Transient and permanent effects of suboptimal incubation temperatures on growth, metabolic rate, immune function, and adrenocortical responses in zebra finches
Bibliographic record
Abstract
In birds, incubation temperature can vary by several degrees Celsius among nests of a given species. Parents may alter incubation temperature to cope with environmental conditions and/or to manipulate embryonic development, and such changes in incubation behavior could have long-lasting effects on offspring phenotype. To investigate short- and long-term effects of suboptimal incubation temperatures on survival and physiological functions in zebra finches, eggs were incubated at 36.2, 37.4 or 38.4 °C for the entire incubation period. The post-hatch environment was identical among the treatment groups. We found that hatching success was lowest in the 38.4 °C group, while post-hatch survival was lowest in the 36.2 °C group. Incubation temperature had sex-specific effects on offspring phenotype: incubation temperatures affected body mass (Mb) but not physiological parameters of males and conversely, the physiological parameters but not Mb of females. Specifically, males from the 38.4 °C group weighed significantly less than males from the 36.2 °C group from the nestling period to adulthood, whereas females from different incubation temperature groups did not differ in Mb. In contrast, females incubated at 36.2 °C had transient but significantly elevated basal metabolic rate and adrenocortical responses during the nestling and fledgling periods, whereas no treatment effect was observed in males. Innate immunity was not affected by incubation temperature in either sex. These results suggest that a 1 °C deviation from what is considered an optimal incubation temperature can lower offspring performance and offspring survival.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".