Report of the Joint 

Marine Mammal Commission –

National Marine Fisheries Service

Passive Acoustic Surveying Workshop

Dennis Heinemann

Jason Gedamke

Erin Oleson

Jay Barlow

Jessica Crance

Marla Holt

Melissa Soldevilla

Sofie Van Parijs

U.S. Department of Commerce

National Oceanic and Atmospheric Administration (NOAA)

National Marine Fisheries Service (NMFS)

NOAA Technical Memorandum NMFS-F/SPO-164

July 2016
Report of the Joint 

Marine Mammal Commission –

National Marine Fisheries Service

Passive Acoustic Surveying Workshop

Dennis Heinemann, Marine Mammal Commission

Jason Gedamke, Office of Science & Technology, NMFS

Erin Oleson, Pacific Islands Fisheries Science Center, NMFS 

Jay Barlow, Southwest Fisheries Science Center, NMFS

Jessica Crance, Alaska Fisheries Science Center, NMFS

Marla Holt, Northwest Fisheries Science Center, NMFS

Melissa Soldevilla, Southeast Fisheries Science Center, NMFS

Sofie Van Parijs, Northeast Fisheries Science Center, NMFS

NOAA Technical Memorandum NMFS-F/SPO-164

July 2016

U.S. Department of Commerce

Penny S. Pritzker, Secretary 

National Oceanic and Atmospheric Administration

Kathryn D. Sullivan, Administrator

National Marine Fisheries Service

Eileen Sobeck, Assistant Administrator for Fisheries

Marine Mammal Commission

Rebecca J. Lent, 

Executive Director
Recommended citation:

Heinemann, D., J. Gedamke, E. Oleson, J. Barlow, J. Crance, M. Holt, M. Soldevilla, and 

S. Van Parijs. 2016. Report of the Joint Marine Mammal Commission-National Marine Fisheries

Service Passive Acoustic Surveying Workshop, 16–17 April, 2015, La Jolla, CA. Marine

Mammal Commission, Bethesda, MD, and National Marine Fisheries Service, Silver Spring,

MD., U.S. Dept. Commerce. NOAA Tech. Memo. NMFS-F/SPO-164, 107 p.

Copies of this report may be obtained from: 

NOAA Fisheries Office of Science and Technology

National Oceanic and Atmospheric Administration

1315 East-West Highway, SSMC 3-Room 12538 

Silver Spring, MD 20910 

or 

Marine Mammal Commission

4340 East-West Highway, Rm 700 

Bethesda, MD 20814 

Or online at:

http://spo.nmfs.noaa.gov/tm/ 

http://www.mmc.gov

Disclaimer

The workshop Steering Committee prepared this report for the National Marine Fisheries 

Service. Any mention of, or reference to, trade names or commercial products does not constitute 

endorsement by the Marine Mammal Commission or the National Marine Fisheries Service.

ii
Passive Acoustic Surveying Workshop, La Jolla, CA, April 2015

iii

Executive Summary

The National Marine Fisheries Service (NMFS) is 

responsible for gathering the information needed 

to support its stock assessments of marine 

mammals. The distribution and abundance of 

each stock is the core of those assessments. Data 

to support stock assessments are traditionally 

gathered by conducting visual observations 

during shipboard and/or aerial surveys.

Increasingly, however, the agency is having 

difficulty provide abundance estimates and other 

data needed for marine mammal stock 

assessments. These challenges have spurred

NMFS to increase its investment in alternative

monitoring methods that may fill some critical 

data gaps more effectively and efficiently than 

large-scale ship and aerial surveys alone. 

For the last several years, research teams across 

NMFS have been investigating the use of 

advanced survey techniques to fill the stock

assessment data gap or to supplement traditional 

survey data. Passive acoustic monitoring (PAM) 

is a promising approach that can be pursued 

within the context of existing ship-based survey 

efforts or as part of an autonomous monitoring 

system. Research teams around the world are 

developing new vehicles, recorders, software and 

analytical techniques to study marine mammals.

However, it is clear that one approach will not 

adequately address all NMFS science goals and 

research requirements for stock assessments. 

Technological, scientific and funding constraints 

are hindering the full and efficient use of passive 

acoustics by NMFS to inform its marine mammal 

stock assessments.

NMFS sponsored a previous workshop on stock 

assessment using passive acoustics (Mellinger 

and Barlow, 2003). Since then, however, there 

has been rapid growth in the hardware and 

software for collecting passive acoustic data and 

in the analytical approaches for processing these 

large datasets. In April 2015, the Marine 

Mammal Commission and NMFS convened a 

workshop to explore how passive acoustics may 

now best contribute to the significant challenges 

in surveying marine mammals and fulfilling stock 

assessment requirements. The workshop 

addressed the breadth and depth of passive 

acoustics development and use across the 

Science Centers in the context of its broader 

development and use throughout the marine 

mammal community. Workshop participants 

included researchers from all six Science Centers, 

a representative of NMFS’s Office of Science & 

Technology (OS&T), a representative of the 

Marine Mammal Commission, and experts from 

academic institutions.

Science Center Resources

Information collected from NMFS’s Science 

Centers before the workshop uncovered a 

number of important issues. The use of passive 

acoustics to gather critical data and to augment 

visual surveys of marine mammals is clearly 

growing in importance. Passive acoustics are 

used to augment ship-based, line-transect 

surveys; to contribute to stock delineation; to 

assess the occurrence and seasonality of marine 

mammals; and to estimate the density, 

abundance, and trends of marine mammals. 

However, limited resources have caused the 

Science Centers to rely primarily on outside 

organizations and researchers for support and 

expertise. Most NMFS staff members engaged in 

passive acoustics are temporary employees or 

students, making it very difficult to build the 

necessary in-house expertise and institutional 

knowledge. In addition, the availability of 

equipment is an issue for several Science Centers:

often they do not have the resources to develop, 
Passive Acoustic Surveying Workshop, La Jolla, CA, April 2015

iv

purchase or lease the equipment they require. An 

exception to this limitation is the Southwest 

Fisheries Science Center (SWFSC), which has led 

the Science Centers in a concerted effort to 

standardize the technology and increase the 

efficiency of NMFS in using and maintaining 

towed-array systems. Another issue affecting the 

Science Centers is that they do not have the 

information technology infrastructure to store 

and disseminate the vast quantities of digital data 

associated with passive acoustic studies.

Using Passive Acoustics in Stock 

Assessment

Occurrence and Seasonality

Deriving a list of species that occur in a 

management area is one of the most basic 

components of stock assessment. When it is not 

feasible to conduct regular surveys to evaluate

species’ seasonal occurrence in a region, passive 

acoustics has contributed significantly to marine 

mammal stock assessments. When a vocalization

from a species is characteristic and well 

described, its detection in an acoustic recording 

can document occurrence of that species in a 

region. In addition, a collection of detections over 

a longer time series helps to determine whether 

the species is common or rare and whether it 

occurs year-round, seasonally or infrequently. 

There are many examples of PAM providing rich 

datasets from which species’ occurrence and 

seasonality have been evaluated. However, there 

is more to be done in the field, especially as 

associations with habitat and environmental 

change become increasingly important aspects of 

stock assessment. 

The assessment of occurrence and seasonality 

requires long-term monitoring, and for this, 

autonomous instruments are ideal. Such 

instrumentation can be deployed at relatively low 

cost, although the large volume of resulting data 

may require significant resources for analysis and 

storage. Increasing capacity in this area will 

require research in a number of areas, including 

establishing species/stock specific vocalization1

repertoires; understanding the influence of 

ecological and social context on vocalization

behavior; development of autonomous platforms 

that can be used over the vast pelagic ocean 

basins; and the development of much better 

automatic vocalization detectors and classifiers. 

Stock Delineation

Distinguishing stocks and defining their 

boundaries is challenging, often requiring genetic 

or morphological differences between groups of 

animals to delineate putative stocks. There has 

been growing interest in using other lines of 

evidence for stock delineation, including 

differences in the characteristics of vocalizations. 

Geographic mapping of the vocalization

characteristics for some baleen whale and 

delphinid species suggests differences in 

vocalizations may be a promising avenue of 

pursuit for identifying putative stocks for further 

study using other non-acoustic lines of evidence. 

Several factors can confound the apparent 

differences in vocalizations among putative 

stocks. Vocalization differences may reflect 

habitat, social or seasonal context, necessitating 

the delineation of differences in vocalizations

that hold up over long periods and that 

encompass the full range of environmental and 

social contexts. 

 1 In this report, the term “vocalization” refers to the 

wide range of sounds (songs, whistles, calls, clicks, 

etc.) made by marine mammals that may be 

recorded and analyzed in passive acoustic research 

and monitoring. We recognize that “vocalization” is 

somewhat of a misnomer because marine mammals 

may not use vocal cords to produce all sound types.
Passive Acoustic Surveying Workshop, La Jolla, CA, April 2015

v

Differences in vocalization characteristics are 

most likely to indicate stock structure in cases

such as baleen whales, where repetitive songs 

with stereotyped structures are used in 

reproduction. In other cases, acoustic differences 

alone are unlikely to provide definitive evidence 

of stock structure, but could be one piece of a 

multidimensional determination of stock 

delineation.

Trends in Relative Abundance

Estimates of cetacean population abundance are 

traditionally derived from data collected during 

visual sighting surveys. Although the assessment 

of trends does not require such intensive survey 

efforts, it is necessary to assume that detection 

probability and other absolute abundance 

parameters remain constant over time and space 

for abundance estimates to be comparable. 

Various measures derived from long-term passive 

acoustic recordings of specific species can 

provide relatively easily obtainable measures of 

relative abundance. For example, comparison of 

encounter rates or total acoustic energy from 

individual locations across many years can 

provide an indication of population growth or 

decline, under certain strict assumptions as 

mentioned above. Comparison of relative 

abundance estimates within and between 

locations and years can additionally reveal trends 

in distribution and seasonal presence over time. 

Like assessment of occurrence and seasonality, 

advancing the use of passive acoustics for 

assessing trends will require establishing 

vocalization repertoires that are species/stock 

specific, and understanding the influence of 

ecological and social context on vocalization

behavior, though the latter is less of a concern if 

a large portion of the stock range can be 

monitored. A robust survey design is required to 

provide relative abundance estimates with 

sufficient precision and constant bias to detect 

trends over time.

Absolute Abundance

The estimation of absolute density (number of 

animals per unit area) and abundance (number of 

animals in a defined area) are among the most 

challenging uses of passive acoustic data. 

Although the use of acoustics for cetacean 

density and abundance estimation continues to 

grow, it is still not routine and is not likely to 

replace visual sighting surveys for most species 

within the next decade. Density and abundance 

estimation of marine mammals using passive 

acoustic detection is still in the early stages of 

development, although it is advanced in avian 

studies. In most cases, passive acoustic detection

is not yet ready to be used alone to estimate 

stock abundance, because key parameters are 

either difficult to estimate (e.g., detection 

probability) or are unknown (e.g., vocalization 

production rates). 

Most acoustic approaches to estimating density 

and abundance are based on methods related to 

distance sampling that have been adapted for 

acoustic data. The most significant challenges for 

using acoustics detection data in this context are 

central to the standard density-estimation 

framework used with line-transect or point 

surveys—knowing the relationship between the 

number of vocalizations received and the number 

of animals present, and locating those animals in 

three-dimensional space. In addition, the ability 

to classify vocalizations to species or stock and 

the influence of behavior on detection may 

influence whether estimation of density and 

abundance is feasible for a given species. Several 

of the limitations of using passive acoustics to 

estimate abundance can be overcome by 

combining ship-based, visual sighting and towed 

hydrophone surveys, which together can 
Passive Acoustic Surveying Workshop, La Jolla, CA, April 2015

vi

overcome some of the shortcomings of visual 

surveys. However, in addition to technological 

advancements, additional behavioral data will be 

needed to apply distance-sampling-related 

methods to acoustic data.

Conclusions and Recommendations

Following the workshop, the Steering Committee met to develop general recommendations for future 

development of passive acoustics to support stock assessment efforts by NMFS. Two primary areas for 

improvements were identified—infrastructure investment and research needs.

Infrastructure Investment

Most of the development of passive acoustics capacity within NMFS has relied on peripheral funding 

and outside collaborations. Development of passive acoustic and related capabilities varies among 

Science Centers. Further, development of this technology generally lags behind the capacity of 

other research technologies that provide data used in stock assessments. The mature development 

of passive acoustics capacity within NMFS will require strategic and dedicated investment in 

infrastructure. A mature system will include state-of-the-art facilities and capacities for the 

development and testing of new technology (platforms, sensors, and analytic tools); maintenance of 

operational technology; training opportunities; deployment and retrieval of devices; storage of data;

and processing and analysis of those data. These resources and capacities are often lacking. The 

Steering Committee concluded that the full development of NMFS’s passive acoustics initiatives 

would require increased and reliable federal and external funding streams. 

A larger force of bioacousticians is needed in general, but especially at the most under-staffed 

Science Centers. In order to provide consistent, long-term, in-house passive acoustics expertise and 

capacity, dedicated, full-time federal positions will need to be created to fill part of this gap. The 

Steering Committee concluded that passive acoustics staffing is the first and most important issue 

that should be addressed.

Access to ship time for the deployment and recovery of acoustic sampling devices is a critical factor 

limiting NMFS’s ability to use passive acoustics to its fullest potential. Ship time is in short supply 

and expensive, meaning that the placement of acoustic sampling devices is dictated often by other 

priorities that determine the timing and track lines of NOAA research ships. Achieving acoustic 

sampling designs that maximize statistical precision and minimize statistical bias (e.g., in 

estimates of the relative abundance of cetaceans) is critical and will require access to dedicated 

ship time.
Passive Acoustic Surveying Workshop, La Jolla, CA, April 2015

vii

Almost all NMFS representatives from different Science Centers identified the storage, archiving,

and security of large-volume, passive acoustic data as a critically important issue. The Steering 

Committee concluded that in order to meet public access requirements, directed funding will be 

necessary. Also necessary is the development of standardized archiving protocols, collaboration 

with the National Centers for Environmental Information (NCEI), investment in storage devices 

and infrastructure, attention to security of sensitive (U.S. Navy) data, and efficient access to the 

data throughout the system.

Research Needs

The use of passive acoustics to survey marine mammals is promising, but still requires considerable 

research effort in a number of areas. Fundamental to all acoustic research is the need to be able to 

identify the source of detected sounds. Although the repertoire of calls, songs, and clicks of a few 

species is well known, for many species repertoires are only partially known, and for some species 

we know very little. The Steering Committee recommended the following: basic research to fill 

this gap, prioritizing focal species; the development of an accessible and centrally located catalog 

of marine mammal vocalizations that have been identified to species and/or stock; and additional 

investments in automated detection and classification algorithms and software.

Many characteristics of marine mammal vocalizations are known or reasonably suspected to be 

highly dependent on environmental and social factors (e.g., season, depth, behaviors, sex, age, 

social context, group size, etc.), although these associations are not well understood for most 

species. Without such contextual information, severe biases may result in estimates of occurrence, 

seasonality, abundance, and trends. The Steering Committee recommended a focus on 

“behavioral bioacoustics” research that will require integrated studies of vocal behavior of known 

animals. This research can be conducted by combining recordings with land-based observation, 

focal follows, or (especially) tagging, all of which are labor intensive and/or expensive.

The estimation of the density of marine mammals recorded by acoustic monitors is highly complex 

and statistically difficult, primarily because it requires sophisticated equipment and processing 

capabilities, and because it depends on the accurate and precise estimation of several parameters. 

The estimation of the distance (range) to an animal that is vocalizing is a tractable problem when an 

array of recording devices (hydrophones) is used. However, in some important circumstances (e.g., 

surveying deep water), the most desirable monitoring configuration involves the use of single 

hydrophones. Methods have been proposed to estimate range in such situations (both actual range 

to identified vocalizations, and effective detection range or detection probability), but they will 

require considerable testing and validation. The Steering Committee identified as a priority 

research goal range estimation from the data provided by a single hydrophone.
Passive Acoustic Surveying Workshop, La Jolla, CA, April 2015

viii

Additional research priorities are identified throughout this report. Although it is likely that 

NMFS will never completely replace ships and piloted aerial platforms for marine mammal 

surveys, it was clear to the Steering Committee that passive acoustics can play an important

role in the cost-effective collection of data for marine mammal stock assessments.
Passive Acoustic Surveying Workshop, La Jolla, CA, April 2015

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Contents

Executive Summary...................................................................................................................................... iii

Science Center Resources........................................................................................................................ iii

Using Passive Acoustics in Stock Assessment.......................................................................................... iv

Occurrence and Seasonality................................................................................................................. iv

Stock Delineation ................................................................................................................................. iv

Trends in Relative Abundance .............................................................................................................. v

Absolute Abundance............................................................................................................................. v

Conclusions and Recommendations........................................................................................................ vi

Infrastructure Investment.................................................................................................................... vi

Research Needs................................................................................................................................... vii

Figures........................................................................................................................................................ xiv

Tables......................................................................................................................................................... xiv

Chapter 1 Introduction and Background ...................................................................................................1

Workshop Background..............................................................................................................................1

Workshop Focus........................................................................................................................................1

Passive Acoustics Overview ......................................................................................................................2

Stock Assessment Requirements..............................................................................................................4

Role of Passive Acoustics in Stock Assessment.........................................................................................5

Chapter 2 Current Acoustic Assessment Capabilities within NMFS Science Centers................................6

Staffing ......................................................................................................................................................6

How NMFS Has Used Passive Acoustics for Assessment..........................................................................7

Common Approaches................................................................................................................................8

Detection, classification, and localization during ship-based surveys..................................................8

Long-term monitoring...........................................................................................................................9

Chapter 3 Stock Delineation ....................................................................................................................11

Data and Technical Requirements..........................................................................................................11

Current Capabilities ................................................................................................................................12

Impediments...........................................................................................................................................16

Species identification..........................................................................................................................16

Behavioral information and seasonality .............................................................................................17
Passive Acoustic Surveying Workshop, La Jolla, CA, April 2015

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Research Needs.......................................................................................................................................17

Data collection and archiving..............................................................................................................17

Vocalization repertoire .......................................................................................................................17

Behavioral studies...............................................................................................................................18

Combined studies ...............................................................................................................................18

Chapter 4 Occurrence and Seasonality....................................................................................................19

Data and Technical Requirements..........................................................................................................19

Current Capabilities ................................................................................................................................20

Impediments...........................................................................................................................................20

Instrumentation..................................................................................................................................21

Species identification and vocalization repertoire .............................................................................21

Behavioral context..............................................................................................................................21

Automated processing and analyst variability....................................................................................22

Detection range ..................................................................................................................................22

Research Needs.......................................................................................................................................22

Chapter 5 Long-Term Trends in Relative Abundance..............................................................................24

Data and Technical Requirements..........................................................................................................24

Current Capabilities ................................................................................................................................26

Impediments...........................................................................................................................................27

Cost and personnel .............................................................................................................................27

Automated detection/classification routines.....................................................................................27

Species-specific vocalizations .............................................................................................................28

Acoustic behavior................................................................................................................................28

Research Needs.......................................................................................................................................28

Characterization of vocalizations, source levels, and directionality...................................................28

Acoustic behavior................................................................................................................................29

Improvement in automated detection routines.................................................................................29

Simulations to assess performance of energy measures....................................................................29

Chapter 6 Absolute Abundance Estimation Using Passive Acoustics......................................................31

Data and Technical Requirements..........................................................................................................31

Current Capabilities ................................................................................................................................32

Impediments...........................................................................................................................................33
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Behavioral information .......................................................................................................................33

Species identification..........................................................................................................................33

Group size ...........................................................................................................................................34

Distance estimation ............................................................................................................................34

Combined visual and acoustic surveys................................................................................................34

Research Needs.......................................................................................................................................35

Behavioral studies...............................................................................................................................35

Species classification...........................................................................................................................35

Group size estimation .........................................................................................................................35

Distance estimation ............................................................................................................................35

Spatial extent and randomized survey design....................................................................................35

Combined visual and acoustic method...............................................................................................35

Chapter 7 Conclusions and Recommendations.......................................................................................37

Infrastructure Investment.......................................................................................................................37

Recognition of importance of passive acoustics.................................................................................37

Improving infrastructure.....................................................................................................................39

Targeted Studies.....................................................................................................................................40

Classification—species/stock identification capability .......................................................................40

Behavioral acoustics............................................................................................................................41

Range estimation ................................................................................................................................41

Detection probability and validation ..................................................................................................42

Automated analyses and quantitative performance measures .........................................................42

References ..................................................................................................................................................43

Acknowledgements.....................................................................................................................................49

Appendix A Participants.........................................................................................................................50

Appendix B Science Center Passive Acoustics Research Programs (Prepared by Erin Oleson) .............60

Northeast Fisheries Science Center Passive Acoustic Research Group ..................................................60

Ongoing projects.................................................................................................................................61

Southeast Fisheries Science Center Passive Acoustic Assessment Program..........................................62

Southwest Fisheries Science Center Passive Acoustics ..........................................................................63

Ongoing projects.................................................................................................................................64

Pacific Islands Fisheries Science Center Passive Acoustics.....................................................................64
Passive Acoustic Surveying Workshop, La Jolla, CA, April 2015

xii

Projects and goals...............................................................................................................................65

Northwest Fisheries Science Center Passive Acoustics ..........................................................................65

Current projects..................................................................................................................................66

Alaska Fisheries Science Center Passive Acoustics.................................................................................67

Appendix C Fixed Autonomous Acoustic Platforms (Prepared by Sofie Van Parijs) .............................70

General Overview ...................................................................................................................................70

Bottom-Mounted Acoustic Recorders (BMARs) .....................................................................................71

Surface-Mounted Acoustic Recorders (SMARs)......................................................................................71

Existing Hurdles.......................................................................................................................................72

Uses of Bottom- and Surface-Mounted Acoustic Recorder Data...........................................................73

Abundance Estimation ............................................................................................................................74

Limitations and Impediments in Stock Assessment ................................................................................74

Other Considerations..............................................................................................................................75

References ..............................................................................................................................................75

Appendix D Uses of Towed Hydrophone Arrays for Cetacean Stock Assessment (Prepared by Jay 

Barlow and Shannon Rankin)......................................................................................................................76

Introduction ............................................................................................................................................76

Hardware and Software Used.................................................................................................................76

Towed hydrophone arrays..................................................................................................................76

Signal conditioning, array power, and noise considerations..............................................................77

Software and recording ......................................................................................................................78

Species- and Population-Specific Vocalization Description....................................................................78

Stock Delineation and Distribution.........................................................................................................79

Abundance Estimation............................................................................................................................79

Absolute abundance ...........................................................................................................................79

Relative density...................................................................................................................................80

Estimation of fraction missed by visual observers..............................................................................80

Limitations and Impediments to the Wider Use of Towed Arrays in Stock Assessment........................80

References ..............................................................................................................................................81

Appendix E Mobile Autonomous Platforms (Prepared by Holger Klinck and Jay Barlow) ....................85

General Overview ...................................................................................................................................85

Autonomous Underwater Vehicles.........................................................................................................86
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Unmanned Surface Vehicles...................................................................................................................86

Free-Drifting Passive Acoustic Monitoring Systems...............................................................................87

Passive Acoustic Monitoring Systems.....................................................................................................88

Developers/users................................................................................................................................88

Existing hurdles...................................................................................................................................90

Future directions.................................................................................................................................91

Other considerations ..........................................................................................................................91

References ..............................................................................................................................................91

Appendix F Absolute Density and Abundance Estimation from Passive Acoustic Data (Prepared by 

Danielle Harris, Tiago Marques, and Len Thomas) .....................................................................................93

General Overview ...................................................................................................................................93

Absolute density and abundance estimators .....................................................................................93

Methods to estimate animal density and abundance ........................................................................94

Variance estimation............................................................................................................................95

Examples and Case Studies.....................................................................................................................95

Census/strip transects ........................................................................................................................95

Distance sampling ...............................................................................................................................96

Spatially explicit capture-recapture....................................................................................................96

Detection probability from auxiliary data...........................................................................................96

Challenges of Passive Acoustic Density Estimation ................................................................................97

Survey design ......................................................................................................................................97

Multipliers...........................................................................................................................................97

Behavioral information .......................................................................................................................97

References ..............................................................................................................................................98

Appendix G Marine Mammal Stock Assessment Requirements (Prepared by Jay Barlow).................100

References ............................................................................................................................................101

Appendix H Marine Mammal Protection Act—Stock Assessment Requirements...............................102

Acronyms and Abbreviations....................................................................................................................103

Devices......................................................................................................................................................106
Passive Acoustic Surveying Workshop, La Jolla, CA, April 2015

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Figures

Figure 1. Proportion of NMFS passive acoustic assessment projects designed to address the different 

assessment components. Some projects may be designed to address more than one component..........7

Figure 2. Fixed autonomous recorders for passive acoustic monitoring of marine mammals. ...............700

Figure 3. Autonomous mobile platforms for passive-acoustic monitoring of marine mammals.............855

Tables

Table 1. Number of current federal and contract staff full-time equivalents (FTEs) dedicated to passive 

acoustics assessment research within each NMFS Science Center, as well as the number of graduate 

students conducting research using passive acoustics for marine mammal assessments. .........................6

Table 2. Capabilities and examples of acoustic differentiation of taxa, species, and populations. ..........14
Passive Acoustic Surveying Workshop, La Jolla, CA, April 2015

1

Chapter 1 Introduction and 

Background

Workshop Background

NMFS is responsible for gathering the 

information needed to support its stock 

assessments of marine mammals. Data on the 

pelagic distribution and abundance of each stock, 

which are the core of those assessments, are 

traditionally gathered by conducting visual 

observations during shipboard and/or aerial 

surveys, from which population estimates are 

derived. However, with the declining 

appropriations for its marine mammal 

conservation, management, and research, the 

agency is experiencing difficulty gathering those 

and other stock-assessment data that are 

necessary to fulfill its obligations under the 

Marine Mammal Protection Act (MMPA) and the 

Endangered Species Act (ESA). 

For the last several years, research teams across 

NMFS have been investigating the use of 

advanced survey techniques to fill this data gap 

or to supplement traditional survey data. One 

promising approach is passive acoustic 

monitoring (PAM) using acoustic recorders that 

can be deployed from a variety of platforms, 

including a stationary (fixed) mooring, 

autonomous mobile vehicle (glider or floating 

buoy), or towed behind a ship. 

Research teams around the world are developing 

new vehicles, recorders, software, and analytical 

techniques to study marine mammals. However,

it is clear that one approach will not adequately 

address all science goals and research 

requirements for stock assessment. In addition, 

estimating abundance of animals using data 

gathered by passive acoustic approaches is 

proving to be a considerable scientific and 

funding challenge. Thus, technological, scientific,

and funding constraints are hindering the full and 

efficient use of passive acoustics by NMFS to 

inform its stock assessments.

Because developments in this new and 

burgeoning area are moving fast, and because 

the technological and scientific challenges are 

substantial, in April 2015 the Marine Mammal 

Commission and NMFS convened a workshop to 

explore the use of passive acoustics for surveying

marine mammals and fulfilling stock-assessment 

requirements. Progress on the development of 

passive acoustics for stock assessment is being 

made at each NMFS Science Center. The 

workshop addressed the breadth and depth of 

passive acoustic development and use across the 

Science Centers in the context of its broader 

development and use throughout the marine 

mammal community. Workshop participants 

included researchers from all six NMFS Science 

Centers, one representative of NMFS’s OS&T, one

representative from the U.S. Marine Mammal 

Commission, and several experts from academic 

institutions (Appendix A). In preparation for the 

workshop, several participants were asked to 

provide background documents (Appendix C

through Appendix H) that were circulated among 

workshop participants prior to the meeting.

Workshop Focus

The goal of the workshop was to build a synoptic 

view of the development and use of passive 

acoustics to provide needed information for 

marine mammal stock assessments within NMFS. 

Information on planned, developing and 

implemented projects was gathered from each of 

the NMFS Science Centers (Appendix B). That 

information was assessed in the workshop with 

respect to performance and potential in the 

context of the general state of science and 

technology development. For each platform, the 
Passive Acoustic Surveying Workshop, La Jolla, CA, April 2015

2

workshop considered the key aspects of passive 

acoustic approaches to gather information for 

marine mammal stock assessments, including

platform design; hydrophone/recorder design;

software for detection, classification, and 

localization; data-stream handling; statistical 

density estimation; survey/monitoring design;

and integration with traditional survey methods. 

The performance of various elements and whole 

systems was assessed relative to several factors 

such as: 1) the “state of the science”; 2) gaps and 

redundancies in NMFS’s efforts; 3) constraints on 

development and use (e.g., regulatory hurdles, 

permitting, funding, platform availability, 

science/technology gaps, lack of available 

expertise, etc.); 4) expected cost-benefit ratios 

and actual performance in the field; and 5) needs 

(research, technology innovation/development, 

expertise, data standards, etc.). Finally, the 

workshop 1) contrasted “competing” technology 

options; 2) identified the most promising 

technologies for different situations and 

requirements; 3) identified opportunities for 

sharing, coordination, collaboration and synergy 

among regions; and 4) identified guidelines for

planning, development, and use. The workshop 

focused entirely on cetaceans, for which passive 

acoustic methods are widely viewed to have the 

most potential. Currently, NMFS is doing little 

passive acoustic work on pinnipeds.

Passive Acoustics Overview

Visual survey techniques are limited when 

applied to marine mammals because many 

species are out of sight much of the time and 

surveying is not possible at night. However, 

because marine mammals generate sound to 

perceive their surroundings, find prey, and 

communicate with each other, researchers can 

use their sounds to detect their presence 

whether the animals are visible or not, as long as 

they are vocalizing. In addition, with the right 

technology and in the right circumstances,

marine mammal vocalizations can be used to 

identify which species are present and to locate 

individuals.

Researchers use PAM approaches to study, 

monitor or survey marine mammals by deploying 

hydrophones in a variety of configurations and on 

a variety of platforms. Passive acoustics, in which 

researchers listen to the sounds produced by 

marine mammals, is different from active 

acoustics. In active acoustics, sounds are 

purposefully generated by the system, and the 

return signals (echoes) are recorded and analyzed 

to provide information on the locations and 

characteristics of objects in the water column. 

Active acoustics is typically used to create a 

picture of bathymetry, or to estimate the number 

or biomass of plankton or nekton (fish and squid) 

in the water column.

Using passive acoustics to survey marine 

mammals requires several steps. The acquisition 

of acoustic data begins with using a hydrophone 

that responds to sounds in the appropriate 

frequency range, depending on research goals 

and species of interest. Signals coming from the 

hydrophone are often conditioned to remove 

noise, filter out unwanted frequencies, and 

amplify desired frequencies. Often the signals 

are then digitized, recorded and stored for later 

analysis in the lab. However, in some situations, 

depending on the overall goals, signals are 

monitored and analyzed in real time and full 

recordings are not stored. In the lab or in real 

time, the signals may be further processed and 

analyzed to detect the clicks, calls, or songs 

generated by marine mammals. That analysis is 

often done with the assistance of computer 

software that detects signals in the data that 

match the characteristics of particular marine 
Passive Acoustic Surveying Workshop, La Jolla, CA, April 2015

3

mammal vocalizations. Next, analysts, often 

assisted by analytical and visualization software,

attempt to classify vocalizations in terms of the 

type (e.g., echolocation clicks, whistles, songs) 

and source of the vocalizations (the species or 

population to which the vocalizing individuals 

belong). If the vocalizations were recorded from 

multiple hydrophones in an array, then arrival 

time differences or beam forming techniques can 

be used to determine the direction and/or 

distance to the individuals or groups that 

produced the vocalizations.2

 These processes are 

referred to as detection, classification and 

localization (DCL). Finally, the data from multiple 

recordings over time, or along a transect, can be 

used to estimate the density of vocalizations and, 

with some other information and assumptions, 

the density of animals (density estimation; 

Appendix F). If methods allow the determination 

of the total area within which those vocalizations 

occurred and the survey area was randomly

sampled, then the abundance of animals in the 

area can be estimated.

