Northern Saw-whet Owl: regional patterns for fall migration and demographics revealed by banding data
Bibliographic record
Abstract
We describe attributes of Northern Saw-whet Owls (Aegolius acadicus) during fall migration using 167,774 records from the U.S. Bird Banding Laboratory for central and eastern North America from 1929–2010. We describe movement among 18 geographic regions using records of 1,444 birds captured and recaptured between 1 September and 31 December of the same year. These data show little exchange between western Lake Superior and eastern North America. The direction of movement within a region was strongly influenced by large water bodies, varied greatly among regions, and showed high dispersal in the absence of shorelines of large water bodies. We used recent banding data to analyze population demographics from northwestern Minnesota to the coast of Maine in the north, and from southern Minnesota and southern Wisconsin to southern Appalachia and the mid-Atlantic coastal region in eastern United States. The weighted mean proportion of Hatch Year (HY) birds declined significantly from 63% in northwestern Minnesota to 42% in southern Minnesota/southern Wisconsin and from 70% in northern Ontario to 48% in southern Appalachia. Annual variation in the proportion of HY birds showed little correlation between eastern and central origin sites but moderate correlation within each of these regions. We define irruptions as years when the proportion of HY birds is 15% or greater than the weighted mean for each site, a level that occurs once in 4 years on average but at irregular intervals. We determined a very high correlation between the proportion of HY birds banded in northeast of Lake Ontario and the abundance of small mammals, suggesting a close relationship between food supply and reproductive success.
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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 | 0.001 |
| 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".