The influence of water availability and defoliation on extrafloral nectar secretion in quaking aspen (<i>Populus tremuloides</i>)
Bibliographic record
Abstract
In recent years, water stress has led to widespread growth declines and dieback of several North American tree species. In addition to its direct effects on tree physiology, water stress may compromise anti-herbivore defenses. We tested whether extrafloral (EF) sugar secretion rate in Populus tremuloides Michx. (quaking aspen) increases in response to defoliation and whether water stress impairs constitutive and inducible EF sugar secretion. We subjected P. tremuloides ramets of four genotypes to water restriction and defoliation in a factorial design and measured EF sugar secretion rates 2, 4, and 6 days after defoliation. The sugar secretion rate of defoliated ramets was significantly higher than that of undefoliated ramets 6 days after defoliation. Low water availability reduced the sugar secretion rate of one of the four aspen genotypes but did not prevent induction. Populus tremuloides genotypes secreted EF sugar at different average rates, suggesting genetic variation for this trait. The results indicate that EF nectar secretion is inducible in P. tremuloides, which could increase the effectiveness of indirect defense following herbivory. Genotypic differences in the response of P. tremuloides to water stress suggest that some clonal stands may be at a disadvantage when faced with compound stresses of drought and herbivory.
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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) | 0.000 | 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".