Testing Predictions of Optimal Migration Theory in Migratory Bats
Bibliographic record
Abstract
Optimal migration theory is a framework used to evaluate trade-offs associated with migratory strategies. Two strategies frequently considered by migration theory are time minimizing, whereby migration is completed as quickly as possible, and energy minimizing, whereby migration is completed as energetically efficiently as possible. Despite extensive literature dedicated to generating analytical predictions about these migratory strategies, identifying appropriate study systems to empirically test predictions is difficult. Theoretical predictions that compare migratory strategies are qualitative, and empirical tests require that both time-minimizers and energy-minimizers are present in the same population; spring migrating silver-haired ( Lasionycteris noctivagans ) and hoary bats ( Lasiurus cinereus ) provide such a system. As both species mate in the fall, spring-migrating males are thought to be energy-minimizers while females benefit from early arrival to summering grounds, and are thought to be time-minimizers. Thermoregulatory expression also varies between species during spring migration, as female silver-haired bats and males of both species use torpor while female hoary bats, which implant embryos earlier, are thought to avoid torpor use which would delay pregnancy. Based on optimal migration theory, we predicted that female silver-haired bats and hoary bats would have increased fuel loads relative to males and the difference between fuel loads of male and female hoary bats would be greater than the difference between male and female silver-haired bats. We also predicted that females of both species would have a greater stopover foraging proclivity and/or assimilate nutrients at a greater rate than males. We then empirically tested our predictions using quantitative magnetic resonance to measure fuel load, δ 13 C isotope breath signature analysis to assess foraging, and 13 C–labeled glycine to provide an indicator of nutrient assimilation rate. Optimal migration theory predictions of fuel load were supported, but field observations did not support the predicted refueling mechanisms, and alternatively suggested a reliance on increased fuel loads via carry-over effects. This research is the first to validate a migration theory prediction in a system of both time and energy minimizers and uses novel methodological approaches to uncover underlying mechanisms of migratory stopover use.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 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) | 0.000 | 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".