Phylogenetic analysis of the ecological correlates of dioecy in angiosperms
Bibliographic record
Abstract
We report on a phylogenetic analysis of correlations between the occurrence of dioecy and several ecological and life-history attributes: tropical distribution, woody growth form, abiotic pollination, small inconspicuous flowers and inflorescences, many-flowered inflorescences and fleshy fruits. Various hypotheses have been proposed to explain why associations occur between dioecy and several of these attributes, yet most assume that dioecy originates more often in clades with these traits than in clades with alternative character states. To investigate correlations between dioecy and these attributes, and to provide insights into the potential evolutionary pathways that have led to these associations, we assigned states of these traits to genera on a large-scale molecular phylogeny of the angiosperms; we then used maximum-likelihood analysis to analyse the presence of correlations and the sequence of acquisition of traits. Phylogenetic analysis revealed correlations between dioecy and six of the seven attributes; only many-flowered inflorescences exhibiting no association with the dioecious condition. The particular correlations that were revealed and the strength of the association differed among the three main monophyletic groups of angiosperms (Rosids, Asterids, and Eumagnoliids). Our analysis provided no general support for the hypothesis that dioecy is more likely to evolve in lineages already possessing the seven attributes we considered. Further analysis of the intercorrelations of the seven attributes provided evidence for non-independence between some of the traits, implying that functional associations among these traits have influenced the ecology and evolution of dioecious species.
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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 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".