Behavioural Response of Bats to Perceived Predation Risk While Foraging
Bibliographic record
Abstract
Abstract The ability to detect and respond to predation risk while foraging may have important fitness consequences for prey organisms. Anti‐predator behaviours may reduce the probability of mortality because of predation, but they may also be associated with reduced foraging efficiency. Several behaviours of bats have been suggested to serve as anti‐predator responses, and there is evidence that predation, particularly by avian predators such as owls, may be an important cause of bat mortality. Previous studies have attempted to determine whether predator presence affects bat behaviour when emerging from roost sites, but few have examined effects of predator presence on bat behaviour while foraging. In this study, we investigated whether foraging bats respond to predator cues by presenting bats with an acoustic cue simulating the presence of an owl. Within matched trials, which were conducted at different locations each of 18 nights, significantly fewer bat detections were recorded at owl playback stations than at control stations (no auditory cue), suggesting an avoidance response by bats. An acoustic control (i.e. station playing woodpecker calls), however, did not have significantly more detections than the stations playing the owl calls, suggesting that bats may simply be avoiding noise and more detailed investigation is warranted. Although evidence for owl predation on bats is minimal in North America, results of this study may indicate that the perceived presence of owls may represent a factor influencing the behaviour of bats while foraging.
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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 | 0.000 | 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".