Levels of Airborne Sound And Substrate-borne Vibration Calling Are Negatively Related Across Neotropical False-leaf Katydids
Bibliographic record
Abstract
Animals often signal in multiple sensory modalities to attract mates, but the level of signaling investment in each modality can differ dramatically between individuals and across species. When functionally overlapping signals are produced in different modalities, their relative use can be influenced by many factors, including differences in signal active space, energetic costs, and predation risk. Characterizing differences in total signal investment across time can shed light on these factors, but requires long focal recordings of signal production. Neotropical pseudophylline katydids produce mate advertisement signals as airborne sound and substrate-borne vibration. Airborne calls, produced via stridulation, are extremely short, high-frequency, and longer-range signals. Conversely, substrate-borne calls produced via abdominal tremulation are longer, low-frequency, relatively more energetically costly, and shorter-range signals. To examine patterns of stridulation and tremulation across species and test hypotheses about the drivers of signal use in each modality, we recorded multimodal signaling activity over 24 hours for males from 10 pseudophylline species from a single Panamanian community. We also collected data on demographic and morphological species characteristics, and acoustic features of airborne calls, such as bandwidth, peak frequency, and duration. Finally, we generated a molecular phylogeny for these species and used phylogenetic generalized least squares models to test for relationships between variables while controlling for evolutionary relationships. We found a negative relationship between sound and vibration calling, indicating that substrate-borne vibrational signaling may compensate for reduced airborne signaling in these species. Sound call bandwidth and the proportion of males collected at lights, a proxy for the amount of male movement, also explained a significant amount of variation in sound calling across species, indicating that the overall relationship between the two types of calling signals may be mediated by the specific characteristics of the signals as well as other species traits.
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 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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".