Long-term satellite tracking reveals patterns of long-distance dispersal in juvenile and adult Arctic foxes (<i>Vulpes lagopus</i>)
Bibliographic record
Abstract
Long-distance dispersal plays a key role in species distribution and persistence. However, its movement metrics and ecological implications may differ whether it is undertaken by juveniles (natal dispersal) or adults (breeding dispersal). We investigated the influence of life stage on long-distance dispersal in the Arctic fox, an important tundra predator. We fitted 170 individuals with satellite collars during a 13-year study on Bylot Island (Nunavut, Canada), and analysed the tracks of 10 juveniles and 27 adults engaging in long-distance dispersal across the Canadian High Arctic. This behaviour was much more common than expected, especially in juveniles (62.5%, adults: 19.4%). Emigration of juveniles occurred mainly at the end of summer while departure of adults was not synchronized. Juveniles travelled for longer periods and over longer cumulative distances than adults, but spent similar proportions of their time travelling on sea ice versus land. Successful immigration occurred mostly in late spring and was similar for juveniles and adults (30% versus 37%). Our results reveal how life stage influences key aspects of long-distance dispersal in a highly mobile canid. This new knowledge is critical to understand the circumpolar genetic structure of the species, and how Arctic foxes can spread zoonoses across vast geographical areas.
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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".