The Soil Microbiome of GLORIA Mountain Summits in the Swiss Alps
Bibliographic record
Abstract
While vegetation has intensively been surveyed on mountain summits, limited knowledge exists about the diversity and community structure of soil biota. Here, we study how climatic variables, vegetation, parent material, soil properties, and slope aspect affect the soil microbiome on 10 GLORIA (Global Observation Research Initiative in Alpine environments) mountain summits ranging from the lower alpine to the nival zone in Switzerland. At these summits we sampled soils from all four aspects and examined how the bacterial and fungal communities vary by using Illumina MiSeq sequencing. We found that mountain summit soils contain highly diverse microbial communities with a total of 10,406 bacterial and 6,291 fungal taxa. Bacterial α-diversity increased with increasing soil pH and decreased with increasing elevation, whereas fungal α-diversity did not change significantly. Soil pH was the strongest predictor for microbial β-diversity. Bacterial and fungal community structures exhibited a significant positive relationship with plant communities, indicating that summits with a more distinct plant composition also revealed more distinct microbial communities. The influence of elevation was stronger than aspect on the soil microbiome. Several microbial taxa responded to elevation and soil pH. Chloroflexi and Mucoromycota were significantly more abundant on summits at higher elevations, whereas the relative abundance of Basidiomycota and Agaricomycetes decreased with elevation. Most bacterial OTUs belonging to the phylum Acidobacteria were indicators for siliceous parent material and several OTUs belonging to the phylum Planctomycetes were associated with calcareous soils. The trends for fungi were less clear. Indicator OTUs belonging to the genera Mortierella and Naganishia showed a mixed response to parent material, demonstrating their ubiquitous and opportunistic behaviour in soils. Overall, fungal communities responded weakly to abiotic and biotic factors. In contrast, bacterial communities were strongly influenced by environmental changes suggesting they will be strongly affected by future climate change and associated temperature increase and an upward migration of vegetation. Our results provide the first insights into the soil microbiome of mountain summits in the European Alps that are shaped as a result of highly variable local environmental conditions and may help to predict responses of the soil biota to global climate change.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".