Data from: Wolf ecology and caribou-primary prey-wolf spatial relationships in low productivity peatland complexes in northeastern Alberta
Bibliographic record
Abstract
Woodland caribou (Rangifer tarandus caribou) in northeastern Alberta have historically been provided a refuge from wolf (Canis lupus) predation by using habitats not typically occupied by moose (Alces alces), which are the primary prey species for wolves in this region. However, in recent years most caribou populations in northeastern Alberta have declined, suggesting that they no longer have a refuge from wolf predation. I tested the hypotheses that (1) primary prey densities have increased since recent industrial expansion into caribou range, resulting in a numeric response by wolves; and (2) an altered wolf-primary prey system has reduced the ability of caribou to spatially separate from other prey - and consequently wolves - in this system. My results showed that wolf densities in the region have increased from approximately 6/1,000 km2 to approximately 11/1,000 km2. Based on my estimates, there has also been a corresponding increase in ungulate biomass, which appears to be primarily due to the recent increase in white-tailed deer (Odocoileus virginianus). My results suggest that wolf use and selection of this novel prey species has also increased dramatically, particularly during the snow season. Similarly, I found that wolf use and selection for beaver (Castor canadensis) was substantively higher than suggested by previous studies in this region. Wolf use of beaver was highest in the snow-free season, and could result in increased wolf-caribou encounters at this time of year. Moose were an important prey species for wolves throughout the year. These results suggest that wolves within caribou range in northeastern Alberta currently utilize multiple primary prey species. The spatial overlap between wolves and caribou has increased substantively within the past decade; however, caribou still attempt to avoid high predation risk by spatially separating from areas that tend to be selected by primary prey species and wolves. Despite differential habitat selection, the proportion of caribou in wolf diet appears to have increased in the past decade, suggesting that bog-fen habitat provides only a partial refuge from predation. These findings are integral to the effective management of primary prey and wolves in caribou ranges in northeastern Alberta, and will help inform caribou landscape planning teams in decision making processes.
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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 | 0.001 |
| Science and technology studies | 0.001 | 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".