Altitudinal Influences on Soil Microbial Diversity and Community Assembly in Topsoil and Subsoil Layers: Insights from the Jinsha River Basin, Southwest China
Bibliographic record
Abstract
Mountain regions play a crucial role in maintaining global biodiversity, with altitude exerting a significant influence on soil microbial diversity by altering plant diversity, soil nutrients, and microclimate. However, differences in microbial community composition between topsoil (0–10 cm deep) and subsoil (10–20 cm deep) remain poorly understood. Here, we aimed to assess soil microbial diversity, microbial network complexity, and microbial community assembly in the topsoil and subsoil layers of the dry–hot Jinsha River valley in southwestern China. Using high-throughput sequencing in soil samples collected along an altitudinal gradient, we found that bacterial diversity in topsoil decreased with increasing altitude, while bacterial diversity in subsoil showed no altitude-dependent changes. Fungal diversity in topsoil also varied with altitude, while subsoil fungal diversity showed no change. These findings suggest that microbial diversity in topsoil was more sensitive to changes in altitude than subsoil. Bacterial community assembly tended to be governed by stochastic processes, while fungal assembly was deterministic. Soil bacterial and fungal network complexity was enhanced with increasing altitude but reduced as diversity increased. Interestingly, the presence of woody plant species negatively affected bacterial and fungal community composition in both soil layers. Soil pH and water content also negatively affected microbial community composition, while organic carbon and total nitrogen positively influenced the microbial community composition. Simultaneously, herb and woody plant diversity mainly affected soil bacterial diversity in the topsoil and subsoil, respectively, while woody plant diversity mainly affected soil fungal diversity in subsoil and soil nutrients had more effect on soil fungal diversity. These findings suggest that altitude directly and indirectly affects microbial diversity in topsoil, subsequently influencing microbial diversity in subsoil through nutrient availability.
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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 | 0.000 | 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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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".