Sampling event Registered September 22, 2022
Mapping and Predictive Variations of Soil Bacterial Richness across French National Territory
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
Pipeline used: https://www.ebi.ac.uk/metagenomics/pipelines/5.0
Bibliography
- Identifier: DOI:10.1186/s12859-020-03829-3Google ScholarDjemiel 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:10.1038/s41598-019-40422-yGoogle ScholarKarimi 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:10.1126/sciadv.aat1808Google ScholarKarimi 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:10.1371/journal.pone.0186766Google ScholarTerrat 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
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