Early-life experience shapes patterns of senescence in a food-caching passerine
Bibliographic record
Abstract
For many species, breeding performance increases through early adulthood followed by declines later in life. Although patterns of age-specific decline have been shown to vary between individuals, the factors that lead to this individual variation in the intensity of reproductive senescence are yet to be fully understood. We investigated whether early-life social status influenced age-related trends in the breeding performance of male Canada jays (Perisoreus canadensis), year-round residents of North America's boreal and sub-alpine forests. Shortly after young become nutritionally independent, intra-brood dominance struggles lead to one juvenile (Dominant Juvenile) remaining on the natal territory after expelling its subordinate siblings (Ejectees). First, we show via radio tracking that in our declining range-edge population Ejectees either join an unrelated pair (67%), form a breeding pair with another bird (28%) or occupy a territory alone (5%). Second, using 39 years of breeding data, we demonstrate that Ejectee males advanced laying dates and increased the annual number of nestlings until 6 years of age before declining, whereas Dominant Juvenile males advanced laying dates until 11 years and increased annual number of nestlings until 12 years of age before declining. This study documents clear variation in ageing patterns between dominant and expelled young, with implications for the role of early-life experiences and phenotypic quality in determining patterns of ageing.
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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".