Leaf variegation is associated with reduced herbivore damage in <i>Hydrophyllum virginianum</i>
Bibliographic record
Abstract
Leaf variegation refers to local regions of the upper surface of a leaf having reduced or obstructed chlorophyll, which results in whitish spots. These lighter spots may compromise the photosynthetic efficiency of a leaf, and many competing hypotheses have been put forward to explain why this patterning may be adaptive. It has been suggested that variegation is either an adaptive response to environmental conditions or a defence mechanism against herbivore damage. To test whether leaf variegation reduces herbivore damage, we first assessed the frequency of variegated and nonvariegated leaves in natural populations of the plant Hydrophyllum virginianum L., and second, measured herbivore damage to both variegated and nonvariegated leaves. We found that variegated leaves were present at high frequencies within natural populations (6%–31%) and that nonvariegated leaves sustained nearly twice the amount of damage by comparison with variegated leaves. Therefore, leaf variegation appears to be beneficial by reducing herbivore damage to leaves. These data are consistent with the fundamental prediction of the herbivory hypothesis for the benefits of leaf variegation.
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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 | 0.000 |
| 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".