An Evaluation of the Science Needs to Inform Decisions on 

Outer Continental Shelf Energy Development in the 

Chukchi and Beaufort Seas, Alaska

U.S. Department of the Interior

U.S. Geological Survey

Circular 1370
Cover: Photograph depicts first-year summer sea ice with melt ponds typically found in 

the Chukchi Sea, Alaska. Photograph taken 100 nautical miles offshore west of Barrow, 

Alaska, July 8, 2010. (Photograph from U.S. Geological Survey files.)
An Evaluation of the Science Needs to 

Inform Decisions on Outer Continental 

Shelf Energy Development in the 

Chukchi and Beaufort Seas, Alaska

Edited by Leslie Holland-Bartels and Brenda Pierce

Circular 1370

U.S. Department of the Interior

U.S. Geological Survey
ii

U.S. Department of the Interior

KEN SALAZAR, Secretary

U.S. Geological Survey

Marcia K. McNutt, Director

U.S. Geological Survey, Reston, Virginia: 2011

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Although this report is in the public domain, permission must be secured from the individual copyright owners 

to reproduce any copyrighted materials contained within this report.

Suggested citation:

Entire publication:

Holland-Bartels, Leslie, and Pierce, Brenda, eds., 2011, An evaluation of the science needs to inform decisions 

on Outer Continental Shelf energy development in the Chukchi and Beaufort Seas, Alaska: U.S. Geological Survey 

Circular 1370, 278 p. 

Example for chapter within the publication:

Kolak, J.J., 2011, Chapter 2. Geological context, in Holland-Bartels, Leslie, and Pierce, Brenda, eds., 2011, An evaluation of the 

science needs to inform decisions on Outer Continental Shelf energy development in the Chukchi and Beaufort Seas, Alaska: 

U.S. Geological Survey Circular 1370, p. 13-40. 
Acknowledgments iii

Acknowledgments

The authors of this report are grateful to the many individuals and organizations (see 

Chapter 1, p. 7) that freely shared their time, expertise, and insights on science and 

energy development in the Arctic with the USGS OCS Team. Their efforts helped us to 

better understand the present state of knowledge and the diversity of stakeholder views 

on science sufficiency, making the scope and completion of our study more manageable. 

We also thank members of our team who helped us envision, organize, and facilitate our 

expert consultations—Rudy Schuster and Joy Geiselman. We appreciate the efforts of 

individuals who provided additional focused expertise in ocean science—Gary Brewer, 

Arctic fisheries and climate—Jennifer Nielsen, and remote sensing—Carl Markon. We 

are deeply indebted to our USGS colleagues who developed databases, entered literature 

information, developed graphics, and managed shared sites—Vanessa Willcox-Healey, 

Mary Whalen, Kat Wheeler, Marla Hood, Lauren Skrocki, and A.C. Brown. The publication 

of our document would have not occurred without the talents and investment of many 

hours by Linda Rogers and her expert staff at the USGS Tacoma Publishing Service Center, 

and Kathie Rankin, USGS Office of Science Quality and Integrity. Our deepest appreciation 

goes to Durelle Smith who took on the daunting task of Chief of Staff for this assignment 

and expertly and always positively “herded” us towards completing our assignment. 

Finally, we thank Dave Bornholdt, Gary Brewer, Jon Childs, Dave Douglas, Don Gautier, 

Linda Gundersen, David Houseknecht, Carl Markon, John Piatt, Lisa Robbins, Steve 

Schwarzbach, Ione Taylor, and several anonymous reviewers for their helpful comments on 

earlier versions of this report and briefing documents. 
iv

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Contents v

Chapter 1.—Framing the Assignment and Process. By Leslie Holland-Bartels 

and Brenda Pierce............................................................................................................1

Chapter 2.—Geological Context. By Jonathan J. Kolak .....................................................13

Chapter 3.—Ecological and Subsistence Context. By Anthony R. DeGange and 

Lyman Thorsteinson .......................................................................................................41

Chapter 4.—Climate Change Considerations. By Gary D. Clow, Anthony R. DeGange, 

Dirk V. Derksen, and Christian E. Zimmerman.............................................................81

Chapter 5.—Oil-Spill Risk, Response, and Impact. By Leslie Holland-Bartels and 

Jonathan J. Kolak ........................................................................................................109

Chapter 6.—Marine Mammals and Anthropogenic Noise. By Deborah R. Hutchinson 

and Richard C. Ferrero ................................................................................................165

Chapter 7.—Cumulative Impacts. By Brenda Pierce ........................................................203

Chapter 8.—Conclusions. By Brenda Pierce and Leslie Holland-Bartels......................217

Appendix A.—Expert Consultations .....................................................................................223

Appendix B.—Science Workshop........................................................................................233

Appendix C.—Structured Decision Making for Energy Exploration and 

Development Decisions on the Arctic Outer Continental Shelf. 

By Sarah J. Converse ..................................................................................................243

Appendix D.—The Exxon Valdez Oil Spill Experience: Lessons Learned 

from a Cold-Water Spill in Sub-Arctic Waters. By Dede Bohn...........................251

Appendix E.—Arctic Marine Synthesis—Data Sources and Data Quality. .................261

Contents
Conversion Factors

Inch/Pound to SI

Multiply By To obtain

Length

foot (ft) 0.3048 meter (m)

mile (mi) 1.609 kilometer (km)

Area

acre 4,047 square meter (m2)

acre 0.4047 hectare (ha)

acre 0.4047 square hectometer (hm2) 

acre 0.004047 square kilometer (km2)

square mile (mi2) 259.0 hectare (ha)

square mile (mi2) 2.590 square kilometer (km2) 

Volume

barrel (bbl), (petroleum, 

1 barrel=42 gal)

0.1590 cubic meter (m3) 

gallon (gal) 3.785 liter (L) 

gallon (gal) 0.003785 cubic meter (m3) 

gallon (gal) 3.785 cubic decimeter (dm3) 

million gallons (Mgal) 3,785 cubic meter (m3)

cubic foot (ft3) 28.32 cubic decimeter (dm3) 

cubic foot (ft3) 0.02832 cubic meter (m3) 
SI to Inch/Pound

Multiply By To obtain

Length

 centimeter (cm) 0.3937 inch (in.)

millimeter (mm) 0.03937 inch (in.)

meter (m) 3.281 foot (ft) 

kilometer (km) 0.6214 mile (mi)

kilometer (km) 0.5400 mile, nautical (nmi) 

meter (m) 1.094 yard (yd) 

Area

square meter (m2) 0.0002471 acre 

square kilometer (km2) 247.1 acre

square kilometer (km2) 0.3861 square mile (mi2)

Volume

cubic meter (m3) 6.290 barrel (petroleum, 1 barrel = 42 gal)

liter (L) 33.82 ounce, fluid (fl. oz)

liter (L) 2.113 pint (pt)

liter (L) 1.057 quart (qt)

liter (L) 0.2642 gallon (gal)

cubic meter (m3) 264.2 gallon (gal) 

cubic centimeter (cm3) 0.06102 cubic inch (in3) 

liter (L) 61.02 cubic inch (in3) 

cubic meter (m3) 35.31 cubic foot (ft3)

cubic meter (m3) 1.308 cubic yard (yd3) 

cubic meter (m3) 0.0008107 acre-foot (acre-ft) 

Mass

gram (g) 0.03527 ounce, avoirdupois (oz)

Pressure

kilopascal (kPa) 0.009869 atmosphere, standard (atm)

kilopascal (kPa) 0.01 bar

kilopascal (kPa) 0.2961 inch of mercury at 60°F (in Hg)

kilopascal (kPa) 0.1450 pound-force per inch (lbf/in) 

kilopascal (kPa) 20.88 pound per square foot (lb/ft2) 

kilopascal (kPa) 0.1450 pound per square inch (lb/ft2) 

 Temperature in degrees Celsius (°C) may be converted to degrees Fahrenheit (°F) as follows:

°F=(1.8×°C)+32.

Temperature in degrees Fahrenheit (°F) may be converted to degrees Celsius (°C) as follows:

°C=(°F-32)/1.8.

Conversion Factors—Continued
2-D two-dimensional

3-D three-dimensional

ACEX Arctic Coring Expedition

AEPS Arctic Environmental Protection Strategy

ANILCA Alaska National Interest Lands Conservation 

Act

ANIMIDA Arctic Nearshore Impact Monitoring in the 

Development Area

ANS Alaska North Slope

AOGCM Atmosphere-Ocean General Circulation 

Model (global climate model) 

AOOS Alaska Ocean Observing System

AR4 IPCC Fourth Assessment Report 

ARCS ARCtic Satellite

ARRT Alaska Regional Response Team

ASD Azimuthal Stern Drive

ASRC Arctic Slope Regional Corporation

BIOS Baffin Island Oil Spill

BLM Bureau of Land Management

BOEMRE Bureau of Ocean Energy Management, 

Regulation and Enforcement

BOWFEST Bowhead Whale Feeding Study

BSIERP Bering Sea and Aleutian Island Integrated 

Ecosystem Research Program

BWASP Bowhead Whale Aerial Survey

cANIMIDA Continuation of the Arctic Nearshore Impact 

Monitoring in the Development Area

CANUSDIX Canada-United States Dixon Entrance

CARA Circum-Arctic Resource Appraisal

CEQ Council on Environmental Quality

CIP Capital Improvement Program

COMIDA Chukchi Offshore Monitoring in Drilling Area 

Program

DASARs Directional Autonomous Seafloor Acoustic 

Recorders

DBO Distributed Biological Observatory

DPS Distinct Population Segments

DOI Department of Interior

EIS Environmental Impact Statement

EP Exploration Plan

EPPR Emergency Prevention Preparedness and 

Response

ERA Environmental Resource Area

ERMA Emergency Response Management 

Application

ESA Endangered Species Act

EVOS Exxon Valdez Oil Spill

G&G Geological and Geophysical

GOM Gulf of Mexico

GPR Ground Penetrating Radar

GPS Global Positioning System

IARPC Interagency Arctic Research Policy 

Committee

IBA Important Bird Areas

IPCC Intergovernmental Panel on Climate Change 

ISB In-situ Burning

JIP Joint Industry Project

LOIS Lamor Oil Ice Separator

LTK Local Traditional Knowledge

MCDA Multi-Criteria Decision Analysis

MMPA Marine Mammal Protection Act

MMS Minerals Management Service

MOR Mineral-to-Oil Ratio

MORICE Mechanical Oil Recovery in Ice-Infested 

Waters

NEPA National Environmental Policy Act

NGO Non-governmental Organization

NMFS National Marine Fisheries Service

NOAA National Oceanic and Atmospheric 

Administration

NOBE Newfoundland Offshore Burn Experiment

NCP National Oil and Hazardous Substances 

Pollution Contingency Plan

NPR-A National Petroleum Reserve-Alaska

NRC National Research Council

NRDA National Resource Damage Assessment

Acronyms
NSB North Slope Borough

NSF National Science Foundation

OCS Outer Continental Shelf

OMA Oil Mineral Aggregates

OPA 90 Oil Pollution Act of 1990

OSRA Oil Spill Risk Analysis

OWM Oil Weathering Model

PAH Polycyclic aromatic hydrocarbons

PAME Protection of the Arctic Marine Environment

PLFs pingo-like-features

PTS Permanent Threshold Shift

R&D Research and Development

rms Root-mean-squared

SDM Structured Decision Making

SEL Sound Exposure Level

SERVS Ship Escort/Response Vessel System

SLP Sea-Level atmospheric Pressure 

SPL Sound Pressure Level

SPM suspended particulate matter

SRES Special Report on Emissions Scenarios 

TAPS Trans-Alaska Pipeline System

TPS Total Petroleum System

TTS Temporary Threshold Shift

UNCLOS U.N. Convention of Law of the Sea

USARC U.S. Arctic Research Commission

USCGC U.S. Coast Guard Cutter

USEPA U.S. Environmental Protection Agency

USFWS U.S. Fish and Wildlife Service

USGS U.S. Geological Survey

WAF Water Accommodated Fraction

WSCs Water Soluble Components

Acronyms—Continued
This page intentionally left blank.
Framing the Assignment and Process 1

Chapter 1

Chapter

1

“As a significant owner of Arctic 

resources, the United States has a 

responsibility to know what it owns, 

to understand basic biology, geology, 

and natural history of its assets, and to 

understand the population dynamics of 

the living resources it manages—alone, 

or in concert with the State of Alaska 

and other Nations” 

(U.S. Arctic Research Commission, 

2010).

“Among the greatest uncertainties in 

future energy supply and a subject of 

considerable environmental concern 

is the amount of oil and gas yet to be 

found in the Arctic” 

(Gautier and others, 2009).

Framing the Assignment 

and Process 

 By Leslie Holland-Bartels and Brenda Pierce

Background

On March 31, 2010, Secretary of the Interior Ken Salazar 

announced a national strategy for Outer Continental Shelf (OCS) oil and 

gas development. In that announcement, the Administration outlined a 

three-pronged approach (U.S. Department of the Interior, 2010a):

Development: “...expand development and production 

throughout the Gulf of Mexico, including resource-rich areas 

of the Eastern Gulf of Mexico...”

Exploration: “...expand oil and gas exploration in frontier 

areas, such as the Arctic Ocean and areas in the Atlantic Ocean, 

to gather the information necessary to develop resources in the 

right places and the right ways.”

Conservation: “...calls for the protection of special areas 

like Bristol Bay in Alaska...national treasure[s] that we must 

protect for future generations.”

In a companion announcement (U.S. Department of the Interior, 

2010b), within the Administration’s “Exploration” component, the 

Secretary asked the U.S. Geological Survey (USGS) to conduct an 

initial, independent evaluation of the science needs that would inform 

the Administration’s consideration of the right places and the right ways 

in which to develop oil and gas resources in the Arctic OCS, particularly 

focused on the Beaufort and Chukchi Seas (fig. 1–1). Why the focus on 

the Arctic OCS? First, oil resource potential is significant. On Alaska’s 

North Slope, the Nation’s largest oil field—Prudhoe Bay—has been 

in production for several decades. Oil has been produced from the 

Beaufort Sea OCS since the early 2000s and the Arctic OCS potential 

for production of additional oil and gas resources is very high. Accessing 

such resources will require development not only in the offshore waters 

of the Arctic OCS, but also additional infrastructure in the coastal 

areas of Alaska’s North Slope. Beyond energy potential, this area (or 

region) supports unique fish and wildlife resources and ecosystems; 

and indigenous peoples who rely on these resources for subsistence. 

While the potential for and interest in energy resources is clear, there is 

significant public discourse over the Nation’s abilities to develop such 

resources safely, to understand environmental and social consequences 

of any development, and to frame effective impact prevention and 

mitigation strategies. That discourse often revolves around different 

views on the sufficiency of the scientific information available to 

consider energy development decision options and to understand 

environmental sensitivity in this frontier area. 
2 An Evaluation of the Science Needs to Inform Decisions on Outer Continental Shelf Energy Development in the Chukchi and Beaufort Seas, Alaska

Canada

U.S.A

68°0'0"N

68°0'0"N

70°0'0"N

70°0'0"N

72°0'0"N

°0'0"N 72

74°0'0"N

74°0'0"N

Figure 1–1. North Slope of Alaska from Point Hope to the United States–Canada border showing principal coastal communities, Outer Continental Shelf oil and gas leasing areas, and major Federal land holdings. From BOEMRE, the Bureau of Ocean Energy Management, Regulation and Enforcement, formerly the Minerals Management Service (2008). 
Framing the Assignment and Process 3

Chapter 1

Thus, the USGS was asked to summarize key existing 

scientific information, develop a rapid process to identify 

where knowledge gaps exist, and provide initial guidance of 

what research is needed to improve decision making. The 

USGS was asked to ensure that its analyses considered some 

key points already identified to the Secretary by a broad 

spectrum of vested parties. These four Issue Topics were 

articulated to the USGS as:

• Climate Change Considerations: How the likely 

effects of climate change over the expected lifetime 

of the development activities will either mitigate or 

compound the impacts from energy production in the 

Arctic environment?

• Marine Mammals and Seismic Activities: What 

effect seismic exploration activities may have on 

marine mammals, especially any particular concerns 

that may be unique to the Chukchi and Beaufort Seas?

• Oil-Spill Response: What is the research needed to 

allow for an effective and reliable oil-spill response in 

ice-covered regions? 

• Cumulative Impacts: What are the cumulative 

impacts of potential energy development, including 

infrastructure and maintenance activities, off-shore 

and on-shore, related to ecosystems, landscapes, 

seascapes, water quality, seafloor and land stability, 

and subsistence hunting and fishing?

The Process

Our team (hereafter called the USGS OCS Team) was 

formed in May 2010 and comprised of scientists from the 

USGS with the assignment to conduct the requested analyses 

and to provide scientific recommendations for the four Issue 

Topics, above, to the Secretary of the Interior in April 2011. 

We conducted an initial examination of a wide range of public 

policy documents from vested parties and materials from 

the Bureau of Ocean Energy Management, Regulation and 

Enforcement (BOEMRE, formerly the Minerals Management 

Service), industry, non-governmental organizations, and 

others that affirmed views that “science gaps” and “sufficient 

science” vary. Interpretation of concepts are dynamic, tied 

to an individual’s or organization’s held beliefs, and what 

they most strongly value within their thought process when 

dealing with complexity and uncertainty. The decision(s) to 

develop resources in the Arctic is inherently complex because 

it must consider factors such as the significant economic and 

environmental stakes and risks, multiple objectives, and high 

levels of project uncertainty inherent in working in a frontier 

environment. The decision(s) also is difficult because of 

the complexity of the multiplicity of choices needing to be 

made and organizations that must make those choices. In a 

regulatory sense, BOEMRE is the vested decision body for the 

Federal government regarding oil and gas development in the 

Arctic OCS. However, in reality there are multiple Federal, 

State, and local and regional communities and organizations 

that influence the ultimate decision outcome (fig. 1–2), each 

of which has downstream responsibilities in the oil and gas 

leasing process and can have differing views of what science 

information is essential. The public also provides input during 

the Federal leasing process at many points (fig. 1–2). In the 

larger public policy arena, public opinion also influences 

both the political domain and the use of litigation tools. 

Here, the views of science sufficiency can be quite different. 

Thus, the USGS OCS Team took an inclusive approach to 

its “science gap and sufficiency” assignment by not only 

examining available literature, but also by gathering input 

from many elements of the “organization” that ultimately 

influence decisions about what science is “needed” for oil 

and gas development in the Arctic OCS. We analyzed some 

400 relevant reports, workshop findings, policy documents 

(for example, see Regional Government, Environmental 

Group, and International Perspectives), and web sites, as 

well as key scientific journal literature. In addition, we held 

seven structured information sessions with key vested parties 

in which we ultimately engaged 46 entities (see Entities 

that Participated in Various USGS OCS Team Information 

Gathering Sessions). All of this information was incorporated 

into our considerations as we independently addressed the four 

topics requested by the Secretary of the Interior.

We started our process by conducting one-on-one 

expert consultations with some 20 entities. These parties 

had management responsibilities, had published key policy 

statements on relevant topics, or were conducting scientific 

projects with a nexus to our assignment. These discussions 

assisted us in understanding current views on scientific gaps, 

identifying key documents, and informing us of new and 

emerging scientific efforts or analyses. 
4 An Evaluation of the Science Needs to Inform Decisions on Outer Continental Shelf Energy Development in the Chukchi and Beaufort Seas, Alaska

Figure 1–2. This simplified schematic illustrates some of the decision points within two initial planning phases of the extensive Bureau 

of Ocean Energy Management, Regulation and Enforcement (BOEMRE) oil and gas leasing process—the 5-Year Plan and Individual 

Lease Sale processes, for which scientific information is required. BOEMRE has many decision points (blue) requiring scientific 

information. Examples of inputs also are shown from the public (brown) and other agencies including the U.S. Environmental Protection 

Agency (USEPA, green) and Federal natural resource agencies (U.S. Fish and Wildlife Service–USFWS and National Oceanic and 

Atmospheric Administration–NOAA, orange). (NPDES, National Pollutant Discharge Elimination System.)

9_fig01-02 

5-Year Plan Individual Lease Sale

The Secretary of the Interior

and BOEMRE requests

comments

Draft 5-Year Program

Proposed 5-Year Program

Final 5-Year Program

Submitted to President

and Congress

If there are no Congressional

objections, the Secretary

approves the program

Planning for individual

lease sale

Informal consultation

with USFWS NOAA

Endangered Species

Act

BOEMRE Produces

Environmental Impact

Statement (EIS) for

5-Year Program

USEPA Comments on

Draft and Reviews

for consideration

of comments

Call for Information and

Notice of Intent to Prepare

EIS published

A call is issued for industry

interest in the area

Notice of Sale

Final EIS (FEIS)

Consistency Determination

for each State's Coastal

Zone Management

done by BOEMRE

Area identification

60-Day Comment Period

with Public Hearings

USEPA Comments on

Draft and Reviews

for consideration

of comments

BOEMRE Produces

EIS for Lease Sale

BOEMRE

consultation with

USFWS NOAA

Environmental Assessment

Produced for a Lease

Sale when over a year

has passed since FEIS

was released

30-day

Comment

Period

USEPA Comments on

Draft to address needs

for future NPDES

General Permit (GP)

USEPA Consultations

with NOAA and USFWS

Draft GP

is produced

Public Comment

Period

Final GP Release

with Lease Sale

Final Notice

of Sale
Framing the Assignment and Process 5

Chapter 1

Components of the overall policy position of a key conservation 

group on Federal decisions related to Arctic Outer Continental 

Shelf oil and gas development (Pew Environment Group, 2010).

Environmental Group Perspective

Science Plan

•	 Complete comprehensive plan

•	 Research and monitoring

•	 Independent science gap analysis

•	 Define ecologically sensitive areas and protect

•	 Incorporate traditional knowledge

•	 Increase research funding and collaboration

Oversight of Oil Development

•	 Review of plans and permits must be free of

undue industry influence

•	 Review and oversight must involve all relevant

agencies

•	 Enhanced inspections and testing

•	 Citizens’ advisory councils incorporated into

oversight

•	 Adequate funding for oversight

Oil-Spill Risk and Response

•	 Risk assessment must reflect Arctic conditions

•	 Technologies must address Arctic-specific risks

•	 Spill response systems and technologies must

be proven in Arctic

•	 Response plans must include relief well and

containment options

•	 A response gap must be prepared

•	 Infrastructure gaps must be assessed and

addressed

•	 Spill trajectory models must be Arctic-based

•	 Worst-case scenarios must be based on actual

conditions

•	 Improve response planning standards

Components of an overall policy position of a key regional 

government likely affected by Federal decisions on Arctic Outer 

Continental Shelf oil and gas development (North Slope Borough, 

2009).

Regional Government Perspective

Baseline Science

•	 Require adequate baseline data prior to activity

•	 Support collaborative approaches

•	 Pre-leasing activities should mirror Bureau of

Land Management’s (BLM) pre-activity study

program

Stricter Regulation

•	 Use of pipelines versus tanker transportation

•	 Apply regulations and stipulation more rigorously

•	 Improve standards in leasing process

•	 Require negotiation of Conflict Avoidance

Agreements for marine mammals beyond whales

Cumulative Impacts

•	 Require area-wide impact discussions in impact

statements and environmental assessment 

documents

•	 Include socio-cultural impacts

•	 Stipulate limits on projects

•	 Effective Coast Guard presence required

•	 Fund year-round oceangoing and airborne

response capacities

Revenue Sharing

•	 Include in all development phases

•	 Use BLM Impact Aid Program or other early

funding

•	 Broaden Coastal Impact Aid Program fund uses

Discharge/Emissions

•	 Require zero-volume discharge

•	 Subsistence consideration in Clean Water Act

•	 Do not allow “disaggregation” of an operation

into separate emission permits, permit as one

Oil-Spill Prevention and Response

•	 Best available technologies

•	 Provable cleanup technologies

•	 Real-world demonstrations of capacities

Compulsory Marine Pilotage

•	 Require State-licensed marine pilots
6 An Evaluation of the Science Needs to Inform Decisions on Outer Continental Shelf Energy Development in the Chukchi and Beaufort Seas, Alaska

Selected recommendations from the Arctic Council’s Arctic Monitoring and Assessment Programme on oil and gas activities

in the circumpolar Arctic (Skjoldal and others, 2010).

International Perspective

 Oil-Spill Prevention

•	 Conduct risk assessments of means of transportation of oil

•	 Use best practices for transportation and storage

•	 Seasonal restrictions

•	 Improve capacities and coordination of spill prevention, preparedness, and response. Provide rapid and

adequate response equipment and well-trained personnel

Best Practices

•	 Consult/collaborate with communities

•	 Reinject, clean, or safely dispose of wastes

•	 Transportation including pipelines to be built to highest industry and international standards

•	 Seasonal restrictions to avoid disturbance of species and sensitive areas

Monitoring to Improve Assessment

•	 Compliance monitoring is necessary

•	 Consistent, rigorous and integrated monitoring programs to detect changes in environment, society, and

human health

•	 Apply new tools such as biological markers and sociological indicators of change

•	 Monitoring including physical, chemical, biological, and socio-economic conditions and based on international

standards

•	 Monitoring to distinguish oil and gas activity impacts from others

•	 Coordination at regional scales to observe interactions and cumulative effects of multiple activities

•	 Site fidelity/local adaptation of Arctic species necessitates better understanding of population structure and

monitoring

•	 Pan-Arctic monitoring of human health

•	 Better use and streamlining of the Environmental Impact Statements/Environmental Assessments

Gaps

•	 Improved technologies, particularly seismic

•	 Oil-spill clean-up technologies and technologies for ice, under-ice, and broken ice

•	 Comparative studies of socio-economic effects including compilation of relevant statistics pan-Arctic, studies

of mitigation effectiveness, and comparative and case studies

•	 Site and population-specific study data on human heath. Obtaining insights from large industry activities in

Russia

•	 Behavior and fate of oil in ice

•	 General need for better information on population (genetic and geographic) structure of animal populations

•	 Fundamental ecological interactions between species and oil and gas development

•	 Map ecologically sensitive areas and improve spill trajectory models

•	 Coordination of research is essential given the breadth of data, scale, timelines of needs
Framing the Assignment and Process 7

Chapter 1

Department of the Interior

U.S. Fish and Wildlife Service

National Park Service

Bureau of Ocean Energy Management, Regulation 

 and Enforcement

Office of the Solicitor

Office of Environmental Policy and Compliance–

 Anchorage Field Office

National Oceanic and Atmospheric Administration

Office of Response and Restoration

National Weather Service

National Marine Fisheries Services–Alaska Fisheries 

 Science Center

U.S. Environmental Protection Agency

U.S. Coast Guard 17th District

National Commission on the BP Deepwater Horizon

 Oil Spill and Offshore Drilling

BP Exploration (Alaska)

ConocoPhillips Alaska Inc

Shell Exploration and Production

Marine Mammal Commission

Community of Barrow

North Slope Borough

Mayor’s Office

Department of Wildlife Management

Planning Department

Eskimo Whaling Commission

University of Alaska Fairbanks

University of Maryland

LGL Alaska

Coastal Response Research Center

ARB, Inc.

Oceanus Alaska

Battelle

United Fishermen’s Marketing Association

North Pacific Research Board

Alaska Ocean Observing System

Ocean Conservancy

Pew Environment Group

The Nature Conservancy

North Slope Science Initiative

Oil Spill Recovery Institute

Audubon Alaska

World Wildlife Fund

Oceana

Earthjustice

State of Alaska

Alaska Department of Natural Resources

Division of Geological and Geophysical Surveys

Division of Oil and Gas

Alaska Department of Fish and Game

Alaska Department of Environmental Conservation

Alaska Oil and Gas Conservation Commission

Canada–US Northern Oil and Gas Research Forum 2010

Entities that Participated in Various USGS OCS Team Information Gathering Sessions
8 An Evaluation of the Science Needs to Inform Decisions on Outer Continental Shelf Energy Development in the Chukchi and Beaufort Seas, Alaska

This initial engagement was followed by a series 

of facilitated group expert consultations to gain a deeper 

understanding of decision constraints and perspectives 

on needed science. Five separate facilitated sessions were 

held with representatives from the energy industry, Federal 

regulators, nonregulatory parties (including nongovernmental 

environmental groups and relevant science boards, 

observatories, and institutes), North Slope representatives 

(including Borough and subsistence leaders and environmental 

and wildlife specialists), and agencies of the State of 

Alaska. Examples of the inputs provided from the sessions 

are provided in appendix A. Our purpose was not to obtain 

analytical survey data from the participants, but rather to use 

an analytical approach to focus discussions and to bring some 

level of consistency across all sessions for gathering input 

from these key stakeholder groups to the USGS task at hand. 

During the consultations, participants were asked 

to brainstorm and identify issues/gaps under each of the 

four Issue Topics requiring scientific information that will 

affect their ability to accomplish their jobs. Results of those 

discussions can be found in appendix table A–1. The USGS 

OCS Team requested that the participants informally consider 

how important a science gap was to their decision making 

associated with oil and gas development on a 5-point scale 

from 0 (not considered) to 4 (foundational) and to assess the 

status of scientific information for the issue (0–no information 

to 4–robust) (see appendix table A–2).

 Our objective was to refine our understanding of the 

priority for a science gap and the sufficiency of the existing 

information (fig. 1–3). Because our allotted time for each 

session was limited to 2 hours, most sessions did not complete 

the entire process of discussing all Issue Topics. We provided 

a summary of all materials to session participants and allowed 

them to provide additional input if they chose to do so at a 

later date. That additional information was included with 

the original session findings. Given time constraints, not all 

participants in any of the five consultations in this series chose 

to use this Grid Tool in their responses back to the USGS OCS 

Team, so we did not proceed with any detailed analyses of 

the observations derived from this approach. However, most 

participants of one of the focus groups did respond and we 

therefore include a preliminary analysis of their responses 

as an example of the types of information and insights that 

might be gained through the use of this or other information 

gathering tools (appendix table A–3). 

 In January 2011, the USGS OCS Team participated in 

the Alaska Marine Science Symposium in Anchorage, Alaska, 

to gain focused input from the science community on key 

topics that had arisen during our assignment. The USGS OCS 

Team contributed to and participated in the Symposium’s 

Poster Session to interact with participants and held a 3-hour 

facilitated technical workshop dedicated to our task to obtain 

scientific input on areas of critical and fruitful investigation 

or approaches informative to the science gap analysis. The 

discussions were centered on four overarching scientific 

questions on topics that were consistently mentioned during 

our other expert consultations or in our literature assessments 

and that cross-cut the Issue Topics that are the focus of our 

assignment (fig. 1–4). These topics were:

• What weather and oceanographic data are immediately 

needed to improve spill risk assessments, response 

planning, and spill response; what approaches are 

recommended to obtain such data?

• What supplements to agency monitoring and 

approaches to integrated ecological monitoring are 

needed for improved development impact assessment, 

including spill assessment (Natural Resource Damage 

Assessment, recovery, and restoration) efforts?

• Given gaps in spatial and temporal understanding 

of resources, how (methods, approaches) can the 

extensive industry site-specific monitoring be coupled 

with synoptic governmental efforts to improve broader 

scale understanding?

• What are important differences in the physical and 

ecological conditions of the Beaufort and Chukchi 

Seas that need to be clearly understood to address the 

Secretary’s commitment to OCS exploration in the 

“right place/right way”?

The 75 participants were provided background on 

the USGS OCS Team’s assignment, context for each of 

the questions, and several discussion starter questions 

(appendix B). They were then asked to self-select one 

of the four breakout groups (above). After 45 minutes of 

facilitated discussion, the participants then self-selected a 

second breakout group. In this second series of discussions, 

participants started with the materials developed by the 

first group and continued discussion. At the end of these 

discussions, each breakout group reported out to the full 

workshop. Materials gathered during these consultations are 

summarized in appendix tables B–1 and B–2. 
Framing the Assignment and Process 9

Chapter 1

Critically 

important

No information 

at all

Robust

Information

Not a 

consideration

Reassess

• Ensure information 

inadequacy in not driving 

consideration score

• Examine for emerging 

issues

• May be driven by 

expense or technical 

limitations

1

1

0

0 2

3

3 4

4

Sucient?

• Is the right information 

being collected?

• Perhaps important to 

other issues but not 

OCS; consider 

reallocating funds to 

identied OCS science 

insuciencies

Gap

• What science is 

necessary?

• What has 

constrained getting 

this science done?

Good Work

• Keep knowledge up 

to date

• Keep up the good 

work

• Reallocate resources 

to strengthen specic 

weaknesses?

Figure 1–3. Grid tool used in the first series of structured consultations with industry, regulatory agencies, nonregulatory groups, 

North Slope representatives, and the State of Alaska. Y-axis represents the importance of an issue to an individual’s decision

making associated with oil and gas development. X-axis represents the participant’s view of the status of the body of scientific

information for that issue. When scores fell within a red or orange portion of the grid, we considered the topic to be an important 

gap for our initial analyses. Scoring is based on definitions provided in appendix table A–2.
10 An Evaluation of the Science Needs to Inform Decisions on Outer Continental Shelf Energy Development in the Chukchi and Beaufort Seas, Alaska

In addition to these consultations, including the facilitated 

discussion session in Barrow, Alaska, described above, the 

USGS OCS Team held an open public session in Barrow to 

discuss community views on science issues and information 

gaps. Approximately 40 community members attended this 

session. This facilitated process was informal to encourage 

community members to have one-on-one discussions with 

individual team members on each Issue Topic. Posters with 

our Issue Topics were placed around the meeting room and 

each was attended by one or more members of the USGS OCS 

Team. Community concerns and suggestions were recorded 

during those discussions. In addition, attendees were able to 

leave their thoughts in writing if they desired. Information 

gathered from this session is included in appendix A, 

table A–1.

Following our review of the literature and expert 

consultations, the USGS OCS Team found that some of its 

emerging strategic findings and recommendations related 

to organized approaches to enhance the transparency and 

collaborative nature of evaluating science priorities in the 

multi-faceted Arctic oil and gas development decisionmaking environment. These findings will be discussed later 

in appropriate chapters. We mention this here because these 

discussions led us to conduct a 1-day prototyping exercise of a 

Structured Decision Making (SDM) concept (see appendix C). 

We took this additional step in our assignment because much 

of what we were hearing in our consultations was not solely 

about science—it was about perception and values. Identifying 

science gaps was not enough, in our opinion, to fully grasp 

Figure 1–4. The USGS conducted two series of formal expert consultations. The first focused on the Issue Topics presented to the 

Team by the Secretary of the Interior (Issues) and the second focused on common cross-cutting science themes that emerged from the 

first consultations and was the subject of the Alaska Marine Science Symposium Workshop. Arrows illustrate examples of where the 

cross-cutting science themes inform the four Issue Topics of the USGS OCS Team’s assignment.

Beaufort Chukchi Nuances

Marine Noise Influences 

Marine Mammals

Oil Spill Risk, Response, 

and Impact Cumulative Effects Climate Influences

Integrated Monitoring

Meteorological and Oceanographic Data and Strategies

Linked Process and Synoptic Approaches 

ISSUES

Shared Data Sources
Framing the Assignment and Process 11

Chapter 1

the complexity of issues surrounding potential development in 

the Arctic. Thus, some tools that go beyond, but incorporate, 

science—such as SDM or similar—are of value in looking at 

what can/should be done about policy and implementation of 

Arctic development, and specifically what and where science 

can best inform decisions. The USGS OCS Team developed 

a broad outline of a decision framework to inform the DOI 

Arctic OCS energy exploration and development decision. 

This framework was developed as an example, or prototype, 

of a more fully articulated framework that could be developed 

with the input of the decision maker or delegates. That is, the 

decision framework presented here is both incomplete and is 

not assumed to represent the true aspects of the decision as 

understood by the decision maker; instead it is intended as 

an illustration of the value of this, or similar, approach. This 

simple prototype should serve the purpose of demonstrating 

the basic process of SDM and how it could be applied to 

synthesize and analyze science and policy information to 

inform Arctic OCS energy exploration and development 

decisions.

The Report

Our report is presented in a series of topical chapters, 

followed by a conclusion section, and various appendixes 

each written by a subset of the USGS OCS Team based on 

their areas of expertise. Three chapters (2, 3, and 4) provide 

foundational information on geology; ecology and subsistence; 

and climate settings important to our assignment. These 

chapters are followed by three chapters that examine the 

scientific understanding, science gaps, and science sufficiency 

questions on the Issue Topics provided to USGS—oil-spill 

response (Chapter 5), marine mammals and seismic activity 

(Chapter 6), and cumulative effects (Chapter 7). In addition to 

discussions in Chapter 3 about observed climate, we address 

the Issue Topic “Climate Change Considerations” in more 

detail in Chapter 4, and as it relates to oil-spill response in 

Chapter 5. 

Based on our initial investigations, we chose to modify 

the Issue Topics slightly, due to what we were learning from 

the literature and during our consultations. The Marine 

Mammal and Seismic Activity Issue was reframed to consider 

the effects of anthropogenic noise on marine mammals more 

broadly rather than just that of seismic noise. We reframed 

the Oil Spill Response Issue to include science within the full 

decision framework that affects spill response. We considered 

science to better understand the potential effects of oil spills 

in pre-decisional planning; within spill contingency planning 

and spill response; and science required to address postspill damage assessment and restoration considerations. We 

also examined lessons learned from the 1989 Exxon Valdez

Oil Spill to identify valuable “pre-positioned” science and 

scientific approaches to improved response and reduced 

uncertainty in damage assessment and restoration efforts 

(appendix D). 

We provide a series of findings and recommendations 

for consideration under our assignment as an independent 

examination of science gaps and sufficiency. These findings 

and recommendations are the informed opinions of the various 

authors as developed through the processes described above. 

References Cited

Gautier, D.L., Bird, K.J., Charpentier, R.R., Grantz, A., 

Houseknecht, D.W., Klett, T.R., Moore, T.E., Pitman, J.K., 

Schenk, C.J., Schuenemeyer, J.H., Sorensen, K., Tennyson, 

M.E., Valin, Z.C., and Wandrey, C.J., 2009, Assessment 

of undiscovered oil and gas in the Arctic: Science, v. 324, 

no. 5931, p. 1175-1179, doi:10.1126/science.1169467, 

accessed March 31, 2011, at http://www.sciencemag.org/

content/324/5931/1175.abstract.

Minerals Management Service, 2008, Beaufort Sea and 

Chukchi Sea Planning Areas: Oil and Gas Lease Sales 209, 

212, 217 and 221: Draft Environmental Impact Statement, 

OCS EIS/EA MMS 2008-0055.

North Slope Borough, 2009, North Slope Borough Arctic 

Offshore Oil and Gas Development Policy Positions: North 

Slope Borough Mayor’s Office, Barrow, Alaska, 78 p.

Pew Environment Group, 2010, Policy recommendations—

Oil spill prevention and response in the U.S. Arctic Ocean: 

Washington, D.C., Pew Environment Group, 19 p., accessed 

March 31, 2011, at http://www.pewenvironment.org/

uploadedFiles/PEG/Publications/Other_Resource/Oil%20

Spill%20Prevention%20Policy%20Recommendations.pdf.

Skjoladal, H.R., Thurston, D., Baffrey, M., Crandall, B., 

Dahle, S., Gilman, A., Huntington, H.P., Klungsøyr, J., 

Lockhart, L., Macdonald, C., Mosbech, A., and Thomas, D., 

2010, Chapter 7, Scientific findings and recommendations, 

in Arctic Monitoring and Assessment Programme, 

Assessment 2007–Oil and gas activities in the Arctic–

Effects and potential effects: Oslo, Norway, p. 7-1–18. 
12 An Evaluation of the Science Needs to Inform Decisions on Outer Continental Shelf Energy Development in the Chukchi and Beaufort Seas, Alaska

U.S. Arctic Research Commission, 2010, Report on goals 

and objectives for Arctic Research 2009-2010: For the 

U.S. Arctic Research Program Plan: U.S. Arctic Research 

Commission, Biennial Report to the President and U.S. 

Congress, Arlington, Virginia: 64 p., accessed April 18, 

2011, at http://www.arctic.gov/publications/2009-10_usarc_

goals.html.

U.S. Department of the Interior, 2010a, Secretary Salazar 

Announces Comprehensive Strategy for Offshore Oil 

and Gas Development and Exploration: Press Release, 

March 31, 2010, available at http://www.doi.gov/news/

pressreleases/2010_03_31_release.cfm. 

U.S. Department of the Interior, 2010b, Secretary Salazar 

Unveils Arctic Studies Initiative that will Inform Oil 

and Gas Decisions for Beaufort and Chukchi Seas: Press 

Release April 13, 2010, available at http://www.doi.gov/

news/pressreleases/2010_04_13_releaseA.cfm.
Chapter 2

Geological Context 13

Chapter

2

Introduction

The purpose of this chapter is to 

describe the status of knowledge of 

the geologic framework of the Arctic, 

and how this knowledge underpins our 

understanding of energy resources—

especially oil and gas accumulations in the 

Chukchi and Beaufort Seas—and supports 

estimates of the potential for these resources 

to be discovered, developed, transported to 

market, and ultimately contribute to the 

energy mix. The larger Arctic system is 

discussed as there are potentially significant 

drivers outside the planning areas that 

merit consideration when identifying Arctic 

research needs, particularly those aimed 

at reducing the uncertainty of estimates 

regarding oil and gas resource endowments 

or potential impacts resulting from aspects 

of oil and gas activities. In a previous 

study of the Arctic Outer Continental Shelf 

(OCS), the National Research Council 

(NRC) noted that “[t]here is a considerable 

range in the amount of data needed to 

provide adequate information for decisions 

regarding development, production, 

transportation, siting of onshore and 

offshore facilities, and termination of 

activities” (National Research Council, 

1994).

Geological Context 

 By Jonathan J. Kolak

Oil and gas have been produced in the Arctic for decades and oil 

has been produced from the Beaufort Sea OCS since the early 2000s 

(Bureau of Ocean Energy Management, Regulation and Enforcement, 

2011). The confluence of several factors, including recent advances 

in technology and the retreat of sea ice, has intensified interest in 

the Arctic. The shrinking Arctic ice cap is one of the key drivers of 

increased interest in Arctic offshore oil and gas, as the increasingly 

ice-free ocean in the summertime creates and (or) extends the 

seasonal window of opportunity for ships to conduct seismic studies 

in parts of the Chukchi and Beaufort Seas (O’Rourke, 2010). There 

is a commensurate interest among Arctic Nations in mapping the 

continental margins beyond the Exclusive Economic Zone as part 

of Article 76 of the United Nations Convention of Law of the Sea 

(UNCLOS). The potential exists for lands included in the mapping 

claims submitted under Article 76 to be prospective for energy and 

other resources (O’Rourke, 2010).

Many activities are associated with the oil and gas resource 

lifecycle (Arctic Monitoring and Assessment Programme, 2007; 

Lifecycle Phases figure, p. 7). This chapter provides an overview of 

data availability and research needs associated with the evaluation 

phase, as information from this phase is used to define the geologic 

framework that underpins estimates of the resource endowment. 

Information from the geologic framework and resource estimates 

can be used as input for scenario modeling to evaluate the potential 

scope and scale of development and concomitant effects on society, 

environment, and ecosystems, including the risk of oil spills. 

Other research and development (R&D) needs pertaining to this 

lifecycle, such as technology R&D related to resource extraction and 

infrastructure/facilities construction given the particular challenges 

with the Arctic environment, are not addressed here, but constitute 

an important consideration in the larger picture. For example, a 1994 

NRC study noted the importance of information of the ice gouging 

of the seabed and potential scouring problems (National Research 

Council, 1994). Since that study, there has been R&D investment to 

understand these processes better (C-CORE, 2008; Engels and others, 

2008). Despite these investments, this area is recognized as one for 

which more information is needed, including new and innovative 

approaches to protect subsea pipelines from ice scour (U.S. Arctic 

Research Commission, 2010), and the potential for regional ice 

scour databases (IMV Projects Atlantic, 2008). Additional research 

needs germane to oil and gas activities on the U.S. Arctic OCS and 

recommendations for areas of advancement, including exploration, 

development, production, and transport infrastructure, are given in a 

recent assessment of cold region oil and gas technology (IMV Projects 

Atlantic, 2008). 
14 An Evaluation of the Science Needs to Inform Decisions on Outer Continental Shelf Energy Development in the Chukchi and Beaufort Seas, Alaska

Overview of Geologic Framework

Fundamental geological and geophysical research and 

information are critical to Earth science initiatives aimed 

at improving our understanding of the Arctic (U.S. Arctic 

Research Commission, 2010). Similarly, assessments of the 

Arctic energy resource endowment and the potential for 

resource extraction also depend on knowledge of regional 

geology. For this reason, obtaining geological and geophysical 

data is important for making appropriate comparisons and 

reducing uncertainty about resource potential, especially in 

frontier areas, to inform policy and other decisions that rely on 

estimates of resources (Minerals Management Service, 2006a). 

Oil and gas resources typically are studied using a total 

petroleum systems approach (Magoon and Dow, 1994). A 

petroleum system is a holistic approach to systematically 

link elements of geological stratigraphic, structural, and 

tectonic history with the timing of discrete events such as 

maturation of source rocks and generation and expulsion of 

oil and gas and migration and accumulation of these resources 

within a geologic trap or seal (Magoon and Dow, 1994). The 

geologic elements of a total petroleum system (TPS) include 

(1) source-rock distribution, thickness, organic richness, 

thermal maturation, and petroleum generation and migration; 

(2) reservoir-rock type (conventional or continuous), 

distribution, and quality; and (3) character of traps and time of 

trap formation relative to petroleum generation and migration. 

A thorough evaluation of these TPS elements requires 

that they be considered within the framework of the 

reconstructed geologic history, including research findings 

from detailed framework studies of stratigraphy, structural 

geology, heat flow, and geochronology, among others. 

This framework, considered in conjunction with analysis 

of petroleum geochemistry and modeling of petroleum 

generation and migration (Peters and others, 2006), and the 

analysis of historical petroleum exploration and production 

data, where available, provide the basis for probabilistic 

estimates of undiscovered, technically recoverable petroleum 

(oil, natural gas, and natural gas liquids) resources. These are 

resources that have yet to be discovered, but if found, could 

be extracted (produced) using currently available technology 

and industry practices. To place these in an economic 

context, the costs of finding and developing the undiscovered 

accumulations are estimated (Attanasi and Freeman, 2009). 

The cost functions that are constructed in these analyses show 

cost and resource-recovery possibilities, but they are not 

supply functions as defined by economists. However, the data 

that underlie the functions commonly provide the basis for 

market-supply models and development scenarios (Attanasi 

and Freeman, 2009).

It is important to keep in mind that risk and uncertainty 

are integral parts of every resource assessment and 

evaluation of economically recoverable resources; nearly 

every component of the assessment process incorporates a 

consideration of risk and uncertainty:

“The accumulation of petroleum in significant 

quantities requires the juxtaposition of many 

complex geologic events: the accumulation of 

organic matter in a source rock; the maturation of 

this organic matter into petroleum; the presence of 

a reservoir rock with sufficient thickness, porosity, 

and permeability; the migration of the petroleum 

into a trap with adequate size and seals; and the 

preservation of the petroleum in the trap. Prior 

to drilling, the actual existence of these geologic 

conditions is unknown. Not only must all of these 

conditions coexist they must also converge at a 

particular location, an unlikely event that results 

in a high probability of failure often described 

as dry hole or geologic risk. Even if all of these 

conditions coexist at a particular location, there 

remains considerable uncertainty regarding the 

effectiveness of a seal, the size of a trap, the quality 

and thickness of the reservoir, and the volume and 

type of hydrocarbons that not only migrated into 

the trap, but were preserved and still remain to 

be recovered. In general, risk and uncertainty in 

estimates of undiscovered oil and natural gas are 

greatest for frontier areas that have had little or no 

past exploratory effort” (Minerals Management 

Service, 2006a).

Therefore, an improved understanding of the geologic 

framework, through availability of additional data and (or) 

application of new geologic concepts, can significantly 

influence estimates of resource potential. For example, the 

recent update of the undiscovered, technically recoverable 

oil and gas resources of the National Petroleum Reserve in 

Alaska (Houseknecht and others, 2010) led to the finding that 

the estimated volume of undiscovered oil is significantly lower 

than estimates released in 2002. The revision resulted mainly 

from new geologic information from recent exploration 

drilling that showed an abrupt transition from oil to gas and 

reduced reservoir quality in the Alpine sandstone reservoir 

15–20 mi (about 24–32 km) west of the giant Alpine oil field. 

In addition to estimates of total resource endowment, 

there exists uncertainty regarding the size distribution of 

undiscovered accumulations, and the probability of finding a 

large accumulation. This uncertainty is evident particularly 

in regions that are not maturely explored, such as the Arctic, 

and is an important factor to consider because large oil 
Chapter 2

Geological Context 15

and gas accumulations are particularly important to future 

development due to the higher costs associated with oil and 

gas exploration, development, and production in the Arctic 

relative to other regions in the World. Generally, the discovery 

of large fields is important for offsetting the costs of new 

infrastructure. The development of the Prudhoe Bay field, for 

example, necessitated the construction of the Trans-Alaska 

Pipeline System (TAPS). Since then, development of smaller 

satellite oil accumulations has been rendered feasible because 

the bulk of the supporting infrastructure was already in place. 

Without the Prudhoe Bay field, it is not likely that the smaller 

Alaska North Slope oil fields would have been developed 

(Budzik, 2009). 

Geology

The Arctic has long been recognized as a region with 

significant petroleum potential, but limited knowledge of the 

location, character, age, and geologic setting of sedimentary 

successions in this region has hindered the understanding of 

the petroleum potential. Areas that have had extensive oil and 

gas exploration and development, such as the North Slope 

of Alaska, are better understood than offshore regions with 

sparse geophysical data, such as the Amerasia Basin. As part 

of an effort to address this knowledge gap, a new map of 

Arctic geology with emphasis on sedimentary successions that 

might contain petroleum was compiled by Grantz and others 

(2010). The map delineates 143 sedimentary successions in 

the Arctic, among which geologic uncertainty varies greatly 

owing to the quality and density of available data. For this 

compilation, Grantz and others (2010) relied on several types 

of data, including aeromagnetic maps, airborne and satellite 

gravity data, seismic reflection and refraction data, piston 

cores, shallow drill holes, and bathymetry. 

Recent scientific drilling in the Arctic Ocean has 

enhanced our understanding of Arctic geology. This drilling 

was feasible in large part due to developments in technology 

and logistics support that enabled operations in ice-covered 

areas. Previously, only shallow (15–50 ft; about 5–15 m) 

sediment samples could be obtained from the Arctic Ocean 

through gravity and piston coring (Coakley and Stein, 2010). 

However, in 2004, the completion of the International Ocean 

Drilling Program Expedition 302 (Arctic Coring Expedition, 

or ACEX) demonstrated for the first time that scientific 

drilling could be successfully completed in a permanently 

ice-covered part of the Arctic Ocean (Coakley and Stein, 

2010). The ACEX penetrated more than 1,300 ft (400 m) of 

sediments on the Lomonosov ridge (Moran and others, 2006). 

In addition to providing information about the sediment 

depositional and climatic history of this setting, this study 

provided information useful for understanding the organic 

carbon sources and cycling and, ultimately, the potential for 

oil and gas generation. 

The geologic connection between the Alaska North 

Slope (ANS) and offshore Alaska, coupled with the generally 

greater availability of onshore information, makes the ANS 

an important source of analog information for the Federal 

offshore planning areas. For example, ANS oil and gas 

exploration activities over the past decade have increasingly 

focused on stratigraphic traps, including the clinoform strata 

of the Cretaceous-Tertiary Brookian sequence (Houseknecht 

and others, 2009). The regional stratigraphic framework of 

these Lower Cretaceous clinoforms is relatively well known, 

but until recently, there have been few publications that detail 

the sequence stratigraphy of these features (Houseknecht and 

others, 2009). These features are important to study given that 

the development of the Nanuq and Qannik oil accumulations, 

taken together with the occurrence of oil-stains in rock 

outcrops of lower-slope sandstone facies, demonstrates the 

exploration potential in Lower Cretaceous clinoforms that 

occur beneath the western North Slope and Chukchi Sea 

(Houseknecht and others, 2009). 

Vörösmarty and others (2010) acknowledged that 

given the remoteness of the Arctic, some of the most basic 

information needed for the exploration, exploitation, and 

recovery of non-renewable energy are inadequate and 

outdated. For example, the U.S. Arctic Research Commission 

(2010) reported that baseline maps of the State of Alaska 

are out of date and, for some areas, have errors in the range 

of kilometers. Similarly, the high-latitude margins of the 

Arctic Ocean remain only sparsely studied, largely due to the 

operational constraints imposed by sea-ice cover (Engels and 

others, 2008). As a result of these constraints, the morphology 

of the Alaska–Beaufort margin, except for the nearshore zone, 

has not been adequately mapped despite the significance of 

this region for important socio-economic and scientific issues, 

such as hydrocarbon deposits, gas-hydrate stability, and the 

history of Arctic Ocean circulation and ice cover (Engels and 

others, 2008).

In addition to regional framework geology, a key 

component for the study of petroleum systems is the 

identification and analysis of source rocks. The National 

Research Council (1994) recognized the need for “...

geochemical studies related to source rock abundance, 

organic carbon types, and thermal maturity...” to further the 

understanding of petroleum systems and underpin estimates 

of undiscovered resources. Peters and others (2006, 2007) 

have investigated the origin of petroleum in northern Alaska. 
16 An Evaluation of the Science Needs to Inform Decisions on Outer Continental Shelf Energy Development in the Chukchi and Beaufort Seas, Alaska

The geochemical composition of oils and source rocks can be 

useful for inferring the identity and regional extent of active 

source rocks, which is regarded as a critical step in delineating 

petroleum systems (Peters and others, 2007). More recently, 

Tertiary oils have been demonstrated in the Mackenzie 

Delta of Canada and offshore of the Alaska North Slope, but 

exploration drilling has yet to penetrate a source rock that may 

have generated these oils (Smith, 2007). Study of the sourcerock potential of some of the Tertiary black shales sampled 

during the ACEX indicated that these shales have a fair to 

good source-rock potential (Stein, 2007). 

Recent studies of seismic and borehole data, and results 

from geologic modeling, indicate that good potential source 

rocks in the Lower Tertiary may be widespread across the 

entire Arctic Basin (Mann and others, 2009). The analyses 

of samples from the ACEX cores suggest the potential for 

organic-rich—and at least partly oil-prone—lower Paleogene 

strata in the Canada Basin, and despite the fact that viable 

source rocks are not typically penetrated during drilling 

activities along the Alaska-Canada margins, the potential 

existence of such source rocks is regarded as likely in the 

course of constructing geologic frameworks for the purpose 

of assessing petroleum resources (Houseknecht and Bird, in 

press). Geochemical analyses of oil samples can be helpful 

in studies of paleogeographic settings and reconstructions 

of tectonic history, as chemical constituents within these 

samples retain information about the depositional setting 

and paleogeography of the source rock (Peters and others, 

2008). The model of possibly widespread Tertiary oils in 

the high Arctic was included in the recent U.S. Geological 

Survey Circum-Arctic Resource Appraisal (Bird and 

Houseknecht, in press; Houseknecht and Bird, in press). Many 

oil accumulations identified within Arctic Alaska petroleum 

systems appear to be mixtures of oil expelled from two 

or more petroleum source rocks (Peters and others, 2006; 

Houseknecht and Bird, in press). The character of the source 

rock systems is documented for the heavily explored area 

of the Arctic Alaska province, but in less explored areas, the 

source-rock quality is poorly known because of limited data 

(Houseknecht and Bird, in press). Other recent studies have 

focused on refining the understanding of petroleum systems in 

the adjacent Mackenzie Delta and Canadian Bent Horn Basin 

areas (Obermajer and others, 2010). 

Geophysical Data 

Geophysical information, including seismic, gravity, 

and magnetic surveys, is key to interpreting the geologic 

framework and provides underpinning to studies of energy 

resources. The Bureau of Ocean Energy Management, 

Regulation and Enforcement (BOEMRE) has acquired 

approximately 90 percent of the data collected by industry 

in the Arctic OCS, but Alaska remains a largely frontier area 

with limited data coverage, a fact that necessitates acquisition 

of as much additional data as is feasible (Dellagiarino and 

Maloney, 2010). Seismic surveys can be characterized by 

a number of criteria including: the type of data collected, 

such as two-dimensional (2-D), three-dimensional (3-D), 

or high-resolution; the timing of the surveys, such as prelease or post-lease; the acoustic sound source, such as an air 

gun, water gun, sparker, pinger, or other source (Minerals 

Management Service and National Oceanic and Atmospheric 

Administration, 2007). The specific type of geophysical 

equipment used in data collection depends on the environment 

of deployment. For example, ocean-bottom cable seismic 

surveys are possible in the Beaufort Sea, but they are not 

anticipated to be used in the Chukchi OCS because of its 

greater water depths, as much as 12,500 ft (3,800 m) in parts 

of the planning area, and the greater efficiency of streamer 

operations in these conditions (Minerals Management Service 

and National Oceanic and Atmospheric Administration, 2007). 

Both 2-D and 3-D seismic surveys are the primary tools 

of oil and gas exploration, because they enable geologists 

and geophysicists to image, map, and interpret subsurface 

structures, identify favorable conditions for the entrapment 

of hydrocarbons, and optimally locate exploration and 

development wells for the purposes of maximizing production 

volumes (Minerals Management Service, 2009). These types 

of data are useful for basin analysis studies of petroleum 

systems concerning source rock maturation, hydrocarbon 

migration and trapping processes, and estimating in advance 

of drilling the potential magnitude and extent of overpressured 

zones in the subsurface (Huffman, 2002). 

Public domain inventories of 2-D seismic data are 

available for onshore and offshore Alaska North Slope in 

the Chukchi Sea and Beaufort Sea planning areas (fig. 2–1). 

A large percentage of the geophysical data in the BOEMRE 

inventory is 2-D common depth point data collected along 

a survey line (table 2–1; Dellagiarino and Maloney, 2010). 

The BOEMRE does not perform any direct geological and 

geophysical (G&G) data-collection activities, but does issue 

permits to industry for collecting pre-lease G&G data. Data 

from pre-lease permits constitute approximately 90 percent 

of the BOEMRE database (Dellagiarino and Maloney, 2010). 

Regulations, promulgated in 1976, require that all pre-lease 

G&G information be held proprietary for 25 years, and then 

be released to the public (Dellagiarino and Maloney, 2010). 

Lessees and operators in turn are required by regulations to 

provide data from their leases to the BOEMRE (Dellagiarino 

and Maloney, 2010). 
Chapter 2

Geological Context 17

tac11-5179_fig02-01

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Figure 2–1. Map compilation showing transects (colored lines) of individual 2-D seismic surveys of the Alaska North Slope and 

offshore. The line colors correspond to different seismic datasets. The seismic data from these transects are publicly available. 

More information on these surveys, and a corresponding map for the spatial distribution of commercially available 2-D and 3-D 

seismic data, are available from State of Alaska (2008a). 

Table 2–1. Summary of geological and geophysical data acquisition by 

data type and region, fiscal years 1968–2008. 

[Modified from Dellagiarino and Maloney (2010; table 4) and G. Dellagiarino and 

S. Banet (BOEMRE, written commun., 2011). 3-D seismic: Outer Continental Shelf 

(OCS) blocks equivalent]

Region 2-D seismic 

(line miles)

High 

resolution 

(line miles)

Gravity and 

magnetics 

(line miles)

3-D 

seismic

Alaska (total)

Beaufort

Chukchi

472,460

158,066

194,938

59,855

2,386

4,620

372,764

29,748

87,433

291

63

226

Atlantic 213,936 49,509 15,783 0

Gulf of Mexico 1,396,174 145,768 669,413 91,113

Pacific 132,841 30,582 110,150 52

1

Total 2-D seismic data in the BOEMRE inventory for the Beaufort and Chukchi 

OCS areas are 70,000 and 111,000 line miles, respectively (see Dellagiarino and 

Maloney, 2010; their table 1), which includes data from other activities, such as 

scientific research. 
18 An Evaluation of the Science Needs to Inform Decisions on Outer Continental Shelf Energy Development in the Chukchi and Beaufort Seas, Alaska

Recent acquisition and analysis of 2-D seismic data 

have furthered the knowledge of the stratigraphic correlations 

within the Chukchi Shelf area (Dinkelman and others, 

2008). High-resolution 2-D seismic data can augment the 

understanding of areas mapped with low-resolution seismic 

data. For example, low-resolution seismic data can be 

helpful in identifying and mapping the extent of clinoform 

depositional sequences, but a higher resolution approach 

is needed for identifying components of aggradational 

trajectories and interpreting the character of associated 

sequence boundaries and lowstand deposits (Houseknecht 

and others, 2009). The UNCLOS 2-D seismic data collected 

during the past few years have significantly greater resolution 

than previously available data. Already, we are recognizing 

stratigraphic and structural features—even beneath the 

Beaufort Shelf and slope—that have not been known 

previously (D.W. Houseknecht, U.S. Geological Survey, 

written commun., 2011). As these data (which cover a tiny 

fraction of the Canada Basin and its margins) become public, 

there will be significant revision of geologic knowledge, 

even in parts of the Arctic considered relatively well known. 

While assembling the geologic map of Arctic sedimentary 

successions, Grantz and others (2010) acknowledged that 

data on the subsurface geology of the Arctic region, seismic 

reflection and refraction data in particular, are insufficient to 

ensure that the identification of all sedimentary successions 

of the region are of sufficient size and character to be of 

interest for commercial hydrocarbon exploration. Despite this 

limitation, the authors assert that perhaps no more than a few 

successions were omitted in their synthesis. 

An increasing percentage of geophysical information 

acquired in the BOEMRE Inventory across all OCS regions 

is 3-D seismic data (Dellagiarino and Maloney, 2010). The 

evolution of 3-D seismic technology enables a more accurate 

portrayal of subsurface structure and stratigraphy, and can 

reveal information about fluids within the subsurface. A newer 

form of information processing is Amplitude Variation with 

Offset, and a new type of data acquisition is 2-D or 3-D Four 

component (4-C), which involves the recording of marine 

seismic data with ocean bottom seismometers on the sea floor 

(Dellagiarino and Maloney, 2010). Data from 3-D seismic 

surveys are available in commercial inventories; no data 

currently are available in the public domain (State of Alaska, 

2008a). For example, the recently collected 3-D seismic data 

on the Alaska North Slope and on the Chukchi Shelf are not 

available in the public domain, and so are not used to refine 

public knowledge of geology and petroleum potential. The 

growing need and utility of these 3-D seismic data give rise 

to an important knowledge gap. There is a disparity in the 

commercially available (proprietary) data relative to publicly 

available data (State of Alaska, 2008a).

Gravity and magnetic data, collectively referred to as 

potential fields data, have been collected in Alaska for more 

than 50 years, and a number of these datasets are available 

in the public domain (State of Alaska, 2008b). Gravity and 

magnetic data can be used to interpret regional geologic 

structures and trends, which have implications for oil and 

gas exploration and evaluation (Saltus and others, 2006). In 

particular, modern gravity and magnetic surveys typically 

contain short-wavelength data that, when processed using 

mathematical filters, can highlight shallow geologic features 

and trends in subsurface strata (Saltus and others, 2006). 

Gravity surveys measure the Earth’s gravitational field at a 

series of locations over an area of interest (Dellagiarino and 

Maloney, 2010). The objective is to map density variations 

that may indicate different rock types, and the resulting gravity 

data typically are displayed as anomaly maps. Magnetic 

surveys measure components of the magnetic field at a 

series of locations over an area of interest to locate magnetic 

anomalies or to determine depth to basement (Dellagiarino and 

Maloney, 2010).

Despite the long history of data acquisition, there 

are gaps in data coverage across the State. That said, the 

existing network of gravity and magnetic data is sufficient 

to define regional anomalies and allows for high-resolution 

interpretations along major transportation corridors and 

in areas that have been heavily explored for energy and 

minerals resources (State of Alaska, 2008b). The collection 

of detailed, high-resolution aeromagnetic and gravity data 

spanning the entire North Slope and the integration of these 

data with existing regional seismic information is regarded as 

one of the key challenges for future geophysical work on the 

Alaska North Slope (Saltus and others, 2006). For example, 

aeromagnetic and gravity data in the western North Slope are 

sparse, but the regional compilations suggest that the North 

Slope magnetic high may connect to the geophysical anomaly 

underlying the Hanna Trough, a major tectonic element in the 

Chukchi Sea (Saltus and others, 2006). Greater availability of 

these data in the western North Slope would enable the testing 

of a hypothesis developed by Sherwood and others (2002) 

regarding the existence of a connection between the Devonian 

and later rifting of the Hanna Trough and tectonic events 

associated with the Ellesmerian depositional sequence beneath 

the North Slope (Saltus and others, 2006). 

 Systematic gravity data covering the entire Arctic Ocean 

are important for global gravity field models and large-scale 

geological and plate tectonic studies (Forsberg and Kenyon, 

2004). Previously, there were “polar gaps” in gravity field 

data collected by satellites. To address this knowledge gap, 

an international initiative known as the Arctic Gravity Project 

(ArcGP) was undertaken. This project, completed in 2002, 

culminated in the compilation of a publicly available set 

of gravity data on a 5 × 5 ft grid of the entire Arctic region 
Chapter 2

Geological Context 19

north of 64°N (Forsberg and Kenyon, 2004). Recently, a new 

method of gravity inversion with an embedded lithosphere 

thermal gravity anomaly correction has been applied to 

the ArcGP data with the aim of testing different plate 

reconstruction scenarios in an attempt to better constrain the 

plate tectonic history of the Amerasia Basin (Alvey and others, 

2008). More recently, a new detailed marine gravity field for 

the Arctic Ocean has been derived solely from satellite data—

ARCtic Satellite-only (ARCS) marine gravity field—which 

has increased the sensitivity to subtle perturbations in the 

gravitational field (McAdoo and others, 2008). The greater 

sensitivity of this new field, evident in the revelation of gravity 

lineations and tectonic fabric, may ultimately prove useful 

in constraining tectonic models for complex terranes such as 

the Amerasia Basin (McAdoo and others, 2008). At the time 

of their study, the ARCS coverage was limited to all Arctic 

areas south of 86°N, but the authors noted plans to augment 

the coverage with additional satellite data, thus extending 

coverage northward to 88°N (McAdoo and others, 2008).

Generally, the need for greater availability and density of 

geophysical data to provide comprehensive Arctic coverage 

and to address gaps specifically on the Alaska North Slope 

and offshore is echoed in the recent U.S. Arctic Research 

Commission (2010) report. To address these gaps, the U.S. 

Arctic Research Commission (2010) recommended that an 

Arctic resource assessment and Earth science research plan 

should include activities to address the major remaining 

geographic and geophysical “unknowns” of the Arctic region, 

such as the geology and tectonic history of the Arctic Ocean 

and the Bering Sea.

2.01. Recommendation: Much of the publicly available seismic data for the Arctic is 2-D and of older vintage. Additionally, Arctic 

seismic data are available at densities (number of track lines per square mile) lower than other offshore areas, such as the Gulf of 

Mexico. These older vintage data retain value for delineating geological relations, but there is a growing need for high-resolution and 

3-D seismic data to better constrain these relationships. 

Recent international meetings and working groups have determined that a better understanding of the geologic and plate tectonic 

history of the Arctic, especially the Amerasian Basin is needed, because the “age and direction(s) of rifting that formed the basin 

have far-reaching implications for the origin of its broad continental shelves, their oil and gas potential, and for claims to extend 

the Outer Continental Shelf limits under Article 76 of the United Nations Convention on Law of the Sea” (Miller and others, 2010). 

Recent scientific drilling activities (ACEX) have yielded information facilitating a better understanding of the tectonic history of the 

Arctic. Further activities in targeted areas of the Arctic Ocean are needed to enhance our understanding, and could supply scientific 

information needed to address a host of multidisciplinary studies. 

Structural and stratigraphic investigations of the continental margins constitute a topic for which Federal research could play a critical 

part. All exploration to date has occurred on the continental shelves, where industry’s most immediate interests lie. Meanwhile, 

tectonic and marine research has largely focused on the deep Arctic Basin, where current industry interest is minimal. Very few studies 

have been completed to date that bridge this gap. 

In the rapidly changing Arctic data environment, improved assessment methodology is needed to accommodate rapid and efficient 

updates of resource estimates based on the availability of new data. Similarly, activities devoted to more rigorous application of 

analog information to inform assessment methodologies should be researched, developed, and implemented.

2.01. Finding: There has been a concerted effort over the last decade to better characterize Arctic geology through a combination 

of activities, including the collection of geophysical data, mapping the offshore, and successfully completing the first Arctic research 

drilling expedition. This knowledge base has enhanced our understanding of the tectonic and climatic history of the Arctic system, 

including carbon cycling, while providing insight into delineating Arctic petroleum systems. 

Inventories of geophysical information exist in the public and commercial domains, including 2-D and 3-D seismic, gravity, and 

aeromagnetic data. Data from previous acquisition enable the synthesis of geologic frameworks as a basis for characterizing and 

delineating petroleum systems, estimating undiscovered resource endowments, and characterizing subsurface pressure-temperature 

conditions in these settings. 
20 An Evaluation of the Science Needs to Inform Decisions on Outer Continental Shelf Energy Development in the Chukchi and Beaufort Seas, Alaska

Overview of Exploration and 

Development Activities

Beaufort Sea Planning Area 

The Beaufort Sea planning area shares many geologic 

similarities with the Alaska North Slope (Minerals 

Management Service, 2006b), but also includes geological 

elements that are strikingly different (Houseknecht and Bird, 

in press). Drilling in the Beaufort Sea OCS commenced in 

1981, and through 1989, 20 wells had been drilled (Thomas 

and others, 2009). Depending on water depth, the OCS 

exploration wells are drilled from either an artificial island 

or large, heavy, usually bottom-anchored drilling structures. 

The first OCS oil discovery was Tern (Liberty) in 1983, 

followed by Seal/Northstar in 1984, Hammerhead in 1985, 

and Sandpiper in 1986. The largest oil discovery to date in 

the Beaufort OCS is the Kuvlum field, discovered in 1993, 

with estimated technically recoverable resources on the order 

of 400 million barrels of oil (Thomas and others, 2009). 

Water depths range from as little as 21 ft (6.4 m) at Liberty 

to as much as 103 ft (31.4 m) at Hammerhead (Thomas and 

others, 2009). These depth variations dictate the type of 

basic exploration drilling structure to be used and the type 

of production facility that would need to be built (Thomas 

and others, 2009). Northstar is located offshore in State of 

Alaska and Federal waters of the Beaufort Sea and is the first 

field to produce from Federal waters: development is from a 

totally contained offshore island and connected to shore by the 

first subsea pipeline on the Alaska North Slope (Thomas and 

others, 2009). Oil has been produced from the Northstar unit 

since 2001 (table 2–2; Bureau of Ocean Energy Management, 

Regulation and Enforcement, 2011). The onshore Alpine 

field in the Colville River Unit and the offshore Northstar 

field in the Beaufort Sea are recent examples of stand-alone 

fields that have been developed using advanced technology 

for drilling and production, while simultaneously reducing 

the development footprint (Thomas and others, 2009). The 

emerging development of the Liberty field through the use of 

directional drilling from onshore (BP Exploration (Alaska), 

Inc., 2007) is another example of the evolution in industry 

practices with respect to Arctic oil and gas development 

through incorporation of recent technological advances such 

as ultra-extended-reach drilling.

Table 2–2. Annual production totals from the Northstar Project in the Beaufort Sea. 

[Source: BOEMRE, “Production Statistics for the Northstar Project,” accessed March 9, 2011, at http://alaska.boemre.gov/fo/

northstar/ns_production.pdf. Total Unitized Production is the volume of production from the entire unit, both from State and 

Federal leases. The State leases are allocated 82.160 percent of the total unitized production and the Federal leases are allocated 

the remaining 17.840 percent. BBLS, Stock Tank Barrels of Oil at Standard Conditions of 14.73 pounds per square inch absolute 

and 60 degrees Fahrenheit; N/A, not applicable]

Year

Total unitized yearly 

production volume 

(BBLS)

Total unitized average 

daily production rate 

(BBLS/day)

Yearly production 

volume from

Federal leases

(BBLS)

Average daily 

production from 

Federal leases

(BBLS/day)

2001 1,256,883 20,417 225,834 3,642

2002 17,902,989 49,049 3,193,869 8,750

2003 22,970,112 62,932 4,097,868 11,227

2004 25,079,017 68,522 4,474,097 12,224

2005 22,421,483 61,429 3,999,993 10,959

2006 18,810,628 51,539 3,355,816 9,194

2007 13,877,290 39,877 2,475,709 7,114

2008 11,136,749 30,428 1,986,796 5,428

2009 7,981,210 22,482 1,423,848 4,011

2010 6,133,516 18,419 1,094,219 3,286

Totals 147,578,877 N/A 26,328,072 N/A
Chapter 2

Geological Context 21

Chukchi Sea Planning Area

Five exploratory wells were drilled on the Chukchi Shelf 

during 1989–91: Klondike, Burger, Popcorn, Crackerjack, and 

Diamond (Minerals Management Service, 2006c). The Burger 

well was drilled to a measured depth of 8,202 ft (2,500 m), 

and two gas-bearing sandstones (Craig and Sherwood, 

2004) were found. The Burger prospect, which has an area 

of closure exceeding 189,800 acres (760 km2), was mapped 

using conventional 2-D seismic data as part of preparations 

for Lease Sale 109 in May 1988 (Craig and Sherwood, 2004). 

The information from these wells, in conjunction with regional 

seismic lines and other data, can be synthesized to yield a 

regional picture of the geologic framework, as shown in the 

Chukchi Shelf well correlation (fig. 2–2). This cross section 

of the geologic framework was updated using paleontologic 

interpretations by Mickey and others (2006) to refine the 

interpretations of the subsurface geology and well correlations. 

For example, the new micropaleontology data led to the 

exclusion of the Jurassic-aged unconformity from the Burger 

well stratigraphic column (Sherwood, 2006). 

The resulting geologic framework from the synthesis of 

these data is useful in understanding the window for petroleum 

generation and occurrence and a picture of the potential 

subsurface pressures and temperatures that may be detected 

at depth. As can be seen in the updated geologic correlation, 

the incorporation of these data are useful for delineating the 

depths to the potential over pressured zone, the top of the oil 

generation zone, and the deepest reservoir of oil within the 

subsurface geology underlying the Chukchi Sea (Sherwood, 

2006). In an analogous study, mud weight and pore pressure 

data from 250 exploration wells were used to delineate the 

fluid pressure regime in the Beaufort-Mackenzie Basin (Chen 

and others, 2010), and for identifying areas of potential over 

pressure. These data, in conjunction with studies of organic 

geochemistry and basin thermal structure in the BeaufortMackenzie Basin, have led to the development of new ideas 

for play types and petroleum system models (Chen and others, 

2010). 

These syntheses of geologic information are useful for 

understanding the driving forces for fluid flow in sedimentary 

basins, which can help in understanding the occurrence and 

distribution of oil and gas resources and fluid migration 

pathways (Peters and others, 2006; Chen and others, 2010). 

This information also can provide further insight into the 

total pressure conditions that may be found during drilling 

(Akhter and others, 2009), and thus be useful for guiding the 

exploration process (Huffman, 2002), as well as evaluating the 

potential risk for a blowout or loss of well control in advance 

of drilling operations. For example, one of the working papers 

from the National Commission on the BP Deepwater Horizon

Oil Spill and Offshore Drilling mentioned that: 

“The Deepwater Horizon containment efforts 

were complicated immensely by the depth of the 

wellhead and the high well pressures encountered 

at the Macondo well. Wells in both the Chukchi and 

the Beaufort Seas would be in far shallower water, 

which could make it easier to contain a blowout or 

riser leak. Shell asserts that well pressures in the 

Chukchi and Beaufort Seas would be approximately 

one-third to one-half of the pressures faced by BP at 

the Macondo well” (National Commission on the BP 

Deepwater Horizon Oil Spill and Offshore Drilling, 

2011).

Although the depth of water in which drilling would 

be conducted and the subsurface pressure detected by wells 

drilled in the Arctic OCS would be substantially lower than 

those at Macondo, it is important to remember that a potential 

spill offshore poses unique challenges for spill response in 

terms of how to access spilled oil when the area may have iced 

over, or be in seasonal slushy conditions, among other factors 

(National Commission on the BP Deepwater Horizon Oil Spill 

and Offshore Drilling, 2011).

Potential for Additions to Global Supply from 

Northern Latitudes

Planning-Area Based

Resource assessments can be useful at various scales, 

such as for OCS programmatic planning, analyses of proposed 

legislation, or estimating effects on investment and revenues 

from various leasing and regulatory policies, like proposals 

for royalty relief (Minerals Management Service, 2006a). The 

BOEMRE routinely updates and revises its resource estimates 

to reflect changing conditions and knowledge. The BOEMRE 

conducts comprehensive national assessments of the 

undiscovered oil and gas resources on the OCS at least every 

5 years. These periodic updates are necessary to incorporate 

changes in technology that occur with time, geological 

and geophysical data available to assessors, and geologic 

interpretations and models, which can lead to higher or 

lower estimates when the assessments are updated (Minerals 

Management Service, 2006a). The following excerpt, from the 

2006 Report to Congress regarding a comprehensive inventory 

of U.S. OCS oil and natural gas resources, provides an 
22 An Evaluation of the Science Needs to Inform Decisions on Outer Continental Shelf Energy Development in the Chukchi and Beaufort Seas, Alaska Figure 2–2. tac11-5179_fig02-02 Geologic cross-section showing regional correlations among wells from the Chukchi Shelf and western Arctic Alaska. This cross-section depicts major stratigraphic relations and delineates approximate extent of oil generation windows and over pressured zones. From a 2009 well correlation update (K. Sherwood, Bureau of Ocean Energy Management , Regulation and Enforcement, written commun., 2011), and modified from Sherwood (2006), including new paleontologic interpretations published by Mickey and others (2006).
Chapter 2

Geological Context 23

overview of the utility of resource assessments for informing 

decisions across sectors (public and private) and at varying 

scales: 

“Regional assessments may be prepared simply to 

develop an inventory of potential oil and natural 

gas resources as part of an evaluation of future 

supply options. Assessments may be undertaken 

to analyze the relative merits of oil and gas 

development proposals and alternatives versus other 

competing uses. Resource estimates provide critical 

input to decision makers regarding the virtues of 

various policy alternatives. Detailed site-specific 

assessments provide data essential for valuing 

Federal lands prior to leasing or analyzing industry 

exploration or development proposals. Large 

corporations and financial institutions use resource 

estimates for long-term planning, the analysis of 

investment options and as a guide in analyzing the 

future health of the oil and gas industry. Exploration 

companies use resource assessments to design 

exploration strategies and target expenditures. 

Increasingly, resource estimates are being used by 

the Administration, Congress, and the public to 

provide objective statements of how much oil and 

natural gas will be available for future domestic 

consumption” (Minerals Management Service, 

2006a).

An assessment of the undiscovered oil and gas 

resources for the Alaska Federal offshore was completed 

in 2006 (Minerals Management Service, 2006d; fig. 2–3). 

Undiscovered, economically recoverable resources (table 2–3) 

consider costs associated with development and production. 

The economic estimates give the greatest insight into the 

areas that are most likely to be of interest for leasing and 

development in the near term, that is, the period covered by 

the next 5-year program (Minerals Management Service, 

2006f). Often, these estimates are reported along with the 

basic economic assumptions, most commonly price (Minerals 

Management Service, 2006f). 

Despite the inherent risk and uncertainty underlying 

estimates of undiscovered resource endowments, results from 

resource assessments frequently are used and reported in a 

manner that underemphasizes the inherent uncertainty, as users 

typically focus on the mean value (Minerals Management 

Service, 2006a). Two important points emerged from analysis 

of mean resource estimates (fig. 2–3). First, the increase in 

geologic knowledge and advances in technology and industry 

practice with time do not necessarily translate to increased 

estimates of undiscovered, technically recoverable resources 

with time. This point is evident in the mean undiscovered, 

technically recoverable natural gas resource endowment 

estimate for the Beaufort Sea OCS (fig. 2–3). A 2010 

downward revision of the resource endowment, as compared 

to the previous assessment in 2002, also occurred for the 

undiscovered, technically recoverable oil and gas resources for 

the National Petroleum Reserve in Alaska (Houseknecht and 

others, 2010). In contrast, the mean estimate for undiscovered, 

technically recoverable natural gas resource endowment 

for the Chukchi Sea OCS was revised upward from 2000 

to the 2006 assessment (fig. 2–3). Second, the F05 and F95 

values plotted about the mean estimates from the 2006 OCS 

assessment (fig. 2–3) can be considered as an indication of 

the uncertainty associated with the mean resource estimate. 

Much of this statistical uncertainty can be attributed to the fact 

that Arctic Alaska is not a mature petroleum province from 

an exploration perspective. Considering these points, it is 

important to note the following: 

“All resource estimates are subject to continuing 

revision as undiscovered resources are converted 

to reserves and reserves to production and as 

improvements in data and assessment methods 

occur. The assessment results do not imply a 

rate of discovery or a likelihood of discovery 

and production within a specific time frame. 

However, uncertainty surrounding the estimates 

decreases as the asset progresses through this cycle. 

Resource estimates should be viewed from the 

perspective of the point in time the assessment was 

performed—based on the data, information, and 

methodology available at that time. In general, risk 

and uncertainty in estimates of undiscovered oil and 

natural gas are greatest for frontier areas that have 

had little or no past exploratory effort” (Minerals 

Management Service, 2006a).

The Beaufort Sea assessment province extends from 

the 3-mi limit of Alaska State waters to the 1,640 ft (500 m) 

isobath (Minerals Management Service, 2006b). Of the area 

of the Beaufort Sea OCS covered by the assessment province, 

all the estimated undiscovered, technically recoverable oil and 

gas resources are considered to be within 650 ft (200 m) water 

depth (Minerals Management Service, 2006e). Although water 

depths in the Chukchi Sea planning area can be as high as 

12,500 ft (3,800 m) (Minerals Management Service, 2006c), 

all (100 percent) of the undiscovered, technically recoverable 

oil and gas resources estimated for the area are considered to 

be within 650 ft (200 m) water depth (Minerals Management 

Service, 2006e). For comparison with the other OCS regions, 

the proportions of the 2006 assessment mean estimates of 

undiscovered, technically recoverable resources considered 

to be within the same water depth range of 0 to 650 ft (0 to 

200 m) are: Atlantic (39 percent oil and 38 percent gas), Gulf 

of Mexico (8.5 percent oil and 37 percent gas), and Pacific 

(30 percent oil and 31 percent gas) (Minerals Management 

Service, 2006e). Within each OCS region, these proportions 

vary by planning area. 
24 An Evaluation of the Science Needs to Inform Decisions on Outer Continental Shelf Energy Development in the Chukchi and Beaufort Seas, Alaska

tac11-5179_fig02-03

0

10

20

30

40

Beaufort Sea OCS Chukchi Sea OCS

F95

F05

Assessment Year

1995

2000

2006

F95

F05

A B

0

50

100

150

200

250

Beaufort Sea OCS Chukchi Sea OCS

Assessment Year

1995

2000

2006

F95

F05

F95

F05

Undiscovered Oil(billion barrels)

Undiscovered Natural Gas 

(trillion cubic feet)

Figure 2–3. Comparison of mean estimates (solid colored bars) for undiscovered, technically recoverable resources for the 

assessment provinces within the Beaufort and Chukchi Sea OCS planning areas for (A) oil and (B) natural gas. Undiscovered oil 

estimates include oil plus natural gas liquids (condensate). The 2006 assessment F95 and F05 values, corresponding to a 95-percent 

probability (a 19 in 20 chance) and a 5-percent probability (a 1 in 20 chance), respectively, of more than these amounts being present, 

are plotted as an indication of uncertainty about the mean. Modified from Minerals Management Service (2006d, 2006f).

Table 2–3. 2006 National Assessment—Arctic Outer Continental Shelf, Arctic Subregion, Chukchi and Beaufort Shelves. 

[Modified from Minerals Management Service (2006b, 2006c). F95 and F05 values correspond to a 95-percent probability (a 19 in 20 chance) and a 

5-percent probability (a 1 in 20 chance). BBO, billion barrels oil; TCFG, trillion cubic feet gas; BBOE, billion barrels of oil equivalent; bbl, barrel; mcfg, 

thousand cubic feet gas]

Risked, undiscovered, technically recoverable oil and gas resources

Oil and condensate (BBO) Gas (TCFG) BOE (BBOE)

F95 Mean F05 F95 Mean F05 F95 Mean F05

Chukchi Shelf 2.32 15.38 40.08 10.32 76.77 209.53 4.15 29.04 77.36

Beaufort Shelf 0.41 8.22 23.24 0.65 27.65 72.18 0.53 13.14 36.08

Risked, undiscovered, economically recoverable oil and gas

($80/bbl, $12.10/mcfg)

Oil and condensate (BBO) Gas (TCFG) BOE (BBOE)

F95 Mean F05 F95 Mean F05 F95 Mean F05

Chukchi Shelf 1.52 12.00 32.66 6.01 54.44 153.70 2.59 21.68 60.01

Beaufort Shelf 0.34 6.92 21.17 0.54 19.97 59.38 0.44 10.47 31.74
Chapter 2

Geological Context 25

is regarded as one of the most important basins for future 

petroleum supply in North America (Chen and others, 2010). 

The findings from the CARA are significant because they 

underscore the need for continuing international cooperation 

and collaboration as a component of overall planning with 

respect to oil and gas exploration and development in the 

Arctic. 

The Arctic could contain some of the largest gas 

accumulations on Earth; however, the probability of finding 

another oil accumulation comparable to Prudhoe Bay is 

low (Gautier and others, 2009b). This result is significant 

in understanding potential development scenarios. As 

mentioned earlier, large oil and natural gas fields are 

particularly important with respect to future oil and natural 

gas development in the Arctic because the development 

costs in the Arctic are sufficiently high that large fields are 

necessary to pay for the required infrastructure (Budzik, 

2009). 

The estimated resources in the CARA were considered 

recoverable without regard to the possible presence of 

sea ice, and without reference to costs of exploration and 

development. That said, given the relatively higher costs 

associated with Arctic oil and gas extraction activities 

as compared to other regions of the World, the CARA 

study considered only accumulations with recoverable 

hydrocarbon volumes larger than 50 million barrels of 

oil or 300 billion cubic feet of gas (50 million barrels of 

oil equivalent) (Gautier and others, 2009a). Hydrocarbon 

accumulations with less than these threshold volumes were 

excluded from the study, as were unconventional resources, 

such as coalbed methane, gas hydrates, oil shales, and heavy 

oil and tar sands. Gautier and others (2009b) note that these 

estimates are intended as a baseline, given that in many 

study areas, the estimates are based on limited geologic 

information, and that our understanding of these resource 

endowments is certain to change as new data become 

available. For example, there are a number of areas assessed 

in the CARA study for which only seismic data (no wells) 

are available, and other areas that are devoid even of seismic 

data (fig. 2–5).

These 2006 OCS assessment results do not preclude the 

occurrence of oil and gas resources at greater water depths 

within the Beaufort and Chukchi Sea planning areas. In 

delineating the Beaufort Sea province assessment boundary, 

the 1,640 ft (500 m) isobath was adopted as a practical limit 

for petroleum development; beyond this limit, the extreme 

water depths and ice conditions were considered likely 

to preclude exploration and development activities using 

existing technologies (Minerals Management Service, 2006b). 

Similarly, after considering the geology and operational 

adversity of the deep Arctic Ocean environment, the deepwater areas within the Chukchi Sea planning area were 

assessed with negligible technically recoverable oil and 

gas resources (Minerals Management Service, 2006c). All 

technically recoverable oil and gas resources of the Chukchi 

Sea planning area west of Hanna submarine canyon are 

considered to be south of the 328 ft (100 m) isobath; east of 

the canyon, all resources are considered to be south of the 

1,640 ft (500 m) isobath (Minerals Management Service, 

2006c).

Within the Context of Larger Arctic Region—

Circum-Arctic Resource Appraisal (CARA)

Using a probabilistic, geology-based methodology, 

the USGS recently assessed the area north of the Arctic 

Circle and concluded that approximately 30 percent of the 

World’s undiscovered gas and 13 percent of the World’s 

undiscovered oil may occur in that region (fig. 2–4; Bird 

and others, 2008; Gautier and others, 2009a). Most of these 

resources occur offshore under less than 1,640 ft (500 m) of 

water. The deep oceanic basins are regarded as having low 

petroleum potential, whereas the Arctic continental shelves 

comprise one of the World’s largest remaining prospective 

areas for petroleum hydrocarbons (Gautier and others, 2009a). 

In particular, the principal investigators concluded that the 

Chukchi and Beaufort Seas offshore Alaska, along with 

the adjacent areas of the Beaufort-Mackenzie Basin, might 

be the most oil prospective areas north of the Arctic Circle 

(Gautier and others, 2009b). The Beaufort-Mackenzie Basin 
26 An Evaluation of the Science Needs to Inform Decisions on Outer Continental Shelf Energy Development in the Chukchi and Beaufort Seas, Alaska

tac11-5179_fig02-04

A

B

Figure 2–4. Assessment units of the Circum-Arctic Resource Appraisal, color-coded according to the mean 

estimated undiscovered, technically recoverable resources for (A) oil and (B) natural gas. The open rectangles 

denote the approximate location of the Alaska North Slope and Beaufort and Chukchi Seas Outer Continental Shelf 

areas. Modified from Gautier and others (2009a).
Chapter 2

Geological Context 27

tac11-5179_fig02-05

EXPLORATION INTENSITY

Producing fields

Discoveries

Wells

Seismic

No seismic

Area of low petroleum potential

Figure 2–5. Assessment units of the Circum-Arctic Resource Appraisal, color-coded according to Exploration Intensity, 

as given by the highest level of petroleum exploration or development activity attained within an assessment unit. The open 

rectangle denotes the approximate location of the Alaska North Slope and Beaufort and Chukchi Seas Outer Continental Shelf 

areas. Modified from Gautier and others (in press).

More work is needed to better constrain the 

understanding of the occurrence and extent of these 

petroleum systems. Even the Alaska North Slope is not a 

mature petroleum province from an exploration perspective, 

although oil has been produced for decades. Most wells 

drilled to date in the Alaska North Slope, including those in 

State-owned onshore and nearshore Beaufort Sea areas, are 

clustered along the Barrow Arch in a relatively low density of 

approximately one exploration well per 22 mi2 (about 57 km2) 

(Thomas and others, 2009). A more refined understanding 

of the Arctic oil and gas resource endowment will become 

apparent with additional exploration wells (Budzik, 

2009). Most oil development to date has been focused on 

conventional resources, although currently there is a growing 

emphasis on development of oil resources in low permeability 

reservoirs and extraction of heavy oil resources. Additionally, 

currently (2011) there is an emerging focus on the possible 

extraction of oil from source-rock systems. Future changes 

in the availability of infrastructure, such as a gas pipeline, 

could provide the impetus for additional exploration and 

development activities, particularly in areas where resources 

are currently stranded with respect to the market. During 

nearly seven decades of exploration in Arctic Alaska, only a 

few wells in recent years have been drilled with the specific 

objective of evaluating natural gas recovery. In the absence of 

a pipeline to move natural gas from northern Alaska to market, 

gas discoveries have largely been viewed as exploration 

failures and additional exploration drilling in large parts of the 

region has been discouraged. A gas pipeline would not only 

result in production of known gas resources but also would 

stimulate additional exploration in those parts of the region 

that are most underexplored. The associated oil and natural 

gas liquids (condensate) produced in conjunction with these 

resources also would increase oil production, although these 

volumes alone are not expected to be sufficient to extend the 

life of the TAPS (Thomas and others, 2009).

In addition to the interest in the Beaufort and Chukchi 

OCS, the Mackenzie Delta has been an exploration focus 

in Arctic Canada for decades. This interest is anticipated to 

continue despite the fact that commercial production has not 

yet begun (Kumar and others, 2009). As with the Alaska North 

Slope, the construction of pipeline infrastructure is regarded 

as critical to the development of oil and gas resources in 

the Mackenzie Delta–Beaufort Sea Basin, and construction 

can drive expansion into offshore resources of the Beaufort 

Sea (Voutier and others, 2008). Given the interest in the 

Mackenzie Gas Project and in anticipation that the Mackenzie 

Delta–Beaufort Sea region may be on the threshold of a 
28 An Evaluation of the Science Needs to Inform Decisions on Outer Continental Shelf Energy Development in the Chukchi and Beaufort Seas, Alaska

extended period of oil and gas development, a process for 

developing the Beaufort Sea Strategic Regional Plan of Action 

(the Strategic Regional Plan) was launched (Voutier and 

others, 2008). This process culminated in the development of a 

Strategic Plan of Action by a multi-agency stakeholder group 

under the guidance of the Beaufort Sea Strategic Regional 

Plan of Action (2008) Steering Committee. 

In support of these integrated ocean managementplanning efforts, a digital atlas was compiled to bring together 

disparate datasets that illustrate the spatial interdependence 

of natural resources and human activities in oil and gas 

production and other matters (Dubuc and others, 2009). 

There is a continuing need to better integrate and disseminate 

existing data to support these types of multidisciplinary 

analyses while facilitating greater public data access, as 

noted by the National Research Council (1994) and recently 

echoed by Vörösmarty and others (2010). The North Slope 

Science Initiative (NSSI) could provide a similar mechanism 

for coordination, while also leveraging research opportunities 

to address emerging science issues (North Slope Science 

Initiative, 2009) and providing a basis for understanding 

potential effects of oil and gas development in a systematic 

context with other drivers, such as climate change. 

Unconventional Resources

Overview

It is important to consider other energy resources in the 

context of resource development and extraction on the OCS. 

For example, unconventional energy sources, such as coalbed 

methane, gas hydrates, shale gas, tight gas sands, heavy oil, 

and both oil and gas in source rocks, are known to occur. A 

number of these resources are located onshore, nonetheless, 

their potential development may affect the development 

and extraction of resources from the OCS. For example, 

the existence of the heavy oil resources has long been 

recognized in the Arctic (Werner, 1987), and production of 

this resource commenced just last year (Mathews and Young, 

2010). Historically, the discussions of Arctic Alaska resource 

potential have focused on conventional oil resources with less 

attention given to conventional gas and unconventional gas 

and liquid resources (Thomas and others, 2009). However, the 

recent development of shale gas resources in the conterminous 

United States, coupled with estimates of further potential, 

may affect the level of interest in developing natural gas in the 

Arctic (Budzik, 2009). Given this context, continued research 

into unconventional resources is important, among other 

things, as a basis for developing technologies to extract these 

resources safely while minimizing environmental impacts 

(Arctic Monitoring and Assessment Programme, 2007).

In its study of the Cumulative Environmental Effects of 

Oil and Gas Activities on Alaska’s North Slope, the National 

Research Council (2003) used a development scenario, 

focused on oil and gas extraction activities, to evaluate 

potential development effects. The committee noted that other 

resources, including coal, and unconventional resources such 

as coalbed methane, could significantly alter the committee’s 

scenarios. However, the uncertainties associated with 

economic and other factors obscured the capability to predict 

the timing and extent to which these resources might be used 

or when exploration might commence (National Research 

Council, 2003). Since that study, numerous research activities 

have expanded our knowledge of these resources. For 

example, the USGS assessed coalbed methane resources on 

the Alaska North Slope, and estimated a mean undiscovered, 

technically recoverable resource of roughly 18 trillion cubic 

feet of gas (Roberts and others, 2006). A substantial portion 

(more than 80 percent) of this resource is thought to occur 

within the Nanushuk Formation assessment unit, which is 

primarily within the National Petroleum Reserve in Alaska.

In the past year, production of heavy oil has commenced 

(Mathews and Young, 2010). However, the magnitude of the 

contribution from this resource to oil supply over the long 

term remains uncertain. Industry has invested considerable 

money over the years to develop and test technologies 

culminating in production of heavy oil (Triolo and others, 

2005; Mathews and Young, 2010). One of the key factors 

to sustained development is the need for lighter oil to serve 

as a diluent to facilitate transfer through the Trans-Alaska 

Pipeline System. The Energy Information Administration, in 

its Annual Energy Outlook 2010 with projections to 2035, 

noted that the greatest uncertainty regarding Alaska oil 

projections is “...whether the heavy oil deposits located on the 

North Slope, which exceed 20 billion barrels of oil-in-place 

can be produced at recovery rates exceeding more than a few 

percent of the in-place resource” (U.S. Energy Information 

Administration, 2010). 

Given recent advances in the geologic understanding of 

unconventional resources and developments in technology, the 

prospects of these resources contributing to the energy supply 

have improved such that these resources merit consideration 

in updated scenarios of energy resource supply. The U.S. 

Arctic Research Commission (2010) recently determined 

that, because much of the oil, heavy oil, gas, shale gas, gas 

hydrates, coal, and coalbed methane deposits within the U.S. 

Arctic are on Federal lands, further research of these resources 

should be undertaken with industry, the State of Alaska, and 

international partners in producing and consuming countries.
Chapter 2

Geological Context 29

Gas Hydrate Studies: Energy Resources

Gas hydrates (or methane hydrates) are ice-like 

crystalline substances occurring in nature where a solid water 

lattice accommodates gas molecules (primarily methane, the 

major component of natural gas) in a cage-like structure, also 

known as clathrate. The amount of natural gas in methane 

hydrate worldwide is estimated to be far greater than the 

World’s conventional natural gas resources. Gas hydrates 

form under conditions of relatively high pressure and low 

temperatures, such as those in the shallow subsurface under 

many of the oceans, including much of the deepwater OCS. 

Gas hydrates also occur under Arctic permafrost that exists 

onshore in northern Alaska, and the hydrate stability zone 

is expected to extend farther offshore into the Beaufort Sea 

OCS. The BOEMRE has recently identified evidence for the 

existence of hydrates in the Alaska Beaufort continental shelf 

through the analysis of seismic data and LWD (logging while 

drilling) gamma ray and resistivity logs from the Hammerhead 

Number 1 and 2 wells, although the lack of acoustic log 

data from these wells precludes the distinction between free 

gas and gas hydrate (Collett and others, 2011). Scientists 

conducting a sampling cruise aboard the USCGC Healy

as part of the Extended Continental Shelf Project recently 

recovered gas hydrate in piston cores of sediment collected 

from the continental margin in the Beaufort Sea (Gibbons, 

2010). 

Early results from recent Arctic field programs have 

provided important new insights into characterization of 

producibility of gas hydrate reservoirs (Dallimore and Collett, 

2005). Analysis of 3-D seismic data has been useful in 

delineating the lateral extent of gas hydrate accumulations. 

In 2007, a joint effort among BP Exploration (Alaska), the 

U.S. Department of Energy, and the USGS culminated in the 

completion of the Mount Elbert Gas Hydrate Stratigraphic 

Test Well in the Milne Point field on the Alaska North Slope. 

This test used 3-D seismic interpretations and wireline log 

correlations to derive pre-drill estimates of gas hydrate 

occurrence in the surbsurface (Rose and others, 2011). The 

Milne Point 3-D seismic analysis revealed a “patchy” nature 

to the occurrence of gas hydrate in the Eileen accumulations, 

with individual gas hydrate prospects ranging in size from 

about 0.1 to 2.7 mi2 (0.3 to 7.0 km2), indicating that gas 

hydrate accumulations in this setting may be more regionally 

extensive than previously thought. The thickness of these 

accumulations probably is highly variable (Collett and others, 

2011).

In 2008, the USGS completed an assessment of the 

undiscovered, technically recoverable gas resources from 

gas hydrates on the Alaska North Slope (fig. 2–6; Collett 

and others, 2008), the first assessment of its kind. This study 

addressed gas hydrate resources onshore and underlying 

State-owned waters. The USGS estimated a mean technically 

recoverable resource of 85.4 TCF of gas, which accounts for 

approximately 11 percent of the volume of gas within all other 

undiscovered, technically recoverable gas resources estimated 

for the onshore and State waters of the United States. Many 

of the techniques used in this study to delineate the gas 

hydrate occurrences are transferable to studies of gas hydrate 

occurrences in the OCS. 

