Reproducible research in the study of biological coloration

Automated workflows using Quantitative Colour Pattern Analysis (QCPA): a guide to batch processing and downstream data analysis

Animal and plant colouration presents a striking dimension of phenotypic variation, the study of which has driven general advances in ecology, evolution, and animal behaviour. Quantitative Colour Pattern Analysis (QCPA) is a dynamic framework for analysing colour patterns through the eyes of non-human observers. However, its extensive array of user-defined image processing and analysis tools means image analysis is often time-consuming. This hinders the full use of analytical power provided by QCPA and its application to large datasets. Here, we offer a robust and comprehensive batch script, allowing users to automate many QCPA workflows. We also provide a complimentary set of useful R scripts for downstream data extraction and analysis. The presented batch processing extension will empower users to further utilise the analytical power of QCPA and facilitate the development of customised semi-automated workflows. Such quantitatively scaled workflows are crucial for exploring colour pattern spaces and developing ever-richer frameworks for analysing organismal colouration accounting for visual perception in animals other than humans. These advances will, in turn, facilitate testing hypotheses on the function and evolution of vision and signals at quantitative and qualitative scales, which are otherwise computationally unfeasible.

Supplementary Information

The online version contains supplementary material available at 10.1007/s10682-024-10291-7.

Analysing biological colour patterns from digital images: An introduction to the current toolbox

Understanding the numerous roles that colouration serves in the natural world has remained a central focus in many evolutionary and ecological studies. However, to accurately characterise and then compare colours or patterns among individuals or species has been historically challenging. In recent years, there have been a myriad of new resources developed that allow researchers to characterise biological colours and patterns, specifically from digital imagery. However, each resource has its own strengths and weaknesses, answers a specific question and requires a detailed understanding of how it functions to be used properly. These nuances can make navigating this emerging field rather difficult. Herein, we evaluate several new techniques for analysing biological colouration, with a specific focus on digital images. First, we introduce fundamental background knowledge about light and perception to be considered when designing and implementing a study of colouration. We then show how numerous modifications can be made to images to ensure consistent formatting prior to analysis. After, we describe many of the new image analysis approaches and their respective functions, highlighting the type of research questions that they can address. We demonstrate how these various techniques can be brought together to examine novel research questions and test specific hypotheses. Finally, we outline potential future directions in colour pattern studies. Our goal is to provide a starting point and pathway for researchers wanting to study biological colour patterns from digital imagery.

Context-dependent coloration of prey and predator decision making in contrasting light environments

A big question in behavioral ecology is what drives diversity of color signals. One possible explanation is that environmental conditions, such as light environment, may alter visual signaling of prey, which could affect predator decision-making. Here, we tested the context-dependent predator selection on prey coloration. In the first experiment, we tested detectability of artificial visual stimuli to blue tits (Cyanistes caeruleus) by manipulating stimulus luminance and chromatic context of the background. We expected the presence of the chromatic context to facilitate faster target detection. As expected, blue tits found targets on chromatic yellow background faster than on achromatic grey background whereas in the latter, targets were found with smaller contrast differences to the background. In the second experiment, we tested the effect of two light environments on the survival of aposematic, color polymorphic wood tiger moth (Arctia plantaginis). As luminance contrast should be more detectable than chromatic contrast in low light intensities, we expected birds, if they find the moths aversive, to avoid the white morph which is more conspicuous than the yellow morph in low light (and vice versa in bright light). Alternatively, birds may attack first moths that are more detectable. We found birds to attack yellow moths first in low light conditions, whereas white moths were attacked first more frequently in bright light conditions. Our results show that light environments affect predator foraging decisions, which may facilitate context-dependent selection on visual signals and diversity of prey phenotypes in the wild.

