Pollinators and herbivores interactively shape selection on strawberry defence and attraction
Bibliographic record
Abstract
Abstract Tripartite interactions between plants, herbivores, and pollinators hold fitness consequences for most angiosperms. However, little is known on how plants evolve in response—and in particular what the net selective outcomes are for traits of shared relevance to pollinators and herbivores. In this study, we manipulated herbivory (“presence” and “absence” treatments) and pollination (“open” and “hand pollination” treatments) in a full factorial common-garden experiment with woodland strawberry (Fragaria vesca L.). This design allowed us to quantify the relative importance and interactive effects of herbivore- and pollinator-mediated selection on nine traits related to plant defence and attraction. Our results showed that pollinators imposed stronger selection than herbivores on traits related to both direct and indirect (i.e., tritrophic) defence. However, conflicting selection was imposed on inflorescence density: a trait that appears to be shared by herbivores and pollinators as a host plant signal. However, in all cases, selection imposed by one agent depended largely on the presence or ecological effect of the other, suggesting that dynamic patterns of selection could be a common outcome of these interactions in natural populations. As a whole, our findings highlight the significance of plant-herbivore-pollinator interactions as potential drivers of evolutionary change, and reveal that pollinators likely play an underappreciated role as selective agents on direct and in direct 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 | 0.001 | 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".