Data from: Age-related prenatal maternal effects and postnatal breeding experience have different influences on nestling development in an altricial passerine
Bibliographic record
Abstract
Reproductive success and nestling performance are related to the age of parents across several vertebrate taxa. However, because breeding experience and prenatal maternal investment in reproduction often covary, the source of these age-related differences can be difficult to determine. In this study, we evaluated the influence of prenatal maternal effects and postnatal breeding experience on the performance of nestling tree swallows Tachycineta bicolor by conducting a carefully controlled partial cross-fostering experiment. We swapped half-broods of nestlings between the nest of a young first-time breeding female and the nest of a female known to have previously raised and fledged young. Our manipulation did not influence the within-brood nestling hierarchies, and controlled for the effects of egg laying order. We found that nestlings of older females were heavier just prior to fledging regardless of the breeding experience of the attending female. In addition, fledglings raised by experienced females grew their flight feathers faster, and had greater probability of fledging. Our study demonstrates that prenatal investment in reproduction by older females can have long-term consequences on nestling mass, and suggests limited potential for compensatory mass gains prior to fledging. Because our analyses controlled for feeding rates, our results also suggest that foraging quantity and quality are not the only benefits nestlings gain by being raised by an experienced female.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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) | 0.008 | 0.001 |
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".