Wolf density and predation patterns in the Canadian High Arctic
Bibliographic record
Abstract
Abstract The Arctic wolf (Canis lupus arctos) is a predator of muskoxen (Ovibos moschatus), Arctic hares (Lepus arcticus), and endangered Peary caribou (Rangifer tarandus pearyi) in the Canadian High Arctic. Although Arctic wolves potentially affect the dynamics of muskoxen and Peary caribou populations, knowledge about their abundance, distribution, and predation patterns is limited. Inuit and Inuvialuit communities value these species for sociocultural and subsistence reasons, and community members are concerned about how interactions among these species and their environment may change in a warming, unpredictable Arctic. We conducted a study from 2014–2018 of wolves in the rolling tundra of central Ellesmere Island (Fosheim Peninsula) and eastern Axel Heiberg Island. This area supported relatively high densities of muskoxen and Arctic hares, and previously supported Peary caribou, although caribou were mostly absent in the area during our study. We deployed global positioning system (GPS) radio‐collars on 10 adult wolves in 6 packs on Ellesmere and Axel Heiberg islands to describe wolf density and predation patterns. Wolves were neither nomadic nor migratory; they remained on territories year‐round, with summer densities of 2.5–8.0 adult wolves/1,000 km2 and 3.7–10.4 wolves/1,000 km2 including pups. Based on a ground search of 312 of 868 location clusters over a 340‐day period, wolves in a focal study pack killed approximately 0.12 muskoxen/day, equivalent to a predation rate of 5.5–17.0% of the estimated muskox population (older than 10 months old). This predation rate is likely sustainable given that calves and yearlings rather than reproductive adults comprised most documented kills, and that muskox populations can increase at rates up to 20%. The kill rate for this pack also implied a biomass intake deficit of 0.82–1.63 kg/wolf/day that could have been offset by each wolf consuming 115–228 Arctic hares annually. The decline of Peary caribou in the study area precluded any assessment of wolf predation influences on their population, but annual telemetry data confirming the year‐round presence of a wolf–ungulate–hare system with relatively high wolf densities suggests that apparent competition could present a challenge to Peary caribou recovery efforts.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 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".