Soil protist function varies with elevation in the Swiss Alps.

Protists are abundant and play key trophic functions in soil. Documenting how their trophic contributions vary across large environmental gradients is essential to understand and predict how biogeochemical cycles will be impacted by global changes. Here, using amplicon sequencing of environmental DNA in open habitat soil from 161 locations spanning 2600 m of elevation in the Swiss Alps (from 400 to 3000 m), we found that, over the whole study area, soils are dominated by consumers, followed by parasites and phototrophs. In contrast, the proportion of these groups in local communities shows large variations in relation to elevation. While there is, on average, three times more consumers than parasites at low elevation (400-1000 m), this ratio increases to 12 at high elevation (2000-3000 m). This suggests that the decrease in protist host biomass and diversity toward mountains tops impact protist functional composition. Furthermore, the taxonomic composition of protists that infect animals was related to elevation while that of protists that infect plants or of protist consumers was related to soil pH. This study provides a first step to document and understand how soil protist functions vary along the elevational gradient.

Predicting spatial patterns of soil bacteria under current and future environmental conditions.

Soil bacteria are largely missing from future biodiversity assessments hindering comprehensive forecasts of ecosystem changes. Soil bacterial communities are expected to be more strongly driven by pH and less by other edaphic and climatic factors. Thus, alkalinisation or acidification along with climate change may influence soil bacteria, with subsequent influences for example on nutrient cycling and vegetation. Future forecasts of soil bacteria are therefore needed. We applied species distribution modelling (SDM) to quantify the roles of environmental factors in governing spatial abundance distribution of soil bacterial OTUs and to predict how future changes in these factors may change bacterial communities in a temperate mountain area. Models indicated that factors related to soil (especially pH), climate and/or topography explain and predict part of the abundance distribution of most OTUs. This supports the expectations that microorganisms have specific environmental requirements (i.e., niches/envelopes) and that they should accordingly respond to environmental changes. Our predictions indicate a stronger role of pH over other predictors (e.g. climate) in governing distributions of bacteria, yet the predicted future changes in bacteria communities are smaller than their current variation across space. The extent of bacterial community change predictions varies as a function of elevation, but in general, deviations from neutral soil pH are expected to decrease abundances and diversity of bacteria. Our findings highlight the need to account for edaphic changes, along with climate changes, in future forecasts of soil bacteria.

Greater topoclimatic control of above- versus below-ground communities.

Assessing the degree to which climate explains the spatial distributions of different taxonomic and functional groups is essential for anticipating the effects of climate change on ecosystems. Most effort so far has focused on above-ground organisms, which offer only a partial view on the response of biodiversity to environmental gradients. Here including both above- and below-ground organisms, we quantified the degree of topoclimatic control on the occurrence patterns of >1,500 taxa and phylotypes along a c. 3,000 m elevation gradient, by fitting species distribution models. Higher model performances for animals and plants than for soil microbes (fungi, bacteria and protists) suggest that the direct influence of topoclimate is stronger on above-ground species than on below-ground microorganisms. Accordingly, direct climate change effects are predicted to be stronger for above-ground than for below-ground taxa, whereas factors expressing local soil microclimate and geochemistry are likely more important to explain and forecast the occurrence patterns of soil microbiota. Detailed mapping and future scenarios of soil microclimate and microhabitats, together with comparative studies of interacting and ecologically dependent above- and below-ground biota, are thus needed to understand and realistically forecast the future distribution of ecosystems.

Archaeorhizomycetes Spatial Distribution in Soils Along Wide Elevational and Environmental Gradients Reveal Co-abundance Patterns With Other Fungal Saprobes and Potential Weathering Capacities.

Archaeorhizomycetes, a widespread fungal class with a dominant presence in many soil environments, contains cryptic filamentous species forming plant-root associations whose role in terrestrial ecosystems remains unclear. Here, we apply a correlative approach to identify the abiotic and biotic environmental variables shaping the distribution of this fungal group. We used a DNA sequencing dataset containing Archaeorhizomycetes sequences and environmental variables from 103 sites, obtained through a random-stratified sampling in the Western Swiss Alps along a wide elevation gradient (>2,500 m). We observed that the relative abundance of Archaeorhizomycetes follows a "humped-shaped" curve. Fitted linear and quadratic generalized linear models revealed that both climatic (minimum temperature, precipitation sum, growing degree-days) and edaphic (carbon, hydrogen, organic carbon, aluminum oxide, and phyllosilicates) factors contribute to explaining the variation in Archaeorhizomycetes abundance. Furthermore, a network inference topology described significant co-abundance patterns between Archaeorhizomycetes and other saprotrophic and ectomycorrhizal fungal taxa. Overall, our results provide strong support to the hypothesis that Archaeorhizomycetes in this area have clear ecological requirements along wide, elevation-driven abiotic and biotic gradients. Additionally, correlations to soil redox parameters, particularly with phyllosilicates minerals, suggest Archaeorhizomycetes might be implied in biological rock weathering. Such soil taxa-environment studies along wide gradients are thus a useful complement to latitudinal field observations and culture-based approaches to uncover the ecological roles of cryptic soil organisms.

