Wolf-Cougar Co-occurrence in the Central Canadian Rocky Mountains
Bibliographic record
Abstract
Cougars and wolves are top carnivores that influence the dynamics of an ecosystem, including prey behavior and dynamics, and interspecific competition. Studies about the interactions between wolves and cougars typically find wolves are dominant competitors to cougars. We examined single-species, single-season occupancy models and co-occurrence models of wolves and cougars in the Central Canadian Rocky Mountains to understand interactions between these two species on a grand landscape. Data was collected from 2012-2013 using remote wildlife cameras and separated into seasons. Naïve occupancy estimates were larger for wolves in both seasons, but both species had smaller ranges in winter. There were only slight differences in environmental covariates for the single-species, single-season occupancy models, yet wolf occupancy estimates were still higher than cougars in both seasons. When wolves were species A in the co-occurrence models, results showed cougar occurrence and detection to be independent of wolf presence. However, when cougars were species A in the co-occurrence models, top models showed wolf occurrence and detection to be conditional on cougar presence. Overall, the top competing models in both seasons for either species A had some conditionality, yet no environmental covariates were significant in any co-occurrence model. These results are difficult to interpret; we suspect slight spatial separation between wolves and cougars in this study area, but further studies about smaller-scale competition could uncover more significant interactions between the two carnivores.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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".