Earlier and slower or later and faster: Spring migration pace linked to departure time in a Neotropical migrant songbird
Bibliographic record
Abstract
Abstract Migratory birds travel vast distances and the timing of migratory flights can affect survival and the ability to reproduce. For Neotropical migrant songbirds, early spring departure from wintering sites, early arrival to the breeding grounds and higher reproductive success have been related to the use of suitable habitats and environmental conditions during the non‐breeding season. However, how migratory strategies are shaped by winter habitat choice is largely unknown due to the general inability to track birds from specific wintering habitats to stopovers or breeding destinations. We assessed how winter habitat (native forest vs. shade‐grown coffee plantations) relates to spring departure date and migration pace in Swainson's Thrush Catharus ustulatus . We also determined the effect of departure date and total migration duration on the arrival date of birds detected near or within their breeding range. We used a novel application of Motus radiotelemetry arrays to track individuals from their wintering grounds in the Andes of South America along their migratory journey to North America. We found variation in migratory strategies between habitats, with birds wintering in native forest departing later than birds in coffee. We present isotopic evidence for native forest being of higher quality than shade‐coffee for Swainson's Thrush and hypothesize that moister conditions in forest, as shown by stable isotope (δ 13 C) analysis of thrush whole blood, provides favourable pre‐migratory conditions allowing birds to delay departure from wintering grounds. Habitat, between‐site and ‐year variation in departure date, suggests that birds made facultative adjustments to winter habitat quality and environmental conditions. Independent of habitat, birds that departed later migrated faster and this pattern was maintained along the migration route ( n = 44). Migrating earlier and slower or later and faster was unlikely to result in significant differences in arrival time to breeding destinations. Our findings reveal underappreciated complexity in migratory decisions by long‐distance migrants that contrast with the current paradigm of earlier departures and arrival from optimal habitats. The next step is to understand the relative fitness benefits of early versus late schedules or whether each strategy is an equally good response to experienced conditions.
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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) | 0.001 | 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 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".