Experimental evidence that migrants adjust usage at a stopover site to trade off food and danger
Bibliographic record
Abstract
Rich habitats, intensive feeding, and large fuel deposits are assumed to improve the capability for long-distance migration by birds but may also heighten their vulnerability or exposure to predators. Studies of habitat use by migrants have emphasized the importance of feeding, and relatively few studies have considered how migrants manage the dangers inherent in acquiring and storing fuel. Migrant western sandpipers (Calidris mauri) stop over on coastal mudflats characterized by a strong feeding–danger gradient, with both food and danger decreasing with distance from the shoreline. We experimentally manipulated danger by adding obstructive cover and measured sandpiper usage along this gradient. We compared sandpiper usage along a transect extending 100 m on either side of the obstruction with that on matched control transects without obstructions. The dropping density accumulated during a low-tide period provided a sensitive measure of sandpiper usage. Mean usage on control transects was 2.3 droppings/m2 and was lower by 1.5 droppings/m2 (65%) on treatment transects. Usage did not differ between control and treatment transects at the furthest distances from the obstruction, the difference increased with proximity to the obstruction, and was greater by on average 0.9 droppings/m2 on the oceanward side (low food abundance) than on the shoreward side (high food abundance). All these findings were predicted by danger management theory. Our study provides experimental evidence that migrant birds are sensitive to danger on stopover and has implications for understanding migration strategies.
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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 | 0.001 | 0.002 |
| 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".