Storms drive altitudinal migration in a tropical bird
Bibliographic record
Abstract
Although migration is a widespread and taxonomically diverse behaviour, the ecological factors shaping migratory behaviour are poorly understood. Like other montane taxa, many birds migrate along elevational gradients in the tropics. Forty years ago, Alexander Skutch postulated that severe storms could drive birds to migrate downhill. Here, we articulate a novel mechanism that could link storms to mortality risks via reductions in foraging time and provide, to our knowledge, the first tests of this hypothesis in the White-ruffed Manakin (Corapipo altera), a small partially migratory frugivore breeding on the Atlantic slope of Costa Rica. As predicted, variation in rainfall was associated with plasma corticosterone levels, fat stores, plasma metabolites and haematocrit. By collecting data at high and low elevation sites simultaneously, we also found that high-elevation residents were more adversely affected by storms than low elevation migrants. These results, together with striking temporal capture patterns of altitudinal migrants relative to storms, provide, to our knowledge, the first evidence that weather-related risks incurred by species requiring high food intake rates can explain altitudinal migrations of tropical animals. These findings resolve conflicting evidence for and against food limitation being important in the evolution of this behaviour, and highlight how endogenous and exogenous processes influence life-history trade-offs made by individuals in the wild. Because seasonal storms are a defining characteristic of most tropical ecosystems and rainfall patterns will probably change in ensuing decades, these results have important implications for understanding the ecology, evolution and conservation of tropical animals.
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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".