Negligible energetic cost of sonar jamming in a bat–moth interaction
Bibliographic record
Abstract
Energetic cost can constrain how frequently animals exhibit behaviors. The energetic cost of acoustic signaling for communication has been the subject of numerous studies; however, the cost of acoustic signaling for predator defense has not been addressed. We studied the energetic cost and efficiency of sound production for the clicks produced by the moth Bertholdia trigona (Grote, 1879) (Grote’s bertholdia) to jam the sonar of predatory bats. This moth is an excellent model species because of its extraordinary ability to produce sound—it clicks at the highest known rate of any moth, up to 4500 clicks·s–1. We measured the metabolic cost of clicking, resting, and flying from moths suspended in a respirometry chamber. Clicking was provoked by playing back an echolocation attack sequence. The cost of sound production for B. trigona was low (66% of resting metabolic rate) and the acoustic efficiency, or the percentage of metabolic power that is converted into sound, was moderately high (0.30% ± 0.15%) compared with other species. We discuss mechanisms that allow B. trigona to achieve their extraordinary clicking rates and high acoustic efficiency. Clicking for jamming bat sonar incurs negligible energetic cost to moths despite being the most effective known anti-bat defense. These results have implications for both the ecology of predator–prey interactions and the evolution of jamming signals.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".