Biogeographical patterns of the soil fungal:bacterial ratio across France.

Soils are one of the major reservoirs of biological diversity on our planet because they host a huge richness of microorganisms. The fungal:bacterial (F:B) ratio targets two major functional groups of organisms in soils and can improve our understanding of their importance and efficiency for soil functioning. To better decipher the variability of this ratio and rank the environmental parameters involved, we used the French Soil Quality Monitoring Network (RMQS)-one of the most extensive and a priori-free soil sampling surveys, based on a systematic 16 km × 16 km grid and including more than 2,100 samples. F:B ratios, measured by quantitative PCR targeting the 18S and 16S rDNA genes, turned out to be heterogenously distributed and spatially structured in geographical patterns across France. These distribution patterns differed from bacterial or fungal densities taken separately, supporting the hypothesis that the F:B ratio is not the mere addition of each density but rather results from the complex interactions of the two functional groups. The F:B ratios were mainly influenced by soil characteristics and land management. Among soil characteristics, the pH and, to a lesser extent, the organic carbon content and the carbon:nitrogen (C:N) ratio were the main drivers. These results improved our understanding of soil microbial communities, and from an operational point of view, they suggested that the F:B ratio should be a useful new bioindicator of soil status. The resulting dataset can be considered as a first step toward building up a robust repository essential to any bioindicator and aimed at guiding and helping decision making. IMPORTANCE In the face of human disturbances, microbial activity can be impacted and, e.g., can result in the release of large amounts of soil carbon into the atmosphere, with global impacts on temperature. Therefore, the development and the regular use of soil bioindicators are essential to (i) improve our knowledge of soil microbial communities and (ii) guide and help decision makers define suitable soil management strategies. Bacterial and fungal communities are key players in soil organic matter turnover, but with distinct physiological and ecological characteristics. The fungal:bacterial ratio targets these two major functional groups by investigating their presence and their equilibrium. The aim of our study is to characterize this ratio at a territorial scale and rank the environmental parameters involved so as to further develop a robust repository essential to the interpretation of any bioindicator of soil quality.

Urban land uses shape soil microbial abundance and diversity.

Soil microbial biodiversity provides many useful services in cities. However, the ecology of microbial communities in urban soils remains poorly documented, and studies are required to better predict the impact of urban land use. We characterized microbial communities (archea/bacteria and fungi) in urban soils in Dijon (Burgundy, France). Three main land uses were considered - public leisure, traffic, and urban agriculture - sub-categorized in sub-land uses according to urban indexes and management practices. Microbial biomass and diversity were determined by quantifying and high-throughput sequencing of soil DNA. Variation partitioning analysis was used to rank soil physicochemical characteristics and land uses according to their relative contribution to the variation of soil microbial communities. Urban soils in Dijon harbored high levels of microbial biomass and diversity that varied according to land uses. Microbial biomass was 1.8 times higher in public leisure and traffic sites than in urban agriculture sites. Fungal richness increased by 25 % in urban agriculture soils, and bacterial richness was lower (by 20 %) in public leisure soils. Partitioning models explained 25.7 %, 46.2 % and 75.6 % of the variance of fungal richness, bacterial richness and microbial biomass, respectively. The organic carbon content and the C/N ratio were the best predictors of microbial biomass, whereas soil bacterial diversity was mainly explained by soil texture and land use. Neither metal trace elements nor polycyclic aromatic hydrocarbons contents explained variations of microbial communities, probably due to their very low concentration in the soils. The microbial composition results highlighted that leisure sites represented a stabilized habitat favoring specialized microbial groups and microbial plant symbionts, as opposed to urban agriculture sites that stimulated opportunistic populations able to face the impact of agricultural practices. Altogether, our results provide evidence that there is scope for urban planners to drive soil microbial diversity through sustainable urban land use and associated management practices.

Potential of Meta-Omics to Provide Modern Microbial Indicators for Monitoring Soil Quality and Securing Food Production.

