Apparent survival of adult Burrowing Owls that breed in Canada is influenced by weather during migration and on their wintering grounds
Bibliographic record
Abstract
Understanding factors that influence the survival of endangered migratory species is critical for making informed management decisions, yet this understanding relies on long-term recapture datasets for species that are, by definition, rare. Using 3 geographically widespread (Saskatchewan, Alberta, and Manitoba, Canada) and long-term (6–15 yr) mark–recapture datasets, we quantified spatial and temporal variation in apparent annual survival and recapture probabilities of Burrowing Owl (Athene cunicularia), an endangered species that breeds in Canada. We then examined how large-scale weather patterns during migration (storms) and on the wintering and breeding grounds (precipitation), in addition to prey irruptions on the breeding grounds, influenced apparent survival of Burrowing Owls. Female Burrowing Owls had lower apparent survival than males in all 3 study areas. Storms during fall migration and above-average precipitation on the wintering grounds were associated with reduced apparent survival of Burrowing Owls in the longest-running study area, Saskatchewan; in Alberta and Manitoba, there were few correlations between apparent survival of Burrowing Owls and weather or prey irruptions. Increases in stochastic events such as storms during migration or precipitation on the wintering grounds could have adverse consequences on the already small Burrowing Owl population in Canada. Local management actions that focus solely on improving adult apparent survival within Canada are likely insufficient for mitigating susceptibility of adults to inclement weather or other factors outside the breeding season, underscoring the need for management of this species across multiple jurisdictions within North America.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 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".