Foraging success in a wild species of bird varies depending on which eye is used for anti-predator vigilance
Bibliographic record
Abstract
Brain lateralisation in animals with laterally placed eyes often leads to preferential eye use for ecologically relevant tasks such as monitoring predators and companions. Few studies of preferential eye use have been conducted in the wild and it is not clear if such preferences in the wild are widespread, how individuals can benefit from them, and which ecological factors influence their evolution. In a wild species of bird the extent to which foraging success varied depending on which eye is used during concomitant anti-predator vigilance was examined. When foraging in open mudflats, semipalmated sandpipers (Calidris pusilla) are frequently exposed to predation attempts by falcons (Falco spp) that originate from the tree cover bordering mudflats. Sandpipers spread along the receding tideline and can face the riskier side of their habitat primarily with the left or the right eye as they forage. If foraging is mostly incompatible with vigilance, the rate at which prey items are collected should decrease when birds use their less-preferred eye to scan cover. If foraging and vigilance can be carried out simultaneously, time spent foraging should not be affected but the efficiency with which their burrowing amphipod prey are located may be reduced, thus leading to decreased capture rate. Birds facing the riskier side of the habitat with their right eye captured significantly more prey than those scanning the same side with their left eye. Specialised eye use in sandpipers may allow individuals to perform simultaneous tasks, such as foraging and vigilance, more efficiently.
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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) | 0.002 | 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".