Predation-induced effects on hatchling morphology in the common frog (<i>Rana temporaria</i>)
Bibliographic record
Abstract
As mortality due to predation is often high at early independent life stages in many animals, it can be expected that predation-induced modifications of early life history and morphology will be common when predation risk varies spatially or temporally. However, studies of such effects are still rare. Predation-induced changes in life history and morphology have often been described in amphibian larvae, but the focus has been on older larvae and little is known about responses of hatchlings or very young larvae. We examined whether predator presence influenced timing of hatching and hatchling morphology in the common frog, Rana temporaria. In a paired design, eggs from 10 clutches were allowed to develop from fertilization to hatching, with or without the nonlethal presence of a larva of the large diving beetle Dytiscus marginalis. We found no evidence that predator presence affected timing of hatching. However, hatchlings raised in the presence of the predator had relatively shorter bodies and deeper tail fins than their full-sibs raised in the absence of the predator, indicating that predation induces morphological responses in R. temporaria hatchlings. This is one of the very few studies showing that predators, or chemical cues released during a predation event, can induce a plastic morphological changes in vertebrates at very early life stages.
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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) | 0.002 | 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".