Long-term winter-site fidelity in Song Sparrows (Melospiza melodia)
Bibliographic record
Abstract
Abstract In migratory animals, the degree to which individuals return to the same wintering sites across multiple years can affect fitness and population dynamics, and thus has important implications for conservation. Despite this, long-term evaluations of wintering-site fidelity are rare for migratory birds: many populations are intensively studied on their breeding grounds but tracking the migratory movements of small birds once they leave the breeding grounds is challenging. To evaluate patterns of overwintering location and fidelity, we collected winter-grown claw tissue from 301 Song Sparrows (Melospiza melodia; 449 samples) captured in spring at their breeding grounds over 6 consecutive yr and assessed stable hydrogen isotope (δ2Hc) values to determine within-individual repeatability and between-year variation in wintering latitudes. We also retrieved useable data from 8 geolocators over 2 consecutive winters. Geolocator-derived wintering positions correlated with origins based on δ2Hc values. Consistent with previous findings, male δ2Hc values reflected more northerly wintering areas than those of females, indicating shorter latitudinal migration distances for males, but the magnitude of the sex difference varied across years. The distribution of wintering latitudes was generally consistent among years, except for the 2015 舑2016 winter, which had unusually negative δ2Hc values. Values of δ2Hc were repeatable for males but not for females, suggesting that winter-site fidelity could differ between sexes. The data presented here emphasize the importance of tracking migratory populations across multiple years to uncover factors affecting population dynamics.
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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 | 0.001 | 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".