Female reproductive success and the evolution of mating‐type frequencies in tristylous populations
Bibliographic record
Abstract
In tristylous populations, mating-type frequencies are governed by negative frequency-dependent selection typically resulting in equal morph ratios at equilibrium. However, Narcissus triandrus generally exhibits long-styled (L)-biased populations with a deficiency of the mid-styled (M)-morph. Here we used a pollen-transfer model and measurements of female fertility in natural populations to investigate whether these uneven morph ratios were associated with variation in female reproductive success. Our theoretical analysis demonstrated that morph ratio bias can result from maternal fitness differences among the morphs, and that these effects were magnified by asymmetrical mating. In nine out of 15 populations of N. triandrus, seed set differed significantly among the morphs, but pollen limitation occurred in only two of 11 populations investigated. Average seed set of the M-morph was positively associated with its frequency in populations. Flower size was negatively correlated with the seed set of the M-morph. Our results suggest that interactions between mating patterns and female fertility are responsible for variation in morph frequencies and loss of the M-morph from tristylous populations of N. triandrus.
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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 | 0.001 | 0.001 |
| 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 | 0.001 |
| 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".