Lars Chittka

The colour hexagon: a chromaticity diagram based on photoreceptor excitations as a generalized representation of colour opponency

SummaryA chromaticity diagram which plots the 3 photoreceptor excitations of trichromatic colour vision systems at an angle of 120° is presented. It takes into acount the nonlinear transduction process in the receptors. The resulting diagram has the outline of an equilateral hexagon. It is demonstrated by geometrical means that excitation values for any type of spectrally opponent mechanism can be read from this diagram if the weighting factors of this mechanism add up to zero. Thus, it may also be regarded as a general representation of colour opponent relations, linking graphically the Young-Helmholtz theory of trichromacy and Herings concept of opponent colours. It is shown on a geometrical. basis that chromaticity can be coded unequivocally by any two combined spectrally opponent mechanisms, the main difference between particular mechanisms being the extension and compression of certain spectral areas. This type of graphical representation can qualitatively explain the Bezold-Brücke phenomenon. Furthermore, colour hexagon distances may be taken as standardized perceptual colour distance values for trichromatic insects, as is demonstrated by comparison with behavioural colour discrimination data of 3 hymenopteran species.

Successful invasion of a floral market.

An exotic Asian plant has moved in on Europes river-banks by bribing pollinators.

Speed–accuracy tradeoffs in animal decision making

The traditional emphasis when measuring performance in animal cognition has been overwhelmingly on accuracy, independent of decision time. However, more recently, it has become clear that tradeoffs exist between decision speed and accuracy in many ecologically relevant tasks, for example, prey and predator detection and identification; pollinators choosing between flower species; and spatial exploration strategies. Obtaining high-quality information often increases sampling time, especially under noisy conditions. Here we discuss the mechanisms generating such speed-accuracy tradeoffs, their implications for animal decision making (including signalling, communication and mate choice) and the significance of differences in decision strategies among species, populations and individuals. The ecological relevance of such tradeoffs can be better understood by considering the neuronal mechanisms underlying decision-making processes.

Are Bigger Brains Better

Attempts to relate brain size to behaviour and cognition have rarely integrated information from insects with that from vertebrates. Many insects, however, demonstrate that highly differentiated motor repertoires, extensive social structures and cognition are possible with very small brains, emphasising that we need to understand the neural circuits, not just the size of brain regions, which underlie these feats. Neural network analyses show that cognitive features found in insects, such as numerosity, attention and categorisation-like processes, may require only very limited neuron numbers. Thus, brain size may have less of a relationship with behavioural repertoire and cognitive capacity than generally assumed, prompting the question of what large brains are for. Larger brains are, at least partly, a consequence of larger neurons that are necessary in large animals due to basic biophysical constraints. They also contain greater replication of neuronal circuits, adding precision to sensory processes, detail to perception, more parallel processing and enlarged storage capacity. Yet, these advantages are unlikely to produce the qualitative shifts in behaviour that are often assumed to accompany increased brain size. Instead, modularity and interconnectivity may be more important.

Ultraviolet as a Component of Flower Reflections, and the Colour Perception of Hymenoptera

Based on the measurements of 1063 flower reflection spectra, we show that flower colours fall into distinct clusters in the colour space of a bee. It is demonstrated that this clustering is caused by a limited variability in the floral spectral reflectance curves. There are as few as 10 distinct types of such curves, five of which constitute 85% of all measurements. UV reflections are less frequent and always lower in intensity than reflections in other parts of the spectrum. A further cluster of colour loci is formed in the centre of the colour space. It contains the colour loci of green leaves, several other background materials and only very few flowers. We propose a system to classify the reflection functions of flowers, and a set of colour names for bee colours.

