Pattern edges improve predator learning of aposematic signals

Green, Naomi F.; Urquhart, Holly H.; Berg, Cedric P. van den; Marshall, N. Justin; Cheney, Karen L.

doi:10.1093/beheco/ary089

Cited by 23 publications

(33 citation statements)

References 44 publications

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“…Importantly, however, not all stimuli that affect receiver fitness trigger a positive emotional evaluation. Aposematic traits, for example, facilitate the recognition and memorization of dangerous species [75] and are judged to be beautiful, but they trigger fear, a negative or aversive emotional evaluation (e.g., in snakes, see [76]; Box 1). Animals can form positive (aesthetic) judgments about stimuli that trigger an aversive emotional response or even about stimuli that are likely neutral with respect to fitness, like artwork or landscapes, suggesting a typical quality indicator model may not be a sufficient explanation.…”

Section: The Processing Biasmentioning

confidence: 99%

Processing bias: extending sensory drive to include efficacy and efficiency in information processing

Renoult

Mendelson

2019

Proc. R. Soc. B.

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Communication signals often comprise an array of colors, lines, spots, notes or odors that are arranged in complex patterns, melodies or blends. Receiver perception is assumed to influence preference and thus the evolution of signal design, but evolutionary biologists still struggle to understand how perception, preference, and signal design are mechanistically linked. In parallel, the field of empirical aesthetics aims to understand why people like some designs more than others. The model of processing bias discussed here is rooted in empirical aesthetics, which posits that preferences are influenced by the emotional system as it monitors the dynamics of information processing, and that attractive signals have either effective designs that maximize information transmission, efficient designs that allow information processing at low metabolic cost, or both. We refer to the causal link between preference and the emotionally rewarding experience of effective and efficient information processing as the processing bias, and we apply it to the evolutionary model of sensory drive. A sensory drive model that incorporates processing bias hypothesizes a causal chain of relationships between the environment, perception, pleasure, preference, and ultimately the evolution of signal design, from simple to complex. GlossaryEfficacy: optimizing information processing at any cost. Efficiency: information processing with an optimal use of resources. Feature: measurable property of a stimulus. Information: property of a stimulus that reduces uncertainty about the environment. Information processing: describes how information is received, transmitted in the nervous system, coded, stored and retrieved in the animal brain and sensory systems. Neuronal selectivity: the range of stimulus features that activate a neuron. Processing bias: judgment modulated by affect, which is influenced by the level of efficacy and efficiency in information processing. In cognitive sciences, processing bias is often referred to as an aesthetic judgment. Sensory drive: the hypothesis that the tuning of perceptual and cognitive systems to effectively and efficiently process information in environmental stimuli generates selection on communication signals due to a direct effect of effective and efficient processing on receiver preference. Stimulus: component of the external environment causing a physiological response (e.g., a landscape, an individual or a communication signal).

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Section: The Processing Biasmentioning

confidence: 99%

Processing bias: extending sensory drive to include efficacy and efficiency in information processing

Renoult

Mendelson

2019

Proc. R. Soc. B.

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“…). Various experiments are now examining the difference between chromatic and achromatic behavioural pathways, a critical factor to understand how reef fishes perceive pattern and luminance differences, as well as colour (Mitchell et al ., ; Green et al ., ; Cheney et al ., 2018).…”

Section: Reef Fishes Colour Visionmentioning

confidence: 99%

“…Tests include wavelength discrimination, the characteristics of its colour space (Champ et al, 2016) and even, like in humans, its ability to see illusory colours (Simpson et al 2016). Various experiments are now examining the difference between chromatic and achromatic behavioural pathways, a critical factor to understand how reef fishes perceive pattern and luminance differences, as well as colour (Mitchell et al, 2017;Green et al, 2018;Cheney et al, 2018).…”

Section: Recent Cross Comparisons Of Reef-fish Colours and Colour Visionmentioning

confidence: 99%

Colours and colour vision in reef fishes: Past, present and future research directions

