Making the dead talk: alarm cue-mediated antipredator behaviour and learning are enhanced when injured conspecifics experience high predation risk
Bibliographic record
Abstract
Due to the costs of antipredator behaviour, prey have the ability to finely modulate their response according to the risk they have experienced, and adjust it over different scales of ecological time. Information on which to base their responses can be obtained from direct experience, but also indirectly from nearby conspecifics. In aquatic environments, alarm cues from injured conspecifics are an important and reliable source of information about current predation risk. We used wood frog tadpoles, Lithobates sylvaticus, to investigate whether prey responses to alarm cues match the level of background predation risk experienced by injured conspecifics. We found that tadpoles exposed to alarm cues from conspecifics raised in a high-risk environment showed a stronger antipredator response and an enhanced learned response to novel predators, when compared with tadpoles exposed to alarm cues from conspecifics raised in a low-risk environment. Alarm cues not only allow prey to cope with an ongoing predation event, but also to adjust their behaviour to match background risk in the environment.
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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) | 0.000 | 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".