The Amazon Basin’s rivers and lakes support Nearctic-breeding shorebirds during southward migration
Bibliographic record
Abstract
ABSTRACT Identifying the migration routes and stopover sites used by declining species is critical for developing targeted conservation actions. Long-distance migratory shorebirds are among the groups of birds declining most rapidly, yet we frequently lack detailed knowledge about the routes and stopover sites they use during their hemisphere-spanning migrations. This is especially true for species that migrate through mid-continental regions in the Western Hemisphere. We therefore used satellite transmitters to track 212 individuals of 6 shorebird species during their southward migrations—Pluvialis dominica (American Golden-Plover), Limosa haemastica (Hudsonian Godwit), Tringa flavipes (Lesser Yellowlegs), Calidris subruficollis (Buff-breasted Sandpiper), C. melanotos (Pectoral Sandpiper), and Bartramia longicauda (Upland Sandpiper)—as they crossed the Amazon Basin of South America, a region from which reports of shorebird numbers are increasing but remain relatively rare. Our results make clear that the Amazon Basin provides stopover habitat for a large number of shorebirds: more than 74% of individuals tracked crossing the Amazon Basin stopped over in the region for an average of 2–14 days, with some spending the entire nonbreeding season there. All species selected stopover sites along the region’s many rivers and lakes, while within stopover sites each species exhibited distinct habitat preferences. The timing of stopovers within sub-basins of the Amazon Basin also coincided with periods of low water, when the muddy, shallow water habitats preferred by most shorebirds are likely plentiful. Together, our results highlight the need for detailed investigations into shorebird abundance and distribution within the Amazon Basin, threats to shorebirds within particular subbasins, and links between shorebird conservation efforts and those targeting the myriad other species that inhabit this dynamic, hyper-diverse region.
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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 | 0.001 | 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 | 0.001 |
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".