Soils are fundamental resources for agricultural production and play an essential role in food security. They represent the keystone of the food value chain because they harbor a large fraction of biodiversity-the backbone of the regulation of ecosystem services and "soil health" maintenance. In the face of the numerous causes of soil degradation such as unsustainable soil management practices, pollution, waste disposal, or the increasing number of extreme weather events, it has become clear that (i) preserving the soil biodiversity is key to food security, and (ii) biodiversity-based solutions for environmental monitoring have to be developed. Within the soil biodiversity reservoir, microbial diversity including Archaea, Bacteria, Fungi and protists is essential for ecosystem functioning and resilience. Microbial communities are also sensitive to various environmental drivers and to management practices; as a result, they are ideal candidates for monitoring soil quality assessment. The emergence of meta-omics approaches based on recent advances in high-throughput sequencing and bioinformatics has remarkably improved our ability to characterize microbial diversity and its potential functions. This revolution has substantially filled the knowledge gap about soil microbial diversity regulation and ecology, but also provided new and robust indicators of agricultural soil quality. We reviewed how meta-omics approaches replaced traditional methods and allowed developing modern microbial indicators of the soil biological quality. Each meta-omics approach is described in its general principles, methodologies, specificities, strengths and drawbacks, and illustrated with concrete applications for soil monitoring. The development of metabarcoding approaches in the last 20 years has led to a collection of microbial indicators that are now operational and available for the farming sector. Our review shows that despite the recent huge advances, some meta-omics approaches (e.g., metatranscriptomics or meta-proteomics) still need developments to be operational for environmental bio-monitoring. As regards prospects, we outline the importance of building up repositories of soil quality indicators. These are essential for objective and robust diagnosis, to help actors and stakeholders improve soil management, with a view to or to contribute to combining the food and environmental quality of next-generation farming systems in the context of the agroecological transition.

Correction: Mapping and predictive variations of soil bacterial richness across France.

[This corrects the article DOI: 10.1371/journal.pone.0186766.].

Inferring microbiota functions from taxonomic genes: a review.

Deciphering microbiota functions is crucial to predict ecosystem sustainability in response to global change. High-throughput sequencing at the individual or community level has revolutionized our understanding of microbial ecology, leading to the big data era and improving our ability to link microbial diversity with microbial functions. Recent advances in bioinformatics have been key for developing functional prediction tools based on DNA metabarcoding data and using taxonomic gene information. This cheaper approach in every aspect serves as an alternative to shotgun sequencing. Although these tools are increasingly used by ecologists, an objective evaluation of their modularity, portability, and robustness is lacking. Here, we reviewed 100 scientific papers on functional inference and ecological trait assignment to rank the advantages, specificities, and drawbacks of these tools, using a scientific benchmarking. To date, inference tools have been mainly devoted to bacterial functions, and ecological trait assignment tools, to fungal functions. A major limitation is the lack of reference genomes-compared with the human microbiota-especially for complex ecosystems such as soils. Finally, we explore applied research prospects. These tools are promising and already provide relevant information on ecosystem functioning, but standardized indicators and corresponding repositories are still lacking that would enable them to be used for operational diagnosis.

BIOCOM-PIPE: a new user-friendly metabarcoding pipeline for the characterization of microbial diversity from 16S, 18S and 23S rRNA gene amplicons.

BACKGROUND: The ability to compare samples or studies easily using metabarcoding so as to better interpret microbial ecology results is an upcoming challenge. A growing number of metabarcoding pipelines are available, each with its own benefits and limitations. However, very few have been developed to offer the opportunity to characterize various microbial communities (e.g., archaea, bacteria, fungi, photosynthetic microeukaryotes) with the same tool. RESULTS: BIOCOM-PIPE is a flexible and independent suite of tools for processing data from high-throughput sequencing technologies, Roche 454 and Illumina platforms, and focused on the diversity of archaeal, bacterial, fungal, and photosynthetic microeukaryote amplicons. Various original methods were implemented in BIOCOM-PIPE to (1) remove chimeras based on read abundance, (2) align sequences with structure-based alignments of RNA homologs using covariance models, and (3) a post-clustering tool (ReClustOR) to improve OTUs consistency based on a reference OTU database. The comparison with two other pipelines (FROGS and mothur) and Amplicon Sequence Variant definition highlighted that BIOCOM-PIPE was better at discriminating land use groups. CONCLUSIONS: The BIOCOM-PIPE pipeline makes it possible to analyze 16S, 18S and 23S rRNA genes in the same packaged tool. The new post-clustering approach defines a biological database from previously analyzed samples and performs post-clustering of reads with this reference database by using open-reference clustering. This makes it easier to compare projects from various sequencing runs, and increased the congruence among results. For all users, the pipeline was developed to allow for adding or modifying the components, the databases and the bioinformatics tools easily, giving high modularity for each analysis.

