Sex in advertising: dioecy alters the net benefits of attractiveness in <i>Sagittaria latifolia</i> (Alismataceae)
Bibliographic record
Abstract
The flowers and inflorescences of animal-pollinated dioecious plants are generally small and inconspicuous in comparison with outcrossing cosexual species. The net benefits of an attractive floral display may be different for dioecious compared to cosexual populations because dioecious species experience a more severe reduction in pollen delivery when pollinators forage longer on fewer individuals. Here, we develop a model that predicts the decrease in pollen delivery in dioecious relative to cosexual populations from female-female, female-male and male-male visit sequences as the number of individuals visited varies. To evaluate the predictions of our model we conducted a common garden experiment with dioecious and monoecious (cosexual) arrays of the insect-pollinated herb Sagittaria latifolia. We find that, although increasing the advertisements of floral rewards (i.e. increasing floral display) attracts more pollinators to individuals, the probability that these pollinators subsequently deliver pollen to neighbouring plants depends on sexual system. Because the number of individual plants visited per foraging trip did not increase significantly with floral display, the relative pollination success of dioecious versus monoecious populations decreases with increased floral display. We propose that this could explain why dioecy is strongly correlated with reduced floral display among angiosperm species.
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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".