The energetics of social signaling during roost location in Spix’s disc-winged bats
Bibliographic record
Abstract
Abstract Long-term social aggregations are maintained by multiple mechanisms, including the use of acoustic signals, which may nonetheless entail significant energetic costs. To date, however, no studies have gauged whether there are significant energetic costs to social call production in bats, which heavily rely on acoustic communication for a diversity of social tasks. We measure energetic expenditure during acoustic signaling in Spix’s disc-winged bats ( Thyroptera tricolor ), a species that commonly uses contact calls to locate the ephemeral furled leaves that they use for roosting. To determine the cost of sound production, we measured oxygen consumption using intermittent-flow respirometry methods, with and without social signaling. Our results show that the emission of contact calls significantly increases oxygen consumption; vocal individuals spent, on average, 12.42 kJ more during social signaling trials than they spent during silent trials. Furthermore, production of contact calls during longer periods increased oxygen consumption for males but not for females. We also found that as resting metabolic rates increased in males, there was a decreasing probability that they would emit response calls. These results provide support to the “allocation model”, which predicts that only individuals with lower self-maintenance costs can afford to spend energy in additional activities. Our results provide a step forward in our understanding of how physiology modulates behavior, specifically how the costs of call production and resting metabolic rates may explain the differences in vocal behavior among individuals. Summary Statement Spix’s disc-winged bats constantly produce contact calls while searching for roosts, which we show significantly increases an individual’s metabolic rate.
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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".