Multiscale analysis reveals restricted gene flow and a linear gradient in heterozygosity for an island population of feral horses
Bibliographic record
Abstract
We studied the genetic (microsatellite) diversity of a feral population of horses ( Equus caballus L., 1758) on Sable Island, Nova Scotia, Canada (1983–2003), at two spatial scales: (1) for the island as a whole and (2) at the level of four equally sized subdivisions along the length of Sable Island, which is a long (42 km) and narrow (1.5 km) vegetated sand bar. At the island scale (n = 264 horses), observed heterozygosity over 10 loci was 0.647 ± 0.035 (mean ± 1 SE), while expected heterozygosity was 0.696 ± 0.029; we observed significant heterozygote deficiency with all loci considered (P < 0.0001). At the subdivision scale, observed heterozygosity ranged from 0.589 to 0.694 in a gradient from west to east. We observed a corresponding gradient in effective number of alleles and allelic richness. Pairwise values of FSTwere significant for most subdivision pairs, ranging as high as 0.067 from west to east. Western areas showed highest levels of inbreeding (FIS = 0.113) with outbreeding indicated in the east (FIS = –0.008). Our results suggest that for a large mammal that lives in polygynous social groups, like the feral horse, gene flow along linear habitats (corridors) may be restricted (relative to the dispersal capabilities of the species), even over short distances.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".