Led by organizations including University College London, the Bat Conservation Trust, and Forest Research, the project gathered 90,000 hours of acoustic data over three years. Open-source artificial intelligence systems processed 98 million audio calls captured across 310 separate woodlands. The resulting findings located populations of hard-to-track species, providing vital visibility into vulnerable native wildlife across the country.
Key points
Artificial intelligence enabled researchers to analyze acoustic wildlife data that was pr…: Artificial intelligence enabled researchers to analyze acoustic wildlife data that was previously impossible to process manually.
The collaborative initiative involved scientists from University College London, Forest R…: The collaborative initiative involved scientists from University College London, Forest Research, and the Bat Conservation Trust.
Conservationists identified key Barbastelle activity hotspots concentrated in Dorset, Cor…: Conservationists identified key Barbastelle activity hotspots concentrated in Dorset, Cornwall, Devon, and Somerset.
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Britain's largest ever woodland survey of bats would "simply not have been feasible" without AI, scientists say.
Researchers left devices on poles among the trees of 310 woodlands across Britain, recording 98 million bat calls over three years, which would have taken more than 30 years to analyse without AI.
Some of Britain's rarest and most threatened bats, including the red-listed Barbastelle, have been recorded in the south-west of England, including Somerset, Devon, Cornwall and Dorset.
Kate Jones, from University College London, said: "AI has fundamentally changed the scale at which we can monitor wildlife." She added the survey was a "nice story of AI for good".
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Jones added: "Previously, analysing this volume of acoustic data would simply not have been feasible.
"These efficient open-source AI tools allow us to identify millions of bat calls across thousands of nights…
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