Pest or pest control? Coyote interactions with cattle and Richardson's ground squirrels
Bibliographic record
Abstract
Coyotes ( Canis latrans Say, 1823) are ubiquitous across Canadian grasslands and have been implicated as causing millions of dollars of damage each year by injuring or killing cattle ( Bos taurus Linnaeus, 1758). Gaining insight into the behaviour of coyotes in proximity to cattle may mitigate these costs. We hypothesized that coyotes obtain direct (e.g., killing calves or scavenging cattle) and indirect (e.g., hunting native prey) benefits from cattle pastures. We further hypothesized that cows respond defensively to coyotes. We conducted 58 focal observations of coyotes from May to August in southwest Saskatchewan and recorded activity, prey species, distance from cattle, and the response of cattle to coyotes. Coyotes hunted native prey more often than they interacted with cattle. Coyotes were often within 100 m of cattle when hunting Richardson's ground squirrels ( Urocitellus richardsonii (Sabine, 1822), formerly Spermophilus richardsonii (Sabine, 1822)), their most common prey. Coyotes scavenged from cattle carcasses ( N = 5), occasionally approached calves ( N = 2), rushed herds ( N = 2), or consumed afterbirth ( N = 1). Cows and/or calves chased coyotes in 43% of observations having encounters within 10 m. Our data suggest coyotes primarily use cattle pastures to obtain native prey, although periodic opportunities to scavenge cattle or kill calves may contribute to their use of these areas.
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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 | 0.000 | 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) | 0.002 | 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".