Migration and winter distribution of the Chestnutcollared Longspur
Bibliographic record
Abstract
Abstract The Chestnut-collared Longspur (Calcarius ornatus) is one of five grassland songbirds, endemic within North America, with populations that have declined >65% since the 1960s. These species breed and winter in the northern and southern Great Plains, respectively. Identifying migration routes, wintering sites, and the timing of their habitat use is key for understanding the relative magnitude of threats across the annual cycle and effectively targeting habitats for conservation. We tracked migratory movements of seven Chestnut-collared Longspurs with light-level geolocators deployed in Canada. Individuals wintered up to 112-1,200km apart. All followed the Central Flyway, circumvented high-elevation terrain, and traveled east of the breeding location. Unlike most songbirds, the durations of spring and fall migrations were similar; on average 42 ± 7d and 41 ± 5d during fall and spring migrations, respectively, for an approximately 2,000km migration; this highlights the need to better understand habitat requirements during migration for grassland songbirds. Using geospatial habitat data, we assessed winter distribution overlap with four other endemic grassland songbirds; wintering range overlapped 63-99%. Future studies should use more precise devices (e.g., archival GPS units), programmed for data collection dates from this study, to identify specific migratory sites for better conserving this and associated grassland species.
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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".