Acoustic monitoring of migratory birds over western Lake Erie: avian responses to barriers and the importance of islands
Bibliographic record
Abstract
Understanding the flight patterns of migrating birds is critical for informing conservation actions and management decisions. We studied the geographic and temporal distribution of birds migrating through the southern Great Lakes using nocturnal acoustic monitoring data and banding records from sites on Pelee Island in Lake Erie and on the mainland along the north shore of Lake Erie. Given that Lake Erie may represent an ecological barrier to migratory birds, we predicted that mainland and island sites would show different patterns in both the number of passage migrants and the timing of their migration. Analysis of over 60,000 flight calls from 6200 h of recordings revealed significantly more migrants over the island than the mainland in both spring and fall 2012. The acoustic data provide evidence that none of the species or species groups examined avoided crossing the lake. Birds were detected significantly earlier on Pelee Island than on the north shore of Lake Erie in spring, although they were not detected earlier on the mainland in fall. These results suggest that Lake Erie is not a major barrier to migration. The large number of birds detected over the island suggest that birds may concentrate their flight over islands in the middle of the lake, although recordings of migrants over open water will be required to support this suggestion. Our results show that Pelee Island is an important part of the migratory route of North American birds and provide valuable information on the movement of nocturnal migrants over the Great Lakes.
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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) | 0.000 | 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 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".