Herbivore-Mediated Selection on Floral Display Covaries Nonlinearly With Plant-Antagonistic Interaction Intensity Among Primrose Populations
Bibliographic record
Abstract
Quantifying the relations between plant-antagonistic interactions and natural selection among populations is important for predicting how spatial variation in ecological interactions drive adaptive differentiation. Here, we investigate the relations between the opportunity for selection, herbivore-mediated selection, and the intensity of plant-herbivore interaction among 11 populations of the insect-pollinated plant Primula florindae over 2 years. We experimentally quantified herbivore-mediated directional selection on three floral traits (two display and one phenological) within populations and found evidence for herbivore-mediated selection for a later flowering start date and a greater number of flowers per plant. The opportunity for selection and strength of herbivore-mediated selection on number of flowers varied nonlinearly with the intensity of herbivory among populations. These parameters increased and then decreased with increasing intensity of plant-herbivore interactions, defined as an increase in the ratio of herbivore-damaged flowers per individual. Our results provide novel insights into how plant-antagonistic interactions can shape spatial variation in selection on floral traits and contribute toward understanding the mechanistic basis of geographic variation in angiosperm flowers.
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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 | 0.001 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".