Patterns and correlates of songbird movements at an ecological barrier during autumn migration assessed using landscape‐ and regional‐scale automated radiotelemetry
Bibliographic record
Abstract
Departure decisions of songbirds at ecological barriers they encounter en route can strongly influence time, energy and survival costs of migration. To date, most field studies of departure decisions and their correlates have used indirect methods and followed migrants at a single stopover site, with limited information on what happens to individuals after they depart from the site. We used an automated radiotelemetry array extending 350 km from southwest Nova Scotia to southern Maine to study the migratory and stopover movements of Northern WaterthrushesParkesia noveboracensis, Red‐eyed VireosVireo olivaceusand Yellow‐rumped WarblersSetophaga coronatain relation to fuel load and weather at the northeastern edge of the Gulf of Maine. From the 105 radio‐transmitters we deployed in southwest Nova Scotia, we recorded 42 landscape‐scale stopover flights and 47 migratory flights by 75 individuals. Of the migratory flights, 57% were orientated southwest, a trajectory that, if held, would require individuals to complete a 350–440 km overwater flight. The remaining 43% of migratory flights were orientated northwest, away from the Gulf of Maine, and 15 individuals were confirmed to have detoured around all or a portion of the barrier, as evidenced by their being re‐detected over the Bay of Fundy and/or along the coast of Maine between 4 h and 15 days later. Across all individuals, initial fat score had a positive effect on departure probability, especially for individuals that made stopover flights. Among weather variables, tailwind assistance was the best predictor of migratory departures but did not appear to be the main factor determining whether individuals orientated towards or away from the Gulf of Maine. Weather had little effect on departure decisions of individuals that made stopover flights. These differences in the correlates of migratory departures and stopover flights would probably not have been distinguishable had our study been restricted to a local scale. Therefore, our findings highlight the importance of expanding the scale at which departure decisions and the ecology of stopover in general are studied.
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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 | 0.001 | 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 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".