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Quantifying Loss of Acoustic Communication Space for Right Whales in and around a U.S. National Marine Sanctuary

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Quantifying Loss of Acoustic Communication Space for Right Whales in and around a U.S. National Marine Sanctuary

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The effects of chronic exposure to increasing levels of human-induced underwater noise on marine animal populations reliant on sound for communication are poorly understood. We sought to further develop methods of quantifying the effects of communication masking associated with human-induced sound on contact-calling North Atlantic right whales (Eubalaena glacialis) in an ecologically relevant area (∼10,000 km2) and time period (peak feeding time). We used an array of temporary, bottom-mounted, autonomous acoustic recorders in the Stellwagen Bank National Marine Sanctuary to monitor ambient noise levels, measure levels of sound associated with vessels, and detect and locate calling whales. We related wind speed, as recorded by regional oceanographic buoys, to ambient noise levels. We used vessel-tracking data from the Automatic Identification System to quantify acoustic signatures of large commercial vessels. On the basis of these integrated sound fields, median signal excess (the difference between the signal-to-noise ratio and the assumed recognition differential) for contact-calling right whales was negative (−1 dB) under current ambient noise levels and was further reduced (−2 dB) by the addition of noise from ships. Compared with potential communication space available under historically lower noise conditions, calling right whales may have lost, on average, 63–67% of their communication space. One or more of the 89 calling whales in the study area was exposed to noise levels ≥120 dB re 1 μPa by ships for 20% of the month, and a maximum of 11 whales were exposed to noise at or above this level during a single 10-min period. These results highlight the limitations of exposure-threshold (i.e., dose-response) metrics for assessing chronic anthropogenic noise effects on communication opportunities. Our methods can be used to integrate chronic and wide-ranging noise effects in emerging ocean-planning forums that seek to improve management of cumulative effects of noise on marine species and their habitats. Cuantificación de la Pérdida de Espacio de Comunicación Acústica para Ballenas Francas Dentro y Alrededor de un Santuario Marino Nacional en E. U. A. Los efectos de la exposición crónica a niveles cada vez mayores de ruido submarino inducido por humanos sobre poblaciones de animales marinos dependientes del sonido para comunicarse están poco entendidos. Buscamos desarrollar métodos para cuantificar los efectos del enmascaramiento de la comunicación asociados con sonidos inducidos por humanos sobre el llamado de contacto de ballenas francas (Eubalaena glacialis) en un área ecológicamente relevante (∼ 10,000 km2) y período de tiempo (tiempo pico de alimentación). Utilizamos un conjunto de grabadoras acústicas autónomas, temporales, montadas en el fondo en el Santuario Marino Nacional Banco Stellwagen para monitorear los niveles de sonido ambiental, medir los niveles de sonido asociados con embarcaciones y detectar y localizar llamadas de ballenas. Relacionamos la velocidad del viento, registrada por boyas oceanográficas regionales, con los niveles de sonido ambiental. Utilizamos datos de embarcaciones rastreadoras del Sistema de Identificación Automática para cuantificar las sintonías de embarcaciones comerciales mayores. Con base en estos campos de sonido integrados, la mediana del exceso de señal (la diferencia entre la relación señal-ruido y el diferencial de reconocimiento asumido) para contactar ballenas francas llamadoras fue negativo (−1 dB) bajo niveles de sonido ambiental actuales y disminuyó (−2 dB) con la adición del ruido de los barcos. En comparación con el espacio de comunicación potencial disponible bajo condiciones de ruido históricamente más bajas, las ballenas pueden haber perdido, en promedio 63–67% de su espacio de comunicación. Una o más de las 189 ballenas llamadoras en el área de estudio estuvieron expuestas a niveles de ruido ≥120dB re1μPa de barcos durante 20% del mes, (y un máximo de 11 ballenas estuvo expuesto a ruido en o por arriba de este nivel durante un solo período de 10 minutos. Estos resultados resaltan las limitaciones de las medidas de exposición-umbral (i.e., dosis-respuesta) para evaluar los efectos del ruido antropogénico crónico sobre las oportunidades de comunicación. Nuestros métodos pueden ser utilizados para integrar los efectos de ruido crónico y de amplio rango en los foros emergentes sobre planeación marina que buscan mejorar el manejo de los efectos acumulativos del ruido sobre especies marinas y sus hábitats.
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Contributed Paper
Quantifying Loss of Acoustic Communication Space
for Right Whales in and around a U.S. National
Marine Sanctuary
LEILA T. HATCH,CHRISTOPHER W. CLARK,† SOFIE M. VAN PARIJS,‡ ADAM S. FRANKEL,§
AND DIMITRI W. PONIRAKIS†
Stellwagen Bank National Marine Sanctuary, NOAA National Ocean Service, 175 Edward Foster Road, Scituate, MA 02066, U.S.A.,
email leila.hatch@noaa.gov
†Bioacoustics Research Program, Cornell Laboratory of Ornithology, 159 Sapsucker Woods Road, Ithaca, NY 14850, U.S.A.
‡Northeast Fisheries Science Center, NOAA Fisheries, 166 Water Street, Woods Hole, MA 02543, U.S.A.
§Marine Acoustics, Inc., 4100 Fairfax Drive #730, Arlington, VA 22203, U.S.A.
Abstract: The effects of chronic exposure to increasing levels of human-induced underwater noise on marine
animal populations reliant on sound for communication are poorly understood. We sought to further develop
methods of quantifying the effects of communication masking associated with human-induced sound on
contact-calling North Atlantic right whales (Eubalaena glacialis) in an ecologically relevant area (10,000 km2)
and time period (peak feeding time). We used an array of temporary, bottom-mounted, autonomous acoustic
recorders in the Stellwagen Bank National Marine Sanctuary to monitor ambient noise levels, measure
levels of sound associated with vessels, and detect and locate calling whales. We related wind speed, as
recorded by regional oceanographic buoys, to ambient noise levels. We used vessel-tracking data from the
Automatic Identification System to quantify acoustic signatures of large commercial vessels. On the basis
of these integrated sound fields, median signal excess (the difference between the signal-to-noise ratio and
the assumed recognition differential) for contact-calling right whales was negative (1 dB) under current
ambient noise levels and was further reduced (2 dB) by the addition of noise from ships. Compared with
potential communication space available under historically lower noise conditions, calling right whales may
have lost, on average, 63–67% of their communication space. One or more of the 89 calling whales in the
study area was exposed to noise levels 120 dB re 1 μPa by ships for 20% of the month, and a maximum of
11 whales were exposed to noise at or above this level during a single 10-min period. These results highlight
the limitations of exposure-threshold (i.e., dose-response) metrics for assessing chronic anthropogenic noise
effects on communication opportunities. Our methods can be used to integrate chronic and wide-ranging
noise effects in emerging ocean-planning forums that seek to improve management of cumulative effects of
noise on marine species and their habitats.
Keywords: endangered species, marine protected area, marine spatial planning, underwater noise
Cuantificaci´
on de la P´
erdida de Espacio de Comunicaci´
on Ac´
ustica para Ballenas Francas Dentro y Alrededor de
un Santuario Marino Nacional en E. U. A.
Resumen: Los efectos de la exposici´
on cr´
onica a niveles cada vez mayores de ruido submarino inducido
por humanos sobre poblaciones de animales marinos dependientes del sonido para comunicarse est´
an poco
entendidos. Buscamos desarrollar m´
etodos para cuantificar los efectos del enmascaramiento de la comu-
nicaci´
on asociados con sonidos inducidos por humanos sobre el llamado de contacto de ballenas francas
Paper submitted July 1, 2011; revised manuscript accepted May 4, 2012.
