Trade-offs Influencing the Physiological Ecology of Hibernation in Temperate-Zone Bats
Bibliographic record
Abstract
Seasonality of temperature and food availability can lead to trade-offs between the benefits of immediate reproduction and costs associated with mortality risk from starvation, inclement weather, or predation. Hibernating mammals exhibit an enormous seasonal shift in physiology and behavior and provide a useful system to examine the effect of this trade-off on key events in the annual cycle. Most of what we understand about the ecological energetics and phenology of hibernation comes from studies of rodent hibernators such as ground squirrels, chipmunks, and dormice. Temperate-zone, insectivorous bats, however, provide another useful model system to examine trade-offs influencing seasonal change within individuals. Here, I review recent studies from my laboratory on little brown bats (Myotis lucifugus) from central Canada to understand the interplay between capacity for energy storage, energy expenditure during hibernation, and the timing of key events in the annual cycle of hibernating mammals. These studies have relied on measurements of body condition to assess energetic status, biologging of skin temperature using temperature telemetry, and use of passive transponders (i.e., PIT tags) to quantify emergence timing. In general, these studies suggest that, in part due to constraints associated with flight, bats exhibit unique, or at least unusual, adaptations for extreme energy savings during winter. The results also support the optimization hypothesis that current energetic status and future energy requirements influence energy expenditure during hibernation and the timing of emergence from hibernation in spring. Taken together, this work provides insight into the influence of reproductive timing and energy availability on hibernation behavior and physiology. It also has implications for understanding responses of bat populations to anthropogenic impacts like climate change and white-nose syndrome.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".