Sampling event Registered September 22, 2022

    Mapping and Predictive Variations of Soil Bacterial Richness across French National Territory

    Published by MGnify

    Description

    Although numerous studies have demonstrated the key role of bacterial diversity in soil functions and ecosystem services, little is known about the variations and the determinism of such diversity on a wide scale. The overall objectives of this study were i) to describe the bacterial taxonomic richness variations across French national territory, ii) to identify the ecological processes (i.e. selection by the environment and dispersal limitation) and environmental filters most 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 rDNA genes directly amplified from DNA of all soil samples 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 111 km, where the main drivers were the soil physico-chemical properties, the spatial descriptors and the land use. 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.

    Methodology

    Sampling

    Although numerous studies have demonstrated the key role of bacterial diversity in soil functions and ecosystem services, little is known about the variations and the determinism of such diversity on a wide scale. The overall objectives of this study were i) to describe the bacterial taxonomic richness variations across French national territory, ii) to identify the ecological processes (i.e. selection by the environment and dispersal limitation) and environmental filters most 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 rDNA genes directly amplified from DNA of all soil samples 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 111 km, where the main drivers were the soil physico-chemical properties, the spatial descriptors and the land use. 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.

    Method steps

    Bibliography

    • Djemiel C, Dequiedt S, Karimi B, Cottin A, Girier T, El Djoudi Y, Wincker P, Lelièvre M, Mondy S, Chemidlin Prévost-Bouré N, Maron PA, Ranjard L, Terrat S. 2020. BIOCOM-PIPE: a new user-friendly metabarcoding pipeline for the characterization of microbial diversity from 16S, 18S and 23S rRNA gene amplicons. BMC Bioinformatics vol. 21
      Identifier: DOI:10.1186/s12859-020-03829-3Google Scholar
    • Karimi B, Dequiedt S, Terrat S, Jolivet C, Arrouays D, Wincker P, Cruaud C, Bispo A, Chemidlin Prévost-Bouré N, Ranjard L. 2019. Biogeography of Soil Bacterial Networks along a Gradient of Cropping Intensity. Sci Rep vol. 9
      Identifier: DOI:10.1038/s41598-019-40422-yGoogle Scholar
    • Karimi B, Terrat S, Dequiedt S, Saby NPA, Horrigue W, Lelièvre M, Nowak V, Jolivet C, Arrouays D, Wincker P, Cruaud C, Bispo A, Maron PA, Bouré NCP, Ranjard L. 2018. Biogeography of soil bacteria and archaea across France. Sci Adv vol. 4
      Identifier: DOI:10.1126/sciadv.aat1808Google Scholar
    • Terrat S, Horrigue W, Dequiedt S, Saby NPA, Lelièvre M, Nowak V, Tripied J, Régnier T, Jolivet C, Arrouays D, Wincker P, Cruaud C, Karimi B, Bispo A, Maron PA, Chemidlin Prévost-Bouré N, Ranjard L. 2017. Mapping and predictive variations of soil bacterial richness across France. PLoS One vol. 12
      Identifier: DOI:10.1371/journal.pone.0186766Google Scholar

    Contacts

    • The French National Sequencing Center (Genoscope)

      Originator
      Metadata author
      Administrative point of contact
      Organization
      The French National Sequencing Center (Genoscope)
      Address
      Le Ponant Building D - 25 rue Leblanc
      Roles
      Originator
      Metadata author
      Administrative point of contact
      Phone

    GBIF registration

    Registration date
    September 22, 2022
    Metadata last modified
    September 22, 2022
    Publication date
    August 06, 2020
    Hosted by
    GBIF Secretariat
    Installation
    GBIF Hosted Datasets
    Endpoints
    Darwin Core Archive
    Preferred identifier
    10.15468/k3589t
    Alternative identifiers

    Citation

    MGnify (2020). Mapping and Predictive Variations of Soil Bacterial Richness across French National Territory. Sampling event dataset https://doi.org/10.15468/k3589t accessed via GBIF.org on 2025-08-04.