Ocean Biodiversity Listening Project
The ocean is full of sounds that are generated from geophysical events, marine animals, and human activities. By using a hydrophone (a microphone for underwater use), we can hear chirps of marine mammals, choruses of soniferous fish, and pulsed sounds of benthic invertebrates. These bioacoustic signals reveal the status of marine biodiversity and ecosystem health. On the other hand, the increased maritime traffic, over-exploitation of marine resources, and the development of renewable energy have led to a global increase in underwater noise. Listening to underwater sounds allows us to remotely acquire ecological data of marine biodiversity and investigate the changes of biodiversity in response to climate change and anthropogenic development.
In this project, we attempt to establish a large-scale soundscape monitoring network and characterize ecosystem-specific soundscapes by separating sounds from geophonic, biological, and anthropogenic sources. Based on information retrieval techniques, the acoustic data are transformed into metrics that describe the quality of acoustic habitat, the behavior of soniferous animals, and noise-generating activities. The outcomes will allow managers and stakeholders to use soundscape information to monitor the trends of marine ecosystems and perform data-driven decision making in conservation management.
Underwater sounds of rainfall
Sounds of a fishing vessel
Sounds of deep-sea hydrothermal vents
Sounds of crustaceans
Chirps of Indo-Pacific humpback dolphins
Fish chorus recorded at 5500 m depth
Soundscape-based Ecosystem Monitoring
We collect underwater sounds from marine ecosystems by using fixed-location platforms, towed surveys, and autonomous underwater vehicles. Audio data are archived in cloud platforms in order to facilitate seamless access for collaborators. On the basis of newly developed techniques of soundscape information retrieval, we extract acoustic indices to visualize the spatial-temporal dynamics of biological and anthropogenic activities.
We collaborate with international scientists to establish a soundscape monitoring network that covers inshore waters, river estuaries, algal reefs, coral reefs, seagrass beds, continental shelves, hydrothermal vents, and various deep-sea benthic habitats. Switch on the sidebar in the following map to see the list of recording locations. Click each recording location to see detail information.
Visualizing the Dynamics of Marine Ecosystems
We visualize the dynamics of marine ecosystems by analyzing the temporal and spectral variations of underwater recordings. We also produce acoustic indices specific to biological and anthropogenic activities to improve the ecological applications of marine soundscapes. Below we show a long-term spectrogram of coral reef soundscapes and the audio separation result of biological choruses and shipping activities.
On the basis of information generated from marine soundscapes, the Ocean Biodiversity Listening Project aims to predict the changes of geophysical environment, marine biodiversity, and anthropogenic activities in marine ecosystems from the inter-tidal zone to the hadal zone of deep-sea trenches. We believe that the outcome will transform soundscapes as a new tool for conservation management. Through global collaboration, we can establish a data-informed platform and help stakeholders assess the resilience of marine ecosystems to environmental and anthropogenic stressors.
Tzu-Hao Lin, Chong Chen, Hiromi Kayama Watanabe, Tomonari Akamatsu, Shinsuke Kawagucci. (2021). Deep-sea soundscapes of Japan [Data set]. https://data.depositar.io/en/dataset/deep-sea-soundscapes-of-japan
Tzu-Hao Lin, Tomonari Akamatsu, Yu Tsao. (2021). Deep water soundscapes off northeastern Taiwan [Data set]. https://data.depositar.io/en/dataset/deep-water-soundscapes-off-northeastern-taiwan
Tzu-Hao Lin, Tomonari Akamatsu, Frederic Sinniger, Saki Harii. (2020). Coral Reef Soundscapes off Sesoko Island, Okinawa, Japan [Data set]. https://data.depositar.io/en/dataset/coral-reef-sesoko
Tzu-Hao Lin, Colin K. C. Wen. (2020). Algal Reef Soundscapes at Taoyuan, Taiwan [Data set]. https://data.depositar.io/en/dataset/algae-reef-soundscape
Chong Chen, Tzu-Hao Lin, Hiromi Kayama Watanabe, Tomonari Akamatsu, Shinsuke Kawagucci (2021) Baseline soundscapes of deep-sea habitats reveal heterogeneity among ecosystems and sensitivity to anthropogenic impacts. Limnology and Oceanography, in press.
Tzu-Hao Lin, Tomonari Akamatsu, Yu Tsao (2021) Sensing ecosystem dynamics via audio source separation: a case study of marine soundscapes off northeastern Taiwan. PLoS Computational Biology, 17: e1008698.
Tzu-Hao Lin, Tomonari Akamatsu, Frederic Sinniger, Saki Harii (2020) Exploring coral reef biodiversity via underwater soundscapes. Biological Conservation, 253: 108901.
Joseph Heard, Wei-chen Tung, Yu-de Pei, Tzu-Hao Lin, Chien-Hsiang Lin, Tomonari Akamatsu, Colin KC Wen (2021) Coastal development threatens area supporting greatest fish diversity at Taoyuan Algal Reef, NW Taiwan. Aquatic Conservation: Marine and Freshwater Ecosystems, 3: 590-604.
Tzu-Hao Lin, Chong Chen, Hiromi Kayama Watanabe, Shinsuke Kawagucci, Tetsuya Miwa, Hiroyuki Yamamoto, Shinji Tsuchida, Yoshihiro Fujiwara (2020) Characterizing habitat-specific soundscapes in deep-sea benthic ecosystems. eDSBS 2020 (online conference).
Tzu-Hao Lin, Chong Chen, Hiromi Kayama Watanabe, Shinsuke Kawagucci, Hiroyuki Yamamoto, Tomonari Akamatsu (2019) Using soundscapes to assess deep-sea benthic ecosystems. Trends in Ecology & Evolution, 34: 1066-1069.
Tzu-Hao Lin, Hsin-Te Yang, Jie- Mao Huang, Chiou-Ju Yao, Yung-Shun Lien, Pei-Jung Wang, Fang-Yu Hu (2019) Evaluating changes in the marine soundscape of an offshore wind farm via the machine learning-based source separation. Underwater Technology 2019. DOI: 10.1109/UT.2019.8734295.
Open for Collaboration
The Ocean Biodiversity Listening Project was initiated since 2018. Please click each recording location on the map to check the list of project collaborators. We are continuing to seek collaborators and funding supports. Please contact us if you are interested in our project.
JSPS KAKENHI (18H06491, 19K21554)
Microsoft AI for Earth (2020)
Ministry of Science and Technology, Taiwan (MOST 109-2621-B-001-007-MY3)
Ocean Conservation Administration, Ocean Affairs Council (2021)