PAM systems typically consist of the hydrophone 

array, a power source, pre-amplifier, recording 

and storage device, and sometimes a computer 

that pre-processes or filters the recordings. PAM 

systems can be combined as in the following 

configurations: 1) a single hydrophone or 

multiple elements in an array; (2) fixed or mobile;

(3) monitored in real time and/or data recorded 

for post-processing; (4) autonomous or not. The 

hydrophones can be linked to a shore station or 

ship via cables, radio or satellite transmissions. In 

this case, the PAM system components are 

distributed, with the hydrophones, power source,

and pre-amp in the water, and signals 

 2 Direction alone can be determined with the use of 

DIFAR sonobuoys, and detection range alone can be 

determined from multipath signals under some 

conditions.

transmitted to the other components on land or 

a ship for recording and real-time processing. 

A common mobile deployment is the towed array 

(Appendix D), which consists of a suite of 

hydrophones in a one- (linear), two-, or threedimensional configuration that is towed behind a 

ship during a survey. Towed arrays often 

augment visual line-transect surveys to extend 

the range of detection, to extend surveys into 

nighttime hours, and to detect submerged 

animals that might be missed by visual survey 

methods. For some species (e.g., sperm whales, 

beaked whales, and harbor porpoises), towed 

arrays are often the primary survey method. 

Data collected from towed arrays are usually 

monitored in real time but are recorded for postprocessing. Towed hydrophones can be severely 

affected by flow noise, ship noise and electrical 

noise, problems that are dealt with at least 

partially by amplifying and filtering signals. In 

general, towed arrays work best for species 

whose vocalizations are above 1 kHz because 

flow and ship noise mask low-frequency sounds 

in most situations. 

Fixed autonomous acoustic recording systems, 

which typically contain all of the necessary 

components of a PAM system, are deployed at 

sea, where they record and store acoustic data 

that are later retrieved, processed and analyzed. 

Acoustic recording systems can be deployed as 

arrays of fixed units and positioned anywhere in 

the water column (Appendix C). Bottommounted acoustic recorders (BMARs) are set on 

the sea floor and are retrieved using a buoy line 

or acoustically triggered float. Surface-mounted 

acoustic recorders (SMARs) are positioned below 

the surface and held in place in the water-column 

by weights and floats, and kept in one location by 

bottom anchors. Both BMARs and SMARs store 

acoustic recordings captured over months or 
Passive Acoustic Surveying Workshop, La Jolla, CA, April 2015

4

years to be off-loaded after the unit is retrieved. 

In some cases, data from a unit with a surface 

expression can be uploaded in near real time 

using very high frequency (VHF), mobile, or 

satellite networks.

Finally, mobile acoustic recorders can also be 

incorporated into drifting platforms or selfpropelled vehicles (Appendix E). These 

deployments come in a few forms: buoyancydriven autonomous underwater vehicles (AUVs);

wind-/wave-powered unmanned surface vehicles 

(USVs); and free-drifting buoy recorders. AUVs, 

including both gliders and floats, can control the 

depth at which they move by altering their

buoyancy. While floats can control only the 

depth at which they drift with the current, gliders 

use wings to generate forward velocity as well as 

vertical motion. Internal control and navigation 

mechanisms can change pitch and heading to 

allow a glider to “fly” a directed route. Typically, 

AUVs periodically surface to upload their location 

and data and to receive control instructions. 

These devices move slowly (average 0.5 kts) but 

can remain at sea for months during which time 

they can survey large areas. Because controlsystem noise is of concern with some mobile 

autonomous platforms, PAM systems are often 

disabled during buoyancy control operations in 

AUVs. Wave-powered USVs consist of two 

components: a surface float roughly the size and 

shape of a surfboard, and a subsurface unit that

is winged and sometimes has a rudder. The 

subsurface unit is connected to the surface unit 

by a cable. Working in tandem, the two units use 

the energy of passing waves to propel the USV 

forward. USVs can move several times faster

than AUVs. As with towed arrays, faster 

movement rates can create flow noise. In 

addition, moving components such as rudders or 

wave-guided surfaces can generate noise that 

can impede the detection of vocalizations.

Free-drifting buoys are designed to drift with 

surface currents or wind. The recorder can be 

packaged within a surface float with wired 

connections to subsurface hydrophones, or 

autonomous hydrophones can be attached to a 

rope line below a surface float. The sonobuoy is

an example of a free-drifting buoy, although it is

not considered autonomous because it lacks an 

onboard data-recording and storage device. 

Autonomous floating recorders are currently 

archival and must be recovered to retrieve full 

data files. However, processors within a surface 

float can send summary information via satellite 

or cell phones. Vertical hydrophone arrays can 

be used with drifting systems to allow range 

estimates.

Stock Assessment Requirements

The MMPA) was amended in 1994 to require 

stock assessment reports of marine mammals 

within U.S. jurisdiction (Appendix G). The 

requirements for stock assessment were further 

refined in the second Guidelines for Assessing 

Marine Mammal Stocks (GAMMS II; NMFS 2005). 

The purpose of stock assessment reports is to 

evaluate human impacts on marine mammal 

populations and to determine stock status. 

Similarly, the ESA requires periodic reviews of all 

endangered species to evaluate progress in 

meeting recovery goals and to re-evaluate their 

status under the ESA. The workshop considered 

the contribution of passive acoustics to both 

MMPA stock assessments and ESA status reviews 

conducted by NMFS.
Passive Acoustic Surveying Workshop, La Jolla, CA, April 2015

5

The requirements for an MMPA stock assessment 

are clearly established, and include:

1) stock definition and geographic range 

(spatio-temporal distribution);

2) estimation of population size and trends 

in abundance, with emphasis on 

obtaining a “minimum population 

estimate”;

3) estimation of current and maximum net 

productivity rates;

4) calculation of potential biological 

removal (PBR);

5) estimation of the rate of human-caused 

mortality and serious injury;

6) evaluation of whether a stock is 

“strategic”3 under the MMPA; and

7) evaluation of other factors causing 

decline or impeding recovery for 

strategic stocks.

The requirements of ESA status reviews are not 

as clearly established, but certainly include many 

of the same elements as MMPA stock 

assessments. The main difference is that the 

standards for delineating management units 

under the ESA (called distinct population 

segments, or DPSs) are stricter than the 

standards for defining population stocks under 

the MMPA. The guidelines for delineating a DPS 

were established as a joint policy by NMFS and 

the U.S. Fish and Wildlife Service.4

 3 A stock is designated “strategic” under the MMPA if 

the level of direct human-caused mortality exceeds 

PBR and the stock is declining and likely to be listed as 

threatened under the ESA within the foreseeable 

future; is already listed as threatened or endangered; 

or is determined to be below its optimal sustainable 

population level as defined in the MMPA.

4 Federal Register Notice: Policy Regarding the 

Recognition of Distinct Vertebrate Population 

Segments Under the Endangered Species Act. 61 FR 

4722, February 7, 1996. 

Role of Passive Acoustics in Stock 

Assessment

Passive acoustics are best suited to address stock 

assessment requirements 1, 2 and 3 listed earlier. 

If there are consistent differences in vocalization

structure between populations, this can aid in 

delimiting population stocks or DPSs using 

passive acoustics and may be helpful in 

subspecies designations. PAM can achieve broad 

temporal and spatial coverage, which can be 

useful in determining seasonal/temporal changes 

in geographic range. Long-term trends in 

detected vocalization rates can be used to infer 

rates of change in population sizes under certain 

strict assumptions, and these rates can help 

determine maximum net growth rates. Passive 

acoustic methods can be combined with distance 

sampling-related methods to estimate absolute

abundance.

Passive acoustic research can be used in a wide 

variety of other contexts that are indirectly 

related to assessing human impacts on marine 

mammals (e.g., stock assessment requirement 7). 

These contexts include studies of ocean noise

conditions and Behavioral Response Studies, 

which evaluate the behavioral impacts of specific 

noise sources on marine mammals.

 

Available at http://www.gpo.gov/fdsys/granule/FR1996-02-07/96-2639
Passive Acoustic Surveying Workshop, La Jolla, CA, April 2015

6

Chapter 2 Current Acoustic 

Assessment

Capabilities within

NMFS Science 

Centers

All NMFS Science Centers currently have some 

passive acoustic expertise and ongoing projects, 

generally within the branch or division that leads 

protected species assessments. The breadth of 

current work represents a significant 

advancement in passive acoustics capacity within 

NMFS since the original acoustics assessment 

workshop (Mellinger and Barlow, 2003). At that 

time, only the Southwest Fisheries Science Center

(SWFSC) and Southeast Fisheries Science Center

(SEFSC) had operational towed hydrophone 

arrays. Most other Science Centers had goals of 

incorporating passive acoustics into their ship 

surveys for long-term monitoring but had not 

implemented projects to do so. Since 2003,

passive acoustics activities have expanded 

significantly within the protected species 

programs in NMFS. However, individual Science 

Centers find it challenging to maintain adequate 

staffing and other resources to use passive 

acoustics as a major element of the stock 

assessment process.

Staffing

Most NMFS Science Centers employ federal staff 

that spends some portion of its time conducting 

passive acoustic research projects or developing 

passive acoustic assessment technology (Table 1). 

The Southeast and Pacific Islands Science Centers 

do not currently have any full-time federal staff 

dedicated to passive acoustic research on 

protected species, although the Pacific Islands 

Fisheries Science Center (PIFSC) is pursuing the 

recruitment of a full-time federal bioacoustician. 

Only three Science Centers (Southwest,

Northwest and Alaska) have more than one 

federal acoustician on staff. 

Table 1. Number of current federal and contract 

staff full-time equivalents (FTEs) dedicated to 

passive acoustics assessment research within each 

NMFS Science Center, as well as the number of 

graduate students conducting research using 

passive acoustics for marine mammal 

assessments.5

Fisheries

Science

Center

Federal

Staff

Cooperative 

Institute or 

Contract 

Staff

Graduate 

Students

Northeast 1 71⁄2 -

Southeast 1⁄2 1 -

Southwest 3 1 3

Pacific Islands 1⁄4 3 1

Northwest 11⁄2 - 1

Alaska 2 5 -

Several Science Centers, especially Northeast and 

Alaska, rely heavily on staffing through 

cooperative institutes or contracting firms. They 

use this method primarily because most of the 

funds within the Science Centers for passive 

acoustic assessment projects are temporary, 

either from internal NMFS funding initiatives or 

from external sources, and cannot be used to 

support federal staff. Alternatively, the 

temporary nature of the funds requires

temporary staff. There has been relatively little 

funding provided by NMFS to support passive 

acoustic assessment projects or staffing.

 5 Table 1 does not show other federal staff that may 

support the theoretical framework behind the 

statistical treatment of passive acoustic datasets for 

use in quantitative assessments. Those staff typically 

do not require acoustics expertise and are mainly 

dedicated to other assessment projects. Also not 

included is temporary staff hired for field-data 

collection projects.
Passive Acoustic Surveying Workshop, La Jolla, CA, April 2015

7

Some Science Centers have provided support for 

graduate students conducting research directly 

related to assessment of NMFS marine mammal 

stocks using passive acoustic techniques. Funds 

for student support are most commonly provided 

through partnerships and funding arrangements 

with external partners such as the U.S. Navy or 

Bureau of Ocean Energy Management (BOEM), 

although occasionally with some partial support 

from NMFS.

How NMFS Has Used Passive 

Acoustics for Assessment

Details on all NMFS acoustic assessment projects, 

at the time of the workshop, are provided in

Appendix B. The majority of passive acoustics 

projects are externally funded or piggy-backed 

onto other assessment projects. The most 

common projects are those aiming to describe 

species or stock occurrence and seasonality, with 

relatively fewer projects designed for estimating 

abundance or assessing human impacts. Very 

few projects are designed specifically to collect 

the data required for stock delineation. Although 

data are often collected under a study design 

specific to assessing seasonality or occurrence, or 

for providing detection and localization capability 

during visual line-transect surveys, those data 

may also prove useful for other assessment 

projects. All Science Centers have collaborated 

with other academic, non-profit and industry 

researchers to accomplish passive acoustic 

assessment projects, with such collaborations 

often providing many of the staff and 

instrumentation required (Figure 1).

With the exception of incorporating passive 

acoustic detection with towed arrays into shipbased assessment surveys, most passive acoustic 

assessment projects are narrowly focused on a 

single priority species or species group. These 

assessments are generally limited to species that 

can be identified to species with high confidence.

Figure 1. Proportion of NMFS passive acoustic assessment projects designed to address the different 

assessment components. Some projects may be designed to address more than one component.

0%

10%

20%

30%

40%

50%

60%

Occurrence/Seasonality Abundance Human Impacts Stock Delineation
Passive Acoustic Surveying Workshop, La Jolla, CA, April 2015

8

Common Approaches

Most of the common technologies used for 

collecting passive acoustic datasets are described 

in the appendices of this report. Most of these 

technologies are widely available through 

academic or commercial sources, and some are 

being built in-house. Some technologies are 

more specialized and are used only by one or few 

Science Centers. Passive acoustics projects 

currently underway within NMFS, including the 

instrumentation used and the questions 

addressed using that technology, are described in 

Appendix B.

Detection, classification, and 

localization during ship-based surveys

All NMFS Science Centers conduct ship-based 

surveys for marine mammals, using line-transect 

methods either to assess abundance or to locate 

specific species for intensive sampling.

Incorporation of passive acoustic monitoring 

during ship-based surveys provides an alternative 

method of detecting vocalizing groups and 

increasing encounter rates (e.g., Rankin et al.

2008). In some cases, this monitoring has

provided an independent method to assess 

abundance (e.g., Barlow and Taylor, 2005).

All NMFS Science Centers currently possess 

towed multi-element hydrophone systems and 

the data acquisition equipment required to use 

these arrays on NOAA ships or other vessels. The 

SWFSC has been the primary driver of developing 

towed-hydrophone-array methods for use during 

ship-based, line-transect surveys for assessment 

of cetacean abundance. The Advanced Sampling 

Technology Working Group (ASTWG) funded a

2-week workshop in the fall of 2012 to bring 

together passive acoustics staff from each 

Science Center to build a hydrophone array for 

their own Science Center’s use (Rankin et al.,

2013). Since that workshop, all Science Centers 

acquired towed array systems that are 

interchangeable, creating redundancy within the 

agency and reducing the need for each Science 

Center to maintain several backup systems.

Technology advances after the 2012 workshop 

mean that individual Science Center systems have 

since diverged somewhat, although the basic 

data-collection system remains the same or 

compatible with newer equipment. Follow-up 

workshops will likely be needed to enable all 

Science Centers to remain up-to-date on 

hydrophone and pre-amp technology, as well as 

new developments in acquisition hardware and 

software. Although the towed-array systems are 

owned by NMFS, some Science Centers provide 

their systems to bioacoustics contracting firms 

for use during ship-based surveys. This exchange 

occurs because the contractors do not have 

enough staff or adequately trained staff to 

conduct all towed-array operations at sea. 

Sonobuoys are also commonly used during NMFS 

assessment surveys, and all Science Centers 

currently have access to these instruments 

through the U.S. Navy. These expendable 

monitoring devices transmit acoustic data over a 

VHF carrier frequency to a monitoring station on 

the ship or shore. Sonobuoys are capable of 

omnidirectional listening up to 24 kHz, or 

directional listening capability to about 4 kHz. 

Sonobuoys are most commonly used for 

recording sighted baleen whales during NMFS 

surveys to identify the vocalizations of a specific 

species or stock (e.g., Oleson et al., 2003; Rankin 

and Barlow, 2007) or for tracking vocalizations to 

find individuals or groups for sampling (e.g., 

Wade et al., 2006; Rone et al., 2012). Sonobuoys 

are provided at no charge by the U.S. Navy, but 

must be requested annually through a 

competitive process open to all passive acoustics 

researchers inside and outside the government. 
Passive Acoustic Surveying Workshop, La Jolla, CA, April 2015

9

Long-term monitoring 

Autonomous long-term, passive acoustics 

systems are also used by most NMFS Science 

Centers for assessment of marine mammal 

occurrence based on detection of their 

vocalizations, as well as measurement and 

monitoring of ocean ambient and anthropogenic 

noise (e.g., Širović et al., 2013; Van Parijs et al., 

2015). Although these systems may be used for 

assessing abundance or trends through 

deployment of autonomous recorders in an array,

or by using modeling approaches to estimate 

detection distance based on the characteristics of 

the vocalization and the local environment, there 

has been relatively little effort toward this type of 

assessment within NMFS. Many different 

autonomous instruments are available for 

collecting passive-acoustic data, and no single 

instrument type can fit all research requirements. 

Each Science Center may use one or more 

autonomous recorder types depending on the 

recording duration and bandwidth required for 

the project. Some of the most commonly used 

autonomous systems within NMFS include 

Autonomous Underwater Recorders for Acoustic 

Listening (AURALs); Ecological Acoustic Recorders 

(EARs); High-Frequency Acoustic Recording 

Packages (HARPs); C-PODs; Marine Autonomous 

Recording Units (MARUs); and Hydrophones for 

Acoustic Research Underwater (HARU Phones). 

Some instruments are calibrated by the 

manufacturer, allowing for true measurement of 

ambient or anthropogenic noise amplitude and 

the received level of animal sounds. Many more 

types of autonomous instruments are not 

calibrated by the manufacturer and must be 

calibrated by NMFS staff, if calibrated 

measurements are required. Alternatively, these 

instruments are used only for relative measures 

of amplitude across the bandwidth of the 

recording. Many autonomous instruments used 

in NMFS projects are not owned by NMFS Science 

Centers, but instead are leased from the 

manufacturer or loaned from collaborating 

institutions for the duration of the project.

Two other instrument types used by some NMFS 

Science Centers are short-duration, free-floating 

or tethered recorders and acoustically equipped

underwater gliders or profiling floats. These 

instruments are at seemingly opposite ends of 

the technological complexity scale, with most 

free-floating or tethered units being assembled 

from a commercially available recorder and 

hydrophone and deployed from small vessels to 

monitor sounds produced by a sighted species or 

stock. These types of data have proven 

particularly useful for developing automated 

classification algorithms and for assessing

differences in vocalization characteristics among

two or more stocks of the same species.

Autonomous underwater vehicles, including 

gliders and profiling floats, have more recently 

been outfitted with passive-acoustic sensors.

This technology has recently received 

considerable attention from academic and 

industry researchers, but has been adopted to a 

lesser extent by NMFS scientists. Development 

of assessment capability for acoustically 

equipped gliders and profiling floats has been 

pursued within the Northeast Fisheries Science 

Center (NEFSC) and to a lesser extent PIFSC, 

primarily with funds from external sources or 

from the ASTWG. This technology has proven 

quite effective for detecting the sounds of 

vocalizing animals to assess geographic 

occurrence or habitat use. However, the 

theoretical framework for conducting abundance 

surveys from mobile autonomous platforms is 

still being developed. Mobile autonomous 

systems are generally leased from commercial or 

academic developers because operational and 
Passive Acoustic Surveying Workshop, La Jolla, CA, April 2015

10

maintenance costs, as well as staff-training 

requirements, have been prohibitively expensive 

for NMFS Science Centers.

Several other passive-acoustic devices have been 

used or developed by NMFS researchers. 

Acoustic recording tags, either the Woods Hole 

DTAG or the Greeneridge Sciences Acousonde,

are commonly used for behavioral-response 

studies. Volumetric towed-hydrophone arrays 

are being developed by staff at SWFSC and PIFSC 

for use during line-transect surveys to increase 

localization accuracy and efficiency, and to 

reduce bias associated with measurement of 

sound location in only two dimensions (Barkley et 

al., in review). Current prototypes are not 

operational for large-scale surveys, although a 

Small Business Innovation Research (SBIR) grant 

issued through the OS&T Ocean Acoustics 

Program to two separate firms in 2015 should 

help overcome the technological and engineering 

challenges that remain. The Drifting Acoustic 

Spar Buoy Recorder (DASBR; Griffiths and Barlow,

2015) is an autonomous, long-term, floating 

recorder similar in its capability to various 

stationary, autonomous, long-term recorders, but 

not tethered to the sea floor. The drifting design 

is intended to allow passive-acoustic sampling in 

very deep water and in the open ocean, where it 

is typically logistically infeasible to deploy 

stationary recording devices. These units are 

currently being developed and used for 

assessment surveys on the West Coast by the 

SWFSC. Use in very distant or remote locations is 

somewhat hindered by lack of consistent and 

low-cost satellite service for tracking the drifting 

unit. Also impeding the use of these units is the 

expense of recovery for units that may have 

drifted far from vessels capable of or willing to 

assist with recovery.
Passive Acoustic Surveying Workshop, La Jolla, CA, April 2015

11

Chapter 3 Stock Delineation

Distinguishing stocks and defining their 

boundaries is generally challenging, often 

requiring genetic or morphological differences 

among groups of animals to delineate putative 

stocks. Use of other lines of evidence for stock 

delineation has been gaining attention, including 

differences in vocalization characteristics among 

putative stocks. Geographic mapping of the

vocalization characteristics for some baleen 

whale and delphinid species has suggested that 

differences in vocalizations may be a promising 

avenue of pursuit for identifying putative stocks 

for further study using other non-acoustic lines of 

evidence. The workshop focused on the current 

capabilities, impediments and improvements 

needed in order to further the use of passive 

acoustics in stock delineation. Toward this end, 

the workshop developed specific 

recommendations for advancing this field of 

research.

Data and Technical Requirements

The MMPA defines “population stocks” or 

“stocks” as “a group of marine mammals of the 

same species or smaller taxa in a common spatial 

arrangement, that interbreed when mature.” 

The term “population stock” is not consistently 

defined within the scientific community, and the 

definition put forth in the MMPA leaves room for 

interpretation. NMFS has developed guidance 

for applying the MMPA definition (NMFS 2005). 

GAMMS II states that a marine mammal stock is a 

“demographically isolated biological population.” 

The guidance notes that “reproductive isolation is 

proof of demographic isolation” and that 

“[e]vidence of morphological or genetic 

differences in animals from different geographic 

regions indicates that these populations are 

reproductively isolated.” GAMMS II also 

recognizes that many types of information can be 

used to identify demographic isolation, including 

“distribution and movements, population trends, 

morphological differences, genetic differences, 

contaminants and natural isotope loads, parasite 

differences, and oceanographic habitat 

differences.” GAMMS II does not provide further 

guidance on how to consider or weigh these lines 

of evidence.

A NMFS Working Group, the Stock Delineation 

Guidelines Initiative (SDGI), has explored the 

strength of using passive acoustic datasets for 

stock delineation by taxa (Martien et al., 2015). In 

addition, the forthcoming SDGI Handbook 

provides guidance on the use of acoustic 

differences versus other lines of evidence for 

delineating stocks. Although the focus of the 

current passive acoustic assessment workshop 

was not on the strength of acoustic differences 

versus other lines of evidence, many of the 

considerations identified in the SDGI Handbook 

are relevant here as well. The species data tables 

from the SDGI Handbook were presented to the 

workshop. Also, some key examples were 

discussed at the beginning of the Stock 

Delineation session to provide context for what is 

ultimately needed to delineate stocks using 

differences in vocalization characteristics or 

geographic patterns of vocalization occurrence. 

At a minimum, positive differences in vocalization

characteristics among groups could be 

considered evidence for stock delineation if the 

differences are independent of geographic 

variation in prey preferences and other 

behavioral factors that may be mainly situational, 

and if vocalization characteristics are consistent 

over the stock range and through time. Changes 

in vocalization features through time may still be 

useful for delineating stocks. However, the 

change must be understood in the context of 

reproductive isolation, and comparisons between 
Passive Acoustic Surveying Workshop, La Jolla, CA, April 2015

12

putative stocks must be appropriate given the 

timing of changes in vocalization characteristics 

(i.e., comparisons across space at the same time, 

or during the same breeding phase).

The technical requirements for acoustic data 

collection for delineating stocks are no different 

than any other component of stock assessment

— recordings must be of adequate bandwidth 

with sufficient signal-to-noise ratio to facilitate

the detection and description of vocalizations. 

The geographic location and time of each 

recording is required, and the species from which 

the vocalizations are recorded must be known 

without error. It is advantageous to collect data 

with calibrated systems (known frequency 

response). Using these systems facilitates

measurement of bandwidth and amplitude and 

reduces the effects of system variability on 

measured characteristics.

Stock delineation using acoustics is in its infancy, 

with few examples of geographic variation in 

vocalization characteristics among groups that 

can be reasonably concluded to be driven by 

demographic independence rather than other 

factors. These factors include prey differences, 

seasonality, or other environmental or behavioral 

differences. Most examples of differences in 

vocalization characteristics among groups serve 

primarily to bound hypothesis tests that may be 

addressed with other lines of evidence, including 

genetics, movements or a combination of factors. 

Several baleen whale species are known to have 

song characteristics that vary geographically. 

These differences map nicely to genetic 

differences where adequate samples are 

available for comparison (e.g., blue whales;

McDonald et al., 2006). 

To the extent feasible, genetic samples should be 

collected from individuals heard producing 

specific sounds so that stock delineation may be 

tested both genetically and based on the 

differences in vocalization characteristics among 

groups. Collection of tissue samples from 

recorded individuals is not trivial, because it is 

often difficult to confirm that samples came from 

the vocalizing animal or even to locate individual 

vocalizing animals for sampling. The success of 

this approach varies across taxa and specific field 

situations. For migratory baleen whales, acoustic 

vocalization characteristics need to be measured 

across the range of breeding and feeding grounds 

and from multiple years to ensure that the full 

song repertoire has been sampled and described. 

For delphinids, social and foraging vocalizations 

should be collected across a broad range of 

behavioral and environmental contexts to ensure 

variations are not related to prey preferences or 

other environmental conditions, such as 

geographic or seasonal variations in background 

noise. For all assessments of stock delineation 

using passive acoustic datasets, data collection 

must be of sufficient duration and across 

sufficient geographic range to identify variability 

among individuals and within groups. 

Current Capabilities

The ability simply to collect passive acoustic data 

from marine mammal species is not sufficient to 

assess stock structure. Vocalization differences 

will likely need to be compared versus other lines 

of evidence to show that differences in 

vocalizations can be attributed to different stocks 

rather than related to geographic or behavioral 

differences within a stock. Most Science Centers 

have the capability to collect tissue samples and 

other environmental and behavioral data that 

may be required to use vocalization differences 

to delineate stocks. However, Science Centers 

vary in the degree to which passive acoustics 

programs and projects are linked to other data 

collection efforts. Assessment of stock structure 
Passive Acoustic Surveying Workshop, La Jolla, CA, April 2015

13

using passive acoustic data will be most 

successful when recordings are linked to other 

measures of behavior, prey, habitat, movements 

or genetic relatedness. Correlational studies may 

be feasible with sounds recorded on autonomous 

datasets, especially for those species whose 

sounds can be reliably identified to species 

despite regional variations in vocalization

characteristics. 

In general, stock delineation using passive 

acoustics occurs in an exploratory phase. The 

specific survey design requirements are not 

known and are likely to vary across taxa,

depending on the plasticity of the vocalizations 

and the ecology of the species or stock. 

Differences in vocalization characteristics at the 

species- and/or population-level have been 

identified for several taxa, primarily pinnipeds, 

baleen whales, some dolphins and beaked whales 

(Table 2), while for others it is not yet possible to 

identify any vocalizations to the correct family. 

Those species that exhibit population-level 

differences in vocalization characteristics appear 

to be those with identified mating-related signals, 

or those with very distinct echolocation clicks, 

likely related either to prey differences or 

morphological characteristics of the melon 

(Soldevilla et al., 2008; Baumann-Pickering et al., 

2013). Most population-level differences in 

pinnipeds have been observed through playback 

studies measuring response of males to territorial 

vocalizations of males from the same or other 

regions, or through the simple assessment of 

geographic variation across regions known to 

different populations based on other lines of 

evidence. Playback studies are more difficult to 

observe with cetaceans. Most assessments of 

stock delineation with cetacean populations have 

been correlational, typically relating changes in 

vocalization characteristics to the structure of the 

population measured using genetic analyses, or 

revealing potential structure that has not yet 

been tested with other lines of evidence. 
Passive Acoustic Surveying Workshop, La Jolla, CA, April 2015

14

Table 2. Capabilities and examples of acoustic differentiation of taxa, species, and populations.

Species / 

Group

Acoustically 

Identify 

Taxa?

Acoustically 

Identify 

Species?*

Examples / Exceptions Acoustically Identify Populations?

Pinnipeds Yes

Yes, generally,

using matingrelated 

vocalizations

Greater 

uncertainty with 

social and

foraging sounds

Several phocids can be identified to 

species

Fewer robust studies on eared seals

Harbor seals: Van Parijs et al., 2000

Bearded seals: Risch et al. 2007; Charrier et al., 2013

Australian sea lions: Attard et al., 2010

Weddell seals: Pahl et al. ,1997; Abgrall et al., 2003;

Terhune et al., 2008

Baleen 

Whales Yes

Yes, generally,

using matingrelated 

vocalizations

Greater 

uncertainty with 

social and

foraging sounds

Bryde's and sei whale vocalizations 

not well characterized

Overlap between bowhead and right 

whale sounds

Blue whales: McDonald et al., 2006.

Fin whales: Hatch and Clark, 2004; Castallote et al., 2012;

Delarue et al., 2009

Humpback whales: Cerchio et al., 2001; Garland et al., 2015;

but cultural transmission complicates assessment: Noad et al., 2000

Bryde's whales: Oleson et al., 2003; Širović et al., 2014

Minke whales: Mellinger et al., 2000; Gedamke et al., 2001;

Rankin and Barlow, 2005; Risch et al., 2014

Sperm 

Whale Yes Yes Watkins, 1980 Unclear. Patterns of coda usage among groups do not correspond 

with genetic structuring or geography: Rendell et al., 2012.

Kogia 

Not yet 

differentiated 

from porpoises 

and other 

narrow-band, 

high-frequency 

species6

Unknown Unknown

 6 E.g., cephalorhynchids, lagenorhynchids, or river dolphins
Passive Acoustic Surveying Workshop, La Jolla, CA, April 2015

15

Species / 

Group

Acoustically 

Identify 

Taxa?

Acoustically 

Identify 

Species?*

Examples / Exceptions Acoustically Identify Populations?

Beaked 

Whales Yes Likely Beaked whales: Baumann-Pickering 

et al., 2013, 2014 Unknown

Small 

Delphinds Yes

Few. More 

sophisticated 

classifiers and 

incorporation of 

behavioral 

information

required.