Divergent Responses of Floral Traits of Lonicera nervosa to Altitudinal Gradients at the Eastern Margin of Hengduan Mountains

Understanding phenotypic responses is crucial for predicting and managing the effects of environmental change on native species. Color and display size are typically used to evaluate the utilization value of ornamental plants, which are also important ornamental characters of Lonicera nervosa Maxim. (L. nervosa). However, there is limited documentation of its floral environmental adaptation. The environmental conditions for the development of an organism changes with altitudinal variation. The aim of this research was to find flower trait variability maintenance and the tradeoff among the organs in five different populations of L. nervosa growing at distinct altitudes. We investigated the distribution patterns of floral color, floral display, and biomass tradeoff along a 700-m altitude gradient from 2,950 to 3,650 m. One-way ANOVA analysis was performed to assess the variability of flower traits and floral color across different altitudes. Moreover, correlations and tradeoffs between flowers and vegetative organs were also observed at different altitude ranges. The results indicated that L. nervosa flowers had a strong adaptability along the elevation and divergent altitude-range-specific patterns, which was divided by an altitude breakpoint at around 3,300 m. Below 3,300 m, petal lightness (petal L) decreased, but total floral display area (TFDA), individual floral dry mass (IFDM), and total floral dry mass (TFDM) increased with an increase in altitude. Whereas, above 3,300 m no significant difference was observed in petal L, TFDA, IFDM, and TFDM decreased slightly with an increase in altitude. The responsibility for the selection on floral color at a lower altitude was stronger than that at a higher altitude, while the selection agents on floral biomass had significant effects within the entire altitude range. However, the effects on floral biomass were opposite on both sides of 3,300 m. Thus, floral trait and floral color can be useful indicators for the domestication of horticultural plants and help to evaluate and initiate management and conservation actions.

A comparison of animal color measurements using a commercially available digital color sensor and photograph analysis

An animal's pelage, feather, or skin color can serve a variety of functions, so it is important to have multiple standardized methods for measuring color. One of the most common and reliable methods for measuring animal coloration is the use of standardized digital photographs of animals. New technology in the form of a commercially available handheld digital color sensor could provide an alternative to photography-based animal color measurements. To determine whether a digital color sensor could be used to measure animal coloration, we tested the ability of a digital color sensor to measure coloration of mammalian, avian, and lepidopteran museums specimens. We compared results from the sensor to measurements taken using traditional photography methods. Our study yielded significant differences between photography-based and digital color sensor measurements of brightness (light to dark) and colors along the green to red spectrum. There was no difference between photographs and the digital color sensor measurements for colors along the blue to yellow spectrum. The average difference in recorded color (ΔE) by the 2 methods was above the threshold at which humans can perceive a difference. There were significant correlations between the sensor and photographs for all measurements indicating that the sensor is an effective animal coloration measuring tool. However, the sensor's small aperture and narrow light spectrum range designed for human-vision limit its value for ecological research. We discuss the conditions in which a digital color sensor can be an effective tool for measuring animal coloration in both laboratory settings and in the field.

Within-individual phenotypic plasticity in flowers fosters pollination niche shift

Phenotypic plasticity, the ability of a genotype of producing different phenotypes when exposed to different environments, may impact ecological interactions. We study here how within-individual plasticity in Moricandia arvensis flowers modifies its pollination niche. During spring, this plant produces large, cross-shaped, UV-reflecting lilac flowers attracting mostly long-tongued large bees. However, unlike most co-occurring species, M. arvensis keeps flowering during the hot, dry summer due to its plasticity in key vegetative traits. Changes in temperature and photoperiod in summer trigger changes in gene expression and the production of small, rounded, UV-absorbing white flowers that attract a different assemblage of generalist pollinators. This shift in pollination niche potentially allows successful reproduction in harsh conditions, facilitating M. arvensis to face anthropogenic perturbations and climate change.

