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.

"One major difficulty is that visual and acoustic surveys of reefs usually rely on labour-intensive methods.

"Visual surveys are also limited by the fact that many reef creatures conceal themselves, or are active at night, while the complexity of reef sounds has made it difficult to identify reef health using individual recordings.