The neuroethology of song cessation in response to gleaning bat calls in two species of katydids,<i>Neoconocephalus ensiger</i>and<i>Amblycorypha oblongifolia</i>
Bibliographic record
Abstract
We investigated whether the use of primary or secondary behavioural defences is related to prey sensory thresholds using two species of North American katydids, Neoconocephalus ensiger and Amblycorypha oblongifolia. Male katydids produce intense calling songs to attract mates, and many gleaning bat species are known to use these calls to locate them as prey. Low duty cycle calling (i.e. sporadic calls) is a primary defence against gleaning bats (prevents attacks), and song cessation is a secondary defence (enables survival of an attack), for which these two species show behavioural differences. Echolocation calls of Myotis septentrionalis, a sympatric gleaning bat species, were broadcast to singing katydids and to neural preparations of these katydids to test if differences in behavioural response were related to differences in auditory sensitivity. We measured thresholds and firing patterns of the T-cell, an auditory interneuron involved in predator detection. We hypothesized that low duty cycle calling is the best defence for species not sensitive enough to mount a secondary defence in response to predator cues; therefore, we predicted that N. ensiger (high duty cycle song) would have lower behavioural and T-cell thresholds than A. oblongifolia (low duty cycle song). Although more N. ensiger ceased singing than A. oblongifolia, the number and maximum firing rate of T-cell action potentials did not differ between species for echolocation call sequences. We suggest that the T-cell has divergent functions within the Tettigoniidae, including predator and mate detection, and the function could be context dependent in some species.
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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 | 0.000 | 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".