OCS Study 

BOEM 2015-026 

U.S. Department of the Interior

Bureau of Ocean Energy Management

Gulf of Mexico OCS Region

Baseline Bioacoustic Characterization for 

Offshore Renewable Energy Development 

in the North Carolina and Georgia 

Wind Planning Areas



OCS Study 

BOEM 2015-026 

Published by

U.S. Department of the Interior 

Bureau of Ocean Energy Management 

Gulf of Mexico OCS Region

New Orleans, LA 

January 2015

Baseline Bioacoustic Characterization for

Offshore Renewable Energy Development

in the North Carolina and Georgia

Wind Planning Areas

Authors

Aaron N. Rice

Janelle L. Morano 

Kristin B. Hodge 

Daniel P. Salisbury 

Charles A. Muirhead 

Adam S. Frankel

Michael Feinblatt

Christopher W. Clark 

Prepared under BOEM Contract

M10PC00087

by

Cornell Laboratory of Ornithology

159 Sapsucker Woods Road

Ithaca, NY 14850
DISCLAIMER

This	report	was	prepared	under	contract	between	the	Bureau of Ocean Energy Management (BOEM)

and	the	Cornell	Lab	of	Ornithology.	This	report	has	been	technically	reviewed	by	BOEM,	and	it	has	

been	approved	for	publication.	Approval	does	not	necessarily	signify	that	the	contents	reflect	the	

views	and	policies	of	BOEM, nor	does	mention	of	trade	names	or	commercial	products	constitute	

endorsement	or	recommendation	for	use.

REPORT AVAILABILITY

To download a PDF file of this Gulf of Mexico OCS Region report, go to the US Department of the 

Interior, Bureau of Ocean Energy Management, Environmental Studies Program Information System

website and search on OCS Study BOEM 2015-026. 

This report can be viewed at select Federal Depository Libraries. It can also be obtained from the National 

Technical Information Service; the contact information is below. 

US Department of Commerce

National Technical Information Service

5301 Shawnee Rd. 

Springfield, VA 22312

Phone: (703) 605-6000, 1(800)553-6847

Fax: (703) 605-6900

Website: http://www.ntis.gov/

CITATION

Rice, Aaron N., Janelle L. Morano, Kristin B. Hodge, Daniel P. Salisbury, Charles A. Muirhead, Adam S. 

Frankel, Michael Feinblatt, Jeff Nield, Christopher W. Clark. 2014. Baseline Bioacoustic 

Characterization for Offshore Alternative Energy Development in North Carolina and Georgia 

Wind Planning Areas. US Dept. of the Interior, Bureau of Ocean Energy Management, Gulf of 

Mexico OCS Region, New Orleans, LA. OCS Study BOEM 2015-026. 183 pp.
i 

CONTENTS

List of Figures....................................................................................................................................iii

List of Tables.....................................................................................................................................vi

Abbreviations and Acronyms............................................................................................................vii

1. Background and Objectives.........................................................................................................9

1.1. Project Objectives and Approach................................................................................................10

1.2. Project History and Evolution .....................................................................................................10

2. Sound Recording Methods....................................................................................................12

3. Baleen Whale Presence.............................................................................................................14

3.1 Introduction ................................................................................................................................14

3.2 Methods......................................................................................................................................16

3.3 Results.........................................................................................................................................19

3.4 Conclusions................................................................................................................................. 21

4. Fish Presence............................................................................................................................24

4.1 Introduction ................................................................................................................................24

4.2 Methods......................................................................................................................................26

4.2.1 Focal Species..........................................................................................................................................26

4.2.2 Acoustic Analysis....................................................................................................................................26

4.3 Results.........................................................................................................................................28

4.4. Conclusions................................................................................................................................. 32

4.4.1. Geographic Variation in Fish Calling..................................................................................................32

4.4.2. Temporal Patterns in Fish Calling ......................................................................................................33

4.4.3. Use of Fish Calls as Ecological Indicators...........................................................................................34

4.4.4. Recommendations for Future Study ................................................................................................. 35

5. Ambient Noise..........................................................................................................................37

5.1 Introduction ................................................................................................................................37

5.2 Methods......................................................................................................................................37

5.3 Results.........................................................................................................................................40

5.3.1 General Trends ......................................................................................................................................40

5.3.2 Noise Patterns............................................................................................................................................53

5.3.3 Potential for Noise Masking.......................................................................................................................54

5.4 Conclusions................................................................................................................................. 65

6. Noise Modeling ........................................................................................................................67

6.1 Introduction ................................................................................................................................67

6.1.1 Technical Background............................................................................................................................67

6.2 Methods......................................................................................................................................68

6.2.1 Acoustic Propagation Models....................................................................................................................69

6.2.2 Acoustic Propagation Modeling Environmental Inputs .............................................................................70

6.2.3 Scenario Construction................................................................................................................................71

6.2.4 Acoustic Characteristics of Modeled Sources............................................................................................72

6.3 Results.........................................................................................................................................78

6.3.1 Acoustic Propagation Modeling Results................................................................................................78

6.4 Conclusions...............................................................................................................................119

6.4.1 Comparison of Sources............................................................................................................................119

6.4.2 Comparison of Locations..........................................................................................................................119

6.4.3 Future Considerations..............................................................................................................................120

7. Habitat Assessment................................................................................................................121

7.1 Introduction .............................................................................................................................. 121
ii

7.1.1 North Carolina Site...............................................................................................................................121

7.1.2 Georgia Site..........................................................................................................................................122

7.2 Physical Habitat Characterization.............................................................................................125

7.2.1 North Carolina Site...............................................................................................................................125

7.2.2 Georgia Site..........................................................................................................................................128

7.3 Biological Habitat Characterization...........................................................................................131

7.3.1 North Carolina Site...............................................................................................................................131

7.3.2 Georgia Site..........................................................................................................................................134

7.4 Marine Vertebrate Species’ Use of the Sites............................................................................137

7.4.1 Fish and Fisheries................................................................................................................................. 137

7.4.2 Marine Mammals................................................................................................................................. 145

7.4.3 Sea Turtles ...........................................................................................................................................150

7.4.4 Discussion ............................................................................................................................................154

8. Summary and Conclusions......................................................................................................155

8.1 Occurrence of Baleen Whales...................................................................................................155

8.2 Occurrence of Fishes.................................................................................................................156

8.3 Ambient Noise Environment.....................................................................................................157

8.3 Habitat Characterization...........................................................................................................157

8.4. Conclusions and Recommendations.........................................................................................158

9. Acknowledgements................................................................................................................159

10. Literature Cited...................................................................................................................160

Appendix: Other Biological Signals ................................................................................................. 178

A.1 Additional Biological Sources of Acoustic Signals.....................................................................178

A.2 Biological Signals from Unknown Sources................................................................................179
iii

LIST OF FIGURES 

Figure 2.1. Views of the MARU...................................................................................................................12

Figure 2.2. Deployment locations of MARUs..............................................................................................13

Figure 3.1. Deployment location of MARUs with respect to protected areas for right whales.................15

Figure 3.2. Examples of right whale contact calls.......................................................................................17

Figure 3.3. Example of fin whale 20 Hz note ..............................................................................................18

Figure 3.4. Examples of humpback whale social sounds............................................................................18

Figure 3.5. Seasonal presence of right whales............................................................................................20

Figure 3.6. Percent vocal presence of right whales....................................................................................21

Figure 4.1. Variation in black drum loud drum and oyster toadfish boat whistle calls identified in North 

Carolina and Georgia. ................................................................................................................................. 27

Figure 4.2. Black drum and toadfish chorusing...........................................................................................28

Figure 4.3. Black drum and oyster toadfish occurrence and chorusing periods in North Carolina and 

Georgia........................................................................................................................................................29

Figure 4.4. Diel pattern of black drum chorus............................................................................................30

Figure 4.5. Mean daily temperature in North Carolina and Georgia..........................................................31

Figure 4.6. Relationship between acoustic occurrence and water temperature.......................................32

Figure 5.1. Example long term spectrogram...............................................................................................39

Figure 5.2. Spectrogram of acoustic data from GA-North (9 June–9 November 2012) .............................41

Figure 5.3. Spectrogram of acoustic data from GA-North (10 November 2012–12 April 2013)................42

Figure 5.4. Spectrogram of acoustic data from GA-Central (9 June–9 November 2012)...........................43

Figure 5.5. Spectrogram of acoustic data from GA-Central (10 November 2012–12 April 2013)..............44

Figure 5.6. Spectrogram of acoustic data from GA-South (9 June–9 November 2012) .............................45

Figure 5.7. Spectrogram of acoustic data from GA-South (10 November 2012–12 April 2013)................46

Figure 5.8. Spectrogram of acoustic data from NC-North (12 June–11 November 2012) .........................47

Figure 5.9. Spectrogram of acoustic data from NC-North (12 November 2012–16 April 2013) ................48

Figure 5.10. Spectrogram of acoustic data from NC-Central (12 June–11 November 2012).....................49

Figure 5.11. Spectrogram of acoustic data from NC-Central (12 November 2012 –16 April 2013)...........50

Figure 5.12. Spectrogram of acoustic data from NC-South (12 June–11 November 2012) .......................51

Figure 5.13. Spectrogram of acoustic data from NC-South (12 November 2012–16 April 2013) ..............52

Figure 5.14. Biological example of black drum chorusing ..........................................................................55

Figure 5.15. Biological example of black drum and toadfish chorusing .....................................................56

Figure 5.16. Example of weather-related noise..........................................................................................57

Figure 5.17. Example of extreme weather noise from Hurricane Sandy....................................................58

Figure 5.18. Anthropogenic example of shipping noise .............................................................................59

Figure 5.19. Internal hydrophone noise .....................................................................................................60

Figure 5.20. Unknown sound source, potentially biological.......................................................................61

Figure 5.21. Unknown sound sources, potentially anthropogenic and biological......................................62

Figure 5.22. Power spectral density of anthropogenic and biological sounds...........................................63

Figure 5.23. Acoustic masking of black drum chorusing.............................................................................65

Figure 6.1. ETOPO1 bathymetry for the modeling areas............................................................................70

Figure 6.2. Source 1/3-octave levels measured from a pile being driven with a diesel impact hammer. . 73

Figure 6.3. Source 1/3-octave levels (solid line) measured from a pile being driven with a vibratory 

hammer.......................................................................................................................................................74

Figure 6.4: Data from Allen et al. (2012) plotted to show strong relationship between vessel speed and 

source level (dB re 1 μPa at 1m, 1-2,500 Hz)..............................................................................................77
iv

Figure 6.5. The maximum received level from the Georgia site is shown as a function of range and depth.

....................................................................................................................................................................79

Figure 6.6. Planar view of sound propagation at Georgia site....................................................................80

Figure 6.7.The maximum received level from NC-North is shown as a function of range and depth........81

Figure 6.8.The received sound level of the boomer source at the NC site at depth of six meters is shown.

....................................................................................................................................................................82

Figure 6.9. The maximum received level of any radial is shown as a function of range and depth at the 

NC site.........................................................................................................................................................83

Figure 6.10.The received sound level of the boomer source at the NC site a depth of six meters is shown.

....................................................................................................................................................................84

Figure 6.11.The propagation of the chirp sonar source is shown. .............................................................85

Figure 6.12. The received level at a depth of six meters is shown. ............................................................86

Figure 6.13.The propagation predicted from the RAM model as a function of range and depth for the 

Georgia site.................................................................................................................................................87

Figure 6.14.The maximum received level at any depth for the Georgia site. ............................................88

Figure 6.15. The inner portion of the maximum received level at any depth is shown for the Georgia site.

....................................................................................................................................................................89

Figure 6.16. The propagation predicted from the RAM model as a function of range and depth for the 

North Carolina site......................................................................................................................................90

Figure 6.17.The maximum received level at any depth for the North Carolina site. ................................. 91

Figure 6.18. The inner portion of the maximum received level at any depth for the NC-North Site.........92

Figure 6.19.The propagation predicted from the RAM model as a function of range and depth for the NCSouth site. ...................................................................................................................................................93

Figure 6.20. The maximum received level at any depth is shown for the NC-South site...........................94

Figure 6.21. The inner portion of the maximum received level at any depth is shown for the NC-South 

site...............................................................................................................................................................95

Figure 6.22.The propagation predicted from the RAM model is shown as a function of range and depth 

for the GA-Central site................................................................................................................................96

Figure 6.23.The maximum received level at any depth is shown for the GA-Central site. ........................97

Figure 6.24.The inner portion of the maximum received level at any depth is shown for the GA-Central 

site...............................................................................................................................................................98

Figure 6.25. The propagation predicted from the RAM model is shown as a function of range and depth 

for the NC-North site. ................................................................................................................................. 99

Figure 6.26. The maximum received level at any depth is shown for the NC-North site.........................100

Figure 6.27. The inner portion of the maximum received level at any depth is shown for the NC-North 

site.............................................................................................................................................................101

Figure 6.28. The propagation predicted from the RAM model is shown as a function of range and depth 

for the NC-South site. ...............................................................................................................................102

Figure 6.29. The maximum received level at any depth is shown for the NC-South site.........................103

Figure 6.30. The inner portion of the maximum received level at any depth is shown for the NC-South 

site.............................................................................................................................................................104

Figure 6.31. The maximum received level for any modeled radial is shown as a function of range and 

depth for the GA-Central site....................................................................................................................105

Figure 6.32. The received level at a depth of six meters is shown for the GA-Central site......................106

Figure 6.33. The maximum received level for any modeled radial is shown as a function of range and 

depth for the NC-North site......................................................................................................................107

Figure 6.34. The received level at a depth of six meters is shown for the NC-North site. .......................108
v 

Figure 6.35. The maximum received level for any modeled radial is shown as a function of range and 

depth for the NC-South site......................................................................................................................109

Figure 6.36. The received level at a depth of six meters is shown for the NC-South site. .......................110

Figure 6.37. The maximum received level for any modeled radial is shown as a function of range and 

depth for the GA-Central site....................................................................................................................111

Figure 6.38. The received level at a depth of six meters is shown for the GA-Central site......................112

Figure 6.39. The maximum received level for any modeled radial is shown as a function of range and 

depth for the NC-North site......................................................................................................................113

Figure 6.40. The received level at a depth of six meters is shown for the NC-North site. .......................114

Figure 6.41. The maximum received level for any modeled radial is shown as a function of range and 

depth for the NC-South site......................................................................................................................115

Figure 6.42. The received level at a depth of six meters is shown for the NC-South site. .......................116

Figure 7.1. North Carolina wind planning area (NC-Site)..........................................................................123

Figure 7.2. Georgia site (GA-Site)..............................................................................................................124

Figure 7.3. NC-Site bathymetry. ................................................................................................................ 126

Figure 7.4. NC-Site geology. ......................................................................................................................127

Figure 7.5. GA-Site bathymetry.................................................................................................................129

Figure 7.6. GA-Site geology. ......................................................................................................................130

Figure 7.7. NC-Site essential fish habitats. ................................................................................................133

Figure 7.8. GA-Site essential fish habitat. ................................................................................................. 136

Figure 7.9. Sightings of fin, humpback, and right whales. ........................................................................147

Figure 7.10. Right whale critical habitat. ..................................................................................................149

Figure A-1. Cusk-eel ..................................................................................................................................178

Figure A-2. Sei whale................................................................................................................................. 179

Figure A-3. Sound from an unknown source #1 .......................................................................................179

Figure A-4. Sound from an unknown source #2 .......................................................................................180

Figure A-5. Sound from an unknown source #3 .......................................................................................180

Figure A-6. Sound from an unknown source #4 .......................................................................................181

Figure A-7. Sound from an unknown source #5 .......................................................................................181

Figure A-8. Sound from an unknown source #6 .......................................................................................182
vi

LIST OF TABLES

Table 1.1. BOEM Outer Continental Shelf (OCS) blocks within the Beaufort and Brunswick regions, 

designated as wind planning areas.............................................................................................................11

Table 2.1. Coordinates and depths of marine autonomous recording units (MARUs) deployed at the 

North Carolina site and the Georgia site. ...................................................................................................13

Table 3.1. Dates fin and humpback whales were detected at the North Carolina site and the Georgia site.

....................................................................................................................................................................19

Table 6.1. Summary of source level information for sources to be considered for modeling. ..................69

Table 6.2. Bottom parameters for the modeling area................................................................................71

Table 6.3: Locations of modeling sites........................................................................................................72

Table 6.4. Estimated source levels (RMS SPL) and beam width from the representative boomer 

distributed into twenty 1/3rd-octave bands................................................................................................75

Table 6.5. Representative chirp sub-bottom profiler specifications (Department of the Interior 2012)...76

Table 6.6: Georgia isopleth range summary.............................................................................................117

Table 6.7: NC-north isopleth range summary...........................................................................................118

Table 6.8: NC-south isopleth range summary...........................................................................................119

Table 7.1. List of fish species present in the South Atlantic Bight. ...........................................................138

Table 7.2. Marine mammal species that may occur in the South Atlantic Bight......................................146
vii

ABBREVIATIONS AND ACRONYMS

dB Decibels, referenced to 1 μPa 

BOEM Department of the Interior’s Bureau of Ocean Energy Management

BRP The Bioacoustics Research program at Cornell University’s Laboratory of Ornithology

BSEE Department of the Interior’s Bureau of Safety and Environmental Enforcement 

EFH Essential fish habitat

GDEM General Digital Environment Model 

HAPC Habitat Areas of Particular Concern

Hz Hertz (frequency measurement) 

μPa mircoPascal (pressure measurement)

MARU Marine autonomous recording unit that records acoustic data; developed by BRP 

ORE Offshore renewable energy

RAM Range-Dependent Acoustic Model 

RMS Root mean square 

SAB South Atlantic Bight 

SEAMAP-SA Southeast Area Monitoring and Assessment Program - South Atlantic 

SEL Sound exposure level

SMA Seasonal Management Area, protected area for North Atlantic right whales

SPL Sound pressure level

USWTR Under sea warfare training range

XBAT eXtensible BioAcoustic Tool, a MATLAB-based interactive sound visualization software

(Figueroa and Robbins 2008) 
9 

1. BACKGROUND AND OBJECTIVES 

The concern with human-driven climate change motivated technological developments for harnessing 

energy from the ocean environment, which is a promising energy resource to offset carbon emissions 

from fossil fuel use (e.g., Pelc and Fujita 2002). However, while technological improvements in offshore 

renewable energy (ORE), specifically wind and hydrokinetic energy capture, have made these energy 

sources a practical reality in the immediate future, there are concerns over what the impact of large 

offshore energy-capture installations may be on the marine environment (Cada et al. 2007; Gill 2005;

Inger et al. 2009; Petersen and Malm 2006; Punt et al. 2009). Locating offshore energy installations 

requires a balance between areas with sufficient wind or tidal energy with shallow seafloor depths which 

are close enough to shore (Punt et al. 2009) and the habitat impact on these coastal ecosystems (Gill 

2005). 

The installation of offshore energy facilities is a multi-phased process that produces varying degrees of 

noise, including ship traffic, sonar use, and construction noise from pile-driving and trenching. These 

steps involve both long- and short-term disturbances with different frequencies and intensities of sound, 

potentially impacting a wide variety of marine vertebrates. The operation and servicing of the installation 

also produces noise, though the range over which these sounds propagate is site-specific and has 

previously not been well documented in the U.S. east coast (Clark et al. 2009; Madsen et al. 2006). 

Marine vertebrates (i.e., mammals and fishes) may be affected by anthropogenic noise (e.g., Clark et al. 

2009; National Research Council 2003; National Research Council 2005; Nowacek et al. 2007; Popper 

2003; Radford et al. 2014; Slabbekoorn et al. 2010; Slabbekoorn 2012), but there is a limited 

understanding of how ORE construction and operation would specifically affect them (marine mammals: 

Madsen et al. 2006; fishes: Wahlberg and Westerberg 2005). Understanding the quality of the noise and 

how far it is transmitted is critical to determining how the area over which the noise might influence the 

acoustic habitat (Clark et al. 2009; Madsen et al. 2006). Fishes may be able to detect operating wind

farms as far as 25 km away (Wahlberg and Westerberg 2005). Harbor porpoises and harbor seals respond 

to the sounds from wind turbines (Koschinski et al. 2003; Madsen et al. 2006), and may be able to detect 

construction-related noise as far as 20–200 km away (Bailey et al. 2010; Madsen et al. 2006; Tougaard et 

al. 2009b). Construction and operation of European OAE installations may result in a significant 

percentage of harbor porpoises abandoning the habitat altogether (Gilles et al. 2009). However, the degree 

and breadth of the acoustic impact of ORE development on communication masking and habitat 

abandonment of both sonic and non-sonic animals is still unclear (Madsen et al. 2006; Wahlberg and 

Westerberg 2005). 

Marine mammals are of principal concern in the context of anthropogenic ocean noise (Hildebrand 2009; 

Nowacek et al. 2007; Tyack 2009); construction and shipping activity potentially mask communicatory 

signals (Clark et al. 2009), increased stress (Nowacek et al. 2007; Rolland et al. 2012), or habitat 

abandonment (Gilles et al. 2009; Rako et al. 2013). Though the reactions of toothed whales (i.e., dolphins 

and porpoises) to ORE development have been explored (Carstensen et al. 2006; Gilles et al. 2009; 

Koschinski et al. 2003; Tougaard et al. 2009a; Tougaard et al. 2009b), there are no data on the reactions 

of baleen whales to ORE development (Madsen et al. 2006). 

Like cetaceans, the behavior of individuals and populations of many fish species can be assessed with 

passive acoustics (Fine and Thorson 2008; Luczkovich et al. 2008a; Luczkovich et al. 2008b; Rountree et 

al. 2006). The U.S. Atlantic coast is home to over 100 species of sonic fishes (Fish and Mowbray 1970; 

Rountree et al. 2006), and many of these species’ biology (and changes in their ecology) can be 
10 

understood using acoustics in a similar manner as used to study to marine mammals (e.g., Hernandez et 

al. 2013; Rountree et al. 2006; Van Parijs et al. 2009). 

1.1. PROJECT OBJECTIVES AND APPROACH

The goal of this effort is to conduct a baseline ecological assessment of two wind planning areas (shown 

below in Figure 2.2) along the U.S. Atlantic coast (Table 1.1) to identify the potential environmental 

impact of offshore wind energy construction. Our goal was to establish a baseline of seasonal activity of 

focal species using passive acoustic monitoring to understand their acoustic presence and calling patterns, 

and establish the baseline noise conditions of the areas. These baseline data would be used to evaluate 

potential changes that may result from future wind energy construction and operation. 

We sought to investigate two suites of organisms as part of this project. The first are three species of 

baleen whales (North Atlantic right whales, fin whales, and humpback whales) that are thought to 

potentially migrate through or near the wind planning area. These species are protected by both the 

Endangered Species Act and the Marine Mammal Protection Act, and as federally protected species, any 

human activities must seek to minimize any possible impact (either direct or indirect) to members of the 

population. The second group of organisms is comprised of two species of acoustically active fishes 

(black drum [Pogonias cromis] and oyster toadfish [Opsanus tau]) that produce sounds as part of their 

life history. Both black drum and toadfish are distributed along the entirety of the U.S. Atlantic coast, and 

produce well-characterized sounds in agonistic and reproductive contexts (Mok and Gilmore 1983); these 

fish choruses are some of the most prominent sounds of the biological sound spectrum (Tavolga 1965; 

Urick 1983). Because toadfish are benthic and poor swimmers, though black drum are demersal and much 

better swimmers, differences in the calling patterns between these two species following construction may 

indicate different degrees of impact on the marine benthic compared to the pelagic community. 

This project had two complementary components to the biological species monitoring. ESS Group, Inc. 

conducted a literature-based habitat assessment of both wind planning areas to investigate the benthic 

habitat and evaluate the natural resources occurring in these areas. Marine Acoustics, Inc. created a sound 

propagation model to estimate the spatial extent and magnitude of noise produced by wind turbine 

construction activities. 

1.2. PROJECT HISTORY AND EVOLUTION

This project was originally designed to implement a broadly applicable approach at four candidate wind 

planning areas (Rhode Island, North Carolina, Georgia, Florida) at the time of the opportunity 

announcement. The characterization of noise activities and impacts was also intended as a before-duringafter monitoring paradigm, with surveys within the wind-planning area and at suitable control sites. After 

the project began, the project sites were narrowed down to the North Carolina and Georgia wind planning 

areas (Table 1.1). As year one of the project came to a close, it became clear that it was unlikely that any 

offshore wind construction would occur at either of the wind planning areas during the course of the 

project, so in consultation and agreement with the Bureau of Ocean Energy Management (BOEM) and the 

Bureau of Safety and Environmental Enforcement (BSEE), the scope of the project was changed to be a 

baseline study to characterize habitat sites, evaluate focal species occurrence, and model wind turbine 

construction activities. 
11 

Table 1.1. BOEM Outer Continental Shelf (OCS) blocks within the Beaufort and Brunswick regions, 

designated as wind planning areas.

Region (Lease Block) OCS Lease Sub-Block Number

Beaufort (NI18-04) 6727

6782, 6781, 6780, 6779, 6778, 6777, 6776, 6775

6833, 6832, 6831, 6830, 6829, 6828, 6827, 6826, 6825

6884, 6883, 6882, 6881, 6880. 6879, 6878, 6877, 6876

6933, 6932, 6931, 6930, 6929, 6928, 6927, 6926

6982, 6981, 6980, 6979, 6978, 6977

7031, 7030, 7029, 7028, 7027

7079, 7078

Brunswick (NH17-02) 6126
12 

2. SOUND RECORDING METHODS

Acoustic data were collected using marine autonomous recording units (MARUs). A MARU is a digital 

audio recording system contained in a positively buoyant 17” glass sphere that is deployed on the bottom 

of the ocean for periods of weeks to months (Figure 2.1, Calupca et al. 2000). A hydrophone mounted 

outside the sphere is the mechanism for acquiring sounds that are recorded and stored in a binary digital 

audio format on internal electronic storage media. The MARU can be programmed to record on a daily 

schedule and deployed in a remote environment, where it is held in place by an anchor. At the conclusion 

of a deployment, the MARU is sent an acoustic command to release itself from its anchor and float to the 

surface for recovery. After the recovery, the MARU data are extracted, converted into audio files and 

stored on a server for analysis. The unit is then refurbished (batteries and hard drive replaced, etc.) in 

preparation for a subsequent deployment. Data recorded by a MARU are thus accessible only after the 

device is retrieved.

Figure 2.1. Views of the MARU. 

A) External and B) internal views of the Marine Autonomous 

Recording Unit (MARU) used for sound data recordings in this 

project. 

The MARUs were deployed at two wind energy planning areas off the coasts of North Carolina and 

Georgia (Figure 2.2). At each site, three MARUs were deployed in a linear formation across the wind 

energy planning area and designated from north to south as NC-North, NC-Central, NC-South, GANorth, GA-Central, GA-South (Figure 2.2, Table 2.1). Distance between MARUs was approximately 35 

km in the North Carolina site and 18 km in the Georgia site, and seafloor depths at the deployment 

locations ranged from 14 m to 38 m (Table 2.1). 

Acoustic data were recorded in two consecutive deployments of the MARUs at each site, from 12 June–

10 November 2012 and 12 November 2012–15 April 2013 at the North Carolina site and 9 June–8 

November 2012 and 10 November 2012–12 April 2013 at the Georgia site. A total of 307 consecutive 

days were recorded at each site, with the exception of 11 November 2012 in North Carolina and 9 

November 2012 in Georgia, when MARUs were replaced for the following deployment. Sound data were 

sampled at 2 kHz with high-pass and low-pass filters set at 10 Hz and 800 Hz, respectively. The high-pass 

filter was implemented to reduce electrical interference produced by the MARU, while the low-pass filter 
13 

reduced aliasing. The effective recording bandwidth of 10 Hz to 800 Hz had a flat frequency response (± 

2.0 dB). 

Sound data from the MARUs at each site were synchronized in time and concatenated into three-channel 

sound files for analysis.

Figure 2.2. Deployment locations of MARUs. 

Deployment locations of three Marine Autonomous Recording 

Units (MARUs) (North (N), Central (C), South (S)) at the (a) North 

Carolina site and (b) Georgia site, with respect to the wind 

planning areas.

