Asymmetrical mating patterns and the evolution of biased style-morph ratios in a tristylous daffodil
Bibliographic record
Abstract
Non-random mating in plant populations can be influenced by numerous reproductive and demographic factors, including floral morphology and inter-plant distance. Here, we investigate patterns of outcrossed mating through male function in Narcissus triandrus, a tristylous, bee-pollinated wild daffodil from the Iberian Peninsula, to test pollen transfer models which predict that floral morphology promotes asymmetrical mating and biased morph ratios. Unlike other tristylous species, N. triandrus has an incompatibility system that permits intra-morph mating and long-level rather than mid-level stamens in the L-morph. Incomplete sex-organ reciprocity should result in significant intra-morph mating in the L-morph. We measured mating patterns in two L-biased populations--dimorphic (two style morphs) and trimorphic (three style morphs)--using multilocus genotyping and maximum-likelihood-based paternity analysis. We also examined the spatial distribution of style morphs and neutral markers to investigate the potential consequence of spatially restricted mating on morph ratios. As predicted, we detected significant amounts of intra-morph mating in the L-morph in both populations. Pollen transfer coefficients generally supported predictions based on the Darwinian hypothesis that anthers and stigmas of equivalent level promote pollinator-mediated cross-pollination in heterostylous populations. There was evidence of significant spatial aggregation of both style morphs and neutral markers in populations of N. triandrus, probably as a result of restricted pollen and seed dispersal. Our results provide empirical support for theoretical models of pollen transfer, which indicate that the commonly observed L-biased morph ratios in Narcissus species result from significant intra-morph mating in the L-morph because of its atypical floral morphology.
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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".