Bats on a Budget: Torpor-Assisted Migration Saves Time and Energy
Bibliographic record
Abstract
Bats and birds must balance time and energy budgets during migration. Migrating bats face similar physiological challenges to birds, but nocturnality creates special challenges for bats, such as a conflict between travelling and refueling, which many birds avoid by feeding in daylight and flying at night. As endothermic animals, bats and birds alike must expend substantial amounts of energy to maintain high body temperatures. For migratory birds refueling at stopovers, remaining euthermic during inactive periods reduces the net refuelling rate, thereby prolonging stopover duration and delaying subsequent movement. We hypothesized that bats could mitigate similar ambient-temperature dependent costs by using a torpor-assisted migration strategy. We studied silver-haired bats Lasionycteris noctivagans during autumn migration using a combination of respirometry and temperature-sensitive radiotelemetry to estimate energy costs incurred under ambient temperature conditions, and the energy that bats saved by using torpor during daytime roosting periods. All bats, regardless of sex, age, or body condition used torpor at stopover and saved up to 91% of the energy they would have expended to remain euthermic. Furthermore, bats modulated use of torpor depending on ambient temperature. By adjusting the time spent torpid, bats achieved a rate of energy expenditure independent of the ambient temperature encountered at stopover. By lowering body temperature during inactive periods, fuel stores are spared, reducing the need for refuelling. Optimal migration models consider trade-offs between time and energy. Heterothermy provides a physiological strategy that allows bats to conserve energy without paying a time penalty as they migrate. Although uncommon, some avian lineages are known to use heterothermy, and current theoretical models of migration may not be appropriate for these groups. We propose that thermoregulatory strategies should be an important consideration of future migration studies of both bats and birds.
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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 | 0.001 |
| 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".