Time-frequency characterization and classification, temporal-spatial, spectral, and source level distributions of fin whale vocalizations in the Norwegian Sea observed with a coherent hydrophone array

The vocalization behavior of fin whales in the Norwegian and Barents Seas is monitored and studied using the Passive Ocean Acoustic Waveguide Remote Sensing (POAWRS) technique. The POAWRS technique is employed to provide detection, bearing-time estimation, time-frequency characterization and classif...

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Online Access:http://hdl.handle.net/2047/D20316367
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Summary:The vocalization behavior of fin whales in the Norwegian and Barents Seas is monitored and studied using the Passive Ocean Acoustic Waveguide Remote Sensing (POAWRS) technique. The POAWRS technique is employed to provide detection, bearing-time estimation, time-frequency characterization and classification, as well as localization and geographic positioning of the fin whale vocalizations received instantaneously over wide areas greater than 10,000 km^2. The observations were made from 18 February to 08 March 2014 in several regions of the Norwegian and Barents Seas coinciding with the spawning season and grounds for three commercially and ecologically important fish species: the Atlantic herring (Clupea harengus) off the coast of Alesund, the Atlantic cod (Gadus morhua) off the Lofoten archipelago, and the capelin (Mallotus villosus) off the Northern Finnmark coast. For marine mammals that are top predators, such as the fin whale, the concentrated fish migrations and spawnings are a tremendous source of prey. Since the fin whale is currently on the endangered species list, it is unclear how the recovery of fin whales will impact large oceanic fish stocks in terms of future harvesting potential. It is, therefore, of crucial importance to develop methodologies to observe fin whales over wide areas, such as developing a specific level of array processing to effectively detect specific types of fin whale vocalizations, and gather the information required to understand their behavior, such as their interaction with fish species. In addition, millions of acoustic signals can be received by the POAWRS system per day and are classified by visual inspection and using unsupervised clustering algorithms. This method of classification is performed during post-processing of the data and is a barrier to identifying fin whales vocalizations and other individual sound sources in near real-time. A near real-time detection and classification system is essential for organizations that are required to comply with federal laws and ...