A study has determined that some flies have evolved to buzz very loudly. They believe that this is to warn other flies of danger and avoid being eaten. This behavior may have something to do with the size of their vocal organs. However, other researchers believe that it may be more complicated than that.
Variability in flies’ songs
There is a great deal of variability in flies’ songs. Each song varies slightly from the previous one and is dependent on the female fly’s speed, distance and sensory environment. Scientists aren’t sure exactly why the song structure changes. The variation could be caused by a noisy neural network or sensory feedback.
To analyze this variability, we measured the duration and amplitude of each song pulse. Then, we calculated the IPI of each song pulse and recorded the duration of each song cycle. We observed that the duration of each song bout was variable and varied with temperature.
Pattern of pulses versus sines of their song
Flies produce songs containing multiple frequencies in a pattern of pulses and sines. The pattern is important in explaining the way that flies locate their target in a landscape. Scientists believe that this pattern is a natural response to sensory information from nearby areas. For example, when a male fly is hunting for a female, he will sing a pulse song to attract her. This is a natural response that many other insects have.
Male Drosophila melanogaster emits two different types of acoustic signals during courtship: pulses and sines. The two different songs contain different features and may have evolved independently. The pattern of pulses and sines produced by male flies is largely dependent on the structure of the insects’ nervous systems, with each feature having its own distinct function. The sine component of male songs is produced by the hg1 motoneuron, whereas the pulse component is produced by a separate ps1 motoneuron.
Fearful flies’ screams
You’ve probably heard the high-pitched screams of a housefly in the kitchen window. It’s almost as if it’s being wrapped in a spider’s web. It’s screaming its heart out and for all its worth. It’s terrifying!
Quick-fire intelligence of flies
Scientists have found the secret behind flies’ ability to avoid being swatted, and it has a lot to do with the way flies plan their moves. Their quick-fire intelligence is due to a complex brain that processes information in less than 100 milliseconds, launching the body accordingly. Despite this intelligence, flies are also known for their good planning and impulse control, making them hard to kill.
Scientists at Oxford University recently uncovered how flies’ brains process information. They found a gene called FoxP that is involved in the decision-making process. This gene is active in 200 nerve cells and controls how the fly’s brain interprets information. The findings offer unprecedented insight into how the brain works.
Planned behavior of flies
Scientists have uncovered that some insects display social behavior in different contexts. For example, fruit flies use social regulation to suppress egg laying in the presence of predatory wasps and reduce erratic turns during evasive flight. However, these behavioral changes are not universal and the exact mechanism is not known.
It is unclear how flies decide which behavior to perform. For example, one theory suggests that the flies use motion cues from their neighbors to decide whether to continue freezing or to exit. This suggests that flies may be using motion cues as a safety signal.
Fly’s ability to predict danger
Fly’s ability to predict danger can be measured by using the probability of a predator attack. The probability of a potential attack increased from zero on day one to 0.9 on day five. The median values are shown in fig. 4. The study concluded that the fly’s ability to predict danger is a function of size and speed.
The study was carried out using data from 20 species of flies. Each species was reared at varying temperatures to assess their resistance to different environments. These data were used to develop a predictive model of fly numbers in different environments. The models used in the experiment incorporated the number of flies at a particular site and the density of that population in a given week.