Reduced microbial diversity induces larger volatile organic compound emissions from soils.

Microorganisms in soil are known to be a source and a sink of volatile organic compounds (VOCs). The role of the microbial VOCs on soil ecosystem regulation has been increasingly demonstrated in the recent years. Nevertheless, little is known about the influence of the microbial soil community structure and diversity on VOC emissions. This novel study analyzed the effect of reduced microbial diversity in soil on VOC emissions. We found that reduced levels of microbial diversity in soil increased VOC emissions from soils, while the number of different VOCs emitted decreased. Furthermore, we found that Proteobacteria, Bacteroidetes and fungi phyla were positively correlated to VOC emissions, and other prokaryotic phyla were either negatively correlated or very slightly positively correlated to VOCs emissions. Our interpretation is that Proteobacteria, Bacteroidetes and fungi were VOC producers while the other prokaryotic phyla were consumers. Finally, we discussed the possible role of VOCs as mediators of microbial interactions in soil.

µgreen-db: a reference database for the 23S rRNA gene of eukaryotic plastids and cyanobacteria.

Studying the ecology of photosynthetic microeukaryotes and prokaryotic cyanobacterial communities requires molecular tools to complement morphological observations. These tools rely on specific genetic markers and require the development of specialised databases to achieve taxonomic assignment. We set up a reference database, called µgreen-db, for the 23S rRNA gene. The sequences were retrieved from generalist (NCBI, SILVA) or Comparative RNA Web (CRW) databases, in addition to a more original approach involving recursive BLAST searches to obtain the best possible sequence recovery. At present, µgreen-db includes 2,326 23S rRNA sequences belonging to both eukaryotes and prokaryotes encompassing 442 unique genera and 736 species of photosynthetic microeukaryotes, cyanobacteria and non-vascular land plants based on the NCBI and AlgaeBase taxonomy. When PR2/SILVA taxonomy is used instead, µgreen-db contains 2,217 sequences (399 unique genera and 696 unique species). Using µgreen-db, we were able to assign 96% of the sequences of the V domain of the 23S rRNA gene obtained by metabarcoding after amplification from soil DNA at the genus level, highlighting good coverage of the database. µgreen-db is accessible at http://microgreen-23sdatabase.ea.inra.fr.

The diversity of soil microbial communities matters when legumes face drought.

The cultivation of legumes shows promise for the development of sustainable agriculture, but yield instability remains one of the main obstacles for its adoption. Here, we tested whether the yield stability (i.e., resistance and resilience) of pea plants subjected to drought could be enhanced by soil microbial diversity. We used a dilution approach to manipulate the microbial diversity, with a genotype approach to distinguish the effect of symbionts from that of microbial diversity as a whole. We investigated the physiology of plants in response to drought when grown on a soil containing high or low level of microbial diversity. Plants grown under high microbial diversity displayed higher productivity and greater resilience after drought. Yield losses were mitigated by 15% on average in the presence of high soil microbial diversity at sowing. Our study provides proof of concept that the soil microbial community as a whole plays a key role for yield stability after drought even in plant species living in relationships with microbial symbionts. These results emphasize the need to restore soil biodiversity for sustainable crop management and climate change adaptation.

Tillage intensity and pasture in rotation effectively shape soil microbial communities at a landscape scale.

