Genetic diversity, structure and gene flow of migratory barren-ground caribou (Rangifer tarandus groenlandicus) in Canada
Bibliographic record
Abstract
Migratory barren-ground caribou (Rangifer tarandus groenlandicus) provide an opportunity to examine the genetic population structure of a migratory large mammal whose movements and distribution, in some instances, have not been heavily influenced by human activities that result in habitat loss or fragmentation. These caribou have likely reached large effective population sizes since their rapid radiation during the early Holocene despite cyclic changes in abundance. Migratory barren-ground caribou are managed as discrete subpopulations. We investigated genetic variation among those subpopulations to determine the patterns of genetic diversity within and among them, and the implications for long-term persistence of caribou. We identified three distinct genetic clusters across the Canadian arctic tundra: the first cluster consisted of all fully-continental migratory barren-ground subpopulations; the second cluster was the Dolphin and Union caribou; and the third cluster was caribou from Southampton Island. The Southampton Island caribou are especially genetically distinct from the other barren-ground type caribou. Gene flow among subpopulations varied across the range. Occasional gene flow across the sea-ice is likely the reason for high levels of genetic variation in the Dolphin and Union subpopulation, which experienced very low numbers in the past. These results suggest that for most migratory caribou subpopulations, connectivity among subpopulations plays an important role in maintaining natural genetic diversity. Our analyses provide insight into the levels of microsatellite genetic diversity and patterns of gene flow that may be common to large subpopulations that historically had a continuous distribution across a large continental range. These data can also be used as a benchmark to compare the effects of habitat fragmentation and bottlenecks on other large caribou 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 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".