Although limited data collection now allows some 

gas hydrate accumulations to be considered technically 

recoverable, there remain questions of long-term producibility 

and economic feasibility of these energy resource occurrences 

(Minerals Management Service, 2009). Collett and others 

(2008) highlighted that further research, including longterm production tests, are needed to demonstrate whether or 

not gas hydrates are an economically producible resource. 

A recent study by Osadetz and Chen (2010) refined the 

resource models used by the Geological Survey of Canada to 

re-evaluate the gas hydrate resources in the Canadian Beaufort 

Sea-Mackenzie Delta Basin, and the results of this work 

further underscored the need to study major Arctic deltas and 

continental shelves for characterizing the resource potential of 

these accumulations. 

The Methane Hydrate Research and Development 

Act of 2000, later amended in Section 968 of Public Law 

109-58 (30 U.S.C. 1902–The Energy Policy Act of 2005), 

directs several Federal agencies (led by the Department of 

Energy, and including BOEMRE, USGS, and the Bureau of 

Land Management) to cooperatively engage in gas hydrate 

research and development efforts. In 2010, the NRC evaluated 

the Department of Energy’s Methane Hydrate Research 

and Development Program and concluded that research 

on methane hydrate to date has not revealed technical 

challenges that are insurmountable in the goal to achieve 

commercial production of methane from methane hydrate 

in an economically and environmentally feasible manner. In 

the course of its evaluation, the National Research Council 

(2010) identified areas critical to achieving the Program 

goals—design of production tests, appraisal and mitigation 

of environmental and geohazard issues related to production, 
30 An Evaluation of the Science Needs to Inform Decisions on Outer Continental Shelf Energy Development in the Chukchi and Beaufort Seas, Alaska

and quantification of the resource. Specific National 

Research Council (2010) recommendations pertaining to the 

quantification of the resource include:

“Pilot seismic surveys using existing geophysical 

methods optimized to map and quantify in-place 

methane hydrate accumulations;”

“Improved understanding of in-situ properties of 

sediments containing methane hydrate through 

comprehensive testing (geophysical, geochemical, 

microbiological, geomechanical) of undisturbed 

natural drill cores and synthetic samples;” and

“Consideration of the development of new 

geophysical imaging, processing, and quantification 

techniques, particularly with respect to quantifying 

the in-place resource.”

In recognizing some of these knowledge gaps and 

research needs, the U.S. Arctic Research Commission (2010) 

recommended gas hydrate research (onshore and offshore) as 

one of the areas of emphasis for the Department of Energy’s 

Arctic Energy Office. The U.S. Arctic Research Commission 

(2010) also noted that it may be appropriate to consider 

the inclusion of Arctic mapping and gas hydrates research 

activities within other agencies’ resource assessment and earth 

science program plans. 

Gas Hydrate Studies—Climate Change Linkages 

and Geohazards

In addition to the study of gas hydrates from an energy 

resource perspective, the potential linkages among subsea gas 

hydrates, climate change, and sea-level changes, particularly 

on the Beaufort continental slope, have long been recognized 

(Kayen and Lee, 1991). One of the key research questions 

regarding these linkages is discerning whether gas hydrate 

degassing plays a causative role in global warming, or is 

merely a response to the effects of rapid global warming 

(Ruppel and Pohlman, 2008). The long-term warming may 

lead to dissociation of the gas hydrates, during which gas is 

released. This release of gas can change the physical properties 

of the surrounding sediments and affect infrastructure through 

loss of borehole integrity and (or) regional subsidence (Lee 

and others, 2010). However, most of the scenarios that may 

suggest gas hydrates as a geohazard to traditional hydrocarbon 

infrastructure do not manifest themselves at the time the well 

is being drilled, but rather result as a consequence of the longterm warming of the sediment associated with hydrocarbon 

production (National Research Council, 2010).

The National Research Council (2010) review 

recommended that further studies are required to address the 

processes involved in (1) the transmission of methane from 

tac11-5179_fig02-06

UNITED STATES

CANADA

Umiat

Barrow

Atqasuk

Nuiqsut Kaktovik Deadhorse

Wainwright

Point 

Hope

Prudhoe

Bay

Cape 

Lisburne

Point 

Lay

Icy 

Cape

Point 

Barrow

Smith

Bay

Harrison

Bay Camden

Bay

Alaska State waters

(outer limit)

Brooks Range

CHUKCHI 

SEA

ARCTIC OCEAN

BEAUFORT SEA

National Petroleum 

Reserve—Alaska (boundary)

Arctic National 

Wildlife Refuge (boundary)

Trans-Alaska

Pipeline System

N o r t h ern A l a s k a 

Gas Hyd r a t e T P S

Northern Alaska Gas Hydrate TPS

EXPLANATION

Limit of gas hydrate stability zone

170° 160° 150° 140°

68°

70°

0 50 100 MILES

Area of

map

ALASKA

Figure 2–6. Map showing extent of the Northern Alaska Gas Hydrate Total Petroleum System (TPS) (shaded in tan), and the 

limit of gas hydrate stability zone in northern Alaska (red outline). Collett and others (2008) used this TPS as a basis for the first 

assessment of undiscovered, technically recoverable gas-hydrate resources beneath the Alaska North Slope and State-owned 

waters. Modified from Collett and others (2008).
Chapter 2

Geological Context 31

the subsurface through the methane-hydrate stability zone 

to the surface and (2) the subsequent fate of the released 

methane. Further, these studies should focus on degassing 

processes and potentially enhanced environmental effects from 

commercial production of methane from methane hydrate 

and from methane hydrate associated with other oil and gas 

developments (National Research Council, 2010). Recent 

study of gas venting on the Arctic seafloor focused on pingolike-features (PLFs), which may be a direct result of gas 

hydrate decomposition, on the Beaufort Sea Shelf (Paull and 

others, 2007). The investigators recovered vibracore samples 

of sediments containing elevated methane concentrations from 

these PLFs (Paull and others, 2007). In a September 2009 

study expedition, Methane in the Arctic Shelf/Slope, aboard 

the USCGC Polar Sea, collected sediments, water column, 

and atmospheric samples to improve the understanding of the 

fate and cycling of methane in these Arctic systems (Coffin 

and others, 2010). Coffin and others (2010) noted that a lack 

of data, “...particularly modern seismic, bathymetry and other 

remote sensing surveys across the U.S. Beaufort Shelf...” 

was one of the challenges to understanding the occurrence 

and fate of gas hydrates in these settings. These are important 

knowledge gaps to address, because despite the fact that gas 

hydrates typically are perceived as posing geohazard risks to 

industry, little documentation exists to constrain the extent and 

magnitude of these potential risks (National Research Council, 

2010). At present, industry practice is to avoid methane 

hydrate-bearing areas during drilling and production for 

conventional oil and gas resources, but this avoidance will not 

be practical if gas hydrates are the production target (National 

Research Council, 2010).

With respect to potential commercial production 

of natural gas from gas hydrate, the National Research 

Council (2010) assigned particular importance to the need 

for better understanding of the potential environmental 

impacts of methane hydrate degassing. The seafloor hazards 

(“geohazards”) resulting from methane hydrate dissociation as 

a result of oil and gas drilling and production are of specific 

importance. To that end, the National Research Council (2010) 

recommended that in addition to further characterization 

and quantification of gas hydrates, there should be research 

activities focused on designing production tests and appraising 

and mitigating environmental and geohazard issues related to 

production.

2.02. Finding: There have been significant advances in characterizing and understanding the geologic context of unconventional resources in the 

Alaska North Slope over the past decade (2000–2010). The potential viability of these resources may affect development scenarios and construction 

of infrastructure. Because potential extraction and transportation of resources from the OCS will require considerable additions to current 

infrastructure, an understanding of the potential role of these unconventional resources in the future energy supply is needed for development of 

holistic scenarios to inform resource management and infrastructure construction decisions.

2.02. Recommendation: Unconventional resources may directly and (or) indirectly affect potential scenarios for development within the 

Beaufort Sea and Chukchi Sea planning areas. Thus, further study of these energy resources (especially coalbed methane, heavy oil, oil and gas 

resources in source-rock systems, tight gas, and gas hydrates) are needed to better understand the potential of these resources to contribute to 

energy supply and to inform potential development scenarios. 

Gas resources in tight reservoirs are known to occur beneath the Alaska North Slope and likely occur beneath the OCS areas as well. Further 

research characterizing these resources, including petrophysical investigations of source-rock systems, should be carried out to better understand the 

petroleum systems of the Arctic and to assess recoverable continuous-type resources, such as oil and gas resources in shale and tight sands. 

Further research is needed to characterize gas hydrates in terms of an energy resource, as well as connections with climate change (and potential 

contribution to the greenhouse gas cycle) and geohazard issues. In particular, an improved understanding of gas hydrate occurrence, quantity, and 

stability in the Beaufort OCS planning area is needed, to inform energy resource decisions and potential for hazards, such as sediment and (or) slope 

stability, with respect to activities on the continental shelf, such as oil and gas development and infrastructure siting. Methane released from gas 

hydrate dissociation could represent a significant flux of greenhouse gas to the atmosphere. A better understanding of the linkages and feedbacks 

between gas hydrates and climate change is needed to address these issues. 
32 An Evaluation of the Science Needs to Inform Decisions on Outer Continental Shelf Energy Development in the Chukchi and Beaufort Seas, Alaska

Economics and Scenarios

Economic analyses of undiscovered, technically 

recoverable oil and gas resources typically consider the 

costs associated with finding, development, and production 

(Minerals Management Service, 2006f). These estimates 

of economically recoverable resources provide information 

about those areas that might receive the greatest interest in 

terms of leasing and development (Minerals Management 

Service, 2006f). They also provide information that can be 

used as input from which to construct development scenarios. 

These scenarios can be used to gauge the potential scope 

and scale of future development, while providing a basis for 

evaluating potential effects on the environment, and as such, 

Exploration and Development scenarios are a component 

of Environmental Impact Statements and Environmental 

Assessments (Coffman and others, 2002). The scenarios 

produce estimates of the infrastructure required to support 

anticipated exploration, development, and production, and are 

based on input from existing geologic data and undiscovered 

resource estimates, and estimates regarding the timing of 

discovery and rates of production at specified price paths 

(Coffman and others, 2002). For example, at the time of the 

Burger discovery in the Chukchi Sea OCS, it was recognized 

that new technology, including subsea wellheads, year-round 

operations in pack ice, and large-diameter high-pressure, 

dense phase subsea pipelines, would be needed to produce 

the gas from this accumulation, but that these had not yet 

been tested under conditions typical of the Chukchi Shelf 

environment (Craig and Sherwood, 2004). In addition to such 

challenges, the potential for development of the resources 

at Burger would require transport through an 80-mi subsea 

pipeline and further transport overland (about 320 mi) to 

Prudhoe Bay on the central North Slope (Craig and Sherwood, 

2004). This underscores the importance of infrastructure to the 

development of this resource. This linkage was reiterated in 

a recent economic analysis of the ANS, which found that the 

extent of Chukchi Sea exploration and development activities 

will be significantly affected by the potential for expansion 

of petroleum-producing infrastructure to western NPRA as a 

means of facilitating transport of resources to market (Thomas 

and others, 2009).

What is important to recognize is that the complex 

interplay among the numerous factors associated with oil 

and gas development in the Arctic, including international 

geopolitics, future energy demand, climate change, and 

other fundamental parameters, such as the geologic setting 

of resources and estimated resource potential, collectively 

provide a significant challenge to precisely and accurately 

projecting the future activity (Arctic Monitoring and 

Assessment Programme, 2007). Previously, several models 

and methods were used in the analysis of economic impacts 

from oil and gas activities. The models and methods used 

typically varied from one planning area to another (Jack 

Faucett Associates, Inc., 2002), but efforts to develop 

more regionally expansive models have resulted in a more 

consistent approach, while recognizing there are differences 

from one region to another (Coffman and others, 2002). For 

example, the readily available regional economic impact 

models contain production functions based on national 

averages that do not accurately reflect the unique Arctic 

production function (Skolnik and Holleyman, 2002). Specific 

to Arctic oil and gas resources, factors such as remoteness, low 

temperatures, and shifting ice rule out traditional platforms, 

and require a modeling approach that accounts for these 

unique circumstances (Skolnik and Holleyman, 2002).

In addition to the modeling approaches developed 

specifically in support of Environmental Impact Statement 

and Environmental Assessment analyses, there have been 

a number of scenarios constructed to evaluate the potential 

scope and scale of oil and gas activities and associated effects 

in the Arctic OCS. Many of these analyses vary in terms of 

geographic scope or particular focus, such as: 

• the National Research Council (2003), which included 

the Alaska North Slope and Beaufort Sea, but did not 

consider the Chukchi Sea area to the west of the North 

Slope; 

• Thomas and others (2009), which included onshore 

Alaska, including Alaska National Wildlife Refuge, as 

well as the Beaufort and Chukchi Sea OCS areas; and

• Burden and others (2009), which focused on the 

Beaufort Sea, Chukchi Sea, and North Aleutian Basin 

areas. 

The regional geological framework, petroleum geology, 

exploration history, and existing fields are used as a basis 

for understanding the prior exploration and development 

activities, and to develop a framework for assessing current 

and future opportunities, and estimate the quantities of 

economically recoverable oil and gas that could be developed 

(Thomas and others, 2009), an approach that is common to all 

such studies. In the short term—2005 to about 2020—Thomas 

and others (2009) estimated that oil exploration would target 

primarily the Central North Slope, NPRA, and Beaufort 

Sea OCS. Given the recently updated NPRA assessment 

(Houseknecht and others, 2010), this outlook may change in 

response to the refined understanding of the potential resource 

base.
Chapter 2

Geological Context 33

Table 2–4. A summary example of output from an Outer Continental Shelf (OCS) 

development scenario. 

[Modified from Burden and others (2009, table 2)].

Beaufort Chukchi

Exploration

Exploration/delineation wells 47 43

Exploration rig seasons 31 27

Development

Number of offshore production platforms 7 4

Offshore/onshore pipelines (miles) 235 680

Shore bases / facilities

Marine terminal Yes Yes

Liquefied natural gas facility No No

Production facility Yes Yes

Support base Yes Yes

Production

Year 1st oil flows 2019 2022

Year 1st gas flows 2029 2036

Number of producing fields 7 4

Total cumulative volume produced (through 2057)

Oil and gas (billion barrels of oil equivalent) 6.34 6.16

Oil and condensates (billion barrels) 5.10 4.79

Gas (trillion cubic feet) 6.96 7.78

Daily peak production

Oil and condensates (barrels per day) 1,165,707 565,472

Gas (million cubic feet per day) 883 1,421

For example, sample output summary from the Burden 

and others (2009) analysis is included (table 2–4). In the 

Burden and others (2009) study, the scenarios used to 

underpin the analysis were derived in part by scenarios 

published in Environmental Impact Statements (EIS) and other 

materials. The study authors acknowledged the uncertainty 

associated with cost estimates for items such as exploration 

and development wells, offshore platforms, and production 

facilities and infrastructure such as pipelines given the unique 

challenges in the Arctic (Burden and others, 2009). Although 

the potential for a gas pipeline through the NPRA has been 

recognized as a potential means for transporting gas produced 

from the Chukchi Sea OCS, particularly in light of the Burger 

discovery (Craig and Sherwood, 2004), such a development 

was not considered in the scenario because of the high level of 

uncertainty associated with that infrastructure. The estimates 

from scenarios such as Thomas and others (2009) also 

provide useful information to help understand the potential 

long-term viability of infrastructure, such as TAPS (fig. 2–7). 

Depending on the level of future exploration and development 

in the Arctic OCS, the challenge may not be whether there is 

sufficient production to sustain TAPs, but whether additional 

pipeline capacity is needed. 
34 An Evaluation of the Science Needs to Inform Decisions on Outer Continental Shelf Energy Development in the Chukchi and Beaufort Seas, Alaska

tac11-5179_fig02-07

Chukchi Sea OCS, 

long term

NPR-A, long term

NPR-A, near term

Beaufort Sea OCS, long term

Beaufort Sea OCS, near term

Northstar

includes Prudhoe Bay Unit 

and other producing fields, 

and other known 

undeveloped fields

Forecast Historical 

(1977 thru 2007)

0

500,000

1,000,000

1,500,000

2,000,000

2,500,000

3,000,000

barrels per day

Year

Explanation

198019902000201020202030204020502060207020802090

TAPS minimum 

~ 200,000 bopd

Figure 2–7. Scenario output for projected estimates of future oil production from producing, known, undeveloped, 

and undiscovered oil fields on the Alaska North Slope and offshore. This composited projection includes 

recognition of two potentially distinct time frames pertaining to Alaska North Slope exploration and development 

activities: near term (2008 to about 2018–2020), which is largely centered on oil, and long term (about 2020–2050), 

which may represent a shift towards natural gas as a significant, perhaps dominant, factor in exploration and 

development. TAPS, Trans-Alaska pipeline system; bopd, barrels of oil per day. Modified from Thomas and others 

(2009).

By providing estimates for the potential scope, scale, 

and timing of development, these scenarios also are helpful 

for planning purposes and for informing research priorities. 

For example, the National Research Council (2003) scenario 

estimated that it might be another 10–15 years (the early 

2020s) before Beaufort OCS development would escalate 

much above historical levels, but that this estimated time lag 

“... also will provide time to more fully research 

and implement technologies that would reduce 

the environmental consequences of Beaufort Sea 

exploration and production, especially under 

conditions of broken ice.” 

There is need for a more comprehensive, holistic 

approach to building resource development and impact 

scenarios to inform planning. Such scenarios would consider 

activities beyond the planning areas to include other onshore 

resources, especially unconventional resources that may 

affect development decisions as well as infrastructure siting. 

Additionally, the National Research Council (2003) study 

determined that 

“... [i]f new technologies were developed, the life of 

the facilities at Prudhoe Bay and other major fields 

would be prolonged, as would use of the TransAlaska Pipeline.” 

The National Research Council (2003) study also noted that an 

important assumption underpinning its scenario is that 

“climate change will not be so great during the next 

50 years as to render current exploration methods 

obsolete or foreclose modifications, such as use of 

Rolligons and new drilling platforms.” 

These findings underscore the need for scenarios that 

account for potential resources and infrastructure beyond 

the immediate planning areas and proposed activities, and 

consider these in the broader context of climate change, to 

develop a comprehensive and systematic analysis of the 

region. Such steps toward a more holistic approach to energy 

planning are favorably aligned with recommendations given 

during recent testimony by the National Commission on the 

BP Deepwater Horizon Oil Spill and Offshore Drilling:

 “The [Macondo well] disaster signals the need to 

consider the broader context of the Nation’s patterns 

of energy production and use, now and in the 

future—the elements of America’s energy policy” 

(Graham and Reilly, 2011).
Chapter 2

Geological Context 35

Although our understanding of the Arctic system has 

advanced, there remain data and knowledge gaps for a number 

of components in the system. The opportunity exists to 

leverage existing research infrastructure and future research 

activities to better characterize this system and lead to 

scientific advances in a number of disciplines. Vörösmarty and 

others (2010) recently noted that the challenge of successfully 

extracting non-renewable resources economically and securing 

environmental protection provides an excellent opportunity 

to forward interdisciplinary and multiscale research. In this 

context, there is a continuing need to support the collection, 

integration, and sharing of multiscale datasets describing 

the inventories of current and potential stocks of various 

non-renewable resources (Vörösmarty and others, 2010). 

Interagency and international fora, such as the North Slope 

Science Initiative, the Interagency Arctic Research Policy 

Committee (IARPC), and the Arctic Council, provide venues 

through which the appropriate integrated and collaborative 

research activities address these knowledge gaps. For 

example, the USARC has recommended that the IARPC adopt 

a Resource Assessment and Earth Science Theme in the U.S. 

Arctic Research Program, and subsequently amended this 

recommendation to include basic earth science research needs 

(U.S. Arctic Research Commission, 2010).

2.03. Finding: Although our understanding of the Arctic as a system has advanced, there remain data and knowledge gaps for a 

number of components in the system. There is a continuing need to facilitate the collection, integration, and sharing of multiscale, 

multidisciplinary datasets, and using these data to develop comprehensive, holistic approaches to building resource development and 

impact scenarios to inform planning. 

2.03. Recommendation: Opportunities for enhanced international cooperation and collaboration. In particular, the Beaufort SeaMackenzie Delta (Canada) is an area with significant energy resource potential, and enhanced cooperation is important for baseline 

studies of resources, status, and trends, and developing overall models of development scenarios, potential impacts, and to address 

emerging science issues. The recent (2010) U.S.-Canada joint mission of the Extended Continental Shelf Project is one example of 

such collaboration. There exists the opportunity to identify these activities under the theme Resource Assessment and Earth Science 

in the U.S. Arctic Research Program adopted by the IARPC. In conjunction with these activities, there is a need for better integration of 

relevant information into a digital environment that can facilitate open and derivative analyses. 

There also is significant potential for collaborative work with academia and the international community, especially with planned marine 

cruises that include seismic and solid-earth geophysical data collection, and sample collection, including coring. 

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Chapter 3

Ecological and Subsistence Context 41

Chapter

3

Introduction

 This chapter provides a general overview of the physical and biological 

environments of the Beaufort and Chukchi Seas. We also include 

information on the human communities and subsistence resources of 

this area. This chapter, along with Chapter 2, Geological Context, which 

discusses the current knowledge of oil and gas resources, sets the stage 

for other chapters in this report that delve into greater detail on important 

aspects of these marine areas and resources and their relationship to oil 

and gas leasing, exploration, and development. In this chapter, we present 

findings and recommendations that speak to the state of the broader science 

foundation of the Arctic. This information informs specific oil and gas 

development-related discussions in later chapters. Two broad syntheses have 

recently captured much of this information, some of which is repeated here 

(Hopcroft and others, 2008a; Minerals Management Service, 2008). These 

summaries are authoritative and should be consulted to develop a broader 

framework of the previous research in the Beaufort and Chukchi Seas.

The Beaufort and Chukchi Seas are marginal seas of the Arctic Ocean 

(fig. 1–1). They lie north and northwest, respectively, of Alaska. Both seas 

are linked atmospherically via the Aleutian Low, whose variable position, 

strength and interactions with Arctic air masses affect meteorological 

conditions. They are linked oceanographically with the Pacific Ocean 

primarily via the Bering Strait, through which northward flow transports 

waters and organisms from the Bering Sea Shelf. The Beaufort Sea extends 

from Point Barrow in Alaska east to Banks and Victoria Islands of the 

Canadian Arctic Archipelago and the Amundsen Gulf. The Chukchi Sea 

extends from Point Barrow, Alaska and the Beaufort Sea in the east to 

Wrangell Island and the East Siberian Sea in the west. The Bering Strait 

forms the southern boundary of the Chukchi Sea and connects it with the 

Bering Sea and Pacific Ocean.

Ecological and

Subsistence Context

 By Anthony R. DeGange and Lyman Thorsteinson
42 An Evaluation of the Science Needs to Inform Decisions on Outer Continental Shelf Energy Development in the Chukchi and Beaufort Seas, Alaska

Physical Oceanography

(from Weingartner and others, 2008, and

Minerals Management Services, 2008)

The marine topographies of the Beaufort and Chukchi 

Seas are starkly different (fig. 3–1). The Chukchi Sea is 

underlain by a broad continental shelf that extends nearly 

900 km from the Bering Strait north to the shelf break. In 

contrast, the Beaufort Sea has a narrow continental shelf. East 

of Point Barrow, the continental shelf narrows to about 70 km 

and then widens again farther east near Mackenzie Bay and as 

it extends eastward into the Amundsen Gulf. The topography 

of this region includes Wrangel Island, at the approximate 

western boundary between the Chukchi and East Siberian 

Seas, and Herald and Hanna shoals in the Chukchi Sea Shelf 

north of Bering Strait. Submarine canyons include the Herald 

Valley and Central Channel in the Chukchi Sea, and the 

Barrow Canyon at the boundary between the Chukchi and 

Beaufort Seas. In the Beaufort Sea, there is little along-shelf 

variability in bathymetry, except for Barrow Canyon to the 

west and Mackenzie Valley near the Alaska-Canada border. 

There are numerous barrier islands along the Beaufort Sea 

coast and a number of bays and lagoons on both shorelines 

that form important wildlife habitats.

The water of the Beaufort Sea reflects three distinct 

oceanic regimes (Weingartner and others, 2008). The first 

consists of Pacific Ocean waters that exit the Chukchi Sea 

Shelf through the Barrow Canyon. The second is the offshore 

boundary of the continental shelf and slope. The upper layer is 

a westward flow that is the southern edge of the wind-driven 

Beaufort Gyre. Below that the flow is eastward over most of 

the slope. The third regime is formed by discharge from the 

Mackenzie River that intrudes into the Beaufort Sea through 

wind-forcing.

Figure 3–1. Schematic circulation map of the northern Chukchi Sea and western Beaufort Sea. From Weingartner and 

others (2008).
Chapter 3

Ecological and Subsistence Context 43

Surface circulation in the Beaufort Sea is dominated 

by the southern edge of the perpetual clockwise gyre of 

the Canadian Basin (fig. 3–1). The subsurface Beaufort 

Undercurrent flows in the opposite direction, to the east, over 

the Outer Continental Shelf. Currents in the shallower waters 

of the inner Beaufort Sea Shelf primarily are wind driven and, 

thus, can flow either east or west. Because the principal wind 

direction during the summer ice-free season is from the east, 

near-shore flow generally is from east to west.

Under persistent east winds, bottom marine water 

can move onshore, where it is forced to the surface. This 

upwelling of marine water can cause some otherwise brackish 

and warm areas along the coast to become colder and more 

saline. 

The Chukchi Sea receives water flowing northward 

through the Bering Strait, driven by the 0.5 m drop in sea 

level between the Aleutian Basin of the Bering Sea and the 

Arctic Ocean. Coachmen and others (1975) provide a good 

overview of the northward movement of Bering Sea waters 

into the Chukchi Sea. Three distinct water masses, each of 

different origin move northward through the Bering Strait. 

Anadyr Water, cold, high salinity, nutrient-laden oceanic water 

that originates along the slope of the Bering Sea Shelf, flows 

northward through Anadyr Strait, west of St. Lawrence Island 

and into the central Chukchi Sea. As much as 72 percent of the 

water transported through the Bering Strait in the summer may 

come through Anadyr Strait. Alaska Coastal Water originates 

in the Gulf of Alaska. This low salinity, seasonally warm water 

hugs the Alaska coast as it transits the Bering Sea into the 

Chukchi Sea. It is influenced by freshwater run-off from major 

rivers in western Alaska. Bering Shelf Water is the resident 

water mass of the central shelf region south of St. Lawrence 

Island. It is intermediate in character between Anadyr and 

Alaska Coastal Water, is advected northward on both sides of 

St. Lawrence Island, and then flows through the Bering Strait 

where it mixes with the other water masses. These waters are 

an important source of plankton and carbon in the Chukchi 

and Beaufort Seas, influencing the distribution and abundance 

of marine biota and seasonal migrations of many species (Piatt 

and Springer, 2003; Hopcroft and others, 2008a; Weingartner 

and others, 2008). The deeper waters offshore in the northern 

Chukchi Sea also are a potentially important source of 

nutrient-rich waters. 

3.01. Findings and Recommendations: Circulation 

processes along the Chukchi Sea shelfbreak and around Hanna 

Shoal in the northeast Chukchi Sea are poorly understood. The 

circulation here is part of a broader circulation field that connects 

the Chukchi and Beaufort slopes and carries waters draining from 

the western Chukchi Sea Shelf through Herald Valley to the eastern 

Beaufort Sea. There is high interest in the Hanna Shoal area for oil 

and gas exploration and development. 

The wind field is poorly understood in the Beaufort Sea and these 

winds are important in shelf and slope dynamics and would 

influence the movement of pollutants in this area. Meteorological 

models and observational studies of the barrier winds and sea 

breeze effect should be undertaken in conjunction with a review of 

existing data to determine the scales of the along- and cross-shelf 

winds.

Circulation processes at the seaward edge of the landfast ice edge 

are complex insofar as these involve ice dynamics and wind and 

buoyancy forcing. Ice edge processes are critical in understanding 

how waters in inshore and offshore areas interact. 

The large-scale circulation and thermohaline structure of the 

Beaufort Sea needs to be better understood with consideration 

given to the large inter-annual variability in winds and ice 

conditions. 

Measurements and models of wave regimes and storm surges 

should be conducted for the Beaufort and Chukchi Seas. A 

preliminary review of the 60-year long Barrow wind record 

suggests that wind intensities and extremes have increased 

over the past 15 years. Summer/autumn ice retreat over the last 

decade also has been unprecedented. These changes will have a 

major influence on the wind wave and storm surge climate of the 

Beaufort Sea and should be factored into offshore, nearshore, and 

onshore development scenarios.
44 An Evaluation of the Science Needs to Inform Decisions on Outer Continental Shelf Energy Development in the Chukchi and Beaufort Seas, Alaska

Sea Ice Dynamics

The presence of ice in the Arctic Outer Continental 

Shelf (OCS) is one of the most important physical conditions 

to be dealt with in developing OCS oil and gas resources. 

The seasonal sea ice cycle is a pervasive force in the Arctic, 

influencing human activities and many aspects of the region’s 

natural history and shows great seasonal and inter-annual 

variability off the coast of Alaska. Generally speaking, there 

are two types of sea ice: fast ice that is anchored along the 

shore and free-floating pack ice which moves with winds and 

currents. These two types of ice interact to cause an extensive, 

somewhat predictable, system of flaw leads (swathes of 

open water in between ice) and polynyas off the coasts of 

the Chukchi and Beaufort Seas eastward to the Canadian 

Archipelago. These flaw leads and polynyas become more 

prevalent in the spring and are important features that dictate 

the seasonal movements and northward migrations of wildlife 

species, such as bowhead whales and marine birds. 

Maximum sea-ice cover occurs in March or early 

April, lagging minimum insolation in late December by 

3 months because of the heat capacity of the ocean and the 

cold atmosphere. At this time, essentially all of the Beaufort 

and Chukchi Seas are ice-covered (fig. 3–2). Winter ice 

cover extent in the Arctic has declined since the late 1970s 

(fig. 3–3) along the southern margins of sea-ice extent, but 

not dramatically so (fig. 3–2). Maximum retreat of the sea 

ice occurs in September, again lagging maximum insolation 

by about 3 months. The extent of sea-ice loss in September 

since the satellite record began has been dramatic (fig. 3–4). 

By September, in normal years, the ice pulls away from the 

Arctic coasts of Canada, Alaska, and Siberia, leaving a nearly 

continuous, relatively ice-free corridor around the permanent 

ice pack. This corridor varies in width. In recent years, the 

ice-free corridor has expanded to hundreds of kilometers in 

the East Siberian Sea and offshore of the northern Alaska 

coast. The contrasts between 1980, a representative year with 

extensive ice cover, and 1987, when sea-ice extent in the 

Arctic was at a record minimum, and the long-term median ice 

edge are dramatic (fig. 3–4).

Figure 3–2. Maps showing sea-ice extent for single months and single years, using 1980 as an example of an extensive ice cover year, 

and 2007 as the record minimum year—maximum winter extent. The magenta line plots the long-term median ice edge based on years 

1979–2000. Source: National Snow and Ice Data Center (2007a), accessed April 15, 2011, at http://nsidc.org/cgi-in/bist/bist.pl?annot=1&le

gend=1&scale=100&tab_cols=2&tab_rows=2&config=seaice_index&submit=Refresh&mo0=03&hemis0=N&img0=extn&mo1=09&hemis

1=N&img1=extn&year0=1980&year1=2007.
Chapter 3

Ecological and Subsistence Context 45

Figure 3–3. Plots of sea-ice extent anomalies for March (maximum sea-ice extent) and September (minimal sea-ice extent) expressed 

as percent-departure from average (that is, anomalies as compared to the 1979–2000 mean). Source: National Snow and Ice Data 

Center (2007b), accessed April 15, 2011, at http://nsidc.org/cgi-bin/bist/bist.pl?config=seaice_extent_trends&submit=Go%21.

Figure 3–4. Maps showing sea-ice extent for single months and single years, using 1980 as an example of an extensive ice cover year, 

and 2007 as the record minimum year. The magenta line plots the long-term median ice edge based on years 1979–2000. Source: National 

Snow and Ice Data Center (2007a), accessed April 15, 2011, at http://nsidc.org/cgi-bin/bist/bist.pl?annot=1&legend=1&scale=100&tab_

cols=2&tab_rows=2&config=seaice_index&submit=Refresh&mo0=03&hemis0=N&img0=extn&mo1=09&hemis1=N&img1=extn&year0=198

0&year1=2007.
46 An Evaluation of the Science Needs to Inform Decisions on Outer Continental Shelf Energy Development in the Chukchi and Beaufort Seas, Alaska

Even in years of extensive sea-ice retreat in the Beaufort 

and Chukchi Seas, storms and winds can cause changes in ice 

cover that can profoundly influence sea-ice dependent wildlife 

movements. For example in 2008, fragments of sea ice that 

were not visible to satellites persisted over the continental 

shelf of the eastern Chukchi Sea and were successfully 

exploited by walrus where they did not need to come ashore to 

rest. This contrasted with 2007, 2009, and 2010 when walrus 

did come ashore in northwest Alaska, presumably in response 

to a lack of sea ice over shallow continental shelf waters in the 

Chukchi Sea. Similarly in 2010, a large swath of broken ice 

persisted north of Cross Island in the central Alaska Beaufort 

and may have contributed to the lack of polar bears found on 

shore in August (L. Peacock, U.S. Geological Survey, oral 

commun., 2010). 

Figure 3–5. Maps showing old versus new ice in the Arctic for February. These maps show the median age of February sea ice from 

1981 to 2009 (left) and February 2009 (right). As of February 2009, ice older than 2 years accounted for less than 10 percent of the ice 

cover. Dark blue equals ice greater than 2 years old; medium blue equals 2 year old ice; pale blue equals annual ice. Source: National 

Snow and Ice Data Center (2010), accessed April 15, 2011, at http://nsidc.org/sotc/sea_ice.html.

In addition to dramatic decreases in sea-ice extent 

during late summer and autumn, the character of sea ice in 

the Arctic also is changing, tending to be younger and thinner 

(fig. 3–5). The longer sea ice remains in the Arctic Ocean 

the thicker it becomes as a result of additional freezing and 

through deformation. The thinning of Arctic Ocean sea ice has 

occurred largely because of the export of older, thicker sea ice 

out of the Arctic through Fram Strait, east of Greenland. This 

is important because younger, thinner ice is more vulnerable 

to melting as a result of warmer air and water temperatures, 

perpetuating a feedback cycle because of the ability of open 

ocean to absorb solar insolation.
Chapter 3

Ecological and Subsistence Context 47

Seafloor Substrates

Soft sediments dominate the seafloors of the continental 

shelves of the Beaufort and Chukchi Seas. These are largely 

combinations of muds, sands, and gravels (fig. 3–6). These 

soft-sediment bottoms support high densities and biomass of 

benthic invertebrates, particularly in the extensive shallow 

shelf areas of the Chukchi Sea where productivity is high 

(see Benthos). Only two areas with hard substrates have been 

identified in the entire region (Smith, 2010) (fig. 3–6)—one in 

Peard Bay, southwest of Barrow, and the other in Steffanson 

Sound near Prudhoe Bay that is known as the “boulder patch” 

(Dunton and others, 1982). The boulder patch is characterized 

as sediment with greater than 10 percent boulder cover. It 

provides attachment habitat for the endemic kelp Laminaria 

solidungula and other macroalgae, which are the primary 

carbon source for consumers living there. 

Primary and Secondary Productivity

(from Hopcroft and others, 2008b; Stockwell and others, 2008; 

and Yager and others, 2008)

Within the Arctic, the combination of cold temperature, 

occurrence of sea ice, and extreme seasonal variations in light 

regimes controls phytoplankton growth and governs its spatial 

and temporal growth patterns. The stabilizing effect of sea 

ice allows production to occur near the surface under low light 

intensities. A large number of planktonic algae thrive in Arctic 

waters but there seem to be relatively few truly Arctic species. 

Estimates of phytoplankton biomass vary widely depending 

on the region, with the highest values found in the Chukchi 

Sea. Algal production and biomass in the Arctic primarily are 

controlled by light, stratification, and nutrient fields. On the 

shelves, advection and turbulent mixing of nutrients through 

the Bering Strait and local nutrient re-mineralization sustain 

extremely high primary production values on the Chukchi Sea 

Shelf (fig. 3–7). Much of that production is not grazed and 

falls to the seafloor to fuel benthic communities. In addition 

to phytoplankton, ice algae contribute to the total primary 

production of the Arctic Ocean with higher production values 

in first-year ice compared to multi-year ice. The contributions 

of ice algae to total primary production range from less than 

1 percent in coastal regions up to 60 percent in the central 

Arctic Ocean. 

Secondary producers include the microbes, protists, and 

zooplankton that consume phytoplankton and algae. Compared 

to phytoplankton and mesozooplankton, much less is known 

about the composition, distribution, and rates of activity of 

microbes and protists in the Arctic Ocean, and this confounds 

the ability to predict the impact of climate change or other 

disturbances on food webs and basic biogeochemical processes. 

Biomass of heterotrophic microbes in Arctic surface waters 

shows a strong response to seasonal changes in phytoplankton 

stocks. In the Chukchi Sea, concentrations of bacteria start 

out low in the spring, increase over the course of the bloom, 

and are highest in late summer. Heterotrophic protists include 

nanoflagellates, ciliates, and dinoflagella.

Recent work in the Gulf of Alaska, the Bering Sea, 

and shelf and slope regions of the western Arctic Ocean 

has confirmed the role of these organisms, known as 

microzooplankton, as consumers of phytoplankton in subArctic and Arctic food webs. Although it is likely that 

phytoplankton and sea ice algae still represent a crucial 

food source for the larger zooplankton, utilization of 

microzooplankton as food is recognized as being of similar 

import, particularly during periods when phytoplankton 

standing stock is low or of poor quality. Because strong local 

pulses of primary production are a frequent characteristic of 

high-latitude oceans, including the Chukchi and Beaufort Seas, 

the response of microbes (including both bacteria and protists) 

to these pulses determines the rate of re-mineralization and 

the fraction of total production exported to the benthos. Weak 

microbial activity in the Arctic contributes to the high degree of 

bentho-pelagic coupling in many shelf regions of the Arctic and 

the consequent strength of demersal ecosystems. 

3.02. Findings and Recommendations: Ice seasons of 

shorter duration and longer open-water seasons will favor longer 

seasons for resource development and transportation.

The northern Chukchi and Beaufort Seas are undergoing rapid ice 

retreat that will result in a change in ocean dynamics that might 

alter upwelling and biological productivity. If so, this could have 

cascading effects on all aspects of marine and coastal ecosystems. 

A reduction in the sea-ice cover and a lengthening of the ice-free 

season, particularly in autumn when wind speeds are strongest, 

will result in larger wind waves and storm surges, resulting in 

more rapid coastal erosion. These changes could influence patterns 

of abundance of fish and wildlife, subsistence use patterns, and 

how development occurs along the coast. Research is needed to 

understand how the wind wave field and storm surges will change 

in response to changes in sea ice concentration and extent. 

Improved understanding is needed of the impact of the changing 

ice regime on species and on biological hot spots in the Chukchi 

Sea and southwestern Beaufort Sea ice, which have high levels of 

biological productivity.
48 An Evaluation of the Science Needs to Inform Decisions on Outer Continental Shelf Energy Development in the Chukchi and Beaufort Seas, Alaska tac11-5179_fig2-06 A R C T I C O C E A N Teshekpuk L.

Colville R,

Mackenzie R.

Noatak R.

Koyukuk R.

Yukon R.

B e r i n g S e a

Norton

Sound

Kotzebue

Sound

B e a u f o r t

S e a

C h u k c h i

S e a

Ledyard

Bay

Harrison

Bay

Camden

Bay

Bering Strait

Kolyuchin

Bay

AnadyrGulf

Mackenzie

Bay

Smith

Bay Kugmallit

Bay

Liverpool

Bay

Peard

Bay

Wrangel Island Herald Island

St. Lawrence Island

R U S S I A

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Old Crow

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Mechigmensk

Bay

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Amgue m Ra .

Demarcation

Bay

Cape Lisburne

Cape

Thompson

Icy Cape

Kasegaluk

Lagoon

Point

Barrow

Stefansson

Sound

Canning R.

Kobuk R.

Tanana R.

uk Y on . R

Yukon R.

CANADA

UNI TED S TAT ES

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S UR AI S

Nome

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Fairbanks

Tok

Savoonga

Kivalina

Diomede

Unalakleet

Emmonak

Gambell

Brevig

Mission

Koyuk

Arctic

Village

Kaktovik

Nuiqsut

Atqasuk

PointHope

Point

Lay

Wainwright

Shishmaref

Noatak

Noorvik

Anaktuvuk

Pass

PrudhoeBay

Deadhorse

Provideniya

Inuvik

Enmelen

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Uelen

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128°0'0"W 132°0'0"W 136°0'0"W 140°0'0"W 144°0'0"W 148°0'0"W 152°0'0"W 156°0'0"W 160°0'0"W 164°0'0"W 168°0'0"W 172°0'0"W 176°0'0"W 180°0'0" 176°0'0"E

72°0'0"N70°0'0"N68°0'0"N66°0'0"N64°0'0"N62°0'0"N

Arctic Marine Synthesis:

Atlas of the Chukchi and Beaufort Seas

150 0 150 300 75

Miles

January 2010

Sea Floor Substrate

Sources: (1) NOAA. 1988. Bering, Chukchi, and Beaufort seas coastal and ocean zones strategic assessment

data atlas; (2) Carmack, E.C., and R. MacDonald. 2002. Oceanography of the Canadian shelf of the Beaufort

Sea: a setting for marine life. Arctic 55:29-45; (3) Dunton, K.H., E. Reimnitz, and S. Schonberg. 1982. An

Arctic kelp community in the Alaskan Beaufort Sea. Arctic 35(4):465-484; (4) NOAA. 2002. Environmental

sensitivity index, version 3.0. NOAA, Seattle, Washington; (5) Mohr, J.L., N.J. Wilimovsky, and E.Y. Dawson.

1957. An arctic Alaskan kelp bed. Arctic 19:45-54; (6) Horowitz, W.L. 2002. Evaluation of sub-sea physical

environmental data for the Beaufort Sea OCS and incorporation into a geographic information system (GIS)

database. OCS Study MMS 2002- 017. <http://www.mms.gov/ itd/pubs/2002/2002-017/

User_Manual_contract30985.pdf>. Accessed June 2009.

Boulder PatchNo Data

3 4 5 6

Gravel1 2Gravelly Mud1Gravelly Muddy Sand1Gravelly Sand1Mud1Muddy Gravel1Muddy Sand1Sand1Sandy Mud1

This map is based on the best available data, which varies in quality across the project area. For more information on

data quality and knowledge gaps, see the introduction to the Arctic Marine Synthesis and the description of this map.

Clay2Silt2

Figure 3–6. Seafloor substrates of the Alaska Beaufort and Chukchi Seas. From Smith (2010).
Chapter 3

Ecological and Subsistence Context 49

tac11-5179_fig03-07

Figure 3–7. Contours of integrated chlorophyll a concentrations (mg m-2, milligrams per square meter) 

based on discrete measurements (black points denote sampling locations), April–September 1976–2004 

(Grebmeier and others, 2006). 
50 An Evaluation of the Science Needs to Inform Decisions on Outer Continental Shelf Energy Development in the Chukchi and Beaufort Seas, Alaska

Zooplankton are the major grazers of the primary 

production in the Arctic and determine the resources available 

to many higher trophic levels, such as fish, seabirds, and 

marine mammals. In the Chukchi Sea, large quantities of 

Pacific zooplankton enter the region through the Bering 

Strait, in a complicated mixture of water masses. The influx 

of the rich Pacific water determines the reproductive success 

of both the imported and resident zooplankton communities. 

Both inter-annual and long-term variation in climate will 

affect the relative transport of these various water masses 

and hence the composition, distribution, standing stock, and 

production of zooplankton and their predators in the Chukchi 

Sea. Zooplankton abundance and community structure also 

affect the amount and quality of carbon exported to the benthic 

communities in this region. In contrast, the Beaufort Sea 

primarily is Arctic in character, with cross-shelf exchange 

mechanisms more important in determining the relative 

contribution of “oceanic,” “shelf,” and estuarine species. In 

the Eastern Beaufort, the outflow of the McKenzie River has 

significant impact on both the composition of the zooplankton 

and its productivity. Thus, the Beaufort Sea is responding 

to a fundamentally different set of factors than the Chukchi 

Sea, even if they are both driven by similar climate-related 

variations and trends. 

Although copepods typically predominate throughout the 

Arctic, there is a broad assemblage of other planktonic groups. 

Euphausiids are less abundant and diverse in Arctic waters 

than elsewhere, but can be important prey for higher trophic 

levels such as bowhead whales, birds, and fishes. Larvaceans 

(Appendicularians) have been shown to be abundant in Arctic 

polynyas, and are transported in high numbers through the 

Bering Strait into the Chukchi Sea. Similarly, important 

and common predatory groups, such as the chaetognaths, 

amphipods, ctenophores, and cnidarians have been reported 

on in detail by only a few surveys. Hyperiid amphipods also 

can be common in Arctic waters, and like chaetognaths, have a 

potential to graze a large proportion of the Calanus population. 

Relatively little is known of the abundance, composition, 

or ecology of the delicate gelatinous zooplankton, such as 

jellyfish. There are indications that climate change has resulted 

in increased numbers of jellyfish in the Bering Sea in recent 

years. Scientists have recorded jellyfish piled up several feet 

deep along shorelines near Barrow, Alaska. The ecological 

impact of these predators is substantial and underestimated in 

polar waters. 

The ongoing reduction of the sea-ice cover will have 

major impacts on the ecosystems and biogeochemical fluxes 

on the extensive continental shelves of the Arctic Ocean. 

Many processes involved in the regulation of the vertical 

and trophic fluxes of particulate organic carbon, and the 

production of dissolved organic carbon, are controlled by the 

zooplankton. Knowledge of zooplankton community ecology, 

especially the temporal and spatial distribution patterns of the 

different classes of zooplankton, is needed to understand the 

role of sea-ice variability in dictating fluxes of biogenic carbon 

on and off the shelves.

Benthos 

(from Bluhm and others, 2008)

Benthic food supply originates in surface waters and 

is highly seasonal in the Arctic. Densities of sedimenting 

particles and their nutritional values range vastly from the 

nutrient rich waters of the northern Bering and Chukchi 

Seas to the oligotrophic deep waters of the Arctic Basins. In 

general, however, comparisons of energy fluxes show that 

the benthic systems receive more energy in the Arctic than 

temperate and tropical systems.

Much of the broad, shallow shelf of the Chukchi Sea is 

strongly influenced by northward flowing nutrient-rich Pacific 

water through the Bering Strait, resulting in very high benthic 

biomass, which is among the highest worldwide in softsediment macrofaunal communities (fig. 3–8). Specifically, 

the south-central Chukchi Sea has the highest algal and faunal 

biomass on the combined Bering Sea and Chukchi Sea Shelf. 

This is the result of high settlement rates of organic production 

that is not grazed by microbes and zooplankton. These rich 

benthic communities, tied to high pelagic production and 

advection, serve as prey for a variety of diving sea birds and 

marine mammals, a key feature of the productive Chukchi 

Sea. Close to 1,200 species are known from the Chukchi 

Sea fauna to date with amphipods, clams, and polychaetes 

dominating infaunal community. Important macrofauna prey 

species for higher trophics include bivalves taken by walrus, 

in particular Macoma spp. and Mya truncata and benthic 

amphipods utilized by gray whales and bearded seals. Within 

the epifauna, ophiuroids dominate abundance and biomass 

in much of the surveyed Chukchi Sea, and other patchily 

distributed echinoderms (especially asteroids), gastropods, 

ascidians, sponges, cnidarians, and bryozoans also are locally 

abundant.

3.03. Findings and Recommendations: Now that some 

recent baselines have been established for phytoplankton, 

microbes, and zooplankton, it is critical that long-term repeated 

measurements are established from the Bering Strait northward 

throughout the Chukchi Sea, and extending into the Beaufort Sea. 

Continued annual sampling at a series of fixed stations/transects 

during a consistent seasonal time-window is required to establish 

long-term and inter-annual trends. 
Chapter 3

Ecological and Subsistence Context 51

tac11-5179_fig 02-08

Figure 3–8. Benthic biomass distribution in the Chukchi and northern Bering Seas. (From Grebmeier and 

others, 2006.) (g C m-2, grams of carbon per square meter.)

The comparatively narrow Beaufort Sea Shelf is 

influenced by large freshwater inflow from numerous small 

rivers and streams, the larger Colville and Mackenzie 

Rivers, and permafrost resulting in estuarine conditions in 

the nearshore. Because of this freshwater flow, non-marine 

sources of carbon may play an increasingly important role for 

the benthic food web in parts of the nearshore Beaufort Sea. 

The Beaufort Sea seafloor is dominated by soft sediments, 

but high ice cover and associated scouring, along with glacial 

erratics, have left coarser sediments (gravel and boulders) in 

various areas of the Beaufort Sea. The Alaskan part of the 

Beaufort Sea coast is fringed by sandy barrier islands forming 
52 An Evaluation of the Science Needs to Inform Decisions on Outer Continental Shelf Energy Development in the Chukchi and Beaufort Seas, Alaska

numerous shallow lagoons with average depths less than 5 m 

and ecological traits different from those in the open water. 

Compared to the Chukchi Sea, productivity and benthic 

biomass in the Alaskan Beaufort Sea are dramatically lower. 

Consequently, benthic-pelagic coupling is not as pronounced 

as in the Chukchi Sea and food chains are longer. 

Much less is known about the slopes of the Chukchi and 

especially the Beaufort Sea, and the adjacent basins (Bluhm 

and others, 2008). The existing investigations of the slopes 

and abyssal infaunal benthos in the western Arctic revealed 

low abundances and biomass values relative to the shelves, 

especially with increasing water depth and distance from 

the shelves. At taxonomic levels of phylum and orders, the 

soft-bottom deep Arctic macrofauna appear to be similar to 

the shelf communities: polychaetes, bivalves, and crustaceans 

are dominant, but on a family, genus, and species level, 

inventories differ from the shelves.

3.04. Findings and Recommendations: Regional hot spots 

for regular monitoring should include the southern Chukchi Sea, 

Barrow Canyon, and the Barter Island area. Secondly, source areas 

of organic and inorganic carbon should receive special attention, 

such as the inflow of nutrient-rich Anadyr water through the Bering 

Strait and river and permafrost run-off along the coastlines. The 

importance lies in regular sampling of the same areas to establish 

long-term time series. 

Routine and robust monitoring of the benthos in areas of offshore 

development would be useful to establish trend information and to 

monitor the impacts of development and pollution.

for restricted permitted take incidental to commercial fishing 

and industrial activities. Additional protection is afforded to 

any species that is classified as depleted under the Act. Any 

species that is classified as threatened or endangered under 

ESA is automatically classified as depleted under MMPA. 

The marine mammals found in the Beaufort and Chukchi 

Seas study area include baleen and toothed whales, ice seals, 

walruses, and polar bears. For many of these species, their 

distribution, movements, and life history events are closely 

tied to the presence or absence of sea ice. Most species are 

harvested by coastal subsistence hunters, and they can make 

up a substantial proportion of the annual diet in coastal 

communities.

Status of Important Marine Mammal Stocks that 

Inhabit the Beaufort and Chukchi Seas

Information on the status of marine mammals is derived 

primarily from the most recent stock assessments provided by 

the National Marine Fisheries Service (NMFS) and U.S. Fish 

and Wildlife Service (USFWS) for whales, pinnipeds, Pacific 

walrus, and polar bears (Allen and Angliss, 2010). Some life 

history information on these marine mammal species also 

is included in the stock assessments, but is widely available 

elsewhere. 

Bowhead Whale (Balaena mysticetus)

The western Arctic stock of the bowhead whale is almost 

exclusively an Arctic species. It summers in the Canadian 

Beaufort Sea, migrates through the U.S. Beaufort Sea into 

the Chukchi Sea and winters in the northern Bering Sea. 

They generally are associated with shelf and slope waters 

of the Arctic, where they feed primarily on copepods and 

euphausiids. With the advent of satellite telemetry, detailed 

information on bowhead whale movements are now available 

(Quakenbush and others, 2010) (fig. 3–9). Bowhead whales 

are classified as endangered under the ESA and depleted 

under the MMPA. The most recent (2001) estimate of the 

population of western Arctic bowhead whales is 10,545 and 

the population is increasing. Bowhead whales are an important 

subsistence species and are hunted in the spring and autumn 

as they pass coastal Alaska villages in the northern Bering, 

Chukchi, and Beaufort Seas. Noise, oil pollution, and climate 

warming are important concerns. Key information needs 

include: continued assessments of population size; integrative 

research on oceanography, prey availability, foraging and 

behavioral ecology; characterization of wintering habitat; and 

development of models incorporating data on whales, sea ice, 

and oceanography to predict the effects of climate change and 

anthropogenic impacts. 

Marine Mammals

The marine mammal fauna of the Chukchi and Beaufort 

Seas off the coast of Alaska are among the most diverse in the 

World and are of high scientific and public interest. Fifteen 

species and (or) stocks of marine mammal are common to 

the study area (table 3–1). Many of the species are used 

for subsistence purposes by Alaska Natives and many have 

an important symbolic role in cultural identity. Some have 

a high profile because they are covered by international 

conservation agreements (polar bear) or because they are 

classified as threatened or endangered under the Endangered 

Species Act (ESA). All marine mammals in the United 

States receive special protection under the Marine Mammal 

Protection Act (MMPA). The MMPA places a moratorium on 

the take, including harassment, of all marine mammals with 

special exemptions for subsistence use by Alaska Natives, for 

permitted activities such as research and public display, and 
Chapter 3

Ecological and Subsistence Context 53

Gray Whale (Eschrictius robustus) 

The eastern North Pacific stock of the gray whale winters 

and calves in lagoons on the Pacific side of Baja California, 

Mexico, and summers primarily in the shallow northern 

Bering and Chukchi Seas. It was formerly listed under the 

ESA, but responded well to protection from overexploitation 

and was delisted in 1994. Recent population estimates range 

from 18,178 to 29,758. The population is believed to be at 

or approaching carrying capacity. It is unclear how climate 

change will affect this species. Because the gray whale is 

primarily a benthic feeder, relaxation of the tight pelagicbenthic coupling that currently fuels high rates of benthic 

productivity in the Chukchi Sea would likely not favor this 

species. 

Beluga Whale (Delphinapterus leucas)

Two stocks of beluga whale are found in the study area: 

the Beaufort Sea stock and the eastern Chukchi Sea stock. 

Satellite tagging suggests that the range of these two stocks 

may widely overlap. Whales tagged in Kasegaluk Lagoon in 

the Chukchi Sea moved north, with males moving into deep 

waters of the Beaufort Sea with more than 90-percent ice 

cover, and adult and immature females moving to the shelf 

break of the Chukchi Sea. The size of the eastern Chukchi 

Sea stock is not known but it is not believed to be declining. 

The Beaufort Sea stock numbers about 39,000 animals. It is 

assumed that most whales from these two stocks winter in the 

Bering Sea where they are closely associated with pack ice. 

Ribbon Seal (Histriophoca fasciata) 

The Alaska stock of the ribbon seal inhabits the Bering, 

Chukchi, and western Beaufort Seas and is associated with 

open water, pack ice, and rarely shorefast ice. They are most 

abundant in the northern edge of the ice front in the central 

and western Bering Sea in the winter and recent data suggest 

that they migrate into the Chukchi Sea in the summer. A 

reliable population estimate is not available. The NMFS 

received a petition to list the ribbon seal under the ESA in 

2007. In December 2008, NMFS determined that listing the 

ribbon seal was not warranted (National Marine Fisheries 

Service, 2008). The NMFS concluded that although a gradual 

decline in the ribbon seal population is likely with a decrease 

in frequency of years with suitable sea-ice habitat, ribbon seals 

are not likely to become an endangered species within the 

foreseeable future (Boveng and others, 2008). 

Table 3–1. Most common marine mammal stocks found in the Chukchi and Beaufort Seas of Alaska.

[Information primarily from Allen and Angliss (2010). Endangered Species Act (ESA) status: D, de-listed; E, endangered; P, proposed for 

listing; T, threatened]

Name Stock Estimated 

population ESA status

Spotted seal (Phoca largha) Alaska Not available

Bearded seal (Erignathus barbatus) Alaska Not available P

Ringed seal (Phoca hispida) Alaska Not available P

Ribbon seal (Histriophoca fasciata) Alaska Not available

Beluga whale (Delphinapterus leucas) Beaufort Sea 39,258

Eastern Chukchi Sea 3,710

Harbor porpoise (Phocoena phocoena) Bering Sea 48,215

Gray whale (Eschrictius robustus) Eastern North Pacific 18,813 D

Humpback whale (Megaptera novaeangliae) Western North Pacific 938 E

Fin whale (Balaenoptera physalus) Northeast Pacific 5,700 E

Minke whale (Balaenoptera acutorostrata) Alaska Not available

Bowhead whale (Balaena mysticetus) Western Arctic 10,545 E

Polar bear (Ursus maritimus) Southern Beaufort Sea 1,526 T

Chukchi/Bering Seas 2,000 T

Pacific walrus (Odobenus rosmarus) Alaska 129,000 P
54 An Evaluation of the Science Needs to Inform Decisions on Outer Continental Shelf Energy Development in the Chukchi and Beaufort Seas, Alaska

Ringed Seal (Phoca hispida)

Ringed seals are the most abundant of the ice seals 

in Alaska, are tightly associated with sea ice, and are an 

important subsistence species. Ringed seals are found 

throughout the Beaufort, Chukchi, and Bering Seas, as far 

south as Bristol Bay in years of extensive ice coverage. They 

are found in the study area year round, but some ringed seals 

obviously migrate south with the ice in the winter. Ringed 

seals are an ice seal that tend to prefer large floes (that is, 

greater than 48 m in diameter) and are often found in the 

interior ice pack where the sea-ice coverage is greater than 

90 percent. Recent research suggests that ringed seal densities 

are higher in nearshore fast and pack ice and lower in offshore 

pack ice. They remain in contact with ice most of the year 

and pup on the ice in late winter-early spring in sub-nivean 

dens on the sea ice. An example of movement data now 

becoming available on ringed seals because of advances in 

satellite telemetry is shown in figure 3–10. An animation of 

these seasonal movements that also shows sea ice is available 

at Kotzebue IRA (2010; http://www.kotzebueira.org/current_

projects.html).

A reliable estimate for the Alaska stock of ringed seals 

is not available but they probably number at least in the low 

hundreds of thousands. The NMFS received a petition to list 

ringed seals under the ESA on May 28, 2008, due to loss 

of sea-ice habitat caused by climate change in the Arctic. 

In December 2010, the NMFS published a proposed rule 

to list the ringed seal as a threatened species. This proposal 

included the Arctic, Okhotsk Sea, Baltic Sea, and Lake 

Ladoga subspecies of ringed seal (National Marine Fisheries 

Service, 2010a). Ringed seals of the Beaufort and Chukchi 

Seas are part of the Arctic subspecies. A fifth subspecies 

from Lake Saimaa in Finland was listed as endangered 

in 1993. Information gaps include: population size; stock 

structure; foraging ecology in relation to prey distributions 

and oceanography; relationship of changes in sea ice to 

distribution, movements, reproduction, and survival; models 

to predict the effects of climate change and anthropogenic 

impacts; and improved estimates of harvest. 

Figure 3–9. Track lines of bowhead whales in the Chukchi Sea in the autumn. Source: Alaska Department of 

Fish and Game (2009), accessed April 18, 2011, at http://www.adfg.alaska.gov/static/home/about/management/

wildlifemanagement/marinemammals/pdfs/bow_move_chukchi_sea.pdf. Also see Quakenbush and others 

(2010) for detailed analysis of bowhead whale movements in the autumn and winter. 
Chapter 3

Ecological and Subsistence Context 55

Figure 3–10. Movements of ringed seals marked with satellite transmitters near Kotzebue, Alaska. Source: Kotzebue IRA 

(2010), accessed April 18, 2011, at http://www.kotzebueira.org/current_projects2.html.
56 An Evaluation of the Science Needs to Inform Decisions on Outer Continental Shelf Energy Development in the Chukchi and Beaufort Seas, Alaska

Figure 3–11. Movements of bearded seals tagged with satellite transmitters in the vicinity of Kotzebue. Source: 

Kotzebue IRA (2010), accessed April 18, 2011, at http://www.kotzebueira.org/current_projects.html.

Bearded Seal (Erignathus barbatus)

Bearded seals, an important subsistence species, 

primarily are a benthic-feeding seal usually associated with 

shallow water over the continental shelf (less than 200 m) that 

is at least seasonally ice covered. During winter, they are most 

common in broken pack ice and also inhabit shorefast ice in 

some areas. In Alaska waters, bearded seals are distributed 

over the continental shelf of the Bering, Chukchi, and 

Beaufort Seas. This species also is found in the study area year 

round and like ringed seals, some individuals migrate south 

in the winter with the sea ice. There is no reliable population 

estimate for the Alaska stock of the bearded seal. Earlier 

estimates of abundance ranged from 250,000 to 300,000. 

The NMFS received a petition to list bearded seals under the 

ESA on May 28, 2008, due to loss of sea-ice habitat caused 

by climate change in the Arctic. The NMFS published a 

Federal Register notice in September 2008 indicating that 

there were sufficient data to warrant a status review of the 

species. In December 2010, the NMFS published a proposed 

rule to list the Beringia Sea and the Okhotsk Sea bearded 

seals as a threatened species (National Marine Fisheries 

Service, 2010b). Figure 3–11 is an example of the kinds of 

information on movements and distribution that are becoming 

available on this species and other ice seals through advances 

in satellite telemetry. An animation that depicts the southerly 

movements of bearded seals with advancing sea ice is 

available at Kotzebue IRA (2010; http://www.kotzebueira.org/

current_projects.html). Information gaps include: population 

size; stock structure; foraging ecology in relation to prey 

distributions and oceanography; relationship of changes 

in sea ice to distribution, movements, reproduction, and 

survival; models to predict the effects of climate change and 

anthropogenic impacts; and improved estimates of harvest. 
Chapter 3

Ecological and Subsistence Context 57

Spotted Seal (Phoca largha)

Spotted seals are distributed along the continental shelf 

of the Bering, Chukchi, and Beaufort Seas. Satellite tagging 

studies showed that seals tagged in the northeastern Chukchi 

Sea moved south in October and passed through the Bering 

Strait in November. Seals overwintered in the Bering Sea 

along the ice edge and made east-west movements along 

the edge. A reliable estimate of spotted seal population 

abundance is currently not available, although the NMFS’s 

current estimate for the eastern and central Bering Sea is 

about 101,500 (National Marine Fisheries Service, 2009). The 

NMFS received a petition on May 28, 2008, to list spotted 

seals under the ESA due to loss of sea-ice habitat caused 

by climate change in the Arctic, but concluded there are 

insufficient data to make reliable predictions of the effects 

of Arctic climate change on the Alaska spotted seal stock. In 

their Final Rule, the NMFS concluded that spotted seals in the 

Pacific exist as three Distinct Population Segments (DPS) and 

determined that only the southern DPS was threatened under 

the ESA (National Marine Fisheries Service, 2009). This DPS 

is located in the Sea of Japan and Yellow Sea, well outside of 

our geographic area of study. The NMFS published a Final 

Rule to that effect in October 2010 (National Marine Fisheries 

Service, 2010c).

Pacific Walrus (Odobenus rosmarus) 

Pacific walrus range throughout the continental shelf 

waters of the Bering and Chukchi Seas, occasionally moving 

into the East Siberian Sea and the Beaufort Sea. They use 

sea ice over shallow, continental shelf waters as a moving 

platform for resting from which they dive to the seafloor for 

benthic invertebrates, such as clams. During the summer 

months, females and young migrate into the Chukchi Sea with 

the sea ice; however, thousands of animals, primarily adult 

males, aggregate near coastal haulouts in the Gulf of Anadyr, 

Bering Strait region, and in Bristol Bay. While in the Chukchi 

Sea, walruses are distributed broadly over the continental 

shelf, especially in the southern Chukchi Sea and along the 

coastlines of Chukotka and Northwest Alaska as indicated 

by satellite tags (fig. 3–12). Recent research has improved 

our understanding of how walruses use sea ice (Udevitz and 

others, 2009; Jay and others, 2010) and is beginning to shed 

light on how walruses will respond to diminishing sea ice in 

the Chukchi Sea (Jay and Fischbach, 2008; Fischbach and 

others, 2009; Jay and others, 2011). Modeling suggests a 

trend of worsening conditions for Pacific walrus through the 

end of this century (Jay and others, 2011). The estimate of 

the population from a 2006 survey of about 129,000 walruses 

is biased low because some areas known to be important to 

walrus were not surveyed due to poor weather conditions 

(Speckman and others, 2010). In February 2008, the USFWS 

received a petition to list the Pacific walrus under the ESA. 

On February 8, 2011, the USFWS announced that listing the 

Pacific walrus under the ESA was warranted, but precluded 

due to other higher priority listing actions. Like other iceassociated pinnipeds, walrus are difficult to study. Information 

gaps include: population size; stock structure; foraging 

ecology in relation to prey distributions and oceanography; 

relationship of changes in sea ice to distribution, movements, 

reproduction, and survival; models to predict the effects of 

climate change and anthropogenic impacts; and improved 

estimates of harvest. Impacts to walrus of changes in Arctic 

and subarctic ice dynamics are not well understood. Harvest 

and oil and gas development also are potential conservation 

concerns. 

Polar Bear (Ursus maritimus)

Polar bears are perhaps the best known of the Arctic 

marine mammals in Alaska. Two stocks of polar bears are 

currently recognized in Alaska, the Chukchi Sea stock that is 

shared with Russia and the southern Beaufort Sea stock that 

is shared with Canada. The two stocks overlap widely in the 

vicinity of Point Barrow. Most polar bears remain with the sea 

ice throughout the year in the Beaufort and Chukchi Seas, but 

as sea ice retreats farther offshore in the summer and autumn 

increasing numbers of bears are coming to shore (Schliebe 

and others, 2008). In both seasonal and non-seasonal seaice environments, recent studies suggest that longer ice-free 

seasons are affecting polar bear size, recruitment and survival, 

and in some cases population size (Amstrup and others, 2008; 

Hunter and others, 2010; Regehr and others, 2010; Rode and 

others, 2010). The southern Beaufort Sea stock is currently 

estimated at 1,526 based on capture-recapture data. It has been 

difficult to derive an estimate for the Chukchi Sea stock, but 

it is estimated at about 2,000 bears based on an extrapolation 

of aerial den surveys. Both stocks of polar bears are classified 

as depleted under the MMPA and threatened under the ESA. 

Both stocks of polar bears are currently under study in Alaska, 

but comparatively less is known about polar bears in the 

Chukchi Sea. 
58 An Evaluation of the Science Needs to Inform Decisions on Outer Continental Shelf Energy Development in the Chukchi and Beaufort Seas, Alaska

Overview—Arctic Marine Mammal Information 

Needs

Because of their high visibility, high public interest, 

and importance to subsistence harvesting, Arctic marine 

mammals have received considerable research interest. Yet, 

many Arctic marine mammals are challenging to study and 

little is known about basic life history metrics, movements, 

and populations. Considerable resources are devoted to 

research and management of Arctic marine mammals by 

management agencies [NMFS, USFWS, and Bureau of 

Ocean Energy Management, Regulation and Enforcement 

(BOEMRE)], and research organizations [for example, 

USGS, National Science Foundation (NSF), North Pacific 

Research Board] and considerable success has been achieved 

in better understanding some of these species. Polar bears in 

the southern Beaufort Sea are perhaps the best studied of all 

Arctic marine mammals in Alaska because they are accessible 

and visible, spending most of their lives on top of the sea 

ice, often close to shore. Most other marine mammals spend 

their lives either in the water or under the ice, sometimes far 

from shore, and are far more difficult to study. Particularly 

lacking are data on abundance, distribution, movements, agespecific vital rates, sea-ice habitat relationships, and humanmarine mammal interactions, although data gaps are being 

filled for some species. Rapidly changing sea-ice conditions 

in the Arctic have exacerbated the difficulty in assessing 

and predicting the impacts of development on many marine 

mammal species. 

tac11-5179_fig 03-12

Figure 3–12. Tracks of Pacific walrus tagged with satellite transmitters depicting distribution 

over the continental shelf (U.S. Geological Survey, unpub. data, 2007–2010).
Chapter 3

Ecological and Subsistence Context 59

3.05. Findings and Recommendations: Population enumeration is poor, 

even non-existent, for many species, and relatively good for a few. Without 

information on stock structure, however, which is poorly known for many species 

but fundamental to management, data are difficult to interpret even for species 

where abundance estimates exist. 

There is little or no information about wintering distribution and habitats for most 

species except polar bears and gray whales. Existing data for most species are 

for non-winter months when researchers can access marine mammal habitat. 

New modeling of the impact of oil pollution on marine mammals using updated 

oil-spill trajectory models, population models, satellite telemetry data, and 

new information on distribution and abundance would be informative for some 

species.

Trophic interactions of marine mammals were first studied 30 years ago. Although 

trophic structure generally is understood for most species (for example, general 

prey types, where they feed in the food web), seasonal, annual, and geographic 

variability in diet are poorly quantified and foraging areas are poorly described.

Thirty years ago, as part of Outer Continental Shelf Environmental Assessment 

Program (OCSEAP), the need for basic biological information about key forage 

species was highlighted by seabird and marine mammal researchers. Little 

progress has been made since those recommendations were made. Among 

the most important forage species are: Arctic cod (Boreogadis saida), saffron 

cod (Eleginus gracilis), sandlance (Ammodytes hexapterus), capelin (Mallotus 

villosus), copepods (Calanus spp.), and euphausiids (Thysanoessa spp.).

Threshold levels quantifying the anthropogenic effects (noise, hydrocarbons, 

contaminants, shipping, displacement, attractants, air pollution, commercial 

fishing, and so on) from industrial development on marine mammals are needed 

for select target species. Sensible mitigation measures should be the end-product 

of these research efforts. 

Long-term ecological monitoring and life history analyses are needed for focal 

marine mammals. Measurements from infrequent studies can be very misleading. 

Because of great changes that have occurred in the Arctic, especially to sea ice, 

measures from studies conducted 30 years ago may or may not reflect current 

population dynamics. These types of studies are expensive, so thought should be 

given to identify and target “indicator” species although ESA requirements force 

study at the species level. 

Conduct long-term, longitudinal studies of habitat use/foraging areas and trophic 

complexes at one or more biological hotspots—that is, include marine mammals 

in long-term and site-specific oceanographic studies such that data on habitat 

are obtained concurrent with information on marine mammal habitat selection. 

Long-term monitoring programs on most marine mammal species are lacking 

because of cost and complex logistics. Exceptions to this do exist (for example, 

mark-recapture studies in the southern Beaufort Sea for polar bears and annual 

aerial surveys for bowhead whales), but costs for these programs are high and 

are increasing. 

Studies using advances in satellite telemetry have revolutionized our ability to 

track wildlife. Continued telemetry studies of a suite of pinnipeds, cetaceans, and 

polar bears are needed to understand spatial distribution, sea-ice relationships, 

migration strategies, and migration corridors and can be used to evaluate sitespecific impacts of development activities.

Local residents are often the first to notice changes in fish and wildlife 

populations. Mechanisms should be developed to better solicit and integrate their 

local traditional knowledge (LTK) as a basic source of information. 

Marine and Coastal Birds

Many bird species that reside in marine 

and coastal habitats (for example, seabirds, sea 

ducks, and loons) are highly vulnerable to oil 

pollution. Most marine birds that occur in the 

Beaufort and Chukchi Seas are there during the 

open water season; exceptions include eiders 

and seabirds that winter in polynyas and at the 

ice edge. Arrival times usually coincide with 

the formation of leads during spring migration 

to coastal breeding areas. Many seabirds (such 

as murres) and sea ducks (such as king and 

common eiders and long-tailed ducks) will 

closely follow leads during spring migration. 

Migration times vary between species, but spring 

migration for most species takes place between 

late March and late May. All marine and coastal 

birds breed outside the OCS lease sale areas, 

but spend time in the Chukchi and Beaufort 

Seas after breeding or during their non-breeding 

seasons. Departure times from the Beaufort 

and Chukchi Seas for the autumn and winter 

vary between species and often by sex within 

the same species, but most marine and coastal 

birds will have moved out of the Beaufort and 

Chukchi Seas by late autumn before or during 

the formation of sea ice. Detailed information 

on marine use of the Chukchi and Beaufort 

Seas by marine birds is relatively sparse. 

Johnson and Herter (1989) in their “Birds of the 

Beaufort Sea” summarize what was known of 

all birds from marine and coastal areas of the 

Beaufort Sea; a similar treatment of the birds of 

the Chukchi Sea is not available. Coastal and 

marine habitats of the Beaufort and Chukchi 

Seas contain a number of areas for birds that 

are of State, continental, and global importance 

(fig. 3–13). These Important Bird Areas, or IBAs, 

are sites that provide essential habitat for one 

or more species of bird. IBAs include sites for 

breeding, wintering, and (or) migrating birds and 

may be a few acres or thousands of acres, but 

usually they are discrete sites that stand out from 

the surrounding landscape. IBAs may include 

public or private lands, or both, and they may be 

protected or unprotected. To qualify as an IBA, 

sites must satisfy at least one of the following 

criteria. The site must support:

• Species of conservation concern (for 

example, threatened and endangered 

species); 
60 An Evaluation of the Science Needs to Inform Decisions on Outer Continental Shelf Energy Development in the Chukchi and Beaufort Seas, Alaska

Figure 3–13. Important Bird Areas (IBAs) of the Beaufort and Chukchi Seas. Green dots = IBAs of State significance; Blue dots 

= IBAs of North American significance; Red dots = IBAs of global significance. Numbers are found in table 3–2. Source: Audubon 

Alaska (2011), accessed April 18, 2011, at http://ak.audubon.org/birds-science-education/important-bird-areas-0. 

Table 3–2. National Audubon Society Important Bird Areas (IBAs) of the Beaufort and Chukchi Seas from the Point Hope area north and 

east to the United States-Canada border.

[Source: Audubon Alaska (2011), accessed April 18, 2011, at http://ak.audubon.org/birds-science-education/important-bird-areas-0. Map No. is shown in figure 3–13]

Map

No. IBA name Primary reasons for designation

1 Cape Thompson One of two major, cliff-nesting seabird colonies in the eastern Chukchi Sea

2 Cape Lisburne The other major, cliff-nesting seabird colony in the eastern Chukchi Sea

3 Ledyard Bay Critical Habitat for threatened spectacled eider; important marine habitat for seabirds

4 Southeast Chukchi (marine) Important marine habitat for fulmars, shearwaters, auklets, and other seabirds

5 Kasegaluk Lagoon Important feeding and staging area for shorebirds and Pacific black brant

6 Peard Bay Important habitat for Pacific black brant, shorebirds, long-tailed ducks, and common and 

spectacled eiders

7 Cooper Island Largest black guillemot colony and northernmost horned puffin colony in Alaska; site of 

long-term research project 

8 Elson Lagoon Important staging habitat for shorebirds, especially red phalaropes and a variety of 

waterfowl species

9 Teshekpuk Lake/Dease Inlet Internationally recognized as a molting area for Arctic nesting geese

10 Colville River Delta Major importance as breeding, feeding, and staging area for waterfowl, shorebirds, and raptors

11 Eastern Beaufort Sea Lagoons and

Barrier Islands

Post-breeding habitat for waterfowl, especially long-tailed ducks, and red and red-necked 

phalaropes

12 Northeast Arctic Coastal Plain Foraging and staging habitat for post-breeding lesser snow geese
Chapter 3

Ecological and Subsistence Context 61

• Restricted-ranges species (species vulnerable because 

they are not widely distributed); 

• Species that are vulnerable because their populations 

are concentrated in one general habitat type or biome; 

or 

• Species, or groups of similar species (such as 

waterfowl or shorebirds), that are vulnerable because 

they occur at high densities due to their congregatory 

behavior. 

Colonial and Non-Colonial Seabirds

Nesting habitat for seabirds is limited in the area, so 

they are aggregated in a few very large colonies. Cliff-nesting 

seabirds reach their northern extent in the Chukchi Sea at Cape 

Lisburne and Cape Thompson. These colonies provide most of 

the cliff-nesting habitat for thick-billed murres (Uria lomvia) 

and black-legged kittiwakes (Rissa tridactyla) in the eastern 

Chukchi and are the largest colonies in the region with more 

than 200,000 birds present at each location. Horned puffins 

(Fratercula corniculata) breed at Cape Lisburne, as well as at 

Chamisso Island in Kotzebue Sound in the southern Chukchi 

Sea, and more recently at Cooper Island, a small barrier island 

in the western Beaufort Sea. A well-studied colony of black 

guillemots (Cepphus grille) is located at Cooper Island. Small 

colonies of glaucous gulls (Larus hyperboreus) and Arctic 

terns (Sterna paradisaea) are distributed in coastal areas 

throughout the study area (Sowls and others, 1978; Weiser and 

Powell, 2010). During the ice-free season, seabirds move into 

the Chukchi Sea from areas farther south and are distributed 

widely. These include murres (Uria spp.), black-legged 

kittiwakes (Rissa tridactyla), crested (Aethia cristatella), least 

(Aethia pusilla), and parakeet (Cyclorrhynchus psittacula) 

auklets, short-tailed shearwaters (Puffinus tenuirostris), 

northern fulmars (Fulmarus glacialis), jaegers (Stercorarius 

spp.), and others. 

Kittlitz’s Murrelets (Brachyramphus brevirostris), a 

small, uncommon, non-colonial seabird that nests primarily 

in glaciated landscapes in southeast and south-central Alaska, 

west through the Aleutian Islands, also nest in small numbers 

on the Seward and Lisburne Peninsulas in northwest Alaska. 

At-sea records for this species exist in Kotzebue Sound, near 

Point Hope and in Ledyard Bay, including the Chukchi Sea 

oil and gas lease area and the Beaufort Sea (R. Day, Alaska 

Biological Research, Inc., oral commun., 2011). Kittlitz’s 

Murrelets are a species of conservation concern because of 

recent population declines in more southerly areas of their 

breeding range. They are considered a candidate species 

under the Endangered Species Act by the USFWS. Very 

little is known about their population status, distribution, and 

abundance in northwest Alaska.

Loons 

Three species of loons nest in coastal areas of the 

Chukchi and Beaufort Seas and use coastal marine habitats 

for foraging: the red-throated loon (Gavia stellata), Pacific 

loon (G. pacifica), and yellow-billed loon (G. adamsii). Redthroated loons tend to nest in small tundra ponds close to 

the coast and feed primarily in saltwater during the breeding 

season, making trips back and forth to their nesting ponds. 

Both Pacific loons and yellow-billed loons nest on larger 

tundra lakes that contain fish. All loons use coastal marine 

habitats during parts of their annual cycle. Red-throated loons 

and yellow-billed loons have an interesting migration strategy. 

Birds from the North Slope migrate and winter in coastal 

habitats along the western North Pacific wintering as far south 

as the Korean Peninsula. In contrast, birds nesting on the 

Seward Peninsula winter in marine waters of western Alaska. 

Recent telemetry data indicate widespread use of coastal 

and marine habitats in the Chukchi Sea during breeding and 

migration (fig. 3–14). 

The USFWS was petitioned to list the Alaska breeding 

population of yellow-billed loons, and after review determined 

that listing the species was warranted but precluded because of 

higher priority listing actions. It is a candidate species under 

the ESA. Relatively little is known about these species in 

Arctic Alaska, although all three species of loons are currently 

under study on the North Slope of Alaska. Ongoing concerns 

include disturbance from development (loons are particularly 

vulnerable to disturbance), oil pollution, and harvest.

Sea Ducks

Fifteen species of waterfowl make up the sea ducks, 

which nest in coastal areas or in freshwater habitats and winter 

primarily in coastal marine habitats. Five species dominate 

the sea duck avifauna of the Chukchi and Beaufort Seas: the 

long-tailed duck (Clangula hyemalis), and the eiders (common 

eider Somateria mollissima, king eider—S. spectabilis, 

spectacled eider—S. fischeri, and Steller’s eider—Polysticta 

stelleri). Common eiders, king eiders, and long-tailed ducks 

are the most abundant of the species. Eiders and long-tailed 

ducks are the first of the waterfowl to appear in the spring, 

exploiting leads in the ice as they open in the Chukchi and 

Beaufort Seas between shorefast and pack ice. Common eiders 

nest primarily in small colonies on barrier islands and other 

coastal habitats. Other sea ducks are more dispersed nesters 

across the North Slope. Sea ducks migrate in large numbers 

along the coasts of the Chukchi and Beaufort Seas to and from 

nesting grounds in Alaska and the Canadian Arctic, and are 

important subsistence species. Coastal lagoons of the Beaufort 

Sea are particularly important habitats for long-tailed ducks 

after breeding and before freeze-up. 
62 An Evaluation of the Science Needs to Inform Decisions on Outer Continental Shelf Energy Development in the Chukchi and Beaufort Seas, Alaska

Figure 3–14. Locations of red-throated (red squares) and yellow-billed (yellow circles) loons based on satellite 

transmitters in 2010. Sites of original marking are indicated by stars (U.S. Geological Survey, unpub. data, 2010). 

(NPR-A, National Petroleum Reserve Alaska.)

Two species of eiders are of particular conservation 

concern for the Department of the Interior: spectacled eider 

and Steller’s eider. Both are listed as threatened by the 

USFWS. Spectacled eiders breed across the North Slope 

of Alaska, especially west of the Prudhoe Bay area. They 

use coastal marine habitats during non-breeding in both 

the Beaufort and Chukchi Seas (fig. 3–15). Ledyard Bay in 

the Chukchi Sea is an important staging area and formally 

designated as Critical Habitat for this species. The entire 

World’s population winters in highly dense concentrations 

within the sea ice of the northern Bering Sea (fig. 3–15) 

between St. Lawrence and St. Matthew Islands. An ongoing 

telemetry study will reveal new information about timing of 

migration, migratory pathways, and residence times in coastal 

areas of the Beaufort and Chukchi Seas that could be impacted 

by development activities.

Steller’s eiders were formerly an abundant breeding bird 

on the Yukon Delta and the North Slope. During summer, they 

are now found primarily between Prudhoe Bay and Point Lay 

and number in the low thousands. Following breeding, they 

undergo a long migration to molting and wintering habitats 

on the Alaska Peninsula and the Aleutian Islands where they 

mix with the more abundant population of Steller’s eiders that 

breeds in Russia. 
Chapter 3

Ecological and Subsistence Context 63

Geese and Swans

Geese and swans are the largest of the waterfowl that 

use coastal areas in the Chukchi and Beaufort Seas. The 

tundra swan (Cygnus columbianus) and four species of geese 

(greater white-fronted goose—Anser albifrons, lesser snow 

goose—Chen caerulescens, Pacific brant—Branta bernicla

nigricans, and Canada goose—B. canadensis) exploit these 

habitats during the summer months. Tundra swans are a 

common breeding bird on tundra habitats of the coasts of the 

Beaufort and Chukchi Seas. Virtually the entire population of 

tundra swans that nest on the Beaufort Sea coast winter in the 

Atlantic Flyway. Marked swans nesting along the coast of the 

Chukchi Sea wintered in the Pacific Flyway. 

All four species of geese breed in the study area. 

Greater white-fronted geese are abundant and breed within 

a 30 km strip along the coasts of the Chukchi and Beaufort 

Seas (Johnson and Herter, 1989). They winter in the Pacific 

and Central Flyways. Lesser snow geese nest colonially 

on Howe Island near Prudhoe Bay and west to the Meade 

River, Teshekpuk Lake, and the Colville River Delta. They 

also nest as far west as the Point Lay area on the coast of the 

Chukchi Sea (Ritchie and others, 2000). Lesser snow geese 

from Alaska primarily winter in California, New Mexico, and 

Mexico. Pacific brant nest on the Arctic Coastal Plain from 

the Sagavanirktok Delta west to the Barrow area and south to 

the Point Lay area on the coast of the Chukchi Sea (Stickney 

and Ritchie, 1996; Ritchie and others, 2000). They stage in the 

autumn at Izembek Lagoon and winter primarily on the Alaska 

Peninsula and south to Baja California, Mexico. Pacific brant 

have exhibited a significant and continuous population decline 

over the period 1965–2009. Suspected limiting factors include 

loss of wintering and staging habitats and harvest. The most 

critical habitats for waterfowl species in the Beaufort and 

Chukchi Seas area include coastal nesting colonies; pre- and 

post-breeding staging habitats in estuaries such as Kasegaluk 

Lagoon, Peard Bay, Smith Bay, and Harrison Bay; and molting 

sites in the large-lake and coastal areas northeast of Teshekpuk 

Lake. Breeding Canada geese have increased in numbers on 

the Arctic Coastal Plain over the last 2 decades, although 

the density of molting birds in the Teshekpuk Lake area has 

remained relatively stable over the past 30 years. 

The Teshekpuk Lake area in the National Petroleum 

Reserve–Alaska (NPR–A) is an internationally important 

habitat for molting Arctic-nesting geese, especially whitefronts, brant, and Canada geese. Many failed-nesting and 

non-nesting brant from the Yukon-Kuskokwim Delta undergo 

a northward migration to molt in this area. Recent research 

suggests that brant are shifting molting sites within the 

NPR–A from freshwater lakes to coastal areas, perhaps in 

response to ecosystem changes related to saltwater intrusion 

into freshwater marshes that enhances growth of saltwater 

tolerant vegetation that brant favor (Flint and others, 2008; 

Lewis and others, 2010). 

Figure 3–15. Locations (yellow dots) of spectacled eiders instrumented with satellite transmitters. Black stars are sites of original 

capture. Note use of the Beaufort Sea and Chukchi Sea coasts and extensive mixing of birds in United States and Russian waters 

(U.S. Geological Survey, unpub. data, 2010).
64 An Evaluation of the Science Needs to Inform Decisions on Outer Continental Shelf Energy Development in the Chukchi and Beaufort Seas, Alaska

Shorebirds

Coastal areas of the Beaufort and Chukchi Seas support 

large numbers of breeding, staging, and migrating shorebirds. 

At least 29 species of shorebirds nest in this region, the 

most abundant being American golden plovers (Pluvialis 

dominica), semipalmated sandpipers (Calidris pusilla), 

pectoral sandpipers (C. melanotos), dunlin (C. alpina), longbilled dowitchers (Limnodromus scolopaceus), and red-necked 

(Phalaropus lobatus) and red (P. fulicaria) phalaropes (Alaska 

Shorebird Group, 2008). The Arctic Coastal Plain of Alaska 

is considered one of the premier shorebird breeding areas in 

the World. Distributions of shorebird species vary within the 

area; in general, the largest numbers and the greatest diversity 

occur west of the Colville River, although certain sites east of 

the Colville River (for example, Prudhoe Bay, Canning River 

Delta) also have high species richness. The Alaska Shorebird 

Group (2008) identified a number of areas on the coasts of the 

Chukchi and Beaufort Seas that are important to shorebirds. 

These include the Colville River Delta, the Canning River 

Delta, Kasegaluk Lagoon, Peard Bay, Elson Lagoon, and 

shorelines and barrier islands along the coastal plain of the 

Arctic National Wildlife Refuge. 

All shorebirds are absent from the Arctic Coastal Plain 

and most also are absent from Alaska during the non-breeding 

season. Many undertake spectacular migrations to southern 

hemisphere wintering areas after gorging on invertebrates on 

western Alaska tideflats (for example, Gill and others, 2008). 

Because of that, Alaskan-breeding shorebirds are vulnerable 

to a variety of threats outside of Alaska (Alaska Shorebird 

Group, 2008). 

All Alaska breeding species of shorebirds are 

considered at-risk. Alaska currently has 20 shorebird 

populations considered to be of high concern or imperiled 

and 21 populations of low to moderate concern. The Alaska 

Shorebird Group (2008) recognized American golden plover, 

upland sandpiper, whimbrel, bar-tailed godwit, red knot, 

sanderling, dunlin, and buff-breasted sandpiper as priority 

conservation species for the Arctic Coastal Plain. Many of 

these species, as well as pectoral, western, and semipalmated 

sandpipers, and red and red-necked phalaropes use coastal 

areas for feeding after breeding and prior to migration and 

could be vulnerable to development and oil spills. Phalaropes 

are the only shorebirds that also regularly use offshore areas. 

Overview—Arctic Birds Information Needs

The most significant information need for birds using 

offshore marine and coastal regions of the study area is 

for recent data on species composition, distribution, and 

abundance. We know little about the present-day distribution 

of marine birds in the region; in fact, most of the data on 

distribution and abundance of birds in coastal and marine areas 

of the Chukchi and Beaufort Seas were gathered in the 1970s 

and 1980s (fig. 3–16) (U.S. Geological Survey, unpub. data, 

1974–79, 1980–89, 1990–99, 2000–2008). These data show a 

wide variety of seabirds using this region, including loons and 

several marine geese and ducks in coastal areas; shearwaters, 

phalaropes, and auklets concentrated in early autumn in the 

Chukchi Sea; and Arctic specialists concentrated on the coast 

or offshore in the Beaufort Sea, for example, Ross’s gull 

(Rhodostethia rosea), Sabine’s Gull (Xema sabini), black 

guillemot, glaucous gull, jaegers, and Arctic tern. The present 

day distribution and abundance of these species are largely 

unknown, although declines are documented or suspected for 

several species (ivory gull [Pagophila eburnean], Ross’s gull, 

some eider, and loon species), and it would require a repeat 

of historical surveys to assess changes. This is especially 

critical because of the large changes that have occurred in the 

Arctic, especially related to the diminished extent of sea ice in 

the Beaufort and Chukchi Seas in summer and autumn. Data 

collected in the 1970s and 1980s may no longer be relevant to 

management needs. This data gap is being addressed to some 

extent by the BOEMRE and USFWS through BOEMRE’s 

Environmental Studies Program, and through Shell’s Chukchi 

Offshore Monitoring In Drilling Area Program (COMIDA). 

In addition to general information on distribution and 

abundance, integrated studies on seabird dynamics of the 

central Chukchi Sea in relation to oceanography, sea-ice 

change, and trophic dynamics are needed. The central Chukchi 

Sea is highly productive during summer, with extremely high 

levels of primary production and enormous standing crops 

of zooplankton. Most of this is due to the conveyor belt of 

rich waters brought north from the Bering/Anadyr current. 

In late summer/early autumn, the central Chukchi Sea also 

supports immigration of vast numbers of shearwaters, auklets, 

phalaropes, and other planktivorous seabirds. Most of what 

we know of the seabird movement into the Chukchi Sea is 

based on limited opportunistic surveys. A more detailed study 

of the dynamics of this area, including the lease sale area, 

is warranted given its strategic position north of the Bering 

Strait, and the pathway through which all vessels (including 

tankers) must travel to get to and from the Arctic Ocean. 

Data needs are not restricted to marine areas. Continued 

monitoring of reproductive performance of seabirds at 

colonies at Cape Lisburne and Cooper Island are essential 

as colony performance provides a window into what is 

occurring in offshore marine areas. Coastal and inland areas 

also are changing and along with it the birds that depend 

on these habitats. Coastal erosion, saltwater intrusion, and 

thermokarsting are all active processes, resulting in habitat 

changes that will influence birds. Offshore development will 

result in onshore development as well, principally to support 

the offshore activities and to move oil and gas products, 

likely through pipelines to the Trans-Alaska pipeline. This 

infrastructure will require careful site planning and mitigation 

to prevent impacts to wildlife populations. 
Chapter 3

Ecological and Subsistence Context 65 Figure 3–16. Distribution of marine bird surveys in the Beaufort and Chukchi Seas by decade showing disparity of temporal and spatial sampling among decades. Source: U.S. Geological Survey (2011), North Pacific Pelagic Seabird Database, accessed April 18, 2011, at http://alaska.usgs.gov/

science/biology/nppsd/index.php
66 An Evaluation of the Science Needs to Inform Decisions on Outer Continental Shelf Energy Development in the Chukchi and Beaufort Seas, Alaska

Marine and Diadromous Fish

The Alaskan Chukchi and western Beaufort Seas support 

at least 112 fish species (L. Thorsteinson, U.S. Geological 

Survey, written commun., 2010; also see Mecklenburg and 

others, 2002). Dominant families of fishes include lampreys, 

sleeper sharks, dogfish sharks, herrings, smelts, whitefishes, 

trouts and salmons, lanternfishes, cods, sticklebacks, 

3.06. Findings and Recommendations: Recent at-sea information on marine birds for most of the study area is lacking or unpublished. 

Similarly, with the exception of information from Cooper Island and Cape Lisburne, much of the seabird colony information is out-of-date. Filling 

these data gaps would enhance our ability to measure the effects of climate change and assess the impacts of development and transportation. 

The Chukchi Sea is a dynamic area for marine birds during the summer. Studies to examine seasonal dynamics of seabirds in the Chukchi Sea 

related to oceanography, climate, sea-ice dynamics, primary and secondary productivity and movements of birds from breeding colonies (for 

example, Cape Lisburne) are necessary. Studies in the Chukchi Sea Lease Sale Area have been underway by Shell to address this but are not yet 

published. Similar studies, but focused on sea ducks and their benthic habitats, also would be helpful to evaluate climate impacts and to assess 

impacts of oil and gas development. 

Data from studies of birds at colonies, for example at Cooper Island and Cape Lisburne, need to be published and continued. Onshore studies of 

seabirds to measure abundance, productivity, and food habitats provide a unique window and understanding into offshore marine processes. 

Modeling the impact of oil pollution on birds using oil-spill trajectory models, population models, satellite telemetry data, and new information 

on seabird distribution and abundance would be informative for some species.

A better understanding of the timing of migration and habitat use of at-risk species of waterbirds in the Chukchi and Beaufort Seas. New 

information based on satellite telemetry is available for common, king, and spectacled eiders, and red-throated and yellow-billed loons. Existing 

data need to be analyzed and published, and additional telemetry studies are necessary to assess timing and pathways of migration and use of 

coastal areas for foraging and molting for other species including Pacific brant, long-tailed ducks, and Pacific and Arctic (G. arctica) loons.

Coastal lagoons of the Chukchi and Beaufort Seas are important stopovers for migrating birds, particularly Pacific brant. Data on distribution, 

numbers, and periods when birds occur in coastal lagoons are needed to identify sensitive areas and times when disturbance should be 

minimized. 

Further analyses and studies are needed to increase the understanding of seasonal and inter-annual variation in shorebird use (numbers of 

birds, timing of their use, change in site quality) of key post-breeding areas, especially coastal areas where oil development is likely to occur (for 

example, the deltas of the Meade, Ikpikpuk, Colville, Sagavanirktok, and Canning Rivers, and coastal sites on NPR–A). 

Sea-level rise, increased frequency and severity of storms, and more frequent and severe episodes of coastal erosion and flooding are occurring 

or are predicted to occur in the study area and could have large impacts on migratory birds. Many northern shorebird and waterfowl species 

are dependent on these littoral habitats during some phase of their annual cycle. Understanding change in coastal geomorphology—from both 

physical and trophic standpoints and whether driven by climate change or other factors—is an important data gap.

If an oil spill were to occur in broken sea-ice habitats, or if lead systems were to become contaminated with oil, understanding and being 

able to predict what wildlife would be affected in these ice habitats and the effectiveness or consequences of hazing Arctic marine animals, 

including birds, will be important.

Local residents are often the first to notice changes in fish and wildlife populations. Mechanisms should be developed to better solicit and 

integrate local traditional knowledge as a basic source of information. 

greenlings, sculpins, sailfin sculpins, fathead sculpins, 

poachers, lumpsuckers, snailfishes, eelpouts, pricklebacks, 

gunnels, wolffishes, sand lances, and righteye flounders. 

Forty-nine species are known to be common to both the 

Beaufort and Chukchi Seas. Additional species are likely to be 

found in the Alaskan Arctic when coastal and offshore waters 

are more thoroughly surveyed.

Marine Arctic fishes of Alaska can be divided into two 

primary assemblages: marine fish and diadromous fish. 
Chapter 3

Ecological and Subsistence Context 67

Marine Fish

Mecklenburg and others (2008) and Minerals 

Management Service (2008) recently described the state of 

knowledge of Arctic marine fishes. Marine waters support the 

most diverse, although least well known, fishes of the area. 

Studies of marine fishes in the region are very limited; most 

of the surveys/studies have been performed in coastal waters 

landward of the 200-m isobath, with few surveys having 

sampled deeper waters. Studies have been hampered by a lack 

of commercial fisheries, short ice-free seasons, and logistical 

difficulties. Marine fishes prefer the colder, more saline 

coastal water seaward of the nearshore brackish-water zone. 

As summer wanes, the nearshore zone of the Alaska Beaufort 

Sea becomes more saline due to decreased freshwater input 

from rivers and streams and marine intrusions associated with 

summer storms. During this time, marine fishes often share 

nearshore brackish waters with diadromous fishes, primarily to 

feed on the abundant epibenthic fauna or to spawn. In autumn, 

when diadromous fishes have moved out of the coastal area 

and into freshwater systems to spawn and overwinter, marine 

fishes remain in the nearshore area to feed. The USGS, in 

collaboration with BOEMRE, is currently developing an 

Arctic Marine Fish Ecology Catalog that will provide a 

complete set of species accounts and synthesize ecological 

knowledge about the marine ecology of fishes in the Chukchi 

and Beaufort Seas (Thorsteinson and others, 2011). This 

catalog also will include aspects of the human dimensions of 

fish use in the region by summarizing subsistence catch data to 

depict regional harvest patterns.

To better understand fish resources, the Minerals 

Management Service (2008) further refined the scale 

of primary fish assemblages into secondary, ecological 

assemblages based on fish behavior and ecology, and general 

oceanographic/landscape features, such as the continental 

shelf break or polar ice. These assemblages and their 

widespread or abundant species include: (1) the neriticdemersal assemblage (at or near the seafloor of the continental 

shelf) with twohorn and fourhorn sculpin, polar eelpout, and 

Arctic flounder; (2) the neritic-pelagic assemblage (within the 

water column of the continental shelf) with Pacific herring, 

Arctic cod, capelin, and Pacific sand lance; (3) the oceanicdemersal assemblage (living on or close to the bottom off the 

continental shelf—seaward of the 200-m isobath) with ogac, 

ribbed sculpin, spatulate sculpin, shorthorn sculpin, spinyhook 

sculpin, archer eelpout, pale eelpout, and daubed shanny; 

(4) the oceanic-pelagic assemblage (inhabiting the water 

column of oceanic waters seaward of the 200-m isobaths) 

with Pacific herring, Arctic cod, polar cod, pollock, Pacific 

sand lance, and the glacier lanternfish; and (5) the cryopelagic 

assemblage (inhabiting neritic or oceanic waters, but during 

their lifecycle, are associated with sea ice) with Arctic cod and 

Pacific sand lance. 

Because of the influence of sea ice in the Arctic, and 

in particular the importance of Arctic cod in Arctic marine 

ecosystems, additional detail is provided here. The term 

“cryopelagic” is used to describe fishes that actively swim 

in neritic or oceanic waters but, during their lifecycle, are 

associated with drifting or fast ice. Both young and adult 

fishes can be associated with ice or water immediately 

beneath the ice. These relationships are usually trophic in 

nature, but in some cases, ice provides fishes with a shelter 

from predators. Andriyashev (1970) described what may 

be the first known cryopelagic fish species, the Arctic cod. 

