A Strategic Plan for Conducting Large Geographic Scale, 

Ship-Based Surveys to Support the U.S. Marine Mammal 

Protection and Endangered Species Acts

Lisa T. Ballance, Mridula Srinivasan, Annette Henry, Robyn Angliss, Lynne Barre, Jay Barlow, 

John Bengtson, Shannon Bettridge, Jim Bohnsack, Steve Brown, Phil Clapham, Christina Fahy, 

Mike Ford, Lance Garrison, Tim Gerrodette, Nicole LeBoeuf, Jeff Moore, Erin Oleson, Debra 

Palka, Frank Parrish, Jessica Redfern, Mike Simpkins, Barbara Taylor, and Paul Wade

U.S. Department of Commerce

National Oceanic and Atmospheric Administration

National Marine Fisheries Service

NOAA Technical Memorandum NMFS-F/SPO-169

March 2017

A Strategic Plan for Conducting Large Geographic Scale, Ship-Based Surveys 

to Support the U.S. Marine Mammal Protection and Endangered Species Acts

Lisa T. Ballance1, Mridula Srinivasan2, Annette Henry1, Robyn Angliss3, Lynne Barre4, Jay 

Barlow1, John Bengtson3, Shannon Bettridge6, Jim Bohnsack8, Steve Brown2, Phil Clapham3, 

Christina Fahy4, Mike Ford9, Lance Garrison8, Tim Gerrodette1, Nicole LeBoeuf6, Jeff Moore1, 

Erin Oleson10, Debra Palka7, Frank Parrish10, Jessica Redfern1, Mike Simpkins7, Barbara 

Taylor1

, and Paul Wade3

1

Southwest Fisheries Science Center, 2Office of Science and Technology, 3Alaska Fisheries Science 

Center, 4 West Coast Regional Office, 5

Southeast Regional Office, 6Office of Protected Resources, 

7

Northeast Fisheries Science Center, 8Southeast Fisheries Science Center, 9Northwest Fisheries Science 

Center, 10Pacific Islands Fisheries Science Center

NOAA Technical Memorandum NMFS- F/SPO-169 

March 2017

U.S. Department of Commerce 

Wilbur L. Ross, Jr., Secretary 

National Oceanic and Atmospheric Administration

Benjamin Friedman, Acting NOAA Administrator

National Marine Fisheries Service

Samuel D. Rauch III, Acting Assistant Administrator for Fisheries
ii

Recommended citation:

Ballance, L., M. Srinivasan, A. Henry, R. Angliss, L. Barre, J. Barlow, J. Bengtson, S. Bettridge, 

J. Bohnsack, S. K. Brown, P. Clapham, C. Fahy, M. Ford, L. Garrison, T. Gerrodette, M.

LeBoeuf, J. Moore, E. Oleson, D. Palka, F. Parrish, J. Redfern, J. Simpkins, B. Taylor, and P.

Wade. 2017. A strategic plan for conducting large geographic scale, ship-based surveys to

support the U.S. Marine Mammal Protection and Endangered Species Acts. NOAA Tech. Memo.

NMFS-F/SPO-169, 20 p.

Copies of this report may be obtained from: 

Dr. Mridula Srinivasan 

NMFS Office of Science and Technology

National Oceanic and Atmospheric Administration 

1315 East-West Highway, SSMC 3

Silver Spring, MD 20910 

Or online at:

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

Table of Contents

BACKGROUND ............................................................................................................................ 1

MOTIVATION AND OBJECTIVES ............................................................................................. 3

SCOPE ............................................................................................................................................ 5

The Survey Model and Survey Regions ....................................................................................... 5

ASSESSING SEA DAY REQUIREMENTS ................................................................................. 6

ASSESSING SURVEY FREQUENCY ....................................................................................... 10

AN EXAMPLE PLAN ................................................................................................................. 10

OPTIONS FOR DECREASING SEA-DAY REQUIREMENTS ................................................ 12

ADDITIONAL CONSIDERATIONS .......................................................................................... 15

THE FUTURE .............................................................................................................................. 15

ACKNOWLEDGEMENTS .......................................................................................................... 17

LITERATURE CITED ................................................................................................................. 17

1

BACKGROUND

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

Service (NMFS) is responsible for the science-based management of 209 species of marine 

mammals under the U.S. Marine Mammal Protection Act (MMPA), and 152 endangered and 

threatened species, some of which are marine mammals—95 domestic and 57 foreign—under 

the Endangered Species Act (ESA).1

The MMPA has a goal of maintaining marine mammals as functioning elements of their 

ecosystems, and provides explicit direction regarding information needs to achieve this goal. 

This information includes estimating abundance and abundance trends, clarifying stock structure, 

and placing marine mammals into an ecosystem context. Two sections of the MMPA are 

particularly relevant to this document: 1) Section 117 requires that NMFS and the U.S. Fish and 

Wildlife Service (USFWS) prepare stock assessment reports (SARs) for all marine mammals in 

U.S. exclusive economic zone (EEZ) waters. Importantly, each SAR should include a stockspecific potential biological removal (PBR) level2

, which requires a minimum population 

estimate (Nmin) for that particular stock; and 2) Section 304 of the MMPA requires research 

“...for those marine mammal species and stocks taken in the purse seine fishery for yellowfin 

tuna in the eastern tropical Pacific Ocean...” (ETP). This research in the ETP supports the U.S. 

delegation to the Agreement on the International Dolphin Conservation Program (AIDCP), a 

binding international agreement to which the United States is a signatory. The primary goal of 

the agreement is to reduce dolphin mortality in the fishery and ensure the long-term 

sustainability of these stocks. Research associated with Section 304 forms the basis for 

management measures taken by the signers of the agreement, including setting annual dolphin 

mortality limits and establishing independent observer program requirements. The AIDCP 

observer program monitors dolphin mortalities and provides certification about whether tuna 

meet “dolphin-safe” labeling standards.

The primary goal of the ESA is to prevent extinction and recover species. This statute also 

provides explicit direction regarding information needs for those species classified as endangered 

or threatened. This information includes estimation of abundance and abundance trends; 

identification of “distinct population segments” (DPSs; i.e., population structure); and 

identification and mitigation of threats. These data needs pertain to listed marine mammals, sea 

turtles, fish, corals, and other taxa. 

