Phylogeny, Classification, and Character Evolution of <i>Acalypha</i> (Euphorbiaceae: Acalyphoideae)
Bibliographic record
Abstract
Abstract— Acalypha (Euphorbiaceae: Acalyphoideae) is a large, monophyletic genus distributed worldwide in tropical and subtropical regions, with a few species extending into temperate areas of southern Africa, Asia, and North and South America. We reconstructed phylogenetic relationships within the genus using DNA sequences from the plastid ndhF and trnL-F regions and the nuclear ribosomal ITS region, sampling 142 species to represent the geographic, morphologic, and taxonomic diversity with the genus, resulting in a 162 (158 in Acalypha) terminal and 3847 character combined dataset. Bayesian and maximum likelihood reconstructions based on the combined dataset yielded a tree with a generally well-supported backbone and several strongly supported clades. Our results strongly supported the monophyly of Acalypha subg. Acalypha as currently recognized but showed that A. subg. Linostachys and almost all other infrageneric taxa recognized in the most recent comprehensive classification of the genus were not monophyletic. We therefore propose a new subgeneric classification comprising A. subg. Acalypha, A. subg. Androcephala, A. subg. Hypandrae, and A. subg. Linostachys (s.s.). Our results also shed light on relationships within some species groups, including in what has been treated as a broadly defined A. amentacea, in which we recognize A. amentacea, A. palauensis comb. nov., and A. wilkesiana as distinct species. Bayesian ancestral state estimations based on the phylogeny of Acalypha demonstrated that inflorescence position and sexuality and habit show high homoplasy, especially within A. subg. Acalypha, and that inflorescence position and habit exhibit correlated evolution.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| 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 | 0.001 | 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".