Influence of Spring Temperatures and Individual Traits on Reproductive Timing and Success in a Migratory Woodpecker
Bibliographic record
Abstract
We investigated the effect of spring temperatures, female age, and female body condition on the timing of laying in a migratory woodpecker, the Northern Flicker (Colaptes auratus), and looked at the relationship between laying date and reproductive success. Average annual laying dates in the population, recorded over 12 years, were not related to the North Atlantic Oscillation or the Pacific-North American climate indices but were earlier when average daily temperatures along the migration route of Northern Flickers along the Pacific coast of North America were warmer. However, the strongest negative correlation between laying dates and ambient temperatures occurred after the arrival of most birds on the breeding site, which suggests that the ability of females to accumulate resources for egg laying on the breeding site was an important determinant of laying times. At the population level, egg laying advanced by 1.15 days for every degree warmer on the breeding grounds. At the level of individuals, laying dates advanced as females aged from 1 to 3 years, and females in better body condition also laid earlier. However, there was no interaction between female age and ambient temperature, which suggests that the age classes had equal capacity to respond to environmental change. Reproductive output declined seasonally as a result of declines in clutch size and not as a result of reduced fledging success. This suggests that there is no ecological mismatch linked to prey availability for Northern Flickers and that individuals could benefit by laying earlier if spring temperatures allow.
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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) | 0.002 | 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".