Prey metabolic responses to predators depend on predator hunting mode and prey antipredator defenses
Bibliographic record
Abstract
Predation risk causes prey to react in numerous ways, from life history changes to shifts in habitat. These responses give some insight into how different types of predators affect prey, but prey responses are often not comparable across taxa and experimental systems. Metabolism is a ubiquitous trait among living organisms, which offers a way to examine predator effects and create generalizable outcomes. We examined metabolic responses of terrestrial and aquatic prey from three antipredator functional groups under varied contexts of predator cues. We found that constitutively defended prey did not exhibit metabolic responses to any type of predator cues, while deimatic and freeze‐flight prey exhibited metabolic responses that were dependent on both the cue type and predator hunting mode. Consistent with previous studies on nonconsumptive effects, we also found that ambush predators elicited a metabolic response while active predators did not. We propose that future work on this topic should continue to take a metabolic approach as a unified, scalable response variable to the sensory ecology of nonconsumptive effects, while identifying additional systems that can evaluate more fully both predator hunting mode and prey antipredator defenses.
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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 | 0.000 |
| 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) | 0.001 | 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".