Does colour vision type drive dietary and nutritional niche differentiation in wild capuchins (Cebus imitator)?
Bibliographic record
Abstract
The polymorphic colour vision system of platyrrhine monkeys is a remarkable example of balancing selection. Yet, the underlying mechanism of natural selection remains debated. Here we test the potential for dietary niche differentiation between sensory phenotypes. Monkeys with dichromacy (red-green ‘colourblindness’) are predicted to eat more camouflaged foods while trichromatic monkeys (‘typical’ human-like colour vision) are predicted to eat more reddish foods. We studied a population of wild Costa Rican capuchins (Cebus imitator), comparing the diet and nutrition of adult female dichromats and trichromats. We classified the conspicuity of diet items in capuchin visual space and calculated dietary intake, nutritional intake and niche overlap during periods of high and low habitat-wide fruit abundance. Dichromats and trichromats had similar nutritional profiles, but we found evidence of niche differentiation in the invertebrate prey consumed. In support for our prediction regarding cryptic invertebrate prey, dichromats ate more camouflaged surface-dwelling invertebrates, while trichromats ate more extracted ants. Contrary to our prediction regarding reddish foods, dichromats consumed more dark reddish figs than did trichromats. However, these fruits were likely to be conspicuous to both dichromats and trichromats in luminance contrast. Overall, our results suggest that monkeys with different colour vision types achieve similar nutritional intakes in slightly different ways. Behavioural flexibility driven by sensory differences may decrease intragroup feeding competition while meeting species-specific nutritional needs. Our research sheds light on the extent of foraging niche differentiation in a population of wild mammals and its potential contribution to maintaining colour vision polymorphism.
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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 | 0.000 | 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 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".