As you walk through a forest, the birds you can hear are a good indicator of the forest health. They're easy to detect and they're sensitive to small changes in environment at the lower levels of the food chain.
But it's time consuming and expensive to send ornithologists out to survey Tasmania's vast forests, so forest managers have relied on spot-surveys, which don't tell the full story.
The University of Tasmania is developing technologies they hope will allow forest managers to use data captured by remote audio recorders. Their 'recognition algorithms' have the potential to automatically detect and count each bird and each species in a recording. University Associate Andrew Hingston has developed recordings annotated with species names that the team has used to teach their machine learning system to confidently predict 20 of the 105 bird species known to Tasmania. Now they're working to train the system to recognise individual birds and a wider range of species.
The public can help, via Birdsong, a citizen science project centred around a web portal where birdwatchers can log their sightings, submit images and audio, and get some online training in bird identification. Listen to birdsong and join the effort at https://birdsong.ecoacoustics.science.
The project came out of an industry-driven need for more cost-effective ways to measure bird populations, says Honorary Research Associate Dr Tim Wardlaw. He is a Partner Investigator for Forestry Tasmania in an ARC Linkage Project that was set up to develop ways to assess forest health using audio recordings of birdsong.
The project will use the work of mathematician Scott Whitemore, who is working with the University's ARC Centre for Forest Value.
"Long-term monitoring quickly produces hundreds of hours of audio recordings," says Whitemore. "To get a high-resolution picture of what is going on in an ecosystem, we need a way to annotate recordings which doesn't require much human input."
He has helped develop a recognition algorithm that uses sonograms and visual representations of audio recordings to identify individual bird species in an ecosystem.
Project partners include the Southern Regional Natural Resource Management Association, VicForests, Sustainable Timber Tasmania, Tasmanian Land Conservancy Inc, and the Forest Practices Authority.
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About the researchers
Associate Professor Michael Charleston is a lecturer and researcher in Mathematics and Physics.
Mr Whitemore is a PhD student on the project "Developing algorithms to automatically identify bird species from audio recordings in order to improve biodiversity monitoring".
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Interested in partnering with the University of Tasmania? Find out more here.