Genetic patterns in Neotropical Magnolias (Magnoliaceae) using de novo developed microsatellite markers
Bibliographic record
Abstract
Conserving tree populations safeguards forests since they represent key elements of the ecosystem. The genetic characteristics underlying the evolutionary success of the tree growth form: high genetic diversity, extensive gene flow and strong species integrity, contribute to their survival in terms of adaptability. However, different biological and landscape contexts challenge these characteristics. This study employs 63 de novo developed microsatellite or SSR (Single Sequence Repeat) markers in different datasets of nine Neotropical Magnolia species. The genetic patterns of these protogynous, insect-pollinated tree species occurring in fragmented, highly-disturbed landscapes were investigated. Datasets containing a total of 340 individuals were tested for their genetic structure and degree of inbreeding. Analyses for genetic structure depicted structuring between species, i.e. strong species integrity. Within the species, all but one population pair were considered moderate to highly differentiated, i.e. no indication of extensive gene flow between populations. No overall correlation was observed between genetic and geographic distance of the pairwise species' populations. In contrast to the pronounced genetic structure, there was no evidence of inbreeding within the populations, suggesting mechanisms favouring cross pollination and/or selection for more genetically diverse, heterozygous offspring. In conclusion, the data illustrate that the Neotropical Magnolias in the context of a fragmented landscape still have ample gene flow within populations, yet little gene flow between populations.
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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 | 0.000 | 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 | 0.000 | 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 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".