Mid-winter temperatures, not spring temperatures, predict breeding phenology in the European starling<i>Sturnus vulgaris</i>
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Bibliographic record
Abstract
In many species, empirical data suggest that temperatures less than 1 month before breeding strongly influence laying date, consistent with predictions that short lag times between cue and response are more reliable, decreasing the chance of mismatch with prey. Here we show in European starlings (Sturnus vulgaris) that mid-winter temperature ca 50-90 days before laying (8 January-22 February) strongly (r (2) = 0.89) predicts annual variation in laying date. Mid-winter temperature also correlated highly with relative clutch size: birds laid later, but laid larger clutches, in years when mid-winter temperatures were lower. Despite a high degree of breeding synchrony (mean laying date 5-13 April = ±4 days; 80% of nests laid within 4.8 days within year), European starlings show strong date-dependent variation in clutch size and productivity, but this appears to be mediated by a different temporal mechanism for integration of supplemental cue (temperature) information. We suggest the relationship between mid-winter temperature and breeding phenology might be indirect with both components correlating with a third factor: temperature-dependent development of the starling's insect (tipulid) prey. Mid-winter temperatures might set the trajectory of growth and final biomass of tipulid larvae, with this temperature cue providing starlings with information on breeding season prey availability (though exactly how remains unknown).
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it