Trends in timing of spring migration along the Pacific Flyway by Western Sandpipers and Dunlins
Bibliographic record
Abstract
Long-distant migrants timing their arrival on the breeding grounds face a tradeoff between optimal timing for breeding and optimal timing for survival. For many shorebird species, the flyway northward spans thousands of kilometers, and both conditions encountered en route and priorities of individuals can affect the timing of migration. We used data from spring migration surveys of Western Sandpipers (Calidris mauri) and Pacific Dunlins (Calidris alpina pacifica) along the Pacific Flyway of North America to determine whether the timing of their northward migration changed from 1985 to 2016. We compiled survey data for both species from 6 sites of varying size along the northern portion of the flyway from Washington, USA, through British Columbia, Canada, to Alaska, USA, and estimated interannual trends in the timing of passage through each site. Peak passage dates at the sites closest to the species' breeding grounds in Alaska became later by 1-2 days over the study period, while dates of peak passage at sites farther south became ~3 days earlier. A post hoc analysis suggested that local temperatures affected peak passage dates at most sites, with warmer temperatures related to earlier passage. Discerning patterns of movement by Dunlins at southern sites was complicated by the presence of winter residents. Simulation analyses of sandpiper movement through a stopover site highlighted both length of stay and timing of arrival as important factors shaping peak passage estimates. We suggest that Western Sandpipers appear to be arriving earlier at southern sites and staying longer at larger stopover sites, such as Alaska's Copper River delta. Our methodology generated specific predictions of peak passage dates on northward migration that may be useful in other systems for which historical count data are available.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| 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 teacher head, 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".