Measuring the Marine Soundscape of the Indian Ocean with Southern Elephant Seals Used as Acoustic Gliders of Opportunity

Abstract

The underwater ambient sound field contains quantifiable information about the physical and biological marine environment. The development of operational systems for monitoring in an autonomous way the underwater acoustic signal is necessary for many applications, such as meteorology and biodiversity protection. This paper develops a proof-of-concept study on performing marine soundscape analysis from acoustic passive recordings of free-ranging biologged southern elephant seals (SES). A multivariate multiple linear regression (MMLR) framework is used to predict the measured ambient noise, modeled as a multivariate acoustic response, from SES (depth, speed, and acceleration) and environmental (wind) variables. Results show that the acoustic contributions of SES variables affect mainly low-frequency sound pressure levels (SPLs), while frequency bands above 3 kHz are less corrupted by SES displacement and allow a good measure of the Indian Ocean soundscape. Also, preliminary results toward the development of a mobile embedded weather sensor are presented. In particular, wind speed estimation can be performed from the passive acoustic recordings with an accuracy of 2 m s−1, using a rather simple multiple linear model.

Animal-Borne Telemetry: An Integral Component of the Ocean Observing Toolkit

“…These data are central to understanding global climate processes given this region's central role in heat and CO2 uptake and unhindered (land barrier free) distribution of climate signals (Sallée, 2018). New sensors also provide expanding opportunities to monitor additional parameters, such as chlorophyll (Guinet et al, 2013) or the wind/wave surface state from accelerometry and magnetometry or hydrophony (Cazau et al, 2017). The current state of development and some of the limitations of integrating animal telemetry with oceanography are reviewed below, with specific focus on advances in technology and scientific findings.…”

“…Developments include new, small, low-power sensors that sample additional parameters capable at extremely low duty cycles to allow for continuous monitoring of animals. Sensors for fluorescence (Guinet et al, 2013), oxygen (Bailleul et al, 2015), light levels (Teo et al, 2004), sound (Cazau et al, 2017), acceleration (Carroll et al, 2014(Carroll et al, , 2016Cox et al, 2018), and active sonar (Lawson et al, 2015) have all been deployed (Figure 1) but most require refinement. Each of these contribute to a better understanding of the link between physical, biogeochemical, and ecological processes.…”

The Use of Underwater Gliders as Acoustic Sensing Platforms

“…Due to the advantages in terms of self-noise and duration, as well as the flexibility for acoustic payload installation [5,6], gliders are considered to have great potential in ocean acoustics applications, for example, studying whales [7,8] and fish sounds [9], acoustic sources detection and tracking [10][11][12], and measuring the marine soundscape [13]. In [8], a real-time passive acoustic monitoring device was developed and installed in the glider, which detected and classified 14 types of calls from four species of baleen whales.…”

“…In [9], a glider integrated with a single hydrophone was deployed on the West Florida Shelf to detect and map fish sounds. Cazau [13] developed an acoustic glider to measure the marine soundscape by using acoustic recordings from southern elephant seals. The results showed that the system performed good measurements of the Indian Ocean soundscape.…”

Do Southern Elephant Seals Behave Like Weather Buoys?

“…Seals were also used to quantify phytoplankton concentration (Guinet et al, 2013) and to collect data for the first complete assessment of dense shelf water formation in Prydz Bay, which improved understanding of the production of globally important Antarctic Bottom Water (Williams et al, 2016). SES were also used as acoustic gliders of opportunity to estimate above-surface meteorological conditions from ocean ambient noise, with promising results obtained for wind speed estimation by Cazau et al (2017), with an accuracy error of 2 m s -1 . The full list of papers using MEOP data, categorized into oceanography and biology, is available from: http://meop.net/publications.html.…”