Soil microbial communities of three grassland ecosystems in the Bayinbuluke, China
Bibliographic record
Abstract
The microbial community plays an important role in soil nutrient cycles and energy transformations in alpine grassland. In this study, we investigated the composition of the soil microbial community collected from alpine cold swamp meadow (ASM), alpine cold meadow (AM), and alpine cold desert steppe (ADS) within the Bayinbuluke alpine grassland, China, using Illumina amplicon sequencing. Of the 147 271 sequences obtained, 36 microbial phyla or groups were detected. The results showed that the ADS had lower microbial diversity than the ASM and AM, as estimated by the Shannon index. The Verrucomicrobia, Chloroflexi, Planctomycetes, Proteobacteria, and Actinobacteria were the predominant phyla in all 3 ecosystems. Particularly, Thaumarchaeota was only abundant in ASM, Bacteroidetes in AM, and Acidobacteria in ADS. Additionally, the predominant genus also differed with each ecosystem. Candidatus Nitrososphaera was predominant in ADS, the Pir4 lineage in ASM, and Sphingomonas in AM. Our results indicated that the soil microbial community structure was different for each grassland ecosystem in the Bayinbuluke.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 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".