Human risk induced behavioral shifts in refuge use by elk in an agricultural matrix
Bibliographic record
Abstract
ABSTRACT Scientists increasingly acknowledge the influence that nonlethal effects of predation have on structuring wildlife‐landscape interactions. In landscapes dominated by human activities, wildlife can respond to human disturbance in a similar fashion to the risk of predation. Further, the risk allocation hypothesis suggests that individuals respond most strongly to risk when it is spatially and temporally predictable. We predict that individuals in agriculturally dominated landscapes will respond to potential risk from humans during hunting season by shifting their behavior to avoid agricultural areas during the day, instead retreating to refuge habitat. We predict that this shift to more nocturnal behavior will be strongest for elk ( Cervus elaphus ) adult female–calf pairs and will be influenced by the level of moon illumination. Using motion‐sensing cameras, we studied the response of elk moving between the Wainwright Dunes Ecological Reserve (a hunting refuge) and surrounding agriculturally dominated landscape in east‐central Alberta, Canada, to human disturbance in relation to sunrise and sunset. Elk became increasingly nocturnal with the onset of hunting, leaving the refuge following sunset and returning to the refuge earlier before sunrise. Further, elk became increasingly nocturnal in response to greater levels of moon illumination. Lastly, we found that adult female–calf pairs perceived greater risks associated with diurnal activity and exhibited the most nocturnal behavior relative to other demographic classes. Our results suggest that ungulate management based on traditional hunting seasons and times may be problematic as it creates strong cues for resident elk, allowing them to minimize risk by avoiding risky places at risky times in accordance with the risk allocation hypothesis. © 2017 The Wildlife Society.
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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 | 0.001 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".