Herkogamy and Mating Patterns in the Self-compatible Daffodil Narcissus longispathus
Bibliographic record
Abstract
BACKGROUND AND AIMS: Floral design in self-compatible plants can influence mating patterns. This study investigated Narcissus longispathus, a self-compatible bee-pollinated species with wide variation in anther-stigma separation (herkogamy), to determine the relationship between variation in this floral trait and the relative amounts of cross- and self-fertilization. METHODS: Anther-stigma separation was measured in the field in six populations of N. longispathus from south-eastern Spain. Variation in herkogamy during the life of individual flowers was also quantified. Multilocus outcrossing rates were estimated from plants differing in herkogamy using allozyme markers. KEY RESULTS: Anther-stigma separation varied considerably among flowers within the six populations studied (range = 1-10 mm). This variation was nearly one order of magnitude larger than the slight, statistically non-significant developmental variation during the lifespan of individual flowers. Estimates of multilocus outcrossing rate for different herkogamy classes (t(m) range = 0.49-0.76) failed to reveal a monotonic increase with increasing herkogamy. CONCLUSIONS: It is suggested that the lack of a positive relationship between herkogamy and outcrossing rate, a result that has not been previously documented for other species, could be mostly related to details of the foraging behaviour of pollinators.
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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".