Data from: Genome-wide assessment of diversity and divergence among extant Galápagos giant tortoise species
Bibliographic record
Abstract
Genome-wide assessments allow for fuller characterization of genetic diversity, finer-scale population delineation, and better detection of demographically significant units to guide conservation compared to those based on “traditional” markers. Galapagos giant tortoises (Chelonoidis spp.) have long provided a case study for how evolutionary genetics may be applied to advance species conservation. Ongoing efforts to bolster tortoise populations, which have declined by 90%, have been informed by analyses of mitochondrial DNA sequence and microsatellite genotypic data, but could benefit from genome-wide markers. Taking this next step, we used double-digest restriction-site associated DNA sequencing to collect genotypic data at >26,000 single nucleotide polymorphisms (SNPs) for 117 individuals representing all recognized extant Galapagos giant tortoise species. We then quantified genetic diversity, population structure, and compared results to estimates from mitochondrial DNA and microsatellite loci. Our analyses detected 12 genetic lineages concordant with the 11 named species as well as previously described structure within one species, C. becki. Furthermore, the SNPs provided increased resolution, detecting admixture in four individuals. SNP-based estimates of diversity and differentiation were significantly correlated with those derived from nuclear microsatellite loci and mitochondrial DNA sequences. The SNP toolkit presented here will serve as a resource for advancing efforts to understand tortoise evolution, species radiations, and aid conservation of the Galapagos tortoise species complex.
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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 | 0.001 | 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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.004 | 0.026 |
| Research integrity | 0.000 | 0.000 |
| 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".