Plastic sexual ornaments: Assessing temperature effects on color metrics in a color-changing reptile

Conspicuous coloration is an important subject in social communication and animal behavior, and it can provide valuable insight into the role of visual signals in social selection. However, animal coloration can be plastic and affected by abiotic factors such as temperature, making its quantification problematic. In such cases, careful consideration is required so that metric choices are consistent across environments and least sensitive to abiotic factors. A detailed assessment of plastic trait in response to environmental conditions could help identify more robust methods for quantifying color. Temperature affects sexual ornamentation of eastern fence lizards, Sceloporus undulatus, with ventral coloration shifting from green to blue hues as temperatures rise, making the calculation of saturation (color purity) difficult under conditions where temperatures vary. We aimed to characterize how abiotic factors influence phenotypic expression and to identify a metric for quantifying animal color that is either independent from temperature (ideally) or best conserves individual's ranks. We compared the rates of change in saturation across two temperature treatments using seven metrics: three that are based on fixed spectral ranges (with two of them designed by us specifically for this system) and three that track the expressed hue (with one of them designed by us to circumvent spurious results in unornamented individuals). We also applied a lizard visual sensitivity model to understand how temperature-induced color changes may be perceived by conspecifics. We show that the rate of change in saturation between two temperatures is inconsistent across individuals, increasing at a higher rate in individuals with higher baseline saturation at lower temperatures. In addition, the relative color rank of individuals in a population varies with the temperature standardized by the investigator, but more so for some metrics than others. While we were unable to completely eliminate the effect of temperature, current tools for quantifying color allowed us to use spectral data to estimate saturation in a variety of ways and to largely preserve saturation ranks of individuals across temperatures while avoiding erroneous color scores. We describe our approaches and suggest best-practices for quantifying and interpreting color, particularly in cases where color changes in response to environmental factors.

Accurate device-independent colorimetric measurements using smartphones

Smartphones provide an ideal platform for colorimetric measurements due to their low cost, portability and image quality. As with any imaging-based colorimetry system, ambient light and device variations introduce error which must be dealt with. We propose a novel processing method consisting of a one-time calibration stage to account for inter-phone variations, and an innovative use of ambient light subtraction with image pairs to account for variation in ambient light. Data collection is kept very simple, making it particularly useful for use in the field, since nothing additional is required in the images. Ambient subtraction is first demonstrated for a range of colors and phones (Samsung S8 and LG Nexus 5X), and the Subtracted Signal to Noise Ratio (SSNR) is defined as a metric for assessing whether an image pair is appropriate at the time of image capture. The experimentally determined SSNR threshold below which to suggest retaking the images is 3.4. The classification accuracy for results using the proposed calibration pipeline is then compared to the simplest image metadata-based alternative and is found to be greatly superior. Finally, a custom colorcard is shown to improve the accuracy of device-independent results for known smaller ranges of colors over a standard colorcard, making this a possible application-specific modification to the overall processing pipeline.

Polyphenism of visual and chemical secondary sexually-selected wing traits in the butterfly Bicyclus anynana: How different is the intermediate phenotype?

Polyphenism is a type of phenotypic plasticity supposedly adaptive to drastic and recurrent changes in the environment such as seasonal alternation in temperate and tropical regions. The butterfly Bicyclus anynana shows polyphenism with well-described wet and dry seasonal forms in sub-Saharan Africa, displaying striking morphological, physiological and behavioural differences in response to higher or lower developmental temperatures. During the seasonal transition in the wild, the intermediate phenotype co-occurs with wet and dry phenotypes. In this study, we aimed to characterize the secondary sexually-selected wing traits of the intermediate form to infer its potential fitness compared to wet and dry phenotypes. Among the previously described wing morphological traits, we first showed that the area of the fifth eyespot on the ventral hindwing is the most discriminant trait to identify wet, dry and intermediate phenotypes in both sexes. Second, we characterized the intermediate form for two secondary sexually-selected wing traits: the area and UV reflectance of the dorsal forewing pupil and the composition of the male sex pheromone. We showed that values of these two traits are often between those of the wet and dry phenotypes. Third, we observed increasing male sex pheromone production in ageing dry and wet phenotypes. Our results contrast with previous reports of values for sexually-selected traits in wet and dry seasonal forms, which might be explained by differences in rearing conditions or sample size effects among studies. Wet, dry and intermediate phenotypes display redundant sexually dimorphic traits, including sexually-selected traits that can inform about their developmental temperature in sexual interactions.

