Evolutionary history of the buildup and breakdown of the heterostylous syndrome in Plumbaginaceae
Bibliographic record
Abstract
The evolutionary pathways leading to the heterostylous syndrome are not well understood, and models concerning the origins of distyly differ in the order in which reciprocal herkogamy and self-incompatibility evolve. We investigated the evolution and breakdown of distyly in Plumbaginaceae, a family with considerable diversity of floral traits and reproductive systems. Using Bayesian Markov chain Monte Carlo analyses and stochastic character mapping, we examined the evolutionary assembly and breakdown of the heterostylous syndrome based on a well-resolved phylogeny of 121 species of Plumbaginaceae and six outgroup taxa using five nuclear and plastid gene regions. We used the distribution of reproductive traits and reconstructed ancestral characters across phylogenies to evaluate competing models for the evolution of distyly. The most likely common ancestor of Plumbaginaceae was self-incompatible and monomorphic for sex-organ arrangement and pollen-stigma characters. Character state reconstructions indicated that reciprocal herkogamy evolved at least three times and that shifts to selfing and apomixis occurred on multiple occasions. Our results provide comparative support for the early ideas of H. G. Baker on evolutionary pathways in Plumbaginaceae, and the more recent selfing avoidance model by D. & B. Charlesworth in which distyly evolves from self-incompatible ancestors.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".