From land to sea: the fall migration of the red phalarope through the Western Hemisphere
Bibliographic record
Abstract
Understanding how and where individuals migrate between breeding and wintering areas is important for assessing threats, identifying important areas for conservation, and determining a species’ vulnerability to changing environmental conditions. Between 2017 and 2020, we tracked post-breeding movements of 72 red phalaropes Phalaropus fulicarius with satellite tags from 7 Arctic-breeding sites in the Alaskan and Central Canadian Arctic. All tracked red phalaropes left their Arctic breeding grounds (i.e. were obligate migrants) but then switched to a more facultative migration strategy with a fly-and-forage migration pattern once in the marine environment. We documented high variability in migration timing and routes, with birds often taking indirect, circuitous routes with numerous stops that greatly lengthened both the duration and distance of their southward migration. Across nearly 500 stopover areas, which were often associated with areas of presumed greater food availability, individuals spent an average of 6 d and traveled within an average area of 1880 km 2 . Stopover areas were concentrated in onshore and nearshore habitats of the Beaufort and Chukchi seas, the western edge of the Bering Strait, along the Alaska Peninsula and Aleutian Islands, and near the Pribilof Islands in Alaska. Within the Beaufort and Chukchi seas, females frequently stopped within the marginal ice zone, whereas males tended to stay on land or in open water. Our results identified important marine areas that can aid future conservation and management decisions. However, conservation of the species will also need to address the numerous direct and indirect anthropogenic threats red phalaropes experience at sea, many of which are not site-specific.
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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 | 0.001 | 0.001 |
| 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".