Quantifying camouflage and conspicuousness using visual salience

Using colour pattern edge contrast statistics to predict detection speed and success in triggerfish (Rhinecanthus aculeatus)

Edge detection is important for object detection and recognition. However, we do not know whether edge statistics accurately predict the detection of prey by potential predators. This is crucial given the growing availability of image analysis software and their application across non-human visual systems. Here, we investigated whether Boundary Strength Analysis (BSA), Local Edge Intensity Analysis (LEIA) and the Gabor edge disruption ratio (GabRat) could predict the speed and success with which triggerfish (Rhinecanthus aculeatus) detected patterned circular stimuli against a noisy visual background, in both chromatic and achromatic presentations. We found various statistically significant correlations between edge statistics and detection speed depending on treatment and viewing distance; however, individual pattern statistics only explained up to 2% of the variation in detection time, and up to 6% when considering edge statistics simultaneously. We also found changes in fish response over time. While highlighting the importance of spatial acuity and relevant viewing distances in the study of visual signals, our results demonstrate the importance of considering explained variation when interpreting colour pattern statistics in behavioural experiments. We emphasize the need for statistical approaches suitable for investigating task-specific predictive relationships and ecological effects when considering animal behaviour. This is particularly important given the ever-increasing dimensionality and size of datasets in the field of visual ecology.

The role of colour patterns for the recognition of flowers by bees

Bees discriminate between many different colours of flower petals, but it is not well understood how they perceive and learn patterns frequently found in flowers with colourful structures. We used multi-spectral imaging to explore chromatic cues in concentric flower patterns as they are seen through the low-resolution eyes of the honeybee. We find a diversity of colour combinations, which suggests that plants might exploit the sensory capabilities of pollinators, like bees, that learn colours easily. A consistent feature is that the surround of the pattern has a stronger chromatic contrast to the foliage background than the centre. This can potentially facilitate the fast identification of floral objects within colourful scenes when a foraging bee moves through a flower patch. In behavioural experiments we trained and tested bees with three types of concentric patterns. They recognized and discriminated patterns accurately in most tests, relying flexibly on both chromatic and spatial cues. Only rarely, depending on the training stimulus, chromatic cues determined their choices whilst pattern cues were ignored. The variability of floral designs and the bees' flexibility in recalling colour and spatial information suggest a role for colour vision in pattern processing. Implications for the signalling strategies of flowers are discussed.

This article is part of the theme issue ‘Understanding colour vision: molecular, physiological, neuronal and behavioural studies in arthropods’.

The Colours of Octopus: Using Spectral Data to Measure Octopus Camouflage

No animal can so effectively camouflage in such a wide range of environments as the octopus. Thanks to their highly malleable skin, they are capable of adapting their body patterns to the brightness and texture of their immediate environment, and they often seemingly match the colour of background objects. However, octopuses are colour-blind as their eyes have only one type of visual pigment. Therefore, chromatophores in their skin are likely to respond to changes in brightness, not chromaticity. To determine whether octopuses actually match background colours, we used a SpectraScan® PR-655 spectroradiometer to measure the reflectance spectra of Octopus tetricus skin in captivity. The spectra were compared with those of green algae, brown algae, and sponges—all of these being colourful objects commonly found in the octopus’s natural environment. Even though we show that octopuses change both lightness and chromaticity, allowing them to potentially camouflage in a wide range of backgrounds in an effective manner, the overall octopus colours did not reach the same level of saturation compared to some background objects. Spectra were then modelled under the visual systems of four potential octopus predators: one dichromatic fish (Heller’s barracuda), two trichromatic fish (blue-spotted stingray and two-spotted red snapper), and one tetrachromatic bird (wedge-tailed shearwater). We show that octopuses are able to match certain background colours for some visual systems. How a colour-blind animal is capable of colour-matching is still unknown.

Camouflaged Nests of Mischocyttarus mirificus (Hymenoptera, Vespidae)

Social wasps present various architectural patterns for their nests, which may differ in shape, size, color, and material used in construction. The distribution pattern of comb cells presented by Mischocyttarus mirificus (Zikán, 1935) is vertical with a single cell of width, resulting in a filiform shape that camouflages in the middle of the substrate. There are few studies regarding this architectural pattern for social wasps and their role in camouflage, and this study aims to detail the nesting habits of this species. In total, 40 colonies were analyzed in their natural habitat and six were dissected in the laboratory. Aspects about the construction of the nests and nesting environment have been described. A test was carried out with nest photographs, to quantify their camouflage percentage within the nesting substrate. The colonies were found mainly in riparian forests where there were elements in the environment that favored their camouflage. According to the nest photograph analysis, their camouflage levels can vary according to the position from which the photograph is taken. It is evident that M. mirificus founders select sites where they can camouflage their colonies, and this gives them advantages in exploring a new environment.

Cascade and Fusion: A Deep Learning Approach for Camouflaged Object Sensing

The demand for the sensor-based detection of camouflage objects widely exists in biological research, remote sensing, and military applications. However, the performance of traditional object detection algorithms is limited, as they are incapable of extracting informative parts from low signal-to-noise ratio features. To address this problem, we propose Camouflaged Object Detection with Cascade and Feedback Fusion (CODCEF), a deep learning framework based on an RGB optical sensor that leverages a cascaded structure with Feedback Partial Decoders (FPD) instead of a traditional encoder–decoder structure. Through a selective fusion strategy and feedback loop, FPD reduces the loss of information and the interference of noises in the process of feature interweaving. Furthermore, we introduce Pixel Perception Fusion (PPF) loss, which aims to pay more attention to local pixels that might become the edges of an object. Experimental results on an edge device show that CODCEF achieved competitive results compared with 10 state-of-the-art methods.

