Avoidance of roads by large herbivores and its relation to disturbance intensity
Bibliographic record
Abstract
Abstract Avoidance of roads has been demonstrated for many animal species, but little is known about the relationship between anthropogenic disturbance levels and the degree of avoidance by animals. We investigated the hypothesis that the strength of road‐avoidance behaviour increases with the intensity of the disturbance for a large, disturbance‐sensitive herbivore: the forest‐dwelling caribou R angifer tarandus caribou . We assessed the behaviour of 53 global positioning system‐collared caribou monitored during the gradual modification of a highway over a 7‐year period, while controlling for potentially confounding factors. We studied caribou movements, resource selection and distribution before, during and after road modifications at multiple scales. We expected that the degree of avoidance would be positively related to road width, traffic density and the presence of active construction sites. The proportion of individuals that excluded the highway from their home range increased as highway modifications progressed. A lower proportion of caribou locations was found in a 5000 m road‐effect zone during and after highway modifications compared with before. Within that zone, caribou avoided habitat types that were selected at the home range scale. Caribou displayed higher movement rates in the vicinity of the highway, especially when traffic density was high. Our data support the hypothesis that avoidance of roads by large herbivores is positively related to disturbance intensity. Our results shed light on the behavioural mechanisms determining avoidance of human infrastructure by large herbivores, and suggest that increased human activity may affect behaviour at multiple scales. Conservation efforts in areas where roads are constructed or modified should be directed towards maintaining access to critical habitat resources, while also restoring habitat quantity and quality.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".