Table 2.1. Coordinates and depths of marine autonomous recording units (MARUs) deployed at 

the North Carolina site and the Georgia site.

MARU Latitude° Longitude° Depth (m)

North Carolina Site NC-North 34.3927 -76.2356 31

NC-Central 34.1741 -76.5098 34

NC-South 33.9613 -76.7925 38

Georgia Site GA-North 31.9922 -80.5970 14

GA-Central 31.8640 -80.7207 14

GA-South 31.7463 -80.8544 14
14 

3. BALEEN WHALE PRESENCE 

3.1 INTRODUCTION

The North Atlantic right whale (Eubalaena glacialis) is one of the most endangered whale species in the 

world; it is protected by the Endangered Species Act and the Marine Mammal Protection Act (Clapham et 

al. 1999; Waring et al. 2013a). Currently, the western North Atlantic population consists of approximately 

400–500 individuals (Pettis 2013; Waring et al. 2013a). Despite a recent growth in stock assessment 

estimation, right whales continue to have a slow and difficult recovery due to low population size, low 

reproductive rates, and exposure to anthropogenic threats (Fujiwara and Caswell 2001; Fujiwara and 

Caswell 2001; Kraus et al. 2007; Kraus et al. 2005; Kraus et al. 2005; Kraus and Rolland 2007; Waring et 

al. 2013a). Ship strikes and entanglement with fishing gear are the leading causes of human-induced 

mortality for this population, and sub-lethal threats, such as noise pollution, may potentially disrupt 

biologically relevant behaviors (Clark et al. 2009; Knowlton and Kraus 2001; Kraus 1990; Parks and 

Clark 2007). 

The National Oceanic and Atmospheric Administration (NOAA)’s National Marine Fisheries Service 

(NMFS) implemented protective measures to mitigate anthropogenic threats to right whales (NMFS 

2005), including designating seasonal management areas (SMAs) along the southeast, mid-Atlantic, and 

northeast nearshore waters of the western North Atlantic that require vessels 65 ft. (19.8 m) or greater to 

reduce speeds during seasons when right whales are likely to be present (NOAA 2008). Although 

reducing vessel speed decreases the risk of ship strike mortality (Conn and Silber 2013; Vanderlaan and 

Taggart 2007; Wiley et al. 2011), current mitigation efforts may not provide adequate protection due to 

incomplete spatial and temporal coverage of right whale habitat and occurrence (Schick et al. 2009; van 

der Hoop et al. 2013). Because the efficacy of current management protocols is uncertain, it has been 

recommended that managers re-evaluate and modify management regulations as necessary (Pace 2011; 

van der Hoop et al. 2013). 

NOAA designated right whale critical habitats to protect and manage geographic areas important for right 

whale conservation (FWS 2011; NOAA 1994). The U.S. Endangered Species Act defines critical habitat 

as geographic areas that contain physical and biological features important for life processes and 

reproduction, which may include breeding and calving grounds, feeding sites, and representative habitats 

of the historical distribution of a species (FWS 2011; NOAA 1994). Currently, protected right whale 

habitats include calving areas along the coasts of Florida and Georgia and feeding areas in the Great 

South Channel (southeast of Cape Cod) and both Massachusetts Bay and Cape Cod Bay (Figure 3.1) 

(NOAA 1994). Other known right whale habitats, however, are not included, and thus not afforded the 

same protections as critical habitats. Because calving and feeding events have been documented outside 

of critical habitat boundaries (Patrician et al. 2009; Whitt et al. 2013), other areas may also be essential 

right whale habitats. Moreover, efforts to conserve right whales may be diminished if right whales are not 

protected within the migratory corridor between critical habitat areas (NMFS 2005). Therefore, 

regulations have been proposed to expand critical habitat boundaries (NOAA 2010). 

Understanding right whale distribution and seasonal migratory patterns is essential to inform current 

management practices. Visual surveys indicate that right whale movements are characterized by an 

annual, round-trip migration in nearshore waters along the western north Atlantic (Winn et al. 1986). 

During this migration, right whales congregate in Florida and Georgia calving grounds during winter, 

migrate in nearshore waters during late winter and early spring to Cape Cod and Massachusetts Bays, 

then travel to the northern feeding grounds in the Great South Channel during spring, and peak during 
15 

summer and autumn either in the Bay of Fundy feeding and nursery grounds or the Scotian Shelf feeding 

grounds (Kenney et al. 2001; Kenney et al. 1995; Kraus et al. 1986; Winn et al. 1986). Although the 

migration explains the distribution of many right whales, recent studies have detected right whales at 

times of the year when their occurrence in a region was not previously expected. For instance, Morano et 

al. (2012) and Whitt et al. (2013) detected right whale occurrence year-round in Massachusetts Bay and 

the New Jersey coast, respectively, and Mellinger et al. (2007) detected right whales on the Scotian Shelf 

in late December, when much of the population would be predicted to have left for more southerly areas. 

These observations suggest seasonal migratory movements are not characteristic of the entire population, 

because only a subset of the population (predominately reproductive females, calves, and juveniles) are 

observed traveling along the migratory corridor between calving and feeding grounds (Kraus et al. 1986; 

Winn et al. 1986), and it is not known where the remaining members of the population spend the winter 

(Kraus et al. 1986; Winn et al. 1986). Given these findings, investigating right whale spatial and temporal 

patterns along the right whale’s migratory route, particularly in regions where movement patterns are not 

well understood, could help inform management decisions. 

Figure 3.1. Deployment location of MARUs with respect to protected areas for right whales. 

Deployment locations of marine autonomous recording units (MARUs) at the A) North Carolina site and 

B) Georgia site, with respect to critical habitats, seasonal management areas (SMAs), and wind planning 

areas.
16 

The coastal waters of Georgia and North Carolina are part of the mid-Atlantic migratory habitat for right 

whales traveling between the southeast calving grounds and the northeast feeding grounds (Waring et al. 

2013a). However, little is understood about right whale spatial and temporal occurrence in the migratory 

corridor, due to limited systematic visual survey effort in the mid-Atlantic U.S. (Firestone et al. 2008; 

Knowlton et al. 2002). Other endangered whales, including fin and humpback whales, also inhabit the 

mid-Atlantic U.S., yet this region has some of the heaviest vessel traffic along the eastern seaboard and is 

considered the region of highest risk for vessel-strike mortality (Knowlton et al. 2002; Silber and 

Bettridge 2010; van der Hoop et al. 2013). Currently, coastal Georgia and North Carolina are being 

considered for offshore wind energy development (BOEM 2012a; BOEM 2012b), which would increase 

vessel traffic and the risk of injury or mortality to cetaceans due to ship strikes (van der Hoop et al. 2012). 

Development activities, including construction and site surveys, would also introduce disturbances that 

could cause acoustic masking, hearing impairment, or stress (Clark et al. 2007; Madsen et al. 2006; 

Rolland et al. 2012; Weilgart 2007). Given that baleen whales are susceptible to these threats, information 

regarding right, fin, and humpback whale occurrence is needed to minimize potential impacts of offshore 

energy development activities. 

We performed an eleven-month ecological baseline study to characterize right, fin, and humpback whale 

occurrence in two proposed offshore wind energy sites in the mid-Atlantic U.S. In this paper, we 

summarize passive acoustic survey data to elucidate spatial and temporal patterns of right whale 

occurrence along the migratory corridor in two survey areas along the Georgia and North Carolina coasts. 

We discuss the management implications of our findings for right whale occurrence along the migratory 

corridor with respect to mitigating threats introduced by offshore energy development. 

3.2 METHODS

Analysis of acoustic recordings (see Chapter 2) focused on the presence of three baleen species: North 

Atlantic right whales, fin whales (Balaenoptera physalus), and humpback whales (Megaptera 

novaeangliae). We determined the acoustic presence of right whales by identifying contact calls (upcalls), the predominant call type of the species (McDonald and Moore 2002; Mellinger et al. 2007; Parks 

and Tyack 2005; Parks and Clark 2007; Parks et al. 2007), with an automated detection algorithm 

(Urazghildiiev et al. 2009). Performance evaluations of the algorithm by Urazghildiiev et al. (2009) and 

Dugan et al. (2010) reported true detection rates of 80% and 75%, respectively. To verify the validity of 

detections in this dataset, we reviewed 10–450 Hz spectrograms of the detection output in the 

MATLAB©-based software program XBAT© (BRP 2012), with a 512-point (256 ms) Hann window and 

75% overlap (frequency resolution of 3.91 Hz, time resolution of 64 ms). We applied the following set of 

criteria to distinguish up-calls from other biological and anthropogenic sounds: (i) starting frequency 

occurred between 65–170 Hz; (ii) minimum and maximum frequencies differed by 75–200 Hz; (iii) 

duration ranged from 0.3–1.3 s; (iv) energy was concentrated in the lower portion of the signal; and (v) 

signal contour sloped upward (Figure 3.2). 

The daily presence of right whales at each site was determined as the occurrence of at least one up-call 

per day on at least one MARU at the site. Percent daily presence during each month was normalized for 

recording effort by dividing the number of days containing up-calls by the number of recorded days 

within the month. To represent presence seasonally, months were grouped into seasons, and the number 

of days containing up-calls within a season was divided by the number of recorded days in the season. 

Seasons were defined as follows: summer (July 2012–September 2012), autumn (October 2012–

December 2012), winter (January 2013–March 2013), and spring (June 2012 and April 2013). To 

determine the proportion of daily presence that occurred while the mid-Atlantic SMA was in effect, we 
17 

divided the number of days containing up-calls during November 1–April 30 by the total number of days 

in the study that contained up-calls. 

Figure 3.2. Examples of right whale contact calls.

Examples of right whale contact calls (up-calls) recorded at the 

Georgia site on A) 3 January 2013, B) 14 October 2012, C) 13 

July 2012, and D) 28 June 2012. The selection box in example 

C) distinguishes the contact call from adjacent noise. 

The daily presence of fin whales was based on the occurrence of the 20 Hz note, a subunit of fin whale 

song and a prominent call type of the species (Thompson et al. 1992; Watkins et al. 1987; Watkins 1981). 

Notes were detected using the data template detector function in XBAT, which performs spectrogram 

cross correlations between a user-defined exemplar signal and the recording (Mellinger and Clark 2000). 

We verified the detection output using 60-second spectrograms spanning 10–100 Hz, with a 1024-point 

(512 ms) Hann window and 75% overlap (frequency resolution of 1.95 Hz, time resolution of 128 ms). 

We applied the following set of criteria to distinguish 20 Hz notes from other biological and 

anthropogenic sounds: (i) minimum frequency occurred between 17–20 Hz; (ii) maximum frequency 

occurred between 20–30 Hz; (iii) note duration was approximately 1 s; (iv) three or more consecutive 

notes were visible with a consistent internote interval; and (v) internote intervals were no less than 6 s and 

no greater than 21 s (Figure 3.3). 

To evaluate the performance of the fin 20 Hz note detector, we manually browsed the days containing 

valid fin whale detections and determined the detector’s accuracy in reporting hourly presence of 20 Hz 

notes. We measured hourly presence of 20 Hz notes instead of daily presence because of the rare 

occurrence of fin 20 Hz notes in the data. Days were manually browsed using 15 min spectrograms 

spanning 10–60 Hz, with a 4,096-point (2,048 ms) Hann window and 75% overlap (frequency resolution 

of .49 Hz, time resolution of 512 ms). The detector had a true positive detection rate of 0.39 (29 of the 75 

hr containing 20 Hz notes). Although these hourly results may be difficult to extrapolate to daily 

presence, this performance provides an estimate of the degree that fin whale presence is unaccounted. 
18 

Humpback whales, which produce highly variable, frequency modulated signals in the form of calls 

(social sounds) (Dunlop et al. 2007; Dunlop et al. 2008) and structured song (Payne and McVay 1971; 

Stimpert et al. 2011), were noted opportunistically when their signals were observed during the 

verification of right whale up-call detections (Figure 3.4) and during fish presence analyses (see Chapter

4.2.2). Because humpback whales were noted opportunistically rather than systematically, we did not 

determine spatiotemporal trends in presence. 

Figure 3.3. Example of fin whale 20 Hz note.

Example of fin whale 20 Hz note recorded at the North 

Carolina site on 15 March 2013.

Figure 3.4. Examples of Humpback Whale Social Sounds

Examples of humpback whale social sounds recorded at the Georgia site on A) 15 November 2012, and 

B) 2 December 2012, and at the North Carolina site on C) 3 December 2012, and D) 4 December 2012. 

The selection boxes in example A) distinguish social sounds from adjacent noise. Note the frequency 

scale in example C) differs from the others.
19 

3.3 RESULTS

Right and humpback whales were acoustically detected in both the Georgia and North Carolina survey 

areas, and fin whale was acoustically detected in the North Carolina survey area. Right whale up-calls 

were acoustically detected on 80 days (26.1%) in the Georgia site and 22 days (7.2%) in the North 

Carolina site out of the 307 total days surveyed. Fin whale 20 Hz notes were detected on six days in the 

North Carolina site, resulting in 2% daily vocal presence (Table 3.1). Humpback whale vocalizations 

were opportunistically found on eight days in the Georgia site and twelve days in the North Carolina site 

(Table 3.1). 

Table 3.1. Dates fin and humpback whales were detected at the North Carolina site and the 

Georgia site.

North Carolina Site Georgia Site

Fin Humpback Fin Humpback

11/21/2012 06/25/2012 08/31/2012

11/23/2012 08/01/2012 11/15/2012

11/24/2012 12/02/2012 12/02/2012

11/26/2012 12/03/2012 12/08/2012

12/16/2012 12/04/2012 12/15/2012

03/15/2013 12/05/2012 12/20/2012

12/06/2012 01/22/2013

12/25/2012 02/06/2013

02/08/2013

03/06/2013

03/07/2013

03/08/2013

03/10/2013

Right whale up-calls were detected acoustically in every season in the North Carolina survey area (Figure 

3.5A). Right whales were not acoustically detected during August 2012, October through November 

2012, and April 2013. February 2013 had the greatest number of detection days, with a total of seven days 

(25%) vocal presence (Figure 3.6A). The peak seasonal daily presence was 14.4% in the winter, followed 

by 6.6% seasonal daily presence in autumn (Figure 3.5A). Summer and spring had 2.2% and 2.9% peak 

seasonal daily presence, respectively. Approximately 13.6% of right whale daily presence occurred 

outside of the mid-Atlantic SMA time window. 

Right whale up-calls were acoustically detected in the Georgia survey area every season (Figure 3.5B), 

present in every month from June 2012 through March 2013 (Figure 3.6B). No detections were found 

during April 2013. Over the sampled months, December 2012 had the greatest number of detection days, 

with a total of 29 days vocal presence out of 31 days recorded. Daily percent presence per month had a 

bimodal trend; an initial peak occurred in June and July 2012, with right whales detected on 18.2% of 

days in June, and 22.6% of days in July. Peak detections dropped at or below 10% in August through 

October 2012. A larger, secondary peak occurred in November and December 2012, with right whales 

detected on 44.8% of days in November and 93.6% days in December (Figure 3.6B). Peak daily presence 

dropped below 30% in January through March 2013. Subsequently, peak seasonal daily presence 
20 

occurred in the autumn and winter, with seasonal daily presence of 49.5% and 21.1%, respectively 

(Figure 3.5B). Summer had 13% seasonal daily presence, and spring had the lowest seasonal daily 

presence of 10.8%. Nearly a third (28.8%) of right whale daily presence occurred outside the mid-Atlantic 

SMA time window.

Figure 3.5. Seasonal presence of right whales.

Seasonal presence, percent of recorded days during each season with 

acoustic presence, of right whales at the (A) North Carolina site and 

(B) Georgia site.
21 

Figure 3.6. Percent vocal presence of right whales.

Percent vocal presence, percent of recorded days during each month 

with acoustic presence, of right whales at the (A) North Carolina site 

and (B) Georgia site. No recordings were made during May.

3.4 CONCLUSIONS

In our acoustic survey, fin whales were detected only in the North Carolina survey site, for a total of six 

days during the autumn and winter months. Our findings are consistent with previous acoustic studies and 

stranding records from similar latitudes (Nieukirk et al. 2004; Webster et al. 1995). The North Atlantic fin 

whale stock is commonly found north of Cape Hatteras within the U.S. Exclusive Economic Zone 

(Waring et al. 2013b). Given that both the Georgia and North Carolina survey sites occur just south of 

Cape Hatteras, it is expected that fin whale presence in lower latitudes would be infrequent. However, fin 

whales are a highly distributed species, and little is still known regarding fin whale migratory movements, 

breeding sites, and calving areas (Nieukirk et al. 2004; Waring et al. 2013b). Fin whale presence and 

absence in the North Carolina and Georgia study sites provides additional baseline information for future 

studies.

Humpback whales were detected opportunistically in both the Georgia and North Carolina survey sites, 

predominately during the autumn and winter months. Our findings are consistent with previous acoustic 

surveys, stranding records, and visual sightings along the mid-Atlantic U.S. (Barco et al. 2002; Hodge 

2011; Nieukirk et al. 2004; Webster et al. 1995). Although the majority of humpback whales migrate 

from northern feeding areas to the southern breeding grounds near the West Indies at this time, many 

individuals stay in the mid-Atlantic U.S., possibly as a supplemental feeding ground (Barco et al. 2002; 

Waring et al. 2013a). A systematic acoustic survey would reveal more information regarding seasonal 

occurrence of humpback whales in the mid-Atlantic U.S. 

In our acoustic survey along the coastal waters of Georgia and North Carolina, right whales were detected 

during all seasons. Right whale sounds were also found in a majority of the months sampled during this 

study, suggesting that right whales may be present in the surveyed sites year-round. Given how little is 
22 

known about right whale movements and distribution in the mid-Atlantic U.S., our data provide a 

baseline understanding of right whale occurrence in the nearshore waters of Georgia and North Carolina.

The traditional migratory paradigm describes a seasonal presence of right whales along the mid-Atlantic 

U.S. between November and April, likely for travel between calving and feeding grounds (Winn et al. 

1986). Although right whales were detected between November and April, our results show right whales 

occurred in the Georgia and North Carolina sites outside of the previously documented migratory period. 

The nearly year-round presence of right whales at the survey sites indicates a pattern of presence 

inconsistent with what has been described as the “typical” seasonal migratory model. Our results suggest 

that these regions along the mid-Atlantic U.S. could also be important non-migratory habitat for right 

whales. The North Carolina site had a fairly consistent low level of presence throughout the survey period 

when compared to the Georgia site, which may have been due to fewer whales in the area, or possibly due 

to the presence of non-vocalizing whales. Peak presence in the Georgia site occurred during the late 

autumn and early winter months, which overlaps with the occurrence of right whales in the designated 

critical calving habitat (Kenney et al. 2001; Kraus et al. 1986). Given our demonstration of right whale 

presence in the Georgia study site during calving periods, and given the proximity of the study site to the 

designated critical calving habitat, it is possible that this region of the mid-Atlantic U.S. could be 

important for calving activities (Waring et al. 2013a). The North Carolina site may also be important for 

calving activities, because rare calving events have occurred outside of the critical calving habitat along 

the mid-Atlantic and northeast U.S. (Patrician et al. 2009; Waring et al. 2013a). 

Peak acoustic presence in the Georgia and North Carolina survey areas occurred between November and 

April, when whales are described to migrate through the mid-Atlantic U.S. (Winn et al. 1986). Peak 

presence may have been due to a greater number of right whales in the area, increased vocal activity, or 

both. Our data shows a decreased percent presence at the Georgia site and an increased percent presence 

at the North Carolina site between January and March. The temporal differences in peak presence 

between survey areas may reflect the previously described northerly migration in the late winter and early 

spring, when right whales depart the southern winter calving grounds along the Florida and Georgia 

coasts and travel to spring feeding areas in the northeast U.S. (Kenney et al. 2001). However, because we 

do not have observational data to confirm right whale behavior, it is unclear in what direction the right 

whales may be traveling, or if our data detected the same individuals between survey sites.

A second, smaller increase in presence occurred in June and July in the Georgia study site, when right 

whales typically aggregate in the Great South Channel, and the Gulf of Maine, and on the Scotian Shelf 

(Winn et al. 1986). Although visual surveys have detected occasional right whales in mid-Atlantic U.S. 

coastal areas during summer months, right whales have not been observed in the southeast at that time 

(Winn et al. 1986). It is unclear if our data indicate a rare occurrence or an unknown but more consistent 

presence of right whales at this time of year. Nevertheless, movement patterns that are not characteristic 

of the entire right whale population have been documented before, including presence in historical ranges 

and unexpected habitats (Jacobsen et al. 2004; Mate et al. 1997; Mellinger et al. 2011; Moore and Clark 

1963). Because right whales are not typically observed so far south outside of the calving season, further 

investigation is needed to understand what is influencing right whale summer distribution along the 

nearshore waters of Georgia.

Our data demonstrate that right whales are within the Georgia and North Carolina survey areas nearly 

year-round, and this information can be used to evaluate management decisions with respect to offshore 

energy development activities. Currently, mitigation protocols are informed by the known right whale 

seasonal distribution, limiting regional management actions to times when right whales are most likely to 

be present (BOEM 2012b). These protocols include: restricted energy development activities during timearea closures, based on the mid-Atlantic SMA time window (November 1 through April 30); constrained 

development activities in designated critical habitat during time-area closures; compliance with vessel 
23 

speed restrictions in the mid-Atlantic SMA; and marine mammal monitoring on survey vessels (BOEM 

2012b). Because right whales are present in the Georgia and North Carolina survey areas outside of the 

designated mid-Atlantic SMA time period, right whales in these areas would be at risk of exposure to 

lethal and sub-lethal threats when restrictions are not in effect. When right whales are not in SMAs or 

DMAs, BOEM Standard Operation Conditions still provide protection for this endangered species to 

restrict or prevent, or both, risk of exposure to lethal and sub-lethal threats. Additionally, the mid-Atlantic 

SMA zone has discontinuous coverage of speed zone areas concentrated around major ports, which offer 

protection within a 20 nmi (37 km) radius (NOAA 2008). Right whales may occupy habitat beyond the 

20 nmi radius, as evidenced by the data collected from the North Carolina survey site, which is located 

approximately 30 nmi (55.6 km) offshore. Therefore, right whales further offshore than the mid-Atlantic 

SMA region would also be at risk of exposure to all threats associated with energy development activities. 

Also, right whales in both the Georgia and North Carolina survey sites will not be afforded the same 

protections as whales within the critical calving habitat. Thus, enacting management decisions based 

solely on the “typical” right whale seasonal migration may not provide adequate protection for right 

whales in the surveyed mid-Atlantic regions. 

The loss of even one individual right whale, particularly a reproductive female, can have severe 

consequences to the recovery of this population from the threat of extinction (Caswell et al. 1999; Kraus 

et al. 2005). Preventing right whale mortality is of utmost importance for the conservation of this species, 

and given the risk of exposure to threats associated with anthropogenic activities, we suggest our data 

warrants a re-evaluation of many previously established management protocols. The current SMA 

geographic coverage in the mid-Atlantic U.S. may need to be amended to include other areas of suitable 

right whale habitat. Our results demonstrate right whale presence nearly year-round outside the 20 nmi 

radius of SMA protection in North Carolina. Extending the protective coverage to a minimum of 30 nmi, 

as suggested in Schick et al. (2009), would potentially mitigate vessel strikes, since reduced vessel speeds 

decrease the risk of ship-strike mortality (Conn and Silber 2013; Vanderlaan and Taggart 2007). The 

SMA time period may also need to be extended to include other seasons when right whales may occur in 

the area (Pace 2011). Last, our data could be used to consider the extension of critical habitat boundaries 

into areas along the mid-Atlantic migratory corridor (NOAA 2010). Nearly year-round presence of right 

whales in mid-Atlantic U.S. coastal waters may indicate that this region contains features important for 

right whale survival and reproduction. 

Although our data show right whale vocal presence in all seasons, our survey period is not long enough to 

elucidate long-term seasonal patterns of distribution and inter-annual variability. Other processes, such as 

prey distribution, are known to affect the movement patterns of right whales, and these patterns may vary 

over time (Baumgartner et al. 2003; Pendleton et al. 2009; Wishner et al. 1995). A longitudinal 

monitoring effort would not only reveal further information about right whale spatial and temporal 

patterns, but could also address questions regarding demography, abundance, and habitat use. Currently, 

visual survey monitoring efforts are not conducted in the North Carolina survey area, and aerial 

monitoring is being discontinued in the Georgia survey area (Hain et al. 2013). Given how little is known 

about right whales in the mid-Atlantic migratory corridor, we recommend long term monitoring efforts be 

conducted along the Georgia and North Carolina coasts in the mid-Atlantic U.S. We recommend 

managers consider the use of passive acoustic monitoring in conjunction with visual survey efforts. 

Visual surveys provide observational data that inform questions regarding demography and behavior of 

right whales, which cannot be addressed with passive acoustic data. However, passive acoustic 

monitoring is an effective and economical tool for monitoring right whales over extended periods, 

particularly when right whale occurrence is infrequent, and when aerial surveys cannot be performed due 

to the time of day or inclement weather (Clark et al. 2010; Mellinger et al. 2007). Passive acoustic 

monitoring, in conjunction with visual survey efforts, would provide the most comprehensive 

understanding of right whale distribution and habitat characterization to better inform management 

decisions. 
24 

4. FISH PRESENCE

4.1 INTRODUCTION

Coastal marine ecosystems provide a range of ecosystem services, yet are under threat from many 

anthropogenic pressures (Foley et al. 2010; White et al. 2012). These ecosystems contain most of the 

world’s fisheries, provide the potential for energy exploration and extraction, facilitate global trade 

through commercial shipping, and provide sources of tourism and recreation (Foley et al. 2010; White et 

al. 2012). The increased awareness of acute and chronic environmental impacts resulting from human 

activities has necessitated a desire to balance the need for such activities with environmental protection 

and preservation, and is central to the concept of environmental sustainability (Clark and Dickson 2003; 

Foley et al. 2010). Emphasis on marine sustainability has coincided with the approach referred to as 

Coastal and Marine Spatial Planning, which seeks to balance human environmental use with sustainable 

development in ocean environments (Foley et al. 2010; Lester et al. 2013; White et al. 2012). 

Evaluating how ecosystems are impacted by human use requires measuring environmental parameters 

that are indicative of an ecological response. Initial environmental impact assessments typically focus on 

acute and/or lethal impacts to organisms, but longer-term study of habitats has revealed the potential 

severity of sub-lethal, chronic impacts. Many human activities in natural habitats create multiple complex 

stressors on the habitat (Crain et al. 2008; Ellison et al. 2012), and it can be challenging to evaluate 

differential effects from different sources, or the cumulative impact from multiple stressors (Crain et al. 

2008). To evaluate impact on an ecosystem, monitoring approaches are needed that include surveys for 

organisms and their behavior or physiology in response to human activities. Such monitoring approaches 

need to account for the fact that ecological change may occur gradually, and unfold over long periods of 

time and at broad spatial scales. Ecological change may manifest itself as the change in habitat quality, 

habitat structure, species composition, or species behavior.

Passive acoustic monitoring has emerged as a non-invasive, data-intensive, low-cost methodology to 

survey the occurrence, abundance and behavior of acoustically active organisms (Bridges and Dorcas 

2000; Van Parijs et al. 2009; Zimmer 2011). Passive acoustic surveys have been used to examine the 

response of specific taxonomic groups to environmental correlates or pressures (Busby and Brecheisen 

1997; Gibbs et al. 2005; Luczkovich et al. 2008a; Rountree et al. 2006), as well as to identify those 

taxonomic groups whose occurrence or behavior could reflect habitat fidelity (Arroyo-Solis et al. 2013; 

Hansen et al. 2005). Acoustic recorders can collect data over long time periods and broad spatial scales to 

provide large-landscape evaluations of environmental change. Additionally, the ability to store and 

archive acoustic files allows for long term accessibility of acoustic survey data to allow datasets to be reexamined to evaluate changes in bioacoustic activity many years after they were first collected. Passive 

acoustic surveys can be conducted in remote locations that are not easily accessible by more traditional 

survey techniques. 