Soil microorganisms are essential to agroecosystem functioning and services. Yet, we still lack information on which farming practices can effectively shape the soil microbial communities. The aim of this study was to identify the farming practices, which are most effective at positively or negatively modifying bacterial and fungal diversity while considering the soil environmental variation at a landscape scale. A long-term research study catchment (12 km2 ) representative of intensive mixed farming (livestock and crop) in Western Europe was investigated using a regular grid for soil sampling (n = 186). Farming systems on this landscape scale were described in terms of crop rotation, use of fertilizer, soil tillage, pesticides treatments, and liming. Molecular microbial biomass was estimated by soil DNA recovery. Bacterial and fungal communities were analyzed by 16S and 18S rRNA gene pyrosequencing. Microbial biomass was significantly stimulated by the presence of pasture during the crop rotation since temporary and permanent pastures, as compared to annual crops, increased the soil microbial biomass by +23% and +93% respectively. While soil properties (mainly pH) explained much of the variation in bacterial diversity, soil tillage seemed to be the most influential among the farming practices. A 2.4% increase in bacterial richness was observed along our gradient of soil tillage intensity. In contrast, farming practices were the predominant drivers of fungal diversity, which was mainly determined by the presence of pastures during the crop rotation. Compared to annual crops, temporary and permanent pastures increased soil fungal richness by +10% and +14.5%, respectively. Altogether, our landscape-scale investigation allows the identification of farming practices that can effectively shape the soil microbial abundance and diversity, with the goal to improve agricultural soil management and soil ecological integrity.

Biogeography of soil bacteria and archaea across France.

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.

Profiles of volatile organic compound emissions from soils amended with organic waste products.

Volatile Organic Compounds (VOCs) are reactive compounds essential to atmospheric chemistry. They are mainly emitted by living organisms, and mostly by plants. Soil microbes also contribute to emissions of VOCs. However, these emissions have not yet been characterised in terms of quality and quantity. Furthermore, long-term organic matter amendments are known to affect the microbial content of soils, and hence the quantity and quality of VOC emissions. This study investigates which and how much of these VOCs are emitted from soil amended with organic waste products (OWPs). Four OWPs were investigated: municipal solid waste compost (MSW), green waste and sludge co-compost (GWS), bio-waste compost (BIOW) and farmyard manure (FYM). These OWPs have been amended every two years since 1998 until now at a rate of ~4 tC ha-1. A soil receiving no organic inputs was used as a reference (CN). VOCs emissions were measured under laboratory conditions using a Proton Transfer Reaction-Quadrupole ion guide Time of Flight-Mass Spectrometry (PTR-QiToF-MS). A laboratory system was set up made of two Pyrex chambers, one for samples and the second empty, to be used as a blank. Our results showed that total VOC emissions were higher in BIOW than in MSW. Further findings outlined that the most emitted compounds were acetone, butanone and acetaldehyde in all treatments, suggesting a common production mechanism for these compounds, meaning they were not affected by the OWP amendment. We isolated 21 VOCs that had statistically different emissions between the treatments and could therefore be considered as good markers of soil biological functioning. Our results suggest that organic matter and pH jointly influenced total VOC emissions. In conclusion, OWPs in soil affect the type of VOC emissions and the total flux also depends on the pH of the soil and the quantity of organic matter.

Biofilm biodiversity in French and Swiss show caves using the metabarcoding approach: First data.

In recent decades, show caves have begun to suffer from microorganism proliferation due to artificial lighting installations for touristic activity. In addition to the aesthetic problem, light encourages microorganisms that are responsible for physical and chemical degradation of limestone walls, speleothems and prehistoric paintings of cultural value. Microorganisms have previously been described by microscopy or culture-dependent methods, but data provided by new generation sequencing are rare. The authors identified, for the first time, microorganisms proliferating in one Swiss and in four French show caves using three different primers. The results showed that both photosynthetic and non-photosynthetic bacteria were the dominant taxa present in biofilms. Microalgae were heavily represented by the Trebouxiophyceae, Eustigmatophyceae and Chlorophyceae groups. Twelve diatoms were also recorded, with dominance of Syntrichia sp. (96.1%). Fungi were predominantly represented by Ascomycota, Zygomycota and Basidiomycota, fully half of the sampled biofilms where Fungi were detected. Comparing microbial communities from bleach-treated caves to those in untreated caves showed no significant difference except for a low-level change in the abundance of certain taxa. These findings provided by Illumina sequencing reveal a complex community structure in the 5 caves based on the assembly of bacteria, cyanobacteria, algae, diatoms, fungi and mosses.

