Energetics of migratory bats during stopover: a test of the torpor-assisted migration hypothesis
Bibliographic record
Abstract
The torpor-assisted migration hypothesis posits that migration is facilitated in bats by the use of torpor during stopover roosting periods, and predicts that at stopover bats regulate time in torpor facultatively so that daily energy expenditure is independent of ambient roosting temperature. Energy savings can thus be directed to migratory movement. However, direct measurements of total roosting energy expenditure in relation to ambient and body temperature are lacking. We captured migratory silver-haired bats (Lasionycteris noctivagans; ∼11g) at Long Point, Ontario, Canada in spring and fall 2016. We used quantitative magnetic resonance analysis to measure body composition change and energy expenditure over a twelve-hour roosting period in a ventilated incubator at 10, 17 and 25°C. We assessed the effects of season, body mass, sex and age on energy expenditure. We found that daily energy expenditure was independent of roosting temperature, and that this was achieved by flexible use of torpor. Variation in body mass at capture was driven mainly by differences in fat, and the amount of body fat was negatively related to torpor use, particularly in spring. Season, sex and age also affected torpor use and energy expenditure, notably with pregnant females being generally fatter and using less torpor than males in spring. We estimate that stopover contributes only 15-20% to the total energy costs of migration in bats compared to 70% or more in typical birds. This study provides support for the torpor-assisted migration hypothesis, and furthers our understanding of the energy budgets of migratory bats.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 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".