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