Camouflage in a dynamic world

Cuthill, Innes C.; Matchette, Samuel R.; Scott‐Samuel, Nicholas E.

doi:10.1016/j.cobeha.2019.07.007

Cited by 41 publications

(45 citation statements)

References 59 publications

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“…There is also growing evidence, in relation to camouflage and concealment, to suggest that the visual noise of dynamic illumination, such as water caustics, could reduce the costs of organism movement (see [12][13][14][15]). This is analogous to the movement of background objects (e.g.…”

Section: Introductionmentioning

confidence: 99%

Underwater caustics disrupt prey detection by a reef fish

et al. 2020

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Natural habitats contain dynamic elements, such as varying local illumination. Can such features mitigate the salience of organism movement? Dynamic illumination is particularly prevalent in coral reefs, where patterns known as ‘water caustics’ play chaotically in the shallows. In behavioural experiments with a wild-caught reef fish, the Picasso triggerfish ( Rhinecanthus aculeatus ), we demonstrate that the presence of dynamic water caustics negatively affects the detection of moving prey items, as measured by attack latency, relative to static water caustic controls. Manipulating two further features of water caustics (sharpness and scale) implies that the masking effect should be most effective in shallow water: scenes with fine scale and sharp water caustics induce the longest attack latencies. Due to the direct impact upon foraging efficiency, we expect the presence of dynamic water caustics to influence decisions about habitat choice and foraging by wild prey and predators.

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Section: Introductionmentioning

confidence: 99%

Underwater caustics disrupt prey detection by a reef fish

et al. 2020

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“…QCPA could also be adapted to investigate moving patterns (e.g. Endler, ; Endler et al, ), given recent advances in the understanding of colour pattern functionality in the context of motion (Cuthill, Matchette, & Scott‐Samuel, ; Fleishman, ; Hughes, Troscianko, & Stevens, ; Murali, ; Nityananda et al, ; Ramos & Peters, ; Umeton, Tarawneh, Fezza, Read, & Rowe, ). There are types of visual information we have barely begun understanding, such as polarization vision, the use of fluorescence as well as their interaction with an animal's perception of colour and brightness (Foster et al, ; Marshall, Cortesi, de Busserolles, Siebeck, & Cheney, ; Marshall & Johnsen, ; Smithers, Roberts, & How, ).…”

Section: Discussionmentioning

confidence: 99%

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

et al. 2019

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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. 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 analyticalThis is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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“…Conversely, a stick insect on a contrasting background has readily detectable features, so its survival depends on a misclassification by a predator at the stage of whole-object recognition (Skelhorn et al, 2010b). Motion similar to the mimicked object reduces discriminability (Bian, Elgar & Peters, 2016;Cuthill et al, 2019); dissimilar motion enhances discriminability. In some cases, it is not a minimization of signal that is effective, but an increase in noise, such as the creation of false edges in disruptive coloration.…”

Section: Discussionmentioning

confidence: 99%

“…The fact that motion breaks camouflage is therefore a significant constraint on activity, and the trade‐off between the camouflage‐breaking costs of motion and the benefits of being able to move is a major factor determining which anti‐predator defences evolve (Edmunds, ; Ruxton et al ., ). There are, however, some mitigating factors (Cuthill, Matchette & Scott‐Samuel, ). Motion of background objects such as foliage (Ord et al ., ; Peters, Hemmi & Zeil, ; New & Peters, ) or rapidly changing illumination (Matchette, Cuthill & Scott‐Samuel, ) can both mask movement.…”

Section: Constraints On Camouflagementioning

confidence: 99%

Camouflage

2019

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Animal camouflage has long been used to illustrate the power of natural selection, and provides an excellent testbed for investigating the trade‐offs affecting the adaptive value of colour. However, the contemporary study of camouflage extends beyond evolutionary biology, co‐opting knowledge, theory and methods from sensory biology, perceptual and cognitive psychology, computational neuroscience and engineering. This is because camouflage is an adaptation to the perception and cognition of the species (one or more) from which concealment is sought. I review the different ways in which camouflage manipulates and deceives perceptual and cognitive mechanisms, identifying how, and where in the sequence of signal processing, strategies such as transparency, background matching, disruptive coloration, distraction marks, countershading and masquerade have their effects. As such, understanding how camouflage evolves and functions not only requires an understanding of animal sensation and cognition, it sheds light on perception in other species.

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Camouflage in a dynamic world

Cited by 41 publications

References 59 publications

Underwater caustics disrupt prey detection by a reef fish

Underwater caustics disrupt prey detection by a reef fish

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

Camouflage

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