Artificial intelligence reveals environmental constraints on colour diversity in insects

Explaining colour variation among animals at broad geographic scales remains challenging. Here we demonstrate how deep learning-a form of artificial intelligence-can reveal subtle but robust patterns of colour feature variation along an ecological gradient, as well as help identify the underlying mechanisms generating this biogeographic pattern. Using over 20,000 images with precise GPS locality information belonging to nearly 2,000 moth species from Taiwan, our deep learning model generates a 2048-dimension feature vector that accurately predicts each species' mean elevation based on colour and shape features. Using this multidimensional feature vector, we find that within-assemblage image feature variation is smaller in high elevation assemblages. Structural equation modeling suggests that this reduced image feature diversity is likely the result of colder environments selecting for darker colouration, which limits the colour diversity of assemblages at high elevations. Ultimately, with the help of deep learning, we will be able to explore the endless forms of natural morphological variation at unpreceded depths.

Functional significance of the optical properties of flowers for visual signalling

BACKGROUND

Flower coloration is a key enabler for pollinator attraction. Floral visual signals comprise several components that are generated by specific anatomical structures and pigmentation, and often have different functions in pollinator attraction. Anatomical studies have advanced our understanding of the optical properties of flowers, and evidence from behavioural experiments has elucidated the biological relevance of different components of floral visual signals, but these two lines of research are often considered independently.

SCOPE

Here, we review current knowledge about different aspects of the floral visual signals, their anatomical and optical properties, and their functional significance in plant-pollinator visual signalling. We discuss common aspects, such as chromatic and achromatic contrast, hue, saturation and brightness, as well as less common types of visual signals, including gloss, fluorescence, polarization and iridescence in the context of salience of floral colour signals and their evolution, and highlight promising avenues for future research.

I see your false colours: how artificial stimuli appear to different animal viewers

The use of artificially coloured stimuli, especially to test hypotheses about sexual selection and anti-predator defence, has been common in behavioural ecology since the pioneering work of Tinbergen. To investigate the effects of colour on animal behaviour, many researchers use paints, markers and dyes to modify existing colours or to add colour to synthetic models. Because colour perception varies widely across species, it is critical to account for the signal receiver's vision when performing colour manipulations. To explore this, we applied 26 typical coloration products to different types of avian feathers. Next, we measured the artificially coloured feathers using two complementary techniques-spectrophotometry and digital ultraviolet--visible photography-and modelled their appearance to mammalian dichromats (ferret, dog), trichromats (honeybee, human) and avian tetrachromats (hummingbird, blue tit). Overall, artificial colours can have dramatic and sometimes unexpected effects on the reflectance properties of feathers, often differing based on feather type. The degree to which an artificial colour differs from the original colour greatly depends on an animal's visual system. 'White' paint to a human is not 'white' to a honeybee or blue tit. Based on our analysis, we offer practical guidelines for reducing the risk of introducing unintended effects when using artificial colours in behavioural experiments.

Color vision models: Some simulations, a general n-dimensional model, and the colourvision R package

The development of color vision models has allowed the appraisal of color vision independent of the human experience. These models are now widely used in ecology and evolution studies. However, in common scenarios of color measurement, color vision models may generate spurious results. Here I present a guide to color vision modeling (Chittka (1992, Journal of Comparative Physiology A, 170, 545) color hexagon, Endler & Mielke (2005, Journal Of The Linnean Society, 86, 405) model, and the linear and log-linear receptor noise limited models (Vorobyev & Osorio 1998, Proceedings of the Royal Society B, 265, 351; Vorobyev et al. 1998, Journal of Comparative Physiology A, 183, 621)) using a series of simulations, present a unified framework that extends and generalize current models, and provide an R package to facilitate the use of color vision models. When the specific requirements of each model are met, between-model results are qualitatively and quantitatively similar. However, under many common scenarios of color measurements, models may generate spurious values. For instance, models that log-transform data and use relative photoreceptor outputs are prone to generate spurious outputs when the stimulus photon catch is smaller than the background photon catch; and models may generate unrealistic predictions when the background is chromatic (e.g. leaf reflectance) and the stimulus is an achromatic low reflectance spectrum. Nonetheless, despite differences, all three models are founded on a similar set of assumptions. Based on that, I provide a new formulation that accommodates and extends models to any number of photoreceptor types, offers flexibility to build user-defined models, and allows users to easily adjust chromaticity diagram sizes to account for changes when using different number of photoreceptors.