1
Conservation Biology, Volume **, No. *, ***–***
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2012 Society for Conservation Biology
DOI: 10.1111/j.1523-1739.2012.01908.x
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4. TITLE AND SUBTITLE
Quantifying Loss of Acoustic Communication Space for Right Whales in
and around a U.S. National Marine Sanctuary
5a. CONTRACT NUMBER
5b. GRANT NUMBER
5c. PROGRAM ELEMENT NUMBER
6. AUTHOR(S) 5d. PROJECT NUMBER
5e. TASK NUMBER
5f. WORK UNIT NUMBER
7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES)
NOAA National Ocean Service,Stellwagen Bank National Marine
Sanctuary,159 Sapsucker Woods Road,Ithaca,NY,14850
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REPORT NUMBER
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Approved for public release; distribution unlimited
13. SUPPLEMENTARY NOTES
Preprint, Conservation Biology, Volume **, No. *, ***?*** published online 14 AUG 2012,Government or
Federal Purpose Rights License
14. ABSTRACT
The effects of chronic exposure to increasing levels of human-induced underwater noise on marine animal
populations reliant on sound for communication are poorly understood. We sought to further develop
methods of quantifying the effects of communication masking associated with human-induced sound on
contact-calling North Atlantic right whales (Eubalaena glacialis) in an ecologically relevant area
(∼10,000 km2) and time period (peak feeding time). We used an array of temporary,
bottom-mounted, autonomous acoustic recorders in the Stellwagen Bank National Marine Sanctuary to
monitor ambient noise levels, measure levels of sound associated with vessels, and detect and locate calling
whales. We related wind speed, as recorded by regional oceanographic buoys, to ambient noise levels. We
used vessel-tracking data from the Automatic Identification System to quantify acoustic signatures of large
commercial vessels. On the basis of these integrated sound fields, median signal excess (the difference
between the signal-to-noise ratio and the assumed recognition differential) for contact-calling right whales
was negative (−1 dB) under current ambient noise levels and was further reduced (−2 dB) by
the addition of noise from ships. Compared with potential communication space available under
historically lower noise conditions, calling right whales may have lost, on average, 63?67% of their
communication space. One or more of the 89 calling whales in the study area was exposed to noise levels
≥120 dB re 1 μPa by ships for 20% of the month, and a maximum of 11 whales were exposed
to noise at or above this level during a single 10-min period. These results highlight the limitations of
exposure-threshold (i.e., dose-response) metrics for assessing chronic anthropogenic noise effects on
communication opportunities. Our methods can be used to integrate chronic and wide-ranging noise effects
in emerging ocean-planning forums that seek to improve management of cumulative effects of noise on
marine species and their habitats.
15. SUBJECT TERMS
16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF
ABSTRACT
Same as
Report (SAR)
18. NUMBER
OF PAGES
13
19a. NAME OF
RESPONSIBLE PERSON
a. REPORT
unclassified b. ABSTRACT
unclassified c. THIS PAGE
unclassified
Standard Form 298 (Rev. 8-98)
Prescribed by ANSI Std Z39-18
2Communication Masking of Right Whales
(Eubalaena glacialis) en un ´
area ecol´
ogicamente relevante (10,000 km2) y per´
ıodo de tiempo (tiempo pico
de alimentaci´
on). Utilizamos un conjunto de grabadoras ac´
usticas aut´
onomas, temporales, montadas en el
fondo en el Santuario Marino Nacional Banco Stellwagen para monitorear los niveles de sonido ambien-
tal, medir los niveles de sonido asociados con embarcaciones y detectar y localizar llamadas de ballenas.
Relacionamos la velocidad del viento, registrada por boyas oceanogr´
aficas regionales, con los niveles de
sonido ambiental. Utilizamos datos de embarcaciones rastreadoras del Sistema de Identificaci´
on Autom´
atica
para cuantificar las sinton´
ıas de embarcaciones comerciales mayores. Con base en estos campos de sonido
integrados, la mediana del exceso de se˜
nal (la diferencia entre la relaci´
on se˜
nal-ruido y el diferencial de
reconocimiento asumido) para contactar ballenas francas llamadoras fue negativo (1 dB) bajo niveles de
sonido ambiental actuales y disminuy´
o(2 dB) con la adici´
on del ruido de los barcos. En comparaci´
on
con el espacio de comunicaci´
on potencial disponible bajo condiciones de ruido hist´
oricamente m´
as bajas,
las ballenas pueden haber perdido, en promedio 63–67% de su espacio de comunicaci´
on. Una o m´
as de las
189 ballenas llamadoras en el ´
area de estudio estuvieron expuestas a niveles de ruido 120dB re1μPa de
barcos durante 20% del mes, (y un m´
aximo de 11 ballenas estuvo expuesto a ruido en o por arriba de este
nivel durante un solo per´
ıodo de 10 minutos. Estos resultados resaltan las limitaciones de las medidas de
exposici´
on-umbral (i.e., dosis-respuesta) para evaluar los efectos del ruido antropog´
enico cr´
onico sobre las
oportunidades de comunicaci´
on. Nuestros m´
etodos pueden ser utilizados para integrar los efectos de ruido
cr´
onico y de amplio rango en los foros emergentes sobre planeaci´
on marina que buscan mejorar el manejo
de los efectos acumulativos del ruido sobre especies marinas y sus h´
abitats.
Palabras Clave: ´
area marina protegida, especies en peligro, planificaci´
on espacial marina, ruido submarino
Introduction
The potential effects of underwater noise produced by
human activities on marine animals have been recognized
for over 40 years (Payne & Webb 1971; Myrberg 1980;
Møhl 1981). Most attention has focused on short-term ef-
fects associated with high-intensity sounds from purpose-
ful signals (e.g., seismic air guns, military active sonars)
and incidental noises (e.g., pile driving, bow thrusters)
produced by human activities in close proximity to ma-
rine animals (e.g., NRC 2000; Southall et al. 2007). More
recently, several reports and studies addressing ocean
noise have highlighted effects associated with longer-
term exposure to lower-intensity human-induced noise
sources that affect animals over much larger spatial ex-
tents (e.g., Clark et al. 2009; Hatch & Fristrup 2009).
These chronic effects may be more substantial than short-
term acute effects over spatial and temporal extents rele-
vant to marine animals that rely on acoustic communica-
tion (e.g., Clark et al. 2009).
Recent studies have focused on characterizing how
chronic noise reduces the area over which species such
as large whales are able to exchange information or hear
important environmental cues. Møhl (1981) considered
the loss in a receiving animal’s ability to detect signals in
the face of increased ambient noise. Clark et al. (2009)
quantified the loss of acoustic habitat or “communication
space” available to calling, not receiving, baleen whales
due to the obscuring of their signals by low-frequency
anthropogenic noise sources, a phenomenon referred
to as “communication masking.” Due to their endan-
gered status in most international waters, the reliance
of baleen whales on low-frequency sounds for feeding,
navigating, and reproducing and the overlap between
their communication frequencies and the frequencies of
most chronic noise produced by human activities, the
effects of masking on baleen whales have been identified
as a primary concern. Noise from large commercial ves-
sels dominates low-frequency underwater background
noise (Richardson et al. 1995) and is increasing (Andrew
et al. 2002; McDonald et al. 2006); thus, commercial ship-
ping has been identified as a primary noise-management
concern.
Ships introduce a variety of noise-exposure patterns
that vary in intensity over space, time, and frequency. In
areas with UN International Maritime Organization (IMO)
routes for commercial vessels (i.e., shipping lanes), the
density of transient-noise peaks is proportional to the
number of ships, whereas the levels of transient-noise
peaks are primarily dependent on ship distances. The
overall effect is that cumulative noises from vessels in
high-traffic areas near shipping lanes and ports gener-
ate a variable pattern of transient-noise peaks on top of
an elevated background noise level that, on average, is
omnipresent. These variances in cumulative noise deter-
mine the communication spaces available to calling and
listening baleen whales. To assess the effects of changes
in communication space, communication masking must
be quantified (Clark et al. 2009) over sufficiently long
periods and large areas so as to be biologically relevant
and to accurately represent natural and human-induced
noise contributions at those scales. We characterized the
effects of communication masking on calling North At-
lantic right whales (Eubalaena glacialis) in an ecologi-
cally relevant area (approximately 10,000 km2surround-
ing and including the Stellwagen Bank National Marine
Sanctuary [SBNMS]) and period (peak month in feeding
season).
