From venison to beef: seasonal changes in wolf diet composition in a livestock grazing landscape
Bibliographic record
Abstract
Wild ungulates are the primary prey for wolves in North America, but livestock predation is a concern in areas where wolves and livestock overlap. Using clusters of global positioning system telemetry relocations and scat analysis, we investigated wolf diets year‐round in southwestern Alberta, where seasonal cattle grazing is the predominant land use and wolf–cattle conflicts have increased in recent years. Both methods indicated a seasonal shift in wolf diets, from wild prey during the non‐grazing season to cattle in the grazing season. Wolves scavenged more frequently during the non‐grazing season than during the grazing season; 85% of all scavenging events occurred at ranchers' boneyards (where livestock carcasses are dumped), where wolves fed on dead livestock. Cattle represent a higher proportion of wolf diets than previously thought; we recommend the sanitary disposal of dead livestock to prevent wolves from becoming accustomed to feeding on livestock, and the development of management plans aimed at reducing predation on cattle if humans and wolves are to coexist on landscapes that are dominated by livestock ranching.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.000 | 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".