Comparing the genetic population structure of two species of arctic lemmings: more local differentiation in <i>Lemmus trimucronatus</i> than in <i>Dicrostonyx groenlandicus</i>
Bibliographic record
Abstract
Collared and brown lemmings ( Dicrostonyx groenlandicus and Lemmus trimucronatus ) are two largely sympatric and ecologically comparable species of arctic microtine rodents, differing however in some respects which allow us to hypothesise differences in the genetic structure of their populations. Collared lemmings are particularly well adapted to life at high latitude, they occasionally emerge to the surface of the snow and may disperse over larger distances than brown lemmings – possibly even over snow and ice. This should result in more local differentiation among populations of brown lemmings than among populations of collared lemmings. We compared the genetic population structure between the two lemming species in a fragmented landscape with small islands in the central Canadian Arctic using four microsatellite loci and partial mitochondrial control region sequences. Both types of genetic markers showed higher differentiation ( F ST values) among local populations for brown lemmings than for collared lemmings. We discuss to what extent the observed genetic differences may be explained by differences in dispersal rates in addition to differences in average effective population size.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".