Revealing the ecological content of long-duration audio-recordings of the environment through clustering and visualisation

PloS One
Yvonne F PhillipsPaul Roe

Abstract

Audio recordings of the environment are an increasingly important technique to monitor biodiversity and ecosystem function. While the acquisition of long-duration recordings is becoming easier and cheaper, the analysis and interpretation of that audio remains a significant research area. The issue addressed in this paper is the automated reduction of environmental audio data to facilitate ecological investigations. We describe a method that first reduces environmental audio to vectors of acoustic indices, which are then clustered. This can reduce the audio data by six to eight orders of magnitude yet retain useful ecological information. We describe techniques to visualise sequences of cluster occurrence (using for example, diel plots, rose plots) that assist interpretation of environmental audio. Colour coding acoustic clusters allows months and years of audio data to be visualised in a single image. These techniques are useful in identifying and indexing the contents of long-duration audio recordings. They could also play an important role in monitoring long-term changes in species abundance brought about by habitat degradation and/or restoration.

References

May 5, 2006·Nature·Christiaan BothMarcel E Visser
Sep 6, 2007·Molecular Ecology·Hans Slabbekoorn, Erwin A P Ripmeester
Dec 31, 2008·PloS One·Jérôme SueurStéphanie Duvail
Jul 21, 2011·Nature Methods·Bang Wong

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Citations

Nov 14, 2019·PeerJ·Rita CarriçoMaria Clara P Amorim
Sep 25, 2020·Royal Society Open Science·T Aran MooneyJenni Stanley
May 27, 2020··Paul RoeTshering Dema
Jan 9, 2019··Michael TowseyJinglan Zhang

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Methods Mentioned

BETA
PCA
two-step hybrid

Software Mentioned

R MASS package
R plotrix package
hclust
Ecosounds Acoustic Workbench
R cluster package
R
R stats package
R class package
Audio Analysis Programs

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