Arctic cod are most common among broken ice or near the 

ice edge. Here, as the ice thaws and breaks up, phytoplankton 

and zooplankton develop and provide food for Arctic cod. 

It is possible that the fish also feed on organisms of the 

amphipod-diatom ice community inhabiting the lower ice 

layer. At the same time, cod apparently use sea ice as shelter 

from the numerous enemies attacking them from both water 

and air. Arctic cod play a significant role in relatively short 

food chains that directly, or indirectly, support subsistence 

lifestyles of indigenous people. The Arctic cod is a key prey 

of many marine mammals and seabirds as evidenced by their 

occurrence in the diets of belugas and ringed and bearded 

seals, Pacific walruses (occasionally), thick-billed and 

common murres, black guillemots, black-legged kittiwakes, 

northern fulmars, Arctic terns, and glaucous, Sabine’s, ivory, 

and Ross’s gulls. Arctic cod also are of indirect importance to 

polar bears and Arctic foxes, because their principal marine 

food, the ringed seal, also relies on them as food. Considerable 

research underscores the critical function of Arctic cod in 

Arctic marine ecosystems, because no alternate food source of 

equivalent trophic value exists. 

Diadromous Fish

Diadromous fishes are those that move between and are 

able to live in fresh, brackish, and (or) marine waters due to 

various biological stimuli, such as feeding or reproduction, 

or ecological factors, such as temperature, oxygen level, 

or specific spawning-habitat need. Diadromous fishes 

include all migration types (anadromous, catadromous, and 

amphidromous) between marine and freshwaters, including 

single lifetime events, repetitive multiyear events, spawning 

migrations, feeding migrations, and seasonal movements 

between environments. Diadromous fishes inhabit many of the 

lakes, rivers, streams, interconnecting channels, and coastal 

waters of the North Slope. Common diadromous fishes include 

Arctic cisco, least cisco, Bering cisco, rainbow smelt (now 

Arctic smelt), humpback whitefish, broad whitefish, Dolly 

Varden char, and inconnu. The highest concentration and 

diversity of diadromous fishes in the area occur in river-delta 
68 An Evaluation of the Science Needs to Inform Decisions on Outer Continental Shelf Energy Development in the Chukchi and Beaufort Seas, Alaska

areas, such as the Colville and the Sagavanirktok Rivers. 

Lakes that are accessible to diadromous fishes typically are 

inhabited by them in addition to resident freshwater fishes. 

The least cisco is the most abundant diadromous fish found in 

these lakes. With the first signs of spring breakup, adult and 

juvenile diadromous fishes move out of freshwater rivers and 

streams and into the brackish coastal waters. 

Some diadromous fishes disperse widely from their 

streams of origin (for example, Arctic cisco and some Dolly 

Varden char). Others, like broad and humpback whitefish and 

least cisco, do not; they are seldom found anywhere but near 

the mainland shore. Most diadromous fishes initiate relatively 

long and complex annual migrations to and from coastal 

waters. However, some populations of Dolly Varden char, 

least cisco, and broad and humpback whitefish never leave 

freshwater. Arctic cisco in the Colville River area originate 

from spawning stocks of the Mackenzie River in Canada. 

The vast majority of the Arctic cisco inhabiting the Alaskan 

Beaufort Sea were carried there from Canada by westerly 

currents. During the Alaska phase of their life history, Arctic 

ciscos reside in the Colville River Delta from autumn to 

spring, and then forage into food-rich coastal waters during 

the brief Arctic summer. The Colville River, by virtue of its 

size, is the major overwintering site for Arctic cisco in Arctic 

Alaska, although other deltas, such as the Sagavanirktok, may 

harbor smaller populations. During the 3- to 4-month openwater season that follows spring breakup, diadromous fishes 

accumulate energy reserves for overwintering, and, if sexually 

mature, they spawn. Although their prey is concentrated in the 

nearshore zone, their preference for this area also is believed 

to be correlated with its warmer temperature.

Overview—Arctic Fish Information Needs

A combination of literature review and expert 

consultations was used to evaluate existing information and 

knowledge about Arctic marine and anadromous fishes in 

light of its adequacy for decision making. Baseline surveys 

for marine fish and shellfish resources tend to be dated for 

most of the study area (1960s to 1990s) with most data 

collections reflecting infrequent sampling with respect 

to time and geography and objectives for environmental 

assessment purposes more so than for fisheries management. 

In the past 5 years, Shell has sponsored surveys in the 

northeastern Chukchi Sea, National Oceanic and Atmospheric 

Administration (NOAA)/BOEMRE surveys offshore and to 

the west of Barrow, and NOAA/Russia expeditions into the 

northern Chukchi Sea and Arctic Basin. With respect to OCS 

oil and gas development, fisheries investigations have focused 

on coastal habitats and their use, primarily during open-water 

periods, by salmonid species valued in subsistence and smallscale commercial fisheries, and nearshore fishes that might 

be affected by changes in brackish water habitats by solid-fill 

causeways in and nearby Prudhoe Bay. The National Science 

Foundation and others have funded ecological research in the 

northern Bering and southeastern Chukchi Seas to investigate 

coupling of regional pelagic and benthic ecosystems.

Resource inventories for freshwater, marine, and 

anadromous/amphidromous fish are reasonably complete 

for the Chukchi and Beaufort Seas. Life cycle information 

is lacking for all species, and with respect to fish species, is 

most complete for Arctic cisco in the Colville River. Although 

information about the population dynamics for key species of 

ecological significance (for example, Arctic cod, sand lance, 

and capelin) or subsistence use (for example, Dolly Varden, 

Arctic cisco, and inconnu) is critical for analysis of potential 

oil-spill impacts or other ecosystem disturbances, this level of 

resolution does not exist. Potential oil-spill impacts in shallow, 

coastal waters during open-water periods (June–September) 

could seriously impact key anadromous/amphidromous fish 

populations including Dolly Varden (from rivers originating 

in the Brooks Range), whitefish (from lower energy rivers/

lakes to the west of the Brooks Range and northwestern 

Alaska), and salmon (Kotzebue Sound). Similarly, existing life 

history and habitat utilization information suggest that certain 

marine populations that seasonally aggregate in nearshore 

and intertidal areas for spawning (for example, herring, 

capelin, and rainbow smelt [now Arctic smelt]) or feeding (for 

example, Arctic cod) could suffer significant losses from spills 

or associated onshore industrial developments supporting OCS 

activities (for example, tankers and service vessels, pipelines, 

or causeways and artificial islands) or other kinds of resource 

extraction (for example, gravel mining).
Chapter 3

Ecological and Subsistence Context 69

Human Settlements, Demographics, and 

Political Organization

(from Minerals Management Service, 2008, and 

North Slope Borough, 2011)

Human communities that have been and could be affected 

by future offshore oil and gas development are located 

primarily along the coasts of the Beaufort and Chukchi Seas 

and include from east to west: Kaktovik, Nuiqsut, Atqasuk, 

Barrow, Wainwright, Point Lay, and Point Hope. Additional 

communities farther south along the Chukchi Sea coast, such 

as Kivalina, Kotzebue, and Shishmaref also could be impacted 

by development but are not discussed further here. The 

North Slope has a fairly homogeneous population of Iñupiat, 

approximately 72 percent in 1990 and 68.38 percent in 2000 

of the population. The percentage in 2000 ranged from 89.1 

percent Iñupiat in Nuiqsut to 64.0 percent Iñupiat in Barrow. 

Each of the Borough’s communities, with the exception of 

Point Lay, has a city government. Although certain municipal 

powers were turned over to the North Slope Borough when 

it was formed in 1972, community governments play an 

important role in the administration of Borough programs. In 

addition, local governments administer some State and Federal 

programs, such as capital improvements and housing. This 

section provides a profile of the North Slope Borough and 

the communities that border the Beaufort and Chukchi Seas 

that have been and could be impacted by offshore oil and gas 

development. 

3.07. Findings and Recommendations: Information about status and trends, habitat requirements, relative distribution and abundance, 

and knowledge of life history stages of marine fish is incomplete and unavailable for large expanses of Arctic nearshore and shelf waters 

and should be developed for indicator species (that is, species that are broadly distributed, of subsistence or ecological significance, readily 

available for vulnerability assessments, and deemed sensitive to offshore oil and gas development). Onshore-offshore linkages associated with 

life history requirements have not been described. 

Logistical, technological, and cost considerations have limited the practicality of winter surveys and under ice resource information is limited 

and inadequate for evaluation of impacts.

Greater reliance on modern scientific technologies and their applications, such as remote sensing, telemetry, genetics and molecular biology, 

and quantitative ecology (for example, predictive models) is needed to establish species environmental relationships, address existing gaps 

about relative importance of habitats, understand natural variation in fluctuating stocks, and to more accurately assess effects of proposed 

offshore oil and gas activities.

Effects of ocean variability on production cycles and the distributional behavior, movement, and abundance of marine and anadromous fishes 

should be emphasized in future research and monitoring on select resources in strategic locations and undertaken to understand natural 

trajectories of change and effects of human interactions. 

Effects of environmental parameters on physiological processes [feeding, digestion, assimilation, growth, responses to stimuli (that is, 

orientation and swimming speed), and reproduction] are poorly known for most Arctic fish species. These processes are dependent on key water 

properties, including temperature, salinity, light penetration, and oxygen concentration. Animal health also is affected by the presence of toxic 

substances, infectious pathogens, and parasites. 

Seismic and noise effects on fishery resources have not been studied and is a research need. Much information could be borrowed from marine 

mammal research in Alaska and elsewhere regarding natural ambient sound and anthropogenic sound levels to guide experimentation.

Effects of invasive species associated with increased tankering, vessel support, and offshore construction activities on important biological 

habitats and ecosystems are unknown.

Biological hotspots for long-term research and monitoring of coastal, marine, and human impacts need to be identified. Potential sites include: 

Bering Strait (marine ecosystem processes); Kasegaluk, Simpson, and Beaufort lagoons (nearshore fish assemblages); Barrow Canyon/Hannah 

Shoal (benthic productivity); Capes Lisburne and Thompson (seabird colony and fishery oceanography dynamics); Point Barrow (transitional 

biogeographic zone); Boulder Patch (kelp bottom ecosystem); Stefansson Sound/Camden Bay (Arctic cod ecology); Mackenzie, Colville, and 

Canning River Deltas (physical and biological onshore-offshore linkages); ice edge and polynyas (biological significance to fish, birds, and marine 

mammals).

Local residents are often the first to notice changes in fish and wildlife populations. Mechanisms should be developed to better solicit and 

integrate local traditional knowledge as a basic source of information.
70 An Evaluation of the Science Needs to Inform Decisions on Outer Continental Shelf Energy Development in the Chukchi and Beaufort Seas, Alaska

The North Slope Borough. Prior to the discovery 

and development of oil and gas on the North Slope and the 

formation of the North Slope Borough (NSB) in 1972, the 

population of the five then-existing villages (that is, Barrow, 

Kaktovik, Anaktuvuk Pass, Point Hope, and Wainwright) 

totaled about 2,500 people. Each village had limited political 

power, social services, and infrastructure. Per capita and 

household incomes were low, and North Slope residents relied 

heavily on local subsistence resources for food, clothing, 

and heat. The majority of NSB growth since 1970 has been 

in the three communities established after the incorporation 

of the NSB; however, large investments have been made in 

the infrastructures of all NSB communities. Iñupiat society 

maintains a strong subsistence-based culture.

The formation of the NSB in 1972 was motivated, 

in part, by the desire to capture petroleum industry based 

property tax revenue for local improvement and to exercise a 

degree of control over the pattern of petroleum development 

through the permitting of onshore oil infrastructure. Other 

factors that contributed to the motivation include the exercise 

of local control over Federal education and health care and 

the providing of services by the State that were lacking. 

Communities deliberately transferred municipal power to the 

Borough government, including basic community services in 

1974, education in 1975 with the formation of the North Slope 

School District, and public safety in 1976. The result has been 

a strong regional government. 

The NSB provides nearly all municipal services to 

the villages, including the operation of basic services and 

facilities. The Borough’s Capital Improvement Program (CIP) 

created most of the infrastructure that serves the needs of the 

communities. Through the provision of these services, the 

Borough either directly or indirectly provides the majority of 

full-time employment in the villages. The NSB government 

and the school district are the largest employers in the region. 

However, in the period from 1998 to 2003, NSB government 

employment declined as did employment in the CIP, primarily 

due to the completion of construction projects in communities 

outside of Barrow. Over the last 25 years, these services have 

improved the economic and social well-being for Borough 

residents in areas of health, social services, public safety, 

education, communications, and transportation. The Borough 

provides utilities in each of the communities, where a large 

majority of housing units now are connected to public water 

and sewer. The NSB Department of Health provides a hospital 

in Barrow and health clinics in outlying villages. Social 

services furnished by the Borough include housing, meals 

and transportation for seniors, mental health counseling, and 

day care. The Borough provides each of the villages with law 

enforcement, fire protection, and search and rescue services, 

with a combination of full-time employees and volunteers. 

Secondary-school facilities have been provided in each 

village, and postsecondary education opportunities have 

improved. The Borough owns and operates public airports 

in all the communities, except Barrow and Deadhorse where 

they are State operated, and fosters community well-being 

through creation and support of other institutions, such as the 

Commission on Iñupiaq History, Language, and Culture. Since 

peaking in 1986, oil tax revenues have declined as the value of 

oil production and pipeline infrastructure depreciates. As these 

revenues have declined, Borough expenditures have similarly 

declined.

Kaktovik. Incorporated in 1971, Kaktovik is the 

easternmost village in the NSB. Its 2006 population was 

288; its population in 2004 of 284 was 84.0 percent Iñupiat. 

The village is on the north shore of Barter Island, one of the 

largest of a series of barrier islands along the north coast, 

situated between the Okpilak and Jago Rivers on the Beaufort 

Sea coast, and is located 300 mi east of Barrow. Kaktovik 

abuts the Arctic National Wildlife Refuge. Until the late 19th 

century, the island was a major trade center for the Iñupiat and 

was especially important as a bartering place for Iñupiat from 

Alaska and Inuit from Canada. 

Nuiqsut. Nuiqsut sits on the west bank of the Nechelik 

Channel of the Colville River Delta, about 25 mi inland from 

the Arctic Ocean and approximately 150 mi southeast of 

Barrow. Its population in 2006 was 417; its 2000 population 

of 433 was 89.1 percent Iñupiat Eskimo. Nuiqsut, one of 

three abandoned Iñupiat villages in the North Slope region 

identified in the Alaska Native Claims Settlement Act, was 

resettled in 1973 by 27 families from Barrow. Today, Nuiqsut 

is experiencing rapid social and economic change due to 

the development of local infrastructure, the development of 

the Alpine oil producing facility, potential Alpine satellite 

development, and potential oil development in the National 

Petroleum Reserve, Alaska. Most of Nuiqsut’s marine 

subsistence-harvest area lies adjacent to areas in the Beaufort 

Sea. 

Barrow. Barrow is the largest community on the North 

Slope and is its regional center. In 1970, the Iñupiat population 

of Barrow represented 91 percent of the total population of 

Barrow, but by 1990, Iñupiat representation had decreased 

to 63 percent. Between 1980 and 1985, Barrow’s population 

grew by 35 percent and by 2006, its population was 4,065. The 

dramatic change in population and demographics primarily 

is the indirect result of oil and gas development. Increased 

revenues from onshore oil development and production at 

Prudhoe Bay and in other smaller oil fields underwrote the 

NSB CIPs which, in turn, stimulated a boom in Barrow’s 

economy and an influx of non-Alaskan Natives to the 

community. The social organization of the Barrow community 

has become diversified with the large increase in the number 

of immigrants of different ethnic groups. Traditional marine 

mammal hunts and other subsistence practices still are an 

active part of the culture. Barrow is the seat of Borough 

government and the largest regional community. 
Chapter 3

Ecological and Subsistence Context 71

Atqasuk. Atqasuk is a small, predominantly Iñupiat 

community on the Meade River, about 60 mi south of Barrow. 

In 2000, there were 228 residents, 94.3 percent of whom 

were Iñupiat; in 2006, there were 237 community residents. 

The community was established in mid-1970 by Barrow 

residents who had traditional ties to the area. By July 1983, 

the population had increased to 231, a 166 percent increase 

since the first census in 1980. Social ties between Barrow and 

Atqasuk remain strong, and men from Atqasuk go to Barrow 

to join bowhead whaling crews. To a large degree, Atqasuk has 

avoided the rapid social and economic changes experienced by 

Barrow and Nuiqsut brought on by oil development activities, 

but future change could accelerate as a result of oil exploration 

and development in the Northwest NPR–A. 

Wainwright. Wainwright is located on the Chukchi Sea 

100 mi southwest of Barrow on the western boundary of 

the NPR–A. In 2000, there were 546 residents, 93 percent 

of whom were Iñupiat; in 2006, Wainwright’s population 

was 517. All of Wainwright’s subsistence marine resources 

are harvested offshore in the Chukchi Sea, and all of the 

community’s terrestrial subsistence use areas are within 

NPR–A. 

Point Lay. Point Lay is one of the more recently 

established Iñupiat villages on the Arctic coast, and has 

historically been occupied year-round by a small group of one 

or two families. The community has the smallest population of 

any community in the NSB. In 2000, there were 247 residents, 

88.3 percent of whom were Iñupiat; in 2006, Point Lay’s 

population was 235. It is the only unincorporated community 

in the NSB. About 90 mi southwest of Wainwright, the 

community sits on the Chukchi Sea coast at the edge of 

Kasegaluk Lagoon near the confluence of the Kokolik River 

and Kasegaluk Lagoon. The community was established 

in the 1920s and its resident population increased until the 

1930s, when it began a slow decline, largely because of the 

decline in reindeer herding. By 1960, it was not included 

in the national census. The village was reestablished on a 

barrier island spit opposite the Kokolik River in the 1970s. 

Residents of Barrow, Wainwright, Point Hope, Kotzebue, and 

other Iñupiat with traditional ties to the area resettled there. 

The town then moved to its present mainland site south of the 

Kokolik Delta in 1981. The community is unique because its 

wild food dependence is relatively balanced between marine 

and terrestrial resources. Unlike the other communities, local 

hunters do not pursue the bowhead whale because the deeply 

indented shoreline and spring ice-lead patterns have prevented 

effective bowhead whaling. However, the village does 

participate in beluga whaling. 

Point Hope. Point Hope had a population of 737 in 

2006. In 2000, there were 757 residents, 90.6 percent of 

whom were Iñupiat. The community, 330 mi southwest 

of Barrow, is located on a large gravel spit that forms the 

westernmost extension of the northwest Alaska coast. Once 

called Tigaraq, it is one of the longest continuously occupied 

areas in Alaska. This likely is due to its proximity to marine 

mammal-migration corridors and favorable ice conditions 

that allow hunting in open leads early in the spring. Local 

government is the main employer of Point Hope residents. The 

city government was incorporated in 1966 and, in the early 

1970s, the community moved, because of erosion and periodic 

storm-surge flooding, to its present location just east of the old 

settlement. Point Hope has better facilities than many other 

communities of the region, but concerns remain because of 

erosion and storm-surge flooding. 

Tribal Governments. Kaktovik, Nuiqsut, Atqasuk, 

Barrow, Wainwright, Point Lay, and Point Hope also have 

either a traditional village or an Indian Reorganization Act 

(IRA) Tribal council. Historically, these Tribal governments 

provided some services and may partner with the Borough 

to manage and operate social-service programs. The Iñupiat 

Community of the Arctic Slope (ICAS), the regional Tribal 

government, recently has taken a more active and visible 

role in regional governance and in providing some services. 

Government-to-government consultations with these Tribal 

governments occur on major Federal actions directly affecting 

the Tribes, including OCS oil and gas actions.

Alaska Native Corporations. Collectively, village 

corporations are the third largest employer and the Arctic 

Slope Regional Corporation (ASRC) is the fourth largest 

employer in the region. The ASRC runs several subsidiary 

corporations and, along with village profit and not-forprofit corporations, has provided employment and other 

services to Borough communities. For example, ASRC and 

village corporations have provided employment and other 

public services to the communities, such as operation and 

maintenance of utilities and operation of stores, hotels, 

and restaurants, while nonprofit corporations primarily are 

involved in education, health/medical, public housing, and 

other community services through funding obtained from the 

Borough and Federal and State governments. Generally, much 

of the surface estate in and around the communities is owned 

by the village corporations, except in Barrow where land 

ownership is a mixture of public (Federal, State, Borough, 

Tribal, and village) and private (Alaska Native regional and 

village corporations and private individuals). Regional and 

village corporations are creating some employment through 

subsidiaries and joint ventures, and some companies involved 

in resource development have undertaken to increase local 

employment through training programs and other actions. 
72 An Evaluation of the Science Needs to Inform Decisions on Outer Continental Shelf Energy Development in the Chukchi and Beaufort Seas, Alaska

Local Traditional Knowledge

The information included in this report primarily is 

derived from “western” scientific studies. These are scientific 

observations, usually developed in a systematic fashion 

and often using instrumentation to record, understand, 

and predict the states of ecosystems and their dynamics 

(Huntington and others, 2004a). Science typically has a strong 

numeric component and attempts to quantify the variability 

associated with various scientific observations. In contrast, 

local traditional knowledge, also known as LTK, refers to 

knowledge gathered and maintained by groups of people, 

often indigenous people, based on intimate experience with 

their environment (Huntington and others, 2004a). Advocates 

of LTK have promoted its use in scientific research and 

ecological understanding (Huntington, 2000), and Huntington 

and others (2004a) argue that combining the two approaches 

can increase confidence in individual observations, broaden 

the scope of information about environmental change, 

and contribute to insights concerning mechanisms of 

change. Huntington and others (2004a) emphasize three 

characteristics of LTK: (1) it often emphasizes unusual events 

or conditions—these may be particularly relevant to safety; 

(2) the assessment of uncertainty (variability) is not explicitly 

addressed in LTK; and (3) it is typically local in spatial scale. 

Because practitioners of LTK are usually local residents 

(and scientists often are not), LTK can be particularly useful 

in documenting changes in distribution and abundance of 

species (for example, increasing abundance of salmon in the 

Beaufort Sea), documenting subsistence harvest areas for 

various species (see S.R. Braund and Assoc., 2010a), and 

documenting changes in harvest patterns. But LTK also has 

been used to identify biases in survey design [see example for 

bowhead whale survey in Huntington (2000)] and problems 

associated with telemetry collar designs for tracking polar 

bears (G. Durner, U.S. Geological Survey, oral commun., 

2010), and in combination with scientific information that has 

been used to more holistically define ranges and habitats used 

by animals over the course of their annual cycles (Huntington 

and others, 2004b). 

S.R. Braund and Associates (2010b) recently conducted 

a literature review of North Slope marine LTK. This review 

includes information on the physical environment, public 

testimony of residents at hearings, subsistence use areas, and 

subsistence harvest studies. 

Subsistence Resources 

Generally, subsistence is considered hunting, fishing, 

and gathering for the primary purpose of acquiring traditional 

food. The Alaska National Interest Land Conservation 

Act (ANILCA) defines subsistence as the customary and 

traditional uses by rural Alaska residents of wild, renewable 

resources for direct personal or family consumption such as 

food, shelter, fuel, clothing, tools, or transportation; for the 

making and selling of handicraft articles out of nonedible 

byproducts of fish and wildlife resources taken for personal 

or family consumption; for barter or sharing for personal or 

family consumption; and for customary trade (16 U.S.C. § 

3113). This ANILCA framework is the basis for all current 

documentation of Alaskan subsistence activity, both by State 

and Federal governments.

Subsistence activities are assigned the highest cultural 

values by the Iñupiat and provide a sense of identity in 

addition to being an important economic pursuit. Besides 

their dietary benefits, subsistence resources provide materials 

for personal and family use, and the sharing of resources 

that helps maintain traditional Iñupiat family organization. 

Subsistence resources also provide special foods for religious 

and social occasions, such as Nalukataq, which celebrates 

the bowhead whale harvest. The sharing, trading, and 

bartering of subsistence foods structure relationships among 

communities, while at the same time the giving of these 

foods helps maintain ties with family members elsewhere in 

Alaska. Additionally, subsistence provides a link to the market 

economy; many households within the communities earn 

cash from crafting whale baleen and walrus ivory and from 

harvesting fur-bearing mammals. 

Subsistence harvest data are primarily from the Alaska 

Department of Fish and Game Community Subsistence 

Information System and the North Slope Borough (Bacon and 

others, 2009). Although subsistence-resource harvests differ 

from community to community in northern and northwestern 

Alaska, with a few local exceptions, the combination of 

marine mammals, large terrestrial mammals, fish and 

waterfowl are the primary groupings of resources harvested 

across the North Slope (fig. 3–17). Of the marine mammals, 

the bowhead whale is the preferred meat and the subsistence 

resource of primary importance because it provides a unique 

and powerful cultural basis for sharing and community 

cooperation. Of the terrestrial mammals, caribou are the 

most important (Bacon and others, 2009). Depending on the 

community, fish is the second or third most important resource 

after caribou and bowhead whales. Pinnipeds and various 

types of birds also are considered primary subsistence species. 

Waterfowl are particularly important during the spring, 

when they provide variety to the subsistence diet (Bacon and 

others, 2009). Although North Slope residents concentrate 

their harvests on certain high value target species and species 

groups, the overall subsistence harvest is quite diverse 

(table 3–3). 
Chapter 3

Ecological and Subsistence Context 73

tac11-5179_fig03-17a

Kaktovik (1992)

marine mammals

land mammals

non-salmon fish

plants & berries

other birds

migratory birds

Nuiqsut (1993)

marine mammals

large land mammals

non-salmon fish

salmon

plants & berries

other birds

migratory birds

Barrow (1989)

marine mammals

large land mammals

non-salmon fish

salmon

migratory birds

Wainwright (1989)

marine mammals

large land mammals

non-salmon fish

salmon

other birds

migratory birds

Point Lay (1987)

marine mammals

large land mammals

non-salmon fish

salmon

plants & berries

bird eggs

other birds

migratory birds

Figure 3–17. Estimated annual harvest of various subsistence resources (pounds) (data that make up these pie 

charts are relatively old, but still provide a relative sense of the importance of various resources in the subsistence 

economies of North Slope villages). Adapted from the Alaska Department of Fish and Game (2011), accessed April 18, 

2011, at http://www.subsistence.adfg.state.ak.us/CSIS/. 

Table 3–3. Species and numbers harvested by Barrow residents, 1987–90.

[3-year average data from Minerals Management Services (2008)]

Species 3-year 

average

Bowhead whale 9

Walrus 81

Bearded seal 174

Ringed seal 394

Spotted seal 3

Polar bear 21

Beluga whale 0

Caribou 1,595

Moose 48

Dall sheep 11

Brown bear 1

Porcupine 2

Ground squirrel 14

Species 3-year 

average

Wolverine 2

Arctic fox 129

Red fox 5

Wolf 0

Ermine 0

Whitefish 28,683

 Non-specified 1,760

 Round 953

 Broad 17,352

 Humpback 1,840

 Least cisco 5,819

 Arctic cisco 958

Grayling 9,914

Species 3-year 

average

Arctic char 83

Burbot 676

Lake trout 147

Northern pike 4

Salmon 788

 Non-specified 169

 Chum 182

 Pink 92

 Silver 334

 King 12

Capelin 1,435

Rainbow smelt 526

Arctic cod 8,321

Species 3-year 

average

Tomcod 65

Sculpin 4

Geese 3,384

 Non-specified 144

 Brant 440

 White-front 2,795

 Snow 4

 Canada 1

Eiders 6,087

Ptarmigan 1,378

Other birds 30
74 An Evaluation of the Science Needs to Inform Decisions on Outer Continental Shelf Energy Development in the Chukchi and Beaufort Seas, Alaska

In addition to accurate, timely information on the 

composition of subsistence harvests by North Slope residents, 

information on where those harvests take place also is of high 

importance in planning industrial activities in coastal and 

marine areas of the Beaufort and Chukchi Seas. S.R. Braund 

and Associates (2010a) recently conducted a literature review 

of North Slope marine traditional knowledge and included 

maps showing subsistence harvest areas for important 

subsistence species, such as whales, seals, walrus, polar bears, 

waterfowl, fish, and invertebrates. Examples of maps for 

Kaktovik are shown in figures 3–18 and 3–19. 

Ongoing work by USGS, in collaboration with 

BOEMRE’s Alaska Region, is providing additional 

information and analysis on the human dimensions of fish 

use for subsistence communities bordering the Chukchi and 

Beaufort seas, including Canada. The following section is 

excerpted primarily from Thorsteinson and others (2011). 

In some cases, fish provides more of a dietary contribution 

than any other food source. In the Kotzebue Sound area, 

fully one-third to one-half of the total subsistence harvest by 

weight consists of fish (fig. 3–20). Although the inhabitants 

of the North Slope are often considered to depend much less 

on fishing and more on marine mammal hunting, significant 

harvests of fish are still made. The fact that fish comprise more 

than 10 percent of the total subsistence harvest of Barrow 

is remarkable, considering the number of bowhead whales 

harvested yearly at that location. Farther east at Nuiqsut, fish 

are the largest single contributors to the subsistence economy 

at nearly 40 percent of the total harvest.

Those areas less directly dependent on fish are mostly still 

reliant on them as a secondary resource in times of scarcity. 

Furthermore, fishing is an important family activity for much 

of the population not otherwise engaged in the hunting of 

sea mammals or caribou, including women, children, and 

elders. Previous research on Beaufort Sea and Chukchi Sea 

subsistence fisheries has to this point been limited in scope 

either geographically or chronologically: few studies have 

combined data for the U.S. and Canadian Arctic, and few 

include data from multiple years or otherwise longer-term 

perspectives than one or two season’s worth of catches. 

Ongoing USGS research (Thorsteinson and others, 

2011) seeks to produce a synthetic, broad-view analysis of 

fishing in its larger regional, cultural, and temporal context. 

Multi-year catch reconstruction analyses have recently 

been published both for the Arctic coasts of Alaska and the 

Northwest Territories. This makes it possible to determine 

each community’s “typical” local fishing tradition. Interviews 

with those currently or previously involved in fishing also 

provide an important contribution, particularly in the form of 

compilations of local traditional knowledge.

tac11-5179_fig03-18

Projection: Alaska Albers Equal Area Conic, NAD 1983 July 2009

Figure 3–18. Overlapping subsistence use areas for Barrow, Kaktovik, and Nuiqsut. From S.R. Braund and Associates 

(2010a).
Chapter 3

Ecological and Subsistence Context 75

tac11-5179_fig03-19

Projection: Alaska Albers Equal Area Conic, NAD 1983 July 2009

Figure 3–19. Subsistence use areas for ringed seals for the Barrow area. From S.R. Braund and Associates (2010a).

Shishmaref (2 years)

 Deering (1 year)

 S elawik (1 year)

 Kiana (1 year)

 Kotzebue (2 years)

 Kivalina (6 years)

 Point lay (1 year)

Wainwright (2 years)

 Barrow (3 years)

 Nuiqsut (2 years)

 Kaktovik (3 years)

0

5

10

15

20

25

30

35

40

45

50

Pounds of fish per capita / pounds total harvest per capita in percent

Fish as percentage of total harvest by community, West to East

Figure 3–20. Fish as a percentage of total overall subsistence harvest by community, 

West to East. Based on harvest records of the Alaska Department of Fish and Game (2011), 

accessed April 18, 2011, at http://www.subsistence.adfg.state.ak.us/CSIS/. 
76 An Evaluation of the Science Needs to Inform Decisions on Outer Continental Shelf Energy Development in the Chukchi and Beaufort Seas, Alaska

tac11-5179_fig 03-21a

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21

Salmon

Dolly Varden

Arctic Char

Whitefish (other)

Broad Whitefish

Humpback Whitefish

Arctic and Least Cisco

Sheefish

Other Fish

EXPLANATION

Map No. Community Map No. Community

1 Wales 12 Atqasuk

2 Shishmaref 13 Barrow

3 Deering 14 Nuiqsut

4 Buckland 15 Kaktovik

5 Selawik 16 Aklavik

6 Kotzebue 17 Inuvik

7 Noatak 18 Tuktoyaktuk

8 Kivalina 19 Paulatuk

9 Point Hope 20 Holman

10 Point Lay 21 Sachs Harbour

11 Wainwright

Figure 3–21. Visualization of the major subsistence fish species for each numbered coastal community in the Beaufort and Chukchi 

Seas, including the Canadian Beaufort.
Chapter 3

Ecological and Subsistence Context 77

When the four most important marine and anadromous 

fish species for each community are visualized on a westeast axis (fig. 3–21), the relationship between geography and 

human fishing habits may be understood; specifically, the great 

variability in local fisheries becomes apparent both on the 

local and regional level. Now, as in the past, the vast majority 

of the total catch consists of species that are either anadromous 

(migrating from the ocean to rivers in order to spawn) or that 

are otherwise known to live in both fresh and salt water and to 

move between the two. 

According to the Alaskan catch reconstruction study 

mentioned above, the total yearly subsistence harvest of 

fish from Wales to Kaktovik in 1950 was approximately the 

same as in 2006 (450–500 tons), with little deviation over 

several decades. In comparison, commercial harvests for 

the same area were extremely variable from year to year, 

with occasionally very large (about 3,000 tons) harvests in 

the 1970s and 1980s. Total commercial harvests have been 

declining since the late 1980s, unlike the comparatively stable 

subsistence harvest levels. Nearly the entire commercial 

harvest is from the southwestern Seward Peninsula/Kotzebue 

Sound region (fig. 3–21). 

To put the harvest estimates in perspective, it is useful 

to compare them to the total weight of bowhead whales 

harvested by the same populations. In 2008, communities 

north of the Bering Strait harvested 32 bowhead whales. Using 

a standard individual weight of 23.4 tons from a sample with 

approximately the same average size, the total harvested whale 

biomass for that year may be estimated at 750 tons. Viewed 

in the light of the whale data, the estimated 1950–2006 yearly 

fish harvests amount to 60–70 percent of the total harvested 

whale biomass for that year. 

Primary subsistence species. Salmon make a notable 

contribution to people’s diets only as far north and east as 

Point Lay, although small numbers of all five salmon species 

are occasionally caught as far to the east as Amundsen Gulf. 

Generally speaking, the closer a community’s proximity 

to the more temperate and productive Bering Sea, the 

greater the number of salmon species caught and the greater 

the contribution of salmon to the local population’s diet. 

This corresponds directly to the distribution of spawning 

populations of various salmon species. Chum salmon 

(Oncorhynchus keta) have the widest range and are the type of 

salmon utilized to the greatest extent.

Dolly Varden trout (Salvelinus malma), another 

anadromous salmonid species, make a significant dietary 

contribution across a very large area. Communities from 

the Seward Peninsula east to Kaktovik rely heavily on this 

species. Reliance on this species by humans is heaviest from 

Kotzebue to Wainwright and in Kaktovik (this easternmost 

community being closest to the spawning populations of the 

Brooks Range rivers (Viavant, 2001). Dolly Varden are not 

normally found to the east of Kaktovik; communities to the 

east of the Babbage and Firth Rivers rely instead on a closely 

related species, Arctic char (Salvelinus alpinus). 

Further north and east, a variety of whitefish and cisco 

species (genus Coregonus) gradually replace salmonids 

as the basis of the subsistence fishery. Sheefish (Stenodus 

leucichthys, also Inconnu), another coregonid species, are 

important in the area of the central Kotzebue Sound as well as 

in the Mackenzie Delta on the eastern North Slope.

3.08. Findings and Recommendations: Subsistence harvests are seasonally and regionally variable. Although general usage patterns are 

known, village surveys have been conducted intermittently. In some cases, the data are old enough and may no longer be representative of actual 

harvests. 

Future work is needed to fully understand the environmental, ecological, and cultural context of Beaufort Sea and Chukchi Sea subsistence 

harvests. To predict or model with any degree of accuracy the future of Arctic subsistence, with or without the impact of hydrocarbon exploration 

and extraction, a greater understanding of the past and present will be necessary. 

Because local patterns of resource exploitation are closely tailored to local environments and ecologies, they are potentially vulnerable to the 

effects of climate change and oil and gas development. The impact of climate change need not necessarily be harmful to human subsistence. A 

growing body of anecdotal evidence suggests that previously rare salmon species are appearing with greater frequency on the North Slope. New 

runs and greater numbers of salmon in the future could well provide the basis of new subsistence traditions. However, the unpredictable effects of 

climatic instability on fish and wildlife populations are not likely to be a net benefit to Arctic subsistence users in the near future. 

Oil and gas exploration and development pose a potential hazard to native subsistence livelihoods. Anadromous fish, marine mammals, and marine 

birds are crucial to human subsistence across the study area and are potentially vulnerable to disturbance and (or) pollutants associated with 

exploration, drilling, and transportation. Many fish species (including those not directly sought after for human use) comprise a major portion of the 

diets of sea mammals and birds that in turn sustain human populations. 

Subsistence users may be among the first to notice changes in abundance and distribution of fish and wildlife species as it relates to climate 

change, development, and other stressors. Local traditional knowledge should be more formally incorporated and integrated into resource 

assessments. 
78 An Evaluation of the Science Needs to Inform Decisions on Outer Continental Shelf Energy Development in the Chukchi and Beaufort Seas, Alaska

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Chapter 4

Climate Change Considerations 81

Introduction

Owing to the high northerly latitude, 

climate conditions in the Beaufort and 

Chukchi Seas are relatively severe. Sea ice 

is present most of the year, temperatures 

average about -27°C during the sunless 

winter period but occasionally drop to 

-48°C, powerful storms move through the 

area from time to time, and ‘white out’ 

conditions are common due to blowing 

snow. Summer temperatures are much 

milder, but still are only a few degrees 

above freezing. Although the sun is above 

the horizon 24 hours a day during summer, 

low-level clouds and fog are very common 

once the sea ice begins to melt. Indigenous 

plants and animals are highly adapted to 

these extreme conditions, as is the local 

Iñupiat culture. The oil and gas industry 

has adapted as well, running on-shore 

seismic exploration lines during the winter 

when the fragile tundra is both frozen 

and covered with snow, and therefore 

more resilient to vehicle traffic. On-shore 

exploration drilling typically is done during 

the winter from ice pads constructed for 

this purpose, while the movement of heavy 

drilling equipment across the tundra is 

facilitated by the construction of ice roads.

It is well established that climate conditions in this region 

have recently been undergoing a remarkable change, particularly 

during the last 20 years (Arctic Council, 2005; Intergovernmental 

Panel on Climate Change, 2007). Environmental changes include 

warmer air and ocean temperatures, earlier spring snowmelt, a 

marked decrease in the extent and thickness of sea ice, accelerated 

coastal erosion, and permafrost degradation. These changes in the 

physical environment are impacting biological and human systems 

in a number of ways. Shrubs are increasing on the Arctic coastal 

plain, as well as various other habitat changes. The distribution 

of some animal species (for example, walrus and polar bear) are 

changing in response to the loss of sea ice during at least part of the 

year. Subsistence hunting has been impacted. And the number of 

days seismic exploration vehicles can operate on the tundra without 

causing environmental harm has decreased from 200 to 100 over the 

last 30 years (Arctic Council, 2005).

Climate projections for the next 50–100 years produced by 

global climate models consistently show a pronounced warming 

over the Arctic, accelerated sea-ice loss, and continued permafrost 

degradation (Intergovernmental Panel on Climate Change, 2007). 

Of all areas on Earth, the Arctic has the greatest sensitivity to 

changes in greenhouse gases, primarily due to the (snow/ice) 

albedo-temperature feedback. Within the Arctic itself, some of the 

largest changes are expected to occur in the Bering, Beaufort, and 

Chukchi Seas (Chapman and Walsh, 2007; Walsh, 2008). If realized, 

the projected climate changes will ultimately affect nearly every 

aspect of the Arctic environment. This is a major concern from a 

biological standpoint because the indigenous plants and animals 

are so highly adapted to the extreme conditions that have been the 

norm in the Arctic. The projected climate changes will undoubtedly 

stress these highly adapted biological systems. In this chapter, we: 

(1) examine those aspects of the projected mid-century climate 

changes relevant for oil and gas activities in the Beaufort and 

Chukchi Seas, and (2) examine how the projected climate changes 

may impact fish, birds, and marine mammals within the Arctic Outer 

Continental Shelf (OCS). The former is important for evaluating 

how future changes in climate may either mitigate or compound the 

effects of Arctic energy development (for example, see Chapter 5, 

Oil-Spill Risk, Response, and Impact), while the latter is needed 

to assess the cumulative impacts on the environment of climate 

change, oil and gas activities, and other factors (see Chapter 7, 

Cumulative Impacts). Future climate change will, to some degree, 

Chapter

Climate Change

Considerations 4 By Gary D. Clow, Anthony R. DeGange, Dirk V. Derksen, and Christian E. Zimmerman
82 An Evaluation of the Science Needs to Inform Decisions on Outer Continental Shelf Energy Development in the Chukchi and Beaufort Seas, Alaska

Substantial improvements in our current understanding of 

future climate conditions in the Arctic are not expected before 

this time. Lacking synthesis documents, information about 

projected changes to important biological systems within the 

Arctic OCS are found in individual reports in the scientific 

literature.

affect the environment in which Arctic OCS exploration and 

development activities occur, the infrastructure needed to 

support those activities, day-to-day operations including ship 

and aircraft logistics, factors that make oil spills more-orless likely to occur, and the difficulty-or-ease of responding 

to those spills. Because of rapid climate-related changes 

projected to occur in the Arctic OCS, management agencies 

will need to manage adaptively, supported by long-term 

research and monitoring programs to effectively evaluate 

management practices.

Available Information. The primary source of 

information about future climate conditions in the Arctic 

is the suite of projections provided by fully coupled 

atmosphere-ocean global climate models (AOGCMs) driven 

by different greenhouse-gas emission scenarios. Secondary 

sources include downscaled1 AOGCM projections, physical 

understanding of the processes governing regional climate 

processes, and recently observed climate changes. Results 

from the most recent set of AOGCM future climate 

simulations were summarized in the Intergovernmental 

Panel on Climate Change (IPCC) Fourth Assessment Report 

(AR4 2007; Intergovernmental Panel on Climate Change, 

2007). This assessment, which synthesized the results from 

thousands of scientific papers on climate change, included 

climate projections from 21 AOGCMs from around the 

World. Climate projections for the Arctic were earlier 

summarized in the Arctic Climate Impact Assessment (Arctic 

Council, 2005), although these results were based on a 

small subset (five) of the previous generation of AOGCMs 

reported in the Third IPCC Assessment (Intergovernmental 

Panel on Climate Change, 2001). These models had coarser 

resolution and tended to have larger biases. Chapman and 

Walsh (2007) and Walsh (2008) synthesized the results from 

14 of the recent IPCC AR4 AOGCMs, focusing specifically 

on the Arctic. Although the projected values for most climate 

variables have not changed much since the release of the 

IPCC AR4 in 2007, the magnitude of sea-level rise during 

this century is an exception. Most in the scientific community 

now view the AR4’s estimate of sea-level rise to be far too 

low. The uncertainties of the AR4 projected sea-ice extent 

during this century also were enormous. Significant work has 

been done to reduce these uncertainties since the release of 

the IPCC AR4. For these variables, we rely on more recent 

estimates reported in the scientific literature. The next IPCC 

Assessment (AR5) is scheduled to be released in June 2013. 

Future Climate Changes and Impacts, 

the Next 50 Years

Physical Environment

Model Validation. The degree to which we can have 

confidence in the future climate projections for the Arctic 

depends to a large extent on how well the models replicate 

the current climate in this region. For the AR4 AOGCMs, 

each of the models were used to simulate Arctic climate 

conditions during 1981–2000; the values and spatial pattern 

of climate variables were then compared with observations 

(Chapman and Walsh, 2007). Each of the models also were 

subject to tests to see how well they replicate the observed 

seasonal cycle during 1958–2000, both for Alaska and for the 

entire Arctic (Walsh and others, 2008). Given the tremendous 

variation of solar radiation between summer and winter at 

high northern latitudes, this test exercises the models over a 

much larger range of forcing conditions than that associated 

with the projected greenhouse gas emissions during the 21st 

century. To provide a better sense of the uncertainties in the 

projections, the results of these tests are discussed below for 

those climate variables for which they are available.

Key documents:

Arctic Climate Impact Assessment, 2005 (Arctic Council, 2005).

Intergovernmental Panel on Climate Change Fourth Assessment Report 

(AR4), 2007.

Arctic Ocean Synthesis: Analysis of Climate Change Impacts in the 

Chukchi and Beaufort Seas with Strategies for Future Research, 2008 

(Hopcroft and others, 2008).

Arctic Sea Ice Decline: Projected Changes in Timing and Extent of Sea Ice 

in the Bering and Chukchi Seas, 2010 (Douglas, 2010).

1

Various techniques can be used to ‘downscale’ the coarse global 

AOGCM projections to much higher spatial resolutions. These methods 

can overcome some of the limitations in the coarse-scale global models as 

long as the large-scale atmospheric circulation produced by the AOGCMs 

does not contain significant errors or biases.
Chapter 4

Climate Change Considerations 83

Across-Model Scatter and Ensemble Averages. In 

numerical weather prediction and climate modeling, the 

average of a suite of models generally out-performs (is more 

accurate than) any individual model. This is because errors in 

the models tend to cancel out in the averaging process. Hence, 

the ‘ensemble-average’ is often given as the best estimate 

of future climate conditions. The range of results among the 

suite of models (across-model scatter) also provides valuable 

information. A large range of model results for a climate 

variable tells us the results are fairly uncertain, due to the 

different ways the models are attempting to represent critical 

processes, or for a number of other reasons. A small range 

of model results gives us some confidence that the result is 

robust.

Emission Scenarios. Projections of future climate change 

depend a great deal on future human activities. Given the 

enormous uncertainty of these activities, a set of ‘emission 

scenarios’ have been developed that hopefully bracket the path 

humans actually take during the 21st century. Each scenario 

makes different assumptions about the rates of technological 

and economic development, population growth, land-use 

changes, and thus of future greenhouse gas emissions and 

the amount of atmospheric particulates (for example, sulfate 

aerosols). Details about the scenarios are described in the 

Special Report on Emissions Scenarios (SRES, Nakićenović 

and others, 2000). Some scenarios (for example, SRES B1) are 

intended to represent the emissions from a globalized World 

with an environmental focus that emphasizes sustainability, 

while others (for example, SRES A2) represent a highly 

regionalized World in which each region independently 

pursues rapid economic development. Of the 40 scenarios 

originally developed for the SRES, six commonly are used 

as ‘marker’ scenarios for future climate experiments. The 

AOGCMs used to project future climate conditions require 

vast amounts of computer resources. Given the constraints 

on these resources, the Intergovernmental Panel on Climate 

Change (IPCC) decided to select a subset of three of these 

marker scenarios for the future climate experiments reported 

in its Fourth Assessment Report (AR4). From an emissions 

perspective, they can be viewed as ‘low’ (B1), ‘medium’ 

(A1B), and ‘high’ (A2) emission scenarios. The IPCC working 

group (WG1) responsible for the future climate simulations 

clearly stated that their selection of these three scenarios was 

not meant to imply that they are in some way preferable or 

more likely than any of the others. The rate at which carbon 

dioxide (CO2) is being added to the atmosphere is currently 

higher than any of the three AR4 emission scenarios (Le Quéré 

and others, 2009).

SRES Emissions Scenarios Used for the AR4 Future 

Climate Projections:

B1 ‘low’ emission rates

A1B ‘medium’ emission rates

A2 ‘high’ emission rates

Uncertainties in Future Climate Projections. For 

Arctic OCS decision making, it is important to recognize the 

scientific gaps and sources of uncertainty in the future climate 

projections for the Beaufort and Chukchi Seas. These include:

1. Several aspects of the Arctic climate system that are 

known to be extremely important are not particularly 

well represented in the current generation of models. 

These include clouds (especially low-level clouds) 

and sea ice. 

2. Our understanding of the Arctic climate system 

is still incomplete due to the complex nature of 

the atmosphere-land-cryosphere-ocean-ecosystem 

interactions that occur there, making it difficult 

to build models that are capable of accurately 

simulating all these interactions. 

3. The climate of the Arctic has a high degree of 

natural variability compared to the rest of the Earth. 

This reduces our ability somewhat to predict how 

climate is likely to change in the Arctic over the next 

few decades. 

4. Future changes of greenhouse-gas concentrations 

and other forcing agents (for example, sulfate 

aerosols and atmospheric dust) on which the model 

projections rely are uncertain. 

The international science community is continually working 

to fill scientific gaps and reduce uncertainties. Steady progress 

is being made, although given the complexity of the problems, 

the time frame for significant advances to occur is on the 

order of 5–10 years. Despite these gaps and uncertainties, the 

current generation of models is able to replicate many aspects 

of the Arctic climate system fairly well as discussed next in 

this chapter.
84 An Evaluation of the Science Needs to Inform Decisions on Outer Continental Shelf Energy Development in the Chukchi and Beaufort Seas, Alaska

Atmosphere

Surface Air Temperature. Results from model validation 

tests show that the 14-member AR4 AOGCM ensemble used 

for Arctic climate projections (Chapman and Walsh, 2007; 

Walsh, 2008; Walsh and others, 2008) is able to simulate the 

magnitude and spatial pattern of surface air temperature in the 

Arctic quite well for each of the four seasons. The magnitude 

and spatial pattern of inter-annual variability during the test 

period (1981–2000) are well simulated, as is the seasonal 

cycle. Through roughly 2070, the range of results among the 

models (across-model scatter) is roughly comparable to the 

range associated with our future emissions pathway (acrossscenario scatter). After 2070, the across-scenario scatter 

dominates. Considering both the across-model and acrossscenario scatter, the total range of projected mean annual 

surface air temperatures for the entire Arctic north of 60°N 

ranges from +1.0°C to +4.5°C by 2050. Although the range is 

large, none of the models project a decrease in temperature in 

the Beaufort and Chukchi Seas by mid-century for any season 

for any of the emission scenarios.

As discussed above, the best estimate of projected 

climate conditions is provided by the ensemble average. As 

with the individual models, the 14-member ensemble average 

shows a pronounced warming in the Arctic during the cold 

seasons, particularly during autumn and winter (fig. 4–1). 

Within the Arctic, the regions projected to experience the 

greatest warming are the Chukchi and Beaufort Seas due 

to the influx of warmer Pacific water through the Bering 

Strait, extensive sea-ice retreat during the summer, delayed 

freeze-up in the autumn, and thinner sea ice during the winter. 

For the A1B (‘medium’) emission scenario, the ensemblemean surface-air warming in the Chukchi and Beaufort Seas 

is roughly 5°C during autumn by mid-century (2040–2059), 

while the projected winter warming is slightly higher (6°C). 

In contrast, the projected summer warming is only about 1°C 

in this region by mid-century (A1B scenario) because any 

additional energy in the climate system during the summer is 

used to melt ice rather than warm temperatures. The spatial 

and seasonal patterns of warming are very similar for the 

other emission scenarios, although the magnitude of the 

changes are smaller and larger for the B1 and A2 emission 

scenarios, respectively. There is a tendency for the models 

that performed best (smallest errors) during Arctic validation 

tests to project the greatest warming in this region. Thus, the 

magnitude of the mid-century warming for the Beaufort and 

Chukchi Seas (stated above) based on ensemble averages is 

conservative, especially for the cold seasons.

Sea-Level Pressure. The distribution of atmospheric 

sea-level pressure (SLP) provides important insights into 

atmospheric circulation, storm tracks, precipitation patterns, 

and near-surface winds. As at mid-latitudes, the pressure 

field in the Arctic displays much more spatial variability 

during the winter than during the summer, reflecting more 

intense atmospheric circulation during the cold season. 

Results from model validation tests show that the 14-member 

AR4 AOGCMs used to study the Arctic (Chapman and 

Walsh, 2007; Walsh, 2008; Walsh and others, 2008) capture 

the seasonal SLP patterns in the Arctic fairly well, although 

not as well as for surface air temperature. Compared to 

the observations, the prevalent anticyclone in atmospheric 

circulation over the Arctic Ocean (the Beaufort Sea High) is 

broadened and shifted northwards in the model simulations. 

SLP biases may partly result from distortions to the Arctic 

atmospheric circulation caused by the Greenland Ice 

Sheet, something that is not well represented in the current 

generation of AOGCMs. There also is a great diversity of 

model responses regarding the Aleutian Low related to their 

present inability to adequately represent the competing effects 

of the El Niño-Southern Oscillation and North American 

mesoscale model variability patterns. Although SLP biases 

still exist, the biases are much smaller than they were for the 

previous generation of models in both the North Pacific and 

downstream of the Greenland Ice Sheet. Thus, the ability 

of the AOGCMs to accurately simulate SLP in the Arctic is 

steadily improving.

One of the most striking results from the future climate 

projections for the Arctic is the significant decrease in winter 

SLP centered over the Bering, Beaufort, and Chukchi Seas 

(fig. 4–2). This is a robust result shown by nearly all the 

models. Among the 14-member AR4 AOGCM suite, the 

best-performing models during model validation tests project 

the greatest SLP decrease in this region. This SLP depression 

likely is related to the decrease of sea ice in the Bering, 

Beaufort, and Chukchi Seas and the consequential shift in 

the surface-temperature pattern (Chapman and Walsh, 2007; 

Walsh, 2008). Smaller SLP decreases are projected to occur 

during the other seasons as well, with autumn again showing 

a significant decrease over the Bering, Beaufort, and Chukchi 

Seas similar to the winter pattern, but with about one-half the 

pressure decrease. The projected SLP decrease over the Arctic 

is associated with a poleward expansion of the planet’s Hadley 

Circulation by mid-century, which will move storm tracks 

farther north by several degrees.
Chapter 4

Climate Change Considerations 85

Figure 4–1. Projected changes in surface air temperature for 2040–2059, relative to 1981–2000, based on the SRES 

A1B emission scenario. Maps show the ensemble average for each season. (From Walsh, 2008.) (DJF, DecemberJanuary-February; MAM, March-April-May; JJA, June-July-August; SON, September-October-November.)

Figure 4–2. Projected changes in sea-level pressure for 2040–2059, relative to 1981–2000, based on the SRES 

A1B emission scenario. Maps show the ensemble average for each season. (From Walsh, 2008.) (DJF, DecemberJanuary-February; MAM, March-April-May; JJA, June-July-August; SON, September-October-November.)
86 An Evaluation of the Science Needs to Inform Decisions on Outer Continental Shelf Energy Development in the Chukchi and Beaufort Seas, Alaska

Storms and Winds. The pronounced changes in SLP 

projected to occur in the Bering, Beaufort, and Chukchi Seas 

during autumn and winter are expected to impact storm tracks 

and surface winds, although exactly what those changes are 

is not entirely clear. We will first discuss winds associated 

with the average SLP patterns for each season. Although the 

winds rapidly change on a daily basis due to passing weather 

systems, there are some patterns that consistently reappear. 

These persistent wind patterns largely drive the mean nearsurface ocean currents and the movement of sea ice. Under 

current climate conditions, the primary SLP features that 

consistently appear in the Pacific sector of the Arctic during 

winter are the Aleutian Low and a ‘bridge’ of high pressure 

that extends between northwestern Canada and Eurasia. 

During spring, high pressure over Canada and Eurasia 

diminishes as the continents warm up, leaving a closed highpressure cell (anticyclone) over the western Arctic Ocean 

known as the Beaufort Sea High (BSH), while the Aleutian 

Low exists in a somewhat diminished form. The SLP field is 

relatively featureless during the summer. During autumn, the 

BSH and Aleutian Low reform, producing an SLP field similar 

to spring. High winds (> 15 m/s) often occur in the Beaufort 

and Chukchi Seas in conjunction with the BSH during the 

transition seasons (spring and autumn), and with the analogous 

high-pressure bridge during winter. By mid-century, the 

western half of the Beaufort Sea High is expected to weaken 

during autumn as it is difficult to establish high pressure over 

the relatively warm water of the ice-free Chukchi Sea. With 

a contracted (and displaced) BSH, autumn winds associated 

with the mean SLP pattern may be more of a southerly nature 

in the Chukchi Sea (that is, from the Bering Strait) than at 

present, while winds in the Beaufort Sea will remain primarily 

easterly over the shelf. During winter, the Aleutian Low is 

projected to migrate northward, as is the high pressure bridge 

between Canada and Eurasia. Migration of the bridge may 

again be linked to the difficulty of establishing high pressure 

over areas of decreased sea ice as the ice edge is projected to 

be farther north at this time of year than at present (2011). The 

net effect is to move the boundary between the Aleutian Low 

and the high-pressure bridge from a location approximately 

over the Bering Strait to a new location over the Chukchi 

Sea by about mid-century. This situation may strengthen the 

predominantly easterly winds in the Beaufort and Chukchi 

Seas associated with the mean winter SLP pattern. Although 

SLP is projected to decrease slightly during spring and 

summer, the decrease is spatially uniform across the region so 

no significant change is anticipated for the mean SLP winds 

during spring or summer. These seasonal wind projections 

are somewhat uncertain because they rely on the projected 

SLP patterns, which are somewhat uncertain as previously 

discussed. Still, the seasonal wind projections in the Chukchi 

and Beaufort Seas make sense on purely physical grounds, 

given the decrease of sea ice there. The magnitude of the 

changes is currently unknown.

The pronounced SLP decrease in the Bering, Beaufort, 

and Chukchi Seas during winter, and to a lesser extent autumn, 

may suggest an increase in storm activity in this region during 

autumn and winter. However, the bulk of the SLP decrease 

also could be due to warmer air temperatures associated with 

the decrease of sea ice or other factors. Nevertheless, several 

arguments can be made suggesting that it will be stormier 

during autumn and winter. 

1. As the Aleutian Low is an expression of the dominant 

cold-season storm track, and the Aleutian Low is 

projected to migrate northward, a greater percentage 

of storms originating in the North Pacific are 

expected to follow a more northerly track through 

the Bering Sea into the west coast of Alaska by 

mid-century rather than crossing the Aleutian Islands 

into the Gulf of Alaska (Chapman and Walsh, 

2007). Although relatively few North Pacific storms 

currently penetrate into the Chukchi and Beaufort 

Seas through the Bering Strait, this likely will be a 

more common occurrence in the future, especially 

during winter. 

2. With the projected decrease of sea ice in the Chukchi 

and Beaufort Seas, more heat and moisture will 

be available to power storms in this region during 

autumn. This in itself is expected to increase the 

frequency and intensity of storms. 

3. The strong temperature contrast at the autumn seaice edge, which is projected to persist longer in the 

Beaufort and Chukchi Seas by mid-century, is likely 

to favor the formation and intensification of Arctic 

cyclones (Serreze and Barry, 2005). 

4. Polar Lows (fig. 4–3) are intense maritime 

mesocyclones that develop when cold continental 

air is advected over relatively warm water. With the 

projected decrease of sea ice in the Chukchi and 

Beaufort Seas, Polar Lows are expected to occur 

more frequently in the future as cold Siberian air 

moves over open water in the Chukchi Sea during 

autumn. Thus, Polar Lows are expected to occur 

more frequently during autumn in the future. 
Chapter 4

Climate Change Considerations 87

Figure 4–3. Wind field for a Polar Low passing eastward through the Chukchi and Beaufort Seas during August 2000. Storms such as 

these can present a significant hazard to activities on the Arctic OCS. Barb vectors indicate wind speed. A full barb equals 5 meters per 

second.

One observation in support of an increased frequency of 

autumn and winter storms by mid-century is that today 

cyclones are twice as likely to occur in the Beaufort and 

Chukchi Seas during summer and autumn as they are during 

winter or spring (Serreze and Barry, 2005). By mid-century, 

today’s autumn conditions are projected to occur in early 

winter. None of these ideas have as of yet been rigorously 

tested through numerical experiments or other means. Thus, 

an increase in the frequency and (or) intensity of autumn and 

winter storms in the Beaufort and Chukchi Seas, although 

likely based on physical arguments, remains uncertain. In 

addition, the magnitude of any such changes is unknown. 

Projected changes in the degree of summer storminess are 

highly uncertain as arguments can be made for both increases 

and decreases in summer storm activity.

Clouds. The Arctic marine environment is one of the 

cloudier places on Earth. Clouds affect Arctic ecosystems 

by modulating the amount of sunlight available for plant 

photosynthesis in marine and terrestrial environments. Once 

sea-ice melting begins in the spring, the fraction of the 

Arctic Ocean covered by low-level clouds and fog rapidly 

increases from 20 to more than 65 percent. These low clouds 

can drastically reduce visibility, affecting ship and aircraft 

operations. Upon the formation of new sea ice in the autumn, 

the fraction of low-level clouds over the Arctic Ocean 

gradually diminishes back to about 20 percent. AOGCMs 

consistently project that the Arctic will become cloudier by 

mid-century. Much of this increase is projected to occur near 

the tropopause in the form of high-level clouds (consistent 

across models). A smaller increase also is projected to occur 
88 An Evaluation of the Science Needs to Inform Decisions on Outer Continental Shelf Energy Development in the Chukchi and Beaufort Seas, Alaska

near the surface as low-level clouds, although deficiencies in 

the AOGCMs regarding boundary-layer processes and lowlevel clouds make this AOGCM result less certain. However, 

because the models project warmer temperatures during 

summer and autumn, there will be a decrease in the number of 

ice nuclei available to scavenge moisture out of the air during 

these seasons. Thus, on purely physical grounds, low-level 

clouds are expected to be more prevalent in the Beaufort and 

Chukchi Seas during the open-water season. In addition, lowlevel clouds are expected to occur over a greater fraction of 

the year in the Beaufort and Chukchi Seas as the frequency of 

low-level clouds in the Arctic maritime environment is highly 

correlated with the availability of open water.

Precipitation. Precipitation is an important freshwater 

input to the Arctic Ocean that helps reduce the salinity of 

the surface waters (upper 50–200 m), and thus is of critical 

importance to marine ecosystems as well as assisting with 

the formation and persistence of sea ice. Model validation 

tests of the 14-member AOGCM suite used for Arctic climate 

simulations show that the models are able to simulate the 

overall seasonal cycle in the Arctic. The spatial pattern 

of precipitation biases is more complex than for either 

temperature or SLP with strong biases occurring in the 

vicinity of major mountain ranges. Precipitation biases in the 

individual models and the ensemble average are relatively 

small in the Beaufort and Chukchi Seas. Projections of 

precipitation by AOGCMs generally are less reliable than 

for air temperature or SLP. Nearly all the AOGCMs project 

a significant increase in precipitation in the Arctic by midcentury, although the magnitude and spatial pattern of those 

increases vary considerably among the models. The intensity 

of precipitation events also is projected to increase, as is the 

number of wet days (that is, days when precipitation occurs). 

Nearly all of the precipitation increase is attributable to the 

fact that warmer air can hold more moisture which is then 

available for precipitation, and very little is due to changes in 

atmospheric circulation (Higgins and Cassano, 2010). By midcentury, the projected ensemble-average precipitation increase 

in the Beaufort and Chukchi Seas is roughly 25 percent 

during winter, and 15 percent during summer (A1B emissions 

scenario). During Arctic validation tests, there was a tendency 

for the best performing AOGCMs (smallest errors) to project 

the largest precipitation increases. Thus, the magnitude of 

the mid-century precipitation increase given by the ensemble 

average may be conservative.

Ocean

Sea Ice. The distribution, thickness, and seasonality of 

sea ice are fundamental in shaping the physical environment 

of the Beaufort and Chukchi Seas. The presence or absence 

of sea ice strongly affects regional temperatures; SLP and 

hence atmospheric circulation; the availability of moisture 

for clouds, precipitation, and icing conditions; and the 

development of Arctic mesocyclones, including Polar Lows. 

In addition, sea ice is intimately connected with the biological 

communities of the Arctic marine environment, including 

shielding organisms from the coldest wintertime temperatures, 

serving as a breeding and feeding platform for marine 

mammals, and modulating the amount of sunlight available 

for photosynthesis by phytoplankton. Sea ice undergoes a 

strong seasonal cycle, completely covering the Arctic Ocean 

during the winter and spring, while extensive melting during 

the summer generally leaves the periphery of the Arctic Ocean 

ice-free adjacent to Alaska and Siberia by September (the 

month of minimum sea-ice extent). One of the primary drivers 

for the transport of sea ice out of the Arctic Basin into the 

North Atlantic is the clockwise pattern of winds associated 

with the Beaufort Sea High.

One of the most dramatic changes in the Arctic during 

the last few decades has been the significant decrease of 

sea ice during the summer; the September sea-ice extent 

decreased almost 25 percent between 1976 and 2006, leaving 

the Beaufort and Chukchi Seas essentially ice-free during 

September to well above 75°N in recent years. Given the 

projections of significant warming in the Arctic during this 

century, a concern that naturally arises is whether the Arctic 

Ocean will become largely ice-free during the summer in the 

not too distant future. Nearly all AR4 AOGCMs that could 

be used to address this question underestimate the observed 

decrease in sea ice during recent years. There are significant 

doubts about the models’ abilities to project future trends in 

sea ice. The enormous range of sea-ice projections among all 

AOCGMs through the end of the century only adds to these 

doubts. Several studies have been done since the release of the 

IPCC AR4 to look at this issue. Wang and Overland (2009) 

concluded that the late-summer Arctic Ocean may become 

nearly ice-free in September by 2037 based on the A1B and 

A2 emissions scenarios, essentially confirming an earlier 

result (Holland and others, 2006) that it could become ice-free 

by 2040. More recently, Zhang (2010) also found that the 

Arctic could become ice-free by the late 2030s while Boè and 
Chapter 4

Climate Change Considerations 89

others (2009) concluded that 2066–2085 is the first 20-year 

period when the Arctic is likely to be ice-free in September. 

As with temperature, SLP, and precipitation, the later study 

found that the AOGCMs that are best at simulating the 

observed sea-ice extent over the last 30 years have the highest 

sensitivity to greenhouse gas emissions and hence project 

the earliest ice-free summers in the Arctic. Focusing on the 

Bering and Chukchi Seas, Douglas (2010) found that sea ice 

typically retreats northward through the Bering Strait in June 

and that this is unlikely to change much through mid-century. 

Thus, June is a hinge-point in the annual sea-ice cycle that is 

linked to the annual cycle of solar radiation. Following June, 

sea-ice melting is projected to be more rapid and extensive, 

leaving the shelves of the Chukchi and Beaufort Seas largely 

ice-free during August–October by mid-century. Substantial 

amounts of ice are not projected to reappear on the shelves 

of the Chukchi and Beaufort Seas until November, followed 

by the advance of the ice edge through the Bering Strait in 

December. Thus, complete freeze-up of the Chukchi and 

Beaufort Seas is expected to be delayed about 1 month by 

mid-century (Douglas, 2010). Again, the exact timing of 

these events is uncertain due to the inherent uncertainty of the 

sea-ice projections. Based on the median ice coverage from 

14 AOGCMs used in the IPCC AR4, the number of openwater days in the Beaufort and Chukchi Seas is projected to 

increase by 50–75 by mid-century (Walsh, 2008). Finally, it 

is important to stress that the projected decrease of sea ice 

is a seasonal phenomena. Sea ice will still be present in the 

Beaufort and Chukchi Seas for most of the year. In addition, 

for those months when it is present, the ice pack will be 

thinner and therefore more dynamic than it historically has 

been.

Sea Level. Recent research shows that erosion rates 

for coastal bluffs consisting of ice-rich permafrost are very 

sensitive to changes in water level on the Beaufort Sea during 

the summer and autumn. When near-coastal water levels rise 

in response to wind stress, erosion rates go up dramatically as 

lower portions of the bluffs are immersed in relatively warm 

water. Conversely, when winds drive the water off-shore 

lowering water levels, erosion rates are very low. Given this 

observation, rising sea levels have the potential to greatly 

accelerate coastal erosion rates. Barrier islands also will be 

strongly affected by rising sea levels. In the IPCC AR4 report, 

global sea levels are projected to rise 0.18–0.6 m by the end 

of this century. However, sea-level rise is not expected to 

be uniform and there is substantial spatial variability among 

the models. The Arctic Ocean is projected to experience the 

greatest sea-level rise on the planet due to a combination of 

thermal expansion, which is projected to be greater here than 

elsewhere, and a decrease of salinity related to increased 

precipitation at high northern latitudes. The Bering and Beaufort 

Seas are one of the few areas on Earth where the projected sealevel rise exceeds the inter-model range.

Following the release of the AR4 report in 2007, the 

consensus of the science community was that the AR4 sealevel rise projections are much too low. At the time of the AR4 

report, the dynamics of the large ice sheets in Greenland and 

Antarctica were too poorly understood to make reliable model 

estimates. Hence, the dynamics of the large ice sheets were not 

included in the AR4 sea-level projections. Subsequent work has 

placed some constraints on this very important effect. Using 

a semi-empirical approach that analyzed how sea level has 

varied in the past in response to global temperature change, 

Vermeer and Rahmstorf (2009) estimate global sea-level rise 

to be in the range 0.75–1.9 m by 2100 for the six SRES marker 

emissions scenarios, or about three times the AR4 projections. 

The comparable mid-century sea-level rise is estimated to be 

0.3–0.5 m. Using a very different kinematic approach to establish 

realistic constraints on the dynamic response of the large sheets 

(that is, there are limits to how fast ice in an ice sheet can move 

to the coast and then out to sea), Pfeffer and others (2008) find 

that the upper limit for sea-level rise by 2100 is about 2 m, close 

to Vermeer and Rahmstorf’s (2009) upper limit. Using more 

realistic values for glaciological parameters, Pfeffer and others 

(2008) estimate a more plausible total sea-level rise to be about 

0.8 m by 2100 (about 0.35 m by mid-century), close to Vermeer 

and Rahmstorf’s (2009) lower limit. In summary, once the 

dynamics of the large ice sheets are considered, the best current 

estimates for mid-century global sea-level rise are in the range of 

0.3–0.4 m. This range should be treated as a lower bound for the 

Beaufort and Chukchi Seas as sea level is expected to rise faster 

in the Arctic Ocean than elsewhere.

Acidification. About one-third of the anthropogenic CO2

released into the atmosphere is absorbed by the oceans, making 

them more acidic and thereby lowering the concentration of 

carbonate ions. These ions are required by a number of marine 

organisms, such as plankton and shellfish, in order for them 

to make the calcium carbonate needed for their shells and 

skeletons. Once the concentration of carbonate ions becomes 

low enough, calcium carbonate begins to dissolve and the waters 

become corrosive to calcifying organisms. Because cold water 

can absorb more CO2 than warm water, and the saturation point 

for calcium carbonate occurs at a lower threshold in relatively 

fresh water than in saline water, the Arctic Ocean is expected 

to reach the point of calcium carbonate dissolution sooner than 

the other oceans as atmospheric CO2 concentrations rise. Recent 

simulations using global ocean models suggest that the surface 

waters of the Arctic Ocean will become undersaturated with 

respect to calcium carbonate, and therefore corrosive, within a 

decade (Steinacher and others, 2009). Recent observations show 
90 An Evaluation of the Science Needs to Inform Decisions on Outer Continental Shelf Energy Development in the Chukchi and Beaufort Seas, Alaska

that the surface waters of the Canada Basin (Beaufort Sea) 

have already reached this point, at least during the summer 

when the surface waters are freshened by extensive sea-ice 

melting (Yamamoto-Kawai and others, 2009). This is the first 

deep ocean basin where the projected corrosive conditions for 

calcifying organisms have been observed. There are significant 

concerns about the impact of acidification on marine 

organisms and marine ecosystems in the Arctic. Although the 

biological response to acidification will likely vary across 

species and life stages, both benthic and planktonic calcifying 

organisms are expected to be impacted. As both types of 

organisms are important elements of the Arctic food web, 

Arctic marine ecosystems are likely to be disrupted (Orr 

and others, 2005; Yamamoto-Kawai and others, 2009). For 

the ‘low’ emissions B1 scenario, more than 50 percent of 

the Arctic surface waters are projected to become corrosive 

to calcifying organisms by the end of the century, while for 

the A2 ‘high’ emissions scenario, 100 percent of the surface 

waters will become corrosive.

Circulation. Water from the Pacific Ocean flowing 

through the Bering Strait has a tremendous influence on the 

characteristics of the Chukchi Shelf, and to a lesser extent on 

the Beaufort Shelf (Hopcroft and others, 2008). The heat flux 

associated with the Bering Strait inflow is large, comparable to 

the solar input to the Chukchi Sea. This heat pre-conditions ice 

in the Chukchi Sea for solar-driven melt in early summer and 

delays the freeze-up in autumn (Woodgate and others, 2010). 

The Pacific inflow is the single largest source of freshwater 

to the Arctic Ocean, providing almost 50 percent of the total 

freshwater input. The nutrient-rich Pacific waters sustain an 

exceptionally high productivity in the southern Chukchi Sea, 

making it a unique ecological region within the Arctic. The 

force driving the northward flow through the Bering Strait 

is thought to be the pressure-head difference between the 

Pacific and Arctic Oceans. This is opposed by the prevailing 

northeasterly winds. Significant variations in both the PacificArctic pressure-head difference and the prevailing winds 

lead to considerable variation in the northerly flow of Pacific 

water through the Bering Strait. On the Beaufort Shelf, the 

prevailing easterly winds drive the shelf waters (and the ice 

pack when present) to the west, although the details of the 

circulation structure are poorly understood. Strong winddriven upwelling at the shelfbreak can occur once the ice edge 

moves seaward of the shelfbreak. This probably is a critical 

process for supplying nutrients to the Beaufort Shelf. Given 

the projected changes in temperature, SLP, precipitation (and 

hence salinity), and sea ice, the dynamics and circulation 

patterns of the Arctic Ocean and Bering Strait inflow likely 

will change during this century. However, little work has 

been done as of yet to predict the details of those changes. 

Development of Arctic Ocean models is currently an area of 

active research (Arctic Ocean Model Intercomparison Project).

Coastal Zone

The coastal zone consists of an assemblage of habitats 

important for many Arctic species. In addition, much of the 

infrastructure (for example, pipelines, storage tanks) needed to 

support oil and gas activities in the Beaufort and Chukchi Seas 

will necessarily cross the coastal zone or be located within 

the coastal zone. The coast of the Beaufort Sea is particularly 

vulnerable to climate change impacts while the coast of the 

Chukchi Sea appears to be less so. 

1. Much of the Beaufort coast is less than 1–2 m above 

current sea level. Thus, portions of this coast are 

expected to be inundated by mid-century given the 

projections of sea-level rise. 

2. Combined with the low topography, large storm 

surges that occasionally happen in this region 

have the potential to do substantial damage to the 

Beaufort coast and structures built on it, as well as 

to the offshore barrier islands. For example, a major 

storm during September 1970 carried driftwood 

logs 1.5–3.4 m above normal sea level, and up 

to 5 km inland along portions of the Beaufort 

coast (Reimnitz and Maurer, 1979). Storm surges 

during autumn carrying blocks of pack ice can do 

substantial damage as they pound the barrier islands 

and the coast. Although storms with the intensity 

of the September 1970 storm are rare, they may 

become more common during autumn in the future 

(see Atmospheric section). Given the projected sealevel rise, storm surges also will penetrate farther 

inland by mid-century. 

3. In areas of ice-rich permafrost (that is, most of 

the Beaufort Sea coast), coastal erosion rates are 

expected to accelerate (fig. 4–4) due to a number 

of factors. First, sea ice which normally protects 

the coast from erosion during the cold seasons 

will be present less of the year, allowing windgenerated waves to impact the coastal bluffs for 

a greater amount of time each year. Second, with 

the projected Arctic warming, permafrost will be 

mechanically weaker during the summer and autumn 

than at present and thus more susceptible to erosion. 

Third, with the projected sea-level rise, the lower 

portions of the coastal bluffs will be immersed in 

relatively warm water a greater fraction of the time, 

a situation that enhances erosion rates. Fourth, based 

on physical factors, the frequency and (or) intensity 

of Polar Lows and other autumn storms likely will 

increase. If this does occur, the mechanical energy 

delivered by waves from these storms will further 

accelerate coastal erosion rates.
Chapter 4

Climate Change Considerations 91

Figure 4–4. JW Dalton well site on the Beaufort Sea coast, National Petroleum Reserve-Alaska (NPR-A). Photograph taken by S. Flora, 

Bureau of Land Management, September 2004. Approximately 100 m of coastal erosion occurred at this site during the summer of 2004.

Data collected by the USGS show that mean annual ground 

temperatures on the Arctic Coastal Plain adjacent to the Beaufort 

and Chukchi Seas have warmed about 3.5°C since 1989 (Clow, 

2008). In conjunction with this warming, a large increase in 

permafrost degradation has been observed (Jorgenson and others, 

2006). This recent degradation primarily is due to the degradation 

of massive ice wedges within permafrost that have been stable 

for thousands of years. With continued warming, it is estimated 

that permafrost degradation (thermokarst) can ultimately affect 

10–30 percent of the landscape in this region, which would 

significantly impact ecosystems and present a challenge to the 

infrastructure. Permafrost degradation along the coasts of the 

Beaufort and Chukchi Seas is expected to continue through midcentury, although the percentage of landscape affected by that 

time is presently unknown.

Biology

The biological communities indigenous to the coastal 

and marine areas of the Beaufort and Chukchi Seas are highly 

adapted to the extreme conditions of this environment. Because 

of this high degree of adaptation, the projected changes to the 

physical environment of this region are expected to have a 

significant impact on fish and wildlife populations. Considerable 

uncertainty exists in how these changes will affect many 

individual species, but there is general agreement that these 

changes will favor some species while being detrimental to 

others.

With projected warming temperatures and further 

decreases in sea ice, terrestrial and marine populations 

generally are expected to shift northward with probable 

large-scale ecosystem shifts in species abundance, food 

web changes, and increased competition for habitats. 

Among the factors that are of particular importance in 

the Beaufort and Chukchi Seas region from a biological 

perspective are the projected decrease of sea ice, circulation 

changes, ocean acidification, and coastal erosion. The 

present-day Arctic marine ecosystem is in many ways 

adapted to the sea-ice cover. At the base of the food 

chain, phytoplankton blooms are intense at the summer 

ice edge. Zooplankton are the primary grazers of these 

phytoplankton, and it is the success of the zooplankton 

communities that ultimately determines the food resources 

available to Arctic fish, seabirds, and marine mammals. 

Thus, changes in the thickness, extent, and seasonal 

location of the sea-ice cover can have repercussions 

throughout the Arctic food web. Potential repercussions 

include changes in predator-prey relationships among 

Arctic cod, seals, and polar bears, for example. Loss 

of sea ice also can have a direct impact on ice-obligate 

marine mammals (for example, ringed seals, walrus, polar 

bears) as it serves as an important rearing, feeding, and 

resting platform for these animals. In the Chukchi Sea, 

the bulk of the nutrients needed for the production of 

organic compounds at the base of the food web (“primary 

production”) are of Pacific origin, carried northward by 
92 An Evaluation of the Science Needs to Inform Decisions on Outer Continental Shelf Energy Development in the Chukchi and Beaufort Seas, Alaska

currents through the Bering Strait. In the Beaufort Sea, winds 

promote upwelling of subsurface waters at the continental 

shelfbreak, bringing nutrients from the Canada Basin onto the 

shelf. In either case, changes in wind and ocean circulation 

patterns will alter the distribution of nutrients available for 

primary production, with consequences for the entire food 

web. In addition, ocean acidification is expected to negatively 

impact planktonic and benthic calcifying organisms in this 

region, both of which are important elements of the Arctic 

food web. Due to the combined effects of sea-level rise, 

storm surges, and accelerated coastal erosion, habitats critical 

to many species in the coastal zone and barrier islands are 

expected to be impacted by the projected climate changes.

Climate-related changes in the physical landscape and 

in biological communities will have far-reaching impacts to 

the human populations on the North Slope of Alaska who still 

rely to a large extent on subsistence foods. Access to coastal 

and marine areas will change as a result of coastal erosion, 

sea-level rise, and changes to sea ice. Opportunities to hunt 

some species (for example, ice seals) may decrease, but 

opportunities to hunt others may increase, at least in the short 

term. The value of local traditional knowledge from those that 

live there can play a bigger role in documenting changes in the 

distributions and status of fish and wildlife populations.

Fish

At least 98 species of marine fish are known to inhabit 

the Beaufort and Chukchi Seas (Mecklenburg and others, 

2002). Because of the paucity of commercial fisheries in 

Arctic Alaska, knowledge of fish ecology in this region is 

among the poorest in Alaska, but it is slowly improving. The 

current understanding of population-level change expected 

from climate change in Arctic fish species is hindered by a 

lack of long-term data and a poor understanding of Arctic 

fish ecology. Present-day relationships between biological 

and environmental parameters must be understood to provide 

the foundation for assessing future climate-change effects on 

fish populations and, in many cases, this basic foundation is 

poor or lacking, making it difficult to predict the response of 

Arctic fishes to climate change. In general, a pole-ward shift 

of fish distributions is predicted, as is a reduction or extinction 

of species that are narrowly adapted to Arctic environments 

(Wrona and others, 2006).

Climate-change effects on Arctic freshwater and 

nearshore ecosystems are expected to result in changes to 

water temperature, hydrology, ice regimes, salinity, pH, 

biogeochemical processes, primary production, food-web 

interactions, and the distribution of prey species. How any 

single species or population responds to these changes 

probably will vary among locations and depend on the 

life history and range of habitats used (Reist and others, 

2006a). Numerous questions remain concerning the potential 

impacts (positive versus negative) resulting from changes 

in large-scale environmental drivers to fish in freshwater, 

nearshore, and marine habitats (fig. 4–5). The projected 

warming of marine waters and changes in salinity, especially 

in nearshore waters, are expected to impact the distribution, 

growth, and survival of fishes, many of which rely on 

nearshore waters as critical migratory and feeding corridors.

Fish of the Beaufort and Chukchi Seas can be broadly 

categorized in two groups based on their use of marine 

habitats: marine species use marine (that is, saltwater) habitats 

exclusively while anadromous species migrate between 

freshwater and marine habitats (see Chapter 3, Ecological 

and Subsistence Context). Given the difference in reliance 

on marine habitats, the two groups are likely to respond 

differently to climate change. Anadromous species spawn in 

freshwaters and feed in marine waters and integrate climate 

change effects across freshwater, estuarine, and marine 

habitats. For such species, the total effect is expected to be 

significantly greater (Reist and others, 2006a, 2006b).

Anadromous Fish. How anadromous fish of the Beaufort 

and Chukchi Seas will respond to climate change will range 

from positive to negative in overall effect and will vary 

among species and among populations (Reist and others, 

2006a). Because anadromous fish migrate between marine and 

freshwater habitats, sometimes annually, they will integrate 

the impacts of climate change in both the freshwater and 

marine habitats, potentially leading to a greater impact than 

that experienced by resident freshwater or marine species. 

Climate-change effects on such fishes may be driven by 

changes in hydrology (timing and quantity of flow), timing 

of freeze-up and break-up, and thermal regime. These 

environmental changes may impact the timing of upstream 

migration by adults, overwinter survival of adults, overwinter 

survival of incubating eggs, and timing of downstream 

migration by juveniles and adults as they migrate to the 

ocean. Environmental factors affecting growth, survival, and 

reproduction in Arctic fishes are numerous, act differently 

on different life stages, and include temperature, salinity, ice 

extent, current or flow of water, turbidity, and pH. Because 

migratory timing is an adaptation to local conditions, in 

general, non-linear changes to marine and freshwater habitats 

of any of these factors may result in decreased survival if 

conditions in freshwater and marine habitats result in a mismatch in timing of saltwater entry (Burkett and others, 2005).

Several species of anadromous fish are found in waters of 

the Beaufort and Chukchi Seas including: Dolly Varden, Arctic 

cisco, least cisco, Bering cisco, broad whitefish, humpback 

whitefish, rainbow smelt, pink salmon, and chum salmon. All 

these species spawn in freshwater and rely on a narrow band 

of brackish water along the coast for migration to and from 

feeding and spawning locations with the exception of Pacific 

salmon, which presumably migrate farther offshore or to the 

northern Bering Sea. Because warming and changing salinity 

are predicted to be most severe in this nearshore region, these 
Chapter 4

Climate Change Considerations 93

fish are expected to be most impacted by climate effects. 

Arctic cisco, for example, spawn in the Mackenzie River and 

shortly after hatching, juveniles migrate downstream and out 

of the Mackenzie River Delta where they are swept west to 

Alaskan waters of the Beaufort Sea by nearshore wind-driven 

currents (Fechhelm and Griffiths, 1990). Potential changes 

in wind regimes or current patterns could, therefore, have 

significant impacts on the number of Arctic cisco recruiting 

to Alaskan waters. Arctic cisco have been captured as far 

as 15 km offshore but are presumed to rely most heavily 

on nearshore waters within 15 km of the coast. As a result, 

changes to prey resources due to projected warming, decreased 

sea ice, changes in freshwater inputs, and changes in nutrient 

availability may affect survival and growth of Arctic cisco.

Similarly, Dolly Varden spawn in a few spring-fed 

streams of the eastern North Slope of Alaska and rivers 

draining to the Chukchi Sea and migrate downstream to 

marine waters. Little is known about the extent of marine 

migrations by Dolly Varden in waters of the Beaufort Sea but 

evidence from the southern Chukchi Sea suggests that marine 

migrations may be long-distance and Dolly Varden may have 

little fidelity to overwintering habitats. Dolly Varden tagging 

experiments indicate that marine migrations by anadromous 

fishes may be extensive and suggest that populations in the 

Beaufort and Chukchi Seas may be characterized by complex 

migratory behaviors and interconnections among streams, 

further complicating our ability to predict the results of climate 

change on these species. Because Dolly Varden and Pacific 

salmon are likely to migrate south through the Bering Strait, 

they also are subject to climate related shifts in the Bering 

Sea ecosystem, where increases in temperature, decreases in 

sea ice, and shifts in species composition have been observed 

(Grebmeier and others, 2006).

In addition to physical oceanographic changes in 

migration corridors, fish may be affected by changes in food 

resources. Resent research suggests an increasing growth trend 

for juvenile Arctic cisco as they migrate from the Mackenzie 

River through the nearshore Beaufort Sea (von Biela and 

others, 2011). Correlations with environmental data suggest 

that decreased sea-ice concentrations and increased river 

discharge fueled primary production, which resulted in 

increased prey species (copepods) and increased juvenile 

growth. While Arctic cisco are characterized by increased 

growth during their first year of life, which appears to be 

correlated with climate change, it is unclear how this increase 

in growth translates to survival or reproduction. Typically, 

Uncertain Effect

Positive Effect

Negative Effect

Indirect Climate Change Effects

Direct Climate Change Effects

Ecosystem Pathways

Figure 4–5. Schematic showing some of the potential direct effects of climate change on Arctic aquatic environments and some 

potential indirect effects on fishes. The complexity of the interactions makes it difficult to predict climate-change effects on these 

fishes. (From Wrona and others, 2005.)
94 An Evaluation of the Science Needs to Inform Decisions on Outer Continental Shelf Energy Development in the Chukchi and Beaufort Seas, Alaska

increased growth is assumed to indicate better conditions 

and, hence, increased survival. Further work is needed to 

determine if increased growth during early life history of 

Arctic cisco translates to increased adult growth, reproduction, 

or survival. Similar trends of increasing juvenile growth have 

been predicted for other Arctic fish species (Reist and others, 

2006b).

Distributional changes are likely to be observed in 

anadromous fishes including colonization by fishes such as 

Pacific salmon. With warming water temperatures, decreasing 

sea ice, and perennial freshwater flow, colonization of Arctic 

rivers by Pacific salmon is expected and may have dramatic 

impacts on aquatic productivity and species composition 

(North Pacific Research Board, 2005). Because Pacific salmon 

die after spawning and thus transport nutrients gained during 

marine rearing into spawning rivers, their colonization of 

relatively nutrient-poor Arctic rivers is likely to result in 

changes to nutrient dynamics with resulting changes to biotic 

communities, both within aquatic and associated terrestrial 

and estuarine ecosystems (Gende and others, 2002). While 

all five species of Pacific salmon have been captured in the 

North American Arctic, it is not clear that successful spawning 

populations exist north and east of Point Hope, Alaska. While 

reports of Pacific salmon captured across this region have 

increased in recent years, it has been suggested that Pacific 

salmon captured north and east of Point Hope were strays 

from other regions (Stephenson, 2006). Lack of suitable 

spawning habitats and extremely cold temperatures are the 

suspected reasons that salmon straying to the Arctic have not 

established perpetuating spawning populations (Craig and 

Haldorson, 1986).

Dolly Varden, like Pacific salmon, are substrate 

spawners and spawn in streams between the Colville River 

and Mackenzie River (Daum and others, 1984). Streams 

currently used by spawning Dolly Varden are mountain 

streams containing perennial springs. Dolly Varden do not 

spawn in rivers west of the Colville River because these 

streams lack perennial flow (Craig, 1989). The distribution of 

Dolly Varden habitats is, therefore, severely restricted. This 

distribution suggests that other substrate spawning salmonids 

(such as Pacific salmon) will be limited by suitable spawning 

habitats and may be predicted by the current distribution of 

Dolly Varden. Development of incubating salmon is strongly 

controlled by temperature and currently observed winter 

water temperatures are too cold to allow for successful 

incubation of Pacific salmon in many rivers draining to the 

Beaufort Sea, although more data are needed to determine the 

potential distribution of adequate salmon spawning habitats. 

Temperatures also are presently too cold in the Arctic Ocean 

to allow for overwinter at-sea survival of salmon and salmon 

would need to migrate to the northern Bering Sea (Irvine 

and others, 2009). While it remains uncertain when Pacific 

salmon will establish sustaining populations in rivers north of 

the Brooks Range, it appears possible that with the warming 

and changes in salinity projected in the next 50 years, salmon 

populations could be established.

Marine Fish. Changes to marine environments due 

to a changing climate potentially can affect marine fish 

in a number of ways, leading to distributional changes, 

increased or decreased mortality, and changes in the timing 

of reproduction and in growth. Very little is presently known 

about marine fish populations in the Beaufort and Chukchi 

Seas. Because of this, the North Pacific Fishery Management 

Council recently adopted a precautionary fishery management 

plan prohibiting commercial fishing in the region until the 

science is available to better understand fish populations there 

(North Pacific Fisheries Management Council, 2009). Other 

regions of the Arctic have recently seen changes in marine 

fish populations that are believed to be climate related. For 

example, the distribution of marine species in the North 

Atlantic Ocean has changed in response to warming sea 

surface temperatures (SSTs) (Rose, 2005). Near Greenland, 

warming SSTs have resulted in a replacement of cod by 

shrimp (Hamilton and others, 2003). Similarly in the subArctic waters of the Bering Sea, decreases in spawning 

Greenland turbot and increases in spawning walleye pollock 

between 1965 and 2004, have been attributed to warming 

SSTs and decreased sea ice (Overland and Stabeno, 2004). 

Detection of these shifts was only possible because data 

existed from long-term and standardized surveys. Similar 

surveys are not available in the Chukchi and Beaufort Seas 

making it difficult to detect shifts in the distribution or ecology 

of these marine fish, or to determine exactly how these fish 

will respond to climate change.

Among marine fish, Arctic cod is one of the most 

abundant fish in the Arctic and is an important predator and 

prey species. Arctic cod commonly is found in the diets of 

beluga whales, ringed and bearded seals, and several sea birds. 

Given their abundance and trophic importance, Arctic cod play 

an important role in Arctic marine ecosystems and climatemediated changes in their abundance, distribution, survival, 

or nutritional content will have cascading effects across the 

Arctic marine ecosystem. Arctic cod are closely associated 

with sea ice (Crawford and Jorgenson, 1993) and, therefore, 

projected decreases in sea ice and changes in salinity are likely 

to affect the distribution and survival of Arctic cod (Gaston 

and others, 2003).

Evidence for shifts in the distributional range of fish 

species in the Beaufort Sea has been recently observed. In 

2008, National Oceanic and Atmospheric Administration 

(NOAA) Fisheries Service conducted an offshore survey of 

Beaufort Sea fish species and compared species composition 

of the catch with surveys conducted in 1976 and 1977. 
Chapter 4

Climate Change Considerations 95

During the 2008 survey, five species of fish not previously 

encountered in the Beaufort Sea, including Bering flounder, 

walleye pollock, bigeye sculpin, and Pacific cod were captured 

(Loggerwell, 2008). It is believed that these fish represent 

an expansion of range from the Bering Sea. Snow crab of 

commercial size also were captured during this survey. This is 

the first time that snow crab of commercial size were observed 

in the Arctic.

There is high inter-annual, seasonal, and short-term 

variation in salinity and temperature of the Beaufort 

Sea nearshore environment that is driven by a complex 

interaction of wind, riverine freshwater discharge, sea ice, 

and oceanographic processes. Fish occurrence, abundance, 

and community structure is driven by these variables. For 

example, in 30-km transects across the nearshore, salinity 

varied strongly among years: ranging from 3 to 29 psu 

(practical salinity units) in 1988 and 1991, and greater than 

25 psu in 1990 (Jarvela and Thorsteinson, 1999). In that study, 

Arctic cod were never encountered in salinities less than 

14.2 psu. Given the strong association between climate and 

oceanographic processes (see Ocean section), further work is 

needed to assess the population response of marine fish to a 

changing oceanographic environment.

Ocean acidification may have significant direct and 

indirect impacts on marine fish in the Beaufort and Chukchi 

Seas because the relative rate of change in sea-water 

acidification is highest at high latitudes (Orr and others, 2005; 

Fabry and others, 2009). Potential impacts to prey species 

with calcareous skeletal structures may result in significant 

and unknown changes to food webs that support marine 

fishes. Further, direct physiological impacts to marine fishes 

may result in changes in skeletal or scale growth but these 

impacts are not fully understood. Recent research suggests 

that migration and homing can be impaired by acidification 

(Munday and others, 2009), a potentially critical problem 

because so many Arctic fish species are migratory. Further 

work is needed to evaluate the potential impacts of ocean 

acidification on fishes of the Beaufort and Chukchi Seas.

Birds

Arctic birds will be impacted by climate change in a 

variety of ways. Over the next 50 years, the abundance and 

distribution of bird populations in the Beaufort and Chukchi 

Seas (and adjacent coastal plains) are likely to be impacted by 

changes to critical nesting and rearing habitats, the availability 

and quality of food resources, the incidence and distribution 

of avian diseases, the frequency of predation, and whether the 

timing of migration and nesting can be adjusted sufficiently 

to accommodate projected seasonal environmental and 

food-availability changes (for example, melting of the winter 

snowpack and sea ice, subsequent greening of the tundra, 

emergence of aquatic insects) (Martin and others, 2009). Bird 

species that are unable to adequately adjust to a change in the 

seasonal timing of optimal food resources during the breeding 

season, and other important events in their annual life cycle, 

are likely to diminish (for example, Stenseth and Mysterud, 

2002; Gaston and others, 2009). Because most bird species 

that occupy the Arctic are migratory, with some undergoing 

spectacular migrations to the southern hemisphere, climate 

effects outside of Alaska, also may have strong influences on 

Alaskan-nesting birds.

Seabirds. Climate effects are best known for black 

guillemots that nest on Cooper Island in the western Beaufort 

Sea and cliff-nesting seabirds that breed in the southern 

Chukchi Sea although the issue is not well studied. At Cooper 

Island, decreases in summer pack-ice extent are correlated 

with changes in black guillemot population size, breeding 

success, and food provided to nestlings (Moline and others, 

2008). Both breeding productivity and the percentage of 

Arctic cod in the diet have decreased as the distance to the 

summer ice edge has increased in recent years. Declines in 

productivity recently have been exacerbated by predation of 

guillemot nestlings by polar bears who are coming onshore on 

the Beaufort Sea coast (including Cooper Island) in increasing 

numbers as sea ice retreats far offshore each summer. Declines 

in Arctic cod during the nesting season associated with seaice retreat also might have been a factor in poor reproductive 

success of black-legged kittiwakes at Cape Lisburne in the 

eastern Chukchi Sea since the early 1990s (Roseneau, 2010).

Sea Ducks. A diversity of marine waterfowl occurs within 

the Arctic OCS and adjacent terrestrial habitats of the Beaufort 

and Chukchi Seas. Keystone species include Steller’s eider, 

spectacled eider, king eider, Pacific common eider, and longtailed duck. Sea ducks are omnivorous with diets that include 

a diversity of freshwater invertebrates (insects, crustaceans, 

mollusks) and aquatic plants during the breeding season, and 

marine invertebrates, fishes (sculpin, cod), and algae during 

the molting and wintering periods (Goudie and others, 1999; 

Petersen and others, 1999a). Despite the projected increase in 

precipitation, there may be a reduction of moist and flooded 

tundra habitats by mid-century due to the improved drainage 

expected to occur with warming ground temperatures and a 

deepening active layer. If this occurs, it would reduce some 

invertebrate taxa important to sea ducks during the nesting 

period. Consequently, there may be decreases in productivity 

and abundance of sea ducks, as well as potential redistribution 

for some species. The projected warming of marine waters and 

changes in salinity regimes, especially in near-shore waters, 

are expected to compromise marine invertebrate abundance 

and the value of these critical habitats to foraging sea ducks. 

Spectacled eiders are a threatened species under authority of 

the Endangered Species Act. They, as well as several other 

species of sea ducks, use polynyas and open leads in fast ice 

during the non-breeding season (Petersen and others, 1999b; 
96 An Evaluation of the Science Needs to Inform Decisions on Outer Continental Shelf Energy Development in the Chukchi and Beaufort Seas, Alaska

Petersen, 2009). Sea ice that surrounds polynyas and leads 

provides a substrate for resting birds during periods when 

they are not actively diving for bivalves and other marine 

invertebrates, and it also reduces wave action that may 

contribute to increased energy expenditure of diving ducks. 

A decrease of autumn sea ice is predicted to have negative 

consequences on thermodynamics and energetics of wintering 

sea ducks (Petersen and Douglas, 2004). Pacific common 

eiders and long-tailed ducks nest on barrier islands of the 

Chukchi and Beaufort Seas. These habitats are expected to 

be particularly vulnerable to projected climate changes. With 

rising sea levels, the size of the barrier islands is expected to 

shrink and they are more likely to be over-washed by storm 

surges. In addition, with the projected decrease in sea ice and 

a likely increase in autumn storm frequency, both the erosion 

and migration rates of these islands are expected to increase. 

These events will likely result in loss of nest habitat. Projected 

environmental changes in the Beaufort and Chukchi Seas and 

adjacent land masses are likely to result in significant changes 

in the incidence and distribution of avian diseases, such as 

influenzas, Newcastle’s Disease, and cholera (AcevedoWhitehouse and Duffus, 2009). In concert with other factors 

already limiting some Arctic-breeding sea ducks (Steller’s 

eider, spectacled eider, long-tailed duck), emerging diseases 

are expected to further reduce populations. The population 

dynamics of lemmings also affect nesting success of sea ducks 

(and other waterbirds). In years of low lemming abundance, 

waterfowl, their eggs, and young are of increased importance 

as prey of predators, such as Arctic foxes, ravens, and jaegers. 

Therefore, climate-related changes in microtine rodent 

populations may indirectly affect sea duck productivity.

Loons. All five of the World’s species of loons (yellowbilled, red-throated, Arctic, common, and Pacific) occur within 

the Arctic OCS and adjacent landmasses of the Beaufort and 

Chukchi Seas (Johnson and Herter, 1989; North, 1994; Barr 

and others, 2000; Russell, 2002a, 2002b; Evers and others, 

2010). They are dispersed in their breeding distribution 

and occur primarily in freshwater, coastal habitats during 

the summer nesting period. For most of their annual cycle, 

they are dependent on marine habitats including estuaries, 

embayments, and pelagic areas. Loons feed primarily 

on freshwater and marine fishes and some invertebrates. 

