Acoustic features as a tool to visualize and explore marine soundscapes: Applications illustrated using marine mammal passive acoustic monitoring datasets.

Passive Acoustic Monitoring (PAM) is emerging as a solution for monitoring species and environmental change over large spatial and temporal scales. However, drawing rigorous conclusions based on acoustic recordings is challenging, as there is no consensus over which approaches are best suited for characterizing marine acoustic environments. Here, we describe the application of multiple machine-learning techniques to the analysis of two PAM datasets.

Trends in summer presence of fin whales in the Western Mediterranean Sea Region: new insights from a long-term monitoring program.

Background: The Mediterranean subpopulation of fin whale (Linnaeus, 1758) has recently been listed as Vulnerable by the IUCN Red List of threatened species. The species is also listed as species in need of strict protection under the Habitat Directive and is one of the indicators for the assessment of Good Environmental Status under the MSFD. Reference values on population abundance and trends are needed in order to set the threshold values and to assess the conservation status of the population.

Noise exposure from commercial shipping for the southern resident killer whale population.

This study assesses vessel-noise exposure levels for Southern Resident Killer Whales (SRKW) in the Salish Sea. Kernel Density Estimation (KDE) was used to delineate SRKW summer core areas. Those areas were combined with the output of a regional cumulative noise model describing sound level variations generated by commercial vessels (1/3-octave-bands from 10 Hz to 63.