Along the U.S. Atlantic coast, a great number of fish species produce sounds for intraspecific 

communication. Atlantic coast fishes are probably the best acoustically characterized assemblage of 

fishes, with research on these species spanning over a century (Fish and Mowbray 1970; Tavolga 1965; 

Tower 1908). Fishes, like many other vertebrates, produce sounds as a fundamental component of their 

life history, primarily in reproductive or agonistic contexts (Bass and McKibben 2003). During spawning 

season, many fishes form large assemblages and produce advertisement calls that are sustained over hours 

or days, and are regularly the most dominant biological acoustic signal in the environment (e.g., Aalbers 

and Drawbridge 2008; Gannon 2008; Locascio and Mann 2011a; Locascio and Mann 2011b; Rowe and 

Hutchings 2006). The acoustic behavior of fishes is advantageous for passive acoustic monitoring 

approaches that can document species occurrence, distribution, behavior, and potential habitat quality 
25 

(Van Parijs et al. 2009), as has similarly been done with frogs (Bridges and Dorcas 2000), birds 

(Blumstein et al. 2011; Hansen et al. 2005), and marine mammals (Mellinger et al. 2007; Zimmer 2011). 

Documented knowledge of sound production among a variety of fish species can be used to identify 

occurrence, population level changes, and important habitat areas (Lowerre-Barbieri et al. 2013; 

Luczkovich et al. 2008b; Luczkovich et al. 1999; Walters et al. 2009), or in an applied context to 

understand population responses to environmental perturbations (Walters et al. 2013). By using passive 

acoustic monitoring to understand and document baseline spawning periodicity of populations, 

observations of changes from these established baselines can be used as an indicator of potential changes 

in population ecology. 

Different fish species can be potential ecological indicators for different habitats. Many of the 

acoustically active fish species often have relatively limited migration distances, and are regularly 

resident in certain areas. Different fish species occupying the same habitat have a diversity of ecological 

roles and requirements, and simultaneous observations of multiple species can reveal differential impacts 

across the ecosystem. Reproductive activity is one of the first measurable behaviors to change in response 

to environmental disturbance; this has been demonstrated in a wide variety of acoustically active taxa 

(Arroyo-Solis et al. 2013; Gibbs et al. 2005; Rako et al. 2013; van Buggenum and Vergoossen 2012). 

Whereas much of coastal marine spatial planning examines the potential impact to protected marine 

species such as marine mammals and sea turtles (White et al. 2012), these protected species are not 

intended to serve as ecological indicators of an ecosystem, and the ability to infer habitat or ecosystem 

changes from monitoring these species is limited. Marine mammal monitoring is targeted for species 

conservation under the U.S. Endangered Species Act, and not targeted or necessarily effective for 

ecosystem assessment. Surveying the behavior of different focal fish species provides a way to evaluate 

their ecology and habitat changes more effectively than low abundance or seasonally migrating species, 

such as whales. Several of the soniferous Atlantic fish species have served as model organisms for 

understanding fish and vertebrate communication (Amorim 2006; Bass and McKibben 2003), and there is 

a detailed understanding of the production, perception, behavioral function, and ecological role and 

importance of their acoustic behavior (Bass and Ladich 2008). We suggest that the knowledge of the 

function, behavior and ecology of fish sounds makes fish a potentially valuable indicator of ecosystem

status.

Several offshore locations along the U.S. Atlantic coast have been identified as potential sites for wind 

energy development. The development of offshore wind as a renewable energy resource offers 

tremendous potential for sustainable energy in the U.S., but there are concerns about the possible 

ecological impacts from wind turbine construction and operation. Ecological monitoring in the North Sea 

has been conducted to evaluate possible impacts of wind farm development and operation on different 

marine species, with mixed results (Andersson and Öhman 2010; Bailey et al. 2010; Gilles et al. 2009; 

Kikuchi 2010). However, these previous studies are primarily evaluating potential impacts to fish 

populations with acute or lethal criteria, and not examining the role of sub-lethal chronic impacts leading 

to behavioral or ecological changes in fish populations resulting from offshore wind development and 

operation. The passive acoustic monitoring methods used in this study allow for the continuous 

monitoring of the behavior of fish populations through different stages of development and operation, and 

have the potential to reveal subtle changes in fish behavior. 
26 

4.2 METHODS

4.2.1 Focal Species

Black drum (Pogonias cromis) and oyster toadfish (Opsanus tau) are coastal fishes, distributed along the 

Atlantic coast of the U.S., from New England to Argentina and New England to Florida, respectively 

(e.g., Silverman 1979). Both species associate closely with the benthic habitat. Black drum are demersal 

and feed on mollusks in mud and sand (Pearson 1929). Oyster toadfish are omnivorous, preferring crabs 

(Gray and Winn 1961). Black drum reside in bays, estuaries, and shallow, euryhaline areas and can 

tolerate hypersaline estuaries (Frisbie 1961; Silverman 1979). Larvae and juveniles may remain within 

these smaller bodies of water, but adults may move offshore (Frisbie 1961) or travel hundreds of 

kilometers up the U.S. coast during spawning season (Murphy et al. 1998). Adult toadfish move into 

shallow water for spawning, but then move offshore in the winter. Juvenile oyster toadfish remain inshore 

(Fine 1978; Isaacson 1964; Schwartz 1974). 

Black drum are group-synchronous, broadcast spawners, aggregating in the spring near mouths of bays 

and rivers to fertilize pelagic eggs (Fitzhugh et al. 1993; Nieland and Wilson 1993; Silverman 1979). 

Using muscles attached to the swimbladder (Tower 1908), males produce a distinct call for reproductive 

advertisement (Fish and Mowbray 1970; Mok and Gilmore 1983) that can be loud, exceeding 160 dB 

(Locascio and Mann 2011a). Male toadfish also produce a call to attract females (Gray and Winn 1961; 

Gudger 1912) using dedicated muscles on the swimbladder (Burkenroad 1931). Males defend benthic 

nests in late spring through summer and remain with the nests until the larvae are free swimming (Gray 

and Winn 1961). During the peak of the reproductive season, when multiple male black drum and 

toadfish are calling simultaneously, the high rate of calls is termed a chorus. Although these calls are 

associated with courtship and spawning, toadfish can continue to call beyond the mating season (Fine 

1978). 

4.2.2 Acoustic Analysis

From the acoustic data collected at three MARUs at each of the North Carolina and Georgia sites (see 

Chapter 2), we determined the daily presence of both black drum and oyster toadfish by identifying the 

loud drum calls of black drum (Mok and Gilmore 1983) (Figure 4.1.A–D) and the boat whistle calls of 

oyster toadfish (Tavolga 1958) (Figure 4.1.E–H). Calls were initially identified opportunistically during 

right whale analysis (see Chapter 2), but on those days without identified calls, we reviewed 60-s 

spectrograms spanning 10–450 Hz with a 512-point (256 ms) Hann window and 75% overlap (frequency 

resolution of 1.95 Hz, time resolution of 26 ms) using the Matlab-based software program XBAT

(Bioacoustics Research Program 2012). Because oyster toadfish call throughout the day (Fine et al. 1977) 

and black drum typically call from dusk to midnight (Mok and Gilmore 1983; Saucier and Baltz 1993), 

we analyzed 12 hours of each day from 0:00–6:00 and 18:00–24:00. Black drum calls were distinguished

from other biological and anthropogenic sounds using the following criteria (sensu Fish and Mowbray 

1970; Mok and Gilmore 1983): (i) fundamental frequency occurred between 70–120 Hz, (ii) 0–4 

harmonics were visible, (iii) duration ranged from 0.2–0.5 s, (iv) signal was preceded by a broadband 

pulse when the signal to noise ratio was optimal, and (v) signal contour sloped downward. Oyster toadfish 

calls were identified by the following criteria (Fine and Thorson 2008; Tavolga 1958): (i) fundamental 

frequency occurred between 100–300 Hz, (ii) 0-2 harmonics were visible, (iii) duration ranged from 0.2–

0.4 s, and (iv) signal contour was flat or sloped downward. Daily presence of each fish species was 

determined as the occurrence of at least one call per day on each MARU. 
27 

Black drum and toadfish choruses were determined by examining 60-min spectrograms spanning 0–1000 

Hz with a 512-point (256 ms) Hann window and 25% overlap (frequency resolution of 1.95 Hz, time 

resolution of 26 ms) and identifying sustained calling by black drum or toadfish, which is visible as a 

continuous band of signals corresponding to the fundamental frequencies and harmonics of each species’ 

call (approximately 80 Hz, 160 Hz, and 240 Hz for black drum; approximately 120 Hz and 240 Hz or 

230-250 Hz for toadfish) (Figure 4.2). This results in a calling rate of approximately one or more calls per 

second, and calls may overlap. Chorusing is distinctly different from individual, isolated calls that cannot 

be seen in 60-min spectrograms. Daily presence of the chorus for each species and the approximate start 

and end times (rounded to the closest hour) was determined for each day on each MARU.

If signals from humpback whales were visible during these analyses for black drum and toadfish, they 

were noted and contributed to humpback whale opportunistic presence analyses (see Chapter 3). 

Water temperature was recorded every 15 minutes with a Hobo® Pro v2 (Onset Computer Corporation, 

Bourne, MA) in each MARU. Daily average temperature was calculated at each recoding site and 

compared to daily presence of black drum and oyster toadfish with a logistic regression in JMP® Pro 10 

(SAS Institute Inc., Cary, NC) to examine the relationship between water temperature and occurrence of 

these fish.

Figure 4.1. Variation in black drum loud drum and oyster toadfish boat whistle 

calls identified in North Carolina and Georgia.

Fundamental frequency (Fo) of black drum calls varied between 70-100 Hz. For example, 

black drum A) Fo = 100 Hz recorded at NC-North on 16 December 2012, B) Fo = 80 Hz 

recorded at GA-Central on 8 January 2013, C) Fo = 75 Hz recorded at GA-Central on 8 

January 2013, and D) Fo = 85 Hz recorded at GA-Central on 8 January 2013. The Fo of 

oyster toadfish calls varied between 100-170 Hz. For example, toadfish E) Fo = 250 Hz 

recorded at GA-North on 15 July 2012, F) Fo = 180 Hz recorded at GA-North on 19 October 

2012, G) Fo = 150 Hz recorded at GA-North on 12 November 2012, and H) Fo = 100 Hz 

recorded at GA-South on 31 March 2013. Spectrograms were created in Raven 1.5 

(Bioacoustics Research Program 2014), for A–D, with a 512-point Hann window and 90% 

overlap (frequency resolution of 3.91 Hz, time resolution of 25.5 ms), and for E–H, with a 

256-point Hann window and 89.8% overlap (frequency resolution of 7.81 Hz, time 

resolution of 13 ms). 
28 

Figure 4.2. Black drum and toadfish chorusing.

A) 12-s spectrogram of black drum chorus and B) a 1-hr spectrogram view of the black drum 

chorus, where the sustained, high rate of calls produces a continuous band of energy with the 

fundamental frequency (Fo) at ~80 Hz and harmonics at ~160 Hz and ~240 Hz at GA-Central

on 6 April 2013. C) 12-s spectrogram of toadfish chorus and D) a 1-hr spectrogram view of the 

toadfish chorus, where the sustained, high rate of calls produces a continuous band of energy 

with the Fo at ~250 Hz at GA-North on 11 June 2012. Spectrograms were created in Raven 1.5 

(Bioacoustics Research Program 2014), for A and C, with a 512-point Hann window and 90% 

overlap (frequency resolution of 3.91 Hz, time resolution of 25.5 ms), and for B and D, with a 

2048-point Hann window and 90% overlap (frequency resolution of 0.977 Hz, time resolution of 

103 ms).

4.3 RESULTS

Black drum and oyster toadfish were present over differing time periods at the North Carolina and 

Georgia sites. Black drum are predominantly present from the autumn through spring (November–April 

2013). Oyster toadfish are predominantly present in the early spring and summer (March–April 2013 and 

June–August 2012) (Figure 4.3). Both species were detected on more days in Georgia than in North 

Carolina (Figure 4.3). Black drum were present on 463 days of 614 days analyzed across three MARUs in 

Georgia, but on only 31 of 614 across three MARUs in North Carolina, Toadfish were present on 257 

days of 614 days analyzed across three MARUs in Georgia, but on only 13 in North Carolina. 

There was greater variation in species presence among MARUs in North Carolina than in Georgia where 

black drum and oyster toadfish were present at all MARUs. In North Carolina, oyster toadfish were 

detected at NC-North and NC-Central for only a total of 13 days and were not detected at NC-South 

(Figure 4.3A). Black drum were present on days at NC-Central in November–December 2012 and 

February–April 2013, and present only one day each at NC-North and NC-South (Figure 4.3A). In 
29 

Georgia, black drum were more frequently present on the same day across all MARUs than were toadfish 

(Figure 4.3B). Toadfish were present in fewer days at GA-Central (38 days), overall, than GA-North (128 

days) and GA-South (91 days) (Figure 4.3B). 

Figure 4.3. Black drum and oyster toadfish occurrence and chorusing periods in 

North Carolina and Georgia. 

A) Black drum (black triangles) and toadfish (gray triangles) presence at each MARU 

in North Carolina, 12 June 2012–15 April 2013. B) Black drum and toadfish presence 

at each MARU in Georgia, 9 June 2012–12 April 2013. Shaded boxes correspond to 

chorusing periods. Black vertical lines indicate days not analyzed in each site.

Black drum chorused 21–25 March and 1–12 April 2013 at GA-North, 18–25 March and 1–12 April 2013 

at GA-Central, and 19-–25 March and 31 March–12 April 2013 at GA-South (Figure 4.3). Black drum 

also chorused 9–15 March and 6–9 April 2013 at NC-North; no chorusing was detected at NC-Central 

and NC-South (Figure 4.3). Start and end times of chorusing were variable between days and among 

MARUs, but chorusing occurs between approximately 15:00 and 06:00. Chorusing started as early as 

10:00 on 12 April 2013 in North Carolina. Chorusing occurred most frequently between 18:00 and 5:00, 

and exceeded amplitudes of 100 dB at frequencies corresponding to the fundamental frequency and 

harmonics of the call, at approximately 80 Hz, 160 Hz, and 240 Hz (Figure 4.4). Oyster toadfish chorused 

9 June–12 July 2012 at GA-North, 18–20 March 2013 and 22 March–12 April 2013 at GA-Central, and 

16–24 March 2013 and 26 March–12 April 2013 at GA-South. Oyster toadfish chorusing was not 

detected in North Carolina. Chorusing occurred continuously throughout the day, creating visible energy 

frequency bands that correspond to the fundamental frequency and harmonics of the calls. Although we 
30 

did not systematically measure the fundamental frequency of oyster toadfish calls, based on our 

identification of boat whistle calls, the fundamental frequency varied throughout the year. During the first 

deployment, June–November 2012, the fundamental frequency varied greatly between approximately 180 

and 270 Hz (Figure 4.1). In the second deployment, November 2012–April 2013, the fundamental 

frequency gradually increased from approximately 120 Hz to 125 Hz (Figure 4.1). 

The average annual water temperature between North Carolina (21.7 o

C ± 0.2 [SE], range = 13.4-29.0 oC) 

and Georgia (21.0 o

C ± 0.1, range = 12.8-29.9 oC) were similar, but daily water temperature was more 

variable between sites and days in North Carolina than in Georgia (Figure 4.5). Excluding the low fish 

presence data from NC-Central and NC-South, the occurrence of both species was associated with water 

temperature at the sites. Oyster toadfish occurrence was significantly associated with water temperatures 

below 20 o

C and above 24 oC (logistic regression, df = 1, χ2 = 5.90, p = 0.0152) (Figure 4.6). Black drum 

occurrence was strongly associated with temperatures below 20 oC (df = 1, χ2

 = 976.36, p < 0.0001). 

Figure 4.4. Diel pattern of black drum chorus. 

Black drum chorusing overnight from approximately 15:00-5:00, 31 March–12 April 2013 

at GA-South. Chorusing produces sound levels >120 dB at the fundamental frequency of 

the call (~80 Hz) and sound levels >100 dB at the first and second harmonics (~160 Hz 

and 240 Hz). Major tick marks identify 0:00, the start and end of each day; minor tick 

marks identify 12:00.
31 

Figure 4.5. Mean daily temperature in North Carolina and Georgia. 

Mean daily temperature at each MARU in A) North Carolina, 12 June 2012–15 April 

2013, and B) Georgia, 9 June 2013–12 April 2013.
32 

Figure 4.6. Relationship between acoustic occurrence and water temperature. 

A) Relationship between black drum occurrence and water temperature. B) 

Relationship between toadfish occurrence and water temperature. Acoustic 

presence = 1, lack of acoustic presence = 0.

4.4. CONCLUSIONS

4.4.1. Geographic Variation in Fish Calling

Our passive acoustic surveys in offshore North Carolina and Georgia reveal vocally active black drum 

and toadfish at both locations over the course of the year. Both black drum and toadfish occurred with 

greater regularity in the Georgia location than in North Carolina; this may be related to the habitat 

differences between locations. The Georgia locations were closer to shore (mean distance to shore ± SE: 

GA=18.7 ± 1.3 km, NC=51.2±11.7 km), and shallower in depth (14 m in Georgia compared with an 

average of 34.3 m in North Carolina. Because much of the calling behavior of both species is associated 

with reproductive advertisement displays (Burkenroad 1931; Fine et al. 1977; Gray and Winn 1961; 

Locascio and Mann 2011b; Locascio et al. 2012; Mok and Gilmore 1983), and both species spawn in 

shallower coastal waters (Gray and Winn 1961; Gudger 1910; Mok and Gilmore 1983), it is possible that 

the Georgia locations provide more suitable habitats for reproductive or social behaviors. Given the 

comparatively low degree of acoustic presence of both black drum and toadfish at the North Carolina 

sites, it is difficult to explore ecological patterns from these data.

Among the three MARUs at the Georgia site, there were differences in the temporal pattern of toadfish 

acoustic presence. There was a longer duration of toadfish calling at GA-North compared to the GACentral and GA-South sites. Because water temperature was similar among the three locations, other 

water quality characteristics (e.g., salinity, dissolved oxygen) or physical habitat differences may account 
33 

for the difference in behavior of toadfish at these three locations. Because toadfish males establish nests 

and guard eggs (Gray and Winn 1961; Gudger 1910), it is likely that the GA-North site had a greater 

number of available nesting habitats compared to the GA-Central and GA-South locations, and may 

account for the prolonged calling activity at GA-North. 

Black drum, in contrast to toadfish, do not seem to indicate the same degree of preference or limitation of 

habitat. As such, the black drum calling data shows a similar temporal pattern across the MARUs in 

Georgia, and a sudden seasonal start of acoustic occurrence that is seen at all three MARUs. This nearly 

simultaneous onset of chorusing activity over a 25 km distance suggests an environmental cue triggering 

the initiation of reproductive behavior (e.g., Mann and Grothues 2009). 

Available nesting habitats in this area may be patchy in distribution across the broader geographical area. 

The bottom structure of the Georgia Bight, the region containing the Georgia study site, is a mixture of 

hard bottom and sand, with intermittent live bottom cover (see Chapter 6, Kendall et al. 2005; Kendall et 

al. 2007). In the context of the present study, the heterogeneous bottom cover, and resulting patchy 

distribution of focal species, warrants caution for identifying and characterizing appropriate control sites 

to compare with the wind planning area (Landres et al. 1988; Noss 1990). If there is a heterogeneous 

distribution of available habitat for toadfishes, differences in calling between locations (particularly after 

the onset of wind farm construction) may reflect physical habitat differences between sites, rather than 

population-level changes in behavior.

Much of Onslow Bay contains a combination of gravel and sand bottom cover with less than 10% of the 

bottom structure comprised of hard- and live-bottom habitats, and less than 6% serving as essential fish 

habitat (Chapter 7, also Department of the Navy 2009). Despite the lower proportion of fish habitat, there 

were numerous sounds being produced by fishes from many unidentified species (see Appendix), which 

suggests that this habitat is outside of the typical range of the two focal species, and not necessarily the 

result of a decrease in biodiversity. Onslow Bay is just south of the dividing lines between the northern 

and southern biogeographic provinces in the Western North Atlantic (Mahon et al. 1998), and this area 

may represent a transitional species composition between the subtropical species assemblages seen to the 

south, and the mid-Atlantic temperate fish assemblages which inhabit northern waters.

4.4.2. Temporal Patterns in Fish Calling

The acoustic survey showed the two focal species calling throughout the survey period. Both focal species 

were acoustically present in a higher proportion of the study period in Georgia than in North Carolina. At 

the Georgia site, toadfish called nearly every day throughout the summer, and then tapered off (except at 

GA-North), and then black drum started calling at all MARUs around November. Sustained chorusing for 

both focal species started in mid-March, with initiation of the choruses starting within a short period of 

time of each other. During these sustained choruses toadfish show little to no diel pattern, whereas black 

drum primarily chorused at night (also see Locascio and Mann 2011b). Given that signals overlap in their 

frequency range (F0 of toadfish and 2F0 of black drum), there may be acoustic competition during these 

chorusing periods, as there are many identified instances during these time periods with overlap of black 

drum and toadfish calls. 

Because the calling behavior of both species shows no decline towards the end of the project, and 

continues until the end of the recording period, it is likely that the chorusing period continues through 

April into May. Because there was only less than a single year of acoustic data collected from these 

locations, year-to-year variability in chorusing duration in offshore populations of these species has not 

been examined, and it would be interesting to evaluate the synchrony of elevated acoustic activity and the 

consistency across years. Accounting for temporal variability in calling behavior would be another critical 

component to assess from a monitoring perspective (Bridges and Dorcas 2000). 
34 

Studying the calling behavior of these species across years would be interesting to evaluate how 

consistent occurrence and seasonality is at these locations. Because both species migrate (Gudger 1910; 

Isaacson 1964; Murphy et al. 1998; Schwartz 1974; Silverman 1979), it would be useful to understand 

whether black drum or toadfish display site fidelity and return to the same locations across multiple years 

for spawning. If the same individuals, or members of the same population, are returning to these locations 

across years, then it further supports the approach that these species could be used as ecological 

indicators, and differences in acoustic activity between years could reflect some degree of ecological 

change within the habitat. However, if the presence of fish and their acoustic activity is variable across 

years, differences in calling of these species across years would not necessarily be indicative of change 

within the ecosystem.

One of the limitations in the approach used for data analysis here was that the patterns of calling for both 

species was only evaluated at a daily-occurrence level of resolution. Daily presence/absence is often used 

as a metric in the course of ecological monitoring (e.g., Morano et al. 2012), when it is not necessarily 

feasible, cost-effective, or required to analyze all calls per unit time. Thus, these daily occurrence data 

combined with a high-level perspective on chorusing behavior can only provide a rough idea of the 

behavior of these populations. Determining the number of calls produced by each species at a smaller 

time interval would provide a greater degree of detail of the acoustic behavior of each species, and 

possibly provide insight into changes in calling rates (Fine et al. 1977; Fine 1978; Grava et al. 2012), as 

well as the relative (or modeled) abundance of each population present at each site (Fine et al. 1977; 

Marques et al. 2013; Royle and Nichols 2003; Royle 2004). With the large amount of data collected, 

analysis of all calls produced by each species is not realistic, but sub-sampling approaches of calling rate 

over the course of the project period could capture potential changes in behavior. Automated detection 

algorithms have been developed to identify calls in the passive acoustic study of marine mammals, (e.g., 

Mellinger and Clark 1997), but, the overlap of black drum calls or the lack of temporal separation 

between black drum or toadfish calls in a chorus would make the automated recognition of these calls 

extremely difficult and would favor an alternative methodology. 

4.4.3. Use of Fish Calls as Ecological Indicators

In addition to conducting a seasonal survey to understand calling and chorusing patterns for these two 

focal fish species, one of the motivations for this approach was to further develop the approach of using 

these two fish species as complementary ecological indicators to evaluate possible habitat disturbance 

during wind farm construction. 

In order for a particular species to serve as an effective indicator, a number of criteria must be met (Cairns 

et al. 1993; Goodsell et al. 2009). In particular, a measurable change in behavior or ecology should be 

exhibited in response to a specific stressor (either a correlative, or preferably, a causal relationship - 

Goodsell et al. 2009), but be biologically and socially relevant, broadly applicable, anticipatory, costeffective and non-invasive to measure (Cairns et al. 1993). Passive acoustic monitoring of fish calls 

satisfies many of these criteria. With further understanding in how patterns of fish calling are influenced 

by habitat changes, passive acoustic monitoring of fish calls offers the potential for evaluating ecological 

changes (Van Parijs et al. 2009). 

In the case of wind farm construction, likely stressors would include increases in noise level and physical 

habitat disturbance associated with pile-driving, trenching, or operation of service boats during the 

construction phase (Kikuchi 2010; Madsen et al. 2006; Wahlberg and Westerberg 2005). From a noise 

perspective, impacts to fishes would likely be chronic and sub-lethal, and include increased stress levels

associated with increased noise levels or acoustic masking. Many of these effects have been suggested in 

fishes (Popper 2003; Slabbekoorn et al. 2010; Slabbekoorn 2012), but have been demonstrated in a wide 
35 

range of vertebrate taxa (Arroyo-Solis et al. 2013; Grava et al. 2012; Hansen et al. 2005; Price et al. 2005; 

van Buggenum and Vergoossen 2012). Recent work has also demonstrated a decrease in fish foraging 

success related to increase in noise levels (Voellmy et al. 2014). Primary or secondary effects from these 

stressors may either inhibit acoustic/reproductive activity or drive the animals from the site (Rako et al. 

2013). Physical habitat modification may also displace animals. Both physical habitat perturbation and 

increases in anthropogenic noise could potentially result in a cessation in advertisement calling, and this 

change in behavior would be measurable during the course of passive acoustic surveys. However, a 

critical step in evaluating the reliability of black drum or toadfish calling as potential indicator species 

would be to demonstrate a causal relationship between increased noise levels and decreased calling 

activity. Many empirical studies in different vertebrate groups have suggested that changes in vocal 

behavior is a measurable ecological indicator of disturbance (Arroyo-Solis et al. 2013; Grava et al. 2012; 

Hansen et al. 2005; Price et al. 2005; van Buggenum and Vergoossen 2012), and this is likely the case in 

fishes. However, future studies would be useful to either demonstrate the use or limitations of using fish 

sounds as ecological indicators. 

Given both species’ regularity of calling, both toadfish and black drum would be significantly more 

effective ecological indicators in the Georgia wind planning area, compared to the North Carolina 

planning area. However, given the wide diversity and abundance of unidentified fish calls (see 

Appendix), it is likely that different acoustically active fish species could be developed to serve as 

ecological indicators in Onslow Bay.

4.4.4. Recommendations for Future Study

This initial baseline survey of fish calling activity at these two locations shows interesting results, and a 

great deal of promise. To better understand the context and ecological drivers of fish acoustic activity, a 

number of recommendations have emerged from this study that should be applied to future efforts. 

There was a wide range of spatial and temporal variability in the amount and seasonality of calling 

behavior of black drum and toadfish. Designing a survey that includes spatial replication would help 

demonstrate the degree of micro-scale variability occurring of the focal species behavior and occurrence 

(e.g., Dawson and Efford 2009; Underwood 1994). Because demersal and benthic species have a 

heterogeneous distribution in different recording areas, single recording locations will not provide 

sufficient spatial representation to characterize focal species occurrence. The behavior of the fishes 

analyzed here show a strong seasonal signal in their acoustic behavior, which warrants a complete yearround survey (only 11 months of data were collected here), and preferably a multi-year baseline survey to 

capture intra- and inter-annual variability in focal species’ behavior. The acoustic detection range of these 

two species has not been established in these locations, so it is unclear the spatial distance that is being 

sampled with the recorders.

Because these two species showed a degree of seasonal separation in their calling activity over the course 

of the study period, it is possible that toadfish calling patterns could be used as an ecological indicator 

through the summer, and black drum calling could serve as an ecological indicator through the winter and 

spring. The abundance of calls and the appearance of a seasonal pattern suggest that the passive acoustic 

monitoring of fish vocalizations could be useful to evaluate population-level or habitat changes. The 

differences calling behavior of fishes across the years and among locations further reveal the value (and 

difficulty) of appropriate baseline studies. 

