Soundscape Ecology Through Automated Acoustic-Based Biodiversity Indices

Soundscape Ecology Through Use of Automated Acoustic-Based Biodiversity Indices: A Test Using RCA Broadband Hydrophone Data. Adapted by OOI from Ferguson et al., 2023.

[media-caption path="" link="#"]Figure a) Location of Regional Cabled Array broadband hydrophones used in this study. b) Acoustic Complexity Index associated with mammal calls, fish sounds, and anthropogenic noise. (After Ferguson et al., 2023).[/media-caption]

Ferguson’s et al., 2003 paper explores the use of myriad biodiversity indices, generated by automated acoustic classifications, using data from three of the Regional Cabled Array (RCA) broadband hydrophones. As the authors point out, human in-the-loop evaluation of marine species and anthropogenic noise from very large data volumes generated by passive acoustic sensors is formidable. Yet, identification of marine organisms and anthropogenic noise is increasingly important for biodiversity conservation and ecosystem monitoring. Automated biodiversity indices have been utilized in terrestrial environments, but only limited studies have used machine learning to study soundscape ecology in marine systems. This study used broadband hydrophone (HYDBBA) data from Slope Base on the Shallow Profiler Mooring (200 m water depth and ~ 100 km offshore), at Oregon Offshore (580 m water depth and ~ 72 km offshore), and the Oregon Shelf site (80 m water depth and ~ 16 km offshore) (Figure 28a) to examine seven diversity indices. Note, these study sites are valuable to making progress in soundscape ecology because the Cascadia Margin is characterized by very high biological productivity impacted by the California current, it is the site of intense shipping lanes, and because of the availability of continuous, real-time acoustic data streams provide by the RCA.

In this initial study, Ferguson et al., evaluated one month of data from the three sites: January 2017 for HYBDDA 103 and 106 and April 2018 for HYBDDA 105. Five minute files were used with 7,101 files for Slope Base, 4,725 files for Oregon Offshore, and 6,410 files for the Oregon Shelf. Data from these instruments had been previously annotated, providing ground truthing for machine learning results. Periods of vocalization of marine mammals occurred less frequently at Slope Base. Three months of data were reviewed to examine periods of mammal vocalizations and anthropogenic sounds.

Identifying the relationship between numerous acoustic indices and species characteristics is complex and requires attention to a significant number of factors and computation of multiple tests, as described in detail in this paper. The Acoustic Complexity Index (ACI, Figure 28b), is generated from an algorithm to quantify biological sounds based on intensity, it is the most commonly used index to assess acoustic indices in marine systems, and has been demonstrated useful in identifying species diversity.  Results from this work show that ACI measurements increased during vocalizations by dolphins and sperm whales. However, evaluation of the seven indices show that biodiversity cannot be explicitly determined from any single acoustic index. A significant finding from this study is that true assessment of large-scale ecosystem health and changes in indicator species, which may be due to differences in seasonal and interannual variability, requires co-located physical and chemical oceanographic data. The authors note that the RCA and Endurance Array instrumentation provides “an ideal scenario for accurately monitoring system health”.


Ferguson, E.L., H.M. Clayton, and T. Sakai (2023) Acoustic Indices Respond to Marine Mammal Vocalizations and Sources of Anthropogenic Noise. Frontiers in Marine Science. 10:1025464; doi: 10.3389/fmars.2023.1025464.

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Update on RCA Broadband Hydrophone Data Availability, File Formats, and Directory Structure

As part of continuing OOI data process improvements, the RCA Data and OOI Software Development Teams have been working closely to expand data availability and improve data file consistency for six Broadband Hydrophones (HYDBBs) located at Axial Base (2), Slope Base (2), and Oregon Offshore (1) and Shelf (1) sites. Additional details are available on these study sites and instruments at these links.