The evolutionary adaptation of flower colours and the insect pollinators' colour vision

SummaryThe evolutionary tuning between floral colouration and the colour vision of flower-visiting Hymenoptera is quantified by evaluating the informational transfer from the signalling flower to the perceiving pollinator. The analysis of 180 spectral reflection spectra of angiosperm blossoms reveals that sharp steps occur precisely at those wavelengths where the pollinators are most sensitive to spectral differences. Straight-forward model calculations determine the optimal set of 3 spectral photoreceptor types for discrimination of floral colour signals on the basis of perceptual difference values. The results show good agreement with the sets of photoreceptors characterized electrophysiologically in 40 species of Hymenoptera.

Colour preferences of flower-naive honeybees

Flower-naive honeybees Apis mellifera L. flying in an enclosure were tested for their colour preferences. Bees were rewarded once on an achromatic (grey, aluminium or hardboard), or on a chromatic (ultraviolet) disk. Since naive bees never alighted on colour stimuli alone, a scent was given in combination with colour. Their landings on twelve colour stimuli were recorded. Results after one reward (“first test”) were analysed separately from those obtained after few rewards (“late tests”).1)After pre-training to achromatic signals, bees preferred, in the first test, bee-uv-blue and bee-green colours. With increasing experience, the original preference pattern persisted but the choice of bee-blue and bee-green colours increased.2)Neither colour distance of the test stimuli to the background or to the pre-training signal, nor their intensity, nor their green contrast, accounted for the colour choice of bees. Choices reflected innate preferences and were only associated with stimulus hue.3)Bees learned very quickly the pre-trained chromatic stimulus, the original colour preferences being thus erased.4)Colour preferences were strongly correlated with flower colour and its associated nectar reward, as measured in 154 flower species.5)Colour preferences also resemble the wavelength dependence of colour learning demonstrated in experienced bees.

Psychophysics: Bees trade off foraging speed for accuracy

Bees have an impressive cognitive capacity, but the strategies used by individuals in solving foraging tasks have been largely unexplored. Here we test bumblebees (Bombus terrestris) in a colour-discrimination task on a virtual flower meadow and find that some bees consistently make rapid choices but with low precision, whereas other bees are slower but highly accurate. Moreover, each bee will sacrifice speed in favour of accuracy when errors are penalized instead of just being unrewarded. To our knowledge, bees are the first example of an insect to show between-individual and within-individual speed– accuracy trade-offs.

Floral Iridescence, Produced by Diffractive Optics, Acts As a Cue for Animal Pollinators

Iridescence, the change in hue of a surface with varying observation angles, is used by insects, birds, fish, and reptiles for species recognition and mate selection. We identified iridescence in flowers of Hibiscus trionum and Tulipa species and demonstrated that iridescence is generated through diffraction gratings that might be widespread among flowering plants. Although iridescence might be expected to increase attractiveness, it might also compromise target identification because the objects appearance will vary depending on the viewers perspective. We found that bumblebees (Bombus terrestris) learn to disentangle flower iridescence from color and correctly identify iridescent flowers despite their continuously changing appearance. This ability is retained in the absence of cues from polarized light or ultraviolet reflectance associated with diffraction gratings.

The correlation of learning speed and natural foraging success in bumble-bees

Despite the widespread assumption that the learning abilities of animals are adapted to the particular environments in which they operate, the quantitative effects of learning performance on fitness remain virtually unknown. Here, we evaluate the learning performance of bumble-bees (Bombus terrestris) from multiple colonies in an ecologically relevant associative learning task under laboratory conditions, before testing the foraging performance of the same colonies under the field conditions. We demonstrate that variation in learning speed among bumble-bee colonies is directly correlated with the foraging performance, a robust fitness measure, under natural conditions. Colonies vary in learning speed by a factor of nearly five, with the slowest learning colonies collecting 40% less nectar than the fastest learning colonies. Such a steep fitness function is suggestive of strong selection for higher learning speed. Partial correlation analysis reveals that other factors such as forager body size or colour preference appear to be negligible in our study. Although our study does not directly prove causality of learning on foraging success, our approach of correlating natural within-species variation in these two factors represents a major advance over traditional between-species correlative analyses where comparability can be compromised by the fact that species vary along multiple dimensions.