Data from: Antiherbivore defenses alter natural selection on plant reproductive traits
Bibliographic record
Abstract
While many studies demonstrate that herbivores alter selection on plant reproductive traits, little is known about whether antiherbivore defenses affect selection on these traits. We hypothesized that antiherbivore defenses could alter selection on reproductive traits by altering trait expression through allocation trade-offs, or by altering interactions with mutualists and/or antagonists. To test our hypothesis, we used white clover, Trifolium repens, which has a Mendelian polymorphism for the production of hydrogen cyanide—a potent antiherbivore defense. We conducted a common garden experiment with 185 clonal families of T. repens that included cyanogenic and acyanogenic genotypes. We quantified resistance to herbivores, and selection on 6 floral traits and phenology via male and female fitness. Cyanogenesis reduced herbivory but did not alter the expression of reproductive traits through allocation trade-offs. However, the presence of cyanogenic defenses altered natural selection on petal morphology and the number of flowers within inflorescences via female fitness. Herbivory influenced selection on flowers and phenology via female fitness independently of cyanogenesis. Our results demonstrate that both herbivory and antiherbivore defenses alter natural selection on plant reproductive traits. We discuss the significance of these results for understanding how antiherbivore defenses interact with herbivores and pollinators to shape floral evolution.
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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) | 0.018 | 0.002 |
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".