Winter Habitat Use by Wolves, <em>Canis lupus</em>, in Relation to Forest Harvesting in West-central Alberta
Bibliographic record
Abstract
Forested landscapes in west-central Alberta are facing increased pressures from forest harvesting and other land-use activities, which may alter the movements and distribution of Wolves and ungulates. Information on habitat use by Wolves in logged forests is scarce, potentially limiting effective land-use planning in the boreal forest. Nine Wolves, from four Wolf packs, were fitted with GPS radiocollars in the Rocky Mountain foothills, near Grande Cache, Alberta (2000-2001). We found Wolves did not use the landscape randomly, but rather exhibited a significant preference for non-forested natural habitats (shrubs, water), relative to their availability. Within forest habitats, Wolves used cutblocks proportionately more than unharvested forest and non-forested anthropogenic habitats (pipelines, clearings); however, selection of forest cutblocks was not statistically significant. We found no evidence that Wolves preferred or avoided forest cutblock edges. Wolf pack territories contained various levels of timber harvesting, but most areas were still in the early stages of harvest. Nevertheless, these areas have been allocated for large-scale harvesting. Understanding the potential responses of Wolves to rapidly changing landscape mosaics poses a significant challenge to researchers and managers, but such information is important to informing future land-management and conservation strategies for boreal forest Wolf-prey systems.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 teacher head, 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".