Tropical delphinids: Oswald et al.,

2003; Azzolin et al., 2013 

Risso’s and white-sided dolphins: 

Soldevilla et al., 2008

Bottlenose and spinner dolphins: 

Baumann-Pickering et al., 2010

Some evidence for Risso’s and Pacific white-sided dolphins: 

Soldevilla, unpublished

Others unknown

Large 

Delphinids 

(Blackfish)

Yes Most

Tropical blackfish: Oswald et al.,

2003

Melon-headed whales: BaumannPickering et al., 2010

Short-finned pilot and false killer 

whales: Baumann-Pickering et al.,

2015

Killer whales: Ford, 1991

Some evidence for false killer whales: Barkley, unpublished

Others unknown

Porpoise

Not yet 

differentiated 

from Kogia 

and other 

narrow-band, 

high-frequency 

species

Unknown Unknown
Passive Acoustic Surveying Workshop, La Jolla, CA, April 2015

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Impediments

Many species of marine mammals use stereotyped 

vocalizations. Although geographic variation in 

these characteristics has been suggested to 

correspond with population structure in some 

species, it can lead to erroneous conclusions about 

stock structure in others. For example, while 

differences in the acoustic properties of calls used 

for foraging could indicate local adaptation, they 

may also represent plasticity in response to habitat 

(e.g., Simard et al., 2010) or prey type (e.g., 

Johnson et al., 2007). Such plasticity could lead to 

incorrectly identifying multiple stocks in an area if 

animals that are part of the same stock use 

vocalizations with different characteristics when 

foraging in different regions within their range. 

Vocal characteristics have also been shown to 

change in response to the presence of boat traffic, 

differences in ambient noise, and/or interactions 

with other species (May-Collado and Wartzok,

2008; May-Collado, 2010; Tripovich et al., 2012;

May-Collado and Quiñones-Lebrón, 2014). These 

changes suggest that variation in the social or 

physical environment can create differences in 

acoustic characteristics that are unrelated to stock 

structure. 

The effectiveness of using passive acoustic datasets 

to define stocks may vary significantly among 

species (see Table 2), because particular

differences in the purpose of produced sounds, and 

their plasticity across environmental and 

behavioral states, may determine whether 

variation in acoustic characteristics is truly 

representative of population segregation versus 

localized or seasonal differences in prey, sociality 

or other factors. The mechanism of vocal learning 

is not well understood for marine mammals. 

Whether vocalization characteristics are passed 

vertically (from mother to offspring) or horizontally 

(between unrelated individuals) may affect the 

utility of acoustic differences for assessing stock 

structure (Musser et al., 2014). Cultural 

transmission of songs of humpback whales (Noad 

et al., 2000) or codas of sperm whales have 

complicated the assessment of population 

structure using acoustic characteristics for those 

species (Rendell et al., 2012). However, using 

acoustic characteristics to delineate stocks is a 

powerful approach because population-specific 

differences in acoustic characteristics could 

develop rapidly, reflecting current movement 

patterns, or structure that has developed recently 

relative to the very long time scales required to 

evolve sufficient differences to be detected using 

genetic or morphological methods (Hatch and 

Clark, 2004).

To date, no stocks have been designated under 

MMPA based solely, or even primarily, on acoustic 

differences between groups. The utility of acoustic 

datasets for stock delineation is likely speciesspecific. For many species, we are currently unable 

to distinguish among species using acoustic 

characteristics, so that finer-scale assessment of 

stock-level differences is currently not possible. 

Workshop participants discussed this and a range 

of other impediments to using vocalization

characteristics for stock delineation. 

Species identification

Most species of baleen whales produce speciesspecific vocalizations, though not all vocalizations 

are species-specific. A combination of social and 

breeding display vocalizations may be required to 

find acoustic differences among stocks. However, 

social sounds in baleen whales are highly variable, 

and in some cases, multiple species make similar 

vocalizations, meaning that the vocalizations 

cannot be attributed to a specific species with 

certainty. Sperm whales and most species of 

beaked whales are also known to produce speciesspecific vocalizations, although for sperm whales, 

coda sharing across populations has been 

observed, suggesting these signals may be 

inappropriate for stock delineation. In contrast, 

many delphinid species cannot yet be reliably 

identified by their vocalizations. Although most are 
Passive Acoustic Surveying Workshop, La Jolla, CA, April 2015

17

known to produce some combination of 

echolocation clicks, tonal whistles, and pulsed 

sounds, in many cases characteristics of these 

classes of sounds have not been described. For the 

Kogia, porpoises, Cephalorhynchus dolphins, some 

Lagenorhynchus dolphins, and river dolphins, 

narrow-band, high-frequency echolocation clicks 

are distinct from other taxa, but have not yet been 

shown to be species-specific, so that additional 

research is needed to quantify whether speciesspecific vocalizations exist and then identify the 

variation in those sounds across stocks. 

Behavioral information and seasonality

One of the most important aspects of using 

variation in vocalizations to assess marine mammal 

stock delineation is the behavioral context of the

vocalizations. Vocalizations produced by males as 

a breeding display may play a large role in mate 

selection, and therefore may be more directly 

linked to population structure. However, male 

breeding displays are subject to learning and may 

be influenced by neighbors, so that an individual 

whale may change its song to align more closely 

with another male’s. Such adaptation has been 

shown with humpback whales (Noad et al., 2000), 

and suggests that variation in song characteristics 

among humpback whale populations is likely 

meaningless for the purposes of assigning an 

individual whale to a specific population. Further, 

there appears to be seasonal and annual variation 

in song characteristics (e.g., McDonald et al., 2009;

Oleson et al., 2014) or song production rates 

(Oleson et al., 2007) among some baleen whales. 

The drivers of these changes may be persistent 

enough to be accounted for and therefore are not 

an impediment to stock delineation. However, 

these drivers must be understood before 

differences in song can be attributed to stocks 

rather than changes induced by the environment 

(e.g., Parks et al., 2007) or other behavioral factors 

such as motivation to attract mates, defend 

territories, or search for food. 

Conversely, foraging signals are more likely to be 

influenced by local prey resources and the need to 

adapt the echolocation signal to locate specific 

prey items most effectively. Clinal variation in prey 

availability that drives slight changes in 

echolocation characteristics may appear, if 

inadequately sampled, to be similar to differences 

between stocks. Understanding these behavioral 

questions is the most significant driver of data 

needs for the purposes of using vocalization data to 

delineate stocks.

Research Needs

Based on workshop discussions, the Steering 

Committee identified several recommendations for 

research that should advance delineation of stocks 

using passive acoustic datasets.

Data collection and archiving

Stock delineation studies in particular tend to rely 

on data from many locations and time periods, and 

potentially on data collected using different 

systems. To allow the comparison of such

datasets, detailed metadata and system-calibration 

information is necessary to avoid conflating 

differences among vocalization characteristics and 

those among recording hardware. 

Vocalization repertoire

Species identification is still challenging for many 

species, particularly for delphinids; however, for 

many baleen whales and beaked whales, multiple

stereotyped vocalizations have been identified. For 

those species, attention to quantifying variability in 

vocalization repertoires in various environmental 

and behavioral contexts should be particularly 

valuable for future assessment of stock delineation 

using acoustic data. Defining a stock’s vocalization

repertoire will be important in many contexts, 

including stock delineation. Further, measurements 

of vocalization characteristics and their variability 

across all marine mammal species is a necessary 
Passive Acoustic Surveying Workshop, La Jolla, CA, April 2015

18

step to make progress toward assessment using 

passive acoustic datasets. 

Further, building a library of sounds with extensive 

metadata will facilitate future research into 

population structure that uses vocalization

characteristics. Such a library, which could be 

housed at a single institution or distributed among 

various online resources such as MobySound, could 

archive representative samples of sounds from 

specific times and places. Workshop participants 

discussed whether contribution of sounds to an 

online archive could be used to satisfy Public 

Access to Research Results (PARR ) requirements, 

thereby making representative data available to 

the community, and facilitating comparison of 

sounds recorded from different populations or 

regions. Workshop participants felt that NMFS is 

especially well positioned to make a large 

contribution toward collecting and archiving the 

data required for examining stock delineation 

because all Science Centers have active passiveacoustic programs. Many of these programs work 

in tandem with other data-collection efforts (visual 

surveys that verify species, tissue sample collection 

for genetic analysis, collection of behavioral data 

for assessing context, and oceanographic sampling 

for assessing prey, etc.).

Behavioral studies

Understanding behavioral context of various 

sounds within a species repertoire is fundamentally 

important to determining which group or type of 

sounds will be most appropriate for stock 

delineation. For most baleen whales, it is likely 

that breeding displays are the best vocalization

types for assessing stock structure; however, the 

plasticity and context of some of these sounds may 

change seasonally. The workshop identified the 

need for cheaper, more cost-effective studies of 

acoustic behavior in general. Focal-follow studies 

and studies using a combination of tagging and 

acoustic monitoring are likely to yield great insights 

into the behavioral context of vocalization and 

provide links to population structure through 

concurrent collection of movement or other data 

types.

Combined studies

It was widely recognized among workshop 

participants that the greatest role passive acoustics 

can play with regard to stock delineation is to 

identify differences in vocalization characteristics 

that may represent stocks, and to use those 

putative stocks to set up hypotheses about 

population structure that may be tested using 

other types of data. The SDGI Workshop (Martien 

et al., 2015) identified differences in morphology, 

genetics and movement as strong indicators of 

population structure; and distributional hiatuses, 

contaminants, habitat differences, and association 

data to be medium strength indicators depending 

on the specific taxonomic group under study. 

Acoustic stock-delineation data collection or data 

analysis projects should be designed so that the 

results may be tested using one or more of these 

other data types.
Passive Acoustic Surveying Workshop, La Jolla, CA, April 2015

19

Chapter 4 Occurrence and 

Seasonality

Deriving the list of species that typically occur in a 

management area is a basic component of stock 

assessment. Evaluating the seasonal occurrence of 

species in a region is more difficult without regular 

surveys, and this is one area in which passive 

acoustics has excelled in its contributions toward 

marine mammal stock assessments. When any 

sound from a species is characteristic and welldescribed, its detection in an acoustic recording 

can provide the first known occurrence of that 

species in a region. A collection of detections over 

a longer time series helps to determine whether 

the species is common or rare and whether it

occurs year-round, seasonally or just infrequently. 

There are many examples of passive acoustic 

monitoring providing rich datasets from which 

species occurrence and seasonality have been 

evaluated, but there is more to be done in the 

field, especially as associations with habitat and 

environmental change become increasingly 

important aspects of stock assessment. The 

workshop participants discussed specific species or 

regional case studies that are ripe for assessment 

using passive acoustics. Participants also discussed

the technological improvements and impediments 

that need to be overcome to further the use of 

passive acoustics toward assessment of occurrence 

and seasonality. 

Data and Technical Requirements

Assessment of occurrence and seasonality using

passive-acoustic datasets minimally requires 

knowledge of the sounds produced by the species 

of interest. Occurrence may be assessed using any 

type of passive-acoustic dataset collected at a 

known location and time and with sufficient 

bandwidth to encompass the sounds of interest. 

Assessment of seasonality requires longer-duration 

datasets spanning several months to years, and a 

complete understanding of a species repertoire to 

ensure that seasonal occurrence is described 

accurately and not biased by monitoring only those 

sounds that are produced seasonally or within 

specific behavioral contexts. It is often necessary 

to collect data using calibrated systems, especially 

when accurate species identification requires 

comparisons among spectral features. 

Autonomous instruments excel at assessing 

occurrence and seasonality because they can be 

deployed at remote sites at relatively low cost. 

However, the hardware requirements for longterm monitoring are not trivial. In order to obtain 

an accurate representation of the recorded 

vocalizations, the sampling rate needs to be at 

least twice the highest frequency in the 

vocalization. At the low acoustic sampling rates 

that are sufficient for monitoring baleen whales 

(less than 5 kHz), there are many instrument types 

capable of multi-month duty cycling (turning 

recording on and off on a fixed schedule) or 

continuous recordings. However, at higher 

sampling rates (200 kHz) required for detection of 

sounds produced by delphinids and beaked whales 

or narrow-band, high-frequency species7 (greater 

than 300 kHz), there are few instruments capable 

of multi-month recording. Continuous acoustic 

sampling at 200 kHz using a single sensor collects 

nearly 1 terabyte (TB) of data per month. Duty

cycling can reduce data volume and allow longer 

overall monitoring duration. Duty-cycled 

recordings are typically required for year-round 

monitoring at remote locations, because currently 

available autonomous instruments are not capable 

of providing adequate power or data storage to

support continuous operations for such a long 

period. Repeated recovery and deployment of 

devices during the monitoring period is generally 

needed when continuous recording is required for 

a year or more. Cabled or remotely powered 

systems, such as most Integrated Ocean Observing 

 7 E.g., Kogia and porpoise species, Cephalorhynchus

dolphins, some Lagenorhynchus dolphins, and river 

dolphins
Passive Acoustic Surveying Workshop, La Jolla, CA, April 2015

20

System (IOOS) passive-acoustic sensors are not 

restricted by these power requirements. However,

they are often constrained by transmission 

bandwidth, preventing or delaying transmission of 

high sample-rate data. A general overview of fixed 

autonomous systems is provided in Appendix C, 

and a detailed overview of the development and 

current diversity in autonomous systems available 

as of late 2012 can be found within Sousa-Lima et 

al., 2013. New autonomous systems regularly 

become available through the development efforts 

of industry, academia, and non-profit organizations 

focused on passive acoustic technology.

Long-term data require significant computer 

processing power to analyze the data, whether 

accomplished with a human analyst and/or an 

automated detector and classifier. Various types of 

automated detectors may be employed to reduce 

analysis time when the characteristics of the 

sounds are well known and have low variability. 

The performance of an individual detection

algorithm must be well characterized to 

understand the potential bias it may introduce into

assessments of seasonality. Human scanning and 

analysis of passive acoustic datasets are common 

when the signals of interest are not well described

or are inconsistent. The development and 

implementation of automated detectors and 

classifiers are important components of all aspects 

of stock assessment using passive-acoustic 

datasets. 

Measurement or estimation of the detection range 

of sounds of interest is not commonly part of 

passive-acoustic studies designed to elucidate 

occurrence or seasonality. However, variations in 

detection range can bias the assessment of 

seasonality if changes in detection rate are due to 

habitat differences or changing environmental 

conditions, rather than changes in the number of 

animals in the monitoring area. 

Current Capabilities

All NMFS Science Centers own, or collaborate with 

partner institutions to use, various types of 

autonomous, long-term, fixed passive-acoustic 

recorders for the assessment of marine mammal 

occurrence. The list of ongoing projects within 

NMFS suggests assessment of occurrence and 

seasonality is one of the most common uses of 

passive acoustics within the agency. Many of these 

projects target specific species or locations, but 

few are capable of sampling the full range or 

seasonality of any species. Both archival and realtime systems are used within NMFS to assess 

occurrence and seasonality, although archival 

instrumentation is much more common given the 

challenges of maintaining real-time systems. 

Mobile autonomous sampling platforms such as 

acoustically equipped gliders and drifting recorders 

are being tested, a particularly important 

advancement for assessing occurrence in deep 

water where fixed moorings are difficult to deploy 

and maintain.

Within the wider acoustics community, many 

studies have employed passive acoustic 

technologies for assessment of occurrence and 

seasonality. These include a range of examples, 

from an assessment of seasonal occurrence of 

baleen whales in the Antarctic (Širović et al., 2009), 

to the occurrence and seasonality of up to 10 

species of beaked whales across the Pacific 

(Baumann-Pickering et al., 2014). Occurrence 

and/or seasonality studies have been done using 

passive acoustic datasets for nearly every species 

of marine mammal that can be identified based on 

its sounds. 

Impediments

Although passive acoustic monitoring has already 

played a significant role in the assessment of 

occurrence and seasonality of many marine 

mammal species, a number of issues remain that 

prevent the use of passive acoustic techniques for 

many species, locations or situations.
Passive Acoustic Surveying Workshop, La Jolla, CA, April 2015

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Instrumentation

The recording volume and battery capacity of 

available autonomous platforms often requires 

duty-cycled recording or regular instrument 

retrieval and redeployment to maintain the longterm time series of observations required to assess 

seasonality. Imposing a duty cycle increases 

monitoring duration, but comes at the cost of 

reduced detection probability, particularly for 

species that vocalize rarely or for very short 

periods. The impact of duty cycling will vary by 

species and situation, and passive acoustics studies 

requiring duty-cycled recording schemes must 

consider the impact on study design. Thomisch et 

al., 2015, found that subsampling of passive 

acoustic data could substantially bias acoustic 

presence estimates or affect the estimation 

accuracy for vocalization rates of focal species. 

Maintaining continuous data collection through 

regular recovery and redeployment of instruments 

typically is feasible only when monitoring locations 

are close to shore or on regular vessel transit 

routes. Monitoring for assessing occurrence or 

seasonality across a management region or other 

area of interest might require monitoring well 

outside areas where regular instrument servicing is 

feasible. At present, most PAM platforms used for 

assessing seasonality are deployed as stationary 

moorings. The limits of such moorings may bias 

assessments of seasonality and range, because it is 

logistically difficult to deploy moorings in very deep 

water, under or near ice, or in high-current regions. 

Mobile sampling platforms will be required to 

sample some of these regions effectively. 

Alternative mooring designs may also be required 

for monitoring in some locations. 

Species identification and vocalization

repertoire

The most fundamental requirement for assessing 

species occurrence using passive acoustics is the 

ability to recognize the vocalizations of the species 

within the acoustic record. Detection of sounds 

during visual sighting surveys provides an 

opportunity to collect this information and to 

establish occurrence. However, most assessments 

of seasonality are carried out from autonomous 

instrumentation without the aid of visual 

observers. The vocalization repertoires of many 

species are known only partially, and many 

vocalization types are detected that cannot yet be 

reliably assigned to species. It is rare that all 

vocalization types produced by a species are known 

and can be reliably classified as being produced by 

that species. A lack of information about a species’ 

vocalization repertoire limits the ability to draw 

conclusions about species absence, potentially 

even creating biases in the conclusions of a PAM

study. 

Behavioral context

Not understanding the behavioral context that 

guides the likelihood and rate at which sounds 

within a species repertoire are produced will also 

create bias in assessments of seasonality and 

range. When a species’ use of different 

vocalization types changes seasonally, the use of 

single vocalization types to document the 

occurrence of the species may not be reliable. For 

example, Oleson et al., 2007, monitored the 

occurrence of two blue whale vocalization types in 

Southern California — a mating-related song 

produced only by males in the summer and fall, 

and a foraging-related vocalization produced by 

both sexes in the spring and summer. Monitoring 

of just call type would have suggested a seasonal 

occupation of the area, when in fact they were 

present nearly year-round. Similar biases will exist 

for all other species’ vocalizations, so that 

knowledge of repertoire and context is required for 

the unbiased assessment of seasonality using 

passive acoustics detections of a species’

vocalizations. 
Passive Acoustic Surveying Workshop, La Jolla, CA, April 2015

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Automated processing and analyst 

variability

Seasonality studies often result in very large 

volumes of data that cover many months or years. 

Those data must be processed by humans, 

automated algorithms, or some combination of the 

two. Automated processing requires quantitative 

measurement of vocalizations of interest in order 

to create automated detection and classification 

algorithms. The challenges inherent in the 

development and use of automated detectors and 

classifiers are discussed several times within this 

report. The alternative is to have a human analyst 

scan the dataset or sub-samples of it. Even highly 

trained analysts are imperfect and will miss or 

misclassify sounds. Attaining an acceptable degree 

of certainty may require more than one analyst to 

scan the same dataset to quantify inter-analyst 

reliability. 

Detection range

The monitoring range around an instrument can be 

very large (hundreds of kilometers) for lowfrequency vocalizations heard across a flat-bottom, 

deep-water region. Or the range could be very 

short (hundreds of meters or less) when 

monitoring high-frequency directional sounds in 

dynamic bathymetry. Furthermore, within a 

maximum detection range, the probability of 

detecting a species’ sounds may vary temporally or 

spatially, thereby creating a variable effective

detection range (Buckland et al., 2001). The 

probability of detecting a species’ sounds will vary 

according to the volume of ocean being monitored. 

If the size of a monitored area and any changes in 

its effective size is unknown, then it is difficult to 

assess whether seasonal changes in vocalization

occurrence may be attributed to changes in the 

presence of animals producing vocalizations or 

changes in the monitoring area (as well as a 

number of other things discussed earlier). The 

choice of monitoring location may also bias 

seasonality assessments. Stationary moorings are 

often limited in their deployment depth so that 

they are inherently less likely to receive sounds 

produced by species that are found primarily or 

exclusively in deep pelagic waters. 

Research Needs

The following are the highest priority research 

needs for robust assessment of marine mammal 

occurrence and seasonality using passive acoustics:

• To determine presence/absence or 

seasonality with certainty, unambiguous 

species-specific vocalizations are needed. 

Geographic and seasonal variability also 

need to be characterized. Vocalization

repertoire libraries would facilitate needed 

research.

• A significant challenge to understanding 

seasonality is the need to disentangle the 

effects of seasonal vocalization behavior 

from seasonal occurrence, especially for 

baleen whales. Targeted behavioral 

studies are needed to understand seasonal

changes in context or vocalization

occurrence.

• The technology for long-term, bottomanchored recording systems is well 

developed, but is not sufficient for acoustic 

studies in the ocean’s vast pelagic basins. 

Additional development of mobile 

sampling technology is needed.

• Automated detectors and species 

classifiers are needed to effectively sort 

through vast quantities of acoustic data 

that can be collected with automated 

recording systems.

• Although species-specific vocalizations are 

well characterized for some species, little 

is known about the vocal repertoire of 

many others. Targeted sampling with 

visual verification of species ID is needed 

— especially for many Mesoplodon

species, Kogia species, porpoise, Bryde’s 

and sei whales, and many delphinids.
Passive Acoustic Surveying Workshop, La Jolla, CA, April 2015

23

• Models and quantitative methods are 

needed for combining visual and acoustic 

datasets and thereby providing validation 

of purely acoustic methods of determining 

occurrence and seasonality.
Passive Acoustic Surveying Workshop, La Jolla, CA, April 2015

24

Chapter 5 Long-Term Trends 

in Relative 

Abundance

Visual surveys have traditionally been the most 

prevalent method for obtaining abundance 

estimates in cetacean populations. Unfortunately, 

such visual surveys are conducted infrequently due 

to their high cost, and are restricted by their 

inherent methodological limitations (e.g., daylight, 

weather, sea ice, visual detection range, etc.; 

Thomas et al., 1986; Gillespie, 1997; Leaper and 

Scheidat, 1998). The acoustic techniques discussed 

at the workshop can overcome many of these 

limitations because data are relatively inexpensive 

to obtain and can be collected continuously for 

years on end, under ice cover and in any weather 

conditions or sea-states. 

Obtaining accurate absolute abundance estimates 

from passive acoustic data is challenging at best. A 

suite of statistical methods has been developed 

(Marques et al., 2012) but absolute abundance 

estimation from passive acoustic data (Chapter 6) 

relies strongly on detailed knowledge about the 

acoustics and associated behavior of a given study 

species. For most cetacean species, these aspects 

are relatively poorly understood. Therefore,

passive acoustic techniques are unlikely to replace 

visual surveys for obtaining accurate absolute 

abundance estimates in the near future. 

Nonetheless, acoustic data can be consistently 

analyzed to give comparatively easily obtainable 

measures of relative abundance, under strict 

assumptions (see the next section). Thus, the 

workshop focused primarily on the use of acoustics 

for assessing long-term trends in population 

abundance. Comparison of relative abundance 

estimates from individual locations across many 

years, whether collected by visual surveys (e.g.,

Noad et al., 2008) or acoustic surveys similar to 

those discussed here (e.g., Stafford et al., 2009; 

Širović et al., 2015), can provide an indication of 

population growth or decline. Comparison of 

relative abundance estimates within and between 

locations and years can additionally reveal trends 

in distribution and seasonal presence over time 

(Širović et al., 2004; Stafford et al., 2009). 

Data and Technical Requirements

Stock assessments under the MMPA include a 

requirement to provide for each stock, “the 

minimum population estimate, current and 

maximum net productivity rates, and current 

population trend.” Although the use of passive 

acoustics to obtain estimates of actual population 

size is discussed in the next chapter, here we focus 

on the potential for NMFS to use passive acoustics 

to assess population trends, and to determine the 

rate at which a population is increasing or

decreasing. 

Towed hydrophone arrays have been used 

successfully to estimate relative density differences 

within a survey region (e.g., Gordon et al., 2000); to 

extrapolate relative densities from regions with 

concurrent visual and acoustic surveys to regions 

with solely acoustic surveys (e.g., Gerrodette et al., 

2010); as well as to create habitat-based models of 

relative density (Fleming et al., 2013; Yack, 2013). 

One drawback of using mobile platforms for 

assessing long-term trends is the need to 

implement a large number of costly and logistically 

challenging repeat surveys to detect any larger 

population trends due to the inherent, potential 

short-term variability in population density (e.g., on 

the order of weeks to months). Although this may 

become more feasible in the future, in particular 

with the increased use of autonomous mobile 

platforms, workshop discussions focused largely on 

the more achievable near-term use of stationary 

data collection methods (e.g., moored, 

autonomous or cabled acoustic instruments). 

Stationary platforms are capable of collecting nearcontinuous or adequately sub-sampled long-term 

data over multiple years to assess trends in relative 

population abundance. The advantage of such 
Passive Acoustic Surveying Workshop, La Jolla, CA, April 2015

25

long-term datasets is that short-term variability can 

be averaged out.

The ability of passive acoustic approaches to detect 

trends in population abundance can vary widely. 

The resolution of detected trends can range from a 

very coarse estimation of whether a population is 

simply increasing, decreasing or remaining stable, 

to a much more refined quantification of the rate 

(e.g., percentage change) at which the change in 

relative abundance is occurring. The accuracy of 

any estimate of trend direction and rate will 

depend directly on survey design (number and 

placement of sensors); the validity of necessary 

ancillary data; and any associated assumptions 

made about the parameters required for absolute 

abundance estimation (e.g., the probability of 

acoustically detecting the focal species, the 

vocalization production rate of the focal species, 

and group size). If not explicitly estimated, the 

values of these parameters would have to be 

assumed (e.g., to be temporally and spatially 

constant) in order to infer animal abundance from 

the indices generated from the collected data. 

A wide variety of methods is available to detect 

individual vocalizations, or “cues.” A dedicated 

analyst can manually detect vocalizations over 

short time frames, but for longer periods, 

automated approaches such as spectral 

correlation, matched filtering, and energy 

summation methods (Mellinger et al. 2007) will be 

required. An alternative approach to detecting 

individual vocalizations is to measure the total 

amount of accumulated energy at whale 

vocalization frequencies through either power 

spectral density (PSD) or long-term spectral 

averaging (LTSA) analyses. Measures of individual 

detections and total accumulated energy at whale 

vocalization frequencies can independently provide 

an acoustic index related to the number of animals 

vocalizing. These measures have previously been 

used to assess changes in relative population 

abundance (e.g., Stafford et al., 2009; Širović et al., 

2015). In its simplest form, vocalization counts or 

energy measures from a single sensor can be used 

to assess changes over time. Over long periods, 

consistent changes in this acoustic index can 

indicate relative changes in the number of 

vocalizing animals. This index can also give a basic 

indication as to whether the population is 

increasing, decreasing or remaining stable. 

If these acoustic indices can be translated into a 

number of vocalizations or vocalizing individuals 

over a known area, more refined acoustic or 

vocalization density estimates can be calculated 

and compared. These estimates are preferred over 

simple vocalization counts or PSD values. In the 

case of vocalization or cue counts, they can be 

“distributed” over the known or likely detection 

range of the instrument by using soundpropagation modeling for a single instrument, or 

using the localization capability of an array of 

instruments. Here, the detection probability (a key 

parameter in a density-estimation framework) of 

cues can be estimated using a suite of statistical 

methods, most related to distance sampling (see 

Appendix F). In cases where energy measures such 

as PSD or LTSA are used, simulations can be run 

using a range of whale densities; information on 

vocalization parameters (typical source levels and 

repetition rates); and acoustic propagation 

modeling outputs to estimate how much energy 

would occur at the sensor. This exercise can then 

be reversed, using actual measured levels to 

predict inversely the number of vocally active 

whales present, which is still a relative abundance 

measure if non-calling animals in the population 

are not accounted for. It is critical to note that

both techniques depend heavily on the precision 

and accuracy of required parameters, the validity 

of underlying assumptions, and the quality of 

associated data (see “Impediments” and “Research 

Needs,” later in this section).

In order to conduct these analyses on the data 

collected, the most fundamental requirement is 

acoustically identifiable and regularly occurring 

vocalizations that are unambiguously species or 
Passive Acoustic Surveying Workshop, La Jolla, CA, April 2015

26

stock specific. For analyses using PSDs or other 

average energy measures, vocalizations must occur 

at a frequency where one can be relatively certain 

that most of the energy measured is from the focal 

species. If other species contribute significantly to 

the energy within the given frequency band during 

the analysis period, then it is difficult to assess how 

much each is contributing. For most species other 

than baleen whales, the small distances over which 

their sounds propagate likely limit their 

contribution to energy within a frequency band. 

Therefore, vocalization counts of individuals or 

groups will be a more effective metric to use, and 

the smaller detection ranges of these species must 

be accounted for in the survey design.

The requirements for data collection are 

straightforward. Recordings can be made from a 

variety of autonomous moored (e.g., HARPs, 

MARUs, or AUHs) or cabled platforms. In addition,

data must be collected at a sampling rate sufficient 

to allow measurement of the vocalizations of 

interest. Alternatively, specialized instruments that 

perform on-board processing and signal detection 

are available and can be used directly to obtain cue 

counts (e.g., C-POD click detectors). However, the 

detection algorithms and parameters of these 

instruments should be more transparently 

available and ideally empirically verified. In 

addition, to assess large-scale trends, recordings 

must be made over long time frames (preferably 

many years) in the same location and ideally with 

the same instrumentation (or at a minimum, 

carefully calibrated) to allow for effective 

comparisons over the period of data collection. 

Finally, there is a large amount of ancillary data 

which, when obtained, will allow for more refined 

estimates of relative abundance over time and 

ultimately absolute abundance, if all required 

parameters are estimated. These parameters

include: background noise measurements;

quantification of source levels and their variability;

acoustic propagation conditions around the 

sensor(s); acoustic behavior (including vocalization 

rates) of the species; demographic differences in 

vocalizing animals; density-dependent acoustic 

behavior (individuals vocalizing more or less in the 

presence of other vocalizing individuals); detection 

probability at different ranges from the sensor (i.e., 

effective detection ranges); and group size 

associated with vocalizations. As discussed earlier,

for assessments of relative abundance, some of 

these parameters can be dealt with through 

assumptions about their values (e.g., percentage of 

population vocalizing at any time or vocal behavior 

related to density), but as these assumptions stray 

further from reality, greater error is introduced 

into the estimates. 

