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.

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 (ΔS) 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 ΔS 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 ΔS - from the average distractor colour. We found the relationship between ΔS and conspicuousness followed-- a sigmoidal function, with high ΔS colours perceived as equally conspicuous. We found that the relationship between ΔS 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 ΔS.

Colour vision mediates ecologically relevant tasks for many animals, such as mate choice, foraging and predator avoidance. However, our understanding of animal colour perception is largely derived from human psychophysics, and behavioural tests of non-human animals are required to understand how colour signals are perceived. Here, we introduce a novel test of colour vision in animals inspired by the Ishihara colour charts, which are widely used to identify human colour deficiencies. In our method, distractor dots have a fixed chromaticity (hue and saturation) but vary in luminance. Animals can be trained to find single target dots that differ from distractor dots in chromaticity. We provide MATLAB code for creating these stimuli, which can be modified for use with different animals. We demonstrate the success of this method with triggerfish, Rhinecanthus aculeatus, which quickly learnt to select target dots that differed from distractor dots, and highlight behavioural parameters that can be measured, including success of finding the target dot, time to detection and error rate. We calculated discrimination thresholds by testing whether target colours that were of increasing colour distances (ΔS) from distractor dots could be detected, and calculated discrimination thresholds in different directions of colour space. At least for some colours, thresholds indicated better discrimination than expected from the receptor noise limited (RNL) model assuming 5% Weber fraction for the long-wavelength cone. This methodology could be used with other animals to address questions such as luminance thresholds, sensory bias, effects of sensory noise, colour categorization and saliency.

Mimicry of warning signals is common, and can be mutualistic when mimetic species harbour equal levels of defence (Müllerian), or parasitic when mimics are undefended but still gain protection from their resemblance to the model (Batesian). However, whether chemically defended mimics should be similar in terms of toxicity (i.e. causing damage to the consumer) and/or unpalatability (i.e. distasteful to consumer) is unclear and in many studies remains undifferentiated. In this study, we investigated the evolution of visual signals and chemical defences in a putative mimicry ring of nudibranch molluscs. First, we demonstrated that the appearance of a group of red spotted nudibranchs molluscs was similar from the perspective of potential fish predators using visual modelling and pattern analysis. Second, using phylogenetic reconstruction, we demonstrated that this colour pattern has evolved multiple times in distantly related individuals. Third, we showed that these nudibranchs contained different chemical profiles used for defensive purposes. Finally, we demonstrated that although levels of distastefulness towards Palaemon shrimp remained relatively constant between species, toxicity levels towards brine shrimp varied significantly. We highlight the need to disentangle toxicity and taste when considering chemical defences in aposematic and mimetic species, and discuss the implications for aposematic and mimicry signal evolution.