Study requirements and selection of focal species should be selected after the project sites are decided 

upon. As mentioned earlier, these fish species were selected before wind planning area selection, and 

were chosen on the basis of their readily identifiable, species-specific sounds, their extensive previous 

study, and wide distribution along the U.S. Atlantic coast. Though black drum and toadfish were recorded 
36 

at nearly all of the locations, they were more commonly recorded at the Georgia sites, and only 

sporadically detected in North Carolina. An evaluation of site-specific acoustic data could reveal which 

fish species are most suitable to serve as focal species at particular locations. 

Though neither black drum nor toadfish were particularly vocally active at the North Carolina sites, there 

were many unidentified biological sounds likely produced by other fish species in the area. This 

abundance of unidentified fish sounds highlights the major acoustic role that fish species have within their 

ecosystems, and demonstrates the value in future efforts to conduct baseline research identifying the 

sources of these sounds. When the sources are identified, these signals may be used in future long-term 

monitoring efforts. 
37 

5. AMBIENT NOISE

5.1 INTRODUCTION

Sound is a critical component of the marine environment, and many, if not most, marine animals use 

sound in different aspects of their life history. Measurements of ocean ambient noise have long been used 

to characterize different geographic areas from an oceanographic or physical perspective (for example, 

see reviews by Urick 1986; Wenz 1962; Wenz 1972); these measurements are now being calculated in 

different ecosystems to evaluate how marine animals may be influenced by sound from environmental 

and anthropogenic processes (Clark et al. 2011; e.g., Samuel et al. 2005; Simard et al. 2010). Analysis of 

the ambient noise environment over large spatial and temporal scales provides a broad, quantitative 

perspective on ecosystem function. 

The term “ocean ambient noise” includes the combination of biological, environmental, and 

anthropogenic sounds occurring within a particular region (Hildebrand 2009; Urick 1986; Wenz 1962). In 

the marine environment, major contributors to the overall acoustic ambient noise environment include the 

combination of surface wave action (generated by wind), marine organisms, and anthropogenic sound 

sources such as ships, geophysical seismic surveys, and construction (Hildebrand 2009). These different 

sound sources are detectable over different orders of magnitude in both temporal and spatial scales. In the 

case of sounds from commercial shipping vessels, this acoustic signature is detectable in the low 

frequency bandwidth thousands of kilometers from the actual ship (Hildebrand 2009). Anthropogenic 

noise between the 20–150 Hz frequency range is usually due to shipping and mining operations (Jobst 

and Adams 1977), and environmental noise above 150 Hz in the deep ocean is surface-generated (Jobst 

and Adams 1977; Urick 1986; i.e., wind and waves, Wenz 1972). Ambient noise analysis characterizes 

the acoustic environment and is a mechanism to evaluate acoustic activity and other stimuli of both focal 

and non-focal species.

One of the fundamental characteristics of the ambient noise environment is its variability (Wenz 1962); 

thus, long term studies are needed to statistically characterize the ambient noise variability (Wenz 1972). 

In these long-term data collection efforts, analysis of ambient noise allows the chance to broadly evaluate 

the periodicity of physical environmental processes, vocally active biological constituents of an acoustic 

environment, and the contribution of anthropogenic sounds to the ambient noise environment. The 

combined analysis of biological acoustic activity in relation to different anthropogenic or environmental 

sound levels offers the chance to examine how increases in noise levels may impact behavior of vocal and 

non-vocal species. Specific to the waters off the coast of Georgia and North Carolina, we provide 

opportunities to assess the possible future impacts of pile driving and other associated construction and 

wind farm operation noise by characterizing the baseline ambient noise environment, and highlight 

potential species that are susceptible to increased risk or impact from anthropogenic noise.

5.2 METHODS

Acoustic data from each MARU (see Chapter 2) were processed using the Noise Analysis tools within the 

SEDNA toolbox for MATLAB© (Dugan et al. 2011), using a Hann window, FFT size of 2000 samples, 

time resolution at 1 s, and frequency resolution at 1 Hz. To evaluate the ambient noise conditions, two

different representations of sound were used: frequency compared to time (spectrogram) and power 

compared to frequency (power spectra). 

Spectrograms of acoustic data were created using 1-hr integration time slices for each MARU, and a FFT 

of 2000 samples. Two different frequency scales were used to represent the data, a linear scale with 
38 

frequencies between 0–1 kHz, and a scale based on 1/3rd octave frequency bands between 10–630 Hz (see 

below). We visually and acoustically analyzed noise events present in the spectrogram and were able to 

categorize them according to the type of source such as weather events, anthropogenic sources or 

biological sources (Figure 5.1). 

Traditional signal processing methods divide the acoustic signal into smaller frequency bands (based on 

octaves), to reduce the amount of data being analyzed for greater ease in processing and interpretation 

(Peterson and Gross 1978). These bands effectively filter the data into smaller subsets. For sound analysis 

in a biological context, 1/3 octave bands are commonly used for two principal reasons: use of these bands 

cover a 10-to-1 frequency range (Peterson and Gross 1978) and the function of the mammalian ear can be 

approximated as a set of bandpass filters with a sensitivity of approximately 1/3 of an octave (Madsen et 

al. 2006; Richardson et al. 1995). With these 1/3 octave bands, the bandwidth is approximately 23% of 

the center frequency (Peterson and Gross 1978). This spectrographic representation also provides a good 

illustration of energy in lower frequency ranges, which are difficult to see with a full-bandwidth linear 

scale spectrogram.

The power spectral density represents the amount of power in the signal as a function of frequency. We 

calculated power spectral densities and represented them as statistical percentiles of total data (Roth et al. 

2012; similar to Samuel et al. 2005). Data were represented using the lower 5th, 25th, 50th (= median), 75th, 

and upper 95th percentiles. In order to understand the variation in sound levels and frequency distribution 

and how they differ depending on type of noise, we calculated and compared power spectral densities for 

time periods where the dominant source of noise was from biological, anthropogenic and weather related 

activities.
39 

Figure 5.1. Example long term spectrogram. 

Spectrogram of acoustic data from GA-South (09 June 2012–12 April 2013) represented as A) linear frequency axis from 10-1000 Hz 

and B) 1/3 octave band frequencies between 10–650 Hz. The color bar to the right of both panels indicates the power scale, in dB (re: 

1 μPa). Example noise events are boxed and labeled. 
40 

5.3 RESULTS

5.3.1 General Trends

Looking at long-term plots of spectrogram noise, we found seasonal and geographical trends in ambient 

noise patterns. Overall, summer and fall months (June–November) had higher levels of noise in 

comparison to winter and spring months (December–April). Geographically, the three sites in Georgia 

qualitatively showed higher levels of noise than the three sites in North Carolina. Within each geographic 

location, there was not a significant, qualitative variation in noise between individual sites. See Figures 

5.2–5.13 for spectrogram noise plots for the entire MARU recording period from each site. In the 

subsequent chapters, we take a look at specific patterns and noise events and categorize the different types 

of noise found in both arrays throughout the year.
41 

Figure 5.2. Spectrogram of acoustic data from GA-North (9 June–9 November 2012). 

Spectrogram of acoustic data from GA-North (9 June–9 November 2012) represented as A) linear frequency axis from 10–1000 

Hz and B) 1/3 octave band frequencies between 10–650 Hz. The color bar to the right of both panels indicates the power scale, in 

dB (re: 1 μPa). 
42 

Figure 5.3. Spectrogram of acoustic data from GA-North (10 November 2012–12 April 2013). 

Spectrogram of acoustic data from GA-North (10 November 2012–12 April 2013) represented as A) linear frequency axis from 10–

1000 Hz and B) 1/3 octave band frequencies between 10-650 Hz. The color bar to the right of both panels indicates the power 

scale, in dB (re: 1 μPa). 
43 

Figure 5.4. Spectrogram of acoustic data from GA-Central (9 June–9 November 2012). 

Spectrogram of acoustic data from GA-Central (9 June–9 November 2012) represented as A) linear frequency axis from 0 Hz-1 kHz 

and B) 1/3 octave band frequencies between 10–650 Hz. The color bar to the right of both panels indicates the power scale, in dB 

(re: 1 μPa). 
44 

Figure 5.5. Spectrogram of acoustic data from GA-Central (10 November 2012–12 April 2013). 

Spectrogram of acoustic data from GA-Central (10 November 2012–12 April 2013) represented as A) linear frequency axis from 

10-1000 Hz and B) 1/3 octave band frequencies between 10–650 Hz. The color bar to the right of both panels indicates the power 

scale, in dB (re: 1 μPa). 
45 

Figure 5.6. Spectrogram of acoustic data from GA-South (9 June–9 November 2012). 

Spectrogram of acoustic data from GA-South (9 June–9 November 2012) represented as A) linear frequency axis from 10–1000 Hz and B) 1/3 

octave band frequencies between 10–650 Hz. The color bar to the right of both panels indicates the power scale, in dB (re: 1 μPa). 
46 

Figure 5.7. Spectrogram of acoustic data from GA-South (10 November 2012–12 April 2013). 

Spectrogram of acoustic data from GA-South (10 November 2012–12 April 2013) represented as A) linear frequency axis from 10–1000 Hz and B) 

1/3 octave band frequencies between 10–650 Hz. The color bar to the right of both panels indicates the power scale, in dB (re: 1 μPa). 
47 

Figure 5.8. Spectrogram of acoustic data from NC-North (12 June–11 November 2012). 

Spectrogram of acoustic data from NC-North (12 June–11 November 2012) represented as A) linear frequency axis from 10_1000 

Hz and B) 1/3 octave band frequencies between 10–650 Hz. The color bar to the right of both panels indicates the power scale, in 

dB (re: 1 μPa). 
48 

Figure 5.9. Spectrogram of acoustic data from NC-North (12 November 2012–16 April 2013). 

Spectrogram of acoustic data from NC-North (12 November 2012–16 April 2013) represented as A) linear frequency axis from 10–000 

Hz and B) 1/3 octave band frequencies between 10–650 Hz. The color bar to the right of both panels indicates the power scale, in dB 

(re: 1 μPa). 
49 

Figure 5.10. Spectrogram of acoustic data from NC-Central (12 June–11 November 2012). 

Spectrogram of acoustic data from NC-Central (12 June–11 November 2012) represented as A) linear frequency axis from 10–

1000 Hz and B) 1/3 octave band frequencies between 10–650 Hz. The color bar to the right of both panels indicates the power 

scale, in dB (re: 1 μPa). 
50 

Figure 5.11. Spectrogram of acoustic data from NC-Central (12 November 2012 –16 April 2013). 

Spectrogram of acoustic data from NC-Central (12 November 2012–16 April 2013) represented as A) linear frequency axis from 

10–1000 Hz and B) 1/3 octave band frequencies between 10–650 Hz. The color bar to the right of both panels indicates the power 

scale, in dB (re: 1 μPa). 
51 

Figure 5.12. Spectrogram of acoustic data from NC-South (12 June–11 November 2012). 

Spectrogram of acoustic data from NC-South (12 June–11 November 2012) represented as A) linear frequency axis from 10–1000 

Hz and B) 1/3 octave band frequencies between 10–650 Hz. The color bar to the right of both panels indicates the power scale, in 

dB (re: 1 μPa). 
52 

Figure 5.13. Spectrogram of acoustic data from NC-South (12 November 2012–16 April 2013). 

Spectrogram of acoustic data from NC-South (12 November 2012–16 April 2013) represented as A) linear frequency axis from 10–1000 Hz and B) 

1/3 octave band frequencies between 10–650 Hz. The color bar to the right of both panels indicates the power scale, in dB (re: 1 μPa).
53 

5.3.2 Noise Patterns

Noise events in the North Carolina and Georgia environments, as seen in the long-term spectrograms, can 

be grouped into several categories: biological, weather, anthropogenic, and unknown sounds. 

5.3.2.1 Biological Sources

The sporadic vocal activity of marine mammals such as the right whale and humpback whale was not 

visible on the multi-month long spectrograms, but black drum and toadfish chorusing were visible from 

mid-March–April at all three Georgia sites (Figures 5.3, 5.5, 5.7). Black drum chorusing is a high rate of 

calls that continue for over an hour (see Chapter 4) and is visible as a band of energy around 70 Hz (the 

fundamental frequency), often with up to two harmonics at 140 Hz and 210 Hz (Figures 5.14, 5.15) . 

Many of these choruses were recorded in excess of 100 dB. Toadfish chorusing, in contrast, can be seen 

in the spectrograms as two solid horizontal, parallel lines, with a fundamental around 100 Hz, with one 

harmonic associated with it (Figures 5.3, 5.15). In toadfish, the fundamental frequency of the call is 

related to water temperature (Fine 1978), so a slight increase (up to 50 Hz) can be seen as the water 

increases in temperature from winter to spring. Compared to black drum, toadfish chorusing had a lower 

sound level, with an average power less than 90 dB. 

5.3.2.2 Weather

Severe weather was found to be a significant contributor to ocean noise in both Georgia and North 

Carolina. Due to the relatively shallow depth of the MARUs, any significant increase in wave action 

introduced anchor-related self-noise into the MARU recordings, which was recorded by the hydrophone. 

In some cases, this self-noise was site specific, such as with the GA-Central during June 2012 (Figure 

5.4). Noise was concentrated below 100 Hz, up to 120 dB at times (Figure 5.16). However, during 

extreme weather, such as Hurricane Sandy, which developed in the fall of 2012 (late October–early 

November), significant broadband noise was recorded on all MARUs at all sites in Georgia and North 

Carolina (Figures 5.2, 5.4, 5.6, 5.8, 5.10, 5.12, 5.17). The higher frequency noise associated with the 

wave-driven motion of the MARU is most likely attributed to the waves themselves.

5.3.2.3 Anthropogenic Sources

Another source of ocean ambient noise is from human related activities such as military, construction, 

shipping and other commercial and recreational activities. Boat vessel noise was recorded throughout the 

year at both sites and appears in the long term spectrograms as low frequency noise, often between 80 and 

120 dB (Figure 5.18). Vessel noise usually appears to increase and then decrease in power as the ship gets 

closer and farther away from the MARU. 

5.3.2.4 Internal Electronic Noise

In a few rare instances, internal electrical interference or temporary problems with the MARU’s recording 

hydrophone caused the unit to malfunction and introduce static or self-generated noise to the recordings. 

This occurred briefly in the GA-Central during late August and early October 2012 (Figure 5.18). In the 

long term spectrograms, this is characterized as a loud (~100 dB) broadband noise event ranging from 

10–1000 Hz (Figure 5.19). Every effort is put forth to eliminate this source of noise, but it is necessary to 

be aware of how internal self-generated noise manifests itself in the recordings so that it can be properly 

accounted for during any analysis.
54 

5.3.2.5 Unknown Sounds

The source of some recorded sounds cannot be definitively identified, but suggest either anthropogenic or 

biological sources, depending on the characteristics of the sound. Some unknown sounds apparent in the 

long duration spectrograms have characteristics that are consistent with the types of signals that fish 

produce; the sounds are short in duration and are repeated in irregular patterns. One sound that is 

potentially from an unidentified fish species is visible as two bands of energy, each with a bandwidth of 

approximately 100 Hz, and centered at 200 Hz and 400 Hz, as a daily pattern on December 2012–April 

2013 spectrogram in North Carolina (Figure 5.13). A closer examination on 15 February–17 March 2013, 

showed that this signal occurred overnight between approximately 1700–0600 hrs (Figure 5.20). These 

signals are short duration (~0.2 s) upsweep-like signals that occurred in bouts lasting approximately 5 s or 

more (see Appendix, Figure A-4). Overlapping signals and bouts suggest that there were multiple sources

for these signals. 

Sound recorded in both Georgia and North Carolina from June through October 2012 illustrated two

unknown sounds (Figure 5.21). The first sound consisted of broadband noise from 200 to 1000 Hz, with 

the noise tapering off in the lower frequencies and averaging six hours in duration. The noise began in the 

evening and ceased in the morning, and this pattern continued for weeks at a time. Signal characteristics 

suggest that this is anthropogenic. The second sound is a band of energy that occurred within a few hours 

after this first unknown sound, but the signal consists of peaks of energy every 100 Hz beginning at 

approximately 250 Hz (Figure 5.21). These signals were stacks of downsweeps, approximately 0.6 s in 

duration, and repeated in an irregular pattern (see Appendix, Figure A-3). These signals also overlapped, 

indicating there were multiple sources. Signal characteristics suggest that this signal may be biological.

5.3.3 Potential for Noise Masking

To investigate whether anthropogenic noise sources can mask fish chorusing events, power spectral 

density measurements were calculated to compare the relative loudness of different types of ocean noise. 

Using data from GA-North, we selected a period of time where the prominent source of noise was from 

anthropogenic shipping (13 December 2012–01 January 2013) and then compared that to a period of time 

(21 March–13 April 2013) when the prominent source of noise was from biological fish chorusing. The 

power spectral density showed that for most of the frequency range between 20–1000 Hz, the noise levels 

from shipping were higher than the noise levels from the black drum and toadfish chorusing activity (50th 

percentile, 80 dB vs ~72 dB). That is, if the shipping noise were to occur at the same time as the fish 

chorusing, the fish signals would be masked at those frequencies (Figure 5.22). This masking can be seen 

at a much smaller time frame (1–2 hr in duration) than the long term spectrograms. On 14 March 2013 at 

NC-Central, black drum choruses are masked by vessel noise from 15:50–16:20 (Figure 5.23). 

Marine mammal vocalizations were recorded throughout the study, but they were not frequent enough to 

be visible on long term spectrogram plots. However, the power spectral density plot for two weeks of 

time where anthropogenic shipping and vessel noise was the dominant source of ocean noise, the 50th

percentile in the right whale communications frequency (~70-300 Hz) was about 80 dB. Depending on 

the proximity of the whale to the ship, the potential for masking is still present.
55 

Figure 5.14. Biological example of black drum chorusing.

Spectrogram of acoustic data from GA-Central (17 March–13 April 2013) represented as A) linear frequency axis from 10–1000 Hz 

and B) 1/3 octave band frequencies between 10–650 Hz. The color bar to the right of both panels indicates the power scale, in dB 

(re: 1 μPa). Black drum chorusing can be seen as pulsed events with stacked harmonics of 10–13 hr in duration, many of which are

>110 dB in power.
56 

Figure 5.15. Biological example of black drum and toadfish chorusing.

Spectrogram of acoustic data from GA-North (01 April–13 April 2013) represented as A) linear frequency axis from 10–1000 Hz and 

B) 1/3 octave band frequencies between 10–650 Hz. The color bar to the right of both panels indicates the power scale, in dB (re: 1 

μPa). Black drum chorusing can be seen as pulsed events with stacked harmonics of 10–13 hr in duration. Toadfish chorusing can 

be seen as two narrow frequency bands at ~100 and 200 Hz, increasing in frequency over time.
57 

Figure 5.16. Example of weather-related noise.

Spectrogram of acoustic data from GA-Central (9 June–30 June 2012) represented as A) linear frequency axis from 10–1000 Hz 

and B) 1/3 octave band frequencies between 10–650 Hz. The color bar to the right of both panels indicates the power scale, in dB 

(re: 1 μPa). MARU banging and jostling due to weather can be seen as the noise below 100 Hz. The broadband pulses are 

examples of the unidentified noise described in Figure 5.21. 
58 

Figure 5.17. Example of extreme weather noise from Hurricane Sandy. 

Spectrogram of acoustic data from GA-South (20 October–6 November 2012) represented as A) linear frequency axis from 10–1000 Hz and B) 

1/3 octave band frequencies between 10–650 Hz. The color bar to the right of both panels indicates the power scale, in dB (re: 1 μPa). Weather 

related to Hurricane Sandy is present as broadband noise, especially from 25 October –28 October 2012.
59 

Figure 5.18. Anthropogenic example of shipping noise. 

Spectrogram of acoustic data from NC-North (12 November–24 November 2012) represented as A) linear frequency axis from 

10–1000 Hz and B) 1/3 octave band frequencies between 10–650 Hz. The color bar to the right of both panels indicates the 

power scale, in dB (re: 1 μPa). Noise due to human shipping, commercial fishing, or other boat traffic is seen as low frequency 

noise events concentrated around 160 Hz.
60 

Figure 5.19. Internal hydrophone noise.

Spectrogram of acoustic data from GA-Central (23 August–31 August 2012) represented as A) linear frequency axis from 10–1000 

Hz and B) 1/3 octave band frequencies between 10–650 Hz. The color bar to the right of both panels indicates the power scale, in

dB (re: 1 μPa). Internal self-generated noise can be seen as broadband noise blocks (10–1000 Hz) of about 105 dB, occurring 

before and after 27 August 2012. The bands of noise occurring before and after the internal-generated noise are an example of two

unknown sources of noise described in Figure 5.21.
61 

Figure 5.20. Unknown sound source, potentially biological.

Spectrogram of acoustic data from NC-South (15 February–17 March 2013) represented as A) linear frequency axis from 10–1000 

Hz and B) 1/3 octave band frequencies between 10–650 Hz. The color bar to the right of both panels indicates the power scale, in 

dB (re: 1 μPa). An unidentified sound source, potentially biological (see Appendix, Figure A-6), can be seen as signals with a 

bandwidth of approximately 100 Hz at approximately 200 Hz and 400 Hz. With closer examination of these signals, these are short 

duration (~0.2 s) upsweep-like signals that occur in bouts lasting approximately 5 s or more. Overlapping signals and bouts 

suggests that there are multiple sources.
62 

Figure 5.21. Unknown sound sources, potentially anthropogenic and biological. 

Spectrogram of acoustic data from GA-North (25 July–6 August 2012) represented as A) linear frequency axis from 10–1000 Hz and 

B) 1/3 octave band frequencies between 10–650 Hz. The color bar to the right of both panels indicates the power scale, in dB (re: 1 

μPa). Broadband noise, with peak energy at approximately 300–500 Hz, occurs in the evening of each day and continues until 

morning of the next day. This unknown sound may be anthropogenic. A second band of energy occurs after this unknown sound, 

but the signal consists of peaks of energy every 100 Hz beginning at approximately 250 Hz. This signal may be biological. 
63 

Figure 5.22. Power spectral density of anthropogenic and biological sounds. 

Power Spectral Density where the sound power level (dB) is plotted versus the frequency (Hz). A) The percent of noise with 95th

(loudest) and 05th (quietest) percentiles for GA-North (13 December 2012–01 January 2013) where anthropogenic shipping noise was 

the dominant source of noise. B) The percent of noise with 95th (loudest) and 05th (quietest) percentiles for GA-North (21 March–13 

April 2013) where biological fish chorusing was the dominant source of noise. C) Overlays of the 50th percentile noise from plots A and 

B. At any given frequency, the line that is at a higher power level will mask any sound at the lower level.
65 

Figure 5.23. Acoustic masking of black drum chorusing. 

Spectrogram from NC-Central on 14 March 2013 from 15:15–17:00. Frequency range is from 10–1000 

Hz. Black drum chorusing can be seen at 15:15 and becomes masked by the incoming vessel around 

15:50. By 16:40, black drum signals are clearly visible again as the ship noise dissipates. 

5.4 CONCLUSIONS

Long term ambient noise spectrograms visualize the noise characteristics of the Georgia and North 

Carolina ecosystems, which can be extremely variable depending on weather, marine animals, human 

shipping, fishing, and construction activities. Within both the Georgia and North Carolina recording 

areas, each site had different noise characteristics. Though some noise events such as extreme weather 

(Hurricane Sandy) were registered on all MARUs, the signals differed in strength depending on specific 

sites. The same could be observed for anthropogenic and biological sounds. Some sites showed higher 

levels of shipping noise than others, and other sites showed black drum and toadfish chorusing at higher 

power intensities. These differences underscore how the ocean acoustic environment at any given location 

is highly variable and dependent on not only the physical noise characteristics (ocean temperature, 

salinity, bathymetry), but the source levels of the target sounds (fish, whales, ships, construction) and 

their proximity to the recording area. However, despite this variability, the baseline data gathered here 

give many opportunities to measure effects of future increases in noise associated with wind farm 

construction, pile driving, and operation. Being able to distinguish different sources of ocean noise is 

critical in comparing changes over time and correlating increases or decreases in certain types of noise in 

relation to each other. 

Combining visual analysis of ocean acoustic noise from long term spectrograms and quantitative analysis 

using power spectral density plots, we have an opportunity to determine how much noise is introduced 

into the environment from shipping, biological fish choruses, and weather events, and whether certain 

types of noise have the potential to acoustically mask one another. With black drum and fish chorusing 

events, the baseline data showed examples of how shipping noise has the potential to mask the fish 
66 

signals, but further monitoring can be done to quantify this impact on the fish and track changes at each 

site. The same concept applies to monitoring impacts from chronic and acute ocean noise on marine 

mammals. Though marine mammal vocalizations were not visible on the long term spectrogram plots, 

noise levels during periods of time where peak marine mammal vocal activity was detected could be 

compared to noise periods where high levels of human construction, pile driving or shipping noise 

occurred. Measuring increases and decreases in levels of construction and ship vessel noise and 

correlating these with levels of biological noise can provide data on ecosystem health in response to 

anthropogenic activities. 

Overall, collecting baseline long term spectrograms of ocean noise is critical to understanding how much 

and what kinds of noise are already present in the ecosystem so that the effects of increased vessel traffic, 

construction, and wind farm operation can be objectively assessed for impacts to marine organisms living 

in these areas. 
67 

6. NOISE MODELING

6.1 INTRODUCTION

The goal of this project is to predict the levels of sound that would be produced during the installation of 

an offshore wind farm at one or two specific locations. A table of potential construction activities and the 

acoustic characteristics associated with those activities was created. After the characteristics of these 

activities were defined, then the acoustic propagation from those sound sources was predicted using 

acoustic propagation models. The model output was used to predict the spatial extent affected by wind 

farm construction noise at the two sites. 

Water depth is one the dominant factors affecting acoustic propagation. The actual depth variation at the 

Georgia modeling site was quite small and therefore a single location was selected for acoustic 

propagation modeling. The range in actual depth was greater at the North Carolina location. There two 

acoustic modeling sites were selected, representing the shallowest and deepest locations. The model 

outputs from these two North Carolina sites will therefore account for any effect of variation in water 

depth. 

6.1.1 Technical Background

6.1.1.1 Amplitude Measurements

Typically, underwater sound is reported in units of decibels (dB). The decibel is defined as a ratio of 

measured acoustic intensity (I) and a reference intensity level (Iref).

dB = 10 log10 � I

Irrr�

More than one reference intensity level can be used to create a decibel value. Care must be taken when 

reporting and reading sound levels in decibels to ensure that measurements are properly described. Sound 

levels are often measured as pressure levels (P) rather than directly as intensity. These two measures can 

be related with the following equation:

I = P2

ρρ

Where ρ is the density of the medium (e.g. water) and c is the speed of sound in that medium. The 

equations can be combined to produce the following: 

dB = 10 log10 � P2

P2

rrr�

or 

dB = 20 log10 � P

Prrr�

In underwater acoustics, the traditional reference pressure is 1 microPascal (μPa), leading to the common 

use of the unit of ‘dB re 1 μPa’, which means a decibel referenced to a pressure of 1 microPascal. 

However, there are more factors that must be considered, specifically measurement type and 

measurement bandwidth. 
68 

Measurement type refers to how the pressure was measured. Changing the type” of measurement can 

change the reported sound level of a given sound by up to 9 dB. The most common types are root-meansquare (RMS), peak (also reported as 0-peak), and peak-to-peak. RMS measures are essentially an 

average intensity over a given amount of time. These measures are most appropriate for longer (i.e., nonimpulsive) signals. Impulsive signals, such as airguns and boomers, are best measured with a peak or 

peak-to-peak measurement. These signals are of such limited duration, that it is difficult to appropriately 

calculate a RMS value. These peak measurements simply measure the maximum amplitude of the signal, 

without consideration of time. 

