Pollinators and herbivores interactively shape selection on strawberry defence and attraction
Bibliographic record
Abstract
Plant-herbivore-pollinator interactions are of ecological relevance for most angiosperms. However little is known on how plants evolve in response – and in particular how these tripartite interactions influence phenotypic selection on traits that link pollination and herbivory. We here conducted a common garden experiment with woodland strawberry (Fragaria vesca L.) to quantify pollinator- and herbivore-mediated selection on nine traits related to plant defence and attraction. Our results showed that pollinators imposed stronger selection than herbivores on both direct and indirect (i.e., tritrophic-related) defence traits – whereas conflicting selection was imposed on inflorescence density. However, in all cases, selection imposed by one agent was context-dependant on the other, suggesting that dynamic patterns of selection are likely a prevalent feature of these interactions. Our findings highlight the significance of plant-herbivore-pollinator interactions as potential drivers of evolutionary change, and reveal that pollinators may play a generally underappreciated role as selective agents on plant defence.
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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) | 0.002 | 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".