Acoustic communication in the pine engraver bark beetle: do signals vary between behavioural contexts?
Bibliographic record
Abstract
Abstract Acoustic communication is taxonomically widespread in bark beetles and is proposed to play an important role in a variety of social and defensive behavioural contexts. Yet our understanding of how signals vary between contexts is currently limited. The present study tests the hypothesis that acoustic signals vary between behavioural contexts in the female pine engraver beetle Ips pini (Say) (Coleoptera: Curculionidae: Scolytinae). Female Ips pini produce acoustic chirps using a vertex‐pronotal stridulatory organ. Randomly sampled chirps generated under three contexts (i.e. distress, predation and premating) are compared for their duration, number of pulses, interpulse intervals, pulse rate and amplitude envelope shapes. The results obtained show that, during premating events, chirps are significantly longer in duration and tend to have a higher proportion of descending amplitude envelopes than chirps occurring during distress and predation events. Chirps produced during distress and predation conditions are indistinguishable from one another. By contrast to the results from previous bark beetle studies, no support is found for categorizing chirps as ‘interrupted’ or ‘uninterrupted’ types based on temporal patterns. The functional significance of context‐dependent variation in chirp characteristics is discussed. Previous studies on acoustic communication in bark beetles are limited as a result of a general lack of objective sampling and measurement criteria for characterizing signals. Recommendations are outlined for future studies on the functions and evolution of acoustic communication in bark beetles.
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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 | 0.001 | 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".