Southern marsh deer (Blastocerus dichotomus) populations assessed using Amplicon Sequencing on fecal samples
Bibliographic record
Abstract
Abstract Populations in isolated and small fragments lose genetic variability very fast and are usually of conservation concern because they are at greater risk of local extinction. The largest native deer in South America, Blastocerus dichotomus (Illiger, 1815), is a Vulnerable species according to the IUCN categorization, which inhabits tropical and subtropical swampy areas. In Argentina, its presence has been restricted to four isolated fragments. Here we examine the genetic diversity and differentiation among three of them, including the three different patches that form the southernmost population, using 18 microsatellite markers genotyped by Amplicon Sequencing of DNA extracted from fecal samples. Genetic diversity was low (HE < 0.45) in all three populations studied. We found three genetic clusters compatible with the geographic location of the samples. We also found a metapopulation dynamics that involves the patches that make up the southernmost population, with evidence of a barrier to gene flow between two of them. Our results point to the creation of a corridor as a necessary and urgent management action. This is the first study, at the population level, employing microsatellite genotyping by Amplicon Sequencing with non-invasive samples in an endangered species.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 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".