What makes an effective warning signal?

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Aposematic species use 'distinctive' and 'conspicuous' colour patterns to advertise a defence, such as being toxic or unprofitable. Understanding why such vibrant warning signals have evolved has provided a test bed for evolutionary theory for more than 150 years. It is therefore surprising that we have no analytical understanding of signal design, i.e. what makes natural warning signals 'conspicuous' or 'distinct'. In this project we take a novel approach to characterise real aposematic patterns, model their effects on the perceptual systems of predators, and test what makes them 'special' via behavioural experiments.
We will develop a database of hyperspectral images of aposematic (AP) and non-aposematic (Non-AP) species. This will allow us to compare the patterns of AP and Non-AP species in a principled way to identify key features of AP patterns. By mathematically analysing the database, we will deliver a set of specific visual features (colour and spatial pattern) that will define a pattern as being AP. We will test which of these features contribute to the efficacy of warning signals using avian predators (via unlearned wariness and avoidance learning paradigms). We will also predict and test the distance at which aposematic patterns become effective against predators.
Recent developments in neuroscience suggest there may be more to AP patterns than being distinctive. Warning patterns may be effective because they are highly unusual in natural scenes, stimulating high levels of neural activity. We will test this 'visual overload hypothesis', using modeling and experiments, and establish if AP patterns trigger stronger brain activity than other conspicuous patterns.
We will disseminate the work across relevant academic disciplines, to the public via school visits, science festivals and museum exhibits, and to stakeholders involved in development of high-visibility clothing and deterrents for birds.

Our proposal is for core evolutionary and computational biology research with no immediate application to UK-plc. However, we have identified three groups of possible indirect stakeholders, and two groups of direct stakeholders.
(1) Technical developers of high-visibility systems
Our work could be of use to those interested in increasing the visibility of workers and sportsmen through high-visibility clothing. We have obtained interest in the idea from two companies specialising in high-performance sports-wear, Tineli and Raceskin. We will discuss our project findings with them to explore how to improve the design of highly visible sports clothing.
(2) Medical professionals and technologists
Our work will be of relevance to medical professionals interested in visual discomfort and in photo-sensitive epilepsy and allow the prediction of uncomfortable images. Harris has collaborative links with the Department of Optometry at Bradford University (Barratt, Bloj). She will arrange a talk to optometry professionals there on the implications of our work for understanding the symptoms of visual stress and discomfort.
(3) Developers of avian deterrents
Birds can cause significant damage to infrastructure and crops. Our data could lead to significant improvements in the design of avian deterrents, for example, on farmland, at airports and on powerlines. We have established contacts in industry and in wildlife control that we will exploit to explore the development and testing of novel deterrents.
(4) The general public
Our research topic is highly engaging for the general public, who have a passion for wildlife, particularly insects and birds. We will engage the public through school visits and the development of a linked classroom activity, events at local zoos and museums, natural history societies, public displays at Science Fairs, and interactive web-based demonstrations our laboratory websites.
(5) Project researchers
The proposal is an interdisciplinary collaboration. Penacchio has a background in pure maths, but is on his way to becoming an interdisciplinary computational biologist. This project will add another string to his biology bow. Halpin is an expert in animal behaviour and cognition, particularly in how predators learn about what to eat. This project will enable her to better understand the sensory and neural processes underlying signal processing, and allow her to develop new skills in image acquisition and analysis. Both researchers will benefit from the development of new skills and knowledge that transcend traditional disciplinary boundaries.