A system update will go live at 17:00 UTC June 7, 2023 and will affect all HYDBB data posted on the Raw Data Archive server after that date.  In the near future, the updates will also be applied to historical HYDBB files previously posted on the Raw Data.

OOI HYDBB data are currently provided to the public on the OOI Raw Data Archive server as MiniSEED-formatted files (extension “.mseed”). This lossless, compressed format is a subset of the Standard for the Exchange of Earthquake Data (SEED) that is in extensive use for archiving and serving seismological data (see IRIS). The HYDBB MiniSEED files are served on the Raw Data Archive in daily subdirectories organized by year and month for each of the sites:

Once the system update goes live on June 7, all HYDBB data posted on the Raw Data Archive server after this date will have the following enhancements:

  • Currently, only HYDBB data arriving at the OOI data repository in near real-time are provided to the public in the daily subdirectories, updated at nominal 5-min intervals. After the system update, data arriving at the OOI repository after Navy review will also be made available on the Raw Data Archive. These delayed and previously publicly unavailable data will be provided as analogously named MiniSEED datafiles but in separate subdirectories named “addendum” under each daily directory.
  • Each individual MiniSEED file will include HYDBB data over fixed 5 min timespans, starting at 00:00 UTC and repeated at subsequent 5 min intervals (beginning at 00:05, 00:10 UTC, etc.). If no data are available for a specific 5 min timespan, the datafile will not be created. Any gaps in the data stream during each 5 min timespan are accounted for by the use of the multi-trace extension of the MiniSEED file format construct, which allows multiple temporal segments within a single file. Previously, each HYDBB file on the Raw Data Archive contained only a single continuous trace of data. An example Python toolbox for accessing/processing such MiniSEED data is available, with additional information on the ObsPy open-source project here.

This change in file construction will allow for more efficient access and delivery of HYDBB data, particularly when there are small and frequent gaps in the data streams which can lead to excessive file fragmentation, as was often the case with these data before this system update.

If you have any questions, please contact the OOI HelpDesk or post your question on the public OOI Discourse Forum. 


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An Overview of Ambient Sound Using OOI Hydrophones

Adapted and condensed by OOI from Ragland, et al., 2022,

[media-caption path="/wp-content/uploads/2022/11/RCA-highlight.png" link="#"]Figure 1: Highlights of acoustic features from the five low frequency (Fs=200Hz) and six broadband (Fs = 64 kHz) hydrophones on the RCA.[/media-caption]

Ragland et al., (2022) provides a wonderful overview of the unique opportunities for data and experimentally driven advancements in acoustics that are provided by (long-term) ambient sound recordings streamed live from hydrophones on the Regional Cabled Array. Figure 1, above (after Figure 5, Ragland et al., 2022), highlights acoustic features from the five low frequency (Fs=200Hz) and six broadband (Fs = 64 kHz) hydrophones on the RCA. Areas of research span the rare ability to conduct offshore monitoring of Fin whale migration, and the seasonal fluctuations and decade-long evolution of their calls, in situ offshore meteorological measurements with high temporal resolution to study wind and rain noise in the NE Pacific, the sound from commercial ships with impacts on the oceanic environment and marine life, ambient noise interferometry, volcanic eruptions, and both local and far-field earthquakes. As the authors note, the RCA-OOI data also provide significant opportunities for the development of machine learning tools for ocean acoustics. This work was supported by an award from the Office of Navy Research. The authors developed a public Python package (OOIPy) to access and explore the hydrophone data more easily (Schwock et al., 2021). OOIPy is also accessible through the OOI website tab Community Tools and Datasets.


Ragland, J., F. Schwock, M. Munson, and S. Abadi (2022) Journal of the Acoustic Society of America, 151, 2085-2100,

Schwock, F., J. Ragland, L. Setiawan, M. Munson, D. Volodin, and S., Abadi (2021). OOIPY v1.1.3: A Python toolbox designed to aid in the scientific analysis of Ocean Observatories Initiative data,


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