Conservation Biology
Volume **, No. *, 2012
Hatch et al.3
Figure 1. Study area in and around the Stellwagen Bank National Marine Sanctuary (SBNMS), distribution of
large commercial vessels tracked with the Automatic Identification System (AIS) (black lines), locations of the 9
marine acoustic recording units (MARUs) in April 2008, locations of 2 fixed oceanographic buoys, and the
boundary of the SBNMS.
Methods
Data Collection
To maximize the number of foraging right whales present
in the study area and the percentage of overall traffic in
the area that could be accounted for with available track-
ing data, we choose April 2008 for this study (Support-
ing Information). Our study area encompassed all waters
within the SBNMS and surrounding waters (Fig. 1). An
array of 9 marine autonomous recording units (MARUs)
was deployed from 7 March to 28 May 2008 to record
continuously low-frequency sound (Fig. 1 & Supporting
Information). We compared empirical measurements of
received sound levels with levels predicted from multi-
ple sound propagation models (D. Cholewiak & A.S.F.,
unpublished data). Subsequently, we used the Bellhop
model (Porter 1992), informed by several environmen-
tal variables that influence sound propagation, to predict
transmission loss (loss of sound energy over distance be-
tween source and receiver) for both vessel and whale
sound sources (Supporting Information).
We identified and tracked all large commercial vessels
present within the study area in April 2008 with the U.S.
Coast Guard’s Automatic Identification System (AIS) (Fig.
1 & Supporting Information). We calculated minimum
great-circle distances (shortest distance between any 2
points on the surface of a sphere measured along a path
on the surface of the sphere) between vessel locations
and MARU locations to determine each vessel’s closest
point to the MARU.
Data Analyses
We divided the 9576 km2(90 km lat, 106 km long) study
area into 1-km2cells for modeling and thus had 7538
unique locations (locations on land were discarded). We
used the Acoustic Integration Model (Frankel et al. 2002)
to predict month-long series of 1-second/10-min (n=
4320) received sound levels (root mean square dB re
1μPa unless otherwise noted) associated with vessel and
whale sound sources throughout the modeling area and
within the frequency band containing the majority of
sound energy in right whale contact calls (71–224 Hz)
(Urazghildiiev & Clark 2006).
NOISE
We calculated the bottom 5th percentile received sound
levels for the 2 MARUs located closest to fixed oceano-
graphic buoys in Massachusetts Bay (GMOOS A01 and
NDBC 44013) (Fig. 1). We regressed these received
sound levels against wind speeds recorded at buoys
and used results to estimate present-day ambient noise
Conservation Biology
Volume **, No. *, 2012
4Communication Masking of Right Whales
levels (1-second/10-min) in the absence of AIS-tracked
discrete vessel signatures. In addition to contributions
from wind as a natural source of noise, estimates of ambi-
ent noise levels retain contributions from nondiscrete an-
thropogenic noise sources, including more distant ships.
We subtracted 10 dB from 1-second/10-min present-day
ambient noise estimates to represent hypothetical levels
of historical ambient noise. We used these approxima-
tions to represent the change in low-frequency ambient
noise levels since the mid 20th century, a period within
the lifetimes of many extant North Atlantic right whales.
The only time-series data sets on low-frequency ambi-
ent noise levels in Northern Hemisphere coastal waters
are from locations off the west coast of the United States
(Andrew et al 2002; McDonald et al. 2006), where these
levels include ocean-basin scale transmission of shipping
noise. Our study area was on the continental shelf where
most noise from ships occurs when they transit through
shelf waters.
Contemporary measurements taken in our study site
and from similar shallow water sites off the U.S. east-
ern seaboard show a 13 dB (Hatch et al. 2008, 2009) to
over 20 dB (Schiefele & Darre 2005) difference in av-
erage 71–224 Hz background noise between sites with
less versus more local vessel traffic. Rolland et al. (2012)
recorded an over 10 dB drop in background noise levels
at frequencies below 150 Hz at a location just north of
our study area after a short-term cessation of large com-
mercial vessel traffic following the terrorist attacks on 11
September 2001. Ambient noise levels recorded in wind-
only versus shipping-traffic conditions in 1982–1983 in a
shallow area also just north of our study site differed
by 10–15 dB in the 100–200 Hz band (Urick 1984).
Conditions labeled quiet during earlier studies often in-
cluded noise from shipping, although at nonquantifi-
able levels. Commonly referenced predictions for low-
frequency background noise levels derived from mea-
surements taken in the 1960–1980s are thus consistent
with contemporary empirical evidence that 10 dB is a
conservative delta value for low versus high traffic on the
continental shelf (for further discussion see Supporting
Information). Acknowledging uncertainty due to lack of
time-series data, but noting that motorized vessel traffic
was already well-established in coastal Massachusetts wa-
ters in the 1950s (Morry 1987), we also used historical
ambient noise levels 20 dB below modern-day levels in
calculations to explore the sensitivity of results to the
choice of historical-reference level.
We used times and locations of vessels passing within
10 km (5.4 nm) of a MARU to match vessel tracks with
acoustic records. When possible, we calculated average
received sound levels centered at the time of closest ap-
proach and used the Acoustic Integration Model to esti-
mate vessel source levels (intensity of sound at the vessel)
in the 71–224 Hz frequency band (Supporting Informa-
tion). The Acoustic Integration Model was subsequently
applied to predict source levels associated with the dura-
tion of each vessel’s transit through the area. We modeled
vessel sources 7 m below the surface to represent average
propeller depth across vessel types in the study area. We
applied directivity to the Acoustic Integration Model’s
calculation of noise levels produced by selected vessels
to account for known differences in sound propagating
from the bow, stern, and sides of ships. We calculated
transmission loss for every 15of relative bearing from
the ship’s bow (Supporting Information). We used Matlab
to sum all coincident vessel noise fields and thus created
a 1-second noise-field grid every 10 min throughout the
month (4320 frames). These frames collectively repre-
sented a time series of cumulative noise from multiple
AIS-tracked large commercial ships.
WHALES
We used an automatic detector (ISRAT) to identify all
right whale contact calls within the array (Urazghildiiev et
al. 2009). We used XBAT and correlation sum estimation
(Supporting Information) (K. Fristrup & K. Cortopassi,
unpublished) to compute locations (x, y) for 744 calls
with good signal-to-noise ratios (generally >10 dB). Lo-
calization was used to identify the spatial and temporal
characteristics of contact-calling whales. We calculated
noise-corrected received sound levels for 100 calls lo-
cated within 2 km of a MARU and estimated call source
levels on the basis of locations of calling whales and
Acoustic Integration Model calculations of transmission
loss (Supporting Information). We integrated the MARU-
derived acoustic detections of contact calls with visual-
sighting information from the U.S. National Oceanic and
Atmospheric Administration Northeast Fisheries Science
Center’s aerial surveys to create coarse estimates of den-
sity and distribution of calling right whales. We then used
the Acoustic Integration Model to model the acoustic be-
havior and movements of 89 artificial animals, referred to
as animats, on the basis of position and movement data
governed by preset parameters (Supporting Information)
(Frankel et al. 2002).
Data Integration
We used Matlab to sum 1-second/10-min gridded surfaces
for contact-calling right whales, hypothesized historical
ambient noise, present-day ambient noise, and present-
day AIS-tracked shipping noise to create month-long,
empirically based, 1 km2-resolution animations of pre-
dicted signal and noise-level variation. Signal excesses for
calling right whales relative to hypothesized historical
ambient, present-day ambient, hypothesized historical
ambient and present-day shipping, and present-day ambi-
ent and present-day shipping noise levels were calculated
as in Clark et al. (2009). We incorporated a detection
threshold of 10 dB and a signal-processing gain of 16 dB,
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Volume **, No. *, 2012
Hatch et al.5
resulting in a recognition differential of 6 dB (see Clark
et al. [2009] eqs. 10a–c). The recognition differential term
accounts for a right whale’s ability to successfully detect
and recognize a contact call in some circumstances in
which ambient noise levels exceed signal noise levels
(Clark et al. 2009). The benefits of this recognition term
are expressed as signal excess; the difference between
the signal-to-noise ratio and the recognition differential.