 1 NMFS also promotes the conservation of migratory bird populations as part of a 2012 memorandum of 

understanding (MOU) with the U.S. Fish and Wildlife Service (USFWS), based on Executive Order 13186 

implemented in 2001. Per the MOU, “NMFS has a responsibility to monitor, understand, and minimize the negative 

impacts of agency actions.....on seabird populations, including seabird bycatch.”

2 Potential Biological Removal (PBR) is defined by the MMPA as the maximum number of animals, not including 

natural mortalities that may be removed from a marine mammal stock while allowing that stock to reach or 

maintain its optimum sustainable population. PBR is the product of the following factors: (A) the minimum 

population estimate of the stock (Nmin); (B) one-half the maximum theoretical or estimated net productivity rate 

of the stock at a small population size; and (C) a recovery factor between 0.1 and 1.0. 
2

These two statutes explicitly state that all U.S. citizens are required to ensure that their activities 

do not impede a species’ recovery. In particular, research on species protected under the MMPA 

and ESA is critical to understand the impact of human activities on these species, and 

consequently, to make management decisions.

Other agency priorities merge with science needs associated with these two protected species 

statutes. For example, the NMFS Climate Science Strategy3 (Link et al., 2015) explicitly 

includes protected species and identifies seven objectives to efficiently and effectively meet 

information requirements of NMFS mandates. 

Two of these pertain directly to this document: 1) Objective 6—track trends in ecosystems, 

living marine resources (LMR), and LMR-dependent human communities and provide early 

warning of change; and 2) Objective 7—build and maintain the science infrastructure needed to 

fulfill NMFS mandates under changing climate conditions. 

43

55 57 58 58 59 59 61 64 65 66 67

72

80

91 91

125 129

150

12

2 1 0 1 0 2 3 1 2 1 5 8 11

0

34

4

21

0

20

40

60

80

100

120

140

160

Number of Species

Total Listed Species New Listings

Figure 1. Total number of ESA-listed species and newly listed species from 1998 to 2016.

These objectives will be implemented through Regional Action Plans, which are tailored to each 

geographic region under NMFS jurisdiction; protected species are woven into each plan through 

existing and future efforts. Other examples of requiring timely assessments include the 2015 

Review of NMFS Protected Species Science Programs4, which reemphasized the need for 

current, precise, and accurate information about species abundance and trends; research plans 

 3 NMFS Climate Science Strategy website, available at http://www.st.nmfs.noaa.gov/ecosystems/climate/nationalclimate-strategy 4 Review of NMFS Protected Species Science Programs http://www.st.nmfs.noaa.gov/science-programreview/index
3

and technical publications (e.g., recovery plans, ESA-status reviews, marine mammal stock 

assessment reports) and documents from independent entities such as the Marine Mammal 

Scientific Review Groups and Marine Mammal Commission that repeatedly emphasize the value 

of foundational science in tackling acute (e.g., fisheries bycatch) or chronic (e.g., climate 

change) threats; and NMFS’ overall work that is guided by two core priorities, one of which is to 

recover and conserve protected resources.

In sum, there is broad legal and agency policy calling for strong science on protected species and 

their ecosystems. NMFS’ ability to meet these obligations has always been somewhat 

constrained, and these constraints have grown during the past decade. For example, NOAA 

regularly receives petitions to list additional species under the ESA, and the number of listed 

species is increasing over time (Figure 1).

Costs associated with conducting science to support management/regulatory analyses also 

continue to increase. Yet, for the past decade, NMFS budgets for protected species have been 

level or reduced (Figure 2), with a widening budgetary gap in appropriations for protected 

species versus sustainable fisheries since 2009. As a result, NMFS’ ability to assess stocks 

protected under the MMPA and ESA has decreased. For example, the proportion of protected 

species stocks under NMFS’ jurisdiction that meet adequate stock assessment standards (Merrick 

et al., 2004) has decreased from 20% (of 400 stocks) in 2013 to about 19% (of 428 stocks) in 

2016. In 2014, only 221 of the 332 marine mammal stocks within NMFS’ jurisdiction had a 

current SAR, and 63 stocks did not have sufficient information to allow for calculation of PBR 

thresholds. The implications of this lack of data range from overly-proscriptive regulatory 

measures to inadequate protection. 

MOTIVATION AND OBJECTIVES

The motivation for this strategic plan is to provide a national, unified approach for meeting 

science needs in partial support of the MMPA and the ESA. The specific objective is to provide a 

framework for discussion of ship time with respect to, chiefly, cetacean science needs. The plan 

presented here is meant to aid in strategic planning for these science requirements in the context 

of other NMFS priorities and NOAA’s Healthy Ocean Goal5

. In particular, it is hoped that a 

proactive and comprehensive strategic plan based on a predictable schedule and geographic area 

rotation will facilitate the continuation, and in some cases, the initial implementation of, research 

that will provide the majority of data required to meet NMFS’ cetacean-related mandates.

 5 NOAA’s Healthy Ocean Goal website, available at http://www.ppi.noaa.gov/goals/
4

Cetaceans constitute almost 75% of the 428 protected species stocks managed by NMFS. Shipbased surveys are a proven and effective approach to collecting data required for stock 

assessments of oceanic animals, including and especially cetaceans. These assessments allow for 

estimation of abundance, clarification of stock structure, assessment of health and condition, and 

placement into an ecosystem context, thereby comprehensively addressing MMPA and ESA 

mandates.

Ship-based surveys can also be very efficient when data are collected for multiple stocks on a 

single survey. Indeed, the vast majority of cetacean stocks under NMFS’ jurisdiction can be 

assessed simultaneously at a regional level. For example, 60 cetacean stocks are recognized in 

the most recent U.S. Pacific Marine Mammal Stock Assessment Report (Carretta et al., 2016). 

