Automated telemetry reveals age specific differences in flight duration and speed are driven by wind conditions in a migratory songbird
Bibliographic record
Abstract
BACKGROUND: Given that winds encountered on migration could theoretically double or half the energy expenditure of aerial migrants, there should be strong selection on behaviour in relation to wind conditions aloft. However, evidence suggests that juvenile songbirds are less choosy about wind conditions at departure relative to adults, potentially increasing energy expenditure during flight. To date, there has yet to be a direct comparison of flight efficiency between free-living adult and juvenile songbirds during migration in relation to wind conditions aloft, likely because of the challenges of following known aged individual songbirds during flight. We used an automated digital telemetry array to compare the flight efficiency of adult and juvenile Savannah sparrows (Passerculus sandwichensis) as they flew nearly 100 km during two successive stages of their fall migration; a departure flight from their breeding grounds out over the ocean and then a migratory flight along a coast. Using a multilevel path modelling framework, we evaluated the effects of age, flight stage, tailwind component, and crosswind component on flight duration and groundspeed. RESULTS: We found that juveniles departed under wind conditions that were less supportive relative to adults and that this resulted in juveniles taking 1.4 times longer to complete the same flight trajectories as adults. We did not find an effect of age on flight duration or groundspeed after controlling for wind conditions aloft, suggesting that both age groups were flying at similar airspeeds. We also found that groundspeeds were 1.7 times faster along the coast than over the ocean given more favourable tailwinds along the coast and because birds appeared to be climbing in altitude over the ocean, diverting some energy from horizontal to vertical movement. CONCLUSIONS: Our results provide the first evidence that adult songbirds have considerably more efficient migratory flights than juveniles, and that this efficiency is driven by the selection of more supportive tailwind conditions aloft. We suggest that the tendency for juveniles to be less choosy about wind conditions at departure relative to adults could be adaptive if the benefits of having a more flexible departure schedule exceed the time and energy savings realized during flight with more supportive winds.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".