Varying behavioral responses of wildlife to motorcycle traffic
Bibliographic record
Abstract
Roads are a pervasive feature across the U.S., and traffic and its associated noise has significant impacts on wildlife. However, we know little about the effect of motorcycle traffic and the potential for prolonged response of animals to loud and periodic traffic disturbances. We studied the behavioral response of multiple species in Devils Tower National Monument to the Sturgis Motorcycle Rally, which raised median A-weighted sound levels by more than 20 dB for 7 days. Different taxa demonstrated different responses to the event, which we categorized into three different patterns of behavioral shifts: weak evidence of a response, temporary response during the rally, and a sustained response that lasted after the rally. We found little evidence that western wood-pewee (Contopus sordidulus) vocal activity, our behavioral metric, was affected by the rally. Activity patterns of white-tailed deer (Odocoileus virginianus) and black-tailed prairie dogs (Cynomys ludovicianus) shifted during the rally, and deer reverted to pre-rally activity patterns when motorcycle activity declined. The diversity of bat species active was also lower during the rally, and the diversity of species active remained low several weeks after the rally. Our observations suggest that most species shifted their behavior to avoid motorcycle traffic but the ability to return to pre-disturbance behavioral patterns varied. Examining responses to traffic activity and noise across a broad array of species can identify relative sensitivity to such disturbances and infer community-level impacts, helping to inform strategies to reduce effects or plan for recovery.
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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 | 0.001 | 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".