Biological and environmental correlates of cougar (Puma concolor) survival in west central Alberta
Bibliographic record
Abstract
Large carnivores have a significant role in ecosystems and their role as apex predators can have cascading effects that influence ecosystem stability. Managing large carnivores requires an understanding of how they use the land and their vital rates, including survival. For cougars (Puma concolor), habitat selection is well documented, but the hazards that cougars face across the landscape are poorly understood. The risks that landscape features present can change temporally, increasing survival in one season while being a danger in another. Between 2016 – 2021 87 cougars were radio-collared and tracked in west central Alberta, Canada, for a total of 1158 cougar months with a mean monitoring time of 13.3 months. I documented 41 deaths, determined causes of mortality, generated survival estimates using Kaplan-Meier models by sex and age class annually and for each season [i.e., summer, winter, and hunting (a subset of winter)], and investigated hazards using Cox proportional hazard models. Humans were responsible for 33 of the 41 mortalities reported, with legal harvest being the highest cause of mortality (16/41 mortalities) for both males and females, with males more likely to be harvested. However, I was unable to detect a difference in survival estimates between sexes or age classes. Annual male subadult survival was 0.857 (CI = 0.633 - 1), male adult survival was 0.586 (CI = 0.406 - 0.845), female subadult survival was 0.857 (CI = 0.629 – 1) and female adult survival was 0.628 (CI = 0.512 – 0.770). While survival estimates of both sexes were lowest in the hunting season, I was unable to detect a difference in survival by season. I modelled the risk that biological and environmental variables imposed on each sex using Cox proportional hazards models with the Anderson-Gill model for staggered entry. Hazards differed by sex annually with both sexes showing increased hazard with high crossing rates of secondary roads and linear features, closer proximity to secondary roads and closer proximity and higher density of residential areas. Sexes differed with males showing increased hazard in open areas and wetlands and areas further from water. Females showed no difference in risk by landcover classification or distance to water but showed increased risk with higher primary road crossing rates. Hazards also varied between sexes within 2 of the seasons investigated. In the winter season both sexes had an increased risk with higher crossing rates of secondary roads and linear features as well as increasing proximity to secondary roads. Males also showed increased risk at higher residential densities and closer proximities. Females however had an increased risk with increased crossing rates of primary roads, and lower terrain ruggedness. Additionally, age class significantly influenced risk of males, with male kittens and subadults being higher risk than male adults, as well as increased risk within open areas and closer proximity to secondary roads. Females had increased risk with higher crossing rates of secondary roads and linear features and increased proximity and density of residences. Survival also was examined at a short temporal scale (ca. 48h) to determine proximate variables that resulted in death. For males 48hrs before death, I found kittens and subadults to be at higher risk than adults and that open areas, shrublands, and wetlands all increased risk as well as closer proximity to roads. For females, I found closer proximity to secondary roads and increasing residential density increased risk. Our results provide insight on how biological and environmental variables affect cougar survival and how hazards vary between sexes.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".