Effects of light intensity and artificial wounding on monoterpene production in <i>Myrica cerifera</i> from two different ecological habitats
Bibliographic record
Abstract
The contributions of multiple factors to plant defense and herbivory in different habitats has received limited study. This study examines the contributions of genotypic differentiation and modification by physical factors to chemical defense and herbivory of Myrica cerifera L. in contrasting habitats. The constitutive leaf monoterpene content of M. cerifera was higher in a sunny habitat than in an adjacent shady habitat at a southeastern USA coastal site. Leaf area loss was higher in the shady habitat than in the sunny habitat. A significant negative correlation of monoterpene content and leaf area loss suggests that monoterpenes may play toxic or deterrent roles in these plants. When plants from the two habitats were grown under uniform greenhouse conditions, the contents and compositions of leaf monoterpenes were not significantly different, implying that two ecotypes were not involved. The plants treated in high light intensity had significantly higher monoterpene content, higher growth rate, and denser glandular trichomes than the plants treated in low light intensity. Artificial wounding induced a significant increase of monoterpene production. However, the wounding responses of the plants from the two habitats were not different, nor did irradiance modify the response.Key words: ecotype, herbivory, light intensity, monoterpenes, wounding induction, Myrica cerifera.
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".