That's So Last Season: Unraveling the Genomic Consequences of Fur Farming in Arctic Foxes ( <i>Vulpes lagopus</i> )
Bibliographic record
Abstract
Humans have relied on animal fur for centuries, yet fur farming only began recently during the mid-19th Century. Little is known about this incipient domestication or the genomic processes involved. Domestication may involve founder effects, population bottlenecks and low population size, which, when combined with intense artificial selection, lead to inbreeding, a limited gene pool and reduced fitness. The arctic fox (Vulpes lagopus) has been farmed intensively since the early 1900s and has been artificially selected for economic phenotypes. We investigated the origin of these lineages and the genomic consequences of intensive farming by comparing the genomes of farmed and wild arctic foxes from across their range. Our research indicates recent inbreeding through long Runs of Homozygosity and reduced genomic variation in farmed foxes relative to their respective wild populations. We identified a coastal ecotype origin for all Fennoscandian farmed arctic foxes, aligning them phylogenetically with the wild Icelandic population, a geographically isolated and phenotypically distinct coastal lineage. The depleted genome-wide heterozygosity and increased recent inbreeding in farmed fox lineages is consistent with a heavy consequence of domestication, shedding light on the demographic history and genomic consequences of human manipulation. We highlight the need for increased genomic investigations into fur farm populations to understand the incipient domestication process and uncover the cost of intense farming. The genomic consequences of domestication must be considered in the management of fur farms, with actionable steps needed to prevent descendants of escaped farmed foxes from polluting the gene pool in the wild through introgression.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| 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".