Age composition of winter irruptive Snowy Owls in North America
Bibliographic record
Abstract
Patterns of winter irruptions in several owl species apparently follow the ‘lack of food’ hypothesis, which predicts that individuals leave their breeding grounds in search of food when prey populations do not allow breeding and are too small to ensure survival. Recent analyses, however, suggest an alternative mechanism dubbed the ‘breeding success’ hypothesis, which predicts that winter irruptions might instead be the result of a very successful breeding season, with a large pool of young birds subsequently migrating south from the breeding grounds. Here we assessed age‐class (juvenile vs. non‐juvenile) composition of winter irruptive Snowy OwlsBubo scandiacusover a 25‐year period (winter 1991–1992 to 2015–2016) between regular (North American Prairies and Great Plains) and irregular wintering areas (northeastern North America) using live‐trapped individuals and high‐resolution images of individual owls. Our results show that the proportion of juveniles (birds less than 1 year of age) varies considerably annually but is positively correlated with irruption intensity in both regions. In irregular wintering areas, it can constitute the majority (up to more than 90%) of winter irruptive Snowy Owls over a large geographical area. These results are consistent with the idea that large winter irruptions at temperate latitudes are not the result of adults massively leaving the Arctic in search of food after a breeding failure but are more likely to be a consequence of good reproductive conditions in the Arctic that create a large pool of winter migrants.
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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".