There is uncertainty in this parameter, although 6 dB is
likely a generous recognition differential for a mammalian
auditory system. Nevertheless, we also calculated recog-
nition differentials of 0 dB and 3 dB. For each 10-min
frame, we mapped summed noise levels (NLs) and signal
excesses under various noise levels. Spatial variation in
signal excess over all grid points and temporal variation
over all 10-min frames were summarized as bottom 5th
(quietest), 50th (median), and upper 95th (noisiest) per-
centiles. We selected 2 10-min frames from the month-
long series to illustrate noisier versus quieter periods.
We calculated indices of communication space and
communication masking for the modeled right whale
animats as a group (rather than as multiple individual
senders) by modifying the approach of Clark et al. (2009).
Signal-excess values per receiver grid point were scaled
and weighted by a probability of recognition term (see
eq. 12 in Clark et al. [2009]). This recognition term ac-
counts for an expected decrease in actual communication
occurring as the distance between senders and receivers
increases. We calculated indices of communication mask-
ing for every 10-min sample throughout the month; the
masking metric was the change in communication space
available to calling whales under hypothesized historical
noise levels relative to the communication space avail-
able under present-day ambient, shipping, and ambient
plus shipping levels. Masking values ranged from 0 (no
difference from historical) to 1 (complete loss of commu-
nication space available relative to hypothesized histor-
ical ambient levels). We averaged spatial variation over
all receiver grid points and temporal variation over all
10-min frames and summarized results as 5th, 50th, and
95th percentiles.
To provide a comparison between assessments of
noise effects derived from currently applied, exposure-
threshold-based metrics versus communication-space
quantifications, we calculated, for every 10-min frame
under present-day levels of shipping noise, the number
of right whales exposed to unweighted ambient noise
levels 120 dB in the 71–224 Hz band. Noise levels at
grid locations were converted from decibels to intensity
and linearly interpolated to determine noise levels at an-
imat locations (latitude and longitude only) per 10-min
frame. These methods did not allow us to differentiate
between unique and repeated events experienced by in-
dividual animats over sequential 10-min samples. How-
ever, total number of exposure events per day (number
of whales exposed to noise levels 120 dB in the 71–224
Hz band summed over all 10-min samples in a day) was
tabulated for the month. We used masking calculations to
compare percent loss of communication space for calling
whales under present-day shipping and present-day ship-
ping plus ambient noise levels with the number of right
whales exposed to noise levels 120 dB in the 71–224
Hz band over all 10-min samples in the month.
Results
Whales
We detected 22,423 right whale contact calls within the
MARU array (average [SD] =747 calls/day [294]). Aver-
age contact-calling rate was 0.47 calls/min (0.38) (n=86
calling bouts). Average contact call source level was 172
dB [6.6] in the 71–224 Hz band (n=100 calls). Eighty-
nine representative right whale animats were distributed
as follows: 27 in the southern sanctuary and Cape Cod
Bay (first region), 37 in a region surrounding the first re-
gion that encompassed the remainder of the sanctuary
and some additional inshore waters (second region), and
26 outside the second region, but within the remainder of
the modeling area. The median received sound levels of
the 89 contact-calling right whale animats, evaluated over
both the area and month of study, was 90 dB (minimum
76, maximum 150) in the 71–224 Hz band.
Noise
The bottom 5th percentile received sound levels for the
2 MARUs closest to the oceanographic buoys averaged
99 dB (SD 4.6) in the 71–224 Hz band. Measured wind
speeds (average 4.9 m/s [2.9]) correlated significantly
with 5th percentile received sound level summary statis-
tics (R2=0.034; analysis of variance F=5.7, p=0.02;
slope 0.16, intercept 96.1). We used this linear relation to
compute spatially uniform, but time-varying (10-min sam-
ple rate), present-day ambient noise levels in the 71–224
Hz band (median 98 dB, minimum 97, maximum 99).
Present-day ambient noise levels were similar to contem-
porary noise levels recorded at other shallow locations
along the U.S. east coast with moderate to heavy vessel
traffic. Hypothesized historical ambient noise levels (me-
dian 88 dB, minimum 87, maximum 89) were higher than
(and thus conservative relative to) noise levels recorded
at several low-traffic shallow locations similar to, within,
or predicted for our study area (Supporting Information).
The median noise level produced by all AIS-tracked
ships was 73 dB in the 71–224 Hz band (minimum 0,
maximum 196). The model analyses included transiting
of 117 vessels: 45 tugs or tows, 27 cargo or container
ships, 23 tankers, 10 military or law enforcement ves-
sels, 5 service or research vessels, 4 passenger vessels
(cruise ships, ferries, or yachts), and 3 fishing vessels. On
the basis of signal-to-noise ratio criteria, received sound
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6Communication Masking of Right Whales
Table 1. Summary of noise-level data by vessel type or class in the Stellwagen Bank National Marine Sanctuary study area in April 2008.
Average (SD) Average (SD) source Average (SD) Average (SD) Average (SD)
Vessel type Source sound source sound sound levelaspeed over minimum maximum
or class n levelalevela(measured) (measured +estimated) groundbdraught (m) draught (m)
Cargo 27 21 191 (6) 190 (6) 4 9 (2) 11 (2)
Liquified natural
gas tanker
3 3 188 (8) 188 (8) 5 10 (0.4) 11 (1)
Large tanker 16 14 192 (8) 192 (8) 3 8 (1) 11 (1)
Medium tanker 4 2 188 (6) 187 (4) 1 5 (0.5) 8 (1)
Large cruise 1 1 191 191 0 7 7
Small cruise 1 1 171 171 1 5 5
Ferry 1 0 168 2 nacnac
Yacht 1 0 150 0 3 3
Large military 1 0 185 0 nacnac
Medium military 9 1 162 159 (1) 1 8 (5) 8 (5)
Marine service 2 0 183 (3) 3 4 (3) 4 (3)
Pilot 1 0 165 11 1 1
Research 2 1 174 168 (8) 4 5 5 (0.4)
Tug 43 9 180 (11) 180 (1) 1 6 (3) 7 (3)
Pusher tug 2 1 179 177 (5) 0 6 (2) 8 (2)
Fishing 3 1 166 168 (3) 4 6 7 (1)
aUnit of measure: dB root mean square 71–224 Hz re 1 μPa.
bKnots (nautical miles/h).
cData not available.
levels at points closest to MARUs were used to estimate
source levels for 55 of the 70 vessels that transited within
10 km (5.4 nm) of an MARU. Empirical source levels
were highest for large tankers, cargo or container ships,
and large cruise ships and lowest for medium-sized mil-
itary or law enforcement vessels (Table 1). Empirically
based source levels were calculated for 22% of the tug
or tows, 78% of the cargo or container ships, 83% of the
tankers, 50% of the passenger vessels, 10% of the mili-
tary or law enforcement vessels, 20% of the service or
research vessels, and 33% of the fishing vessels. Average
source levels for all vessels of the same type (drawing
from both empirical and estimated or literature values)
were similar to averages for those measured empirically
(Table 1).
For 9 of the 16 types of vessels, the average SD for
speed over ground (hereafter speed) was <1.03 m/s (Ta-
ble 1). For 6 other vessel types, average speed SD was
1.5–2.6 m/s, and for a single-pilot vessel the speed SD
was 5.7 m/s. Differences between average minimum and
average maximum draughts per vessel type ranged from
0 to 3 m (AIS data) (Table 1).
Five cargo vessels and 2 cruise ships closely ap-
proached MARUs and had similar patterns of received
sound levels relative to bearing to the MARU: broadside
measures (30–140) were on average 5 dB higher than
stern and bow measures (0–30and 140–180). We used
this pattern to model sound propagation for all cargo
ships (n=27) and cruise ships (n=2). Directivity pat-
terns among the other vessel types were either not con-
sistent or sample sizes were too small to support altering
the default omnidirectional modeling pattern.
