Although minerals represent important soil constituents, their impact on the diversity and structure of soil microbial communities remains poorly documented. In this study, pure mineral particles with various chemistries (i.e., obsidian, apatite, and calcite) were considered. Each mineral type was conditioned in mesh bags and incubated in soil below different tree stands (beech, coppice with standards, and Corsican pine) for 2.5 years to determine the relative impacts of mineralogy and mineral weatherability on the taxonomic and functional diversities of mineral-associated bacterial communities. After this incubation period, the minerals and the surrounding bulk soil were collected to determine mass loss and to perform soil analyses, enzymatic assays, and cultivation-dependent and -independent analyses. Notably, our 16S rRNA gene pyrosequencing analyses revealed that after the 2.5-year incubation period, the mineral-associated bacterial communities strongly differed from those of the surrounding bulk soil for all tree stands considered. When focusing only on minerals, our analyses showed that the bacterial communities associated with calcite, the less recalcitrant mineral type, significantly differed from those that colonized obsidian and apatite minerals. The cultivation-dependent analysis revealed significantly higher abundances of effective mineral-weathering bacteria on the most recalcitrant minerals (i.e., apatite and obsidian). Together, our data showed an enrichment of Betaproteobacteria and effective mineral-weathering bacteria related to the Burkholderia and Collimonas genera on the minerals, suggesting a key role for these taxa in mineral weathering and nutrient cycling in nutrient-poor forest ecosystems.IMPORTANCE Forests are usually developed on nutrient-poor and rocky soils, while nutrient-rich soils have been dedicated to agriculture. In this context, nutrient recycling and nutrient access are key processes in such environments. Deciphering how soil mineralogy influences the diversity, structure, and function of soil bacterial communities in relation to the soil conditions is crucial to better understanding the relative role of the soil bacterial communities in nutrient cycling and plant nutrition in nutrient-poor environments. The present study determined in detail the diversity and structure of bacterial communities associated with different mineral types incubated for 2.5 years in the soil under different tree species using cultivationdependent and -independent analyses. Our data showed an enrichment of specific bacterial taxa on the minerals, specifically on the most weathered minerals, suggesting that they play key roles in mineral weathering and nutrient cycling in nutrientpoor forest ecosystems.KEYWORDS mineral chemistry, bacterial communities, forest soil, mesh bags, mineral weatherability

It has been rarely questioned as to whether the enrichment of specific bacterial taxa found in the rhizosphere of a given plant species changes with different soil types under field conditions and under similar climatic conditions. Understanding tree microbiome interactions is essential because, in contrast to annual plants, tree species require decades to grow and strongly depend on the nutritive resources of the soil. In this context, we tested using a natural toposequence the hypothesis that beech trees select specific taxa and functions in their rhizosphere based on the soil conditions and their nutritive requirements. Our 16S rRNA gene pyrosequencing analyses revealed that the soil type determines the taxa colonizing the beech rhizosphere. A rhizosphere effect was observed in each soil type, but a stronger effect was observed in the nutrient-poor soils. Although the communities varied significantly across the toposequence, we identified a core beech rhizosphere microbiome. Functionally, GeoChip analyses showed a functional redundancy across the toposequence, with genes related to nutrient cycling and to the bacterial immune system being significantly enriched in the rhizosphere. Altogether, the data suggest that, regardless of the soil conditions, trees enrich variable bacterial communities to maintain the functions necessary for their nutrition.

Co‐occurrence network analysis based on amplicon sequences is increasingly used to study microbial communities. Patterns of co‐existence or mutual exclusion between pairs of taxa are often interpreted as reflecting positive or negative biological interactions. However, other assembly processes can underlie these patterns, including species failure to reach distant areas (dispersal limitation) and tolerate local environmental conditions (habitat filtering). We provide a tool to quantify the relative contribution of community assembly processes to microbial co‐occurrence patterns, which we applied to explore soil bacterial communities in two dry ecosystems. First, we sequenced a bacterial phylogenetic marker in soils collected across multiple plots. Second, we inferred co‐occurrence networks to identify pairs of significantly associated taxa, either co‐existing more (aggregated) or less often (segregated) than expected at random. Third, we assigned assembly processes to each pair: patterns explained based on spatial or environmental distance were ascribed to dispersal limitation (2%–4%) or habitat filtering (55%–77%), and the remaining to biological interactions. Finally, we calculated the phylogenetic distance between taxon pairs to test theoretical expectations on the linkages between phylogenetic patterns and assembly processes. Aggregated pairs were more closely related than segregated pairs. Furthermore, habitat‐filtered aggregated pairs were closer relatives than those assigned to positive interactions, consistent with phylogenetic niche conservatism and cooperativism among distantly related taxa. Negative interactions resulted in equivocal phylogenetic signatures, probably because different competitive processes leave opposing signals. We show that microbial co‐occurrence networks mainly reflect environmental tolerances and propose that incorporating measures of phylogenetic relatedness to networks might help elucidate ecologically meaningful patterns.