Dioecy does not consistently accelerate or slow lineage diversification across multiple genera of angiosperms
Bibliographic record
Abstract
Dioecy, the sexual system in which male and female organs are found in separate individuals, allows greater specialization for sex-specific functions and can be advantageous under various ecological and environmental conditions. However, dioecy is rare among flowering plants. Previous studies identified contradictory trends regarding the relative diversification rates of dioecious lineages vs their nondioecious counterparts, depending on the methods and data used. We gathered detailed species-level data for dozens of genera that contain both dioecious and nondioecious species. We then applied a probabilistic approach that accounts for differential speciation, extinction, and transition rates between states to examine whether there is an association between dioecy and lineage diversification. We found a bimodal distribution, whereby dioecious lineages exhibited higher diversification in certain genera but lower diversification in others. Additional analyses did not uncover an ecological or life history trait that could explain a context-dependent effect of dioecy on diversification. Furthermore, in-depth simulations of neutral characters demonstrated that such bimodality is also found when simulating neutral characters across the observed trees. Our analyses suggest that - at least for these genera with the currently available data - dioecy neither consistently places a strong brake on diversification nor is a strong driver.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".