Another preferred metric when considering impulsive signals and their effect upon animals is Sound 

Exposure Level (SEL). This metric, appropriate for all signal types, is the integration of all sound energy 

produced from a source, which is then normalized to the level necessary to produce that amount of energy 

in a single second. These values are reported with units of dB re 1 μPa2

-sec.

The bandwidth of the signal and the measurement must also be properly considered. In general, most of 

the sounds addressed in this study can be classified as tonal (or narrow-band) or broadband (incorporating 

many frequencies). The difference is relevant when considering the sound level of the signal. For a given 

sound pressure level (SPL), the acoustic energy can be concentrated in a single, or a very small number of 

frequencies. Broadband signals have their energy distributed over a large range of frequencies. Thus it is 

important to report the bandwidth over which the measurements were made. Spectral Levels are 

measurements made at a single frequency, and have units of dB re 1μPa2

/Hz. Broadband measurements 

encompass all of the frequencies in a signal, and are reported in units of dB re 1μPa.

6.2 METHODS

The acoustic propagation models used to predict the regions of sound influence require multiple input 

datasets. First, the acoustic parameters of the sources must properly characterized. This includes their 

loudness, or source level. Spectral and temporal characteristics of the acoustic sources also need to be 

included in the model. The specific sources and values for this project are summarized in Table 6.1. 

Acoustic propagation models also require information on the physical characteristics of the underwater 

environment. These include the sound velocity profile of the water column, the roughness of the water 

surface which influences acoustic reflection from the surface, and the reflective properties or geologic 

composition of the seafloor. All of these factors affect how sound propagates through the underwater 

environment. 

Acoustic propagation models produced predicted sound fields for each source and location combination. 

These were used to estimate the distance from the source to various regulatory sound threshold levels. 

These begin to estimate the area that would be ensonified by activities that would likely occur during the 

construction of alternative energy installations at modeling sites off Georgia and North Carolina.
69 

Table 6.1. Summary of source level information for sources to be considered for modeling.

6.2.1 Acoustic Propagation Models

Low frequency sources were modeled using the range-dependent acoustic model (RAM). RAM is a PEbased model that incorporates a geoacoustic ocean bottom model (Collins 1993). Low-frequency 

propagation modeling in shallow water is commonly regarded as difficult. However, a comparison of 

measured sound propagation and model prediction found that RAM was able to predict the sound field 

from a shallow water pile driver with good accuracy (Malme et al. 1998). The mid- and high- frequency 

sources were modeled with the Bellhop ray-trace model (Porter 1992). 

Source Frequency 

Range 

Signal 

Duration 

Modeled 

SL

( dB re 

1μPa)

Source Level 

Range 

( dB re 1μPa)

Type Reference

Boomer 200 H–16 kHz ~500 μs See Fig 6.8 190–220 Peak

(Department 

of the 

Interior 

2012)

Chirp 3.5, 12, 200 

kHz 4–64 ms 217 215–222 218–225 

SPL

Peak

(based on 

Au et al. 

1988)

Geotechnical 

Drilling 2–2050 Hz Continuous 145 141–148 RMS (Mann et al. 2009)

Impact Pile 

Driving

Broadband 

(10 Hz–10 

kHz)

400–500 ms See Fig 6.2 222–235 

239–244 

SPL

Peak

(Blackwell 

2005) 

Vibratory 

Pile Driving

Broadband 

(10 Hz–10 

kHz), with LF 

tonals

Continuous See Fig 6.2 199–212 SPL

(Blackwell 

2005) 

Vessel Noise Broadband Continuous 178 175–195 RMS

(Hatch et al. 

2008a; 

Kipple and 

Gabriele 

2004)

DPS Vessel 

Noise

Broadband 

(e.g., 10 Hz–10 

kHz)

Continuous 193 190–193 RMS

(McCauley 

1998; Roth 

et al. 2013)
70 

6.2.2 Acoustic Propagation Modeling Environmental Inputs

6.2.2.1 Sound Velocity Profile

Sound velocity profiles were extracted from the National Coastal Data Development Center’s General 

Digital Environmental Model (GDEM-V) (version 3.0) database for the month of September. 

6.2.2.2 Bathymetry

The NOAA National Geophysical Data Center’s ETOPO 1 database (Amante and Eakins 2009) was used 

to extract the bathymetry for the two modeling areas. This database has a 1° resolution in latitude and 

longitude. It was the finest resolution database available that covered all of the area to be modeled. For 

the higher frequency sources with lower source levels that required modeling over a smaller area, the 

higher resolution (three arc-seconds) Coastal Relief Model (NOAA National Geophysical 2013) was used 

to supply bathymetry. 

Figure 6.1. ETOPO1 bathymetry for the modeling areas. 
71 

6.2.2.3 Bottom Characterization 

The bottom characteristics of the area from Cape Hatteras to Cape Canaveral was summarized in Volume 

III (page 13) of the Fishery Ecosystem Plan of the South Atlantic Region (South Atlantic Fishery 

Management Council 2009b): “Most of the bight substrate is covered by a vast plain of sand and mud 

(Newton et al. 1971) underlain at depths of less than a meter by carbonate sandstone (Riggs et al. 1996; 

Riggs et al. 1998).” This description was used for both the North Carolina and Georgia sites. The USGS 

sediment thickness database reported that the depth to the acoustic basement was 34.5 meters in the North 

Carolina site and 35 meters for the Georgia site (Divins 2003). 

6.2.2.4 Bottom Loss Model: Geoacoustic Model Construction

The propagation of low frequency sources was modeled with RAM using the geoacoustic model 

presented in DOI (2012, Table D-18) for sandy bottoms (Table D-18). his model is shown in Table 6.2. 

The mid and high frequency sources were modeled with the Bellhop model, which incorporates a loss v. 

angle bottom loss function. This was calculated using the Rayleigh bottom loss scattering model (Officer 

1958). 

Table 6.2. Bottom parameters for the modeling area. 

Depth 

(m)

Density 

(g/cm3) 

Compressional 

wave velocity 

(m/s)

Compressional 

Wave 

attenuation 

(dB/λ)

Shear Wave 

Velocity 

(m/s)

Shear Wave 

Attenuation 

(dB/λ)

0–10 1.87 1,648–1,785 0.45–0.92

158 0.07 

10–50 1.87 1,785–1,987 0.92–1.45

50–150 1.87–2.04 1,987–2,276 1.45–1.79

150–300 2.04 2,276–2,482 1.79–2.08

300–600 2.04 2,482 2.08

6.2.2.5 Surface Loss Model

Surface loss is the loss of acoustic energy resulting from interaction with the water’s surface. The Bellhop 

model runs used the Beckman-Spizzichino Model (Leibiger 1978) to estimate surface loss. The RAM PE 

model used its integral surface loss model. The data input to both of these models is windspeed. 

Windspeed data was extracted from the National Data Buoy Center database (NOAA NDBC 2015). The 

two weather buoys nearest to the modeling locations were buoy number 41008 (31.4°N, 80.86°W) for the 

Georgia location and buoy number 41036 (34.207°N, 76.949°W) for the North Carolina location. The 

2012 data for windspeed was downloaded for both of these buoys and the monthly average for September 

was calculated. The mean windspeed was 5.45 knots for the North Carolina location and 5.69 knots for 

the Georgia location.

6.2.3 Scenario Construction

This acoustic modeling study was conducted as part of a larger project to predict and assess the 

environmental impact of noise that may be produced during the construction of offshore wind farms. 

Prospective locations were identified and ambient noise measurements were made at those sites. These 

locations were used as the basis for selecting locations for acoustic noise field predictions. This study has 

focused on pre-construction and construction activities. However, some of these results, specifically the 

vessel noise results, would also be applicable for operational assessment.
72 

A subset of the six ambient noise recorders sites was selected for modeling locations (see Table 6.3). 

Because the range of depths between the three Georgia locations was small, only a single modeling 

location was chosen for Georgia. For the North Carolina site, the shallowest and the deepest water 

locations were chosen for modeling efforts. 

For each construction activity the associated noise characteristics were established through a literature 

review. These characteristics include source level, frequency bandwidth, beam pattern and duty cycle. A 

separate acoustic modeling run was constructed for each sound type at each modeling location. A virtual 

sound source was placed in the environment at each of the three modeling locations. The depth selected 

for each source is dependent on the activity. For example, vessels were modeled with a source depth of 

four meters, the approximate depth of the propellers while pile-driving sources were placed on the ocean

floor. The horizontal range of each model was selected based on loudness of the source being modeled. 

For example, pile drivers were modeled with a distance of 50 km, whereas chirp sonars were modeled to a 

range of only 1 km. 

Table 6.3: Locations of modeling sites. 

Site Longitude Latitude Depth (m) Modeled

GA-North -80.20946382 31.95322182 20

GA-Central -80.65711959 31.91721722 15 Y

GA-South -80.72975008 31.82680252 15

NC-North -76.41164212 34.23590549 29

NC-Central -76.40920941 34.23585906 28 Y

NC-South -76.82990523 34.00456306 37 Y

6.2.4 Acoustic Characteristics of Modeled Sources

6.2.4.1 Pile Driving Acoustic Parameters

Piles that are being driven are actually line sources, with sound being emitted from the total length of the 

pile, which couples to both the water column and the sediment and rock of the bottom. However, 

propagation models that can handle line sources are not readily available. Nevertheless, a comparison of 

measured data and propagation predictions made with the RAM PE model showed good agreement when 

the pile was modeled as a point source on the ocean floor (Malme et al. 1998). 

Impact and vibratory pile drivers were measured in Knik Arm, AK (Blackwell 2005) with shallow and 

deep hydrophones. The piles were 150 feet long (~46m), 36 inches (91cm) in diameter and had 1-inch 

thick steel walls. The measured acoustic characteristics of these pile driving activities were used as inputs 

for the current modeling study.
73 

Figure 6.2. Source 1/3-octave levels measured from a pile being driven with 

a diesel impact hammer. 

The impact-driven pile was recorded at a distance of 62 meters from the pile. The transmission loss was 

measured in situ, and those data were used to estimate the source levels shown in Figure 6.2. The pile 

driven with the vibratory driver was recorded at a distance of 56 meters, and the in situ measured 

transmission loss function for that pile was used to estimate the source levels shown in Figure 6.3.
74 

Figure 6.3. Source 1/3-octave levels (solid line) measured from a pile being 

driven with a vibratory hammer. 

6.2.4.2 Boomers

A Huntec ED10 boomer has been characterized as being capable of producing zero-to-peak levels of 190 

to 220 dB re 1μPa at 1m, depending upon the power setting (Simpkin 2005). In a recent EIS, this source 

was modeled with a broadband source level of 212 dB re 1 μPa at 1m (Department of the Interior 2012). 

This source level was used in this analysis.

 

The transmission loss for each 1/3-octave band from 200 Hz to 16 kHz was predicted separately with the 

Bellhop transmission loss model. The source was placed at a depth of five meters. The model was run 

with 1600 rays and used coherent addition of the rays. The lower frequencies had an omnidirectional 

radiation pattern, and the rays modeled for these ranged from -90 to 90 degrees (i.e., all possible angles). 

At mid and higher frequencies, the beam pattern of the source became more focused downward. For these 

frequencies the angular range of outgoing rays was limited to the beam angle specified in Table 6.4. Thus 

at high frequencies, only rays representing straight down and angles up to 8° from straight down were 

modeled. This accounted for the beam pattern at each of the frequencies.

These transmission loss values were then subtracted from the appropriate 1/3-octave source level (Table 

6.4) to produce a set of sound pressure level predictions for the boomer source as a function of bearing, 

range and depth. 
75 

Table 6.4. Estimated source levels (RMS SPL) and beam width from the 

representative boomer distributed into twenty 1/3rd-octave bands. 

Third-Octave

Band Center 

Frequency (Hz)

RMS SPL

(dB re 1 μPa

at 1 m)

SEL (dB re 1

μPa2·s at 1 m)

Beam Width

200 196.0 158.6 omnidirectional

250 196.4 159.0 omnidirectional

315 197.1 159.7 omnidirectional

400 197.7 160.3 omnidirectional

500 198.5 161.1 omnidirectional

630 199.4 162.0 omnidirectional

800 200.0 162.6 omnidirectional

1,000 200.8 163.4 omnidirectional

1,250 201.5 164.1 105°

1,600 201.6 164.2 78°

2,000 201.9 164.5 60°

2,500 201.4 164.0 47°

3,150 200.8 163.4 37°

4,000 200.1 162.7 29°

5,000 198.9 161.5 23°

6,400 197.8 160.4 18°

8,000 196.1 158.7 14°

10,000 192.8 155.4 11°

12,800 186.8 149.4 9°

16,000 176.8 139.4 8°
76 

6.2.4.3 Chirp Sonar

Chirp sonar signals are shorter than the measured marine mammal integration time. Dolphin integration 

times have been measured at 264 ms (Au et al. 1988). Therefore the peak and RMS source levels were 

reduced using a conservative 200 ms value for all species. The reduction was 5 dB for the 3.5 and 12 kHz 

source and 17 dB for the 200 kHz source. 

Table 6.5. Representative chirp sub-bottom profiler specifications (Department of the Interior 2012). 

Frequency

3.5 kHz 12 kHz 200 kHz

Beam Pattern Circular 30° Rectangular

26° by 38°

Circular 8°

Output power 3 kW 3 kW 0.5 kW

rms SPL (dB re 1 μPa at 1 m) 222 222 215.2

Peak level (dB re 1 μPa at 1 m) 225 225 218.2

SEL (dB re 1 μPa2·s at 1 m) 210.1 210.1 191.2

Total peak level (dB re 1 μPa at 1 m) 228.2

Ping duration (max) 64 ms 4 ms

6.2.4.4 Geotechnical Drilling and Cone Penetrometers

The sound levels associated with geotechnical drilling were estimated using the measured under ice 

values for a small coring drill and a large casing drill (Mann et al. 2009). A small drill had RMS levels of 

127.8 dB re 1 μPa at a distance of five meters. The larger casing drill had a received level of 124.5 dB re 

1 μPa at a distance of fifteen meters. Assuming spherical spreading these translate into RMS source levels 

of 141.8 and 148.0 dB re 1 μPa at 1 meter. Note that the measured peak sound pressure levels at times 

were over 20 dB higher than these RMS measures, suggesting the presence of transient sounds associated 

with drilling activity.

Cone penetrometers are used to assess sediment characteristics and stiffness. They are typically 

comprised of a 60° metal cone at the end of a metal shaft that is driven into the sediment with hydraulic 

pressure (Lee and Peterson 2001). No description of the noise characteristics of cone penetrometers could 

be located. However, given the lack of a significant vibration source (as would occur in pile driving or 

rotational drilling), this activity is not expected to produce substantial acoustic levels.

6.2.4.5 Characterization of Vessel Noise Parameters

The source level of tugs and research vessels were estimated in the band of 71-141 Hz (Hatch et al. 

2008b). Three tugs had source levels of 174 ± 3, 175 ± 2 and 166 ± 2 dB re 1 μPa at 1 m. Two research 

vessels had source levels of 158 ± 2 and 161 ± 2 dB re 1 μPa at 1 m. These two classes of vessels most 

closely approximate the service vessels expected to support the renewable energy installation construction 

and maintenance activities.

Overall vessel noise level was examined as a function of vessel length, at a vessel speed of 10 knots 

(Kipple and Gabriele 2004). Vessels in the length range of 50 to 100 ft had a broadband source level of 

169 ± 3 dB re 1μPa at 1 yd, while vessels greater than 100 ft in length had a source level of 177 ± 5 dB re 

1μPa at 1 yd. 
77 

Numerous fishing vessels have recently been characterized at various speeds (Allen et al. 2012). Fishing 

vessels are an appropriate representative for support vessels for the construction activity at these 

locations. Source levels in the 1–2,500 Hz band ranged from 173 to 195 dB re 1 μPa at 1m. There was a 

strong correlation between vessel speed and source level as shown in Figure 6.4. 

Figure 6.4: Data from Allen et al. (2012) plotted to show strong relationship 

between vessel speed and source level (dB re 1 μPa at 1m, 1-2,500 Hz).

6.2.4.7 Characterization of Vessels in Dynamic Positioning Mode

The characteristics of a vessel using dynamic positioning system (DPS) have not been measured directly. 

However, a drilling rig support vessel equipped with a bow thruster (a major DPS component) had a 

measured broadband source level of 137 dB re 1 μPa at a distance of 405 meters (McCauley 1998). 

Assuming spherical spreading, this gives a broadband source level value of approximately 190 dB re 1 

μPa at 1m. Measurement of the bow thruster of the R/V Healey found octave-band source levels as high 

as 193 dB re 1 μPa at 1m (Roth et al. 2013). This value was used for the acoustic modeling for the current 

study. 
78 

6.3 RESULTS

6.3.1 Acoustic Propagation Modeling Results

The results of the acoustic propagation modeling are presented for each source and for each modeling 

location. For each combination of source and modeling location there are multiple presentations. First will 

be a transmission loss slice, which is a presentation of sound received level plotted as a function of both 

range and depth. This presentation gives an overall view of how that particular sort sound source is likely 

to propagate at each of the modeling areas. 

Sound propagation is affected by bathymetry. In general, sound travelling into deeper water will 

propagate farther than sound that is traveling into shallower water. Some propagation is also bearing 

dependent. Therefore, the models were run 36 times at 10° intervals, for every location-source 

combination. These are summarized by plotting the maximum received sound level from all of the 

bearings in one figure. Thus each TL slice figure represents the “best” possible acoustic propagation.

To describe the bearing dependent component of the acoustic propagation one or more plan view figures 

will also be presented for each source location combination. These figures represent an overhead view 

looking down on the sound field; where appropriate, multiple versions of the same analysis represented at 

different spatial scales are shown. Because propagation is also depth dependent the slices are shown at a 

nominal depth of 6 m. This depth was chosen, in part, because all marine mammals have to return to the 

surface and will pass through this depth. 

The approximate ranges to the 160 and 180 dB isopleths are determined from these figures and 

summarized in tables at the end of the results section. Approximate ranges are specified because the exact 

parameters of the exact construction activities to be conducted have not been specified. Therefore, these 

distances represent approximate guidelines for a given activity.
79 

6.3.1.1 Boomer Source

The acoustic propagation of boomer was predicted at each of the modeling sites, for frequencies from 200 

Hz to 16 kHz. A total of 20 1/3-octave bands were modeled and then combined to produce the broadband 

transmission loss predictions. 

The maximum received for each modeled radial is shown. As seen in Figure 6.5, the sound pressure level 

varies by depth and range. To illustrate the spatial extent of any particular sound pressure isobath, the 

maximum sound pressure from all depths was calculated for each range and bearing step. These twodimensional representations illustrate the maximum range to regulatory thresholds (i.e., 160 dB and 180 

dB re 1 μPa (RMS). 

Figure 6.5. The maximum received level from the Georgia site is shown as a 

function of range and depth.
80 

Figure 6.6 shows the sound pressure level at each range and bearing at a sample depth of 6 meters. The 

isopleths of 150, 160 and 180 dB are specified. The 150 dB isopleths are shown as the light blue color. 

The 160 dB isopleth can be easily recognized as the inner greenish circle and a torus at a range of about 

2.5 km. The 180 dB isopleth is at a range of about 100 meters. 

Figure 6.6. Planar view of sound propagation at Georgia site.
81 

Figure 6.7.The maximum received level from NC-North is shown as a function of 

range and depth.
82 

Figure 6.8.The received sound level of the boomer source at the NC site at 

depth of six meters is shown. 

The maximum range of the 160 dB isopleth is ~3.5 km.

These two data presentations are repeated for the North Carolina site #3.
83 

Figure 6.9. The maximum received level of any radial is shown as a function of 

range and depth at the NC site.
84 

Figure 6.10.The received sound level of the boomer source at the NC site a depth 

of six meters is shown. 

The maximum range of the 160 dB isopleth is ~3.5 km.
85 

6.3.1.2 Chirp Source

Chirp sonars typically have frequencies of 3.5, 12, or 200 kHz. The 3.5 kHz signal will propagate further 

than the others because of the frequency-dependent effect of sound absorption. The modeling was based 

on a center frequency of 3.5 kHz. Chirp sonars also have a narrow beam pattern which is focused 

downward toward the seafloor. This effect is seen in Figure 6.11. The energy hitting the seafloor is 

reflected upwards, but the downward reflection from the surface is weak, limiting the horizontal extent of 

these sonars.

Figure 6.11.The propagation of the chirp sonar source is shown. 

Due to the very narrow beam pattern, the range scale of this figure has been reduced. 
86 

Figure 6.12. The received level at a depth of six meters is shown. 

The outer ring shows the 160 dB contour at a range of ~20 meters.

6.3.1.3 Geotechnical Drilling

The low source level identified for geotechnical drilling obviated the need for acoustic propagation 

modeling, as the source level was less than the 160 dB regulatory threshold.

6.3.1.4 Impact Pile Drivers

Impact pile drivers operate by repeatedly hammering a pile with a large driven weight. The city signal is 

that of a repeating impulse that can have considerable amplitude. Piles typically take many hours to be 

completely driven. Thus both the signal duration and event duration qualify them as an “intermittent” 

activity for which the 160 and 180 dB thresholds clearly apply. 
87 

Figure 6.13.The propagation predicted from the RAM model as a function of range

and depth for the Georgia site. 

The received levels have been contoured in 10 dB steps to aid readability. The 160 and 

180 dB isopleths are reached at ranges of approximately 10 km and 1800 meters, 

respectively.
88 

Figure 6.14.The maximum received level at any depth for the Georgia site.

The received levels have been contoured in 10 dB steps to aid readability. The 

160 and 180 dB isopleths are reached at ranges of approximately 10 km and 1800 

meters, respectively. The effect of the coastline to the northwest of the site can be 

readily seen.
89 

Figure 6.15. The inner portion of the maximum received level at any depth is 

shown for the Georgia site. 

The received levels have been contoured in 10 dB steps to aid readability. The 

160 and 180 dB isopleths are reached at ranges of approximately 10 km and 1800 

meters, respectively.
90 

Figure 6.16. The propagation predicted from the RAM model as a function 

of range and depth for the North Carolina site.

The received levels have been contoured in 10 dB steps to aid readability. The 

160 and 180 dB isopleths are reached at ranges of approximately >10 km and 

1500 meters, respectively.
91 

Figure 6.17.The maximum received level at any depth for the North Carolina 

site. 

The received levels have been contoured in 10 dB steps to aid readability. The 

160 and 180 dB isopleths are reached at ranges of approximately 15 km and 

1800 meters, respectively.
92 

Figure 6.18. The inner portion of the maximum received level at any depth 

for the NC-North Site. 

The received levels have been contoured in 10 dB steps to aid readability. The 

160 and 180 dB isopleths are reached at ranges of approximately >10 km and 

1500 meters, respectively.
93 

Figure 6.19.The propagation predicted from the RAM model as a function of 

range and depth for the NC-South site.

The received levels have been contoured in 10 dB steps to aid readability. The 

160 and 180 dB isopleths are reached at ranges of approximately >10 km and 

1800 meters, respectively.
94 

Figure 6.20. The maximum received level at any depth is shown for the NCSouth site. 

The received levels have been contoured in 10 dB steps to aid readability. The 

160 and 180 dB isopleths are reached at ranges of approximately 15 km and 1800 

meters, respectively.
95 

Figure 6.21. The inner portion of the maximum received level at any depth 

is shown for the NC-South site.

The received levels have been contoured in 10 dB steps to aid readability. The 

160 and 180 dB isopleths are reached at ranges of approximately >10 km and 

1800 meters, respectively.
96 

6.3.1.5 Vibratory Pile Drivers

Vibratory pile drivers operate by oscillating the pile back and forth to work the pile into the sediment. 

While they are operating, they represent a continuous sound source. However, the total duration of the 

activity is typically short, so the 160 and 180 DB thresholds were considered for this activity as well. 

Figure 6.22.The propagation predicted from the RAM model is shown as a 

function of range and depth for the GA-Central site.

The received levels have been contoured in 10 dB steps to aid readability. The 

160 and 180 dB isopleths are reached at ranges of approximately 6 km and 750 

meters, respectively.
97 

Figure 6.23.The maximum received level at any depth is shown for the GACentral site.

The received levels have been contoured in 10 dB steps to aid readability. The 

160 and 180 dB isopleths are reached at ranges of approximately 6 km and 750 

meters, respectively.
98 

Figure 6.24.The inner portion of the maximum received level at any depth is 

shown for the GA-Central site.

The received levels have been contoured in 10 dB steps to aid readability. The 

160 and 180 dB isopleths are reached at ranges of approximately 6 km and 1800 

meters, respectively.
99 

Figure 6.25. The propagation predicted from the RAM model is shown as a 

function of range and depth for the NC-North site.

The received levels have been contoured in 10 dB steps to aid readability. The 

160 and 180 dB isopleths are reached at ranges of approximately 7 km and 500 

meters, respectively.
100 

Figure 6.26. The maximum received level at any depth is shown for the NCNorth site.

The received levels have been contoured in 10 dB steps to aid readability. The 

160 and 180 dB isopleths are reached at ranges of approximately 9 km and 500 

meters, respectively.
101 

Figure 6.27. The inner portion of the maximum received level at any depth is 

shown for the NC-North site.

The received levels have been contoured in 10 dB steps to aid readability. The 

160 and 180 dB isopleths are reached at ranges of approximately 8 km and 1200 

meters, respectively.
102 

Figure 6.28. The propagation predicted from the RAM model is shown as a 

function of range and depth for the NC-South site.

The received levels have been contoured in 10 dB steps to aid readability. The 

160 and 180 dB isopleths are reached at ranges of approximately >5 km and 500 

meters, respectively.
103 

Figure 6.29. The maximum received level at any depth is shown for the NCSouth site.

The received levels have been contoured in 10 dB steps to aid readability. The 

160 and 180 dB isopleths are reached at ranges of approximately 9 km and 500 

m, respectively.
104 

Figure 6.30. The inner portion of the maximum received level at any depth 

is shown for the NC-South site.

The received levels have been contoured in 10 dB steps to aid readability. The 

160 and 180 dB isopleths are reached at ranges of approximately > 5 km and 

800 meters, respectively.
105 

6.3.1.6 Vessel Noise

The propagation of vessel noise was considered because it is a component of preconstruction, 

construction, and operational phases of a renewable energy installation. Both normal and dynamic 

positioning system vessel signatures were considered. Ranges to the 160 and 180 dB isopleth were 

estimated, as with the other activities. However, it should be noted that, traditionally, vessel noise itself 

has not been subject to regulatory thresholds. Therefore the values presented here are for informational 

purposes. Finally, it should be remembered that vessels are, of course, mobile and their sound footprint 

will follow them as they move from port to the energy installation and back. 

Figure 6.31. The maximum received level for any modeled radial is shown as a 

function of range and depth for the GA-Central site. 

The 160 dB isopleth is only a few hundred meters away from the source.
106 

Figure 6.32. The received level at a depth of six meters is shown for the GACentral site.

The 160 dB isopleth is only a few hundred meters away from the vessel.
107 

Figure 6.33. The maximum received level for any modeled radial is shown as 

a function of range and depth for the NC-North site. 

The 160 dB isopleth is only a few hundred meters away from the source.
108 

Figure 6.34. The received level at a depth of six meters is shown for the NCNorth site.

The 160 dB isopleth is only a few hundred meters away from the vessel.
109 

Figure 6.35. The maximum received level for any modeled radial is shown as a 

function of range and depth for the NC-South site.

The 160 dB isopleth is only a few hundred meters away from the source.
110 

Figure 6.36. The received level at a depth of six meters is shown for the NCSouth site.

The 160 dB isopleth is only a few hundred meters away from the vessel.
111 

6.3.2.4 Dynamic Positioning System Vessel Noise

Vessels employing dynamic positioning systems (DPS) are louder than those using only conventional 

propulsion. 

Figure 6.37. The maximum received level for any modeled radial is shown 

as a function of range and depth for the GA-Central site. 

The 160 dB isopleth is approximately 1500 away from the source.
112 

Figure 6.38. The received level at a depth of six meters is shown for the GACentral site.

The 160 dB isopleth is approximately 800 meters away from the vessel.
113 

Figure 6.39. The maximum received level for any modeled radial is shown 

as a function of range and depth for the NC-North site. 

