What Can Birds Tell Us about the Migration Physiology of Bats?
Bibliographic record
Abstract
Many species of bats undergo annual migrations, in some cases covering distances of 1,000 km or more. However, very little is known about the physiological and biochemical mechanisms underlying bat migration. In contrast, the physiology of migrating birds has been studied for decades and many migration-related changes have been documented. Although bats and birds evolved flight and long-distance migration independently, they have likely experienced many similar selective pressures. We therefore suggest that knowledge of bird migration physiology can be used to generate predictions for emerging studies of bat migration physiology. In this review, we discuss major physiological and biochemical adaptations relating to fuel acquisition and fuel utilization. For each, we summarize knowledge gained from migration studies of birds and bats (if any) and make predictions of bat migration physiology. For many aspects, we predict that bats will have evolved similar physiological mechanisms to birds. However, there are some potentially major differences in the energetic models for bats and birds, including torpor, fuel selection at high-intensity exercise, and trade-offs between reproduction and migration.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.003 | 0.007 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".