Irruptive fall migrations are linked to elevated breeding abundance but are not associated with body condition or stopover duration in Northern Saw-whet Owls
Bibliographic record
Abstract
Abstract Bird species that undertake irruptive migrations are good candidates for assessing density-dependent effects on stopover ecology because the number of birds using stopover sites varies considerably from year to year. Using morphometric data from a 9-year banding program and radiotelemetry (n = 25 females), we found that increases in the annual density of Northern Saw-whet Owls (NSWO; Aegolius acadicus) encountered at a fall stopover site in Nova Scotia, Canada, were not linked to female body condition or minimum stopover duration. Rather, most NSWO spent no more than 1 or 2 full days at the stopover site following radio-tagging and during their return visits to the site. Body condition indices were highest for NSWO captured near the end of the migration monitoring season, possibly reflecting birds that had recently established wintering ranges and were elevating energy stores. We used breeding abundance indices derived from Birds Canada’s Atlantic Nocturnal Owl Survey to help test the hypothesis that irruptive fall migrations in NSWO were driven by elevated breeding productivity and dispersal of immature birds (breeding success hypothesis). Indeed, irruptive fall migrations were characterized by elevated densities of immatures, but not adults, and mean breeding abundance indices for the Maritime provinces during years with irruptive migrations were higher than those for non-irruptive years. We hypothesize that prey abundance during years with irruptive migrations was sufficient to enable high breeding densities and minimize effects of elevated fall densities of NSWO on rates of mass gain and stopover duration.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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".