Movements of Wolves at the Northern Extreme of the Species' Range, Including during Four Months of Darkness
Bibliographic record
Abstract
Information about wolf (Canis lupus) movements anywhere near the northern extreme of the species' range in the High Arctic (>75°N latitude) are lacking. There, wolves prey primarily on muskoxen (Ovibos moschatus) and must survive 4 months of 24 hr/day winter darkness and temperatures reaching -53 C. The extent to which wolves remain active and prey on muskoxen during the dark period are unknown, for the closest area where information is available about winter wolf movements is >2,250 km south. We studied a pack of ≥20 wolves on Ellesmere Island, Nunavut, Canada (80°N latitude) from July 2009 through mid-April 2010 by collaring a lead wolf with a Global Positioning System (GPS)/Argos radio collar. The collar recorded the wolf's precise locations at 6:00 a.m. and 6:00 p.m. daily and transmitted the locations by satellite to our email. Straight-line distances between consecutive 12-hr locations varied between 0 and 76 km. Mean (SE) linear distance between consecutive locations (n = 554) was 11 (0.5) km. Total minimum distance traveled was 5,979 km, and total area covered was 6,640 km(2), the largest wolf range reported. The wolf and presumably his pack once made a 263-km (straight-line distance) foray to the southeast during 19-28 January 2010, returning 29 January to 1 February at an average of 41 km/day straight-line distances between 12-hr locations. This study produced the first detailed movement information about any large mammal in the High Arctic, and the average movements during the dark period did not differ from those afterwards. Wolf movements during the dark period in the highest latitudes match those of the other seasons and generally those of wolves in lower latitudes, and, at least with the gross movements measurable by our methods, the 4-month period without direct sunlight produced little change in movements.
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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 | 0.001 | 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".