Experimental temperature manipulations alter songbird autumnal nocturnal migratory restlessness
Bibliographic record
Abstract
Abstract Migrating birds may respond to a variety of environmental cues in order to time migration. During the migration season nocturnally migrating songbirds may migrate or stop-over at their current location, and when migrating they may vary the rate or distance of migration on any given night. It has long been known that a variety of weather-related factors including wind speed and direction, and temperature, are correlated with migration in free-living birds, however these variables are often correlated with each other. In this study we experimentally manipulated temperature to determine if it would directly modulate nocturnal migratory restlessness in songbirds. We experimentally manipulated temperature between 4, 14, and 24°C and monitored nocturnal migratory restlessness during autumn in white-throated sparrows (Zonotrichia albicollis). White-throated sparrows are relatively shortdistance migrants with a prolonged autumnal migration, and we thus predicted they might be sensitive to weatherrelated cues when deciding whether to migrate or stopover. At warm temperatures (24°C) none of the birds exhibited migratory restlessness. The probability of exhibiting migratory restlessness, and the intensity of this restlessness (number of infra-red beam breaks) increased at cooler (14°C, 4°C) temperatures. These data support the hypothesis that one of the many factors that birds use when making behavioural decisions during migration is temperature, and that birds can respond to temperature directly independently of other weather-related cues.
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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 | 0.000 |
| 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 | 0.001 |
| 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".