Anthropogenic noise affects song structure in red-winged blackbirds (<i>Agelaius phoeniceus</i>)
Bibliographic record
Abstract
Anthropogenic noise can mask animal signals that are crucial for communicating information about food, predators and mating opportunities. In response to noise masking, signallers can potentially improve acoustic signal transmission by adjusting the timing, frequency or amplitude of their signals. These changes can be a short-term modification in response to transient noise or a long-term modification in response to chronic noise. An animal's ability to adapt to anthropogenic noise can be crucial to its success. In this study, we evaluated the effects of anthropogenic noise on the structure of red-winged blackbird song. First, we manipulated the presence of anthropogenic noise by experimentally broadcasting either silence or low-frequency white noise to subjects inhabiting quiet marshes located away from roadsides. Subjects exhibited increased signal tonality when temporarily exposed to low-frequency white noise, suggesting that red-winged blackbirds can alter their signals rapidly in response to sudden noise. Second, we compared songs produced in quiet marshes located away from roadsides with songs produced during quiet periods at roadside marshes that are normally noisy. This allowed us to test whether birds that are exposed to chronic anthropogenic noise exhibit altered song structure during temporarily quiet periods. Subjects residing in roadside marshes that are normally polluted with anthropogenic noise sang songs with increased tonality during quiet periods. Overall, our results show that anthropogenic noise influences the structure of birdsong. These effects should be considered in conservation and wildlife management.
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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) | 0.001 | 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".