Effect of <i>Ageratina adenophora</i> invasion on the composition and diversity of soil microbiome
Bibliographic record
Abstract
In the present study, high throughput 16S rRNA gene sequencing was used to investigate soil invaded by the aggressive weed Ageratina adenophora to determine its effect on the species composition, distribution, and biodiversity of the bacterial communities. Soil samples from 12 micro-sites containing a monoculture of A. adenophora plants, mixtures of A. adenophora and different native plant species, and native species alone were studied. We found that the invasion of this weed resulted in a selection of bacteria belonging to phyla Acidobacteria and Verrucomicrobia and the lack of bacteria belonging to phyla Actinobacteria and Planctomycetes, but did not affect significantly the percentage abundances of members of other phyla. A similar bacterial population selection was also observed at genus or subgroup levels. The NO3–-N level was an important factor affecting soil bacterial communities and contributed to the dominance of A. adenophora. However, the numbers of total bacterial species, and the diversity and structure of soil bacterial microbiome did not (P > 0.05) change significantly following invasion by this weed.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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".