Individual responses to novel predation risk and the emergence of a landscape of fear
Bibliographic record
Abstract
Abstract Elucidating changes in prey behavior in response to a novel predator is key to understanding how individuals acclimate to shifting predation regimes. Such responses are predicted to vary among individuals as a function of the level of risk to which individuals are exposed, temporal changes in risk, and landscape‐mediated changes in perceived risk. We tested how GPS‐tracked moose ( Alces alces , n = 19) responded to an emerging risk landscape with the introduction of hunting to a naïve population (large‐scale reduction experiment in Gros Morne National Park, Canada). We predicted that predation risk associated with hunters would influence moose habitat selection: Avoidance responses would be stronger during the day when hunting was allowed, and moose would learn to avoid risky locations which would strengthen in successive years for survivors occupying overall riskier home ranges. We found that moose avoided areas associated with a high risk of encounters with hunters but did not alter selection patterns between day and night. We did not find evidence of moose reacting more strongly to emerging risk as a function of risk within their home range. Moose did not increase their avoidance of areas associated with hunter risk across years but over time survivors selected non‐hunted refuge areas more frequently. Our results suggest that while moose did not adjust fine‐scale habitat selection through time to increased hunting risk, they did adjust selection at broader scales (based on proportions of hunter‐free habitat included in home range relative to study area). This finding supports the hypothesis that habitat selection at larger spatio‐temporal scales may reflect behavioral responses to a population’s most important limiting factors, which may not be apparent at finer 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 | 0.000 | 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) | 0.003 | 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".