google Scholar 

  85. Escalas A, Hale L, Voordeckers JW et al (2019) Microbial functional diversity : From concepts to applications. Ecol Evol 9:12000–12016. https://doi.org/10.1002/ece3.5670

    Article  PubMed  PubMed Central  Google Scholar 

  86. Pan Y, Cassman N, de Hollander M et al (2014) Impact of long-term N, P, K, and NPK fertilization on the composition and potential functions of the bacterial community in grassland soil. FEMS Microbiol Ecol 90:195–205. https://doi.org/10.1111/1574-6941.12384

    Article  CAS  PubMed  Google Scholar 

  87. Purahong W, Schloter M, Pecyna MJ et al (2014) Uncoupling of microbial community structure and function in decomposing litter across beech forest ecosystems in Central Europe. Sci Rep 4:1–7. https://doi.org/10.1038/srep07014

    Article  CAS  Google Scholar 

  88. Louca S, Polz MF, Mazel F et al (2018) Function and functional redundancy in microbial systems. Nat Ecol Evol 2:936–943. https://doi.org/10.1038/s41559-018-0519-1

    Article  PubMed  Google Scholar 

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Acknowledgements

The authors are grateful for the funding provided by the National Research Foundation of South Africa for this project.

Funding

YN was supported through a Free standing and Research and Development Programme Grant funded by the National Research Foundation (NRF) of South Africa. AV was supported by the project ‘CLU-2019–05 – IRNASA/CSIC Unit of Excellence’, funded by the Junta de Castilla y León and co-financed by the European Union (ERDF ‘Europe drives our growth’).

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Authors and Affiliations

  1. Centre for Microbial Ecology and Genomics, Department of Biochemistry, Genetics and Microbiology, University of Pretoria, Lynnwood Road, Pretoria, 0002, South Africa

    Yashini Naidoo & Don A. Cowan

  2. IRNASA-CSIC, C/Cordel de Merinas 40-52, 37008, Salamanca, Spain

    Angel Valverde

  3. Biotechnology Platform, Agricultural Research Council, Soutpan Road, Onderstepoort Campus, Pretoria, 0110, South Africa

    Rian E. Pierneef

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  1. Yashini Naidoo
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  2. Angel Valverde
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  3. Rian E. Pierneef
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  4. Don A. Cowan
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Contributions

Yashini Naidoo, conceptualization, investigation, writing (original draft); Angel Valverde Portal, writing (review and editing), supervision, funding acquisition; Rian Pierneef, software, validation, writing (review and editing); Don Cowan, supervision, funding acquisition, writing (review and editing).

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Correspondence to Yashini Naidoo.

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Naidoo, Y., Valverde, A., Pierneef, R.E. et al. Differences in Precipitation Regime Shape Microbial Community Composition and Functional Potential in Namib Desert Soils. Microb Ecol 83, 689–701 (2022). https://doi.org/10.1007/s00248-021-01785-w

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