Weak evidence of carry-over effects of overwinter climate and habitat productivity on spring passage of migratory songbirds at a northern stopover site in Ontario
Bibliographic record
Abstract
Abstract Reduced rainfall in tropical regions decreases the availability of food resources for overwintering songbirds, with negative impacts on their body condition. Increasingly dry conditions at tropical wintering sites as a result of climate change may impact the ability of temperate-breeding songbirds to prepare for and execute their spring migration. We studied the carry-over effects of natural climatic fluctuations created by the El Niño–Southern Oscillation (ENSO) in tropical overwintering areas on 7 long-distance migratory songbirds at a Canadian stopover site. We used the Normalized Difference Vegetation Index as a proxy for tropical habitat productivity and resource availability and a 34-year bird banding dataset from Long Point, Ontario, Canada to assess migration timing and stopover body condition. To increase our ability to detect potential carry-over effects, we employed a novel approach of using recent migratory connectivity studies to restrict the wintering ranges to areas most likely used by individuals passing through southern Ontario. Using linear models, we found that overwinter habitat productivity was significantly negatively influenced by dry ENSO events in the overwintering ranges in 3 of 7 species, with a fourth near-significant. Subregional differences in the effect of ENSO on precipitation patterns may explain why we did not detect a consistent effect of ENSO on overwinter habitat productivity for all species. Despite restricting the wintering range and using a robust dataset for species with diverse life histories, we detected only weak and often conflicting evidence of population-level carry-over effects from dry ENSO events and overwinter habitat productivity. Negative carry-over effects may be strongest and most evident during the earlier stages of migration because birds may be able to compensate to some extent for poor departure condition and late departure while en route.
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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) | 0.000 | 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".