Incubation behaviour of a boreal, food-caching passerine nesting in sub-zero temperatures
Bibliographic record
Abstract
Our understanding of avian incubation behaviour is primarily derived from species that nest in the temperate conditions of spring and summer. This leaves uncertainties about strategies employed by a relatively small number of species adapted to breed under sub-zero, winter-like conditions. We used in-nest temperature loggers (iButtons) to monitor incubation behaviours of Canada Jays, cache-reliant, year-round residents of boreal and sub-alpine environments that breed in the late winter/early spring and have female-only incubation. Females had high levels of daytime nest attentiveness (92 ± 3% of daytime spent on the nest; ± SD), taking an average of only 5.5 (± 0.1) off-bouts per day with a mean duration of 13.3 (± 0.2) min. per bout. Variation in nest attentiveness was primarily driven by off-bout duration, suggesting that the number of off-bouts per day may be limited to reduce nest activity around the nest and avoid attracting nest predators. In contrast to expectations, weather conditions (mean daily temperature and total daily rainfall) were not associated with variation in either the number or duration of off-bouts. Our results suggest that incubation strategies of Canada Jays are likely not shaped by prevailing weather conditions but instead by predation threat and availability of cached food, the latter of which reduces foraging opportunity costs by allowing females to reliably acquire sufficient food during the few times they leave the nest each day.
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".