Little information is available regarding the landscape-scale distribution of microbial communities and its environmental determinants. However, a landscape perspective is needed to understand the relative importance of local and regional factors and land management for the microbial communities and the ecosystem services they provide. In the most comprehensive analysis of spatial patterns of microbial communities to date, we investigated the distribution of functional microbial communities involved in N-cycling and of the total bacterial and crenarchaeal communities over 107 sites in Burgundy, a 31 500 km² region of France, using a 16 × 16 km² sampling grid. At each sampling site, the abundance of total bacteria, crenarchaea, nitrate reducers, denitrifiers- and ammonia oxidizers were estimated by quantitative PCR and 42 soil physico-chemical properties were measured. The relative contributions of land use, spatial distance, climatic conditions, time, and soil physico-chemical properties to the spatial distribution of the different communities were analyzed by canonical variation partitioning. Our results indicate that 43–85% of the spatial variation in community abundances could be explained by the measured environmental parameters, with soil chemical properties (mostly pH) being the main driver. We found spatial autocorrelation up to 739 km and used geostatistical modelling to generate predictive maps of the distribution of microbial communities at the landscape scale. The present study highlights the potential of a spatially explicit approach for microbial ecology to identify the overarching factors driving the spatial heterogeneity of microbial communities even at the landscape scale.

Over the last two decades, a considerable effort has been made to decipher the biogeography of soil microbial communities as a whole, from small to broad scales. In contrast, few studies have focused on the taxonomic groups constituting these communities; thus, our knowledge of their ecological attributes and the drivers determining their composition and distribution is limited. We applied a pyrosequencing approach targeting 16S ribosomal RNA (rRNA) genes in soil DNA to a set of 2173 soil samples from France to reach a comprehensive understanding of the spatial distribution of bacteria and archaea and to identify the ecological processes and environmental drivers involved. Taxonomic assignment of the soil 16S rRNA sequences indicated the presence of 32 bacterial phyla or subphyla and 3 archaeal phyla. Twenty of these 35 phyla were cosmopolitan and abundant, with heterogeneous spatial distributions structured in patches ranging from a 43- to 260-km radius. The hierarchy of the main environmental drivers of phyla distribution was soil pH > land management > soil texture > soil nutrients > climate. At a lower taxonomic level, 47 dominant genera belonging to 12 phyla aggregated 62.1% of the sequences. We also showed that the phylum-level distribution can be determined largely by the distribution of the dominant genus or, alternatively, reflect the combined distribution of all of the phylum members. Together, our study demonstrated that soil bacteria and archaea present highly diverse biogeographical patterns on a nationwide scale and that studies based on intensive and systematic sampling on a wide spatial scale provide a promising contribution for elucidating soil biodiversity determinism.

Summary: There is ample evidence that microbial processes can exhibit large variations in activity on a field scale. However, very little is known about the spatial distribution of the microbial communities mediating these processes. Here we used geostatistical modelling to explore spatial patterns of size and activity of the denitrifying community, a functional guild involved in N‐cycling, in a grassland field subjected to different cattle grazing regimes. We observed a non‐random distribution pattern of the size of the denitrifier community estimated by quantification of the denitrification genes copy numbers with a macro‐scale spatial dependence (6–16 m) and mapped the distribution of this functional guild in the field. The spatial patterns of soil properties, which were strongly affected by presence of cattle, imposed significant control on potential denitrification activity, potential N ₂ O production and relative abundance of some denitrification genes but not on the size of the denitrifier community. Absolute abundance of most denitrification genes was not correlated with the distribution patterns of potential denitrification activity or potential N ₂ O production. However, the relative abundance of bacteria possessing the nosZ gene encoding the N ₂ O reductase in the total bacterial community was a strong predictor of the N ₂ O/(N ₂ + N ₂ O) ratio, which provides evidence for a relationship between bacterial community composition based on the relative abundance of denitrifiers in the total bacterial community and ecosystem processes. More generally, the presented geostatistical approach allows integrated mapping of microbial communities, and hence can facilitate our understanding of relationships between the ecology of microbial communities and microbial processes along environmental gradients.