Food availability and long‐term predation risk interactively affect antipredator response
Bibliographic record
Abstract
Food availability and temporal variation in predation risk are both important determinants of the magnitude of antipredator responses, but their effects have rarely been examined simultaneously, particularly in wild prey. Here, we determine how food availability and long-term predation risk affect antipredator responses to acute predation risk by monitoring the foraging response of free-ranging snowshoe hares (Lepus americanus) to an encounter with a Canada lynx (Lynx canadensis) in Yukon, Canada, over four winters (2015-2016 to 2018-2019). We examined how this response was influenced by natural variation in long-term predation risk (2-month mortality rate of hares) while providing some individuals with supplemental food. On average, snowshoe hares reduced foraging time up to 10 h after coming into close proximity (≤75 m) with lynx, and reduced foraging time an average of 15.28 ± 7.08 min per lynx encounter. Hares tended to respond more strongly when the distance to lynx was shorter. More importantly, the magnitude of hares' antipredator response to a lynx encounter was affected by the interaction between food-supplementation and long-term predation risk. Food-supplemented hares reduced foraging time more than control hares after a lynx encounter under low long-term risk, but decreased the magnitude of the response as long-term risk increased. In contrast, control hares increased the magnitude of their response as long-term risk increased. Our findings show that food availability and long-term predation risk interactively drive the magnitude of reactive antipredator response to acute predation risk. Determining the factors driving the magnitude of antipredator responses would contribute to a better understanding of the indirect effects of predators on prey populations.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| 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) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".