Diurnal and nocturnal mosquitoes escape looming threats using distinct flight strategies

Current Biology(2022)

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摘要
Flying insects have evolved the ability to evade looming objects, such as predators and swatting hands. This is particularly relevant for blood-feeding insects, such as mosquitoes that routinely need to evade the defensive actions of their blood hosts. To minimize the chance of being swatted, a mosquito can use two distinct strategies—continuously exhibiting an unpredictable flight path or maximizing its escape maneuverability. We studied how baseline flight unpredictability and escape maneuverability affect the escape performance of day-active and night-active mosquitoes (Aedes aegypti and Anopheles coluzzii, respectively). We used a multi-camera high-speed videography system to track how freely flying mosquitoes respond to an event-triggered rapidly approaching mechanical swatter, in four different light conditions ranging from pitch darkness to overcast daylight. Results show that both species exhibit enhanced escape performance in their natural blood-feeding light condition (daylight for Aedes and dark for Anopheles). To achieve this, they show strikingly different behaviors. The enhanced escape performance of Anopheles at night is explained by their increased baseline unpredictable erratic flight behavior, whereas the increased escape performance of Aedes in overcast daylight is due to their enhanced escape maneuvers. This shows that both day and night-active mosquitoes modify their flight behavior in response to light intensity such that their escape performance is maximum in their natural blood-feeding light conditions, when these defensive actions by their blood hosts occur most. Because Aedes and Anopheles mosquitoes are major vectors of several deadly human diseases, this knowledge can be used to optimize vector control methods for these specific species.
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关键词
Aedes aegypti,Anopheles coluzzii,insect flight,evasive maneuvers,unpredictable behavior,protean insurance,real-time three-dimensional videography,Bayesian generalized linear model,hidden Markov model
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