The Next Wave of Passive Acoustic Data Management: How Centralized Access Can Enhance Science

Abstract

Passive acoustic data collection has grown exponentially over the past decade resulting in petabytes of data that document our ocean soundscapes. This effort has resulted in two big data challenges: (1) the curation, management, and global dissemination of passive acoustic datasets and (2) efficiently extracting critical information and comparing it to other datasets in the context of ecosystem-based research and management. To address the former, the NOAA National Centers for Environmental Information recently established an archive for passive acoustic data. This fast-growing archive currently contains over 100 TB of passive acoustic audio files mainly collected from stationary recorders throughout waters in the United States. These datasets are documented with standards-based metadata and are freely available to the public. To begin to address the latter, through standardized processing and centralized stewardship and access, we provide a previously unattainable comparison of first order sound level-patterns from archived data collected across three distinctly separate long-term passive acoustic monitoring (PAM) efforts conducted at regional and national scales: NOAA/National Park Service Ocean Noise Reference Station Network, the Atlantic Deepwater Ecosystem Observatory Network, and the Sanctuary Soundscape Monitoring Project. Nine sites were selected from these projects covering the Alaskan Arctic, Northeast and Central Pacific, Gulf of Mexico, Caribbean Sea, and Mid and Northwest Atlantic. Sites could generally be categorized into those strongly influenced by anthropogenic noise (e.g., vessel traffic) and those that were not. Higher sound levels, specifically for lower frequencies (<125 Hz), and proximity to densely populated coastal zones were common characteristics of sites influenced by anthropogenic noise. Conversely, sites with lower overall sound levels and away from dense populations resulted in soundscape patterns influenced by biological sources. Seasonal variability in sound levels across selected decidecade bands was apparent for most sites and often represented changes in the presence or behavior of sound-producing species. This first order examination of levels across projects highlights the utility of these initial metrics to identify patterns that can then be examined in more detail. Finally, to help the PAM community collectively and collaboratively move forward, we propose the next frontier for scalable data stewardship, access, and processing flow.