Current Capabilities

A wide range of existing instruments are available 

that could be used in passive acoustic studies of 

trends in abundance to collect the baseline 

acoustic data (e.g., a variety of autonomous 

moored acoustic recorders, C-PODs, cabled 

hydrophone arrays, towed hydrophone arrays, or 

autonomous mobile instruments). There is a need, 

however, for further technology and software 

development in order to more effectively conduct 

these studies (e.g., instruments with on-board 

detection and real-time reporting capabilities, 

automated detection software; see Impediments 

section, next). There has also been more focus on 

analysis techniques in recent years to allow the 

measurements of acoustic indices to be translated 

into measures of relative abundance, and 

eventually absolute abundance. Investigators at 

the University of St. Andrews, Scotland, have led 

this groundbreaking research into survey design 

and statistical analyses (e.g., Marques et al., 2012). 

All NOAA Fisheries Science Centers have passive 

acoustic research programs and conduct passive 

acoustic research to varying degrees (Chapter 2,

Appendix B). Science Centers use various 

autonomous moored instruments (e.g., HARPs, 

MARUs, AUHs and EARs), towed arrays, and most 

recently, autonomous mobile instruments such as 
Passive Acoustic Surveying Workshop, La Jolla, CA, April 2015

27

gliders or drifting buoys (see Appendix C through 

Appendix E). All Science Centers are currently 

capable of conducting the types of analyses of 

acoustic data that can be used for the assessment 

of trends in relative abundance (e.g., autodetection of vocalizations of interest and PSD 

acoustic energy measures). However, an essential 

aspect of this type of study is an effective survey 

design that collects long-term, multi-year datasets 

from a sufficient number and appropriately placed 

set of stationary instruments (or systematic 

transect lines for mobile instruments). These 

studies must also use appropriate analyses to 

assess trends in relative abundance for the species 

of interest. Until these survey design and analysis 

techniques become more commonplace, 

researchers with this specific expertise, such as

those at the University of St. Andrews, will likely 

need to be consulted.

Impediments

Cost and personnel

Acoustic trends in relative abundance can be 

assessed from single sensors, provided the dataset 

is of sufficient duration. In contrast, a carefully 

designed survey with multiple sensors that enable 

the localization of vocalizing whales, or an increase

in the survey area, will likely have greater statistical

power to detect trends and greater accuracy and 

precision of any subsequent estimate of the rate of 

change. The greatest impediment to conducting 

these expanded studies is the cost of 

instrumentation and associated deployment and 

recovery costs (i.e., ship-time and personnel), along 

with the considerable time required for NMFS 

personnel to conduct the analyses. Currently, 

there is very little dedicated funding for acoustic 

research at the Science Centers. Most of their 

work is conducted using funds from external 

sources (e.g., BOEM, Navy and industry), which can 

shape the objectives of the research. In addition, 

the Science Centers have different numbers of 

personnel to support passive acoustic research, 

ranging from only one-fourth to three FTEs, with 

additional contractor support dependent on 

funding. For passive acoustics to be more fully 

integrated into the stock assessment process, 

additional dedicated research funding and support 

for additional FTE personnel will be required. 

Automated detection/classification 

routines

Directly related to the previous section in terms of 

personnel time required to conduct the analyses is 

the need for improved automatic detection 

algorithms. To assess trends in abundance, two 

levels of analyses must be conducted. The first is 

extracting an acoustic index in terms of 

vocalization/cue counts or measures of acoustic 

energy such as PSDs. The second level of analysis 

then takes these measures and uses them to make 

comparisons over time to assess trends. The first is 

the most labor intensive. An individual analyst can, 

in theory, go through the datasets visually logging 

the vocalizations of interest in long-term 

spectrograms. This, however, is simply not 

practical for the length of datasets that will be 

necessary to detect trends in abundance; 

therefore, automated detection routines will be 

necessary. These routines are currently being used 

at most of the Science Centers that collect longterm acoustic datasets. However, the Alaska 

Fisheries Science Center (AFSC) has had little 

success with automated detection routines and 

currently uses only manual scanning to detect 

marine mammal vocalization in the acoustic data it 

collects. However, there was consensus among 

workshop participants that running automated 

detection routines requires a high level of expertise 

and remains very labor intensive to minimize false 

detections. At the same time, it is important to 

maximize the ability to detect weaker vocalizations. 

These concerns, and the need to quantify false and 

missed detections, also apply to instruments with 

onboard detection and classification processing like 

the C-POD and DMON, and are particularly 

important for those instruments that do not retain 
Passive Acoustic Surveying Workshop, La Jolla, CA, April 2015

28

the raw acoustic data to ground-truth detections. 

Improved and consistently applied automated 

detection, classification, and localization routines 

will greatly increase the agency’s ability to conduct 

these types of analyses.

Species-specific vocalizations

In order to detect vocalizations, or measure the 

energy present in a whale-vocalization frequency 

band, species-specific vocalizations must be 

present for detection, and ideally should be the 

primary contributor to energy above ambient 

levels. Many baleen whales have species-specific, 

if not population-specific, vocalizations (see

Chapter 3). In addition, there is increasing ability 

to detect and discern those of various species of 

beaked whales. Therfore, the workshop noted the 

current difficulties in applying these passive 

acoustic techniques to most delphinid species. 

Acoustic behavior 

As with all other uses of passive acoustics 

examined at the workshop (absolute abundance, 

occurrence and seasonality, and stock delineation), 

well-defined, species-specific acoustic behavior 

remains one of the most consequential data gaps. 

Factors that can potentially introduce large errors 

into the interpretation of acoustic metrics include: 

1) Lack of knowledge about vocal rates of 

individuals, density-dependent acoustic behavior,

demographic variability in acoustic behavior, and 

the depths at which vocalizations are commonly 

produced; and 2) Changes in acoustic behavior over 

time (e.g., seasonal behavior) and space (e.g., for 

species with separate breeding and feeding areas) 

and in response to environmental changes (e.g.,

introduction of noise). Vastly simplified 

assumptions, such as assuming stable vocal rates 

over time or lack of density-dependence of 

acoustic behavior, can be used to obtain coarse 

relative abundance metrics that may indicate 

whether a population is increasing, decreasing, or 

remaining stable. However, even these basic 

metrics can be strongly influenced by the validity of 

underlying assumptions.

Research Needs

Although it is currently possible to coarsely

estimate trends in abundance even from singleelement, passive acoustic instruments (given 

known species-specific vocalizations), such 

estimates depend heavily on assumptions used to 

derive them. The following research needs were 

highlighted at the workshop as important data gaps 

to fill in order to reduce uncertainty, modify 

assumptions with empirical data, and ultimately 

increase NMFS’s ability to provide reliable relative 

abundance trends over time.

The first requirement of any type of passive 

acoustic analysis is to have knowledge of speciesspecific vocalizations that will distinguish a given

species from co-occurring species. Obtaining this 

knowledge requires sonobuoy and/or towed array 

surveys conducted concurrently with visual 

monitoring that allow vocalizations to be 

conclusively linked to a species or stock. Existing 

datasets examined for vocalizations or classes of 

vocalizations with distinguishing features (i.e.,

suitable for use in acoustic analyses such as these) 

that currently have an unknown source would be 

good candidates for further study.

Characterization of vocalizations, source 

levels, and directionality

An associated research need is the full 

characterization of identified species-specific 

vocalizations. In particular, a quantification of the 

range and distribution of source levels of 

vocalizations, and any directionality in these 

vocalizations, are important components that will 

allow for more accurate propagation modeling of 

these sounds. Effective propagation modeling, 

along with measurements of background noise and 

oceanographic parameters, such as sound speed 

profile and bottom composition surrounding 

deployment locations, will help refine estimation of 
Passive Acoustic Surveying Workshop, La Jolla, CA, April 2015

29

the probability of detection of these vocalizations 

at various distances from the acoustic instrument. 

Localization using multiple hydrophones 

(sonobuoys, towed arrays, or stationary 

instruments) with concurrent visual observations 

can be used to achieve these measures.

Acoustic behavior 

A common theme throughout workshop 

discussions was the limited understanding of 

various behavioral parameters characterizing 

cetacean acoustic behavior, and the critically 

important ramifications these could have for

results of passive acoustic analyses for stock 

assessment purposes. Essential data gaps include

individual vocalization- or cue-production rates; 

density dependence of vocalization rates; context 

related to acoustic behavioral changes (e.g., 

breeding, feeding, and noise); variability in acoustic 

behavior related to age, sex, or population

structure; and the relationship of group size to 

acoustic behavior. 

In some instances, assessing trends in relative 

abundance (as opposed to absolute abundance) 

may not necessarily require data to fill these gaps. 

For example, an assumption could be made that 

the ratio of vocalizing individuals to total 

population size is constant, although unknown. 

With this assumption, understanding differences 

between the sexes in vocal production is not 

necessary to estimate changes in relative 

abundance over time. The results, however, then 

become fundamentally dependent on these 

assumptions, and testing their validity is essential. 

Techniques to address these questions include 1)

vessel-based sonobuoy and towed-array surveys 

conducted concurrently with visual surveys and 

observation; 2) shore-based visual observation 

with concurrent acoustic monitoring; 3) localization 

with passive acoustic arrays of vocalizing 

individuals to assess density dependence of 

acoustic behavior; and 4) long-term acoustic tags 

to document individual behavior (e.g., vocalization

rates over time or depth of vocalization).

Improvement in automated detection 

routines

Running auto-detection software currently requires 

an experienced analyst and a substantial effort to 

adjust detector parameters to maximize detections 

of actual vocalizations while simultaneously 

minimizing false detections. In addition, it is 

difficult to generalize processing from one region 

or dataset to another. These factors have likely

limited the wider application of passive acoustics 

for stock assessments. Increased effort should be 

put into optimizing the detection algorithms for 

various vocalization types, making software more 

accessible to less experienced analysts, and 

ensuring future detector and configuration 

parameters are openly available for a range of 

researchers.

Simulations to assess performance of 

energy measures

The use of acoustic energy measures (e.g., PSDs or 

LTSAs) represents a promising and less laborintensive option for the use of passive acoustics in 

assessing trends in abundance (e.g. Širović et al., 

2015). These measures, however, do not detect 

individual vocalizations or animals. Rather, the 

total energy present in species-specific frequency 

bands is measured and then used to estimate the 

number of vocalizing animals required to produce 

the measured acoustic energy. Simulations can be 

run to test the ability of these metrics to detect 

changes in the relative abundance of the focal 

species. For example, simulations could include a 

range of densities of vocalizing individuals 

distributed around a passive acoustic sensor. 

Propagation loss from vocalizing individuals to the 

sensor can be modeled, allowing total received 

acoustic energy to be measured for each simulated 

density of the species, and the ability to measure

changes with varying densities assessed. The 

relationship between density and received energy 
Passive Acoustic Surveying Workshop, La Jolla, CA, April 2015

30

can then be applied to empirical measurements of 

energy to back-calculate the relative density of 

vocalizing individuals.
Passive Acoustic Surveying Workshop, La Jolla, CA, April 2015

31

Chapter 6 Absolute 

Abundance

Estimation Using 

Passive Acoustics

Estimating absolute density (number of animals per 

area) and abundance (number of animals in a 

defined area) are among the most challenging uses 

of passive acoustic data. Although the use of 

acoustics for cetacean density and abundance 

estimation continues to grow, it is still not routine 

and is not likely to replace visual sighting surveys 

for most species within the next decade. The 

workshop reviewed the data and technical 

requirements, current capabilities, and 

impediments for density and abundance estimation 

using passive acoustics, from which the Steering 

Committee developed specific recommendations 

for advancing this field of research.

Data and Technical Requirements

Most acoustic approaches to density and 

abundance estimation are based on distance 

sampling methods adapted for acoustic data

(Buckland et al., 2003; Marques et al., 2013). 

Distance sampling methods are so named because 

they depend on the estimation of detection 

probabilities as a function of distance from either a 

transect line (in line-transect surveys) or from a 

point (in point-transect surveys). The expectation 

is that the probability of detecting the acoustic 

signals made by an animal will decrease with its 

increasing distance from a detecting instrument 

(hydrophone). In distance sampling, distance is

generally estimated for every detection, and the 

change in detection probability with distance is 

estimated empirically from these observations. 

Other methods, such as spatially explicit capturerecapture, have different data requirements (see 

Appendix F). There have been some attempts to 

analytically estimate acoustic detection 

probabilities from estimates of source levels and 

models of sound propagation when empirical 

estimates of detection distances are not available 

(e.g., Küsel et al., 2011). However, that approach 

depends on a large number of assumptions. For 

beaked whales, novel non-distance sampling 

methods have been developed to estimate 

abundance by counting all starts of foraging dives 

within a defined study area (Moretti et al., 2006). 

The latter approach appears limited to the 

situation within a Navy range with an extensive 

array of seafloor-mounted hydrophones. For this 

reason, the workshop concentrated on distance 

sampling-related methods, including spatially

explicit mark-recapture.

Acoustic density estimation is typically based on 

detecting groups of animals, individual animals, or 

individual cues (in this case, vocalizations made by 

the animals). The data requirements and 

assumptions for each method differ, but a common 

requirement for use of distance sampling-related 

methods is the need to estimate detection 

probability as a function of distance, specifically 

horizontal distance from the hydrophone to the 

animal. Animal depth has to be estimated or 

assumed. Another common requirement for all 

density estimation methods is the ability to 

recognize species (or categories of species) from 

their vocalization types.

Group-based abundance estimation methods 

require an estimate of group size in order to 

estimate individual density or abundance (although 

group density can be estimated without this 

information). Purely acoustic methods to estimate 

group size are not currently available. As a result,

group size information often comes from other 

sources such as visual sighting surveys. If distance 

sampling is used, the distance to groups should 

theoretically be the centroid of the group. 

However, for large, spread-out groups the centroid 

may be outside the acoustic detection range and 

therefore difficult to localize. The group-based 

approach also requires an estimate of the fraction 
Passive Acoustic Surveying Workshop, La Jolla, CA, April 2015

32

of time that at least one member of the group is 

making sounds.

Individual-based density estimation methods do 

not require group-size estimates, which might be 

viewed as an advantage for this method. However, 

the method does require information for each 

individual, such as horizontal range. For large 

groups, this added requirement is likely to make 

individual-based methods impractical. Software 

such as PAMGUARD (Gillespie et al., 2009) and its 

predecessor, RainbowClick, can be used to track 

individual odontocetes such as sperm whales, using 

consistent changes in bearing angles with ship 

movement and inter-click intervals. However, this 

approach breaks down for groups with more than 5

to 10 individuals. The individual-based approach 

also requires an estimate of the fraction of time 

that individuals are making sounds.

Cue-count distance sampling methods are based on 

estimating the density of cues per unit of time. In 

this case, cues are vocalizations made by the 

animals (e.g., clicks km-2 hr-1

). This estimate is 

converted to animal density by dividing by the cue 

production rate (e.g., clicks hr-1

). Unlike group- and 

individual-based methods, cue-count methods do 

not require an explicit parameter for the fraction of 

time spent silent, but do equivalently require 

estimates of the cue production rate (which must 

incorporate periods of silence).

In addition to purely acoustic methods to estimate 

cetacean abundance, passive acoustics can be used 

in conjunction with visual sighting surveys (Barlow 

and Rankin, 2007). Combined visual and acoustic 

surveys from the same vessel provide improved 

ability to detect cetaceans that are either visible at 

the surface or completely submerged. The two 

semi-independent modes of detection can be used 

to estimate the probability of detection by either 

method as well as the probability of being missed 

by both methods.

Current Capabilities

All six NMFS Science Centers have at least some 

capabilities for towed hydrophone line-transect 

surveys and fixed or free-floating point-transect 

surveys (Appendix B). All Science Centers 

standardized on the same modular towed 

hydrophone, cable, and connector design in 2013. 

Some Science Centers have made improvements in 

hydrophone and preamplifier design and array 

geometry, and it will probably be necessary to restandardize occasionally to maintain inter-center 

compatibility and to facilitate equipment sharing. 

Towed hydrophone surveys are typically conducted

in conjunction with visual sighting surveys from the 

same ship, greatly decreasing the cost of surveys 

that use towed hydrophones. Autonomous

hydrophone recorders (anchored instruments, 

drifters, and gliders) currently being used at the 

Science Centers have not been standardized. The

field is changing rapidly, and currently there is no 

single device that can meet the various needs of 

each Science Center. 

Outside NMFS, most research on passive acoustic 

abundance estimation in the United States is 

sponsored by the U.S. Navy and is carried out at its

research facilities and by researchers at the 

University of California at San Diego, Oregon State

University (OSU), Cornell University, and others. 

Elsewhere in the world, the center for research on 

the use of passive acoustics for cetacean 

abundance estimation is at the Centre for Research 

into Ecological and Environmental Modelling of the 

University of St. Andrews in Scotland. The largest 

absolute abundance estimation project in Europe 

using passive acoustics is the multinational Static 

Acoustic Monitoring of the Baltic Sea Harbour 

Porpoise project, which used C-PODs to estimate 

the abundance of harbor porpoises in the Baltic 

Sea.
Passive Acoustic Surveying Workshop, La Jolla, CA, April 2015

33

Impediments

Currently, acoustic abundance estimation for 

cetaceans is in its infancy. This approach is not 

currently used for stand-alone abundance 

estimates in U.S. Marine Mammal Stock 

Assessment Reports. However, in a few cases 

acoustic methods are used in conjunction with 

visual surveys to estimate abundance. Most 

studies that have produced acoustic abundance 

estimates to date have typically involved small 

areas and can be viewed as pilot or demonstration 

projects. Greater spatial coverage is needed to 

provide representative samples of larger study 

areas in order to provide abundance estimates on 

an appropriate scale for stock assessment. The 

situation is similar in the rest of the world. 

Workshop members recognized this as a problem 

and identified a number of impediments to 

advancement in this field.

Behavioral information 

All acoustic abundance estimation methods 

described here require additional information on 

cetacean acoustic behavior. The required behavior 

information includes estimates of the fraction of 

time that groups and individuals are acoustically 

active; the rate at which acoustic cues are 

produced; and the seasonal, social, geographic, and 

depth- or density-dependent variability in cue

production rates. However, this information has

proven difficult to collect. For some cetacean 

species greater than approximately 4 meters in 

length, acoustic recording tags can be attached by 

suction cup to provide this data. For some 

cetaceans, focal follows may provide some of the 

needed information, at least during daylight hours. 

Direct observation may produce biased

representations of typical behavior because 

animals are easier to follow when they are in 

particular behavioral states, and because the 

observation vessel can affect their behavior. 

Acoustic-only tracking studies may also give a 

biased representation of behavior because they 

require the tracked animals to be acoustically 

active. Because animal behaviors vary with 

location, time of day, season, activities, and among 

individuals, behavioral studies must obtain large 

sample sizes to characterize acoustic behavior

adequately. Such studies are expensive. Densitydependent vocalization rates are particularly vexing 

for abundance estimation because abundance may 

not be linearly related to vocalization rates. Groupbased abundance estimation may be a more robust 

method for highly vocal delphinid species. 

Although individual behavior is variable, at least 

some group members may be vocally active at any 

given time, eliminating the need to estimate the 

fraction of time that individuals are vocalizing.

Species identification

All abundance estimation methods also depend on 

accurate species identification based on acoustic 

vocalizations. Prior research indicates that baleen 

whale species produce species-specific 

vocalizations, but not all of their vocalizations are 

species-specific. In addition, for some species, only 

males may produce species-specific vocalizations. 

Sperm whales make very distinctive echolocation 

clicks that can be easily recognized. All beaked 

whales that have been studied appear to have 

species-specific echolocation clicks. A few 

delphinids have species-specific vocalizations or 

echolocation clicks. However, species 

identification for most delphinids is problematic, 

with computer algorithms producing high 

classification error rates. Some taxonomic groups 

(porpoises, Cephalorhynchus8

, and Kogia9) produce 

similar narrow-band, high-frequency clicks that are 

distinguishable from those of other odontocetes. 

Although this is an area of active research, little has 

been published on distinguishing among these 

high-frequency species.

 8 Commerson’s, Heaviside’s, Chilean, and Hector’s 

dolphins 9 Pygmy and dwarf sperm whales
Passive Acoustic Surveying Workshop, La Jolla, CA, April 2015

34

Group size

The group-based abundance estimation methods 

require estimates of mean group size. Group size 

cannot be effectively estimated from acoustics 

alone, and the use of group sizes from visual 

surveys negates some of the potential advantages 

of acoustic surveys. Group sizes may vary 

geographically, diurnally, and seasonally, making

the extrapolation from one visual survey to 

another acoustic survey difficult. The extrapolation 

of visually estimated daytime group sizes to 

nighttime acoustic detections is a particular 

concern. Although visual estimates from ships may 

be the only available group-size information, these 

estimates are typically imprecise and may be 

biased (Gerrodette and Forcada, 2005). 

Distance estimation

The estimation of the distance from a vocalizing 

individual to a transect line or point is a critical 

element of all abundance estimation methods 

based on standard distance sampling. For towed 

hydrophone arrays, perpendicular distance to the 

trackline can be estimated accurately for a 

stationary sound source using changes in bearing 

angle, but distances may be biased if animals are 

moving. This is a particular problem for towed 

hydrophones because animals may be detected

after they have reacted to the presence of the 

vessel. The perpendicular distances estimated 

from typical linear towed arrays cannot distinguish 

between horizontal distances (needed for 

abundance estimation) and vertical distances. 

Assuming that an estimated perpendicular distance 

is a horizontal distance results in a significant bias 

when estimating density of species that vocalize at 

depth (e.g., beaked and sperm whales). The 

development of towed tetrahedral arrays may 

eliminate this problem and resolve the left/right 

ambiguity of localizations by towed arrays. Vertical 

hydrophone arrays can be used to estimate 

distance to a vocalizing animal, but this approach 

has seldom been implemented to date. Large 

spatial arrays of time-synchronized autonomous 

hydrophones can be used to localize vocalizing

animals and thereby estimate detection distance. 

However, the array spacing must be sufficiently 

dense to ensure that animals are recorded on at 

least three hydrophones. Clock drift in 

autonomous recorders is an impediment for 

accurate localization, and very accurate clocks may 

double the cost of autonomous recorders. 

Directional Frequency Analysis and Recording 

(DIFAR) sonobuoys and other types of pressurevector sensors can determine the bearing angle to 

a sound source with a single sensor, and thus can 

be used to localize animals and estimate distance if 

a signal is received on two receivers. Clock drift is 

not a significant problem for this method because 

it does not require accurate measurements of time 

difference of arrival. Currently, however, vector 

sensors are limited to low frequencies (less than

2 kHz), and their use is therefore limited to studies 

of baleen whales. Most methods of distance 

estimation require multiple hydrophones, which 

increases costs. Some research has been done on 

estimating detection distances for a single 

hydrophone based on sound propagation theory

(Küsel et al., 2011; Bonnel et al., 2014). This 

approach requires many assumptions or external 

measurements of sound-source levels and their 

variation, sound propagation conditions, 

directionality of the sound source, and 

distributions of animal orientation. These 

theoretical approaches are likely to be of limited 

value until they are empirically validated.

Combined visual and acoustic surveys

Although there are clear benefits of combining 

visual sighting surveys with towed hydrophone 

surveys, this approach is not without compromises. 

From a visual survey perspective, a towed 

hydrophone array reduces vessel maneuverability,

which is a particular concern as the ship 

approaches cetaceans for species identification and 

group size estimation (in a “closing mode” survey). 

In some cases, the array must be retrieved before 

other studies such as photo-identification and 
Passive Acoustic Surveying Workshop, La Jolla, CA, April 2015

35

biopsy sampling can begin, resulting in lost time 

and potentially lost opportunities. From an 

acoustic survey perspective, visual surveys in 

closing mode are not optimal. The orientation of 

the ship toward a group of cetaceans after a 

sighting is made (again in “closing mode”) limits 

acoustic detection range (acoustic reception is low 

along the axis of the array) and prevents acoustic 

estimation of range using changes in bearing 

angles. These conflicting needs often put visual 

and acoustic teams into conflict and result in poor 

cooperation between teams.

Research Needs

Considering the impediments to acoustic 

abundance estimation, described previously, the 

workshop identified research to help fill these gaps.

Behavioral studies

There is a need for more behavioral studies of 

vocalization rates; the fraction of time that 

individuals and groups are silent; and the seasonal, 

social, geographic, depth-dependent, and densitydependent variability in both the vocalization rates 

and periods of silence. More studies with acoustic 

recording tags on a wider assortment of cetaceans

would be helpful, but such studies are very 

expensive and sample sizes are typically limited. 

The workshop identified the need for less 

expensive, more cost-effective studies of acoustic 

behavior. Focal-follow studies and land-based 

observations, in conjunction with acoustic 

monitoring, were identified as potentially valuable 

for estimating the parameters needed for 

abundance and density estimation.

Species classification

Species identification is most challenging for small 

delphinids and porpoises. Additional information is 

needed on these species as well on underresearched beaked and baleen whales. Most 

species-classification algorithms have been based 

on tonal calls, pulsed calls, or clicks. Better species 

classification might be obtained by combining 

information from all three types of vocalizations, 

especially in the case of small delphinids.

Group size estimation

Members of the workshop did not identify clear 

alternatives to using mean group size estimates 

from visual sighting surveys. Nonetheless, 

additional research is needed to quantify temporal 

(diurnal, seasonal, and annual) and spatial changes 

in group size to determine the validity of 

extrapolating group-size estimates from one study 

to another. Visual estimates of group size can be 

improved by aerial photogrammetry from 

helicopters (Gerrodette et al., 2002) or unmanned 

aircraft.

Distance estimation

Range estimation typically requires localization of 

the sound source with respect to the hydrophone. 

This topic has been an important research focus in

the last decade. Many methods are available for 

different configurations of hydrophone arrays. 

However, with a single hydrophone, this empirical 

approach is generally not practical and theoretical 

models are needed. There is a need to validate 

such models with empirical observations.

Spatial extent and randomized survey 

design

Acoustic surveys need to be spatially extensive to 

provide abundance estimates for management. 

Broad-scale surveys are likely to require mobile 

hydrophones—towed arrays, gliders, or drifting 

arrays. Surveys should be designed with an equal 

probability of sampling every point within a study 

area. This method is a design-based survey

approach that typically is based on a systematic 

survey grid with a randomly chosen starting point. 

Combined visual and acoustic method

Because towed hydrophone arrays are already 

being used in conjunction with many visual sighting 
Passive Acoustic Surveying Workshop, La Jolla, CA, April 2015

36

surveys, there is undeveloped potential for using 

both sources of information for improved 

abundance estimates. The most direct approach 

might be to use an independent acoustic detection 

platform to help estimate the track-line detection 

probability (g(0)) for visual observers. Additional 

analytical developments are needed to deal with 

the potential negative correlation between 

acoustic and visual detection. Acoustic detections 

and localization can also be used in real time to 

increase the number of detections for abundance 

estimation, particularly for rare species like false 

killer whales (Bradford et al., 2014). Clearly, 

combined surveys are the best way to obtain 

acoustic recordings from known species for 

developing better species-classification algorithms.
Passive Acoustic Surveying Workshop, La Jolla, CA, April 2015

37

Chapter 7 Conclusions and 

Recommendations

Following the workshop, the Steering Committee

met to discuss findings and to develop general 

recommendations for future development of 

passive acoustics to support stock assessment 

efforts by NMFS. Two primary areas for 

improvements were identified—investment in new 

or improved infrastructure and the need for 

additional research and development (R&D). 

Encompassing the issues of infrastructure and R&D 

is the need for the strategic development of this 

technology and its resourcing. A strategic 

approach to developing and using the technology 

needs to be integrated across NOAA, involving each 

NMFS Science Center, Leadership, OS&T in NMFS 

headquarters, and the Office of Marine and 

Aviation Operations. In addition, the Steering 

Committee suggested that the development of the 

technology could be facilitated by a new working 

group within NMFS that would serve a similar role 

as the ASTWG; that is, by coordinating and 

supporting research into advanced survey and 

sampling technologies for marine mammals.

Infrastructure Investment

As with many research areas within NMFS, passive 

acoustics requires investment in infrastructure. 

Passive acoustics research and the use of passive 

acoustics to support marine mammal stock 

assessment requires access to equipment, lab 

facilities, software, field research platforms, 

training, data archiving resources, and 

computational capacity. Most of the development 

of passive acoustics capacity within NMFS has 

relied on peripheral funding and outside 

collaborations. Development of those capabilities

varies among Science Centers and lags behind the 

capacity of other research technologies that 

provide data used in stock assessments. The 

mature development of passive acoustic capacity 

within NMFS will require strategic and dedicated 

investment in infrastructure. A mature system will 

include state-of-the-art facilities and capacities for 

the development and testing of new technology 

(platforms, sensors, and analytic tools);

maintenance of operational technology; training 

opportunities; deployment and retrieval of devices;

storage of data; and processing and analysis of 

those data. Some of the most important elements 

necessary to achieve this vision are discussed in the 

next section. However, it is important to recognize 

that NMFS’s primary focus is on the 

implementation of the technology, and secondarily 

on its development. Currently, most of NMFS’s

development activities are undertaken in 

collaboration with universities and industry. It will 

be important for NMFS to balance its internal 

development investments with external 

investment activities.

Recognition of importance of passive 

acoustics 

Passive Acoustics FTEs. Across NMFS,

approximately 31 individuals are involved in 

passive acoustics research. However, just over 

eight FTEs are dedicated to this area. The SWFSC 

has three FTEs, the AFSC has two FTEs, and the 

Northwest Fisheries Science Center (NWFSC) has

one and one-half FTEs, but two Science Centers 

have less than one each. Most passive acoustic 

“personnel” are contractors, graduate students, or 

affiliates paid with external funds. One Science 

Center, NEFSC, has seven and one-half individuals 

working on passive acoustics, but the average is 

just under four, and one Science Center, NWFSC, 

has only one. In most cases, the temporary 

employees conduct the majority of passive 

acoustics research, making it difficult to build 

capacity and knowledge within NMFS and to retain 

institutional knowledge of the technology and 

research. In addition, NMFS personnel are not able 

to spend enough time on passive acoustics 

development and research to build their expertise

in the field fully. The mature development of 

passive acoustics capacity within NMFS will require 
Passive Acoustic Surveying Workshop, La Jolla, CA, April 2015

38

a substantially larger force of NMFS personnel 

primarily tasked with the development, testing, 

and operationalization of passive acoustics for 

stock assessments.

Development of New Funding Sources. The lack of 

sufficient dedicated passive acoustic FTEs reflects 

to some degree a still developing recognition of the 

importance of passive acoustics within the agency, 

but also a shortage of funding for stock 

assessments in general. For passive acoustics 

capacity to grow to meet its demand, substantially 

increased funding is required. Funding is required 

to fill the additional FTEs with highly qualified 

bioacousticians, pay for the development of the 

next generation of passive acoustics technology, 

secure and equip the bench and testing space for 

that development, and to build/lease/purchase the 

platforms necessary to collect the acoustic data 

needed for stock assessments and related 

research. 

Funding currently comes from a variety of internal 

and external sources. Internally, resources are 

provided primarily by the Science Centers, OS&T,

and the Office of Protected Resources (OPR). 

Within the OS&T, the Oceans Acoustics Program 

and the ASTWG are particularly important. 

