Overlapping vocalizations produce far-reaching choruses: a test of the signal enhancement hypothesis
Bibliographic record
Abstract
Many animals gather in large groups to mate. When these animals produce sexual signals, their signals may overlap. The signal enhancement hypothesis proposes that overlapping signals exhibit enhanced transmission properties, increasing the active space and potency of the signal. We tested this hypothesis using multispeaker playback to simulate a chorus of explosively breeding Neotropical Yellow Toads (Incilius luetkenii). We varied the number of simulated males and the frequency of their vocalizations and we rerecorded the choruses at different distances through this species’ native habitat in Costa Rica. Our results support the signal enhancement hypothesis: transmission distance increased with the number of simultaneous calls. Call frequency varies inversely with body size in many animals, including Yellow Toads, and our results reveal that the signal enhancement effect of overlapping calls is heightened when the calls are low in frequency (i.e., a chorus of large-bodied animals) compared to medium or high frequency (i.e., a chorus of smaller-bodied animals). Our findings represent the first experimental demonstration of chorus-level signal enhancement in the vocalizations of vertebrates.
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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 | 0.001 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".