The simple ears of noctuoid moths are tuned to the calls of their sympatric bat community
Bibliographic record
Abstract
Insects with bat-detecting ears are ideal animals for investigating sensory system adaptations to predator cues. Noctuid moths have two auditory receptors (A1 and A2) sensitive to the ultrasonic echolocation calls of insectivorous bats. Larger moths are detected at greater distances by bats than smaller moths. Larger moths also have lower A1 best thresholds, allowing them to detect bats at greater distances and possibly compensating for their increased conspicuousness. Interestingly, the sound frequency at the lowest threshold is lower in larger than in smaller moths, suggesting that the relationship between threshold and size might vary across frequencies used by different bat species. Here, we demonstrate that the relationships between threshold and size in moths were only significant at some frequencies, and these frequencies differed between three locations (UK, Canada and Denmark). The relationships were more likely to be significant at call frequencies used by proportionately more bat species in the moths' specific bat community, suggesting an association between the tuning of moth ears and the cues provided by sympatric predators. Additionally, we found that the best threshold and best frequency of the less sensitive A2 receptor are also related to size, and that these relationships hold when controlling for evolutionary relationships. The slopes of best threshold versus size differ, however, such that the difference in threshold between A1 and A2 is greater for larger than for smaller moths. The shorter time from A1 to A2 excitation in smaller than in larger moths could potentially compensate for shorter absolute detection distances in smaller moths.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".