An Estimate of Wolverine Density for the Canadian Province of Alberta
Bibliographic record
Abstract
ABSTRACT Wolverines (Gulo gulo) are a circumboreal species that has experienced substantial range reduction worldwide. In Canada, the wolverine has been extirpated entirely from the east, and from prairie regions in the west. The province of Alberta holds the south‐central portion of wolverines' Canadian range, and there they have been designated as Data Deficient since 2001 due to a historical lack of information. Our aim was to provide a first approximation of a wolverine abundance estimate at the provincial scale to inform science‐based management as well as status designation. We synthesised existing density estimates and wolverine–habitat relationships to create a province‐wide density estimate for wolverines. Densities were derived from five landscapes, spanning protected National Parks in the Rocky Mountains, the highly developed Foothills and the northcentral and northwestern boreal forests. Densities were estimated using spatially explicit capture–recapture (SECR) models. Densities ranged from 6.74 wolverines/1000 km2 in the northwest boreal to 0.71 wolverines/1000 km2 in the foothills. The proportion of adults was based on a study from the northwest, which estimated 57% adults to 43% subadults. Extrapolating densities across natural subregions (bioclimatic ecoregions), based on known habitat relationships, it was estimated that there were 955 wolverines in the province, of which 544 were adults. This number falls well below an IUCN threshold for a legally listed species; we suggest a reassessment of the wolverine status in Alberta and considering commensurate conservation actions.
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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 | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".