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Sensing ecosystem dynamics via audio source separation: A case study of marine soundscapes off northeastern Taiwan.
Lin, Tzu-Hao; Akamatsu, Tomonari; Tsao, Yu.
Afiliação
  • Lin TH; Biodiversity Research Center, Academia Sinica, Taipei, Taiwan (R.O.C).
  • Akamatsu T; The Ocean Policy Research Institute, The Sasakawa Peace Foundation, Tokyo, Japan.
  • Tsao Y; Research Center for Information Technology Innovation, Academia Sinica, Taipei, Taiwan (R.O.C).
PLoS Comput Biol ; 17(2): e1008698, 2021 02.
Article em En | MEDLINE | ID: mdl-33600436
ABSTRACT
Remote acquisition of information on ecosystem dynamics is essential for conservation management, especially for the deep ocean. Soundscape offers unique opportunities to study the behavior of soniferous marine animals and their interactions with various noise-generating activities at a fine temporal resolution. However, the retrieval of soundscape information remains challenging owing to limitations in audio analysis techniques that are effective in the face of highly variable interfering sources. This study investigated the application of a seafloor acoustic observatory as a long-term platform for observing marine ecosystem dynamics through audio source separation. A source separation model based on the assumption of source-specific periodicity was used to factorize time-frequency representations of long-duration underwater recordings. With minimal supervision, the model learned to discriminate source-specific spectral features and prove to be effective in the separation of sounds made by cetaceans, soniferous fish, and abiotic sources from the deep-water soundscapes off northeastern Taiwan. Results revealed phenological differences among the sound sources and identified diurnal and seasonal interactions between cetaceans and soniferous fish. The application of clustering to source separation results generated a database featuring the diversity of soundscapes and revealed a compositional shift in clusters of cetacean vocalizations and fish choruses during diurnal and seasonal cycles. The source separation model enables the transformation of single-channel audio into multiple channels encoding the dynamics of biophony, geophony, and anthropophony, which are essential for characterizing the community of soniferous animals, quality of acoustic habitat, and their interactions. Our results demonstrated the application of source separation could facilitate acoustic diversity assessment, which is a crucial task in soundscape-based ecosystem monitoring. Future implementation of soundscape information retrieval in long-term marine observation networks will lead to the use of soundscapes as a new tool for conservation management in an increasingly noisy ocean.
Assuntos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Som / Oceanos e Mares / Ecossistema / Organismos Aquáticos Tipo de estudo: Prognostic_studies Limite: Animals País como assunto: Asia Idioma: En Ano de publicação: 2021 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Som / Oceanos e Mares / Ecossistema / Organismos Aquáticos Tipo de estudo: Prognostic_studies Limite: Animals País como assunto: Asia Idioma: En Ano de publicação: 2021 Tipo de documento: Article