Combining phylogenomic and morphological data reveals new patterns of diversity in the national tree of Brasil, Paubrasilia echinata
Bibliographic record
Abstract
Abstract Paubrasilia echinata (Lam.) Gagnon, H. C. Lima & G. P. Lewis (“Pau Brasil”) is the national tree of Brazil and an endangered species endemic to the Brazilian Atlantic Forest. The extensive range of distribution, spanning over 2000 km distance, is matched by extensive plasticity in leaf morphology. Three morphotypes are commonly identified based on the size of the leaflets but it is unclear if they represent distinct taxa or a single polymorphic species. This study aims to clarify the taxonomic position of the three morphotypes to inform conservation decisions. A comprehensive morphometric study based on herbarium specimens from the entire distribution range of the species was coupled with genetic analyses of population structure using genotype-by-sequencing data. We found that the three morphotypes do not match separately evolving lineages. Rather, P. echinata is composed of five genetic lineages that are geographically structured, although we did find evidence of genetic admixture in two individuals. Leaflet size varied by over 35-fold and although morphological clustering generally matched the genetic patterns, there were some overlaps, highlighting the cryptic diversity within this group. Finally, our genetic and morphological results provide some evidence that cultivated trees from different states in Brazil seem to be most closely related to a genetic lineage from northern Brazil, which suggests that more care is needed to protect and preserve the overall genomic diversity of this highly endangered and iconic species.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".