Nest habitat selection of White-winged Scoters on Yukon Flats, Alaska
Bibliographic record
Abstract
Breeding bird surveys indicate a long-term decline in numbers of scoters (Melanitta spp.) breeding in North America. Little is known about the breeding habitat and reproductive life history of White-winged Scoters (M. fusca) in their primary breeding areas in the boreal forest of Alaska and northern Canada. We characterized selection of nest habitats and attributes within those habitats by measuring variables at nests and random sites on the Yukon Flats National Wildlife Refuge, Alaska. White-winged Scoters avoided nesting in meadows, but nested in scrub or forested habitat types in proportion to their availability (χ25 = 9.7, P = 0.08). Nests of radio-marked females were farther from water and edge ( 210 ± 43 and 10 ± 4 m, respectively), and in slightly thicker cover ( 6 ± 4%) than nests located without aid of radio transmitters. Females selected sites with more variable and abundant overhead and lateral cover, and sites closer to edge and water than random sites. The results imply nearly random use of scrub and forested habitat types within the study area, but selective use of attributes within those habitat types. This generalist approach to nest site selection at a larger scale may be an adaptive response to reduce detection by nest predators. Nests located without use of radio-marked females may not be representative of the population of nests at a study site. White-winged Scoters often selected nest sites with dense cover far from water, which may increase nest survival. However, concealed sites are difficult for heavy-bodied birds to escape and females may be trading productivity against their own mortality.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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".