Early-Life Corticosterone Body Condition Influence Social Status and Survival in a Food-Caching Passerine
Bibliographic record
Abstract
Individuals undergo profound changes throughout their early life as they grow and transition between life-history stages. As a result, the conditions that individuals experience during development can have both immediate and lasting effects on their physiology, behavior, and, ultimately, fitness. In a population of Canada jays in Algonquin Provincial Park, Ontario, Canada, we characterized the diet composition and physiological profile of young jays at three key time points during development (nestling, pre-fledge, and pre-dispersal) by quantifying stable-carbon (δ13C) and -nitrogen (δ15N) isotopes and corticosterone concentrations in feathers. We then investigated the downstream effects of early-life diet composition, feather corticosterone, and environmental conditions on a juvenile's social status, body condition, and probability of being observed in the fall following hatch. Across the three time points, the diet of Canada jay young was composed primarily of vertebrate tissue and human food with the proportion of these food items increasing as the jays neared dispersal. Feather corticosterone concentrations also shifted across the three time points, decreasing from nestling to pre-dispersal. Dominant juveniles had elevated corticosterone concentrations in their feathers grown pre-dispersal compared with subordinates. High body condition as nestlings was associated with high body condition as juveniles and an increased probability of being observed in the fall. Together, our results demonstrate that nestling physiology and body condition influence the social status and body condition once individuals are independent, with potential long-term consequences on survival and fitness.
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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) | 0.001 | 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".