Effects of <i>Pleioblastus viridistriatus</i> expansion on species diversity of understory vegetation and soil bacterial community in subtropical forests
Bibliographic record
Abstract
As one of the most widely used dwarf bamboos, Pleioblastus viridistriatus has well-developed rhizome and root systems, which can rapidly expand into forest stands. However, little is known about the influence of P. viridistriatus expansion on the undergrowth diversity in subtropical forests of China and its association with the diversity of soil bacterial microbiota. The species diversity and soil bacterial community structure were investigated in a forest where P. viridistriatus was expanding into coniferous and broad-leaved mixed forest. We found that P. viridistriatus expansion reduced species diversity in the shrub and herbaceous layers and had significant effects on major soil physicochemical properties. In addition, the alpha diversity indexes were significantly increased and the abundance of Actinobacteria and Candidatus Saccharibacteria increased, while the abundance of Nitrospirae and Deinococcus-Thermus decreased with the increasing expansion. At the genus level, a total of 25 genera of soil bacteria showed significant difference in abundance. Overall, expansion of P. viridistriatus reduced forest species diversity, while increased soil nutrient accumulation and specific bacterial abundance to improve nutrient acquisition. Our results can provide guidance for controlling dwarf bamboo expansion and help the sustainable forest management.
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 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".