Improved funding for the Oceans Acoustics 

Program would foster the proposed development 

and capacity-building. Although the ASTWG has 

provided a number of grants that have supported 

the development of passive acoustics for marine 

mammal research, their primary focus has been on 

new technology to sample fish. Increasingly 

advanced survey technology is needed to support 

the assessment of marine mammal populations 

and research into the impacts of human activities. 

In addition to passive acoustics, the development 

of unmanned aerial vehicles, genomics, hormone 

analyses, and habitat modeling are just a few of the 

advanced survey/sampling technologies that are 

growing rapidly. 

External funding comes primarily from the 

Department of the Navy and the Bureau of Ocean 

Energy Management (BOEM). The reliance of the 

different Science Centers on the various Navy 

commands (e.g., Office of Naval Research (ONR), 

Living Marine Resources, or the Fleets) varies 

among the centers. NMFS’s partnerships with 

these agencies are very important to advancing the 

development of passive acoustics and its 

application to marine mammal research and 

monitoring. The Navy and BOEM bring substantial 

resources to these partnerships, with the Navy also 

bringing expertise in passive acoustics, and NMFS 

bringing bioacoustics and biological expertise. 

Although the Navy and BOEM provide large sums 

of critically needed funding for passive acoustics, 

two problems need to be addressed. First, fund 

transfers can be complicated and carry a heavy 

administrative load, which could be addressed by 

streamlining the memorandum of understanding

process. Second, the funds are understandably

focused on the needs and challenges faced by the 

Navy or the energy industry. Because those needs 

and challenges can change frequently over time, it 

can be difficult for NMFS to sustain technology 

development and research efforts when relying on 

these fund sources. Additional strategic effort is 

needed to establish partnerships with the Navy and 

BOEM that will support long-term efforts in

technology development that will meet the needs 

of all of the partners.

NMFS acoustic research receives little direct 

funding from non-governmental sources, in part 

because of the administrative difficulty in 

transferring private funds to the government. The 

oil and gas Exploration and Production Sound and 

Marine Life Joint Industries Program (JIP) has 

funded the private and university-based 

development of software tools for cetacean 

surveys and species recognition, most notably the 

software platform PAMGUARD. This indirect 

support has benefitted NMFS acoustic assessment 

research. NMFS should consider developing 

collaborative relationships with organizations such 
Passive Acoustic Surveying Workshop, La Jolla, CA, April 2015

39

as the National Fish and Wildlife Foundation 

(NFWF) and Small Business Innovation Research 

(SBIR) program, and with private sector 

organizations, where a conflict of interest can be 

avoided, to promote the further development of 

passive acoustics for marine mammal research.

Improving infrastructure 

Technology Development Partnerships. Because 

the field of passive acoustics is relatively young, 

new technologies and methods are being proposed 

and tested regularly. As the use of passive 

acoustics matures and transitions from pilot 

projects to implementation, there is a need to 

assess different approaches and invest in the 

subset of possible methods that show the most 

promise. Standardization has a number of benefits 

for NMFS, including economies of scale, building 

equipment pools, equipment and expertise sharing, 

and ensuring comparability and compatibility of 

datasets. Investment in some technologies (e.g.,

sophisticated gliders) can exceed the resources of 

individual Science Centers and might be managed 

more efficiently by a centralized group within 

NMFS. Alternatively, various Science Centers could 

be made the home for development, training, and 

maintenance of particular technologies (e.g., towed 

arrays, fixed moorings, gliders, etc.). 

The development of passive acoustics technology 

and uses in the field has proceeded at different 

paces and in somewhat different directions at the 

various NMFS Science Centers. This non-uniformity 

has impeded the sharing of equipment, 

information, and knowledge among Science 

Centers. In 2012, the SWFSC sponsored a 

workshop on the development of standardized 

methods for the construction and use of towed 

arrays. The workshop proved very successful at 

equalizing knowledge and experience across 

Science Centers and at establishing an equipment 

standard that has enhanced sharing among Science 

Centers. Other areas of technology development 

could similarly benefit from workshops designed to 

share knowledge and standardize equipment and 

field methods. Examples are glider technology, 

data archiving, and DCL analyses.

Raw Data Archiving Support. The use of passive 

acoustics results in the collection of large amounts 

of digital data that need to be stored for later 

analysis and archived. For example, a

4-hydrophone array monitoring dolphin 

vocalizations over a 400 kHz bandwidth could 

generate 1 TB of data every 2 days. Currently the 

Science Centers generally use external hard drives 

to store and archive their acoustic data using local 

protocols. That system leaves data vulnerable to 

loss and impedes the sharing of data and 

combining of data sets. NMFS should develop a 

standardized protocol for storing passive acoustic 

data and support the distributed infrastructure 

required to securely store and archive those data. 

This capacity should be standardized and 

developed in-house and in collaboration with the

NCEI. The pilot study undertaken by the Alaska and 

Northeast Science Centers and NCEI will provide 

standards, guidelines, and important process 

lessons. 

Secure Data Access and Serving. In response to a 

request from the U.S. Navy, NOAA Fisheries has 

agreed to follow several data-handling protocols to 

ensure that acoustic data that may contain 

sensitive information is not released publically. 

These protocols include the secure, locked storage 

of potentially sensitive data until the Navy reviews 

those data and approves them for public release. 

This step requires NMFS researchers to copy all 

requested data and securely transport the datasets 

to Navy facilities for review. If some data are 

deemed sensitive, these data must be maintained 

separately in a secure, locked facility and cannot be 

released. 

The Federal Government is also required by the

new PARR policy to make all data publically 

available. Both of these requirements are 
Passive Acoustic Surveying Workshop, La Jolla, CA, April 2015

40

unfunded and require staff time and new 

facility/hardware capabilities.

Random Deployment Capacity. The estimation of 

the population/stock sizes of marine mammals 

requires surveys of large areas because the ranges 

of most species are extensive. Unbiased sampling 

requires the randomized placement of sampling 

locations or, when environmental features 

significantly affect abundance, randomized 

placement within strata. For efficiency, systematic 

sampling grids, transect lines, or sampling stations 

can be used if their placement is randomized. 

Although this is standard protocol for towed 

acoustic surveys conducted in conjunction with 

visual sighting surveys, the random placement of 

autonomous acoustic recorders within a large 

study area will require additional resources. These 

resources include dedicated NOAA or charter 

vessel time, mooring with acoustic releases, 

drifting recording systems, broad-scale glider 

surveys, etc. 

Targeted Studies

The use of passive acoustics to survey marine 

mammals is promising but still requires

considerable research in a number of areas. Based 

on the workshop discussions, the Steering 

Committee identified the need for research studies 

targeted on particular science gaps or needs.

Classification—species/stock 

identification capability

Detecting acoustic signals from marine mammals is 

of limited utility if they cannot be classified to 

species or stock. The capacity to identify the 

vocalizations of a species or stock varies 

taxonomically. Careful research that pairs visual 

identification with acoustic detections, or the 

placement of recording tags on marine mammals, 

has allowed researchers to identify the 

vocalizations of many species and stocks. Most 

species of baleen whales produce species-specific 

vocalizations, although not all vocalization types 

are species-specific. However, the distinctiveness 

of a vocalization may be environmentally or socially 

dependent or linked to gender. Sperm whales and 

most species of beaked whales produce speciesspecific echolocation clicks, but many delphinid 

species cannot be reliably identified by their 

vocalizations. The narrow-band, high-frequency 

echolocation clicks of Kogia, porpoises, 

Cephalorhynchus dolphins, some Lagenorhynchus

dolphins, and river dolphins are distinct from other 

taxa, but have not yet been shown to be speciesspecific. 

Classification relies on the ability of an analyst or 

computer algorithm to identify a vocalization as 

coming from a particular species or stock. This 

identification can be made by pattern matching or 

the statistical comparison of acoustic features of 

the signals. However, as just described, only some 

vocalizations have been associated with particular 

species or stocks, and for many species, speciesspecific vocalizations have yet to be identified. In 

addition, vocalizations that an analyst can identify 

may defy automatic classification by computer 

algorithms. These problems currently limit the 

usefulness of passive acoustic data for stock 

assessment. The ability to distinguish species by a 

single vocalization type varies among vocalization

types and species. 

Because NMFS is responsible for conducting stock 

assessments of every species and stock of 

cetaceans and most pinnipeds in the U.S., 

comprehensive knowledge of their vocalizations is 

required. NMFS should take a leadership role in 

developing a comprehensive catalog of marine

mammal vocalizations and species/stock 

repertoires. That development would encompass 

several elements, such as the specification of 

vocalization types, guidelines for obtaining full 

repertoires, specification of the metadata to be 

kept, and the construction of the infrastructure 

necessary to house the catalog and to make it 

easily accessible to researchers. The catalog could 

be housed at a single institution or distributed 
Passive Acoustic Surveying Workshop, La Jolla, CA, April 2015

41

among several, with a website that would allow 

researchers to access the data. Such a repository 

of acoustic data should, at least partially, satisfy 

PARR requirements for passive acoustic research.

10

Researchers, statisticians, and mathematicians are 

always exploring new and promising algorithms for 

the automatic and real-time classification of marine 

mammal vocalizations. Because of the very large 

time commitments needed to analyze passive 

acoustic data, the full integration and use of 

passive acoustics to support stock assessment will 

require the development of efficient automatic 

detection and classification algorithms. NMFS 

should identify and contribute to the development 

of the most promising algorithms. Finally, NMFS 

should further focus on signal classification in 

particularly high-need cases, such as the 

classification of delphinid whistles, beaked whale 

echolocation signals, and the differentiation of 

similar vocalizations in closely related species (e.g., 

the gunshot calls of bowhead and North Pacific 

right whales). 

Behavioral acoustics

The detection, classification, and localization of 

marine mammal vocalizations depend on those 

signals being consistent and predictable. However, 

it is well known that the types of vocalizations and 

their characteristics can change significantly in 

different circumstances. For example, receivedlevel can change depending on the type or 

directionality of the vocalization and the 

orientation of the animal with respect to the 

hydrophone. In addition, vocalization types and 

rates can change in different social contexts, 

locations, depths, ecological situations, or seasons. 

Vocalizations can be sex-specific and can be 

affected by anthropogenic noise. The rate at which

individuals vocalize can be a critical variable in 

 10 In 2013, the White House Office of Science and 

Technology Policy released a memorandum requiring 

federal agencies to develop plans for public access to 

research results (PARR).

estimation of density, but that rate can vary by 

orders of magnitude depending on a range of social 

and environmental factors. One of the most vexing 

problems stems from the fact that vocalization

rates can depend on the density of animals

(density-dependent vocal behavior), which can lead 

to severe biases in abundance estimates if it is not 

corrected for. 

Research is critically needed to understand how 

ecological and social environments can affect 

marine mammal vocalizations, if those data are to 

prove useful in stock assessments. The research

required depends on the aspect of stock 

assessment being addressed. For example, 

determining which vocalizations within a repertoire 

are most characteristic of a population is important 

for stock delineation. However, identifying a 

species’ repertoire is not essential for abundance

estimation. Conversely, vocalization rates are 

critical to estimating absolute abundance but less 

so for stock delineation. Understanding the role 

factors such as vocalization rate play in the 

variance and bias of measures such as population 

density is critical. Studies that link behavioral 

observations, the collection of ecological data, and 

the recording of vocalizations of tagged marine 

mammals are necessary to provide the required 

information. However, studies that require tagging 

animals are expensive and generate relatively small 

sample sizes. Alternative research approaches, 

such as focal follows and land-based observations 

paired with acoustic monitoring, require

investigation.

Range estimation

Estimation of the distance from the hydrophone or 

a transect line to the source of a vocalization (i.e., 

the range) is critical to the estimation of density. 

When multiple hydrophones are used in linear, 

two-dimensional or three-dimensional arrays, then 

differences in the timing of the arrival of signals at 

the hydrophones can be used to estimate the 

bearing angle. With multiple vocalizations over 
Passive Acoustic Surveying Workshop, La Jolla, CA, April 2015

42

time, the convergence of bearing angles in a 

moving array can be used to estimate the range. 

However, other techniques must be used when 

single hydrophones or stationary small-aperture 

arrays are used, as with autonomous floating PAM 

systems. One approach in this situation is to model 

sound propagation based on assumptions about 

the source levels of the signal and physical 

characteristics of the water and bathymetry. 

Another approach is to use multipath signals such 

as those from surface/bottom reflections and 

sound refraction. Both approaches have promise, 

and additional testing and validation is required 

before these methods can be used in practice.

Detection probability and validation

The application of distance-based sampling theory 

to the estimation of marine mammal densities 

from acoustic data collected along transects often 

requires the estimation of detection probabilities

that are specific to particular taxa and situations. 

Research effort is needed to estimate detection 

probabilities for most taxa and to understand how 

those probabilities vary in time and space, and in 

response to different environmental, ecological,

and social factors. Further research is needed to 

validate those estimates using tagged animals, 

where all vocalizations from an animal are logged 

and animal position from the hydrophone is 

measured at each vocalization, so detection 

probability can be estimated empirically. 

Automated analyses and quantitative 

performance measures

Several researchers have developed software 

packages that automate the analysis of acoustic 

data, particularly the detection and classification of 

signals. However, detection and, especially,

classification can be very difficult. Distinguishing 

coherent signals from background noise is 

problematic in many situations. In addition, the 

identification of the species or stock that produced 

the signal can be highly error-prone for a variety of 

reasons explained earlier in the stock delineation 

chapter (Chapter 3). It is difficult to know, 

however, when a classifier is good enough to use. 

Research that would establish performance 

measures and guidelines should improve the 

usefulness of many classifiers. In addition, 

research is needed to assess whether those 

performance measures could be used to 

compensate for the error rates experienced by 

some classifiers.
Passive Acoustic Surveying Workshop, La Jolla, CA, April 2015

43

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Acknowledgements

We want to express our heart-felt thanks to the 

workshop participants who gave freely of their 

time and expertise, and in some cases traveled a 

long distance to attend. NMFS’s Southwest 

Fisheries Science Center provided excellent 

facilities for holding the workshop, and the 

Center’s Marine Mammal and Turtle Division 

Director, Dr. Lisa Ballance, kindly opened the 

workshop and provided the participants with 

background and context. Several individuals at the 

Southwest Fisheries Science Center contributed 

their time and effort to make the workshop a 

success. Shannon Rankin put in an amazing 

amount of work, even while sick with the flu, to 

organize all of the local meeting logistics. In 

implementing the plans for and running the 

workshop, Shannon had considerable help from 

Jennifer Keating and Emily Griffiths, who made sure 

that everything we needed was available when it 

was needed. Ravi Shiwmangal was quite helpful in 

setting up the audio and making sure that 

everything electronic within his control ran 

perfectly. In addition, we had the assistance of 

four graduate students (Amy Van Cise, Anne 

Simonis, Eiren Jacobson, and Eric Keen) who 

volunteered to take notes.
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Appendix A Participants

Note: An asterisk after a participant’s name indicates that he/she is on the Steering Committee.

Jay Barlow, Ph.D.*

NOAA Fisheries – Southwest Fisheries Science Center – Marine Mammal and Turtle

Division – EEZ Mammals and Acoustics Program

Expertise: Population dynamics

Taxa/species: Marine mammals and sea turtles

Dr. Jay Barlow is a research scientist within the EEZ Marine Mammals and Acoustics Program at the

Southwest Fisheries Science Center (SWFSC), La Jolla, CA, where he has worked for 33 years. Jay received 

his Ph.D. from Scripps Institution of Oceanography (SIO) in 1982. He is also an Adjunct Professor at SIO. Dr.

Barlow’s research is directed primarily at assessing human impacts on marine mammal populations, 

estimating their abundance and dynamics, understanding the role of mammals in marine ecosystems, and 

developing survey methods that use passive acoustics to detect and localize cetaceans.

Simone Baumann-Pickering, Ph.D.

University of California at San Diego – Scripps Institution of Oceanography

– Behavioral Acoustic Ecology Lab

Expertise: Long-term PAM, signal description and classification

Taxa/species: Odontocetes

Dr. Simone Baumann-Pickering is an Assistant Research Scientist at Scripps Institution of Oceanography. 

Her focus is on the behavioral ecology of marine organisms using passive acoustic methods. Dr. BaumanPickering has experience in signal description, acoustic species discrimination, and automatic signal 

detection and classification, particularly of odontocete echolocation signals. Recently, she has been 

involved in improving and comparing methods for density estimation of beaked whales using stationary 

long-term passive acoustic sensors in the Gulf of Mexico.
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Mark Baumgartner, PhD

Woods Hole Oceanographic Institution – Biology Department

Expertise: Biological oceanography, ecology of cetaceans 

and zooplankton

Taxa/species: Cetaceans, particularly baleen whales

Dr. Mark Baumgartner is a scientist at the Woods Hole Oceanographic Institution (WHOI) specializing in top 

predator ecology and the physical and biological oceanographic processes that allow those predators to 

survive in the ocean. He focuses much of his research on baleen whales and their zooplankton prey as a 

tractable system in which questions can be addressed about how prey behavior, life history, and 

aggregation mechanisms can influence top predator distribution and behavior. Mark has been using 

passive acoustics from autonomous platforms to assess whale occurrence in his studies, and has recently 

developed a capability to report in near real time the calls of several baleen whale species for both scientific 

and conservation applications.

Jessica Crance, M.S.

NOAA Fisheries – Alaska Fisheries Science Center – National Marine Mammal Laboratory

Expertise: Acoustic detection, classification, localization of marine mammals

Taxa/species: Marine mammals (emphasis on Arctic species)

As the lead research assistant and project manager for the acoustics program at the National Marine 

Mammal Lab, Jessica is involved in all aspects of data collection, management, and analysis for several 

projects. She has experience in the deployment and analysis of three acoustic platforms (moored 

recorders, sonobuoys, and towed arrays), and has acted as Chief Acoustic Scientist on field surveys in the 

Alaskan Arctic. Through her analysis of long-term passive acoustic recorders, she helps provide information 

on the seasonal distribution of marine mammals in the Arctic and sub-Arctic. She also has extensive

experience in fine-scale acoustic analysis of call characteristics and call patterns.
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Karin A. Forney, Ph.D.

NOAA Fisheries – Southwest Fisheries Science Center – Marine Mammal and Turtle 

Division – EEZ Mammals and Acoustics Program

Expertise: Marine mammal ecology and population assessment

Taxa/Species: Marine mammals

Since 1987, Dr. Karin Forney has conducted research on the abundance, distribution, ecology, fishery 

bycatch, and status of more than 20 species of cetaceans and pinnipeds in the eastern and central North 

Pacific Ocean, with special emphasis on harbor porpoise, false killer whales, and other small cetaceans. Her 

research interests include: 1) ocean variability and its effect on marine mammals and other marine 

vertebrates; 2) habitat-based predictive models of cetacean distribution and abundance; 3) assessment and 

mitigation of human-caused mortality and injury of protected species; and 4) the development of improved 

methodology for estimating marine animal abundance and evaluating population trends. Dr. Forney coauthors annual stock assessment reports for the Pacific marine mammal stocks under NMFS’s jurisdiction. 

Jason Gedamke, Ph.D.*

NOAA Fisheries – Office of Science and Technology – Ocean Acoustics Program

Expertise: Marine bioacoustics

Taxa/Species: Marine mammals

Dr. Jason Gedamke manages the Ocean Acoustics Program within NOAA Fisheries’ Office of Science and 

Technology. Jason completed his Ph.D. in 2004 at the University of California, Santa Cruz, studying minke 

whale acoustic behavior and acoustically tracking singer movements. Following that, he worked for the 

Australian Antarctic Division conducting acoustic research on cetaceans in the Southern Ocean and 

providing scientific advice on the potential impact of anthropogenic sound on marine mammals. The Ocean 

Acoustics Program aims to increase understanding of how animals use sound, how underwater acoustics 

can be used to assess marine animal populations, the degree to which anthropogenic activities are changing 

the underwater soundscape, how these changes may potentially impact marine animals, and what 

measures can be taken to mitigate these potential impacts. 
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Douglas Gillespie, Ph.D.

University of St. Andrews – School of Biology – Scottish Oceans Institute – Sea Mammal 

Research Unit

Expertise: Algorithms and software tools for the detection, classification, and 

localisation of marine mammal vocalisations

Taxa/species: Many species including North Atlantic right whale, sperm whale, harbour 

porpoise, and dolphin species

Dr. Douglas Gillespie is a physicist by training. Since 2005, he has been developing algorithms and software 

tools for the detection and tracking of marine mammals using passive acoustics. He currently manages and 

is a key developer of the PAMGUARD PAM software. Other research interests include the development of 

embedded low-power PAM systems for use in remote buoys and autonomous vehicles. Dr. Gillespie is 

based at the Sea Mammal Research Unit at the University of St. Andrews, Fife, Scotland.

Danielle Harris, Ph.D.

University of St. Andrews – Centre for Research into Ecological and Environmental 

Modelling (CREEM) and Sea Mammal Research Unit

Expertise: Abundance/density estimation of marine mammals using acoustic data

Taxa/species: Cetaceans 

Dr. Danielle Harris is a post-doctoral research fellow at CREEM with a multi-disciplinary background 

involving biological, statistical, and acoustical analyses. Her research focuses on cetacean density 

estimation using acoustic data, particularly investigating cost-effective approaches by exploring existing 

opportunistic data sets and new technologies. Most of her work has focussed on blue and fin whales, 

although she has also worked on projects involving deep-diving odontocetes and harbour porpoises.

Dennis Heinemann, Ph.D.*

U.S. Marine Mammal Commission

Expertise: Marine ecology

Taxa/species: Pinnipeds, seabirds

Dr. Dennis Heinemann is the Science Director at the Marine Mammal Commission. Dennis was the lead 

organizer of the workshop. He does not have a background in marine bioacoustics, but is a statistician and 

is experienced with stock assessment, population dynamics, and the design of shipboard and aerial surveys 

for seabirds and marine mammals.
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John Hildebrand, Ph.D.

University of California, San Diego – Scripps Institution of Oceanography – Scripps 

Whale Acoustic Lab

Expertise: Underwater sound and marine mammals

Taxa/Species: Marine mammals

Dr. John A. Hildebrand is a Professor at SIO at the University of California at San Diego. He obtained a B.S. 

degree in Physics and Electrical Engineering at the University of California, San Diego, and a Ph.D. in Applied 

Physics from Stanford University. He has been on the research staff of the Scripps Institution of 

Oceanography since 1983. He regularly teaches classes on bioacoustics, experimental laboratory acoustics, 

and marine mammal biology. Dr. Hildebrand has contributed to more than 165 referred publications on 

topics ranging from underwater noise to sound production by marine mammals. His recent research has 

focused on ambient noise and acoustic techniques for marine mammal population census.

Marla Holt, Ph.D.

NOAA Fisheries – Northwest Fisheries Science Center – Conservation Biology Division 

Expertise: Bioacoustics (including sound production, acoustic communication, noise 

effects, acoustic risk factors, sensory ecology, and PAM)

Taxa/species: Marine mammals

Dr. Marla Holt is a Research Wildlife Biologist for the Marine Mammal and Seabird Ecology (MMSE) Team. 

She received her Ph.D. in Ocean Sciences at the University of California, Santa Cruz; her dissertation focused 

on directional hearing and acoustic communication in pinnipeds. Dr. Holt joined the NWFSC as a National 

Research Council Postdoctoral Associate in October 2006. Marla's current research focuses on cetacean 

acoustics including Southern Resident killer whales’ (SRKW) use of sound, noise and vessel effects on their 

behavior, mechanisms and energetics of sound production in odontocetes, and passive acoustic monitoring

of marine mammals. Current PAM investigations of the MMSE Team include work using towed arrays and 

sonobuoys for the Pacific Orcinus Distribution Survey (PODS) cruises, EARs for documenting SRKW winter 

coastal distribution, DTAGs for understanding vessel noise exposure and effects on behavior in SRKWs, and 

C-PODs for detecting porpoise clicks in Puget Sound.
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Holger Klinck, Ph.D.

Cornell University – Cornell Lab of Ornithology – Bioacoustics Research Program, 

Oregon State University (OSU) – Department of Fisheries and Wildlife and National 

Oceanic and Atmospheric Administration – Office of Oceanic and Atmospheric Research 

– Pacific Marine Environmental Laboratory

Expertise: Passive acoustic monitoring, autonomous platforms, detection and 

classification

Taxa/species: Marine mammals 

Dr. Holger Klinck was recently appointed as the Technology Director of Cornell University’s Bioacoustics 

Research Program. He also holds an appointment as Assistant Professor at OSU and is affiliated with OAR’s 

Pacific Marine Environmental Laboratory (PMEL). His current research at Cornell and OSU focuses on the 

development of hardware and software tools for passive acoustic monitoring of marine life. This work 

includes the use and modification of autonomous underwater vehicle (AUV) and unmanned surface vehicle

(USV) systems to study and monitor marine mammals. In collaboration with researchers from the 

University of Washington, NOAA, and the Austrian Society for Innovative Computer Sciences, he has used 

AUVs and USVs to monitor and study marine mammals in remote regions throughout the world. He is also 

involved in ocean noise studies and is currently leading a collaborate effort with PMEL, all the NMFS Science 

Centers, National Marine Sanctuary System, and the National Park Service to establish a large-scale Ocean 

Noise Reference Station (NRS) network to monitor long-term changes and trends in the underwater 

ambient sound field in U.S. waters.

Tiago André Marques, Ph.D.

University of St. Andrews – Centre for Research into Ecological & Environmental 

Modelling, and Universidade de Lisboa

Expertise: Animal density estimation, distance sampling, passive acoustic density 

estimation

Taxa/species: Mostly marine mammals

Dr. Tiago Marques is a Senior Research Fellow at the University of St. Andrews, although permanently 

residing in Lisboa, Portugal. He was the main postdoctoral researcher in the Density Estimation for 

Cetaceans from passive Acoustic Fixed (DECAF) sensors project, during which methods for estimating animal 

density from passive acoustic data were developed and implemented in a variety of case studies. Most 

recently, he has been working on the Linking Acoustic Tests and Tagging using Statistical Estimation

program, evaluating the impact of navy sonar on marine mammals. Tiago is a biologist (1998) with M.Sc.

(2002) and Ph.D. (2007) degrees in statistics. His M.Sc. and Ph.D. research was on extending distancesampling methods for estimating animal abundance in situations where conventional assumptions do not 

hold, namely non-random transect placement and error in distance measurements. 
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David K. Mellinger, Ph.D.

Oregon State University – National Oceanic and Atmospheric Administration – Office of Oceanic and 

Atmospheric Research – Cooperative Institute for Marine Resources Studies (CIMRS)

Expertise: Software and hardware for detecting, classifying, and locating animals acoustically and 

application of these methods to research and conservation

Taxa/species: Cetaceans, pinnipeds, fishes

Dr. Dave Mellinger is the program leader for the CIMRS Bioacoustics Lab. The lab develops new tools for 

studying marine mammals acoustically: algorithms for detection, classification, localization, and density

estimation; and user-friendly software to make these algorithms easily accessible by people everywhere. 

The lab develops these methods for new hardware platforms such as ocean gliders, robotic sailboats, and 

fixed pop-up sensors. In addition, the lab applies these new technologies for research and conservation of 

marine species throughout the world.

Jeff Moore, Ph.D.

NOAA Fisheries – Southwest Fisheries Science Center – Marine Mammal 

and Turtle Division – EEZ Mammals and Acoustics Program

Expertise: Population dynamics, statistics, survey design and modeling

Taxa/species: Marine mammals and sea turtles

Dr. Jeff Moore is a population-assessment scientist within the SWFSC Marine Mammal and Sea Turtle 

Division, joining the group in 2010. His expertise and responsibilities include developing methods for 

quantifying population impacts of bycatch on sea turtles and marine mammals; risk assessment; Bayesian 

statistics; developing quantitative decision tools for policy and management; estimating cetacean 

abundance, trends, and population dynamics parameters; designing marine mammal abundance surveys;

and analysis. Jeff serves on advisory committees such as the Biological Review Team for assessing the 

status of northeastern Pacific white sharks, and the International Union for Conservation of Nature’s 

Cetacean Specialist Group. He regularly contributes to protected species management processes such as 

Take Reduction Planning and activities related to the Pacific Fishery Management Council.
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Erin Oleson, Ph.D.*

NOAA Fisheries – Pacific Islands Fisheries Science Center – Protected Species 

Division – Cetacean Research Program (CRP)

Expertise: Marine bioacoustics

Taxa/species: Cetaceans

Dr. Erin Oleson has been the leader of the CRP at the Pacific Islands Fisheries Science Center since 2009. 

Erin received her Ph.D. from the Scripps Institution of Oceanography. She has conducted acoustic tagging 

of humpback, blue, and fin whales off California and in the eastern tropical Pacific; conducted shipboard 

and acoustic surveys for cetaceans; and used long-term autonomous acoustic recorders to assess seasonal 

species occurrence off the U.S. West Coast, Alaska, Hawaii, Mexico, and the Antarctic. As leader of the CRP, 

Erin oversees field investigations, conducts statistical analyses, provides scientific advice, and prepares 

status reports and manuscripts on research to assess cetacean populations in the Pacific Islands Region.

Julie Oswald, Ph.D.

Bio-Waves, Inc.

Expertise: Acoustic species identification

Taxa/species: Cetaceans

Dr. Julie Oswald is Vice President and Senior Scientist at Bio-Waves, Inc., a small bioacoustic research and 

consulting firm located in Encinitas, California. Her main area of expertise is the development of 

classification methods for sounds produced by odontocete species. She is also involved in the analysis of 

acoustic data collected using towed hydrophone arrays and seafloor-mounted acoustic recorders. These 

projects include examinations of species occurrence and distribution patterns, acoustic behavior, and 

impacts of anthropogenic sound on marine mammals.
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Shannon Rankin

NOAA Fisheries – Southwest Fisheries Science Center – Marine Mammal and Turtle

Division – EEZ Mammals and Acoustics Program

Expertise: Bioacoustics

Taxa/species: Cetaceans

Ms. Shannon Rankin is a wildlife research scientist specializing in passive acoustic monitoring of marine 

mammals. Specifically, she is interested in using passive acoustics as a tool for monitoring marine mammal 

populations through systematic surveys. Shannon works primarily with towed hydrophone arrays and Navy 

sonobuoys on shipboard surveys throughout the Pacific Ocean, as well as the Gulf of Mexico and the 

Antarctic. 

Professor Marie A. Roch, Ph.D.

San Diego State University – Computer Science Department

Expertise: Bioacoustics, classification

Taxa/species: Marine mammals

Dr. Marie Roch is an interdisciplinary computer scientist who works on the classification of marine mammal 

vocalizations as well as methods to integrate marine mammal call detections with environmental 

measurements and anthropogenic acoustic sources for data exploration and habitat modeling. Her work 

ranges from species identification to extraction of call parameters and the recognition of call component 

archetypes. Recent classification work has focused on quantifying and mitigating the effects of site and 

equipment variability for fixed PAM units deployed within a geographic region.

Ana Širović, Ph.D.

University of California at San Diego – Scripps Institution of Oceanography – Marine 

Physical Laboratory

Expertise: Passive acoustics, ocean ambient sound, long-term time series analysis

Taxa/species: Cetaceans, with a focus on mysticetes and fishes

Dr. Ana Širović is a researcher at the Scripps Institution of Oceanography. She has been working on the use 

of passive acoustic tools to answer population-level questions relevant to the management of animal 

resources since 2000, and during this time has analyzed many decades’ worth of passive acoustic data. She 

is currently working on projects relating to estimation of baleen whale call rates as they pertain to density 

estimation. She is also interested in ambient noise and the effects human activities have on marine 

organisms. 
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Melissa Soldevilla, Ph.D.