Of these, 46 stocks (77%) can be comprehensively assessed through multispecies cetacean and 

ecosystem assessment surveys conducted regionally (see section below). Three stocks can 

benefit from additional small boat-based efforts to augment ship surveys: Main Hawaiian Island 

stock of false killer whale, Pseudorca crassidens; California/Oregon/Washington stock of 

humpback whale, Megaptera novaeangliae; and eastern north Pacific stock of blue whale, 

Balaenoptera musculus. Only 11 stocks (18%) require field efforts using other means: six harbor 

porpoise (Phocoena phocoena) stocks using aerial surveys; three stocks (California coastal and 

Hawaiian Islands stocks of common bottlenose dolphin, Tursiops truncatus, and western north 

Pacific stock of gray whale Eschrichtius robustus) using small boat-based research; one (eastern 

north Pacific stock of gray whale) using shore-based research; and one (southern resident killer 

whale, Orcinus orca) with a dedicated ship survey. Ship-based surveys can also accommodate 

research on other protected species, such as pinnipeds and marine turtles, and nearly all seabirds 

(Ballance, 2007). Thus, this strategic plan provides value-added for assessment of these taxa. 
5

SCOPE

The Survey Model and Survey Regions

This strategic plan is based on surveys that are designed to collect data for assessment of 

cetaceans, where assessment includes: 1) estimation of abundance (and through time, trends in 

abundance); 2) clarification of population structure (stocks under the MMPA and DPSs under the 

ESA); 3) collection of data to determine health and condition (because deteriorating health and 

condition can be early warnings of decreases in abundance); and 4) characterization of the 

ecosystem of which cetaceans are a part. Importantly, this model is based on the collection of 

data for all relevant cetacean species/stocks within the region being surveyed, rather than 

focusing a survey on a single targeted species/stock. This regionally based, multispecies survey 

model is referred to as the Multispecies Cetacean and Ecosystem Assessment Survey (MCEAS). 

The MCEAS model has been used by NMFS since its introduction in 1986 by the Southwest 

Fisheries Science Center (SWFSC) in the Eastern Tropical Pacific (ETP). The model is widely 

embraced nationally.

Abundance estimation is based on data collected using mainly visual line-transect methods 

(Buckland et al., 2001; Barlow and Forney, 2007). For some species, passive acoustics may 

contribute to abundance estimation (Barlow and Taylor, 2005; Marques et al., 2013, reviewed in 

Heinemann et al., 2016). Typically, visual line-transect methods are conducted in “closing 

mode”: After each cetacean sighting, effort is suspended and the ship approaches the sighting so 

that species determination can be made and group size can be estimated (Schwarz et al., 2010). 

Population structure is determined primarily using skin and blubber biopsy samples collected 

from cetaceans during surveys and from molecular genetics methods using these samples in the 

lab (e.g., Archer et al., 2010; Mesnick et al., 2011; Morin et al., 2012; Martien et al., 2012; 

Archer et al., 2013; Lang et al., 2014; and Martien et al., 2014). Here too, increasingly, data to 

clarify population structure comes from passive acoustic recordings of cetacean vocalizations, 

which can be specific to a population or stock (reviewed in Heinemann et al., 2016). 

Health and condition can be determined from skin and blubber biopsy samples, which can be 

analyzed in the laboratory for a variety of indicators: contaminants, hormone levels (indicating 

sex), maturity, reproductive condition, and stress (e.g., Krahn et al., 2008; Kellar et al., 2013). 

Health and condition can also be determined from lateral and aerial photographs, which are 

particularly valuable when photogrammetry (precise measurements of morphology) can be used. 

In addition, to the greatest extent possible, ecosystem characterization should include the 

following information: physical habitat (e.g., sea surface temperature, salinity, chlorophyll, and 

thermal and chemical properties of the water column); distribution, abundance, and identity of 

mid-trophic (i.e., forage) fishes and invertebrates through active acoustics and net sampling; and 

distribution, abundance, and identity of other apex predators (i.e., competitors, commensals, and 

indicators), including seabirds, because they are easy to identify, count, and survey in a 

scientifically rigorous manner.

Characterization of the ecosystem provides data needed to understand the roles of cetaceans in 

marine ecosystems (per the MMPA), but these ecosystem data are also critical to cetacean 

assessment for two explicit reasons. First, cetacean “habitat” in oceanic systems is described by 
6

physical and chemical attributes of water masses and oceanographic features. These can be 

powerful predictors of cetacean density (e.g., Forney et al., 2012). Because these features move 

in space and time, they influence, strongly in some cases, cetacean density patterns and therefore 

must be incorporated into any analysis that aims to accurately document abundance and 

distribution. In addition, as awareness of climate change increases, so does the importance of 

incorporating ecosystem data into cetacean assessments to more fully understand the impacts of 

climate variability on cetacean distribution and abundance. Second, mitigation measures to 

address a detected problem (e.g., a decline in abundance, an indication of poor health or 

condition) depend on a solid understanding of the factors associated with that problem. 

Ecosystem characterization allows for a more thorough investigation of causation and 

identification of possible drivers (e.g., Reilly et al., 2005). The power of ecosystem 

characterization combined with the collection of cetacean assessment data provides an accurate 

match in space and time between the two data sets, and something that remotely sensed data can 

rarely provide. 

ASSESSING SEA DAY REQUIREMENTS

The survey regions relevant to this strategic plan (Figure 3) include all of the large marine 

ecosystems (LMEs) that NOAA recognizes and for which NMFS has jurisdiction under the 

MMPA (Sections 117 and 304).

MCEAS are designed to assess all cetaceans and characterize the ecosystem at the LME scale. 

For this reason, tracklines were designed to systematically cover an entire region. For this plan, 

we have divided the LMEs into 16 distinct survey regions (Figures 4, 5, and 6).

Tracklines for each region were designed using a spatial grid of 60 x 60 nautical miles, following 

the grid used in the California Current and widely recognized as effective in assessing cetaceans 

and the ecosystem there (e.g., Barlow and Forney, 2007; Moore and Barlow, 2013). The 

exception to this spatial resolution is the ETP, simply because its size excludes the possibility of 

such fine spatial coverage. For the ETP only, tracklines have been designed following previous 

surveys, which have been extensively reviewed and accepted as scientifically rigorous (e.g., 

Gerrodette and Forcada, 2005; Reilly et al., 2005; and Wade et al., 2007).
7

Figure 4. Proposed survey regions and tracklines (spatial grid 60 x 60 nautical miles) in U.S. EEZ waters 

bordering the Atlantic and Pacific continental United States

Figure 3. LMEs for which NMFS has jurisdiction under the MMPA.