The 160 dB isopleth is approximately 1 km away from the source.
114 

Figure 6.40. The received level at a depth of six meters is shown for the NCNorth site.

The 160 dB isopleth is approximately 800 meters away from the vessel.
115 

Figure 6.41. The maximum received level for any modeled radial is shown 

as a function of range and depth for the NC-South site. 

The 160 dB isopleth is approximately 1 km away from the source.
116 

Figure 6.42. The received level at a depth of six meters is shown for the NCSouth site. 

The 160 dB isopleth is approximately 800 meters away from the vessel.
117 

6.3.2.5 Summary of Affected Ranges

Table 6.6: Georgia isopleth range summary. 

Activity

Modeled 

SL (dB re 

1 μPa at 

1m)

Modeled 

Frequency

Distance to 

160 dB 

SPL 

isopleth 

(m)

Distance to 180 

dB SPL isopleth 

(m)

Boomer See Fig X 200 Hz–16 

kHz ~3500 -100 

Chirp Sonar 217 3.5 kHz ~ 250 ~20 (horizontal)

~70 (vertical)

Geotechnical 

Drilling 145 2–2050 Hz <1 <1

Impact Pile 

Driving

See Fig BI Broadband 

(10 Hz–10 

kHz)

~10,000 ~1,800 

Vibratory Pile 

Driving

See Fig BV Broadband 

(10 Hz–10 

kHz)

~6,000 ~800 

Vessel Noise 178 

Broadband 

with peak at 

100 Hz

~100 <1

DPS Vessel 

Noise 193 

Broadband 

with peak at 

100 Hz

~1,000 ~100 
118 

Table 6.7: NC-north isopleth range summary. 

Activity

Modeled 

SL (dB re 

1 μPa at 

1m)

Modeled 

Frequency

Distance to 

160 dB 

SPL 

isopleth 

(m)

Distance to 180 dB 

SPL isopleth (m)

Boomer See Fig X 200 Hz–16 

kHz ~3500 -100 

Chirp Sonar 217 3.5 kHz ~ 250 ~20 (horizontal)

~70 (vertical)

Geotechnical 

Drilling 145 2–2050 Hz <1 <1

Impact Pile 

Driving

See Fig BI Broadband 

(10 Hz–10 

kHz)

~15,000 ~1,500 

Vibratory Pile 

Driving

See Fig BV Broadband 

(10 Hz–10 

kHz)

~7,000 ~500 

Vessel Noise 178 

Broadband 

with peak at 

100 Hz

~100 <1

DPS Vessel 

Noise 193 

Broadband 

with peak at 

100 Hz

~800 ~100 
119 

Table 6.8: NC-south isopleth range summary. 

Activity

Modeled 

SL (dB re 

1 μPa at 

1m)

Modeled 

Frequency

Distance to 

160 dB 

SPL 

isopleth 

(m)

Distance to 180 

dB SPL isopleth 

(m)

Boomer See Fig X 200 Hz–16 

kHz ~3500 -100 

Chirp Sonar 217 3.5 kHz ~ 250 ~20 (horizontal)

~70 (vertical)

Geotechnical 

Drilling 145 2–2050 Hz <1 <1

Impact Pile 

Driving

See Fig BI Broadband 

(10 Hz–10 

kHz)

~15,000 ~1,800 

Vibratory Pile 

Driving

See Fig BV Broadband 

(10 Hz–10 

kHz)

~7,000 ~600 

Vessel Noise 178 

Broadband 

with peak at 

100 Hz

~100 <1

DPS Vessel 

Noise 193 

Broadband 

with peak at 

100 Hz

~800 ~100 

6.4 CONCLUSIONS

6.4.1 Comparison of Sources

Current marine mammal regulatory thresholds are based on received sound pressure levels. Renewable 

energy installation construction activities with higher source levels have greater probability of affecting 

marine mammals. The loudest source considered for this study was impact pile driving. This study found 

that the range to the behavioral effects threshold was up to 15 km under current regulatory guidelines. 

Vibratory pile driving produces less noise and a correspondingly smaller potentially-affected area. These 

two types of pile driving are the only activities that ensonify a large area to a level that could create 

potential physiological effects to marine mammals. The range for potential physiological impacts made 

by the boomer is much smaller, approximately 100 meters. A similar range was predicted for a vessel 

operating in dynamic positioning mode; however, vessel propulsion noise has not been subject to 

regulation in the past. Finally, this study’s acoustic modeling results indicated that chirp sonar and 

geotechnical drilling are not expected to have much effect on marine mammal species. This is due to the 

narrow beam pattern of the chirp sonar and the low source level for geotechnical drilling.

6.4.2 Comparison of Locations

The geographic location will affect the results based on local propagation conditions. The primary 

differences between the two locations studied here arise from the proximity to shore and the depth of the 

water column. The Georgia location is both nearer to shore and in shallower water. This results in poorer 

acoustic propagation than is found at the North Carolina site, and smaller ranges to regulatory thresholds. 

However, the closer proximity of the Georgia site to the shore may mean that some species will be found 
120 

in higher abundance, such as the very coastal Northern Right whale. Animal densities need to be 

considered when or if a choice is to be made between these two potential construction locations. 

6.4.3 Future Considerations

The regulatory thresholds considered during this study are those currently in effect, namely 160 dB for 

behavioral responses and 180 dB for physiological response to intermittent sources. There is also a 120 

dB threshold for continuously operated sources. However, NMFS has proposed an additional regulatory 

threshold that is based on the SEL metric. The proposed metric would either, 1) integrate all of the sound 

emitted by a source for one hour, or 2) integrate the received levels of modeled animals over a period of 

24 hours. These proposed guidelines are still undergoing review. 

These proposed new guidelines were not considered during this study. However, a quick comparison 

between the current and proposed metrics was made using impact pile driving propagation as measured 

by Blackwell (2005). This comparison assumed 30 hammer blows per minute and a total time of one 

hour. Under the current regulatory scheme the behavioral threshold would be reached at a range of 

approximately 5 km and the physiological take threshold would be reached at a distance of approximately 

2 km. Under the proposed NMFS SEL metrics, the TTS onset threshold would be reached at a distance of 

approximately 20 km and the PTS onset threshold would occur at a distance of approximately 4 km. 

Implementation of the proposed NMFS guidelines may increase the regulated area around offshore 

alternative energy installation construction activities. It should be noted that this simple modeling 

approach of integrating source output over one hour is known to produce more conservative results than 

the more sophisticated animal movement modeling approach (e.g., the Acoustic Integration Model). 

Because these new guidelines have not been finalized, they were not considered during the study. 

However, a quick comparison was made using measured impact piledriving propagation. This comparison 

assumed 30 hammer blows per minute and a total time of one hour. Under the current regulatory scheme, 

the behavioral threshold would be reached at a range of approximately 5 km and the physiological take 

threshold would be reached at a distance of approximately 2 km. Under the proposed SEL metrics, the 

TTS onset threshold would be reached at a distance of approximately 20 km and the PTS onset threshold 

would occur at a distance of approximately 4 km. Therefore it is clear that implementation of the 

proposed NMFS guidelines may increase the area around these activities which are considered to affect 

marine mammals. It should also be noted that this very simple modeling approach is known to produce 

more conservative results than the more sophisticated animal movement modeling approach (e.g, the 

Acoustic Integration Model) (Frankel et al. 2002) that is based on the received sound level of moving 

animal models.
121 

7. HABITAT ASSESSMENT

As part of the study team, ESS supported Cornell University by conducting habitat assessments to 

identify marine species potentially impacted by noise producing activities on the Outer Continental Shelf 

(OCS). The desktop habitat assessments examined the distribution and relative abundance of indigenous 

subsurface marine species as a baseline study to potential wind energy development. Though the habitat 

studies will identify a diverse range of potentially affected marine species, it is anticipated the potential 

noise impacts of wind energy development construction activities will be evaluated with respect to their 

effects on marine mammals.

The two study sites contain wind planning areas located off the coasts of North Carolina and Georgia (see 

Chapter 2), referred to as the NC-Site and GA-Site, which are located in federal waters on the Atlantic 

Outer Continental Shelf. These sites are the potential future locations of offshore renewable energy 

development activities. From an ecological perspective, the sites are located within the South Atlantic 

Bight (SAB) on the inner-to-mid portions of the continental shelf in waters less than 45 m in depth. 

Habitats in these areas are predominantly soft bottom comprised of sandy sediments. Some hardbottom 

habitats, including live and artificial coral are also found in the general vicinities of the two sites.

Marine vertebrate species composition and usage of the sites for baseline study was determined to be 

representative of the western North Atlantic south of Cape Hatteras, North Carolina. Factors influencing 

marine species usage of the study areas are related to habitat characteristics such as depth, circulation, 

temperature, and salinity, which correlate to distance from shore. It happens that the two study areas are 

relatively close to shore and lie upon fairly homogenous portions of the continental shelf lacking dramatic 

variations in oceanographic features. 

7.1 INTRODUCTION

This desktop study involves a limited examination of the biological oceanography of NC-Site and GASite. It is limited in the sense that the data and discussion presented here are historical in nature; it 

describes baseline conditions of the marine habitats and species composition associated with these areas 

from a perspective of what is inherently a dynamic ecosystem. No field work or original data collection 

and analysis were conducted for this effort and no ongoing monitoring of marine species is underway. 

This level of study is adequate in support of the current study, however; because it provides background 

information for the broader project that aims to better understand the potential impacts on marine species 

from noise-producing activities associated with offshore renewable energy development.

The purpose of this desktop study is to better understand the biological components of the two candidate 

sites in order to determine the marine vertebrates that are likely to use these areas and consequently, be at 

risk of exposure to anthropogenic sounds. To achieve this understanding, research efforts focused on 

technical sources from federal and state agencies, as well as academia, to understand the physical and 

biological attributes of each site so that habitat types could be characterized. Site habitat characterization 

was conducted discretely and also within a regional context in order to refer habitat types and species 

composition with respect to a broader geographic area.

7.1.1 North Carolina Site

BOEM identified 48 OCS Lease Blocks within the BOEM Official Protraction Diagram Beaufort NI18-

04 of its South Atlantic Planning Area as the second candidate site to conduct the habitat characterization 

and further acoustical analysis under this task (Figure 7.1). NC-Site lies approximately 22 miles south of 

Cape Lookout, North Carolina. NC-Site is located within the SAB in a sub-region known as the Carolina 

Capes Region. It is also within the Carolinian Atlantic Marine Ecoregion. NC-Site is within an 
122 

oceanographic setting marked by a relatively narrow continental shelf that is approximately 60 km wide 

south of Cape Lookout. This region of the OCS lies within the mid-shelf zone between 30 to 40 m of 

water depth. 

7.1.2 Georgia Site

BOEM identified OCS Lease Block 6126 within the BOEM Official Protraction Diagram Brunswick NH 

17–02 of its South Atlantic Planning Area as the first candidate site to conduct the habitat characterization 

and further acoustical analysis under this task. Lease Block 6126 is the subject of an interim lease to the 

Southern Company to install meteorological measurement set equipment for the purposes of measuring 

wind speeds.

GA-Site is approximately 3 miles southeast of Little Tybee Island, Georgia with Wassaw Sound and 

Wassaw Island being two other coastal features geographically associated with the site (Figure 7.2). 

Georgia site is located within a region of the Atlantic OCS off of the southeastern U.S. referred to as the 

SAB. The SAB is defined as the shallow-curving geographic landform extending from Cape Hatteras, 

North Carolina, to Cape Canaveral, Florida. The northern part of the SAB is known as the Carolina Capes 

Region; the middle and southern areas are called the Georgia Embayment or the Georgia Bight. The 

International Commission for Environmental Cooperation classifies this area as the Carolinian Atlantic 

Marine Ecoregion, signifying a distinct assemblage of ecological attributes that will be discussed below.

GA-Site is within an oceanographic setting that conforms with the relatively wide (120 km) and flat 

portion of the OCS off of Georgia. This region of the OCS is marked by three zones comprising the 

oceanographic regime of these waters: inner shelf (0 to 20 m in depth), mid-shelf (21 to 40 m in depth), 

and outer (41 to 75 m in depth). GA-Site sits shoreward of the Florida-Hatteras Slope and the Blake 

Plateau (NOAA 2004b) on the inner shelf where the oceanographic conditions are dominated by tidal 

currents, river runoff, local wind forcing, and seasonal atmospheric changes (SAFMC 2009a). 
123 

Figure 7.1. North Carolina wind planning area (NC-Site). 

Depth and location of wind planning area at the North Carolina 

site. 
124 

Figure 7.2. Georgia site (GA-Site). 

Depth and location of wind planning area at the Georgia site. 
125 

7.2 PHYSICAL HABITAT CHARACTERIZATION

This Chapter presents summaries of the physical resources found within the boundaries of the two 

candidate sites and the region around them. The presentations discuss bathymetry, bottom substrate, water 

temperature, salinity, and circulation. 

7.2.1 North Carolina Site

7.2.1.1 Bathymetry

NC-Site is located in the vicinity of Cape Lookout Shoals. It occupies a relatively flat portion of the 

continental shelf, shoreward of the Florida-Hatteras Slope (NOAA 2004b). In general, NC-Site sits in 

waters ranging from 30 to 40 m in depth; shallower waters are generally to the north and west of the 

Project Area and deeper waters to the south and east (Figure 7.3). Southeast and east of the site water 

depths increase rapidly to more than 100 m. Between the Project Area and Cape Lookout to the North are 

the Cape Lookout Shoals. These shoals are a shallow water area, running in southeasterly direction with 

water depths as low as one to two m (NOAA 1973a; NOAA 1973b; NOAA 1974). 

7.2.1.2 Bottom Substrate

The seafloor geology of NC-Site has been identified as sand by the US Geological Survey (USGS 2005) 

(Figure 7.4). As outlined by the South Atlantic Fisheries Management Council, much of the seafloor of 

the SAB is composed of a relatively thin layer of mud and sand over carbonate sandstone (SAFMC 

2009a). Scattered within this broad coastal plain are often found areas of “live bottom” or areas of dense 

invertebrate and algal assemblages associated with changes in bottom topography and often times 

exposed bedrock or hard bottom. These outcroppings are normally found in water depths between 30 to 

70 m. However, the Fisheries Ecosystem Plan for the South Atlantic Region cites observations that 

additional live bottom areas in shallower waters are more prevalent than previously believed (SAFMC 

2009a). Parker et al. (1983) estimated that in North Carolina waters, hard bottom assemblages covered 

approximately 14% of the seafloor in the depth range of 27 to 101 m between the geographic areas of 

Cape Hatteras and Cape Fear. 

Areas of Essential Fish Habitat-Habitat Areas of Particular Concern (EFH-HAPC) pertaining to Coral 

Reefs and Hard/Live Bottom have been identified in the area surrounding NC-Site (FFWCC 2005). 

Additionally, Southeast Area Monitoring and Assessment Program—South Atlantic (SEAMAP-SA) 

mapping efforts in 2001 indicate numerous hard bottom locations within the overall Project Area 

(SEAMAP-SA 2001). Based on these maps, two major areas of coral reefs, hard bottoms, or live bottoms 

were identified within the boundaries of NC-Site. Ten Fathom Ledge is a large HAPC located along the 

northern boundary of NC-Site. Big Rock is identified as an HAPC and is located to the east of the site.

7.2.1.3 Water Temperature and Salinity

Temperature and salinity are known to fluctuate on a seasonal basis throughout the inner continental shelf 

zone in which NC-Site is located. Water temperatures have been reported to range between 10° to 29°C 

and salinity has been reported to range between 33.0 and 36.5 ppt (SAFMC 2009a). Further offshore, near 

the continental shelf break, water temperatures and salinity are influenced more by the Gulf Stream than 

by freshwater inputs and local weather patterns, and are therefore more stable (18 to 22°C and 36.0 to 

36.2 ppt). 
126 

Figure 7.3. NC-Site Bbathymetry. 

Bathymetry at NC-Site. 
127 

Figure 7.4. NC-Site geology. 

Geology at NC-Site. 
128 

7.2.1.4 Circulation and Upwelling

Circulation in the inner shelf zone of the continental shelf (0 to 20 m of water depth) in the vicinity of 

NC-Site is dominated by tidal currents, fresh water runoff (rivers), and seasonal weather patterns 

(SAFMC 2009a). A major influx of fresh water into the North Carolina coastal system is from the Cape 

Fear River; additional southern flowing fresh water from Chesapeake Bay also influences North Carolina 

coastal waters. Offshore of Cape Hatteras, there is a major confluence of the Gulf Stream and the Virginia 

Coastal Labrador Current (CHPP 2010). This meeting of warm southerly waters and cold northern waters 

effectively separates the middle and southern Atlantic. Further out on the continental shelf, the wind 

patterns and the Gulf Stream’s influence increases, as tidal effects and freshwater runoff weaken. Given 

the area’s many shoals, and the major confluence of currents discussed above, the coastal area adjacent to 

Cape Hatteras is the most likely location for upwelling currents (CHPP 2010). 

 

7.2.2 Georgia Site

7.2.2.1 Bathymetry

The bathymetry of GA-Site, according to NOAA National Ocean Service data, resembles that of the 

surrounding area with waters depths that generally increase moving away from the coastline in a 

southeasterly direction (NOAA 1973a; 1973b; 1974; 2004a). The site occupies waters ranging from 13 to 

15 m in depth. A small area of slightly shallower water (12 to 13 m) runs across the center of the site, and 

small pockets of deeper water (15 to 17 m) can be found along the southeastern boundary of the site 

(Figure 7.5). 

7.2.2.2 Bottom Substrate

The seafloor geology of GA-Site has been identified as sand by the US Geological Survey (USGS 2005) 

(Figure 7.6). The South Atlantic Fisheries Management Council classifies much of the seafloor of the 

South-Atlantic Bight as being composed of a relatively thin layer of mud and sand over carbonate 

sandstone (SAFMC 2009a). Scattered within this broad coastal plain are commonly found areas of “live 

bottom” or areas of dense invertebrate and algal assemblages associated with changes in bottom 

topography and often times exposed bedrock or hard bottom. These outcroppings are normally found in 

water depths between 30 and 70 m. However, the Fisheries Ecosystem Plan of the South Atlantic Region 

cites reports that additional live bottom areas in shallower waters are more prevalent than had been 

previously believed (South Atlantic Fishery Management Council 2009a). 

7.2.2.3 Water Temperature and Salinity

Temperature and salinity throughout the upper continental shelf area are known to fluctuate on a seasonal 

basis. Water temperatures have been reported to range between 10° to 29°C and salinity has been reported 

to range between 33.0 parts per thousand (ppt) and 36.5 ppt (SAFMC 2009a). Further offshore, near the 

continental shelf break (55 to 110 m of water depth), water temperatures and salinity are influenced more 

by the Gulf Stream than by freshwater inputs and local weather patterns, and are therefore more stable (18 

to 22°C and 36.0 to 36.2 ppt). GA-Site is found within the inner shelf area, and is exposed to the 

seasonably variable conditions described above. 
129 

Figure 7.5. GA-Site bathymetry. 

Bathymetry at GA-Site. 
130 

Figure 7.6. GA-Site geology. 

Geology at GA-Site. 
131 

7.2.2.4 Circulation and Upwelling

Circulation in the inner shore zone of the continental shelf (0 to 20 m of water depth) in the vicinity of the 

Project Area is dominated by tidal currents, fresh water runoff (rivers), and seasonal weather patterns 

(SAFMC 2009a). Further out on the continental shelf the wind patterns and the Gulf Stream’s influence 

increase, as tidal effects and freshwater runoff weaken. 

Southeast of Charleston, South Carolina a geologic feature known as the Charleston Bump rises from the 

seafloor and redirects the Gulf Stream to the northeast. This redirection allows for the formation of the 

Charleston Gyre, which is considered an important nursery habitat for certain offshore fish species 

(SAFMC 2009a). The Charleston Gyre causes upwelling of nutrient rich water from the ocean floor, 

which supports a wide variety of biological process. Though the Charleston Bump and Gyre are not 

located in the immediate vicinity of the candidate site, their influence is considered to be regional in 

nature.

7.3 BIOLOGICAL HABITAT CHARACTERIZATION

7.3.1 North Carolina Site

Marine offshore systems encompass a diversity of habitats off the coast of North Carolina. These habitats 

are either benthic or pelagic and vary both laterally and longitudinally with distance from shore. Benthic 

habitats are categorized into three major groups: 

1. Coral, coral reefs and live/hardbottom habitat

2. Artificial reefs

3. Marine soft bottom habitat 

Pelagic habitats are primarily categorized as Marine Water Column or sargassum habitat. 

The continental shelf off the coast of North Carolina lies at an important physical, chemical, and 

biological boundary between the Mid-Atlantic Bight (MAB) and SAB. Here, the Gulf Stream is diverted 

away from the southeastern U.S. coastline and directed out to sea. As a result, the MAB and SAB have 

drastically different water sources, water temperatures and biological composition. Cape Hatteras in 

North Carolina is the upland geographic point that divides these two marine systems. Because the 

candidate site lies to the south of Cape Hatteras, the SAB habitat and species will be the focus of this 

report.

Water depth within NC-Site ranges from approximately 30 to 40 m. In general, water depth increases 

from the north to the south, with the shallowest depths in the northwest of the site and the deepest areas in 

the southeast. 

7.3.1.1 Coral, Coral Reefs, and Live/Hardbottom Habitat

Coral and hardbottom habitats are scattered throughout the waters off the coast of North Carolina 

(SAFMC 2009a). Approximately 109 square km or 1% of the shelf within NC-Site consists of live bottom 

habitats (Figure 7.7). Within the site are several patches of coral or live/hardbottom habitat. These 

hardbottom habitats are not characterized as coral communities because of their low diversity of coral 

species, but still harbor several species of coral. Furthermore, these rocky habitats provide substrates for 

many ascidians, hydroids, bryozoans, and sponges to attach. These organisms provide both food and 

refuge for a number of invertebrate and vertebrate species to survive. As a result, habitat areas of 

particular concern for commercial snapper and grouper fish species strongly overlap with these hard 

bottomed ecosystems. 
132 

7.3.1.2 Artificial Reefs

Artificial reefs are managed by the North Carolina Department of Environment and Natural Resources 

Division of Marine Fisheries. The goals of the artificial reef program are aimed at fishery and habitat 

conservation and improvement and fishing or diving recreation. Artificial reefs are scattered throughout 

the continental shelf bordering North Carolina’s coast and consist of many different materials (concrete, 

steel, old ships, etc.). Two mapped artificial reefs are located close to NC-Site and one mapped artificial 

reef lies within it. All three of these artificial reefs are a combination of sunken ships or sunken ships and 

concrete pipes. 

7.3.1.3 Marine Soft Bottom Habitats

A majority of the benthic habitat in North Carolina’s coastal waters is marine soft bottom habitat. NC-Site 

is almost entirely soft bottom habitat with small patches of hardbottom habitat as mentioned earlier. The 

physical structure of marine soft bottom habitat is characterized by sandy sediments. This habitat is 

extensive off the coast of North Carolina and harbors many species of benthic invertebrates. The 

invertebrate community is dominated by species tolerant of disturbance as storms over the continental 

shelf have the ability to disturb the soft bottom substrate in waters as deep as 35 m. These invertebrates 

are also an important prey item for many fish species. 

7.3.1.4 Sargassum Habitat

Sargassum habitat is built by two species of floating brown algae (Sargassum natans and S. fluitans). 

These brown algae float near the surface of the water and provide a substrate where many other 

organisms live and take refuge. It is estimated that at least 145 species of invertebrates, 100 species of 

fish, four species of sea turtles, and many marine birds all use floating sargassum habitat (SAFMC 

2009a). Sargassum is considered essential fish habitat for the snapper-grouper complex according to the 

SAFMC. The presence of sargassum is likely in the waters off the coast of North Carolina. Because it is 

transient (floating habitat that moves based on ocean currents and winds), it is hard to determine how 

much sargassum habitat would be in the candidate site at the time of any offshore renewable energy 

development activities. 

7.3.1.5 Marine Water Column

The continental shelf off the coast of North Carolina extends for just 51.5 km from Cape Hatteras to as 

many as 128.7 km off the coast near Wilmington, North Carolina. Along this shelf three major zones 

(inner-, mid- and outer- shelf habitats) can be identified, based on the water column depth and the sources 

of water feeding that environment. The Gulf Stream dominates the outer shelf (40 to 75 m deep) habitat 

with only minor effects from winds and tides. Water column mixing by the Gulf Stream, winds and tides 

equally contribute to the characterization of the mid-shelf habitat (20 to 40 m deep). The inner shelf water 

column (0 to 20 m deep) habitat is primarily influenced by freshwater runoff, tides, wind and bottom 

friction. NC-Site off the coast of North Carolina spans both the mid-shelf and outer shelf habitat depths. 

However, the majority of the NC-Site corresponds to the mid-shelf habitat depth range and is the most 

characteristic of the site.
133 

Figure 7.7. NC-Site essential fish habitats. 

Essential fish habitats (EFH), characterized by benthic habitat 

types, at NC-Site. 
134 

7.3.2 Georgia Site

Marine offshore systems encompass a diversity of habitats off the coast of Georgia. Either benthic or 

pelagic in nature, these habitats vary both laterally and longitudinally with distance from shore. The 

benthic habitats found off the Georgia coast are categorized into three major groups: 

1. Coral, coral reefs and live/hardbottom habitat

2. Artificial reefs

3. Marine soft bottom habitat 

Pelagic habitats found in coastal Georgia waters are primarily categorized as Marine Water Column or 

sargassum habitat. 

7.3.2.1 Coral, Coral Reefs, and Live/Hardbottom Habitat

Coral and hardbottom habitats (live bottom) are sparsely scattered throughout the waters off the coast of 

Georgia (SAFMC 2009a). Areas of these habitats are predominantly hardbottom with a low diversity and 

abundance of coral species. It is estimated that only 5% of the continental shelf off the coast of Georgia 

consists of these live bottom habitats. The patches of live bottom are found in waters of approximately 10 

m in depth, or greater, which corresponds to waters outside of the three-nautical-mile state jurisdictional 

limit. 

There are no identified patches of coral or live/hardbottom habitat with the boundaries of GA-Site but 

there are mapped coral and/or live/hardbottom habitats at similar depths along the Georgia coastline 

(Figure 7.8). These patches constitute less than 5% of the benthic habitat within the candidate site. 

Furthermore, these rocky habitats provide substrates for many ascidians, hydroids, bryozoans and sponges 

to attach. These organisms provide both food and refuge for a number of invertebrate and vertebrate 

species to survive, including fish species of commercial importance. Mapped locations of federallydesignated Habitat Areas of Particular Concern for commercial snapper and grouper fish species strongly 

overlap with these hard bottomed ecosystems. 

7.3.2.2 Artificial Reefs

Twenty-three artificial reefs exist off the coast of Georgia (GADNR 2011). Two artificial reefs are 

located close to the GA-Site. One artificial reef (Reef ID: KC), lying 9 to 16.6 km southeast of Wassaw 

Island, Georgia, is within 5 km of the southwestern corner of GA-Site. It was created mostly of vessel 

hulks and concrete pipes. A second artificial reef is located 6 km to the northwest of GA-Site. This reef 

comprises concrete pipes and barge hulks and lies 11.1 km southeast of Tybee Island, Georgia (Reef ID: 

SAV). These artificial reefs are managed by the Georgia Department of Natural Resources Coastal 

Resources Division. The goals of the artificial reef program are aimed at fishery and habitat conservation, 

fishing recreation, and economic growth for coastal communities. 

7.3.2.3 Marine Soft Bottom Habitats

The physical structure of marine soft bottom habitat is dynamic in nature and is characterized by sandy 

sediments. This habitat type is extensive off the coast of Georgia and harbors many species of benthic 

invertebrates. The invertebrate community is dominated by species groups such as polychaetes and 

amphipods tolerant of disturbance as storms over the continental shelf have the ability to disturb the soft 

bottom substrate in waters as deep as 35 m. These invertebrates are also an important prey item for many 

fish species including the tomtate (Haemulon aurolineatum), whitebone porgy (Calamus leucosteus), 

cubbyu (Equetus umbrosus), black sea bass (Centropristis striata), and scup (Stenotomus chrysops) 

(Lindquist et al. 1994). 
135 

The greater proportion of the benthic habitat in Georgia’s coastal waters is marine soft bottom habitat. 

