‘A most complex marriage arrangement’: recent advances on heterostyly and unresolved questions
Bibliographic record
Abstract
Heterostylous genetic polymorphisms provide paradigmatic systems for investigating adaptation and natural selection. Populations are usually comprised of two (distyly) or three (tristyly) mating types, maintained by negative frequency-dependent selection resulting from disassortative mating. Theory predicts this mating system should result in equal style-morph ratios (isoplethy) at equilibrium. Here, I review recent advances on heterostyly, focusing on examples challenging stereotypical depictions of the polymorphism and unresolved questions. Comparative analyses indicate multiple origins of heterostyly, often within lineages. Ecological studies demonstrate that structural components of heterostyly are adaptations improving the proficiency of animal-mediated cross-pollination and reducing pollen wastage. Both neutral and selective processes cause deviations from isoplethy in heterostylous populations, and, under some ecological and demographic conditions, cause breakdown of the polymorphism, resulting in either the evolution of autogamy and mixed mating, or transitions to alternative outcrossing systems, including dioecy. Earlier ideas on the genetic architecture of the S-locus supergene governing distyly have recently been overturned by discovery that the dominant S-haplotype is a hemizygous region absent from the s-haplotype. Ecological, phylogenetic and molecular genetic data have validated some features of theoretical models on the selection of the polymorphism. Although heterostyly is the best-understood floral polymorphism in angiosperms, many unanswered questions remain.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.011 |
| Scholarly communication | 0.003 | 0.014 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".