 Gulf of Mexico

Chukchi & Beaufort 

seas

 U.S. West Coast Gulf of Alaska

 U.S. East Coast Caribbean

 Bering Sea
8

The total sea-day requirement for MCEAS in each of the 16 survey regions (Table 1) was 

estimated as follows. It was assumed that, on average, 100 linear nautical miles of trackline 

would be surveyed each day. This number corresponds to the trackline survey rate during 

multiple years of surveys following the MCEAS model conducted by the SWFSC and Pacific 

Islands Fisheries Science Center (PIFSC) in the California Current; the Hawaiian Archipelago; 

Johnston, Palmyra, and Kingman; and the ETP (Figures 4, 5, and 6). This approach allowed for 

an additional 20% of each region-specific, sea-day survey requirement for unanticipated events 

(e.g., mechanical breakdowns, weather). This approach was also based on extensive experience 

by the SWFSC and PIFSC in the California Current; the Hawaiian Archipelago; Johnston, 

Palmyra, and Kingman; and the ETP. Finally, for survey regions in Pacific Oceana (Figure 5), 

the region-specific, round-trip sea-day requirement for transit to and from Honolulu, where ships 

are likely to be based, was calculated.

Commonwealth of the 

Northern Mariana 

Islands Wake

Howland & Baker

Johnston

Palmyra & 

Kingman

Hawaiian Archipelago

Jarvis

Figure 5. Proposed survey regions and tracklines (spatial grid 60 x 60 nautical miles) in 

Pacific Oceana.

American 

Samoa
9

Table 1. Total sea-day requirement for MCEAS in 16 regions for which NMFS has jurisdiction under 

the MMPA. See Figures 4, 5, and 6 for geographic locations of survey regions and proposed 

tracklines. “Total Distance” reflects the total length of trackline. “Survey Requirement” equals total 

number of sea days required to survey all tracklines, assuming 100 nautical miles/day. 

“Unanticipated Events” is 20% of “Survey Requirement.” Roundtrip transit is calculated for Pacific 

Oceana only and equal to the number of sea days required to transit from Honolulu (where 

research vessels are likely to be based) to each survey region.

Survey Region Total 

Distance 

(n.mi.)

Survey 

Requirement 

(days)

Unanticipated 

Events (days)

Roundtrip 

Transit 

(days)

Total 

Requirement 

(days)

U.S. East Coast 8,043 81 16.2 NA 97.2

Caribbean 2,240 23 4.6 NA 27.6

Gulf of Mexico 6,255 63 12.6 NA 75.6

Chukchi & Beaufort seas 8,843 89 18 NA 107

Bering Sea 14,491 145 29 NA 174.0

Gulf of Alaska 15,893 159 31.8 NA 190.8

U.S. West Coast 8,866 89 17.8 NA 106.8

Hawaiian Archipelago 23,204 232 46.4 NA 278.4

Commonwealth of the 

Northern Mariana Islands

9,357 94 18.8 24.9 137.7

Wake 3,528 36 7.2 15 58.2

Howland & Baker 4,166 41 8.2 12 61.2

American Samoa 3,994 40 8 21.4 69.4

Johnston 4,282 43 8.6 4.3 55.9

Jarvis 2,871 29 5.8 9.2 44.0

Palmyra & Kingman 3,456 35 7 6.2 48.2

Eastern Tropical Pacific 37,000 240 48 NA 288.0

Total 156,489 1,439 288 93 1820

Figure 6. ETP survey region and tracklines for the 2006 survey (red—NOAA Research Vessel 

David Starr Jordan; black—NOAA Research Vessel McArthur II).
10

ASSESSING SURVEY FREQUENCY

The ideal survey frequency can be precisely modeled based on the species/stock of interest and 

the management objective. Because MCEAS address multiple facets of two statutes for multiple 

stocks/DPSs/species, survey frequency must reflect a combination of factors. 

Currently, the NMFS Guidelines for Assessing Marine Mammal Stocks (NMFS, 2016) state that 

unless compelling evidence indicates that a stock has not declined since the last census, the Nmin 

estimate used to calculate PBR should be considered unknown if 8 years have passed since the 

last abundance survey. If Nmin is unknown, then PBR cannot be determined. Therefore, surveys 

must be conducted at least every 8 years to calculate PBR and meet the requirements of the 

MMPA. 

Research on the ability to detect trends in abundance indicates that surveys should be conducted 

much more frequently. Taylor et al., 2007, modeled the ability to detect a precipitous decline 

(50% or greater decline over 15 years) for a variety of marine mammal species. Depending on 

the taxon and associated challenges of collecting data on abundance, survey frequency ranged 

from 1 to 4 years for an 80% probability of detecting the decline. These numbers apply, 

respectively, to Cuvier’s beaked whales (Ziphius cavirostris), a cryptic species for which 

abundance estimation is challenging; and bowhead whales (Balaena mysticetus), for which 

abundance estimation is relatively easy. 

Additional considerations pertain to the degree of threats, environmental variation, and capacity 

to conduct surveys. For example, survey frequency should be positively correlated with the 

number and intensity of threats in a given region to better detect negative impacts of threats as 

early as possible. Regions in close proximity to human centers of population would, therefore, 

seem to be candidates for more frequent surveys than regions in remote, oceanic locations. Interannual variation in environmental conditions (physical and biological) will influence cetacean 

distribution and density. Ideally, surveys should be able to distinguish effects of inter-annual 

variation from absolute changes in density (distribution and/or abundance). Finally, regionspecific capacity to conduct MCEAS should be taken into account.

AN EXAMPLE PLAN

This plan proposes a 6-year cycle of surveys whereby regions in U.S. EEZ waters bordering the 

Atlantic and Pacific continental United States (Figure 4) be surveyed during 2 consecutive years 

every 5 years, and regions in Pacific Oceana and the ETP (Figures 5 and 6) be surveyed once 

every 6 years. These are minimum recommendations for survey frequency and are a compromise 

based on survey frequency factors listed earlier, and availability of ship time and funds to 

implement surveys (both of which are highly limited).

