Herbivore-induced volatile emission from old-growth black poplar trees under field conditions
Bibliographic record
Abstract
Herbivory is well known to trigger increased emission of volatile organic compounds (VOCs) from plants, but we know little about the responses of mature trees. We measured the volatiles emitted by leaves of old-growth black poplar (Populus nigra) trees after experimental damage by gypsy moth (Lymantria dispar) caterpillars in a floodplain forest, and studied the effect of herbivory on the transcript abundance of two genes involved in the biosynthesis of VOCs, and the accumulation of defence phytohormones. Herbivory significantly increased volatile emission from the experimentally damaged foliage, but not from adjacent undamaged leaves in the damaged branches (i.e., no systemic response). Methylbutyraldoximes, 4,8-dimethyl-1,3,7-nonatriene (DMNT), (Z)-3-hexenol and (E)-β-ocimene, amongst other compounds, were found to be important in distinguishing the blend of herbivore-damaged vs. undamaged leaves. Herbivory also increased expression of PnTPS3 (described here for the first time) and PnCYP79D6-v4 genes at the damaged sites, these genes encode for an (E)-β-ocimene synthase and a P450 enzyme involved in aldoxime formation, respectively, demonstrating de novo biosynthesis of the volatiles produced. Herbivore-damaged leaves had significantly higher levels of jasmonic acid and its conjugate (-)-jasmonic acid-isoleucine. This study shows that mature trees in the field have a robust response to herbivory, producing induced volatiles at the damaged sites even after previous natural herbivory and under changing environmental conditions, however, further studies are needed to establish whether the observed absence of systemic responses is typical of mature poplar trees or if specific conditions are required for their induction.
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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 | 0.000 |
| 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".