What makes an effective warning signal?

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Many animals exhibit camouflage patterns that help them remain hidden against their background and be less visible to predators. But some animals have vivid, bright colouring that makes them stand out in their environment. Whilst some conspicuous patterns are known to be involved in attracting a mate, others have evolved to warn a predator that the animal is poisonous or unpalatable. These warning patterns are described as being 'aposematic', and are commonly found in insects, for example, monarch butterflies, ladybirds and wasps. Although aposematic patterns look like they might attract predators, in fact they act as a deterrent. Predators are wary towards prey that are warningly coloured, such as being red or yellow, and are quick to learn that warning colours signal danger and avoid aposematically coloured prey. Although warning signals, like camouflage patterns, have fascinated biologists for more than 150 years, there is still no clear understanding of what features make these patterns distinctive and effective against predators, or how they are designed to exploit the ways in which predators see the world. Indeed, definitions of aposematic patterns are loosely descriptive, for example, they are described as 'striking', 'conspicuous' or 'distinctive'. But what is it that sets these patterns apart from others in the natural world: what makes an effective warning signal?In this project, we propose to tackle this important question through mathematical modeling, and experiments with chicks and humans. For the first time, we will measure the patterns of aposematic and non-aposematic species, and use image processing techniques to quantify the characteristics of aposematic patterns. We will collect photographs of butterflies, moths and beetles from museum collections using techniques that allow us to 'see' the patterns as a foraging bird would. For example, we know what colours and patterns avian visual systems are most sensitive to, and can calculate how warning signals stimulate their visual systems. Once the models have made their predictions we can test them using behavioural experiments that measure how birds react to the aposematic patterns and what features enhance prey survival.We also plan to test a novel hypothesis for why aposematic patterns act as warning signals. Humans find particular classes of pattern (e.g. stripes or spots of specific sizes and arrangements) aversive or uncomfortable. It has been suggested that these patterns could 'overload' the brain, and make these signals aversive. We will build a computational model of the early stages of visual processing in the brain, and test if aposematic patterns do deliver excessive responses. We will then test the model by choosing patterns that should visually overload humans, and taking classic visual discomfort measures.The project will allow us to understand the form and function of aposematic patterns, and finally give us a precise and working definition. The work will broad appeal to the general public, and potentially improve the efficacy of visual alerts and avian deterrents.