Swimming behaviour tunes fish polarization vision to double prey sighting distance
Bibliographic record
Abstract
The analysis of the polarization of light expands vision beyond the realm of colour and intensity and is used for multiple ecological purposes among invertebrates including orientation, object recognition, and communication. How vertebrates use polarization vision as part of natural behaviours is widely unknown. In this study, I tested the hypothesis that polarization vision improves the detection of zooplankton prey by the northern anchovy, Engraulis mordax, the only vertebrate with a demonstrated photoreceptor basis explaining its polarization sensitivity. Juvenile anchovies were recorded free foraging on zooplankton under downwelling light fields of varying percent polarization (98%, 67%, 19%, and 0% - unpolarized light). Analyses of prey attack sequences showed that anchovies swam in the horizontal plane perpendicular, on average, to the polarization direction of downwelling light and attacked prey at pitch angles that maximized polarization contrast perception of prey by the ventro-temporal retina, the area devoted to polarization vision in this animal. Consequently, the mean prey location distance under polarized light was up to 2.1 times that under unpolarized conditions. All indicators of polarization vision mediated foraging were present under 19% polarization, which is within the polarization range commonly found in nature during daylight hours. These results demonstrate: (i) the first use of oriented swimming for enhancing polarization contrast detection of prey, (ii) its relevance to improved foraging under available light cues in nature, and (iii) an increase in target detection distance that is only matched by polarization based artificial systems.
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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 | 0.000 |
| 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 | 0.000 |
| 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".