Increasing freshwater and oceanic temperatures, and changes 

to hydrology may have direct impacts on forage fishes 

important in the diets of these species. The abundance and 

distribution of loons on the Arctic Coastal Plain will be 

primarily dictated by the ecological response of a few key 

fish species (for example, sticklebacks and ciscos) to climate 

change. Loss of sea ice and a larger expanse of open water in 

near-shore areas of the Beaufort and Chukchi Seas have been 

shown to contribute to extensive erosion of coastal habitats 

important to breeding loons. Furthermore, increased oceanic 

warming, especially in near-shore areas of the Arctic OCS, 

along with alteration of barrier island systems resulting from 

storm events, will likely negatively affect the composition 

and biomass of marine fishes exploited by loons (Martin and 

others, 2009).

Shorebirds. More than 25 species of waders nest in 

freshwater and palustrine habitats of the Arctic Coastal Plain 

of the Beaufort and Chukchi Seas (Alaska Shorebird Group, 

2008). Shorebirds have diverse diets that include terrestrial 

and aquatic invertebrates. Warming temperatures are expected 

to influence the timing and patterns of insect (terrestrial and 

aquatic) emergence and peak densities, which may result in 

an ecological mismatch for some species that are not able to 

adjust migration phenology to keep track of advancement 

of spring phenomena in Arctic breeding areas (Meltofte and 

others, 2007). Accumulation of organic matter may affect 

habitats of breeding populations of some species depending on 

the rate at which it occurs and how this in turn influences the 

availability of invertebrate prey species. Likewise, predicted 

acidification of aquatic habitats associated with increasing 

atmospheric CO2 levels may reduce diversity and biomass 

of invertebrates important in the diets of species such as 

phalaropes. As previously noted, improved drainage and a 

deepening active layer due to the projected warming may 

lead to a reduction in aquatic and semi-aquatic habitats on 

the Arctic Coastal Plain. If a significant reduction of these 

habitats does occur, it will negatively affect invertebrate 

productivity and availability, as well as a loss of nesting and 

rearing habitats for shorebirds. The red phalarope is dependent 

on food resources associated with offshore pack ice during the 

pre- and post-breeding periods. The dynamics of sea ice under 

changing climate scenarios may affect timing and availability 

of these resources and consequently affect survival of this 

species. Breeding shorebirds on the Arctic Coastal Plain 

also may be affected by increased predation associated with 

increasing numbers of avian predators, such as ravens, foxes, 

and glaucous gulls on the North Slope (Alaska Shorebird 

Group, 2008, Weiser and Powell, 2010).

Geese. Pacific black brant, lesser snow goose, Canada 

goose, cackling goose, and greater white-fronted goose are 

the prominent species that occur within the subject area. All 

are grazers that exploit grasses and sedges that occur adjacent 

to freshwater basins and salt-tolerant plants that dominate 

near-shore and inter-tidal zones. Forage quality, rather than 

quantity, is considered the most important factor limiting 

survival. Clearly, warmer ambient temperatures will affect the 

growing season on the Arctic Coastal Plain and consequently 

plant biomass, but not necessarily forage quality. Sea-level 

rise in concert with increased storm-surge frequency and 

elevated water temperature has resulted in significant erosion 

of coastal habitats that are critical to nesting and molting birds, 

and this trend is expected to continue through mid-century. 

Additionally, it has been demonstrated that increased storm 

surge heights within the last decade have caused intrusion 

of salt water in low-lying areas of the Arctic Coastal Plain 
Chapter 4

Climate Change Considerations 97

of the Beaufort and Chukchi Seas, which initially results 

in barren areas of no value to herbivorous geese (Flint and 

others, 2008). However, an influx of marine waters provides 

conditions suitable for salt-tolerant plants that also may 

generate expansive, single-species “grazing lawn” that can be 

exploited by geese during the pre- and post-breeding periods. 

Warming ambient temperatures in combination with drying 

conditions on the Arctic Coastal Plain have been shown to 

favor invasion of woody plants, such as willows and alders, 

which replace grasses, sedges, and forbs important as nesting 

cover and forage for geese. The trend towards an increasing 

prevalence of woody plants on the Arctic Coastal Plain is 

expected to continue through mid-century.

Marine Mammals

Factors that can affect marine mammals in Alaska are 

of concern to many in the United States, Canada, and Russia. 

Climate change is a pervasive force that could influence 

other factors that affect marine mammals in the Beaufort and 

Chukchi Seas, such as oil and gas development, shipping, 

tourism, and subsistence hunting. Many Arctic marine 

mammals are associated with sea ice for all or part of their 

annual life cycle. Climate change also could affect marine 

mammals through a number of pathways, for example, 

• decreases in sea ice that could affect foods, foraging 

or other aspects of their life cycles; 

• increased primary and secondary production;

• reduced benthic and pelagic biomass in coastal/shelf 

areas due to increased river runoff and change in 

turbidity and salinity; and 

• increased pelagic grazing and recycling in open 

water of the Chukchi Sea at the expense of the 

current tight benthic-pelagic coupling in ice-covered 

shelf regions. 

Should these scenarios come to fruition, pelagic-feeding and 

generalist marine mammals might have an advantage over 

benthic shelf-feeding, ice-dependent species such as walrus 

and bearded seals (Bluhm and Gradinger, 2008). Moore and 

Huntington (2008) developed a useful conceptual model 

(fig. 4–6) that examines the potential impacts of climate 

Ice-obligate species

Polar bear 

Walrus 

Bearded seal 

Ringed seal 

Seasonally migrant species

Fin whale 

Minke whale 

Humpback whale 

Gray whale 

Killer whale 

Ice-associated species

Harp seal 

Hooded seal 

Ribbon seal 

Spotted seal 

Beluga 

Narwhal 

Bowhead whale 

↑Sea ice

↑Benthic community 

↑Human subsistence activities 

↓Human commercial activities 

↓Sea ice

↑Pelagic community 

↓Human subsistence activities 

↑Human commercial activities 

+

+

_ +

_

_

Figure 4–6. A conceptual model of sea-ice impacts on ice-obligate, ice-associated, and seasonally migrant 

marine mammal species: positive impacts are indicated by circled plus signs; negative impacts by circled minus 

signs. Dashed lines indicate uncertainty regarding potential impacts of sea-ice gain or loss for ice-associated 

species. (From Moore and Huntington, 2008.)
98 An Evaluation of the Science Needs to Inform Decisions on Outer Continental Shelf Energy Development in the Chukchi and Beaufort Seas, Alaska

change to Arctic marine mammals based on the gain or loss of 

sea ice. Ice-obligate species, such as polar bears and walrus, 

are sensitive to the loss of sea ice because they depend on 

it for hunting, breeding, and resting. The impacts to iceassociated species are harder to predict; some species such as 

ribbon seals and spotted seals seasonally rely on sea ice for 

whelping, but apparently can survive without sea ice during 

the remainder of the year. The seasonally migrant cetacean 

species are likely to benefit from sea-ice loss due to greater 

access to Arctic waters.

Whales. Seven species of whales are found in Arctic 

waters of the Beaufort and Chukchi Seas: bowhead whale, 

beluga, fin whale, humpback whale, gray whale, minke whale, 

and killer whale. Bowhead whales and belugas are capable of 

living in waters that are highly ice-covered. Beluga whales 

are known to seasonally migrate to 80°N with greater than 

90 percent ice cover (Suydam and others, 2001). However, 

bowhead whales and beluga also are capable of surviving 

at great distances from sea ice and sometimes select openwater habitats (Moore, 2000). Decreases in sea ice may 

enhance feeding opportunities on prey, at least for bowhead 

whales (Moore and Laidre, 2006). Another indication of how 

bowhead whales are responding to decreased sea ice is that 

the population has increased steadily during roughly two 

decades of sea-ice loss in the western Beaufort Sea (George 

and others, 2004). This suggests that sea-ice loss is not 

hindering productivity of this population as it slowly recovers 

from commercial over-exploitation. Although the long-term 

effects of climate change on bowhead whales are unclear, 

from the perspective of sea ice, this species will likely fair 

well compared with highly ice-dependent species (George and 

others, 2008). 

For migrant whales, it is likely they will range farther 

north and remain longer in response to declining sea-ice cover. 

These species now occur within seasonal sea-ice habitats in 

the Bering Sea where they feed primarily on forage fishes 

whose stocks may have increased as a result of a boost to 

pelagic community production predicted to accompany 

decreases in sea ice (Hunt and others, 2002; Moore and 

Huntington, 2008). There is evidence that gray whales are 

responding to ecosystem change by feeding predominantly 

in the Chukchi Sea as opposed to the northern Bering Sea, 

coincident with a decline in amphipods in the Chirikov Basin 

of the Bering Sea (George and others, 2008). Evidence for 

migrant whales overwintering farther north in recent years 

includes fin whales overwintering in the Bering Sea (Moore 

and Huntington, 2008), humpback whales wintering in 

southeast Alaska and Kodiak, and gray whales overwintering 

in the western Beaufort Sea (Moore and others, 2006).

With the exception of beluga and killer whales, all 

of the whales in the Beaufort and Chukchi Seas are filter 

feeders, feeding primarily on plankton and invertebrates with 

calcareous exoskeletons. Recent simulations using global 

ocean models suggest the surface waters of the Arctic Ocean 

will become undersaturated with respect to calcium carbonate, 

and therefore corrosive to calcifying organisms, within a 

decade (Steinacher and others, 2009). For filter-feeding 

whales, there are concerns about the impact of acidification 

on their invertebrate prey. Although the biological response 

to acidification will likely vary across species and life stages, 

both benthic and planktonic calcifying organisms are expected 

to be impacted, as are the whales that feed on them. The extent 

to which filter-feeding whales will be impacted is currently 

unknown.

Pinnipeds (Ice Seals and Pacific Walrus). Four species 

of ice seals are found in the Beaufort and Chukchi Seas of 

Alaska: ringed, bearded, ribbon, and spotted seals. Ringed and 

bearded seals are considered ice-obligate species, whereas the 

ribbon and spotted seals are ice-associated species (Moore 

and Huntington, 2008). All four species are at least seasonally 

dependent on sea ice, using it as a platform for resting, 

breeding, whelping, nursing, and molting. But ribbon and 

spotted seals use sea ice for much shorter durations of time. 

The ribbon seal is pelagic during the ice-free season, whereas 

the spotted seal uses terrestrial haulouts and feeds at sea 

during the open-water season. The Pacific walrus is considered 

an ice-obligate species (Moore and Huntington, 2008). 

Laidre and others (2008) developed a climate-change 

sensitivity index for Arctic marine mammals. They considered 

walrus, spotted seal, and ribbon seal to be moderately sensitive 

and ringed and bearded seals to be least sensitive. Ringed 

and bearded seals were deemed to have lower sensitivity to 

climate change because of their large population size, wide 

circumpolar distributions, and plasticity in regards to habitat 

specificity, diet diversity, movements, and site fidelity. Ribbon 

seals, spotted seals, and Pacific walrus all have smaller 

populations that are restricted to the western North Pacific, 

Bering, Chukchi, and Beaufort Seas. All five species were 

determined to be highly sensitive to sea-ice changes (Laidre 

and others, 2008).

Bearded seals are distributed across the circumpolar 

Arctic. They generally prefer ice habitat that is in constant 

motion and produces natural openings, such as leads, fractures, 

and polynyas for breathing, hauling out on the ice, and access 

to water for foraging. They are primarily a benthic feeding 

seal. To remain associated with their preferred ice habitat, they 

generally move north in late spring and summer as the ice 

melts and retreats, and then move south in the autumn as seaice forms (Cameron and others, 2010). Bearded seals whelp on 

the ice and pups enter the water shortly after birth as a means 

to avoid predation. They also use sea ice as a platform to haul 

out during the annual molt, which is concentrated during late 

spring and early summer (National Marine Fisheries Service, 

2010b). The main concern about the conservation status of 

bearded seals stems from the likelihood that their sea-ice 

habitat has been modified by climate warming and will likely 

continue to decrease in extent through mid- to late century. 

A second concern related to greenhouse gas emissions, is the 
Chapter 4

Climate Change Considerations 99

modification of habitat by ocean acidification, which may alter 

prey populations and trophic relationships for bearded seals. 

To adapt to a regime of decreased sea ice, bearded seals likely 

will need to shift their nursing, rearing, and molting areas to 

ice-covered seas north of the Bering Strait, where projections 

suggest there is potential for the ice edge to retreat to deep 

waters of the Arctic Basin. There appears to be a high threat 

that decreases in spring and summer sea ice will result in a 

large separation between sea ice resting areas and benthic 

feeding habitat. Decreases in sea ice suitable for molting 

and pup maturation also appear to pose a high threat. Based 

primarily on projected changes to sea ice, the National Marine 

Fisheries Service (NMFS) recently proposed the Beringia 

subspecies of bearded seal be listed as threatened under the 

Endangered Species Act (ESA) (National Marine Fisheries 

Service, 2010b). 

The Arctic ringed seal is the most widespread and 

abundant of the five subspecies of ringed seals and is found 

across the circumpolar Arctic including the Beaufort and 

Chukchi Seas. The main concern about the conservation status 

of ringed seals is the likelihood that their sea-ice habitat has 

been modified by climate warming and likely will continue 

to decrease in extent through mid-late century. Ringed seals 

depend on sea ice for reproduction. They build lairs under 

the drifting snow on sea ice where they give birth and nurse 

their pups (Kelly and others, 2010). Following weaning, 

ringed seals undergo molt and spend large amounts of time 

basking in the sun on sea ice. The NMFS recently proposed 

Arctic ringed seals for listing under the ESA (National Marine 

Fisheries Service, 2010a) because of the implications of 

climate change on this species. The proposal concludes that 

within this century, snow cover is forecast to be inadequate 

for the formation and occupation of birth lairs over most 

of the subspecies’ range. The projected decrease in sea ice, 

and especially snow cover, will likely lead to decreased pup 

survival and a substantial decline in the abundance of the 

Arctic subspecies. Predation risk from polar bears, Arctic 

foxes, gulls, and ravens is expected to increase with declining 

snow depth and duration of snow cover. Although loss of 

sea ice and snow cover is the principal justification for the 

proposed listing, other factors such as changes to their prey 

base from ocean acidification, increased shipping, and oil 

and gas development could negatively affect ringed seals. 

The significance of these other threats would increase for 

populations diminished by the effects of climate change 

(National Marine Fisheries Service, 2010a).

Ribbon seals use annually formed sea ice for reproduction 

and molting in the spring, but are largely unassociated with 

sea ice during summer, autumn, and early winter (Boveng 

and others, 2008). They have an apparent affinity for stable, 

moderate-sized ice floes that are slightly interior to the pack 

ice edge where they give birth, nurse, and later molt. In years 

of low ice, ribbon seals likely will adjust by shifting their 

breeding locations in response to the position of the ice edge, 

as they have likely done in the past in response to interannual sea ice variability. Decreased availability of stable ice 

platforms for adults to complete their molt out of the water 

may lower survival, but it is not currently possible to quantify 

this impact or the extent to which ribbon seals may adapt by 

shifting locations for molting. Changes in ribbon seal prey, 

anticipated in response to habitat changes resulting from 

ocean warming and loss of sea ice, have the potential for 

negative impacts, but these impacts are not well understood. 

Some changes already documented in the Bering Sea could 

be beneficial. For example, several fish species, including 

walleye pollock (Theragra chalcogramma), a common 

ribbon seal prey, have shown northward distribution shifts 

in response to warming. The NMFS has found that listing 

the ribbon seal under the ESA is not warranted (National 

Marine Fisheries Service, 2008). Although the ribbon seal 

abundance is likely to decline gradually, primarily from slight 

but chronic impacts on reproduction and survival caused by 

reduced frequency of years with sea ice of suitable extent, 

quality, and duration of persistence, the NMFS concluded it is 

not in danger of extinction or likely to become an endangered 

species (National Marine Fisheries Service, 2008).

The distribution of spotted seals is seasonally related 

to life history events that can be broadly divided into 

two periods: late autumn through spring, when breeding, 

whelping, nursing, and molting all take place in association 

with sea ice on which the seals haul out; and summer through 

autumn, when the sea ice has melted and spotted seals remain 

closer to shore to use land for hauling out. The annual timing 

of spotted seals’ reproduction has evolved to coincide with 

the average period of maximum extent and stability of the 

seasonal sea ice. Sea ice provides a platform away from land 

predators during the breeding, whelping, nursing, and molting 

periods. When sea ice begins to form in the autumn, spotted 

seals start to occupy it immediately, concentrating on the 

early ice that forms near river mouths and estuaries. In winter, 

as the ice thickens and becomes shorefast along the coasts, 

spotted seals move seaward to areas near the ice front with 

broken ice floes. Spotted seals are divisible into three Distinct 

Population Segments (DPS) (Boveng and others, 2009), of 

which the Bering DPS (Bering, Chukchi, and Beaufort Seas) 

is most relevant to this report. While the effects of climate 

change may decrease suitable habitat for spotted seals in the 

southern portion of the Bering DPS’ range, such losses may 

be offset, in part, by increases in suitable habitat in the north. 

Even if sea ice were to completely vanish from the Bering 

Sea, this population of spotted seals may adjust by relocating 

their breeding grounds to follow the northward shift of the 

annual ice front into the Chukchi Sea. Therefore, the Bering 

DPS is not presently in danger of extinction nor likely to 

become an endangered species. The NMFS has concluded 

that listing the Bering DPS of spotted seals as threatened 

or endangered is not presently warranted (National Marine 

Fisheries Service, 2009).
100 An Evaluation of the Science Needs to Inform Decisions on Outer Continental Shelf Energy Development in the Chukchi and Beaufort Seas, Alaska

Pacific walrus use sea ice throughout much of their 

annual cycle. In winter, the entire population uses sea ice in 

the Bering Sea and in late winter are found in distinct breeding 

aggregations in the southeast, central, and western Bering 

Sea. As the sea ice retreats in spring, most male walrus move 

to terrestrial haulouts in Bristol Bay and on the Chukotka 

Peninsula (Russia). Females and young stay with the ice 

as it retreats into the Chukchi Sea. Walrus are dependent 

on sea ice as a platform for birthing, nursing, and resting 

between foraging trips. They are a benthic feeder, feeding 

on bivalves and other invertebrates on the seafloor. Summer 

sea-ice extent in the Chukchi Sea has decreased rapidly in 

recent years, retreating off the shallow continental shelf and 

over deep Arctic Ocean waters where walruses presumably 

cannot feed. Declines in sea-ice extent, duration, and thickness 

are expected to continue (Douglas, 2010). Over the past 

decade, the number of walrus coming to shore along the 

coastline of the Chukchi Sea in Russia has increased. Female 

and young walrus are arriving earlier and staying longer at 

coastal haulouts as summer ice disappears. Numbers in the 

tens of thousands have been reported anecdotally from some 

haulouts in Chukotka and large walrus aggregations also were 

observed along the northwest Alaska coast in autumn 2007, 

2009, and 2010. Walrus are able to survive using terrestrial 

haulouts, but there are potentially two primary impacts of 

this behavioral change. First, the ability of the benthic food 

supply within foraging range of coastal haulouts to support 

large numbers of walruses over the long term is a concern. 

Second, as demonstrated in Russia and in Alaska in 2009, 

calves on terrestrial haulouts are susceptible to disturbances 

and can be killed when walruses stampede to safety in the 

water (Fischbach and others, 2009). The USGS developed 

a Bayesian network model to integrate potential effects 

of changing environmental conditions and anthropogenic 

stressors on the future status of the Pacific walrus population 

for four time periods through the 21st century (Jay and others, 

2011). Outcome probabilities through the century reflected a 

clear trend of worsening conditions for Pacific walrus. The 

summed probabilities for vulnerable, rare, and extirpated 

outcome states increased from a level of 5 percent in 2004 

to 22 percent by 2050 and 40 percent by 2095. In the model, 

sea-ice habitat and harvest levels had the greatest influence 

on future population outcomes. Other potential stressors, such 

as ocean acidification, had much smaller influences on walrus 

outcomes, mostly because of uncertainty in future states of 

these variables and our current poor understanding of their 

influence on walrus abundance. In response to a petition to 

list Pacific walrus under the ESA, the U.S. Fish and Wildlife 

Service (USFWS) completed a status review, and in February 

2011, concluded that listing the Pacific walrus was warranted, 

but precluded, due to other higher priority listing actions (U.S. 

Fish and Wildlife Service, 2011). 

Polar Bears. Polar bears are dependent on sea ice for 

much of their life history. Polar bears are an ice-obligate 

species (Moore and Huntington, 2008) considered to be one 

of the most sensitive of Arctic marine mammals to climate 

change (Laidre and others, 2008). Although range-wide, 

polar bears use sea ice to varying degrees depending on its 

seasonal availability, in the Beaufort and Chukchi Seas, they 

spend most of their time on sea ice where they hunt for their 

primary prey, ringed and bearded seals. Polar bears breed 

on the sea ice and many females in the Beaufort Sea den on 

sea ice although they also den on land. In places where polar 

bears come ashore for long periods of time because the sea 

ice seasonally disappears, such as in Hudson Bay and Davis 

Strait, polar bears largely fast until the sea ice returns in the 

autumn and can again hunt seals. Research has begun to 

document the effects of decreasing sea ice on this species. In 

western Hudson Bay, sea ice is now absent for about 3 weeks 

longer than just a few decades ago. There, survival of the 

youngest and oldest bears has declined and is correlated with 

years of earlier sea ice break-up. The western Hudson Bay 

polar bear population is now believed to be in decline (Regehr 

and others, 2007). In the southern Beaufort Sea, where polar 

bears have historically denned on sea ice in large numbers, 

more polar bears are now denning on land (Fischbach and 

others, 2007). The growth rate of the polar bear population in 

the southern Beaufort Sea was related to the length of time sea 

ice was absent from the continental shelf, with about 127 days 

as the break point between good years and bad years (Regehr 

and others, 2009). Based on this relationship, modeling using 

AOGCM climate projections suggests that the Beaufort Sea 

polar bear population will decline to just a fraction of its 

current size by the end of this century (Hunter and others, 

2010). Declines in sea ice, presumably mediated through 

poorer hunting of ice seals, has also resulted in diminished 

size of polar bears in the southern Beaufort Sea (Rode and 

others, 2010). As sea ice has retreated farther and farther 

away from the Beaufort Sea coast of Alaska, more bears are 

showing up on shore where many forage on carcasses of 

subsistence-harvested bowhead whales. It is unclear which 

strategy, staying with the sea ice as it retreats offshore or 

moving to the coast, is better for polar bears; this is currently 

under investigation. Modeling by the USGS suggests that if 

current patterns of sea ice loss continue, up to two-thirds of 

the current World’s polar bear population will disappear by the 

end of this century (Amstrup and others, 2008). The polar bear 

was listed as threatened by the USFWS in May 2008.
Chapter 4

Climate Change Considerations 101

Expected Climate and Environmental Changes in 

the Beaufort and Chukchi Seas by Mid-Century

Significant climate changes are projected to occur in the 

Arctic OCS by mid-century as we summarize in table 4–1. 

These will affect the physical environment in which Arctic 

OCS energy activities occur, biological systems, which also 

may be impacted by Arctic OCS energy activities (cumulative 

impacts), and indigenous populations. Here, we list a number 

of findings regarding the projected climate changes in the 

Arctic OCS that are most relevant to oil and gas activities 

and how those changes may affect fish, birds, and marine 

mammals within the Arctic OCS. How these changes may 

either mitigate or compound the effects of Arctic energy 

development is largely described in other chapters of this 

report (for example, see Chapter 5, Oil-Spill Risk, Response, 

and Impacts and Chapter 7, Cumulative Impacts). There is 

a strong seasonality to many of these changes. Some of the 

changes will compound the effects of Arctic energy activities 

while others will tend to mitigate them. By judiciously 

choosing when energy activities occur, environmental risks 

associated with those activities may be minimized. Finally, we 

offer a few recommendations.

Table 4–1. Projected climate-change impacts for Beaufort and Chukchi Seas landform areas.

[–, no direct impact, or little impact, relative to the other landform areas]

Coastal plain Coast Continental shelf

Warmer temperatures Accelerated permafrost

degradation.

Biological shifts.

Accelerated coastal erosion.

Biological shifts.

Warmer surface waters.

Reduced sea ice.

Biological shifts.

Increased precipitation Warmer ground temperatures

due to thicker snow pack.

Warmer ground temperatures

due to thicker snow pack.

Reduced salinity of surface

waters.

Increased clouds/fog Less radiation available for

photosynthesis.

Reduced visibility.

Less radiation available for 

photosynthesis.

Reduced visibility.

Less radiation available for

photosynthesis.

Reduced visibility.

Storms – Accelerated coastal erosion.

Increased storm surges.

More wave action.

Reduced sea ice – Accelerated coastal erosion. Increased light in water

column.

Warmer surface waters.

More wave action.

Circulation changes.

Biological shifts.

Sea-level rise – Areas of western Beaufort coast

will be inundated.

Barrier islands shrink.

Ocean acidification – – Disruptions to the food web,

marine ecosystems.

Ocean circulation – – Changes in availability and

distribution of nutrients.
102 An Evaluation of the Science Needs to Inform Decisions on Outer Continental Shelf Energy Development in the Chukchi and Beaufort Seas, Alaska

4.01. Findings:

•	 Temperature. Significant temperature increases are projected to occur in the Beaufort and Chukchi Seas by mid-century, particularly during the 

autumn and winter. For the A1B (‘medium’) emission scenario, autumn temperatures are projected to increase roughly 5°C in this region by 

mid-century, while winter and summer temperatures are projected to increase about 6°C and about 1°C, respectively. These values, based on 

ensemble averages probably are conservative. 

• Sea Ice. The seasonal extent and thickness of sea ice are projected to continue to decrease. The Beaufort and Chukchi Seas will still be icecovered during winter and spring. As at present (2011), the ice edge is projected to move northward through the Bering Strait roughly during 

June at mid-century. Rapid and extensive summer melting is expected to leave the Beaufort and Chukchi Seas largely ice-free during August–

October. Complete freeze-up of the Beaufort and Chukchi Seas is expected to be delayed about 1 month by mid-century, with the ice edge 

moving back through the Bering Strait in December. The projected timing of the onset of melting in the Beaufort and Chukchi Seas is fairly 

robust, while that of the autumn freeze-up is much less certain. The ice pack, when present, will be thinner and therefore more dynamic than 

it historically has been. 

• Precipitation. Significant precipitation increases are projected to occur during all seasons with the largest percentage of changes occurring 

during autumn and winter. The intensity of precipitation events also is projected to increase, as is the number of days when precipitation 

occurs. For the A1B scenario, current models project a 30–50 percent increase during the winter in this region and a 20–30 percent increase 

during summer. Mid-century values may be roughly one-half this. There is considerable uncertainty associated with the magnitude of the 

increases. Precipitation increases are expected to contribute to a freshening of the surface waters in the Arctic Ocean.

• Clouds. Models consistently project that the Arctic will become cloudier by mid-century. Some of the increase is expected to occur in the form 

of high-level clouds. Low-level clouds and fog are expected to become more prevalent during the open-water season. In addition, because 

low-level clouds and fog tend to be associated with open water, they are expected to be present over a greater fraction of the year due to the 

decrease of sea ice.

• Icing Conditions. Icing conditions are expected to occur more frequently in the coastal and marine environments of the Arctic OCS as openwater conditions persist longer during autumn.

• Winds. By mid-century, the western side of the Beaufort Sea High (atmospheric anticyclone) may weaken during the autumn season, allowing 

winds in the Chukchi Sea to be of a more southerly nature (that is, from the Bering Strait) than at present. During winter, the boundary 

between the Aleutian Low and the high-pressure bridge between Canada and Eurasia is expected to move northward into a location over the 

Chukchi Sea. This situation may strengthen the predominantly easterly winds during the winter.

•	 Storms. An increase in the frequency and (or) intensity of Polar Lows and other storms during autumn and winter appears likely in the Beaufort 

and Chukchi Seas based on a number of physical arguments. However, these ideas have not as of yet been rigorously tested so the projected 

increase in autumn/winter storminess remains uncertain. Projected changes in the degree of summer storminess are highly uncertain.

•	 Sea Level. Current estimates for global sea-level rise are in the range 0.3–0.4 m by mid-century. Sea-level rise in the Beaufort and Chukchi 

Seas is expected to be somewhat higher due to enhanced thermal expansion and a decrease in salinity. Some areas of the western Beaufort 

Sea coast are expected to be inundated by rising seas and barrier islands are expected to shrink. Low-lying areas will be increasingly 

susceptible to damage from storm surges. Artificial islands and causeways built for offshore energy development will be increasingly 

vulnerable to inundation from sea-level rise and damage from storm surges.

•	 Coastal Zone. The low-lying ice-rich Beaufort Sea coast appears to be particularly vulnerable to climate change impacts, while the Chukchi 

Sea coast is less so. The expected impacts include: inundation of low-lying coastal areas due to sea-level rise, greater damage caused by 

storm surges, and accelerated coastal erosion due to a number of factors. Permafrost degradation is expected to increase along both coasts. 

Barrier islands also are expected to be increasingly susceptible to climate change impacts. A loss of critical habitat is expected for many 

Arctic species that currently utilize the coastal zone and (or) nearby barrier islands. Unless properly engineered, land-based infrastructure (for 

example, pipelines, storage tanks) designed to support offshore energy development will be much more vulnerable to damage due to sea-level 

rise, storm surges, permafrost degradation, and accelerated coastal erosion.

•	 Ocean Acidification. Surface waters in the Arctic Ocean are expected to become increasingly corrosive (acidic) to calcifying organisms, 

potentially with significant impacts on the Arctic food web and marine ecosystems.

• Ocean Circulation. Given the projected changes in many of the factors that control ocean currents (for example, temperature, salinity, windfields, sea ice), it is likely that circulation patterns in the Beaufort and Chukchi Seas will change during this century. However, little work has 

been done as of yet to predict the details of those changes.
Chapter 4

Climate Change Considerations 103

4.01. Findings:—Continued

• Fish. The distribution, abundance, and species composition of fish populations in the Beaufort and Chukchi Seas and adjacent freshwaters 

will very likely change over the next 50 years due to climate change. A northward shift of some species and reductions in species with narrow 

adaptation to Arctic conditions is likely. It is difficult to predict specific changes because we lack critical information concerning relationships 

between environmental and biological parameters for most species inhabiting this region. Although anadromous fish in the Beaufort and 

Chukchi Seas are, in general, likely to be more strongly impacted by climate change than marine fish, changing sea ice conditions, salinity, and 

ocean acidification may strongly impact both diadromous and some marine fish species.

• Birds. The distribution, abundance, and species composition of bird populations in the Beaufort and Chukchi Seas and nearby coastal plains 

will very likely change over the next 50 years due to climate change. The details of those changes remain uncertain due to the high degree of 

complexity in climate-ecosystem interactions.

• Whales. Bowhead whales are not expected to be negatively impacted by decreases in sea ice. Migrant whales (fin, minke, humpback, 

gray, killer) are likely to be seen more frequently in the Beaufort and Chukchi Seas, and to remain there longer each season in response to 

decreasing sea ice cover. However, continued acidification of the Arctic Ocean is likely to negatively impact calcifying organisms that form an 

important part of the diet of filter-feeding Arctic whales (bowhead, fin, humpback, gray, minke).

• Pinnipeds (Ice Seals and Pacific Walrus). Bearded seals and Arctic ringed seals are expected to be negatively impacted by projected decreases 

in sea ice in the Beaufort and Chukchi Seas. The population of ribbon seals likely will decline gradually in the future with projected decreases 

in the timing and extent of sea ice, but the ribbon seal is not likely to become threatened in the foreseeable future. The seasonal distribution 

of spotted seals within the Bering, Chukchi, and Beaufort Seas may adjust in response to changing sea ice extent, following the sea-ice front 

farther north during the summer. The walrus population is expected to be negatively impacted by ocean acidification, which will reduce their 

benthic food supply, and by continued decreases in sea ice, which will separate them from the majority of their benthic foraging areas.

•	 Polar Bears. The polar bear populations of the Beaufort and Chukchi Seas are expected to be severely impacted by projected decreases of sea 

ice cover.

4.01. Recommendations: 

•	 Regional Climate Modeling and Climate Impact Assessments. The science community is actively engaged in developing state-of-the-art global 

climate models (AOGCMs) under the auspices of the International Panel on Climate Change (IPCC). However, these models lack the resolution 

needed to address many of the issues discussed in this report. Support for the development of fully integrated (atmosphere-ocean-land) 

regional climate models specifically for the Arctic region, as well as periodic Arctic climate impact assessments, is important. 

• Storms. Several physical arguments have been advanced suggesting the frequency and (or) intensity of storms is likely to increase during 

autumn and winter. It may be possible to test these ideas without further advances in the AOGCM models. Thus, these tests could be done in 

the near term. Little is known about how storminess also may change during the summer. Because the Arctic is somewhat decoupled from the 

global climate system during the summer, it may be possible to investigate changes in future summer storminess with regional climate models. 

We recommend these investigations be done as soon as possible to reduce the uncertainty of the storminess projections. 

•	 Ocean Circulation. Little work has been done as of yet projecting how circulation patterns in the Beaufort and Chukchi Seas may change during 

the next 50 years. Because those patterns are critical in shaping both the physical and biological environments of the Arctic OCS, and are an 

important element of spill response models, support for research aimed at better understanding how these patterns may change in the future 

is important.

•	 Biota. To better assess the potential impact of future climate change on biota in the Beaufort and Chukchi Seas, (1) more research focused 

on the response of species to changes in various environmental factors should be done, and (2) periodic population and distributional surveys 

should be undertaken.

•	 Science to Inform Arctic OCS Activities. The best climate models we have today suggest significant environmental changes will occur in the 

Arctic OCS by mid-century. Given the uncertainties in the magnitude and timing of these changes, and their impact on biological systems, it 

would be prudent to use an adaptive management approach to Arctic OCS activities. Such an approach would periodically incorporate new 

knowledge gained from monitoring systems designed to track the actual trajectory of climate change within the Arctic OCS, new research that 

for example elucidates the response of Arctic biological systems to climate change, and from better climate-prediction models as they are 

developed.
104 An Evaluation of the Science Needs to Inform Decisions on Outer Continental Shelf Energy Development in the Chukchi and Beaufort Seas, Alaska

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Chapter 5

Oil-Spill Risk, Response, and Impact 109

Chapter

5

Introduction / Rationale

Parties with interest in oil and gas 

development decisions in the Arctic Offshore 

Continental Shelf (OCS) have varying views 

and concerns over the probability that such 

activities will result in an oil spill in the 

Arctic. They also differ in their views of how 

prepared government and industry are to 

respond to and understand the consequences 

of any such spills. The Bureau of Ocean 

Energy Management, Regulation and 

Enforcement (BOEMRE) expresses the 

challenge the Nation faces in understanding 

and balancing the risks to its environmental 

assets as it explores and utilizes energy 

endowments.

 “Estimating large oil-spill occurrence 

or large oil-spill contact is an exercise 

in probability. Uncertainty exists 

regarding whether exploration or 

development will occur at all and, 

if it does, the location, number, and 

size of large oil spill(s) and the wind, 

ice, and current conditions at the 

time of a spill(s). Although some of 

the uncertainty reflects incomplete 

or imperfect data, a considerable 

amount of uncertainty exists simply 

because it is difficult to predict 

events 15–40 years into the future” 

(Minerals Management Service, 

2008a).

Oil-Spill Risk, 

Response, and Impact

By Leslie Holland-Bartels and Jonathan J. Kolak

The tiered decision process used to inform OCS actions 

regarding whether and how to proceed with oil and gas 

development involves making decisions that in the early planning 

phases have high unknowns but progress to actions whose 

potential effects and footprint can often be more easily judged. For 

example, the Federal planning process for oil and gas development 

steps from general, national OCS-wide 5-year plans, which have 

the highest unknowns, to lease sale plans, to individual exploration 

activities, with significantly more project detail. After the U.S. 

Geological Survey (USGS) OCS Team completed its preliminary 

examination of documents, it was evident that scientific and 

technical information related to our Issue Topic of Oil-Spill 

Response (research needs to allow for an effective and reliable 

oil-spill response in ice-covered regions) occurs throughout the 

tiered planning and decision process. Similarly, science needs 

exist for other agencies that are “downstream” of these planning 

and decision processes. Within the leasing decision process, for 

example, there are biological opinions (such as those from the 

National Marine Fisheries Service, 2008; U.S. Fish and Wildlife 

Service, 2009) or water and air permit actions (from the U.S. 

Environmental Protection Agency). There are other processes 

outside the leasing process that also have a critical nexus to 

decision making about energy development, and these also require 

information. For example, while not specific to any leasing 

process, the Alaska Regional Response Team (ARRT; 2010) 

provides Federal, State, and local governmental agencies with the 

means to participate in response to pollution incidents. The ARRT 

also provides these governments’ overall joint spill preparedness 

and response plans, and its policies on spill countermeasure use are 

important to spill response in the Arctic and elsewhere. Industry 

may have the capability to use dispersants; however, they cannot 

do so without following ARRT guidelines. Similarly, the Natural 

Resource Damage Assessment (NRDA; National Oceanic and 

Atmospheric Administration, 2011), which takes place after a spill 

event and is outside of the BOEMRE program, is an important 

consideration within the decision framework of many of those that 

participated in our expert consultations. The main questions are, 

can the environmental consequences of any potential oil spill in 

the Arctic be understood and quantified sufficiently to judge the 

risks and benefits of energy development, and can restoration be 

accomplished should a spill occur? Uncertainty in the answer to 

those questions influences public perception, which in turn feeds 
110 An Evaluation of the Science Needs to Inform Decisions on Outer Continental Shelf Energy Development in the Chukchi and Beaufort Seas, Alaska

into the various permitting processes, or into legislative or 

litigation action. Planning and (or) regulatory actions are 

taken by a wide range of entities that require scientific and 

technological information. Based on these considerations we 

reframed our assignment to consider science needs within the 

full array of issues that influence the public’s perception on the 

ability to develop effective and reliable responses to oil spills 

in the Arctic.

First, we provide a brief description of major on-going 

efforts that identify necessary science and related technologies 

to help minimize the probabilities of an oil spill and to 

improve spill preparedness activities. We then focus our 

examination on how scientific information informs and what 

gaps might exist for these subjects: (1) estimating the potential 

effects of oil spills in pre-decisional planning, (2) informing 

spill contingency planning and spill response, and 

(3) informing post-spill damage assessment and restoration 

considerations. At the conclusion of this chapter, we bring 

in materials first presented in Chapter 4, Climate Change 

Considerations related to potential future climate conditions in 

the Arctic and how any changes in environmental conditions 

might influence our present understanding of oil-spill risk, 

response, and impact.

Overarching Efforts and Real-Time 

Communications

The engagement and investment to develop data, 

approaches, and technologies that inform effective spill 

response comprise an ongoing and rapidly evolving effort 

that the USGS OCS Team wanted to ensure was not lost as 

we delve into specific details later in this chapter. It is best 

reflected in the numerous on-going study programs and recent 

documents, forums, and bibliographies that examine research 

and other preparedness issues. The BOEMRE environmental 

(Bureau of Ocean Energy Management, Regulation and 

Enforcement, 2010b) and technology (Bureau of Ocean 

Energy Management, Regulation and Enforcement, 2010c) 

programs and ongoing Joint Industry Program (JIP) activities, 

such as SINTEF (2010), provide up-to-date links to proposed, 

ongoing, and completed projects. The Prince William Sound 

Oil Spill Recovery Institute, established by Congress under the 

Oil Pollution Action of 1990 to support research, education, 

and demonstration projects designed to address oil spills in 

Arctic and sub-Arctic marine environments, maintains an 

active program to examine science associated with issues like 

the fate and effects of spilled oil in the Arctic and the ability of 

spill responders to mitigate impacts of spilled oil as reflected 

in their 2011–2015 Research Plan (Prince William Sound Oil 

Spill Recovery Institute, 2010). 

Scientists, managers, and regulators meet often in 

a variety of venues to present the most recent progress 

and challenges. For example, the 2011 Alaska Marine 

Science Symposium sponsored a workshop “Lessons 

Learned from the Gulf of Mexico” (http://vislab-ccom.unh.

edu/~schwehr/2011AkMarSciSym/, accessed March 30, 

2011). Speakers discussed aspects of the Deepwater Horizon

oil-spill response approaches and challenges as they might 

inform Alaska spill preparedness. The 2007 International Oil 

and Ice Workshop (http://www.boemre.gov/tarprojects/587/

webpages/home.html, accessed May 5, 2011), the second 

such workshop, brought together an international audience 

to advance knowledge of spill response in cold water and 

ice, including remote sensing, enhancements to mechanical 

recovery systems, chemical herders in ice, cold-water 

dispersants, experimental spills, case studies, and ongoing and 

future research programs. The bi-national U.S. and Canada 

Northern Oil and Gas Research Forum and the BOEMRE 

Information Technology Meetings offer opportunities to share 

new information in many topical areas. Discussions cover, 

for example, environmental conditions in exploration areas, 

interaction of oil and gas activities with sensitive coastal 

habitats, ice engineering for offshore operations, oil-spill 

prevention and management in the Arctic, and monitoring 

for cumulative effects. Presentations are publicly available 

(for example, North Slope Science Initiative, 2010; Bureau 

of Ocean Energy Management, Regulation and Enforcement, 

2011a). Focused workshops, such as the U.S. Coast Guard 

(2010) on operating in the Arctic or Coastal Response 

Research Center (2009, 2010), examine factors to improve 

preparation and response to marine incidents and document 

practitioner perspectives on operational and science gaps. 

A wide variety of near real-time information related to 

oil and gas development considerations is generated and 

shared in a variety of these forums. The question is not if 

such information is being produced, but rather what that 

information is and how it moves into the appropriate planning 

and decision processes of regulators and other vested parties. 
Chapter 5

Oil-Spill Risk, Response, and Impact 111

Minimize Spill Probabilities Through 

Infrastructure Decisions

The USGS OCS Team is not well positioned 

to rigorously consider the state of knowledge or key 

information and technology gaps related to infrastructure 

engineering. However, it generally is accepted that effective 

Arctic technologies are the first step in overall oil-spill 

risk minimization. In addition to technologies, a sound 

understanding of bathymetry, ice scour, and shoreline erosion 

data and processes can improve infrastructure siting decisions. 

The BOEMRE has an active program to develop safety-related 

information in advance of future operations in the Arctic. As 

part of their Technology Assessment and Research Program, 

engineering properties and forces of moving ice on structures 

and pipelines are being studied (http://www.boemre.gov/

tarprojectcategories/ice.htm, accessed March 30, 2011). The 

IMV Projects Atlantic (2008) assessed the current state of 

offshore technology in Arctic and sub-Arctic regions that 

might be applied in the Beaufort, Chukchi, and Bering Seas. 

They suggested the following to be valuable: 

– development of a regional ice gouge database for the 

U.S. Beaufort and Chukchi Seas; 

– identification of ice gouge recurrence rates; 

– collection of multi-year ice thickness distribution, 

ridge dimensions and frequency within a floe, floesize distribution, floe-speed distribution; 

– definition of first-year ice thickness distribution, 

ridge dimensions; 

5.01. Recommendation: The coordinated organization of data for access and distribution by all parties of particular 

workshop findings and recommendations would improve the value of such forums to help guide science planning and funding 

decisions. A holistic and up-to-date analysis of recommendations and insights presented in these “real-time” symposia 

also would help clarify and bring more transparency to what new or continued science investments are needed. Potential 

approaches to consider are systems similar to the National Biological Information Infrastructure portal (http://www.nbii.gov/) 

or enhancements of existing systems, such as Alaska Ocean Observing System (AOOS) (http://www.aoos.org/) or the North 

Slope Science Initiative (http://www.northslope.org/). 

5.01. Finding: The level of information and the number of entities generating scientific and technical information on spill 

preparedness topics are increasing exponentially as enhanced attention is turned towards the Arctic in general, and resource 

development more specifically. Individually, sources are well structured, but they roll up to a complex information challenge. It 

is difficult to know which identified needs are being addressed fully or partially, what new issues or insights have emerged, or 

how one should weigh the importance of identified gaps. 

– development of a regional geotechnical database; 

– advancements in allowable/acceptable pipeline strain 

limits, repair techniques, leak detection systems;

– advancements in subsea protection systems, and 

trenching technologies; 

– increased clarity on emergency well-control 

requirements; and 

– advancements in determining maximum gouge depth 

based on ice strength and driving forces. 

The IMV Projects Atlantic authors also examined openwater conditions with large fetches and waves because of the 

potential and now realized higher waves resulting from greater 

ice-free periods. The authors felt limited in their ability to 

consider this topic and supported the need for the compilation 

and collection of ice, meteorological, and oceanographic 

information to be used by all parties involved in infrastructure 

decisions. The generation of such data is an ongoing process 

within the BOEMRE annual studies process.

As noted above, information exchanges, such as the 

bi-national U.S. and Canada Northern Oil and Gas Forums, 

offer the best insight into topics that need to be addressed in 

the near term. Practitioners are investigating approaches to 

address ice forces on offshore platforms; offshore structure 

design challenges from ice load, scour, and thaw strain; 

predictive advances for critical sea-ice characteristics; extreme 

ice events; and impacts of increased open-water summer 

storms. These and other international forums support rapid and 

efficient transfer of state-of-the-art information on advancing 

technological challenges and successes.
112 An Evaluation of the Science Needs to Inform Decisions on Outer Continental Shelf Energy Development in the Chukchi and Beaufort Seas, Alaska

Examples of the BOEMRE Technology Assessment and Research Program titles for Arctic safety and ice mechanics 

projects. 

(http://www.boemre.gov/tarprojectcategories/ice.htm)

•	 Sea-ice scaling effects

•	 Engineering model for ice/soil/pipeline interaction

•	 Sea Ice Mechanics Workshop

•	 Safety/integrity of Arctic marine pipelines

•	 Scour and Arctic Marine Pipeline Workshop

•	 Risk assessment for ice damage to seabed facilities

•	 Ice Scour and Arctic Marine Pipeline Workshop

•	 22nd International Offshore Mechanics and Arctic Engineering 

Conference

•	 Construction and maintenance of ice islands: Current practice 

and future research

•	 Measurement and control of underwater noise from oil drilling 

and production operations

•	 Design options for offshore pipelines in the U.S. Beaufort and 

Chukchi Seas

•	 Arctic offshore technology assessment of exploration and 

production options for cold regions of the U.S. Outer Continental 

Shelf

•	 Banff 1999, 2001, 2003 Pipeline Workshops

•	 Sea spray icing of drilling and production platforms

•	 Assessment of superstructure ice protection as applied to 

offshore oil operations safety

•	 Seabed scour and buried-pipeline deformation due to ice ridges

•	 Collection and archiving of environmental data relevant to design 

of Arctic structures

•	 Beaufort and Chukchi Seas ice design criteria

•	 Frictional sliding of sea ice

•	 Tracking ice islands and extreme ice features from Ellesmere 

Island to the Chukchi Sea

•	 2009 freeze-up study of the Alaskan Beaufort Sea and Chukchi 

Sea 

•	 ICESTRUCT JIP: Ice Effects on Arctic Offshore Structures

•	 Arctic Offshore Technology Assessment 

•	 2010 freeze-up study of the Alaskan Beaufort and Chukchi Seas

5.02. Recommendation: Efforts by the BOEMRE and industry to facilitate discussions of infrastructure needs and advances 

should receive continued support. For example, the recommendations of the BOEMRE-commissioned study by IMV Projects 

Atlantic (2008) to compile and collect ice, meteorological, and oceanographic information to be used by all parties involved in 

infrastructure decisions should continue to be considered and incorporated into the annual Federal and industry work planning 

process. However, many-faceted and different entities examine infrastructure needs and potential solutions and this is a highly 

technical discipline. Thus, communication of advances and discussion of remaining critical needs could be enhanced through a 

coordinated, transparent full-cycle risk model. While this would be valuable within the engineering and technical community, 

such an approach also could provide a more effective means for the non-engineering community to see, understand, and 

engage in discussions about development benefits and risks. 

5.02. Finding: Significant coordinated international effort by industry and governments is taking place to develop safe 

and effective infrastructure and technologies to access energy resources in ice-covered Arctic waters. It appears that 

potential individual stress points are being well analyzed. Practitioners are investigating approaches to address offshore 

structure design challenges from forces, such as: ice load, scour, and thaw strain; and predictive advances for critical sea-ice 

characteristics, extreme ice events, and impacts of increased open-water summer storms. It was not evident to us how these 

efforts come together in a holistic analysis of full system risks to identify sensitive infrastructure components and the priority 

science and technology needed to enhance performance and safety. The types of physical threats to infrastructure related to 

ice (described above) generally are known but their distribution and the degree of the threat across the geography of potential 

leasing areas were not fully evident in our limited examination. 
Chapter 5

Oil-Spill Risk, Response, and Impact 113

Assessing Risks and Potential Effects of 

Oil Spills

Background 

Oil-spill risk analyses and their models and input data 

requirements used in Beaufort Sea and Chukchi Sea Planning 

Area decisions follow national protocols outlined in numerous 

documents (for example, Minerals Management Service, 2006 

[appendix C], 2008a; Bureau of Ocean Energy Management, 

Regulation and Enforcement, 2010a). The major modeled 

components in these analyses include estimates of spill 

occurrence, spill trajectories, oil weathering patterns, and 

intersection probabilities with specific landscape units that are 

used to estimate fate and effect. 

Two key probability analyses are considered—the 

hazard-based Conditional Probability and the risk-based 

Combined Probability. The former assumes a spill has 

occurred and then estimates the percent chance that a large 

spill would reach coastal habitats or other critical assets (for 

example, archeological sites, harbors). The latter expresses the 

percent chance of one or more oil spills ≥1,000 barrels (bbl) 

occurring and that such oil contacts a certain environmental 

resource area or land segment. The chance of one or more 

large spills occurring is derived from the spill rate (obtained 

from a fault-tree analysis discussed below) and the assumed 

resource volume. These analytically derived risk probabilities 

are subsequently combined with best available ecological 

information to qualitatively express potential impacts as 

illustrated in this excerpt from the Minerals Management 

Service (2007):

“ The Oil-Spill-Risk Analysis (OSRA) model 

estimates a 40% chance of one or more large spills 

≥1,000 bbl occurring over the production life of 

Alternative I, but only 1% chance of one or more 

large spills occurring and contacting the U.S. 

Chukchi coastline within 3 days over the production 

life of Alternative I. If a large oil spill did contact 

this coastline, the oil probably would persist in a 

few of the tidal and subtidal sediments for a couple 

of decades, leading to a local but moderate effect 

on the few intertidal lower trophic-level organisms. 

The chance of one or more large spills contacting 

the U.S. Chukchi coastline increases to 6% within 

30 days over the production life of Alternative I, 

demonstrating the advantages of requirements for 

rapid response capability.”

Estimation of Spill Occurrence

 Because there is limited Arctic OCS development, 

sufficient historical data on offshore Arctic oil spills 

do not exist to calculate spill probabilities directly. 

The BOEMRE has used Gulf of Mexico (GOM) and 

Pacific OCS data as analogs. However, since 2002, the 

BOEMRE has modified and supplemented these data to 

represent expected Arctic performance for large spills 

through a statistical fault-tree approach (for example, 

Bercha Group, Inc., 2006a, 2006b, 2008a, 2008b). 

Figure 5–1 shows a typical fault tree for both large 

pipeline and platform spills. Input rational is developed 

for Arctic modified effects, such as for process plant 

and storage tank release, structural failure, storms, and 

collision events (table 5–1). Arctic-unique effects are 

additive components whose quantifications are done in 

a “relatively cursory” way based on judgment (Minerals 

Management Service, 2006, appendix C). Updating the 

methodology and input data are a regular part of the 

BOEMRE Alaska OCS annual study planning process. 

For example, the 2011 proposed plan includes the 

updating of the fault-tree analyses with any new oilspill occurrence reports, geohazard data, or GOM OCS 

historical data inputs; generation of fault-tree analyses 

for Arctic oil and gas lease sales based on the BOEMRE 

exploration and development scenarios; and generating 

life-of-field oil-spill occurrence rates and indicators 

(Prentki, 2010). 
114 An Evaluation of the Science Needs to Inform Decisions on Outer Continental Shelf Energy Development in the Chukchi and Beaufort Seas, Alaska

Figure 5–1. Typical fault tree for pipeline or large platform spill outlining key inputs including Arctic-specific factors, such as 

upheaval bucking, ice gouging, thaw settlement, scour and ice force, and facility temperature (Minerals Management Service, 2006, 

appendix C, figs. C–2 and C–3). 

tac11-5179_fig4-01a

Process

Facility

Release

Storage

Tank

Release

Structure

Failure

Hurricane

Storm Collison

Facility Low

Temperature

Ice Force

Arctic

Other

Event

Or Gate

Explanation

Large Platform Spill

Large Pipeline Spill

Mechanical Natural

Hazard

Unknown Arctic Operation

Impact

Third

Party Impact Corrosion

Connection

Failure Mud Slide Ice Gouging Upheaval

Buckling

Rig

Anchoring

Anchor

Impact Internal

Material

Failure

Storm/

Hurricane

Strudel

Scour

Thaw

Settlement

Work Boat

Anchoring

Jackup Rig

Spud Barge External

Trawl/

Fishing Net Event

Or Gate

Explanation

Other
Chapter 5

Oil-Spill Risk, Response, and Impact 115

Table 5–1. Example of platform fault-tree input rational for Arctic modifications and unique considerations from Gulf of Mexico base 

data. 

[Minerals Management Service, 2006, appendix C, table C–2. Spill size: All, all spill sizes combined; SM, small (≥50 and <100 bbl) and medium (≥100 and 

<1,000 bbl); HL, large (≥1,000 and <10,000 bbl) and huge (≥10,000 bbl)]

Event classification Spill size Percentage of frequency change Reason

Shallow Medium Deep

Arctic modified

Process facility release All (30) (30) (30) State-of-the-art now, high quality 

control, high inspection and 

maintenance requirements

Storage tank release All (30) (30) (30) State-of-the-art now, high quality 

control, high inspection and 

maintenance requirements

Structural failure All (20) (20) (20) High safety factor, monitoring programs

Hurricane/storm All (50) (40) (30) Less severe storms

Collision All (50) (50) (50) Very low traffic density

—

Frequency increment per 104 well-year

Median Median Median —

Expected Expected Expected

Arctic unique

Ice force

SM

0.1447 0.2170 0.3256 Assumed 10,000 year return period 

ice force causes spill 4 percent of 

occupancy 85 percent of the spills 

are SM

0.0340 0.0510 0.0765

HL

0.0255 0.0383 0.0575

0.0060 0.0090 0.0135

Facility low 

temperature

SM 0.1000 0.1000 0.1000 Assumed 10 percent of historical 

process facilities release frequency 

and corresponding spill size 

distribution

0.1000 0.1000 0.1000

HL 0.0080 0.0080 0.0080

0.0080 0.0080 0.0080

—

SM

0.0244 0.0316 0.0424

10 percent of above 0.0134 0.0151 0.0177

HL 0.0033 0.0046 0.0065

0.0014 0.0017 0.0022

5.03. Recommendation: Continued updating of spill data, re-examination of statistical approaches used in the 

application of non-Arctic analogs (see Eschenbach and others, 2010), and rigorous development and incorporation of climateinfluenced forecasts on factors such as storms, vessel traffic, or other fault-tree model adjustments would provide improved 

understanding of and confidence in spill risk estimates over the proposed project life. 

5.03. Finding: The spill probability—fault-tree process—is a well documented, transparent, and best available approach 

to deal with estimations of spill likelihood in the Arctic OCS given that regional historical data on spills are not available. 

However, the approach depends on accurate adjustments of non-Arctic data to likely Arctic outcomes, which are admittedly 

done in a somewhat cursory manner. Climate change considerations also may alter the validity of spill frequency adjustments. 

For example, adjustment of GOM spill frequency probabilities downward because of an assumption that storms are less 

severe in the Arctic and that a reduced collision rate exists because of less traffic (table 5–1) as compared to GOM values 

may need to be reconsidered. For example, increases in storm severity and traffic patterns have already been observed and 

may increase in response to changing climate and ice conditions in the Arctic (see Chapter 4, Climate Change Considerations). 
116 An Evaluation of the Science Needs to Inform Decisions on Outer Continental Shelf Energy Development in the Chukchi and Beaufort Seas, Alaska

Spilled-Oil Weathering and Persistence

The weathering characteristics of spilled oil influence 

the range of drift and spreading considered within spill 

trajectory assessments and dictate the effectiveness of 

chemical dispersants, in-situ burning, or mechanical responses 

(Daling and others, 1997; Prenki and others, 2004; fig. 5–2). 

The BOEMRE employs the Norwegian-developed and field 

tested (Daling and others, 1997; Daling and Strøm, 1999) 

SINTEF Oil Weathering Model (OWM) that incorporates oil 

density, viscosity, pour point, flash point, and water content 

and physical processes, such as spreading, evaporation, 

oil-in-water dispersion, and water uptake, as factors within 

its model-weathering calculations. The OWM is run over a 

30-day time horizon, but has not been verified against field 

data for more than 4–5 days, nor does the SINTEF OWM 

incorporate the effects of currents, beaching, photo-oxidation, 

microbiological degradation, adsorption to particles, or 

encapsulation by ice that might affect degradation rates and 

toxicological characteristics. A summary of the model and 

uses within OCS analyses are presented by Prentki and others 

(2004). 

Weathering is the combination of numerous physical, 

chemical, and biogeochemical processes acting to alter the 

phase and (or) composition of the oil. The processes affecting 

the weathering of oil spilled in open water, even in cold-water 

environments, generally are well understood (Fingas, 2008b). 

Many of the fundamental processes—such as evaporation, 

dissolution, spreading, and photodegradation—affecting oil 

weathering in the Arctic also occur elsewhere, but may occur 

at different rates given the specific meteorological conditions 

present in the Arctic. Yet, when compared with the current 

body of knowledge regarding oil weathering processes in 

open-water and temperate conditions, the body of knowledge 

regarding these processes in the context of Arctic oil spills is 

“very limited” (Brandvik and Faksness, 2009).

Laboratory testing provides a view into the nominal 

response of various oil types to weathering under different 

environmental conditions. Simulations of spills in various 

ice conditions have been done (for example, Prentki and 

others, 2004), but with limited field testing. The JIP on oil 

spill contingency for Arctic and ice-covered waters addresses 

some of these shortfalls by conducting a suite of studies from 

laboratory testing to full-scale field tests. Efforts, such as 

those by Brandvik and others (2010a) to conduct mesoscale 

weathering experiments in both the laboratory and at smallscale field scales, provide data to improve the capacity of oil 

weathering models to better predict oil weathering in cold 

and ice scenarios. Oil properties (for example, evaporation, 

emulsification, natural dispersion, flash point) have been 

experimentally assessed in the laboratory through time in 

different ice coverages (for example, 0, 30, 50, 70, 90 percent) 

and for different oils; these assessments directly inform spill 

response planning. Mesoscale field experiments conducted 

under the JIP, such as those conducted in Svalbard, Norway 

(Brandvik and others, 2010a) reduce the uncertainties of oil 

behavior characteristics that are critical to spill trajectory 

models and spill contingency plan strategies. For example, 

Brandvik and others (2010a) found that ice presence can slow 

weathering processes such as evaporation and emulsification, 

and can extend the operational window for the use of tools 

such as dispersants and in-situ burning. 

Oil emulsification is an important weathering process to 

understand because emulsification can inhibit the effectiveness 

of oil-spill countermeasures, and preserve some of the 

constituents in oil that would otherwise tend to degrade—

such as n-alkanes and some classes of polycyclic aromatic 

hydrocarbons (PAHs). This preservation also can prolong 

the potential for spilled oil to serve as a source of toxic 

contaminants, such as PAHs, to the environment. For example, 

Short and others (2007) noted that residual emulsified oil 

(“oil mousse”) contained abundant levels of these compounds 

in subsurface sediments of Prince William Sound shorelines 

some 16 years after the Exxon Valdez oil spill, indicating that 

the “...remaining subsurface oil may persist for decades with 

little change.” 

There has been extensive study of water-in-oil emulsions 

(Fingas, 2008b) under different conditions ranging in scale 

from laboratory bench top to field tests. Three categories of 

emulsions—stable, unstable, and meso-stable—with distinct 

Figure 5–2. Schematic from Daling and others (1997, 

fig. 2) showing how oil properties change over time and 

influence spill response tool effectiveness.
Chapter 5

Oil-Spill Risk, Response, and Impact 117

physical properties generally are recognized. For example, 

viscosity can vary by several orders of magnitude across 

these categories, and thus have ramifications for the fate and 

transport of emulsified oil in the marine environment. The 

composition of the source oil is a key factor affecting the 

potential of forming and the resulting stability of emulsions. 

The addition of energy, such as through wave action, is needed 

to initiate emulsification, but the threshold energy level 

needed to initiate this process is not well understood. Recent 

attempts to derive empirical models describing the formation 

of oil-in-water emulsions have been hindered by our limited 

understanding of the chemical behavior of oil constituents in 

the environment (Fingas, 2008b). 

Sea ice also can affect the formation of water-in-oil 

emulsions. Studies conducted on the fate of oil released in 

multi-year ice documented that ice morphology is a key 

parameter affecting oil weathering in the presence of ice 

(Payne and others, 1991). These researchers have observed 

that

 “[m]elting first-year ice produced substantial 

amounts of slush ice, and a stable water-in-oil 

emulsion of Prudhoe Bay crude oil containing up 

to 60 percent water was formed within 4 hours of 

the onset of wave agitation in this slush ice field. In 

contrast, rotting multi-year ice appeared to have a 

much lower tendency to produce a slush ice matrix 

during melting, and the formation of stable waterin-oil emulsions occurred over a relatively longer 

period of time.” 

A better understanding of these processes could help delineate 

the timeframe over which emulsions can form and the “time 

window” for effective operational response. Knowledge of the 

stability of emulsions over time underpins monitoring the fate 

and transport of spilled oil through trajectory modeling and the 

compilation of oil weathering budgets.

Full-scale field experiments provide invaluable groundtruthing and adaptive learning opportunities. Few such 

experiments have been conducted in the Arctic and none in 

U.S. waters. Sørstrøm (2009) and Brandvik and others (2010b) 

document the most recent large-scale effort conducted in the 

Barents Sea in spring 2009. Oil weathering experiments, oil 

distribution and bioavailability, and actual systems of spill 

contingency were assessed. Field data support findings from 

mesoscale laboratory efforts on the nature of physical and 

chemical change as oil weathers under ice conditions. 

Persistence of oil was significantly underestimated 

after the Exxon Valdez oil spill. Short and others (2007) 

found that during early stages of the spill, less viscous oil 

readily percolated into finer grained beaches and, as the 

spill progressed along the Gulf of Alaska, more exposed and 

bouldered beaches allowed the increasingly viscous oil to 

percolate into “protected” interstitial areas. It remains unclear 

what “refugia” sea ice and eroding shoreline characteristics 

in the Arctic may offer oil and what might be the influences 

on the spatial or temporal degradation of oil. Oil spilled 

under the ice may be incorporated into the ice sheet where 

comparatively little weathering/degradation may occur; 

however, during the spring melt, the encapsulated oil may be 

released and undergo evaporation and other processes. For 

this reason, the effect of sea ice on oil weathering is a critical 

consideration to oil spill contingency planning and response in 

the Arctic. A substantial body of work was conducted during 

the 1970s and 1980s to characterize the fundamental processes 

affecting how oil may become incorporated within ice, and 

subsequently affect oil weathering (Payne and others, 1991). 

This incorporation may occur fairly rapidly, in as little as 18 

to 72 hours, depending on the time of year (Dickins and Buist, 

1981). Recent studies of oil-in-ice interactions addressed a 

knowledge gap pertaining to how these interactions may affect 

the efficacy and (or) timing of the potential deployment of 

spill countermeasures. Brandvik and Faksness (2009) reported 

that: 

“[o]perationally important weathering processes 

for oil spill operations like water uptake, emulsion 

stability and viscosity vary with oil type. Normally 

they increase relatively fast with increased 

weathering time in open water. In ice-infested water, 

several studies have indicated that this increase with 

time (for example, water content) can be drastically 

changed depending on ice type, ice coverage and 

energy conditions in the ice. Little knowledge 

concerning this is available today, and only for a 

limited number of oil types and ice regimes... .” 

One example of the need to understand these processes in the 

context of oil-spill response operations is as follows: 

“after only a few hours of weathering on open 

waters, an oil spill may become too viscous for 

application of dispersants; yet that same spilled oil, 

if associated with dense ice, may be amenable to 

treatment with dispersants even after several days of 

weathering” (Brandvik and Faksness, 2009). 

As a result, the presence of sea ice may serve to inhibit 

natural weathering processes, and could thus serve to expand 

the operational “time window” for deployment of spill 

countermeasures. 

Seasonal variations in sea ice also merit consideration for 

oil-spill response. For example, if oil was spilled under ice in 

the spring (after May), the oil might not become encapsulated 

in the ice due to insufficient new ice growth before seasonal 

melting commenced (Buist and others, 2008a). Conversely, 

a spill occurring just prior to or during freeze-up (Lewis 

and others, 2008) may become rapidly incorporated in ice, 

such that response efforts could include a combination of oil 

recovery and ice tracking and monitoring operations. State-ofthe-art models, such as the SINTEF model, require detailed 
118 An Evaluation of the Science Needs to Inform Decisions on Outer Continental Shelf Energy Development in the Chukchi and Beaufort Seas, Alaska

physical and chemical information to characterize the oilice interaction; such level of detail typically is not available 

(Brandvik and others, 2006). Further, Brandvik and others 

(2006) reported that the state of modeling of oil weathering 

in the presence of sea ice remained constrained by the ability 

to model sea-ice physics at the appropriate scale. The need to 

further refine and verify these models of physical processes 

on oil fate and transport is identified as an information need 

for oil-spill response in the Arctic (U.S. Arctic Research 

Commission, 2010). 

One of the key processes of oil weathering is the extent 

and nature of interaction of oil with brine channels in ice. For 

example, in earlier studies, Payne and others (1991) noted that 

“[i]f oil is released into water under freezing 

conditions of active ice growth, lower molecular 

weight aromatic components can be advected 

with the sinking brine generated during frazil ice 

formation to the stable bottom boundary layer 

where, as conservative dissolved compounds, they 

can persist without evaporation for periods of up to 

several months.” 

To further investigate the fate of hydrocarbons from spilled 

oil in ice, Faksness and Brandvik (2008) conducted field 

experiments to evaluate the potential for dissolution of watersoluble components (WSCs) into and through first-year 

(annual) ice. The transport of WSCs from the oil through the 

ice was documented, and low but detectable concentrations of 

these components at the bottom of the ice core were measured. 

This transport mechanism may serve as a vector by which 

biota at the bottom of the ice sheet are exposed to these WSCs, 

with the potential for entrainment into the Arctic marine food 

web. The authors compared the field studies with laboratory 

experiments—using the Chemical Response to Oil Spills: 

Ecological Effect Research Forum procedure—and the similar 

distribution of WSCs in both sets of samples was interpreted 

to reflect that the brine channels in the ice sheet serve as a 

transport mechanism of WSCs from oil, through ice via the 

channels, and into the underlying water.

Natural biodegradation of oil in the marine environment 

is part of the process of oil weathering, and biostimulation 

and bioaugmentation have been considered as oil-spill 

countermeasures (Swannell and others, 1996). In general, 

however, oil biodegradation rates are difficult to predict, given 

the influence of oil type, variability of substrates, and other 

variable factors, such as temperature and nutrients (Zahed 

and others, 2010). In 1981, an experimental spill, known as 

the Baffin Island Oil Spill (BIOS) Project, was conducted 

on the northern tip of Baffin Island in Nunavut, Canada, as 

a means of studying natural biodegradation from an Arctic 

marine oil spill (Sergy and Blackall, 1987). Although much 

of the original oil has naturally degraded over time, follow-up 

studies have shown that some patches of the spilled oil 

remain essentially unaltered after decades of exposure (Prince 

and others, 2002). The interactions with sea ice may affect 

oil biodegradation processes, and can provide routes for 

components from spilled oil to enter the Arctic marine food 

web (Faksness and Brandvik, 2008). 

A good understanding of ambient microbial communities 

and processes is needed for the water column, sediments, 

and ice to understand the potential for microbial degradation 

of oil in the Arctic, and the potential impact of this on oil 

fate and ecosystem uptake. There have been recent activities 

to increase our knowledge in these areas (Interagency 

Coordinating Committee on Oil Pollution Research, 2009). 

Braddock and others (2004) noted that despite large-scale 

development on the Alaska North Slope, there was limited 

understanding of microbial communities in this setting, and 

much of this derived from studies that were decades old. 

Garneau and others (2009) reiterated this point, noting that 

the microbial characteristics of the coastal Arctic Ocean have 

been little explored, but that studies conducted to date on the 

Mackenzie Shelf in the Beaufort Sea provide information on 

the existence of diverse and active microbial communities, 

with variation among communities across salinity gradients. A 

survey of microbial populations from offshore of Barrow and 

5.04. Recommendation: There is a need to better understand 

oil-in-ice weathering, particularly as it relates to the effectiveness 

of spill response countermeasures and the potential for ecosystem 

exposure. Oil-water partitioning is recognized as needing further 

study, especially the potential toxicity of the partitioned phases, as 

oil trapped in ice may remain relatively fresh (that is, toxic). This 

process also points to the potential for a longer term spill response 

that follows the initial event for potentially several months given 

seasonal changes to the ice column (melting). 

5.04. Finding: The interaction of ice and oil has long been 

recognized as an important factor affecting oil fate and toxicity in 

the Arctic environment. Recent studies have focused on oil-water 

partitioning (water-soluble compounds, WSCs) associated with ice 

melt and brine channel flux in the ice column. 
Chapter 5

Oil-Spill Risk, Response, and Impact 119

Prudhoe Bay, Alaska, provides a more recent characterization 

of endemic populations and metabolic capability to 

degrade petroleum hydrocarbons (Braddock and others, 

2004). Braddock and others (2004) reported that the total 

microscopic counts of bacteria and culturable heterotrophs in 

the sediment samples were comparable with estimates from 

studies conducted in the 1970s and 1980s in the same areas. 

Kirchman and others (2010) investigated potential seasonal 

and spatial variations of bacterial community structures in the 

Arctic Ocean to help improve the fundamental understanding 

of relationships between bacteria and phytoplankton in 

the Arctic Ocean, which appear to differ from those found 

in lower latitude oceans. This information helps inform 

our understanding of primary production during the rapid 

transition from spring to summer when ice coverage decreases 

in the Arctic Ocean. In water column samples collected from 

various locations in the Chukchi and Beaufort Seas, there 

generally was no significant seasonal variation in communities 

despite strong seasonal gradients in biogeochemical properties 

(Kirchman and others, 2010). These findings may have 

ramifications regarding the ecophysiological flexibility of 

bacterial communities in the areas sampled (Kirchman and 

others, 2010). This is an area for further research as it could 

have implications for the adaptability of indigenous microbial 

communities to changes in carbon source, such as in the event 

of an oil spill.

Recent studies following the Deepwater Horizon oil 

spill have shown the importance of characterizing not only 

the indigenous microbial communities in benthic sediments, 

but also those in the water column. In particular, Hazen 

and others (2010) reported natural biodegradation of the 

dispersed oil plume in deep water. Because the microbial 

communities appeared to rapidly adapt—as reflected in 

hydrocarbon-degrading genes—in response to the oil plume, 

the researchers concluded that there was potential for intrinsic 

bioremediation of oil contaminants in the deep sea. As such, 

these communities may have an important role in the fate 

of hydrocarbons in the GOM (Hazen and others, 2010). 

Analogous studies of indigenous microbial populations in 

the Arctic are warranted to gain a better understanding of the 

potential for these processes to naturally attenuate an Arctic oil 

spill.

Oil-Spill-Trajectory Models 

The OSRA Model (Smith and others, 1982) as refined by 

Labelle and Anderson (1985), Ji and others (2004), and others 

simulates oil-spill transport and is dependent on realistic wind 

velocity and ocean surface current data, as well as accurate 

information of the ecological, economic, and (or) social 

resources located along coastlines that might be transected by 

oil. State-of-the-art trajectory models and quality input data for 

spill trajectory likelihoods are represented by analyses for the 

GOM. Johnson and others (2007) reaffirm the conclusions of 

Ji and others (2004) that oil-spill risk analyses are dependent 

on detailed information of ocean currents and wind fields. The 

ocean current inputs are computed from an ocean circulation 

model driven by analyzed meteorological forces through 

models such as the Princeton-Dynalysis Ocean Model, which 

have been extensively assessed with field observations in the 

GOM (Herring and others, 1999) including data from some 

340 drifting buoys (Ji and others, 2004). Similar rigorous data 

are not presently available for the Arctic OCS, but a strong 

scientific framework is emerging for 3-D coupled ice-ocean 

models and 2-D ice-associated oil spill models (for example, 

Wang and others 2003, 2010) that will improve as knowledge 

about oceanographic characteristics of the Beaufort and 

Chukchi Seas increases. Efforts to understand and address data 

insufficiencies are the focus of numerous ongoing studies by 

BOEMRE, the Alaska Ocean Observing System, and others. 

5.05. Recommendation: Recent studies underscore the 

need to better characterize Arctic-based indigenous microbial 

populations in the water column and benthic sediment, and define 

rates of microbial processes. This will ultimately allow for the 

full characterization of the role such communities have in the oil 

weathering process. 

5.05. Finding: Natural biodegradation of oil in the marine 

environment is part of the process of oil weathering. The presence 

of microbial communities gives rise to the potential for intrinsic 

bioremediation of oil spills. Indigenous microbial populations in 

the Arctic may play an important role in the fate of hydrocarbons 

following an oil spill. However, the effect of these populations on 

such oil weathering in the Arctic is not well understood. 
120 An Evaluation of the Science Needs to Inform Decisions on Outer Continental Shelf Energy Development in the Chukchi and Beaufort Seas, Alaska

Well documented analyses of data and technology 

needs for meteorological and physical oceanography can be 

found in Beaufort Sea assessments by Hoefler Consulting 

(2006, 2007) and Weingartner and others (2010a). Present 

Arctic assets are listed within the interactive Alaska Ocean 

Observing System’s Arctic Assets Application (fig. 5–3). 

Hoefler Consulting (2006) recommends the establishment of 

a redundant sensor system. The current lack of redundancy 

may result in a critical link remaining down for some time 

should it fail, due to weather and logistical limitations to 

access the site and the cost of site visits. Such a system also 

would serve as an enhanced Arctic coast-wide network to 

serve spill response goals and inform broader questions such 

as how climate change may affect system dynamics (fig. 5–4). 

Weingartner and others (2010a) outline a series of large-scale 

studies that would help define the critical oceanographic 

characteristics of the Beaufort Sea OCS to better inform 

pre- and post-spill modeling/response. These also would 

define environmentally sensitive marine areas by examining 

oceanographic exchanges, understanding shelf-basin exchange 

via wind and eddies, better defining characteristics of the 

coastal boundary and under-ice river plumes, and defining 

the sea-ice boundary through examination of thickness and 

under-ice topography. New analyses of mooring data by 

Weingartner and others (2009) provide a scientific foundation 

to understand likely movement of a spill in near-shore waters, 

such as oil spilled beneath landfast ice. Such work appears 

to be more mature for the Beaufort Sea dating back to efforts 

under the 1970s Outer Continental Shelf Environmental 

Assessment Program (OCSEAP, for example, Aagaard, 1981), 

but attention to Chukchi Sea conditions has increased (for 

example, Weingartner and others, 2005). Newly installed highfrequency land-based radar (fig. 5–5) holds promise to provide 

near-shore real-time current data of value for spill modeling, 

as well as for spill response (Potter and Weingartner, 2009; 

Weingartner and others, 2010b). The International Ocean 

Observing System (2009) presents partner perspectives on 

the present needs for this technology for all their regional 

networks. Should development in the Arctic OCS continue, 

it is likely that an increased number of such sites should be 

considered. Regardless of the development future, while the 

number of Arctic sites presently is not dramatically different 

from those in the GOM, the Arctic has fewer oceanographic 

assets (for example, buoys) in general and would benefit from 

increased access to this new technology. Analyses critical 

to such large-scale integrated efforts to better understand 

oceanographic circulation factors in Arctic oil-spill risk 

analyses are ongoing through BOEMRE (fig. 5–6).

Figure 5–3. Examples of recent oceanographic cruises and sensor assets in the Beaufort and Chukchi Seas taken from 

the interactive Alaska Ocean Observing System’s Arctic Assets Application. (Screen grab: http://data.aoos.org/maps/arctic_

assets.php, last accessed February 1, 2011.)
Chapter 5

Oil-Spill Risk, Response, and Impact 121

Figure 5–4. Examples of meteorological sites for the Beaufort Sea and spatial distribution wind roses generated by such 

stations, and other meteorological data useful for spill planning and response (from Hoefler Consulting, 2007, figs. 3–2, 4–21). 

(MMS, Minerals Management Service.)
122 An Evaluation of the Science Needs to Inform Decisions on Outer Continental Shelf Energy Development in the Chukchi and Beaufort Seas, Alaska

5.06. Finding: The modeling framework used by the BOEMRE throughout its OCS program is well developed and has 

undergone rigorous analysis. However, physical oceanography and meteorology of the Arctic OCS are highly dynamic and 

not well understood because of the challenge of instrumenting a remote ice-influenced system such as the Arctic OCS. 

This is particularly true for the Chukchi Sea. Thus, the physical understanding of the Arctic OCS needed to inform models is 

not comparable with that of the GOM. This also is true for circulation or weather modeling that informs oil-spill-trajectory 

models. Outputs from such trajectory models influence ecological affect analyses, which are limited by the accuracy and 

precision of the physical data that inform them. 

Figure 5–5. Existing High Frequency Radar (HFR) sites (black dots) and proposed sites (blue dots) 

modified from International Ocean Observing System (2009). The map of Alaska’s North Slope and

the Gulf of Mexico are to scale to demonstrate existing and proposed coverages (indicated by 

green areas) for these two major OCS regions.
Chapter 5

Oil-Spill Risk, Response, and Impact 123

5.06. Recommendation: Existing recommendations for the Beaufort Sea from Weingartner and others (2010a) and 

Hoefler Consulting (2006, 2007), if implemented, could significantly improve the weather and oceanographic data required by 

trajectory models. These recommendations include establishment of a redundant meteorological sensor system to enhance 

Arctic coast-wide spill response goals and a series of large-scale studies of oceanographic exchanges, shelf-basin exchanges 

via wind and eddies, coastal boundary, under-ice river plumes, and sea-ice boundary to better inform pre- and post-spill 

modeling and response. We did not find similar synthesized recommendations for the Chukchi Sea. If they do not exist, then 

producing such analyses would be quite valuable to improve model confidence. Physical oceanographic and meteorological 

data help inform a wide variety of issues in the Arctic. The international Arctic resource community might benefit from a 

broader discussion on core data needs and the efficient development of multi-purpose, multi-agency monitoring networks to 

inform energy development needs as well as climate forecasting, aviation, and shipping safety. The visualization and serving 

of data through a fully operational Arctic node similar to that of the Alaska Ocean Observing System would help ensure 

efficient access to information and improved asset planning that is critical in the Arctic where scientific instrumentation costs 

are high. 

Figure 5–6. Schematic illustrating the progression of science developed under the BOEMRE OCS 

Environmental Studies Program to better inform an understanding of ocean circulation critical to topics such 

as oil-spill-trajectory models [Bureau of Ocean Energy Management, Regulation and Enforcement (BOEMRE), 

written commun., 2011].

tac11-5179_fig4-04

PROGRESSION IN UNDERSTANDING

OCEANOGRAPHY CIRCULATION MODELING

2011 Agency Workshop: Hindcast vs. Forecast in a changing Arctic

2006+ OCS Arctic Mesoscale Meteorological Model

2003 Agency Workshop on Small-Scale Sea-Ice and Ocean Modelling

1996 Agency incorporates historical NWS wind fields into hindcast coupled model

2000 Assimilation of satellite data into model validation and testing into coupled model

1999 Agency use of multi-year hindcast simulations of coupled model

1995+ Start of Coupled Model Intercomparison Project

1990+ Start of Atmospheric Model Intercomparison Project

1987 Agency develops coupled ice/ocean/atmospheric models for Arctic OCS

1984 Agency develops winter stochastic Beaufort ice model

1982 3-dimensional Ice-Ocean Model with stochastic winds

1979 2-dimensional open water circulation model for inshore Beaufort Sea using observed shoreline winds

SYSTEMATIC TACKLING OF CRITICAL QUESTIONS

2007 Wind, Ocean, Ice Circulation Fields from Multiple Production Models | New Sea Ice Dynamic Models

2001+ Arctic Ocean Model Intercomparison Project (international effort to improve Arctic Models)
124 An Evaluation of the Science Needs to Inform Decisions on Outer Continental Shelf Energy Development in the Chukchi and Beaufort Seas, Alaska

Ecological and Social Resource Intersection 

Analyses

 Ultimately, oil-spill-trajectory models and their 

supporting oceanographic inputs are used to inform analyses 

of potential effects of spills on areas of environmental, 

social, and (or) economic interest. The processes described 

in the section “Oil-Spill-Trajectory Models” define where 

oil might transect an area (for example, shoreline, reef, 

migration route) in a very quantitative analytical approach 

that can be tested for sensitivity and become a foundation 

for documented improvement when new data or insights are 

developed (for example, Wang and others, 2010). The value 

of the area (for example, for subsistence, cultural needs, 

community infrastructure, or wildlife habitat) is based on 

best available information. Analysts designate segments 

important to various resources, and the time periods that 

those resources occupy that spatial location. This process 

is often done collaboratively through “expert” discussions 

and reviews of available literature and is well presented, 

for example, in the Draft Environmental Impact Statement 

for the Beaufort and Chukchi Seas multiple lease sales 209, 

212, 217, 221 (Minerals Management Service, 2008a). 

An example of an Environmental Resource Area (ERA) 

designation and supporting scientific literature (fig. 5–7, 

table 5–2) helps illustrate the scientific foundation behind 

the resource designations. There is a significant range in 

the data that support ERAs from quite limited or dated [for 

example the Outer Kotzebue Sound (ERA 57)] to those 

with some 10 supporting sources covering some 40 years 

(for example the Chukchi Spring Lead System, ERA 19, 

table 5–2). The USGS OCS Team believes that the literature 

presented represents a current picture of available scientific 

information. However, unlike the earlier components of the 

Risk Assessment Process, the ecological considerations in the 

assessment are qualitative in nature with no measures of data 

quality or data uncertainty. It is difficult to judge the value of 

existing information in the decision-making process, or where 

and what new ecological data would result in substantially 

improved decision making. In other words, one cannot run a 

sensitivity analysis under the present process to examine how 

important the limitations of the literature or variation in expert 

opinion might be to the decision-making process. 

The challenge to quantitatively include ecological 

resources is not unique to the Arctic OCS process, but exists 

throughout the discipline of environmental assessment. 

Emerging information products and tools, such as those 

developed by the Alaska Ocean Observing System and 

Smith’s (2010) Arctic Marine Synthesis: Atlas of the Chukchi 

and Beaufort Seas, represent emergent approaches about data 

quality and sufficiency that can be built upon. These products 

and tools represent great advances for the Arctic, where much 

remains unknown; many different entities conduct work; 

the landscapes are remote and enormous; and each piece of 

information is expensive to collect. Even with such tools, 

insights into what ecological resources might be at risk and 

the data gaps that are most critical to fill will rely on a mix of 

expert knowledge and existing data for some time. Structured 

Decision Making and its supporting tools, from the simplest 

influence diagrams to the more complex mixed analytical 

and expert Bayesian Network models, provide discipline to 

technical or value-based deliberations (for example, Varis 

1997; Faber and others, 2002) and can provide inputs to and 

complement existing regulatory processes. These tools are 

particularly helpful when there is disagreement about whether 

a decision needs more information and what information 

might improve that decision. 

5.07. Recommendation: The application of the maturing 

science of Structured Decision Making and supporting tools (from 

the simplest influence diagrams to the more complex mixed 

analytical and expert Bayesian Network models) could provide 

a transparent and quantitative discipline to technical or valuebased deliberations. Such collaborative processes could help 

better define what uncertainty is unacceptable to vested parties 

and what new information could address that uncertainty in a 

structured and testable manner. 

5.07. Finding: Oil-spill risk assessment processes have a strong, 

transparent, and quantitative model framework through the spilltrajectory model phase. The social and (or) ecological value of an 

area and the potential impact should oil transect it is based on 

“expert” discussions and review of available literature. They are 

more qualitative in nature, with limited measures of data quality 

or data uncertainty expressed.
Chapter 5

Oil-Spill Risk, Response, and Impact 125 tac11-5179_fig4-05

68°0'N 66°0'N

68°0'N

70°0'N

70°0'N

72°0'N

74°0'N 72°0'N

Figure 5–7. Example of Environmental Resource Areas (ERAs) used in the oil-spill-trajectory model (Minerals Management Service, 2008a, appendix A). 
126 An Evaluation of the Science Needs to Inform Decisions on Outer Continental Shelf Energy Development in the Chukchi and Beaufort Seas, Alaska Table 5–2. Example of resource definition and supporting literature for Environmental Resource Areas (ERA) presented in figure 5–7. [Modified from Mineral Management Services, 2008a. ERA IDs found in figure 5–7. References are found in Minerals Management Service, 2008a] ERA ID Vulnerable General resource Specific resource Reference

2 May–October Birds, barrier island Spectacled eiders, Long tailed ducks Lehnhausen and Quinlan, 1981; Johnson, 1993; Johnson, Wiggins, and Wainwright, 1993; Laing 

and Platte, 1994; Dau and Larned, 2004

3 September–October Subsistence Bowhead whales, Grey whales, walrus Mel’nikov and Bobkov, 1993.

4 January–December Subsistence Bowhead whales, Grey whales, walrus Mel’nikov and Bobkov, 1993.5 April–September Subsistence Polar Bears, walrus, weals Sobelman, 1985; Wisniewski, 2005.7 January–December Lower tropic International Russian waters U.S. Dept. of State, 1990.

11 July–November Marine mammals Polar bears, walrus Kochnev, 2002; Kochnev and others, 2003; Kochnev, In prep.; Fay, 1982.

13 January–December Whales Beluga whales Suydam and others, 2001; Suydam, Lowry and Frost, 2005.13 January–December Subsistence Polar bears, walrus, weals, Bowhead 

whales, Beluga whales

Burch, 1985.

16 June–September Whales Bowhead whales, Gray whales Mel’nikov and Bobkov, 1993; Bogoslovskaya,Votrogov and Krupnik, 1982.

18 May–October Birds Murre foraging, rearing, and molting area Springer and others, 1984; Piatt and Springer, 200319 April–June Birds, marine

mammals

Seabird foraging; spring migration area 

for Long tailed ducks, eiders, loons

Swartz, 1967; Connors, Myers, and Pitelka,1979; Sowls and others, 1978; Gill, Handel and 

Connors, 1985; Johnson and Herter, 1989; Piatt and others, 1991; Piatt and Springer, 2003; Oppel, 2007.

23 July–November Marine mammals Walrus Fay, 1982; Jay, 2007. pers. commun.38 January–December Subsistence Beluga whales, Bowhead whales, walrus, 

seals

Braund and Burnham, 1984.

39 January–December Subsistence Fish, seals, waterfowl, Beluga whales Braund and Burnham, 1984; Impact Assessment, 1989; Huntington and Mymrin, 1996; USDOI, 

BLM and MMS, 2003.

40 January–December Subsistence Bowhead whales, Beluga whales Braund and Burnham, 1984; Braund & Associates, 1993a, Kassam and Wainwright Traditional 

Council, 2001; USDOI, BLM, and MMS, 2003.

41 April–May Subsistence Bowhead whales, Beluga whales, walrus,

Waterfowl, seals, ocean fish

Braund and Burnham, 1984; S.R. Braund & Associates, 1993b; North Slope Borough, 2001; 

USDOI, BLM and MMS, 2003.

42 August–October Subsistence Bowhead whales, Beluga whales, walrus,

waterfowl, seals, ocean rish

Braund and Burnham, 1984; Braund and Associates, 1993b; North Slope Borough, 2001; USDOI, 

BLM, and MMS, 2003.

48 May–October Whales Bowhead whales,gray whales, walrus Moore and DeMaster, 1997.

50 May–October Marine mammals Walrus Fay, 1982; Jay, 2007. pers. commun.51 May–October Marine mammals Walrus Fay, 1982; Jay, 2007. pers. commun.52 May–October Marine mammals Walrus Fay, 1982; Jay, 2007. pers. commun.57 May–June Marine mammals Walrus Fay, 1982; Jay, 2007. pers. commun.58 May–October Marine mammals Walrus Fay, 1982; Jay, 2007. pers. commun.

59 July–November Marine mammals Polar bears, walrus Kochnev and others, 2003; Kochnev, In prep.; Fay, 1982.61 April–December Whales Bowhead, fin, and humpback whales Melnikov, 2000; Melnikov and Bobkov, 1993; Melnikov, and others 2004; USDOC, NMFS, 2006; 

Rice, 1974, Bogoslovskaya, Votrogov and Krupnik, 1982; Marqueette and others 1982; Mizroch, In Prep.; Mizroch, Rice and Breiwick,1984; Angliss and Outlaw 2005; 2007.

66 July–November Marine mammals Polar bears, walrus Ovsyanikov,1998; Stishov, 1991, Fay, 1982; Jay, 2007 pers. com.

74 August–October Whales, Polar Bears, 

Walrus

Bowhead whales Bogoslovskaya and others 1982.

82 September Whales Bowhead whales Mel’nikov and Bobkov, 1993; Bogoslovskaya,Votrogov and Krupnik, 1982.

83 August–October Whales Bowhead whales Bogoslovskaya, Votrogov and Krupnik, 198291 August–October Whales Bowhead whales Bogoslovskaya, Votrogov and Krupnik, 1982
Chapter 5

Oil-Spill Risk, Response, and Impact 127

Science and Oil-Spill Contingency Planning

Contingency plans, as defined under the National Oil 

and Hazardous Substances Pollution Contingency Plan (NCP) 

(http://www.epa.gov/oem/content/lawsregs/ncpover.htm), 

require information, much of which is not within the purview 

of science (for example, response resources, command and 

control structures, communications, and relationship to other 

plans). Here, we discuss points where scientific insights and 

data help inform the planning process. For example, the 2008 

International Oil Spill Conference (2008) outlined factors that 

may be desired in plans (table 5–3). The areas of potential 

spill coverage must be defined based on scenarios identified 

in a risk analysis. Presently, for the Arctic such scenarios are 

limited (Alaska Regional Response Team, 2010). Whether 

part of the formal NCP process or not, assessment of risk 

and development of plans include spill scenarios, surface 

trajectories, subsurface trajectories, stochastic modeling, 

real-time forecasting, oil characterization, oil fate and effects 

modeling, and oil weathering. Much of the foundational 

science for these elements is similar to that required in oil-spill 

risk assessments detailed previously and will not be described 

again. 

During our expert consultations, participants raised a 

number of issues relevant to this topic. Potential spill volume 

is an early input to and an overriding influence on the spill 

scenario and requires an understanding of the source reservoir 

volume and pressure. Several entities we met with felt there 

was insufficient information to reasonably constrain estimates 

of likely spill volume. In particular, Coast Guard leaders 

responsible for spill response in the Arctic felt this was an 

essential input to the series of downstream decisions that they 

must make within spill contingency plans. 

Table 5–3. Spill Response Planning and Assessment Categories as suggested in the 2008 International Oil Spill 

Conference proposed guide on response planning and readiness assessments.

[Modified from International Oil Spill Conference, 2008, table 1] 

Setting the Stage Operational Response

 1. Legislation and regulation 16. Source control, salvage, and firefighting

 2. Multi-national agreements 17. Response technologies

Developing a Plan 18. Waste management

 3. Resources at risk 19. Wildlife recovery

 4. Spill risk analysis Response Support

 5. Risk minimization 20. Spill monitoring, tracking, and sampling

 6. Evaluation of response technologies 21. Cleanup assessment

 7. Net environmental benefit analysis 22. Data management and success

 8. Expert information sources 23. Logistics

 9. Contingency planning 24. Finance, administration, and procurement

Organization and Communications 25. Demobilization

10. Response management systems Developing and Sustaining Response Capability and Readiness

11. Notification systems 26. Exercises

12. Communications 27. Training

13. Safety for responders and public 28. Sustainability and improvement

14. Security

15. Public information development and distribution
128 An Evaluation of the Science Needs to Inform Decisions on Outer Continental Shelf Energy Development in the Chukchi and Beaufort Seas, Alaska

In our consultations, various parties expressed the need 

to develop and test approaches to address “Organization and 

Communication” capacities for spill response. For example, 

the National Oceanic and Atmospheric Administration 

(NOAA) and key partners are actively expanding the 

successful Emergency Response Management Application 

(ERMA®) system, most recently used during the Deepwater 

Horizon oil spill in the GOM, to Arctic planning and response. 

This geospatial decision-support tool combines product 

output from NOAA sources as well as datasets agreed upon 

by stakeholders (Coastal Response Research Center, 2011) to 

provide onsite coordinators critical background and real-time 

data. 

5.08. Recommendation: A national investment in 

foundational geologic and geophysical data can provide an 

improved understanding of how oil and gas resources are formed 

and emplaced in reservoirs in the Arctic. However, substantial 

improvements in estimates will require data from exploration wells 

that are made publicly available. 

5.08. Finding: Because of the frontier nature of oil and gas 

exploration in the U.S. Arctic, few empirical data are available 

to constrain the estimates of oil reservoir volume and pressure 

patterns throughout the Arctic OCS, which results in uncertainty 

within spill risk assessments and oil-spill contingency planning. 

We are not aware of any large-scale field testing of the 

types of assets and communications that must come together 

rapidly and successfully for a spill event in the Beaufort 

or Chukchi Seas. However, the 2009 “Sound Predictions” 

effort by the Alaska Ocean Observing System (AOOS; 2009) 

and others in Prince William Sound (Gulf of Alaska) is an 

example of operational testing that can better improve the 

science/data component of oil-spill response. Through such 

field experimentation, the accuracy of ocean current and 

weather model forecasts, data access, and the utility of an 

ocean observing system for oil-spill response can be assessed 

and improved. Underpinning any of these efforts is the need 

to have data easily accessible and current. The Alaska Data 

Integration Working Group (2011) is a broad effort to facilitate 

improved data transparency and access across organizations 

that will feed well into the needs of Arctic ERMA® and 

AOOS.

5.09. Recommendation: Significant improvements in spill 

preparedness could be accomplished through the completion of 

decision support and data systems, such as the Arctic Emergency 

Response Management Application, the Alaska Ocean Observing 

System, and the State-Federal Alaska Data Integration Working 

Group. Field testing of assets and data systems as was done in 

the 2009 “Sound Predictions” experiment in Prince William Sound, 

Alaska, could significantly improve preparedness by highlighting 

significant data and operational needs.

5.09. Finding: Management, spill response, and science 

communities are actively engaged in developing essential decision 

support and ocean observing systems. However, these systems are 

not yet fully funded, operational, or fully tested for Arctic waters. 
Chapter 5

Oil-Spill Risk, Response, and Impact 129

Oil-Spill Response

All spill response requires effective planning, 

tracking, surveillance, and understanding of environmental 

considerations. For the Arctic, the unique challenge is to 

understand how oil will move if spilled; how it will respond to 

environmental conditions; what natural and cultural resources 

and historical properties are at risk; and how effective 

response tools will be in cold and ice-covered conditions. 

Many of the topics we have discussed in our oil-spill risk 

assessment sections inform actions during oil-spill response. 

The need for a multi-faceted science and technology effort as 

the foundation to an efficient and effective oil-spill response 

capacity is widely understood particularly because of unique 

Arctic challenges and is evident in the focus on this topic 

applied under the BOEMRE OCS research program (fig. 5–8).

Multiple Research Programs*

Accidental Oil Spills In Ice

Experimental Oil Spills Under Ice

OIL IN ICE

1990-Present MMS Technology Assessment and Research Program Arctic Oil Spill Response

1985-Present SINTEF Oil spill/ice

1982-1984 State of Alaska/Oil Industry Tier II Studies

1980-1984 Canadian Offshore Oil Spill Research Association

1977-Present Arctic and Marine Oilspill Program

1976-1987 Dome Petroleum Research Program

1975-Present Alaska Outer Continental Shelf Environmental Assessment Program (OCSEAP) | NOAA | BLM | MMS | BOEMRE

1973-1977 Canada Beaufort Sea Project

1970-1979 Arctic Petroleum and East Coast Operators Associations

1974-2006 Bouchard #65 | Snake River | Potomac | Kurdistan | Cepheus | Antonio Gramsci | Chesapeake Trader | Saraband | Seabulk Pride

1970 North Slope | Chukchi

1980 Beaufort Sea

1990 Eastern Canada | Beaufort Sea | European Arctic

2000 European Arctic

2010 European Arctic

* Each listed program is searchable on the Internet.

PROGRESSION IN UNDERSTANDING

SYSTEMATIC TACKLING OF CRITICAL QUESTIONS

Figure 5–8. Schematic illustrating progression of science developed under the BOEMRE OCS Environmental Studies Program 

to better understand the behavior of oil in ice [Bureau of Ocean Energy Management, Regulation and Enforcement (BOEMRE), 

written commun., 2011]. BLM, Bureau of Land Management; MMS, Minerals Management Service (now BOEMRE); NOAA, 

National Oceanic and Atmospheric Administration; OCSEAP, Outer Continental Shelf Environmental Assessment Program. 
130 An Evaluation of the Science Needs to Inform Decisions on Outer Continental Shelf Energy Development in the Chukchi and Beaufort Seas, Alaska

Response Gap

In later sections, we focus on the various spill response 

methods and technologies as they relate to Arctic and 

ice-covered waters. Those included are containment and 

mechanical recovery, burning, bioremediation, and enhanced 

dispersion. The materials we discuss in those sections 

highlight the scientific issues, progress, and information 

gaps that have been expressed for each of the various tools. 

However, here we discuss the broader issue of oil-spill 

countermeasures and the topic of “response gap.” Lessons 

learned from the 1989 Exxon Valdez oil spill in the sub-Arctic 

waters of Prince William Sound Alaska (see appendix D) 

and the most recent 2010 Deepwater Horizon oil spill in the 

GOM (National Commission on the BP Deepwater Horizon 

Oil Spill and Offshore Drilling, 2011) reiterate that there is 

no single response technique suitable for all circumstances. 

The National Research Council (NRC; 2003) stated that 

reliance on only one recovery system is “unlikely to be 

successful” to respond to an oil spill offshore of the Alaska 

North Slope. Most recently, Lee (2010) emphasized the need 

for the availability of multiple tools, and the challenges in the 

Arctic of ice dynamics, cold temperatures, and limited light 

in the winter. Many individual tools will not be available to 

responders at specific times because of wind, sea, ice, or light 

conditions (table 5–4; also see Nuka Research and Planning 

Group, LCC, 2007b; Nuka Research and Planning Group, 

LCC and Pearson Consulting, LCC, 2010). Understanding 

what combination of countermeasures will likely be available 

under the temporal and spatial variability of the Arctic is 

essential to assess environmental risks from any potential 

spilled oil. Beyond that, as discussed previously in Chapter 4, 

Climate Change Considerations, environmental conditions 

in the Arctic that affect countermeasure effectiveness are 

changing. And they are changing in complex ways not yet 

understood.

