Evolution of Colour Terms: 2 Environmental Constraints

Continuing my series on the Evolution of Colour terms, this post reviews evidence for environmental constraints on colour perception. For the full dissertation and for references, go here.

Regan et al. (2001) show that colour vision co-evolved with the colour of the objects that it was used to identify.  Specifically, colour vision facilitated the detection of coloured fruit against a background of leaves.  Reciprocally, primates helped disperse the seeds (zoochory) so that, over time, the plants adapted to become more detectable (dispersal syndrome).  Regan et al. give a thorough review of the research into the evolution of colour vision.  There is a large variation in primate visual morphology, ranging from monochromaticity (Owl monkeys, Aotus trivirgatus) to trichromaticity (all old-world monkeys and apes, catarrhine) and polymorphism (e.g., dichromaticity in males and a percentage of trichromaticity in females).  However, dichromaticity is not necessarily disadvantageous compared to trichromaticity.  Trichromaticity does appear to be optimised for the detection of certain fruit at close range (see Regan et al., p 260-262).  However, dichromats may be better at breaking camouflage of predators or prey (e.g., edible insects).  Therefore, in a society where foraging is done in groups and individuals may cooperatively signal to others about the presence of resources, polymorphic colour vision may be advantageous, since different individuals are ‘specialised’ for different tasks (a frequency-dependent advantage, see Clarke 1979, Mollon, Bowmaker & Jacobs, 1984).

However, this is a long-term explanation.  The particular properties of the immediate environment may affect perception during individual development.  For example, focal colours have been shown to vary between populations from distant environments (Webster et al., 2002).  This may reflect either a cultural bias or an environmental bias.  Laeng et al. (2007) studied individuals from the same town in Norway, that is, a culturally homogenous population.  Colour sensitivity in adults varied depending on where they were born.  Those born at higher latitudes, where sunlight is shifted towards blue, had reduced sensitivity to yellow-green and blue-green contrasts, but a higher sensitivity to variations in the purple range.  Therefore, differences in the environment may have repercussions for the colour term system.

Dowman (2007) ran a cultural transmission model where agents had to converge on categorisations for a uniformly-spaced colour space.  However, certain colours in the space were set to be more salient.  These ‘universal colours’ were not evenly spaced.  The analysis was done by converting the population’s convergent categorisation to the same format as the WCS data.  The fit between the model’s outcome and actual attested types in human cultures could then be compared.  Dowman found that the emergent systems fitted with attested types in the WCS only with the inclusion of unevenly-spaced ‘universal foci’.  This implies that the spacing and frequency of salient colours constrain colour term systems.  However, Dowman emphasises that the nature of these foci could be environmental, genetic or cultural.  To achieve this, Dowman configured the model so that the ‘universal foci’ were chosen as the topic during communications 20 times more often than other colours, and were 20 times more likely to be remembered, meaning that universal foci were up to 400 times more salient, and not 20 times more salient, as stated in Dowman (2007, p.118).

Griffin (2006) found that linguistic partitionings of the colour spectrum are optimised for the recognition of natural objects.  Images of objects were classified based on the distribution of pixels belonging to each colour category (e.g., trees are mainly green and brown while bananas are yellow and brown).  Natural colour categories proved to be better at classifying objects than other random categorisations.  This implies that colour terms are optimised for functionality, as Embodied cognition predicts.  In conclusion, and as expected, the visual environment does seem to impose constraints on colour categorisation.

Next, Perceptual Constraints ->

Regan, B., Julliot, C., Simmen, B., Vienot, F., Charles-Dominique, P., & Mollon, J. (2001). Fruits, foliage and the evolution of primate colour vision Philosophical Transactions of the Royal Society B: Biological Sciences, 356 (1407), 229-283 DOI: 10.1098/rstb.2000.0773

Clarke, B.C. (1979). The evolution of genetic diversity Proceedings of the Royal Society of London B, 205, 453-474

Mollon, J., Bowmaker, J., & Jacobs, G. (1984). Variations of Colour Vision in a New World Primate Can be Explained by Polymorphism of Retinal Photopigments Proceedings of the Royal Society B: Biological Sciences, 222 (1228), 373-399 DOI: 10.1098/rspb.1984.0071

Webster, M., Webster, S., Bharadwaj, S., Verma, R., Jaikumar, J., Madan, G., & Vaithilingham, E. (2002). Variations in normal color vision. III. Unique hues in Indian and United States observers Journal of the Optical Society of America A, 19 (10) DOI: 10.1364/JOSAA.19.001951

LAENG, B., BRENNEN, T., ELDEN, A., GAAREPAULSEN, H., BANERJEE, A., & LIPTON, R. (2007). Latitude-of-birth and season-of-birth effects on human color vision in the Arctic Vision Research, 47 (12), 1595-1607 DOI: 10.1016/j.visres.2007.03.011

Dowman, M. (2007). Explaining Color Term Typology With an Evolutionary Model Cognitive Science: A Multidisciplinary Journal, 30 (1), 99-132 DOI: 10.1207/s15516709cog3101_4

Griffin LD (2006). Optimality of the basic colour categories for classification. Journal of the Royal Society, Interface / the Royal Society, 3 (6), 71-85 PMID: 16849219

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