NOAA Fisheries – Southeast Fisheries Science Center (SEFSC) – Protected Resources Division – Marine 

Mammal Program

Expertise: Echolocation, bycatch, stock assessment

Taxa/species: Delphinids, North Atlantic right whales

Dr. Melissa Soldevilla is a Research Fishery Biologist at NOAA's SEFSC. She received her Ph.D. at SIO where 

she developed methods to identify delphinid echolocation clicks to species and applied this work to study 

Risso's dolphin and Pacific white-sided dolphin ecology from fixed passive acoustic sensors in the Southern 

California Bight. Currently, her work at the SEFSC includes fishery bycatch estimation and data-gap 

evaluations; developing passive acoustic methodologies to enhance stock assessments, including acoustic 

abundance estimation of deep diving cetaceans and odontocete click-classification techniques; and 

developing surveys and analyzing PAM and mitigation studies for conservation of North Atlantic right 

whales on their southeast calving grounds, including evaluation of survey method effectiveness, localization 

and estimation of detection distances, and characterization of shipping noise.

Sofie van Parijs, Ph.D.*

NOAA Fisheries – Northeast Fisheries Science Center (NEFSC) – Resource Evaluation 

and Assessment Division – Protected Species Branch – Passive Acoustics Research 

Group

Expertise: Marine bioacoustics 

Taxa/species: Marine mammals, fish

Dr. Sofie Van Parijs has worked on passive acoustic research from the poles to the tropics for more than 20 

years. She has undergraduate and master’s degrees from Cambridge University and a Ph.D. from Aberdeen 

University in the U.K. She worked as a postdoctoral scientist at the Norwegian Polar Institute, James Cook 

University in Australia, and Cornell University before moving to the NEFSC in Woods Hole in 2004. At NMFS,

she leads the passive acoustic research program within the Protected Species Branch, which consists of 

postdoctoral scientists, Ph.D. students, research analysts, and summer interns. Her expertise in marine 

bioacoustics has addressed questions on behavioral ecology, distribution, abundance, long-term 

monitoring, mitigation, and effects of ocean noise on marine mammals.
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Appendix B Science Center Passive Acoustics Research Programs

(Prepared by Erin Oleson)

Northeast Fisheries Science Center Passive Acoustic Research Group11

NEFSC is responsible for cetacean stock assessments in the northeast U.S. Atlantic waters. The Passive 

Acoustic Research Group within the Protected Species Branch at NEFSC extensively uses well-proven and 

new technology to monitor and understand the occurrence and abundance of, and human-impacts on,

large whales and other cetaceans in the region.

Passive Acoustics Personnel: 

• 1 FTE (Van Parijs)

• 1 senior scientist

• 1 postdoctoral researcher (shared by NEFSC and Stellwagen Bank National Marine Sanctuary 

(SBNMS))

• 1 data manager

• 4 research assistants

• 1⁄2 field work manager

Other than 1 FTE, all others are temporary contractors paid through competitive external funds/grants. 

Instrumentation Available:

• 2 linear towed hydrophone arrays

• 8 leased HARPs (with SEFSC in West Atlantic through BOEM)

• Leased MARUs (~20 per year for large whale work; various external funding sources)

• 2 ocean NRSs (1 for NE Atlantic, 1 for SBNMS through NOAA)

• 1 leased AMAR (U.S. Navy)

• 2 Liquid Robotics Wave Gliders, 1 Slocum glider, 2 EOM surface real-time moorings (owned and 

maintained by WHOI) for real-time monitoring (ESTCP/LMR U.S. Navy)

• 50 sonobuoys (donated by U.S. Navy)

• Leased MARU or MiniHARPs; ~15 upcoming for migration corridor work (Atlantic Marine 

Assessment Program for Protected Species (AMAPPS))

Data Management Support: 

• In-house data manager (contractor) and NEFSC IT support for archiving and managing all passive 

acoustic data

• Backup data housed at NEFSC and with collaborators

• Metadata management database in progress (Tethys through M. Roch at San Diego State University 

(SDSU))

• Long-term archiving pilot project in progress (with NCEI and AFSC)

 11 Website: http://www.nefsc.noaa.gov/psb/acoustics/
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Ongoing projects 

1. Long-term archiving of assessment PAM data: 

• National Oceanographic Partnership Program (NOPP) funding for development of metadata 

base 

• Ongoing pilot project with NGDC to archive PAM data and understand full cost/effort involved 

per TB of data with National Marine Mammal Laboratory (NMML) and NGDC

 Partners: SDSU, SIO, NMFS Science Centers, NGDC

 Funders: NOPP (ONR), PIFSC, NMML, OS&T, NMFS Ocean Acoustics Program

2. Autonomous technology projects: 

• Demonstration project to show feasibility of integrating autonomous and real-time passive 

acoustic monitoring into assessment and mitigation needs throughout the northeast U.S. (Gulf 

of Maine and N.Y. Bight) using Slocum gliders, Wave Gliders, and fixed real-time moorings with 

WHOI

 Partners: WHOI

 Funders: ONR, ASTWG, ESTCP, LMR

 Website: http://dcs.whoi.edu/

3. Fish Acoustics: 

• Using archival acoustic recorders, gliders, and acoustic telemetry to find, define, and protect 

spawning areas for fish (especially Atlantic Cod) 

 Partners: Massachusetts Department of Marine Fisheries, University of Massachusetts 

School of Marine Science and Technology, The Nature Conservancy, SBNMS, WHOI 

 Funders: NMFS Co-Operative Research Grant Program, NOAA Saltonstall-Kennedy Grant 

Program

4. Marine Mammal Acoustics: 

• Seasonal occurrence, distribution, and migration patterns for baleen whales in the Western 

Atlantic using historic (2005 to present) and new data for large whales 

 Partners: Dave Mellinger and Sharon Nieukirk, Hilary Moors-Murphy, Erin Summers, Maine 

Department of Marine Resources, College of the Atlantic, New England Whale Center, 

JASCO Ltd., Cornell University, SEFSC, Duke University, Naval Facilities Engineering 

Command, Kate Stafford, Ana Širović, Scripps, Susan Parks, Syracuse University, NEFSC, Gary 

Buchanan, New Jersey Department of Environmental Protection, Helen Bailey, University of 

Maryland, Catherine Berchok, NMML 

 Funders: BOEM, GAFRO, OPR 

• Towed array for stock assessment (mainly sperm and beaked whale) as part of AMMAPS 

 Partners: SEFSC

 Funders: BOEM

• Integrating PAM and visual data (density estimates from long-term array data for right whales, 

new integration methods for fixed sensors and visual) 

 Partners: SBNMS, SEFSC, University of Maryland, others 

 Funders: U.S. Navy 

5. Northeast Passive Acoustic Network (NEPAN) 

• Combining projects 2 and 4 above with Canadian partners to produce an integrated monitoring 

and mitigation network throughout the northeast 

 Partners and Funders: See above 
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6. Noise Impacts 

• Shelf-break monitoring throughout the Western Atlantic as part of a Before-After ControlImpact (BACI) design for full range of species before and during seismic exploration 

 Partners: SEFSC, Duke University, SIO

 Funders: BOEM

Southeast Fisheries Science Center Passive Acoustic Assessment Program

SEFSC is responsible for cetacean stock assessments in the southeast U.S. Atlantic waters, the northern Gulf 

of Mexico, and the Caribbean. Passive acoustics are used currently for ship-based stock assessments in the 

Gulf of Mexico and southeast U.S. Atlantic. In the same locations, passive acoustics are also used for

seasonal assessments of cetacean occurrence from fixed platforms.

Passive Acoustics Personnel: 

• 1⁄2-time FTE (Soldevilla; other 1⁄2 time on take reduction team support)

• 1 full-time contractor (externally funded)

• Occasional volunteer student help

Instrumentation Available:

• 3 linear towed hydrophone arrays

• 2 dedicated HARPs (BOEM, Dry Tortugas)

• Leased MARUs (~12 per year for right whale work through the Southeast Implementation Team of 

the North Atlantic right whale recovery plan)

• 2 NRSs (1 for Gulf of Mexico, 1 for southeast Atlantic through NOAA)

• Leased MARUs or MiniHARPs (~8 upcoming for migration corridor work (AMAPPS))

• Leased HARPs (~3 for upcoming BOEM pre-seismic study)

Data Management Support:

• Limited – Serial Advanced Technology Attachment (SATA) disks in office, backup disks with 

collaborators

• Metadata management database in progress (Tethys through M. Roch at SDSU)

• Long-term archiving project in progress (NGDC and NEFSC collaboration)

Primary Research Partners: 

• SIO

• Cornell University

• NEFSC, PIFSC, SWFSC, PMEL

• Duke University

• Bio-Waves, Inc.

• SDSU

Primary Near-Term Goals:

• Shelf-break monitoring throughout the western Atlantic as part of a BACI design for full range of 

species before and during seismic exploration 

• Seasonal occurrence, distribution, and migration patterns for right whales in the western Atlantic 

using historic (2005 to present) and new data for large whales 

• Towed array surveys in the Atlantic for stock assessment (sperm whale abundance estimation and 

delphinid species classification) as part of AMMAPS 

• Localization and tracking of North Atlantic right whales on calving grounds for detection distance 

estimation and PAM effectiveness evaluation
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• Ship noise characterization on North Atlantic right whales calving grounds

• Gulf of Mexico towed array surveys for stock assessment (sperm whale abundance estimation and 

delphinid species classification)

• Dry Tortugas sperm whale monitoring for assessment of seasonal occurrence and habitat use

• NOAA’s Noise Recording Station (NRS) network in the Gulf of Mexico and southeast U.S. Atlantic

Southwest Fisheries Science Center Passive Acoustics

The SWFSC EEZ Mammals and Acoustics Program (EMAP) is responsible for monitoring marine mammal 

populations off the West Coast of the United States. The Program has been developing methods for using 

passive acoustics as a tool for population estimation of sperm whales, beaked whales, and porpoise. The

acoustics program has been actively involved in the research and development to improve detection, 

localization, and classification of cetaceans using passive acoustic monitoring for other cetaceans.

Passive Acoustics Personnel: 

• 1 FTE senior scientist (Barlow)

• 2 FTEs (Rankin, Keating)

• 1 research assistant (contractor)

Other than Program Director, all personnel are paid through competitive external funds/grants.

Instrumentation Available:

• 5 linear towed hydrophone arrays, 2 experimental tetrahedral arrays

• Various over-the-side and free-floating recorders for short-duration recordings

• 4 DASBRs

• 1 NRS (PMEL)

Data Management Support:

• Limited – SATA disks in office

• Small server for network access to subset of data

Primary Research Partners: 

• Other Science Centers

• Bio-Waves, Inc.

• SIO

• Cascadia Research Collective

• Southall Environmental Associates

• PMEL

Primary Funding:

• LMR

• OS&T (Ocean Acoustics Program, ASTWG, Cooperative Research Program)

• BOEM

• SBIR

Acoustic Projects and Goals:

The bulk of SWFSC acoustic efforts are focused on hardware development and implementing towedhydrophone-array data collection for combined visual/acoustic line-transect cetacean surveys. Our 

extensive shipboard surveys (10 years of 4- to 5-month surveys in addition to other smaller projects) have 

led to an extensive data archive but few remaining resources to analyze this data. Most data collection 

includes simultaneous visual observation (confirmation of species) and ecosystem sampling. All funding to 
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support the program comes through external grants/funds; we make a strong effort to identify funds that 

overlap with NMFS priorities. One of our greatest hurdles is addressing our great need for improvement in 

hardware/software/analysis with limited piecemeal funding. We have been successful in obtaining NOAA 

Cooperative Research Program funds to obtain moderate amounts of vessel time (fishing vessels) for 

hardware testing. 

Ongoing projects

• California Current Cetacean Ecosystem Assessment Survey (CalCurCEAS): Combined visual/acoustic 

line-transect shipboard cetacean surveys off the West Coast of the United States. Towed 

hydrophone arrays collected recordings for detection, localization, and classification of odontocetes 

and minke whales. U.S. Navy surplus sonobuoys were used to obtain recordings of baleen whales. 

This survey was conducted from August to December 2014. Possible repeat of this survey from 

August to December 2015.

• Southern California Behavioral Response Survey: Use towed arrays to identify potential target 

species for controlled experiment exposures to study response of cetaceans to navy sonar.

• Development of volumetric towed hydrophone arrays: Research and development to date has been 

performed in-house or in conjunction with SIO. Future development will include collaboration with 

business partners funded by NOAA’s SBIR (in process).

• Development of Drifting Autonomous Spar Buoy Recorders (DASBRs): Research and development 

of drifting buoys as an alternative means of estimating cetacean density and for measuring ocean 

noise.

• Development of a compound acoustic classifier for odontocetes: Incorporating whistles, 

echolocation clicks, and burst pulses to improve classification. We are in the final testing phase 

using towed array data collected during CalCurCEAS survey. 

• Acoustics as a tool for stock structure in fin whales in the North Pacific.

• Passive acoustic density estimation of baleen whales: Using sonobuoys to estimate vocalizationrate correction factors. Project start date July 2015.

• Development of methods to calibrate hydrophones at the SWFSC Technology Tank.

• NRS Network in Channel Islands, CA.

Pacific Islands Fisheries Science Center Passive Acoustics

The PIFSC CRP is responsible for cetacean stock assessments in the Pacific Islands Region, including Hawaii, 

American Samoa, Guam, and the Northern Mariana Islands, as well as the Pacific Remote Islands and Atolls. 

Passive acoustics are currently being used for ship-based stock assessments in Hawaiian waters and for 

year-round assessments of cetacean occurrence and ambient noise from fixed platforms throughout the 

central and western Pacific.

Passive Acoustics Personnel: 

• 1⁄4 FTE (Oleson; other 75% of time as CRP Leader)

• 1.5 Cooperative Institute staff (Joint Institute of Marine and Atmospheric Research) 

• 1.5 contract staff (externally funded)

• 1 Ph.D. student

• Field assistants for cruises as needed

• 1 new FTE anticipated in late FY2015

Instrumentation Available:

• 4 linear towed hydrophone arrays, 1 experimental tetrahedral array

• 8 HARPs (1 capable of 320 kHz acoustic sampling)

• 5 mini-HARPs
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• Various over-the-side and free-floating recorders for short-duration recordings

• 1 NRS (PMEL)

• Seaglider with integrated DMON (owned by University of Hawaii, used for cooperative projects)

Data Management Support:

• Limited – SATA disks in office, backup disks with collaborators

• Metadata management database in progress (Tethys through M. Roch at SDSU)

• Long-term archiving project in progress (NGDC and NEFSC collaboration)

Primary Research Partners: 

• SIO

• University of Hawaii

• SWFSC, SEFSC, PMEL

• Cascadia Research

Primary Funding:

• PIFSC, PIRO, OS&T (Ocean Acoustic Program, Advanced Sampling Technology Working Group, 

Bycatch Reduction Engineering Program)

• U.S. Navy Pacific Fleet

Projects and goals

The bulk of PIFSC’s acoustic efforts are focused on various aspects of false killer whale assessment 

(detection, classification, tracking, and mitigation of fisheries interactions); long-term monitoring for 

cetaceans at various sites in the central and western Pacific (Hawaii, Wake, Commonwealth of the Northern 

Marianas, Palmyra); and development and use of towed hydrophone arrays for abundance estimation.

Significant hurdles to our work include lack of robust delphinid species-classification algorithms for many 

species; lack of support for post-processing towed array data collected at sea; and theoretical hurdles 

related to estimation of group size, subgroup structure, and robust estimation of group location. PIFSC and 

its partners have invested heavily in the integration of the DMON into the Seaglider and are now working 

on testing onboard detection and classification algorithms for efficient data collection from the glider. 

Technical issues still plague glider deployments, including inconsistent communications between the DMON 

and glider infrastructure, and insufficient battery and data storage for missions longer than 1 month.

Other projects include:

• Acoustic characterization and geographic and temporal occurrence trends in Kogia and beaked 

whales

• Monitoring longline fisheries for evidence of false killer whale depredation and other interactions

• Ambient noise monitoring and characterization

• NRS Network in Hawaii

Northwest Fisheries Science Center Passive Acoustics

Passive acoustics research plays a prominent role within the MMSE Team’s research into Southern Resident 

killer whales and other Puget Sound and Pacific Northwest cetaceans.

Passive Acoustics Personnel: 

• 1.5 FTE (Holt, Emmons; other 1⁄2 dedicated to non-PAM projects)

• Research assistants primarily for field work, as needed

• University of Washington graduate student
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Instrumentation Available: 

• 2 linear hydrophone arrays

• 17 leased EARs

• Sufficient inventory of surplus sonobuoys

• 3 owned C-PODs

• 2 leased DTAGs 

Data Management Support:

• Limited – hard drives in office, backups through in-house services (NWFSC IT data 

retention/storage) and some data sets with collaborators

• Metadata management – custom databases (limited); Tethys potentially

• Long-term archiving – either through project with NGDC and other NMFS Science Center

collaborations, or NWFSC IT data retention/storage

Primary Research Partners:

• Bio-Waves, Inc.

• Cascadia Research Collective

• University of Washington

• University of California, Davis

• University of Hawaii

Primary Funding:

• NMFS Ocean Acoustics Program

• U.S. Navy

• ASTWG

Current projects

• PODS cruise

Orcinus “species” occur in the Pacific Ocean throughout the West Coast of North America. Data 

concerning their precise locations and abundance are critical to understanding their population 

trends and movement patterns. PODS provide such data, allowing scientists and managers to 

better understand and manage Orcinus “species.” Passive acoustic monitoring provides the means 

for detecting, localizing, and tracking groups of killer whales when visual observations are not 

possible (e.g., tracking through night/inclement weather to get photo IDs and prey/fecal/biopsy 

samples, satellite tag deployments when possible).

• Coastal distribution of Southern Resident killer whales (SRKWs) using PAM recorders

SRKWs are listed as a Distinct Population Segment of killer whales under the Endangered Species 

Act (ESA). Their distribution varies by season according to a variety of factors. Determining the 

patterns of SRKW occurrence provides understanding of the factors that contribute to their 

seasonal distribution. Their winter distribution is an identified data gap. A series of passive

acoustic recorders moored in various locations on the coasts of Washington, Oregon, and California 

are being used to determine the seasonal occurrence of SRKWs.

• Passive acoustic monitoring of Puget Sound harbor porpoise

Drs. Marla Holt, Brad Hanson, and Candice Emmons of the NWFSC, along with efforts from the 

NWFSC dive team (coordinated by Nick Tolimieri), are currently conducting PAM of harbor 

porpoises in Puget Sound. The occurrence of harbor porpoises is being acoustically documented 

using porpoise detectors (C-PODs, made by Chelonia, Ltd), which detect and log harbor porpoise 
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echolocation clicks and store the data on flash memory cards. C-PODs are deployed on the sea floor 

by scientific divers, and must be recovered every 3 months to replace batteries and memory cards. 

The project, which is ongoing, will document the occurrence and habitat use of this protected 

species. The project is a well-defined component of a larger study that addresses harbor porpoise 

occurrence and habitat use in the Salish Sea.

• Using DTAGs to study acoustics and behavior of SRKWs

Drs. Marla Holt, Brad Hanson, and Candice Emmons of the NWFSC, along with collaborators from 

Cascadia Research Collective, University of Washington, and UC Davis, are conducting a study using 

digital acoustic recording tags (DTAGs) to examine sound exposure, sound use, and behavior of 

SRKWs in their core summer habitat. The DTAG is temporally attached with suction cups and 

consists of a number of different sensors that record sound, pitch, roll, heading, and depth. Prey 

samples and vessel data are also concurrently collected relative to tagged whales in a manner 

similar to previous work (Giles and Cendak, 2010; Hanson et al., 2010). The project research goals 

include: (1) measure noise levels in biological-relevant frequency ranges that are received by 

individual SRKWs; (2) quantify the relationship between received noise levels and detailed vessel 

traffic variables obtained from precise geo-referenced data collected concurrently; (3) investigate

whale acoustic and fine-scale movement behavior during various activities, including foraging, to 

understand sound use and behavior in specific biological and environmental contexts; and (4) 

determine potential effects of vessels and associated noise on behavior. The results of this study 

will provide pertinent data to address multiple risk factors of SRKWs, including vessel disturbance, 

noise exposure, effects on foraging, and cumulative effects. 

Alaska Fisheries Science Center Passive Acoustics

The acoustic group led by Catherine Berchok and affiliate researcher, Manuel Castellote, undertakes passive 

acoustics research at AFSCs NMML. Berchok’s acoustics team works as part of large-scale, multi-disciplinary 

projects, of which the primary research goals are three-fold: 1) assess the long-term, year-round seasonal 

occurrence and distribution of marine mammals (with a focus on baleen whales) in Alaskan waters;

2) evaluate how environmental conditions and prey abundance influence these distributions; and

3) monitor ambient noise levels in the Arctic. Castellote focuses primarily on behavioral ecology questions 

and the effect of anthropogenic noise on cetaceans. His primary species of focus are beluga, killer whale, 

porpoises, and fin whales. 

Passive Acoustics Personnel: 

• 2 FTEs (Berchok, Crance)

• 2 research assistants

• 2 junior analysts (all except FTE externally funded)

• 1 affiliate researcher (Castellote)

Instrumentation Available: 

• Berchok Acoustic Team

 50 AURAL recorders

 Sufficient inventory of surplus sonobuoys

 Towed array

• Castellote

 Moored recorders (owned by ADFG)

 Leased DTAGs (WHOI)
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Primary Research Partners: 

• Berchok Acoustic Team: 

 PMEL

 AFSC/Resource Assessment and Conservation Engineering Division

 Cornell University

 APL

• Castellote: 

 ADFG

 APL

 Oceanwide Science Institute (Lammers)

 WHOI

 Department of the Army

 Alaska Boroughs (Yakutat, Kotzebue, North Slope)

 Alaska Marine Ecosystem Research (Frost and Lowry)

Primary Funding:

• Berchok Acoustics Team: 

 BOEM

 OS&T

 International Fund for Animal Welfare

• Castellote: 

 ADFG

 Department of Defense

 U.S. National Park Service

 Alaska Boroughs

 OS&T

 Alaska Regional Office (NMFS) 

The most important limitation for the Berchok team is analysis time. Currently, we do not have any autodetectors or classifiers for our Arctic species. The team has tried to incorporate auto-detectors in the past, 

but with no success. One team member has been working on implementing Mark Baumgartner’s (WHOI)

low-frequency detection and classification system on the team’s Arctic dataset, with limited success. There 

are still too many errors (both false positives and false negatives) to consider it a viable option for anything 

other than fin whales. As a result, we manually analyze 100 percent of our data using a program written by 

Dr. Berchok (SoundChecker). It takes one analyst approximately 75 days to analyze one recorder for all 

species (cetaceans and pinnipeds). Problems that we have encountered by subsampling our analyses 

include losing contextual clues to species identification. 

The second most important limitation is an inability to obtain abundance estimates from a single 

hydrophone. The team now has a methodology to overcome this limitation based on the MMC-sponsored 

workshop on density estimation led by Len Thomas and Tiago Marques of the University of St. Andrews 

from January 2015. By including dedicated focal follows using sonobuoys during the field season, we can 

collect simultaneous acoustic/visual data to obtain vocalization rates on visually detected individuals, and 

then apply those vocalization rates to our acoustic data. 

The third problem is the large number of unknown vocalization types detected on our long-term recorders. 

If we are able to conduct more focal follows with concurrent visual/acoustic data, we can begin to attribute 

some of the unknown vocalizations to certain species, and possibly clear up some confusion regarding 

shared vocalization types. Additional problems include the high cost of sea time (due to vessel size 

requirements, the size of the survey area, and the remote location), moorings being fished up, and a lack of 

any significant NOAA funds, despite the Arctic being an area of concern/interest.
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Dr. Castellote conducts research primarily using moored autonomous recorders deployed for the long term, 

although shorter deployments, with the use of acoustic tags and associated sampling (e.g., trawling, visual 

observations) are common in his projects. Another technique used in his research is collecting hearing 

sensitivity. In collaboration with Dr. Aran Mooney (WHOI), Dr. Castellote has also been investigating 

hearing sensitivity in wild and captive belugas.

The biggest limitations faced by Dr. Castellote are the analysis demands, inefficient automated detection 

tools for large datasets, and a lack of funding for long-term research programs. In addition, he would 

benefit from an advancement in noise analysis tools (e.g., support in developing new Matlab codes) to 

streamline his analyses. A general challenge for coastal studies has been the difficulty deploying and 

maintaining long-term acoustic moorings in typical beluga habitats—shallow, high-current areas exposed to 

ice interaction in winter (e.g., Cook Inlet, Kotzebue).
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Appendix C Fixed Autonomous Acoustic Platforms 

(Prepared by Sofie Van Parijs)

General Overview

Figure 2 illustrates several fixed acoustic recorders that have been, and currently are, used by NOAA for 

PAM research of marine mammals. For more technical details about and in-depth specifications for these

and other recorders, see a recent review by Sousa-Lima et al., 2013.

Figure 2. Fixed autonomous recorders for passive acoustic monitoring of marine mammals.
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Bottom-Mounted Acoustic Recorders (BMARs)

• Mode of operation: BMARs are bottom-mounted recorders that collect acoustic data and 

archive data on internal hard drives.

• Anchorage: BMARs are anchored to the sea floor using various anchorage mechanisms that may

have a surface expression in the form of a line and float. Systems with no surface expression are 

mostly retrieved by using an acoustic release system.

• Duration: Several months to years of continuous and/or duty-cycled acoustic recordings are 

possible.

• Deployment: Deployment has become a relatively routine process for most sensors. Depending 

on the system, a unit can be deployed by hand using an A-frame or crane from a wide variety of

vessels. BMARs require little further investment after deployment because they can be left at 

sea for long periods until the time of recovery.

• Cost: The purchase or lease price for commercially available BMARs ranges widely from 

approximately $2,000 to $80,000 USD. Purchase or lease can include the anchorage and/or an 

acoustic release system. If you purchase a BMAR, then you need to include the technical 

capability and the personnel to service, refurbish, and maintain these recorders.

• Frequency range: Individual recorders vary widely in frequency range and capabilities, from lowfrequency recorders (~10 Hz to 5 kHz) to those that completely cover the marine mammal 

frequency spectrum (~10 Hz to 200 kHz). The higher the frequency range required, the more 

data storage capacity needed, resulting in shorter deployment duration or the need to duty 

cycle the recorders.

• Configuration: BMARs are highly versatile and can be deployed as single fixed-point sensors, in 

lines at set distances apart or in array configurations allowing for the localization of signals. This 

allows for data collection of long-term seasonal presence and distribution covering large spatial 

scales, monitoring of migration routes, estimation of relative (and sometimes absolute)

abundance of species, and trends in ocean noise.

• Other considerations: A wide range of options is available for shallow and deep water

deployments. The cost and recording duration of BMARs is framed by the location, depth, and 

frequency range of the requirement. In order to meet the widely varying depth, species, and 

frequency requirements of each project, it is important to have a range of options to suit each 

goal.

Surface-Mounted Acoustic Recorders (SMARs)

• Mode of operation: SMARs are surface-mounted recorders that collect acoustic data and can 

both archive data on internal hard drives and relay data back in near real time through a VHF, 

mobile, or iridium connection. Several acoustic recording packages can be installed onto a 

SMAR (see the PAM systems options in Appendix E). In addition, an SMAR can be equipped with
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a detection and classification software package so that it relays specific vocalizations/events 

that are of interest, or a series of detections of multiple species. Continuous data streaming is 

expensive and often not vital to a real-time operation.

• Anchorage: SMARs are anchored to the sea floor using various anchorage mechanisms but can 

suffer from “self noise” due to wave action on the surface buoy. EOM Offshore Pte Ltd has

created an anchorage system that buffers the wave action with a stretch hose and isolates 

unwanted “self noise” from the recordings. These types of anchorage systems are essential but 

require custom building.

• Duration: A single deployment can yield several months to years of continuous real-time and 

continuous or duty-cycled archived data.

• Deployment: Deployment is relatively routine and can be done using an A-frame or crane from 

a wide variety of vessels. After deployment, SMARs require little further investment and can be

left at sea with minimal maintenance for long periods until the time of recovery.

• Cost: The lease price for commercially available SMARs ranges from approximately $60,000 to

$80,000 USD and can include the anchorage system. If a purchase is considered, then having 

the in-house technical capability and personnel to service, refurbish, and maintain these 

recorders is essential.

• Frequency range: Individual recorders vary in the frequency range at which they can record. 

The higher the frequency range required, the more data storage capacity is required, resulting in 

shorter deployment duration or the need to duty-cycle recordings.

• Configuration: SMARs can be deployed as single fixed-point sensors, in lines at set distances 

apart, or in arrays allowing for the localization of signals. SMARs are starting to be used for data 

collection similar to that described in the BMAR section (Appendix C). Additionally, they are a 

valuable tool for directed mitigation requirements aimed at reducing the impact of ship strike 

and other anthropogenic risks.

• Other considerations: A wide range of options is available for shallow and deeper water 

deployments. The cost and recording duration of SMARs is framed by the location, depth, and 

frequency range of the requirements. In order to meet the widely varying depth, species, and 

frequency requirements of each project, it is important to have a range of options to suit each 

goal.

Existing Hurdles

• Leasing versus owning: The costs of leasing and owning can vary significantly. However, leasing 

is advantageous in that it does not require in-house qualified personnel to service, refurbish,

and maintain the equipment. In addition, leasing prices tend to include the anchorage and 

acoustic release system. When purchasing, all of these requirements—personnel time, 

refurbishment materials (batteries, hard drives, etc.), costs of a new anchorage and acoustic 
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release system required at each new deployment—need to be included in the running costs. Of 

course, at the end of a lease, you no longer have in-house passive acoustic recording capacity.

• Dedicated vessel time: NOAA usually conducts stock assessment surveys for marine mammals

in blocks of time during one particular season. However, the deployment and retrieval of 

passive acoustic sensors at sea requires vessel availability for short periods to deploy, service, 

and recover/swap recorders. The current process for requesting NOAA vessel time does not 

lend itself to passive acoustic data collection and needs to be adjusted to incorporate these 

requirements.

• Data processing and analysis: A large suite of software exists for processing and analyzing 

archival acoustic data for detection, classification, and localization of signals. However, 

improvements are still needed in terms of specific species detections and classifications. 

Additionally, using localization software is time consuming and could be improved to meet

requirements, such as the tracking of multiple species and extracting information for the 

purposes of density estimation. Only a few software options exist for real-time relaying of 

specific acoustic signals back to shore (e.g., Spaulding et al., 2009; Baumgartner et al., 2013).

