Detoured flight direction responses along the southwest coast of Lake Erie by night-migrating birds
Bibliographic record
Abstract
Abstract Migratory birds encounter the Great Lakes while moving through eastern North America toward breeding grounds to the North, which offers a good opportunity to study variation in migratory behavior as birds face a potentially influencing topographical feature. Using passive infrared technology, we documented the direction of relatively low-flying, nocturnal, mostly passerine migration in spring along the southern coast of Lake Erie’s western basin. We examined the extent to which spring migrants flew across Lake Erie as a continuation of the inland, northeasterly broad front migratory direction, as determined by weather radar and infrared observations, or displayed a tendency to deviate to more closely follow the direction of the coastline. We found that an estimated 62% of all low-flying migrants deviated their flight directions toward the coast of Lake Erie at 2 coastal sites, Cedar Point and Ottawa, which were characterized by northwest–southeast oriented coastlines. Migrants at a third coastal location, Maumee Bay, which has a more east–west oriented coastline, did not display similarly deviated flight directions. We found that even when winds were energetically favorable for a lake crossing, many migrants still routinely displayed deviated flight directions that approached paralleling the coastline. Further, the mean flight direction at one site, Ottawa, shifted more in the direction of the coastline as the night progressed, suggesting that time of night could influence the shift to a more coastal flight direction. The data indicate that the western basin of Lake Erie acts as a salient topographical feature influencing the flight directions of nocturnal migrants. The data further suggest that birds are making active decisions while in flight, based on current environmental and physiological conditions, about whether to continue to cross Lake Erie or take a coastal detour.
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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) | 0.003 | 0.001 |
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".