Signal Excess, Communication Masking, and Exposure to
Noise
Median signal excess for contact-calling right whales un-
der present-day ambient noise levels without shipping
noise was -1 dB (Fig. 2a), whereas median signal excess
for the same calling whales evaluated over the same area
and period under hypothesized historical ambient noise
levels was 9 dB (Fig. 2a). Median signal excess was posi-
tive (7 dB) in the presence of hypothesized historical am-
bient noise plus noise from ships (Fig. 2a), but was nega-
tive (median –2 dB) when noise from ships was added to
present-day ambient noise (Fig. 2a).
Communication masking under present-day ambient
levels was at least 0.60 for 95% (bottom 5th percentile) of
the month, a 60% loss of communication space relative
to hypothesized historical ambient levels (Fig. 2b). For
50% of the month, communication masking was 0.63,
a loss of 63% of the communication space available rela-
tive to hypothesized historical ambient noise levels. In the
presence of only shipping noise, for 50% of the month,
communication masking was 0.14, a 14% loss of commu-
nication space relative to hypothesized historical noise
levels. For 5% of the month, however, communication
masking due to shipping noise alone was 0.38, a loss of
38% of the communication space relative to hypothe-
sized historical levels (Fig. 2b). Under present-day ambi-
ent plus shipping noise, masking resulted in a communi-
cation space loss of 62% for 95% of the month, 67%
for 50% of the month, and 74% for 5% of the month
(Fig. 2b).
We used a first-order sensitivity analysis to explore
the relation of values that parameterized historical
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Hatch et al.7
Figure 2. Temporal variation (a) in median signal excess (the difference between the signal-to-noise ratio and the
recognition differential) of contact calls of North Atlantic right whales in and around the Stellwagen Bank
National Marine Sanctuary per 10-min sample in April 2008 relative to hypothesized historical ambient (HA),
present-day ambient (PrA), hypothesized historical ambient plus present-day shipping (HA +PrS), and present-day
ambient plus present-day shipping (PrA +PrS) noise levels and (b) in communication masking calculated for the
modeled contact-calling North Atlantic right whales per 10-min sample in April 2008 for PrA, HA +PrS, and PrA
+PrS noise levels relative to HA noise level. All levels are in the 71–224 Hz frequency band (dB root mean square
re 1 μPa), and triangles indicate quieter and noisier 10-min samples, which are shown spatially in Fig. 3.
ambient noise level and recognition differential to com-
munication masking. For a historical ambient noise level
of 10 dB below present-day ambient noise levels and
recognition differentials of 0, 3, and 6 dB, monthly av-
erage lost communication space was 81%, 76%, and
67% respectively. When the historical level of ambient
noise was 20 dB below present-day ambient noise and
recognition differentials were 0, 3, and 6 dB, the aver-
age lost communication space was 90%, 83%, and 74%
respectively.
Comparison of received sound level and signal-excess
maps for the 89 contact-calling right whales and present-
day shipping noise during quiet versus noisy periods il-
lustrates the relative loss of communication space asso-
ciated with higher densities of nearby large commercial
vessels (Fig. 3). Median signal excess during the quiet
period was –2 and –9 dB during the noisy period. This
relative difference was quantified by calculating mask-
ing for these 2 periods. During the noisy period, com-
munication masking was 0.87, which indicates a loss of
87% of the communication space for calling right whales
relative to what they would have had available under
hypothesized historical levels of ambient noise. During
the quiet period masking was 0.65, which indicates a
loss of 65% of communication space relative to hypoth-
esized historical levels of ambient noise for the same
callers.
The number of right whale animats exposed to ambi-
ent noise levels 120 dB in the 71–224 Hz band due to
ship noise was 0.32 whales/10-min (SD 0.8) (minimum
0, maximum 11) (Fig. 4). Thus, an average of <1% of
the whales in the study area were exposed to ambient
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8Communication Masking of Right Whales
Figure 3. Spatial distribution of (a and b) summed received levels and (c and d) signal excess (defined in Fig. 2)
of contact calls of North Atlantic right whales relative to noise from ships (71–224 Hz, dB root mean square re 1
μPa) during 2 10-min sampling periods selected to represent quieter (a and c) and noisier (b and d) periods
(triangles in Fig. 2) (white and yellow lines, the boundary of the Stellwagen Bank National Marine Sanctuary).
noise levels 120 dB per 10-min sample. The average
level of masking to which 89 calling right whales were
subjected due to noise from the close passage of ships
(per 10-min sample period) was 0.16 (SD 0.12) (min-
imum 0.0, maximum 0.82). Under the combination of
present-day ambient noise and noise from ships, there
were, on average, 46 whale-exposure events/day with
noise levels 20 dB (SD 28) in the 71–224 Hz band
(minimum 9, maximum 121), and the average level of
communication masking was 0.67 (SD 0.04) (minimum
0.57, maximum 0.90) (Fig. 4). No right whales were ex-
posed to noise levels 120 dB in the 71–224 Hz band
during the quiet 10-min sample period (Fig. 5a), whereas
5 right whales were exposed to levels 120 dB in the
71–224 Hz band during the noisy 10-min sample period
(Fig. 5b).
Discussion
We quantified dramatic losses in the potential commu-
nication space available to North Atlantic right whales
associated with changes in noise conditions that we hy-
pothesize took place within the lifetimes of many of the
whales alive today. We estimated that on average contact-
calling right whales in this ecologically important area
have conservatively lost 63% of the communication op-
portunities estimated to have been available to them in
the mid 20th century. During the passage of commer-
cial vessels, lost communication space increased to 67%.
This supports the claim made by Clark et al. (2009) that
compared with other vocally active baleen whales, the
lower source levels produced by contact-calling North
Atlantic right whales make them particularly vulnerable
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Hatch et al.9
Figure 4. Temporal variation per 10-min sampling period in April 2008 in the number of North Atlantic right
whales within the study area exposed to noise levels 120 dB (71–224 Hz, root mean square re 1 μPa) from ships
and average value of communication-masking index under hypothesized historical ambient plus present-day
shipping noise levels (HA +PrS) and under present-day ambient plus PrS noise levels (PrA +PrS), both relative to
HA level (triangles indicate quieter and noisier 10-min samples shown spatially in Fig. 5).
to communication masking as a result of chronic noise
from vessel traffic.
We identified several parameters that define commu-
nication space for calling whales, but many of them are
poorly understood. Although further research and mod-
eling efforts are needed to address uncertainty in signal-
recognition processes and long-term, large-scale trends
in ambient noise levels, our results also point to the
roles population dynamics can play in shaping commu-
nication capacity. Baleen whales, like most animals, are
not distributed uniformly. Calling was modeled for areas
with both high and low densities of whales, and signal
Figure 5. Spatial distribution of cumulative ship noise levels (71–224 Hz, dB root mean square re 1 μPa).
Contours are in 10-dB increments (120 dB contour in pink) relative to the locations of 89 modeled North Atlantic
right whales (black asterisks) and to whales exposed to noise levels 120 dB (red asterisks) during 2 10-min
sampling periods selected to represent (a) quieter and (b) noisier periods (triangles in Fig. 4) (white line,
boundary of the Stellwagen Bank National Marine Sanctuary).
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10 Communication Masking of Right Whales
excess was low in areas with high noise levels and in
areas with few or widely spaced calling whales. This
underscores the importance of accurately representing
the density and distribution of both calling and receiving
whales when evaluating communication space and of
understanding the effects of changes in population size
on probability of communication. Extant North Atlantic
right whales are more likely to be subjected to higher
levels of communication masking from vessel noise than
other baleen whale populations because of their low pop-
ulation size and the low density of calling. In addition,
relative to other species of baleen whale, right whales
do not produce intense, patterned acoustic displays (i.e.,
songs), and their call source levels and call rates are rel-
atively low. Thus, even when right whale populations
were at prewhaling abundance levels and call density was
proportionately greater, greater calling density would
not have added substantially to background noise lev-
els or reduced opportunities for communication among
individuals.