High Microbial Diversity Promotes Soil Ecosystem Functioning.

In soil, the link between microbial diversity and carbon transformations is challenged by the concept of functional redundancy. Here, we hypothesized that functional redundancy may decrease with increasing carbon source recalcitrance and that coupling of diversity with C cycling may change accordingly. We manipulated microbial diversity to examine how diversity decrease affects the decomposition of easily degradable (i.e., allochthonous plant residues) versus recalcitrant (i.e., autochthonous organic matter) C sources. We found that a decrease in microbial diversity (i) affected the decomposition of both autochthonous and allochthonous carbon sources, thereby reducing global CO2 emission by up to 40%, and (ii) shaped the source of CO2 emission toward preferential decomposition of most degradable C sources. Our results also revealed that the significance of the diversity effect increases with nutrient availability. Altogether, these findings show that C cycling in soil may be more vulnerable to microbial diversity changes than expected from previous studies, particularly in ecosystems exposed to nutrient inputs. Thus, concern about the preservation of microbial diversity may be highly relevant in the current global-change context assumed to impact soil biodiversity and the pulse inputs of plant residues and rhizodeposits into the soil.IMPORTANCE With hundreds of thousands of taxa per gram of soil, microbial diversity dominates soil biodiversity. While numerous studies have established that microbial communities respond rapidly to environmental changes, the relationship between microbial diversity and soil functioning remains controversial. Using a well-controlled laboratory approach, we provide empirical evidence that microbial diversity may be of high significance for organic matter decomposition, a major process on which rely many of the ecosystem services provided by the soil ecosystem. These new findings should be taken into account in future studies aimed at understanding and predicting the functional consequences of changes in microbial diversity on soil ecosystem services and carbon storage in soil.

Soil microbial diversity drives the priming effect along climate gradients: a case study in Madagascar.

The priming effect in soil is proposed to be generated by two distinct mechanisms: 'stoichiometric decomposition' and/or 'nutrient mining' theories. Each mechanism has its own dynamics, involves its own microbial actors, and targets different soil organic matter (SOM) pools. The present study aims to evaluate how climatic parameters drive the intensity of each priming effect generation mechanism via the modification of soil microbial and physicochemical properties. Soils were sampled in the center of Madagascar, along climatic gradients designed to distinguish temperature from rainfall effects. Abiotic and biotic soil descriptors were characterized including bacterial and fungal phylogenetic composition. Potential organic matter mineralization and PE were assessed 7 and 42 days after the beginning of incubation with 13C-enriched wheat straw. Both priming mechanisms were mainly driven by the mean annual temperature but in opposite directions. The priming effect generated by stoichiometric decomposition was fostered under colder climates, because of soil enrichment in less developed organic matter, as well as in fast-growing populations. Conversely, the priming effect generated by nutrient mining was enhanced under warmer climates, probably because of the lack of competition between slow-growing populations mining SOM and fast-growing populations for the energy-rich residue entering the soil. Our study leads to hypotheses about the consequences of climate change on both PE generation mechanisms and associated consequences on soil carbon sequestration.

Correction: Mapping and predictive variations of soil bacterial richness across France.

[This corrects the article DOI: 10.1371/journal.pone.0186766.].

The interaction of soil phototrophs and fungi with pH and their impact on soil CO2, CO18O and OCS exchange.

The stable oxygen isotope composition of atmospheric CO2 and the mixing ratio of carbonyl sulphide (OCS) are potential tracers of biospheric CO2 fluxes at large scales. However, the use of these tracers hinges on our ability to understand and better predict the activity of the enzyme carbonic anhydrase (CA) in different soil microbial groups, including phototrophs. Because different classes of the CA family (α, ß and γ) may have different affinities to CO2 and OCS and their expression should also vary between different microbial groups, differences in the community structure could impact the 'community-integrated' CA activity differently for CO2 and OCS. Four soils of different pH were incubated in the dark or with a diurnal cycle for forty days to vary the abundance of native phototrophs. Fluxes of CO2, CO18O and OCS were measured to estimate CA activity alongside the abundance of bacteria, fungi and phototrophs. The abundance of soil phototrophs increased most at higher soil pH. In the light, the strength of the soil CO2 sink and the CA-driven CO2-H2O isotopic exchange rates correlated with phototrophs abundance. OCS uptake rates were attributed to fungi whose abundance was positively enhanced in alkaline soils but only in the presence of increased phototrophs. Our findings demonstrate that soil-atmosphere CO2, OCS and CO18O fluxes are strongly regulated by the microbial community structure in response to changes in soil pH and light availability and supports the idea that different members of the microbial community express different classes of CA, with different affinities to CO2 and OCS.

