Characterization of the root and soil mycobiome associated with invasive <i>Microstegium vimineum</i> in the presence and absence of a native plant community
Bibliographic record
Abstract
The potential role of fungal root endophytes (including mycorrhizae) in the invasiveness of Microstegium vimineum (Trin.) A. Camus, was researched using automated ribosomal intergenic spacer analysis (ARISA) and brightfield microscopy. Fungal communities of roots from two native plants (Onoclea sensibilis L. and Amphicarpaea bracteata (L.) Fernald) were compared with those found in Microstegium. Fungal communities from the bulk soils also were examined in terms of their potential influence on the root mycobiomes. All three plants occurred in natural communities as monocultures and together in one mixed community in Northern Virginia where Microstegium has recently invaded. Principal coordinate analysis of ARISA data identified fungal communities unique to roots from each monoculture. When the three plants co-occurred in a mixed setting, Microstegium was found to maintain its distinct fungal community while the fungal communities of the two native plants overlapped. In contrast, soil fungal communities showed no specific plant associations. Brightfield microscopy confirmed the presence of endophytic fungi in all three plants. The results recorded here suggest a positive contribution by the root mycobiome in promoting the invasive ability of Microstegium, providing a basis for future experiments testing this hypothesis.
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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 | 0.000 | 0.000 |
| 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) | 0.000 | 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".