Influence of anthropogenic features and traffic disturbance on burrowing owl diurnal roosting behavior
Bibliographic record
Abstract
Birds that forage nocturnally should select daytime roosts that minimize predation risk to themselves, maximize their ability to warn mates or young about predators, and reduce their exposure to inclement weather. The objective of this study was to identify landscape features used by burrowing owls Athene cunicularia hypugaea during the day and to determine if traffic disturbance altered patterns of daytime space use. We tracked 17 adult male owls for 0.6 to 2.8 d each with GPS dataloggers and used resource utilization and resource selection functions to examine the response of each owl to nest burrows, perches, and roads. Selection for roads decreased as average vehicle speed increased. Roads with vehicle speeds > 80 km h -1 were avoided. Owls may avoid roads with high traffic speeds because auditory disturbance from passing vehicles interferes with their ability to communicate the presence of predators to their mates and young. Owls also spent more time near fences and posts, likely because these elevated perches are good vantage points for predator detection. Perches near burrowing owl nests should be maintained, and speed limits on roads near burrowing owl nests should be set to < 80 km h -1 to help ensure owls are able to effectively detect and react to predators.
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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 | 0.000 |
| 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".