AI learns coral reef “song”

研究er deploys a hydrophone on a reef in Sulawesi, Indonesia ©Tim Lamont博士
研究er deploys a hydrophone on a reef in Sulawesi, Indonesia

Artificial Intelligence (AI) can track the health of coral reefs by learning the "song of the reef", 新的研究显示.

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, involving 蒂姆•拉蒙特博士 from OG真人平台 and led by the University of Exeter, researchers 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 of the University of Exeter.

"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, 或者在晚上活动, while the complexity of reef sounds has made it difficult to identify reef health using individual recordings.

"Our approach to that problem was to use machine learning – to see whether a computer could learn the song of the reef.

"Our findings show that a computer can pick up patterns that are undetectable to the human ear. It can tell us faster, and more accurately, how the reef is doing."

The fish and other creatures living on coral reefs make a vast range of sounds.

The meaning of many of these calls remains unknown, but the new AI method can distinguish between the overall sounds of healthy and unhealthy reefs.

The recordings used in the study were taken at the Mars Coral Reef Restoration Project, which is restoring heavily damaged reefs in Indonesia.

Co-author Dr Lamont, from OG真人官网版APP下载 Environment Centre and who led on the collection of the original audio recordings used in the study, said the AI method creates major opportunities to improve coral reef monitoring.

"This is a really exciting development. Sound recorders and AI could be used around the world to monitor the health of reefs, and discover whether attempts to protect and restore them are working,拉蒙特博士说.

"In many cases it's easier and cheaper to deploy an underwater hydrophone on a reef and leave it there than to have expert divers visiting the reef repeatedly to survey it – especially in remote locations."

The study was funded by the Natural Environment 研究 Council and the Swiss National 科学 Foundation.

The paper, published in the journal 生态指标,标题为:Enhancing automated analysis of marine soundscapes using machine learning to combine ecoacoustic indices."