The Perceptual and Cognitive Processes That Govern Egg Rejection in Hosts of Avian Brood Parasites

Hosts of avian brood parasites are under intense selective pressure to prevent or reduce the cost of parasitism. Many have evolved refined egg discrimination abilities, which can select for eggshell mimicry in their parasite. A classic assumption underlying these coevolutionary dynamics is that host egg recognition depends on the perceivable difference between their own eggs and those of their parasite. Over the past two decades, the receptor noise-limited (RNL) model has contributed to our understanding of these coevolutionary interactions by providing researchers a method to predict a host’s ability to discriminate a parasite’s egg from its own. Recent research has shown that some hosts are more likely to reject brown eggs than blue eggs, regardless of the perceived differences to their own. Such responses suggest that host egg recognition may be due to perceptual or cognitive processes not currently predictable by the RNL model. In this perspective, we discuss the potential value of using the RNL model as a null model to explore alternative perceptual processes and higher-order cognitive processes that could explain how and why some hosts make seemingly counter-intuitive decisions. Further, we outline experiments that should be fruitful for determining the perceptual and cognitive processing used by hosts for egg recognition tasks.

Pressure for rapid and accurate mate recognition promotes avian-perceived plumage sexual dichromatism in true thrushes (genus: Turdus)

Ecological conditions limiting the time to find a compatible mate or increasing the difficulty in doing so likely promote the evolution of traits used for species and mate recognition. Here, we tested this recognition hypothesis for promoting plumage sexual dichromatism in the true thrushes (Turdus), a large and diverse genus of passerine birds. We used receptor-noise limited models of avian vision to quantify avian-perceived chromatic and achromatic visual contrasts between male and female plumage patches and tested the influence of breeding season length, spatial distribution, and sympatry with other Turdus species on plumage dichromatism. As predicted, we found that 1) true thrush species with migratory behaviour have greater plumage sexual dichromatism than non-migratory species, 2) species with longer breeding seasons have less plumage sexual dichromatism, and 3) the number of Turdus thrush species breeding in sympatry is associated with more plumage sexual dichromatism. These results suggest that social recognition systems, including species and mate recognition, play a prominent role in the evolution of thrush plumage sexual dichromatism.

Does conspicuousness scale linearly with colour distance? A test using reef fish

To be effective, animal colour signals must attract attention—and therefore need to be conspicuous. To understand the signal function, it is useful to evaluate their conspicuousness to relevant viewers under various environmental conditions, including when visual scenes are cluttered by objects of varying colour. A widely used metric of colour difference (Δ S ) is based on the receptor noise limited (RNL) model, which was originally proposed to determine when two similar colours appear different from one another, termed the discrimination threshold (or just noticeable difference). Estimates of the perceptual distances between colours that exceed this threshold—termed ‘suprathreshold’ colour differences—often assume that a colour's conspicuousness scales linearly with colour distance, and that this scale is independent of the direction in colour space. Currently, there is little behavioural evidence to support these assumptions. This study evaluated the relationship between Δ S and conspicuousness in suprathreshold colours using an Ishihara-style test with a coral reef fish, Rhinecanthus aculeatus . As our measure of conspicuousness, we tested whether fish, when presented with two colourful targets, preferred to peck at the one with a greater Δ S ­ from the average distractor colour. We found the relationship between Δ S and conspicuousness followed­­ a sigmoidal function, with high Δ S colours perceived as equally conspicuous. We found that the relationship between Δ S and conspicuousness varied across colour space (i.e. for different hues). The sigmoidal detectability curve was little affected by colour variation in the background or when colour distance was calculated using a model that does not incorporate receptor noise. These results suggest that the RNL model may provide accurate estimates for perceptual distance for small suprathreshold distance colours, even in complex viewing environments, but must be used with caution with perceptual distances exceeding­ ­10 Δ S .

