Maternal body condition influences magnitude of anti-predator response in offspring
Bibliographic record
Abstract
Organisms exhibit plasticity in response to their environment, but there is large variation even within populations in the expression and magnitude of response. Maternal influence alters offspring survival through size advantages in growth and development. However, the relationship between maternal influence and variation in plasticity in response to predation risk is unknown. We hypothesized that variation in the magnitude of plastic responses between families is at least partly due to maternal provisioning and examined the relationship between maternal condition, egg provisioning and magnitude of plastic response to perceived predation risk (by dragonfly larvae: Aeshna spp.) in northern leopard frogs (Lithobates pipiens). Females in better body condition tended to lay more (clutch size) larger (egg diameter) eggs. Tadpoles responded to predation risk by increasing relative tail depth (morphology) and decreasing activity (behaviour). We found a positive relationship between morphological effect size and maternal condition, but no relationship between behavioural effect size and maternal condition. These novel findings suggest that limitations imposed by maternal condition can constrain phenotypic variation, ultimately influencing the capacity of populations to respond to environmental change.
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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 | 0.001 |
| 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".