Human colour in mate choice and competition

The colour of our skin and clothing affects how others perceive us and how we behave. Human skin colour varies conspicuously with genetic ancestry, but even subtle changes in skin colour due to diet, blood oxygenation and hormone levels influence social perceptions. In this review, we describe the theoretical and empirical frameworks in which human colour is researched. We explore how subtle skin colour differences relate to judgements of health and attractiveness. Also, because humans are one of the few organisms able to manipulate their apparent colour, we review how cosmetics and clothing are implicated in courtship and competition, both inside the laboratory and in the real world. Research on human colour is in its infancy compared with human psychophysics and colour research in non-human animals, and hence we present best-practice guidelines for methods and reporting, which we hope will improve the validity and reproducibility of studies on human coloration.This article is part of the themed issue 'Animal coloration: production, perception, function and application'.

Digital photography provides a fast, reliable, and noninvasive method to estimate anthocyanin pigment concentration in reproductive and vegetative plant tissues

Anthocyanin pigments have become a model trait for evolutionary ecology as they often provide adaptive benefits for plants. Anthocyanins have been traditionally quantified biochemically or more recently using spectral reflectance. However, both methods require destructive sampling and can be labor intensive and challenging with small samples. Recent advances in digital photography and image processing make it the method of choice for measuring color in the wild. Here, we use digital images as a quick, noninvasive method to estimate relative anthocyanin concentrations in species exhibiting color variation. Using a consumer‐level digital camera and a free image processing toolbox, we extracted RGB values from digital images to generate color indices. We tested petals, stems, pedicels, and calyces of six species, which contain different types of anthocyanin pigments and exhibit different pigmentation patterns. Color indices were assessed by their correlation to biochemically determined anthocyanin concentrations. For comparison, we also calculated color indices from spectral reflectance and tested the correlation with anthocyanin concentration. Indices perform differently depending on the nature of the color variation. For both digital images and spectral reflectance, the most accurate estimates of anthocyanin concentration emerge from anthocyanin content‐chroma ratio, anthocyanin content‐chroma basic, and strength of green indices. Color indices derived from both digital images and spectral reflectance strongly correlate with biochemically determined anthocyanin concentration; however, the estimates from digital images performed better than spectral reflectance in terms of r² and normalized root‐mean‐square error. This was particularly noticeable in a species with striped petals, but in the case of striped calyces, both methods showed a comparable relationship with anthocyanin concentration. Using digital images brings new opportunities to accurately quantify the anthocyanin concentrations in both floral and vegetative tissues. This method is efficient, completely noninvasive, applicable to both uniform and patterned color, and works with samples of any size.

Trait allometries generate super-honesty in Anolis dewlaps and may underlie sexual dimorphism

Whether or not sexually selected traits consistently exhibit positive allometry (i.e. are disproportionately large in larger individuals) is an ongoing debate. Multiple models and exceptions to this rule suggest that the underlying drivers of sexual trait allometry are nuanced. Here, we compare allometries of sexual and non-sexual traits of a species (Anolis aquaticus) within a well-studied lizard genus to test the competing hypotheses that sexual traits are, or are not, defined by positive allometry. We further consider the relationships of trait functions, which are relatively well understood in the genus Anolis, and allometry to identify potential drivers of allometric patterns. In particular, we explore how trait allometries interact to influence total organism function and generate sexual dimorphism. We quantified size (of targeted traits) and color of a sexual signal (the dewlap) in Anolis aquaticus in the field. The dewlap conveyed information relevant to intra-sexual combat and exhibited positive allometry. Overall, our results suggest that using single-trait allometries as indicators of past selection provides only an incomplete understanding of trait evolution. Although the function of positive allometry in some individual sexual signals (e.g. those conveying "super-honest" information) may be straightforward, we illustrate how scaling relationships interact synergistically to influence the function of phenotypes and propose avenues for future research.

