Considerations of varied thermoregulatory expressions in migration theory
Bibliographic record
Abstract
Optimal migration theory has been used for three decades to generate predictions of stopover behavior and understand migration ecology. Yet, to date, there have been no attempts to understand the impacts of thermoregulation on migration theory predictions of stopover behavior. Though most migrants are homeothermic, a diverse group of migrants from bats to hummingbirds and warblers make use of some degree of heterothermy. We consider how thermoregulation influences stopover fuel deposition rates, and thus alters optimal migration theory predictions of stopover behavior using a hypothetical migratory bat as a model organism. We update the analytical models of optimal migration theory by considering scenarios of fixed metabolic rate (the current assumption of optimal migration theory) and three different mass‐specific metabolic rates including homeothermy, shallow torpor heterothermy and deep torpor heterothermy. Our results predict that heterotherms will make shorter stopovers, have a decreased departure fuel load, and reduce the overall time and energy costs associated with stopovers relative to homeotherms, highlighting that thermoregulation can drastically influence stopover behavior and ultimately play a critical role in population level patterns of 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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".