Colour vision and information theory: the receptor noise-limited model implies optimal colour discrimination by opponent channels

In order to interpret animal behaviour we need to understand how they see the world. As colour discrimination is almost impossible to test directly in animals, it is important to develop theoretical models based in the properties of visual systems. One of the most successful is the receptor noise-limited (RNL) model, which depends only on the level of noise in photoreceptors and opponent mechanisms. Here optimal colour discrimination properties are obtained using information theoretical tools, for the early stages of visual systems with and without colour opponent mechanisms. For most biologically relevant conditions the optimal discrimination function of an ideal observer coincides with the one obtained with the RNL model. Many variants of the model can be cast into the same framework, which permits meaningful comparisons across species. For example, it is shown that the presence of opponency seems to be the preferred hypothesis for bees, but not for budgerigars. Since this is a consequence of the presence of oil droplets, this could also be true for most other species of birds.

Quantitative Colour Pattern Analysis (QCPA): A Comprehensive Framework for the Analysis of Colour Patterns in Nature

To understand the function of colour signals in nature, we require robust quantitative analytical frameworks to enable us to estimate how animal and plant colour patterns appear against their natural background as viewed by ecologically relevant species. Due to the quantitative limitations of existing methods, colour and pattern are rarely analysed in conjunction with one another, despite a large body of literature and decades of research on the importance of spatiochromatic colour pattern analyses. Furthermore, key physiological limitations of animal visual systems such as spatial acuity, spectral sensitivities, photoreceptor abundances and receptor noise levels are rarely considered together in colour pattern analyses.Here, we present a novel analytical framework, called the ‘Quantitative Colour Pattern Analysis’ (QCPA). We have overcome many quantitative and qualitative limitations of existing colour pattern analyses by combining calibrated digital photography and visual modelling. We have integrated and updated existing spatiochromatic colour pattern analyses, including adjacency, visual contrast and boundary strength analysis, to be implemented using calibrated digital photography through the ‘Multispectral Image Analysis and Calibration’ (MICA) Toolbox.This combination of calibrated photography and spatiochromatic colour pattern analyses is enabled by the inclusion of psychophysical colour and luminance discrimination thresholds for image segmentation, which we call ‘Receptor Noise Limited Clustering’, used here for the first time. Furthermore, QCPA provides a novel psycho-physiological approach to the modelling of spatial acuity using convolution in the spatial or frequency domains, followed by ‘Receptor Noise Limited Ranked Filtering’ to eliminate intermediate edge artefacts and recover sharp boundaries following smoothing. We also present a new type of colour pattern analysis, the ‘Local Edge Intensity Analysis’ (LEIA) as well as a range of novel psycho-physiological approaches to the visualisation of spatiochromatic data.QCPA combines novel and existing pattern analysis frameworks into what we hope is a unified, user-friendly, free and open source toolbox and introduce a range of novel analytical and data-visualisation approaches. These analyses and tools have been seamlessly integrated into the MICA toolbox providing a dynamic and user-friendly workflow.QCPA is a framework for the empirical investigation of key theories underlying the design, function and evolution of colour patterns in nature. We believe that it is compatible with, but more thorough than, other existing colour pattern analyses.

A generalized equation for the calculation of receptor noise limited colour distances in n -chromatic visual systems

Researchers must assess similarities and differences in colour from an animal's eye view when investigating hypotheses in ecology, evolution and behaviour. Nervous systems generate colour perceptions by comparing the responses of different spectral classes of photoreceptor through colour opponent mechanisms, and the performance of these mechanisms is limited by photoreceptor noise. Accordingly, the receptor noise limited (RNL) colour distance model of Vorobyev and Osorio (Vorobyev & Osorio 1998 Proc. R. Soc. Lond. B 265 , 351–358 ( doi:10.1098/rspb.1998.0302 )) generates predictions about the discriminability of colours that agree with behavioural data, and consequently it has found wide application in studies of animal colour vision. Vorobyev and Osorio (1998) provide equations to calculate RNL colour distances for animals with di-, tri- and tetrachromatic vision, which is adequate for many species. However, researchers may sometimes wish to compute RNL colour distances for potentially more complex colour visual systems. Thus, we derive a simple, single formula for the computation of RNL distance between two measurements of colour, equivalent to the published di-, tri- and tetrachromatic equations of Vorobyev and Osorio (1998), and valid for colour visual systems with any number of types of noisy photoreceptors. This formula will allow the easy application of this important colour visual model across the fields of ecology, evolution and behaviour.