Mechanical Containment and Recovery

A number of recent advances have been made in 

mechanical containment and recovery devices as oil-spill 

mitigation countermeasures (Brandvik and others, 2006; 

Minerals Management Service, 2008b). However, the 

effectiveness of mechanical countermeasures, particularly 

in ice-infested waters, poses an ongoing challenge (World 

Wildlife Fund, 2009). In a recent review of technologies to 

improve oil-spill response effectiveness in the Arctic, Nuka 

Research and Planning Group, LCC (2007a) documented 

a number of promising mechanical recovery technologies 

that could be utilized in open water, but some of these 

lacked sufficient field testing in ice conditions to evaluate 

their effectiveness. Mechanical containment and recovery 

countermeasures, such as booming, sorbents, and skimmers, 

are affected by the presence of sea ice. Their recovery rate 

of spilled oil diminishes rapidly with increasing amounts of 

sea ice. For example, ice can induce tears in booming, or can 

clog skimmer systems and prevent them from encountering 

spilled oil. One additional challenge with mechanical recovery 

systems is the need for a platform from which to operate or 

deploy, requiring the availability of ice-class vessels, tugs, or 

barges to support response activities (World Wildlife Fund, 

2009). With sea ice coverage greater than about 60 percent, the 

ice itself can potentially serve as a natural containment barrier 

(Dickins and Buist, 1999). There also is a need for mechanical 

recovery systems capable of removing oil that is under the ice 

(Brandvik and others, 2006).

There are a number of types of booms available 

depending on whether the purpose of the booming is to 

contain the spill for recovery purposes (containment or 

diversion booming) or to protect sensitive areas from the 

spilled oil (exclusion or deflection booming) (DeCola and 

others, 2006). Recent advances in technology have been made 

to extend the capability of ice booms, adapting technology that 

had been in use for several decades to protect water intakes 

upstream of hydroelectric power plants into a countermeasure 

for oil-spill response. Ice booms also have the capability 

to assist other mechanical recovery systems by providing 

an ice-free environment, and in separating oil from ice 

5.10. Recommendation: Spill planning and response would 

benefit from a collaboratively derived Response Gap analysis 

of countermeasures, a rigorous analysis of the likelihood of the 

availability of a multi-countermeasure suite in different Arctic 

locations and seasons, and the forecasting of climate change 

influences on the Response Gap. While industry is responsible for 

stockpiling response equipment, continuation of the Federal and 

Joint Industry Program approach could inform efforts to develop 

suites of new technologies and approaches to improve effective 

response in the Arctic. An independent analysis of the Response 

Gap could help better articulate what overall risks exist from 

potential failures in spill response. 

5.10. Finding: While efforts are ongoing to develop 

countermeasures to address the potential of an oil spill in Arctic 

and ice-covered waters, it remains unclear when and where 

any one of these countermeasures, or countermeasures in 

combination, will be available under current and future weather, 

sea state, ice, and light conditions of the Arctic—or whether they 

will work even if available. 
Chapter 5

Oil-Spill Risk, Response, and Impact 131

Table 5–4. One example of physical and timing limitations on oil-spill response tools for the U.S. Arctic. 

[From Nuka Research and Planning Group, LCC and Pearson Consulting, LCC (2010, tables 6–1, 6–2). Color code: Green, conditions generally considered 

to be favorable; yellow, conditions may impede response operations; red, response would not be possible. Visibility: Moderate, light fog or less than 1 mile 

visibility; Low, heavy fog, less than one-quarter mile visibility, or darkness. n/a, not applicable; mph, miles per hour; ft, feet]

Limiting

factor Ice coverage Wind Wave height Visibility

Conditions <10%

11%

to

30%

31%

to

70%

>70% Solid

ice

0–20

mph

21–35

mph

>35

mph <3 ft 3–6 ft >6 ft High Moderate Low

Mechanical

recovery with no 

ice management

Mechanical 

recovery with ice 

management

n/a

In-situ burning

Environmental factors and response gaps

(Estimated percentage of time when operating limits are impaired or exceeded in U.S. Arctic)

Winter

(January–March)

Spring

(April–June)

Summer

(July–September)

Fall

(October–December)

Ice Condition: solid (100%)

Approximate daylight hours: 4.5

Average number days peak gust

>30: 20 (22%)

Average number of days of fog: 

51 (57%)

Average external minimum

temperature: -49°F

Ice condition: solid (80%),

Broken Ice (20%)

Approximate daylight hours: 19

Average number of days peak

gust >30: 12 (1%)

Average number of days of fog:

53 (58%)

Average external minimum

temperature: -9°F

Ice condition: broken ice (60%)

Open Water (40%)

Approximate daylight hours: 21

Average number of days peak

gust >30: 19 (21%)

Average number of days of fog:

44 (49%)

Average external minimum

temperature: 20°F

Ice condition: open water (20%), 

Broken ice (60%), solid (20%)

Approximate daylight hours: 5.5

Average number of days peak

gust >30: 30 (34%)

Average number of days of fog:

51 (57%)

Average external minimum

temperature: -32°F

(Abdelnour and Comfort, 2001; Abdelnour and others, 2001). 

Fire-resistant booms also have been developed for in-situ

burning, as a means of containing and concentrating the oil 

into a layer atop the water surface that is sufficiently thick to 

sustain ignition and burning (Tebeau, 2003; Potter and Buist, 

2008). There are a couple notable partnerships that culminated 

in the development of mechanical oil recovery systems for 

deployment in ice-infested waters—the Mechanical Oil 

Recovery in Ice-Infested Waters (MORICE) project (Jensen 

and Mullin, 2003) and the Lamor Oil Ice Separator (LOIS) 

(Minerals Management Service, 2008b). The concept for 

MORICE emerged from a review of the status of mechanical 

recovery devices and culminated in the development of a fullscale system that was tested at the National Oil Spill Response 

Research and Renewable Energy Test Facility in 2002, 

under a variety of ice conditions and under relatively mild 

weather conditions (Jensen and Mullin, 2003). The LOIS is a 

commercially available mechanical recovery system consisting 

of an oscillating ice grid that washes oil from ice chunks as 

they move along a grid; the oil is subsequently concentrated 

for recovery by a skimmer (Minerals Management Service, 

2008b).
132 An Evaluation of the Science Needs to Inform Decisions on Outer Continental Shelf Energy Development in the Chukchi and Beaufort Seas, Alaska

5.11. Recommendation: An evaluation of the presence or 

lack of standardized testing approaches (especially wave tanks), 

the cross-comparability of results, and collaborative development 

of protocols would be beneficial. This information would inform 

the practical recovery limits that can be achieved during response 

operations, and refine our understanding of the appropriate 

setting and scale at which these devices could be effectively 

deployed. Finally, there remains a need to further develop 

mechanical recovery systems to recover oil accumulated under 

ice.

5.11. Finding: There are a number of recent technological 

advances in mechanical containment and recovery devices as oilspill mitigation countermeasures. The effectiveness of mechanical 

countermeasures, particularly in ice-infested waters, poses 

an ongoing challenge. Scaling up test results from laboratoryand mesoscale testing into practical field recovery rates is a 

recognized information need. Further, an understanding of the 

types and (or) amounts of platforms needed to deploy these 

devices is needed. This lack of information currently is a limiting 

factor in translating the technological advances from these 

devices into an operational context, particularly at the scale at 

which these devices might be deployed in response to a large spill 

event in the presence of sea ice.

Skimming systems are designed to recover oil from the 

water surface. Recent overviews of the state-of-the-art of 

these technologies are given in Brandvik and others (2006), 

Nuka Research and Planning Group, LLC (2007a), Hänninen 

and Sassi (2010), S.L. Ross Environmental Research, Ltd., 

and others (2010), and Fingas (2011a). There have been 

recent efforts to develop standardized testing protocols 

for determining the recovery capacity of skimmer systems 

(Schmidt and others, 2009). Oleophilic skimmers are the most 

common type of mechanical oil-spill response equipment 

(Broje and Keller, 2006). Efforts to develop better skimmer 

systems for cold and ice conditions (Broje and Keller, 2006; 

Keller and Clark, 2008) have found they still have limited oil 

encounter and recovery rates. Thus, S.L. Ross Environmental 

Research, Ltd., and others (2010) recommended that 

deployment of skimmers in the Beaufort Sea may be best 

suited for responding to oil spills covering a small area and 

with relatively small ice pieces, given the current limitations 

of the oil encounter and recovery rates. 

The National Research Council review (2003) cited 

results from a Robertson and DeCola (2001) study involving a 

field trial using a barge-based recovery system in a simulated 

spill response on the North Slope under varying seasonal 

ice conditions. The authors found that realistic maximum 

operation limits for mechanical recovery of a simulated spill 

ranged from about 0 to 1 percent in fall ice conditions; about 

10 percent in spring ice conditions without ice management; 

and about 30 percent in spring ice conditions with extensive 

ice management. The National Research Council (2003) 

noted that given these estimates, reliance only on mechanical 

recovery systems to respond to an oil spill offshore of the 

Alaska North Slope is “unlikely to be successful.” They called 

into question the viability of mechanical recovery technologies 

to clean up spills, particularly large oil spills, in broken ice, 

citing statements by the Alaska Department of Environmental 

Conservation that the mechanical recovery technologies 

available then were not likely to be successful in the Beaufort 

and Chukchi Seas. The NRC also noted that the results of 

research on the effectiveness and environmental liabilities and 

advantages of alternative countermeasures, such as dispersants 

and in-situ burning, especially in broken-ice conditions, would 

be useful in facilitating needed contingency planning. The 

potential scale of the response needed to an offshore oil spill 

in ice-infested waters is a major challenge to the mechanical 

recovery systems, as many of these technologies appear best 

suited for batch recovery of spilled oil in pits or ice leads 

(Nuka Research and Planning Group, LLC, 2007a). In a recent 

review commissioned by the Canadian Environmental Studies 

Research Funds, S.L. Ross Environmental Research, Ltd., and 

others (2010) noted that 

“[t]here has been little research done with regard to 

the problem of removing oil from larger ice floes 

with diameters ranging from 10s to 1,000s of meters 

that typify breakup and pack ice conditions during 

winter in the Beaufort Sea.” 
Chapter 5

Oil-Spill Risk, Response, and Impact 133

In a recent review of countermeasure technologies 

for spill response in Beaufort Sea spring breakup or fallfreeze-up seasons, Solsberg (2008) reported that there 

have been advances made in mechanical recovery systems. 

However, many of these may face severe limitations during 

deployment due to ice-processing challenges, extreme 

weather (freezing) conditions, and changing conditions in the 

ice itself. Nuka Research and Planning Group, LLC (2007b) 

points out that the range of ice conditions that may be 

encountered in the Beaufort Sea is an important factor when 

determining what types of technologies are “appropriate and 

reliable” for oil-spill response and recovery. For example, 

“[a]vailable estimates from mechanical response 

in broken ice vary from 1 to 20 percent depending 

on the degree of ice coverage and if responding 

during freeze-up or spring break-up. This compares 

with estimates of 5 to 30 percent for open ocean 

response without broken ice. Recent barge trials 

on the Beaufort Sea demonstrated that even trace 

amounts of ice (less than 1/10 ice coverage) 

can cause significantly reduced efficiencies in 

mechanical recovery” (Minerals Management 

Service, 2008b).

One of the challenges to oil recovery in ice-infested 

waters is the availability of ice coverage information on the 

time scales (shorter) and conditions (dynamic) of a spill 

response operation. Solsberg (2008) noted that 

“[a] common way of presenting the potential 

use of countermeasures in Arctic conditions is a 

chart or table that assigns the standard approaches 

of mechanical operations, in-situ burning and 

dispersant application to a specific range of ice 

cover. The problem with this approach, however, is 

that conditions in Beaufort Sea ice are so dynamic 

during the transition seasons that any response 

would likely prove to be limited to a small (time) 

window of opportunity—leave alone the obvious 

safety concerns.”

For any countermeasure, and mechanical recovery systems in 

particular, it is important to have a better understanding of ice 

drift and oil movement so as to inform response operations 

and deployment of appropriate countermeasures (Solsberg, 

2008). The ability to predict ice movements to inform the 

use of mechanical recovery systems dovetails with other 

information needs for an improved understanding of the 

Arctic Ocean and sea ice. Uniting monitoring and process 

studies and facilitating modeling at different scales will lead 

to better understanding of sea ice response to various forcing 

factors (U.S. Arctic Research Commission, 2010). 

5.12. Finding: One of the challenges to mechanical oil 

recovery in ice-infested waters is the availability of ice coverage 

information, on the short time scales and in the dynamic conditions 

of a spill response operation. 

5.12. Recommendation: There is a need to develop a system 

with the ability to make short-term ice dynamics forecasts to 

inform windows for mechanical recovery operations and to 

improve recovery technologies in the “ice gap” (about 30 to 70 

percent ice coverage). From an operational perspective, there also 

is a need for information to inform response planning in the event 

of shifting ice coverage.

In-Situ Burning 

In-situ burning (ISB) has been studied for several decades 

as a response tool for oil spills in ice. Some of the earliest 

activities were laboratory, tank, and field studies conducted in 

the 1970s associated with drilling in the Canadian Beaufort 

Sea (Potter and Buist, 2008). Later oil exploration efforts 

in Svalbard (1980–94) also considered ISB as a primary 

countermeasure for use in Arctic oil spills (Brandvik and 

others, 2006). 

One of the key challenges to the effectiveness of ISB is 

maintaining sufficient thickness of oil to sustain a burn. The 

minimum ignitable thickness of a fresh crude oil slick on 

water is about 1 mm, whereas for aged, unemulsified crude oil 

the minimum thickness is on the order of 2–5 mm (Potter and 

Buist, 2008). Emulsification is an important process affecting 

the effectiveness or the response window of opportunity for 

use of ISB, because the oil in the emulsion is not able to reach 

a temperature to burn until the water is first boiled off (Potter 

and Buist, 2008). Emissions from ISB include the release to 

the atmosphere as well as burn residue. The residue from an 

ISB may float on water or sink, depending on the oil type and 

the extent of the burn. 

There is a large body of scientific work based on 

laboratory, mesoscale, and to some extent field trials that 

demonstrate ISB to be effective in removing oil from the 

water surface under Arctic conditions, but it remains to be 

determined whether these results translate into real-world 

conditions. The effectiveness of ISB can be affected by 

weather and sea-state conditions, but ice is a particular 

challenge. At ice coverage exceeding 70 percent, ISB can be 

conducted without any mechanical containment systems, as 

the ice provides a natural barrier to restrict the movement of 

oil across the water surface. At ice concentrations less than 
134 An Evaluation of the Science Needs to Inform Decisions on Outer Continental Shelf Energy Development in the Chukchi and Beaufort Seas, Alaska

5.13. Finding: There is a large body of scientific work 

demonstrating that in-situ burning (ISB) of oil is effective in 

removing spilled oil from the water surface under certain 

experimentally controlled Arctic conditions. However, there are 

insufficient data to assess the effectiveness of ISB under the full 

suite of real-world conditions that might be experienced during a 

response to an oil spill. 

5.13. Recommendation: Many of the mesoscale and field 

tests show a considerable range in the in-situ burning (ISB) 

effectiveness. However, because ISB is one of the few response 

options that exist for the Arctic, it is important to conduct 

additional research to improve its effectiveness. Thus, further 

focused study is essential to better define the applicability of ISB 

under various conditions.

30 percent, open-water ISB may be feasible (Brandvik and 

others, 2006; Potter and Buist, 2008), including the use of oil 

containment with a fire-resistant boom. Ice concentrations 

of 30–70 percent are considered to be the “most difficult 

from an in-situ burning perspective” (Juurmaa, 2006). The 

particular challenge for ISB in ice concentrations in this range 

is that these ice concentrations are high enough to impede the 

effectiveness of mechanical containment systems, yet too low 

to serve as a natural containment barrier for the oil (Brandvik 

and others, 2006; Potter and Buist, 2008). 

In addition to the abundance of sea ice, the type of sea 

ice present can impact the effectiveness of ISB. S.L. Ross 

Environmental Research, Ltd., and others (1998) reported that 

for freeze-up scenarios at low and medium ice concentration, 

ISB offered little advantage over containment and recovery 

techniques. However, there was potential to contain and burn 

oil in their 70-percent ice scenario as suggested above. For 

break-up scenarios, burning on water provided effectiveness 

similar to containment and recovery. And, burning oil on floes 

or concentrated in melt pools was as effective as on-water 

burning or containment and recovery approaches. Conducting 

ISB in pack ice during break-up may be more effective at 

removing spilled oil than when there is a similar amount of ice 

coverage during the fall freeze-up, because the fall freeze-up 

generates significant amounts of slush ice that can impede 

containment of slicks (Potter and Buist, 2008). In a recent 

review of countermeasures in the Beaufort Sea, Solsberg 

(2008) noted that 

“...the relative behaviour of spilled oil and ice 

require further investigation to determine how 

feasible it is, in fact, to burn oil during the transition 

seasons .... While small and meso-scale testing 

is needed, field work is the ultimate means of 

measuring the feasibility of burning.” 

Brandvik and others (2010a) report ISB efficiencies ranging 

from 50 to 90 percent from a field test (during about 70–90 

percent ice coverage) and mesoscale laboratory experiments in 

a wave tank under varying ice coverage conditions (at 0, 50, 

and 90 percent). In field and the mesoscale trials at 90-percent 

ice coverage, ISB had a longer window of opportunity 

(about 120 and about 140 hours, respectively). Mesoscale 

experiments at 0-percent ice coverage had less than a 5-hour 

window of opportunity and slightly better at 50-percent ice 

coverage (about 10 hours). The authors concluded that the 

favorable comparisons among results from the field test 

and mesoscale basin experiments at high percentage ice 

coverage were an indication that the mesoscale trials could be 

considered to reflect realistic conditions (Brandvik and others, 

2010a). In the course of the field experiment, the authors noted 

that strong winds caused the dense ice field being tested to 

move at a rate of approximately 40 km/d (Brandvik and others, 

2010b), underscoring the need for information on weather and 

coupled ice-transport conditions to inform potential oil-spill 

responses operations. 

As we discussed in section, “Spilled-Oil Weathering and 

Persistence,” in the event spilled oil becomes entrained in ice, 

the rate of oil weathering may be slowed to the extent that the 

response window for using ISB is expanded. For example, oil 

in brine channels could potentially be released during spring 

ice melt in melt pools. Oil that is released from ice during 

the melting and collects in pools atop the pack ice may be 

treatable by ISB (Brandvik and others, 2010a). However, 

this approach could provide an additional exposure route to 

wildlife given that melt pools can form thaw holes, which in 

turn may serve as breathing holes for wildlife and provide an 

important ecosystem for other marine life (World Wildlife 

Fund, 2009). Features such as leads, polynyas, and ice edges 

tend to be focal points of biological activity, as well as targets 

for pooled spilled oil (World Wildlife Fund, 2009). 
Chapter 5

Oil-Spill Risk, Response, and Impact 135

There are a number of studies on the emissions from 

ISB, including air emissions (soot and gases) and ISB 

residues, which could float to the water surface or sink to 

the ocean floor. Recent syntheses of the state-of-knowledge 

on atmospheric emissions from ISB are given in Potter 

and Buist (2008), S.L. Ross Environmental Research, 

Ltd., and others (2010), and Fingas (2011b). Recent 

studies of atmospheric emissions from ISB point to the 

need for an expanded characterization of the composition 

of air emissions. For example, Aurell and Gullett (2010) 

studied atmospheric ISB emissions in the GOM during the 

Deepwater Horizon oil-spill response and found examples 

of halogenated organic compounds (toxic environmental 

pollutants) above background levels. These results contrast 

with previous conclusions drawn from limited mesoscale 

laboratory studies of ISB. These compounds have potential 

health effects, such as immunotoxicity, carcinogenicity, and 

teratogenicity. S.L. Ross Environmental Research, Ltd., and 

others (2010) provide an overview of the environmental 

issues with ISB and the evolution of ISB procedures 

confirming that most research has focused on characterizing 

the atmospheric emissions from ISB with fewer studies 

characterizing and testing for potential toxicity arising from 

ISB residues. Nuka Research and Planning Group, LCC 

and Pearson Consulting, LCC (2010) point out that earlier 

studies have shown that there is greater potential for ISB to 

form residues in the presence of sea ice than when ISB is 

conducted in open water—citing Fingas (2004) and Buist 

and others (2003). Previous studies have acknowledged 

that ISB residues may contain toxic materials, and should 

be removed from the marine environment where possible 

(Nuka Research and Planning Group, LCC and Pearson 

Consulting, LCC, 2010). Nuka Research and Planning 

Group, LCC, and Pearson Consulting, LCC (2010) cite 

previous studies, such as the American Petroleum Institute 

(2004) that investigated the proclivity for ISB residues to 

sink and identified the need for technologies to recover 

sunken ISB residues. Potter and Buist (2008) stated that 

residues from efficient burns of crude oil generally are 

environmentally inert, but that potential environmental 

effects are derived from physical properties, including 

whether residues float or sink, and what chemical 

constituents are retained. In that regard, the potential 

for residues that will sink can be predicted based on the 

properties of the initial oil to some extent. 

Several field and mesoscale efforts are informative 

on the topic of concentrations of toxics (for example, 

polycyclic aromatic hydrocarbons or PAHs) resulting from 

ISB. One foundational study is the Newfoundland Offshore 

Burn Experiment (NOBE; Fingas and others, 1995). In 

addition to extensive characterization of the atmospheric 

emissions, including soot and gases, from the NOBE, 

Fingas and others (1995) also analyzed the residue from the 

experiment. They reported that the residues resembled highly 

weathered oil with lower amounts of PAHs than the starting 

oil. However, Brenner and others (1990) found that PAH 

concentrations in ISB residues and Alberta sweet crude oil 

samples were comparable and that there was a lower total 

amount of PAHs emitted via smoke at thinner slick layers 

(2-mm versus 10-mm layer). In a synthesis of data from 

45 mesoscale burns, Fingas and others (2001) found that 

PAHs in the soot and residue were about 2–8 percent of that 

in the starting oil. Wang and others (1999) conducted detailed 

chemical analyses on ISB residues from several mesoscale 

burns in Mobile Bay, AL. They concluded that high-molecular 

weight PAHs were derived largely from the combustion 

process itself. Garrett and others (2000) also support this 

finding. Therefore, there is a need for thorough chemical 

analysis in conjunction with measurement of ISB effectiveness 

under mesoscale and larger test conditions. The potential for 

less effective burns resulting from ice and weather conditions 

may yield higher amounts of high-molecular weight PAHs. 

This is consistent with Buist and others (1999) who found that 

the chemical composition of residue depends on the parent 

oil, the degree of weathering, and the efficiency of the burn. 

Levels of PAHs in residue could be as much as 40 percent 

more than in the parent, but considering the volume reduction 

accomplished by burning, the total amount of PAHs could be a 

fraction of what was in the slick before ignition. 

There has been limited research on the toxicological 

effects of burnt oil relative to other oil-spill remediation 

techniques and some results appear contradictory (Cohen and 

Nugegoda, 2000). DeCola and others (2006) echoed this idea 

and stated that few published data exist on sublethal effects of 

burn residues, and no information on impacts of burn residues 

to benthic-feeding whales. Some insights on the comparative 

toxicity of ISB residues can be gleaned from Cohen and 

Nugegoda (2000). They tested the water accommodated 

fraction (WAF) from crude oil, chemically dispersed crude, 

and burnt crude oil. They found that of the three elements, 

dispersed crude oil WAF was the most toxic and burnt crude 

oil WAF was the least toxic to their marine fish test species. 

But, they also noted that sublethal toxicities of crude oil WAF 

and burnt crude oil WAF were observed at dilutions seven to 

eight times less than in the dispersed crude oil WAF. These 

results leave the relative toxicity ISB residue on marine 

organisms unclear.

Despite the relatively few studies characterizing 

ISB residues and potential toxicological or other effects, 

there appears to be a general operational consensus that 
136 An Evaluation of the Science Needs to Inform Decisions on Outer Continental Shelf Energy Development in the Chukchi and Beaufort Seas, Alaska

5.14. Finding: There are relatively few studies characterizing 

emissions and residues from in-situ burning (ISB), including their 

potential toxicology. However, the studies that do exist suggest 

there is a potential for health effects from compounds released 

from ISB. Robust characterization of likely ISB air plumes and 

toxicological testing, especially on potential effects to benthic 

organisms, of ISB residue are lacking. 

5.14. Recommendation: Our review underscores the 

importance of three points: 

1. There is a need for thorough chemical analysis and 

measurement of in-situ burning (ISB) effectiveness under 

mesoscale and larger test conditions. 

2. Better characterization of ISB residues is needed, especially 

toxicity, physical properties, and bioavailability of contaminants 

contained within the residue matrix; this is especially true in 

relation to potential effects to benthic communities.

3. Improving pre- and post-spill plume modeling would help 

inform whether or not an ISB should be conducted and would 

facilitate On-Scene Coordinator decisions on measures to 

protect local populations. The potential effect of “fall out” from 

a smoke plume that goes over land-based (plant) subsistence 

resources is of particular concern.

ISB residues should be collected and removed from the 

environment (for example, Buist and others 1999). This 

concept is included in the ARRT’s In-Situ Burning Guidelines 

for Alaska, Revision 1 (Alaska Department of Environmental 

Conservation and others, 2008), which states that 

“[t]he toxicological properties and effects of the 

residue demonstrate the need and importance of 

a residue recovery plan which is an operational 

requirement.” 

They further note that the longer term effects of ISB residues 

on marine organisms have not been investigated. 

Recently, in the Deepwater Horizon oil-spill response, 

the National Marine Fisheries Service and others (2010) 

issued a temporary emergency rule closing a specific portion 

of the GOM to red shrimp fishing due to the presence of ISB 

residues. Such actions underscore the continuing need for 

additional information on the composition, characteristics, 

bioavailability/bioaccessibility of ISB residues, as well as 

emissions from ISB, to inform response decisions and natural 

resource damage assessments and restoration activities.

Dispersants 

Dispersants are chemical mixtures consisting of 

three main items: surfactants, solvents, and additives. The 

surfactant molecules contain components that tend to bond 

with water (hydrophilic) and others that tend to bond with oil 

(oleophilic). Thus, the aim of dispersants as a spill mitigation 

countermeasure is not to reduce the volume of spilled oil in 

the environment—in contrast with other countermeasures such 

as mechanical recovery and ISB—but rather to facilitate the 

mixing and dispersion of spilled oil within the water column 

by promoting the formation of tiny oil droplets and preventing 

the recoalescence of those droplets into larger accumulations, 

such as slicks. The National Research Council recently 

(2005) conducted an extensive review of the effectiveness 

and impacts from the application of dispersants to oil spills, 

which we will summarize briefly here. Based on our expert 

consultations, the findings in the NRC report remain valid and 

applicable to the issue of data gaps for the Arctic. They noted 

that the

“...objective of dispersant use is to enhance 

the amount of oil that physically mixes into 

the water column, reducing the potential that a 

surface slick will contaminate shoreline habitats...

[but] increase[s] the potential exposure of watercolumn and benthic biota to spilled oil. Dispersant 

application thus represents a conscious decision to 

increase the hydrocarbon load... on one component 

of the ecosystem...reducing the load on another... 

This trade-off reflects the complex interplay of 

many variables, including the type of oil spilled, 

the volume of the spill, sea state and weather, 

water depth, degree of turbulence (thus mixing and 

dilution of the oil), and relative abundance and life 

stages of resident organisms” (National Research 

Council, 2005).

Some of the key questions regarding dispersant applications, 

and recommendations for research priorities most applicable 

to our assignment from National Research Council (2005) are:

• Is the spilled oil or refined product known to be 

dispersible?

Example: The need for research into the mechanisms 

and rates of weathering processes—including 

parameters such as the rheology of chemistry of both 

oil and dispersants and energy dissipation—affecting 

the chemical effectiveness of dispersants, including 

both bench-scale and well-coordinated wave-tank 

studies.
Chapter 5

Oil-Spill Risk, Response, and Impact 137

• Are the environmental conditions conducive to 

the successful application of dispersants and their 

effectiveness?

Example: The need for research in support of 

modeling and forecasting of the effectiveness of a 

dispersant application, including the need for data 

from wave-tank studies and the updating of protocols 

for Specialized Monitoring of Advanced Response 

Technologies.

• Will the effective use of dispersants reduce the impacts 

of the spill to shoreline and water surface resources 

without significantly increasing impacts to watercolumn and benthic resources?

Example: The need for research into improving oil 

trajectory and fate models for both planning and 

real-time decision-making needs, with appropriately 

designed experiments to verify and validate these 

models. Such experiments could include research into 

quantifying weathering rates and fate of chemically 

dispersed oil droplets relative to undispersed oil.

Subsequent research activities have targeted these 

knowledge gaps, some of which are highlighted in the 

Biennial Report of the Interagency Coordinating Committee 

on Oil Pollution Research (2009) and the synthesis of the 

Arctic Oil Spill Response Research and Development Program 

(Minerals Management Service, 2008b). Fingas (2008a) also 

conducted a review of scientific literature related to oil-spill 

dispersants, spanning the years 1997–2008 and noted that 

a Canadian Research Council workshop on dispersant 

research priorities established priorities similar to those of 

the NRC. 

There has been recent work to develop new 

formulations of dispersants (Nedwed and others, 2008) that 

can be applied to an oil slick as a gel, and thus potentially 

be more effective on oils with higher viscosities. Such 

advances may hold promise for extending the response 

window for dispersant application by facilitating use on 

higher viscosity oil slicks stemming from either weathering 

oil or due to the cold temperatures. 

Li and others (2008) note that two of the most 

important factors in the effectiveness of a chemical 

dispersant are the energy dissipation rate which affects 

the penetration of oil into the bulk aqueous phase and 

the particle size distribution of the dispersed oil. Waves 

can provide a significant source of mixing energy to the 

dispersion process. Thus the effectiveness of dispersants 

is derived from a physical-chemical process that includes 

the chemical properties of the oil and dispersant, and the 

physical action of the waves (National Research Council, 

2005; Li and others, 2008). Vörösmarty and others (2010) 

note that sea-ice cover is especially important to address 

in studies of Arctic Ocean circulation given the unique 

momentum and buoyancy forcing that arise from overlying 

sea-ice cover. Furthermore, dispersants can be effective in 

broken ice provided there is some mixing energy available, 

and wave reflection among broken and brash ice may serve 

as highly localized sources of mixing energy (Minerals 

Management Service, 2008b). Given this potential source of 

mixing energy, there also is a need to characterize specific 

energy distributions on a more localized scale, that is, at the 

point of dispersant application, such as energy added from 

the ship’s propellers or via high-pressure water systems 

to enhance mixing (Sørstrøm and others, 2010). A recent 

study by Nedwed and others (2007) tested the potential for 

an azimuthal stern drive (ASD) from an icebreaker as a 

means to provide the mixing energy necessary to disperse 

chemically treated oil slicks in broken ice. The authors 

found that this approach holds promise for mixing and 

dispersion of oil spilled on top of and under continuous ice 

and within leads, and could significantly supplement the 

dispersion that would take place with wave energy alone. 

5.15. Finding: Although significant research and technological 

studies have examined chemical dispersants over the past 

decade, including focus on cold-water and Arctic applications, the 

scientific understanding is yet incomplete. 

5.15. Recommendation: Our examination suggests that 

substantial scientific and technical work as outlined by various 

expert groups still must be done before dispersants can be 

considered a practical response tool for the Arctic.
138 An Evaluation of the Science Needs to Inform Decisions on Outer Continental Shelf Energy Development in the Chukchi and Beaufort Seas, Alaska

5.16. Recommendation: We concur with the National 

Research Council (2005) recommendation that a focused 

series of studies should be developed and implemented that 

will enable practitioners to better predict the effectiveness of 

dispersant use for different oil and environmental conditions. 

For example, further study of oceanographic characteristics such 

as salinity, temperature, and circulation and wave patterns, 

and the influence of sea ice cover on these, in the Arctic Ocean 

would facilitate our understanding of the magnitude of the 

effectiveness of dispersants as a countermeasure against an 

oil spill in the Beaufort and Chukchi Seas. This information, 

aided by increased monitoring and prediction of winds, currents, 

temperature, and salinity, would be particularly useful in 

understanding the regional aspects of dispersant applications.

5.16. Finding: How environmental conditions might actually 

affect dispersant effectiveness during oil-spill response is not 

yet well understood. As noted in our review, it has not yet 

been established whether wave-tank experimental conditions 

are typical or representative of wave conditions that could be 

encountered at sea with ice present. Factors, such as salinity 

and temperature, also can vary dispersant effectiveness by a 

factor of 10 or more. 

The issue of energy dissipation may help to describe 

some of the disparity observed across studies. For example, 

Belore and others (2009) in a study of dispersant application 

at the National Oil Spill Response Research and Renewable 

Energy Test Facility achieved dispersant effectiveness results 

that generally were higher than results from similar testing at 

a different facility, and the authors postulate this difference 

could have been due to higher wave energies achieved during 

their tank studies. Likewise, Venosa and others (2008) in 

a series of wave tank experiments found that the energy of 

the system had a strong influence on the ability to transfer 

oil from the surface into the water column even with the 

aid of dispersants. Further, Venosa and others (2008) noted 

a difference in the effectiveness of the two dispersants they 

tested and postulated that some dispersants may be more 

suitable for low- to moderate-energy settings, whereas others 

may be better suited for application in moderate to higher 

energy conditions.

As discussed previously, the weathering of oil entrained 

in sea ice may be inhibited. When it is subsequently released 

as the ice melts, the timeframe may be significantly extended 

for dispersant use as a countermeasure (Dickins and others, 

2008; Brandvik and others, 2010a). This process would 

significantly alter the paradigm under which the “response 

window” for application of dispersants to spilled oil is 

viewed (Lewis and Daling, 2007). Further characterization 

of the effectiveness of dispersants under these conditions is 

needed to inform the “response window.” This underscores 

the recommendation raised in National Research Council 

(2005) that 

“[r]elevant state and federal agencies and industry 

should develop and implement a focused series 

of studies that will enable the technical support 

staff advising decisionmakers to better predict the 

effectiveness of dispersant application for different 

oil types and environmental conditions over time.”

Brandvik and others (2006) report that dispersants can 

be a suitable mitigation countermeasure in Arctic waters, 

both open water and up to 50-percent ice covered. In a recent 

review of dispersant effectiveness under Arctic conditions, 

Lewis and Daling (2007) identify that factors such as salinity 

of sea ice and colder temperatures affect the viscosity of 

spilled oil and may reduce the effectiveness of dispersant 

applications. These conditions also inhibit oil weathering 

factors, such as the formation of emulsions (Fingas, 2008b). 

Thus, the window of opportunity during which dispersants 

may be effective may be extended. Laboratory studies by 

Moles and others (2002) found that at the conditions typical of 

Alaskan estuaries and marine waters, dispersant effectiveness 

was at study detection limits (less than 10 percent). Some 

dispersants are more sensitive to salinity and temperature, and 

measured effectiveness can vary by roughly a factor of 10 or 

more (Lewis and Daling, 2007). However, recent results from 

tests conducted at the National Oil Spill Response Research 

and Renewable Energy Test Facility using four Alaskan North 

Slope crude oils and two dispersants found that the dispersants 

were more than 90 percent effective at dispersing fresh and 

weathered forms of the oils under cold weather conditions 

(Mullin and others, 2008; Belore and others, 2009).
Chapter 5

Oil-Spill Risk, Response, and Impact 139

In addition to understanding the window of opportunity 

during which dispersants can be successfully used, there 

is a need to improve our understanding of the long-term 

viability of the dispersed oil. Fingas (2008a) reported that 

many researchers recognize that oil-spill dispersants are not 

stable and will destabilize and rise to the surface: half-lives 

of dispersions may be between 4 and 24 hours. However, 

in a recent study (Nedwed and others, 2007) using an ASD 

icebreaker to enhance mixing energy in a Canadian basin test, 

the researchers postulated that the dispersed oil would be “...

unlikely to resurface even in very low energy conditions” 

based on their study results.

There is uncertainty regarding the effects of dispersants 

on marine organisms in the Arctic (World Wildlife Fund, 

2009). One of the uncertainties is the potential effect of 

dispersants on the natural processes of microbial degradation 

of oil and how this may affect the toxicity of the residual oil. 

One of the key compound classes within crude oil, in terms of 

toxicity and other long-term deleterious effects on ecosystems, 

are PAHs, yet there are few studies to date that quantify the 

fate and potential for biodegradation of these compounds 

(National Research Council, 2005). Recent reviews (National 

Research Council, 2005; Fingas, 2008a) indicate that a 

scientific consensus regarding the effect of dispersants on 

toxicity of dispersed oil and effects on biodegradation of oil 

is lacking. The National Research Council (2005) concluded 

that there was no compelling evidence that the toxicity 

of chemically dispersed oil is enhanced relative to that of 

physically dispersed oil or that there were any reproducible 

effects of chemical dispersion on the rate of biodegradation of 

crude oil. However, Fingas (2008a) reported that 

“[i]t is clear, on the basis of current literature that 

the surfactants in some of the current dispersant 

formulations can inhibit biodegradation.”

 Lindstrom and Braddock (2002) reported that “the effect 

of dispersant on biodegradation of a specific hydrocarbon 

was not predictable by class [of hydrocarbon]” and either 

an increase or a decrease in the toxicity of the residual oil 

could result. Adding to this discussion, Zahed and others, 

2010) found that the dispersant Corexit 9500 appeared to 

enhance biodegradation of crude oil, including at higher 

initial concentrations of crude oil, based on laboratory-scale 

bioremediation trials.

In contrast, there are a number of earlier studies 

indicating that chemically dispersed oil is more toxic to 

marine organisms than untreated oil (Pew Environment Group, 

2010). The National Research Council (2005) found that 

“[i]n order to better understand the fate and effects 

of dispersed oil, studies should be conducted to 

estimate the relative contribution to toxicity of 

dissolved-, colloidal-, and particulate phase oil in 

representative species.”

 Fingas (2008a) states that 

“[l]ong-term effects of chemically-dispersed oil 

are poorly-studied and relatively unknown at this 

point in time. Again little has changed from the 

first review in 2002, but it is very clear now that 

the toxicity of dispersed oil is greater than that 

of physically dispersed oil, primarily because of 

the large increase (5 to 50 times) in the amount of 

aromatics and PAHs in the water column.” 

Subsea dispersants were used for the first time during 

the Deepwater Horizon oil spill and in larger quantities, both 

surface and subsurface, than during any previous spill (Pew 

Environment Group, 2010). Given this large-scale application 

of dispersants, there is a critical need to understand the 

potential toxicity of dispersants and other effects on marine 

organisms (Judson and others, 2010). Samples collected 

following the application of dispersants to the Deepwater 

Horizon oil spill have documented the presence of one of 

the dispersant surfactants in deepwater hydrocarbon plumes 

at 1,000–1,200 m water depth (Kujawinski and others, 

2011). The researchers concluded that the surfactant itself 

underwent no biodegradation. Researchers also noted that 

they could not yet determine if the dispersant application 

successfully reduced the size of the oil droplets or facilitated 

the entrainment of these droplets within the deepwater 

plume (Kujawinski and others, 2011). Finally, because of the 

emphasis now placed on subsea dispersant use by the National 

Response Team, it will be important to address research needs 

regarding such use. However, the USGS OCS Team had 

insufficient time to consider this new emerging issue. We note 

here that further consideration of the potential applicability 

of the technique to Arctic scenarios and any unique Arctic 

consequences of such use should be assessed.

5.17. Recommendation: Surface dispersants are used 

in response to oil spills internationally, but improving the 

understanding of the “window of opportunity” for potential 

deployment of all dispersants in the Arctic is needed. A more 

extensive understanding of the toxic and sublethal effects 

and ramifications for microbial communities (and the natural 

biodegradation of oil) also is needed.

5.17. Finding: The interplay of factors such as weather and sea 

ice on the “window of opportunity” for use of dispersants and 

how sea-ice conditions may affect the stability of dispersed oil 

is yet not well understood. The understanding of the potential 

toxicological effects of dispersants on Arctic ecosystems is 

lacking. 
140 An Evaluation of the Science Needs to Inform Decisions on Outer Continental Shelf Energy Development in the Chukchi and Beaufort Seas, Alaska

Chemical Herders 

Chemical herders—also referred to as oil collecting 

agents—are chemicals applied to the water surrounding 

an oil spill in order to thicken the spill, without the need 

for mechanical containment, to a point that it can sustain 

a burn (Buist and others, 2008a; Minerals Management 

Service, 2008b). Chemical herders constitute an oil-spill 

countermeasure that can be used in conjunction with ISB 

(Sørstrøm and others, 2010). This is because one of the 

critically limiting factors with ISB is the need to have a slick 

that is sufficiently thick to sustain a burn. Recent studies are 

also investigating the potential for application of chemical 

herders to enhance mechanical recovery of oil when used in 

conjunction with deployment of skimmers, and the potential 

for herding agents to contract the slick area, and thus 

improve the efficacy of dispersant applications (S.L. Ross 

Environmental Research, Ltd., 2010).

Chemical herders have been available for several decades 

(Buist and others, 2008b), but not used extensively offshore to 

date because they are effective under largely calm conditions 

(S.L. Ross Environmental Research, Ltd., 2010). There 

are currently no commercially available chemical herders 

approved for use in Arctic waters (World Wildlife Fund, 

2009).

Reviews on the state-of-the-art of oil-spill 

countermeasures, as by D.F. Dickins Associates, Ltd. (2004), 

have identified chemical herder behavior in ice environments 

as a knowledge gap. Subsequent research activities 

(Interagency Coordinating Committee on Oil Pollution 

Research, 2009; Minerals Management Service, 2008b; and 

Buist and others, 2008a) have sought to address this gap. 

Recent studies have focused on the potential utility of herders 

in responding to oil spills in cold waters, and particularly 

in ice-covered waters. For example, Minerals Management 

Service (2008b) suggested that 

“[i]n loose broken ice.... conditions, even with 

no possibility of booming, if these slicks could be 

thickened to the 2- to 5-mm range, effective burns 

could be conducted.” 

In this context, herding agents may be helpful in the “ice 

response gap” window of 30- to 70-percent coverage (World 

Wildlife Fund, 2009). 

These recent studies (as with ISB and dispersants) 

involved public-private sector collaborations, such as 

BOEMRE and ExxonMobil (Minerals Management Service, 

2008b), and the JIP on oil-spill contingency for Arctic and 

ice-covered waters. International cooperation, at a variety of 

scales, also has facilitated research from laboratory testing to 

mid-scale testing at the U.S. Army Cold Regions Research 

and Engineering Laboratory, the National Oil Spill Response 

Research and Renewable Energy Test Facility, and the Fire 

Training Grounds in Prudhoe Bay, Alaska. Recently, two fullscale burn experiments involving the use of chemical herders 

were conducted in the offshore of Svalbard, Norway (Minerals 

Management Service, 2008b; Pew Environment Group, 2010). 

One large-scale experiment with chemical herders was carried 

out on a free-floating crude oil slick in low (10 percent) ice 

coverage as part of the JIP Oil-in-Ice effort in 2008 (Sørstrøm 

and others, 2010). One of the formulations used in recent 

studies of chemical herders in cold-water conditions is the 

U.S. Navy cold-water herder formulation (Buist and others, 

2008b; Buist, 2010). This herding agent was successful 

in producing slicks in excess of 3 mm and in significantly 

contracting oil slicks in the presence of ice (Buist, 2010). One 

of the recommendations from this work is to conduct a largescale field trial to test the effectiveness of chemical herding (as 

a precursor to ISB) in pack ice, and to investigate the influence 

of wind and sea conditions on this potential spill mitigation 

countermeasure. One of the key objectives would be to 

determine how long a herded slick can maintain its thickness 

with regular re-application of the surfactant under a realistic 

scale (Buist, 2010). New formulations of chemical herders are 

under development and testing (Buist and others, 2010). 

While an important measure in support of ISB, the 

application of chemical herders may affect other recovery 

and mitigation countermeasures. S.L. Ross Environmental 

Research, Ltd. (2010) notes that 

“...the active ingredient in herding agents (the 

surfactant) renders sorbent pads less hydrophobic 

and their water retention increases considerably. 

This could be a significant detriment to oleophilic 

skimmers such as drums, discs and rope mops whose 

recovery surfaces contact herding agent (SIC). This 

should not be an issue with other skimmers types 

such as weirs and vacuums.”
Chapter 5

Oil-Spill Risk, Response, and Impact 141

The question of potential toxicity of chemical herding 

agents to marine species is noted in the literature (Buist and 

others, 2008a; World Wildlife Fund, 2009). Although direct 

toxicity data appear to be lacking, it has been postulated that 

the risk posed to the marine environment may be modest 

(Buist and others, 2008b). Buist and others (2008a) note 

that toxicity data on the U.S. National Contingency Plan 

(NCP) website indicate that one herder, for example, is only 

about one-half as toxic as approved chemical dispersants. 

Toxicity information, from Material Safety Data Sheets, 

for the components of the U.S. Navy chemical herder is 

given in Buist (2010). However, information on toxicity 

that is currently required in Subpart J of the NCP does not 

necessarily relate to species of concern to Alaska. Research 

on the potential toxicity of chemical herders to Arctic and 

subsistence marine organisms would help determine if shortand (or) long-term effects might occur. 

Oil-Mineral Aggregates

The association of oil and fine mineral particulates, 

typically referred to as oil-mineral aggregates (OMAs) or 

oil-suspended particulate matter aggregates and oil and fine 

particle interaction, has long been recognized as a process 

by which hydrocarbons are transported in marine systems 

(Owens, 1999). Several case studies, spills of opportunity, 

and field studies—such as the Baffin Island Oil Spill (BIOS) 

project—have demonstrated that this oil-clay flocculation 

process merits consideration in conjunction with other oildegradation processes (physical weathering, photodegradation, 

and biodegradation) in understanding the natural attenuation 

and removal of oil from shorelines (Owens and others, 1994).

This process garnered considerable attention in studies of 

coastal processes following the Exxon Valdez oil spill, as 

researchers noted the association between oil and mineral fines 

as a mechanism for the natural removal and attenuation of 

hydrocarbons on the shoreline (Bragg and Yang, 1995). Once 

formed, OMAs are relatively stable structures, the particlesize distribution and density (or buoyancy) of which are 

dependent on the mineral-to-oil ratio (MOR) in the structure. 

Both the composition of the oil and the type of mineral fines 

can affect this ratio (Zhang and others, 2010). Some basic 

OMA properties are in need of further study, such as the size 

distribution of the OMAs, particularly in the presence of 

dispersants, and how this may affect the settling velocity of 

OMAs in the water column. There is relatively little known 

about the specific effect of salinity and clay mineral type on 

OMA formation (Li and others, 2007). The Arctic Ocean in 

general is fresher than other marine environments studied. 

Thus, understanding how regional salinity may affect OMA 

formation is important. Further, the potential timing of a spill 

event could influence these processes. For example, should 

a spill coincide with the spring melt (Yunker and others, 

2002), associated discharge pulse from the Mackenzie River 

system salinity levels would be greatly reduced at some 

regional scale. The discharge from this fluvial system could 

significantly affect the salinity and (or) suspended particulate 

matter (SPM) concentrations, particularly in the nearshore 

environment. The fate and transport of OMAs are important 

considerations for oil-spill-trajectory modeling in nearshore 

waters (Sterling and others, 2004). 

5.18. Recommendation: A better understanding of the 

comparative value and impact of chemical herders may be 

warranted to inform oil-spill response scenarios and the timing 

for deployment of various countermeasures, particularly given 

the potential for a second-stage recovery effort during ice melt 

to target oil that had previously been entrained in sea ice. 

Developing toxicological data for Arctic species of interest would 

better define the relative value and impact of chemical herders 

within the countermeasure suite of available tools.

5.18. Finding: Although chemical herders are important to 

improved effectiveness of in-situ burn countermeasures, they 

affect oil recovery efficiencies from various mechanical recovery 

systems. The resulting trade-offs in countermeasure efficiencies 

are not fully understood under Arctic field conditions. The toxicity 

of chemical herders to organisms may not be significant, but this 

belief has not been validated for Arctic species of concern. 
142 An Evaluation of the Science Needs to Inform Decisions on Outer Continental Shelf Energy Development in the Chukchi and Beaufort Seas, Alaska

Given the natural propensity for oil and SPM to form 

OMAs, there exists the potential that OMAs also could be 

used as an oil-spill countermeasure. The Canadian Coast 

Guard has recently conducted studies looking into the 

potential utility of this process as a countermeasure to combat 

oil spills in ice-covered waters (Cloutier and Doyon, 2008). 

The Centre for Offshore Oil, Gas and Energy Research also 

is conducting research into this potential use of OMAs, such 

as the application of mineral fines as a powder or an aerosol 

mixture to oil slicks at the surface (Lee and others, 2009). In 

the event additional mixing energy is needed, one potential 

mechanism under consideration is adding mixing energy to 

accelerate the OMA formation process (Lee and others, 2009). 

Utilization of the OMA formation process may be a helpful 

tool to address the ‘ice response gap’ in which conventional 

mechanical technologies may not be effective (Lee and others, 

2009). 

If OMAs are considered for use in the Arctic, a thorough 

understanding of how OMAs are incorporated into the sea ice, 

such as slush, is needed. This understanding is important to 

oil fate and transport analyses, as OMAs could be transported 

with the slush ice away from the site of the spill. Payne and 

others (1991) studied the process by which oil-contaminated 

sediments could be incorporated into sea ice and thus it is 

likely that sea ice also could have scavenging potential for 

OMAs and facilitate greater dispersal of oil (as OMA) over a 

much larger area. 

There is a need to understand how the potential process 

of OMA formation may be affected by other countermeasures 

used in response to an oil spill. For example, 

“[t]he synergistic effect of dispersants and mineral 

fines enhances the transfer of oil from the surface 

downward into the water column; and a large 

number of small particles is produced as a result 

of interaction of dispersants and mineral fines with 

crude oil” (Li and others, 2008). 

Li and others (2007) utilized wave-tank studies to examine 

these processes, and found that OMA formation can occur 

with both physically- and chemically-dispersed oil. These 

studies were conducted under breaking waves. Absent this 

energy, it is unclear of the effect. Li and others (2007) note 

that additional factors, such as oil type and weathering 

state, the type of mineral fines, and the MOR are areas for 

future study as well as testing under a variety of sea-energy 

conditions.

Detection, Monitoring, and Tracking 

There are numerous technologies available for use in 

detecting and tracking oil spills on open water, and on top 

of, within, or under sea ice. These can include: GPS tracking 

buoys (Dickins and Buist, 1999); tethered balloons (Dome 

Petroleum Limited and others, 1982); satellite imagery; 

airborne reconnaissance; trained visual observers; ground, 

airborne, and space remote sensing technologies; vessel 

surveillance; optical methods (still and video cameras); 

unmanned aerial systems (Lehr, 2008); and on-ice surveys. 

Recent technological advances in the development of 

lightweight sensors with improved sensitivity (Brown and 

Fingas, 2009) can augment the utility of these platforms 

through deployment of multi-sensor systems. For example, 

there are now efforts investigating the use of a tethered 

balloon to carry a visible and infrared surveillance system as 

a means of augmenting real-time spill monitoring capabilities 

(Prince William Sound Oil Spill Recovery Institute, 2009). 

In oil-spill response, a suite of these techniques is needed to 

accommodate the spatial and temporal (especially real-time) 

needs, as many factors, such as percent ice coverage and 

thickness, oil slick thickness, oil type and state of weathering, 

and weather conditions, affect the utility of these technologies. 

Several recent syntheses, including Dickins (2010), S.L. Ross 

Environmental Research, Ltd., and others (2010), Interagency 

Coordinating Committee on Oil Polution Research (2009), 

Brown and Fingas (2009), Jha and others (2008), Minerals 

Management Service (2008b), and Tebeau (2003), have 

documented advances in these technologies over the past 

decade. 

In a review of these technologies and their general 

effectiveness in response, DeCola and others (2006) noted that 

“estimates vary regarding the impacts of sea ice on 

spill surveillance and tracking. Response experts 

often use 50 percent ice coverage as a rule-ofthumb for defining the extent to which open water 

detection and mapping may be applied. When ice 

coverage exceeds 50 percent, methods such as visual 

observation become much less reliable because 

of problems in detecting the presence of oil in ice 

leads; however, remote sensing technologies may 

still apply.”
Chapter 5

Oil-Spill Risk, Response, and Impact 143

Some technologies require further testing under Arctic 

conditions. For example, a critical gap identified in spill 

response is the lack of capability to accurately measure and 

map the thickness of oil on water and to rapidly send this 

information to response personnel in the command post 

(Mineral Management Service, 2008b). World Wildlife Fund 

(2009) noted that the combination of multi-spectral aerial 

imagery and infrared detection shows promise for mapping 

oil slick thickness, but that these tools need further refinement 

under Arctic conditions and with specific Arctic oil types in 

order to better demonstrate their feasibility as an operational 

tool in Arctic oil-spill response. Similarly, DeCola and others 

(2006) stated that the 

“latest generation of high resolution radar satellites 

could be used to map large spills in an open pack 

condition, but radar signatures of new ice, oil, and 

calm water can be very confusing.” 

Several recent BOEMRE efforts focus on mapping the 

thickness of oil, including Bureau of Ocean Energy 

Management, Regulation and Enforcement (2011b).

In a study of ground penetrating radar (GPR), D.F. 

Dickins Associates (2005) found that, at frequencies above 

800 MHz, GPR yielded clear, well defined frequency, phase, 

and amplitude anomalies where oil was known to be present 

at the ice/water interface and trapped within ice tested under 

lab conditions. The agreement of experimental results with 

initial modeling indicates the potential to accurately predict 

GPR response to a variety of Arctic spill scenarios and radar 

parameters. 

Overall, the results clearly demonstrate the potential for 

detecting oil under sea ice with GPR. Measurements with 

GPR and airborne radar were conducted over an intentional 

oil spill in Svea, Svalbard, Norway, in April 2006 and in April 

2008 (Dickins and others, 2008). The overall results from 

two field tests are very promising in that they indicate that 

GPR using currently available systems is capable of detecting 

and mapping oil in ice over a broad operational time window 

from early to late winter, typically November to April in the 

Beaufort Sea area. This timeframe covers approximately 

70 percent of the nearshore fast ice season in most years. 

The current generation GPR is capable of mapping oil under 

or trapped within growing winter ice from 30 to 210 cm. 

Minimum oil thickness detection limit appears to be roughly 

2 cm. 

Airborne radar also was tested and found to detect oil on 

frozen ground under snow and oil encapsulated in or under 

fresh ice. The test also showed that radar can detect oil in 

and under first year ice with relatively even top and bottom 

surfaces. Detecting oil through multi-year ice or rafter/ridged 

first year ice is expected to be difficult because of the voids 

and jumbled blocks of rough ice which may scatter the radar 

signal in many different directions.

The time of year also may be important to the detection 

of oil on or under ice. The overall results from a Dickins and 

Bradford (2008) study of airborne radar system capabilities in 

selected Arctic spill scenarios indicate that currently available 

systems are capable of detecting and mapping oil in ice over a 

broad operational time window in the Beaufort Sea area. The 

most reliable months for detection are January and February 

with results in November, December, and March depending on 

the internal brine volume of the ice (combination of salinity 

and temperature). There are still challenges in detecting oil 

early in the winter with thin, high salinity ice sheets (October) 

and in the spring (May/June) with warm thick ice having a 

high volume of liquid brine. During these periods, higher 

powered radar systems and (or) a corresponding improvement 

in signal to noise ratios would need to be developed to cover 

the beginning and end phases of the ice cycle. Detection of 

trapped oil is not as critical during May and June, however, 

as the oil will naturally surface through the porous ice and 

provide a clear visual indication of the presence of residual 

trapped oil. 

Based on previous work, there are limited prospects for 

developing operational radar based systems to detect oil in 

sea ice that is floating, but not bottom fast ice. The optimum 

direction for future radar research and development needs to 

focus on systems that can evolve into practical operational 

devices, readily deployed and maintained in Arctic conditions. 

Future tests need to combine both laboratory and field trials 

with oil spilled under ice. A sole reliance on laboratory or 

tank tests will not provide an adequate basis for developing 

operational systems for future use. 

Satellite imagery also is an important component and can 

inform oil-spill response and other operations in the Arctic, 

although radar systems are the most practical because of their 

ability to be used during both the day and the night, and during 

most cloud cover conditions. For example, as part of the JIP 

Oil-in-Ice project to assess the overall capabilities of Synthetic 

Aperture Radar satellites to detect oil spills in ice and monitor 

ice conditions, Babiker and others (2010) commented that 

high quality ice information and all-weather satellite coverage 

is viewed as essential by most companies with operators in 

the Arctic. Regular satellite surveillance minimizes the need 

for floating rigs to disconnect riser and drill string in response 

to advancing ice features and reduces spill risk. In addition, 

seismic surveys may be completed more efficiently by taking 

into account ice conditions. 
144 An Evaluation of the Science Needs to Inform Decisions on Outer Continental Shelf Energy Development in the Chukchi and Beaufort Seas, Alaska

The most effective solution may not be a single sensor, 

but rather could require the integration of several different 

technologies (Brown and Fingas, 2009). In a recent review 

of the state-of-knowledge regarding airborne remote sensing, 

Dickins and Andersen (2010) noted that multi-spectral remote 

sensing, when supplemented by visual observation from 

trained observers, is presently the most effective method for 

detecting and mapping the presence and spatial distribution 

of oil on water. There have been many recent studies to test a 

variety of sensors under different conditions. In their review, 

Jha and others (2008) stated that laser fluorosensors were 

5.19. Recommendation:

1. For spilled oil detection in and (or) under ice, two avenues stand out as the likely focus of future development: acoustics (including the potential 

use of ultrasound), and electromagnetic (primarily the wave domain systems commonly referred to as impulse radars or ground-penetrating 

radars). Further testing could be pursued in both these areas. Continued development of practical operational systems for detecting oil in or 

under ice will be extremely challenging. It is recommended that the latest evolution of the acoustic system first tried in the 1980s be tested over 

a realistic mix of first year sea ice under field conditions. At the same time, it would be valuable to test the capabilities of the latest generation 

of ground-penetrating radars in areas of bottom-fast ice where the interface is ice to frozen sediment rather than ice to water.

2. Of the sensors currently available, the laser fluorosensor appears to hold the most promise, given its potential to detect oil in the presence of ice 

and snow. However, to facilitate broader use of this sensor and its incorporation into multi-sensory packages that can be deployed from a variety 

of platforms, a reduction in the size and energy consumption—requiring advances in solid-state laser technology—of these systems is critical 

(Brown and Fingas, 2009).

3. More work is needed on testing of multi-sensor systems to inform remote-sensing operations for spill response. In particular, expanded testing 

of unmanned aircraft systems is needed to augment observations from trained observers.

4. Research is needed to enhance satellite remote sensing and surface validation capabilities, including development and (or) refinement of 

satellite-based oil detection algorithms for ice-covered areas.

5. Assessing system performance under real-world conditions during a future offshore controlled spill exercise is seen as a critical need. Such an 

exercise would provide information essential to refining these capabilities from an operational standpoint.

5.19. Finding: There are numerous technologies available for use in detecting and tracking oil spills on open water and in or under sea ice, with 

varying levels of detection and spatial resolution. Improvements have been made to individual sensors over the past decade; these improvements 

are documented in a number of available syntheses. Of these, the laser fluorosensor is among the most highly regarded in terms of ability to detect 

oil in certain snow and ice conditions (Brown and Fingas, 2009). However, there is consensus in the scientific and response communities that no 

single sensor or approach is sufficient to address all the needs for effective Arctic oil-spill response, particularly given other challenges, such as 

long hours of darkness and the presence of sea ice. In this regard, high quality ice information and all-weather satellite coverage are viewed as 

essential by most Arctic operators (Arctic Council, 2009). Given the limitations for each individual type of sensor, packages of multi-sensor systems 

appear to hold the most promise for versatile and comprehensive remote sensing. Hence, there is growing emphasis on the development of multisensor systems that can be deployed from a variety of platforms.

the best available sensor for oil-spill surveillance, given the 

ability to detect oil against many backgrounds, including ice 

and the shoreline. However, the authors cautioned that no 

single sensor is capable of providing all requisite information 

needed to support an effective oil-spill surveillance operation. 

Advances in technology also may be needed to produce 

smaller, less energy-intensive systems that could be installed 

on smaller airframes that are more widely available and (or) 

affordable to oil-spill responders and government regulators 

(Brown and Fingas, 2009).
Chapter 5

Oil-Spill Risk, Response, and Impact 145

Field Trials and International Coordination

The National Research Council (1994) recommended 

“the design and completion of one or more 

experimental oil spills in the general area of the 

Chukchi and Beaufort Seas. We believe that 

experimental spills are essential because they 

can contribute to the scientific understanding of 

processes, and fill data gaps, about the interaction 

of ice and oil. These tests also can contribute to 

accurate assessments of the abilities and limits of 

countermeasures, and remediation and restoration 

procedures. The data from recent tests should be 

evaluated. Carefully controlled field tests would be 

an invaluable extension of such work into a realistic 

environmental setting.” 

This finding appears to remain valid today. The lack of any 

consistent regulatory framework to facilitate field trials with 

oil represents a critical science and technology obstacle to 

achieving real progress in the field of at-sea spill response. 

Most significant technical advances in Arctic spill response 

can be attributed to a series of highly successful field trials 

with oil carried out in U.S., Canadian, and Norwegian waters. 

Many of these trials have involved moderate-size releases at 

an affordable cost and have been carried out safely and in an 

environmentally responsible manner with a high degree of 

confidence, through a rigorous process of program design and 

execution. A major point regarding the near-term possibilities 

for new field trials with oil revolves around the likelihood of 

obtaining appropriate permits for such experimentation (D.F. 

Dickins and Associates, 2004). Permits, obtainable in Canada 

and Norway, are considered unlikely in the United States 

given that all permit applications have been declined during 

the last 10 years and no spills in U.S. waters for experimental 

purposes have been allowed for nearly two decades. 

Certainly the previously discussed JIP efforts represent 

a strong international science and technical collaboration. 

In addition, at a government level, the Emergency 

Prevention Preparedness and Response (EPPR) Working 

Group establishes a framework for future cooperation in 

responding to the threat of environmental emergencies in the 

Arctic. The EPPR works within the Arctic Environmental 

Protection Strategy (AEPS), which was adopted by Canada, 

Denmark/Greenland, Finland, Iceland, Norway, the Russian 

Federation, Sweden and the United States through the 

Ministerial Declaration at Rovaniemi, Finland in 1991. The 

other working groups within AEPS are the Arctic Monitoring 

and Assessment Program, Protection of the Arctic Marine 

Environment, Conservation of Arctic Flora and Fauna, and 

Sustainable Development and Utilization. The EPPR Working 

Group provides a forum in which member governments and 

indigenous peoples work to better prevent, prepare for, and 

respond to environmental threats from discharges of pollution 

from activities which take place in the Arctic. The EPPR 

operates through a system of National Contacts and meets at 

least annually to assess progress and to develop EPPR Work 

Plans. EPPR efforts include risk analyses; response exercises 

for emergencies such as radiological accidents and major 

oil spills; assessing environmental agreements; evaluating 

warning systems and communication networks; and sharing 

experience and technical information, including research and 

development data.

While not in Arctic waters, CANUSDIX, an effort 

between Canada and the United States, is a unique annual 

exercise held near Dixon Entrance, at the southern tip of 

the Alaskan panhandle and is an example of an innovative 

combination of spill scenarios, training workshops, equipment 

deployment, and coordinated multi-year planning (for 

example, see Canadian Coast Guard, 2010). Like the Arctic, 

coordinated planning and exercising by partner agencies are 

a necessity for Dixon Entrance, an environment that also is 

remote, environmentally sensitive, and characterized by severe 

weather and limited infrastructure (Gardner and others, 2008). 

5.20. Recommendation: Efforts to conduct exercises such 

as CANUSDIX and “Sound Predictions” in the Arctic could 

significantly advance understanding of the tactical science and 

information issues that must be addressed. Even if there is not 

a broader acceptance of conducting actual oil-spill field trials, 

having scientific protocols in place to take advantage of “spills of 

opportunities” are essential.

5.20. Finding: Exercises such as CANUSDIX, an annual 

emergency response exercise between Canada and the United 

States near Dixon Entrance at the southern tip of the Alaskan 

panhandle, and the previously discussed Alaska Ocean Observing 

System’s and others ”Sound Predictions” effort in Prince William 

Sound, Gulf of Alaska, provide practical means to not only identify 

operational weaknesses but are the only existing practical tools 

to routinely determine if and what model, real-time data, and data 

management uncertainties and weaknesses significantly affect 

desired operational outcomes. 
146 An Evaluation of the Science Needs to Inform Decisions on Outer Continental Shelf Energy Development in the Chukchi and Beaufort Seas, Alaska

Natural Damage Assessment, Recovery, and 

Restoration Phase 

Background

Discussed in this section are those research needs 

required to defensibly assess resource injuries, recovery 

progress, and restoration approaches should oil be released. 

Our intent is not to suggest that a spill is likely, but to think 

through such a scenario in a very broad sense and identify 

approaches and types of scientific information that might 

reduce societal uncertainties about government capacity to 

deal with the consequences of oil spills in the Beaufort Sea or 

Chukchi Sea Planning Areas. 

The primary legal framework to determine resource 

damage is vested within the Natural Resource Damage 

Assessment (NRDA) process. The NRDA generally is 

implemented in three phases, which require the natural 

resource trustees, which in the case of a spill in the Beaufort 

or Chukchi Seas include the State of Alaska, NOAA, and the 

Department of the Interior (DOI), to: 

1. Determine whether injury to public trust resources 

has occurred (Preliminary Assessment); 

2. Quantify injuries and identify possible restoration 

projects (Injury Assessment/Restoration Planning); 

and 

3. Implement restoration strategies and monitor 

effectiveness of such actions.

These are straightforward in language but as stated by the 

National Oceanic and Atmospheric Administration (2011):

“Although the concept of assessing injuries may 

sound simple, understanding complex ecosystems, 

the services these ecosystems provide, and the 

injuries caused by oil and hazardous substances 

takes time—often years. The season the resource 

was injured, the type of oil or hazardous substance, 

and the amount and duration of the release are 

among the factors that affect how quickly resources 

are assessed and restoration and recovery occurs. 

The rigorous scientific studies that are necessary 

to prove injury to resources and services—and 

withstand scrutiny in a court of law—also may take 

years to implement and complete.”

It is unlikely that even with foreknowledge of where 

and when an oil spill might occur the suite of baseline 

information useful to NRDA would be fully available (for 

example, population, physiological, or toxicological). This 

is particularly true for the Arctic OCS because of the suite of 

physical and ecological uncertainties discussed throughout 

this report, as well as the practical challenges inherent in 

Arctic research in general. Here, because of the nature of our 

assignment, we have not attempted to review the scientific 

literature that would inform the likely exponential suite of 

possible scenarios and associated potential injured resources 

that would inform the NRDA-related activities. Instead, we 

examine strategic science and approach capacities in the 

Arctic and potential gaps in those capacities that might be 

informative. We also take advantage of insights gained from 

the 1989 Exxon Valdez oil spill (appendix D) in Prince William 

Sound, Alaska (http://www.evostc.state.ak.us/ website, 

accessed May 11, 2011), and the more recent Deepwater 

Horizon oil spill in the GOM to inform our assignment. 

Scenarios and Science Planning

Both the Exxon Valdez oil spill and the 2010 Deepwater 

Horizon oil spill demonstrate the logistical, technical, and 

scientific challenges of responding to rare, but significant 

events. The success of the NRDA process, particularly in the 

“Preliminary Assessment” stage is dependent on the rigorous 

collection of time critical and (or) ephemeral information. 

Previous large oil spills have demonstrated that access to 

immediate post-spill survival, physiological, behavioral, 

toxicological, and habitat information could have improved 

the ultimate level of confidence in NRDA findings. Despite 

previous lessons learned from the Exxon Valdez oil spill, 

coordinated science plans for the integrated collection of 

critical data needed for NRDA-related activities have not been 

prepared in the areas of proposed development. A coordinated 

joint State–Federal Gulf Coast Ecosystem Restoration Council 

to inform strategic and efficient restoration efforts into the 

future has been proposed (Recommendation E6: National 

Commission on the BP Deepwater Horizon Oil Spill and 

Offshore Drilling, 2011) as was the case after the Exxon 

Valdez oil spill; however, the opportunity to collect much of 

the time critical data will be past before such establishment. 

In the case of the Deepwater Horizon oil spill, the region had 

fairly easy and robust access to scientific capacities (multiple 

Federal and State laboratories, academic specialists), extensive 

citizen volunteers to help capture early resource mortality 

data, and community infrastructure (for example, boats), all of 

which improved the likelihood that critical early post-spill data 

were captured. The Arctic OCS and coastal environment is not 

similarly positioned. 
Chapter 5

Oil-Spill Risk, Response, and Impact 147

Although the Exxon Valdez oil spill is scientifically 

informative for many aspects of our later discussions, it was 

a spill that occurred from tanker grounding rather than from 

drilling activities. Thus, contemporary environmental studies 

of the nature produced through the BOEMRE Environmental 

Studies Program for the Arctic OCS described previously 

were not available. The spill also occurred after a period 

of ocean climate regime shift (for example, Anderson and 

Piatt, 1999), whose consequence to effective injury and 

recovery assessment was not well understood for some time 

into restoration efforts. In that regard, our existing scientific 

foundation and progress towards expanded understanding 

of the distribution of species, potential fate and effect of oil, 

and the nature of environmental change (including changing 

climate scenarios) could be argued to be more robust than 

was available for Prince William Sound in 1989. There is the 

current effort invested in environmental studies under the 

BOEMRE, project efforts by industry (for example, Funk and 

others, 2010), the agency mission-specific monitoring ongoing 

at both Federal and State levels, and the broad collation and 

synthesis efforts by many parties (for example, Smith, 2010). 

The existing Oil Spill Risk Assessment (OSRA) 

framework described earlier, while at some level limited 

because of the qualitative manner in which ecological 

information is presently incorporated, does provide 

information on likely landscapes and resources affected under 

simulated spills. This foundation is valuable and provides 

information useful to better understand and narrow the range 

a priori of likely NRDA injured resources under the various 

oil-spill scenarios. 

In the report prepared by Integral Consulting Inc. (2006) 

for the Exxon Valdez Oil Spill Trustees Council, scientists who 

gained experience from the Exxon Valdez oil spill provided 

a strong foundation for understanding the types of scientific 

information needed to assess recovery status, lingering oil 

impacts, and restoration progress to inform what types of “prespill” data should be readily available (fig. 5–9). Information 

on population characteristics (for example, abundance and 

productivity, physiological metrics, and habitat) and exposure 

metrics (for example, bioaccessibility, exposure pathways, and 

biomarkers) all must come together in a weight-of-evidence 

to inform NRDA activities (Integral Consulting Inc., 2006, 

fig. B–4).

5.21. Finding: The remoteness of the Arctic OCS, the small 

resident population, and limited community infrastructure likely 

would limit the probability of early science responses that were 

seen during the Deepwater Horizon or Exxon Valdez oil spills, 

resulting in the loss of time-critical data informative to Natural 

Resource Damage Assessment. 

5.21. Recommendation: The development and pre-positioning 

of a multi-agency coordinated Oil Spill Science Contingency Plan 

could potentially mitigate some of the challenges inherent in 

spill response in the Arctic. The planning process itself would be 

valuable by identifying what skills and protocols exist or need to be 

developed. The Deepwater Horizon oil-spill response demonstrated 

the need for local citizen engagement in sample collections. 

This is likely more true in the Arctic, due to access limitations. 

Local community members could be the first available on scene. 

Consideration of a “Citizen Scientist” program as a component of 

Science Contingency Plans might be fruitful.

5.22. Finding: The Oil Spill Risk Assessment (OSRA) process 

employed by the BOEMRE provides information to help define 

where natural resources might be exposed to oil under various 

spill scenarios. 

5.22. Recommendation: A strategic follow-on analysis to the 

present Environment Resource Area OSRA that would examine 

the state of knowledge of specific NRDA metrics (for example, 

see fig. 5–9) could help identify specific population, physiological, 

habitat, and exposure data for future NRDA activities. This would 

help establish priorities for needed science under BOEMREfocused planning as well as ongoing efforts by science and 

resource agencies.
148 An Evaluation of the Science Needs to Inform Decisions on Outer Continental Shelf Energy Development in the Chukchi and Beaufort Seas, Alaska

Population Characteristics Physiological/Behavioral Metrics Habitat Metrics

• Abundance/Productivity

• Spatial/Temporal Structure

• Genetic/Phenotypic Diversity

Examples

• Condition

• Enzymes

• Activity Budgets

Examples

• Tidal Height

• Substrate Type

• Macrophytes

• TOC

Other Stressors

Examples

• Climate Change

• Earthquake

• Predators

• Industrial Releases

Baseline

Reference Data

Habitat

Community

Context Signicant

Eects

Relative to

Baseline?

Resource

Recovered

Resource

Status Uncertain

Resource Not

Recovered

Results of Population

and Exposure

Analysis

Population Model

Time to Recovery

Other Stressors

Examples

• Climate Change

• Earthquake

• Predators

• Industrial Releases

Residual Eects of

Initial Impact

Manage Eects of

Other Stressors

Lingering Oil Eect

Sucient

Time for

Recovery?

Eect of

Other

Stressors?

Y

Y

Y

N

N

?

N

Figure 5–9. Factors incorporated into population level evaluations of recovery status (modified from 

Integral Consulting Inc., 2006, figs. B3 and B5). TOC, total organic carbon; N, No; Y, Yes.
Chapter 5

Oil-Spill Risk, Response, and Impact 149

Integrated Monitoring and Process 

Understanding

As discussed elsewhere in our report, there are high 

accumulated uncertainties associated with any development 

activity in the Arctic and what science is “essential” to 

informing decisions. In addition to project uncertainty, 

climate changes may affect the relevancy of historical data 

to future decisions, and there is a huge spatial extent under 

consideration. Thus, having the “right” science, at the “right” 

time, and at the “right” scale is problematic. In such an 

environment, there may be great value to a more aggressive 

science strategy to integrate sampling approaches to ultimately 

improve inferences from sampling available at one scale 

to another, or one time or location to another. As discussed 

above, the same could be said for the ability to develop a full 

pre-understanding of all the essential NRDA metrics for each 

potential injured resource (or resource being examined in 

pre-decisional leasing documents). Here, we discuss several 

elements of this challenge and potential approaches to provide 

some level of mitigation.

Several existing study programs for the Beaufort and 

(or) Chukchi Seas serve as examples of approaches that may 

provide the framework for improving our ability to scale 

understanding from one level to another. The BOEMRE has 

undertaken a wide variety of integrated monitoring efforts 

over the last decade. These include: 

1. ANIMIDA, the “Arctic Nearshore Impact 

Monitoring in the Development Area” study 

designed to assess potential environmental 

contaminant inputs from Beaufort Sea oil and gas 

development and its continuation cANIMIDA (for 

example, Boehm, 2001; Neff and Associates, LLC, 

2010), and 

2. COMIDA, the “Chukchi Sea Offshore Monitoring 

in Drilling Area” effort which conducts an extensive 

multi-study examination of the environment. 

Both these efforts provide a mid-scale view of environmental 

background conditions associated with prospects. When 

coupled with the more detailed prospect-specific industry 

efforts such as those in the Chukchi Sea Lease Area, 

significant process and scaleable information could be 

generated informative to both permitting and future NRDA 

needs (fig. 5–10). 

Another approach that is likely valuable in the effort 

to better generate and understand factors critical to NRDA, 

particularly in a changing climate, is formal integrated 

multidisciplinary monitoring and process studies. The 

Exxon Valdez oil spill can be used as an example to gain 

perspective—more than 30 biological resource types were 

considered to be injured by the Exxon Valdez Oil Spill 

Trustee Council during the Exxon Valdez Oil Spill NRDA 

process (Exxon Valdez Oil Spill Trustee Council, 2001) with 

the majority recovered or recovering and four viewed as not 

recovered or recovery unknown by 2010 (Exxon Valdez Oil 

Spill Trustee Council, 2010). The challenge faced by the 

Trustee Council to judge recovery was largely due to: 

1. Variability in population estimates as a result of 

highly mobile fish, birds, and marine mammals 

causing wide confidence limits for population size 

estimation; 

2. Lack of pre-spill data; 

3. Interaction of the spill and other natural factors 

(for example, climate) that constrained the ability 

to judge the role of oil in population status; and 

4. Geographic scale of studies conducted both before 

and after the spill which ranged from scales to 

assess populations to others keyed to localized 

effects and oil exposure. 

To compensate for incomplete information, injury often 

was inferred from comparisons of oiled and unoiled areas, 

with recovery defined as a return to conditions comparable 

to those of unoiled areas. Confidence in such designs is 

limited because of natural variability among sites oiled and 

unoiled prior to a spill. Ultimately, efforts turned towards 

the development of ecosystem-based integrated studies 

to attempt to better establish population status relative to 

recovery and factors still constraining recovery through 

a weight-of-evidence approach across suites of species 

whose status remained uncertain (Exxon Valdez Oil Spill 

Trustee Council, 1994). Efforts like those described in 

Peterson and Holland-Bartels (2002) for a suite of species 

whose recovery status was still uncertain or deemed nonrecovered after extensive study and some 5 years after the 

oil spill highlight that coordinated multi-species sampling 

and coupled hypothesis-driven studies can mitigate many 

weaknesses in incomplete pre-spill data. Efforts such 

as those proposed by Grebmeier and others (2010) for a 

Distributed Biological Observatory (DBO) or underway in 

the Bering Sea and Aleutian Island Integrated Ecosystem 

Research Program (BSIERP, http://bsierp.nprb.org/) of 

the North Pacific Research Board and National Science 

Foundation offer examples of approaches that could well 

serve the full suite of interested parties and their decisionmaking requirements that cascade out of DOI OCS 

decisions. 
150 An Evaluation of the Science Needs to Inform Decisions on Outer Continental Shelf Energy Development in the Chukchi and Beaufort Seas, Alaska

tac11-5179_fig4-08

0 20 40 60 80 10

Nautical Miles

Chukchi Sea Environmental Studies Program

2010 Study Areas

STATOIL

BURGER with 2009 survey lines

KLONDIKE with 2009 survey lines

B

Stations occupied with epibenthic trawl (n=30)

Other stations occupied (n=18, n=48 total)

Lease sale 193 area

Sale 193 Blocks Bidded

Prospects

COMIDA 2009 Study Areas

COMIDA and Industry Field Studies

1

5

Base map and study

sites COMIDA 2009

CSESP study areas

from Day et al. 2010

5

2

1

3

4

6

7

8

9

10

12 13

14

15 16

18

19

20

21

22

23

24

26

27

28

29

D

33

34 35

36 37

38

42

43

44

45

46

47

48 50

39

31 32

40

30

25

11

17

Figure 5–10. Example of the BOEMRE-sponsored COMIDA sampling and the more spatially detailed industry-sponsored sampling 

(modified from Dunton, 2010; Day, 2010). 

5.23. Finding: Significant advances have taken place with the 

COMIDA (“Chukchi Sea Offshore Monitoring in Drilling Area”) 

and cANIMIDA (“continuation of the Arctic Nearshore Impact 

Monitoring in the Development Area”)-like efforts funded by the 

BOEMRE and the more spatially detailed efforts by industry. Such 

efforts individually provide critical information on ecosystems, 

potential anthropogenic effects from development, and climate 

factors. 

5.23. Recommendation: The benefits from these individual 

efforts to improve scientifically defensible inference of findings 

to different geographic and temporal scales could be significantly 

enhanced through additional focused coordination and joint study 

planning. Discussions in a workshop format to outline specific 

experimental designs presently employed and to discuss fruitful 

efforts to link study efforts might be beneficial as one approach.
Chapter 5

Oil-Spill Risk, Response, and Impact 151

The DBO (fig. 5–11), as envisioned by 

Grebmeier and others (2010), would provide a 

monitoring and experimental framework:

“...to detect, measure, and track 

the combined effects of changing 

oceanographic conditions on 

the ecosystem....[with] holistic, 

integrating measurements of basic 

oceanographic variables [and] 

with data on species- and trophic 

level interactions, from primary 

producers to marine mammals...

The DBO is envisioned as an array 

to identify and consistently monitor 

biophysical responses in four pivotal 

geographic areas that exhibit high 

productivity, biodiversity, and rates 

of change. ...The DBO would 

support a suite of in-situ time-series 

measurements to evaluate ecosystem 

status, supplemented by satellite 

observations. Sea ice observations 

include ice and snow thickness and 

biological sampling to evaluate 

changes to productivity in sea ice 

systems and habitat sustainability 

for predators.”

A DBO approach, which would bring 

value to resource missions beyond that 

required by the BOEMRE, would require 

a concerted multi-agency and international 

planning effort. However, once established, 

a DBO might provide a critical and essential 

complement to mission-specific sampling by 

the BOEMRE and species studies by NOAA, 

U.S. Fish and Wildlife Service, and (or) the 

State of Alaska. This is particularly true as 

climate is hypothesized to force significant 

ecosystem-level changes that will require 

rigorous understanding if they are to be 

defensibly incorporated into OCS-specific 

or the broad array of other agencies mission 

considerations.

tac11-5179_fig4-09

Figure 5–11. Schematic of the location of the proposed Distributed Biological 

Observatory for standard hydrological and biological measurements in the Bering, 

Chukchi, and Beaufort Seas (Grebmeier and others, 2010). 

5.24. Finding: The Arctic environment is highly variable both 

physically and biologically. Here, it is difficult to conduct and 

maintain the suite of individual surveys and sampling efforts of 

ecosystem components at sufficient levels to understand potential 

future impacts from development. As was demonstrated in the 

Exxon Valdez Trustee Council recovery science efforts, this is 

particularly true for information needed to establish population 

status. 

5.24. Recommendation: The Distributed Biological 

Observatory concept is one that holds significant scientific promise 

to mitigate some of the major constraints to a defensible science 

framework for critical Arctic decision making. 
152 An Evaluation of the Science Needs to Inform Decisions on Outer Continental Shelf Energy Development in the Chukchi and Beaufort Seas, Alaska

Finally, the conceptual approach used by the North 

Pacific Research Board in its BSIERP, which considers 

commercial fishery research within the context of an 

ecosystem framework, offers another successful approach to 

understanding anthropogenic factors in the context of complex 

ecosystems and changing environments (North Pacific 

Research Board, 2006). The BSIERP was envisioned to 

address scientific challenges to effective fishery management 

associated with expected changes in the ecosystem such as:

• “Physical phenomena (for example, weather patterns, 

sea ice characteristics, transport, mixed layer 

dynamics, temperature, nutrient fluxes);

• Composition, abundance, distribution, and 

demographic parameters of biological components 

from plankton to seabirds and marine mammals;

• Strength of existing predator-prey linkages and 

development of new linkages; 

• Human strategies for resource extraction, 

transportation, and community adaptation.” 

This effort considered hypotheses that included how the 

distributions and abundances of species might be changing; 

characteristics of physical and chemical attribute change; 

changes in lower trophic level production; processes 

controlling energy pathways; the role of climate change in 

these processes; and the economic and sociological impacts 

of a changing ecosystem on the coastal communities and 

resource users of the Bering Sea. The concepts and the 

efficient approaches forwarded under the BSIERP (fig. 5–12) 

are appealing when considering the functionally similar 

challenges of resource decision making for the Arctic. 

tac11-5179_fig4-11

Figure 5–12. Conceptual design of the North Pacific Research 

Board Bering Sea and Aleutian Island Integrated Ecosystem 

Program. Graphic available at: http://doc.nprb.org/web/BSIERP/

zzWebsite/proj_mgmt/01.10_bsag_web.pdf, accessed March 8, 

2011.

5.25. Finding: Similar to findings 5.23 and 5.24, the nature of 

resource variability and uncertainty in the Arctic challenges the 

development of the full suite of scientific information needed 

by decision makers and vested parties relative to resource 

management in the Arctic. 

5.25. Recommendation: The BSIERP (North Pacific Research 

Board-National Science Foundation Bering Sea and Aleutian 

Island Integrated Ecosystem Research Project) and the DBO 

(Distributed Biological Observatory) concepts and enhanced 

industry-COMIDA (“Chukchi Sea Offshore Monitoring in Drilling 

Area”)-like efforts offer the potential to create a transparent and 

scientifically rigorous study framework to support and enhance 

existing BOEMRE and other organizational interests in the Arctic.

As a final consideration, any of these larger integrated 

approaches, as well as the existing BOEMRE program, 

requires input from many other resource programs. Should 

these efforts be lost or reduced, the science-based decision 

making about oil and gas development in the Arctic may be 

compromised. For example, Grabmeier and others (2010) 

discuss that the DBO would require collaboration and joint 

data collection with vessel cruises through the Pacific Arctic 

Group network of governments and scientists working in the 

Pacific Arctic, inclusion within international Sustaining Arctic 

Observing Networks, and (or) Arctic Council (website: http://

www.arctic-council.org/, accessed May 10, 2011) efforts. 

The BSIERP, as mentioned previously, is a close partnership 

with the National Science Foundation with strong in-kind 

funding leverage from mission work from many State and 

Federal agencies. Thus, not only is the support for new 

collaborations key to developing enhanced insights for oil 

and gas development in the Arctic, but also the maintenance 

of core agency mission work. One only has to turn to the 
Chapter 5

Oil-Spill Risk, Response, and Impact 153

environmental documents of the BOEMRE (for example, 

Minerals Management Service, 2006) or to the data sources 

that were the basis of “The Arctic Marine Synthesis: Atlas 

of the Chukchi and Beaufort Seas” document (Smith, 2010) 

to capture the critical nature of core mission work of other 

Federal and State agencies. The amount of such existing work 

is encouraging, but the general quality as defined by spatial 

and temporal coverage should be increased (appendix E, 

table E–1).

5.26. Finding: The information that presently supports sciencebased decision making on oil and gas development in the Arctic 

comes from both the topic-focused work of agencies such as 

BOEMRE, and the efforts of broader agency-specific mission work 

of many Federal, State, community, and nongovernmental entities. 

5.26. Recommendation: The ability to develop oil and gas 

resources in as safe and environmentally sound a way as feasible 

relies on many data sources outside the formal annual planning 

process of the BOEMRE. Understanding the potential jeopardy 

these data collections might be in across organizations because of 

different planning processes and national and regional priorities, 

and development of a strategic collaboration to maintain and 

enhance such scientific efforts could prove valuable. Such 

information could be identified as part of an overall science plan.

Oil-Spill Risk, Response, and Impact Under 

Future Climate Considerations

In Chapter 4, Climate Change Considerations, the authors 

discuss how physical characteristics important to oil-spill risk, 

response, and impact may change under climate forecasts 

in the next 50 years. A number of significant changes are 

expected to occur in the physical environment of the Beaufort 

and Chukchi Seas. Some of these changes will stress the 

biological systems that are so highly adapted to the extreme 

conditions of this region. These changes are also expected 

to affect the environment in which Arctic OCS exploration 

and development activities occur. Some climate changes will 

mitigate the environmental risks of energy development in the 

region, while others will compound them. The interactions 

between future climate change over the next 50 years and 

potential energy development within the Arctic OCS are 

described briefly in the following paragraphs.

• Temperature: Extremely cold temperatures are cited as 

a factor contributing to the risk of accidents and spills. 

The large warming projected to occur within the Arctic 

OCS during autumn and winter is expected to reduce 

the risk of accidents and spills during those seasons, as 

is the more modest warming during spring. 

• Sea Ice: The Chukchi and Beaufort shelves are 

expected to be ice-free for a greater period of time 

each year. This will reduce the portion of the year 

when the presence of sea ice may contribute to the 

risk of accidents resulting in spills, and will increase 

the time when spill sites will be accessible to vessels 

without icebreaking capabilities. Mechanical devices 

for recovering oil (booms, skimmers, pumps) may 

function more effectively for a greater part of the year. 

However, sea ice will still be present throughout winter 

and spring. With its projected reduced thickness, the 

ice pack will be more dynamic, increasing the risk 

of spill-producing accidents during these seasons. 

Oil-spill response may be more difficult in the more 

dynamic sea-ice environment.

• Clouds: The increasing prevalence of low-level clouds 

and fog during the open-water season will increase 

the occurrence of poor-visibility conditions during 

summer and autumn. In addition, these poor-visibility 

conditions are expected to occur over a greater fraction 

of the year, extending into late autumn. Poor visibility 

is a factor that increases the risk of accidents resulting 

in oil spills, makes vessel and aircraft operations 

extremely dangerous, increases the response time of 

vessels and aircraft trying to respond to an accident 

or spill, hampers onsite spill response operations 

once the needed equipment and personnel arrive, and 

makes it difficult to monitor the location and condition 

of a spill by using aircraft. The projected increase in 

high-level clouds (all seasons) compounds the problem 

by limiting satellite-based surveillance. In contrast 

to summer and autumn, the occurrence of low-level 

clouds and fog is not projected to change substantially 

during winter or spring.

• Icing Conditions: Icing conditions present a significant 

hazard in the Arctic, both to personnel and equipment. 

These conditions are expected to occur more 

frequently during autumn. Icing conditions increase the 

risk of accidents resulting in oil spills, make aircraft 

operations extremely dangerous, increase the response 

time of aircraft trying to respond to an accident or 

spill, and hamper onsite spill response operations once 

the needed equipment and personnel arrive. This is 

primarily an autumn phenomena, and is not expected 

to increase risks during winter, spring, or summer.
154 An Evaluation of the Science Needs to Inform Decisions on Outer Continental Shelf Energy Development in the Chukchi and Beaufort Seas, Alaska

• Precipitation: The increasing frequency and intensity 

of precipitation (all seasons), as well as the number of 

wet days, may elevate the risk of accidents resulting 

in oil spills. Such conditions also may make it 

more difficult to respond to spills when they occur. 

Increased precipitation during winter and spring may 

contribute to the severity of ‘white-out’ conditions 

which greatly reduce visibility. The projected increase 

in precipitation is expected to reduce the salinity of 

the surface waters in the Beaufort and Chukchi Seas, 

potentially reducing the effectiveness of chemical 

dispersants applied to oil spills.

• Storms: A number of physical arguments suggest 

Arctic cyclones, including Polar Lows, will become 

more frequent and (or) more intense during autumn 

and winter. Although this projected change has not 

yet been rigorously tested (and so is uncertain), we 

note that there are no physical arguments to suggest 

storms will become less frequent and (or) less intense 

during these seasons. An increase in storminess during 

autumn and winter, if it occurs, will increase the 

risk of accidents resulting in oil spills if oil and gas 

operations are conducted during those seasons. Such 

storms would increase the frequency of strong winds 

(autumn, winter) and rough seas (autumn). High winds 

can prevent or hamper aircraft and vessel access to 

spill sites, adversely affecting spill response times. 

Mechanical recovery systems and ISB are hampered 

by high winds. Accurate application of chemical 

dispersants is more difficult during high winds. 

However, rough seas may enhance the effectiveness 

of chemical dispersants once applied to a spill. Rough 

seas, drifting pack ice, and storm surges may cause 

significant damage to offshore equipment, artificial 

islands, and onshore coastal infrastructure. At this 

time, there are no convincing arguments that storms 

will become either more or less frequent during spring 

or summer.

• Sea-Level Rise: Artificial islands and causeways 

built for offshore energy development will be 

increasingly vulnerable to inundation from sea-level 

rise and damage from storm surges. This risk can be 

substantially reduced through proper engineering that 

takes sea-level rise into account.

• Coastal Zone: Land-based infrastructure (for example, 

pipelines, storage tanks) designed to support offshore 

energy development will be much more vulnerable to 

damage due to sea-level rise, storm surges, permafrost 

degradation, and accelerated coastal erosion. Proper 

engineering and site selection may mitigate this risk to 

a large extent.

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164 An Evaluation of the Science Needs to Inform Decisions on Outer Continental Shelf Energy Development in the Chukchi and Beaufort Seas, Alaska

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Chapter 6

Marine Mammals and Anthropogenic Noise 165

Introduction

In the ocean realm, where vision often is limited by turbidity and darkness, 

marine mammals rely upon hearing as their primary sense. The scientific 

consensus is that audition is used in a wide range of activities, for example, 

to communicate, to forage, to hunt, to sense the environment, to navigate, to 

socialize, to seek mates, to find open water amidst ice, and to flee predators. 

Cetacean and pinniped auditory systems are adapted to exploit the ease with which 

sound travels in water—roughly five times faster than in air, and for far greater 

distances. For marine mammals, the oceans are relatively opaque to light, but 

transparent to sound. 

The oceans also are noisy places. Among the natural contributors to ocean 

ambient noise are wind, rain, waves, ice cracking, surf, earthquakes, volcanoes, 

lightning strikes, and biological sources including the wide array of sounds 

made by marine mammals. Superimposed on these sounds are manmade 

(“anthropogenic”) sounds from shipping, industrial activities, naval operations, 

marine research, aquaculture, and aircraft, among others. For the same reasons 

that marine mammals use sound for survival and reproduction, humans use sound 

as the most cost-effective and efficient tool for remote sensing and mapping of 

the seafloor and sub-seafloor to understand, among other issues, habitats and 

mineral and energy resources. The characteristics of all these sources of sound 

can be intermittent or sustained, loud or barely audible, and cover a wide range of 

frequencies (for example, Wenz, 1962). The Arctic Outer Continental Shelf (OCS) 

is one of the few relatively pristine regions on Earth where shipping and coastal 

community development is minimal. With the possible exception of the Prudhoe 

Bay region, the introduction of anthropogenic sound also has been minimal, 

because of the harsh ice-covered, cold, and remote location. Hence the Arctic 

offers the potential opportunity to understand the impacts of anthropogenic sound 

before animals have become widely sensitized, habituated, or disturbed by chronic 

manmade sounds.

Chapter

Marine Mammals and

Anthropogenic Noise 6 By Deborah R. Hutchinson and Richard C. Ferrero
166 An Evaluation of the Science Needs to Inform Decisions on Outer Continental Shelf Energy Development in the Chukchi and Beaufort Seas, Alaska

It has been recognized for some time that humangenerated noise has the potential to have deleterious effects 

on marine mammals (for example, Payne and Webb, 1971; 

Greene and Richardson, 1988; Richardson and others, 1995; 

Gordon and others, 2004; Southall and others, 2007; Tyack, 

2008, 2009). Elevated background noise from manmade 

sources may prevent animals from hearing sounds they use for 

their survival or reproduction (masking). Manmade sound may 

trigger behavior changes, such as avoidance or displacement, 

which interrupts normal activities. Loud sounds may cause 

temporary or permanent changes in hearing. Some sounds also 

may initiate physiological stress responses or even physical 

injury that could affect survival or reproduction. The great 

challenge in understanding these impacts is that studying wild 

populations of Arctic marine mammals is expensive, difficult, 

and sometimes dangerous. Furthermore, extrapolating limited 

observations from individual animals to understand longer 

term characteristics of a population is often more speculative 

than substantive. 

 The past two decades have witnessed a growth in 

concern about and research into human-generated sound 

in the oceans and its potential impacts on the health and 

sustainability of marine mammals. A synthesis book was 

published in 1995 (Richardson and others, 1995). Four 

National Research Council (NRC) reports have directly 

explored the association between anthropogenic noise and 

marine mammals (National Research Council, 1994, 2000, 

2003a, 2005). The Marine Mammal Commission also has 

published synthesis documents (Vos and Reeves, 2005; Marine 

Mammal Commission, 2007; Simpkins and others, 2007; 

Bradley and Stern, 2008). Additional syntheses have explored 

the effects of anthropogenic sound on marine mammals, 

including seismic studies (for example, Ketten, 1997; Popper 

and others, 1997; National Resources Defense Council, 1999; 

Au and others, 2000; Wartzok and others, 2004; Southall 

and others, 2007; Tyack, 2008; Marine Ecology Progress 

Series, 2009). Special studies have investigated the effects 

of oil and gas activities, particularly seismic experiments, on 

marine mammals (for example, National Research Council, 

2003b; Tolstoy and others, 2009); and a Joint Industry Project 

(JIP) on sound produced from exploration and production 

(E&P) developed a report identifying knowledge gaps and 

recommended research for anthropogenic sound and marine 

life (Thorson and others, 2005). Phase 2 of this JIP lasted 

from 2006 to 2009 with additional publications (International 

Association of Oil & Gas Producers, 2011) and a third phase 

began in January 2010. The U.S. interagency task force on 

Anthropogenic Sound and the Marine Environment issued an 

integrated research plan in 2009 (Southall and others, 2009). 

Since 2006, the Acoustic Ecology Institute has released annual 

summaries of science, policy, and legal developments related 

to ocean noise (Acoustic Ecology Institute, 2007). 

Marine mammals known to occur in the U.S. Arctic 

OCS include both year-round or seasonal inhabitants as well 

as a broader collection of occasional visitors. Cetaceans most 

notably associated with the Beaufort and Chukchi Seas include 

bowhead, beluga, and gray whales with less frequent sightings 

of harbor porpoise, and fin, humpback, and killer whales. Five 

pinniped species are found in these waters, including ringed, 

bearded, ribbon, and spotted seals, as well as Pacific walrus. 

Likewise, polar bears are found throughout this area. 

In this chapter, which focuses on the impacts of sound 

in the Arctic, we emphasize species that could potentially 

be affected at the population level (owing to more frequent 

occurrence than the occasional visit)—bowhead, beluga, and 

gray whales; ringed, ribbon, bearded, and spotted seals; Pacific 

walrus; and polar bears (table 6–1). In addition, several of 

these species warrant close attention given their legal status. 

Bowhead and fin whales have long been listed as endangered 

under the Endangered Species Act (ESA). The polar bear was 

listed as threatened in 2008 (U.S. Fish and Wildlife Service, 

2008) and in November 2010, the U.S. Fish and Wildlife 

Service (USFWS) further designated critical habitat for the 

polar bear (U.S. Fish and Wildlife Service, 2010). The gray 

whale was considered endangered until 1994, when it was 

delisted (National Marine Fisheries Service, 1994). Among 

the pinnipeds, National Marine Fisheries Service (NMFS) 

initiated an ESA consultation for the four Arctic seal species—

the ribbon seal (National Marine Fisheries Service, 2008a) 

and the spotted seal (National Marine Fisheries Service, 

2009a) did not warrant listing action for U.S. waters; however, 

in December 2010, NMFS proposed that the U.S. Arctic 

populations of the bearded (National Marine Fisheries Service, 

2010a) and ringed (National Marine Fisheries Service, 2010b) 

seals warranted threatened listings. USFWS recently published 

a finding for Pacific walrus of warranted but precluded under 

ESA (U.S. Fish and Wildlife Service, 2011).

Aside from these species or population specific 

considerations, this collection of marine mammals derives 

unique stewardship consideration through multiple layers 

of legislative mandate. The Marine Mammal Protection Act 

(MMPA), the Endangered Species Act (ESA), and the National 

Environmental Policy Act (NEPA) are important drivers in 

management decisions and the need for science to support 

them. Of these and with particular relevance to this report, 

NEPA particularly affects the Department of the Interior 

because of the regulatory responsibilities of the Bureau of 

Ocean Energy Management, Regulation and Enforcement 

(BOEMRE) for offshore oil and gas development. The 

National Oceanic and Atmospheric Administration (NOAA)/

NMFS and USFWS share responsibility for implementing 

MMPA and ESA, with a particular concern for authorizing 

activities that produce anthropogenic sound in the oceans.
Chapter 6

Marine Mammals and Anthropogenic Noise 167

Despite the research and interest in the impacts of noise 

on marine mammals, considerable controversy surrounds 

how MMPA, NEPA, and ESA are applied to regulate offshore 

activities and protect marine mammals. A recent court case 

in the Arctic OCS is the July 2010 decision halting activities 

under Lease Sale 193 in the Chukchi Sea citing the need for 

further environmental review. Tension exists between the 

advocates for more precautionary approaches to decision 

making and regulation (National Resources Defense Council, 

1999) and the regulatory agencies implementing MMPA 

and ESA (that is, NMFS and USFWS). Both behavioral and 

auditory effects associated with anthropogenic sound are 

considered “takes” under MMPA and ESA, especially if the 

effects are considered “biologically significant,” a finding 

that also is controversial in how “biologically significant” is 

determined and applied (National Research Council, 2003a, 

2005). 

Table 6–1. Marine mammals of concern in the Arctic Outer Continental Shelf.