Mapping and predictive variations of soil bacterial richness across France.

Although numerous studies have demonstrated the key role of bacterial diversity in soil functions and ecosystem services, little is known about the variations and determinants of such diversity on a nationwide scale. The overall objectives of this study were i) to describe the bacterial taxonomic richness variations across France, ii) to identify the ecological processes (i.e. selection by the environment and dispersal limitation) 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 rRNA genes 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 111km, where the main drivers were the soil physico-chemical properties (18% of explained variance), the spatial descriptors (5.25%, 1.89% and 1.02% for the fine, medium and coarse scales, respectively), and the land use (1.4%). 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.

Soil C and N models that integrate microbial diversity.

Industrial agriculture is yearly responsible for the loss of 55-100 Pg of historical soil carbon and 9.9 Tg of reactive nitrogen worldwide. Therefore, management practices should be adapted to preserve ecological processes and reduce inputs and environmental impacts. In particular, the management of soil organic matter (SOM) is a key factor influencing C and N cycles. Soil microorganisms play a central role in SOM dynamics. For instance, microbial diversity may explain up to 77 % of carbon mineralisation activities. However, soil microbial diversity is actually rarely taken into account in models of C and N dynamics. Here, we review the influence of microbial diversity on C and N dynamics, and the integration of microbial diversity in soil C and N models. We found that a gain of microbial richness and evenness enhances soil C and N dynamics on the average, though the improvement of C and N dynamics depends on the composition of microbial community. We reviewed 50 models integrating soil microbial diversity. More than 90 % of models integrate microbial diversity with discrete compartments representing conceptual functional groups (64 %) or identified taxonomic groups interacting in a food web (28 %). Half of the models have not been tested against an empirical dataset while the other half mainly consider fixed parameters. This is due to the difficulty to link taxonomic and functional diversity.

Microbial Diversity Indexes Can Explain Soil Carbon Dynamics as a Function of Carbon Source.

Mathematical models do not explicitly represent the influence of soil microbial diversity on soil organic carbon (SOC) dynamics despite recent evidence of relationships between them. The objective of the present study was to statistically investigate relationships between bacterial and fungal diversity indexes (richness, evenness, Shannon index, inverse Simpson index) and decomposition of different pools of soil organic carbon by measuring dynamics of CO2 emissions under controlled conditions. To this end, 20 soils from two different land uses (cropland and grassland) were incubated with or without incorporation of 13C-labelled wheat-straw residue. 13C-labelling allowed us to study residue mineralisation, basal respiration and the priming effect independently. An innovative data-mining approach was applied, based on generalized additive models and a predictive criterion. Results showed that microbial diversity indexes can be good covariates to integrate in SOC dynamics models, depending on the C source and the processes considered (native soil organic carbon vs. fresh wheat residue). Specifically, microbial diversity indexes were good candidates to help explain mineralisation of native soil organic carbon, while priming effect processes seemed to be explained much more by microbial composition, and no microbial diversity indexes were found associated with residue mineralisation. Investigation of relationships between diversity and mineralisation showed that higher diversity, as measured by the microbial diversity indexes, seemed to be related to decreased CO2 emissions in the control soil. We suggest that this relationship can be explained by an increase in carbon yield assimilation as microbial diversity increases. Thus, the parameter for carbon yield assimilation in mathematical models could be calculated as a function of microbial diversity indexes. Nonetheless, given limitations of the methods used, these observations should be considered with caution and confirmed with more experimental studies. Overall, along with other studies on relationships between microbial community composition and SOM dynamics, this study suggests that overall measures of microbial diversity may constitute relevant ways to include microbial diversity in models of SOM dynamics.