Correlations among Fertility Components Can Maintain Mixed Mating in Plants
Bibliographic record
Abstract
Classical models studying the evolution of self-fertilization in plants conclude that only complete selfing and complete outcrossing are evolutionarily stable. In contrast with this prediction, 42% of seed-plant species are reported to have rates of self-fertilization between 0.2 and 0.8. We propose that many previous models fail to predict intermediate selfing rates because they do not allow for functional relationships among three components of reproductive fitness: self-fertilized ovules, outcrossed ovules, and ovules sired by successful pollen export. Because the optimal design for fertility components may differ, conflicts among the alternative pathways to fitness are possible, and the greatest fertility may be achieved with some self-fertilization. Here we develop and analyze a model to predict optimal selfing rates that includes a range of possible relationships among the three components of reproductive fitness, as well as the effects of evolving inbreeding depression caused by deleterious mutations and of selection on total seed number. We demonstrate that intermediate selfing is optimal for a wide variety of relationships among fitness components and that inbreeding depression is not a good predictor of selfing-rate evolution. Functional relationships subsume the myriad effects of individual plant traits and thus offer a more general and simpler perspective on mating system evolution.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".