Social, not genetic, programming of development and stress physiology of a colonial seabird
Bibliographic record
Abstract
Phenotypic differences often stem from genetic/maternal differences and/or early-life adaptations to local environmental conditions. In colonial animals, little is known on how variation in the social environment is embedded into individual phenotypes, nor what the consequences are on individual fitness. We conducted an experimental cross-fostering study on king penguins ( Aptenodytes patagonicus ), exchanging eggs among 134 pairs breeding in high-density (67 pairs) or low-density (67 pairs) areas of the same breeding colony. We investigated differences in parent and chick phenotypes and survival in relation to the density of their origin and foster environment. Adults breeding in colony areas of high density exhibited decreased resting behaviour and increased aggression and vigilance, increased hypometabolism during incubation fasts, and more moderate corticosterone responses shaped by exposure to chronic stressors (e.g. constant aggression by neighbours). Chick phenotypes were more influenced by the environment in which they were raised than their genetic/maternal origin. Chicks raised in high-density colonial environments showed enhanced weight gain and survival rates regardless of the density of their genetic parents’ breeding areas. Our study experimentally shows advantages to breeding in colonial areas of higher breeder densities in king penguins, and highlights the importance of social settings in shaping phenotype expression in colonial seabirds.
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 | 0.000 |
| 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) | 0.001 | 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".