Mate attraction by male anurans in the presence of traffic noise
Bibliographic record
Abstract
Abstract We previously found that males of two anuran species – H yla versicolor and R ana clamitans – alter their mating calls in response to traffic noise. To test whether these alterations compensate for an effect of traffic noise on mate attraction, we (1) recorded a male calling at a quiet site; (2) played traffic noise at the same male and recorded its altered call; (3) used these recordings to attract females to a trap at sites either with or without broadcast traffic noise. The calls produced without traffic noise attracted fewer females when they were played at sites with traffic noise than when they were played at sites without noise. However, the calls of the same individuals produced with traffic noise attracted as many females at sites with noise as at sites without noise, and they attracted as many females as did the call of the same male made without noise and played at sites without noise (the ‘natural’ situation). Therefore, for these species, traffic noise does not affect mate attraction; males change their calls to compensate for a potential effect of traffic noise on mate attraction. A third species – B ufo americanus – does not alter its call in response to traffic noise, and its call made in the absence or presence of traffic noise was equally able to attract females in the absence or presence of traffic noise, indicating that traffic noise does not negatively affect mate attraction. Therefore, it appears that traffic noise does not negatively affect mate attraction in these three species of anurans. We suggest that, if our results apply to anurans in general, the previously documented negative effects of roads on anuran populations are likely caused mainly by road mortality. If this is true, road mitigation for anurans should focus mainly on reducing this mortality.
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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 | 0.001 | 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".