This method allows scientists to analyse the vocalisations of animals, providing valuable information about their populations, movements and habitats. The scientists are applying a technique adapted from brain wave analysis, known as the Superlet transform (SLT), to study the vocalisations of various animals, including birds and elephants.  

This method transforms sound signals into images, providing clearer insights into the animals' calls. Through sound analysis, scientists can estimate animal population sizes, track their movements, and identify their habitats – allowing them to create more effective conservation strategies to help safeguard these species from extinction. 

The SLT method also helps them detect the impact of increasing human noise on animal behaviour. Previously, existing methods struggled to capture both time and frequency information simultaneously, which compromised the accuracy and effectiveness of sound analysis. 

“The new method we demonstrated offers increased accuracy and requires less expertise to use, so it should prove to be a hugely valuable tool for animal sound researchers that don’t have an engineering background," said Ben Jancovich, lead researcher from University of New South Wales.  

When visualising the rumbles of Asian elephants, the SLT method revealed a ‘pulsing’ pattern that has never been seen in spectrograms (a visual picture of sound) before. The SLT also showed new timing details in the calls of the southern cassowary and the roar of the American crocodile that earlier spectrograms didn’t capture. 

Although initial discoveries seem promising, further analysis is needed to confirm and explain the results. Overall, this breakthrough in sound analysis highlights how new technologies can help support wildlife conservation. By offering clear insights into animal communication, researchers hope to improve efforts to protect endangered species and their habitats. 

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