The Effect of Light on Plant Growth and Physiology of Acmella radicans and A. paniculata in China
Bibliographic record
Abstract
Acmella radicans (Jacquin) R.K.Jansen is an annual herb native to Central America. In China, it is becoming increasingly invasive and often co-occurs with the native congener A. paniculata (Wall. ex DC.) R.K.Jansen in some habitats. In order to understand the invasion mechanism of A. radicans, we investigated the growth parameters of both the invasive A. radicans and the native congener, A. paniculata, under different light conditions (5%, 25%, 50%, 75%, and 100% of light availability) using potted plants in a glasshouse. Light level, plant species, and their interaction were significant, with plant species generally having a greater effect than light level. Acmella radicans and A. paniculata showed great phenotypic plasticity to various light intensities and had a similar trend with increased shade. The plasticity indices of all parameters of A. radicans, except for branch length and inflorescence number, were greater than those of A. paniculata under the same light intensity. The physiological parameters for A. radicans under both favorable (high light intensity) and unfavorable (low light intensity) conditions showed less inhibition than those of A. paniculata. All these responses indicated that A. radicans had greater phenotypic plasticity and higher adaptability to low light, which may contribute to its invasion success.
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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 | 0.000 |
| 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".