June 2025 | Oceanography
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directional passive acoustic dataset and associated environmen
tal time series from an acoustically undersampled region of the
United States Exclusive Economic Zone along the southeast
ern OCS. Data collected are applicable to marine spatial plan
ning and ecosystem-based management, and they also pro
vide a mechanistic understanding of cumulative impacts on
marine resources. ADEON acquired measurements and devel
oped objective metrics that enabled a quantitative assessment
of the Mid- and South Atlantic Ocean region soundscape, with
consideration of ecosystem conditions, as they may be linked
to extant biologic, geophysical-chemical, and/or anthropogenic
processes. Consideration was also given to resolving periodic
ities in regional processes over long timescales to establish an
acoustic baseline for extracting trends and for comparing to his
torical oceanographic time series in the region.
ADEON MULTI-PLATFORM APPROACH
The backbone of the measurement program was the ALTO
lander developed by JASCO Applied Sciences specifically for
the ADEON program (Figure 1b). The lander sensors included
a passive, four-channel autonomous acoustic recorder (AMAR),
a four-frequency echo sounder (Acoustic Zooplankton Fish
Profiler – AZFP by ASL Environmental Sciences, Canada), a
VEMCO VR2W fish tag receiver, and a Sea-Bird-37 CT-DO
unit. This combination of technology is transferable and relo
catable and has been successfully deployed by other projects and
in additional regions since the conclusion of ADEON, including
AEON (Acoustic and Environmental Observation Network in
the NW Atlantic; https://eos.unh.edu/aeon), multiple projects to
monitor the movement of marine mammals around oil and gas
developments off Canada and Australia, and many wind farm
developments in the United States, Scotland, and Australia.
Lander sites were selected by considering ecological rele
vance, diversity of anthropogenic activities, 200–900 m target
depth range (with three sites less than 400 m deep to accommo
date the echosounder depth maximum), sufficient along-shelf
and across-shelf comparisons, and locations of other known
observation assets to support the analysis of soundscape por
tability (Figure 1c,d). Five University-National Oceanographic
Laboratory System (UNOLS) cruises were devoted to servic
ing lander deployments, turnarounds, and recovery and also
supported vessel-based, biological net tows performed during
fine-scale acoustic surveys (FSASs) of water column backscat
ter, marine mammal surveys, full water column CTD casts,
and acoustic propagation characterization at each lander loca
tion. Kowarski et al. (2022) present the details of the deploy
ment dates, durations, and AMAR lander passive acoustic
array parameters.
The landers were deployed from November/December 2017
to December 2020. The four-channel AMARs sampled approx
imately 45 minutes of each hour, alternating between a single
channel at 16 kHz sampling rate for 20 minutes, all four channels
at 16 kHz for 20 minutes, and a high frequency 512 kHz sam
pling rate for a total of five minutes. The echo sounder system
sampling for 10–12 minutes each hour occurred during the por
tion of the hour when the AMAR was sleeping to eliminate con
tamination of the passive acoustic recordings. The AZFP emitted
a 750 μs ping every four seconds during the 10–12 minute sam
pling period. The CT-DO unit sampled every 30 minutes.
To link the long-term measurements to environmental con
ditions, the network design included remote sensing of oceanic
and atmospheric variables to be used as covariates in the eco
system and soundscape models. These data included: (1) auto
mated identification system (AIS) ship tracks, (2) sea sur
face temperature (a combination of data from the NASA Jet
Propulsion Laboratory [JPL] and Copernicus), (3) chlorophyll a
concentrations obtained from the NASA-NOAA Visible Infrared
Imaging Radiometer Suite (VIIRS) onboard the Suomi National
Polar-orbiting Partnership (SNPP) satellite, (4) net primary pro
ductivity derived from NASA using the Vertically Generalized
Production Model (VGPM) by Behrenfeld and Falkowski (1997),
(5) mixed layer depth derived from the Hybrid Coordinate
Ocean Model (HYCOM), (6) wind speed and direction from
the Advanced SCATterometer (ASCAT) real aperture sensor
onboard the meteorological operational platforms of the French
Institute for Ocean Science (IFREMER), and (7) upper surface
current speed and direction from the Ocean Surface Current
Analysis Real-time (OSCAR) project at JPL. The final element of
the network design incorporated mobile measurements that pro
vided a broader context for the long-term measurements. These
consisted of data from the FSASs performed by the lander ser
vice vessel, a horizontal array of hydrophones towed by a drifting
sailboat, and an autonomous sailboat that measured variability
of the soundscape between lander locations and across the Gulf
Stream—the dominant regional oceanographic feature.
ADEON STANDARDS
The standardization component of ADEON increased the value
of its data by providing products comparable to data from other
national and international acoustic programs. ADEON adopted
the international standard for underwater acoustical terminol
ogy ISO 18405 Underwater acoustics – Terminology (ISO 18405,
2017; Ainslie et al., 2021), compatible with the International
System of Units (BIPM 2019) and the International System of
Quantities (ISO 80000-8 Quantities and units – Acoustics). A
dictionary of terms was created to facilitate internal commu
nication among project team members as well as with exter
nal stakeholders. The ADEON Project Dictionary: Terminology
Standard (https://doi.org/10.6084/m9.figshare.12436199.v2) was
also used by the Joint Monitoring Programme for Ambient Noise
in the North Sea (JOMOPANS; Robinson and Wang, 2021), the
EU’s SATURN program (Ainslie et al., 2024), and ISO/DIS 7605
Underwater Acoustics—Measurement of Underwater Ambient
Sound
(https://www.iso.org/standard/82844.html).
ADEON