Uses of Bottom- and Surface-Mounted Acoustic Recorder Data

• Description of species- and population-specific vocalization: As described in the towed array 

section (Appendix D): “Species-specific vocalization characterization is not, by itself, an 

important component of stock assessment. However, it is a necessary precursor to any other 

use of acoustics for stock assessment.” Recordings from arrays of BMARs can provide

information on new species vocalization types by overlaying tracks of known species 

vocalizations with unknown vocalization types to demonstrate their co-occurrence (such as the 

recent description of several new sei whale vocalizations, Tremblay et al., 2015). Additionally, 

both opportunistic and planned visual surveys conducted concurrently with BMAR and SMAR 

deployments are proving fruitful in their ability to identify species vocalizations, evaluate species 

behavior, and improve our understanding of visual and acoustic biases.

• Stock delineation and distribution: Currently, recordings collected using BMARs and SMARs 

provide large-scale information (e.g., along an entire coast line) on long-term (e.g., decadal) 

occurrence and distribution, as well as the delineation of migration corridors of key species (still 

poorly understood for nearly all western Atlantic baleen whale species, for example). These 

data provide the timely assessment of changes in population distribution and improve stock 

delineation. SMARs are currently providing highly valuable real-time information on shifts in 

species habitat usage. An example of this are the rapid changes noted in large whale 

distributions in the northeast U.S. SMARs in this case provide critical information on the whales’ 

habitat changes as well as help direct photo-ID surveys to assess population abundance and 

individual health status. We foresee that the combination of BMARs and SMARs will enable an 

improved and responsive understanding of changes in species distribution, given the rapid 

changes in species movements that are observed in the western Atlantic.
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Further use of these large spatial-scale data will help further delineate stocks using similar 

methods as those being used with towed arrays in the Pacific Ocean. Acoustic identification of 

species such as Risso's dolphins and pilot whales, improved identification of sei whales, and 

breeding ground delineation of humpback whales are just some of the possible applications that 

require further study during subsequent years in the western Atlantic.

Abundance Estimation

• Absolute abundance: As mentioned in Appendix D, “[t]he use of passive acoustics to estimate 

absolute abundance (number of animals within a defined study area) has and continues to be

a great challenge.” Arrays of BMARs are currently deployed to evaluate the feasibility of using 

these techniques for large whales, especially North Atlantic right whales. However, these

techniques require realistic data on animal vocalization rates. Obtaining this information

remains a challenge to the implementation of this methodology for non-odontocete species.

• Relative density: BMARs and SMARs can be used readily to estimate relative density of 

vocalizing animals. The integration of this information with the extensive large-scale visual data 

that is collected has the potential to provide valuable insights for the stock assessment of 

species such as large whales.

Limitations and Impediments in Stock Assessment

BMARs and SMARs can detect the full range of species effectively; however, logistical and 

financial decisions are often made that restrict the data collection to low-, mid-, or highfrequency species. BMARs have been used extensively to detect the occurrence and distribution 

of many species on an ocean-basin-wide scale. They can therefore provide detailed information 

on species presence, their relative abundance, and the timing of their movements, but cannot 

provide information on absolute abundance. Currently, BMARs/SMARs cannot provide 

information on individuals or health status in a population. However, SMARs and AUVs can

direct and optimize time spent collecting visual data on specific endangered species where this 

information is of essence.

As is true for towed arrays, “Species classification in this case for all cetaceans has seen rapid 

improvement in recent years; however, significant hurdles remain in acoustic species 

classification (Appendix D).”

Localization using BMARs/SMARs can be very informative and useful in improving the 

understanding of vocalization types and behavior for a given species. However, it

remains a very time-consuming and laborious undertaking.

Future efforts will focus on continuing to expand the use of fixed platforms to: a) monitor 

changes in marine mammal populations during long periods and spatial scales; b) estimate 

population densities; c) integrate acoustic information from long-time series across large spatial 

scales with available visual and other ecological data; and d) reduce the risk of human impacts.
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Other Considerations

Fixed bottom-mounted recorders are widely used by many NMFS Science Centers for data 

collection. However, these groups do not have sufficient financial and personnel resources to 

maintain an active program. Funding currently comes from external sources or from sporadic 

and unpredictable internal funds. Due to the varying needs for both BMARs and SMARs among

regions, the primary way to integrate this technology into NOAA's current technology would be 

to provide a set line item funding directed at acoustic equipment. This approach would allow 

the lease or purchase of the BMAR, SMAR, or other technology that is most appropriate for the 

regional goal and species.

References

Baumgartner, M. F., D. M. Fratantoni, T. P. Hurst, M. W. Brown, T. V. N. Cole, S. M. Van Parijs, and

M. Johnson. 2013. Real-time reporting of baleen whale passive acoustic detections from ocean 

gliders. Journal of the Acoustical Society of America. 134:1814–1823.

Spaulding, E., M. Robbins, T. Calupca, C. W. Clark, C. Tremblay, A. Waack, A. Warde, and

K. Newhall. 2009. An autonomous, near-real-time buoy system for automatic detection of 

North Atlantic right whale calls. In: Proceedings of Meetings on Acoustics, Acoustical

Society of America Conference 6(1):010001.
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Appendix D Uses of Towed Hydrophone Arrays for Cetacean 

Stock Assessment (Prepared by Jay Barlow and 

Shannon Rankin)

Introduction

Towed hydrophones have been used to collect data for cetacean stock assessment (Appendix 

G) for more than a decade. Arrays of towed hydrophones are often added to visual linetransect surveys of cetaceans to extend the range of detection, to extend surveys into 

nighttime hours, and to detect submerged animals that might be missed by visual survey 

methods. For some species (e.g., sperm whales and harbor porpoises), towed arrays can be the 

primary survey method. In general, towed hydrophones are best for species whose sounds are 

above 1 kHz because flow noise and ship noise mask low-frequency sounds in most situations. 

Although very low frequency baleen whale calls can be detected at very low tow speeds (Clark 

and Fristrup, 1997), this is not practical in most applications. For this reason, towed arrays are 

most useful for detecting odontocetes and minke whales.

In this report, we briefly review the hardware and software systems that typically are used with

towed hydrophone surveys, and discuss the primary uses of the resulting acoustic data in stock 

assessments. We also summarize the limitations of towed hydrophone arrays and discuss the 

practical impediments to increasing their contributions in cetacean stock assessment.

Hardware and Software Used

Towed hydrophone arrays

Towed hydrophone arrays are usually constructed using a series of two or more hydrophones 

distributed linearly along a cable. The hydrophone elements are encapsulated in polyurethane 

nodes (Barlow et al., 2008) or contained within an oil-filled tube (Rankin et al., 2013a). The 

hydrophones within a single array are typically close enough (30 to 300 cm separation) to 

receive the same coherent signal and to estimate a conical bearing angle to that signal using 

time-difference-of-arrival (TDOA) methods. The convergence of several bearing angles over 

time are needed to identify the location of the sound source (with a left-right ambiguity). 

These localization methods are successful for single animals or tight schools that are close to 

the surface and moving slowly relative to the vessel speed (Rankin et al., 2008). However, 

these methods break down for groups that are large and spread out, swimming fast (greater 

than ~half the survey speed), or when there are multiple distinct groups with overlapping 

vocalizations. Likewise, the time required to obtain a location using these methods potentially 

violates a key requirement for line-transect surveys: that the location of the initial detection 

occurs before the animals have responded to the vessel. 
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Improved localization performance can be attained using more complicated array 

configurations, such as multiple in-line arrays, dual towed hydrophone arrays, spatial arrays, 

towed vector sensors, and long arrays with many elements (Norris et al., 2007; Hanson et al.,

2010; Thode et al., 2010; Rankin et al., 2013a, 2013b; Zimmer, 2013; Tran et al., 2014). Current 

spatial array configurations are limited to tow speeds below that required for shipboard linetransect surveys of most cetacean species; however, we expect that design modifications will 

rectify these issues within a few years. 

Hydrophones are usually towed 200 to 300 meters behind a research ship (to decrease radiated 

ship noise and cavitation bubbles) using a multi-conductor cable with an internal strength 

member made of Kevlar or similar material. The tow cable provides power to the hydrophone 

pre-amps and any other sensors within the array (e.g., depth or directional sensors) and carries 

signals from the hydrophones to the ship. Shorter tow cables (approximately 100 m) can be 

used on smaller or quieter research ships. A modular design with underwater connectors can 

allow substitution of different hydrophone arrays with a single tow cable. State-of-the-art 

components such as digital hydrophones, vector sensors, and fiber optics cable could vastly 

improve the quality of the data collected (and therefore expand the possible uses of the data). 

However, to date these technologies have exceeded the financial resources available to NMFS. 

The tow cable can be weighted using a spiral of lead wire to increase the tow depth. Shorter 

(less than 200 m) and smaller diameter (less than 13 mm) tow cables can be deployed by hand 

and stacked on the deck, but the deployment of longer and thicker cables is greatly facilitated 

by use of a winch. When a winch is used, a waterproof connector is needed to disconnect a 

“deck cable” from the tow cable when the winch is turning.

Signal conditioning, array power, and noise considerations

Flow noise, ship noise, and electronic noise are significant concerns for towed hydrophone 

arrays. To reduce their effects, amplification and filtering are typically applied within the 

hydrophone array. Pre-amps amplify the signals by boosting them and thereby making them 

less susceptible to electronic noise after they reach the ship. Recent testing by the SWFSC 

showed that a two-stage amplification design, which provides differential output and gains up 

to 60 dB, improved signal quality by reducing susceptibility to radiated electronic noise and 

cross-talk between different hydrophone signals. A high-pass filter (approximately 1 to 2 kHz) 

is typically built into the hydrophone pre-amp to prevent low-frequency flow noise from 

clipping the signal and to allow passage of higher frequency signals. Because ship power 

frequently introduces noise, an independent 12 V battery bank typically powers all components 

of the array.

On the ship, signals are converted from analog to digital signals for real-time processing and 

storage. In some cases, additional signal-processing hardware receives the hydrophone signals 

and provides additional amplification and filtering. High-quality commercial audio digitizers can 
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provide additional analog amplification and digital conversion at rates of 192 k samples per 

second on four or more channels. For very high-frequency signals, scientific analog-to-digital 

converters can digitize four or more signals at greater than 500 k samples per second. 

Software and recording

Recent developments in computer hardware and software allow for full bandwidth recording of 

multiple channels for relatively low cost. There are a large number of software programs 

available for stereo audio recordings. These can run on off-the-shelf digital signal processing 

devices that can provide high-quality recording up to 96 or 192 kHz sampling rates for up to 

two channels (varies by device). Recording a larger number of channels at higher sampling 

rates requires software that can interface with the scientific analog-to-digital converters (of 

which there are several options). Specialized software programs allow for real-time detection, 

classification, and localization of some sounds, as well as integration of this information with 

recordings, streaming GPS input, and other metadata. A trained field technician facilitates realtime detection and tracking. However, rapid improvements in all aspects of software 

development will enhance automation in both real-time and post-processing of data collected 

using towed hydrophone arrays. 

Species- and Population-Specific Vocalization Description

Towed hydrophone arrays have been used to document the sounds made by different cetacean 

species and to determine whether sound types differ among populations. Species-specific 

vocalization characterization is not, by itself, an important component of stock assessment. 

However, it is a necessary precursor to any other use of acoustics for stock assessment. 

Recordings from towed hydrophones have been the primary source of information for building 

many vocalization-classification algorithms (Oswald, 2006; Oswald et al., 2007b).

The combination of expert visual observers and towed hydrophone arrays on line-transect 

surveys has been especially helpful in documenting vocalization characteristics. Hydrophone 

arrays provide directional information that is critically important in determining that a sound is 

coming from a specific identified individual or group. Species for which towed hydrophone 

arrays have contributed significantly to vocalization characterization include: minke whales 

(Rankin and Barlow, 2005); false killer whales (Oswald, 2006); Fraser’s dolphins (Oswald et al.,

2007a); striped dolphins (Papale et al., 2013); northern right whale dolphins (Rankin et al.,

2007); Sowerby’s beaked whale (Cholewiak et al., 2013); Longman’s beaked whale (Rankin et

al., 2012); Baird’s beaked whale (Baumann-Pickering et al., 2013); and rough-toothed dolphins 

(Rankin et al., 2015). The vocalization types of many cetacean species still have not been 

documented, and we anticipate that towed hydrophone arrays will play a significant role in 

filling these knowledge gaps.
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Stock Delineation and Distribution

Recordings collected using towed hydrophone arrays can contribute to stock delineation and 

distribution for those species that can be reliably detected using a towed array (odontocetes 

and minke whales). Given that shipboard surveys that use towed arrays typically have 

experienced marine mammal observers on board, towed arrays may be most useful for 

providing distribution information for cryptic species (such as minke whales) or during 

nighttime and poor weather conditions. 

Identification of the minke whale “boing” using towed hydrophone arrays also provided 

information of geographic variation in vocalization structure that may indicate different stocks 

in the North Pacific Ocean (Rankin and Barlow, 2005). Acoustic identification of stocks has 

been suggested for Risso’s dolphins and Pacific white-sided dolphins (Soldevilla et al., 2008).

However, application of this for towed hydrophone arrays (or other hardware methods) 

requires further research and testing.

Abundance Estimation

Absolute abundance

The use of passive acoustics to estimate absolute abundance (number of animals within a 

defined study area) has been a great challenge. This activity requires not only the random or 

systematic coverage of a study area, but also requires range estimation, accurate species 

identification, group size estimates (for group-based estimation methods), cue production rates 

(for cue-based estimation methods), and the fraction of animals on the trackline that are 

missed (for group- and individual-based estimation methods).

Using group-based estimation methods, towed hydrophone arrays have been used to estimate 

sperm whale abundance in the eastern tropical Pacific (Barlow and Taylor 2005); however, that 

study relied on group sizes estimated from the visual sighting survey conducted on the same 

ship. Group size was estimated acoustically in abundance estimates of sperm whales in the 

Ionian Sea (Lewis et al., 2007). Sperm whales are ideal for acoustic density estimation because 

they make sounds (echolocation clicks) that are readily identifiable, frequently produced 

(typically 1 to 2 per second for 80 percent of the day), and propagate long distances. Bearing 

angles are accurately estimated for these types of impulsive signals, which allows distance from 

the transect line to be estimated (Barlow and Taylor, 2005). Because echolocation clicks are 

produced in regular sequences, different bearing angles can often be estimated for multiple 

individuals, allowing use of individual-based abundance estimation methods (Gillespie and 

Leaper, 1996), although these methods may not work when group sizes exceed 5 to 10

individuals.

Cue-based methods hold some potential for estimating absolute abundance for sperm whales, 

beaked whales, and other species that produce very regular echolocation clicks. Click rates and 
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silent times have been relatively well quantified for these species. To date, however, these 

methods have not been applied to estimate abundance from towed array data.

Relative density

Using towed hydrophones to estimate relative density can be easier than estimating absolute 

abundance. Gordon et al. (2000) used acoustic detections as a measure of relative density for 

striped dolphins in the Ligurian Sea. Gerrodette et al. (2010) used data from a towed 

hydrophone to estimate relative density for vaquita and thereby extrapolate vaquita density to 

areas that could not be covered by the visual sighting survey (which was used to estimate 

absolute abundance). Fleming et al. (2013), Leaper and Gordon (2015), and Yack (2013) use 

acoustic detections from towed arrays to create habitat-based models of relative density for 

Dall’s porpoise, harbor porpoise, and beaked whales, respectively.

Estimation of fraction missed by visual observers

Cetacean line-transect surveys typically employ visual observers to detect animals when they 

are at the surface. To estimate density or abundance, corrections are needed to account for 

cetaceans that never surface within the range of visual observers or are otherwise not seen. 

One method to estimate the fraction missed is to use one or more independent visual 

observers recording sightings that were missed previously by the primary team. However, this 

approach cannot account for animals that never surface within visual range. Acoustic methods 

can detect submerged animals and thereby provide a more complete accounting of animals 

missed by visual observers. This approach has been used for false killer whales (Barlow and 

Rankin, 2007); rough-toothed dolphins (Rankin et al., 2009); and harbor porpoises (Gordon et 

al., 2011). If visual and acoustic methods are independent, this dual-platform approach can 

estimate both the fraction missed visually and the fraction missed acoustically (Leaper and 

Gordon, 2015). 

Limitations and Impediments to the Wider Use of Towed Arrays in Stock 

Assessment

Towed hydrophone arrays are particularly effective for detecting odontocetes but have limited 

ability to detect mysticetes (except minke whales). Species classification for many odontocetes 

has seen rapid improvement in recent years; however, significant hurdles remain in acoustic 

species classification for many delphinids.

Localization has typically relied on the convergence of vocalizations from a group based on 

differences in arrival time. The best location using these methods is obtained after the group 

has passed the beam (900) of the ship. If animals react to the vessel by moving toward or away 

from the transect line, acoustic localizations using towed arrays are likely to occur after this 

reactive movement, a factor that may bias line-transect density estimates. With the exception 

of porpoise, group size estimation of cetaceans using towed hydrophone arrays has made very 

little progress. Acoustic behavior is variable based on a large number of factors—one of which 
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is group size. Disentangling these variables presents one of the hurdles to estimating group 

size based on acoustic detections. There is a spatial and temporal disconnection between visual 

sightings ahead of the ship and acoustic detections, which are typically behind the ship. For 

some species, it can be very difficult to match visual and acoustic detections due to the time 

delay. This is especially true for species for which the acoustic detection range is extremely 

short (porpoise and beaked whales). This is an impediment to the use of combined visual and 

acoustic surveys to estimate the fraction missed by both methods.

Towed arrays perform best when the ship maintains a constant course and speed. Inopportune 

changes in course or speed can negatively affect localization and recording quality by increasing 

the noise. Also, changes in course and speed make it extremely difficult to effectively use 

towed array data as an independent “observer” to estimate the fraction of animals missed by 

the visual observation team.

Collection of data from towed arrays requires trained field personnel and extended periods. It 

is difficult to train and retain field personnel. Ideally, NMFS Science Centers could have a 

trained pool of experienced acoustic field technicians. This approach would improve the

quality of data collection and continuity between surveys.

Effective analysis of towed array data requires additional software improvements to improve 

post-processing of acoustic data. Currently, PAMGUARD provides good visualization, data 

processing, and analysis for echolocation clicks. Expansion of these modules to include 

detection and analysis of other vocalization types would vastly improve post-processing of 

towed array data. In addition, improved synchronization of data from different vocalization

types with each other and with data obtained from a visual observation platform would 

improve matching of acoustic and visual detections.

References

Barlow, J., and B. L. Taylor. 2005. Estimates of sperm whale abundance in the northeastern temperate 

Pacific from a combined acoustic and visual survey. Marine Mammal Science 21(3):429–445.

Barlow, J., and S. Rankin. 2007. False killer whale abundance and density: preliminary estimates for the 

PICEAS study area south of Hawaii and new estimates for the US EEZ around Hawaii. Southwest 

Fisheries Science Center (SWFSC) Administrative Report LJ-07-02. 15 p.

Barlow, J., S. Rankin, and S. Dawson. 2008. A guide to constructing hydrophones and hydrophone arrays 

for monitoring marine mammal vocalizations. NOAA Technical Memorandum NOAA-TM-NMFSSWFSC-417. 19 p.

Baumann-Pickering, S., T. M. Yack, J. Barlow, S. M. Wiggins, and J. A. Hildebrand. 2013. Baird’s beaked 

whale echolocation signals. Acoustical Society of America 133(6):4321–4331
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Clark, C. W., and K. M. Fristrup. 1997. Whales ’95: A combined visual and acoustic survey of blue and fin 

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Appendix E Mobile Autonomous Platforms (Prepared by 

Holger Klinck and Jay Barlow)

General Overview

This appendix focuses on buoyancy-driven, autonomous underwater vehicles (AUVs), wind/wavepowered unmanned surface vehicles (USVs), and free-drifting buoy recorders. Vehicles featuring 

electric or combustion engines are outside the scope of this white paper. Figure 3 illustrates several 

AUVs and USVs that have been used for passive acoustic monitoring (PAM) of marine mammals.

Figure 3. Autonomous mobile platforms for passive-acoustic monitoring of marine mammals.
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Autonomous Underwater Vehicles

• Mode of operation: Buoyancy-driven AUVs, such as gliders and floats, use changes in volume 

(usually generated by pumping oil back and forth between a reservoir and an external bladder) 

to create positive and negative buoyancy. Although floats can control only the depth at which 

they drift with the current, gliders utilize wings to generate forward velocity as well as vertical 

motion. Additional internal control and navigation mechanisms to change pitch (e.g., by 

changing the center of gravity) and heading (e.g., by using a rudder) allow a glider to fly in a sawtooth pattern from waypoint to waypoint. When the glider reaches the surface between dives,

a bidirectional satellite link allows remote communication with the device. 

• Speed/Depth: Gliders are slow-moving vehicles. Average speed is approximately 0.5 knots. 

Floats drift at the speed of the current. The maximum operating depth of the available 

gliders/floats varies from a few hundred meters to 2 km.

• Duration (including PAM): Several weeks to a few months.

• Cost: The purchase price for commercially available floats (without a PAM system) ranges from

$15,000 to $20,000; gliders cost approximately $100,000 to $150,000.

• Other considerations: The internal glider control and navigation mechanisms can hinder 

acoustic observations (e.g., saturating the PAM system). In the case of the Seaglider, the related 

acoustic data loss during a typical 1,000 m dive is approximately 5 to 10 percent. In addition, 

some gliders are and some are not well suited for operation in areas with strong ocean currents. 

Unmanned Surface Vehicles

• Mode of operation: Wind/wave-powered USVs have not been used extensively for passive 

acoustic monitoring of marine mammals. Wind-powered USVs (a.k.a. robotic sailboats) such as 

the Roboat and Saildrone are prototype vehicles and not commercially available at this point. 

The wave-powered Wave Glider is composed of two components: a surface float that is roughly 

the size and shape of a surfboard and a subsurface unit that is equipped with wings. The surface 

and subsurface units are connected by a 7 m umbilical tether. A rising wave lifts the float, 

causing the tethered subsurface unit to rise. The articulated wings on the subsurface unit are 

pressed down, and the upward motion of the subsurface unit becomes an up-and-forward 

motion, in turn pulling the float forward and off the wave. This causes the subsurface unit to 

drop, the wings pivot up, and the subsurface unit moves down-and-forward. 

• Speed: Wind-powered USVs can reach speeds of several knots (depending on the size of the 

boat and sails). The Wave Glider SV3 reaches speeds up to 2.5 knots.

• Duration (including PAM): In principal, months to years.

• Cost: The purchase price (for academic institutions) for the Wave Glider SV3 (without the PAM 

system) is approximately $250,000. Wind-powered USVs are not commercially available at this 

time.
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• Other considerations: Compared with AUVs, USVs provide an increased payload capacity (e.g., 

for additional environmental sensors), the capability of harnessing solar power to extend the 

survey duration, real-time data access, and increased speed. However, increased speed can 

hinder the detection of low-frequency vocalizations because of increased flow noise. This is 

especially an issue for the fast-moving, wind-powered USVs. The Wave Glider, too, has been 

reported to make the detection of low-frequency vocalizations challenging due to noise caused 

by the subsurface unit. USVs are generally not well-suited for towing long hydrophone cables 

because the cables reduce their maneuverability and speed (drag). Consequently, the acoustic 

sensors are restricted to the upper water column. Depending on local sound-propagation 

conditions, this can reduce the detection range for marine mammal vocalizations. 

Free-Drifting Passive Acoustic Monitoring Systems

• Mode of operation: Free-drifting PAM systems are designed to drift with surface currents or the 

wind. The recorder can be packaged within a surface float with wired connections to subsurface 

hydrophones, or autonomous hydrophones can be attached to a rope line below a surface float. 

Recorders must be recovered to retrieve full data files, but processors within a surface float can 

send summary information via satellite or cell phones. Retrieval can be facilitated with satellite 

locators and VHF beacons. 

• Speed: Drift rates depend on ocean currents but are typically 0.2 to 0.5 knots. Drifts cannot be 

controlled directly, but can be influenced by using windage or subsurface drogues at different 

depths to take advantage of predominant wind and current directions. 

• Duration (including PAM): Several months.

• Cost: Costs for a simple 2-element vertical hydrophone array, 100 m of conducting cable, and a 

surface recording package with GPS synchronization is approximately $4,000 to $5,000

excluding labor. Complete systems may be commercially available soon.

• Other considerations: Vertical hydrophone arrays are easy to incorporate in drifting systems, 

and these can be used to help approximate detection ranges for cetacean density estimation. 

Vertical hydrophone arrays at 100 m have been found to detect surface reflections of beaked 

whale echolocation signals that can be used to improve range estimation. The effect of surface 

waves on hydrophone noise can be mitigated by using elastic cords and dampener disks, thus 

allowing free-drifting systems to record ambient sound levels with little self-noise. Being at the 

surface allows the use of GPS signals to precisely synchronize clocks in multiple units and allow 

localization by time difference of arrival (TDOA). Payload is limited only by the size of the 

surface buoy. Long-duration deployments may be able to utilize solar or wave energy for 

power. 
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Passive Acoustic Monitoring Systems

There are many different PAM systems available for use with mobile autonomous platforms. For AUVs 

and USVs, systems fall into two general categories:

• Integrated PAM systems are fully incorporated into the platform of choice. Most of these systems 

utilize the main vehicle battery for power. Integrated PAM systems feature real-time detection and 

reporting capabilities and can be controlled remotely throughout a mission.

• Piggyback PAM systems (mostly recording only) are completely independent systems (including a

battery) that utilize the AUV/USV as a carrier with no communication between the PAM system and 

the AUV/USV or a shore station.

Each system has advantages and disadvantages. For short-duration surveys (1 to 2 weeks) without realtime detection requirements, piggybacked PAM systems work well. One advantage of these systems is 

that they do not share any electronic connections with the AUV/USV, reducing the risk of potential 

electronic noise issues. For repeated long-duration surveys, a full integration of the PAM system into 

the AUV/USV is preferable. Fully integrated PAM systems allow for remote and flexible programming 

(turn off passive acoustic monitoring during transits; record only every other dive, etc.); utilization of the 

AUV/USV main vehicle battery (extended operation); and GPS time synchronization (e.g., accurate time 

stamping of files). Free-floating PAM systems are currently independent systems that may include their 

own processing and communication system.

The recommended vehicle-PAM combination largely depends on four factors: 1) the species of interest 

(e.g., low- vs. high-frequency vocalizations, shallow vs. deep diver); 2) the environmental conditions in 

the study area (e.g., shallow vs. deep water, weak vs. strong current); 3) your research question; and

4) your budget.

Developers/users

Following is a list of individuals who have been involved in passive acoustic monitoring of marine 

mammals using mobile autonomous platforms (in no specific order):

• Erin Oleson (NOAA/PIFSC), Bruce Howe and Lora Van Uffelen (University of Hawaii)

Platform: Seaglider

PAM: DMON

Status: Active

• Martin Siderius, Lisa Zurk, and Elizabeth Kuesel (Portland State University)

Platform: Slocum Glider

PAM: DMON

Status: Active 
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• David Mellinger (OSU, PMEL), Haru Matsumoto (OSU, PMEL), Holger Klinck (Cornell University), 

OSU, PMEL), Jim Luby (University of Washington)

Platforms: Seaglider, Slocum Glider, APEX autonomous profiling float, Roboat

PAM: Various proprietary systems, Songmeter SM2+

Status: Active 

• John Hildebrand, Sean Wiggins and Gerald D’SPain (SIO), Marie Roch (SDSU)

Platforms: Wave Glider, ZRay Glider

PAM: Various proprietary systems

Status: Unknown

• Aaron Thode (SIO)

Platforms: Spray Gilder

PAM: Acousonde

Status: Unknown 

• Harold Cheyne (Cornell University)

Platform: Wave Glider

PAM: Proprietary system

Status: Not active

• Mark Baumgartner and David Fratantoni (WHOI)

Platform: Slocum Glider, APEX autonomous profiling float, Wave Glider

PAM: DMON

Status: Active

• Phil Abbot (Ocean Acoustical Services and Instrumentation Systems)

Platform: Slocum Glider, Remus AUV

PAM: Proprietary systems

Status: Active

• Doug Nowacek (Duke University)

Platform: Seaglider 

PAM: DMON

Status: Not active

• David Mann (Loggerhead Instruments)

Platform: Slocum Glider

PAM: Proprietary system

Status: Not active

• Doug Gillespie and Mark Johnson (University of St. Andrews)

Platform: Seaglider, Slocum Glider, Wave Glider 

PAM: Proprietary systems

Status: Active
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• Alberto Dassatti and Walter Zimmer (NATO Undersea Research Centre)

Platform: Slocum Glider, Spray Glider

PAM: Proprietary system (PAMBuoy, Decimus)

Status: Unknown

• Jay Barlow (NOAA/SWFSC)

Platform: DASBR free-drifting buoy recorder (custom)

PAM: Wildlife Acoustics SM2BAT+ w/GPS

Status: Active

The most active groups in the U.S. are currently WHOI (Baumgartner); OSU/APL/PMEL (Mellinger, 

Matsumoto, Klinck, and Luby); and SWFSC (Barlow). Although WHOI’s efforts focus primarily on 

mysticetes in coastal waters using the Slocum glider, OSU/APL targets mostly odontocetes in offshore 

waters using the Seaglider and APEX float. The SWFSC targets beaked whale and sperm whale density 

estimation with free-drifting systems.

Existing hurdles

• Initial cost: The initial costs to buy mobile autonomous platforms are high. Most models cost 

more than $100,000 (without PAM) and often require an additional investment in training 

(piloting, maintenance, etc.) and infrastructure (base station, Iridium contracts, etc.). Costs are 

considerably less for free-drifting systems. Kongsberg Inc. now offers an acoustics package 

(originally developed by OSU and EOS, Inc.) as an option when buying a Seaglider. This is 

currently—to our knowledge—the only available off-the-shelf AUV featuring a PAM system.

• Deployment duration: The duration of most AUVs is limited to a few weeks (4 to 8 weeks when 

recording continuously). USVs can, in principal, operate for months. However, such longduration PAM surveys have not been conducted yet. Free-drifting systems have been deployed 

for months.

• Liability: USVs are potential navigational hazards and can cause liability issues when operated in 

areas with high recreational and commercial shipping activity (collisions). 

• Data analysis: The acoustic data recorded with mobile autonomous platforms often contains 

electronic and mechanical noise that is caused by the vehicle itself. Noise sources include the 

buoyancy pump, rotating battery packs, rudder movements, etc. Therefore, the data analysis 

with automated detectors and classifiers can be challenging (false positives). Free-drifting 

systems can record with very low levels of self-noise, and standard software (e.g., PamGuard) 

has been used to analyze their WAV files.

• Density estimation: A statistical framework for estimating marine mammal densities using data 

collected with (slow moving) mobile autonomous platforms has not been developed yet. 

However, the ONR recently funded (FY2015 funding cycle) such an effort lead by Danielle Harris, 

University of St. Andrews. This project is intended to be completed by 2017.

• Slow development: The number of users is still very limited, and we just started to use AUVs 

regularly for long-duration (longer than 1 month) surveys. The lessons learned from these 

survey efforts are critical for improving the systems (reliability, data quality, etc.). However, 
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because the deployments are sparse, the “maturing process” takes a long time. Funding is, of 

course, also a limiting factor.

Future directions

There is no doubt that mobile autonomous platforms will play a major role in future marine mammal 

monitoring efforts, especially considering the reduced availability and high cost of ship time for 

traditional marine mammal surveys and the deployment of stationary recorders.

