Analysis - Finding bats is hard. They are small, fast and they primarily fly at night.
could improve the way conservationists find bat roosts. We've developed a new algorithm that significantly reduces the area that needs to be searched, which could save time and cut labour cost.
Our new research combines our previous mathematical model of bat motion with data gathered from acoustic recorders known as"bat detectors". These bat detectors are placed around the environment and left there for several nights.Bats use echolocation, which allows them to"see with sound" when they're flying.
Our model can also be used to predict the proportion of bat calls based on a given roost location. So, we split the environment up into a grid and simulate bats flying from each grid square. The grid square, or squares, whose simulations best reproduce the bat detector data will then be the most likely locations of the roost.
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