[From Allen and Angliss (2010) unless otherwise noted. Locale: B, Beaufort abundance; C, Chukchi abundance; 

P, Pacific abundance; T, total abundance. Population status: +, increasing; ?, unknown. MMPA (Marine Mammal 

Protection Act) ESA (Endangered Species Act) status: From http://www.nmfs.noaa.gov/pr/species/; 

Cd, candidate; E, endangered; D, depleted; DL, delisted; Th, threatened]

Common name Latin name Locale Stock 

abundance

Population 

status

MMPA 

ESA 

status

Bowhead whale Balaena mysticetus T 9,400 + E,D

Beluga whale Delphinapterus leucas B 32,500 ?

C 3,700 ?

Gray whale Eschrichtius robustus P 17,500 + DL

Ringed seal Pusa hispida T ? ? Cd

Ribbon seal Histriophoca fasciata T ? ?

Bearded seal Erignathus barbatus T ? ? Cd

Spotted seal Phoca largha T ? ?

Pacific walrus Odobenus rosmarus divergens T 129,000 ? Cd1

Polar bear Ursus maritimus C 2,000 ? Th

B 1,800 ?

1

U.S. Fish and Wildlife Service (2011). 

6.01. Finding: For all the many studies conducted on ocean noise and marine mammals, large uncertainty still exists in extrapolating 

how impacts of noise on individual animals may affect survivorship or reproductive rates of populations. The National Research Council 

(2005) addressed how to determine “when noise causes biologically significant effects” (subtitle of the report) but the proposed model 

involves five core components for which transition inputs and outputs are not always specified or quantified (for example, Clark and 

others, 2009). More work is needed that is designed to determine how to most effectively determine the impacts of noise at both 

individual and population levels.

6.01. Recommendation: Investment in efforts such as those of BP and the North Slope Borough with the University of California, 

Santa Barbara—Cumulative Effects of Anthropogenic Underwater Sound on Marine Mammals—which is to summarize and 

synthesize the literature on effects of anthropogenic sound on marine mammals, develop suggested approaches for routinely assess 

such effects, and to define fruitful avenues of future research (http://www.eri.ucsb.edu/adminstrative/research_awards_icess, 

accessed April 1, 2011)—and the conduct of resulting high priority research would improve the science foundation for a myriad of 

planning and permitting actions related to Arctic OCS.
168 An Evaluation of the Science Needs to Inform Decisions on Outer Continental Shelf Energy Development in the Chukchi and Beaufort Seas, Alaska

Finally, marine mammals are integral to the culture 

and identity of the Iñupiat Native community of the North 

Slope of Alaska. The bowhead whale is a vital dietary 

component, source of bone and baleen for traditional crafts, 

and an essential symbol of the subsistence culture of the 

Iñupiat community. The MMPA protections for marine 

mammals include making them available for subsistence 

hunting. Annual hunting quotas for the bowhead whale are 

determined by the International Whaling Commission. The 

U.S. quotas are allotted to the 11 North Slope communities 

by the Alaska Eskimo Whaling Commission. For 2010, 

NOAA issued a quota of 75 strikes to the Alaska Eskimo 

Whaling Commission. Walruses, polar bears, and seals also 

are hunted and used by the Native community. A significant 

recurring concern of the Native community is that oil and gas 

related activities may displace marine mammals from hunting 

grounds, thereby threatening the livelihood and existence of 

the Native community. Moreover, they seek to ensure that 

local traditional knowledge is used to augment understanding 

of seasonal movements, distributions, and abundance of 

marine mammals (for example, Noongwook and others, 2007). 

In response to concerns about noise associated with 

oil and gas activities in the Arctic, NOAA/NMFS initiated 

an Environmental Impact Statement (EIS) on the effects of 

Arctic OCS oil and gas activities (seismic and exploratory 

drilling), and held scoping meetings in February and March 

2010, in seven North Slope villages and Anchorage (National 

Marine Fisheries Service, 2010d). The EIS, still in preparation, 

examines the effects of oil and gas activities, including noise, 

on marine mammal species and stocks, as well as their effects 

on communities and subsistence.

Characterization of Sound in the Oceans

Sound is not intuitive to measure or describe. Technically, 

sound travels in water as a mechanical vibration, or pressure 

wave (also called a p-wave) comprising mechanical particle 

motion oscillations associated with alternating compressions 

and rarefactions. The physics of sound measurement and 

transmission are covered in many places and are only briefly 

summarized here, for example, American National Standards 

Institute (1986, 1994), Richardson and others (1995), 

National Research Council (2003), and Erbe (2011). Sound 

is composed of waves of varying frequencies (measured 

in cycles/second, Hz) that are of sufficient strength to be 

detected. In basic terms, sound can be loud or soft, high 

frequency or low frequency, continuous or pulsed, and its 

measured loudness and pitch will depend on how distant or 

close one is to the source. The description of sound necessarily 

involves relative measures of its character (for example, 

compared to a reference), and will depend on whether the 

measurement is done at the source or at some distance from 

the source. Complicating the characterization is that sound in 

water attenuates and weakens as it travels (“propagates”) away 

from the source, depending on factors such as salinity and 

temperature of the water, presence or absence of ice, reflection 

off the sea or ice surface, the depth of the water, and hardness 

of the seafloor (in coastal waters). Because higher sound 

frequencies attenuate more rapidly, low-frequency sounds also 

travel farther than higher frequency sounds. Hence the sound 

characteristics at the source (where the sound is created) may 

have very different characteristics by the time they travel to 

the marine mammal (where the sound is received).

The methods used to measure sound magnitude include 

pressure, energy, and intensity. For any acoustic wave, the 

measure of the pressure on the sound wave can be from zeroto-peak (zero to maximum pressure), peak-to-peak (maximum 

negative to maximum positive pressure), or a root-meansquared (rms) value (average of the squared pressure over the 

duration of a pulse) (fig. 6–1). Sound Pressure Level (SPL) 

gives the sound pressure relative to a reference pressure, 

which for water is 1 micropascal (μPa). Because of the large 

dynamic range of sound pressures, the decibel unit (dB) 

quantifies pressures (relative to the reference pressure) on a 

logarithmic scale, so that the SPL of a sound in water using the 

rms value is given as 20log10(P/Pref), where Pref is 1 μPa and 

the units are dB re 1 μPa (rms). Sounds at the source typically 

are standardized to 1 m distance from the source and are given 

in units of dB re 1 μPa (rms) at 1 m. Sound Pressure Level 

using the rms approach is the current metric used in MMPA 

for establishing zones of safety for marine mammals. 

Sound also can be characterized by energy, which 

integrates the pressure through a time window and is 

proportional to the time integral of pressure squared. 

Typically, 1 second is the standard for the time, and is referred 

to as a Sound Exposure Level (SEL), in units of dB re 1 

μPa2s. Intensity measures the energy that passes through 

a unit area per unit time and also generally is derived from 

pressure squared. Sound Exposure Level is sometimes used to 

understand sound propagation for seismic arrays (Tolstoy and 

others, 2009). 
Chapter 6

Marine Mammals and Anthropogenic Noise 169

The use of the logarithmic scale can be confusing. For 

example, a doubling of pressure will add 6 dB to the SPL, 

whereas a doubling of intensity adds only 3 dB. For a sound 

pulse such as an airgun, where the pulse duration is less than 

1 second, the SEL value will always be less than the SPL (rms) 

value. Further, the SPL (rms) will be less than SPL (zero-topeak) and both will be less than SPL (peak-to-peak). Hence it 

is important to be rigorous in describing and measuring sound 

levels to specify SPL versus SEL and to identify whether 

SPL is for peak-to-peak, zero-to-peak, or rms. The media 

frequently quote dB estimates for measurements that do not 

specify the type of SPL or SEL measurement. Further, dB 

measurements in water use a reference of 1 μPa whereas for 

air the reference is 20 μPa, rendering comparisons between 

the two inappropriate. Imprecision in describing sound adds 

confusion and sometimes alarm to reasoned public discourse. 

Because sound also contains different frequency contents, 

the SPL of different sound sources in not necessarily additive 

(and, if additive, must be added using logarithmic, rather than 

linear, rules). 

Airgun size is classified by its chamber volume. The 

way this volume is related to level of sound also is not linear. 

Excellent summaries describe how changes in source strength, 

operating pressure, and number of airguns in an array affect 

SPL measurements (Dragoset, 1990, 2000).

Although the current regulatory framework uses the 

SPL (rms) pressure measurement, some researchers have 

suggested that the energy metric, SEL, is more useful because 

Figure 6–1. Example of a seismic sound signal showing how zero-to-peak and peak-topeak pressure would be measured. 

Time

Pressure

Zero-to-Peak

Peak-to-Peak

Seismic Signal

total energy enables sounds of differing durations to be 

more readily compared (for example, Southall and others, 

2007; Tolstoy and others, 2009). It perhaps may be most 

useful to use both. Extremely high but nearly instantaneous 

sound waves have low energy levels (because the energy is 

averaged over a much longer time frame than the duration 

of the pulse), but may still cause damage to auditory or 

other tissues. Additionally, cumulative energy contained in 

low-amplitude sounds may interfere with hearing after long 

exposures. As an example, one can imagine how a gunshot or 

firecracker going off near one’s ear would affect hearing, and 

also imagine how working with constant background noise 

for a long period of time also might affect hearing.

Different animal species have different frequency 

sensitivities. Five functional hearing groups of marine 

mammals exist based on their presumed hearing frequency 

range (for example, Southall and others, 2007), which are 

summarized in table 6–2. Only four of these apply to the 

Arctic marine mammals of interest (the high-frequency 

cetaceans, such as harbor porpoise, which are only seasonally 

present in the Arctic in low abundance, are not among the 

subjects of this chapter). It is important to note that sound 

frequencies particularly greater than 1,000 Hz (1 kHz) 

attenuate rapidly in water. 

A useful diagram summarizing the magnitude and 

frequency of different kinds of sounds found in the oceans 

is that created by Wenz (1962), which is still widely used 

(fig. 6–2). 
170 An Evaluation of the Science Needs to Inform Decisions on Outer Continental Shelf Energy Development in the Chukchi and Beaufort Seas, Alaska

Table 6–2. Arctic Outer Continental Shelf Marine Mammal Hearing Groups.

[Modified from Southall and others (2007) for the marine mammals of interest in this report. Hz, hertz; kHz, kilohertz]

Functional hearing group Genera Estimated auditory

bandwidth

Low-frequency cetaceans Balaena, Eschrichtius 7 Hz – 22 kHz

Mid-frequency cetaceans Delphinus 150 Hz – 160 kHz

High-frequency cetaceans (none) 200 Hz – 180 kHz

Pinnipeds in water Erignathus, Histriophoca, Pusa 75 Hz – 75 kHz

Pinnipeds in air (same as species in water) 75 Hz – 30 kHz

Ocean Traffic (Deep)

Ocean Traffic (Shallow)

Heavy Precipitation

Earthquakes/Explosions

Ocean Traffic (Heavy)

Low frequency Noise from wind 

 in very shallow water

Sea-state Dependent

Wind, Waves, Spray, Bubbles

Upper Limit of Prevailing Noise

Lower Limit of Prevailing Noise

Deep-Penetration Seismic High-Resolution Seismic

Low Frequency Cetaceans

Mid-Frequency Cetaceans

High-Frequency Cetaceans

Pinnipeds in Water

Pinnipeds in Air

7Hz - 22 kHz

150 Hz - 160 kHz

200 Hz - 180 kHz

75 Hz - 75 kHz

75 Hz - 30 kHz

Bowhead

Gray

Beluga

Figure 6–2. Upper: diagram showing 

pressure spectral density of marine 

ambient noise modified from Wenz (1962) 

and National Research Council (2003b). 

The gray shaded region gives the general 

band of ambient noise and the contained 

curves identify specific sources of sound 

contributing to the ambient noise. Lower: 

marine mammal hearing groups and their 

estimated auditory bandwidth (black lines) 

as defined by Southall and others (2007). 

Dominant bandwidth for selected whales 

(red lines) is from National Research 

Council (2000). Approximate frequency 

ranges for deep-penetration (blue) and 

high-resolution (green) seismic surveys 

are superimposed on the cetacean ranges. 
Chapter 6

Marine Mammals and Anthropogenic Noise 171

Anthropogenic Sound Categories

For the purposes of understanding anthropogenic sound 

in the Arctic OCS, we use seven categories of sound. These 

categories discriminate among the source level, frequency 

(Hz), and temporal patterns of the sound. The source level is 

the SPL (rms) measured or estimated/modeled at 1 m from 

the source. The frequency is captured as a power spectrum 

that relates sound level and frequency. The temporal pattern 

of sound refers to its occurrence, as in transient (for example, 

explosion), continuous (for example, drilling), or pulsed (for 

example, seismic airguns). The seven categories are:

1. Deep-penetration seismic surveys

Deep-penetration, low-frequency seismic surveys are 

considered to be high-energy intermittent pulsed sounds, 

typically two-dimensional (2-D) regional surveys and 

three-dimensional (3-D) local surveys utilizing airgun 

arrays consisting of several large to many small airguns. 

The frequency level generally is from several to 100–

250 Hz. The purpose of these surveys is to image geology 

at moderate to crustal depths for geologic framework and 

exploration purposes.

Statistics maintained by BOEMRE (See websites accessed 

April 30, 2011, at http://alaska.boemre.gov/re/permits/

xpermits/arctic_charts.pdf, http://alaska.boemre.gov/

re/permits/xpermits/arctic_table.pdf, and http://alaska.

boemre.gov/fo/Geohazards/chukchi_hazard_surveys.mdb) 

show that deep-penetration surveys in the Beaufort and 

Chukchi regions for oil and gas exploration have been 

historically, and continue to be, the most plentiful types of 

surveys conducted. Since 1968, there have been 119 openwater exploration surveys in the Beaufort region and 48 in 

the Chukchi region. An additional 67 on-ice seismic surveys 

were conducted in the Beaufort region between 1970 and 

2000. The peak in seismic permits for both areas occurred 

in the early to mid-1980s with a maximum of nine permits 

issued for marine 2-D geophysical surveys in the Beaufort 

region in 1984 and a maximum of six permits for similar 

work in the Chukchi region in 1985 (fig. 6–3). Recently 

(since 1994), there have been no 2-D surveys in the Beaufort 

region and only one in the Chukchi region (in 2006). This 

decrease in 2-D surveys contrasts with the growth of 3-D 

exploration surveys: since 1990, there have been ten 3-D 

surveys in the Beaufort region, but only three in the Chukchi 

region. The trends from these permits suggest that future 

oil and gas seismic exploration activity in the Beaufort 

and Chukchi regions is likely to be with 3-D surveys. 

Details about the surveys, such as time of year, lease block 

locations, and duration of surveys are available from 

BOEMRE. These BOEMRE statistics do not include seismic 

programs that might have occurred in Canada or Russia for 

oil and gas activities (for which the air gun sounds could 

propagate into U.S. waters). Nor do the BOEMRE statistics 

cover seismic activities conducted by U.S. or foreign 

research groups for non-petroleum related purposes (for 

example, 2005 NSF-funded seismic transect across the pole 

aboard the U.S. Coast Guard Cutter (USCGC) Healy, or 

the 2007–10 United Nations Convention on Law of the Sea 

(UNCLOS) work conducted aboard the Canadian icebreaker 

CGGS Louis S. St-Laurent). Hence these statistics are 

representative of the bulk of the seismic exploration work, 

but underestimate total seismic activities. 

6.02. Finding: Despite the large number of seismic surveys conducted over time in the Beaufort and Chukchi Seas, an inventory/

database of seismic sound sources used in the Arctic Ocean does not exist. 

6.02. Recommendation: Such an inventory would provide standardized information about source arrays (for example, number 

of airguns, dimensions of arrays, frequencies, firing pressure), physical oceanographic conditions at the time of measurement, and 

timing and duration of surveys. Such a database could be used to evaluate multiple sound sources that a marine mammal might 

hear in space and time, and help validate models that estimate sound propagation. The database may ultimately reduce the need 

for expensive or redundant acoustic modeling and monitoring, especially in sensitive or biologically significant habitats as well as 

contribute to developing more effective mitigation strategies. 
172 An Evaluation of the Science Needs to Inform Decisions on Outer Continental Shelf Energy Development in the Chukchi and Beaufort Seas, Alaska Number of Permitted Activities Number of Permitted Activities

Figure 6–3. BOEMRE permitted exploration seismic activities in the Beaufort (upper) and Chukchi (lower) Seas since 1968. 

High-resolution seismic surveys done to address site-specific hazards related to drilling are not included in this chart. The 

peak number of seismic surveys occurred in the 1980s. Source: Bureau of Ocean Energy Management, Regulation and 

Enforcement, written commun., February 2011. G&G, geological and geophysical. 
Chapter 6

Marine Mammals and Anthropogenic Noise 173

2. High-resolution seismic surveys

High-resolution seismic surveys are considered to be 

mid-to high-frequency, low-energy intermittent pulsed 

sound, typically used in shallow hazards surveys for 

siting drill holes (including strudel surveys to understand 

ice scour) or high-resolution surveys for understanding 

near-seafloor geologic evolution. The sources usually are 

not airgun arrays but consist of boomer, sparker, chirp, 

and individual (or arrays of several) small water guns 

or Generator-Injector airguns (GI-guns). The frequency 

range generally is from 100 Hz to several kilohertz. 

High-resolution surveys related to oil and gas activities 

have occurred in the Beaufort Sea [see Minerals 

Management Service (2007) for permitted activities 

and see Horowitz (2002) for additional high-resolution 

surveys in the Beaufort Sea] and Chukchi Sea (see 

Minerals Management Service, 2007). These surveys are 

required to address safety and risk assessment prior to 

Figure 6–4. Comparison of zones of mitigation under MMPA for deep-penetration (right) and high-resolution seismic surveys 

(middle, left). Inner and outer circles are for Level A and B harassment, respectively. Source: Jana Lage, Bureau of Ocean Energy 

Management, Regulation and Enforcement, January 2011.

siting final drill locations. Hence, these kinds of surveys 

are expected to increase when drilling resumes in order to 

satisfy permitting requirements. Because of the generally 

lower energy and higher frequencies associated with 

these surveys, these surveys are often considered to be 

lower impact on marine mammals, although some studies 

are beginning to question this conclusion (for example, 

Southall and others, 2007). 

The distinction between deep-penetration and highresolution seismic categories separates both the frequency 

and energy levels of the different survey types. Figure 6–2 

shows how the deep-penetration surveys overlap primarily 

with the low-frequency cetaceans (such as the bowhead 

and gray whales). The high-resolution surveys overlap 

primarily with the mid- and high-frequency cetaceans 

(such as the beluga whale). Figure 6–4 illustrates how 

the higher energy of the deep-penetration surveys results 

in significantly larger zones of mitigation under MMPA 

compared to high-resolution seismic surveys. 
174 An Evaluation of the Science Needs to Inform Decisions on Outer Continental Shelf Energy Development in the Chukchi and Beaufort Seas, Alaska

3. Drilling activities

Drilling activities generate continuous, generally lowenergy sound at low frequencies (for example, less than 

several tens of hertz) that decay to ambient noise levels 

within 1 to several kilometers (Richardson and others, 

1995). There are variations depending on type of drill rig 

(for example, gravel island versus semi-submersible) and 

type of drilling (for example, rotary versus hammering). 

Drilling in the Arctic OCS has been limited to shelf-depth 

waters (generally less than 100 m water depth). Winter ice 

currently precludes the installation of year-round floating 

or semisubmersible drill rigs used in conventional openwater deep-water drilling operations. Benchmark noise 

studies of gravel-island and shallow-water caisson and 

semisubmersible drilling have been done for the Beaufort 

OCS around Prudhoe Bay (Greene, 1987; Richardson 

and others, 1995). Additional monitoring of the noise of 

drilling continues through the present (for example, with 

the BP Liberty gravel-island drilling reported in the last 

3 years of NOAA/BOEMRE Arctic Ocean Open Water 

meetings). The data collected as part of monitoring are 

not publicly available, and the reports associated with 

these monitoring studies show images and analyses that 

are sometimes in peer-reviewed journals (for example, 

Blackwell and others, 2004a), but generally only available 

in gray literature. 

4. Ships/Vessels

Ship and vessel noise is continuous and consists of a 

combination of frequencies that are both broadband 

(over a range of frequencies) and narrow band (tonal 

at specific frequencies). Ships are considered a major 

contributor to ocean noise at frequencies less than 500 Hz 

(National Research Council, 2005) with significant spatial 

variability associated with shipping lanes and ports. 

Levels and frequencies of sounds are dependent on vessel 

size, design, and mode of propulsion. Smaller vessels 

with small propellers and high revolutions per minute 

generate noise at higher frequencies. There is an abundant 

literature on shipping noise (for example, National 

Research Council, 2005). 

Although there are currently no commercial shipping 

lanes in the Arctic OCS, the possibility exists for these 

routes to develop as summer ice retreats or disappears 

with climate warming, as well as for large cruise vessels 

to bring tourists to the Beaufort and Chukchi Seas. 

Currently, the commercial ship traffic occurs with barges 

in the near shore in open water during the summer, 

primarily to re-supply the Native community with bulk 

supplies. Gray literature exists for the sounds made by 

individual ships participating in oil and gas activities in 

the Arctic OCS as a result of permits issued under MMPA 

that generally require measurements of ship noise prior 

to the start of exploration activities. These data are not 

readily available digitally, although reports written as 

a result of the oil and gas activity sometimes include 

summaries of the noise studies. 

5. Icebreaking

Icebreaking is a special category of ship and vessel noise 

that is associated with higher levels of sound because of 

the additional power required for a vessel to break thin ice 

continuously or thicker ice through backing and ramming. 

Icebreaking also is unique to ice-covered regions such 

as the Arctic. Some of the earliest studies on the sound 

of icebreaking were done in the Arctic (for example, 

Richardson and others, 1995, and references therein) 

and these studies continue to be cited extensively in the 

absence of more recent publications. Roth and Schmidt 

(2010) presents interpretations of the noise of icebreaking 

for USCGC Healy during a 2008 cruise and compares 

SPLs at 5/10 ice coverage and greater. The noise of 

continuous icebreaking exceeded the noise of backing and 

ramming by about 5 dB. The inclusion of icebreaking as 

potential impact for Level B marine mammal harassment 

under MMPA is new in 2010 (Haley and others, 2010). 

6.03. Finding: As in Finding 6.02 for seismic survey-generated 

noise, there is a similar lack of an organized inventory/database 

for the noise generated by vessel types that presently frequent 

the Arctic Ocean, or may do so in the future with changing ice 

conditions.

6.03. Recommendation: An inventory and synthesis of vessel 

noise for vessels used in the Arctic Ocean will enable researchers 

to understand the contributions of potential new ship traffic to 

ambient background levels of noise in the Arctic. This inventory/

database should contain standardized information about vessel 

noise, duration, time of measurement, and location. Most industry 

exploration activities measure ship noise prior to commencing 

surveying as part of the permitting process. 
Chapter 6

Marine Mammals and Anthropogenic Noise 175

7. Aircraft overflight

Aircraft (including helicopters and fixed-wing 

aircraft) are a special category of noise because of 

(a) the potential transient nature of the noise, (b) the 

complications of relating source level and propagation 

paths through air and water, and (c) the potential 

impacts to marine mammals (seals, walrus, and polar 

bear) that spend considerable time out of the water. It 

is only for a relatively narrow angular cone beneath 

the aircraft (about 13° for calm water, Richardson 

and others, 1995) that the noise of the aircraft 

penetrates into the water. At larger angles, the sound 

is effectively reflected at the sea surface. Hence, the 

height and speed of the aircraft, in addition to the noise 

it generates, affect how much of the ocean surface 

will be insonified. Moreover, a persistent challenge in 

interpreting observations of marine mammal behavior 

associated with the presence of aircraft is to know 

whether the aircraft sound or the visual presence of the 

aircraft has triggered the disturbance.

In the Arctic OCS, aircraft are used in offshore oil 

and gas activities as well as in conducting monitoring 

and population assessments of marine mammals (for 

example, Bowhead Whale Aerial Survey Program, 

BWASP). Shell also has proposed using drones to 

monitor for marine mammals near seismic operations 

(A. Macrander, Shell Exploration and Production, oral 

commun., March 2010) to augment visual monitoring 

in areas far offshore (such as the Chukchi) where 

manned fixed-wing aircraft monitoring is impractical or 

unsafe.

6.04. Finding: Icebreakers, an important subset of vessels used in 

the Arctic from a noise and marine mammal encounter perspective, are 

highlighted in addition to the more general vessel topic of Finding 6.03. 

There are essentially no data relating the noise of icebreaking to the 

type of icebreaker, and the character of the ice (for example, percent 

coverage, age of ice, thickness of ice). Preliminary data included in 

Haley and others (2010) suggest that the noise from icebreaking is not 

of higher amplitude than a modest seismic array. But, the paucity of 

data on icebreaker-generated noise is particularly critical because of 

sea ice’s importance as habitat for many marine mammals. It is difficult 

at present, if not impossible, to know how to define “takes” from 

icebreaking or how to predict its impact on marine mammals.

6.04. Recommendation: As in Recommendations 6.02 and 6.03, 

the development of a standardized inventory/database would greatly 

facilitate the accumulation of information required to better understand 

the characteristics of icebreaker-generated noise under different ice, 

oceanographic, and operating conditions. 

6.05. Finding: Aircraft represent another potential sound 

source that must be considered along with seismic (Finding 6.02), 

vessel (Finding 6.03), and icebreaker (Finding 6.04) sources. Very 

little information exists that quantifies aircraft noise as a function 

of aircraft type and approach geometry. 

6.05. Recommendation: Information that quantifies aircraft 

noise as a function of aircraft type and approach geometry would 

help to understand the responses of several species of Arctic 

OCS marine mammals to overflight.

6. Construction

Construction for the purposes of this report is considered to 

include localized relatively brief duration or one-time noise 

associated with, for example, siting drill rigs, installing 

pipelines, developing shore-based infrastructure such as 

docks and piers, building ice roads on sea ice, and so on. 

Similar to drilling activities, the noise associated with 

construction generally is at the lower frequencies (less than 

several hundred hertz) and attenuates relatively close to the 

location of construction. Unlike drilling, the noise generally 

is short-term for the duration of the construction project 

only.

For the Arctic OCS, shore-fast and winter sea ice preclude 

year-round floating or surface structures. Hence the noise 

of construction has been limited to near-shore (Beaufort) 

and shallow water (Chukchi) seasonal activities. A large 

literature exists on the sounds of construction related to 

developing the Liberty and Northstar prospects in the 

Beaufort Sea (for example, Richardson and others, 1995). 

Dredging is not yet an activity conducted along the North 

Slope (Beaufort/Chukchi) shorelines.
176 An Evaluation of the Science Needs to Inform Decisions on Outer Continental Shelf Energy Development in the Chukchi and Beaufort Seas, Alaska

8. Other Considerations

To completely understand the contribution and impacts 

of anthropogenic noise to the environment, knowledge of 

the levels and spatial-temporal variability of background 

(ambient, non-anthropogenic) noise is essential, as well 

as which anthropogenic sounds occur simultaneously. 

The magnitude of ambient sound gives context to 

understanding increased sound levels from anthropogenic 

sources. However, it is important to correctly characterize 

the sound, because not all these sounds are additive when 

occurring together, owing to the different frequencies, 

shapes, and amplitudes of the different sources of sound. 

Potential Effects of Sound Exposure 

A range of effects may result from exposure of 

marine mammals to anthropogenic sound, ranging from 

no observable effect to physical injury or, in the extreme, 

death. As with people, the reactions of marine mammals can 

depend on factors such as species, individual, age, sex, prior 

experience with the sound, activity at the time of the sound, 

and behavioral state. When observing animals in the natural 

environment, external non-auditory stimuli also may affect 

reactions. In this section, we describe some of the potential 

effects of exposure to anthropogenic sound sources, which 

may or may not result in observable or measurable behavioral 

changes. 

1. No Observable Effect

Marine mammals have been observed in close proximity 

to loud sound sources associated with oil and gas 

activities (for example, Richardson and others, 1995). 

They could be unaffected by the sound, they could be 

tolerating the sound because critical resources were in 

the area (food, mates, open water, haulout sites, and 

so on), or they could be deaf. The individuals could be 

unaffected because their auditory systems are insensitive 

to the frequency-intensity combinations of the sound. 

Alternatively, the individuals may be able to detect the 

sound, and may have reacted during their first exposures, 

but over time have learned that the sound is of no 

consequence and thus have become habituated, evidence 

of which is reduced or absent response during subsequent 

exposures. 

There are documented cases of apparent tolerance of 

marine mammals to noise, which also demonstrate much 

variability. For example, bowhead whales tolerated an 

increase in 40 dB in seismic survey noise when feeding 

in summer as opposed to during the fall migration 

(Richardson and others, 1995, 1999). 

2. Sensitization

Sensitization occurs when an individual associates a 

specific sound with a specific outcome that alters the 

animal’s behavior. Evidence of sensitization is observed 

in animals that change their behavior when they receive 

sound levels that are far below levels associated with 

auditory interference or injury. For example, seals 

that survive hunting or harassment (for example, by 

humans, polar bears, or killer whales) likely will take the 

appropriate actions as soon as they detect sounds made by 

the hunters in the future. 

6.06. Finding: The overall ambient noise budgets of the Arctic, 

particularly how they vary temporally (for example, seasonally) and 

spatially (for example, shallow versus deep water) are not well 

known. Very little data exist to inventory the seasonal and spatial 

levels of ambient noise in the Beaufort and Chukchi Seas. Some 

annual measurements in specific locations are beginning to be 

done and seasonal measurements are recorded as by-recordings 

of listening to and locating whale calls before, during, and after 

seismic surveys in the Beaufort and Chukchi Seas (for example, 

Blackwell and others, 2007; Kosiara and others, 2008).

6.06. Recommendation: A time-series database of ambient 

ocean noise for the Arctic will be essential for understanding the 

changes to ambient noise created through climate warming and 

seasonal reductions in sea ice so that the distinction of impacts 

between anthropogenic and natural sources on marine mammals 

can be made.

A little-studied factor that also will affect sound 

measurements in the oceans is ocean acidification, the process 

by which the oceans become more acidic because of the 

anthropogenic emissions of carbon dioxide (for example, 

Ilyina and others, 2009). Because propagation of sound in 

the oceans is affected by the dissolved chemical constituents, 

an increase in ocean acidity will decrease the absorbtion of 

sound, that is, increase the propagation of sound. According 

to models, this affect may be greatest in high latitudes in the 

frequency ranges of 100 Hz to 10 kHz, or exactly in the range 

that encompasses both deep-penetration and high-frequency 

seismic surveys (Ilyina and others, 2009).
Chapter 6

Marine Mammals and Anthropogenic Noise 177

3. Avoidance/Displacement

Marine mammals may avoid sound sources, or be 

displaced from areas associated with the sound. This 

behavior has been observed in bowhead whales from 

underwater acoustic monitoring, which has shown that 

the calls of bowhead whales deflect seaward away from 

the sound of airguns during nearshore seismic surveys 

(Blackwell and others, 2007). An uncertainty associated 

with this deflection behavior is whether all whales 

exhibited the displacement or only those whales making 

calls. When whales cease calling in the presence of 

nearby seismic signals, this is a variant on avoidance and 

displacement (for example, Blackwell and others, 2010). 

4. Masking

Masking is the decreased ability to detect one sound 

due to the presence of another sound. Fletcher (1940) 

suggested that masking of a signal is especially 

pronounced if the frequency spectrum of the masking 

noise overlaps within a critical band around the frequency 

of the signal. Most anthropogenic underwater activities 

produce sound at frequencies below 1 kHz, which is 

within the frequency band used for communication 

signals of baleen whales, and some toothed whales, 

such as belugas (for example, Clark and others, 2009). 

It may not be possible to distinguish hearing loss (that 

is, an animal that fails to detect a signal because of 

reduced hearing) from masking (that is, an animal with a 

normally functioning auditory system that fails to detect 

a signal because it is masked by a louder sound of similar 

frequency). 

An increase in ambient ocean noise (for example, by 

increased shipping in a region) can contribute to masking. 

If marine mammal navigation or communication signals 

are masked by anthropogenic noise, there will be obvious 

implications for population cohesion and other social 

interactions. However, it is important to note that masking 

has never been conclusively demonstrated in freeranging marine mammals, only implied by observations 

of animals changing their calling in the presence of 

anthropogenic sound.

5. Auditory Threshold Shift 

Exposure to loud or repetitive sounds may degrade 

the individual’s ability to hear, with effects ranging 

from reversible temporary threshold shifts (TTS) to 

permanent reduction in thresholds (PTS) at narrow or 

broad frequencies (Kryter, 1994). TTS is recoverable and 

is considered to result from the temporary, noninjurious 

distortion of hearing-related tissues. An animal that 

experiences a TTS suffers no injury to its auditory system 

but temporarily may not perceive some sounds due to 

the reduction in sensitivity. In contrast, PTS results from 

the nonrecoverable destruction of tissues within the 

auditory system and is considered an injury in the U.S. 

regulatory environment (see summary in Southall and 

others, 2007). Recent anatomical and behavioral studies 

suggest that cetaceans may be more resistant than many 

land mammals to TTS, having evolved in a relatively 

high noise environment. Data suggest, however, that, like 

humans, cetaceans suffer from hearing loss as a result of 

increasing age (Ketten, 1997).

6. Physiological Stress Responses

Although several reviews have entertained the possibility 

that noise induces a physiological stress response in 

marine mammals, there have been few studies. Romano 

and others (2004) exposed a captive beluga whale to 

sounds from a seismic water gun and measured various 

hormones in the blood, including cortisol, before and after 

exposure. They measured changes that were considered 

detrimental. These changes increased with increasing 

sound levels. Thomas and others (1990), however, did 

not find elevated stress hormone levels in the blood after 

playbacks of oil drilling platform noise to captive belugas. 

Because of the inherent difficulty, if not impossibility, of 

taking frequent tissue or blood samples from live wild 

animals, conclusions about physiological stress responses 

will remain the purview of studies of captive animals. 

7. Physical Injury

PTS is considered an injury and can occur either after 

long exposure to a sound (for example, Richardson and 

others, 1995) or from instantaneous exposure to very 

high sound levels, such as an explosion. There is some 

speculation that anthropogenic sound has the ability to 

induce other injurious effects, such as debilitating bubble 

formation or tissue damage in deep- or long-diving 

species (Houser and others, 2001). While evidence of 

tissue damage (including auditory structures) has been 

reported, this has been associated with exposure to 

extremely loud sounds associated with use of explosives 

or military training and testing (Jepson and others, 2003; 

National Research Council, 2005). To the best of our 

knowledge, this has little relevance to the sound sources 

and levels and environmental acoustics associated with 

OCS oil and gas exploration and production. 

8. Cascading Effects

Vessel noise, in addition to potentially impacting marine 

mammals, produces sounds in the hearing range of fish 

(Amoser and others, 2004). If anthropogenic sound affects 

the distribution of fish, it could therefore impact marine 
178 An Evaluation of the Science Needs to Inform Decisions on Outer Continental Shelf Energy Development in the Chukchi and Beaufort Seas, Alaska

mammals that rely on those fish. Vessels (that is, trawlers, 

ferries, small boats) also can alter behavior in fish (for 

example, induce avoidance, alter swimming speed and 

direction, and alter schooling behavior), similar to marine 

mammals (for example, Engås and others, 1995). 

Although the above list produces convenient categories 

for describing the possible effects of sound on marine 

mammals, in actuality, linking an effect to an observation 

and an explanation is much more difficult. For example, 

if a marine mammal tolerates a sound, it may represent 

acclimation or habituation of some kind, but it also may 

represent an unrelenting need, for example, for feeding 

or reproduction, to remain in a particular location despite 

exposure to a potentially damaging sound. Alternatively, 

the sound may be harmless. Science, however, is based on 

observations, and in the absence of observable changes, 

it is risky to attempt to speculate about contributions of 

potential invisible factors.

6.07. Finding: Substantial challenges exist to confidently interpret the magnitude and significance of the potential effects of anthropogenic 

sound on marine mammals. Limitations in our understanding affect the confidence that many entities expressed during the USGS OCS Team 

expert consultations (see appendix A). The topic of the impact of anthropogenic sound on marine mammals remains a key topic of concern.

6.07. Recommendation: Continued or new attention to the following topics could significantly improve the assessment and potential 

mitigation of human-generated noise effects on marine mammals of concern. Some of these challenges are: 

1. Attempting to distinguish between transient or ephemeral behavioral effects of sound versus those that are more meaningful to survival or 

reproduction. An example would be walruses waking up and raising their heads when they hear a sound, as compared to injury or mortality 

caused by the same walruses stampeding into the water when they hear a sound. A second example would be the movement of animals away 

from a sound source—is displacement fractional relative to the animals’ normal movements, or is it substantial, and how long does it persist? 

2. Using observations of individual animals to make inferences about possible implications for populations. In general, the body of available 

scientific information supports the potential for near-term reaction of individuals to various forms of anthropogenic sound sources, but longterm impacts at the population level are not well understood. 

3. Using one set of observations for predicting reactions when the interaction parameters are different. The same sounds may elicit different 

responses at different times of year or in different locations associated with different types of activity (for example, migration, feeding, 

reproduction, sheltering). 

4. The degree to which context of a sound influences a reaction. In some instances, animals of a given species may occupy locations with 

substantial types of some noise (for example, pipe-driving) but avoid other locations where the anthropogenic sound levels are much lower. For 

example, ringed seals may forage nearby active seismic surveys, but escape reactions will be elicited when they detect faint sounds of polar 

bears or subsistence hunting boats. 

5. The degree to which we can discriminate between the effects of sound, other aspects of human activity, and environment variation, especially 

for understanding behavior of animals in the wild. An animal that is observed in close proximity to a loud sound source could be unaffected by 

the sound, it could be tolerating the sound because critical resources were in the area (for example, food, mates, open water, haulout sites), 

or it could be deaf. The observed behavior is the sum of the external environmental stimuli detected by the animal, behavior of its peers, 

behavior of other species, plus the animal’s physiological state. Further, if the source of sound has been close enough to the animal that it 

was visible and perhaps detectable by other sensory cues, such as odor or vibration, the animal could be reacting to these other cues. Unless 

research demonstrates that individuals are exposed only to sound, the precautionary interpretation is that the sound can be associated with 

the behavior rather than that the sound explains the behavior.

6. Quantifying secondary or cumulative effects of sound on population persistence. While sound may alter the behavior of individual animals, 

other factors also may affect outcomes (for example if sound caused prey abundance or availability to change). Cumulative effects also 

may occur but are difficult to quantify (for example, if physiological stress caused by sound exposure combines with stress induced by 

environmental contaminants to affect a population). These are difficult, if not impossible, measurements to make on wild animals.
Chapter 6

Marine Mammals and Anthropogenic Noise 179

Monitoring and Mitigation

Both the ESA and the MMPA require monitoring and 

mitigation measures to protect marine mammals from potential 

harm caused by exposure to anthropogenic sound sources. The 

MMPA places a moratorium on “takes” of marine mammals, 

in which “take” means “to hunt, harass, capture or kill” (from 

National Marine Fisheries Service, 2008b). Exceptions exist, 

for example, for subsistence hunting, and exceptions also 

can be granted for example, for incidental takes associated 

with fishing. For permitting, harassment for MMPA is further 

defined as level A (in which the harassment has the potential to 

cause death or injury) or level B (in which the harassment has 

the potential to disturb the animal by disrupting its behavior) 

(National Marine Fisheries Services, 2009b). 

The USGS OCS Team’s expert consultations 

(appendix A) raised concerns about both monitoring and 

mitigation strategies, particularly by the Marine Mammal 

Commission and the Alaskan Native Community. Protected 

species observers are required participants on many oil 

and gas exploration and development activities to monitor 

marine mammals and determine when mitigation strategies 

must be implemented. Data recorded by these observers are 

inconsistent. This inconsistency limits how these datasets 

can be integrated and merged for a more complete picture of 

marine mammal behavior in the presence of anthropogenic 

sound. As technology advances, the requirements for 

monitoring also have evolved, so that deficiencies in visual 

observations (for example, only possible for daylight 

hours) can be augmented by acoustic observations (for 

example, passive acoustic monitoring). Despite the array 

of tools available for monitoring (ship observations, aerial 

observations, acoustic monitoring, infrared detection, and so 

on), no single monitoring strategy gives a complete picture 

of the marine mammal presence. Hence monitoring contains 

inherent uncertainty about missing animals, which raises 

questions about how effective monitoring is for ensuring 

whether “takes” occur. 

Mitigation also is problematic. First, the objectives of 

mitigation (for example, to avoid hearing impairment or to 

minimize disturbance) may require multiple criteria. Yet, a 

single, simple criterion is the easiest to implement. Second, 

some mitigation measures significantly restrict human 

activities with little evidence of benefit to marine mammals. 

Third, a standard mitigation strategy is applied broadly (for 

example, one for cetaceans, another for pinnipeds). Yet, 

the hearing ranges and communication frequencies differ 

for different species, raising questions whether mitigations 

strategies should be specific to a species (for example, 

Southall and others, 2007). Fourth, practical decisions about 

regulatory and mitigation issues are being made based on best 

available, but incomplete, knowledge which raises questions 

about how defensible these decisions are. And, finally, many 

concerns and questions raised by managers require integration 

across a range of temporal and spatial scales, involve 

understanding the ecosystem in which the marine mammals 

live, and now commonly require evaluating species responses 

to climate change. Regulators and scientists are in agreement 

that additional data are needed for each marine mammal 

species, such as baseline data on current abundance, seasonal 

distribution, movements, population dynamics, and other basic 

biological information.

Bowhead Whale (Balaena mysticetus)

Of the five recognized stocks of bowhead whales, the 

Bering-Chukchi-Beaufort (BCB) stock frequents the Alaska 

Arctic coastal area. As part of its annual migration, the 

bowhead whale passes from the Bering Sea to the Chukchi and 

Beaufort Seas en route to its summer grounds in the Canadian 

Arctic and returns to the northern Bering Sea in the autumn 

(Moore and Reeves, 1993; Moore and others, 2000). Its 

migration routes along the Alaska coastline and in the Chukchi 

Sea (fig. 6–5) overlap with the current areas of leasing and oil 

and gas exploration and production. 

Of the baleen whales, the U.S. bowhead is among the 

most studied. The convergence of three events served to 

promote research about the bowhead whale. First was the 

recognized depletion of the bowhead population, initially 

in the early 1900s when it was given protected status by the 

International Convention for the Regulation of Whaling and 

later when the bowhead was listed as endangered under the 

ESA of 1973 and further protected by MMPA. Second was the 

controversy accompanying the proposed ban on subsistence 

whaling by the International Whaling Commission in 1977, 

which led to negotiation of a reduced subsistence harvest to 

be accompanied by expanded research about the bowhead. 

Finally, the mid-1970s initiated the first oil and gas activities 

in the Arctic OCS for which research into the impacts of oil 

and gas activities on the bowhead whale was required under 

ESA and MMPA. Consequently, the late 1970s and early 

1980s were a time of many observations and publications 

about BCB bowhead whales, especially as they reacted to 

anthropogenic activities (for example, Richardson and others, 

1986, 1987). These early studies were followed by seminal 

syntheses in the 1990s (for example, Richardson and others, 

1995) and served to raise awareness more broadly of marine 

mammal and ocean sound issues (for example, National 

Research Council, 1994). As mentioned earlier, the bowhead 

whale is still listed as endangered under ESA. The Native 

community participates in setting hunting quotas and bowhead 

management through the Alaska Eskimo Whaling Commission 

(2007, website accessed April 30, 2011, at http://www.alaskaaewc.com/aboutus.asp). 
180 An Evaluation of the Science Needs to Inform Decisions on Outer Continental Shelf Energy Development in the Chukchi and Beaufort Seas, Alaska

Many of these early studies combined observations of 

bowhead behavior with anthropogenic noise, for example 

seismic surveys (Fraker and others, 1985; Richardson and 

others, 1986), ship movement (LGL Ecological Research 

Associates, Inc., 1982), drilling and dredging (Richardson 

and others, 1987, 1990), icebreaking (Richardson and others, 

1995), and aircraft noise (Richardson and others, 1985). 

Details of these studies identify sound levels, whale distances 

from the sound sources, context of whale activities where 

available (for example, feeding, migrating), and behavioral 

changes. These studies also revealed the general vocalization 

frequencies of bowhead whales (100–400 Hz dominant, 

25–3,500 Hz range), calling patterns, and loudness (for 

example, Ljungblad and others, 1982; Clark and Johnson, 

1984; Würsig and others, 1989; Würsig and Clark, 1993), 

although the age, sex, and activity associated with the 

individuals making the sounds were largely unknown. Missing 

from these early studies is whether the observed behaviors 

and (or) behavior changes are biologically meaningful and 

affect the survival of either the individual or the bowhead 

population. The BCB bowhead population, however, is 

estimated at about 9,400 and is increasing at about 3 per year 

(Allen and Angliss, 2010). 

Since the mid-1990s, both observational data and new 

kinds of studies have focused on understanding the habitat, 

behavior, and distribution of BCB bowhead whales, both 

in relation to anthropogenic noise and as baseline data to 

help understand the life histories of the species. One of the 

longest term monitoring programs is the Bowhead Whale 

Aerial Survey Project (BWASP; Bureau of Ocean Energy 

Management, Regulation and Enforcement, 2011) begun 

in 1979 and now a multi-agency effort to understand the 

distribution of whales during the summer, open-water months. 

A parallel effort, the Chukchi Offshore Monitoring in Drilling 

Area (COMIDA), began in 2008. One objective of this effort 

was to study the distribution of whales during the summer, 

open-water months in the Chukchi Sea Planning Area, a 

resumption of similar surveys that were conducted for many 

years between 1979 and 1991. The Bowhead Whale Feeding 

Ecology Study (BOWFEST) is a multiyear and multiorganization collaborative study integrating aerial surveys, 

physical oceanography, acoustic monitoring, local traditional 

knowledge, and ecosystem analysis to understand the late 

summer distribution of bowhead whales and sources of food 

in the vicinity of Barrow, Alaska (for example, Ashjian and 

others, 2010; Moore and others, 2010). The aerial surveys 

also can be used to study other topics, such as the relationship 

Figure 6–5. Seasonal 

occurrences of the Bowhead 

whale in winter (blue), 

summer (purple), and fall 

(green) migration feeding 

areas, together with general 

migration paths (arrows). From 

Moore and Laidre (2006).
Chapter 6

Marine Mammals and Anthropogenic Noise 181

between the ice edge and location of migration (Treacy, 2002; 

Treacy and others, 2006). Researchers are conducting longterm (multi-year) deployments of acoustic buoys to record 

ambient ocean noise and build baseline time series datasets of 

ambient ocean noise, at least for the few locations where the 

buoys are located (Scripps Whale Acoustic Lab, 2007). Most 

of these long-term and new-generation studies are funded to 

collect data for better understanding the impact of petroleumrelated activities on the bowhead whale.

A significant database of bowhead whale vocalizations 

exists as a result of BOEMRE research (for example, Heimlich 

and others, 2010) and both BP and Shell drilling and seismic 

activities in the Beaufort Sea (for example, Blackwell and 

others, 2007). The BOEMRE research has utilized long-term 

buoy deployments as part of BOWFEST. BP has utilized 

Directional Autonomous Seafloor Acoustic Recorders 

(DASARs) to localize and record bowhead whale calls around 

the Northstar production facility on a gravel island offshore 

Prudhoe Bay. This monitoring has occurred since the facility 

began production in 2000. Shell also has funded acquisition 

of acoustic data from multiple arrays of DASARs on the 

Beaufort Shelf as part of its monitoring and mitigation strategy 

for its seismic exploration program (for example, Thode and 

others, 2008). DASARs have been deployed in multiple years 

for more than 50 days in open-water conditions with the 

intention of being able to conduct statistical analyses of whale 

vocalizations before, during, and after seismic surveys (for 

example, Mathias and others, 2008). Despite shorter peerreviewed publications interpreting the results of these studies, 

these databases of vocalizations generally are proprietary 

and the substantive reports associated with full analysis 

reside in industry archives that are not routinely accessible 

by the public. These DASAR records also have been used to 

investigate long-range sound propagation under the ice and in 

open water north of Alaska (Thode and others, 2010). 

Perhaps the greatest challenge in observations of any 

marine mammal, including the bowhead, is that of visual 

observations (such as with BWASP) can miss animals that are 

submerged or hidden, and acoustic monitoring (such as with 

DASARs) misses animals that are not vocalizing. Adding a 

new dimension to understanding the behavior and distribution 

of bowhead whales is a tagging program that began in 2006, 

utilizing Native community whaling captains and scientists 

working together to tag bowheads in the Barrow (AK) and 

Tuktoyaktuk (Canada) areas. Satellite tracking of individual 

whales has provided information on dive behavior, movement 

and use of habitat (Alaska Department of Fish and Game, 

2011). Integrating these observations with the details of 

seismic (or other anthropogenic) noise is not always rigorous 

because the details of the seismic (or other anthropogenic) 

signals are not always publicized or known other than in a 

general sense. 

For the seven noise categories, we discuss observations 

of bowhead behavior for all but the seismic low-energy 

category. In the summers of 1980–84, general activities of 

bowheads exposed to underwater pulses from seismic vessels 

6–99 km away were observed (Richardson and others, 1986). 

Activities were indistinguishable from those without seismic 

noise; there was no detectable avoidance. In a test involving 

a seismic vessel (30 airguns, source level 248 dB re: 1 μPa, 

closest point of approach = 1.5 km), bowheads began to 

orient away when the airgun array began to fire 7.5 km away. 

However, some whales continued apparent near-bottom 

feeding until the vessel was 3 km away. In general, bowheads 

exhibit avoidance reactions when they receive seismic pulses 

stronger than about 160 dB re: 1 μPa. Evidence of reactions to 

lower received levels remains inconclusive.

Playback studies have found that most bowhead 

whales avoided drillship or dredging noise with broad-band 

frequency range (20–1,000 Hz) when received levels were 

around 115 dB re 1μPa, levels that could occur 3–11 km 

from typical drilling and dredging vessels (Richardson and 

others, 1990). This equates to a response threshold of about 

110 dB re 1μPa in the 1/3-octave band where industrial noise 

is most prominent. Whales may be observed in locations with 

higher noise levels, possibly because alternative habitat is not 

available (Richardson and Greene, 1993).

Bowheads reacted to boats or small ships in two main 

ways. When boats were nearby, whales altered their surfacing 

and diving patterns by decreasing the mean time at the surface 

and mean dive duration. When boats closed to within 3 km, 

the whales, in addition to the above responses, swam rapidly 

away from the boat and scattered (LGL Ecological Research 

Associates, Inc., 1982). In contrast, bowheads were sighted 

as close as 6 km from a seismic ship firing 12 large sleeve 

exploders. Surfacing and respiration behavior was similar to 

that without seismic noise. 

Bowhead whales were less responsive to passing 

aircraft when actively engaged in feeding, social activities, 

or mating, than when resting (Richardson and others, 

1995). Opportunistic observations of behavioral responses 

of bowhead whales to a helicopter and fixed-wing aircraft 

suggested that the helicopter elicited only few responses, and 

most of those occurred when the helicopter was at altitudes 

equal to or less than 150 m and lateral distances equal to 

or less than 250 m. For the fixed-wing aircraft, very few 

bowheads were observed to react, and of those, most reactions 

occurred when the fixed-wing aircraft was at altitudes equal to 

or less than 182 m and lateral distances equal to or less than 

250 m. Most observations of aircraft disturbance have been 

made from aircraft creating the disturbance, greatly limiting 

what can be observed, and precluding comparison of behavior 

before, during, and after disturbance.
182 An Evaluation of the Science Needs to Inform Decisions on Outer Continental Shelf Energy Development in the Chukchi and Beaufort Seas, Alaska

In many of these studies, conclusions often have 

qualifications, for example, of bowhead deflection in one 

observation but not in another. These studies have raised the 

importance of understanding context of the whale activity 

at the time of the observation. Limited visual or acoustic 

observations of wild animals or of small sample sizes 

emphasize the difficulty of generalizing from specific animals 

in specific conditions to conclusions about the potential 

effects on the population. As a whole, there are essentially no 

observations about physical injury or quantitative indicators 

of stress responses, because of the difficulty of making these 

measurements on wild animals. Moreover, although there are 

exceptions, physiological measures of stress rarely point to 

a single causal factor and thus typically are better indices of 

overall health of the habitat in which the population lives.

community, non-governmental organizations, and the Marine 

Mammal Commission (among others) that tend to consistently 

cluster into categories: 

(a) More baseline data are needed to understand behavior 

when there are no seismic surveys;

(b) More verification of sound source levels is required;

(c) More holistic monitoring strategies that integrate visual, 

acoustic, and other observations are needed; and 

(d) More precautionary approaches to mitigation and defining 

the radii of safety zones are warranted. 

6.08. Finding: There are many observations and databases related 

to bowhead whales, but no major integration or synthesis, especially 

for linkages to anthropogenic noise.

6.08. Recommendation: A synthesis of existing databases 

on bowhead population abundance and structure with databases 

giving sources and levels of anthropogenic noise would provide a 

comprehensive framework for analyzing how sounds impact the 

whales. This would presumably require public access to the many 

databases that are within government and industry purview for 

rigorous integration. Particularly illustrative will be integrating 

observations from tagged animals to overall activities.

For the first time in 2010, NOAA, together with 

BOEMRE conducted a peer-review analysis of applications 

for oil-and-gas-related activities in the Beaufort and Chukchi 

OCS areas, and has publicly released the summary of their 

findings (National Marine Fisheries Service, 2010e). One of 

the recommendations is to consider sound from an ecosystem 

perspective. They recommend transitioning away from using 

a single metric of acoustic exposure (that is, sound pressure 

level) to measure the potential effects of anthropogenic sound 

on marine mammals; and to integrate single-criteria mitigation 

strategies (the practical approach) with comprehensive 

assessment. Additional recommendations for improving 

aerial surveys, near-field and far-field visual monitoring, 

and collecting routine baseline biological information were 

included. This peer-review panel integrated scientists, 

regulators, and members of the Native community.

For all that is known about the BCB bowhead whale 

and behavior in the presence of anthropogenic sounds, 

relatively little is known about long-term trends or the 

biological significance of these observations. During the 

Incidental Harassment Authorization permitting process for 

seismic surveys, NOAA receives comments from the Native 

6.09. Finding: Although research is ongoing, the understanding of 

essential spatial and temporal habitat needs of the bowhead whale, 

particularly the oceanographic parameters that most influence 

foraging, breeding, raising young, and migrating is not yet sufficient 

to confidently determine the times and places where whales might 

be most impacted by anthropogenic sounds.

6.09. Recommendation: Understanding the essential spatial 

and temporal habitat needs for the bowhead whale (for example, 

Ashjian and others, 2010) needs to include those areas where the 

introduction of anthropogenic sounds might significantly disrupt 

the whale at key parts of its life cycle. This knowledge base should 

incorporate local traditional knowledge of bowhead whales (and 

other marine mammals) and their habitat contributed by the Native 

community.

6.10. Finding: Much scientific attention focuses on 

understanding the cumulative impacts of anthropogenic sounds 

at the population demographic level for marine mammals, in large 

part because of regulatory requirements. However, the USGS 

OCS Team heard often in our expert consultations that how noise 

affects individual behaviors, short of any health effect, is of great 

importance to Native communities because of concerns of impacts 

on potential hunting success of the subsistence community (see 

appendix A). For example, if the impact means a whale deflects 

offshore it then is unavailable for subsistence use. 

6.10. Recommendation: Behavioral alterations are important 

factors that need to be understood and monitored to ensure 

effective mitigation during the hunting seasons to minimize 

impacts to subsistence hunting. This issue would benefit from 

enhanced integration of industry and agency acoustical monitoring 

network data (whale vocalizations), satellite telemetry data of 

whale movements, local traditional knowledge observations, and 

application of new statistical approaches to assess behavioral 

responses (for example, Blackwell and others, 2010) as a 

framework to better judge under what conditions whales may 

behaviorally respond to (for example, avoid) noise sources.
Chapter 6

Marine Mammals and Anthropogenic Noise 183

Beluga Whale (Delphinapterus leucas)

The Beluga, or white, whale has long been known to be 

a highly vocal species (for example, Schevill and Lawrence, 

1949) and carries the nickname of canary of the sea. Using 

sound, particularly for echolocation, is a trademark of this 

species (Au and others, 1985, 1987). 

Beluga whales are managed as two distinct populations 

in the Arctic OCS: the Eastern Chukchi stock and the Beaufort 

stock. This distinction is based on distribution patterns (Lowry 

and others, 1989) and is supported by molecular genetic 

studies (O’Corry-Crowe and others, 1997). The Beaufort stock 

is estimated to be ten times larger than the Eastern Chukchi 

stock (32,500 versus 3,700; Allen and Angliss, 2010). Neither 

of the Eastern Chukchi or Beaufort stocks is considered 

threatened or endangered (National Marine Fisheries Service, 

2010f). Analysis of biological samples of beluga whales 

harvested for subsistence use has revealed much about stock 

structure, contaminant levels, age, growth, and reproductive 

status, though these statistics may be biased by hunting 

method (for example, Suydam, 2009). Belugas are harvested 

primarily by villages along the Chukchi Sea: a recent analysis 

of historical data showed that only 1 percent of the subsistence 

take of whales in Barrow between 1962 and 1982 was beluga 

whales, and none were harvested between 1987 and 1989 

(Braund and Kruse, 2009). The Native community participates 

in managing the Eastern Chukchi and Beaufort stocks through 

the Alaska Beluga Whale Committee.

Beluga whales also were among the first whales tagged 

and tracked in the Arctic (National Marine Fisheries Service, 

2010g). These early tagging studies revealed that some beluga 

whales ventured deep within ice of greater than 90 percent 

coverage in the summer (for example, Suydam and others, 

2005). These tagging studies have been used to understand 

beluga movement and distribution (for example, Richard and 

others, 2001; Suydam and others, 2001) as well as diving 

behavior (Heide-Jørgensen and others, 1998; Kingsley and 

others, 2001). Arctic OCS belugas migrate annually from 

their wintering grounds presumably in the Bering Sea to 

their summer grounds in the Chukchi and Beaufort Seas 

(Allen and Angliss, 2010). Thus it is important to include 

seasonal information for understanding potential effects of 

anthropogenic sound on these stocks.

Beluga whales survive in captivity and are therefore 

accessible for research on life habit and functions that could 

not be conducted easily on whales in the wild. For example, 

they can directionally echolocate targets in a narrow and 

slightly upward tilted forward direction (Penner and others, 

1986; Au and others, 1987). Although the underwater hearing 

sensitivity of belugas is quite large (Awbrey and others, 1988; 

Johnson and others, 1989b), they are most sensitive to about 

20–80 kHz, which is mostly above the frequencies produced 

in large energy low-frequency seismic surveys used in oil 

exploration (fig. 6–2). In-air hearing has not been measured in 

belugas, but cetacean ears are adapted for underwater function 

and thus in-air hearing likely is very insensitive. Belugas also 

have been extensively studied for temporary threshold shifts in 

hearing, documented through disruption of trained behaviors 

(Finneran and others, 2000, 2002; Schlundt and others, 2000). 

Full recovery of baseline hearing and responses occurred 

within hours. These studies suggest that there is potential for 

acoustic disturbance, possibly from low-frequency surveys but 

more likely from higher frequency sound than is used in deeppenetration surveys.

There are many published studies about hearing, 

behavior, and responses of beluga whales to the kinds of 

sounds associated with Arctic oil and gas activities. When 

exposed to vessel noise, beluga whales can exhibit a variety 

of behaviors ranging from no response to fleeing (see Wartzok 

and others, 2004). Behavioral responses associated with this 

type of noise exposure often are considered transient. An 

unknown is whether repeated short-term behavioral responses 

translate to cumulative or population-level impacts (Bejder 

and others, 2006). At this time, there is limited information 

on whether and to what extent beluga whale migration will be 

affected by changes in shipping.

Beluga reactions to icebreaking are among the most 

cited and dramatic in the literature. Observations of changes 

in pod cohesion, surfacing behavior, and call types indicate 

that belugas detected the presence of icebreaker vessels at 

distances greater than 80 km. They exhibited strong avoidance 

responses at distances 35–50 km away and travelled up to 

80 km from the ship track and typically remained away for 

1–2 days (Finley and others, 1990). Bioacoustic models 

suggest that bubbler systems and cavitation associated with 

icebreaker movement have the ability to potentially mask 

hearing and vocalization of Arctic inhabitants (Erbe and 

Farmer, 1998, 2000). For beluga whales, it was hypothesized 

that the zone of masking could extend from 14 to 71 km from 

the source (Erbe and Farmer, 2000). There is an increased 

possibility of temporary threshold shift if animals are exposed 

6.11. Finding: Beluga whales appear to be unusually sensitive to 

the sounds of icebreaking. 

6.11. Recommendation: Understanding the sensitivity 

of beluga whales to icebreaking might require knowledge of 

the history of exposure to icebreaking or other anthropogenic 

factors to account for the possibility that some belugas may be 

either habituated or sensitized to this type of human activity. 

Application of telemetry to capture information on individual 

movement histories and access to noise histories (for example, 

from inventories suggested in Findings 6.02, 6.03, and 6.04) may 

be required.
184 An Evaluation of the Science Needs to Inform Decisions on Outer Continental Shelf Energy Development in the Chukchi and Beaufort Seas, Alaska

to these types of sounds for an extended duration (that is, for 

animals that do not or cannot alter behavior to avoid this type 

of exposure if, for example, they are confined to a lead within 

heavy ice). 

The reaction of beluga whales to drilling activities has 

been mixed and may be related to context. Observations have 

been made around “operational” artificial islands (Fraker, 

1977a, 1977b; Fraker and Fraker, 1979), around a stationary 

drillship (Norton Fraker and Fraker, 1982), and in playback 

experiments with drilling noise (Richardson and others, 1990, 

1991a). The variety of responses (or lack of responses) from 

these observations “may be another example of the degree 

to which belugas can adapt to repeated or ongoing manmade 

noise when it is not associated with negative consequences” 

(Richardson and others, 1995, p. 283).

Short-term behavioral responses of beluga whales to 

helicopters and fixed-wing aircraft have been noted since 

the late 1970s. Behaviors classified as reactions consisted 

of short surfacings, immediate dives or turns, changes in 

behavior state, vigorous swimming, and breaching (Caron and 

Smith, 1990; Richardson and others, 1991b, 1995). For both 

helicopters and fixed-wing aircrafts, the observed avoidance 

reactions by belugas generally occurred when the aircraft was 

at altitudes equal to or less than 150 m and lateral distances 

equal to or less than 250 m. The dominant low-frequency 

components of aircraft sound may be inaudible, or at most 

only weakly audible, to belugas. Mid-frequency sound 

components, visual cues, or both, probably are important in 

eliciting beluga reactions to aircraft.

Gray Whale (Eschrichtius robustus)

The gray whales that frequent the Chukchi and Beaufort 

Seas are managed as part of the eastern North Pacific gray 

whale population. Gray whales were first listed as endangered 

in 1970 in the Endangered Species Conservation Act, the 

precursor of the Endangered Species Act. After status reviews 

in 1984 and 1991, the eastern North Pacific gray whale was 

delisted from ESA in 1994 (see historical summary in National 

Marine Fisheries Service, 1994). The NMFS conducted a 

5-year status review of the stock in 1999 (Rugh and others, 

1999). In October 2010, the NMFS received a petition to 

again list the gray whale under ESA (California Gray Whale 

Coalition, 2010), but declined to do so in the 60-day review 

(National Marine Fisheries Service, 2010c). The eastern 

Pacific stock has an estimated minimum population size of 

about 17,500 with a population increasing at 1.9–2.6 percent 

per year (Allen and Angliss, 2010). Gray whales typically are 

not harvested as a subsistence resource. 

Gray whales engage in one of the longest annual 

migrations of any marine mammal, travelling thousands of 

kilometers from as far south as Baja California in the winter 

to the Chukchi Sea in the summer. Although gray whales 

sometimes are seen around Barrow, they are a rare occurrence 

when seen east of Barrow in the Beaufort Sea (Nelson and 

others, 1993). The long coastal migration may expose this 

whale to more anthropogenic threats than the other Arctic 

whales because of its migration past major urban centers and 

sources of pollution (Rugh and others, 1999). There are some 

indications that, in the last decade, gray whales have moved 

farther into the Beaufort Sea and delayed their southbound 

migration in the fall (for example, Moore and others, 2003, 

2007; Moore and Overland, 2008). Gray whales have been 

sighted more frequently near Barrow and their calls have been 

recorded in instruments deployed on the Beaufort Shelf during 

the winter (Stafford and others, 2007). Some of these changes 

may be related to changes in the physical environment of the 

north Bering Sea (Grebmeier and others, 2006). 

Studies show gray whales, similar to other baleen whales, 

produce sounds generally below 1 kHz (Crane and Lashkari, 

1996). Whereas gray whale response to anthropogenic sound 

has been studied in lower latitudes, the degree to which those 

results are predictive of whale responses in the Arctic OCS 

areas is speculative in part because the whales have highly 

structured annual cycles of feeding (summer in high latitudes) 

and breeding (winter in low latitudes). In one experiment 

with a long-range sonar, migrating whales avoided exposure 

to the signals when the source was placed within their 

migration corridor (Clark and others, 1999). However, in all 

cases, whales resumed their normal activities within tens of 

6.12. Finding: The present understanding of the essential spatial 

and temporal habitat needs of the beluga whale in the Arctic is 

limited and constrains the ability to confidently understand and 

efficiently mitigate potential anthropogenic noise impacts. Similar 

data limitations exist for many other marine mammal species that 

will be noted in subsequent Findings and Recommendations. 

6.12. Recommendation: Better understanding and inventory of 

essential spatial and temporal habitat needs of the beluga whale, 

particularly the oceanographic parameters that determine foraging, 

breeding, raising young, and migrating, will help managers 

determine how best to protect belugas from the impacts of 

anthropogenic sounds. Knowledge of these critical habitats for the 

beluga whale will enable managers to better identify and protect 

those places and times where the introduction of anthropogenic 

noise might significantly disrupt the whale at key parts of its life 

cycle. 
Chapter 6

Marine Mammals and Anthropogenic Noise 185

minutes after the initial exposure to the signal, making minor 

course changes to go around the source. When the source was 

relocated outside of the migration corridor, but with the signal 

level increased so as to reproduce the same sound field inside 

the corridor, the whales continued their migration unabated. 

This result stresses the importance of context in interpreting 

animals’ responses to underwater sounds (Clark and others, 

1999). 

Gray whale responses to airgun shots included changes 

in swimming speed and direction away from the sound 

sources (Malme and others, 1984), changes from feeding with 

a resumption of feeding after exposure (Malme and others, 

1988), changes in call rates and structure (Dahlheim, 1987), 

and changes in surface behavior (Moore and Clarke, 2002). 

Some behavioral responses were dramatic—whales were seen 

to move into the shallow surf zone and into sound shadows 

of rocks (Malme and others, 1983, 1984). Approximately 

one-half of the gray whales exposed to a single airgun in 

the Bering Sea showed avoidance and noticeable changes in 

respiration behavior (Malme and others, 1986, 1988). There is 

essentially no information describing gray whale behavior in 

the presence of mid- and high-frequency pulsed sources.

Drilling and other continuous sounds have triggered 

avoidance responses in playback experiments with migrating 

gray whales (Malme and others, 1983, 1984). There are 

some data suggesting that gray whales respond to variations 

in underwater noise by changing the structure and timing of 

their calls (Dahlheim and others, 1984; Dahlheim, 1987), 

but it is unknown whether these changes in calling affected 

survival or reproduction. Gray whales were virtually absent 

from a wintering lagoon in Baja California, for several years 

during which shipping increased, possibly caused by the nearconstant dredging needed to keep the channel open. Whales 

returned to the lagoon after shipping decreased (Jones and 

Swartz, 1984). Much of the nearshore range of the gray whale 

is heavily used by vessels and other human activity, which 

suggests habituation to or coexistence with noisy human 

activities (Richardson and others, 1995).

Gray whale responses to aircraft are variable and may be 

context dependent. Some observations suggest that mothercalf pairs off Alaska may be particularly sensitive to small (for 

example, turboprop) survey aircraft (Ljungblad and others, 

1983). Mating gray whales did not react immediately to the 

arrival of a survey aircraft but dispersed after it had circled 

for a few minutes (Clarke and others, 1989). Migrating gray 

whales rarely showed detectable reactions to a straight-line 

overflight by a fixed-wing aircraft at 60 m altitude (Green and 

others, 1992). Playbacks of helicopter noise caused minor 

avoidance reactions in gray whales, suggesting that helicopter 

sound (rather than visual cues) could affect gray whales 

(Malme and others, 1983). 

6.13. Finding: The present understanding of the essential spatial 

and temporal habitat needs of the gray whale in the Arctic is limited 

and constrains the ability to presently confidently understand and 

efficiently mitigate potential anthropogenic noise impacts. 

6.13. Recommendation: Better understanding and inventory 

are needed of essential spatial and temporal habitat needs of the 

gray whale during its summering in the Chukchi and Beaufort Seas, 

particularly the oceanographic parameters that determine foraging, 

breeding, raising young, and migrating. Knowledge of these 

essential habitats for the gray whale will enable managers to better 

identify and protect those places and times where the introduction 

of anthropogenic noise might significantly disrupt the whale at 

key parts of its life cycle. The Chukchi Sea is of primary interest 

because it is a major foraging ground for the gray whale (Rice and 

Wolman, 1971; Fay, 1982). Because the development of petroleum 

resources (or mining for sand) in the Chukchi Sea could occur in 

regions of high concentration of prey species, the gray whale may 

be particularly vulnerable to petroleum-related development in the 

Arctic OCS (Nelson and others, 1994).

Polar Bear (Ursus maritimus)

Polar bears, the top predators in the Arctic marine 

ecosystem, are managed as two distinct populations, the 

southern Beaufort stock (primarily in the southern Beaufort 

Sea) and the Chukchi-Bering stock, which occurs farther south 

and west in both the U.S. and Russian Chukchi Sea (Amstrup 

and others, 2004). Based on satellite radio-telemetry data, a 

large overlap occurs between these two populations (Amstrup 

and others, 2004, 2005). In 2008, the U.S. Fish and Wildlife 

Service (2008) published a final determination to list polar 

bears as threatened under ESA. In 2010, the USFWS further 

published a final determination of critical habitat associated 

with the listing (U.S. Fish and Wildlife Service, 2010).
186 An Evaluation of the Science Needs to Inform Decisions on Outer Continental Shelf Energy Development in the Chukchi and Beaufort Seas, Alaska

Polar bears are a well-studied Arctic marine mammal. 

Research on polar bears in Alaska has occurred since the late 

1960s and numerous estimates of population stock exist (for 

example, Amstrup, 1986, 1995; McDonald and Amstrup, 

2001; Allen and Angliss, 2010). Radiotelemetry was initiated 

in 1981, followed soon after with satellite telemetry, for 

understanding survival and recruitment. Genetic studies have 

helped identify discrete populations (for example, Paetkau and 

others, 1999; Amstrup, 2003). Sufficient data exist to model 

their distribution and denning patterns and examine population 

status and trends (for example, Aars and others, 2006).

Studies also have associated polar bears with 

“ecoregions” (for example, Amstrup and others, 2007). Polar 

bears tend to be more abundant over shallow water of the 

polar continental shelves, suggesting that these areas of higher 

productivity and therefore higher concentrations of potential 

prey are preferred habitat (Amstrup and others, 2000, 2004; 

Durner and others, 2007). Polar bears move in response to 

changing ice conditions and prey availability (Stirling and 

others, 1993; Arthur and others, 1996; Ferguson and others, 

2000a, 2000b; Mauritzen and others, 2001; Durner and others, 

2004, 2006, 2009). There are some data indicating that polar 

bear distribution may reflect factors such as prey availability, 

energetic costs, and safer ice conditions (for example, 

Mauritzen and others, 2003). 

Despite the abundant research on the baseline biological 

information of the polar bear, relatively little information 

exists regarding its hearing, use of its auditory functions in 

survival or reproduction, and impacts from anthropogenic 

sounds. Importantly, in contrast to other marine mammals, 

the polar bear spends most of its life out of the water. When 

swimming, it carries its head above the water surface. Thus, 

while extremely intense underwater sound may impact a polar 

bear while in the water, the impacts of anthropogenic sound 

are considered primarily to be from sounds in air.

There are no measurements of the underwater hearing 

of polar bears. In-air hearing was measured using evoked 

auditory potentials on three anesthetized polar bears 

for frequencies of 1.4–22.5 kHz (Nachtigall and others, 

2007). Results can not be taken as measures of absolute 

sensitivity, but sensitivity was relatively flat across the 

range of frequencies tested with a slight peak from about 

11.2–22.5 kHz. 

Ecological observations support these measured hearing 

ranges. Ringed seals (Phoca hispida) and bearded seals 

(Erignathus barbatus) are prominent in the diet of polar bears. 

Ringed seals produce underwater sounds in these frequency 

ranges (2–8 kHz; Stirling, 1973) suggesting that polar bear 

hearing can optimally detect and locate this preferred prey. 

Playback of ringed seal calls in the air has triggered changes 

in behavior in captive polar bears (for example, Cushing and 

others, 1988). Polar bears also may be able to detect and locate 

bearded seals by their distinctive underwater trills (Stirling 

and Thomas, 2003).

Many observations document polar bear responses to 

anthropogenic sound. On-ice seismic techniques (Vibroseis) 

have caused polar bears to locally (and temporarily) leave 

the area (Richardson and others, 1995). Moore and Quimby 

(1975) reported that females with cubs abandoned their dens 

during nearby seismic exploration activity, and this effect 

was more pronounced early in the denning season (Linnell 

and others, 2000). Polar bears appear to tolerate sounds and 

vibrations associated with stationary drill rigs on caissons and 

artificial islands (Stirling, 1988; Amstrup, 1993). Polar bear 

reactions to vessels and icebreakers are unremarkable (Fay 

and others, 1984). Reactions may include walking, running, 

or swimming away, and generally are of short duration; some 

bears show no reactions (for example, Richardson and others, 

1995, and references therein). Helicopters are sometimes 

used to frighten polar bears away from human activities or 

facilities, and low-flying aircraft are known to cause polar 

bears to run away (Shideler, 1993). In general, these studies 

support the notion that polar bears may be sensitive to some 

kinds of in-air sounds. 

6.14. Finding: Joint industry-agency programs have successfully 

mitigated, to date, the disturbance effects of oil and gas activities, 

including noise, on polar bears in the U.S. Arctic. An example of 

this has been the development of polar bear denning models to help 

define potential denning sites for avoidance during winter on-land 

seismic surveys and the application of Forward-Looking Infrared 

(FLIR) imagery for real-time monitoring and den avoidance. But 

declines in sea ice are resulting in changes in polar bear distribution 

and in denning habitat, as well as body condition and survival 

patterns, and portend declines in overall population size. 

6.14. Recommendation: Broadly, and with respect to 

noise, to successfully mitigate the effects of existing and new 

development in the Arctic under changing climate conditions will 

require continual reassessment of what is understood about polar 

bear distribution and habitats to ensure mitigation measures are 

accomplishing intended outcomes. 
Chapter 6

Marine Mammals and Anthropogenic Noise 187

Ice Seals 

Of the Arctic marine mammals, ice seals remain the least 

known and studied. For each of the ice seal species, the 2009 

stock assessment begins “A reliable minimum population 

estimate for this stock cannot presently be determined 

because current reliable estimates of abundance are not 

available” (Allen and Angliss, 2010). Subsistence harvests are 

incompletely known (for example, Allen and Angliss, 2010). 

Some progress is being made to identify habitat requirements 

(for example, Cameron and others, 2010). The large range 

over which these animals are found, their generally low 

densities, cryptic or incompletely understood behaviors, 

their habitat across multiple political boundaries, lack of 

information about how ice seals use habitat, the inability to 

correct inventories for seals in the water, and the high costs 

associated with surveying large areas remain the greatest 

impediments to improving the knowledge base (Boveng and 

others, 2008, 2009). 

Four species of ice seals are found in the Chukchi 

and Beaufort Seas: bearded (Erignathus barbatus), ribbon 

(Histriophoca fasciata), ringed (Pusa hispida), and spotted 

(Phoca largha). In contrast to the three species that are yearround Beaufort and Chukchi inhabitants, the spotted seal is 

only a seasonal summer visitor to the Beaufort and Chukchi 

Seas. Neither spotted nor ribbon seals are listed as threatened 

or endangered according to ESA (table 6–3).

The distribution and life history of these seals are 

intimately linked to the presence of ice and snow: mating 

occurs near the ice edge; subnivean lairs (for the ringed 

seals) are utilized as dens for whelping and nurturing pups; 

whelping coincides with near-maximum ice extent; and 

adult seals undergo annual molting after which seals spend 

prolonged periods out of water on the ice warming the skin in 

the sun during late spring and summer (Hopcroft and others, 

2008). The timing of snow and ice melt may be critical to the 

survival or reproduction of ringed seals (for example, Kelly, 

2001; Smith and Harwood, 2001; Stirling and Smith, 2004). 

When they are not breeding, ice seals may move hundreds or 

thousands of miles through the Arctic and surrounding waters 

(Kapel and others, 1998; Lowry and others, 1998; Harwood 

and others, 2000). 

During the late 1970s and 1980s, the OCS Environmental 

Assessment Program (OCSEAP) funded and supported 

numerous studies of ice seals in conjunction with the increased 

OCS exploration activities in the Arctic, identifying some of 

the diet and trophic relations for these animals. After a hiatus 

in the 1990s, renewed research began with the formation 

of the Ice Seals Committee in 2005 consisting of members 

of the Native community for the purpose of developing a 

coordinated plan for management of ice seals in Alaska (for 

example, Ice Seal Committee, 2006). Tagging of bearded seals 

(starting in 2004) and ringed seals (starting in 2007) initiated 

with the Native village of Kotzebue (http://kotzebueira.org, 

accessed April 14, 2011) and biologists significantly added to 

the knowledge base about specific individuals for the duration 

6.15. Finding: There is a basic lack of information about ice 

seals. Key information about the abundance, distribution, and vital 

aspects of ice seals is incomplete. (Information on ice seal auditory 

characteristics and response to sound also is lacking and will be 

discussed in Findings and Recommendations 6.16 and 6.17). 

6.15. Recommendation: Habitat requirements of ice seals 

need to be better identified and quantified, particularly the 

importance of habitat in the context of seasonal activities. Annual 

harvest rates for subsistence needs should be estimated more 

consistently. Knowledge of such basic biological information should 

be integrated across political boundaries of the Nations in which 

the species occur (for example, Canada and Russia). For example, 

ringed seals from the Beaufort and Chukchi Seas were radio- and 

satellite-tracked showing that in the summer, they ranged up to 

1,800 km from their winter/spring home, but returned to the same 

small (1–2 km2) winter sites (Kelly and others, 2010). During the icebound winter and spring (including breeding season), ringed seals 

are therefore spatially limited in their foraging ability for significant 

parts of the year. If ringed seals cannot habituate to oil and gas 

activities or utilize human-free habitat, they may be limited in their 

ability to adapt.

Table 6–3. Ice Seals—Endangered Species Act (ESA) Information. 

Seal Status review Federal Register Notice ESA listed 

for the Arctic

Bearded Cameron and others, 2010 December 10, 2010 Candidate

Ribbon Boveng and others, 2008 December 30, 2008 No

Ringed Kelly and others, 2010 December 10, 2010 Candidate

Spotted Boveng and others, 2009 October 20, 2009

October 22, 2010

No
188 An Evaluation of the Science Needs to Inform Decisions on Outer Continental Shelf Energy Development in the Chukchi and Beaufort Seas, Alaska

The effects of seismic surveys on ice seals have been 

summarized in the 2010 status review of the bearded seal:

“Reported seal responses to seismic surveys have 

been variable and often contradictory, although they 

do suggest that pinnipeds frequently do not avoid the 

area within a few hundred meters of operating airgun 

arrays (Brueggeman and others, 1991; Harris and 

others, 2001; Miller and Davis, 2002). Telemetry 

work by Thompson and others (1998) indicated that 

harbor seals and grey seals (Halichoerus grypus) 

exhibit strong avoidance behavior of small seismic 

airgun arrays, including swimming rapidly away 

from seismic sources, ceasing feeding activities, and 

hauling out, possibly to avoid underwater noise. The 

behavior of most of the seals reportedly returned to 

normal within 2 hours of the seismic array falling 

silent. The authors suggested that responses to more 

powerful commercial arrays might be more dramatic 

and occur at greater ranges.”

 (Cameron and others, 2010, p. 162)

Tagging studies conducted on ringed seals in 2001, 

when Canadian marine seismic surveys were occurring, 

did not appear to affect the timing or route of the western 

fall migration of ringed seals in the Beaufort Sea (Cott and 

others, 2003). Ringed seals in the Prudhoe Bay region often 

tolerated exposure to high received levels (180–190 dB re: 

1 μPa rms) of low-frequency sound pulses from airgun arrays, 

with little evidence of changes in behavior and no more than 

localized avoidance (Harris and others, 2001; Moulton and 

Lawson, 2002). Many seals remained within 100–200 m of 

the operating airguns, which is often within the radius where 

received sound levels are greater than 190 dB re 1 μPa (rms). 

There are seemingly inconsistent results concerning reactions 

of seals to small airgun sources (Blackwell and others, 

2004b). The seals may initially show an avoidance response 

to these sounds, but rapidly habituate, demonstrated by their 

adjustment to Acoustic Harassment Devices that are similar to 

sounds used in sub-bottom surveys (Richardson, 2002).

There are few data on auditory threshold shifts, either 

temporary or permanent, for ice seals. In experiments 

done primarily on sea lions, the results from pulsed sounds 

(Finneran and others, 2003) and continuous, but lower 

energy, octave band noise (Kastak and others, 1999, 2005) 

demonstrated the importance of considering both amplitude 

and duration when estimating the impacts of sounds on marine 

mammals and these results are reiterated by Southall and 

others (2007). Each of the ice seal reviews conducted by the 

NOAA (table 6–3) suggested that “Although it is unlikely 

that airgun operations during most seismic surveys would 

cause PTS in (bearded, ribbon, ringed, or ice) seals, caution is 

warranted given the limited knowledge about noise induced 

hearing damage in this species.”

of the tagging (generally less than 1 year). Each of the ice 

seal species has undergone extensive reviews in the past 

4 years as part of the process by which the NOAA determines 

whether the species should be listed under the ESA. The major 

reviews summarizing biological knowledge of the species and 

associated Federal Register notices for ice seals are given in 

table 6–3.

Bearded and ringed seals are primary prey of polar bears 

as well as food for the Native community. The bearded seal is 

the largest of the seals and preys on benthic organisms. Hence 

they are more frequently found in shallow water areas where 

light can sustain a benthic ecosystem (for example, less than 

200 m water depth). The ringed seal, also an important food 

source for the Native community, is the smallest of the ice 

seals and feeds on fish, so it can travel long distances over 

deep water along and within the ice (Kelly and others, 2010). 

As with other marine mammals, ice seals are thought 

to use sound to aid in navigation, to socialize, and to avoid 

predators. Typically, pinnipeds are thought to spend as 

much as 80 percent of their time in the water (Gordon and 

others, 2004); thus anthropogenic sound associated with 

seismic surveys, vessel noise, icebreaking, and drilling may 

potentially disturb their habitat, distribution, and behavior. 

Ice seals make variable vocalizations in the water, generally 

associated with mating (for example, Watkins and Ray, 1977; 

Boveng and others, 2009; Cameron and others, 2010). The 

underwater hearing sensitivity for ringed seals showed peak 

sensitivities between about 4–16 kHz, although sensitivity 

to frequencies below 1 kHz was not measured (Terhune and 

Ronald, 1975). Based on the similarity of these hearing ranges 

to the hearing of many other pinnipeds, one might expect that 

the other ice seals also have hearing at similar ranges (Moore 

and Schusterman, 1987). A recent review suggests that the 

auditory bandwidth generalized for all pinnipeds in water 

should be about 75 Hz – 75 kHz (Southall and others, 2007). 

Most seismic surveys have peak energy below 200 Hz, hence 

the level of disturbance expected from large seismic surveys is 

at the low end of pinniped hearing. 

6.16. Finding: Basic auditory information about ice seals is 

lacking. 

6.16. Recommendation: Key information about the amplitude, 

character, seasonal variation, and function of vocalizations of 

ice seals as well as studies of pinniped diving profiles, auditory 

structures, and physiological effects of sound are needed. This 

information is essential for determining whether and how 

anthropogenic sounds could mask, impact, or injure these animals.
Chapter 6

Marine Mammals and Anthropogenic Noise 189

Reactions of most pinnipeds to drilling and related 

activities have not been extensively studied. Ringed seals are 

often seen near drillships drilling in the Arctic during summer 

and autumn. As part of construction efforts for the Northstar 

oil production island 5 km offshore of Long Island, northwest 

of Prudhoe Bay, Alaska, in the western Beaufort Sea, ringed 

seals showed little or no reaction to any industrial noise except 

approaching helicopters (Blackwell and others, 2004b). There 

is no evidence of reduced seal densities near the Northstar 

gravel island drilling platform (Moulton and others, 2003). 

Very few data exist for the effects of vessels and icebreaking 

on ice seals, but observations suggest sensitivity occurs only 

when icebreaking occurred within several hundred meters of 

the seals (for example, Kanik and others, 1980; Brueggeman 

and others, 1992). It was not clear whether vessel noise or 

visual cues triggered the escape responses. 

Noise disturbance to ice seals also must account for 

in-air sound, although few data exist for this. When on the ice, 

ringed seals and bearded seals often dive when approached 

by low-flying aircraft or helicopters, but do not always do so 

(Burns and others, 1982). Spotted seals may be particularly 

sensitive to low-flying aircraft leading to concerns about 

potential separation of mothers and pups during nursing (Frost 

and others, 1993; Richardson and others, 1995). The levels of 

received sound are unknown in these observations.

Pacific Walrus (Odobenus rosmarus divergens)

The Pacific walrus ranges across the continental shelf of 

the Bering and Chukchi Seas but is only infrequently observed 

in the Beaufort Sea (for example, Allen and Angliss, 2010). 

Walruses winter in the Bering Sea in large communities and 

move north with the ice edge as the pack ice recedes each 

summer (Fay, 1982). Ice is essential for their existence, 

providing a location to rest, molt, give birth, and escape 

predators (Richard, 1990). Land aggregations are becoming 

more common as the ice recedes north of the Chukchi and 

Beaufort Shelf edges (Jay and Fischbach, 2008). Although 

walruses can dive deeper than 200 m (Born and others, 2005), 

they typically live where water depths are less than 80 m so 

that the benthic communities they prefer for prey are more 

easily reached (Fay and Burns, 1988; Jay and others, 2001). 

Radio tags and more recently satellite tags are beginning to 

yield more continuous measurements of walrus activities 

(Jay and Fischbach, 2008). Walruses can significantly disturb 

seafloor sediment during feeding on benthic organisms, and 

are thought to be a major influence the structure of benthic 

ecosystems of the Chukchi and Bering Seas (for example, 

Oliver and others, 1983). 

The current estimate of minimum population size for 

the Pacific walrus is approximately 129,000 individuals, with 

insufficient data to determine annual trends in abundance 

(Allen and Angliss, 2010). As a result of a petition filed by the 

Center for Biological Diversity in 2008, the USFWS issued 

a 90-day finding on September 10, 2009, that the petitioners 

had submitted enough scientific information to indicate that 

listing of the Pacific walrus under ESA may be warranted 

(U.S. Fish and Wildlife Service, 2009). On February 10, 2011, 

the USFWS issued their 12-month finding that listing the 

Pacific walrus as endangered or threatened is “warranted but 

precluded” (U.S. Fish and Wildlife Service, 2011). 

Walruses can be extremely vocal when out of the 

water and produce a variety of sounds in the water (Ray and 

Watkins, 1975). Only the male walrus makes the unusual 

“bell” sound comprising two frequencies produced in 

succession (Schevill and others, 1966). Tests of hearing on 

captive walruses indicate that underwater hearing sensitivity 

covers a broad range of frequencies, with the best hearing 

generally above 1 kHz, although sensitivity was good down to 

125 Hz (Kastelein and others, 2002). In-air hearing sensitivity 

was measured from 125 Hz to 8 kHz, with best sensitivity 

between 1 and 8 kHz and rapid decline below 1 kHz 

(Kastelein and others, 1993, 1996). Similar to ice seals, lowfrequency seismic surveys are likely to impact the low-end 

of the walrus hearing spectrum whereas medium- to highfrequency hazards surveys are more likely to coincide with the 

range of walrus hearing. 

6.17. Finding: There is a lack of information on the response of ice 

seals to aircraft or differential response to fixed-wing aircraft versus 

helicopter. 

6.17. Recommendation: Controlled exposure (sound playback) 

experiments with ice seals might aid in understanding their 

hearing sensitivities and reactions. At any given moment, behavior 

in free-ranging animals is controlled by a multitude of factors 

including the individual’s internal physiological state, physical 

environmental conditions, time of day and time of year, the behavior 

and distribution of peers, behavior and distribution of other species 

(including predators and prey), and human activity. When making 

passive observations, any observed behavior in an individual may 

be caused by the anthropogenic factor under study, other natural 

factors, or some combination of both. Controlled exposure is a 

quasi-experimental method used to evaluate response to sound by 

observing the behavior of free-ranging animals before, during, and 

after exposure to specific sound (for example, Tyack, 2009), either 

by playback of recorded sounds using an underwater sound system 

or by controlling the sound of a vessel, sensor (for example, sonar), 

or tool (for example, airgun, bubbler, pipe driver).

These experiments might determine whether observed responses 

could have been caused by the sight, sound, or vibration associated 

with the noise.
190 An Evaluation of the Science Needs to Inform Decisions on Outer Continental Shelf Energy Development in the Chukchi and Beaufort Seas, Alaska

Walrus appear to be sensitive to some noises and can 

stampede from haulouts in response to sight, sound, and odors 

of humans (for example, Fischbach and others, 2009). It is not 

currently understood whether these reactions are uniformly 

caused by visual, olfactory, or vibrational cues rather than 

noise. A similar uncertainty exists about the cause of some 

walrus reactions to vessels either in open water or during 

icebreaking, particularly whether avoidance responses are 

triggered by ship noise versus sight and smell of the vessel 

(for example, Fay and Kelly, 1982; Fay and others, 1984). 

When near icebreakers, most walruses on ice were more 

cautious of vessels compared to walruses in the water (Fay and 

others, 1984). The observed reactions were commonly waking 

up, raising their heads, or entering the water. Some walruses in 

the water reacted by hauling themselves out of the water. 

Walrus responses to drilling operations are closely 

linked to icebreaking because of ice management during 

drilling. During the 1989–91 drilling of the Popcorn, Burger, 

Crackerjack, and Diamond wells in the Chukchi Sea (Minerals 

Management Service, 2005), escape responses were more 

frequent the closer the icebreaker operated to the walrus 

(Brueggeman and others, 1990, 1991, 1992). Evidence from 

aerial surveys in one study suggested that walruses may have 

avoided the area of icebreaking by as much as 10–15 km 

(Brueggeman and others, 1990), which contrasts with reports 

of avoidance only at much shorter distances (Fay and others, 

1984). Icebreaking may have the potential to cause behavioral 

avoidance or injury, and for these communal large animals, 

may degrade habitat by reducing floe size and availability for 

haul out. Animals that show no avoidance may be undisturbed, 

but alternatively may be disturbed but have no avenue of 

escape. 

Responses of walrus to aircraft (both helicopters and 

fixed-wing aircraft) were similar, in that the level of response 

was usually related to distance and altitude of the approaching 

aircraft (Johnson and others, 1989a). Aircraft overflight of 

walrus haulout locations have triggered stampedes from 

flight elevations of 150–800 m (Fay, 1981; Ovsyanikov and 

others, 1994). Stampedes may lead to trauma, injury, and 

death of walruses, particularly calves. One study identified 

different reaction distances depending on whether a helicopter 

approached the walrus group from an upwind or downwind 

direction (Fay and others, 1984), raising the possibility that 

smell could have been a factor in the response. 

6.18. Finding: Considerable uncertainty exists about whether 

walrus reactions to anthropogenic activities are caused by sight, 

sound, or smell. Quantitative data are lacking about the character 

of deep-penetration, high-resolution seismic and other acoustic 

sounds (such as sonar or chirp) and the responses of walruses to 

these sounds. 

6.18. Recommendation: Basic information about walrus 

reactions to anthropogenic sound, particularly seismic and 

acoustic sounds, needs to be better documented and studied. 

Detailed studies that examine responses in controlled 

environments could help efficiently elucidate key areas of 

walrus response. This information coupled with quantitative 

characterizations of anthropogenic noise sources could better 

define whether and how these kinds of anthropogenic sounds 

could mask, impact, or injure walrus.

6.19. Finding: There is a newly emerging, yet still incomplete 

understanding of the manner in which walruses select their 

benthic foraging habitats (Jay and others, 2011) and limited 

information on the role of walruses in ecosystem structure. 

Such information is needed (in concert with information in 

Recommendation 6.18) to assess if seasonal, annual, or persistent 

sources of anthropogenic sound may cause walruses to avoid 

certain places or times. And, if so, what the effect might be to 

both population and ecosystem.

6.19. Recommendation: Better understanding and inventory 

of essential spatial and temporal habitat needs of Pacific 

walrus during its summering in the Chukchi Sea, particularly the 

oceanographic parameters that determine foraging, are needed. 

Should evidence develop that walrus are displaced due to 

human-generated sound, future studies will be needed to assess 

if cascading ecological consequences result. Walrus modify the 

seafloor during their foraging by resuspending sediments, which 

in turn may enhance primary productivity by releasing nutrients 

into the water and maintaining sand substrates on the seafloor 

as fine-grained muds and silts are suspended, for example, and 

carried by the Alaska Coastal Current (Nelson and others, 1994). 
Chapter 6

Marine Mammals and Anthropogenic Noise 191

Conclusions: While scientific uncertainty exists regarding the scope and nature of environmental disturbances arising from 

anthropogenic sound sources in the oceans, and particularly in the Beaufort and Chukchi Seas, some simple conclusions may still be 

drawn. 

•	 Sound is of vital biological importance to the marine mammals of interest in the Arctic, and anthropogenic noise can have 

various adverse effects. The wide-scale introduction of commercial, military, and research activities into Arctic areas that will 

accompany oil and gas activities, with concomitant associated increases in anthropogenic sound, are very likely to impact both 

the acoustic environment and the sound-centric marine mammals living there. 

•	 Vessel activities and other industrial sound sources increase sound in the oceans; the Beaufort and Chukchi Seas offer the 

unique opportunity to measure and understand both the increase in anthropogenic sound and its potential impacts on marine 

mammals because these areas are essentially pristine with limited anthropogenic sound sources compared to the rest of the 

oceans around the United States. 

•	 Different species hear and use sound differently. Therefore, impacts from anthropogenic sound will vary by sound source (for 

example, vessel operation, seismic, and hydroacoustic devices, icebreaker operations), as well as by marine mammal species. 

•	 Very few of the impacts from anthropogenic sound are expected to include direct physical injuries to hearing (or other systems) 

of the marine mammals. 

•	 Concern regarding behavioral disturbance and avoidance of key areas is a major concern for the Native community. Any change 

in individual marine mammal behavior that causes the animal to move away from coastal waters, particularly the bowhead 

whale, has the potential to make the animals unavailable for subsistence hunting.

•	 Cumulative-, population-, and ecosystem-level impacts of exposure to chronic sources of anthropogenic sound from oil and 

gas activities remain poorly understood but are important considerations, particularly for the survival, sustainability, and 

reproductive health of marine mammals. 

•	 Key knowledge gaps include baseline data from which to measure the changes that might be caused by the introduction of 

anthropogenic sound, inventories of anthropogenic sound (especially vessels and seismic sources), and the spatial and temporal 

habitat needs of the marine mammals of concern. 

•	 The Native community has much at stake in the regulatory process and has much knowledge, both traditional and local, to offer 

in augmenting scientific studies about marine mammals and anthropogenic sound. 

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Cumulative Impacts 203

Chapter 7

Chapter

7

Introduction

 The final topic the USGS OCS 

Team was asked to consider was that of 

cumulative effects. Here we examine 

the state of cumulative impact or effect 

assessment approaches and the present 

challenges of conducting science-based 

cumulative effect analyses in the Arctic.

Cumulative impacts are the combined, 

incremental effects of human activity. 

 Cumulative impacts can result 

from factors that may be insignificant 

by themselves but significant when 

interacting and (or) accumulating over 

time and space, through repetition, or 

in combination with other effects. When 

actions are considered individually 

or independently, their combined 

consequences—or cumulative 

impact—may not be fully considered 

or evaluated. This results in not 

understanding, and not considering, the 

long range impact of multiple decisions 

over a large area.

Cumulative Impacts 

 By Brenda Pierce

The impetus to study and evaluate cumulative impacts lies with 

the passage of the National Environmental Policy Act (NEPA) of 

1969. The NEPA requires Federal agencies to develop Environmental 

Impact Statements and Environmental Assessments for major projects. 

However, if these studies are done independently of one another and 

considered separately, the studies may not take into account cumulative 

effects from each activity on the whole and the projects’ effects may not 

be fully accounted for nor be taken into account in the final decision.

The Council on Environmental Quality (CEQ) was established 

under NEPA. The CEQ’s regulations (40 CFR Part 1500–1508) 

implementing the procedural provisions of the NEPA (Council on 

Environmental Quality, 1997) define cumulative effects as:

“The impact of the environment which results from the 

incremental impact of the action when added to other past, 

present, and reasonably foreseeable future actions regardless 

of what agency (Federal or non-Federal) or person undertakes 

such other actions.”

The words “effects” and “impacts” are used synonymously in CEQ’s 

NEPA regulations, which govern NEPA implementation (Council on 

Environmental Quality, 1984). Effects and (or) impacts are meant to be 

inclusive and include ecological, aesthetic, historical, economic, social, 

and health, and are both beneficial and detrimental.

Cumulative effects result from spatial (geographic) and temporal 

(time) environmental disturbances and both must be given consideration 

in analyzing cumulative impacts.

The National Research Council (NRC) conducted a study on the 

cumulative effects of oil and gas activities on Alaska’s North Slope 

(National Research Council, 2003). That study, which focused on the 

onshore portion of oil and gas development, is the most comprehensive 

look at the considerations that should go into cumulative impact 

analyses. The National Research Council (2003) emphasized the fact 

that significant research has been carried out in Arctic Alaska over the 

last several decades, but that an integrated, comprehensive assessment of 

those effects has not been attempted. That is still true today—there are 

a significant number of important and landmark environmental studies, 

and there are some studies of cumulative effects, but no integrated, 

comprehensive assessment of those effects has been conducted or even 

attempted.
204 An Evaluation of the Science Needs to Inform Decisions on Outer Continental Shelf Energy Development in the Chukchi and Beaufort Seas, Alaska

Policy decisions are usually made at the regional or 

national level, but environmental effects are usually analyzed 

and assessed at the project level. Decisions and permitting of 

industrial activities are often done on a case by case basis by 

many different entities and therefore without the benefit of a 

comprehensive plan or understanding of the scope, intensity, 

and consequences of the industrial activities. Long-term 

decision making and land and resource management must take 

into account the cumulative impact of the nature and extent of 

the benefits and challenges and the costs of both. 

Considerations in Conducting Cumulative 

Impact Studies

The Council on Environmental Quality’s (1997) 

guidance emphasizes the need to incorporate a cumulative 

impact evaluation in the development of alternatives for an 

Environmental Analysis or Environmental Impact Statement. 

It stresses that only by considering cumulative effects can 

appropriate mitigation and monitoring measures be effectively 

developed. 