Baleen whale species use a variety of complex acous-
tic behaviors to conduct vital activities such as foraging,
raising of young, migrating, and selecting mates (Tyack
2008). Thus, increasing levels of background noise within
the frequency bands used by whales to send and re-
ceive information are likely to affect their abilities to sur-
vive and reproduce (Ellison et al. 2012). More generally,
higher levels of background noise can affect multiple,
hearing-dependent, life-critical behaviors (e.g., foraging,
predator detection, navigation), and individuals living in
noisier conditions are less able to use sound to detect
changes in their environment. Many animals maintain
constant auditory vigilance. Sounds that do not awaken
sleeping humans but cause physiological arousal are as-
sociated with long-term, negative health effects (Spreng
2000; Babisch 2006; Haralabidis 2008), and increases in
ambient noise affect development and academic perfor-
mance in humans (Evans 2003). There is a correlation
between reduced ship traffic and decreased baseline lev-
els of stress-related glucocorticoids in North Atlantic right
whales (Rolland et al. 2012). This finding provides pre-
liminary evidence that exposure to low-frequency noise
may be associated with chronic stress in this species.
Chronic background noise thus diverts attention and
disrupts behavior, leads to habituation to background
noise, masks auditory signals, and stimulates spurious
physiological responses. These problems may compro-
mise physiological function, reduce energy and time
available to support critical activities, result in failure
to detect important cues, impair transmission of cues
and communication, and reduce use of important habi-
tat areas or resources (Hatch & Fristrup 2009). These
problems have fitness consequences. Although at least
2 marine mammals will increase call source levels in re-
sponse to increased noise levels (Holt et al. 2009, Parks
et al. 2010), such compensation is constrained by biome-
chanical, behavioral, and sound-propagation limits and
incurs potential fitness costs.
The U.S. Endangered Species Act of 1973, as amended
through 2004 (ESA), and U.S. Marine Mammal Protection
Act of 1972, as amended through 2007) (MMPA), were
passed specifically to identify and reduce or eliminate
negative fitness effects on species threatened with extinc-
tion or otherwise deemed priorities for protection. Un-
der the MMPA, human-induced underwater noise sources
that expose baleen whales to continuous noise above 120
dB (frequency bandwidth is not specified in the regula-
tions) are identified as potential sources of disturbance
(“acoustic harassment”) (Ellison et al. 2012) and must be
permitted (NOAA 2005). Although noise from commer-
cial vessels in transit is currently not regulated under the
MMPA, we applied the 120-dB threshold to our data to
estimate the proportion of right whales in the study area
that were behaviorally disturbed by noise from commer-
cial ships. We estimated that as many as 11 out of 89
(12%) of the whales in the model were exposed to unreg-
ulated noise from commercial shipping 120 dB in the
71–224 Hz band during one 10-min period.
The average contribution of discrete nearby ships
to levels of communication masking experienced by a
sparsely distributed population of right whales was rela-
tively low (16%), as were average levels of acoustic ha-
rassment (1%). This is because present-day ambient noise
levels throughout the study area are elevated and are now
the main contributor to estimates of lost communication
space (on average 63% for the month). This highlights
the need to incorporate measures of ambient noise in
methods that evaluate chronic-noise effects (Ellison et al.
2012). In addition, determining loss of communication
space relative to ambient noise levels before large-scale,
human-induced alteration of acoustic habitats is impor-
tant for evaluating long-term population viability. Cur-
rently, assessments of chronic noise sources conducted
under the ESA largely apply the same metrics used in per-
mitting under the MMPA and thus share the weaknesses
of this approach. However, under the ESA there is the
opportunity to incorporate assessments of lost acoustic
habitat in consultations and long-term assessments of re-
covery potential.
Interest in developing methods that integrate quantifi-
cation of acoustic habitat loss and effects from additional
stressors that affect listed species is growing (Hatch &
Fristrup 2009). It has been 30 years since the National
Environmental Policy Act (1969 as amended through
1982) and other cumulative-effect regulations were im-
plemented in the United States and worldwide, and the
state of global marine ecosystems is still declining (e.g.,
Halpern et al. 2008; Foley et al. 2010). This decline has
spurred ocean planning initiatives in the United States
(Interagency Ocean Policy Task Force 2009) and other
countries (Ehler & Douvere 2009) that are designed to
comprehensively manage human uses in both nearshore
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Hatch et al.11
and offshore waters. Nearly all emerging ocean planning
efforts assert the goal of protecting marine ecosystems
yet integration of information regarding the ecological
implications of human activities continues to lag behind
efforts to map human uses (Foley et al. 2010). However,
ocean planning represents a promising strategy for incor-
porating the accumulated effects of wide-ranging stres-
sors, such as chronic noise, in decisions regarding future
human activity.
More complete integration of the effects of communi-
cation masking on marine mammals and other animals
will require the development of methods for translat-
ing the effects of masking on ecosystem services. Baleen
whales have been given legally codified, cultural value
in U.S. waters, support whale-watching businesses, and
play a variety of roles in ecosystem dynamics that sup-
port commercial and recreational fisheries. Measures of
the effects of noise that relate directly to functional conse-
quences for whales can thus be integrated in models that
evaluate trade-offs among ecosystem services (e.g., man-
agement choices that change the type, magnitude, and
relative mix of services provided by ecosystems). Efforts
to define such measures for marine mammals and noise
continue to focus primarily on disturbance of important,
obvious behaviors (e.g., reproduction, foraging). We ar-
gue that measures of acoustic communication or degrada-
tion of acoustic awareness can document wider-ranging
and increasingly relevant functional consequences of in-
creased ambient noise levels for marine animal popu-
lations. Thus, we believe research and policy develop-
ment should explore the individual and population-level
costs of habitat loss caused by acoustic masking. Finally,
we believe the integration of the effects of noise and
the effects of other environmental stressors should be
prioritized.
Acknowledgments
This work was supported by an Office of Naval Research
grant (number N00014–07-1–1029) awarded by the Na-
tional Oceanographic Partnership Program to C.W.C.,
L.T.H., and S.V.P. We thank K. Cortopassi, P. Dugan, H.
Figueroa, D. Hawthorne, L. Strickland, and C. Tremblay,
D. Wiley, M. Thompson, B. Cabe, D. Cholewiak, D. Risch,
J. Stanistreet, S. Mussoline, W. T. Ellison, and D. Zeddies
for their assistance with field work, data analyses, and
help with acoustic concepts.
Supporting Information
More information on the experimental design (Appendix
S1) and methods and modeling (Appendix S2) are avail-
able online. The authors are solely responsible for the
content and functionality of these materials. Queries
(other than absence of the material) should be directed
to the corresponding author.
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... At the same time, sound from human activity, such as vessel traffic, has increased steadily over the past 70 years (National Research Council, 2003;McDonald et al., 2006;Miksis-Olds and Nichols, 2016). To help understand and monitor how marine animals use sound and the impacts of anthropogenic noise on these communication pathways, scientists throughout the world use passive acoustic monitoring (PAM; Holt et al., 2009;Jensen et al., 2009;Hatch et al., 2012;Nieukirk et al., 2012;Rolland et al., 2012;Houghton et al., 2015;Au and Lammers, 2016;Erbe et al., 2016;Haver et al., 2017;Hawkins and Popper, 2017;Marley et al., 2017;Dunlop, 2019;Howe et al., 2019). Ocean sound has been identified as an Essential Ocean Variable by the Global Ocean Observing System (Tyack and A Partnership for Observation of the Global Oceans International Quiet Ocean Experiment Working Group, 2017). ...
... Extensive contribution of low frequency sound (<200 Hz) from large commercial vessels has been documented at the Stellwagen Bank National Marine Sanctuary (Hatch et al., 2008). As a result of these noise levels, the communication space of marine animals, and efficacy of communication between them, has been reduced (Hatch et al., 2012;Redfern et al., 2017;Putland et al., 2018). In addition to vessel activity, the Gulf of Mexico and Mid Atlantic Ocean are also impacted by regional or ocean-basin scale seismic airgun activity, which contributes significantly to the low frequency SPL (Nieukirk et al., 2004(Nieukirk et al., , 2012Haver et al., 2017Haver et al., , 2018. ...
