Arctic fox dispersal from Svalbard to Canada: one female’s long run across sea ice
Bibliographic record
Abstract
We report the first satellite tracking of natal dispersal by an Arctic fox (Vulpes lagopus) between continents and High-Arctic ecosystems. A young female left Spitsbergen (Svalbard Archipelago, Norway) on 26 March 2018 and reached Ellesmere Island, Nunavut, Canada, 76 days later, after travelling a cumulative distance of 3506 km, bringing her ca. 1789 km away (straight-line distance) from her natal area. The total cumulative distance travelled during the entire tracking period, starting when she left her natal area on 1 March 2018 and ending when she settled on Ellesmere Island on 1 July 2018, was 4415 km. This is among the longest dispersal events ever recorded for an Arctic fox. Crossing extensive stretches of sea ice and glaciers, the female moved at an average rate of 46.3 km/day ± 41.1 SD. The maximum movement rate was 155 km/day and occurred on the ice sheet in northern Greenland. This is the fastest movement rate recorded for this species. The northernmost location recorded was on the sea ice off northern Greenland at a latitude of 84.7°N. The Arctic fox was of the blue colour morph typical for coastal environments, where Arctic foxes are adapted to food webs without lemmings but with substantial inputs of marine food resources. The Arctic fox settled on Ellesmere Island in a food web with lemmings, thereby switching ecosystems. Our observation supports evidence of gene flow across Arctic regions, including those seasonally bridged by sea ice, found in studies of the circumpolar genetic structure of Arctic fox populations. View the supplementary animation. This article has a related Erratum.
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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 | 0.003 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".