Data from: Ecology of fear alters behaviour of grizzly bears exposed to bear-viewing ecotourism
Bibliographic record
Abstract
Humans are perceived as predators by many species and may generate landscapes of fear, influencing the spatiotemporal activity of wildlife. Additionally, wildlife might seek out human activity when faced with predation risks (human shield hypothesis). We used the Anthropause, a decrease in human activity resulting from the COVID-19 pandemic, to test the ecology of fear and human shield hypotheses and quantify the effects of bear-viewing ecotourism on grizzly bear (Ursus arctos) activity. We deployed camera traps in the Khutze watershed in Kitasoo Xai’xais Territory in the absence of humans in 2020 and with experimental treatments of variable human activity when ecotourism resumed in 2021. Daily bear detection rates decreased with more people present and increased with days since people were present. Human activity was also associated with more bear detections at forested sheltered sites, and less at exposed sites, likely due to the influence of habitat on bear perception of safety. The number of people negatively influenced adult male detection rates, but we found no influence on females with young detections, providing no evidence that females responded behaviourally to a human shield effect from reduced male activity. We also observed apparent trade-offs of risk avoidance and foraging. When salmon levels were moderate to high, detected bears were more likely to be females with young than adult males on days with more people present. Should managers want to minimize human impacts on bear activity and maintain baseline age-sex class composition at ecotourism sites, multi-day closures and daily occupancy limits may be effective. More broadly, this work revealed that antipredator responses can vary with the intensity of risk cues, habitat structure, and forage trade-offs, as well as manifest as the altered age-sex class composition of individuals using human-influenced areas, highlighting that wildlife avoids people across multiple spatiotemporal scales.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.009 | 0.010 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.016 | 0.087 |
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; both teacher heads agree on what is shown here.
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".