Under Biological Invasion: Impacts of Litter Decomposition Mediated by Invasive Plant Species on Soil Nutrients and Functional Growth Traits of both Invasive and Native Plant Species
Bibliographic record
Abstract
Abstract An invasive plant, Solidago canadensis is quickly encroaching across Eastern China and has become a crucial concern in the alteration of native ecosystem structure and function. However, the impact on invaded soil from S. canadensis litter is still under consideration. This study evaluated the effects of different levels of litter mass (Control: L0, 5 g: L5, 10 g: L10, 15 g: L15, and 20 g: L20) of invasive S. canadensis on the functional traits of two congeneric plant species (S. canadensis and S. decurrens), as well as resulting variations in soil nutrient levels. Our results indicated that shoot and root length, fresh and dry biomass, leaf chlorophyll and leaf nitrogen were significantly higher at L15 compared to the other treatments in the experiment. Additionally, in the L20 treatment all traits were decreased drastically, although these were higher than the control treatment, i.e. L0. Soil nutrients increased as the level of litter mass was raised in the soil. Furthermore, our study showed that high litter mass from S. canadensis can adversely impact the functional traits of both plant species. Further studies are required to assess the allelopathic effect of litter mass, as well as biological and physicochemical properties of field soil where high quantities of the invasive plant litter are found.
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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 | 0.001 |
| 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".