Evolutionary History of the Galápagos Rail Revealed by Ancient Mitogenomes and Modern Samples
Bibliographic record
Abstract
The biotas of the Galápagos Islands are one of the best studied island systems and have provided a broad model for insular species’ origins and evolution. Nevertheless, some locally endemic taxa, such as the Galápagos Rail Laterallus spilonota, remain poorly characterized. Owing to its elusive behavior, cryptic plumage, and restricted distribution, the Galápagos Rail is one of the least studied endemic vertebrates of the Galapagos Islands. To date, there is no genetic data for this species, leaving its origins, relationships to other taxa, and levels of genetic diversity uncharacterized. This lack of information is critical given the adverse fate of island rail species around the world in the recent past. Here, we examine the genetics of Galápagos Rails using a combination of mitogenome de novo assembly with multilocus nuclear and mitochondrial sequencing from both modern and historical samples. We show that the Galápagos Rail is part of the “American black rail clade”, sister to the Black Rail L. jamaicensis, with a colonization of Galápagos dated to 1.2 million years ago. A separate analysis of one nuclear and two mitochondrial markers in the larger population samples demonstrates a shallow population structure across the islands, possibly due to elevated island connectivity. Additionally, birds from the island Pinta possessed the lowest levels of genetic diversity, possibly reflecting past population bottlenecks associated with overgrazing of their habitat by invasive goats. The modern and historical data presented here highlight the low genetic diversity in this endemic rail species and provide useful information to guide conservation efforts.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 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".