Dynamic landscapes in northwestern North America structured populations of wolverines (<i>Gulo gulo</i>)
Bibliographic record
Abstract
Abstract Cyclic climatic and glacial fluctuations of the Late Quaternary produced a dynamic biogeographic history for high latitudes. To refine our understanding of this history in northwestern North America, we explored geographic structure in a wide-ranging carnivore, the wolverine (Gulo gulo). We examined genetic variation in populations across mainland Alaska, coastal Southeast Alaska, and mainland western Canada using nuclear microsatellite genotypes and sequence data from the mitochondrial DNA (mtDNA) control region and Cytochrome b (Cytb) gene. Data from maternally inherited mtDNA reflect stable populations in Northwest Alaska, suggesting the region harbored wolverine populations since at least the Last Glacial Maximum (LGM; 21 Kya), consistent with their persistence in the fossil record of Beringia. Populations in Southeast Alaska are characterized by minimal divergence, with no genetic signature of long-term refugial persistence (consistent with the lack of pre-Holocene fossil records there). The Kenai Peninsula population exhibits mixed signatures depending on marker type: mtDNA data indicate stability (i.e., historical persistence) and include a private haplotype, whereas biparentally inherited microsatellites exhibit relatively low variation and a lack of private alleles consistent with a more recent Holocene colonization of the peninsula. Our genetic work is largely consistent with the early 20th century taxonomic hypothesis that wolverines on the Kenai Peninsula belong to a distinct subspecies. Our finding of significant genetic differentiation of wolverines inhabiting the Kenai Peninsula, coupled with the peninsula’s burgeoning human population and the wolverine’s known sensitivity to anthropogenic impacts, provides valuable foundational data that can be used to inform conservation and management prescriptions for wolverines inhabiting these landscapes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 teacher head, 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".