More than just refuelling: lengthy stopover and selection of departure weather by sandpipers prior to transoceanic and transcontinental flights
Bibliographic record
Abstract
The evolutionary and behavioural ecology of migratory birds has received much theoretical and empirical attention. We contribute to this field by contrasting the weather at departure and stopover durations of a long‐distance migratory sandpiper prior to initiating lengthy transoceanic vs. transcontinental flights of potentially variable duration. Transoceanic flights provide few if any stopover options. We predicted that transoceanic migrants should therefore be more selective of energetically favourable weather at departure and have longer stopover durations prior to departing, using time as a surrogate for cumulative fuel acquisition, compared with transcontinental migrants. We used recent advances in capture–recapture modelling to quantify how weather conditions, length of stay, including estimated residence time prior to capture, and age class correlated with daily departure probabilities of Semipalmated Sandpipers Calidris pusilla at a coastal and an inland stopover site at comparable latitude. As expected, departure probabilities from both sites were higher with increasing strength of tailwinds, and the strength of this effect was larger for birds facing transoceanic vs. transcontinental flights. Cloud cover and temperature conditions at departure converged between sites at intermediate values from different background distributions. Stopover durations at both sites were substantially longer than needed if the birds were pursuing a simple tactic of arrive–fatten–leave at the stopover site. We infer that both sites provided high levels of both food and safety relative to other stages in the birds’ annual cycle, favouring lengthy stopovers and subsequent use of lengthy flights from both sites. Our study shows that recent advances of capture–recapture models can provide additional resolution to studies of the migration strategies of birds and refine our perspective on global patterns of migration routes and stopover decisions.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".