Stopover habitats of spring migrating surf scoters in southeast Alaska
Bibliographic record
Abstract
Abstract Habitat conditions and nutrient reserve levels during spring migration have been suggested as important factors affecting population declines in waterfowl, emphasizing the need to identify key sites used during spring and understand habitat features and resource availability at stopover sites. We used satellite telemetry to identify stopover sites used by surf scoters migrating through southeast Alaska during spring. We then contrasted habitat features of these sites to those of random sites to determine habitat attributes corresponding to use by migrating scoters. We identified 14 stopover sites based on use by satellite tagged surf scoters from several wintering sites. We identified Lynn Canal as a particularly important stopover site for surf scoters originating throughout the Pacific winter range; approximately half of tagged coastally migrating surf scoters used this site, many for extended periods. Stopover sites were farther from the mainland coast and closer to herring spawn sites than random sites, whereas physical shoreline habitat attributes were generally poor predictors of site use. The geography and resource availability within southeast Alaska provides unique and potentially critical stopover habitat for spring migrating surf scoters. Our work identifies specific sites and habitat resources that deserve conservation and management consideration. Aggregations of birds are vulnerable to human activity impacts such as contaminant spills and resource management decisions. This information is of value to agencies and organizations responsible for emergency response planning, herring fisheries management, and bird and ecosystem conservation. © 2010 The Wildlife Society
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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".