Future efforts will focus on using mobile autonomous platforms to: 1) monitor marine mammal 

populations in remote and inaccessible areas; 2) estimate population densities; and 3) conduct holistic 

ecosystem studies by utilizing additional biological and chemical oceanographic sensor packages.

Other considerations

It is obvious that most groups interested in collecting data with these instruments do not have the 

proper financial and personnel resources to establish and maintain an AUV/USV program. As indicated 

earlier, several AUV/USV efforts are currently not active likely because of the lack of funding.

This lack of funding raises the question of how to make this technology available to the broader 

community. One solution could be the establishment of a few centers, which provide AUVs/USVs as a 

service. External (project) funding would help these centers to maintain the personnel and 

infrastructure necessary to operate and maintain the vehicles. This funding would also ensure a certain 

degree of uniformity of data products across the surveys, which would be extremely useful when 

pooling multiple surveys data sets for large-scale studies. 

References

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Klinck, H., D. K. Mellinger, K. Klinck, N. M. Bogue, J. C. Luby, W. A. Jump, G. Shilling, B. T. Litchendorf,

A. S. Wood, G. S. Schorr, and R. W. Baird. 2012. Near-real-time acoustic monitoring of beaked 

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Appendix F Absolute Density and Abundance Estimation from 

Passive Acoustic Data (Prepared by Danielle 

Harris, Tiago Marques, and Len Thomas)

General Overview

The aim of this document is to provide a broad overview of the topic of animal density and abundance 

estimation using passive acoustic data, examples of applications, and a summary of associated 

challenges. We encourage readers to refer to a comprehensive review paper (Marques et al., 2013) for 

more detail on the information presented here, as well as the cited literature. We also note that while 

the focus of this white paper will be on marine mammal studies, passive acoustic density/abundance 

estimation is applicable to a wide range of both aquatic and terrestrial taxa (see Marques et al., 2013, 

and Stevenson et al., 2015, for more details and references). 

Traditionally, marine mammal density and abundance estimates have been derived from ship-based 

visual sightings surveys. However, the potential to use acoustic data to estimate marine mammal 

absolute density or abundance has been recognized for several years (e.g., McDonald and Fox, 1999). 

During the last decade or so, research efforts into the topic of density/abundance estimation from 

passive acoustic data has grown. Both fixed passive-acoustic instruments and ship-towed instruments 

have been used for marine mammal studies (e.g., fixed: Marques et al., 2009; towed: Barlow and Taylor,

2005). More recently, density/abundance estimation from mobile autonomous platforms has become 

an active research topic. 

Absolute density and abundance estimators

Visual or acoustic encounters of animals are sometimes presented as relative indices of density or 

abundance. However, in order to interpret spatial and temporal patterns in such indices as changes in 

the underlying density or abundance of the study species, it must be assumed that the same proportion 

of animals are always detected across all surveyed sites and time periods. There are often many reasons 

such an assumption would be violated, leading to the need for absolute density and abundance 

methods. A fundamental concept of absolute density or abundance estimation is that animals missed in 

a surveyed area must be accounted for. This task is accomplished by estimating the probability of 

detecting an animal during the survey. 

A typical density estimator, which estimates absolute density from animals observed during a survey, is 

as follows:

DD� = nn

pp�aa (Eqn. 1)

where DD� is the estimated density, n is the number of observations made during the survey, pp̂ is the 

estimated average probability of detecting an animal, and a is the total surveyed area.
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If the survey has been designed so that the surveyed area represents the whole study area, A, then 

absolute abundance, NN�, can be estimated as:

NN� = DD� × AA (Eqn. 2)

In passive acoustic monitoring, individual animals often cannot be easily counted. However, acoustic 

“objects,” such as individual vocalizations or vocally active groups, can. Furthermore, automated 

routines, which can generate false detections, are often used in acoustic data processing. Therefore, 

density estimators linked to acoustics are often based on the following:

DD� = nn�1−ff̂�

pp�aarr̂ (Eqn. 3)

where n is now the number of observed objects, f is the proportion of false detections generated by the 

detection routine, and r represents the appropriate multiplier(s) that will convert the object density to 

animal density. For example, if individual vocalizations are counted, the required multipliers will include 

the average vocalization rate and the amount of time spent monitoring (in addition to the probability of 

detection, which is also a multiplier). 

Methods to estimate animal density and abundance

Although an entire population can rarely be censused, it may be possible to detect all animals within 

monitored lines or points. These survey types are known as strip-transect sampling (using lines) or plot 

sampling (using points). Given an appropriate survey design (i.e., a sufficient number of survey lines or 

points have been randomly placed with respect to the underlying distribution of animals), then the 

density in the lines or points can be used as a representative estimate for the rest of the study area. 

Strip-transect or plot sampling are examples of design-based surveys, where the surveyed areas can be 

assumed to be a random sample of all the possible survey lines or points. Resulting density estimates 

are applicable to the wider study area. Conversely, if a standard survey design has not been followed, 

then inference about density and abundance in the wider study area is made using a statistical model. 

The model links density or abundance to covariates, which can be used to predict numbers of animals in 

the unsurveyed regions of the study area. 

In cases where animals are missed within surveyed areas, several methods can be used to estimate the 

probability of detection. These include traditional, commonly used methods, such as distance sampling 

and mark-recapture (Buckland et al., 2001; Borchers et al., 2002). Distance sampling can be conducted 

from surveyed lines (line-transect sampling) or points (point-transect sampling). An extension of markrecapture is spatially explicit capture-recapture (SECR), which is also related to distance sampling 

(Borchers, 2012; Borchers et al., 2015). The advantage of SECR over mark-recapture is that density, as 

well as abundance, is easily inferred. In mark-recapture methods, it is difficult to estimate the size of 

the surveyed area, making it possible to estimate abundance; however, density estimation becomes 

non-trivial. Other “non-standard” methods to estimate detection probability also exist that often rely 

on auxiliary information (e.g., Marques et al., 2009). Many of the non-standard methods were 

developed specifically for use with passive acoustic data; some examples are given later in this section.
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Each method requires different information to be recorded about the observations. Distance sampling 

requires horizontal ranges to each detection be estimated. Spatially explicit capture-recapture 

(originally developed for trapping small terrestrial mammals) requires detections to be identifiable 

across “traps” and knowing the location of the “traps.” In passive acoustic surveys, this means that the 

same acoustic event must be identifiable across multiple instruments in an array (where the location of 

the instruments is known). Non-standard methods generally require less information about the 

detections, but rely on more assumptions and modeling to compensate for the lack of empirical data. It 

is important to note that most of the methods discussed earlier have associated assumptions, which, if 

violated, can result in biased estimates of the detection probability and, ultimately, density or 

abundance.

Variance estimation

Estimating the uncertainty in a density or abundance estimate is a crucial part of an analysis. It is 

important to generate estimates that are as precise as possible so that they can be useful in, for 

example, management and mitigation decisions. The coefficient of variation (CV) is often reported as a 

measure of uncertainty of density or abundance estimates. The CV of an estimated parameter is 

calculated as the standard error of the estimate, divided by the estimate. This is a useful measure 

because levels of uncertainty can then be compared between estimated parameters that have different 

measurement units. The overall CV of a density or abundance estimate can be estimated by combining 

the CVs associated with all the estimated parameters in the estimator, using the delta method (Seber,

1982). 

Examples and Case Studies

All methods described earlier (except mark-recapture, for the reasons cited) have been implemented in 

marine mammal studies using acoustic data. Examples are given here, but it should be noted that this is 

a non-exhaustive list.

Census/strip transects

Moretti et al. (2010) estimated Blainville’s beaked whale density at the Atlantic Undersea Test and 

Evaluation Center (AUTEC). The dense array of fixed hydrophones at AUTEC allowed the number of 

diving beaked whale groups to be detected with certainty, and there was no need to estimate the 

probability of detection. Therefore, this analysis was essentially a census of diving beaked whale groups. 

Other multipliers (mean group size and an average rate of diving) were required to estimate the density 

of animals from the density of diving groups.

Ward et al. (2012) also estimated sperm whale density at the AUTEC range using a plot sampling 

approach. However, in this case, the number of sperm whales in specific time bins was counted, leading

to a different density estimator than the one used in Moretti et al. (2010). The differences in the two 

analyses provide a good demonstration of the flexibility of density or abundance estimation methods; 

the estimators can be adapted to suit a given vocalization type or a particular signal-processing scheme. 
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Distance sampling

Distance-sampling approaches have been used with both towed and fixed acoustic instruments. Shipbased surveys using towed hydrophones can determine distances to vocalizing animals, which can then 

be analyzed using distance-sampling methods. For example, sperm whale abundances have been 

estimated from such data (e.g., Barlow and Taylor, 2005; Lewis et al., 2007). Lewis et al. (2007) counted 

individual vocalizing animals, whereas Barlow and Taylor (2005) counted the number of vocalizing

groups and therefore required an average group-size multiplier in their estimator, as in Moretti et al.

(2010). Distance sampling requires the horizontal distance from the line or point to the animal. 

However, distances estimated using towed instruments are often the direct distance to the vocalizing

animal. Without an estimate of the depth of the animal and the angle of detection from the transect 

line, the horizontal distance cannot be estimated. This fact can pose a potential issue because using 

direct distances in the analysis may cause bias in the probability of detection estimate. Recently, 

methods to extend standard distance sampling that consider the potential depths of vocalizing animals 

have been developed and implemented (Yack et al., 2015).

Marques et al. (2011) used point-transect sampling to estimate North Pacific right whale density from 

three HARPs deployed in the Bering Sea. Normal-mode propagation could be used to estimate the 

range of right whale calls using separate sensors. The number of calls was counted and an average 

vocalization rate, which converts estimated call density to estimated animal density, was used from 

combined visual and acoustic focal follows of right whale groups. Harris et al. (2013) also used pointtransect sampling to estimate the density of fin whale vocalizations recorded on Ocean Bottom 

Seismometers in the Atlantic Ocean. No suitable vocalization rate was available, and therefore the 

estimation of animal density was not possible. 

Spatially explicit capture-recapture

Marques et al. (2012) estimated the density of minke whale vocalizations at the Pacific Missile Range 

Facility using SECR. This analysis was extended using more data in Martin et al. (2013) to estimate 

minke whale density. The number of minke whale vocalizations was counted, and a vocalization rate 

was estimated from acoustically tracking a suspected single whale on the hydrophone range for several 

hours. 

Detection probability from auxiliary data

There are several different ways in which the probability of detection can be estimated using auxiliary 

data. Marques et al. (2009) used acoustic tag data to estimate the detection probability of Blainville’s 

beaked whales on the fixed hydrophones at AUTEC. The location of the tagged animal when it was 

clicking was known, and its clicks could be matched to those received on the fixed hydrophones. Click 

detectability could then be modeled as a function of distance using a logistic regression analysis. A 

similar approach was taken by Kyhn et al. (2012) to estimate harbour porpoise density. As an 

alternative to using acoustic tags to conduct the trial to assess detection probability, porpoises were 

visually tracked from a land vantage point. The distances from the fixed instruments at which the 

animals were acoustically detected could then be estimated.
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Finally, a simulation-based method has been developed that mimics animals around a single instrument 

and predicts the average probability of detecting their vocalizations based on information about 

vocalization source level, sound propagation, ambient noise levels, and the efficiency of the automatic 

detection process. This approach was first used to estimate beaked whale density (Küsel et al., 2011) 

and has been subsequently used for blue and humpback whales (Harris, 2012; Helble et al., 2013a, b). 

Challenges of Passive Acoustic Density Estimation

A suite of statistical methods now exists to estimate absolute density or abundance using passive 

acoustic data. As more case studies use these methods, the research should focus on three key areas:

1) survey design; 2) the accuracy and precision of multipliers; and 3) understanding animals’ acoustic 

behavior.

Survey design

The way that a survey is designed will affect not only the precision and accuracy of the density or 

abundance estimate, but also the applicability of those estimates to the wider study area of interest. 

Many of the density-estimation methods discussed earlier were first developed or implemented for 

marine mammals using hydrophone arrays that were not optimized for marine mammal monitoring 

(e.g., military hydrophone ranges). In cases where hydrophones were deployed to monitor marine 

mammals, only a few sensors were available (e.g., Marques et al., 2011). In these cases, methods could 

be demonstrated as a proof of concept, but it was acknowledged that survey design needed 

improvement. Therefore, focus should now be placed on implementing robustly designed acoustic 

surveys that have enough instruments to provide the required spatial and temporal coverage. In 

addition, at the survey-design stage, consideration must be given to how the detection probability will 

be estimated (preferably using a “standard” method such as distance sampling or SECR), because this 

will also affect instrument configuration.

Multipliers

Multipliers of any kind (e.g., vocalization rates, group size, or detection probability) will add additional 

uncertainty to the overall density or abundance estimate. Therefore, survey designs that do not require 

such multipliers are preferred. However, should multipliers be required, and they are often 

unavoidable, they ideally should be estimated using data collected from the study animals at the same 

time and place of the acoustic survey. This approach ensures that any given multiplier will be the 

correct average for those animals at the time of the survey, helping to achieve unbiased density or 

abundance estimates. Where multipliers can be estimated from collected data, such as false positive

proportions, systematic random-sampling schemes will ensure that an appropriate sample of the data is 

taken to estimate the required parameter.

Behavioral information

Finally, it is clear that for passive acoustic monitoring of marine mammals to be successful, a good 

understanding of the acoustic behavior of the study species is required. This is true not only for density 

and for abundance estimation, but also for other research questions that can be answered using 
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acoustic monitoring. For many cetacean species, little is known about the full repertoire of their 

vocalizations and the contexts in which vocalizations are made. Such information is vital to plan 

efficient passive acoustic surveys; therefore, continued research focus on cetacean vocal behavior is 

required. Furthermore, for density or abundance estimates, fine-scale behavioral studies are essential 

for the estimation of multipliers such as vocalization rates and group sizes, and should also be included 

as part of the survey design process.

References

Barlow, J., and B. Taylor. 2005. Estimates of sperm whale abundance in the northeastern temperate 

Pacific from a combined acoustic and visual survey. Marine Mammal Science 21:429–445.

Borchers, D. 2012. A non-technical overview of spatially explicit capture-recapture models. Journal of 

Ornithology 152(2):S435–S444.

Borchers, D. L., S. T. Buckland, and W. Zucchini. 2002. Estimating Animal Abundance: Closed Populations. 

Springer, New York. 

Borchers, D. L., B. C. Stevenson, D. Kidney, L. Thomas, and T. A. Marques. 2015. A unifying model for 

capture-recapture and distance sampling surveys of wildlife populations. Journal of the American 

Statistical Association 10:195–201.

Buckland, S. T., D. R. Anderson, K. P. Burnham, J. L. Laake, D. L. Borchers, and L. Thomas. 2001.

Introduction to distance sampling—Estimating abundance of biological populations. Oxford 

University Press, Oxford, England.

Harris, D. 2012. Estimating whale abundance using sparse hydrophone arrays. Ph.D. dissertation.

University of St. Andrews, Fife, Scotland.

Harris, D., L. Matias, L. Thomas, J. Harwood, and W. Geissler. 2013. Applying distance sampling to fin 

whale calls recorded by single seismic instruments in the northeast Atlantic. Journal of the 

Acoustical Society of America 134:3522–3535.

Helble, T. A., G. L. D’Spain, G. S. Campbell, and J. A. Hildebrand. 2013a. Calibrating passive acoustic 

monitoring: Correcting humpback whale call detections for site-specific and time-dependent 

environmental characteristics. The Journal of the Acoustical Society of America 134:EL400–EL406.

Helble, T. A., G. L. D’Spain, J. A. Hildebrand, G. S. Campbell, R. L. Campbell, and K. D. Heaney. 2013b.

Site-specific probability of passive acoustic detection of humpback whale calls from single fixed 

hydrophones. The Journal of the Acoustical Society of America 134:2556–2570.

Küsel, E. T., D. K. Mellinger, L. Thomas, T. A. Marques, D. J. Moretti, and J. Ward. 2011. Cetacean 

population density from single fixed sensors using passive acoustics. Journal of the Acoustical 

Society of America 129:3610–3622.

Kyhn, L. A., J. Tougaard, L. Thomas, L. R. Duve, J. Steinback, M. Amundin, G. Desportes, and J. Teilmann. 

2012. From echolocation clicks to animal density—acoustic sampling of harbour porpoises with 

static dataloggers. Journal of the Acoustical Society of America 131:550–560.

Lewis, T., D. Gillespie, C. Lacey, J. Matthews, M. Danbolt, R. Leaper, R. McLanaghan, and A. Moscrop. 

2007. Sperm whale abundance estimates from acoustic surveys of the Ionian Sea and Straits of Sicily 

in 2003. Journal of the Marine Biological Association of the UK 87:353–357. 
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Marques, T. A., L. Thomas, S. W. Martin, D. K. Mellinger, S. Jarvis, R. P. Morrissey, C.-A. Ciminello, and

N. DiMarzio. 2012. Spatially explicit capture-recapture methods to estimate minke whale abundance 

from data collected at bottom-mounted hydrophones. Journal of Ornithology 152:S445–S455.

Marques, T. A., L. Thomas, S. Martin, D. Mellinger, J. Ward, D. Moretti, D. Harris, and P. Tyack. 2013.

Estimating animal population density using passive acoustics. Biological Reviews 88:287–309.

Marques, T. A., L. Thomas, L. Munger, S. Wiggins, and J. A. Hildebrand. 2011. Estimating North Pacific 

right whale (Eubalaena japonica) density using passive acoustic cue counting. Endangered Species 

Research 13:163–172.

Marques, T. A., L. Thomas, J. Ward, N. DiMarzio, and P. L. Tyack. 2009. Estimating cetacean population 

density using fixed passive acoustic sensors: an example with beaked whales. Journal of the 

Acoustical Society of America 125:1982–1994.

Martin, S. W., T. A. Marques, L. Thomas, R. P. Morrissey, S. Jarvis, N. DiMarzio, D. Moretti, and

D. K. Mellinger. 2013. Estimating minke whale (Balaenoptera acutorostrata) “boing” sound density 

using passive acoustic sensors. Marine Mammal Science 29:142–158.

McDonald, M. A. and C. G. Fox. 1999. Passive acoustic methods applied to fin whale population density 

estimation. Journal of the Acoustical Society of America 105:2643–2651.

Moretti, D., T. A. Marques, L. Thomas, N. DiMarzio, A. Dilley, R. Morrissey, E. McCarthy, J. Ward, and

S. Jarvis. 2010. A dive counting density estimation method for Blainville's beaked whale 

(Mesoplodon densirostris) using a bottom-mounted hydrophone field as applied to a Mid-Frequency 

Active (MFA) sonar operation. Applied Acoustics 71:1036–1042.

Seber, G. A. F. (1982). The Estimation of Animal Abundance. Second Edition. Griffin, London.

Stevenson, B. C., D. L. Borchers, R. Altwegg, R. J. Swift, D. M. Gillespie, and G. J. Measey. 2015. A general 

framework for animal density estimation from acoustic detections across a fixed microphone array. 

Methods in Ecology and Evolution 6:38–48.

Ward, J., L. Thomas, S. Jarvis, N. DiMarzio, D. Moretti, T. A. Marques, C. Dunn, D. Claridge, E. Hartvig, 

and P. Tyack. 2012. Passive Acoustic Density Estimation of Sperm Whales in the Tongue of the 

Ocean, Commonwealth of the Bahamas. Marine Mammal Science 28:E444–E455.

Yack, T. M., S. Coates, D. Harris, L. Thomas, T. Norris, E. Ferguson, and B. K. Rone. 2015. From Clicks to 

Counts: Using passive acoustic monitoring to estimate the density and abundance of Cuvier’s 

beaked whales in the Gulf of Alaska. Presentation at the 7th International Workshop on Detection, 

Classification, Localization, and Density Estimation of Marine Mammals using Passive Acoustics, July 

13–16, 2015, La Jolla, CA.
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Appendix G Marine Mammal Stock Assessment Requirements

(Prepared by Jay Barlow)

The Marine Mammal Protection Act (MMPA) was amended in 1994 to require stock assessment reports 

for marine mammal stocks within U.S. jurisdiction (Appendix H). The requirements for stock assessment 

are further refined in the GAMMS II (NMFS 2005). The purpose of stock assessment reports is to 

evaluate human impacts on marine mammal populations and to determine their status under the 

MMPA. Similarly, the Endangered Species Act (ESA) requires periodic reviews of all endangered species 

to evaluate progress in meeting recovery goals and to reevaluate their status under the ESA. The 

contribution of passive acoustics to both MMPA stock assessments and ESA status reviews conducted by 

NMFS were considered at the MMC/NMFS Workshop. The requirements for an MMPA stock 

assessment are clearly established and include the following:

1. Stock definition and geographic range (including seasonal/temporal variation)

2. Estimation of population size and trends in abundance (with emphasis on approximating a 

“minimum population estimate”)

3. Estimation of current and maximum net productivity rates

4. Calculation of PBR

5. Estimation of annual human-caused mortality and serious injury

6. Evaluation of other factors causing decline or impeding recovery for strategic stocks

7. Evaluation to determine whether a stock is “strategic” under the MMPA

The requirements of ESA status reviews are not as clearly established, but certainly include, many of the 

same elements as MMPA stock assessments. The main difference is that standards for delineating 

management units under the ESA (called distinct population segments, or DPSs) are stricter than the 

standards for population stocks under the MMPA. The guidelines for delineating a DPS were established

in 1996 as a joint policy by NMFS and the U.S. Fish and Wildlife Service.12

Passive acoustics can help most directly in meeting stock assessment requirements 1, 2, and 3. 

Consistent differences in vocalizations between populations can aid in delimiting population stocks or 

DPSs and may be helpful in subspecies designations (as is common for birds). Passive acoustic 

monitoring can achieve broad temporal and spatial coverage that can be useful in determining 

seasonal/temporal changes in geographic range. Long-term trends in vocalization rates can be used to 

infer rates of change in population sizes, and these rates can help determine maximum net growth 

rates. Passive acoustic methods can be combined with distance-sampling methods to estimate absolute 

or minimum population size.

Passive acoustic research can be used in a wide variety of contexts that are indirectly related to 

assessing human impacts on marine mammals, including studies of ocean noise and behavioral response 

studies. It is not the intent of this workshop to include the potential application of all such acoustic 

 12 61 Federal Register 4722, Policy Regarding the Recognition of Distinct Vertebrate Population Segments Under the 

Endangered Species Act.
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research. Rather, the workshop narrowly focus on providing information currently needed for MMPA 

stock assessment reports and ESA status reviews. 

References

Federal Register. 1996. Policy regarding the recognition of distinct vertebrate population segments 

under the Endangered Species Act.

http://www.nmfs.noaa.gov/pr/pdfs/fr/fr61-4722.pdf

NMFS. 2005. Revisions to Guidelines for Assessing Marine Mammal Stocks. 24 p. 

http://www.nmfs.noaa.gov/pr/pdfs/sars/gamms2005.pdf
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Appendix H Marine Mammal Protection Act—Stock Assessment 

Requirements

St ock Assessments

16U.S.C. 1386

Se c . 117 . (a) I N G EN ERAL. — Not later than August 1, 1994, the Secretary shall, in consultation with

the appropriate regional scientific review group established under subsection (d), prepare a draft stock

assessment for each marine mammal stock which occurs in waters under the jurisdiction of the United

States. Each draft stock assessment, based on the best scientific information available, shall—

I. describe the geographic range of the affected stock, including any seasonal or temporal

variation in such range;

II. provide for such stock the minimum population estimate, current and maximum net

productivity rates, and current population trend, including a description of the information upon which

these are based;

III. estimate the annual human-caused mortality and serious injury of the stock by source

and, for a strategic stock, other factors that may be causing a decline or impeding recovery of the

stock, including effects on marine mammal habitat and prey;

IV. describe commercial fisheries that interact with the stock, including—

A. the approximate number of vessels actively participating in each such fishery;

B. the estimated level of incidental mortality and serious injury of the stock by each such

fishery on an annual basis;

C. seasonal or area differences in such incidental mortality or serious injury; and

D. the rate, based on the appropriate standard unit of fishing effort, of such incidental

mortality and serious injury, and an analysis stating whether such level is insignificant and is

approaching a zero mortality and serious injury rate;

V. categorize the status of the stock as one that either—

A. has a level of human-caused mortality and serious injury that is not likely to cause the

stock to be reduced below its optimum sustainable population; or

B. is a strategic stock, with a description of the reasons therefor; and

VI. estimate the potential biological removal level for the stock, describing the information used

to calculate it, including the recovery factor.
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Acronyms and Abbreviations

ADFG – Alaska Department of Fish and Game

AFSC – Alaska Fisheries Science Center (NMFS)

AMAPPS – Atlantic Marine Assessment Program for Protected Species

(NOAA, BOEM, U.S. Fish and Wildlife Service, U.S. Navy)

APL – Applied Physics Laboratory (University of Washington)

ASTWG – Advanced Sampling Technology Working Group (OS&T)

AUV – Autonomous underwater vehicle

BACI – Before-After-Control-Impact (experimental design)

BMAR – Bottom-mounted autonomous recorder

BOEM – Bureau of Ocean Energy Management (Department of the Interior)

CalCurCEAS – California Current Cetacean Ecosystem Assessment Survey (SWFSC)

CREEM – Centre for Research into Ecological and Environmental Modelling

(University of St. Andrews)

CRP – Cetacean Research Program (PIFSC)

CIMRS – Cooperative Institute for Marine Resources Studies (OAR/OSU)

CV – Coefficient of variation

DCL – Detection, classification, and localization

DECAF – Density Estimation for Cetaceans from Passive Acoustic Fixed Sensors Project (JIP)

DIFAR – Directional Frequency Analysis and Recording sonobuoy (US Navy)

DPS – Distinct population segment

EMAP – EEZ Mammals and Acoustics Program (SWFSC)

EEZ – Exclusive Economic Zone

ESA – Endangered Species Act

ESTCP – Environmental Security Technology Certification Program (Department of Defense)

FR – Federal Register
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FTE – Full-time equivalent

GAMMS – Guidelines for Assessing Marine Mammal Stocks

GPS – Global Positioning System

ID – Identification

IOOS – Integrated Ocean Observing System (NOAA)

IT – Information Technology

JIP – Exploration and Production Sound & Marine Life Joint Industry Programme

LMR – Living Marine Resources program (Department of the Navy)

LTSA – Long-term spectral averaging

MMPA – Marine Mammal Protection Act

MMSE – Marine Mammal and Seabird Ecology Team (NWFSC)

NCEI – National Centers for Environmental Information (NOAA)

NEFSC – Northeast Fisheries Science Center (NMFS)

NEPAN – Northeast Passive Acoustic Network (NEFSC)

NMFS – National Marine Fisheries Service13 (NOAA)

NMML – National Marine Mammal Laboratory (AFSC)

NOAA – National Oceanic and Atmospheric Administration (Department of Commerce)

NOPP – National Oceanographic Partnership Program (independent federal program)

NRS – Ocean Noise Reference Station network (NOAA)

NWFSC – Northwest Fisheries Science Center (NMFS)

OAR – Office of Oceanic and Atmospheric Research14 (NOAA)

ONR – Office of Naval Research (Department of the Navy)

OPR – Office of Protected Resources (NMFS)

OS&T – Office of Science & Technology (NMFS)

 13 Also known as NOAA Fisheries 14 Also known as NOAA Research
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OSU – Oregon State University

PAM – Passive acoustic monitoring

PARR – Public Access to Research Results (federal policy)

PBR – Potential biological removal

PICEAS – Pacific Islands Cetacean Ecosystem Assessment Survey (SFSC)

PIFSC – Pacific Islands Fisheries Science Center (NMFS)

PMEL – Pacific Marine Environmental Laboratory (OAR)

PODS – Pacific Orcinus Distribution Survey (NWFSC)

PSD – Power spectral density

SBIR – Small Business Innovation Research (NOAA)

SBNMS – Stellwagen Bank National Marine Sanctuary (NOAA)

SDGI – Stock Delineation Guidelines Initiative (SWFSC)

SDSU – San Diego State University

SEFSC – Southeast Fisheries Science Center (NMFS)

SIO – Scripps Institution of Oceanography (UCSD)

SMAR – Surface-mounted autonomous recorder

SRKW – Southern Resident killer whale

SWFSC – Southwest Fisheries Science Center (NMFS)

TB – Terabyte

TDOA – Time difference of arrival

USV – Unmanned surface vehicle

VHF – Very high frequency

WHOI – Woods Hole Oceanographic Institution
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Devices

Acousonde – miniature, self-contained autonomous acoustic/ultrasonic

AMAR – Autonomous Multichannel Acoustic Recorder (underwater acoustic and oceanographic data 

recorder)

APEX Float – Autonomous Profiling Explorer (autonomous drifting profiler used to measure subsurface 

currents and make profile measurements)

AURAL – Autonomous Underwater Recorder for Acoustic Listening (underwater equipment for 

continuous recording)

C-POD – Cetacean and Porpoise Detector (PAM instrument that identifies toothed whale, dolphin, and 

porpoise clicks)

DASBR – Drifting Acoustic Spar Buoy Recorder (drifting autonomous passive acoustic monitoring buoy 

system)

Decimus – passive acoustic monitoring system

DMON – Digital acoustic MONitoring instrument (low-power digital acoustic monitoring instrument)

DTAG – archival behavior monitoring tag

DSG-ST – long-term acoustic data logger

EAR – Ecological Acoustic Recorder (long-term, low-power digital acoustic recording system)

EOM Offshore, Ltd Mooring System – auto-detection mooring system that reduces high-flow, noise-tosignal ratios in passive acoustic applications

HARP – High-frequency Acoustic Recording Package (long-term, high-bandwidth acoustic data recorder)

HARU Phone – Hydrophone for Acoustic Research Underwater (long-term autonomous hydrophone 

system)

MARU – Marine Autonomous Recording Unit (small, portable, bottom-mounted pop-up buoy)

MobySound – website that hosts a database for research in automatic recognition of marine animal 

vocalizations

PAMBUOY – now Decimus

PAMGUARD – open-course, integrated PAM software infrastructure
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RainbowClick – analytic program designed for the detection and analysis of sperm whale and other 

odontocete vocalizations

Remus – Remote Environmental Monitoring UnitS (low-cost AUV)

Roboat – small, automated sailboat that can carry a variety of PAM equipment

Song Meter – long-term PAM system

Spray Glider – small, long-range autonomous glider

Seaglider – AUV glider developed for continuous, long-term measurement of oceanographic parameters

Slocum Glider – versatile, long-endurance AUV glider driven by buoyancy change

Sonobouy – expendable, free-floating PAM buoys obtained from the U.S. Navy that transmit acoustic 

data over a VHF carrier frequency to a monitoring station on the ship or shore

SoundChecker – Matlab-based, multi-species passive acoustic analysis program

Tethys – knowledge management system that actively gathers, organizes, and provides access to 

information on the environmental effects of marine energy, offshore wind energy, and land-based wind 

energy development

Wave Glider – wave- and solar-powered AUV linked to a surface float that is capable of directed 

movements

Wildlife Acoustics SM2BAT+ w/ GPS – see Song Meter

XRay/ZRay – high-performance, long-distance, high-speed, wing-shaped AUV gliders