Is physiological stress state reflected in acoustic structure of vocalizations? An experimental test in wild North American red squirrels
Bibliographic record
Abstract
Abstract Acoustic signaling is an important means by which animals communicate both stable and labile characteristics. Although it is widely appreciated that vocalizations can convey information on labile state, such as fear and aggression, very few studies have experimentally examined the acoustic expression of short-term stress state. The transmission of such information about physiological state could have broad implications, potentially allowing other individuals to modify their behavior or life history traits in response to this public information. North American red squirrels ( Tamiasciurus hudsonicus ) produce vocalizations known as rattles that advertise territorial ownership. We examined the influence of changes in physiological stress state on rattle acoustic structure through the application of a stressor (trapping and handling the squirrels) and by provisioning squirrels with exogenous glucocorticoids (GCs). We characterized the acoustic structure of rattles emitted by these squirrels by measuring rattle duration, mean frequency, and entropy. Our results provide mixed evidence that rattles show a “stress signature”. When squirrels were trapped and handled, they produced rattles that were longer in duration with a higher frequency and increased entropy. However, squirrels that were administered exogenous GCs had similar rattle duration, frequency, and entropy as squirrels that received control treatments and unmanipulated (unfed) squirrels. Our results indicate that short-term stress does affect the acoustic structure of vocalizations, but elevated circulating GC levels are not solely responsible for such changes.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".