Flies that feed on blood, such as tsetse flies and horseflies, inflict painful bites and spread debilitating diseases among both people and animals. So much work has gone into designing the most efficient traps to control populations of these flies.
Sting traps tend to be blue, because decades of field research have shown that these flies find this color particularly attractive. But it’s never been clear why these flies find blue so irresistible, especially since blue objects aren’t a common sight in the natural environment.
Scientists speculated that blue surfaces might look like shady places for flies since shadows have a bluish tinge. Tsetse flies, in particular, seek such shady places to rest, which may explain their attraction to blue traps.
Another possibility is that blue surfaces may attract hungry flies by providing them with the telltale markings they use to distinguish animals against a background of foliage. According to this theory, a fly could mistake a blue trap for an animal that wishes to bite and feed.
But assessing these possibilities is particularly tricky because flies perceive color differently than people. Humans perceive color using responses from three types of light-sensing photoreceptors in the retina that are broadly sensitive to blue, green, and red light wavelengths.
But most higher flies such as tsetse and horseflies have five types of photoreceptors sensitive to UV, blue and green wavelengths. So, a blue trap won’t look to a fly like it did to the human who designed it.
From flies to artificial intelligence
In our study, we addressed the problem using artificial intelligence (AI). We have used artificial neural networks which are a form of machine learning inspired by the structure of real nervous systems. Artificial neural networks learn by changing the strengths of connections between a network of artificial neurons.
We fed these webs with photoreceptor signals that a fly would experience when looking at backgrounds of animals or foliage, in both light and shade. We then trained the networks to distinguish animals from leaves and shaded from unshaded objects, using only that visual information.
The trained networks would find the most efficient way to process visual cues, which we expected to share properties with mechanisms that have evolved in the nervous systems of real flies. We then investigated whether artificial neural networks classified blue traps as animals or as shaded surfaces.
Blue or brightness?
After training, our neural networks could easily distinguish animals from leaf backgrounds and shaded from unshaded stimuli, using the sensory information available to a fly. However, what surprised us is that they solved these problems in completely different ways.
The networks identified shade using simply brightness and not color—the darker a stimulus appeared, the more likely it was to be classified as shaded. Meanwhile, the animals were identified using the relative strength of the blue and green photoreceptor signals. Relatively greater blue signals than green signals indicated that a stimulus was probably an animal rather than a leaf, and vice versa.
The implications of this became clear when we fed these networks with the visual cues caused by the blue traps. Blue traps have never been mistaken for shaded surfaces, but have commonly been misclassified as animals.
Of course, artificial neural networks are not real flies, nor exact models of a fly’s nervous system. But they show us the most efficient way to process a fly’s visual cues to identify natural stimuli. And we expect evolution to have exploited similar principles in the nervous systems of real flies.
The best way to identify the shade using the visual information a fly has is through the brightness and not the blue. Meanwhile, the best way to identify animals was, somewhat counterintuitively, to use blue. This mechanism is strongly stimulated by blue traps, which explains why they prove such powerful bait for hungry flies. Further evidence for this idea comes from field studies showing that tsetse that land on colored traps are relatively hungry.
If we can understand the sensory cues and behavior that cause flies to get caught in traps, we can design traps to more efficiently exploit those mechanisms and more effectively control flies. We’ve already had some success doing this for tsetse flies.
More effective traps will help minimize the impact of these flies on the health and welfare of people and animals. They could help prevent the harmful effects of biting flies on livestock, aid in the fight against dangerous fly-borne diseases such as sleeping sickness, and protect us and animals from fly attacks in general.
#Stinging #flies #attracted #blue #traps #figure
Image Source : theconversation.com