Quantifying pigment cover to assess variation in animal colouration

The study of animal colouration addresses fundamental and applied aspects relevant to a wide range of fields, including behavioural ecology, environmental adaptation and visual ecology. Although a variety of methods are available to measure animal colours, only few focus on chromatophores (specialized cells containing pigments) and pigment migration. Here, we illustrate a freely available and user-friendly method to quantify pigment cover (PiC) with high precision and low effort using digital images, where the foreground (i.e. pigments in chromatophores) can be detected and separated from the background. Images of the brown shrimp, Crangon crangon, were used to compare PiC with the traditional Chromatophore Index (CI). Results indicate that PiC outcompetes CI for pigment detection and transparency measures in terms of speed, accuracy and precision. The proposed methodology provides researchers with a useful tool to answer essential physiological, behavioural and evolutionary questions on animal colouration in a wide range of species.

Nonindependence and sensitivity analyses in ecological and evolutionary meta-analyses

Meta-analysis is an important tool for synthesizing research on a variety of topics in ecology and evolution, including molecular ecology, but can be susceptible to nonindependence. Nonindependence can affect two major interrelated components of a meta-analysis: (i) the calculation of effect size statistics and (ii) the estimation of overall meta-analytic estimates and their uncertainty. While some solutions to nonindependence exist at the statistical analysis stages, there is little advice on what to do when complex analyses are not possible, or when studies with nonindependent experimental designs exist in the data. Here we argue that exploring the effects of procedural decisions in a meta-analysis (e.g. inclusion of different quality data, choice of effect size) and statistical assumptions (e.g. assuming no phylogenetic covariance) using sensitivity analyses are extremely important in assessing the impact of nonindependence. Sensitivity analyses can provide greater confidence in results and highlight important limitations of empirical work (e.g. impact of study design on overall effects). Despite their importance, sensitivity analyses are seldom applied to problems of nonindependence. To encourage better practice for dealing with nonindependence in meta-analytic studies, we present accessible examples demonstrating the impact that ignoring nonindependence can have on meta-analytic estimates. We also provide pragmatic solutions for dealing with nonindependent study designs, and for analysing dependent effect sizes. Additionally, we offer reporting guidelines that will facilitate disclosure of the sources of nonindependence in meta-analyses, leading to greater transparency and more robust conclusions.

Image calibration and analysis toolbox - a free software suite for objectively measuring reflectance, colour and pattern

Quantitative measurements of colour, pattern and morphology are vital to a growing range of disciplines. Digital cameras are readily available and already widely used for making these measurements, having numerous advantages over other techniques, such as spectrometry. However, off-the-shelf consumer cameras are designed to produce images for human viewing, meaning that their uncalibrated photographs cannot be used for making reliable, quantitative measurements. Many studies still fail to appreciate this, and of those scientists who are aware of such issues, many are hindered by a lack of usable tools for making objective measurements from photographs.We have developed an image processing toolbox that generates images that are linear with respect to radiance from the RAW files of numerous camera brands and can combine image channels from multispectral cameras, including additional ultraviolet photographs. Images are then normalised using one or more grey standards to control for lighting conditions. This enables objective measures of reflectance and colour using a wide range of consumer cameras. Furthermore, if the camera's spectral sensitivities are known, the software can convert images to correspond to the visual system (cone-catch values) of a wide range of animals, enabling human and non-human visual systems to be modelled. The toolbox also provides image analysis tools that can extract luminance (lightness), colour and pattern information. Furthermore, all processing is performed on 32-bit floating point images rather than commonly used 8-bit images. This increases precision and reduces the likelihood of data loss through rounding error or saturation of pixels, while also facilitating the measurement of objects with shiny or fluorescent properties.All cameras tested using this software were found to demonstrate a linear response within each image and across a range of exposure times. Cone-catch mapping functions were highly robust, converting images to several animal visual systems and yielding data that agreed closely with spectrometer-based estimates.Our imaging toolbox is freely available as an addition to the open source ImageJ software. We believe that it will considerably enhance the appropriate use of digital cameras across multiple areas of biology, in particular researchers aiming to quantify animal and plant visual signals.