Rapid recovery by fat- and muscle-depleted Blackpoll Warblers following trans-oceanic migration is driven by time-minimization
Bibliographic record
Abstract
Non-stop endurance flights are a defining characteristic of many long-distance migratory birds but subsequent recovery phases are not typically distinguished from fueling phases (collectively ‘stopovers’), despite endurance flights inducing marked physiological changes including flight muscle atrophy and gastrointestinal tract reductions. Here, we hypothesize that recovery requires unique behavioral adaptations, leading to departures from the predictions of optimal migration theory for time-minimizing migrants. We predict that recovering birds will 1) select (moist) food-rich habitats on arrival; 2) have slow initial fueling rates due to decreased gastrointestinal capacity; 3) show a negative correlation between stopover duration and arrival condition instead of a negative correlation with fuel deposition rate (FDR); 4) stopover longer than required to store energy reserves for subsequent flights; and 5) show evidence of rebuilding flight muscles. To test these predictions, we studied Blackpoll Warblers Setophaga striata in northern Colombia following trans-oceanic flights >2250 km. Birds selected dry seasonal habitats, despite proximity of moist forests, and among 1227 captured individuals, 14-21% were emaciated and 88% had atrophied flight muscles. We recaptured 74 individuals, revealing net positive mass gains and, contrary to Prediction 2, no evidence for slow initial recovery rates. Contrary to Prediction 3, stopover duration was only weakly correlated with arrival condition and birds with high FDR (4.9% LBM/day) had shorter durations (3 days) relative to birds with slower rates (7 days) - both groups accumulated sufficient fuel to reach non-breeding (over-wintering) grounds 500-1000 km away. Mass increases were largely attributable to fat deposition but some birds improved flight muscle condition (31.9%), consistent with Prediction 5. Together these results reveal a strong selection for time-minimization in the decisions made by Blackpoll Warblers following trans-oceanic flights, likely mediated through advantages to early arrival on non-breeding grounds, contrary to our hypothesis of recovery imposing unique selection pressures.
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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 | 0.000 |
| 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 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".