Responses of tadpoles to hybrid predator odours: strong maternal signatures and the potential risk/response mismatch
Bibliographic record
Abstract
Previous studies have established that when a prey animal knows the identity of a particular predator, it can use this knowledge to make an 'educated guess' about similar novel predators. Such generalization of predator recognition may be particularly beneficial when prey are exposed to introduced and invasive species of predators or hybrids. Here, we examined generalization of predator recognition for woodfrog tadpoles exposed to novel trout predators. Tadpoles conditioned to recognize tiger trout, a hybrid derived from brown trout and brook trout, showed generalization of recognition of several unknown trout odours. Interestingly, the tadpoles showed stronger responses to odours of brown trout than brook trout. In a second experiment, we found that tadpoles trained to recognize brown trout showed stronger responses to tiger trout than those tadpoles trained to recognize brook trout. Given that tiger trout always have a brown trout mother and a brook trout father, these results suggest a strong maternal signature in trout odours. Tadpoles that were trained to recognize both brown trout and brook trout showed stronger response to novel tiger trout than those trained to recognize only brown trout or only brook trout. This is consistent with a peak shift in recognition, whereby cues that are intermediate between two known cues evoke stronger responses than either known cue. Given that our woodfrog tadpoles have no evolutionary or individual experience with trout, they have no way of knowing whether or not brook trout, brown trout or tiger trout are more dangerous. The differential intensity of responses that we observed to hybrid trout cues and each of the parental species indicates that there is a likely mismatch between risk and anti-predator response intensity. Future work needs to address the critical role of prey naivety on responses to invasive and introduced hybrid predators.
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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 | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".