Black‐capped chickadees <i>Poecile atricapillus</i> sing at higher pitches with elevated anthropogenic noise, but not with decreasing canopy cover
Bibliographic record
Abstract
Several songbird species sing at higher frequencies (i.e. higher pitch) when anthropogenic noise levels are elevated. Such frequency shifting is thought to be an adaptation to prevent masking of bird song by anthropogenic noise. However, no study of this phenomenon has examined how vegetative differences between noisy and quiet sites influence frequency shifting. Variation in vegetative structure is important because the acoustic adaptation hypothesis predicts that birds in more open areas should also sing at higher frequencies. Thus, vegetative structure may partially explain the observation of higher frequency songs in areas with high levels of anthropogenic noise. To distinguish between frequency shifting due to noise or vegetative structure we recorded the songs of black‐capped chickadees Poecile atricapillus vocalizing in high and low noise sites with open and closed canopy forests. Consistent with the noise‐dependent frequency hypothesis, black‐capped chickadees sang at higher frequencies in high noise sites than in low noise sites. In contrast, birds did not sing at higher frequencies in sites with more open canopies. These results suggest that frequency shifting in chickadees is more strongly related to ambient noise levels than to vegetative structure. A second frequency measure, inter‐note ratio, was reduced at higher levels of canopy cover. We speculate that this may be due to a non‐random distribution of dominant males. In sum, our results support the hypothesis that some birds sing at higher frequencies to avoid overlap with anthropogenic noise, but suggest that vegetative structure may play a role in the modification of other song traits.
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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 | 0.000 |
| 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) | 0.002 | 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".