In 2018 the Global Ocean Observing System (GOOS) approved Ocean Sound as an Essential Ocean Variable (EOV) within the Biology and Ecosystems Panel. This designation recognized that long-term monitoring of sound in the ocean will yield information on ecosystem health, climate change, and the effects of human activity on the environment. The bulk of the current ocean acoustic data collection is performed by archival recorders, supplemented by a small number of real-time gliders, buoys and cabled observatories.

Estimates of the population density of marine mammals in an area and the change in population over space and time are critical inputs for managing the interactions of human activity and mammal populations. Visual surveys from boats, shore stations, and aircraft have served as the basis for most population estimates currently used by managers. However, these survey methods are generally only performed in good weather conditions and require many trained observers. These factors make visual surveys expensive and reduce the temporal and spatial coverage of population estimates.

Estimates of the population density of marine mammals in an area and the change in population over space and time are critical inputs for managing the interactions of human activity and mammal populations. Visual surveys from boats, shore stations, and aircraft have served as the basis for most population estimates currently used by managers. However, these survey methods are generally only performed in good weather conditions and require many trained observers. These factors make visual surveys expensive and reduce the temporal and spatial coverage of population estimates.

Underwater acoustic propagation modeling was largely advanced by the world’s Navies from WWII until the early 2000’s. Growing evidence of the effects of sounds from human activities on marine life has made propagation modeling relevant to a much broader community including marine biologists, ecologists, regulators and environmental non-governmental organizations.

Several fish species produce species-specific sounds that can be identified in the wild using Passive Acoustic Monitoring (PAM) (i.e. dataloggers configured with underwater microphones). Our project will use existing and new PAM recordings to monitor the distribution of several fish species in the western Canadian Arctic, with particular focus on a keystone Arctic species, the Arctic cod (Boreogadus saida). Acoustic signal detection techniques will be implemented to identify fish sounds from large acoustic datasets.

Several fish species produce species-specific sounds that can be identified in the wild using Passive Acoustic Monitoring (PAM) (i.e. dataloggers configured with underwater microphones). Our project will use existing and new PAM recordings to monitor the distribution of several fish species in the western Canadian Arctic, with particular focus on a keystone Arctic species, the Arctic cod (Boreogadus saida). Acoustic signal detection techniques will be implemented to identify different fish species from large acoustic datasets.