Author(s): Maia, Rafael; Gruson, Hugo; Endler, John; White, Thomas | Abstract: Abstract Biological colouration presents a canvas for the study of ecological and evolutionary processes. Enduring interest in colour-based phenotypes has driven, and been driven by, improved techniques for quantifying colour patterns in ever-more relevant ways, yet the need for flexible, open frameworks for data processing and analysis persists. Here we introduce pavo 2 , the latest iteration of the R package pavo . This release represents the extensive refinement and expansion of existing methods, as well as a suite of new tools for the cohesive analysis of the spectral and (now) spatial structure of colour patterns and perception. At its core, the package retains a broad focus on (a) the organisation and processing of spectral and spatial data, and tools for the alternating (b) visualisation, and (c) analysis of data. Significantly, pavo 2 introduces image-analysis capabilities, providing a cohesive workflow for the comprehensive analysis of colour patterns. We demonstrate the utility of pavo with a brief example centred on mimicry in Heliconius butterflies. Drawing on visual modelling, adjacency, and boundary strength analyses, we show that the combined spectral (colour and luminance) and spatial (pattern element distribution and boundary salience) features of putative models and mimics are closely aligned. pavo 2 offers a flexible and reproducible environment for the analysis of colour, with renewed potential to assist researchers in answering fundamental questions in sensory ecology and evolution.

pavo 2: New tools for the spectral and spatial analysis of colour in r

1. 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 spatio‐chromatic 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. 2. 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 spatio‐chromatic 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. 3. This combination of calibrated photography and spatio‐chromatic 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’ as well as a range of novel psycho‐physiological approaches to the visualization of spatio‐chromatic data. 4. QCPA combines novel and existing pattern analysis frameworks into what we hope is a unified, free and open source toolbox and introduces a range of novel analytical and data‐visualization approaches. These analyses and tools have been seamlessly integrated into the MICA toolbox providing a dynamic and user‐friendly workflow.

https://besjournals.onlinelibrary.wiley.com/doi/epdf/10.1111/2041-210X.13328

Quantitative Colour Pattern Analysis (QCPA): A comprehensive framework for the analysis of colour patterns in nature

Colors often appear to differ in arbitrary ways among related species. However, a fraction of color diversity may be explained because some signals are more easily perceived in one environment rather than another. Models show that not only signals but also the perception of signals should regularly evolve in response to different environments, whether these primarily involve detection of conspecifics or detection of predators and prey. Thus, a deeper understanding of how perception of color correlates with environmental attributes should help generate more predictive models of color divergence. Here, I briefly review our understanding of color vision in vertebrates. Then I focus on opsin spectral tuning and opsin expression, two traits involved in color perception that have become amenable to study. I ask how opsin tuning is correlated with ecological differences, notably the light environment, and how this potentially affects perception of conspecific colors. Although opsin tuning appears to evolve slowly, opsin expression levels are more evolutionarily labile but have been difficult to connect to color perception. The challenge going forward will be to identify how physiological differences involved in color vision, such as opsin expression levels, translate into perceptual differences, the selection pressures that have driven those differences, and ultimately how this may drive evolution of conspecific colors.

Sensory Drive, Color, and Color Vision.

Most of our current understanding on colour discrimination by animal observers is built on models. These typically set strict limits on the capacity of an animal to discriminate between colour stimuli imposed by physiological characteristics of the visual system and different assumptions about the underlying mechanisms of colour processing by the brain. Such physiologically driven models were not designed to accommodate sigmoidal-type discrimination functions as those observed in recent behavioural experiments. Unfortunately, many of the fundamental assumptions on which commonly used colour models are based have been tested against empirical data for very few species and many colour vision studies solely rely on physiological measurements of these species for predicting colour discrimination processes. Here, we test the assumption of a universal principle of colour discrimination only mediated by physiological parameters using behavioural data from four closely related hymenopteran species, considering two frequently used models. Results indicate that there is not a unique function describing colour discrimination by closely related bee species, and that this process is independent of specific model assumptions; in fact, different models produce comparable results for specific test species if calibrated against behavioural data.

The path to colour discrimination is S-shaped: behaviour determines the interpretation of colour models.

Author(s): Endler, John; Cole, Gemma; Kranz, Alexandrea | Abstract: Abstract Colour patterns are used by many species to make decisions that ultimately affect their Darwinian fitness. Colour patterns consist of a mosaic of patches that differ in geometry and visual properties. Although traditionally pattern geometry and colour patch visual properties are analysed separately, these components are likely to work together as a functional unit. Despite this, the combined effect of patch visual properties, patch geometry, and the effects of the patch boundaries on animal visual systems, behaviour and fitness are relatively unexplored. Here we describe Boundary Strength Analysis (BSA), a novel way to combine the geometry of the edges (boundaries among the patch classes) with the receptor noise estimate ( ΔS ) of the intensity of the edges. The method is based upon known properties of vertebrate and invertebrate retinas. The mean and SD of ΔS (m ΔS , s ΔS ) of a colour pattern can be obtained by weighting each edge class ΔS by its length, separately for chromatic and achromatic ΔS . This assumes those colour patterns, or parts of the patterns used in signalling, with larger m ΔS and s ΔS are more stimulating and hence more salient to the viewers. BSA can be used to examine both colour patterns and visual backgrounds. BSA was successful in assessing the estimated conspicuousness of colour pattern variants in two species, guppies ( Poecilia reticulata ) and Gouldian finches ( Erythrura gouldiae ), both polymorphic for patch colour, luminance and geometry. The pattern difference between chromatic and achromatic edges in both species reveals the possibility that chromatic and achromatic edges could function differently. BSA can be applied to any colour pattern used in intraspecific and interspecific behaviour. Seven predictions and four questions about colour patterns are presented.

https://besjournals.onlinelibrary.wiley.com/doi/pdf/10.1111/2041-210X.13073

Boundary strength analysis: Combining colour pattern geometry and coloured patch visual properties for use in predicting behaviour and fitness

In the study of the evolution of animal colors, the conspicuousness of a pair of colors (e.g., stimulus vs. background) is often modeled by determining the distance between them in perceptual color space. For similar colors, receptor noise models have been demonstrated to be an effective way to estimate discrimination thresholds. However, the best way to quantify conspicuousness of color pairs that are distant in perceptual space is not widely agreed upon. In experiments where an animal is presented with different colors that it can easily discriminate, its response may be strongly influenced by the biological significance of a color, in addition to its conspicuousness, a phenomenon known as color categorization. This has made it difficult to test and confirm the validity of different models of perceptual distance. We tested the relative conspicuousness of different stimulus/background color combinations in the lizard Anolis sagrei using a visual attention reflex, which has been shown in earlier experiments to be less influenced by color categorization than other commonly used behavioral assays. We compared the results to predictions based on two different visual system-based models. The Euclidian distance between pairs of points plotted in a lizard chromaticity diagram effectively predicted the relative responses. A receptor noise model, in which color space distance was estimated in units of “just noticeable difference,” yielded a similarly accurate prediction of the results. We concluded that for studies of color signal evolution, either of these methods may be effectively employed to make behaviorally-relevant predictions of perceptual distance among colors that are widely separated in visual space.

Elizabeth Almonte

Papers

Perceptual distance between colored stimuli in the lizard Anolis sagrei : comparing visual system models to empirical results