The influence of natural and artificial light on the migratory patterns of an obligate nocturnal bird
Bibliographic record
Abstract
Nearly all organisms evolved with natural light-dark rhythms, making light a key sensory cue for regulating behaviour. Seasonal and daily variation in light-dark rhythms provide timing cues for long-distance avian migrants, and nocturnal migrants also require natural light at night to navigate visually during migration. Natural light cues have been disrupted by the rapid growth of artificial light within the migratory landscape, affecting the timing and movements of many nocturnally migrating birds. Research has focussed on diurnal species that migrate at night, leaving open questions about how obligate nocturnal bird species, which are highly sensitive to light, respond to variation in light at night during migration. I used an obligate nocturnal bird, the Eastern Whip-poor-will (Antrostomus vociferous), to explore how natural daylight, the lunar cycle, and artificial light influence migration movements in a nocturnal species. I GPS-tracked Whip-poor-wills during their fall migrations between Canada and Central America to generate the highest resolution migration data yet for this species. I found that Whip-poor-will migration timing followed natural light-dark rhythms, which implies potential limitations to flexibility in migration timing. Daily flights were restricted to dark hours, contradicting theory about optimal time management that has generally been supported by evidence from diurnal species. Whip-poor-wills synchronized their fall departures around the full moon, supporting the hypothesis that full-moon foraging facilitates fuel deposition in preparation for migration. Birds from different breeding locations appeared to adjust migration timing differently in anticipation of a late-season full moon, although individuals maintained remarkably repeatable departure dates across years. I also found some of the first evidence for artificial light avoidance in migrating birds: Whip-poor-wills avoided brightly lit urban areas during migratory flights, and especially during stopovers. Finally, I demonstrated that Whip-poor-wills undergo a leap-frog migration to maintain migratory connectivity. This result can inform tailored conservation plans for specific groups of birds that encounter different threats, such as artificial light, between their breeding and non-breeding grounds. Overall, my research resolved some of the mystery around this understudied, at-risk species, and provided a foundation for more nuanced hypotheses about the endogenous and environmental light cues that control nocturnal species’ migration movements.
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 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 | 0.001 |
| Scholarly communication | 0.001 | 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 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".