Within the 6-year cycle, multiple surveys would be conducted each year. It is suggested that 

surveys be combined in any given year based on two factors: 1) Geography—Each year should 

include at least one survey in each of the Atlantic and Pacific U.S. EEZ waters bordering the 

continental United States (Figure 4) and Pacific Oceana (Figure 5); and 2) Science Center 

capacity—Each year should divide the responsibility for surveys among the Science Centers to 
11

Table 2. Example 6-year cycle of MCEAS, including all regions for which NMFS has jurisdiction under 

the MMPA. See Figures 4, 5, and 6 for geographic locations of survey regions and proposed 

tracklines, and Table 1 for details pertaining to total sea-day requirements.

ensure sustainability of the workload. An additional benefit to this approach pertains to logistical 

constraints on the vessels capable of performing such surveys.

A proposed cycle is presented in Table 2. In this example, the annual total sea-day requirement 

ranges from 306 (year 6) to 623 (year 2) sea days. For any given year, this total can be adjusted 

by changing the combination of regions to be surveyed.

Year Regions to be Surveyed Total Sea Day 

Requirements

1 U.S. East Coast, U.S. West Coast, Bering Sea, Chukchi & Beaufort 

seas, Palmyra & Kingman, Jarvis

577

2 U.S. East Coast, U.S. West Coast, Bering Sea, Chukchi & Beaufort 

seas, Commonwealth of the Northern Mariana Islands

623

3 Gulf of Mexico, Gulf of Alaska, Howland & Baker 328

4 Gulf of Mexico, Gulf of Alaska, Johnston 322

5 Caribbean, ETP, American Samoa, Wake 443

6 Caribbean, Hawaiian Archipelago 306

Table 3 compares the total sea-day requirement for MCEAS in each of the 6 years of the 

proposed cycle with the total annual NMFS sea-day allocation intended to fill all of NMFS’ 

mandates (aboard NOAA research vessels) in fiscal years 2013, 2014, and 2015 (allocation totals 

provided by M.S. Gallagher, personal communications). For the most recent year (2015), the 

MCEAS annual requirement ranges from 21% to 42% of this annual NMFS allocation.
12

Table 3. Comparison of annual sea-day requirements for MCEAS following the proposed 6-year 

cycle presented in Table 2 and the annual sea-day allocation to NMFS in each fiscal year from 2013 

to 2015. Annual allocation totals represent only sea days aboard NOAA research vessels; NMFS 

sea days on charter or other vessels are excluded.

Percent of Total Annual Allocation of NMFS Sea Days

Year Total 

MCEAS 

Requirement 

(days)

Fiscal Year 2013 

(%)

Fiscal Year 2014 

(%)

Fiscal Year 2015 (%)

(n = 949 sea days) (n = 1,273 sea days) (n = 1,481 sea days)

1 577 60.8 45.3 39.0 

2 623 65.6 48.9 42.1 

3 328 34.6 25.8 22.1 

4 322 33.9 25.3 21.7 

5 443 46.7 34.8 29.9 

6 306 32.2 24.0 20.7 

OPTIONS FOR DECREASING SEA-DAY REQUIREMENTS

NMFS does not have adequate ship time to meet its needs. For this reason, we explore four 

options for decreasing the sea-day requirements for MCEAS. All changes are associated with 

compromises in the ability to assess abundance, estimate PBR, and/or detect trends.

1) This plan calls for regions in U.S. EEZ waters bordering the Atlantic and Pacific continental 

United States (Figure 2) to be surveyed during consecutive years, but sea-day requirements could 

be decreased if each region was surveyed only once every 4 years (following recommendations 

by Taylor et al., 2007). The resulting compromise is that influences of inter-annual 

environmental variability on distribution and density may be more difficult to distinguish from 

distribution and density changes associated with other factors (e.g., fisheries bycatch, impacts of 

ocean noise). The hiatus in survey frequency during the 1990s in the ETP provides an example 

of this (Gerrodette et al., 2008).

2) This plan calls for a 60 x 60 nautical mile grid for all surveys except for the ETP. However, it 

is possible to survey a geographic region at a coarser spatial scale, thereby decreasing the annual 

sea-day requirement for any given region. (Actually, the spatial resolution of tracklines has been 

coarser for some of the LMEs in which past cetacean surveys have been and/or are currently 

being conducted.) A decrease in the number of sea days associated with any particular region 

will statistically result in an increased coefficient of variation (CV) of abundance estimates. 

There are two important implications of this relationship. 
13

First, as the CV of an abundance estimate increases, Nmin will decrease as will PBR (Wade and 

Angliss, 1997). Therefore, the allowable level of human-induced mortality will decrease as the 

number of sea days dedicated to a survey decreases. The converse is also true. An economic 

analysis using as a case study harbor porpoise (Phocoena phocoena) in the northeast gill net 

fishery of the U.S. found that abundance surveys were more cost-effective than increasing 

observer coverage of the fishery for keeping bycatch below PBR. In addition, total benefits to the 

private sector exceeded the costs of collecting additional scientific data to decrease CVs and 

increase PBR (Bisack and Magnusson, 2014). 

Second, increased CVs of abundance estimates result in a decrease in the statistical power to 

detect trends in abundance, and a consequent increase in the number of surveys required to detect 

trends. The relationship between survey effort (i.e., number of sea days), precision of abundance 

estimates, and power to detect trends in abundance can be calculated for any particular survey. 

An example is provided in Figure 7 for two dolphin species in the ETP. In the example, a 25% 

decrease in sea days results in a 15% increase in the CV of the abundance estimate, an associated 

decrease in power from 0.8 to 0.7, and an increase in the number of surveys required to detect a 

trend from 6 to 7 (Gerrodette, unpublished). At a 3-year survey interval, this would correspond to 

an increase from 18 to 21 years before a significant trend in abundance would be detected.

