Geographic variation in the use of torpor and roosting behaviour of female western long‐eared bats
Bibliographic record
Abstract
Abstract The costs and benefits of torpor may vary across the range of widespread heterothermic species, resulting in different thermoregulatory patterns and other behaviours for individuals inhabiting different environments. We compared torpor use and roosting behaviour for rock‐roosting populations of western long‐eared batsMyotis evotisliving in the mountains and prairies of Alberta, Canada. We monitored body temperatures and located roosts for pregnant and lactating females using radio‐telemetry. We also took roost measurements, and assessed roost microclimate using temperature dataloggers. Females in the mountains entered torpor less frequently and spent less time in torpor than bats in the prairies, supporting our hypothesis that reproductive time constraints in the mountains outweigh the benefits of torpor. Alternatively, increased torpor use in the prairies may be attributed to a greater need for water conservation. Females in the mountains minimized thermoregulatory costs and maintained homeothermy by selecting exposed roosts with warm microclimates during pregnancy, and then switching to clustering with other individuals during lactation when conditions were cooler. In the prairies, females roosted alone in cooler, less exposed roost types, which facilitate the use of torpor. Our results illustrate the importance of considering geographic variation in behaviour across the range of a species.
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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".