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Mapping and predictive variations of soil bacterial richness across France

Author

Listed:
  • Sébastien Terrat
  • Walid Horrigue
  • Samuel Dequietd
  • Nicolas P A Saby
  • Mélanie Lelièvre
  • Virginie Nowak
  • Julie Tripied
  • Tiffanie Régnier
  • Claudy Jolivet
  • Dominique Arrouays
  • Patrick Wincker
  • Corinne Cruaud
  • Battle Karimi
  • Antonio Bispo
  • Pierre Alain Maron
  • Nicolas Chemidlin Prévost-Bouré
  • Lionel Ranjard

Abstract

Although numerous studies have demonstrated the key role of bacterial diversity in soil functions and ecosystem services, little is known about the variations and determinants of such diversity on a nationwide scale. The overall objectives of this study were i) to describe the bacterial taxonomic richness variations across France, ii) to identify the ecological processes (i.e. selection by the environment and dispersal limitation) influencing this distribution, and iii) to develop a statistical predictive model of soil bacterial richness. We used the French Soil Quality Monitoring Network (RMQS), which covers all of France with 2,173 sites. The soil bacterial richness (i.e. OTU number) was determined by pyrosequencing 16S rRNA genes and related to the soil characteristics, climatic conditions, geomorphology, land use and space. Mapping of bacterial richness revealed a heterogeneous spatial distribution, structured into patches of about 111km, where the main drivers were the soil physico-chemical properties (18% of explained variance), the spatial descriptors (5.25%, 1.89% and 1.02% for the fine, medium and coarse scales, respectively), and the land use (1.4%). Based on these drivers, a predictive model was developed, which allows a good prediction of the bacterial richness (R2adj of 0.56) and provides a reference value for a given pedoclimatic condition.

Suggested Citation

  • Sébastien Terrat & Walid Horrigue & Samuel Dequietd & Nicolas P A Saby & Mélanie Lelièvre & Virginie Nowak & Julie Tripied & Tiffanie Régnier & Claudy Jolivet & Dominique Arrouays & Patrick Wincker & , 2017. "Mapping and predictive variations of soil bacterial richness across France," PLOS ONE, Public Library of Science, vol. 12(10), pages 1-19, October.
  • Handle: RePEc:plo:pone00:0186766
    DOI: 10.1371/journal.pone.0186766
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    References listed on IDEAS

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    1. Storlie, Curtis B. & Helton, Jon C., 2008. "Multiple predictor smoothing methods for sensitivity analysis: Description of techniques," Reliability Engineering and System Safety, Elsevier, vol. 93(1), pages 28-54.
    2. Jizhong Zhou & Ye Deng & Lina Shen & Chongqing Wen & Qingyun Yan & Daliang Ning & Yujia Qin & Kai Xue & Liyou Wu & Zhili He & James W. Voordeckers & Joy D. Van Nostrand & Vanessa Buzzard & Sean T. Mic, 2016. "Temperature mediates continental-scale diversity of microbes in forest soils," Nature Communications, Nature, vol. 7(1), pages 1-10, November.
    3. Jeff R. Powell & Senani Karunaratne & Colin D. Campbell & Huaiying Yao & Lucinda Robinson & Brajesh K. Singh, 2015. "Deterministic processes vary during community assembly for ecologically dissimilar taxa," Nature Communications, Nature, vol. 6(1), pages 1-10, December.
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    Cited by:

    1. Maëva Labouyrie & Cristiano Ballabio & Ferran Romero & Panos Panagos & Arwyn Jones & Marc W. Schmid & Vladimir Mikryukov & Olesya Dulya & Leho Tedersoo & Mohammad Bahram & Emanuele Lugato & Marcel G. , 2023. "Patterns in soil microbial diversity across Europe," Nature Communications, Nature, vol. 14(1), pages 1-21, December.
    2. Anne C. Richer-de-Forges & Dominique Arrouays & Marion Bardy & Antonio Bispo & Philippe Lagacherie & Bertrand Laroche & Blandine Lemercier & Joëlle Sauter & Marc Voltz, 2019. "Mapping of Soils and Land-Related Environmental Attributes in France: Analysis of End-Users’ Needs," Sustainability, MDPI, vol. 11(10), pages 1-15, May.

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