Carry-Over Effects of Nonbreeding Habitat on Start-to-Finish Spring Migration Performance of a Songbird
Bibliographic record
Abstract
For migratory animals, conditions during the nonbreeding period may carry-over to influence spring migration performance. Animals in low-quality habitats are predicted to be in poorer condition, show later migration timing, and travel at slower speeds. This can result in subsequent negative effects on fitness. We tested the hypothesis that nonbreeding season body condition and habitat quality carry-over to affect spring migration performance of a long-distance migratory songbird, the Wood Thrush (Hylocichla mustelina). We tracked individual birds between multiple breeding sites in North America and nonbreeding sites in Central America. First, we compared body condition of nonbreeding birds migrating to the same general region of the breeding range with spring migration performance (timing, speed, and duration) obtained from light-level geolocators. Second, we assessed the Normalized Difference Vegetation Index (NDVI) as a proxy for nonbreeding habitat quality, and predicted that birds from wetter habitat or in wetter years (higher NDVI) would show improved migration performance relative to birds from drier sites. We found no evidence of individual-level carry-over effects of nonbreeding season body condition on spring migration performance. Lower NDVI of nonbreeding habitat resulted in delayed spring migration departure, but this effect disappeared by arrival at breeding sites. Birds occupying drier nonbreeding sites migrated faster and for fewer days, compensating for their relatively late departure. We also documented a broader pattern in NDVI and migration timing and distance, in that birds that occupied the wettest areas in the southern part of the nonbreeding range departed significantly later and migrated farther. Our results suggest that individual carry-over effects of nonbreeding habitat quality may be compensated for by a faster and shorter migration strategy. At a broad scale, consistently later spring timing and longer migration distances were associated with the wettest areas (the highest quality habitats) of the Wood Thrush non-breeding range. This supports the theory that high-quality habitats offset the costs of farther migration, resulting in a leap-frog migration pattern.
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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".