However, there is an area approximately three miles east of Tybee and Little Tybee Island where the 

benthic habitat comprises gravelly-sand. GA-Site is almost entirely over soft bottom habitat (with the 

exception of the two hardbottom habitat patches mentioned earlier). 

7.3.2.4 Sargassum Habitat

Sargassum habitat is built by two species of floating brown algae (Sargassum natans and S. fluitans). 

These brown algae float near the surface of the water and provide a substrate for many other organisms to 

live, rest, and take refuge. It is estimated that at least 145 species of invertebrates, 100 species of fish, four 

species of sea turtles, and many marine birds all use floating sargassum habitat (South Atlantic Fishery 

Management Council 2009a). Sargassum is considered essential fish habitat for the snapper/grouper 

complex, according to the SAFMC. The presence of sargassum is likely in the waters off the coast of 

Georgia. Because it is transient (floating habitat that moves based on ocean currents and winds) , it is hard 

to determine how much sargassum habitat is associated with the waters in and around GA-Site. 

7.3.2.5 Marine Water Column

The continental shelf off the coast of Georgia extends 120 km to the east. Along this shelf three major 

zones can be identified based on the water column depth and the sources of water feeding that 

environment. The Gulf Stream dominates the outer shelf (40 to 75 m deep) habitat with only minor effects 

from winds and tides. Water column mixing by the Gulf Stream, winds and tides equally contribute to the 

characterization of the mid-shelf habitat (20 to 40 m deep). The inner shelf water column (0 to 20 m deep) 

habitat is primarily influenced by freshwater runoff, tides, wind, and bottom friction. Because GA-Site is 

located off the coast of Georgia and reaches only 17 m in depth, it is predicted that it comprises inner 

shelf water column habitat. 
136 

Figure 7.8. GA-Site essential fish habitat. 

Essential fish habitats (EFH), characterized by benthic habitat 

types, at GA-Site. 
137 

7.4 MARINE VERTEBRATE SPECIES’ USE OF THE SITES

This Chapter provides the results of the assessment of marine vertebrate species’ use of the two candidate 

sites. For the Georgia and North Carolina sites, population, ecological, and management information for 

fish and fisheries, marine mammals and sea turtles was reviewed. No sources of information reviewed 

contained marine species data at the site-level. Data included in this assessment describe species 

population and habitat association at much larger scales. However, the available data does allow room for 

inferences about species composition with the site boundaries and relative abundance based on factors, 

such as time of year, as discussed below.

7.4.1 Fish and Fisheries

A number of fish species’ ranges encompass both NC-Site and GA-Site (Table 7.1); these species could 

be influenced by sound-producing activities within either site. The list of fishes in Table 7.1 does not 

represent the community of fish species at both sites, but is simply a list of potential fishes that, given 

their population ranges, could be encountered at either site. Table 7.1 is a very liberal description of 

potential species using each site. Many of these species are seasonal or pelagic migrants, or both, of the 

SAB and would likely be present for only short durations throughout the year. Furthermore, many of 

these fish have specific habitat requirements or preferences. These preferences can be both structural and 

temporal. Though the unique habitat of a given species might not be within each candidate site, if the 

potential for this species to move through a site exists, it was still included in this list of fishes. The true 

fish community regularly using each candidate site is likely a small subset of species from the list in 

Table 7.1. A shortage of data restricts the evaluation of fish density within each site and so inhibits any 

discussion of fisheries impacts from anthropogenic activity at either site.

7.4.1.1 Essential Fish Habitat

Essential Fish Habitat (EFH) judged to be particularly important to the long-term productivity of 

populations of one or more managed species, or to be particularly vulnerable to degradation, is often 

identified as “habitat areas of particular concern” (HAPC) to help provide additional focus for 

conservation efforts. Figures 7.7 and 7.8 illustrate documented EFH and HAPC with respect to the 

locations of NC-Site and GA-Site. The general vicinity of the two sites includes EFH and HAPC for 

shrimp; snapper and grouper; spiny lobster; coral, coral reef, live or hard bottom; coastal pelagic species.
138 

Table 7.1. List of fish species present in the South Atlantic Bight.

Group Family Genus Species Common Name Spawning 

Periodα

Juvenile 

Presenceα

Adult 

Presenceα

Abundance 

Dataβ

Grouper or 

Snapper

Balistidae Triggerfishes

Balistes capriscus Gray triggerfish

April–

Aug All Year All Year

vetula Queen triggerfish All Year All Year

Canthidermis sufflamen Ocean triggerfish All Year All Year All Year

Carangidae Jacks

Caranx bartholomaei Yellow jack Feb–Oct All Year All Year

crysos Blue runner Feb–Sept All Year All Year

hippos Crevalle jack All Year All Year

ruber Bar jack

Seriola dumerili

Greater 

amberjack Jan–June All Year All Year

fasciata Lesser amberjack

rivoliana Almaco jack All Year All Year

zonanta

Banded 

rudderfish All Year All Year

Eppiphidae Spadefishes

Chaetodipterus faber

Atlantic 

spadefish May–Sept All Year All Year

Haemulidae Grunts

anistotremus surinamensis Black margate*

Haemulon aurolineatum Tomtate

March–

July All Year All Year

flavolineatum French grunt*

plumieri White grunt

March–

Sept All Year
139 

Group Family Genus Species Common Name Spawning 

Periodα

Juvenile 

Presenceα

Adult 

Presenceα

Abundance 

Dataβ

Labridae Wrasses

Halichoeres radiatus Puddingwife All Year All Year

Lachnolaimus maximus Hogfish

Sept–

April All Year All Year

Lutjanidae Snappers

Apsilus dentatus Black snapper*

Etelis oculatus Queen snapper

Lutjanus analis Mutton snapper All Year

apodus Schoolmaster All Year All Year

buccanella Blackfin snapper All Year

campechanus Red snapper May–Oct All Year All Year

cyanopterus Cubera snapper*

griseus

Gray (mangrove) 

snapper

jocu Dog snapper

mahogoni

Mahogany 

snapper

synagris Lane snapper All Year

vivanus Silk Snapper

Ocyurus chrysurus

Yellowtail 

snapper Summer YES

Rhomboplites aurorubens

Vermilion 

snapper

April–

Sept All Year All Year YES

Malacanthida

e Tilefishes

Caulolatilus microps Blueline tilefish Feb–Oct All Year All Year

Lopholatilus chamaeleonticeps Golden tilefish

Malacanthus plumieri Sand tilefish All Year

Polyprionidae Polyprion americanus Wreckfish
140 

Group Family Genus Species Common Name Spawning 

Periodα

Juvenile 

Presenceα

Adult 

Presenceα

Abundance 

Dataβ

Serranidae

Sea basses and 

grouper

Centropristis ocyurus Bank sea bass Jan–April All Year

philadelphica Rock sea bass

striata Black sea bass

March–

July All Year All Year YES

Cephalopholis cruentata Graysby

Epinephelus adcensionis Rock hind*

drummondhayi Speckled hind All Year All Year

guttatus Red hind

morio Red grouper Feb–June NA** All Year

nigritus Warsaw grouper All Year

niveatus Snowy grouper YES

Mycteroperca bonaci Black grouper*

interstitialis

Yellowmouth 

grouper

microlepis Gag NA**

Sept to 

Oct All Year YES

phenax Scamp†

Feb to 

July NA** All Year

venenosa

Yellowfin 

grouper‡

Sparidae Porgies

Archosargus probatocephalus Sheepshead*

Calamus bajonado Jolthead porgy All Year All Year

calamus Saucereye porgy All Year

leucosteus Whitebone porgy

April–

Aug All Year All Year

nodosus Knobbed porgy

March–

July All Year All Year

pagrus Red porgy Dec–May All Year All Year YES
141 

Group Family Genus Species Common Name Spawning 

Periodα

Juvenile 

Presenceα

Adult 

Presenceα

Abundance 

Dataβ

Pagrus caprinus Longspine porgy All Year

Stenotomus chrysops Scup

Migratory 

Pelagics and 

Other 

Managed 

Fishes

Acipenseridae Sturgeons

Acipenser brevirostrum

Shortnose 

Sturgeon YES

oxyrinchus Atlantic sturgeon NA** NA** All Year YES

Anguillidae Anguilla rostrata American eel YES

Clupeidae Herring

Alosa aestivalis Blueback herring YES

mediocris Hickory shad YES

pseudohargengus Alewife* YES

sapidissima American shad YES

Brevoortia smithi

Yellowfin 

menhaden YES

tyrannus

Atlantic 

menhaden YES

Istiophoridae Marlins

Istiophorus platypterus Sailfish YES

Makaira migricans Blue marlin YES

Tetrapturus albidus White marlin YES

pfluegeri

Longbill 

spearfish YES

Moronidae Morone saxatilis Striped bass NA** All Year YES
142 

Group Family Genus Species Common Name Spawning 

Periodα

Juvenile 

Presenceα

Adult 

Presenceα

Abundance 

Dataβ

Pomatomidae Pomatomus saltatrix Bluefish

March–

June

NovMarch All Year YES

Paralichthyidae Paralichthys dentatus Summer flounder

Oct–

March NA** All Year YES

Pristidae Pristis pectinata

Smalltooth 

sawfish YES

Sciaenidae

Drums and 

croakers

Cynoscion regalis Weakfish* YES

Leiostomus xanthurus Spot

Oct–

March NA**

Oct–

March YES

Micropogonias undulatus Atlantic croaker Aug–Nov NA** All Year YES

Sciaenops ocellatus Red drum Aug–Oct NA**

Dec–

April YES

Scombridae

Tunas and 

mackerels

Acanthocybium solandri Wahoo

Scomberomous cavalla King mackerel YES

maculatus Spanish mackerel YES

regalis Cero mackerel

Euthynnus alleterattus Little tunny

Rachycentron canadum Cobia

Thunnus alalunga

Atlantic albacore 

tuna YES

albacares

Atlantic 

yellowfin tuna* YES

obesus

Atlantic bigeye 

tuna YES
143 

Group Family Genus Species Common Name Spawning 

Periodα

Juvenile 

Presenceα

Adult 

Presenceα

Abundance 

Dataβ

pelamis

Atlantic skipjack 

tuna YES

thynnus

Atlantic bluefin 

tuna YES

Xiphiidae Swordfishes

Xiphias gladius

Atlantic 

swordfish YES α Spawning Period, Juvenile, and Adult Presence information is given for species likely present in the Candidate site only. Blank cells indicate a 

lack of data for species that have presence information in other categories.

β Blank cells indicate the availability of abundance data is “unknown,” rather than abundance data are “not available.”

*Species may not be found in either NC or GA waters because distribution boundary is ambiguous.

** NA indicates that lifestage is not present in the candidate site due to habitat restrictions.

† Species likely found in NC, but not in GA.

‡ Species likely found in GA, but not in NC.
145 

7.4.2 Marine Mammals

Several species of marine mammals have the potential to occur in the SAB (Table 7.2); however, only 

some of these species are likely to occur within the boundaries of GA-Site or NC-Site. The relatively 

shallow water and lack of developed feeding habitat decrease the likelihood that many of the marine 

mammals known to occur in the SAB would be found with regularity in the candidate site. 

The marine mammals listed as “rare species” in the SAB (Table 7.2) consist of ten species that are rarely 

seen in the SAB (SAFMC 2009a) and therefore are also unlikely to occur within GA-Site or NC-Site. 

Seven of these species (false killer whale, pygmy killer whale, killer whale, melon-headed whale, roughtoothed dolphin, Fraser’s dolphin, and spinner dolphin) either occur in low numbers naturally, or occur in 

the waters adjacent to the SAB (such as the Gulf of Mexico or waters off the northeastern U.S.), and 

either occasionally or never appear in the SAB (SAFMC 2009a). The harbor porpoise and spinner dolphin 

may occur in the SAB when they travel to the southernmost portions of their ranges; however, sightings 

of these species are much more common north of Cape Hatteras, North Carolina or in deeper waters than 

found at NC-Site or GA-Site (Waring et al. 2007; Waring et al. 2010). Cuvier’s beaked whale could 

potentially occur in the SAB; however, little is known about its distribution (South Atlantic Fishery 

Management Council 2009a). As a result, it is unlikely that these species would occur in the vicinity of 

GA-Site or NC-Site and no further assessment of these species was conducted. 

The marine mammals listed as “occasional or offshore species” in the SAB in Table 7.2 consist of 12 

species whose range includes the northern portions of the SAB (north of Cape Hatteras, North Carolina). 

When these species occur in the SAB, they are generally found at or beyond the continental shelf (≥ 200 

m) (South Atlantic Fishery Management Council 2009a), well outside the boundaries of GA-Site or NCSite. Because these species tend to occur north of and in much deeper offshore waters than the two 

candidate sites, they are not likely to occur in the vicinity of NC-Site or GA-Site, and no further 

assessment of these species was conducted. 

Eleven of the marine mammals listed in Table 7.2 are considered “common” in the SAB; however, only 

five of these species (humpback whale, Northern right whale, West Indian manatee, bottlenose dolphin 

[coastal stock] and Atlantic spotted dolphin) have a high probability of occurring within the two candidate

sites. The bottlenose dolphin, the Atlantic spotted dolphin, and the humpback whale have the potential to 

occur in the vicinity of the candidate sites year-round; the Northern right whale and the West Indian 

manatee use the southeast Atlantic during portions of the year. A brief summary of the distribution and 

estimated population size for the five marine mammal species that have a higher probability of occurring 

in the vicinity of GA-Site and NC-Site is included below.

Humpback Whale

In the western North Atlantic Ocean, most humpbacks winter in the West Indies, where they mate and 

calve. These whales then migrate to summer feeding grounds from the Gulf of Maine to Iceland. 

However, a notable number of humpbacks do not undertake this extensive seasonal migration but instead 

overwinter in mid- and high latitude regions (Clapham et al. 1993 and Swingle et al. 1993 cited in 

SCDNR 2006a). There have been increased sightings of this species off the U.S. mid-Atlantic and 

southeastern states since the mid-1980s (Wingle et al. 1993 and Wiley et al. 1995 cited in SCNDR 

2006a). Historical records do contain sightings within the study areas (Figure 7.9). In this region, 

sightings have been reported in all seasons but are more predominant from January to March (Barco et al. 

2001 cited in SCDNR 2006a). Therefore, although humpbacks have the possibility of occurring off the 

coast of Georgia or North Carolina year-round, they are most likely to be present between January and 

March. The humpback whale is considered a pelagic and coastal species. They are typically encountered 

over shallow banks and in shelf waters while feeding or breeding but may traverse open waters during 
146 

migration (SCNDR 2006a). The best available estimate of the population size for the North Atlantic 

population of the humpback whale is 11,570 humpback whales (Waring et al. 2010). 

Table 7.2. Marine mammal species that may occur in the South Atlantic Bight.

(*) ESA-listed species; (**) The U.S. Fish and Wildlife Service have ESA jurisdiction for manatees.

Common Name Scientific Name Relative Abundance re: 

Project Sites

Rare Species

False killer whale Pseudorca crassidens Rare

Pygmy killer whale Feresa attenuate Rare

Cuvier's beaked whale Ziphius cavirostris Rare

Killer whale Orcinus orca Rare

Harbor porpoise Phocoena phocoena Rare

Melon-headed whale Peponocephala electra Rare

Rough-toothed dolphin Steno bredanensis Rare

Fraser’s dolphin Lagenodelphis hosei Rare

Spinner dolphin Stenella longirostris Rare

Striped dolphin Stenella coeruleoalba Rare

Occasional/Offshore Species

Dwarf sperm whale Kogia sima Rare

Pygmy sperm whale Kogia breviceps Rare

Long-finned pilot whale Globicephala melas Rare

Short-finned pilot whale Globicephala macrorhynchus Rare

Risso’s dolphin Grampus griseus Rare

Common dolphin Delphinus delphis Rare

True's beaked whale Mesoplodon mirus Rare

Gervais' beaked whale Mesoplodon europaeus Rare

Blainville’s beaked whale Mesoplodon densirostris Rare

Sowerby’s beaked whale Mesoplodon bidens Rare

Pantropical spotted dolphin Stenella attenuata Rare

Clymene dolphin Stenella clymene Rare

Common/ESA Protected Species

Blue whale* Balaenoptera musculus Rare

Fin whale* Balaenoptera physalus Rare

Humpback whale* Megaptera novaeangliae Common (winter). May 

occur year-round.

Northern right whale* Eubalaena glacialis Common (winter). May 

occur year-round.

Sei whale* Balaenoptera borealis Rare

Sperm whale* Physeter macrocephalus Rare 

West Indian manatee (Florida stock)** Trichechus manatus latirostris Frequent (summer)

Atlantic spotted dolphin Stenella frontalis Common (year-round)

Bottlenose dolphin (Coastal stock) Tursiops truncatus Common (year-round)

Bottlenose dolphin (Offshore stock) Tursiops truncatus Unlikely

Minke whale Balaenoptera acutorostrata Limited information 

available
147 

Figure 7.9. Sightings of fin, humpback, and right whales. 

Sightings of fin, humpback, and right whales in relation to the wind 

planning areas. 
148 

North Atlantic Right Whale 

North Atlantic right whales in the western North Atlantic range from winter calving and nursery areas off 

the southeastern U.S. to summer feeding grounds off New England and north to the Bay of Fundy and 

Scotian Shelf (SCDNR 2006b). Other than calving females and a few juveniles that winter off the coasts 

of Georgia and Florida, the wintering location of the remaining individuals in the population is unknown. 

In October, a portion of the population, mostly pregnant females, migrates southward to waters off 

southern Georgia and northern Florida to calve. Currently, the southeastern U.S. is the only known 

calving ground for the western North Atlantic right whale (SCDNR 2006b). Historical records do contain 

many sightings of right whales in the study areas (Figure 7.9). One of the important habitat areas for right 

whales is found off of southern Georgia and north Florida in nearshore waters. This area serves as a 

nursery ground and is characterized by large shallow embayments that provide safe areas for females to 

calve in the winter (SCDNR 2006b). Calving occurs from December through March in the known 

wintering area that is located along the southeastern U.S. coast (SAFMC 2009a). NMFS has designated 

five critical habitats for the North Atlantic Right Whale. One of these habitats, the Southeast Atlantic 

Critical Habitat is approximately 60 miles south of GA-Site and 500 miles south of NC-Site (Figure 

7.10). Neither of the candidate sites is located within any of the NMFS identified critical habitats. 

The population size of the North Atlantic right whale is at a critical level with an estimated population 

size of 400 animals or less remaining in western North Atlantic waters (SCDNR 2006b). According to 

Waring et al. (2010), a review of the photo-ID recapture database as of June 24, 2009 indicated that 361 

individually recognized whales in the catalog were known to be alive during 2005. This number 

represents a minimum population size (Waring et al. 2010). 
149 

Figure 7.10. Right whale critical habitat.

Right whale critical habitat in relation to NC-Site and GA-Site. 
150 

West Indian Manatee 

The West Indian manatee (Florida stock) is found throughout the southeastern U.S. and is the stock that 

has the potential to occur in the vicinity of the proposed candidate sites. These manatees do not tolerate 

cold well and are generally restricted to the inland and coastal waters of peninsular Florida during the 

winter where they shelter in or near (or both) warm-water springs, industrial effluents, and other warm 

water sites. In warmer months, manatees leave these sites and can travel great distances. Individuals have 

been sighted as far north as Massachusetts, as far west as Texas, and in all states in between. Warm 

weather sightings are most common in Florida and coastal Georgia (Waring et al. 2009). 

The best available count of the Florida stock of West Indian manatees is 3,802 animals, based on a single 

synoptic survey of warm-water refuges in January 2009 (Waring et al. 2009). This is not a complete count 

because it does not include the number of manatees located away from the wintering sites on the day of 

the count. 

Bottlenose Dolphin (Coastal Stock) 

The Southern Migratory stock of the bottlenose dolphin is defined primarily on satellite tag telemetry 

studies and is thought to migrate south from waters of southern Virginia and north central North Carolina 

to waters south of Cape Fear and as far south as coastal Florida during winter months. During summer 

months when the Southern Migratory stock is found in waters north of Cape Fear, North Carolina, 

bottlenose dolphins are still seen in coastal waters of South Carolina, Georgia, and Florida, which 

indicates the presence of additional stocks of coastal animals (Waring et al. 2010). 

The best population estimate for the South Carolina-Georgia Coastal stock of bottlenose dolphins is 7,738 

as reported in Waring et al. (2010). Most survey effort to date has been concentrated in waters shallower 

than 20 m deep (Waring et al. 2010). The coastal ecotype prefers waters less than 30 m in depth and is 

adapted for warm, shallow waters (SCDNR 2006c). Because GA-Site occurs in waters from 13 to 15 m in 

depth and NC-Site occurs in waters from 30 to 40 m in depth, it is assumed that the coastal stock of 

bottlenose dolphins would be the likely stock to occur in each of the candidate sites.

Atlantic Spotted Dolphin

Atlantic spotted dolphins regularly occur in the inshore waters south of Chesapeake Bay and near the 

continental shelf edge and continental slope waters north of this region (Waring et al. 2007). The best 

recent abundance estimate for Atlantic spotted dolphins according to Waring et al. (2007) is 50,978 (the 

sum of the estimates from the two 2004 western U.S. Atlantic surveys). Another survey of the U.S. 

Atlantic Outer Continental Shelf and continental slope (water depths >50 m) was conducted during June 

through August 2004, where the abundance estimate for this species between Florida and Maryland was 

47,400 during this survey (Waring et al. 2007). 

7.4.3 Sea Turtles

Five species of sea turtles occur in the SAB. These species are the green turtle (Chelonia mydas), Kemp’s 

Ridley turtle (Lepidochelys kempii), leatherback turtle (Dermochelys coriacea), loggerhead turtle (Caretta 

caretta) and, rarely, the hawksbill turtle (Eretmochelys imbricate) (SAFMC 2011a). All of these species 

are either listed as endangered or threatened under the Endangered Species Act.

Green Sea Turtle

Green sea turtles are listed as threatened in U.S. waters except for the Florida breeding population, which 

is listed as endangered. However, because it is not possible to distinguish between the populations away 

from nesting beaches, green sea turtles are considered endangered wherever they occur in U.S. waters 

(SAFMC2011b). In the U.S., the primary nesting area is located along the eastern coast of Florida; 
151 

nesting occurs from June through early October (SAFMC 2011b). According to SAFMC (2011b), green 

turtle nests have also been recorded on both North and South Carolina beaches. 

The Sea Turtle Nest Monitoring System managed by Seaturtle.org reported that three green sea turtle 

nests were recorded on Georgia beaches in 2011 and six green sea turtle nests were recorded on Georgia 

beaches in 2010. Zero nests were observed in 2009 and no data are available for years prior to 2009 for 

Georgia beaches (Seaturtle.org 2011a). For North Carolina beaches, the Sea Turtle Nest Monitoring 

System reported that 15 green sea turtles nests were recorded in 2011, 18 in 2010, three were reported in 

2009, and zero were reported in 2008. No data are available for years before 2008 for North Carolina 

beaches (Seaturtle.org 2011b). Although some nests have been recorded on Georgia and North Carolina 

beaches, the primary nesting in the continental U.S. is on the east coast of Florida. No critical habitat has 

been designated by NOAA Protected Resources for the green turtle in the continental U.S. The NOAAdesignated critical habitat for the green turtle are the coastal waters surrounding Culebra Island, Puerto 

Rico (NOAA Fisheries Office of Protected Resources 2011a). 

Green turtles are reported to be found in fairly shallow waters (except when migrating) and are attracted 

to lagoons and shoals with high densities of marine grass and algae. Adults migrate between nesting and 

foraging habitats along corridors adjacent to coastlines and reefs (SAFMC 2011b). Because sea grasses 

are not abundant in the coastal waters of Georgia or North Carolina near NC-Site or GA-Site, these areas 

are not likely to be a high concentration area for green turtles. Green turtles would occur in higher 

abundance south of the site in nearshore coastal waters of eastern Florida.

Hawksbill Sea Turtle

Hawksbill sea turtles are listed as endangered under the Endangered Species Act. These turtles are the 

most tropical of the marine turtles and typically range from 30o

N to 30oS, well south of the two candidate 

sites. Although hawksbills are found primarily in Florida and Texas within the continental U.S., they have 

been recorded in all the Gulf States and along the east coast as far north as Massachusetts (NOAA 

Fisheries Office of Protected Resources 2011b). 

Zero hawksbill nests were reported on Georgia and North Carolina beaches from 2009 to 2011 by The 

Sea Turtle Nest Monitoring System managed by Seaturtle.org (Seaturtle.org 2011a; Seaturtle.org 2011b). 

No critical habitat has been designated by NOAA Protected Resources for the hawksbill turtle in the 

continental U.S. The NOAA-designated critical habitat for the hawksbill turtle are the coastal waters 

surrounding Mona and Monito Islands, Puerto Rico (NOAA Fisheries Office of Protected Resources 

2011a). 

Given the habitat and distribution characteristics of the hawksbill turtle, it is unlikely that hawksbills 

would be found with any frequency in the vicinity of the two candidate sites. There is the potential for 

some hawksbill sea turtles to be found in waters offshore of the two sites on a transient basis, but most 

likely in small numbers.

Kemp’s Ridley Sea Turtle

Kemp’s ridley sea turtles are listed as Endangered under the Endangered Species Act throughout their 

range (NOAA Fisheries Office of Protected Resources 2011c). Kemp’s ridley turtles range from the Gulf 

coasts of Mexico and the U.S.to the Atlantic coast of North America as far north as Nova Scotia and 

Newfoundland (USFWS 2011a). Aside from nesting habitat, the major habitat for these turtles is the 

nearshore and inshore waters of northern Gulf of Mexico, especially Louisiana waters. They are often 

found in salt marsh habitats (USFWS 2011a). 
152 

The primary nesting beaches for Kemp’s ridley turtles are along a beach called Rancho Nuevo in 

Tamaulipas, Mexico; however, according to SAFMC (2011c), nests have also been recorded in Florida 

and the Carolinas in recent years. Nesting occurs from April to June. During this time, Kemp’s ridleys

appear off the Tamaulipas and Veracruz coasts of Mexico (USFWS 2011a). After leaving the nesting 

beach, hatchlings are believed to become entrained in eddies within the Gulf of Mexico and are then

dispersed within the Gulf and Atlantic by oceanic surface currents. After they reach about 20 cm in 

length, they enter coastal shallow water habitats (USFWS 2011a). According to SAFMC (2011c), posthatchlings appear to inhabit pelagic waters of the Gulf and North Atlantic for 1–4 years where they feed 

on sargassum and associated fauna. They are then reported to move into shallow, nearshore waters after 

one or two years (SAFMC 2011c). 

SAFMC (2011a) reports that the nearshore waters of both the Gulf and Atlantic provide important habitat 

for juvenile Kemp’s ridleys. According to capture records from NOAA Fisheries sea turtle trawling 

research projects in the Southeast, juvenile Kemp’s ridleys may overwinter near Cape Canaveral, Florida. 

The juveniles then move northward along the Atlantic coast as sea temperatures increase and have been 

found foraging as far north as the New England. In the fall, as sea temperatures begin to cool, these turtles 

will then migrate southward. These seasonal movements up and down the coast may continue until they 

reach sexual maturity when most are assumed to return to the Gulf of Mexico to breed (South Atlantic 

Fishery Management Council 2011c). 

Zero Kemp’s ridley nests were reported on Georgia beaches from 2009 to 2011 by The Sea Turtle Nest 

Monitoring System managed by Seaturtle.org (SeaTurtle.org 2011b). This same monitoring system 

reported that two Kemp’s ridley nests were recorded in 2010 on North Carolina beaches. Zero Kemp’s 

ridley nests were reported on North Carolina beaches in 2008, 2009, and 2011 (SeaTurtle.org 2011b). 

