Summary: A new artificial intelligence algorithm trained using the soundscapes of both healthy and degraded reefs can determine reef health 92% of the time. Coral reefs have a complex soundscape – and even experts have to conduct painstaking analysis to measure reef health based on sound recordings. In the new study, published in Ecological Indicators, scientists trained a computer algorithm using multiple recordings of healthy and degraded reefs, allowing the machine to learn the difference. The computer then analyzed a host of new recordings, and successfully identified reef health 92% of the time. The team used this to track the progress of reef restoration projects.

Coral reefs have a complex soundscape -- and even experts have to conduct painstaking analysis to measure reef health based on sound recordings. In the new study, University of Exeter scientists trained a computer algorithm using multiple recordings of healthy and degraded reefs, allowing the machine to learn the difference. The computer then analysed a host of new recordings, and successfully identified reef health 92% of the time. The team used this to track the progress of reef restoration projects. "Coral reefs are facing multiple threats including climate change, so monitoring their health and the success of conservation projects is vital," said lead author Ben Williams.