Marshall

Cortesi

Busserolles

et al. 2018

Journal of Fish Biology

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Many fishes, both freshwater or marine, have colour vision that may outperform humans. As a result, to understand the behavioural tasks that vision enables; including mate choice, feeding, agonistic behaviour and camouflage, we need to see the world through a fish's eye. This includes quantifying the variable light environment underwater and its various influences on vision. As well as rapid loss of light with depth, light attenuation underwater limits visual interaction to metres at most and in many instances, less than a metre. We also need to characterize visual sensitivities, fish colours and behaviours relative to both these factors. An increasingly large set of techniques over the past few years, including improved photography, submersible spectrophotometers and genetic sequencing, have taken us from intelligent guesswork to something closer to sensible hypotheses. This contribution to the special edition on the Ecology of Fish Senses under a shifting environment first reviews our knowledge of fish colour vision and visual ecology, past, present and very recent, and then goes on to examine how climate change may impinge on fish visual capability. The review is limited to mostly colour vision and to mostly reef fishes. This ignores a large body of work, both from other marine environments and freshwater systems, but the reef contains examples of many of the challenges to vision from the aquatic environment. It is also a concentrate of life, perhaps the most specious and complex on earth, suffering now catastrophically from the consequences of our lack of action on climate change. A clear course of action to prevent destruction of this habitat is the need to spend more time in it, in the study of it and sharing it with those not fortunate enough to see coral reefs first‐hand. Sir David Attenborough on The Great Barrier Reef: “Do we really care so little about the Earth upon which we live that we don't wish to protect one of its greatest wonders from the consequences of our behaviours?”

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“…While useful for many studies of animal colouration, these 87 individual analyses ignore the interaction of visual information at various perceptual stages (for 90 Spatiochromatic colour pattern analyses overcome these limitations as they are designed to 91 consider perceptual interactions between spatial, chromatic and achromatic information ( Endler et al, 2018). For example, not only is the efficiency of visual signals dependent on the presence 97 or absence of colours, but also how those colours are arranged in patterns (Endler, 1984(Endler, , 2012Endler 98 et al, 2018; Green et al, 2018;Troscianko et al, 2018). The importance of this approach for 99 understanding the design, function and evolution of visual signals has been highlighted repeatedly (e.g.…”

mentioning

confidence: 99%

“…focuses on pattern geometry, whereas visual contrast analysis is designed285 to investigate colour, pattern and luminance simultaneously(Endler & Mielke, 2005). This is important286 because spatial, chromatic and achromatic properties of colour patterns and visual scenes can interact287 to promote or suppress functional components of pattern conspicuousness such as its saliency,288 vividness, memorability and detectability (e.g Endler & Houde, 1995;Green et al, 2018)…”

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confidence: 99%

Quantitative Colour Pattern Analysis (QCPA): A Comprehensive Framework for the Analysis of Colour Patterns in Nature

Berg

Troscianko

Endler

et al. 2019

Preprint

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11 1. To understand the function of colour signals in nature, we require robust quantitative 12 analytical frameworks to enable us to estimate how animal and plant colour patterns appear 13 against their natural background as viewed by ecologically relevant species. Due to the 14 quantitative limitations of existing methods, colour and pattern are rarely analysed in 15 conjunction with one another, despite a large body of literature and decades of research on 16 the importance of spatiochromatic colour pattern analyses. Furthermore, key physiological 17 limitations of animal visual systems such as spatial acuity, spectral sensitivities, photoreceptor 18 abundances and receptor noise levels are rarely considered together in colour pattern 19 analyses. 20 2. Here, we present a novel analytical framework, called the 'Quantitative Colour Pattern 21 Analysis' (QCPA). We have overcome many quantitative and qualitative limitations of existing 22 image segmentation, which we call 'Receptor Noise Limited Clustering', used here for the first 30 time. Furthermore, QCPA provides a novel psycho-physiological approach to the modelling of 31 spatial acuity using convolution in the spatial or frequency domains, followed by 'Receptor 32 Noise Limited Ranked Filtering' to eliminate intermediate edge artefacts and recover sharp 33 boundaries following smoothing. We also present a new type of colour pattern analysis, the 34 'Local Edge Intensity Analysis' (LEIA) as well as a range of novel psycho-physiological 35 approaches to the visualisation of spatiochromatic data.36 4. QCPA combines novel and existing pattern analysis frameworks into what we hope is a unified, 37 user-friendly, free and open source toolbox and introduce a range of novel analytical and data-38 visualisation approaches. These analyses and tools have been seamlessly integrated into the 39 MICA toolbox providing a dynamic and user-friendly workflow. 40 5. QCPA is a framework for the empirical investigation of key theories underlying the design, 41 function and evolution of colour patterns in nature. We believe that it is compatible with, but 42 more thorough than, other existing colour pattern analyses. 43 44 Keywords: colour pattern analysis, colour perception, image analysis, visual modelling, receptor noise 45 limited model, animal colouration, colour space 46 47 65

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Pattern edges improve predator learning of aposematic signals

Cited by 23 publications

References 44 publications

Processing bias: extending sensory drive to include efficacy and efficiency in information processing

Processing bias: extending sensory drive to include efficacy and efficiency in information processing

Colours and colour vision in reef fishes: Past, present and future research directions

Quantitative Colour Pattern Analysis (QCPA): A Comprehensive Framework for the Analysis of Colour Patterns in Nature

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