Integrating morphological and genetic limits in the taxonomic delimitation of the Cuban taxa of Magnolia subsect. Talauma (Magnoliaceae)
Bibliographic record
Abstract
An accurate taxa delimitation, based on a full understanding of evolutionary processes involved in taxa differentiation, can be gained from a combination of ecological, morphological, and molecular approaches. The taxonomy of Magnolia subsect. Talauma in Cuba has long been debated and exclusively based on traditional morphological study of a limited number of individuals. A more accurate description of leaf morphology variation using geometric morphometrics combined with genetic data could bring consistency to taxa delimitation in this group. Leaf samples for the morphological (243) and genetic (461) analyses were collected throughout the entire distribution range. The variability of each taxon was analyzed through multivariate and geometric morphometry, and 21 genetic markers (SSR). The observed leaf morphological variability was higher than previously described. Morphological and genetic classifications were highly congruent in two out of four taxa. Our data brought evidence that Magnolia orbiculata can be considered a true species with very clear genetic and morphological limits. The main taxonomic issues concern the north-eastern Cuban populations of Magnolia subsect. Talauma. The data supported the existence of two clear groups: corresponding mainly to M. minor - M. oblongifolia and T. ophiticola . However, these two groups cannot be considered fully delimited since genetic markers provided evidence of genetic admixture between them. Due to the likely absence of, at least strong, reproductive barriers between these three taxa, we propose therefore to consider them as a species complex.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".