3) MCEAS can be conducted aboard vessels of opportunity. Ideal characteristics of trips on such 

vessels include even coverage of regional areas using a regular grid (e.g., oceanographic research 

surveys, which frequently sample at predetermined, regularly spaced stations; crab pot fishery 

vessels that may set traps at regularly spaced intervals); and repeated sampling at regular 

intervals over time to establish a time series for detection of trends. Some fish stock assessment 

surveys may also fall into this category. The most significant compromise of such an approach is 

that vessels of opportunity typically provide no dedicated ship time for closing mode cetacean 

surveys (i.e., diverting the ship to identify species and count individuals). 
14

 Figure 7. Estimated annual survey effort and precision of abundance estimates for two stocks of 

dolphins (eastern spinner, Stenella longirostris orientalis; northeastern offshore spotted dolphin, S. 

attenuata attenuata) in the eastern tropical Pacific. The fitted lines assume the CV is inversely 

proportional to the square root of the expected number of sightings. Data from Gerrodette et al., 2008.

Without operating in closing mode, many cetacean sightings will not be identified to 

species/stock level, and estimates of group size will be more imprecise. In an empirical 

comparison between “passing mode” (where the ship does not turn to approach cetacean 

sightings) and closing mode surveys (Schwarz et al., 2010), observers were able to identify 

sightings to the species level less frequently in passing mode (57% versus 81% of sightings). 

Also, uncertainty in group size both within and between observers was higher, and point 

estimates of delphinid group size were 58% lower at perpendicular distances between 1.0 and 5.5 

km from the trackline. Rapidly developing technology (see next section), particularly the use of 

unmanned aerial systems (UAS) to fly line-of-sight distances from a moving vessel, may soon at 

least partially relieve the negative impacts of closing mode on cetacean data integrity. 

Another compromise pertains to space allocated for sea-going scientists. Typically, platforms of 

opportunity include at best a few berths for “opportunistic” research, although rigorous survey 

methods for cetaceans require more, and the full complement of scientists required for MCEAS 

using the model presented here is around 15. Such vessels of opportunity are still valuable; they 

may provide information on the presence or absence of species or stocks, and offer opportunities 

to deploy acoustic and environmental instrumentation. In addition, they may be used to collect 

physical and biological data, including prey field information, which may enhance understanding 

of marine mammals and their ecosystems. Ultimately, these vessels are not replacements for 

dedicated surveys but can complement or enhance such data.

 

 y 

0

5

10

15

20

25

30

35

40

45

20000 30000 40000 50000 60000

Survey effort in one year (km)

CV of abundance estimate (%)

Eastern spinner

NE offshore spotted

2 ships 3 ships 4 ships
15

4) In addition to research vessels, MCEAS can be augmented with sampling platforms, both 

manned and unmanned. Such an approach is already used in various regions. For example, 

manned aerial platforms to survey continental shelf and/or low-density waters (for cetaceans, 

marine turtles, and seabirds) are regularly used in the Gulf of Mexico, the U.S. east coast, and 

U.S. Arctic. Unmanned in-water platforms (geographically fixed, passive drifters, and actively 

moving) have been fitted with passive acoustic recording devices to characterize presence and 

species of cetaceans in many regions. Small UAS have been used aboard NOAA research vessels 

to photograph cetacean schools or pinniped haulouts, and research and development associated 

with these platforms is escalating with great promise. For example, ship-launched UAS with 10-

to 12-hour endurance now exist. With additional research and development, these devices could 

be used for species/stock identification, school size estimation, morphometrics, and school 

composition (all through photographs or video), as well as collection of biological samples 

(breath sampling of whales is already possible; further research may enable collection of skin 

and blubber biopsies). One or more UAS operated from a survey vessel could possibly work in 

concert with human observers to reduce the time a vessel spends in closing mode; fly a series of 

transects to add enough supplementary data to enable coarser spacing of vessel line transects 

without compromising the statistical power of the derived abundance estimates; or reduce the 

number of visual observers required.

ADDITIONAL CONSIDERATIONS

Although the LMEs recognized by NMFS reflect true ecosystems as characterized by 

oceanography and biology, the survey regions used in this plan are instead based on geo-political 

boundaries, as stipulated in the MMPA. The objectives of cetacean and ecosystem assessments 

will be achieved more accurately if these survey areas could be based on physical and biological, 

rather than political, ecosystem boundaries (i.e., if survey areas could extend into non-U.S. 

waters and the high seas to better encompass the relevant ecosystem).

THE FUTURE

There is great benefit to a national approach in collecting protected species data required to 

fulfill NMFS mandates and priorities. The framework presented in this plan provides a readymade approach. However, essential survey components can also be adapted or modified to 

accommodate a variety of fiscal scenarios and resource availability in the future. A multi-year 

timetable, as presented here or modified, will facilitate ship-time scheduling, allow the agency to 

engage in advanced planning and prioritization of resource allocation with other federal partners, 

and provide for timely release of scientific products.

A global assessment of the distribution and intensity of cetacean line-transect surveys clearly 

illustrates that the geographic regions for which NMFS is responsible under the MMPA are 

among those with the highest number of surveys and abundance estimates, particularly in the 

ETP, California Current, U.S. east coast, and Gulf of Mexico (Kaschner et al., 2012). Though 

some regions for which the U.S. is responsible have never been surveyed, the MMPA is 

considered to be the “gold standard” worldwide with respect to effective management of marine 

mammals. In addition, the surveys associated with meeting this mandate have produced rigorous 
16

science to form the basis of many successful management and regulatory decisions. These same 

surveys and the time series they form are critical for understanding the impact of current and 

future anthropogenic impacts. Yet their often infrequent occurrence and unpredictable timetable 

has resulted in nearly 80% of the protected species under U.S. jurisdiction not meeting target 

assessment standards (Merrick et al., 2004). 

In contrast, fish stock assessments operate under different criteria. An assessment is considered 

adequate if the stock has an assessment level of 3 or higher, according to the 2001 Marine 

Fisheries Stock Assessment Improvement Plan; has been updated within 5 years; and is 

recommended as best scientific information available after a rigorous regional peer review 

process. In fiscal year 2015 (FY2015), NMFS assessed 88 of the 199 stocks included in the Fish 

Stock Sustainability Index (FSSI)6, an indicator used to measure the performance of 

commercially and recreationally important fisheries. That year, the percentage of sustainable fish 

stocks with adequate assessments increased to an all-time high of 64.8% (129/199). Also, for 

non-FSSI stocks, 71% of the assessments conducted during FY2015 were completed at a level 3 

or higher. This success was due to the regularity of fisheries research surveys (NMFS and its 

partners conduct an average of 1857 fish assessments each year) and the availability of lengthy 

time series for most stocks to refine modeling approaches for population analysis. Importantly, 

accurate and precise fish stock assessments have allowed the agency to make significant strides 

in reducing overfishing and non-target fish bycatch and advance ecosystem-based fisheries 

management. Regular and predictable MCEAS could do the same for the cetacean stocks under 

NMFS jurisdiction.

