Lunar synchrony, geography, and individual clocks shape autumn migration timing in an avian migrant
Bibliographic record
Abstract
Abstract Timing programs in animal migrants have been selected to synchronize movements that coincide with predictable resources on the breeding and nonbreeding grounds. Migrants face potential temporal conflicts if their migration schedules benefit from synchrony to conflicting rhythms associated with annual biogeographical (circannual) cues, lunar (circalunar) cues, or individually repeatable internal clocks. We repeat-tracked individuals of an avian lunaphilic species, Eastern Whip-poor-will (Antrostomus vociferus), for two to three successive autumn migrations to determine the influence of the lunar cycle, breeding location, and individual repeatability on migration timing. Almost all birds avoided departing for migration during a full moon, likely to take advantage of the bright moonlight to facilitate visual foraging and enhance pre-migration fattening. However, groups from two latitudinally distant sampling areas adjusted their autumn departure timing differently relative to the timing of the September full moon, presumably due to differences in seasonal prey availability. Individual repeatability increased throughout autumn migration, suggesting that the factors responsible for shaping migration timing may differ for different migration stages. Our results, that lunar synchrony, local climate, and individual internal clocks appeared to account for much of the variation in migration timing in whip-poor-wills, underscore the value of measuring potentially interacting factors that shape migratory behavior at species, group, and individual levels. It remains unclear if, or how, maintaining individually repeatable annual migration schedules provides an adaptive benefit for whip-poor-wills or other lunaphilic migrants. Further clarifying the reasons for phenotypic variation in whip-poor-will migration timing will improve predictions of their abilities to adjust migratory movements under changing environmental conditions.
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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 | 0.001 |
| 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".