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No PDF available 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: the curation, management, and global dissemination of passive acoustic datasets and 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 established a passive acoustic data archive, which contains over 100 TB of audio files mainly collected from stationary recorders throughout waters in the U.S. 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 will present a previously unattainable comparison of first order sound level-patterns from archived data collected across three distinctly separate long-term passive acoustic monitoring efforts conducted at regional and national scales: NOAA/National Park Service Ocean Noise Reference Station Network, the NOPP-funded Atlantic Deepwater Ecosystem Observatory Network, and the NOAA-Navy Sanctuary Soundscape Monitoring Project. Further, we will propose the next frontier for scalable data stewardship, access, and processing flow to help the community collaboratively move forward.
... Over the past 50 years, commercial shipping has doubled, increasing low-frequency background noise in contemporary oceans [1]. In the last four decades, an increase of 15-20 dB in the ambient noise has been reported in ocean basins off Ireland due to commercial shipping activities [2,3]. ...
... Several studies in baleen whales, such as the fin, blue (Balaenoptera musculus), right (Eubalaena), Bryde's (Balaenoptera brydei), and minke (Balaenoptera acutorostrata) whales, have shown a reduction and fragmentation in communication space as a consequence of masking potentially incurring detrimental impacts on communication and breeding activities [1,4,23,75,76]. Another impact is the abandonment of a preferred or critical habitat, such as the breeding ground as observed in gray whales (Eschrichtius robustus), to evade the high shipping and dredging activities [77] and returning only years after the industry closed [78,79]. Such compensations come with high energy costs, compromising the foraging and reproductive success, thus jeopardising the survival of the population [4,21,80]. ...
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Little is known about the ecological importance of fin whales found year-round in southwestern offshore Irish waters. Understanding their ecology is important to reduce potential harm through any spatio-temporal overlap with commercial shipping and fishing activities. This study explored the potential environmental drivers and impacts of low-frequency shipping noise on fin whale calling at Porcupine Ridge using the presence/absence of call detections as a proxy for observed changes due to possible masking. Acoustic call data was collected at a low sampling rate (2 ksps) from the end of March 2016 to June 2016 (97 days) using a bottom-moored autonomous acoustic recorder with an omni-directional hydrophone. The high zero-inflated and binary nature of the data was addressed using generalised linear models. The results of our habitat modelling predicted call detections to increase significantly during night-time (p ≤ 0.01) with sea surface height and chlorophyll-a concentration (p ≤ 0.01), implying higher prey availability may occur on Porcupine Ridge. It also indicated a significant decrease in call detections with increasing shipping noise (p ≤ 0.01). Unfortunately, the model had a type II error. To provide robust results, a longer study not limited by data on the prey, and oceanographic drivers including spatial and temporal parameters is required. This study provides the foundations on which further ecological data could be added to establish management and mitigation measures to minimize the effects of shipping noise on fin whales.
... The 50 th percentile (L 50 ) is the median sound level measured across a certain analysis window. Percentiles provide an estimate of the distribution of sound levels over time and have been used to characterise the percentage of time in which sound levels exceed a certain threshold level (Hatch et al., 2012;Putland et al., 2018). The definition of percentiles can be somewhat ambiguous when comparing different studies. ...
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Soundscapes have substantially changed since the industrial revolution and in response to biodiversity loss and climate change. Human activities such as shipping, resource exploration and offshore construction alter natural ecosystems through sound, which can impact marine species in complex ways. The study of underwater sound is multi-disciplinary, spanning the fields of acoustics, physics, animal physiology and behaviour to marine ecology and conservation. These different backgrounds have led to the use of various disparate terms, metrics, and summary statistics, which can hamper comparisons between studies. Different types of equipment, analytical pathways, and reporting can lead to different results for the same sound source, with implications for impact assessments. For meaningful comparisons and derivation of appropriate thresholds, mitigation, and management approaches, it is necessary to develop common standards. This paper presents a brief overview of acoustic metrics, analysis approaches and reporting standards used in the context of long-term monitoring of soundscapes.
... Anthropogenic activities that produce low frequency sounds have been shown to mask animal communication with conspecifics and other biologically important sounds such as calls of predators (Dolman & Simmonds, 2004;Clark et al., 2009;Jensen et al., 2009;Hatch et al., 2012;Blackwell et al., 2013;Williams et al., 2014b). Masking occurs when the natural background sound level of the ocean increases, preventing marine fauna from detecting important sounds relative to their individual needs (Hawkins, Pembroke & Popper, 2014). ...
Conference Paper
Algoa Bay, South Africa has a diverse array of marine top-predators, including Indo-Pacific bottlenose dolphin (Tursiops aduncus), Indian Ocean humpback dolphin (Sousa plumbea), long-beaked common dolphin (Delphinus capensis), Bryde’s whale (Balaenoptera brydei), southern right whale (Eubalaena australis), humpback whale (Megaptera novaeangliae), African penguins (Spheniscus demersus) and Cape fur seals (Arctocephalus pusillus). Algoa Bay also has a number of anthropogenic activities that may acoustically affect marine fauna, including seismic surveys conducted to locate oil and gas reserves in the sub-surface of the seabed. We modelled the estimated level of sound received by marine top-predators observed during a seismic survey conducted in 2013. To do this, we used an airgun array simulation tool (Agora) to model the source level of the airguns and a sound propagation model RAMSGeo to model the transmission loss. Using recently published sound exposure criteria, we determined whether marine fauna encountered by Marine Mammal Observers during this survey were exposed to sound exposure levels that could result in temporary or permanent hearing damage. The results of this study are aimed at informing the development of legal instruments to mandate acoustic modelling before conducting seismic and other acoustic activities in South Africa’s exclusive economic zone, particularly in relation to sensitive biodiverse areas, or proximities to marine protected areas.
... Although it is unclear whether humpback whales in the NYB are affected by vessel noise, the sounds made by heavy vessel traffic can mask whale vocalizations (Hatch et al., 2012). This makes them more difficult to detect using passive acoustic monitoring (PAM) devices, which are currently being used to monitor for whales occurring near the shipping lanes in the NYB (WCS, 2021). ...
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Humpback whales (Megaptera novaeangliae) have recently been observed feeding in the New York Bight (NYB), the section of ocean from Montauk, New York to Cape May, New Jersey, United States (US). This feeding technique brings humpback whales to the surface of the water which puts them at a greater risk of vessel strike. The NYB is already an area of concern due to shipping traffic leading to the Ports of New York and New Jersey (PNYNJ). In this study, data collected by Gotham Whale from 2011 to 2019 were analyzed on humpback whales lunge feeding in the NYB apex, near the entrance to the PNYNJ. Clusters of lunge feeding were investigated, along with the water depths of lunge feeding locations. Using ArcGISPro, six significant hot spot clusters were identified, and water depth of lunge feeding locations ranged from 4.50 to 35.00 m with a mean of 14.83 m. The results of this study provide the first documentation on potential lunge feeding hot spot clusters in the NYB apex. Future studies should obtain comprehensive data looking at the amount of time humpback whales in the NYB are spending on the surface and time they are spending feeding in shipping lanes. This information will be important for the management of marine mammals in this area and may help to mitigate and reduce the incidence of boat strikes to humpback whales in this region.
... Furthermore, the current choice of MSFD frequency bands at 63 Hz and 125 Hz may inadequately reflect the risk of acoustic masking (Hermannsen et al., 2014), and can be contaminated by flow noise (Merchant et al., 2014), and higher frequency bands (e.g. at 250 or 500 Hz) appear to better correlate with broadband levels of shipping noise (Merchant et al., 2014). Merchant et al. (2016) rather recommend the use of percentile-based metrics that also directly related to the temporal distribution of noise levels, making them more appropriate for assessing the risk of acoustic masking (Hatch et al., 2012), as well as being more straightforward to interpret and communicate to policymakers. ...
