Predator‐induced life history changes in amphibians: egg predation induces hatching
Bibliographic record
Abstract
The timing of transitions between life history stages should be affected by factors that influence survival and growth of organisms in adjacent life history stages. In a series of laboratory experiments, we examined the influence of predation risk as a cue to trigger a life history switch in amphibians. In the Oregon Cascade Mountains, some populations of Pacific treefrogs ( Hyla regilla ) and Cascades frogs ( Rana cascadae ) are under intense egg predation by predatory leeches (families Glossiphonidae and Erpobdellidae). We document that both treefrogs and Cascades frogs show plasticity in hatching characteristics in response to the threat of egg predation. Pacific treefrogs hatch sooner and at an earlier developmental stage when either predatory leeches or non‐predatory earthworms are allowed direct contact with the developing egg mass. The same response is elicited even without direct contact. Chemical cues of predatory leeches and chemicals released from injured eggs appear to elicit the same early hatching response in treefrogs. For Cascades frogs, cues of leeches, but not those of injured eggs, elicit an early hatching response. Hatching early in response to egg predators may reduce predation. Plasticity of hatching characteristics has rarely been examined. However, we suspect that it may be common, particularly in populations or species that experience high variability in predation pressure between years.
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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) | 0.003 | 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".