Ultraviolet vision aids the detection of nutrient-dense non-signaling plant foods.

To expand our understanding of what tasks are particularly helped by UV vision and may justify the costs of focusing high-energy light onto the retina, we used an avian-vision multispectral camera to image diverse vegetated habitats in search of UV contrasts that differ markedly from visible-light contrasts. One UV contrast that stood out as very different from visible-light contrasts was that of nutrient-dense non-signaling plant foods (such as young leaves and immature fruits) against their natural backgrounds. From our images, we calculated color contrasts between 62+ species of such foods and mature foliage for the two predominant color vision systems of birds, UVS and VS. We also computationally generated images of what a generalized tetrachromat, unfiltered by oil droplets, would see, by developing a new methodology that uses constrained linear least squares to solve for optimal weighted combinations of avian camera filters to mimic new spectral sensitivities. In all visual systems, we found that nutrient-dense non-signaling plant foods presented a lower, often negative figure-ground contrast in the UV channels, and a higher, often positive figure-ground contrast in the visible channels. Although a zero contrast may sound unhelpful, it can actually enhance color contrast when compared in a color opponent system to other channels with nonzero contrasts. Here, low or negative UV contrasts markedly enhanced color contrasts. We propose that plants may struggle to evolve better UV crypsis since UV reflectance from vegetation is largely specular and thus highly dependent on object orientation, shape, and texture.