The CEQ suggests that in conducting cumulative impact 

analysis, the life cycle of effects and impact zones, rather than 

individual projects, should be evaluated. It emphasizes that 

looking at the affected environment in a cumulative impact 

analysis is basically the same as it is in a project-specific 

analysis, with the important addition that the analysis should 

be extended in terms of geography, time, and the potential 

for resource or system interactions. In project-specific NEPA 

analysis, description of the affected environment is based on a 

list of resources that may be directly or indirectly affected by 

the proposed project. In cumulative effects analysis, there is 

an attempt to identify and characterize effects of other actions, 

including those of other geographic areas or other time frames, 

on these same resources. 

To conduct a cumulative effects analysis, one should 

understand what would occur in the absence of a given 

activity. This is best done when there are reliable baseline 

data available for the analysis and by using tools that indicate 

ecological integrity and landscape conditions. This is 

important because when an analysis is performed, the baseline 

or thresholds of environmental change are set, thus influencing 

the cumulative impact assessment. Effects typically 

accumulate as the result of repeated activities, but also may be 

affected by a single action or event if significant. Therefore, a 

full cumulative impact analysis requires multiple assessments.

It is very important to be transparent regarding the 

uncertainties associated with any of these studies, especially 

in cumulative impact. There will always be uncertainty, as 

there will never be enough data and information on every 

facet of the impact of development to know the impact in 

its full extent. Therefore, it is important to be transparent 

about what data do or do not exist and what is modeled and 

what is empirical, so the users of the information understand 

the extent of the uncertainty surrounding the assessment or 

impact.

Conducting cumulative impact analysis needs to be an 

iterative process. Results from cumulative impact assessments 

should contribute to refining alternatives and designing 

mitigation techniques and approaches. Thus, monitoring 

change and the accuracy of the predictions made is an 

important part of cumulative impact analysis and contributes 

directly to the success of the mitigation measures.

The U.S. Environmental Protection Agency (USEPA) has 

review guidance regarding the NEPA and cumulative effects 

and suggests that its reviewers determine whether resources 

are cumulatively impacted by considering the following (U.S. 

Environmental Protection Agency, 1999): 

1. Whether the resource is vulnerable to incremental 

effects; 

2. Whether the proposed action is one of several similar 

actions in the same geographic area; 

3. Whether other activities in the area have similar 

effects on resources; 

4. Whether these effects have been historically 

significant for this resource; and 

5. Whether other analyses in the area have identified a 

cumulative effects concern.

Some project analyses consider only certain resources 

and only direct impacts or limited impacts among those 

particular resources. To conduct a cumulative impact analysis, 

consideration must be given to a broader array of effects, such 

as ecosystems functions (for example, ability to minimize 

downstream flooding or improve water quality) instead of 

simply the acreage of wetland potentially lost by a project. 

Other potential effects to consider, as suggested by the U.S. 

Environmental Protection Agency (1999), include changes in 

hydrologic patterns, alteration of discharge and water retention 

rates, changes in water velocity, secondary or tertiary effects 

of chemicals in the wetland and how plants may take up those 

chemicals, to name just a few. 

Additionally, some analyses limit the area considered to 

those areas over which an agency might have direct purview 

or management authority (U.S. Environmental Protection 

Agency, 1999). This limits the full evaluation of cumulative 

impacts, because impacts may be caused by factors outside 

the specific project’s spatial or temporal scope, including 

the life of the project. For example, the effects sometimes 

last longer than the project’s useful life, and (or) future 

related or unrelated projects will be additive to the effects of 

the one considered project, and so should not be evaluated 

independently.
Cumulative Impacts 205

Chapter 7

The USEPA guidance document (U.S. Environmental 

Protection Agency, 1999) points out that past environmental 

conditions are not adequately addressed in most cumulative 

impact analyses—not fully analyzing how the system 

has changed from previous conditions and thus not fully 

accounting for the cumulative impact. Because the Arctic has 

had very little development thus far, we are in a somewhat 

unique situation in which there have been few previous 

impacts so today’s conditions form our baseline. 

It is true that there have been activities in the Arctic, 

including seismic surveys in State and Federal waters, some 

drilling, acoustic surveys, vessel traffic, aircraft surveys, and 

hunting activities, but the amount is less than in many other 

areas under consideration for oil and gas development. Human 

industrial activities in the Alaskan Arctic have been limited 

primarily to petroleum-related activities in the southeastern 

Beaufort Sea. The Arctic environment is experiencing 

large-scale transformation associated with climate change 

that eventually may result in an opening of frontier areas to 

increased human developments and commerce associated 

with fisheries, shipping, and tourism. The relative absence 

of human activity presents a unique regional opportunity to 

develop and analyze the cumulative impacts in a relatively 

pristine environment and show how cumulative effects can be 

studied and properly evaluated.

To evaluate or analyze cumulative impacts, one needs 

to determine whether the effects interact or accumulate over 

time and space. Effects most often accumulate as a result 

of repeated or compounded activities. However, individual 

or single actions also can contribute to cumulative impacts, 

especially if the effects persist for a long time and (or) are 

augmented by the effects of other activities. As early as 1986, 

a National Research Council (1986) study identified the most 

important factors in regards to cumulative effects (and were 

reiterated in the 2003 NRC study). These factors generally 

agree with the Council on Environmental Quality’s (1997) 

identified examples of cumulative effects:

• Time crowding—frequent and repeated effects on a 

single environmental medium.

• Space crowding—high density of effects on a single 

environmental medium.

• Compounding effects—synergistic effects 

attributable to multiple sources on a single 

environmental medium.

• Thresholds—effects that become qualitatively 

different once some threshold of disturbance is 

reached.

• Nibbling—progressive loss of habitat resulting 

from a sequence of activities, each of which is fairly 

innocuous, but the consequences for the environment 

accumulate.

Because cumulative impact assessments are difficult 

undertakings, the National Research Council (2003) described 

several essential components:

• Specify the class of actions whose effects are to be 

analyzed.

• Designate the appropriate time and space domain in 

which the relevant actions occur.

• Identify and characterize the set of receptors to be 

assessed.

• Determine the magnitude of effects on receptors 

and whether those effects are accumulating.

Thus, for example, specific activities might include seismic 

exploration and whether these activities had significant effects 

on specific receptors, such as specific species or subsistence 

hunting. One of the most challenging aspects of conducting 

a cumulative impact analysis is determining the area and 

vulnerable resources over which the effects have occurred or 

will occur.

In addition to identifying and evaluating the accumulation 

of effects, factors such as magnitude, biotic impact, recovery 

times, and socioeconomic importance must be evaluated.

Arctic Alaska

Energy and mineral resources are significant in Arctic 

Alaska (Chapter 2, Geological Context), and the large 

potential of oil and natural gas resources is of near term 

interest. Production of some of these resources is already 

underway, especially onshore, yet many of the areas of 

Arctic Alaska have not yet been influenced by such industrial 

activity. As sea ice continues to retreat and allows for more 

navigation, use of Arctic waters for activities, such as tourism 

and shipping, is expected to add to the effects of industrial 

development. Further complicating the issues are those of 

transboundary impacts—including the United States and 

Canada for the Beaufort Sea and the United States and Russia 

for the Chukchi Sea. These factors complicate the delineation 

and understanding of cumulative impacts, as well as the ability 

to develop effective monitoring. 

There are benefits to energy and mineral production, but 

there also are social and environmental costs and impacts. 

Each individual development activity affects the ecosystem, 

including marine life, habitat, air quality, water quality, and 

local communities. These effects, combined with those of 

other projects or activities, will have unanticipated additional, 

or cumulative, impacts. Climate change adds significant 

complexity to cumulative impacts, perhaps more so in the 

Arctic where its effects may be more pronounced. The climate 

of the Arctic (Chapter 4, Climate Change Considerations) is a 

complicating factor in evaluating cumulative impacts in that 

recovery from disturbance in the Arctic may take much longer 

than in warmer climates.
206 An Evaluation of the Science Needs to Inform Decisions on Outer Continental Shelf Energy Development in the Chukchi and Beaufort Seas, Alaska

Cumulative effects analyses have been done by various 

groups since the passage of the NEPA, but conducting 

such analyses remains extremely challenging because of 

the complexity and variety of factors that might impact 

cumulative disturbances. Although studies and research 

have been done by many organizations on many factors in 

the Arctic, there has been relatively little specific focus on a 

holistic, integrated, comprehensive assessment of cumulative 

effects of industrial activities in the Arctic. 

An additional complicating factor is that Arctic research 

is conducted by a myriad of entities, and the management of 

Arctic resources is overseen by many different groups with 

different mandates, interests, and budgets, and thus research 

needs. Different agencies have different responsibilities—

for air, water, endangered and (or) migratory species, and 

so on. No single organization has the responsibility for 

comprehensive planning for oil and gas development in Arctic 

Alaska. This is, in part, why much of the information is not 

synthesized or integrated. There is value to having different 

groups conduct research and analysis, and to some degree 

management, but there needs to be more coordination and 

an integrated decision-making process for these large areas 

that are potentially going to be developed. If an integrated 

decision-making process is not implemented, then the projectbased approach to environmental impact analysis will preclude 

true cumulative impact analysis or evaluation.

 Further complicating the analysis of cumulative impact, 

especially in the Arctic, the National Research Council 

study (2003) pointed out that technological advances have 

significantly changed many factors related to petroleum 

development, including the type of resource obtained, as well 

as how and where it can be produced (for example, directional 

drilling, ice roads, and so on). Technology develops very 

rapidly when the stakes are large, and it adds a complicating 

factor to predicting cumulative impact. Climate change, also, 

significantly impacts the ability to predict or even determine 

cumulative impact. As climate change is expected to accelerate 

in the future, its effect on cumulative impact is difficult to 

predict. It will, however, likely influence petroleum and other 

development and in turn, those activities on the environment. 

The National Research Council (2003) study outlined 

specific issues (only some of which follow) that must 

be addressed when considering cumulative effects on 

Arctic Alaska. Many of these issues are related to onshore 

development, as the study was focused on the Alaska’s North 

Slope. However, this list, which is not comprehensive, gives 

a sense of the many issues that must be considered when 

addressing comprehensive cumulative impact assessments:

• Industrial activity has grown on the North Slope 

with oil field development, pad development, 

interconnecting roads, pipelines, power lines, and 

other infrastructure. Environmental effects of these 

structures occur both at the site as well as up to a 

few miles/several kilometers away, but visual impact 

can be farther. There also is an issue of legacy sites, 

including abandoned infrastructure and unrestored 

landscapes. However, there has been significant 

improvement in reducing the drilling footprint with 

technological advances, such as directional drilling, 

replacing gravel pads with ice pads, and other 

developments. 

• Off-road damage to tundra originates primarily from 

seismic operations. Most of the damage is legacy 

damage, caused by earlier surveys, but is long term 

and persistent. Technology, as well as seasonal 

limitations to off-road travel, has substantially 

improved and has significantly reduced, but not 

totally eliminated, damage to the tundra. It is 

difficult to predict what will be the impact as drilling 

expands into new areas and as climate continues to 

warm.

• Roads affect areas of development like they 

do in many areas by increasing dust, habitat 

fragmentation, and permafrost effects. Roads also 

can allow access by hunters, tourists, and others 

to an area previously difficult to access. Yet, roads 

can enhance communications among isolated 

communities and increase contacts between the 

North Slope and those communities outside the area.

7.01. Recommendation: More coordination and 

comprehensive planning are needed among the various 

stakeholders in the Arctic, including those with responsibility 

for resources, those that conduct research, and those that use 

resources. These groups should all have input into coordinated, 

comprehensive cumulative impact analyses. Shared stakeholder 

visions regarding purpose and data sharing may reduce 

redundancies and help streamline regulatory processes. These 

actions must be informed by improved access to information 

through geospatial technologies, regular synthesis of research, 

forecasting, and multidimensional evaluations of human 

developments.

7.01. Finding: Cumulative effects analysis can benefit from 

applications of sophisticated geospatial technologies, regular 

synthesis of environmental data and information, ecological 

forecasting, and multidimensional evaluations of planned human 

developments. These elements exist for the Arctic OCS at some 

level, but are insufficient or not well integrated to support 

comprehensive cumulative impact analyses.
Cumulative Impacts 207

Chapter 7

• Animal and plant impacts (terrestrial and marine) 

include those to bowhead whales and denning polar 

bears. These may affect predator densities (related 

to new food sources people bring to the oil fields) 

and may impact the reproductive capabilities of 

some species, but that is not yet known. Some 

species on the North Slope are in decline here and 

elsewhere, and industrial activities may affect those 

trends. The Arctic Coastal Plain contains some of the 

richest areas of Arctic fens, thaw lakes, and tussock 

tundra in the World. Despite its low biological 

productivity, the Arctic Ocean supports a specialized 

biotic community, especially near the coast. Many 

species of plants and animals are found onshore and 

offshore. 

• Oil spills to date have been from pipelines but 

there have been no major oil spills from oil field 

operations. Small spills in the oil fields are not large 

enough nor frequent enough to be considered in a 

cumulative impact evaluation, but a future large oil 

spill, especially offshore in sea ice, would likely 

accumulate, especially as there is no comprehensive 

method for clean-up of spilled oil in sea ice. 

• Air quality and the effects of air pollution on the 

North Slope are areas in which relatively little 

research is conducted. As a result, there is no 

quantitative baseline and it is very difficult to 

determine local effects from long-range transport of 

air contaminants. 

• Human factors—

Socioeconomic changes.—Oil development, and 

attendant modern Western culture, has resulted in 

major and most likely irreversible changes to North 

Slope communities. Changes include funds for 

schools, housing, health care, and other community 

services, as well as changes in culture, diet, disease, 

and economic systems. These changes, which are 

viewed by some as both positive and negative, 

are complex and cumulative, because they are 

multifactoral and interactive. Just as oil revenues 

have changed the North Slope community, both 

positively and negatively, declining revenues also 

will affect life there and additional cumulative 

impacts will occur should financial resources 

decline. 

Impact on subsistence activities.—The Iñupiat 

of the North Slope have a nutritional and cultural 

relationship with the bowhead whale and offshore 

industrial activity is largely viewed as a major threat. 

Bowhead whales are affected by noise (as discussed 

in Chapter 6, Marine Mammals and Anthropogenic 

Noise), which alters their migratory pathways, 

which in turn puts hunters at risk by having to travel 

farther, by increasing exposure to adverse weather, 

and by increasing the possibility that the whale meat 

will not last on the return journey home. Increasing 

awareness of these risks has led to agreements on 

limiting or moving activities, but the Iñupiat still 

view the possibility of an offshore oil spill as a 

potential catastrophe. These threats are cumulative 

because they interact and because they are repeated 

with each new lease sale or activity.

Aesthetic, cultural, spiritual impacts.—Oil 

development activities have changed the Alaskan 

landscape so that there is an accumulation of 

aesthetic, cultural, and spiritual consequences, 

including lessening scenic values and diminishment 

of the solitude of the area, the wilderness, and the 

“spirit of the land.” 

Human health effects.—The direct health effects of 

petroleum activities have not been well documented 

in Arctic villages. Within Native communities, 

there are increased alcohol and drug use, increasing 

obesity, and other issues, but it is not possible to 

determine which are specifically tied to petroleum 

activities. Effects on traditional foods and their 

consumption are of great concern. It also is not 

possible to determine the degree to which increased 

financial resources have contributed to improving 

the quality of health care and accessibility and have 

offset the adverse effects of oil and the oil industry. 

7.02. Recommendation: Develop a cost/benefit analysis of 

petroleum activities on residents of the North Slope of Alaska, 

to understand what effect onshore development has had and to 

provide a baseline for the effects of potential offshore development. 

7.02. Finding: There are no known studies that attempt to 

separate the effects of oil and gas activities from other causes of 

socioeconomic change in communities of the North Slope of Alaska.
208 An Evaluation of the Science Needs to Inform Decisions on Outer Continental Shelf Energy Development in the Chukchi and Beaufort Seas, Alaska

The National Research Council (2003) cumulative 

effects report makes the point that some information on the 

effects of development should be gathered concurrent with 

information on oil and gas activities, so as to maximize 

learning opportunities and promote better and (or) adaptive 

management. The study recommended filling the knowledge 

gaps by undertaking numerous studies. We have only included 

those that have specific impact on offshore development 

potential:

1. Comprehensive planning—decisions generally 

are made on a case-by-case basis, without a 

comprehensive plan or regulatory strategy; 

2. Ecosystem research—ecosystem-level research is 

largely lacking at the regional scale in Arctic Alaska; 

most studies have been local in nature; 

3. Offshore oil spills—this was of such concern to the 

NRC committee that it recommended research into 

mitigating their effects, as well as research in how 

to deflect marine mammals from spill areas, and 

clean-up technologies should a spill occur; 

4. Zones of influence—impacts from industrial 

development are not limited to the specific area of 

development, but extend some ways beyond and 

there is a need for quantification of those effects;

5. Human communities—there is important missing 

information on the effects (beneficial and harmful) 

to the North Slope communities; a better mechanism 

is needed to increase Alaska Native input into 

the research process and a way to translate their 

observations into hypotheses that can be addressed 

by research; 

6. Human health effects—health effects of oil and gas 

activities are not well documented; 

7. Air contamination and its effects; 

8. Bowhead whales—better information is needed on 

the migratory and acoustic behavior of bowhead 

whales, including from multiple sources and their 

feeding patterns; 

9. How to deal with uncertainty—because there 

will never be sufficient data to meet all needs for 

information, transparency is needed when a model 

or statistical evaluation is performed to assess an 

environmental effect, which gives voice to the 

uncertainty surrounding the use of models;

10. Trade-offs—effects of industrial development may 

accumulate despite efforts to minimize impacts; it 

is open to discussion whether the benefits derived 

from oil and gas activities are worth the trade-offs of 

their impacts; the nature and extent of these impacts 

must be fully acknowledged and incorporated into 

regulatory strategies and decision making. 

There is a significant body of work on the actual and 

potential effect of oil and gas activity in Arctic Alaska, as 

well as on the physical, biotic, and human environment that 

could be used for cumulative impact analysis. For example, 

the Bureau of Ocean Energy Management, Regulation and 

Enforcement (BOEMRE) provided figure 7–1 showing the 

progression in understanding through time of the social 

systems in Arctic Alaska. This is but one organization that 

funds research in the Arctic. 

The BOEMRE formally consults with other organizations 

regarding environmental impacts on potential petroleum 

development in the Beaufort and Chukchi Seas, including 

the National Marine Fisheries Service (NMFS) and the U.S. 

Fish and Wildlife Service (USFWS). These organizations 

have published biological opinions and environmental impact 

statements regarding development (National Marine Fisheries 

Service, 2008, 2009; National Oceanic and Atmospheric 

Administration, 2009; U.S. Fish and Wildlife Service, 2009).

There is a growing recognition of the interaction of 

factors and issues. Shell Gulf of Mexico Inc. submitted an 

Exploration Plan to the BOEMRE for several exploration 

blocks from OCS Lease Sale 193 (February 2008) in the 

Chukchi Sea, Alaska, in July 2009 to conduct exploration 

drilling and evaluate petroleum potential in three prospects 

(Minerals Management Service, 2009). Shell proposed to 

drill several exploration wells within its lease blocks. Its 

Exploration Plan (EP) includes an environmental impact 

analysis, a Chukchi Sea Regional oil discharge prevention 

and contingency plan, environmental monitoring information, 

site-specific geohazards survey data and assessment, and 

mitigation measures. With the EP, Shell submitted a Plan of 

Cooperation to reduce potential conflicts with subsistence 

activities, and a description of their Cultural Awareness 

and Health, Safety, Security, and Environmental Awareness 

Programs. In addition to these documents, Shell submitted 

reports relating to distribution and abundance of seabirds, 

acoustic modeling of underwater noise, bird strike avoidance, 

marine mammal surveys, and drill mud impacts from 

exploratory drilling.
Cumulative Impacts 209

Chapter 7

Figure 7–1. Example of studies funded by the Bureau of Ocean Energy Management, Regulation and Enforcement 

(BOEMRE, written commun., 2011).

PROGRESSION IN UNDERSTANDING

SOCIAL SYSTEMS

SYSTEMATIC TACKLING OF CRITICAL QUESTIONS

2011 New Social Indicators

2008 Synthesis Report: Three Decades of Research on Socio-economic Effects

Related to Offshore Petroleum Development in Coastal Alaska

2006 Social Network Analysis

Sharing and Resilience | Drift Gillnet Fishery

2009 Mitigation Monitoring

Aggregation Effects | Technical Dialogue | Arctic Cisco | OCS Community Impacts

Systems Analysis

Subsistence Harvest | Commercial Fishing | Transportation

1983

1995 Oil Spill Impact Assessments

Exxon Valdez | Glacier Bay | Selendang Ayu

1985

Baselines

Community Case Studies

1978

Core Studies

Oil Development Scenarios | Effects Forecasting

1976

Geospatial Mapping: Local and Traditional Knowledge

Cross Island Whaling | Beaufort Subsistence Mapping

2001

Social Indicators Monitoring

Despite the growing awareness and care that is taken to 

evaluate environmental impacts, there is still grave concern 

regarding the cumulative impacts to the environment as a 

whole and to native communities. This concern was voiced 

in a number of our structured discussion sessions (see 

appendix A).

Although there is a great deal of information on the 

Arctic Ocean, including the Chukchi and Beaufort Seas, 

the information is not synthesized and is not integrated. 

This has implications for impact analysis, but especially for 

cumulative impact analysis. The data and information also are 

not collected in a geospatially sufficient manner to provide as 

strong a data underpinning as we have on land (fig. 7–2).

There also is a body of knowledge regarding behavioral 

animal studies related to drilling activities (related to the full 

range of activities including impacts from boats, aircraft, 

noise, light, and more), but some studies are anecdotal and 

cite behavior of animals in certain circumstances, certain 

times of the year, with certain activities. It is unclear if there 

is any synthesis of cumulative impacts, especially of repeated 

behavior. Because there is not yet offshore development in 

the U.S. Arctic, now is the optimal time to develop studies to 

determine cumulative impact, which includes a full synthesis 

of the literature and studies that are available to determine 

what is already known and what remains uncertain. There 

is a great deal of literature on different species, activities, 

behavior, and a synthesis of these studies would likely show 

findings different than individual studies. 
210 An Evaluation of the Science Needs to Inform Decisions on Outer Continental Shelf Energy Development in the Chukchi and Beaufort Seas, Alaska Figure 7–2. Map showing combined sensitive species habitat areas and core subsistence areas for onshore Arctic Alaska. Similar data and visualizations are yet not available at this level for the Arctic OCS. (The Nature Conservancy and Wainwright Traditional Council, 2008.) tac11-5179_fig7-01 (Barrow) (Wainwright) (Point Lay) Ut qiabvik Ut qiabvik Ulbuniq Kali Kali A t qas uk A t qas uk Peard Bay

W est e r n A r c t i c C a r i bou H e r d C a l v i n g G r ou n ds

Steller' s E ider

B reeding A rea

Spotted Seal

H aulouts

B eluga W hale

A rea

Survey B oundary

B ird

Kas egulak

L ag oo n

This map combines the core subsistenceareas from Map 11 and the combinedsensitive species habitat areas from Map

17. There is strong overlap between the

combined core subsistence area and the

important habitat for many sensitive and

Threatened and Endangered species,

demonstrating the biological and cultural

importance of these areas. The importance

of these habitats demonstrates the need forcareful land use planning.

As land use decisions are made in the

NPR-A, the information in this report can

be used as a tool for crafting management

recommendations that balance conservation

and development. Well informed decisionsthat consider all available information can

ensure that areas of high cultural and

ecological value are conserved.

Traditional Use Area Boundary

0 20 40 10

Miles

0 40 80 20

Kilometers

Data Sources: Traditional Use Area Boundary based on Pedersen, 1979.

Inupiaq Names: North Slope Borough, Traditional Land Use Inventory, 1997. Core Subsistence Area Composite: Wainwright Traditional

Council with The Nature Conservancy, 2007.

Bird Density Surveys: USFWS Aerial Breeding Pair Surveys of the

Arctic Coastal Plain, 1992-2005. 

Steller's Eider: Observed Range - ABR, 2003; Primary Breeding Range

- USFWS with The Nature Conservancy 2004. 

Fish Distribution: Anadromous Waters Catalog, ADF&G, 2007. 

Caribou: North Slope Borough, ABR, AK Dept. of Fish and Game. 

Belgua Whale: ADF&G, Alaska Habitat Management Guides, 1986; 

modified by experts, 2003. 

Spotted Seal: expert data collected by The Nature Conservancy, 2003.

Map Date: July, 2008

Combined Species &

Core Subsistence Area

Map 18

U SF W S

Spectacled E ider

D esignated C ritical

H abitat A rea

Core Subsistence Area composite 

of all key resources (Caribou, Fish,

Marine Mammals and Waterfowl)

High Density Areas for Sensitive Birds:Number of Species 

(Black Brant, Long-tailed Duck, 

Red-throated Loon, and 

White-fronted Goose)

Caribou

Anadromous Waters CatalogSteller's Eider observed range Steller's Eider breeding range

Spectacled Eider - high density area

USFWS Spectacled Eider 

Designated Critical Habitat

Yellow-billed Loon - high density area

Western Arctic Herd

Calving grounds

Beluga Whale 

Coastal Concentration Areas

Fish

Threatened or Endangered Birds

Marine Mammals

Teshekpuk Lake Herd

Over-wintering grounds

(50% probability)

3

Spotted Seal Haulouts

12

Survey 

Boundary
Cumulative Impacts 211

Chapter 7

7.03. Recommendation: A thorough synthesis of the existing 

Arctic literature needs to be conducted to develop a body of 

knowledge about cumulative impacts. This analysis would point 

out where studies show consistency and where there is need for 

more robust analysis of cumulative impacts on certain species 

or during certain times of the year or during certain behaviors 

(breeding, feeding, migrating, molting, staging, for example). 

Significant mitigation measures are being planned and in many 

cases may be enough (temporary disturbance for certain species 

during certain times of the year). But a thorough analysis of the 

literature would give greater assurance of the scientific validity of 

such assumptions, especially since the literature is detailed and 

plentiful for some species and sparse and anecdotal for others. 

This literature synthesis and evaluation should be supplemented 

with local traditional knowledge. This baseline for cumulative 

impact analysis will also help in dealing with the effects of 

climate change on cumulative impact. The data reviewed in the 

synthesis need to be made digital, where appropriate, so as to 

facilitate combining data sets and providing a foundation upon 

which to add more data and to identify data gaps. 

7.03. Finding: There is a growing volume of scientific 

information for the Arctic and the Arctic OCS, more specifically, 

that is not synthesized and is not integrated. This has implications 

for confident impact analyses, but particularly for the development 

of rigorous cumulative impact analyses.

Through reviewing the literature and looking at the 

issues associated with industrial activity, this author compiled 

a list of just some of the issues that need to be evaluated and 

how they accumulate when considering a comprehensive 

cumulative impact evaluation of offshore development: 

1. How the resource will be transported—pipeline or 

tanker?; 

2. What onshore infrastructure will be needed to support 

offshore exploration and development?; 

3. How this onshore infrastructure will impact current 

Alaska North Slope oil and gas development and the 

cumulative impacts of that development and the two 

(onshore and offshore) combined; 

4. Whether or not offshore development will affect or be 

affected by the coastal erosion currently occurring at 

unprecedented rates; 

5. Invasive species; 

6. Potential from oil spills (not just from drilling activities, 

but from other factors, such as ships); 

7. Socioeconomic changes to affected communities; and 

8. Effect on or interaction with subsistence activities. 

This is but a small list of factors that need to be considered, 

in addition to the others listed in this chapter (climate change 

effects and others) and the other chapters of this report (such 

as effect on marine mammals, ecosystems, and oil-spill risk).

Effects of Climate Change on Cumulative Impact 

Analysis

Climate change and resulting ecosystem changes 

complicate evaluating cumulative effects. Continued climate 

change effects will themselves accumulate and affect sea ice, 

plant and animal distribution (both terrestrial and marine), 

permafrost, human activities, and oil field operations. 

The National Research Council (2003) found in their 

assessment that it appeared customary for practitioners to 

assume that the only source of environmental change in the 

evaluation of cumulative impacts is the action under study 

and that the environmental setting itself does not affect the 

analysis. Climate change, however, alters this assumption 

especially in Arctic Alaska, because the climate is changing 

rapidly and is affecting the landscape and environment itself, 

independent of, and in addition to, any potential petroleum 

activity. These factors must be taken into account when 

evaluating cumulative effects.

Climate change is only peripherally considered in most 

cumulative impact evaluations or assessments. Climate change 

can have significant effect on the ecosystem, which in turn 

will be additive to other impacts, although not directly related. 

An excellent example of this can be seen in figure 7–3, which 

illustrates the shift from benthic to pelagic ecosystems, which 

is already being documented in Arctic waters. 

The conditions that are postulated to occur with climate 

change may have a profound effect on the environment 

even in the absence of development, and thus will have a 

profound effect on any cumulative impact analysis. Yet little 

is understood about how to incorporate these changes into a 

cumulative impact assessment.

7.04. Recommendation: A methodology needs to be 

developed to incorporate climate change effects into a cumulative 

effects analysis that is transparent, robust, and sufficiently 

structured to incorporate existing scientific uncertainty about 

future climate scenarios. 

7.04. Finding: Climate change considerations in cumulative 

impact evaluations are often peripherally handled with limited 

analytical rigor. Yet, climate change can significantly affect 

ecosystems, which in turn will be additive to other impacts under 

consideration.
212 An Evaluation of the Science Needs to Inform Decisions on Outer Continental Shelf Energy Development in the Chukchi and Beaufort Seas, Alaska

Figure 7–3. How different ice conditions may affect Arctic marine ecosystems (Bluhm and others, 2008).

Abundant sea ice Limited sea ice

Ice

Algae

Phytoplankton

Phytoplankton

Ice

Algae

Zooplankton

Benthos

Zooplankton

Benthos

Diving Ducks

Walrus

Gray Whale

Bearded Seal Demersal Fish

Sea birds

Pelagic Fish

Minke

Bowhead

 Methodology for Cumulative Impact Analysis

No universally accepted framework or approach for 

cumulative effects analysis exists and, thus, there are different 

approaches to cumulative impact analysis. Further, each 

government agency handles it differently. This leads to the 

perception that cumulative impacts are ignored, or when 

not ignored, are met with confusion. This issue was voiced 

in each of the structured listening sessions. However, there 

are accepted general principles that need to be included in 

all cumulative effects analysis—the analysis needs to be 

conducted within a context of understanding the resources, 

ecosystem, and human community thresholds, that is, levels of 

stress beyond which the desired condition degrades (Council 

on Environmental Quality, 1997). Determining this threshold 

is often difficult and problematic. Cumulative impact analysis 

is complex and difficult, and impacted by a number of factors, 

but confusion is increased by the different approaches and 

scales. The different approaches make the results or findings 

very difficult to compare and contrast. A single methodology 

could be consistently applied to different areas, account for 

regional variables, and allow for a comparison of results. 

Different factors are currently counted in many different ways 

and words and terms are used differently by different groups: 

for example, what are threshold indicators; what mitigation 

measures are prompted when (what kind of threshold has been 

passed); what are acceptable impacts. A single Department 

of the Interior approach (1) could alleviate the perception 

that factors are not being weighed equally (either positive or 

negative impacts); (2) will resolve the issue of cumulative 

impact analysis being done differently in different planning 

areas by different agencies; and (3) will increase the clarity 

about what is really being considered. One approach also will 

address the perception that individual development projects 

are not being adequately addressed by cumulative impact 

analysis.
Cumulative Impacts 213

Chapter 7

The National Research Council (2003) report was unable 

to attribute the absolute degree of importance to effects, 

so it attempted a descriptive approach to the importance of 

the effects. Since then, there have been efforts to develop 

standardized, quantitative approaches to cumulative effects 

[for example, Johnson and others (2005) and Halpern and 

others (2008)], but these have only described some of the 

impacts and no benefits of proposed activities. Another study 

that bears watching is the BP- and North Slope Boroughfunded study at the University of California, Santa Barbara to 

develop an approach to quantitatively assess the cumulative 

impact of noise on marine mammals (namely gray whales and 

bowheads). These are excellent examples from which to build, 

but more work needs to be done.

What seems to be missing from many of the cumulative 

impact analyses is the consideration of future actions. This 

is very difficult to do, but in an area such as the Arctic where 

development is still relatively new, one must consider future 

development in order to account for cumulative impact. 

The challenge of trying to determine future development 

is exacerbated by the various oversight responsibilities 

of the different agencies. Consideration must be given to 

developing a consistent approach to “reasonably foreseeable 

future actions,” to account for the various projects among 

and between the various agencies, geographic regions, and 

time frames, but not overestimate projects that may never be 

developed. What is considered reasonable and foreseeable is 

going to be different in each area, but guidelines, definitions, 

and thresholds need to be developed so they are common and 

consistent.

Monitoring is an important part of the iterative nature 

of cumulative impact analysis, to assess the accuracy of 

predictions of effects and to evaluate the success of mitigation. 

Consequences should be evaluated repeatedly in the 

cumulative impact analysis and a monitoring program should 

include the following (Council on Environmental Quality, 

1997): 

1. Measurable indicators of the magnitude and 

direction of ecological and social change; 

2. Appropriate timeframe; 

3. Appropriate temporal and spatial scales; 

4. Means of assessing causality; and 

5. Means of measuring mitigation.

It also is important to note that possible effects, both 

positive and negative, are perceived differently by different 

groups and individuals. It is not clear that there is a method to 

attribute a degree of importance to effects, so often the effects 

are descriptive or qualitative instead of quantitative.

Recently, ecosystem-based marine spatial planning 

(MSP) is being discussed as a possible tool for assessing and 

managing for cumulative effects of multiple activities (Foley 

and others, 2010) as well as a viable strategy for managing 

human activities in Federal waters. Marine spatial planning 

is a comprehensive, adaptive, integrated, ecosystem-based 

spatial planning process for analyzing current and anticipated 

uses of the oceans (National Ocean Council, 2010, accessed 

March 31, 2011, at http://www.whitehouse.gov/administration/

eop/oceans/cmsp). MSP is a process that analyzes the spatial 

distribution of activities in the ocean so that ecosystem 

health and services can be protected and that existing and 

future uses can be maintained, reducing use conflict. Some 

MSP efforts, notably those in Norway, explicitly cover 

multiple sectors including oil and gas development (Olsen 

and others, 2007). Marine spatial planning takes into account 

two fundamental principles, namely those of context and 

uncertainty (Foley and others, 2010), as well as stakeholder 

input—all issues mentioned previously as important to 

consider when conducting cumulative impact analysis. Marine 

spatial planning, as outlined in a number of studies, many of 

which are described in Foley and others (2010), can be used to 

reduce the level of cumulative impacts in any one area, as well 

as the number of trade-offs and conflicts between users and 

between users and the ecosystem.

7.05. Recommendation: A methodology for comprehensive, quantitative cumulative 

impact analysis that is transparent, externally vetted, and adopted consistently across at 

least the Bureaus of the Department of the Interior should be developed. In order to help 

develop the methodology, an evaluation of the various approaches should be conducted, 

including marine spatial planning, to determine best practices of all agencies both 

domestic and international. A common language and a common set of metrics should 

be developed. One methodology that can take into account regional variables should 

be developed. The analysis should include more than single projects, and the scope 

of the analysis should be determined by an expert panel. The approach should define 

the information needed for a decision and what to do when a decision is required but 

there are no data. The methodology and resultant analysis should include a plan for the 

number and types of projects in the region and be able to account for both positive and 

negative tradeoffs. An approach must be developed to incorporate or predict reasonable 

future development and monitoring of impacts as development progresses. 

7.05. Finding: No universally accepted 

framework or approach for cumulative 

effects analysis exists, which leads to the 

perception among some stakeholders that 

cumulative effects are ignored. The lack of 

a clear structure and quantitative analytical 

process leads stakeholders to question the 

sufficiency of approaches taken and validity 

of resulting findings. 
214 An Evaluation of the Science Needs to Inform Decisions on Outer Continental Shelf Energy Development in the Chukchi and Beaufort Seas, Alaska

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http://ceq.hss.doe.gov/nepa/regs/ceq/toc_ceq.htm.

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Act: Council on Environmental Quality, Executive Office of 

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D., Beck, M.W., Carr, M.H., Crowder, L.B., Duffy, J.E., 

Hacker, S.D., McLeod, K.L., Palumbi, S.R., Peterson, 

C.H., Regan, H.M., Ruckelshaus, M.H., Sandifer, P.A., 

and Steneck, R.S., 2010, Guiding ecological principles 

for marine spatial planning: Marine Policy, v. 34, issue 5, 

p. 955-966, doi:10.1016/j.marpol.2010.02.001, accessed 

March 31, 2011, at http://www.sciencedirect.com/science/

article/B6VCD-4YFT5CW-1/2/48ba1aed48b4adfa4db3c9f

a326457c5.

Halpern, B.S., Walbridge, S., Selkoe, K.A., Kappel, C.V., 

Micheli, F., D’Agrosa, C., Bruno, J.F., Casey, K.S., Ebert, 

C., Fox, H.E., Fujita, R., Heinemann, D., Lenihan, H.S., 

Madin, E.M., Perry, M.T., Selig, E.R., Spalding, M., 

Steneck, R., and Watson, R., 2008, A global map of human 

impact on marine ecosystems: Science, v. 319, no. 5865, 

p. 948-952.

Johnson, C.J., Boyce, M.S., Case, R.L., Cluff, H.D., Gau, 

R.J., Gunn, A., and Mulders, R., 2005, Cumulative effects 

of human developments on Arctic wildlife: Wildlife 

Monographs, v. 160, issue 1, p. 1-36, doi:10.2193/0084-

0173(2005)160[1:CEOHDO]2.0.CO;2, accessed March 31, 

2011, at http://onlinelibrary.wiley.com/doi/10.2193/0084-

0173(2005)160%5B1:CEOHDO%5D2.0.CO;2/abstract.

Conclusion

The evaluation of cumulative impacts—the combined, 

incremental effects of human activity—has a basis in NEPA 

and is guided by CEQ guidelines. In practice, study of 

cumulative impacts is complex and difficult, especially when 

consideration is given to potential future development and 

the overprint of climate change. There is confusion among 

all parties interested in cumulative impacts regarding what 

they are and how to evaluate them. Several agencies and 

organizations evaluate cumulative effects, but there is little 

coordination of efforts or resultant findings. Furthermore, 

there is no universally accepted methodology for the study of 

cumulative impacts. Society’s ability to judge the potential 

effects of oil, gas, and other development considerations 

in the Arctic would benefit greatly from the creation of a 

methodology for comprehensive cumulative impact analysis to 

be adopted consistently. To develop such a new methodology 

will require an evaluation of best practices across all 

agencies, domestic and international, and taking advantage 

of new analytical approaches emerging in fields outside of 

environmental sciences. A consistent national approach, with 

common language and a common set of metrics that can take 

into account regional variables, would allow for the scientific 

underpinning of an assessment for Arctic development to 

be viewed relative to actions elsewhere. Efforts to develop 

such a methodology should consider how best to incorporate 

more than single projects. Any new approach needs to define 

the amount of data needed for a decision and what to do 

when a decision is needed and there are few or no data. The 

methodology and resultant analysis should include a plan 

for the number and types of projects in the region and be 

able to account for both positive and negative tradeoffs. An 

approach must be developed that is flexible and robust enough 

to incorporate or predict reasonable future development 

and define essential monitoring of impacts as development 

progresses. Synthesis activities must be regularly conducted 

to document our growing understanding of ecosystems and 

effects. Development and implementation of cumulative 

impact analysis must include the various stakeholders in the 

Arctic. A thorough synthesis of the existing Arctic literature 

is needed to develop a body of knowledge about cumulative 

impacts from which to develop the cumulative impact 

assessment. This synthesis also will aid in incorporating 

climate change into the new cumulative impact assessment 

methodology. Only in this way will we start to appreciate what 

cumulative impacts, both positive and negative, will truly be 

associated with development in the Arctic.
Cumulative Impacts 215

Chapter 7

Minerals Management Service, 2009, Environmental 

Assessment: Shelf Gulf of Mexico Inc., 2010 Exploration 

Drilling Program, Burger, Crackerjack, and SW Shoebill 

Prospects, Chukchi Sea Outer Continental Shelf, Alaska: 

Office of Leasing and Environment, Alaska OCS Region, 

Chukchi Sea OCS Leases OCS-Y-2280, OCS-Y-2267, OCSY-2321, OCS-Y-2111, and OCS-Y-2142, 132 p, accessed 

March 31, 2011, at http://alaska.boemre.gov/ref/EIS%20

EA/2009_Chukchi_2010EA/2009_EA2010_Chukchi_

EP.pdf.

National Marine Fisheries Service, 2008, Endangered Species 

Act, Section 7 Consultation: Biological Opinion: Oil and 

Gas Leasing and Exploration Activities in the U.S. Beaufort 

and Chukchi Seas, Alaska and Authorization of Small 

Takes Under the Marine Mammal Protection Act: Seattle, 

Washington, U.S. Department of Commerce, National 

Oceanic and Atmospheric Administration, 140 p., accessed 

March 31, 2011, at http://www.mms.gov/alaska/ref/

BioOpinions/2008_0717_bo.pdf.

National Marine Fisheries Service, 2009, Issuance of an 

Incidental Harassment Authorization to Shell Offshore, Inc. 

and Shell Gulf of Mexico, Inc. to Take Marine Mammals by 

Harassment Incidental to Conducting an Open-water Marine 

Survey Program in the Chuckchi Sea, Alaska: accessed 

March 31, 2011, at http://www.nmfs.noaa.gov/pr/pdfs/

permits/shell_openwater_iha_signed.pdf.

National Ocean Council, 2010, Coastal and Marine Spatial 

Planning: accessed March 31, 2011, at http://www.

whitehouse.gov/administration/eop/oceans/cmsp.

National Oceanic and Atmospheric Administration, 2009, 

Small takes of marine mammals incidental to specified 

activities; Open-water marine survey program in the 

Chukchi Sea, Alaska during 2009-2010: Federal Register, 

v. 74, no. 103, p. 26217-26234, accessed March 31, 2011, at 

http://federalregister.gov/a/E9-12659.

National Research Council, 1986, Ecological knowledge and 

environmental problem-solving: Concepts and case studies: 

Washington, D.C., National Academy Press, 388 p.

National Research Council, 2003, Cumulative environmental 

effects of oil and gas activities on Alaska’s North Slope: 

Washington, D.C., National Academies Press, ISBN: 0-309-

50625-5, 304 p., accessed March 31, 2011, at http://www.

nap.edu/catalog/10639.html.

Olsen, E., Gjøsaeter, H., Røttingen, I., Dommasnes, A., 

Fossum, P., and Sandberg, P., 2007, The Norwegian 

ecosystem-based management plan for the Barents Sea: 

ICES Journal of Marine Science, v. 64, no. 4, p. 599–602, 

doi:10.1093/icesjms/fsm005, accessed March 31, 2011, at 

http://icesjms.oxfordjournals.org/content/64/4/599.abstract.

The Nature Conservancy and Wainwright Traditional Council, 

2008, Wainwright Traditional use Area Conservation Plan 

Map Book: Anchorage, Alaska, 40 p.

U.S. Environmental Protection Agency , 1999, Consideration 

of cumulative impacts in EPA review of NEPA documents: 

U.S. Environmental Protection Agency, Office of Federal 

Activities (2252A), EPA 315-R-99-002/May 1999, 

22 p., accessed March 31, 2011, at http://www.epa.gov/

compliance/resources/policies/nepa/cumulative.pdf.

U.S. Fish and Wildlife Service, 2009, Final Biological Opinion 

for Beaufort and Chukchi Sea Program Area Lease Sales 

and Associated Seismic Surveys and Exploratory Drilling: 

Fairbanks, Alaska, 174 p., accessed March 31, 2011, at 

http://www.mms.gov/alaska/ref/BioOpinions/2009_0903_

BO4BFCK.pdf.
216 An Evaluation of the Science Needs to Inform Decisions on Outer Continental Shelf Energy Development in the Chukchi and Beaufort Seas, Alaska

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Conclusions 217

Chapter 8

Chapter

8

The Arctic has had relatively little 

industrial development thus far, 

giving us a unique opportunity to 

determine the future land use and 

resource management of this area 

and “get it right.” We have the chance 

to study the environment and all its 

components and how any changes 

(human-induced or natural, including 

climate change) will affect the 

Arctic. Specific and detailed USGS 

summaries of key existing scientific 

information, key knowledge gaps, 

and recommendations are found in 

each chapter. Those recommendations 

are important for understanding 

what the USGS discovered in the 

course of this study and to help 

inform and improve decision making. 

Within this conclusions section, we 

provide a higher level summary and 

synthesis of our findings to help 

inform the Secretary of the Interior’s 

considerations of the right places and 

the right ways in which to develop oil 

and gas resources in the Arctic Outer 

Continental Shelf. 

Conclusions 

 By Brenda Pierce and Leslie Holland-Bartels

Impacting all Arctic components and affecting any resource 

management strategies will be climate change. Climate conditions in 

the Arctic have recently been undergoing a marked change, particularly 

during the last 20 years. Environmental changes include warmer air and 

ocean temperatures, earlier spring snowmelt, a marked decrease in the 

extent and thickness of sea ice, accelerated coastal erosion, permafrost 

degradation, an increase in shrubs on the Arctic coastal plain, and other 

habitat changes. These changes in the physical environment influence 

biological, human, and industrial systems in a number of ways: 

• The distribution of some animal species (for example, walrus and 

polar bear) is responding to changes in, or the loss of, critical 

habitat (for example, sea ice) during parts of the year. 

• This in turns impacts subsistence hunting.

• The number of days seismic exploration vehicles can operate on 

the tundra without causing environmental harm has decreased 

from 200 to 100 over the last 30 years.

Climate projections for the next 50–100 years produced by global 

climate models consistently show a pronounced warming over the 

Arctic, accelerated sea-ice loss, and continued permafrost degradation. 

Of all areas on Earth, the Arctic has the greatest sensitivity to changes 

in greenhouse gases, with some of the largest changes expected to occur 

in the Bering, Beaufort, and Chukchi Seas. If realized, these projected 

climate changes will ultimately affect nearly every aspect of the Arctic 

environment. This is a major concern from a biological standpoint 

because the indigenous plants and animals are so highly adapted to the 

specific extreme conditions that have been the norm in the Arctic.

The effects of climate change are anticipated to influence all 

components of the Arctic ecosystem, and Arctic Outer Continental Shelf 

energy activities may exacerbate those changes, unless careful analysis 

of risks and tradeoffs is conducted. By judiciously planning when energy 

activities occur, environmental risks associated with those activities 

may be reduced. For example, extreme cold is a contributing factor in 

drilling accidents and spills, and thus the significant warming of mean 

autumn and winter temperatures expected by mid-century will lessen 

the likelihood of accidents and spills. Although portions of the Chukchi 

and Beaufort Seas are expected to be ice-free for a greater period of 

time each year, the pack ice is predicted to be more dynamic at certain 

times, increasing the risk of accidents and making oil-spill response more 
218 An Evaluation of the Science Needs to Inform Decisions on Outer Continental Shelf Energy Development in the Chukchi and Beaufort Seas, Alaska

difficult during these times. Ice seasons of shorter duration 

and longer open-water seasons could have profound effects 

on many different components of the Arctic system, likely 

affecting Arctic ecosystems and the species within them, 

especially in areas of particularly high biological productivity 

and potentially allowing for longer seasons of energy 

development and transportation. 

Climate change also may affect: 

• clouds, which in turn affect visibility; 

• icing conditions, which are a significant hazard 

in the Arctic, and can increase the potential for 

accidents and make response more difficult; 

• precipitation, an increase of which would hinder spill 

response and increase the potential for accidents; 

• storms (possibly increasing in frequency or intensity 

during certain parts of the year); 

• sea-level rise, which can affect coastal areas and 

infrastructure; 

• ocean acidification, which can significantly 

impact calcifying organisms due to the corrosive 

effect of the acid on their shells and would have 

reverberations throughout the Arctic food chain; 

• ocean circulation patterns, which are likely to 

change, although what those changes would be and 

what their effects would be are highly uncertain. 

Climate change also will impact organisms in the Arctic 

(including fish, birds, whales), pinnipeds (ice seals and 

walrus), and polar bears in many different ways including 

through the warming of Arctic waters from sea-ice declines 

and from changes in the food chain notably from the potential 

effects of acidification of the Arctic Ocean. 

Understanding climate change is an important piece of 

any type of development in the Arctic. More research needs 

to be conducted on the proposed effects of climate change 

on factors such as storms and ocean circulation. Storminess 

will directly affect the safety of oil and gas development. 

Ocean circulation patterns are critical in shaping both the 

physical and biological environments of the Arctic Outer 

Continental Shelf. The science community is actively engaged 

in developing state-of-the-art global climate models, but 

these models currently lack the resolution needed to address 

many of the issues discussed in this report. The United 

States, as one of the Arctic Nations, would benefit greatly 

from participating in the development of fully integrated 

(atmosphere-ocean-land) regional climate modeling efforts. 

Continued and enhanced efforts in this arena, specifically for 

the Arctic region, will provide a fundamental tool needed to 

better understand the degree and nature of any consequences 

of climate change as it relates to decisions regarding energy 

development in the Arctic. Periodic Arctic climate impact 

assessments can help ensure that an up-to-date scientific 

understanding of climate is achieved.

This theme of fully integrated regional modeling and 

analysis resonated throughout every topic that we studied. Our 

analysis of the many different literature sources—scientific 

reports, public policy documents, workshop findings, web 

sites—and discussions with a diverse range of stakeholders 

has resulted in a recognition that in recent years there has been 

a concerted effort to obtain more data and information on and 

conduct more research in the Arctic, so there is a great deal 

of information existing about the Arctic. Yet, in many ways, 

relatively little is known about the Arctic in large part because 

many of the studies are targeted in focus and independently 

conducted with limited synthesis, even within studies on the 

same topics. There is a critical need for large-scale synoptic 

efforts that synthesize the many different studies on the full 

range of topics by the numerous researchers and organizations 

examining the Arctic. However, there also is a need for some 

very specific research to address the identified science gaps (in 

the previous chapters, specifically, and here in general). 

Recent research and evaluation efforts in the Arctic have 

resulted in better understanding of Arctic geology, including 

the acquisition of geophysical data, offshore mapping, and 

successfully completing the first Arctic research drilling 

expedition. Such efforts also have enhanced our understanding 

of the tectonic and climatic history of the Arctic system, 

including carbon cycling, and delineating Arctic petroleum 

systems. Yet, there is a growing need for 3-D seismic data 

in the Arctic in order to better understand the geologic 

history of the area and its oil and gas potential (conventional 

and unconventional), to provide information regarding the 

safe development of these resources, and to support claims 

regarding the Outer Continental Shelf under Article 76 of the 

U.N. Convention on Law of the Sea. 

Improved estimates of the oil and gas resources in the 

Arctic are needed to provide a better baseline for effective 

resource management. But characterization of the oil reservoir 

volume and pressure also is needed throughout the Arctic 

Outer Continental Shelf, as these parameters have direct 

bearing on oil-spill risk assessment and oil-spill contingency 

planning. Underpinning research in foundational geology and 

geophysics can provide an improved understanding of how oil 

and gas resources are formed and emplaced in reservoirs in the 

Arctic.

Information on the physical oceanography (such as 

circulation processes and wind) is critical for oil-spill 

modeling, oil-spill response, and cleanup efforts, as well 

as for understanding biological resources. The physical 

oceanography and meteorological Arctic Outer Continental 

Shelf characteristics that are inputs into this modeling are 

highly dynamic as a result of complex factors including ocean 
Conclusions 219

Chapter 8

source waters, freshwater inflows, and ice melt differences 

between the Chukchi and Beaufort planning areas. Such 

complexities are not yet well understood because of the 

challenge of instrumenting a remote ice-influenced system 

such as the Arctic Outer Continental Shelf. Thus, the physical 

understanding of the Arctic Outer Continental Shelf is not 

comparable with that of the Gulf of Mexico Outer Continental 

Shelf, nor is the circulation or weather modeling that informs 

oil-spill trajectory models yet of similar rigor. Outputs 

from such trajectory models also influence ecological effect 

analyses, as well as spill contingency planning and real-time 

response considerations. These analyses are limited by the 

accuracy and precision of the physical data that inform them. 

In addition, physical oceanographic and meteorological data 

help inform a wide variety of issues in the Arctic beyond 

trajectory modeling or contingency planning. The United 

States and Canada might benefit from the development of 

multi-purpose, multi-agency funded monitoring networks that 

could inform climate forecasting, aviation and shipping safety, 

and oil-spill response and mitigation plans. The visualization 

and serving of data through tools of the Alaska Ocean 

Observing System (AOOS) and (or) the Emergency Response 

Management Application under development for the Arctic 

(Arctic ERMA) would ensure efficient access to information 

and improved asset planning that is critical in the high cost 

instrumentation environment of the Arctic. 

Development in the Arctic is challenging and complex 

because of the many unknowns and because of the 

inherent risks of working in frontier and relatively pristine 

environments. Beyond the focused question of “science gaps” 

the USGS Outer Continental Shelf Team was challenged 

with, we observed a need to evaluate all relevant information 

available to help develop guidelines, best practices, 

regulations, and policies. Lessons learned from all existing 

Arctic or sub-Arctic examples must be used to inform future 

decisions and optimize future actions. The Exxon Valdez oil 

spill in 1989 was the largest oil spill in United States waters 

until the Deepwater Horizon spill of 2010. The lessons learned 

from the Exxon Valdez oil spill are included in our report 

for the purposes of highlighting Alaska-based experience 

ranging from spill response through Natural Resource Damage 

Assessment components. Any Arctic Outer Continental Shelf 

evaluation and planning effort for oil development can benefit 

from the lessons learned from Exxon Valdez oil spill, which 

can better inform overall preparedness and particularly oilspill prevention and response. 

Current information and recent baselines developed for 

different components of the Arctic ecosystems need to be 

supplemented with ongoing monitoring so as to understand the 

changes in the ecosystem and monitor its health. Information 

is needed on all levels of species, from phytoplankton, 

microbes, and zooplankton, to fish and birds, to marine 

mammals. It is important to include not just those species that 

live in the Arctic year-round, but also migratory species as 

well.

A particular concern, voiced by many stakeholders 

and cited in the literature, is the impact of noise on marine 

mammals. Even with multiple studies conducted on ocean 

noise and marine mammals, large uncertainty still exists in 

understanding how impacts to individual animals may affect 

characteristics in the populations and research is needed on 

this topic. An inventory of seismic sound sources used in 

the Arctic Ocean does not exist. Such an inventory would 

provide standardized information about source, physical 

oceanographic conditions, and timing and duration of surveys. 

This database could be used to evaluate multiple sound 

sources that a marine mammal might hear in space and time, 

and help validate models that estimate sound propagation. 

The database may ultimately reduce the need for expensive 

or redundant acoustic modeling and monitoring, especially 

in sensitive or biologically significant habitats, as well as 

contribute to developing more effective mitigation strategies. 

Further, there is a need for an inventory of all non-natural 

noise in the Arctic Ocean, such as vessel noise, ship-induced 

icebreaking, and aircraft. Such databases will be important 

to distinguish between anthropogenic and natural sources of 

noise impacts to marine mammals and will point out where 

there are significant information gaps (there is relatively 

little information on any of these). Data gaps also include 

the overall ambient noise budgets of the Arctic and how 

these vary seasonally and spatially. These data are needed 

because substantial challenges remain for scientists to 

understand the magnitude and significance of potential effects 

of anthropogenic sound on marine mammals. Additional 

research is needed to discriminate between the effects of 

sound, other aspects of human activity, and environmental 

variation (natural background). A synthesis of existing data 

on whale population abundance, structure, and habitats 

would provide a framework for analyzing how sound impacts 

whales and help managers determine times and places where 

whales might be most impacted by anthropogenic sounds. 

Similarly, fundamental biologic and habitat information about 

ice-dependent species, such as ice seals, is lacking, as is any 

information on how anthropogenic sound impacts them. This 

information needs to be obtained and integrated into these 

anthropogenic effects databases. In addition, walrus reactions 

to anthropogenic sounds also need to be better documented 

and studied (there is even considerable uncertainty as to 

whether walrus reactions to anthropogenic activities are 

caused by sight, sound, or smell) and a better understanding 

and inventory of habitat needs for walrus are needed.
220 An Evaluation of the Science Needs to Inform Decisions on Outer Continental Shelf Energy Development in the Chukchi and Beaufort Seas, Alaska

There is a continuing need to facilitate the collection, 

integration, and sharing of multi-scale data sets to advance 

our understanding of the Arctic as a complex, interdependent 

system. Such multidisciplinary data sets need to be used 

to develop comprehensive, holistic approaches to resource 

development and impact scenarios to inform planning. The 

multiple agencies, responsible for different parts of the system, 

make this task challenging, but it is a critical need. There must 

be a comprehensive approach taken to any type of industrial 

development in the Arctic. This comprehensive approach 

would benefit greatly from international cooperation and 

coordination. We share a border with Canada, which faces 

many of the same questions and challenges that we do, and 

other countries, particularly those of northern Europe, have 

experience from which we could benefit.

Also resonating throughout many of the issues examined 

was the challenge of relating the rapidly emerging science 

and technical information to the decision-making process. 

The level of information, the number of agencies and entities 

generating information, and the manner in which information 

from these sources is served is becoming more important 

as attention is turned towards the Arctic in general, and 

resource development in the Arctic more specifically. These 

information sources, while individually well structured, roll 

up to a complex information picture that is a challenge to 

interpret. It is difficult, if not impossible, in attempting to 

examine such information holistically, to know which needs 

are being addressed fully or partially, what new information 

needs or insights have emerged, how one weighs the relative 

importance of the information, and which new or continued 

investments are critical to reducing uncertainty among vested 

parties. 

This information challenge is particularly important 

when it comes to evaluating cumulative impacts. Cumulative 

impacts are the combined, incremental effects of human 

activity. Cumulative impacts can result from factors which 

may be insignificant by themselves but significant when 

interacting and (or) accumulating over time and space, 

through repetition, or from a combination with other effects. 

When actions are considered individually or independently, 

their combined consequences—or cumulative impact—

may not be fully considered or evaluated. This results in 

misunderstanding, and failure to consider the long range 

impact of multiple decisions over a large area or over time. 

Policy decisions are usually made at the regional or national 

level, but environmental effects are usually analyzed and 

assessed at the project level. Decisions about and permitting 

of industrial activities are often done on a case by case basis 

by multiple entities responsible for oversight of different 

aspects of the activity. These entities often operate without 

the benefit of a comprehensive plan or understanding of the 

scope, intensity, and consequences of the industrial activities, 

especially if overseen by another entity. Long-term decision 

making must take into account the cumulative nature and 

extent of the development benefits and challenges, and the 

costs and risks of both. 

Cumulative effects analysis requires application of 

sophisticated geospatial technologies, regular synthesis of 

environmental data and information, ecological forecasting, 

and multidimensional evaluations of planned human 

developments. Thus, there is need for more coordination and 

comprehensive planning among the various stakeholders in the 

Arctic, including those with responsibility for resources, those 

that conduct research, and those that use resources. In order 

to conduct cumulative impact analysis, a thorough synthesis 

of the existing Arctic literature that builds on the initial work 

in this report needs to be conducted to develop a body of 

knowledge about cumulative impacts, a theme that resonates 

throughout this report. It is critical that this cumulative impact 

information synthesis and evaluation include local traditional 

knowledge. The indigenous, subsistence community is 

extremely knowledgeable about the environment, ecosystem, 

and changing conditions of the Arctic. Local traditional 

knowledge is a critical resource and should be incorporated 

into all of the above syntheses and databases described 

throughout this report. 

Equally important is the critical need to develop a 

methodology for comprehensive, quantitative cumulative 

impact analysis that is transparent, externally vetted, and 

adopted consistently. An evaluation of the current approaches 

should be conducted, including marine spatial planning, to 

determine best practices and develop a common language and 

a shared set of metrics. An approach must be developed to 

incorporate or predict reasonable future development and the 

monitoring of impacts as development progresses. 

The subsistence community and culture are an essential 

component of the Arctic and all of the issues studied in this 

report will have an impact on these people and their way 

of life. To predict with any degree of accuracy the future of 

Arctic subsistence, with or without energy exploration and 

development, will require a greater understanding of the 

potential changes in local environments and ecologies because 

subsistence patterns closely correlate to these factors. Thus, 

subsistence patterns are vulnerable to the effects of climate 

change and anthropogenic development (whether it be oil and 

gas development, shipping, tourism, or another). Additional 

information is needed to determine the potential hazard to 

native subsistence livelihoods from oil and gas exploration and 

development, since such development can impact all parts of 

the spectrum from the specific subsistence animals themselves 

through their food chain and ecosystem. 
Conclusions 221

Chapter 8

In discussions with individuals and groups in the course 

of our assignment, and to some degree in the literature, it 

became clear that evaluating the science and filling identified 

science gaps will not be enough to address the issues 

surrounding energy development in the Arctic. Opinions on 

development run the gamut from “there is already enough 

science” to “there will never be enough science.” There are 

areas of significant scientific research that form a sound 

basis upon which to make decisions; there are areas where 

additional science is needed; but there also is an area in 

which more than science is needed. For that reason, we 

offer the appendix on Structured Decision Making (SDM), 

as an example of a type of tool that might be used to help 

inform decisions about energy development in the Arctic. 

SDM is a tool to help decision makers when a great deal of 

complex information and substantial uncertainty exists about 

the potential effects of development on the many resources 

of management interest. SDM consists of deconstructing 

decisions into their component parts, analyzing each part, 

and synthesizing the parts into a decision framework that can 

produce direct recommendations to decision makers about 

which decision is most likely to lead to attainment of their 

management objectives. This process helps the decision maker 

develop the fullest possible understanding of the complexities 

of the decision, including decision objectives, tradeoffs, 

uncertainties, and risks.

As stated in Chapter 1, Framing the Assignment and 

Process, our discussions and analyses highlighted that science 

sufficiency and science gaps are not absolutes but exist in 

large part in the eye of the beholder. As dynamic concepts, 

they are tied to an individual’s or organization’s held beliefs 

and what weighs most heavily in the decision process when 

complexity and uncertainty come into play. Whether to 

develop oil and gas resources, where they might be developed, 

when they might be developed, and what science is needed to 

inform those decisions are complex questions because Arctic 

Outer Continental Shelf development, particularly in the 

Chukchi Sea, would be a new, frontier activity with limited 

information and previous experience to guide the decisions 

being made. Positions about how to deal with any complex 

issue are informed by a mix of held and technically derived 

beliefs, and science influences those beliefs to different 

degrees. So, the questions become: 

How necessary does the vested party consider new 

information to its decision process? and 

How informative is the available science to be 

considered (uncertainty, applicability)? 

Because of the complex nature and diversity that exist across 

human belief structures and the difficult-to-study and changing 

nature of Arctic ecological systems, development of full 

agreement about science sufficiency is a challenge. 

Thus, while there is a growing base of scientific and 

technical information for the Arctic, which is synopsized in 

this report, as are critical science gaps to be addressed, many 

of the challenges emerging in Arctic oil and gas development 

decision making are beyond the ability of science alone to 

resolve. There is no “silver bullet.” However, we believe a few 

strategic actions can better support decision making and make 

for a more transparent process for all vested parties to express, 

understand, and perhaps balance their respective views on 

tradeoffs associated with “inaction until more information is in 

hand” versus “action not sufficiently informed.” 

In conclusion, the use of SDM approaches brings 

vested and interested stakeholders into the decision process 

in a transparent and documented way. The process allows 

for learning and adaptation, which are critical concepts 

in a changing frontier environment like the Arctic and we 

encourage its use. Second, oil and gas development decision 

making occurs within the broader context of Arctic issues. 

A collaborative and comprehensive Arctic science planning 

process would bring great value to the decisions required to 

proceed with development of oil and gas and other strategic 

assets in the Arctic in a changing climate environment. Such 

a science plan and its implementation must be informed 

by an SDM-like process and the syntheses of information 

we discussed earlier. Third, the Arctic science and resource 

community, and particularly the Alaska community, is a model 

of collaboration. We found throughout our consultations 

an open and energized desire to understand different views 

on development and to find means to move forward. Thus, 

the development of integrated monitoring efforts and 

collaborative science efforts across governmental, industry, 

and nongovernmental entities can be accomplished. However, 

we believe focused attention is required to envision and 

implement such a fully collaborative environment. Finally, 

our study found many excellent examples of thoughtful 

analyses of science and technology needs to inform oil and gas 

development decisions in the Arctic. Our recommendations 

and findings add to those already in the literature. To move 

forward, we strongly recommend that a collaborative 

implementation process that includes appropriate measures 

of accountability for all responsible parties/entities be put 

in place. In our many discussions, we heard from managers, 

responders, scientists, and community members that they 

are willing to engage in discussing information needs but 

that they have a growing expectation that those needs will 

be considered and, if appropriate, addressed in a visible and 

traceable manner.
222 An Evaluation of the Science Needs to Inform Decisions on Outer Continental Shelf Energy Development in the Chukchi and Beaufort Seas, Alaska

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Appendix A 223

Appendix A

Appendix A. Expert Consultations

Issue topics and detailed input Industry 

session

North 

Slope 

session

Federal 

session

Nonregulatory 

session

State 

session

North 

Slope 

public 

session

Climate change

Hardware for data collection, especially in shoulder seasons X

Lack of climate data X

Ability to down scale models to regional development X X

Lack of data collection network/coordination of research 

(data sharing...)

X

Issues created by multiple agencies’ climate agendas X

Unknown biological response to climate change and adaptability X X

Adequacy of physical models for climate change X

Baseline data for biological systems (spatial and temporal) X

Use of existing technology/resources to understand climate change 

in the Arctic

X

Predictability of refugia in time and space X

Relationship between water chemistry and environmental changes 

due to climate change

X

Human response to climate change (for example, ship traffic, 

noise, hunting patterns, fishing, subsistence)

X X

Relationship between subsistence use/Native culture and changing 

environmental conditions

X X

Construction must be sufficient to cover any range of conditions

including climate change

X

What happens to platforms at the end of their productive life? X

Oil-spill response

Inability to conduct field tests X X

Secondary data are perceived as not applicable X

Inability to access gray literature (in electronic forms) X

Detection and tracking X

Mechanical response X

Risk assessment X

Ice management X

Non-mechanical response options—Dispersants X X X

Ecosystems and human response to spill X

Impacts of spill response on ecosystems and human systems X

Capacity assessment X

Fate and effect of spill X X

Table A–1. Input received during the five facilitated expert consultations and the North Slope Public Session.

[Participants were asked to identify issues/gaps under each of the four Issue Topics (Climate Change, Oil-Spill Response, Marine Mammals and Noise, and 

Cumulative Impacts) requiring scientific knowledge that will affect their ability to accomplish their jobs. Sessions often did not cover all four Issue Topics as 

noted by dark blue. EIS, Environmental impact statement; LTK, local traditional knowledge; NSB, North Slope Borough; OCS, Arctic Outer Continental Shelf]
224 An Evaluation of the Science Needs to Inform Decisions on Outer Continental Shelf Energy Development in the Chukchi and Beaufort Seas, Alaska

Issue topics and detailed input Industry 

session

North 

Slope 

session

Federal 

session

Nonregulatory 

session

State 

session

North 

Slope 

public 

session

Oil-spill response—Continued

Baseline for damage assessments X

Sensitivity mapping and response planning X

Planned response options X

Protocols and standards (damage assessment, restoration) X

Information availability X

Well safety/control X

Systems for humans monitoring wells and identifying issues,

ability to reduce human error

X

Regulations to prevent accidents X

Public perception on response capability X

Contaminant load in environment—baseline X

Ability to test response equipment and methods X

Decision making and critical time needs during response X

Length of time oil persists in the Arctic environment X

Oil spill response gap analysis X

A combination Coast Guard Oil Spill Response Team X

Toxicity of dispersant on Arctic ocean organisms X

Timing of drilling of relief well(s) in case of blowouts X

Closeness/locations of oil spill cleanup team and equipment X

Drilling only during favorable times of the year, to mitigate the

chance of a catastrophic event

X

Marine mammals and noise

There is no standard for measuring underwater sounds (science) X X X

Acoustic propagation is not well understood X X

Lack of understanding of what sound levels cause impacts 

(behavioral changes, fallout from behavior changes, and other 

considerations)

X X

Context of received noise levels for marine mammals, feeding 

versus migrating, habitual versus naïve

X X

Mitigation/quieting technology X

Development of remote sensing technology X

Effects of anthropogenic sound on bowhead whales from

multiple sources/projects

X X X X

Baseline data for species other than bowhead whale, especially

related to climate change and seismic noise

X X X X

Knowledge of spatial/temporal distribution, use of satellite

tagging/aerial surveys/acoustic surveys 

X X X

Baseline data for the current state of the Chukchi Sea and ability 

to track changes and new species

X X

Table A–1. Input received during the five facilitated expert consultations and the North Slope Public Session.—Continued
Appendix A

Appendix A 225

Issue topics and detailed input Industry 

session

North 

Slope 

session

Federal 

session

Nonregulatory 

session

State 

session

North 

Slope 

public 

session

Marine mammals and noise—Continued

Ability to translate impacts on individual bowhead whales to

larger bowhead populations

X

Ability for LTK to document changes in the area as well as 

identify new species

X

Information sharing among groups to reduce the risk of 

redundancy (seismic)

X X

Baseline information on natural sound levels and anthropogenic

sound levels

X X

Information on the ability of marine mammals to communicate

function with increased anthropogenic noise (ship traffic from

multiple sources) and animal health

X X

Information about climate change and ice X

Information on ship strikes/ship interactions/entanglements X X

Amount of seismic information being collected X

Need for alternatives to seismic surveys X

Process for assessing the effects of multiple activities (for 

example, seismic) on marine mammals, information available for 

decision making

X X

Information on duration of deflection, on individual as well as

populations, when/if marine mammals return after deflection

X

Ability to access information about where and when proprietary

seismic activities take place to access the impacts on bowhead

whales, both on individuals and populations

X

Information on the physiological effects of noise X X

Baseline information about how animals use habitats X X

Impacts on marine mammals by spills/leaks X

Population dynamics of species (birth, growth, death) and

sensitivities to disturbances at these life stages, behavioral changes

X X

Behavioral changes of animals and impacts these changes have 

on humans who depend on them

X

Data that reflect trends and variability in species baseline X

Ability to identify differences between adaptation from climate

change and seismic activity

X

Information on state-of-the-art seismic activity for on-ice and inwater use (what it is and how it is used)X

Data on functional relationship between seismic technology use

and marine mammals

X

Data on the thresholds for seismic impacts to marine mammals X

Cascading effects of impacts to marine mammals resulting from

impacts to other species

X

Table A–1. Input received during the five facilitated expert consultations and the North Slope Public Session.—Continued
226 An Evaluation of the Science Needs to Inform Decisions on Outer Continental Shelf Energy Development in the Chukchi and Beaufort Seas, Alaska

Issue topics and detailed input Industry 

session

North 

Slope 

session

Federal 

session

Nonregulatory 

session

State 

session

North 

Slope 

public 

session

Marine mammals and noise—Continued

Efficacy of monitoring and mitigation efforts of seismic activities 

(180/190 Criteria)

X X X

Sensitivity to noise and variation in time and space X

Cumulative impacts, acute and chronic, time and space X

Chronic effect at drilling structure X

Unique behavioral patterns in the Arctic X

Synthesis of existing science X

Unique acoustics in Arctic X

Cumulative impacts to behavior from industrial activities 

(not just noise)

X

Ambient noise mapping X

Avoidance capabilities of wildlife X

Habituation potential X

Predictive models for wildlife impacts and climate change 

impacts to species

X X

Baseline environmental contaminant level for marine mammals X

Creation of a marine mammal co-association to help monitor 

and study the cumulative impacts on the marine mammals

X

Ability to detect marine mammals during the seismic activity X

Plankton and noise X

Ocean bathymetry/seafloor relief data for both Chukchi and

Beaufort Seas from coast line to 200 mile area for NSB

X

Cumulative impacts

Lack of updated guidelines on how cumulative impact activities

for EISs are written and used (sufficiency and applicability)

X X X

Outcomes of cumulative impact assessments are not functional 

for intended purposes

X X X

Lack of clear indicators and standards for cumulative impact

analysis, inconsistencies between agencies, how science is

incorporated

X X X

Coordinated effort among industry to reduce impacts

(for example, sharing seismic equipment/data)

X X

Efforts to integrate current cumulative impacts data into 

industry planning

X

Cumulative impacts of exploratory drilling on food availability,

breeding, behavior, predator/prey relationships, and contaminant

levels

X X X

Functional relationship between existing/historical data

management decision-making needs

X

Table A–1. Input received during the five facilitated expert consultations and the North Slope Public Session.—Continued
Appendix A

Appendix A 227

Issue topics and detailed input Industry 

session

North 

Slope 

session

Federal 

session

Nonregulatory 

session

State 

session

North 

Slope 

public 

session

Cumulative impacts—Continued

Access to information on activities in Russia and Canada that

effect cumulative impacts on animals exposed at multiple 

locations along migratory routes or over multiple years

X

Ability to link onshore and offshore activities in cumulative

impacts assessment

X

Connection between cumulative impacts on species and on 

human subsistence/traditional (cultural) uses and social structure

X X

Information on drilling muds, discharges and what effects it 

might have on subsistence food sources

X

Meaningful analysis of impacts to human health X

Attribution of impacts and thresholds (impacts for oil 

production versus other sources) (thresholds for unacceptable 

impacts to species)

X

Data on functional relationships between risk factors X

Lack of data to run integrated multi-variant models of 

cumulative impacts

X

Cumulative effects: linking spatial and species Bayesian models X

Waste management X

Amount of scientific information on cumulative impacts X X

Consideration of the time and space scales that cumulative impacts 

are assessed

X

Relationship between technology and cumulative impacts X

Risk assessment/technology changes of various development 

scenarios

X

Terrestrial/marine interaction X

Uncertainty in development levels and potential development,

unlikely scenarios included in decision making

X X

Unknown mitigation efforts to respond to cumulative impacts X

Inability to identify independent and cumulative impacts X X

Public perception of cumulative impacts X

Not equally weighing positive and negative outcomes X

Cumulative impacts of on-land infrastructure for OCS exploration, 

damage to the tundra, and abandonment of infrastructure with end 

of exploration

X

Sea currents and winds will carry the spilled oil all over the Arctic,

chain reaction destruction of the food chain

X

Increased shipping in OCS resulting in black carbon/soot

emissions-cumulative impacts ocean acidification, chemical sink

X

Permitting is issued on individual bases and does not account

enough for multiple activities

X

Disposals of all leases–total of all permits issued X

Table A–1. Input received during the five facilitated expert consultations and the North Slope Public Session.—Continued
228 An Evaluation of the Science Needs to Inform Decisions on Outer Continental Shelf Energy Development in the Chukchi and Beaufort Seas, Alaska

Issue topics and detailed input Industry 

session

North 

Slope 

session

Federal 

session

Nonregulatory 

session

State 

session

North 

Slope 

public 

session

Other concerns

Social impacts with new development; income, population,

lifestyle, way of life, lack of privacy

X X

Effectiveness of mitigation acts X

Efficiency of mitigation acts X

Utilize traditional knowledge, western science alone is a fraction

of knowledge of what the Iñupiat know

X

Are studies being conducted to look at the socioeconomic effects

on the people of the NSB?

X

Publicize all findings from ALL study groups X

Table A–1. Input received during the five facilitated expert consultations and the North Slope Public Session.—Continued

Table A–2. Information-Consideration Grid to organize science and issue needs used in the U.S. Geological Survey 

Arctic Outer Continental Shelf (OCS) Team’s facilitated expert consultation sessions.

[This information was used to consider science sufficiency as illustrated in figure A–1]

How important is issue XX in your decision making associated with oil and gas leasing, development, and policy topics?

Not a consideration Minimally important Moderately 

important Important Critically important

Some

consideration,

but as an ancillary

topic, not enough

to result in

accommodation in

project design or

policy topic

One of several

main issues

considered in

project design or

policy topic

One of a few

issues that are

considered

in decision

outcomes

Foundational to

determining

decision

outcomes

0 1 2 3 4

Please assess the body of scientific information status for issue XX

None Minimal body Moderate body Good body Robust

No information

available at all

Information with

high uncertainty or

very limited in

scope, scale, or

applicability to

Arctic OCS

Body of

information

expanding but

with notable

insufficiencies,

functional in most

cases

Good body of

information

across most

aspects of issue

with limited

uncertainty, data

gaps may exist for

minor elements

Robust information

directly applicable

to Arctic OCS

decision making

0 1 2 3 4
Appendix A

Appendix A 229

Table A–3. Example of science questions and assessment of sufficiency for one of the expert consultation sessions, the 

non-regulatory session. 

[Information-Consideration Grid scores (see table A–2) for four respondents are provided; however, for some issues, not every respondent provided a score. 

General judgment of sufficiency is based on the definitions provided in table A–2 and placement of the score within the Grid Graphic (see figure A–1). 

Scores that fell generally within red and orange zones of the graphic were placed as a gap. Often individuals differed either in the value of the topic to their 

decision making or to their opinion about status of the body of scientific information on the topic. These are listed as “variable” responses in Sufficiency 

column]

Issue/gap Information-Consideration Grid Score

Importance, Information Status Sufficiency

Climate change

Unknown biological response to climate change (models),

adaptability

2,2; 3,1; 4,1; 3,1 Gap

Adequacy of physical models for climate change 1,2; 3,2; 4,1; 3,3 Variable

Baseline data for biological systems (spatial and temporal) 3,2; 4,2; 4,1 Gap

The ability to link larger models to near shore processes/response

(down scale)

0,1; 2,2; 3,1; 2,1 Variable

Use of existing technology/resources to understand climate change

in the Arctic

2,3; 2,1; 2,2 Variable

Predictability of refugia in time and space 1,1; 4,1; 4,0; 2,1 Gap

Relationship between water chemistry and environmental change

due to climate change

0,1; 2,2; 1,2; 1,1 Reassess

Human use response to climate change (for example, ship traffic, 

noise, hunting patterns, fishing, subsistence)

0,1; 3,2; 4,1; 4,2 Gap

Relationship between subsistence use and changing environmental

conditions

1,2; 2,2; 4,1; 2,2 Variable

Relationship between human cultural changes and changing

environmental conditions

0,1; 2,2; 2,1; 1,2 Reassess

Oil-spill response

Detection and tracking 4,2; 4,1; 4,0; 4,1 Gap

Mechanical response 4,2; 4,2; 4,1; 4,2 Gap

Risk assessment 2,1; 4,2; 4,1; 4,2 Gap

Ice management (includes subcategories) 4,2; 4,1; 4,1 Gap

Non-mechanical response options 3,2; 3,1; 4,2 Gap

Ecosystems and human response to spill 4,2; 4,1; 4,1; 3,2 Gap

Impacts of spill response on ecosystems and human systems 4,1; 3,1; 2,1; 3,2 Gap

Capacity assessment 3,1; 4,3; 4,2; 4,2 Variable

Trajectory assessment/models 3,1; 4,0; 3,2 Gap

Fate and effects of spill 4,2; 4,1; 4,1; 3,1 Gap

Baseline for damage assessments 3,3; 3,1; 4,1; 4,1 Gap

Pre-identification of sensitive areas 2,3; 4,1; 4,1; 3,1 Gap

Sensitivity mapping and response planning 3,3; 4,1; 4,1; 3,1 Gap

Planned response options 3,3; 3,2; 2,2 Good

Protocols and standards (damage assessment, restoration) 3,2; 2,1; 3,1 Gap

Information availability 4,2; 3,1; 4,1 Gap
230 An Evaluation of the Science Needs to Inform Decisions on Outer Continental Shelf Energy Development in the Chukchi and Beaufort Seas, Alaska

Issue/gap Information-Consideration Grid Score

Importance, Information Status Sufficiency

Marine mammals and noise

Location/tracking (habitat use) 4,1; 4,1; 3,3 Variable

Sensitivity to noise and variation in time and space 4,2 ; 3,2 Gap

Cumulative impacts, acute and chronic, time and space 4,0; 4,2, 4,0; 4,1 Gap

Chronic effect at drilling structure 3,1; 4,1; 2,2 Gap

Unique behavioral patterns in the Arctic 3,2; 2,1; 2,2 Gap

Modeling wildlife impacts 3,1; 4,1; 2,1 Gap

Synthesis of existing science 4,1; 4,1; 4,2 Gap

Unique acoustics in Arctic 2,1; 1,1 Reassess

Relationship between changes in behavior and changes in 

sensitivity 

3,1; 1,1 Variable

Cumulative impacts to behavior from industrial activities (not just

noise)

3,1; 4,1; 3,1 Gap

Ambient noise mapping 2,0; 2,1 Gap

Avoidance capabilities of wildlife 3,1; 2,1; 2,1 Gap

Habituation potential 2,1; 2,1 Gap

Cumulative impacts

Waste management 2,3; 2,1; 2,2 Variable

Amount of scientific information on cumulative impacts 4,1; 4,0; 4,1 Gap

Methods to conduct cumulative impacts assessments (sufficiency

and applicability)

3,2; 4,1; 4,1 Gap

Knowledge of individual impacts 3,2; 3,1; 2,1; 3,2 Gap

Consideration of the time and space scales that cumulative impacts

are assessed

3,1; 4,1; 4,2 Gap

Relationship between technology and cumulative impacts 1,1; 2,1; 3,2 Variable

Risk assessment/technology changes of various development

scenarios

1,1; 4,1; 3,0; 2,1 Variable

Infrastructure development scenarios related to oil/gas development 1,1; 3,1; 4,0; 4,1 Variable

Terrestrial/marine interaction 2,2; 3,1; 4,1; 1,2 Gap

Uncertainty in resource condition 3,1; 2,1; 2,1 Gap

Uncertainty in development levels and potential development 3,1; 4,0; 3,1 Gap

Table A–3. Example of science questions and assessment of sufficiency for one of the expert consultation sessions, the 

non-regulatory session.—Continued 
Appendix A 231

Appendix A

Critically 

important

No information 

at all

Robust

Information

Not a 

consideration

Reassess

• Ensure information 

inadequacy in not driving 

consideration score

• Examine for emerging 

issues

• May be driven by 

expense or technical 

limitations

1

1

0

0 2

3

3 4

4

Sucient?

• Is the right information 

being collected?

• Perhaps important to 

other issues but not 

OCS; consider 

reallocating funds to 

identied OCS science 

insuciencies

Gap

• What science is 

necessary?

• What has 

constrained getting 

this science done?

Good Work

• Keep knowledge up 

to date

• Keep up the good 

work

• Reallocate resources 

to strengthen specic 

weaknesses?

Figure A–1. Grid tool used in the first series of structured consultations sessions. Y-axis represents the importance of an issue 

to an individual’s decision making associated with oil and gas development. X-axis represents the participant’s view of the status

of the body of scientific information for that issue. When scores (see table A–3) generally fell within a red or orange portion of the 

grid, the topic was considered a gap. 
232 An Evaluation of the Science Needs to Inform Decisions on Outer Continental Shelf Energy Development in the Chukchi and Beaufort Seas, Alaska

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Appendix B 233

Appendix B

Appendix B. Science Workshop

As part of our series of expert consultations the 

USGS Outer Continental Shelf (OCS) Team participated 

in the January 2011 Alaska Marine Science Symposium 

in Anchorage, Alaska, to gain focused input from the 

science community on key topics that had arisen during 

our assignment. The USGS OCS Team participated in the 

Symposium’s Poster Session to interact with participants 

and held a 3 hour facilitated technical workshop to obtain 

scientific input on areas of critical and fruitful investigation 

or approaches informative to the science gap analysis. The 

discussions were centered on four overarching scientific 

questions on topics that were consistently mentioned during 

our other expert consultations or in our literature assessments 

and that cross-cut the issues that are the focus of our science 

gap analysis (fig. 1–4). These topics were:

• What weather and oceanographic data are immediately 

needed to improve spill risk assessments, response 

planning, and spill response; what approaches are 

recommended to obtain such data?

• What supplements to agency monitoring and 

approaches to integrated ecological monitoring are 

needed for improved development impact assessment, 

including spill assessment (Natural Resource Damage 

Assessment, recovery, and restoration) efforts.

• Given gaps in spatial and temporal understanding 

of resources, how (methods, approaches) can the 

extensive industry site-specific monitoring be coupled 

with synoptic governmental efforts to improve broader 

scale understanding.

• What are the important differences in the physical and 

ecological conditions of the Beaufort and Chukchi 

Seas that need to be clearly understood to address the 

Secretary’s commitment to OCS exploration in the 

“right place/right time.”

The participants were provided background on the USGS 

OCS Team’s assignment, context for each of the questions, 

and several discussion starter questions. They then were asked 

to self-select one of the four break-out groups to participate 

in. After 45 minutes of facilitated discussion, groups were 

disbanded and participants self-selected another break-out 

group to participate in. In this second series of discussions, 

participants started with the materials developed by the 

first group and continued discussion. At the end of these 

discussions, each break-out group reported out to the full 

workshop. Input from those break-out groups is summarized 

in appendix tables B–1 and B–2. 

The following includes the materials that were provided 

to Symposium participants at the poster session in preparation 

for the January 21, 2011 USGS-sponsored 3-hour workshop.
234 An Evaluation of the Science Needs to Inform Decisions on Outer Continental Shelf Energy Development in the Chukchi and Beaufort Seas, Alaska

Break-Out Topic One: What weather and oceanographic data are needed immediately to improve spill risk assessments, response 

planning, and spill response; what approaches are recommended to obtain such data?

Framing the Topic: Information, assumptions, and predictions of weather, ice, currents, and other physical oceanographic data occur 

throughout pre-decisional documents and implementation plans for oil and gas development. Such information and its uncertainty influence 

infrastructure design and placement decisions; spill risk probability determination; modeled spill trajectories and predicted ecological 

outcomes; and spill contingency planning, response gap estimates, and real-time spill response. The importance of these data to sound 

decision making is acknowledged and reflected in ongoing study efforts. For example, a recent Bureau of Ocean Energy Management, 

Regulation and Enforcement (BOEMRE)-sponsored product by Weingartner and others (2010a) provides recommendations on physical 

oceanography studies for the Beaufort Sea. New technologies also are being assessed in BOEMRE- and industry-funded efforts as in Potter 

and Weingartner (2009) or Weingartner and others (2010b) who examine the use of a high-frequency radar system to map surface currents 

for improved spill trajectory models and spill response planning and how viable such systems are in partially ice-covered waters. However, 

what the potential fate and effect of oil might be from an accidental spill, the level of risk to be tolerated, and the sufficiency of science 

informing these topics remain points of discussion and disagreement among vested parties. 

In this break-out group, we would like to know what is going well and needs to continue, what is a good start and needs enhancement, 

what has not been addressed and should be and WHY. In the latter two cases, we would appreciate your understanding of how proposed 

increases in existing efforts or new data would inform the decision process. 

Discussion Starter Questions: 

1. Are there proven technologies and sampling regimes that should be expanded temporally or spatially, or initiated? If so, how might 

that happen? 

2. Logistics in the Arctic are challenging. Are there alternate technologies that should be investigated or whose use can be enhanced to 

obtain sufficient metocean data to support effective spill assessment, planning, and response?

3. The Arctic is not a static system, but is undergoing climate-driven change. What data collections and approaches should be 

considered to improve our ability to understand and forecast key weather and oceanography information to improve risk analyses over 

the multi-decade horizon of leasing decisions?

4. Are there different data needs or approaches that should be considered for the Chukchi Sea versus Beaufort Sea and vice versa?

5. What are some “low hanging fruit” opportunities, if any, that could be considered immediately?

References Documents: (intended only as examples of a few study efforts)

Potter, R., and Weingartner, T., 2009, Surface circulation radar mapping in Alaskan coastal waters: Beaufort Sea and Cook Inlet: Final

 Report OCS Study MMS (BOEMRE) 2009-049. 

Weingartner, T., Pickart, R., and Johnson, M., 2010a, Recommended physical oceanography studies in the Alaskan Beaufort Sea: Final

 Report OCS Study MMS (BOEMRE) 2010-018. 

Weingartner, T., Winsor, P., Potter, R., and Statscewich, H., 2010b, Chukchi Sea surface currents: accessed March 31, 2011, 

 at http://www.ims.uaf.edu/hfradar/. 
Appendix B 235

Appendix B

Break-Out Topic Two: What supplements to agency monitoring and approaches to integrated ecological monitoring are needed for 

improved development impact assessment, including spill assessment (NRDA, recovery) efforts?

Framing the Topic: : Information and assumptions about the status and trends of ecosystem components occur throughout predecisional documents and implementation plans for oil and gas development. Such information and its uncertainty influence estimation of 

potential ecological impacts in Oil Spill Risk Assessment Models by providing likely resource intersections based on spill trajectory models. 

Spill contingency planning incorporates best understanding of ecologically sensitive areas to be protected during response. Status and 

trends in distribution, demographics, physiological condition, and the like provide the foundation for assessing damage under the National 

Resource Damage Assessment (NRDA) process and later inform restoration strategies, recovery goals, and progress towards those goals. In 

addition, experience from the 1989 Exxon Valdez Oil Spill restoration effort demonstrates the need for understanding of individual species 

to be coupled with a more holistic ecosystem framework in which to assess and judge recovery. Cumulative effects analyses also examine 

species and community perspectives. There is significant investment to develop improved species and system’s knowledge. Various Federal 

and State agencies have ongoing mission-specific population-level sampling. The BOEMRE’s Environmental Studies Program also funds 

key work across a wide spectrum of ecological components informative to the OCS planning process. Examples range from traditional 

knowledge as reported in Quakenbush and Huntington (2009) and satellite telemetry (Alaska Department of Fish and Game, 2010) collected 

to provide a broader understanding of single species such as bowhead whale, to studies of species groups such as shorebirds (Powell 

and others, 2009) to integrated biomonitoring/bioaccumulation sampling for nearshore areas (Neff, 2010). However, what the potential 

ecological consequences might be from oil and gas infrastructure or an accidental spill, the level of risk to be tolerated, and the sufficiency 

of science to inform these topics remain points of discussion and disagreement among vested parties. 

In this break-out group, we would like to know what is going well and needs to continue, what is a good start and needs enhancement, 

what has not been addressed and should be and WHY. In the latter two cases, we would appreciate your understanding of how proposed 

increases or new data would inform the regulatory decision process. 

Discussion Starter Questions: 

1. Are there proven technologies and sampling regimes that should be expanded temporally or spatially, or initiated? If so, how might 

that happen? 

2. Many different monitoring, population, and ecosystem studies and sampling efforts are ongoing within the BOEMRE, other Federal and 

State agencies, and academic and non-governmental organization communities within the Arctic OCS, both specifically to inform oil 

and gas development decisions and with other goals, informative to OCS decision making. Are there science frameworks or modeling 

approaches that might be fruitful to bring knowledge from such sources together in a transparent way to better inform annual study 

priority setting and determination of progress towards filling data gaps?

3. Logistics in the Arctic are challenging. It may not be feasible to sample all populations and communities of interest at the desired 

intensity to reduce uncertainty. Are there alternate metrics that could be added to existing population survey efforts as surrogates for 

population status?

4. The Arctic is not a static system, but undergoing climate-driven change. What data collections and approaches should be considered 

to improve our ability to understand and forecast key population and ecological functions to improve cumulative effects and risk 

analyses over the multi-decade horizon of leasing decision?

5. Are there different data needs or approaches that should be considered for the Chukchi Sea versus Beaufort Sea and vice versa?

6. What are some “low hanging fruit” opportunities, if any, that could be considered immediately?

References Documents: (intended only as examples of a few study efforts)

Alaska Department of Fish and Game, 2010, Satellite tracking of Western Arctic Bowhead Whales: Alaska Department of Fish and Game

 (ADFG) Final OCS Study BOEMRE (MMS) 2010-033. 

Neff, J., 2010, Continuation of the Arctic nearshore impact monitoring in the development area (cANIMIDA) - Synthesis, 1999–2007: 

 Final Report OCS Study BOEMRE 2010-032. 

Powell, A., Taylor, A., and Lanctot, R., 2009, Pre-migratory ecology and physiology of shorebirds staging on Alaska’s North Slope: OCS 

 Study MMS (BOEMRE) 2009-034. 

Quakenbush, L., and Huntington, H., 2009, Traditional knowledge regarding Bowhead Whales in the Chukchi Sea near Wainwright, Alaska:

 Final Report OCS Study MMS (BOEMRE) 2009-063. 
236 An Evaluation of the Science Needs to Inform Decisions on Outer Continental Shelf Energy Development in the Chukchi and Beaufort Seas, Alaska

Break-Out Topic Three: Given gaps in spatial and temporal understanding of resources, how (methods, approaches) can extensive 

industry site-specific monitoring be coupled with synoptic governmental efforts to improve broader scale understanding?

Framing the Topic: There are inherent uncertainties in estimates of undiscovered oil and gas resources and in economic conditions that 

define when and where development may occur as a result of a leasing program. From 5-year Lease Sale Plans through specific sale EIS 

documents, estimates of environmental effects must rely on assumed exploration and development scenarios. The question often asked 

is—how is what we know, at the scale we know it, applicable to environmental assessments. How much confidence should we have in 

that understanding. 

In this break-out group, we would like to discuss your thoughts on mechanisms that could be considered to gain greater knowledge and 

improve scales of inference through strategic linkages of project or scale-specific studies or process studies by industry, academia and 

others with larger scale synoptic efforts. 

Discussion Starter Questions: 

1. What are the types of site-specific studies underway today? Process studies? Broader scale synoptic efforts? 

2. Are there mechanisms in place to facilitate linkages among different scaled studies? If not, what would you like to see?

3. Could modeling and process study design approaches, such as those in the North Pacific Research Board-National Science Foundation 

Bering Sea Integrated Ecosystem Research Project, be fruitful to Arctic OCS decisions? Are there other such ecosystem-based 

”tactical” efforts that could be examined?

4. What are some “low hanging fruit” opportunities, if any, that could be considered immediately?

Break-Out Topic Four: What are the important differences in the physical and ecological conditions of the Beaufort and Chukchi Seas 

that need to be clearly understood to address the Secretary’s commitment to OCS exploration in the “right place/right time.”

Discussion Starter Questions: 

1. Consider the other Break-out Topics (1) metocean data, (2) monitoring information, and (3) addressing scales of inference. Is there a 

difference in sufficiency or importance of specific science between the Beaufort and Chukchi Seas that need to be highlighted? 

2. Are there particular ecological areas that need focus?

3. Are there unique socioeconomic considerations between the planning areas for which different science attention is warranted?
Appendix B 237

Appendix B

Table B–1. Listing of science concerns expressed by participants at the technical workshop held at the Alaska Marine Science 

Symposium on January 21, 2011, in Anchorage, Alaska.

Science concerns

Topic 1:

Meteorologicalocean

data needs

Topic 2:

Monitoring 

efforts

Topic 3:

Scaling 

issues

Climate down scaling has to be used to develop ranges of parameters not to

expect precise results X

Distributed Biological Observatory (DBO) X X X

DBO done on an ongoing basis where drilling may take place X

Make physical oceanographic models accessible to researchers, public, and

oil-spill response. Combine on single interface (Alaska Ocean Observing 

System site?)

X

Comprehensive ecological monitoring of subsurface phytoplankton, benthic

ecology, substrate, diversity, production, ice seal stock, beluga stock, prey

structure, cod, euphausiids, copepods, and identify biology

X X

Trace material flow through the ocean, including river melt water and

sediment transport

X

Monitoring for real-time met-ocean data and water-level observations X

Make sure ocean circulation data keep up with depth of oil exploration X

Ice thickness, scale of measurements needed, scale of time observations, 

ice gouging, met-forcing affects on ice-floe movement

X

Understanding of the variations of the ocean from lease block to lease block X

Develop an incentive for public data (build and update database), publish 

raw data as it is collected, up-to-date data in GIS

X X

Make sure ocean/atmosphere models account for extreme events X

Coast Guard and oversight of spill cleanup X

Improve efficiency and collaboration between industry, academia, and

government agencies including disciplines not used to collaborating

X X

Establish on-going consistent monitoring strategies done in a broad

integrated manner that provides ability to quantitatively measure/predict

impacts

X X X

Interactive online research assets map showing where instruments in field

season exists, need to show this same information historically

X

Determine when equipment cannot be deployed due to wind, waves, fog, 

cold, darkness

X

Ranking of environmentally sensitive areas especially nearshore and

shoreline, changes to priority protection sites based on projects

X X

Trajectory modeling particularly in ice conditions X

Physical oceanography effects on infrastructure seasonally and during 

storm events

X

High resolution circulation patterns around sensitive areas, subsurface 

current information, seasonal variability of currents

X

Greater focus on effects of potential submarine pipelines and onshore

support facilities

X

Fish species lists are slowly being developed, but population, total numbers,

distribution, genetics, movement, and ice association are missing

X

Effects of natural gas/methane on subsurface species X

Effects of gas blowout at depth X
238 An Evaluation of the Science Needs to Inform Decisions on Outer Continental Shelf Energy Development in the Chukchi and Beaufort Seas, Alaska

Table B–1. Listing of science concerns expressed by participants at the technical workshop held at the Alaska Marine Science 

Symposium on January 21, 2011, in Anchorage, Alaska.—Continued

Science concerns

Topic 1:

Meteorologicalocean

data needs

Topic 2:

Monitoring 

efforts

Topic 3:

Scaling 

issues

Characterization of biological aspects of Barrow Canyon and other unique

features that may be considered exempt from lease sales or need data at a

higher resolution

X X

What compartment is the Chukchi/Beaufort biomass in during various

seasons, years?

X

National Resource Damage Assessment (NRDA) Process: how does 

monitoring relate, integration of historical and contemporary data, develop 

training [Shoreline Cleanup Assessment Technology (SCAT)], subsistence 

considerations in Bering Sea

X X

Conduct experiments including test spill with dye tracer, spill recovery

methods, oil in water and oil in ice

X X

Consult with Norway and United Kingdom for their risk assessment and

safety case planning as well as research on oil/ice interactions

X X

Local residents may be interested in working on compromises that 

determine right time/right place

X

Use of models and datasets not representative of Arctic conditions may lead

to incorrect conclusions and decisions

X

Increase coordination for planning, lease sales, mitigation measures,

permitting, on-going monitoring, and rehabilitation including oil-spill

response

X

Food web cycles are lacking adequate description especially low in food 

web, annual variability, and potential to disrupt these systems

X

Develop oil vulnerability index for species in Beaufort/Chukchi X

Give emphasis for site-specific studies to sites located in areas likely to 

be effected, that is, lease areas

X

Concern for cultural and resource impacts from development, need 

socio-economic baseline

X

Better framing in terms of temporal/spatial – percent chance of occurrence X

First assess relative abundance/importance then prioritize areas for more 

in-depth studies

X

Pair oceanographic observations with biological X

Data need for restoration of Arctic Ocean systems and populations X

Regular surveying of local communities for changes they are seeing X

How will we know the baseline data are representative given the potential

changes occurring already due to climate change

X

Marine mammal range extensions and response to ecosystem variability X

Incorporation of Alaska Ocean Observing System data into biological 

studies, especially for food web/prey structure/energy flow

X

Continued development of autonomous underwater vehicles (AUVs) and 

unmanned aircraft, augment acoustic recorders with sensors to capture 

biological activity and develop new technologies to increase monitoring 

capabilities

X X

How is oil breakdown effected by dispersants in ice and ice-free

environments

X
Appendix B 239

Appendix B

Table B–1. Listing of science concerns expressed by participants at the technical workshop held at the Alaska Marine Science 

Symposium on January 21, 2011, in Anchorage, Alaska.—Continued

Science concerns

Topic 1:

Meteorologicalocean

data needs

Topic 2:

Monitoring 

efforts

Topic 3:

Scaling 

issues

Effects of oil containments and dispersants to the ecosystem, what is the

adaptation of organisms to the oil

X

Long-term carbon assessment in water [for example, chromophoric dissolved 

organic matter (CDOM)] as baseline assessment, seawater chemistry, locate 

natural seeps

X X

Successful monitoring of Boulder Patch (Beaufort) year-round could be

considered for other significant habitats – (Chukchi?)