Generalizing soil properties in geographic space: Approaches used and ways forward.

Soil is one of the most complex systems on Earth, functioning at the interface between the lithosphere, biosphere, hydrosphere, and atmosphere and generating a multitude of functions. Moreover, soil constitutes the belowground environment from which plants capture water and nutrients. Despite their great importance, soil properties are often not sufficiently considered in other disciplines, especially in spatial studies of plant distributions. Most soil properties are available as point data and, to be used in spatial analyses, need to be generalised over entire regions (i.e. digital soil mapping). Three categories of statistical approaches can be used for such purpose: geostatistical approaches (GSA), predictive-statistical approaches (PSA), and hybrid approaches (HA) that combine the two previous ones. How then to choose the best approach in a given soil study context? Does it depend on the soil properties to be spatialized, the study area's characteristics, and/or the availability of soil data? The main aims of this study was to review the use of these three approaches to derive maps of soil properties in relation to the soil parameters, the study area characteristics, and the number of soil samples. We evidenced that the approaches that tend to show the best performance for spatializing soil properties were not necessarily the ones most used in practice. Although PSA was the most widely used, it tended to be outperformed by HA in many cases, but the latter was far less used. However, as the study settings were not always properly described and not all situations were represented in the set of papers analysed, more comparative studies would be needed across a wider range of regions, soil properties, and spatial scales to provide robust conclusions on the best spatialization methods in a specific context.

Meta-scale mountain grassland observatories uncover commonalities as well as specific interactions among plant and non-rhizosphere soil bacterial communities.

Interactions between plants and bacteria in the non-rhizosphere soil are rarely assessed, because they are less direct and easily masked by confounding environmental factors. By studying plant vegetation alliances and soil bacterial community co-patterning in grassland soils in 100 sites across a heterogeneous mountain landscape in the western Swiss Alps, we obtained sufficient statistical power to disentangle common co-occurrences and weaker specific interactions. Plant alliances and soil bacterial communities tended to be synchronized in community turnover across the landscape, largely driven by common underlying environmental factors, such as soil pH or elevation. Certain alliances occurring in distinct, local, environmental conditions were characterized by co-occurring specialist plant and bacterial species, such as the Nardus stricta and Thermogemmatisporaceae. In contrast, some generalist taxa, like Anthoxanthum odoratum and 19 Acidobacteria species, spanned across multiple vegetation alliances. Meta-scale analyses of soil bacterial community composition and vegetation surveys, complemented with local edaphic measurements, can thus prove useful to identify the various types of plant-bacteria interactions and the environments in which they occur.

Local Environmental Factors Drive Divergent Grassland Soil Bacterial Communities in the Western Swiss Alps.

Mountain ecosystems are characterized by a diverse range of climatic and topographic conditions over short distances and are known to shelter a high biodiversity. Despite important progress, still little is known on bacterial diversity in mountain areas. Here, we investigated soil bacterial biogeography at more than 100 sampling sites randomly stratified across a 700-km2 area with 2,200-m elevation gradient in the western Swiss Alps. Bacterial grassland communities were highly diverse, with 12,741 total operational taxonomic units (OTUs) across 100 sites and an average of 2,918 OTUs per site. Bacterial community structure was correlated with local climatic, topographic, and soil physicochemical parameters with high statistical significance. We found pH (correlated with % CaO and % mineral carbon), hydrogen index (correlated with bulk gravimetric water content), and annual average number of frost days during the growing season to be among the groups of the most important environmental drivers of bacterial community structure. In contrast, bacterial community structure was only weakly stratified as a function of elevation. Contrasting patterns were discovered for individual bacterial taxa. Acidobacteria responded both positively and negatively to pH extremes. Various families within the Bacteroidetes responded to available phosphorus levels. Different verrucomicrobial groups responded to electrical conductivity, total organic carbon, water content, and mineral carbon contents. Alpine grassland bacterial communities are thus highly diverse, which is likely due to the large variety of different environmental conditions. These results shed new light on the biodiversity of mountain ecosystems, which were already identified as potentially fragile to anthropogenic influences and climate change. IMPORTANCE: This article addresses the question of how microbial communities in alpine regions are dependent on local climatic and soil physicochemical variables. We benefit from a unique 700-km2 study region in the western Swiss Alps region, which has been exhaustively studied for macro-organismal and fungal ecology, and for topoclimatic modeling of future ecological trends, but without taking into account soil bacterial diversity. Here, we present an in-depth biogeographical characterization of the bacterial community diversity in this alpine region across 100 randomly stratified sites, using 56 environmental variables. Our exhaustive sampling ensured the detection of ecological trends with high statistical robustness. Our data both confirm previously observed general trends and show many new detailed trends for a wide range of bacterial taxonomic groups and environmental parameters.