Isolation of peripheral populations of Canada lynx (<i>Lynx canadensis</i>)
Bibliographic record
Abstract
Landscape barriers to gene flow, such as rivers, can affect animal populations by limiting the potential for rescue of these isolated populations. We tested the riverine barrier hypothesis, predicting that the St. Lawrence River in eastern Canada would cause genetic divergence of Canada lynx (Lynx canadensis Kerr, 1792) populations by restricting dispersal and gene flow. We sampled 558 lynx from eastern Canada and genotyped these at 14 microsatellite loci. We found three genetic clusters, defined by the St. Lawrence River and the Strait of Belle Isle, a waterway separating Newfoundland from mainland Canada. However, these waterways were not absolute barriers, as we found 24 individuals that appeared to have crossed them. Peripheral populations of lynx are threatened in parts of Canada and the USA, and it is thought that these populations are maintained by immigration from the core. Our findings suggest that in eastern North America, rescue might be less likely because the St. Lawrence River restricts dispersal. We found that ice cover was often sufficient to allow lynx to walk across the ice in winter. If lynx used ice bridges in winter, then climate warming could cause a reduction in the extent and longevity of river and sea ice, further isolating these peripheral lynx populations.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 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".