X

Community-based monitoring and assessment as a framework for

determining current status and future trends, include local communities for

on-the-ground response

X X

Pre-identify in-state resources with appropriate and current training, publish

roster at least within planning, response, and government and industry

X

Pre-identify mechanisms to distribute response-related research funding X

Address unique Arctic logistical issues regarding chain of custody, such as 

sample storage/handling issues

X

Pre-identify the process by which monitoring and sampling would be

temporarily expanded or initiated

X

What processes control the marine system, use this to help determine what to

measure and monitor

X

Scale at which things vary on benthos is much shorter than in water column X

Consider health impact, assessment and linking (and social parameters)

human health with the ecosystem

X

Necessary to identify what regions of the Arctic are important habitat for

particular species

X

Need migration/movement not just population for risk analysis X

More studies needed in microbiology (bacteria), bioremediation X X

Consider shifting baselines during monitoring programs and comparison 

to baselines

X

Distinguish between monitoring of potential impacts of ‘regular’ operations

versus those from ‘spill’ scenarios and monitor species recovery after a

hydrocarbon release

X X

Standardized studies need to be done to calculate locally meaningful

correction factors for things like marine mammal density estimates.

X

Gaps are seasonal, lacking early season and over winter so monitoring 

should include seasonal components, for example, winter oceanographic 

monitoring for circulation

X X

Synthesis and integration of existing information including observations,

model data, fate and effects of spilled oil, dispersant use, ecological data 

and baseline data

X X X

Under Ice system monitoring (including seasonality) = huge productivity X X

Ice-edge tracking (underway; relationship to ecosystem) X

Species adaptation capability/capacity X

Expand buoy array X X
240 An Evaluation of the Science Needs to Inform Decisions on Outer Continental Shelf Energy Development in the Chukchi and Beaufort Seas, Alaska

Table B–1. Listing of science concerns expressed by participants at the technical workshop held at the Alaska Marine Science 

Symposium on January 21, 2011, in Anchorage, Alaska.—Continued

Science concerns

Topic 1:

Meteorologicalocean

data needs

Topic 2:

Monitoring 

efforts

Topic 3:

Scaling 

issues

Transparency, quantitative/qualitative X

Recognize different monitoring needs/platforms/suitability to meet needs 

of the questions posed, proactive monitoring design

X

Need time-sensitive sites (transect) that are spatially placed to capture 

upstream and downstream work

X

Transport models that incorporate key physical and biological parameters X

Nested site selection X

What is the type/discipline of ecosystems data received to understand that

ecosystem

X

Longer comparable data sets from existing spatially distributed sampling

stations, replicate Outer Continental Shelf Environmental Assessment 

Program (OCSEAP) studies

X X

Fisheries—epibenthos abundance and distribution, species composition, 

ecological process, habitat association

X

Opportunistic opportunities to collect data and explore/analyze existing X

Broader scope oceanographic understanding is needed for better 

understanding of smaller scale

X

Tiering of information/studies is an important technique X

Do more research about planning to respond to oil spills in ice-infested 

Arctic waters, burning oil in ice, identify areas for pre-positioned protection

X X

Propagation of sound through oceans X

Passive acoustic monitors for mining data from other sounds X

Seismic data – through water column X

Spatial and temporal variability of ecology X

Ecological asset inventory X

Indices for keystone species X

Model verification – especially validation X

Process (in addition to coordination) for defining “sufficiency” across

spectrum of data/understanding, different for different levels of activity

X X
Appendix B 241

Appendix B

Table B–2. Differences in Beaufort and Chukchi Seas as noted by participants 

at the technical session held at the Alaska Marine Science Symposium on 

January 21, 2011, in Anchorage, Alaska.

Chukchi Sea

Cumulative impacts – shipping

Less infrastructure in place

Wave height, cold (affects weathering and clean up), visibility, wind driven leads

More complex, topographically, Barrow Canyon

Shoal habitat (Hanna and Harold)

Bering Sea influence; nutrients and carbon 

Shallow sea with oil resource far offshore in deep water

Sea bottom very productive, hot spots

More shelf and areas of interest for exploration are ice free longer

Most development areas beyond coastal subsistence use areas

Spring whaling, seal hunting on shear ice, walrus and seal hunting in pack ice

Development farther offshore, greater risk?

More historical and ongoing work

Primarily ship provided transport, shorter transit from south, no road access

Walrus haulouts changing due to changing ice, modeling of walrus distribution

Critical feeding areas for migrating birds

Point Lay, Point Hope – very traditional village lifestyles

Beaufort Sea

Cumulative impacts – oil and gas in Canadian Beaufort

Ice-driven leads, land-fast ice

Current OSC exploration, more infrastructure

Nutrients and carbon from upwelling and shore, more complex circulation

Beaufort gyre influenced, longer sea ice in summer, river influenced

Deep sea with oil resource in shallow water

Flat shelf, sea bottom mostly barren, ice gouging, active gouging zone

Dissolved organic carbon terrestrial carbon utilization 

Perhaps more viable, trending towards less ice cover

Lots of overlap between subsistence and development

Fall whaling, cisco/white fish

Importance of cod, 96 percent of fish abundance and biomass, keystone species

Need synthesis of existing data (census of marine life)

Multi-modal, road access to Prudhoe Bay, cargo aircraft, access to small vessels, 

used to heavy equipment, longer ship transport times

Much more subsistence, but perhaps not as traditional lifestyles
242 An Evaluation of the Science Needs to Inform Decisions on Outer Continental Shelf Energy Development in the Chukchi and Beaufort Seas, Alaska

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Appendix C 243

Appendix C

Background

Decisions facing the Department of the Interior (DOI) on 

behalf of the Federal Government about whether and where 

to permit oil and gas exploration and development on the 

Arctic Outer Continental Shelf (OCS) are challenging. The 

challenge arises primarily as a function of four characteristics. 

First, there are complex and potentially competing objectives 

associated with a diverse stakeholder contingent (for example, 

energy development, marine mammal protection, oil-spill 

prevention). Second, there are a wide variety of different 

decision alternatives available to the decision maker, including 

many possible combinations of temporal and spatial structures 

in development permitting. Third, there is an unknown array 

of decisions required of other agencies resulting from each 

possible oil and gas development decision alternative that 

could be selected by the DOI. Fourth, as demonstrated by the 

analyses outlined in the chapters of this report, there exists 

a great deal of complex information as well as substantial 

uncertainty about the potential effects of development on the 

myriad resources of management interest.

Structured decision making (SDM; sensu Clemen, 1996; 

Possingham and others, 2001; Williams and others, 2007) is 

the application of decision science to assist decision makers in 

the process of making decisions, and is especially important 

and applicable in the case of decisions that are both important 

(that is, high stakes) and challenging. SDM rests on the idea 

that decisions can be made more effectively (that is, more 

likely to lead to attainment of management objectives) if a 

structured analysis is conducted. This analysis consists of 

deconstructing decisions into their component parts, analyzing 

each part, and synthesizing the parts into a decision framework 

that can produce direct recommendations to decision makers 

about which decision is most likely to lead to attainment of 

management objectives. More generally, engagement in a 

formal decision-analytic process helps the decision maker to 

develop the fullest possible understanding of the complexities 

of the decision, such as decision objectives, tradeoffs, 

uncertainties, and risks.

Structured decision making is not appropriate in all cases. 

The use of the process requires that a decision maker can be 

identified and that the management objectives (potentially 

multiple and competing) of that decision maker can be 

articulated. In addition, the set of decision alternatives under 

consideration must be known or knowable, and there must be 

an ability to make predictions about how different alternatives 

would impact the objectives of interest; such predictions 

can arise from data or from expert judgment and may (and 

often do) involve substantial uncertainty. Finally, and most 

generally, the process requires transparency in development of 

all decision components. 

Value of Structured Decision Making

A formal decision-analytic process can help most 

specifically by producing a recommended course of action 

most likely to lead to attainment of management objectives. 

More generally, however, the process is useful for informing 

a decision maker about the complexities of the decision. For 

instance, the process is useful in helping the decision maker to 

develop a clear articulation of the management objectives, to 

contemplate tradeoffs, to be aware of uncertainty and integrate 

risk attitudes into the decision (that is, the degree of risk the 

decision maker is willing to accept in order to obtain some 

potential benefit), and to develop a sense of what information 

is available and what uncertainties are relevant. When used 

appropriately, formal decision processes are designed to lead 

to decisions that are (Runge and others, 2009): 

• Transparent—SDM is designed to produce 

transparency in the decision-making process, 

to remove the “black box” aspects of decision 

making, such that decisions can be understood and 

communicated. 

• Explicit and Able to be Documented—The 

transparency required by the SDM process results in 

decision processes that are explicit in their treatment 

of decision components, which results in decisions that 

can be effectively documented within an administrative 

record. 

• Deliberative—SDM encourages careful deliberation 

about the various components of the decision-making 

process. This is expected to lead to better decision 

outcomes because deliberation encourages more 

thorough identification of management objectives 

and tradeoffs, a wider search for creative decision 

alternatives, more complete use of scientific 

information in developing predictions of decision 

outcomes, and more thorough articulation of important 

uncertainties and risks in the decision. 

Appendix C. Structured Decision Making for Energy Exploration and 

Development Decisions on the Arctic Outer Continental Shelf

 By Sarah J. Converse
244 An Evaluation of the Science Needs to Inform Decisions on Outer Continental Shelf Energy Development in the Chukchi and Beaufort Seas, Alaska

• Robust—SDM recognizes that uncertainty and risk 

influence decision making. As such, SDM is designed 

to produce decision processes that fully recognize 

the type and magnitude of uncertainty and risk; 

such decision processes are designed to produce 

recommendations that are robust to the uncertainty and 

risk that exist; that is, decision processes that are most 

likely to lead to attainment of management objectives.

Stakeholders and Structured Decision 

Making

Within the public policy realm, consideration of the 

values of stakeholders is of paramount importance in framing 

decisions. In the U.S. Department of the Interior Adaptive 

Management Technical Guide, engagement with stakeholders 

is identified as the first step of the adaptive management 

process, which itself is recognized as a structured decisionmaking process (Williams and others, 2007). Stakeholders 

have multiple roles in developing decision processes, and 

should be effectively engaged in the development of each 

component of the process. Perhaps most critically, the 

objectives of stakeholders must be understood and integrated. 

The decision maker, in public policy decisions, has ultimate 

responsibility for understanding and articulating stakeholder 

objectives, and for weighing tradeoffs between competing 

objectives of diverse stakeholder groups. As such, we assume 

herein that the values of stakeholders are included as they are 

understood by and embodied in the objectives and tradeoffs of 

the decision maker. 

Components of Structured Decision Making

Structured decision making consists, most basically, of 

deconstructing decisions into their component parts, analyzing 

the individual components, and synthesizing the components 

into an integrated decision framework that is designed to lead 

to recommended courses of action. As such, decision analysts 

recognize that every decision involves a consistent set of 

components (for example, Hammond and others, 1999). These 

components are: 

Decision Problem.—The decision problem is a clear 

statement of the decision that is to be made. It includes 

information on the factors prompting the decision, the 

identity of the decision maker, the particular decision to 

be made, the spatial and temporal scope of the decision, 

the timing of the decision, and whether the decision will 

be repeated through time or is a one-time decision. 

Objectives.—The objectives are the things that the 

decision maker wants to achieve in the context of 

the particular decision. They are representations of 

values, policy, and stakeholder objectives guiding the 

decision maker. In decision analysis, it is often useful to 

differentiate between fundamental and means objectives. 

Fundamental objectives reflect ultimate statements of 

values—in essence, the most basic values of the decision 

maker. Means objectives, by contrast, are objectives 

the decision maker would like to achieve because they 

are themselves means to achieving the fundamental 

objective(s). For example, if a fundamental objective, 

in the context of the OCS energy exploration and 

development decision, is to maintain the tourism value of 

the Arctic system, a means objective may be to minimize 

the construction of energy development infrastructure in 

critical viewsheds.

Alternatives.—The decision alternatives are the 

comprehensive set of alternative management actions 

available to the decision maker. The alternatives will 

depend on the particular decision to be made, and may 

have many elements (for example, spatial and temporal 

components). 

Model.—The system model and predictions component 

is the component most familiar to scientists. This 

component encompasses all information available about 

the implications of different decision alternatives on the 

management objectives. That is, science in a decisionmaking context serves to link our decision alternatives to 

our objectives, such that we can make predictions of the 

form, “if we take action ‘a’, the result in terms of a given 

management objective will be ‘b’.” More specifically, we 

often make such predictions in a probabilistic framework, 

because we have substantial uncertainty about the 

functioning of complex systems. 

Optimization.—The tradeoffs analysis, or optimization, 

is the final step necessary in identifying an optimal 

decision, and involves searching among the proposed set 

of decision alternatives for the option that is most likely 

to lead to the attainment of management objectives. 

In many cases, this means weighing tradeoffs among 

competing objectives. In addition, some decisions involve 

an additional component.
Appendix C 245

Appendix C

Monitoring and Feedback.—Monitoring and feedback 

are applicable when decisions are repeated through time. 

In these cases, monitoring data can be used to assess 

whether management objectives are met, to measure 

the state of the system for informing state-dependent 

decisions (that is, where the decision that one takes 

depends on some aspect of on-the-ground conditions), and 

to reduce uncertainty about how the system responds to 

management (Lyons and others, 2008). These monitoring 

data can then be used to update predictions about system 

responses to management, thus facilitating improved 

decision making through time (Nichols and Williams, 

2006). 

Prototyping of a Decision Framework

With the input of the U.S. Geological Survey (USGS) 

OCS Team, the broad outline of a decision framework 

to inform the DOI Arctic OCS energy exploration and 

development decision was developed. This framework 

was developed as an example of a more fully articulated 

framework that could be developed with the input of the 

decision maker or delegates. That is, this decision framework 

is both incomplete and not assumed to represent the true 

aspects of the decision as understood by the decision maker; 

instead it is intended as an illustration. This simple prototype 

demonstrates the basic process of SDM and how it could 

be applied to synthesize and analyze science and policy 

information to inform Arctic OCS energy exploration and 

development decisions. 

Decision Problem.—The national strategy for energy and 

economic security defines the intent by the Administration 

to open certain OCS areas to exploration, set aside those 

areas deemed inappropriate for development, and increase 

oil and gas exploration in some frontier areas. The Arctic 

OCS is identified as one of the most promising frontier 

areas for consideration because of its high potential 

of oil and gas resources, a substantial portion of the 

global potential. This is evidenced by the fact that oil 

and gas leases already exist in the Arctic OCS. It also 

is an environment containing substantial ecological 

and social resources of high spatial and temporal 

complexity. Within this area, there exist federally 

mandated conservation requirements within the context 

of the National Environmental Policy Act, International 

treaty, and Endangered Species Act regulations. The DOI 

holds authority for decisions on energy exploration and 

development in the Arctic OCS.

There are two decisions facing the DOI—one short term 

and one long term. The short-term decision involves 

deciding what to do with current Arctic OCS leases that 

are on hold. The long-term decision involves deciding 

when and where to permit exploration, development, 

and production of oil and gas resources in the Arctic 

OCS; that process is nested within ongoing and repeated 

revision of the OCS 5-year planning process. There are 

decisions made at each stage (exploration, development, 

and production) that can be seen as linked decisions (that 

is, decisions made at one stage influence the decision 

alternatives available at the subsequent stage), and there 

are substantial stakeholder concerns related to the linked 

nature of these decisions. Concern in the conservation 

community is based on the perception that once 

exploration begins, it is inevitable that production will 

occur; the energy industry is concerned that any one of 

these linked stages can result in termination of exploration 

and development prior to production. 

There are disparate stakeholders with vested interests 

and substantial influence through the congressional, 

judicial, and regulatory processes whose views must be 

considered and incorporated into the decision. Industry 

has made significant investments in the Arctic OCS. 

Other stakeholders include the subsistence community 

(who have invested generations in the region and whose 

culture is tied to the marine environment), the general 

public (who have a stake in the biodiversity, remoteness, 

the domestic energy resource, and the lease revenue), 

and the conservation community (who have a stake in 

the biodiversity and ecological function of the Arctic). 

Federal agencies with stakes in the decision include 

the Bureau of Ocean Energy Management, Regulation 

and Enforcement (BOEMRE) (regulatory authority 

over leases), the National Oceanic and Atmospheric 

Administration (NOAA) (regulatory authority over listed 

species), and the Coast Guard (ultimately responsible for 

spill response and safety). 

There is substantial scientific uncertainty about the 

impacts of energy exploration and development on 

resources of interest. The DOI has recognized this 

uncertainty and has tasked the USGS with describing the 

state of scientific knowledge in order to inform decisions 

regarding the Arctic OCS; results of the USGS analyses 

are described in the chapters of this report. In addition, 

the linked nature of these decisions does have the effect 

of allowing monitoring data to inform future steps in the 

decision process, indicating the importance of welldesigned and well-executed monitoring plans. 

4.
246 An Evaluation of the Science Needs to Inform Decisions on Outer Continental Shelf Energy Development in the Chukchi and Beaufort Seas, Alaska

Objectives.—The USGS OCS team developed a 

draft objectives hierarchy consisting of fundamental 

objectives grouped in thematic areas, and linked to 

means objectives. This objectives hierarchy is expected 

to represent at least some of the objectives of the DOI 

in the context of the Arctic OCS energy exploration 

and development decision, but it is not expected to be 

a complete or necessarily accurate set of the DOI’s 

objectives. The objectives are illustrated graphically in 

figures C–1 through C–3 and also are provided below. 

First tier elements are thematic areas (that is, groupings 

of fundamental objectives). There were three thematic 

areas identified: human communities, ecosystem 

values, and economic vitality. Second tier elements are 

fundamental objectives, of which 10 were identified. 

Third tier elements are means objectives. 

The identified objectives are as follows:

1. Maintain Values of Human Communities

a. Protect Human Health and Maintain Human 

Safety

b. Protect and Maintain Subsistence Communities

i. Maintain Populations of SubsistenceHunted Species

ii. Maintain Culturally Critical Components of 

Subsistence Hunting 

c. Meet Trust Responsibilities to Native 

Communities 

2. Maintain Ecosystem Values 

a. Protect and Maintain Ecological Function

b. Protect and Maintain Biological Diversity

i. Maintain Populations of Endangered 

Species

ii. Maintain Populations of Marine Birds

iii. Maintain Populations of Marine Mammals

iv. Maintain Populations of Fishes

c. Protect Wilderness Values and Experience

3. Maintain Economic Vitality of Region

a. Meet Energy Production Targets

b. Meet Lease Revenue-Generation Targets

c. Provide Employment Opportunities

d. Maintain Tourism Value

Protect and Maintain 

Subsistence 

Communities

Maintain Values of

Human Communities

Protect Human Health 

and Maintain Human 

Safety

Maintain Populations 

of Subsistence-Hunted 

Species

Maintain Culturally 

Critical Components of 

Subsistence Hunting

Meet Trust 

Responsibilities to 

Native Communities

Figure C–1. Objectives hierarchy for the “Maintain Values of Human

Communities” theme.
Appendix C 247

Appendix C

Alternatives.—Decision alternatives will involve 

different spatial and temporal patterns of permitting. 

Spatial aspects include the particular blocks opened 

for permitting, such as whether to allow drilling inside 

the current exclusion area or to expand the exclusion 

area, and the physical location of permitted sites within 

permitted blocks, including the allowable proximity to 

resources of spatial interest. Temporal aspects include the 

timing of exploration and production activities within a 

permitted area (for example, drilling could be staggered 

through time) and whether to impose seasonal constraints 

on activities. Additional aspects include which mitigation 

measures to mandate (for example, such as constraints 

on the density and spacing of drill sites). Decision 

alternatives will be defined by various combinations of 

different spatial and temporal patterns of permitting, 

both with and without mandates for various mitigation 

measures.

Models.—The modeling stage is the stage during which 

scientific information is used to develop predictions 

of the impact of decision alternatives on the various 

management objectives. We note, however, that building 

predictive models can only commence after the preceding 

elements of the decision process are fully understood 

(that is, the decision problem, objectives, and decision 

alternatives). 

To build predictive models, we would begin by 

developing conceptual models that link components of 

the system through logical relationships; these logical 

relationships are described in narrative form throughout 

the chapters of this report. Conceptual models must 

demonstrate links between alternatives and objectives, 

so the basis for predictions about the impacts of decision 

alternatives on objectives can be made. Development 

of conceptual flow diagrams is a useful precursor to 

development of quantitative predictions. An example 

can be seen in figure C–4, linking the spatial location of 

permitted sites to the objective of maintaining populations 

of marine mammals. 

Maintain Ecosystem 

Values

Protect and Maintain 

Ecological Function

Maintain Populations 

of Endangered 

Species

Protect and Maintain 

Biological Diversity

Protect Wilderness 

Values and Experience

Maintain Populations 

of Marine Birds

Maintain Populations 

of Marine Mammals

Maintain Populations 

of Fishes

Figure C–2. Objectives hierarchy for the “Maintain Ecosystem Values” theme.

Maintain Economic 

Vitality of Region

Meet Energy 

Production Targets

Meet Lease 

RevenueGeneration Targets

Provide 

Employment 

Opportunities

Maintain Tourism 

Value

Figure C–3. Objectives hierarchy for the “Maintain Economic Vitality of Region” theme.
248 An Evaluation of the Science Needs to Inform Decisions on Outer Continental Shelf Energy Development in the Chukchi and Beaufort Seas, Alaska

Maintain Populations 

of Marine Mammals

Maintain Bowhead 

Whale Populations

Maintain Sustainable 

Survival Rates

Maintain Sustainable 

Reproductive Rates

Population Behavior 

and Movement 

Patterns

Population 

Disturbance and 

Displacement

Spatial Location of 

Permitted Sites

Figure C–4. An example logical flow 

diagram linking actions (the spatial 

location of permitted sites) to an 

objective (maintain populations of 

marine mammals).

Once such conceptual models are developed, they can 

be used to form the basis of quantitative predictions. 

Separate predictive models are needed for each of the 

fundamental objectives, where outputs of the models will 

be in units related to the objective (for example, for the 

objective “maintain populations of marine mammals,” 

models for each species of interest would produce output 

in the form of numbers of individuals or probability of 

population viability). These models will make predictions, 

then, of the impact of each decision alternative on each of 

the identified management objectives. 

One appropriate quantitative modeling tool for at least 

some of the objectives may be Bayesian Belief Networks 

(Marcot and others, 2006), which are graphical models 

that allow for propagation of uncertainty via conditional 

dependencies between model components. These are 

probabilistic models that frequently can be developed 

even with sparse scientific information. Much of the 

scientific information necessary to build the predictive 

models of interest may be in the form not of data but 

of expert knowledge. In this case, techniques for expert 

elicitation could be used to capture this information in 

a fashion appropriate for building quantitative models 

(Meyer and Booker, 1990; Ayyub, 2001). 

Optimization.—Once predictions are made about the 

impact of each decision alternative on each management 

objective, a wide variety of formal techniques can be used 

to search among the decision alternatives to identify the 

optimal decision alternative. Given the complexity and 

multi-objective nature of the OCS energy exploration 

decision, it is likely that Multi-Criteria Decision Analysis 

(MCDA; Keeney and Raiffa, 1976) will be the source of 

appropriate optimization techniques. In multi-objective 

decisions, optimization consists of making tradeoffs 

among multiple objectives. That is, certain alternatives 

will perform best on some objectives, while different 

alternatives will perform best on other objectives. The 

task, then, is to consider these tradeoffs. 

A variety of methods are available for tradeoff analysis in 

MCDA, but frequently the techniques involve developing, 

in concert with the decision maker or delegates, weights 

on objectives and then normalizing and summing the 

predicted outcomes across alternatives to develop 

“scores” for each alternative, where the alternative with 

the highest score is identified as the preferred alternative. 

A necessary final step, then, is sensitivity analysis to 

evaluate the impact of any uncertainty on the model 

predictions or the objective weights to inform the decision 

maker if the decision is highly sensitive to these elements. 

Sensitivity analyses may suggest places for improvement 

in the decision framework before final recommendations 

are developed. 
Appendix C 249

Appendix C

References Cited

Ayyub, B.M., 2001, Elicitation of expert opinions for 

uncertainty and risks: CRC Press, Boca Raton, FL, USA.

Clemen, R.T., 1996, Making hard decisions: an introduction 

to decision analysis: Duxbury Press, Belmont, California, 

USA.

Hammond, J.S., Keeney, R.L., and Raiffa, H., 1999, Smart 

choices: a practical guide to making better life decisions: 

Broadway Books, New York, USA.

Keeney, R.L., and Raiffa, H., 1976, Decisions with multiple 

objectives: preferences and value tradeoffs: New York, John 

Wiley and Sons.

Lyons, J.E., Runge, M.C., Laskowski, H.P., and Kendall, 

W.L., 2008, Monitoring in the context of structured decision 

making and adaptive management: Journal of Wildlife 

Management, v. 72, p. 1683-1692.

Marcot, B.G., Steventon, J.D., Sutherland, G.D., and McCann, 

R.K., 2006, Guidelines for developing and updating 

Bayesian belief networks applied to ecological modeling 

and conservation: Canadian Journal of Forest Research, 

v. 36, p. 3063-3074. 

Meyer, M.A., and Booker, J.M., 1990, Eliciting and analyzing 

expert judgment: a practical guide: Office of Nuclear 

Regulatory Research, Division of Systems Research, U.S. 

Nuclear Regulatory Commission, Washington D.C., USA.

Nichols, J.D., and Williams, B.K., 2006, Monitoring for 

conservation: Trends in Ecology and Evolution, v. 21, 

p. 668-673.

Possingham, H.P., Andelman, S.J., Noon, B.R., Trombulak, 

S., and Pulliam, H.R., 2001, Making smart conservation 

decisions, in Soulé, M., and Orians, G., eds., Conservation 

biology: research priorities for the next decade: Island 

Press, Washington, D.C., p. 225-244. 

Runge, M.C., Cochrane, J.F., Converse, S.J., Szymanski, J.A., 

Smith, D.R., Lyons, J.E., Eaton, M.J., Matz, A., Barrett, 

P., Nichols, J.D., and Parkin, M.J., 2009, An overview of 

structured decision making, pilot edition: U.S. Fish and 

Wildlife Service, National Conservation Training Center, 

Shepherdstown, West Virginia.

Williams, B.K., Szaro, R.C., and Shapiro, C.D., 2007, 

Adaptive management: The U.S. Department of the Interior 

Technical Guide: Adaptive Management Working Group, 

U.S. Department of the Interior, Washington, D.C.

Capacity for Structured Decision Making and 

Requirements of the Process

Capacity for supporting decision-analytic processes 

exists both within USGS and in academic and non-profit 

settings around the United States. Recommendations for 

conducting decision analysis include: 

1. Designate a team coordinator who can act as the 

decision maker’s representative in the decisionanalytic process. The team coordinator should have 

an accurate understanding of the decision maker’s 

objectives (which will integrate the objectives of 

stakeholders as described above). 

2. The team coordinator should work directly with 

the decision analyst(s) to form a team consisting of 

experts with relevant knowledge on the different 

components of the decision, as well as relevant legal 

and administrative matters. 

3. The decision analyst(s) should work with team 

members in a workshop setting to develop an initial 

sketch of the elements of the decision (this is known 

as rapid prototyping the decision framework). 

4. Individual team members can then work individually 

to further develop different components of the 

decision framework, for example, complete 

development of relevant predictive models. This 

individual work should be done in close coordination 

and with regular input from other members of the 

team. 

5. A final workshop may be held during which the final 

tradeoffs analysis can be conducted. This, paired 

with appropriate sensitivity analyses, can be used to 

complete the report on the decision-analytic process. 

Summary Recommendations: Formal decision-analytic 

methods are useful for supporting decision making in challenging 

settings with multiple objectives, complex sets of available 

decision alternatives, and substantial uncertainty and risk. Using 

the collective knowledge of the USGS OCS team, we developed 

a Structured Decision Making framework as an example of what 

could be developed to inform decisions about energy exploration 

and development in the Arctic OCS. Although development of such a 

framework would require input of the decision maker or delegates in 

order to accurately represent management objectives and tradeoffs, 

we present this example to illustrate the process as well as the 

potential utility of SDM in this setting, wherein adoption of SDM 

could facilitate a more robust, transparent, and deliberative decision. 

We encourage careful consideration of SDM as a useful process 

in the Arctic Outer Continental Shelf energy exploration decision 

setting. 
250 An Evaluation of the Science Needs to Inform Decisions on Outer Continental Shelf Energy Development in the Chukchi and Beaufort Seas, Alaska

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Appendix D 251

Appendix D

Background

The March 24, 1989 Exxon Valdez Oil Spill (EVOS) 

was not related to oil and gas development activities, but 

was the result of the grounding of the tanker Exxon Valdez

on Bligh Reef in Prince William Sound, Alaska, while 

outside of normal traffic shipping lanes to avoid icebergs. 

This accident was the largest oil spill in U.S. waters until the 

Deepwater Horizon spill of 2010. The lessons learned from 

the spill are included here for the purposes of highlighting 

Alaska-based experience ranging from spill response through 

Natural Resource Damage Assessment components that can 

help inform the U.S. Geological Survey (USGS) Arctic Outer 

Continental Shelf (OCS) Team assignment. 

Most of the oil from the grounding of the Exxon Valdez

was spilled in the first 6 hours as approximately 10.9 million 

of the 53 million gallons of North Slope crude oil aboard 

leaked into the water. Within 2 months, the spread of this 

oil had impacted more than 1,300 discontinuous miles of 

the 9,000-mi long coastline in the Prince William Sound 

and the Gulf of Alaska region (fig. D–1). Less than 1 of the 

1,300 mi of oiled beaches was accessible by road (Hunt, 

2009). Exxon was not prepared for a spill of this magnitude, 

nor was its pipeline service company and responder Alyeska, 

nor the Federal or State governments (Skinner and Reilly, 

1989). Efforts were made to remove oil from the water, and 

included booms to collect oil, test areas of burning, surface 

dispersants to break up the oil into smaller concentrations, 

and mechanical skimming to remove oil on the surface. Once 

the oil had reached shorelines, chemical cleaners, hot water 

and high pressure, and manual removal by shovels, human 

hands and absorbent materials were used (Alaska Department 

of Environmental Conservation, 1993). For the past 20 years, 

the $900 million in civil settlement funds paid by Exxon have 

supported restoration, monitoring and research activities in the 

spill-impacted area (Exxon Valdez Oil Spill Trustee Council, 

2011b).

The OCS Arctic evaluation and planning effort for oil 

development can benefit from the EVOS experience through 

two aspects: (1) improvements in oil-spill prevention and 

response made as a result of the EVOS, which have enhanced 

our protection capabilities; and (2) lessons learned from the 

EVOS, which can inform better preparedness and protection. 

Improvements in Spill Prevention and Response 

Triggered by the EVOS Have Enhanced Our 

Preparedness

Significant progress has been made in oil-spill prevention 

and response as a direct consequence of lessons learned from 

the EVOS, applicable to both its spill area as well as spills 

elsewhere. Some of these improvements better prepare the 

OCS Arctic planning effort, and are listed below. The Federal 

Oil Pollution Act of 1990 (OPA 90), passed by Congress in 

response to the EVOS, established a procedure for assessing 

natural resource damages and establishing liability, and 

designates specific Federal, State and Tribal Government 

officials to act as trustees on behalf of the public to recover 

damages from the responsible parties to restore injured, 

destroyed, or lost natural resources. The OPA 90 also added 

“oil” to the other hazardous substances covered by the 

Comprehensive Environmental Response, Compensation, 

and Liability Act of 1980. In the EVOS area itself, specific 

advances include:

• Alyeska Pipeline Service Company (established in 

1970 to oversee the Trans Alaska Pipeline System, 

and Exxon’s first responder to the EVOS), now spends 

more than $60 million annually under the Ship Escort/

Response Vessel System (SERVS) created in 1989, 

to plan, prepare, and enhance oil-spill prevention and 

response measures in Prince William Sound. 

◦ Alyeska oversees oil spill contingency plans such as 

those required by the State of Alaska for all tankers 

traveling in Prince William Sound, which must 

include scenarios for open-water, nearshore, and 

shoreline responses and support operations.

Appendix D. The Exxon Valdez Oil Spill Experience: Lessons Learned from a 

Cold-Water Spill in Sub-Arctic Waters

 By Dede Bohn
252 An Evaluation of the Science Needs to Inform Decisions on Outer Continental Shelf Energy Development in the Chukchi and Beaufort Seas, Alaska

Alaska

Peninsula Shelikof Strait

Kodiak I.

Gulf of

Alaska

Exxon Valdez

grounding site

Homer

0 50 100

Miles

0 50 100

Kilometers

Kenai

Map Area Peninsula

Alaska

Cook

Inlet

Day 4

March 27

37 miles

Day 7

March 30

90 miles

Day 11

April 3

140 miles

Day 14

April 7

150 miles

Day 19

April 14

250 miles

Day 40

May 2

350 miles

Day 56

May 18

470 miles

Seward

Figure D–1. Within 8 weeks after the spill, wind and currents had distributed the oil from the site of the accident at Bligh Reef in 

Prince William Sound into the Gulf of Alaska areas of Cook Inlet, Kodiak Island, and the Alaska Peninsula, a maximum distance of 

470 miles. Source: 1993 State On-Scene Coordinator’s Report (Alaska Department of Environmental Conservation, 1993).
Appendix D 253

Appendix D

◦ Under Aleyska’s SERVS program:

– The design of skimming systems to separate and 

remove oil from the surface of water has been 

improved and is now 10 times greater than it was 

in 1989.

– Seven barges, capable of holding 818,000 barrels 

of oil, have been made available in Prince William 

Sound. At the time of the spill, even if oil could 

have been collected, there was no holding facility.

– Forty miles of containment boom is available in 

Prince William Sound, seven times as much as in 

1989.

– Dispersants are stockpiled for use and application 

systems via helicopters, airplanes, and boats have 

been designated. 

– Contingency planning for spills in Prince William 

Sound, held annually, must include a scenario for 

a spill of at least 12.6 million gallons.

• The U.S. Coast Guard, via satellite, has expanded the 

area where it monitors for icebergs and other potential 

hazards in the paths of tankers transporting oil across 

Prince William Sound.

• Two, rather than one, escort vessels now accompany 

and, if needed, assist each tanker while it is in the 

Sound, as directed by an executive order from the 

Alaska Governor soon after the EVOS.

• At the State level, a dozen new laws for oil-spill 

prevention, response, and oversight were passed by 

the Alaska Legislature between April 1989 and May 

1990, including: (1) enlarging the State’s emergency 

oil and hazardous substance response fund to 

50 times its previous size; (2) revisions to the oil-spill 

prevention, response, contingency plan regulations; 

and (3) increased liabilities and penalties for polluters.

• Congress enacted legislation requiring double hulls 

on all oil tankers by 2015, including those traveling 

in Prince William Sound. A U.S. Coast Guard study 

estimated that, had the Exxon Valdez been doublehulled at the time of the spill, the amount of oil spilled 

would have been reduced by more than one-half 

(Exxon Valdez Oil Spill Trustee Council, 2011b).

• The OPA 90 established two oversight and monitoring 

programs, one in Prince William Sound, and one 

in Cook Inlet, to foster partnership of industry, 

government, and local communities in overseeing 

the environmental compliance for crude oil terminals 

(Cook Inlet Regional Citizens Advisory Council, 2011; 

Prince William Sound Regional Citizens’ Advisory 

Council, 2011).

• The Oil Spill Recovery Institute, established by 

Congress in the OPA 90 after the spill, is charged 

with identifying and developing the best available 

techniques, equipment and materials for responding 

to oil spills in the Arctic marine environment and to 

complement Federal and State damage assessment 

efforts. The Institute is actively conducting research 

and educational and demonstration projects to carry 

out its mission, and is mandated through September 

2012 (Prince William Sound Science Center Oil Spill 

Recovery Institute, 2011).

Planning for Preparedness in the Arctic OCS 

Region: Lessons Learned from the EVOS

Below we list in italics some of the lessons learned from 

the EVOS, which have bearing on the potential strengths and 

weaknesses of the scientific and technical understanding for 

Arctic OCS activities. Following each lesson is an explanation 

of the EVOS activities that comprised it.

Oil-Spill Response

Move quickly and be prepared to contain the oil to keep the 

situation from worsening. 

The extent of injuries to natural resources and services 

resulting from a spill depends on the circumstances of 

the incident and the prevailing environmental conditions. 

Although the weather was calm for the first 3 days after 

the EVOS, Alyeska Pipeline Company, the designated first 

responder under the Prince William Sound contingency plan, 

had few pieces of equipment available and ready for use. In 

addition to Alyeska’s contingency plan, National, regional, 

and local plans mandated by Federal regulation also had 

been developed, but the plans were not coordinated, had not 

established a response command hierarchy for responding to 

a spill, and lacked specific measures to address such problems 

as how to address spills in remote areas (Skinner and Reilly, 

1989). 

• Lightering, the process of unloading the remaining 

oil from the damaged tanker, took 11 days until the 

seepage of oil could be stopped. Underwater divers 

had located holes in 11 of the ship’s holding tanks. 

(Skinner and Reilly, 1989).

• Only two skimmers and little or no containment boom 

were deployed initially (Skinner and Reilly, 1989).

• A small initial test burn successfully consumed 12,000 

to 15,000 gal, but further tests were thwarted due to 

stormy weather (Skinner and Reilly, 1989).
254 An Evaluation of the Science Needs to Inform Decisions on Outer Continental Shelf Energy Development in the Chukchi and Beaufort Seas, Alaska

• There were not enough dispersants available, nor 

enough vessels and equipment ready to deploy the 

dispersants. An initial trial application on the first day 

of the spill failed because of a lack of mixing energy 

(wind) and a later trial was inconclusive (Skinner and 

Reilly, 1989).

• A severe winter storm with wind gusts up to 73 mph 

arrived the evening of March 26 quickly dispersing 

the oil into patches, which spread to beaches up to 

40 mi south of the site of the accident, at the same time 

temporarily grounding the response vessels. 

• Eventually the oil reached as far as 470 mi away, to 

Chignik, on the Alaska Peninsula. Because the escaped 

oil was so widespread, it was necessary to continue 

cleanup efforts for four summers. Some oil lingers 

today, and cleanup efforts for it remain underway.

Spill response should aim to prevent oil from reaching 

streams, fine sediment beaches, and estuaries.

• Oil persisted in the sediments of streams, mussel beds, 

and estuaries, contaminating natal and nursery fish 

habitats for several years (Moles, 2001).

Damage and Injury Assessment

Fate of the oil, and thus the potential and nature of subsequent 

environmental effects, depends on a complex interaction of 

variables at the time of the spill, including chemistry, weather, 

shoreline characteristics, currents, temperature, and season.

• Estimates on the fate of the spilled oil are (Wolfe and 

others, 1994): 

◦ 20 percent evaporated, 

◦ 50 percent biodegraded either where it was deposited 

or in the water column, 

◦ 14 percent was recovered or disposed during the trial 

burning and dispersant treatments, 

◦ Less than 1 percent remained in the water column, 

◦ 2 percent remained on intertidal shorelines, and 

◦ About 13 percent remained in subtidal sediments, 

mostly as highly weathered residues. 

• Within days, a winter storm had widely dispersed the 

oil slick both on the surface and subsurface of the 

seawater; oil droplets in the water column reached 

depths of at least 75 ft (Short and Harris, 1996); 

some mousse formed as the oil churned and mixed 

with water, and some tar balls formed as a result of 

evaporation (Payne and others, 1996).

• Wind, tide, and currents continued to redistribute the 

oil for at least 2 months, as shown in figure D–1.

• Spring tides were nearly 18 ft, stranding some oil high 

on shorelines, giving rise to a “bathtub ring” which 

was protected from wave action, resulting in no further 

dispersal (Spies, 2007).

• The total number of animals killed by the spill is 

unknown. The carcasses of more than 35,000 birds and 

1,000 sea otters were found after the spill, but since 

most carcasses sink, this is a minimum estimate of the 

actual loss. The EVOS Trustee Council estimates are: 

250,000 seabirds, 2,800 sea otters, 300 harbor seals, 

250 bald eagles, up to 22 killer whales, and billions 

of salmon and herring eggs (Exxon Valdez Oil Spill 

Trustee Council, 2011c). 

• Biologically, the end of March is particularly stressful 

for organisms because they have nearly depleted 

their stored energy and are beginning migration 

and reproduction cycles and the added impact of 

being oiled or having oiled prey takes a big toll. The 

populations of plankton and herring, which form the 

base of the food chain supporting much of the wildlife, 

were hard hit because the spring plankton bloom 

had just begun, and Pacific herring were entering the 

nearshore habitat of Prince William Sound in order 

to spawn. All age classes of herring and a significant 

portion of spawning habitats were contaminated by oil, 

and subsequently, lesions and elevated hydrocarbon 

levels were documented in some adult herring (Rice, 

2010).

Emphasize preplanning: develop and maintain a regularly 

updated scientific sampling or biological response plan. 

• Develop assessment approaches that do not require 

extensive baseline data, such as ecosystem models that 

identify pathways and processes at risk to oil injury; 

increase the accuracy of these models by running 

the models with parameters gleaned from pre-spill 

biological samples so that a baseline condition can 

be better established, and perturbations tested prespill. Monitor populations that can serve as surrogates 

for others, such as monitoring harlequin ducks as a 

surrogate for benthic-feeding birds (See, 2001). 

• Develop a multi-species integrated approach to test 

mechanisms limiting recovery; an example in the 

nearshore environment included a study focused on 

the invertebrate-feeding sea otter and harlequin duck 

combined with the fish-feeding river otter and pigeon 

guillemot seabird (Peterson and Holland-Bartels, 

2002).

• Pre-plan coordination and designate trained staff; 

maintain a scientific sampling or biologic response 

plan. Otherwise, collections can be haphazard, and data 

and specimens can be lost and unreported, inaccurate, 

and incomplete. Plan for a central data clearinghouse 

(See, 2001).
Appendix D 255

Appendix D

Obtain a geochemical signature of the spilled oil; not all of the 

oil encountered on the beaches of the spill area was sourced 

from the Exxon Valdez accident.

• Some of the oil residues found on some of the Prince 

William Sound shorelines were chemically distinct 

from the spilled oil (Kvenvolden, 1993).

• Flattened tar balls found throughout the northern and 

western parts of the Sound had carbon-isotopic and 

biomarker signatures of oil products used in Alaska 

before 1970, and are thought to have been created 

when storage facilities ruptured during the 1964 Alaska 

earthquake (Kvenvolden, 1995).

Cleanup

Cleanup was slow to get started, but eventually involved 

more than 11,000 workers. The combination of the presence 

of such a large workforce and its supporting infrastructure 

on sensitive coastal areas, coupled with effects from 

cleanup approaches, resulted in confounded impacts to the 

environment. 

Detrimental effects of shoreline cleanup methods are complex 

and sometimes oversimplified. 

• High-pressure, hot-water washing of the Prince 

William Sound shorelines effectively removed stranded 

oil, but damaged flora and fauna directly and indirectly, 

and received much public criticism, which caused it to 

be discontinued. Studies from the EVOS were among 

the first to document these impacts (Mearns, 1996).

• Response methodologies continue to include the 

high-pressure, hot-water washing techniques, but the 

National Oceanic and Atmospheric Administration 

(NOAA) Office of Response and Restoration now 

gives greater weight to evaluating the complexities and 

competing interests and the environmental tradeoffs 

before these methodologies are used (National Oceanic 

and Atmospheric Administration Office of Response 

and Restoration, 2011). 

Restoration

A number of factors affected the ability of agencies to 

assess damage, define restoration goals, and judge progress 

towards those goals. Main among these was the lack of prespill data for potentially damaged natural resources and (or) 

the lack of current data. While, for example, significant data 

were available for seabirds and their prey, such data were 

collected in the 1970s prior to a decadal oceanic regime shift, 

which brought in different oceanic temperatures and salinities, 

resulting in changes to the food web, which triggered 

restructuring of the biological communities (Anderson and 

Piatt, 1999). Thus, the use of available pre-spill data such 

as seabird colony population surveys and demographic 

information as a pre-spill data set upon which to judge damage 

or recovery was confounded (Piatt and Anderson, 1996). 

The United States Government and the State of Alaska 

settled their claims against Exxon Shipping Company and 

Exxon Corporation on October 9, 1991, with a settlement 

agreement comprised of a criminal plea agreement and fine of 

$150 million, criminal restitution for injuries to fish, wildlife, 

and land for $100 million, and a $900 million civil settlement 

fine. A Memorandum of Agreement between the Federal and 

State governments established the Exxon Valdez Oil Spill 

Trustee Council to manage the $900 million civil settlement 

for restoration activities. The Council is comprised of three 

Federal and three State Trustees.

Define restoration objectives and strategies to achieve the 

goal of recovering the oil spill area ecosystem. 

• Since the EVOS, the OPA 90 Natural Resource 

Damage Assessment (NRDA) regulations have 

established that the restoration goal is achieved 

when the injured natural resources and services have 

returned to the condition they would have been, had 

the spill not occurred.

• In the 1994 EVOS Restoration Plan, some recovery 

objectives specified a return to pre-spill conditions or 

to stable or increasing population trends, which did 

not account for stressors other than oil, which became 

increasingly important as time went by.

Injury assessment of natural resources is complicated by a 

lack of pre-spill data and compounded by natural variation 

and will always involve uncertainties. 

• In lieu of applicable pre-spill population data, animal 

carcass counts, a crude and minimal measure, had to 

be used in order to measure the extent of damages. 

Actual losses were higher than counted because some 

carcasses sank or were never discovered. For example, 

research studies have estimated the actual loss of the 

seabird murre population at 40 percent of its prespill level, or a loss of 250,000 murres, compared 

with the carcass recovery of 21,000 (Piatt and Ford, 

1996). Such extrapolations are highly sensitive to 

the “observed versus not observed” ratio applied 

to calculate total loss, which in turn is affected by 

weather conditions that hamper the ability to make 

observations. 

• Sources of uncertainty in assessing both the short- and 

long-term damage following a spill include variability 

in the available population estimates, lack of pre-spill 

data, ongoing changes to the ecosystem as a result of 

changing climate and other natural factors, emergence 

of new effects (for example, new contamination 

arising from contact with lingering oil), difficulty 

establishing causation (an unequivocal cause-and-
256 An Evaluation of the Science Needs to Inform Decisions on Outer Continental Shelf Energy Development in the Chukchi and Beaufort Seas, Alaska

effect relationship between the biological resource and 

the oil), and comparing studies of differing spatial and 

temporal scales (Integral Consulting, Inc., 2006).

• Additional measures and approaches to measure 

damage in lieu of contemporary pre-spill baselines 

proved essential to developing an understanding of 

system recovery. Recovery status has been determined 

by evaluating the initial magnitude of oil impacts to 

a population through carcass counts, comparing the 

population demographics between oiled and unoiled 

areas, comparing the health of biological community 

members from oiled and unoiled areas, measuring to 

determine continued exposure to lingering oil through 

biomarker or tissue concentrations, establishing the 

persistence of sublethal or chronic injuries, evaluating 

the intrinsic ability of the population to recover, 

and accounting for other stressors from natural or 

anthropogenic sources (Exxon Valdex Oil Spill Trustee 

Council, 2006).

Track the status of recovery by updating the status of injury 

through monitoring.

• A list of natural resource and human service injuries 

caused by the EVOS helped guide the Restoration 

Plan adopted by the EVOS Trustee Council in 

1994. The listings include the recovery status of 

individual species as well as sediments, subtidal 

and intertidal communities, commercial fishing, 

subsistence, recreation and tourism, archeological 

resources, and designated wilderness areas. The list 

has been instrumental to the EVOS Trustee Council 

in prioritizing the expenditure of public restoration 

funds received from the civil settlement with Exxon, 

ensuring that money was expended on resources 

needing attention. As restoration has proceeded and 

recovery statuses have changed, the list has been 

updated and re-published in 1996, 1999, 2002, 2006, 

and 2010. The list serves to track and document the 

status of recovery of the oil spill area; as of 2010, 

2 resources have not recovered (Pacific herring, 

pigeon guillemots), 10 resources are recovering 

(Barrow’s Goldeneyes, black oystercatchers, clams, 

designated wilderness areas, harlequin ducks, intertidal 

communities, killer whales, mussels, sea otters, 

sediments), 10 resources have recovered (archeological 

resources, bald eagles, common loons, common 

murres, cormorants, Dolly Varden fish, harbor seals, 

pink salmon, river otters, sockeye salmon), 3 resources 

are very likely recovered (cutthroat trout, rockfish, 

subtidal communities), and the recovery status of 2 

resources (Kittlitz’ and Marbled Murrelets) is unknown 

(Exxon Valdez Oil Spill Trustee Council, 1994, 2006, 

2010). 

Use an ecosystem perspective; examine food chains, and use 

ecosystem models to pinpoint pathways and processes at risk 

to oil injury. Do not ignore lower trophic levels. 

• Multi-disciplinary, multi-species approaches increased 

the power to detect and evaluate recovery: the Sound 

Ecosystem Assessment project evaluated factors 

affecting productivity of Pacific herring and pink 

salmon; the Nearshore Vertebrate Predator program 

addressed factors affecting the recovery of four 

indicator species; and the Alaska Predator Ecosystem 

Experiment evaluated the productivity and recovery of 

seabirds based on the availability of forage fish (Exxon 

Valdez Oil Spill Trustee Council, 2011b). Recovery 

also will involve complex interactions, such as those 

associated with the dynamics of both microbial 

communities and food webs, which will cascade 

changes up to the largest predator. 

Oil can remain toxic in the environment a surprisingly long 

time; oil degradation rates depend upon localized conditions 

(Michel and Esler, 2010, and citations therein). 

• Some oil has persisted more than 2 decades 

in unexpected amounts and in toxic relatively 

unweathered forms, buried in the subsurface intertidal 

area of approximately 50 discontinuous beach sites, 

which put together, total a shoreline length of about 

1.5 mi.

• The beaches with persistent oil have an upper, highly 

permeable layer and a lower layer of low permeability 

where the oil has remained trapped, physically 

protected from disturbance, oxygenation, and 

photolysis.

• The oiling history (high, medium, low) of the beaches, 

surveyed after the spill and again in 2001 and 2008, 

is one important indicator of predicting where oil 

persists. 

• Biodegradation of the oil has been limited by a low 

concentration of dissolved oxygen as well as a nutrient 

concentration too small to sustain oil-consuming 

microorganisms. Bioremediation projects are being 

undertaken in 2011, 22 years after the spill.
Appendix D 257

Appendix D

Some of the lingering oil has been bioavailable to wildlife and 

has induced chronic exposure in nearshore species (Michel 

and Esler, 2010, and citations therein).

• Organisms that use the intertidal zone were severely 

impacted by initial oiling and cleanup and continued to 

show adverse impacts from continued exposure such 

as reduced survival rates and diminished populations. 

Studies have addressed and documented exposure 

to lingering oil in birds (harlequin ducks, Barrow’s 

Goldeneyes, black oystercatchers, pigeon guillemots), 

sea otters, and fish (masked greenlings and crescent 

gunnels).

• Some harlequin ducks and sea otters in the nearshore 

environment have continued to exhibit signs of 

exposure to oil through 2006 and 2009, as measured 

through elevated oil biomarkers in blood and tissues or 

in gene expression. Studies are ongoing and awaiting 

the results of laboratory analyses of the most recent 

harlequin duck samples collected in March 2011 to see 

if oil exposure continues.

Long-term chronic exposure is now recognized as a major 

component of injury and may equal or exceed acute effects 

(Peterson and others, 2003).

• Effects of the EVOS have revised the paradigm 

for assessing ecological risks of oil in the ocean. 

Previously, it was assumed that acute mortality is 

the main impact to a population, but EVOS research 

has shown that chronic, delayed and indirect longterm risks and impact play a much larger role than 

previously envisioned. Risk assessment models that 

project biological injury need to be updated from 

treating species independently to instead provide for 

interacting variables.

• A delay in population reduction was caused, for 

example, by ingestion of oiled prey, by lower survival 

rates for harlequin ducks in the winters following the 

spill due to cumulative stress from encountering the 

lingering oil, and by damage to fish over time through 

oil exposure which increased embryo mortality and 

deformity and resulted in poor predator avoidance and 

low growth rates.

• Recovery was postponed as cascades of indirect 

effects, such as a food shortage of forage fishes as well 

as a reduction of high-quality forage fish prey reduced 

seabird populations of murres, puffins, and pigeon 

guillemots. Animal communities may experience 

delayed recovery depending on complex interactions, 

and communities may not soon return to their original 

configurations. For example, a loss of experienced 

breeders in seabird colonies disrupted the phenology 

of breeding for several years, imperiling late-fledging 

young, such as murres. On rocky shorelines, indirect 

interactions resulting from oiling and loss of the 

ubiquitous rockweed plant cover, as well as grazing 

and predatory gastropods, are thought to have delayed 

the recovery process for a decade or more, while 

opportunistic barnacles colonized the open rock spaces 

and disrupted the food chain.

• Injury to seabirds, mammals, fish, and invertebrates 

continues long term through chronic exposure from 

ingesting contaminated prey and through foraging 

in oiled sediments, and through disruption of 

reproduction. Long-term exposure of fish embryos 

to weathered oil has had population consequences 

through indirect effects on growth, deformities, and 

behavior (Rice, 2010, and citations therein).

Oil effects can be subtle, indirect, and long term. 

• Long-term monitoring and research have been essential 

in identifying the full impacts of the spill, as evidenced 

particularly for sea otters and harlequin ducks. The 

EVOS Trustee Council has sponsored a multitude of 

projects to monitor the recovery of injured species, 

and final reports can be found on their website 

(Exxon Valdez Oil Spill Trustee Council, 2011b) as 

well as throughout the published literature. Longterm monitoring of the recovery of the nearshore 

environment, where patches of toxic oil still linger, is 

one such project which is ongoing, and which is being 

considered for 5 to 20 additional years of funding by 

the EVOS Trustee Council at its August 2011 meeting.

• Some injuries cannot be determined until years later, 

such as the significant long-term biological effects 

of lingering oil; studies are currently in progress for 

harlequin ducks and sea otters. 

• Delays in the recovery of bird and mammal predators 

of fish and invertebrates resulted from chronic and 

indirect effects, such as the loss of their habitat due 

to oiling or cleanup activities and the subsequent 

spread of opportunistic species, such as algae or small 

intertidal fishes, which inhibited the return of the 

original fish and invertebrate food sources (Peterson, 

2000). 
258 An Evaluation of the Science Needs to Inform Decisions on Outer Continental Shelf Energy Development in the Chukchi and Beaufort Seas, Alaska

• Sublethal exposures to oil caused mortalities due 

to compromised health, growth, or reproduction; 

for example, long-term exposure of the black 

oystercatchers that foraged on heavily oiled shores, 

documented up to 3 years post-spill, showed reduced 

breeding and smaller eggs than those that bred in 

unoiled areas; higher chick mortality occurred in 

areas where their diet consumption had included oiled 

mussels; and the oystercatcher parents gathering prey 

on oiled shores fed chicks more to achieve less growth 

than those on unoiled shores, at a higher energetic cost 

(Peterson and others, 2003). 

• The acute, initial loss of killer whales following the 

spill has had a long-term impact on the recovery of the 

ecosystem because the species is long-lived with low 

reproductive rates, and, as the predator at the top of 

the food chain, significantly affects the structure of the 

ecosystem (Rice, 2010).

• Pacific herring, a primary forage fish for many seabird 

and marine mammals, still have not recovered. Despite 

numerous studies, the causes of this phenomenon are 

not well understood, but appear to include disease, 

predation, and poor recruitment (the survivability of 

juveniles) (Exxon Valdez Oil Spill Trustee Council, 

2010). 

Not much real (that is, direct) restoration can be done; so 

instead the environment must be restored. 

• Lost services, such as commercial and sport fishing, 

recreation and tourism, and subsistence are assumed 

to be restored when the species upon which they were 

based are restored (Exxon Valdez Oil Spill Trustee 

Council, 1994).

• To date, because direct restoration opportunities are 

few, the $900 million civil settlement funds received 

from Exxon and managed by the EVOS Trustee 

Council have been allocated 24 percent to research, 

monitoring, and direct and indirect restoration; 

37 percent to habitat protection and acquisition; 

22 percent reimbursements for assessments and 

response; and 17 percent in an investment trust fund 

to increase the amount of funds available for future 

studies (Exxon Valdez Oil Spill Trustee Council, 

2011b).

• Natural recovery was selected under the 1994 EVOS 

Restoration Plan as the preferred alternative for 

restoration, and research and monitoring were directed 

at tracking the status of recovery (Exxon Valdez Oil 

Spill Trustee Council, 1994).

◦ Because natural recovery over the past 20 years has 

failed to remediate the 50 beach segments identified 

recently with the most significant persistent oil, 

bioremediation projects using oxygenation and 

nutrient enrichment techniques are being tested by 

the EVOS Trustee Council in 2011 as a way to clean 

up the remaining oil (Exxon Valdez Oil Spill Trustee 

Council, 2011a).

• Habitat acquisition to promote natural recovery of 

spill-injured resources, especially on lands under 

imminent threat of development, has been a significant 

and well-received component of the EVOS restoration 

program, and could be an effective tool elsewhere. 

As of 2006, the Council has protected more than 

630,000 acres of habitat, including more than 1,400 mi 

of coastline and more than 300 streams valuable for 

salmon spawning and rearing (Exxon Valdez Oil Spill 

Trustee Council, 2010). 

A Reopener clause, part of the 1991 legal settlement between 

Exxon and the State and Federal governments, provided for 

unanticipated injury.

• Some of the long-term injury from the spill was 

not identifiable initially, but has been established 

since, under research funded by the EVOS Trustee 

Council. Under the oil spill Reopener clause in the 

1991 litigation settlement with Exxon, on August 31, 

2006, the Federal and State governments submitted 

a demand letter to Exxon to pay up to $100 million 

for additional restoration work for the recovery of a 

population, habitat or species suffering a substantial 

loss or decline from an injury that could not have been 

known or reasonably anticipated on the date of the 

settlement. The plan focuses on the restoration of sites 

where lingering toxic oil persists (U.S. Department of 

Justice, 2006). Studies assessing the linkage of injury 

from the lingering oil to damage at the population 

level, particularly in sea otters and sea ducks, which 

inhabit the nearshore environment where the lingering 

oil occurs, are ongoing, and their outcome will help 

inform the Reopener claim. Trustee Council-sponsored 

research is underway to continue to identify lingering 

oil site locations, factors limiting the degradation of the 

oil, and to test pilot projects to remediate the pockets 

of lingering oil. Negotiations between the governments 

and Exxon to address this claim remain underway 

since September 2006. 

Prepare for conflicting studies. 

• Exxon Corporation has continued to fund its own 

damage assessment studies, and the resulting 

conclusions have consistently contrasted with those 

funded by the EVOS Trustee Council. The studies 

have differed in concept, statistical rigor, and choice of 

study sites and those differences have led to differing 

conclusions (Spies, 2007; Rice, 2010).
Appendix D 259

Appendix D

• Sampling design begets conclusions: Despite having 

common goals, four studies on the impact of the spill 

on intertidal biota involved different sampling efforts, 

analytical methodologies, and the choice of biological 

response variables that led to differing conclusions. 

Two of the studies were funded by Exxon Corporation, 

one by the EVOS Trustee Council, and one by the 

NOAA Hazmat program (Peterson and others, 2001).

Summary Points for the OCS Oil Planning Team 

Effort

Prevention is the principal defense against oil spills. 

Preparedness is the next best thing, with the caveat that no two 

oil spills are the same. Full recovery from the Exxon Valdez 

oil spill has not yet occurred, 22 years later. Keeping oil from 

reaching shorelines, where it is difficult to treat, may remain 

in a toxic form in the subsurface for up to 22 years—as in 

the EVOS—and takes an enormous toll on the food chain, 

must be a top priority in spill response. Not all species are 

equally affected, and not all species recover at the same rate. 

Initial wildlife mortalities from the EVOS were extreme, 

and likely understated due to lack of pre-spill population 

data and the difficulty in recovering carcasses. Studies of 

the long-term environmental and health effects on wildlife 

of acute and chronic exposure to oil have yielded surprising 

findings emphasizing the magnitude and complexity of the 

long-term impact. The effects of chronic oil exposure, delayed 

impacts, and sub-lethal impacts on growth, development, 

and reproduction have caused decreases at the population 

level; this finding is significant. An ecosystem-approach, 

allowing for the effects of indirect and cascading reactions, is 

imperative in evaluating restoration.

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Appendix E

The “Arctic Marine Synthesis: Atlas of the Chukchi and Beaufort Seas” by Audubon Alaska and Oceana (Smith, M.A., 2010, 

Arctic Marine Synthesis—Atlas of the Chukchi and Beaufort Seas: Audubon Alaska and Oceana, Anchorage) represents an 

emergent approach about data quality and sufficiency. Before the creation of this effort few others had assembled broad-scale 

information for this area. This broad synthesis utilizes spatial data from more than 100 sources plus literature and reports 

from another 400 sources, resulting in 44 thematic maps that cover six categories for the Chukchi and Beaufort Seas: Physical 

Oceanography, Water Column and Benthic Life, Fish, Birds, Mammals, and People. A listing of maps, data sources, and data 

quality ratings compiled from this synthesis is shown in table E–1. 

Appendix E. Arctic Marine Synthesis—Data Sources and Data Quality
262 An Evaluation of the Science Needs to Inform Decisions on Outer Continental Shelf Energy Development in the Chukchi and Beaufort Seas, Alaska Table E–1. Listing of maps, data sources, and data quality ratings as compiled from “The Arctic Marine Synthesis: Atlas of the Chukchi and Beaufort Seas” by Audubon Alaska in partnership with Oceana (Smith, 2010).

[Good: provides a complete geographic picture of the resource or species; data are consistent and of decent quality for mapping at the scale used (1:5,000,000); this rating does not indicate that fine-scale, project level data are available; Fair: provides a partial geographic picture of the resource or species; data are variable, some portions of the map are represented by reliable, high-quality data and data for 

other portions of the map are outdated, opinion-based, or missing data altogether; some key features, such as concentrations areas, may be missing. Poor: provides an incomplete geographic picture of the 

resource or species; information is missing, outdated, or deficient, but it is the best known data available (Smith, M.A., 2010, Arctic Marine Synthesis—Atlas of the Chukchi and Beaufort Seas: Audubon Alaska and Oceana, Anchorage)]

Map title

Data quality 

rating 

(Good, Fair, Poor)

Data sources for individual maps

Physical OceanographyProject Area Good AOOS. 2009. 1 km topographic/bathymetric map of Alaska. Raster dataset. <http://ak.aoos.org/aoos/tools.htm>. Accessed February 2009.

Alaska State Geospatial Data Clearinghouse. 2008. Base data. GIS shapefiles. <http://www.asgdc.state.ak.us/>. Accessed June 2008.

Audubon Alaska. 2009. Bathymetric contour lines. GIS feature class (based on AOOS 2009).Johnson, G.W., A.G. Gaylord, J.J. Brady, M. Dover, D. Garcia-Lavigne, W.F. Manley, R. Score, and C.E. Tweedie. 2009. Arctic Research 

Mapping Application (ARMAP). CH2M HILL Polar Services, Englewood, Colorado. <http://www.armap.org>. Accessed January 2010.

Bathymetry Good AOOS. 2009. 1 km topographic/bathymetric map of Alaska. Raster dataset. <http://ak.aoos.org/aoos/tools.htm>. Accessed February 2009.

Alaska State Geospatial Data Clearinghouse. 2008. Base data. GIS shapefiles. <http://www.asgdc.state.ak.us/>. Accessed June 2008.Audubon Alaska. 2009. Bathymetric contour lines. GIS feature class (based on AOOS 2009).Audubon Alaska. 2009. Chukchi Sea shoals. GIS feature class (based on AOOS 2009).

Ecoregions Good Piatt, J.F., and A.M. Springer. 2007. Marine ecoregions of Alaska. Pages 522–526 in Long term ecological change in the Northern Gulf 

of Alaska. R. Spies, editor. Elsevier, Amsterdam. <http:/www.absc.usgs.gov/research/NPPSD/marine_ecoregions.htm>. Accessed July 2008.

Nowacki, G., P. Spencer, T. Brock, M. Fleming, and T. Jorgenson. 2001. Ecoregions of Alaska. GIS shapefile. USGS, Reston, Virginia.World Wildlife Fund. 2009. Terrestrial ecoregions. GIS shapefile. <http://www.worldwildlife.org/science/ecoregions/item1267.html>.

Accessed November 2009.

OceanCirculation

Fair AOOS. 2009. 1 km topographic/bathymetric map of Alaska. Raster dataset. <http://ak.aoos.org/aoos/tools.htm>. Accessed February 2009.

Audubon Alaska. 2009. Bathymetric contour lines. GIS feature class (based on AOOS 2009).Audubon Alaska. 2009. Ocean circulation. GIS feature class (based on Weingartner et al. 2005; Weingartner 2006; MMS 2007; University 

of Alaska Fairbanks, Institute of Marine Science 2009).

MMS (Minerals Management Service). 2007. Chukchi Sea Planning Area, Oil and Gas Lease Sale 193 and seismic surveying activities in 

the Chukchi Sea final environmental impact statement. U.S. Department of the Interior, MMS, Alaska OCS Region, Anchorage, Alaska.

University of Alaska Fairbanks, Institute of Marine Science. 2009. Chukchi Sea circulation. Digital map. <http://www.ims.uaf.edu/ 

chukchi/>. Accessed March 2009.

Weingartner, T. 2006. Circulation, thermohaline structure, and cross-shelf transport in the Alaskan Beaufort Sea. Report OCS Study MMS 

2006-031. MMS.

Weingartner, T., K. Aagaard, R. Woodgate, S. Danielson, Y. Sasaki, and D. Cavalieri. 2005. Circulation on the north central Chukchi Sea 

shelf. Deep Sea Research Part II: Topical Studies in Oceanography 52:3150-3174.
Appendix E 263

Appendix E

Map title

Data quality 

rating 

(Good, Fair, Poor)

Data sources for individual maps

Physical Oceanography—ContinuedSea Ice Dynamics Fair AOOS. 2009. 1 km topographic/bathymetric map of Alaska. Raster dataset. <http://ak.aoos.org/aoos/tools.htm>. Accessed February 2009.

Audubon Alaska. 2009. Chukchi Sea shoals. GIS feature class (based on AOOS 2009).Audubon Alaska. 2009. Landfast ice (≥3 months per year). GIS feature class (based on National Ice Center 2008).Audubon Alaska. 2009. Monthly sea ice concentration (≥50 percent based on monthly median from 2003–2007). GIS raster dataset (based 

on National Ice Center 2008).

Audubon Alaska. 2009. Recurring leads and polynyas. GIS feature class (based on Stringer and Groves 1991; USFWS 1995; Carmack and 

MacDonald 2002; Eicken et al. 2005).

Carmack, E.C., and R. MacDonald. 2002. Oceanography of the Canadian shelf of the Beaufort Sea: a setting for marine life. 

Arctic 55:29-45.

Eicken, H., L.H. Shapiro, A.G. Gaylord, A. Mahoney, and P.W. Cotter. 2005. Mapping and characterization of recurring spring leads and 

landfast ice in the Beaufort and Chukchi seas. OCS Study MMS 2005-068. MMS, Anchorage, Alaska.

Hearon, G., D. Dickins, K. Ambrosius, and K. Morris. 2009. Mapping sea ice overflood using remote sensing: Smith Bay to Camden Bay.

Report prepared by DF Dickins Associates, Coastal Frontiers Corporation, Aerometric, and University of Alaska, The Geophysical Institute, for U.S. Department of Interior, MMS, Alaska OCS Region.

National Ice Center. 2008. National Ice Center Arctic sea ice charts and climatologies in gridded format. GIS datasets. F. Fetterer and C. 

Fowler, editors. National Snow and Ice Data Center, Boulder, Colorado.

National Snow and Ice Data Center. 2010. Monthly sea ice extent. GIS shapefile. <ftp://sidadscolorado.edu/DATASETS/NOAA/G02135 

shapefiles/>. Accessed January 2010.

NOAA. 1988. Bering, Chukchi, and Beaufort seas coastal and ocean zones strategic assessment data atlas.Stringer, W.J., and J.E. Groves. 1991. Location and areal extent of polynyas in the Bering and Chukchi seas. Arctic 44, Supplement 1:164-

171.

USFWS. 1995. Habitat conservation strategy for polar bears in Alaska. USFWS, Anchorage, Alaska.

Sea FloorSubstrate

Poor Carmack, E.C., and R. MacDonald. 2002. Oceanography of the Canadian shelf of the Beaufort Sea: a setting for marine life. 

Arctic 55:29-45.

Dunton, K.H., E. Reimnitz, and S. Schonberg. 1982. An Arctic kelp community in the Alaskan Beaufort Sea. Arctic 35(4):465-484.Horowitz, W.L. 2002. Evaluation of sub-sea physical environmental data for the Beaufort Sea OCS and incorporation into a geographic 

information system (GIS) database. OCS Study MMS 2002 017. <http://www.mms.gov/itd>. Accessed June 2009.

Mohr, J.L., N.J. Wilimovsky, and E.Y. Dawson. 1957. An Arctic Alaskan kelp bed. Arctic 19:45-54.

NOAA. 1988. Bering, Chukchi, and Beaufort seas coastal and ocean zones strategic assessment data atlas.NOAA. 2002. Environmental sensitivity index, version 3.0. NOAA, Seattle, Washington.

Table E–1. Listing of maps, data sources, and data quality ratings as compiled from “The Arctic Marine Synthesis: Atlas of the Chukchi and Beaufort Seas” by AudubonAlaska in partnership with Oceana (Smith, 2010)—Continued[Good: provides a complete geographic picture of the resource or species; data are consistent and of decent quality for mapping at the scale used (1:5,000,000); this rating does not indicate that fine-scale, project level data are available; Fair: provides a partial geographic picture of the resource or species; data are variable, some portions of the map are represented by reliable, high-quality data and data for 

other portions of the map are outdated, opinion-based, or missing data altogether; some key features, such as concentrations areas, may be missing. Poor: provides an incomplete geographic picture of the 

resource or species; information is missing, outdated, or deficient, but it is the best known data available (Smith, M.A., 2010, Arctic Marine Synthesis—Atlas of the Chukchi and Beaufort Seas: Audubon Alaska and Oceana, Anchorage)]
264 An Evaluation of the Science Needs to Inform Decisions on Outer Continental Shelf Energy Development in the Chukchi and Beaufort Seas, Alaska Map title Data quality rating (Good, Fair, Poor) Data sources for individual maps Physical Oceanography—Continued Sea Surface Temperature Good Audubon Alaska. 2009. Average yearly mean sea surface temperature, May–October, 2004–2008 GIS raster dataset (based on Feldman and McClain 2009). Feldman, G.C., and C.R. McClain. 2009. Ocean color web, aqua MODIS, NASA Goddard Space Flight Center. N. Kuring, S. Bailey, and W. April, editors. <http://oceancolor.gsfc.nasa.gov/>. Accessed June 2009. Observed Climate Change Good Halpern, B., S. Walbridge, K. Selkoe, C. Kappel, F. Micheli, C. D’Agrosa, et al. 2008. A global map of human impact on marine ecosystems. Science 319:948-952. National Snow and Ice Data Center. 2010. Monthly sea ice extent. GIS shapefile. <ftp://sidadscolorado.edu/DATASETS/NOAA/G02135 shapefiles/>. Accessed January 2010. Water Column and Benthic Life Chlorophyll-A Good Audubon Alaska. 2009. Average seasonal mean chlorophyll-a, May–October, 2004–2008. GIS raster dataset (based on Feldman and McClain 2009). Feldman, G.C., and C.R. McClain. 2009. Ocean color web, aqua MODIS, NASA Goddard Space Flight Center. N. Kuring, S. Bailey, and W. April, editors. <http://oceancolor.gsfc.nasa.gov/>. Accessed June 2009. Net Primary Productivity Good Audubon Alaska. 2009. Mean yearly sum of net primary productivity, 2003–2007. GIS raster dataset (based on Behrenfeld and Falkowski 1997; Oregon State University 2009). Behrenfeld, M.J., and P.G. Falkowski. 1997. Photosynthetic rates derived from satellite-based chlorophyll concentration. Limnology and Oceanography 42:1-20. Oregon State University. 2009. Ocean productivity. GIS datasets. <http://www.science.oregonstate.edu/ocean.productivity/index.php>. Accessed April 2009. Zooplankton Poor NOAA. 1988. Bering, Chukchi, and Beaufort seas coastal and ocean zones strategic assessment data atlas. Benthic Biomass Fair AOOS. 2009. 1 km topographic/bathymetric map of Alaska. Raster dataset. <http://ak.aoos.org/aoos/tools.htm>. Accessed February 2009. Audubon Alaska. 2009. Bathymetric contour lines. GIS feature class (based on AOOS 2009). Audubon Alaska. 2009. Benthic biomass. GIS raster dataset (based on Grebmeier et al. 2006; Shelf Basin Interaction 2008). Grebmeier, J.M., L.W. Cooper, H.M. Feder, and B.I. Sirenko. 2006. Ecosystem dynamics of the Pacific-influenced northern Bering and Chukchi seas in the Amerasian Arctic. Progress in Oceanography 71:331-361. Shelf Basin Interaction. 2008. Benthic samples. Microsoft Access database. <http://www.eol.ucar.edu/projects/sbi/all_data.shtml>. Accessed July 2008. Table E–1. Listing of maps, data sources, and data quality ratings as compiled from “The Arctic Marine Synthesis: Atlas of the Chukchi and Beaufort Seas” by Audubon Alaska in partnership with Oceana (Smith, 2010)—Continued Good: provides a complete geographic picture of the resource or species; data are consistent and of decent quality for mapping at the scale used (1:5,000,000); this rating does not indicate that fine-scale, project level data are available; Fair: provides a partial geographic picture of the resource or species; data are variable, some portions of the map are represented by reliable, high-quality data and data for other portions of the map are outdated, opinion-based, or missing data altogether; some key features, such as concentrations areas, may be missing. Poor: provides an incomplete geographic picture of the resource or species; information is missing, outdated, or deficient, but it is the best known data available (Smith, M.A., 2010, Arctic Marine Synthesis—Atlas of the Chukchi and Beaufort Seas: Audubon Alaska and Oceana, Anchorage)]
Appendix E 265

Appendix E

Map title

Data quality 

rating 

(Good, Fair, Poor)

Data sources for individual maps

Water Column and Benthic Life—ContinuedOpilio (Tanner or SnowCrab)

Poor AOOS. 2009. 1 km topographic/bathymetric map of Alaska. Raster dataset. <http://ak.aoos.org/aoos/tools.htm>. Accessed February 2009.

Audubon Alaska. 2009. Bathymetric contour lines. GIS feature class (based on AOOS 2009).Audubon Alaska. 2009. Opilio crab. GIS feature class (based on NOAA 1988; Paul and Paul 1997; NOAA and MMS 2008).NMFS (National Fisheries Management Service). 2005. Final environmental impact statement for essential fish habitat identification and 

conservation in Alaska. NOAA National Marine Fisheries Service, Alaska Region, Anchorage.

NOAA (National Oceanic and Atmospheric Administration) and MMS. 2008. Cruise report for the 2008 Beaufort Sea Survey, July 27–

August 30, 2008.

NOAA. 1988. Bering, Chukchi, and Beaufort seas coastal and ocean zones strategic assessment data atlas.Paul, J.M., and A.J. Paul. 1997. Reproductive biology and distribution of the snow crab from the northeastern Chukchi Sea. American 

Fisheries Society Symposium 19:287-294.

FishCapelin Poor AOOS. 2009. 1 km topographic/bathymetric map of Alaska. Raster dataset. <http://ak.aoos.org/aoos/tools.htm>. Accessed February 2009.

Audubon Alaska. 2009. Bathymetric contour lines. GIS feature class (based on AOOS 2009).Johnson, S. 2008. Capelin counts from beach seine surveys near Barrow, 2004–2008. Excel spreadsheet. NOAA, Juneau, Alaska.

NOAA. 1988. Bering, Chukchi, and Beaufort seas coastal and ocean zones strategic assessment data atlas.

Pacific Herring Poor AOOS. 2009. 1 km topographic/bathymetric map of Alaska. Raster dataset. <http://ak.aoos.org/aoos/tools.htm>. Accessed February 2009. 

Audubon Alaska. 2009. Bathymetric contour lines. GIS feature class (based on AOOS 2009).NOAA. 1988. Bering, Chukchi, and Beaufort seas coastal and ocean zones strategic assessment data atlas.

Saffron Cod Poor AOOS. 2009. 1 km topographic/bathymetric map of Alaska. Raster dataset. <http://ak.aoos.org/aoos/tools.htm>. Accessed February 2009.

Audubon Alaska. 2009. Saffron cod. GIS feature class (based on NOAA 1988; NOAA and MMS 2008; Wilson 2009)Geological Survey of Canada. In review. Environmental atlas of the Beaufort coastlands. <http:/gsc.nrcan.gc.ca/beaufort/fisheries_e.php>.

Accessed January 2010. 

NOAA (National Oceanic and Atmospheric Administration) and MMS. 2008. Cruise report for the 2008 Beaufort Sea Survey, July 27–

August 30, 2008

NOAA. 1988. Bering, Chukchi, and Beaufort seas coastal and ocean zones strategic assessment data atlas.NMFS (National Fisheries Management Service). 2005. Final environmental impact statement for essential fish habitat identification and 

conservation in Alaska. NOAA National Marine Fisheries Service, Alaska Region, Anchorage.

Wilson, Bill, NOAA. 2009. Personal communication with Melanie Smith, Audubon Alaska. 25 June.

Table E–1. Listing of maps, data sources, and data quality ratings as compiled from “The Arctic Marine Synthesis: Atlas of the Chukchi and Beaufort Seas” by AudubonAlaska in partnership with Oceana (Smith, 2010)—ContinuedGood: provides a complete geographic picture of the resource or species; data are consistent and of decent quality for mapping at the scale used (1:5,000,000); this rating does not indicate that fine-scale, project level data are available; Fair: provides a partial geographic picture of the resource or species; data are variable, some portions of the map are represented by reliable, high-quality data and data for 

other portions of the map are outdated, opinion-based, or missing data altogether; some key features, such as concentrations areas, may be missing. Poor: provides an incomplete geographic picture of the 

resource or species; information is missing, outdated, or deficient, but it is the best known data available (Smith, M.A., 2010, Arctic Marine Synthesis—Atlas of the Chukchi and Beaufort Seas: Audubon Alaska and Oceana, Anchorage)]
266 An Evaluation of the Science Needs to Inform Decisions on Outer Continental Shelf Energy Development in the Chukchi and Beaufort Seas, Alaska Map title Data quality rating (Good, Fair, Poor) Data sources for individual maps Fish—Continued Pink Salmon Poor ADFG. 2009. Anadramous waters catalog. GIS shapefile. AOOS. 2009. 1 km topographic/bathymetric map of Alaska. Raster dataset. <http://ak.aoos.org/aoos/tools.htm>. Accessed February 2009. Audubon Alaska. 2009. Bathymetric contour lines. GIS feature class (based on AOOS 2009). NOAA. 1988. Bering, Chukchi, and Beaufort seas coastal and ocean zones strategic assessment data atlas. Chum Salmon Poor ADFG. 2009. Anadramous waters catalog. GIS shapefile. AOOS. 2009. 1 km topographic/bathymetric map of Alaska. Raster dataset. <http://ak.aoos.org/aoos/tools.htm>. Accessed February 2009. Audubon Alaska. 2009. Bathymetric contour lines. GIS feature class (based on AOOS 2009). NOAA. 1988. Bering, Chukchi, and Beaufort seas coastal and ocean zones strategic assessment data atlas. Birds Yellow-Billed Loon Fair Audubon Alaska. 2009. Yellow-billed Loon. GIS feature class (based on USFWS 1992-2008; Schmutz 2002-09; Drew and Piatt 2003; Fair, 2009; Schmutz 2009). BirdLife International. 2009. Important Bird Areas. GIS feature class Drew, G.S., and J.F. Piatt. 2003. North Pacific pelagic seabird database, version 1.0. Alaska Science Center, USGS, Anchorage. Fair, J. 2009. Personal communication with M. Smith/Audubon Alaska. 18 December. Schmutz, J. 2009. Yellow-billed Loon satellite telemetry locations 2002-09. Alaska Science Center, USGS, Anchorage. Schmutz, J./USGS. 2009. Personal communication with M. Smith/Audubon Alaska. June. USFWS. 1992–2005. Density polygons (based on USFWS Eider breeding population survey and USFWS Arctic Coastal Plain aerial breeding pair survey). USFWS. 1992–2006. Eider breeding population survey. USFWS. 1992–2008. Arctic Coastal Plain aerial breeding pair survey. USFWS. 1998–2003. Arctic Coastal Plain molting sea duck survey. USFWS. 1999–2001. Beaufort Sea nearshore and offshore waterbird aerial survey. USFWS. 1999–2007. Common Eider survey. USFWS. 2003–2004. Arctic Coastal Plain Yellow-billed Loon survey. USFWS. 2005–2007. Western Alaska Yellow-billed Loon survey. USFWS. 2007. Yellow-billed Loon (Gavia adamsii) fact sheet. May. USFWS, Alaska Region, Anchorage. Table E–1. Listing of maps, data sources, and data quality ratings as compiled from “The Arctic Marine Synthesis: Atlas of the Chukchi and Beaufort Seas” by Audubon Alaska in partnership with Oceana (Smith, 2010)—Continued Good: provides a complete geographic picture of the resource or species; data are consistent and of decent quality for mapping at the scale used (1:5,000,000); this rating does not indicate that fine-scale, project level data are available; Fair: provides a partial geographic picture of the resource or species; data are variable, some portions of the map are represented by reliable, high-quality data and data for other portions of the map are outdated, opinion-based, or missing data altogether; some key features, such as concentrations areas, may be missing. Poor: provides an incomplete geographic picture of the resource or species; information is missing, outdated, or deficient, but it is the best known data available (Smith, M.A., 2010, Arctic Marine Synthesis—Atlas of the Chukchi and Beaufort Seas: Audubon Alaska and Oceana, Anchorage)]
Appendix E 267

Appendix E

Map title

Data quality 

rating 

(Good, Fair, Poor)

Data sources for individual maps

Birds—ContinuedRed-ThroatedLoon

Fair Audubon Alaska. 2009. Red-throated Loon. GIS feature class (based on Portenko 1981; Flint et al. 1984; USFWS 1992-2008; Barr et al. 

2000; Schmutz 2000-09; Drew and Piatt 2003; Ridgely et al. 2007; Schmutz 2009).

Barr, J.F., C. Eberl, and J.W. Mcintyre. 2000. Red-throated Loon (Gavia stellata). In The birds of North America Online. A. Poole, editor. 

Cornell Lab of Ornithology, Ithaca, New York. <http://bna.birds.cornell.edu/bna/species/513>. Accessed June 2009.

Drew, G.S., and J.F. Piatt. 2003. North Pacific pelagic seabird database, version 1.0. Alaska Science Center, USGS, Anchorage.Flint, V.E., R.L. Boehme, Y.V. Kostin, and A.A. Kuznetsov. 1984. A field guide to birds of the USSR. NJ: Princeton University Press, 

Princeton, New Jersey.

NOAA. 2002. Environmental sensitivity index, version 3.0. NOAA, Seattle, Washington.Portenko, L.A. 1981. Birds of the Chukchi Peninsula and Wrangel Island (translated from Russian). Published for the Smithsonian 

Institution and the National Science Foundation, Washington, D.C. Amerind, Springfield, Virginia.

Ridgely, R.S., T.F. Allnutt, T. Brooks, D.K. McNicol, D.W. Mehlman, B.E. Young, et al. 2007. Digital distribution maps of the birds of the 

Western Hemisphere, version 3.0. NatureServe, Arlington, Virginia.

Schmutz, J. 2009. Red-throated Loon satellite telemetry locations, 2002-09. Alaska Science Center, USGS, Anchorage.Schmutz, J./USGS. 2009. Personal communication with M. Smith/Audubon Alaska. June.USFWS. 1992–2005. Density polygons (based on USFWS Eider breeding population survey and USFWS Arctic Coastal Plain aerial 

breeding pair survey).

USFWS. 1992–2006. Eider breeding population survey.USFWS. 1992–2008. Arctic Coastal Plain aerial breeding pair survey.USFWS. 1998–2003. Arctic Coastal Plain molting sea duck survey.USFWS. 1999–2001. Beaufort Sea nearshore and offshore waterbird aerial survey.USFWS. 1999–2007. Common Eider survey.USFWS. 2003–2004. Arctic Coastal Plain Yellow-billed Loon survey.USFWS. 2005–2007. Western Alaska Yellow-billed Loon survey.

Table E–1. Listing of maps, data sources, and data quality ratings as compiled from “The Arctic Marine Synthesis: Atlas of the Chukchi and Beaufort Seas” by AudubonAlaska in partnership with Oceana (Smith, 2010)—ContinuedGood: provides a complete geographic picture of the resource or species; data are consistent and of decent quality for mapping at the scale used (1:5,000,000); this rating does not indicate that fine-scale, project level data are available; Fair: provides a partial geographic picture of the resource or species; data are variable, some portions of the map are represented by reliable, high-quality data and data for 

other portions of the map are outdated, opinion-based, or missing data altogether; some key features, such as concentrations areas, may be missing. Poor: provides an incomplete geographic picture of the 

resource or species; information is missing, outdated, or deficient, but it is the best known data available (Smith, M.A., 2010, Arctic Marine Synthesis—Atlas of the Chukchi and Beaufort Seas: Audubon Alaska and Oceana, Anchorage)]
268 An Evaluation of the Science Needs to Inform Decisions on Outer Continental Shelf Energy Development in the Chukchi and Beaufort Seas, Alaska Map title Data quality rating (Good, Fair, Poor) Data sources for individual maps Birds—Continued Spectacled Eider Fair Audubon Alaska. 2009. Important Bird Areas. GIS feature class. Audubon Alaska. 2009. Spectacled Eider. GIS feature class (based on USFWS 1992-2008; Larned et al. 1995; Larned and Tiplady 1997; Larned 1999; Petersen et al. 1999; Petersen et al. 2000; Drew and Piatt 2003; Petersen 2009). BirdLife International. 2009. Important Bird Areas. GIS feature class. Drew, G.S., and J.F. Piatt. 2003. North Pacific pelagic seabird database, version 1.0. Alaska Science Center, USGS, Anchorage. Larned, W.W. 1999. Ledyard Bay survey. August. USFWS, Anchorage, Alaska. Larned, W.W., and T. Tiplady. 1997. Late winter population and distribution of Spectacled Eiders (Somateria fischeri) in the Bering Sea, 1996–97. October. USFWS, Anchorage, Alaska. Larned, W.W., G.R. Balogh, and M.R. Petersen. 1995a. Distribution and abundance of Spectacled Eiders (Somateria fischeri) in Ledyard Bay, Alaska, September 1995. November. USFWS, Anchorage, Alaska. Larned, W.W., G.R. Balogh, and M.R. Petersen. 1995b. Late winter distribution of Spectacled Eiders (Somateria fischeri) in the Bering Sea, 1995. September. USFWS, Anchorage, Alaska. Larned, W.W., J.I. Hodges, and M.R. Petersen. 1995c. Distribution and abundance of Spectacled Eiders (Somateria fischeri) in Mechigmenskiya Bay, Chukotka, Russia, September 1995. November. USFWS, Anchorage, Alaska. Larned, W.W., M.R. Petersen, K. Laing, R. Platte, and J.L. Hodges. 1995d. Progress report: location and characteristics or Spectacled Eider molting and wintering areas, 1993-94. February. USFWS, Anchorage, Alaska. Petersen, M./USGS. 2009. Personal communication with M. Smith/Audubon Alaska. July. Petersen, M.R., J.B Grand, and C.P. Dau. 2000. Spectacled Eider (Somateria fischeri). In The birds of North America online. A. Poole, editor. Cornell Lab of Ornithology, Ithaca, New York. <http:/bna.birds.cornell.edu/bna/species/547/articles/introduction>. Accessed June 2009. Petersen, M.R., W.W. Larned, and D.C. Douglas. 1999. At-sea distribution of spectacled eiders: A 120-year-old mystery resolved. Auk 116:1009-1020. USFWS. 1992–2005. Density polygons (based on USFWS Eider breeding population survey and USFWS Arctic Coastal Plain aerial breeding pair survey) USFWS. 1992–2006. Eider breeding population survey. USFWS. 1992–2008. Arctic Coastal Plain aerial breeding pair survey. USFWS. 1999–2007. Common Eider survey. USFWS. 2008. Critical Habitat portal: Spectacled Eider Critical Habitat. GIS shapefile. <http://criticalhabitat.fws.gov/crithab/>. Accessed August 2008. Table E–1. Listing of maps, data sources, and data quality ratings as compiled from “The Arctic Marine Synthesis: Atlas of the Chukchi and Beaufort Seas” by Audubon Alaska in partnership with Oceana (Smith, 2010)—Continued Good: provides a complete geographic picture of the resource or species; data are consistent and of decent quality for mapping at the scale used (1:5,000,000); this rating does not indicate that fine-scale, project level data are available; Fair: provides a partial geographic picture of the resource or species; data are variable, some portions of the map are represented by reliable, high-quality data and data for other portions of the map are outdated, opinion-based, or missing data altogether; some key features, such as concentrations areas, may be missing. Poor: provides an incomplete geographic picture of the resource or species; information is missing, outdated, or deficient, but it is the best known data available (Smith, M.A., 2010, Arctic Marine Synthesis—Atlas of the Chukchi and Beaufort Seas: Audubon Alaska and Oceana, Anchorage)]
Appendix E 269

Appendix E

Map title

Data quality 

rating 

(Good, Fair, Poor)

Data sources for individual maps

Birds—ContinuedSteller’s Eider Fair Audubon Alaska. 2009. Steller’s Eider. GIS feature class (based on USFWS 1992-2008; Fredrickson 2001; Drew and Piatt 2003; Ridgely 

et al. 2007; Martin 2009).

BirdLife International. 2009. Important Bird Areas. GIS feature class.Drew, G.S., and J.F. Piatt. 2003. North Pacific pelagic seabird database, version 1.0. Alaska Science Center, USGS, Anchorage.Fredrickson, L.H. 2001. Steller’s Eider (Polysticta stelleri). In The Birds of North America online. A. Poole, editor. Cornell Lab of 

Ornithology, Ithaca, New York. <http://bna.birds.cornell.edu/bna/species/571>. Accessed February 2009.

Martin, P. 2009. Steller’s Eider satellite telemetry locations 2000-02. USFWS, Fairbanks, Alaska.Martin, P./USFWS. 2009. Personal communication with M. Smith/Audubon Alaska. June.Ridgely, R.S., T.F. Allnutt, T. Brooks, D.K. McNicol, D.W. Mehlman, B.E. Young, et al. 2007. Digital distribution maps of the birds of the 

Western Hemisphere, version 3.0. NatureServe, Arlington, Virginia.

USFWS. 1992–2006. Eider breeding population survey.USFWS. 1992–2008. Arctic Coastal Plain aerial breeding pair survey.USFWS. 1998–2003. Arctic Coastal Plain molting sea duck survey.USFWS. 1999–2007. Common Eider survey.

Table E–1. Listing of maps, data sources, and data quality ratings as compiled from “The Arctic Marine Synthesis: Atlas of the Chukchi and Beaufort Seas” by AudubonAlaska in partnership with Oceana (Smith, 2010)—ContinuedGood: provides a complete geographic picture of the resource or species; data are consistent and of decent quality for mapping at the scale used (1:5,000,000); this rating does not indicate that fine-scale, project level data are available; Fair: provides a partial geographic picture of the resource or species; data are variable, some portions of the map are represented by reliable, high-quality data and data for 

other portions of the map are outdated, opinion-based, or missing data altogether; some key features, such as concentrations areas, may be missing. Poor: provides an incomplete geographic picture of the 

resource or species; information is missing, outdated, or deficient, but it is the best known data available (Smith, M.A., 2010, Arctic Marine Synthesis—Atlas of the Chukchi and Beaufort Seas: Audubon Alaska and Oceana, Anchorage)]
270 An Evaluation of the Science Needs to Inform Decisions on Outer Continental Shelf Energy Development in the Chukchi and Beaufort Seas, Alaska Map title Data quality rating (Good, Fair, Poor) Data sources for individual maps Birds—Continued King Eider Fair Audubon Alaska. 2009. King Eider. GIS feature class (based on NOAA 1988; USFWS 1992-2008; Larned et al. 1995; Dickson et al. 1997; Larned 1999; Dickson and Gilchrist 2002; Drew and Piatt 2003; Ridgely et al. 2007; Oppel 2008; Oppel 2009; Oppel et al. 2009). Audubon Alaska. 2009. Important Bird Areas. GIS feature class. Dickson, D.L., and H.G. Gilchrist. 2002. Status of marine birds of the southeastern Beaufort Sea. Arctic 55, Supplement 1:46-58. Dickson, D.L., R.C. Cotter, J.E. Hines, and M.F. Kay. 1997. Distribution and abundance of King Eiders in the western Canadian Arctic. In Occasional paper number 94. D.L. Dickson, editor. Canadian Wildlife Service, Edmonton, Alberta. Drew, G.S., and J.F. Piatt. 2003. North Pacific pelagic seabird database, version 1.0. Alaska Science Center, USGS, Anchorage. Larned, W.W. 1999. Ledyard Bay survey. August. USFWS, Anchorage, Alaska. Larned, W.W., G.R. Balogh, and M.R. Petersen. 1995a. Distribution and abundance of Spectacled Eiders (Somateria fischeri) in Ledyard Bay, Alaska, September 1995. November. USFWS, Anchorage, Alaska. Larned, W.W., G.R. Balogh, and M.R. Petersen. 1995b. Late winter distribution of Spectacled Eiders (Somateria fischeri) in the Bering Sea, 1995. September. USFWS, Anchorage, Alaska. Larned, W.W., M.R. Petersen, K. Laing, R. Platte, and J.L. Hodges. 1995d. Progress report: location and characteristics or Spectacled Eider molting and wintering areas, 1993-94. February. USFWS, Anchorage, Alaska. NOAA. 1988. Bering, Chukchi, and Beaufort seas coastal and ocean zones strategic assessment data atlas. Oppel, S. 2008. King Eider migration and seasonal interactions at the individual level. Dissertation, University of Alaska Fairbanks, Fairbanks, Alaska. Oppel, S./University of Alaska Fairbanks. 2009. Personal communication with M. Smith/Audubon Alaska. September. Ridgely, R.S., T.F. Allnutt, T. Brooks, D.K. McNicol, D.W. Mehlman, B.E. Young, et al. 2007. Digital distribution maps of the birds of the Western Hemisphere, version 3.0. NatureServe, Arlington, Virginia. USFWS. 1992–2005. Density polygons (based on USFWS Eider breeding population survey and USFWS Arctic Coastal Plain aerial breeding pair survey). USFWS. 1992–2006. Eider breeding population survey. USFWS. 1992–2008. Arctic Coastal Plain aerial breeding pair survey. USFWS. 1998–2003. Arctic Coastal Plain molting sea duck survey. USFWS. 1999–2001. Beaufort Sea nearshore and offshore waterbird aerial survey. USFWS. 1999–2007. Common Eider survey. Table E–1. Listing of maps, data sources, and data quality ratings as compiled from “The Arctic Marine Synthesis: Atlas of the Chukchi and Beaufort Seas” by Audubon Alaska in partnership with Oceana (Smith, 2010)—Continued Good: provides a complete geographic picture of the resource or species; data are consistent and of decent quality for mapping at the scale used (1:5,000,000); this rating does not indicate that fine-scale, project level data are available; Fair: provides a partial geographic picture of the resource or species; data are variable, some portions of the map are represented by reliable, high-quality data and data for other portions of the map are outdated, opinion-based, or missing data altogether; some key features, such as concentrations areas, may be missing. Poor: provides an incomplete geographic picture of the resource or species; information is missing, outdated, or deficient, but it is the best known data available (Smith, M.A., 2010, Arctic Marine Synthesis—Atlas of the Chukchi and Beaufort Seas: Audubon Alaska and Oceana, Anchorage)]
Appendix E 271

Appendix E

Map title

Data quality 

rating 

(Good, Fair, Poor)

Data sources for individual maps

Birds—ContinuedCommon Eider Fair Audubon Alaska. 2009. Common Eider. GIS feature class (based on Drew and Piatt 2003; USFWS 1992–2008; NOAA 1988; Kendall 

2005).

Audubon Alaska. 2009. Important Bird Areas. GIS feature class.Drew, G.S., and J.F. Piatt. 2003. North Pacific pelagic seabird database, version 1.0. Alaska Science Center, USGS, Anchorage.Kendall, S.J. 2005. Surveys of breeding birds on barrier islands in the Arctic National Wildlife Refuge, 2003–2004. USFWS, Arctic 

National Wildlife Refuge, Fairbanks, Alaska.

Larned, W.W., M.R. Petersen, K. Laing, R. Platte, and J.L. Hodges. 1995d. Progress report: location and characteristics or Spectacled 

Eider molting and wintering areas, 1993-94. February. USFWS, Anchorage, Alaska.

NOAA. 1988. Bering, Chukchi, and Beaufort seas coastal and ocean zones strategic assessment data atlas.USFWS. 1992–2008. Arctic Coastal Plain aerial breeding pair survey.USFWS. 1998–2003. Arctic Coastal Plain molting sea duck survey.USFWS. 1999–2001. Beaufort Sea nearshore and offshore waterbird aerial survey.USFWS. 1999–2007. Common Eider survey.USFWS. 2005–2007. Western Alaska Yellow-billed Loon survey.USFWS. 2008. Beringian seabird colony catalog. Microsoft Excel spreadsheet.

Long-Tailed Duck Fair Alexander, S.A., D.L. Dickson, and S.E. Westover. 1997. Spring migration of eiders and other waterbirds in offshore areas of the western 

Arctic. In King and Common eiders of the western Canadian Arctic. D.L. Dickson, editor. Occasional Paper Number 94. Canadian Wildlife Service, Edmonton, Alberta.

Audubon Alaska. 2009. Important Bird Areas. GIS feature class.BirdLife International. 2009. Important Bird Areas. GIS feature class.NOAA. 1988. Bering, Chukchi, and Beaufort seas coastal and ocean zones strategic assessment data atlas.NOAA. 2002. Environmental sensitivity index, version 3.0. NOAA, Seattle, Washington.Portenko, L.A. 1981. Birds of the Chukchi Peninsula and Wrangel Island (translated from Russian). Published for the Smithsonian 

Institution and the National Science Foundation, Washington, D.C. Amerind, Springfield, Virginia.

USFWS. 1992–2005. Density polygons (based on USFWS Eider breeding population survey and USFWS Arctic Coastal Plain aerial 

breeding pair survey).

USFWS. 1992–2006. Eider breeding population survey.USFWS. 1992–2008. Arctic Coastal Plain aerial breeding pair survey.

Table E–1. Listing of maps, data sources, and data quality ratings as compiled from “The Arctic Marine Synthesis: Atlas of the Chukchi and Beaufort Seas” by AudubonAlaska in partnership with Oceana (Smith, 2010)—ContinuedGood: provides a complete geographic picture of the resource or species; data are consistent and of decent quality for mapping at the scale used (1:5,000,000); this rating does not indicate that fine-scale, project level data are available; Fair: provides a partial geographic picture of the resource or species; data are variable, some portions of the map are represented by reliable, high-quality data and data for 

other portions of the map are outdated, opinion-based, or missing data altogether; some key features, such as concentrations areas, may be missing. Poor: provides an incomplete geographic picture of the 

resource or species; information is missing, outdated, or deficient, but it is the best known data available (Smith, M.A., 2010, