Structures and determinants of soil microbiomes along a steep elevation gradient in Southwest China
Bibliographic record
Abstract
Soil microbial communities play a vital role in accelerating nutrient cycling and stabilizing ecosystem functions in forests. However, the diversity of soil microbiome and the mechanisms driving their distribution patterns along elevational gradients in montane areas remain largely unknown. In this study, we investigated the soil microbial diversity along an elevational gradient from 650 m to 3,800 m above sea level in southeast Tibet, China, through DNA metabarcode sequencing of both the bacterial and fungal communities. Our results showed that the dominant bacterial phyla across elevations were Proteobacteria, Acidobacteriota and Actinobacteriota, and the dominant fungal phyla were Ascomycota and Basidiomycota. The Simpson indices of both soil bacteria and fungi demonstrated a hollow trend along the elevational gradient, with an abrupt decrease in bacterial and fungal diversity at 2,600 m a.s.l. in coniferous and broad-leaved mixed forests (CBM). Soil bacterial chemoheterotrophy was the dominant lifestyle and was predicted to decrease with increasing elevation. In terms of fungal lifestyles, saprophytic and symbiotic fungi were the dominant functional communities but their relative abundance was negatively correlated with increasing elevation. Environmental factors including vegetation type (VEG), altitude (ALT), soil pH, total phosphorus (TP), nitrate nitrogen (NO3−-N), and polyphenol oxidase (ppo) all exhibited significant influence on the bacterial community structure, whereas VEG, ALT, and the carbon to nitrogen ratio (C/N) were significantly associated with the fungal community structure. The VPA results indicated that edaphic factors explained 37% of the bacterial community variations, while C/N, ALT, and VEG explained 49% of the total fungal community variations. Our study contributes significantly to our understanding of forest ecosystems in mountainous regions with large elevation changes, highlighting the crucial role of soil environmental factors in shaping soil microbial communities and their variations in specific forest ecosystems.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".