Raising young with limited resources: supplementation improves body condition and advances fledging of Canada Jays
Bibliographic record
Abstract
Food availability early in life can play a vital role in an individual's development and success, but experimental evidence for the direct effects of food on body condition, physiology, and survival of young animals in the wild is still relatively scarce. Food-caching Canada Jays (Perisoreus canadensis) begin breeding in the late winter and, therefore, rely on either cached food or seemingly limited quantities of fresh food to feed nestlings in the early spring. Using a 2-yr food supplementation experiment conducted during the nestling period and 40 yr of observational data on food supplemented by the public, we examined whether food quantity during early life influenced the physiology, body condition, timing of fledging, and survival of young Canada Jays in Algonquin Provincial Park, Ontario, Canada. Experimental food supplementation of breeding pairs advanced the fledging date of young by 24% (5.5 d) compared to controls. In 1 yr of the experiment, nestlings raised on experimentally supplemented territories had lower feather corticosterone concentrations and were in higher body condition than controls. Across treatment and control nests, young that successfully fledged had lower concentrations of feather corticosterone and were in higher body condition than those that did not fledge. Based on 40 yr of observational data, nestling body condition was positively related to the degree of food supplementation by park visitors and nestlings in higher body condition were more likely to be observed in the population in the following fall. Our results demonstrate how food availability early in life can have important downstream consequences on metrics related to individual fitness, including first year 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 | 0.000 |
| 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".