Validity of the Prey‐Trap Hypothesis for Carnivore‐Ungulate Interactions at Wildlife‐Crossing Structures
Bibliographic record
Abstract
Wildlife-exclusion fencing and wildlife-crossing structures (e.g., underpasses and overpasses) are becoming increasingly common features of highway projects around the world. The prey-trap hypothesis posits that predators exploit crossing structures to detect and capture prey. The hypothesis predicts that predation events occur closer to a highway after the construction of fences and crossing structures and that prey species' use of crossings increases the probability that predators will attack prey. We examined interactions between ungulates and large carnivores at 28 wildlife crossing structures along 45 km of the Trans-Canada Highway in Banff National Park, Alberta. We obtained long-term records of locations where ungulates were killed (kill sites) before and after crossing structures were built. We also placed remote, motion-triggered cameras at two crossing structures to monitor predator behavior following ungulate passage through the structure. The proximity of ungulate kill sites to the highway was similar before and after construction of fencing and crossing structures. We found only five kill sites near crossing structures after more than 32,000 visits over 13 years. We found no evidence that predator behavior at crossing structures is affected by prey movement. Our results suggest that interactions between large mammals and their prey at wildlife-crossing structures in Banff National Park are not explained by the prey-trap hypothesis.
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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 | 0.000 | 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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".