Population Genetic Structure of an Endangered Endemic Primate (Leontopithecus chrysomelas) in a Highly Fragmented Atlantic Coastal Rain Forest
Bibliographic record
Abstract
This study evaluated the genetic structure of wild populations of the endangered primate, Leontopithecus chrysomelas. We tested the assumption that populations of L. chrysomelas, given their larger population size and a higher degree of habitat continuity, would have higher genetic diversity and less genetic structuring than other lion tamarins. We used 11 microsatellites and 122 hair samples from different locations to assess their genetic diversity and genetic structure, and to make inferences about the isolation by distance. The overall expected heterozygosity (0.51 ± 0.03) and the average number of alleles (3.6 ± 0.2) were relatively low, as is the case in other endangered lion tamarins. Genetic clustering analyses indicated two main clusters, whereas the statistical analyses based on genotype similarities and Fst suggested further substructure. A Mantel test showed that only 34% of this genetic differentiation was explained by the linear distance. In addition to linear distance, structural differences in the landscape, physical barriers and behavioural factors may be causing significant genetic structuring. Overall, this study suggests that these populations have a relatively low genetic diversity and a relatively high population genetic structure, putting in question whether the presence of agroforest systems (known locally as cabruca) is enough to fully re-establish functional landscape connectivity.
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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) | 0.001 | 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) | 0.002 | 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 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".