Reproductive assurance varies with flower size in <i>Collinsia parviflora</i> (Scrophulariaceae)
Bibliographic record
Abstract
A central question in plant evolutionary ecology is how mixed mating systems are maintained in the face of selection against self-pollination. Recently, attention has focused on the potential reproductive assurance (RA) benefit of selfing: the ability to produce seeds via autonomous selfing when the potential for outcrossing is reduced or absent. To date, there is little experimental support for this benefit under natural pollination conditions. In addition, the RA hypothesis has not been tested experimentally in a species displaying morphological variation for traits expected to influence the mating system, such as flower size, which affects both attractiveness to pollinators and ability to self autonomously. Here, we document significant among-population variation in flower size in Collinsia parviflora and show that pollinators preferred large flowers over small flowers in experimental arrays. The pollinator community varied among three study sites, and two small-flowered populations had lower pollinator visitation rates than one large-flowered population. We compared seed production between intact flowers (can self) and experimentally emasculated flowers (require a pollinator) on large- and small-flowered plants. As predicted by the RA hypothesis, small-flowered plants show a greater RA benefit of selfing than large-flowered plants; emasculated, small flowers produced very few seeds, relative to intact, small flowers or either emasculated or intact, large flowers. We also show that the RA benefit is pollination-context dependent, differing between small- and large-flowered test sites, likely due to a combination of pollinator discrimination against small flowers and differences between test sites in the pollinator community. This paper is the first experimental evidence showing a trait-dependent RA benefit of selfing under natural pollination conditions.
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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".