There is significant support for MCEAS outside of NMFS, including funding commitments that 

span multiple years and regions. In particular, three other federal government agencies, the U.S. 

Navy, the Bureau of Ocean Energy Management (BOEM), and the USFWS have partnered with 

NMFS to conduct MCEAS in LMEs under U.S. jurisdiction in the Atlantic through the Atlantic 

Marine Assessment Program for Protected Species (AMAPPS). This partnership is based on 

common information needs: distribution and abundance of cetaceans, pinnipeds, marine turtles, 

and seabirds required for NMFS and USFWS to fulfill their mandates; and to the Navy and 

BOEM for environmental compliance, obtaining regulatory authorization for various activities, 

and for meeting associated environmental monitoring and reporting requirements. The 

partnership among these four federal agencies, each providing funding, staff, and infrastructure 

to support a single effort, represents efficient leveraging of resources while simultaneously 

accomplishing individual agency mission objectives. This successful model has resulted in 

similar partnerships in the Gulf of Mexico and Pacific Ocean with great promise for the future.

 6 http://www.st.nmfs.noaa.gov/Assets/stock/documents/report/FY15Q4_FishAssessmentReportSummary&Appendices_final.pdf

7 http://www.st.nmfs.noaa.gov/stock-assessment/reports
17

ACKNOWLEDGEMENTS

This strategic plan has benefitted greatly from support and encouragement of many individuals 

within and outside NMFS. They are too many to name but we wish to particularly acknowledge 

Cisco Werner, Richard Merrick, Kristen Koch, Roger Hewitt, the U.S. Marine Mammal 

Commission, and the Pacific Scientific Review Group. Doug DeMaster and Mike Gallagher 

provided thorough and constructive comments on a previous version.

LITERATURE CITED

Archer, F. I., K. K. Martien, B. L. Taylor, R. G. LeDuc, B. J. Ripley, G. H. Givens, and J. C. 

George. 2010. A simulation-based approach to evaluating population structure in non-equilibrial 

populations. J. Cetacean Res. Manage. 11(2):101–113. 

Archer, F. I., P. A. Morin, B. L. Hancock-Hanser, K. M. Robertson, M. S. Leslie, M. Bérubé, S. 

Panigada, and B. L. Taylor. 2013. Mitogenomic phylogenetics of fin whales (Balaenoptera 

physalus spp.): genetic evidence for revision of subspecies. PLoS ONE 8(5):e63396, 10 p. 

https://doi.org/10.1371/journal.pone.0063396

Ballance, L. T. 2007. Understanding seabirds at sea: why and how? Mar. Ornithol. 35:127–135.

Barlow, J., and K. A. Forney. 2007. Abundance and population density of cetaceans in the 

California Current ecosystem. Fish. Bull. 105:509–526.

Barlow, J., and B. L. Taylor. 2005. Estimates of sperm whale abundance in the northeastern 

temperate Pacific from a combined acoustic and visual survey. Mar. Mamm. Sci. 21:429–445. 

https://doi.org/10.1111/j.1748-7692.2005.tb01242.x

Bisack, K. D., and G. Magnusson. 2014. Measuring the economic value of increased precision in 

scientific estimates of marine mammal abundance and bycatch: harbor porpoise Phocoena 

phocoena in the Northeast U.S. Gill-Net Fishery. North Am. J. Fish. Manage. 34:311–321. 

https://doi.org/10.1080/02755947.2013.869281

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, 448 pp. 

Oxford University Press, Oxford, UK.

Carretta, J. V., E. M. Oleson, J. Baker, D. W. Weller, A. R. Lang, K. A. Forney, M. M. Muto, B. 

Hanson, A. J. Orr, H. Huber, M. S. Lowry, J. Barlow, J. E. Moore, D. Lynch, L. Carswell, and R. 

L. Brownell Jr. 2016. U.S. Pacific Marine Mammal Stock Assessments: 2015. NOAA Tech. 

Memo. NOAA-TM-NMFS-SWFSC-561, 355 p. 

Forney, K. A., M. C. Ferguson, E. A. Becker, P. C. Fiedler, J. V. Redfern, J. Barlow, L. I. 

Vilchis, and L. T. Ballance. 2012. Habitat-based spatial models of cetacean density in the eastern 

Pacific Ocean. Endanger. Species Res. 16:113–133. https://doi.org/10.3354/esr00393
18

Gerrodette, T., and J. Forcada. 2005. Non-recovery of two spotted and spinner dolphin 

populations in the eastern tropical Pacific Ocean. Mar. Ecol. Prog. Ser. 291:1–21. 

https://doi.org/10.3354/meps291001

Gerrodette, T., G. Watters, W. Perryman, and L. Ballance. 2008. Estimates of 2006 dolphin 

abundance in the eastern tropical Pacific, with revised estimates from 1986–2003. NOAA Tech. 

Memo. NOAA-TM-NMFS-SWFSC-422, 37 p. 

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. NOAA Tech. Memo. NMFS-F/SPO-164, 107 p.

Kaschner, K., N. J. Quick, R. Jewell, R. Williams, and C. M. Harris. 2012. Global coverage of 

cetacean line-transect surveys: status quo, data gaps and future challenges. PLoS ONE 7(9): 

e44075. https://doi.org/10.1371/journal.pone.0044075

Kellar, N. M., M. L. Trego, S. J. Chivers, and F. I. Archer. 2013. Pregnancy patterns of 

pantropical spotted dolphins (Stenella attenuata) in the eastern tropical Pacific determined from 

hormonal analysis of blubber biopsies and correlations with the purse-seine tuna fishery. Mar. 