Thesis
Whales have become an important topic in marine science. One of the best solutions for their protection is a better understanding of their social structure and the way they communicate with each other. To this end, Underwater Passive Acoustics (UPA) offers a unique solution to simultaneously capture both source-specific and more contextual information, thus providing a better understanding of both the behavior of whales and their relationships with the ecosystem around them. As the volume of APSM data to be processed has become very large, the development of automated artificial intelligence (AI) methods to analyze this data is now of prime importance in marine bioacoustics. These rely heavily on the quantity and quality of the annotated data, which is the main limitation in their use. This work explores two approaches in a weakly supervised context, by acting or on the context itself, through the question of where and how one can better extract useful information to supervise AI methods; or by acting on AI methods in this context, through the question of how to develop AI methods to better respond to weak supervision. Our contribution has enabled the development of new tools to aid in the recognition of cetacean sounds through open science with the OsmOSE project, a collaborative and interdisciplinary project following the principles of Findable, Accessible, Interoperable and Reusable data.
... Passive acoustic monitoring archival recordings are also increasingly being used to monitor the long-term ambient noise and communication space available to marine animals is a given area, in addition to the composition and health of marine soundscapes e.g., the prevalence of non-biological or anthropogenic sound sources Hatch et al., 2012;Staaterman et al., 2014;Erbe et al., 2016;Merchant et al., 2016;Haver et al., 2018). Potential effects of anthropogenic activities on marine species can be evaluated through applying the collected data to analytical frameworks, such as Before-After-Control-Impact (BACI) and Beyond-BACI designs (e.g., Underwood, 1992Underwood, , 1994, or Before-After-Gradient (BAG) analyses (Ellis and Schneider, 1997;Brandt et al., 2011;Methratta, 2020). ...
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Offshore wind energy development is rapidly ramping up in United States (U.S.) waters in order to meet renewable energy goals. With a diverse suite of endangered large whale species and a multitude of other protected marine species frequenting these same waters, understanding the potential consequences of construction and operation activities is essential to advancing responsible offshore wind development. Passive acoustic monitoring (PAM) represents a newer technology that has become one of several methods of choice for monitoring trends in the presence of species, the soundscape, mitigating risk, and evaluating potential behavioral and distributional changes resulting from offshore wind activities. Federal and State regulators, the offshore wind industry, and environmental advocates require detailed information on PAM capabilities and techniques needed to promote efficient, consistent, and meaningful data collection efforts on local and regional scales. PAM during offshore wind construction and operation may be required by the National Oceanic and Atmospheric Administration and Bureau of Ocean Energy Management through project-related permits and approvals issued pursuant to relevant statutes and regulations. The recommendations in this paper aim to support this need as well as to aid the development of project-specific PAM Plans by identifying minimum procedures, system requirements, and other important components for inclusion, while promoting consistency across plans. These recommendations provide an initial guide for stakeholders to meet the rapid development of the offshore wind industry in United States waters. Approaches to PAM and agency requirements will evolve as future permits are issued and construction plans are approved, regional research priorities are refined, and scientific publications and new technologies become available.
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We compare the status of regional or ecosystem frameworks for managing airborne and underwater noise sources in the US, with particular emphasis on transportation noise in national marine sanctuaries and national parks. The Organic Act demands that the US National Park Service (NPS) preserve natural and cultural resources unimpaired for future generations, and NPS policies provide explicit guidance for managing acoustical environments to meet this standard. The US Office of National Marine Sanctuaries identifies noise as a threat to sanctuary resources, but does not address how the program should manage noise levels to minimize impacts to wildlife and protect the aesthetic resources within sanctuaries. Methods and results from 2 case studies that address noise management in spatially explicit contexts are highlighted: the Gerry E. Studds Stellwagen Bank National Marine Sanctuary and the Grand Canyon National Park. In both case studies, noise generated by transportation networks that extend far beyond protected area boundaries must be managed to conserve local resources. Effective noise control policies must be developed through partnerships among transportation and resource management agencies, surmounting differences in their missions, professional cultures, and historical precedents. Four collective approaches for managing noise in protected natural areas emerge from this analysis: (1) investing in monitoring programs and data management; (2) expanding the resolution and scope of impact assessment tools; (3) enhancing coordination and the governance structure; and (4) engaging and educating US citizens regarding the benefits of quieting.
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ii ABSTRACT Although ambient (background) noise in the ocean is a topic that has been widely studied since pre-World War II, the effects of noise on marine organisms has only been a focus of concern for the last 25 years. The main point of concern has been the potential of noise to affect the health and behavior of marine mammals. The Stellwagen Bank National Marine Sanctuary (SBNMS) is a site where the degradation of habitat due to increasing noise levels is a concern because it is a feeding ground and summer haven for numerous species of marine mammals. Ambient noise in the ocean is defined as “the part of the total noise background observed with an omnidirectional hydrophone.” It is an inherent characteristic of the medium having no specific point source. Ambient noise is comprised of a number of components that contribute to the “noise level” in varying degrees depending on where the noise is being measured. This report describes the current understanding of ambient noise and existing levels in the Stellwagen Bank National Marine Sanctuary Noise Levels and Sources in the Stellwagen Bank National Marine Sanctuary and the St. Lawrence River Estuary. Available from: https://www.researchgate.net/publication/242184833_Noise_Levels_and_Sources_in_the_Stellwagen_Bank_National_Marine_Sanctuary_and_the_St_Lawrence_River_Estuary [accessed May 12, 2017].
Book
Many marine mammals communicate by emitting sounds that pass through water. Such sounds can be received across great distances and can influence the behavior of these undersea creatures. In the past few decades, the oceans have become increasingly noisy, as underwater sounds from propellers, sonars, and other human activities make it difficult for marine mammals to communicate. This book discusses, among many other topics, just how well marine mammals hear, how noisy the oceans have become, and what effects these new sounds have on marine mammals. The baseline of ambient noise, the sounds produced by machines and mammals, the sensitivity of marine mammal hearing, and the reactions of marine mammals are also examined. An essential addition to any marine biologists library, Marine Mammals and Noise will be especially appealing to marine mammalogists, researchers, policy makers and regulators, and marine biologists and oceanographers using sound in their research.
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Many marine mammals communicate by emitting sounds that pass through water. Such sounds can be received across great distances and can influence the behavior of these undersea creatures. In the past few decades, the oceans have become increasingly noisy, as underwater sounds from propellers, sonars, and other human activities make it difficult for marine mammals to communicate. This book discusses, among many other topics, just how well marine mammals hear, how noisy the oceans have become, and what effects these new sounds have on marine mammals. The baseline of ambient noise, the sounds produced by machines and mammals, the sensitivity of marine mammal hearing, and the reactions of marine mammals are also examined. An essential addition to any marine biologists library, Marine Mammals and Noise will be especially appealing to marine mammalogists, researchers, policy makers and regulators, and marine biologists and oceanographers using sound in their research.
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The amount of underwater sound from ship traffic, commercial, research, and military sound sources has increased significantly over the past century. Marine mammals and many other marine animals rely on sound for short- and long-range communication, for orientation, and for locating prey. This reliance has raised concern that elevated sound levels from human sources may interfere with the behavior and physiology of marine animals. The dominant source of human sound in the sea stems from propulsion of ships. Shipping noise centers in the 20- to 200-Hz band. Frequencies this low propagate efficiently in the sea, and shipping has elevated the global deepwater ambient noise 10- to 100-fold in this frequency band. Baleen whales use the same frequency band for some of their communication signals, and concern has been raised that elevated ambient noise may reduce the range over which they can communicate. Marine mammals have a variety of mechanisms to compensate for increased noise, but little is known about the maximum range at which they may need to communicate. Some of the most intense human sources of sound include air guns used for seismic exploration and sonar for military and commercial use. Human sources of sound in the ocean can disturb marine mammals, evoking behavioral responses that can productively be viewed as similar to predation risk, and they can trigger allostatic physiological responses to adapt to the stressor. Marine mammals have been shown to avoid some human sound sources at ranges of kilometers, raising concern about displacement from important habitats. There are few studies to guide predictions of when such changes start to lower the fitness of individuals or have negative consequences for the population. Although acute responses to intense sounds have generated considerable interest, the more significant risk to populations of marine mammals is likely to stem from less visible effects of chronic exposure.
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