Drinking and Flying: Does Alcohol Consumption Affect the Flight and Echolocation Performance of Phyllostomid Bats?
Bibliographic record
Abstract
BACKGROUND: In the wild, frugivorous and nectarivorous bats often eat fermenting fruits and nectar, and thus may consume levels of ethanol that could induce inebriation. To understand if consumption of ethanol by bats alters their access to food and general survival requires examination of behavioural responses to its ingestion, as well as assessment of interspecific variation in those responses. We predicted that bats fed ethanol would show impaired flight and echolocation behaviour compared to bats fed control sugar water, and that there would be behavioural differences among species. METHODOLOGY/PRINCIPAL FINDINGS: We fed wild caught Artibeus jamaicensis, A. lituratus, A. phaeotis, Carollia sowelli, Glossophaga soricina, and Sturnira lilium (Chiroptera, Phyllostomidae) sugar water (44 g of table sugar in 500 ml of water) or sugar water with ethanol before challenging them to fly through an obstacle course while we simultaneously recorded their echolocation calls. We used bat saliva, a non-invasive proxy, to measure blood ethanol concentrations ranging from 0 to >0.3% immediately before flight trials. Flight performance and echolocation behaviour were not significantly affected by consumption of ethanol, but species differed in their blood alcohol concentrations after consuming it. CONCLUSIONS/SIGNIFICANCE: The bats we studied display a tolerance for ethanol that could have ramifications for the adaptive radiation of frugivorous and nectarivorous bats by allowing them to use ephemeral food resources over a wide span of time. By sampling across phyllostomid genera, we show that patterns of apparent ethanol tolerance in New World bats are broad, and thus may have been an important early step in the evolution of frugivory and nectarivory in these animals.
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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".