Geographic variation in incubation behavior of a widely distributed passerine bird
Bibliographic record
Abstract
Incubating birds must trade-off leaving the nest to forage with staying on the nest to maintain optimal temperatures for developing embryos. This trade-off is expressed through incubation behavior, which can be heavily influenced by climate, food availability, attentiveness of their mates, and nest predation risk. Comparative studies across species have shown that incubation behavior varies across latitude, but few studies have explored how incubation behavior varies across sites within species. We might expect incubation behavior to be flexible and respond to local environmental challenges; alternatively, behavior may be relatively fixed and vary little across a species' range. We explored four incubation behaviors (male feeding rate, female off-bout duration, female off-bout frequency, and the proportion of time incubating females spent on the nest) in a widespread songbird, the yellow warbler (Setophaga petechia), breeding at a temperate and subarctic site. As temperatures warmed at both sites, males fed females less often, and as male feeding rates decreased, off-bout durations and frequencies increased causing the proportion of time on the nest to decrease. While incubation behaviors changed in similar ways between sites, off-bout durations shortened with increasing male feeding rates most strongly at the temperate site. Overall, these results show flexibility in incubation behaviors in response to different environmental cues, which likely minimize costs associated with provisioning incubating parents and maintaining warm nest temperatures, and suggests that male feeding may be especially important for breeding in cold regions.
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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 | 0.001 | 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".