Neoptile feathers contribute to outline concealment of precocial chicks

Camouflage is a widespread strategy to increase survival. The cryptic plumage colouration of precocial chicks improves camouflage often through disruptive colouration. Here, we examine whether and how fringed neoptile feathers conceal the outline of chicks. We first conducted a digital experiment to test two potential mechanisms for outline concealment through appendages: (1) reduction of edge intensity and (2) luminance transition. Local Edge Intensity Analysis showed that appendages decreased edge intensity whereas a mean luminance comparison revealed that the appendages created an intermediate transition zone to conceal the object's outline. For edge intensity, the outline diffusion was strongest for a vision system with low spatial acuity, which is characteristic of many mammalian chick predators. We then analysed photographs of young snowy plover (Charadrius nivosus) chicks to examine whether feathers increase outline concealment in a natural setting. Consistent with better camouflage, the outline of digitally cropped chicks with protruding feathers showed lower edge intensities than the outline of chicks without those feathers. However, the observed mean luminance changes did not indicate better concealment. Taken together, our results suggest that thin skin appendages such as neoptile feathers improve camouflage. As skin appendages are widespread, this mechanism may apply to many organisms.

Commercial Harvesting Has Driven the Evolution of Camouflage in an Alpine Plant

Color in nature mediates numerous among and within species interactions,¹ and anthropogenic impacts have long had major influences on the color evolution of wild animals.² An under-explored area is commercial harvesting, which in animals can exert a strong selection pressure on various traits, sometimes greater even than natural selection or other human activities.^3,4 Natural populations of plants that are used by humans have likely also suffered strong pressure from harvesting, yet the potential for evolutionary change induced by humans has received surprisingly little attention.⁵ Here, we show that the leaf coloration of a herb used in traditional Chinese medicine (Fritillaria delavayi) varies among populations, with leaves matching their local backgrounds most closely. The degree of background matching correlates with estimates of harvest pressure, with plants being more cryptic in heavily collected populations. In a human search experiment, the time it took participants to find plants was greatly influenced by target concealment. These results point to humans as driving the evolution of camouflage in populations of this species through commercial harvesting, changing the phenotype of wild plants in an unexpected and dramatic way.

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.

How conspicuous are peacock eyespots and other colorful feathers in the eyes of mammalian predators?

Colorful feathers have long been assumed to be conspicuous to predators, and hence likely to incur costs due to enhanced predation risk. However, many mammals that prey on birds have dichromatic visual systems with only two types of color-sensitive visual receptors, rather than the three and four photoreceptors characteristic of humans and most birds, respectively. Here, we use a combination of multispectral imaging, reflectance spectroscopy, color vision modelling and visual texture analysis to compare the visual signals available to conspecifics and to mammalian predators from multicolored feathers from the Indian peacock (Pavo cristatus), as well as red and yellow parrot feathers. We also model the effects of distance-dependent blurring due to visual acuity. When viewed by birds against green vegetation, most of the feathers studied are estimated to have color and brightness contrasts similar to values previously found for ripe fruit. On the other hand, for dichromat mammalian predators, visual contrasts for these feathers were only weakly detectable and often below detection thresholds for typical viewing distances. We also show that for dichromat mammal vision models, the peacock's train has below-detection threshold color and brightness contrasts and visual textures that match various foliage backgrounds. These findings are consistent with many feathers of similar hue to those studied here being inconspicuous, and in some cases potentially cryptic, in the eyes of common mammalian predators of adult birds. Given that birds perform many conspicuous motions and behaviors, this study suggests that mammalian predators are more likely to use other sensory modalities (e.g., motion detection, hearing, and olfaction), rather than color vision, to detect avian prey. This suggests new directions for future behavioral studies and emphasizes the importance of understanding the influence of the sensory ecology of predators in the evolution of animal coloration.

Discrete or indiscrete? Redefining the colour polymorphism of the land snail Cepaea nemoralis

Biologists have long tried to describe and name the different phenotypes that make up the shell polymorphism of the land snail Cepaea nemoralis. Traditionally, the view is that the ground colour of the shell is one of a few major colour classes, either yellow, pink or brown, but in practise it is frequently difficult to distinguish the colours, and define different shades of the same colour. To understand whether colour variation is in reality continuous, and to investigate how the variation may be perceived by an avian predator, we applied psychophysical models of colour vision to shell reflectance measures. We found that both achromatic and chromatic variation are indiscrete in Cepaea nemoralis, being continuously distributed over many perceptual units. Nonetheless, clustering analysis based on the density of the distribution did reveal three groups, roughly corresponding to human-perceived yellow, pink and brown shells. We also found large-scale geographic variation in the frequency of these groups across Europe, and some covariance between shell colour and banding patterns. Although further studies are necessary, the observation of continuous variation in colour is intriguing because the traditional theory is that the underlying supergene that determines colour has evolved to prevent phenotypes from “dissolving” into continuous trait distributions. The findings thus have significance for understanding the Cepaea polymorphism, and the nature of the selection that acts upon it, as well as more generally highlighting the need to measure colour objectively in other systems.