Examining shifts in boreal carnivore species’ resource selection in response to predator control to conserve woodland caribou (Rangifer tarandus caribou) in western Canada
Bibliographic record
Abstract
Predators play a critical role in regulating the structure and function of ecosystems by exhibiting top-down forces on lower trophic levels. Despite their important contributions in maintaining ecosystem health, lethal predator control remains a global wildlife management strategy to reduce predation on livestock, culturally and/or economically important species, and species at risk, as well as to reduce conflict with humans. Predator control has received criticism due in part to a paucity of rigorous research on the community-level impacts of this practice, beyond the target prey species. Specifically, there is a lack of understanding of the behavioural consequences of predator control on the wider ecological community. In this thesis, I used a multi-year camera trap dataset to evaluate how government-mandated grey wolf (Canis lupus) population reduction to conserve boreal woodland caribou (Rangifer tarandus caribou) could impact the resource selection of the carnivore community in northeast Alberta, Canada. In my second chapter, I investigated whether perceived persecution risk due to predator control may alter wolf habitat selection. I found that wolves switched from positively associating with roads before predator control to avoiding anthropogenic linear features and selecting for block features after predator control. These results suggest that lethal control may prompt wolves to prioritize local prey acquisition near block features over movement on linear features. In my third chapter, I examined whether coyote, lynx, and black bear exhibited shifts in co-occurrence with habitat features, competitors, and prey consistent with a release from top-down suppression in response to predator control. I found that predator control triggered unexpected behavioural changes among coyote and lynx consistent with a release from top-down suppression, but not among black bears. Non-apex predator response to predator control may depend on the strength of competition between the apex and non-apex predator, emphasizing the need to consider bottom-up processes when trying to understand the indirect effects of predator control. This research demonstrates that predator control can have trickle-down effects within the larger ecological community, specifically affecting how species utilize resources. As predator control continues to be a recommended wildlife management strategy, it is imperative to continue investigating its unintended consequences throughout the ecological community.
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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 | 0.000 |
| 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".