Currently there is no critical habitat designated by NOAA Protected Resources for the Kemp’s ridley 

turtle in the continental U.S.; however, in February 2010, NOAA Fisheries and USFWS were jointly 

petitioned to designate critical habitat for Kemp’s ridley sea turtles for nesting beaches along the Texas 

coast and marine habitats in the Gulf of Mexico and Atlantic Ocean. The petitioned habitats do not 

include Georgia or North Carolina beaches or coastal waters (NOAA Fisheries Office of Protected 

Resources 2011c). 

Given the habitat preferences and nesting areas for Kemp’s ridley sea turtles, they are not likely to be 

found in the vicinity of GA-Site or NC-Site except during migration up and down the coast to and from 

foraging and nesting sites. 

Leatherback Sea Turtle

Leatherback sea turtles are listed as Endangered under the Endangered Species Act throughout their range 

(NOAA Fisheries Office of Protected Resources 2011d). Leatherbacks are distributed worldwide in 

tropical and temperate waters of the Atlantic, Pacific and Indian Oceans. In the U.S. and its territories, 

small nesting populations occur on the east coast of Florida, Sandy Point in the U.S. Virgin Islands, and 

in Puerto Rico. Leatherback nesting activity has also been reported on the beaches of Georgia and the 

Carolinas; North Carolina is the northernmost state on the east coast with confirmed nesting (SAFMC 

2011d). The Sea Turtle Nest Monitoring System reported that 11, four, and seven leatherback sea turtle 

nests were recorded on Georgia beaches in 2011, 2010, and 2009, respectively. No data are available for 

years before 2009 (SeaTurtle.org 2011a). This same monitoring system reported that two leatherback 

nests were recorded in 2010 and one in 2009 on North Carolina beaches. Zero leatherback nests were 

reported on North Carolina beaches in 2008 and 2011 (SeaTurtle.org 2011b). Nesting areas required by 

adult females have sandy beaches backed with vegetation and sloped so the crawl to dry sand is not too 

far. Preferred beaches have proximity to deep water and generally rough seas (USFWS 2011b). 
153 

Although some nests (very low numbers) have been recorded on Georgia and North Carolina beaches, the 

primary nesting in the U.S. occurs in the U.S. Caribbean (Puerto Rico and the U.S. Virgin Islands) and 

southeast Florida. These areas, far south of the two candidate sites, represent the most significant nesting 

activity within the U.S. (NOAA Fisheries Office of Protected Resources 2011d). No critical habitat has 

been designated by NOAA Protected Resources for the leatherback sea turtle in the continental U.S. The 

NOAA designated critical habitat for the leatherback is the coastal waters adjacent to Sandy Point, St. 

Croix, U.S. Virgin Islands (NOAA Fisheries Office of Protected Resources 2011a). 

In the U.S., nesting occurs from about March to July (USFWS 2011b). SAFMC (2011d) reports that the 

main nesting area for leatherbacks in the continental U.S. is the eastern coast of Florida, where 

leatherbacks begin nesting as early as late February and continue into August and early September. Very 

little is known about the pelagic habits of hatchlings and smaller juveniles because aerial surveys are 

limited to observations of larger individuals. When hatchlings leave the nesting beaches, they move 

offshore but have not been documented to associate with rafts of sargassum, as are other species. 

Eventually they use both coastal and pelagic waters. Large juveniles and adults from the southeastern 

coast appear to move to the mid-Atlantic in the spring with individuals continuing further north to 

Canadian waters in the summer. During the fall and winter, leatherbacks travel southward or perhaps 

further offshore (South Atlantic Fishery Management Council 2011d). 

Leatherback sea turtles are the most pelagic of the sea turtles and thus may have a greater chance of

occurring in the waters surrounding the two candidate sites. They could be present in the vicinity of GASite and NC-Site during migration periods, for foraging, and in small numbers for nesting on Georgia or 

North Carolina beaches. 

Loggerhead Sea Turtle 

Loggerhead sea turtles are listed as Endangered under the Endangered Species Act (NOAA Fisheries 

Office of Protected Resources 2011e). Loggerheads are considered the most abundant species of sea turtle 

occurring off U.S. shores (SAFMC 2011e). Aerial surveys indicate that 90% of U.S. loggerhead nesting 

occurs in Florida, 6% in South Carolina, 2% in Georgia and 2% in North Carolina (SAFMC 2011e). The 

Sea Turtle Nest Monitoring System reported that 1,975, 1,760, and 998 loggerhead sea turtle nests were 

recorded on Georgia beaches in 2011, 2010, and 2009, respectively (SeaTurtle.org 2011a). This same 

monitoring system reported that 930, 847, and 290 loggerhead sea turtle nests were recorded on North 

Carolina beaches in 2011, 2010 and 2009, respectively (SeaTurtle.org 2011b). Loggerhead nests are by 

far the dominant nests found on Georgia and North Carolina beaches as reported by Seaturtle.org (2011a; 

2011b). The nesting season in the U.S. is reported to extend from approximately May through August, 

with nesting primarily occurring at night (USFWS 2011c). In Florida, nesting is reported to occur from 

March to August and in North Carolina from mid-May to mid-August(SAFMC 2011e). No critical habitat 

has been designated by NOAA Protected Resources for the loggerhead sea turtle (NOAA Fisheries Office 

of Protected Resources 2011a). 

According to SAFMC (2011e), loggerheads spend their first 7 to 13 years in the pelagic environment until 

they reach a size of approximately 16–24 in (40–60 cm). After they reach that size, they move to 

nearshore and estuarine waters and live in benthic habitats where they feed primarily on invertebrates; 

however, it has been reported that some loggerheads may alternate between the pelagic and benthic 

environment. There is little data on the movements of immature loggerheads because it is hard to monitor

marine turtles before they return to their nesting beaches. Subadults were the most abundant turtles 

captured in trawl surveys conducted off east-central Florida; however, there was a shift to a larger size 

class during April to July as reproductively active adults arrived at the nesting beaches. During this time, 

immature loggerheads are thought to migrate to foraging grounds as far north as Chesapeake Bay. Adult 

loggerheads captured in trawl surveys declined by late summer, coinciding with the end of nesting season, 

whereas the presence of subadult loggerheads increased again with the approach of winter. Juvenile 
154 

feeding populations are known to occupy the Indian River in Florida, as well as harbors and sounds of 

Georgia and the Carolinas (SAFMC 2011e). 

The loggerhead is the sea turtle that is most likely to occur in the vicinity of GA-Site and NC-Site and is 

reported to be the most abundant based on nesting data compared to the other species of sea turtles. 

Loggerhead sea turtles are documented to use Georgia and North Carolina beaches for nesting in greater 

numbers than the other species and therefore are more likely to occur in greater numbers in the coastal 

waters and offshore waters of NC-Site and GA-Site.

7.4.4 Discussion

The two sites are located within the SAB, which is formed by the long, bending coastline of the United 

States from Cape Hatteras, North Carolina to approximately West Palm Beach, Florida. Despite its name, 

the SAB is a part of the western North Atlantic and is habitat to many of the marine vertebrates found 

both to the north and the south of the project study areas, including the Gulf of Mexico. The ecological 

characteristics of the SAB are influenced by many factors, including the relatively narrow (i.e., 40 to 140 

km wide) continental shelf and the ever-present northeasterly flow of the Gulf Stream. Unlike the waters 

north of Cape Hatteras, which are more diverse and dynamic because of the dramatic eastward deflection 

of the Gulf Stream, the SAB is generally considered less productive ecologically. Eighty percent of the 

SAB is soft bottom habitat (sand) and 20% live hard bottom habitat, which is made up of rock reefs 

covered by coral or algae. This habitat supports a wide range of resident fish species from the Lutjanidae 

and Serranidae families that are common to subtropical waters south of Cape Hatteras to the Gulf of 

Mexico.

The marine mammals that use the SAB can be generally categorized into two groupings: coastal, 

residential stocks and migratory stocks. The coastal grouping consists of the bottlenose dolphin and West 

Indian manatee. These species have defined coastal stocks along Georgia and Florida, respectively, and 

can occur in the areas of the two sites throughout the year, but are most commonly in the warmer months. 

In contrast, a wide range of migratory cetaceans, including North Atlantic right whale, fin whale, and 

humpback whale, pass through the SAB on a seasonal basis. Given that the two sites are in the relatively 

shallow waters of the inner and mid continental slope, most migratory cetaceans would be expected to 

pass to the east of these locations about 140 km from shore at the continental slope. The exception to this 

point is the North Atlantic right whale because of its use of coastal waters along Georgia as nursery 

habitat. Historical sightings data confirm that this species congregates in these waters on an annual basis 

and may occur with some regularity in the vicinity of the two sites making it one of, or the, most 

abundant marine mammal in the study area.

Sea turtles use the waters of the SAB including the nearshore marine environments associated with the 

two sites. Four species of sea turtles are known to occur in these waters with varying degrees of 

regularity: hawksbill, Kemp’s Ridley, leatherback, and loggerhead. Any of these species could pass 

through the two sites during migration. However, loggerheads are known to nest with relatively high 

density, compared to the other three turtle species, along the coastline from Florida to North Carolina. 

Although Kemp’s Ridley and leatherback turtles are also known to nest in this region, documented 

nestings are fewer than for the loggerhead turtle. These nesting species could pass through or in close 

proximity to the candidate sites, swimming to or from nesting sites along the shoreline. 
155 

8. SUMMARY AND CONCLUSIONS

This study was conducted for BOEM as a baseline biological study of focal marine vertebrate species at 

two wind planning areas in the U.S. Southeast Atlantic coast section of the Outer Continental Shelf 

(OCS). The wind planning areas are part of the Beaufort (block NI18-04; North Carolina) and Brunswick 

(block NH 17-02; Georgia) lease blocks, within Onslow Bay and the Georgia Bight, respectively. The 

study sites are herein referred to as the North Carolina and Georgia sites. These sites are coastal, shallow

water habitats that are home to range of fish species, marine mammals, turtles, and sub-tropical coral 

reefs that have varying degrees of protected status or fisheries importance. Because these sites are highly 

productive coastal ecosystems, in this study we performed a baseline survey for future research in the 

environmental impacts of offshore wind energy development. 

The Bioacoustics Research Program (BRP) at the Cornell University’s Laboratory of Ornithology, in 

collaboration with ESS Group, Inc. and Marine Acoustics, Inc. (MAI;), conducted an ecological 

characterization of the North Carolina and Georgia sites with the following approaches:

1. Evaluate the seasonal occurrence of North Atlantic right whales (Eubalaena glacialis), fin 

whales (Balaenoptera physalus), and humpback whales (Megaptera novaeangliae) as 

representative, protected marine mammal species, and baleen whales, to understand the 

environmental risks associated with their presence (BRP).

2. Evaluate the occurrence and spawning behavior of black drum (Pogonias cromis) and oyster 

toadfish (Opsanus tau) as representative fish species to understand these populations and 

evaluate the utility of these two species as ecological indicators of the ecosystems (BRP).

3. Characterize the ambient noise environment around the wind planning areas (BRP) and 

model the propagation of wind farm construction activities (MAI). 

4. Characterize the physical structure of the benthic habitats and associated flora and fauna 

(ESS).

To address the occurrence of marine mammals and fishes and the ambient noise conditions, acoustic data 

were collected using marine autonomous recording units (MARUs) (Calupca et al. 2000) at the North 

Carolina and Georgia sites. At both sites, three MARUs were deployed in a linear formation across the 

wind energy planning area. Acoustic data were recorded in two consecutive deployments of the MARUs 

at each site, from 12 June–10 November 2012 and 12 November 2012–15 April 2013 at the North 

Carolina site and 9 June–8 November 2012 and 10 November 2012–12 April 2013 at the Georgia site. A 

total of 307 consecutive days were recorded at each site, with the exception of 11 November 2012 in 

North Carolina and 9 November 2012 in Georgia, when MARUs were replaced for the following 

deployment. Sound data were sampled at 2 kHz with high-pass and low-pass filters set at 10 Hz and 800 

Hz, respectively.

8.1 OCCURRENCE OF BALEEN WHALES

We characterized the occurrence of North Atlantic right whales (Eubalaena glacialis), fin whales 

(Balaenoptera physalus), and humpback whales (Megaptera novaeangliae) at the North Carolina and 

Georgia sites. Contact calls, or up-calls, of right whales were detected with an automated detection 

algorithm (Urazghildiiev et al. 2009), and 20 Hz song notes of fin whales were also detected with an 

automated detection algorithm (Bioacoustics Research Program 2012). Daily presence of right whales and 

fin whales was determined by one or more species-specific calls detected in each site. Humpback whales 

were opportunistically identified during these analyses. 
156 

Right whales were detected throughout the study, with peak presence November–April, when whales 

have previously been described as migrating through the mid-Atlantic (Winn et al. 1986). As presence 

decreases in Georgia while increasing in North Carolina between January and March, this shift 

corresponds to the migration of right whales from the calving grounds to the feeding grounds in the 

northeast U.S. (Kenney et al. 2001). Surprisingly, a secondary peak of right whale presence occurred in 

June and July in the Georgia site, when right whales typically aggregate in the North Western Atlantic 

(Winn et al. 1986). Additionally, 14% of daily presence in North Carolina and nearly a third (29%) in 

Georgia occurred outside of the mid-Atlantic seasonal management area (November 1–April 30) (NOAA 

2008). These data suggest that right whales may occur in this region more often than previously 

documented. Although researchers have discovered right whales in other regions during times of the year 

when right whales were previously unexpected to be found, or have documented unexpected movement 

patterns (Mate et al. 1997; Mellinger et al. 2011; e.g., Moore and Clark 1963), without multiple years of 

acoustic surveys, it is unclear if these results are an aberration in right whale occurrence during this study 

period or indicate an annual pattern of previously undocumented occurrence. 

In Georgia and North Carolina, we did not detect a significant presence of fin whales or humpback 

whales. Fin whales were detected on only six days in the North Carolina site, in November 2012 and 

March 2013, consistent with previous records of fin whale occurrence in this region (Nieukirk et al. 2004; 

Waring et al. 2013b; Webster et al. 1995). Humpback whale vocalizations were opportunistically found 

on eight days in the Georgia site and twelve days in the North Carolina site, across the year, but primarily 

in December 2012. Humpback whales can occur in the mid-Atlantic in the autumn and winter, but they 

primarily migrate from feeding grounds in the North Atlantic to breeding grounds in the West Indies in 

these seasons (Barco et al. 2002; Waring et al. 2013a). 

8.2 OCCURRENCE OF FISHES

The daily presence of black drum (Pogonias cromis) and oyster toadfish (Opsanus tau) was determined 

by identifying the loud drum calls of black drum (Mok and Gilmore 1983) and the boat whistle calls of 

oyster toadfish (Tavolga 1958). Black drum and oyster toadfish were acoustically detected over differing 

time periods at the North Carolina and Georgia sites. Black drum are predominantly present from the fall 

through spring (November–April 2013). Oyster toadfish are predominantly present in the early spring and 

summer (March–April 2013 and June–August 2012). 

Chorusing of black drum and oyster toadfish was detected in late June 2012 and late March and April 

2013 at the Georgia site, and was visible in multi-day long spectrograms. Black drum chorusing was also 

detected at NC-North in March–April, but no toadfish chorusing was detected in North Carolina. This 

seasonal chorusing is consistent with previous research on the winter and spring spawning season for 

black drum (Macchi et al. 2002; Murphy and Taylor 1989; Saucier and Baltz 1993) and spring to summer 

for toadfish (Gray and Winn 1961). Toadfish chorused throughout the day and black drum had a strong 

diel signature, chorusing overnight. Both chorusing patterns are consistent with previous research (Fine et 

al. 1977; Mok and Gilmore 1983; Saucier and Baltz 1993). 

The presence of both fish in our data is related to daily average water temperature, collected at each 

MARU, which may be one of the environmental triggers for spawning in these fishes. Environmental 

conditions are cues for the timing of spawning in black drum and toadfish, including light, water 

temperature, and dissolved oxygen (e.g., Aalbers 2008; Lowerre-Barbieri et al. 2008; Mann and Grothues 

2009; Rice and Bass 2009). Specific conditions in salinity and temperature are triggers for black drum

spawning (Saucier and Baltz 1993). However, because both species were acoustically detected on fewer 

days in North Carolina than in Georgia, and there was variability in the presence of each species between 

MARUs, habitat conditions also likely influence the occurrence of these species. There may be greater 

availability of preferred habitat in the shallow Georgia site, and this site may be patchy.
157 

Based on the lower acoustic occurrence of black drum and toadfish in North Carolina, these two species 

would not be effective indicator species at this site. However, other sound signals, likely from 

unidentified fish species, occurred throughout the study period. With additional research to identify the 

sources of these signals and the pattern of occurrence, these may be more reliable indicators of the 

environment than black drum and oyster toadfish. 

At the Georgia site, black drum and oyster toadfish occurred regularly, but within different seasons, with 

some overlap. Therefore, these species may be good indicators of environmental change at different times 

of the year. By monitoring the occurrence and chorusing of these species over multiple years, these 

species could be effective indicators of ecological change. Additionally, monitoring these changes within 

the context of offshore wind energy development would identify the effects of wind farm construction 

and operation. 

8.3 AMBIENT NOISE ENVIRONMENT

To evaluate the ambient noise conditions of North Carolina and Georgia, acoustic data from each MARU 

were processed (Dugan et al. 2011) and presented in long duration (i.e., multiple weeks or months) 

spectrograms and power spectra. Overall, summer and fall months (June–November) had higher levels of 

noise in comparison to winter and spring months (December–April). Geographically, the three MARUs in 

Georgia showed qualitatively higher levels of noise than the three MARUs in North Carolina. Within 

each geographic location, there was no significant variation in noise between individual sites. 

Sources of noise events in the North Carolina and Georgia environments include weather, biological, 

anthropogenic, and unknown sources of sounds. Fish chorusing, most notably black drum, is the 

dominant biological sound source in these sites. In addition, several unknown sources of sound, 

potentially biological, had significant contributions to the noise environment. Though marine mammal 

vocalizations were recorded throughout the study, they did not occur frequently enough to be visible on 

long term spectrograms. Anthropogenic noise, produced predominantly by ship traffic, has the potential to 

mask biological sounds, but further research is needed to address if masking is a biologically significant 

impact (i.e., if masking prevent intra-species communication).

Overall, these ambient noise data provide a baseline of the noise conditions in these ecosystems, so that 

relative contributions to the baseline noise from future increases in ship traffic, construction, and wind 

farm operation can be measured and the impacts to marine organisms can be assessed. 

8.3 HABITAT CHARACTERIZATION

The benthic habitats of the North Carolina and Georgia sites are predominantly soft-bottom substrates 

comprised of sandy sediments, with some hard-bottom outcroppings, including live and artificial coral. In 

the region of these sites, there is a diverse assemblage of marine animals, turtles, and fishes. These 

species have a variety of protected statuses and importance to commercial and recreational fisheries. 

Habitat characteristics, such as depth, circulation, temperature, and salinity, influence the marine species’ 

use of these sites; therefore, to assess ecological changes, research should monitor the populations of 

focal species and the influential environmental conditions. 
158 

8.4. CONCLUSIONS AND RECOMMENDATIONS

A scientific survey of the ecosystem should be carried out before engaging in activities that may perturb 

the environment. A baseline understanding of the occurrence of species and quality of the habitat provides 

information to compare and measure ecosystem changes. This study provided a baseline understanding of 

the occurrence of focal marine mammal and fish species, ambient noise environment, and habitat 

characteristics. Additional monitoring of these sites would elucidate inter-annual variability in the 

occurrence of species and habitat in the North Carolina and Georgia sites.

Passive acoustic monitoring has emerged as a non-invasive, data-intensive, low-cost method to survey the 

occurrence, abundance and behavior of acoustically active organisms. These techniques have provided 

previously unknown information about the occurrence of species in these sites. Previously available data 

on the occurrence of right whales had not identified that right whales occur in the summer. Because the 

Georgia site is just north of the southeastern U.S. critical habitat and the North Carolina and Georgia sites 

are part of the migratory corridor, the documented presence of right whales during the winter is useful 

when evaluating right whale management practices. Passive acoustic monitoring cannot determine 

behavioral changes in individuals, but it can address population-level behavioral changes. Environmental 

management decisions are best made with comprehensive data, and so passive acoustic monitoring can be 

combined with other survey techniques. 

Fish species should be considered as indicators of environmental change, and selected species should 

reflect the habitat requirements and seasonal occurrence of a larger species assemblage with similar 

ecological requirements in a region. Given that there was a wide range of spatial and temporal variability 

in the amount and seasonality of calling behavior of black drum and toadfish, future surveys should 

include spatial replication to demonstrate the degree of micro-scale variability of the focal species’ 

behavior and occurrence. Our acoustic data reflects how little research has been done to identify speciesspecific calls for many fishes. By identifying sound potentially produced by fish in Onslow Bay, 

researchers can develop a different set of fishes as possible ecological indicators at the North Carolina 

site.

To comprehensively assess the North Carolina and Georgia sites, BOEM could coordinate with other 

state and federal agencies to leverage survey efforts for natural resource inventories and management. For 

example, the U.S. Naval Facilities Command Atlantic (NAVFAC) has surveyed the habitat, marine 

mammals, and fish species in Onslow Bay as part of the environmental impact assessment for the 

Undersea Warfare Training Range (USWTR). This survey location is relatively close to the North 

Carolina wind planning area, and much of this survey information would be useful in the context of 

BOEM’s efforts. Further interagency cooperation could benefit multiple projects and reduce overall study 

costs, including biological surveys conducted for the U.S. Navy Onslow Bay Undersea Warfare Training 

Range (USWTR) and the Gray’s Reef National Marine Sanctuary. 

Future studies should address how marine organisms respond to potential noise stressors and habitat 

disturbance introduced by construction and operation of offshore wind farms. This study did not address 

this, but could be used as baseline information to explore the potential impacts. 
159 

9. ACKNOWLEDGEMENTS

Bioacoustics Research Program, Cornell Laboratory of Ornithology 

Director: Aaron N. Rice, Ph.D. 

Program Manager: Deborah Dennis

Director of Commercial Operations: Stan DeForest

Senior Scientist: Christopher W. Clark, Ph.D. 

Elephant Listening Project Director: Peter Wrege, Ph.D.

Senior Research Engineer: Harold A. Cheyne, Ph.D. 

Administration: Brian Cusimano, Tish Klein, Linda Harris, Christianne McMillan-White, Leon 

Stoll, Kevin White 

Report Authors: Aaron N. Rice, Ph.D., Janelle L. Morano, Kristin B. Hodge, Daniel S. Salisbury, 

Charles, M. Muirhead 

Data Analysis: Russ Charif, Christiana Diamond, Bobbi Estabrook, Emily Griffiths, Kristin 

Hodge, Maureen Loman, Chris Pelkie, Charles Muirhead, Janelle Morano, Kaitlin Palmer, 

Ashakur Rahaman, Elizabeth Rowland, Daniel Salisbury, Jamey Tielens 

Deployment and Fabrication: David Doxey, Jason Michalec, Edward Moore, Christopher 

Tessaglia-Hymes, Chris Tremblay, James Walluk, Fred Channell 

Hardware Engineering: Sam Fladung, Rich Gabrielson Amanda Kempf, Rob Koch, Raymond 

Mack, Peter Marchetto

Software Engineering: Peter Dugan, Sam Fladung, Melania Guerra, Ph.D., Sara Keen-Chester, 

Dean Hawthorne, Ph.D., William Hoagland, Timothy Krein, Matt MacGillivray, Michael 

Pitzrick, Dimitri Ponirakis, C. Marian Popescu, Mohammad Pourhomayoun, E. Lynette Rayle, 

Matthew Robbins, Jesse Ross, Yu Shiu, Ph.D., Eric Spaulding, Ann Warde, Ildar Urazghildiiev, 

Ph.D., John Zollweg, Ph.D. 

ESS Group, Inc.: Michael Feinblatt, Jeff Nield

Marine Acoustics, Inc. (MAI): Adam S. Frankel, Ph.D.
160 

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APPENDIX: OTHER BIOLOGICAL SIGNALS

The acoustic environment of the North Carolina and Georgia study sites are rich with biotic and abiotic 

signals, most of which have not previously been studied. In whale and fish analysis (see Chapters 3 and 4, 

respectively), we identified signals from known biological sources and signals from unidentifiable 

sources. Although we did not examine patterns of occurrence of these identifiable species or unknown 

signals, here we provide examples of our observations, because these may useful for future acoustic 

research. 

A.1 ADDITIONAL BIOLOGICAL SOURCES OF ACOUSTIC SIGNALS

We identified signals from cusk eel and sei whales in North Carolina and Georgia.

Figure A-1. Cusk-eel

Vocalizations from cusk-eels, unidentified species (Family: Ophidiidae), 

were seen in the North Carolina and Georgia sites. The signal is a rapid 

series of broadband bursts and sounds like knocking. The rate is constant 

within a bout, but the rate may vary between bouts. These are similar to 

the vocalizations of striped cusk-eel (Ophidion marginatum) (Mann et al. 

1997). The duration of the series of pulses varies, but the range of 

duration was not measured. Spectrogram: 256-point Hann window and 

89.9% overlap (frequency resolution of 7.81 Hz, time resolution of 13 ms).
179 

Figure A-2. Sei whale

Vocalizations from sei whales (Balaenoptera borealis) were seen in the 

North Carolina site (Baumgartner and Fratantoni 2008; Baumgartner et al. 

2008). Hodge (2011) reported these signals in Onslow Bay. Spectrogram: 

512-point Hann window and 90% overlap (frequency resolution of 3.91 Hz, 

time resolution of 25.5 ms).

A.2 BIOLOGICAL SIGNALS FROM UNKNOWN SOURCES

Here we present seven signals that occurred often enough for us to note the signals, and to avoid 

confusing these signals with signals from the focal study species (black drum, oyster toadfish). Given the 

irregular pattern and characteristics of the signals, we believe these to be from a biological source, most 

likely a fish species whose signals have not yet been described.

Figure A-3. Sound from an Unknown Source #1

Non-linear signals appear as a stack of downsweeps, approximately 0.6 s duration, 

and approximately 200–700 Hz. These signals were identified in Georgia and North 

Carolina. Spectrogram: 256-point Hann window and 89.8% overlap (frequency 

resolution of 7.81 Hz, time resolution of 13 ms).
180 

Figure A-4. Sound from an Unknown Source #2

These signals are a very short upsweep, approximately 0.2 s duration, appearing 

to begin at 430 Hz, but some signal can be visible at approximately 200 Hz. These 

were identified in Georgia and North Carolina, and noted as a significant sound 

source in the ambient noise environment in North Carolina (see Chapter 5.3.2.5, 

Figure 5.13). Spectrogram: 256-point Hann window and 50% overlap (frequency 

resolution of 7.81 Hz, time resolution of 64 ms).

Figure A-5. Sound from an Unknown Source #3

These signals are continuous, very rapid pulse-like, 3-4 s duration, below 500 Hz. 

These were identified in Georgia and North Carolina. Spectrogram: 256-point 

Hann window and 89.8% overlap (frequency resolution of 7.81 Hz, time resolution 

of 13 ms).
181 

Figure A-6. Sound from an Unknown Source #4

These signals are similar to #2, but are short downsweeps, 0.2 s duration, and 

begins at 350 Hz. These were identified in Georgia and North Carolina.

Spectrogram: 256-point Hann window and 50% overlap (frequency resolution of 

7.81 Hz, time resolution of 64 ms).

Figure A-7. Sound from an Unknown Source #5

These signals are similar to #2 and #4, but have a different sound quality. They 

are approximately 0.2 s duration, beginning at 350 Hz, and were identified in 

Georgia and North Carolina. Spectrogram: 256-point Hann window and 50% 

overlap (frequency resolution of 7.81 Hz, time resolution of 64 ms).
182 

Figure A-8. Sound from an Unknown Source #6

These signals were identified in Georgia and North Carolina. Spectrogram: 128-

point Hann window and 89.8% overlap (frequency resolution of 15.6 Hz, time 

resolution of 6.5 ms).




The Department of the Interior Mission

As the Nation’s principal conservation agency, the Department of the Interior has 

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