Bibliographic record
Abstract
Predation by cougars (Puma concolor) variously can structure ecosystems and preserve biodiversity, engender conflict where livestock and pets are killed, and even drive prey populations to extinction. Effective management requires a firm grasp of the ecological drivers of predation, but these remain poorly understood due to difficulty obtaining sufficient data. My objective was to test hypotheses about drivers of predation in a population of wild cougars foraging in a multi-prey system in west-central Alberta, Canada. To obtain necessary data, I began by refining Global Positioning System (GPS) telemetry cluster techniques to monitor predation. I found that models alone were insufficient and that field visitation was required to estimate kill rate and prey composition accurately, but logistic regression models could direct field-work to improve efficiency, permitting continuous monitoring of cougar predation and generating large sample sizes. I assessed the role of scavenging as a foraging strategy and found that cougars scavenged opportunistically, reducing predation when carrion availability was high. Scavenging also made cougars susceptible to incidental snaring at wolf bait stations, and survival analysis revealed important consequences for cougar population trajectory and harvest management. I evaluated competing hypotheses about the magnitude of cougar predation and the influence of season and prey vulnerability on kill rate and prey composition. Cougars were effective predators, killing ungulates at rates near the upper end of the previously reported range. Cougar kill-rate increased by a factor of 1.5 in summer and cougars shifted prey composition seasonally as predicted by the juvenile and reproductive vulnerability hypotheses. Analysis of a multi-species functional response (MSFR) revealed that cougar impact on small populations of endangered prey is reduced by a tendency towards prey-switching but can be aggravated by the presence of individual specialists. Contrary to expectation, cougar MSFR was not driven by prey density, but rather by cougar demography and relative abundance of various prey. Finally, I reject the notion that cougars are nocturnal ambush predators, demonstrating instead that they hunt actively and make kills frequently during the day, exhibiting activity patterns loosely tied to those of their prey. I discuss the application of my findings for management and conservation.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".