Insights on the effect of aircraft traffic on avian vocal activity
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Aircraft noise is pervasive across the USA, including in national parks, but its effects on wildlife remain unresolved. As with other noise sources, aircraft noise may affect species physiology and behaviour by being perceived as a threat, distracting individuals, or degrading the sensory environment. This study aimed to understand the effect of aircraft traffic and associated noise on the richness of bird vocalization activity in a remote national park in the USA. We used a continent‐wide acoustic dataset encompassing over 30:00 h of annotated recordings to identify two geographically similar sites with high rates of bird vocalizations and both high and low rates of aircraft noise. We selected sites in Denali National Park, both of which experience little human presence, and quantified the richness of bird vocalizations before, during and after aircraft events. We present evidence of a community‐level behavioural response to aircraft noise, with increased bird vocalization richness after aircraft events at a site with relatively lower aircraft noise. At the site with low rates of aircraft noise, we found bird vocalization richness did not significantly change during an aircraft event but did increase after an aircraft event. At the site with high rates of aircraft noise, bird vocalization richness did not significantly change during or after an aircraft event. This study provides new insights into wildlife responses to aircraft traffic and associated noise and highlights the importance of noise research in the management of relatively quiet and undisturbed landscapes.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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) | 0.000 | 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 it