Characterization of rhizosphere and endophytic fungal communities from roots of <i>Stipa purpurea</i> in alpine steppe around Qinghai Lake
Bibliographic record
Abstract
Stipa purpurea is among constructive endemic species in the alpine steppe on the Qinghai-Xizang Plateau. To reveal the fungal community structure and diversity in the rhizosphere and roots of this important grass and to analyze the potential influence of different habitats on the structure of fungal communities, we explored the root endophyte and the directly associated rhizosphere communities of S. purpurea by using internal transcribed spacer rRNA cloning and sequencing methods. We found that the roots of S. purpurea are associated with a diverse consortium of Basidiomycota (59.8%) and Ascomycota (38.5%). Most fungi obtained from rhizosphere soil in S. purpurea have been identified as Ascomycetes, while the high proportion detected in roots were basidiomycetous endophytes. The species richness, diversity, and evenness of fungal assemblages were higher in roots than in the rhizosphere soil. Fungi inhabiting the rhizosphere and roots of S. purpurea are significantly different, and the rhizosphere and endophyte communities are largely independent with little overlap in the dominant phyla or operational taxonomic units. Taken together, these results suggested that a wide variety of fungal communities are associated with the roots and rhizosphere soil of S. purpurea and that the fungal assemblages are strongly influenced by different habitats.
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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 | 0.001 | 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) | 0.000 | 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".