Biol. 160:3113–3324. https://doi.org/10.1007/s00227-013-2299-0

Krahn, M. M., R. L. Pitman, D. G. Burrows, D. P. Herman, and R. W. Pearce. 2008. Use of 

chemical tracers to assess diet and persistent organic pollutants in Antarctic Type C killer 

whales. Mar. Mamm. Sci. 24:643–663. https://doi.org/10.1111/j.1748-7692.2008.00213.x

Lang, A. R., J. Calambokidis, J. Scordino, V. L. Pease, A. Klimek, V. N. Burkanov, P. Gearin, 

D. I. Litovka, K. M. Robertson, B. R. Mate, J. K. Jacobsen, and B. L. Taylor. 2014. Assessment 

of genetic structure among eastern North Pacific gray whales on their feeding grounds. Mar. 

Mamm. Sci. 30:1473–1493. https://doi.org/10.1111/mms.12129

Link, J. S., R. Griffis, and S. Busch (eds.). 2015. NOAA Fisheries Climate Science Strategy. 

NOAA Tech. Memo. NMFS-F/SPO-155, 70 p.

Marques, T. A., L. Thomas, S. W. Martin, D. K. Mellinger, J. A. Wards, D. J. Moretti, D. Harris, 

and 

P. L. Tyack. 2013. Estimating animal population density using passive acoustics. Biol. 

Rev. 88:287–309. https://doi.org/10.1111/brv.12001

Martien, K. K., R. W. Baird, N. M. Hedrick, A. M. Gorgone, J. L. Thieleking, D. J. McSweeney, 

K. M. Robertson, and D. L. Webster. 2012. Population structure of island-associated dolphins: 

evidence from mitochondrial and microsatellite markers for common bottlenose dolphins 

(Tursiops truncatus) around the main Hawaiian Islands. Mar. Mamm. Sci. 28:E208–E232. 

https://doi.org/10.1111/j.1748-7692.2011.00506.x
19

Martien, K. K., S. J. Chivers, R. W. Baird, F. I. Archer, A. M. Gorgone, B. L. Hancock-Hanser, 

D. Mattila, D. J. McSweeney, E. M. Oleson, C. Palmer, V. L. Pease, K. M. Robertson, G. S. 

Schorr, M. 

B. Schultz, D. L. Webster, and B. L. Taylor. 2014. Nuclear and mitochondrial patterns of 

population structure in North Pacific false killer whales (Pseudorca crassidens). J. Hered. 

105(5):611–626. https://doi.org/10.1093/jhered/esu029

Merrick, R., L. Allen, R. Angliss, G. Antonelis, T. Eagle, S. Epperly, L. Jones, S. Reilly, B. 

Schroeder, and S. Swartz. 2004. A requirements plan for improving the understanding of the 

status of U.S. protected marine species: report of the NOAA Fisheries national task force for 

improving marine mammal and turtle stock assessments. NOAA Tech. Memo. NMFS-F/SPO-63, 

64 p.

Mesnick, S. L., B. L. Taylor, F. I. Archer, K. K. Martien, S. E. Treviño, B. L. Hancock-Hanser, 

S. C. M. Medina, V. L. Pease, K. M. Robertson, J. M. Straley, R. W. Baird, J. Calambokidis, G. 

S. Schorr, P. Wade, V. Burkanov, C. R. Lunsford, L. Rendell, and P. A. Morin. 2011. Sperm 

whale population structure in the eastern and central North Pacific inferred by the use of singlenucleotide polymorphisms, microsatellites and mitrochondrial DNA. Mol. Ecol. Res. 11:278–

298. https://doi.org/10.1111/j.1755-0998.2010.02973.x

Moore, J. E., and J. P. Barlow. 2013. Declining abundance of beaked whales (family Ziphiidae) 

in the California Current large marine ecosystem. PLoS ONE 8(1):e52770. 

https://doi.org/10.1371/journal.pone.0052770

Morin, P. A., F. I. Archer, V. L. Pease, B. L. Hancock-Hanser, K. M. Robertson, R. M. 

Huebinger, K. K. Martien, J. W. Bickham, J. C. George, L. D. Postma, and B. L. Taylor. 2012. 

Empirical comparison of single nucleotide polymorphisms and microsatellites for population and 

demographic analyses of bowhead whales. Endanger. Species Res. 19:129–147. 

https://doi.org/10.3354/esr00459

National Marine Fisheries Service. 2016. Guidelines for preparing stock assessment reports 

pursuant to the 1994 amendments to the MMPA. NMFS Instruction 02-204-01, February 22, 

2016, 24 p. [Available at http://www.nmfs.noaa.gov/pr/sars/pdf/gamms2016.pdf.] 

Reilly, S. B., M. A. Donahue, T. Gerrodette, K. Forney, P. Wade, L. Ballance, J. Forcada, P. 

Fiedler, A. Dizon, W. Perryman, F. A. Archer, and E. F. Edwards. 2005. Report of the scientific 

research program under the International Dolphin Conservation Program Act. NOAA Tech. 

Memo. NOAA-TM-NMFS-SWFSC-372, 34 p. 

Schwartz, L. K., T. Gerrodette, and F. I. Archer. 2010. Comparison of closing and passing mode 

from a line-transect survey of delphinids in the eastern Tropical Pacific Ocean. J. Cetacean Res. 

Manag. 11(3):253–265.

Taylor, B. L., M. Martinez, T. Gerrodette, J. Barlow, and Y. N. Hrovat. 2007. Lessons from 

monitoring trends in abundance of marine mammals. Mar. Mamm. Sci. 23:157–175. 

https://doi.org/10.1111/j.1748-7692.2006.00092.x
20

Wade, P. R., and R. P. Angliss. 1997. Guidelines for assessing marine mammal stocks: report of 

the GAMMS workshop. NOAA Tech. Memo. NMFS-OPR-12, 93 p.

Wade, P. R., G. M. Watters, T. Gerrodette, and S. B. Reilly. 2007. Depletion of spotted and 

spinner dolphins in the eastern tropical Pacific: modeling hypotheses for their lack of recovery. 

Mar. Ecol. Prog. Ser. 343:1–14. https://doi.org/10.3354/meps07069