Passerines Use Nocturnal Flights for Landscape-Scale Movements during Migration Stopover
Bibliographic record
Abstract
Knowledge of stopovers made by migratory birds comes mostly from studies at relatively fine spatial scales. While this focus yields important information about processes at those scales, it ignores possible processes acting at broader spatial scales. We established an array of three automated radio-telemetry receiver towers housing ten antennas arranged to sample a landscape and its associated airspace at Lake Erie in southern Canada. We used digitally coded tags to monitor the behavior of multiple Swainson's and Hermit Thrushes (Catharus ustulatus and C. guttatus) simultaneously during fall 2008. The towers registered flight activity of 86% of the 69 radio-tagged individuals, whose flights occurred predominantly shortly after the end of evening civil twilight. We recorded 15 nocturnal flights that were not departure flights, indicating that during stopover passerines make nocturnal flights for purposes other than the continuation of migration. The flights we recorded were distributed throughout the night, and in eight cases they resulted in individuals moving many kilometers. These multiple instances of nocturnal landscape-scale movements represent an ecological process that is not detectable when the focus of sampling is too small. We suggest that in most studies of passerines' stopover ecology, researchers need to consider temporal and spatial scales more carefully.
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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".