Migration strategy and constraint in migration behavior vary among shorebird species with different life histories
Bibliographic record
Abstract
Abstract Migration strategy is a key behavioral characteristic guiding how migratory species time their annual cycles and use habitat. Understanding variation in migration strategy within and among species and individuals can be useful for understanding how birds navigate energetic trade‐offs and designing or modifying conservation plans meant to benefit multiple species and life histories. We compared migration strategies among three migratory shorebird species with variable life history traits and short, medium, and long migration distances, respectively: American avocets ( Recurvirostra americana ), black‐bellied plovers ( Pluvialis squatarola ), and Hudsonian godwits ( Limosa haemastica ). Avocets (short distance) exhibited the most within‐species variation in migration duration, proportion of migration time spent at stopovers, and stopover duration. Plovers (medium distance) and godwits (long distance) showed less variation in these metrics, but godwits showed the most variation in the number of stopovers used. There were significant differences among species in migration distance, number of stopovers used, proportion of time stopped over, departure and arrival dates, and migration duration, but not mean stopover duration. We also found that avocets spent more time stopped over relative to migration distance than plovers or godwits, indicating that avocets showed the most energy‐minimizing strategy of the three species. Our findings set the stage for future work assessing the effects of climate change and land use on characteristics associated with different migration strategies for additional migratory species.
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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 | 0.001 |
| 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".