A dated molecular perspective of eucalypt taxonomy, evolution and diversification
Bibliographic record
Abstract
The eucalypts, which include Eucalyptus, Angophora and Corymbia, are native to Australia and Malesia and include over 800 named species in a mixture of diverse and depauperate lineages. We assessed the fit of the eucalypt taxonomic classification to a phylogeny of 711 species scored for DNA sequences of plastid matK and psbA–trnH, as well as nuclear internal transcribed spacer and external transcribed spacer. Two broadly similar topologies emerge from both maximum likelihood and Bayesian analyses, showing Angophora nested within Corymbia, or Angophora sister to Corymbia. The position of certain species-poor groups on long branches fluctuated relative to the three major Eucalyptus subgenera, and positions of several closely related species within those subgenera were unstable and lacked statistical support. Most sections and series of Eucalyptus were not recovered as monophyletic. We calibrated these phylogenies against time, using penalised likelihood and constraints obtained from fossil ages. On the basis of these trees, most major eucalypt subgenera arose in the Late Eocene and Early Oligocene. All Eucalyptus clades with taxa occurring in south-eastern Australia have crown ages <20 million years. Several eucalypt clades display a strong present-day geographic disjunction, although these clades did not have strong phylogenetic statistical support. In particular, the estimated age of the separation between the eudesmids (Eucalyptus subgenus Eudesmia) and monocalypts (Eucalyptus subgenus Eucalyptus) was consistent with extensive inland water bodies in the Eocene. Bayesian analysis of macroevolutionary mixture rates of net species diversification accelerated in five sections of Eucalyptus subgenus Symphyomyrtus, all beginning 2–3 million years ago and associated with semi-arid habitats dominated by mallee and mallet growth forms, and with open woodlands and forests in eastern Australia. This is the first time that a calibrated molecular study has shown support for the rapid diversification of eucalypts in the recent past, most likely driven by changing climate and diverse soil geochemical conditions.
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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 | 0.000 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".