Movements and habitat use of the Rocky Mountain Population of trumpeter swans
Bibliographic record
Abstract
Abstract The Rocky Mountain Population (RMP) of trumpeter swans Cygnus buccinator (hereafter, swans) in North America includes breeders in the Greater Yellowstone Area (GYA) and other western states (together, United States segment) and western provinces of Canada (Canada segment). Conservation concern for the United States segment stems from its slow population growth and the resident nature of GYA swans, which intermingle with migrating Canada segment swans in wintering habitats. Thus, understanding variation in migratory behavior and habitat use by swans in the two population segments can inform how management actions may affect the RMP. We used telemetry data from 55 RMP swans captured in the western United States to understand their movements and habitat use. For 45 swans (60 swan‐years) that spent the summer in the United States, distance traveled between breeding and wintering areas ranged from 0 km (i.e., no migration in 22% of swan‐years) to 473 km, with an average of nonzero movements of 118 ± 95 km (SD). Swans traveled farther distances when maximum temperatures were lower. For 10 swans (16 swan‐years) that spent the summer in Canada, five appeared to molt but not to nest, and four appeared to nest in one or more years. Migration timing was similar for molting and nesting swans. All five molting swans and one nesting swan spent at least one previous summer in the GYA. Migratory connectivity of all birds was weaker in years when more swans migrated to Canada for the summer. During the breeding season, Canada swans used low‐elevation lakes, but United States swans used high‐elevation lakes. Both groups of swans increased use of crop fields outside of the breeding season. Our study shows interchange between the United States and Canada segments, a finding that challenges the efficacy of existing population designations. Furthermore, variation in movement behavior of GYA swans suggests possible actions, such as restoring winter habitats to increase swan distribution and migration, to support swan conservation.
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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".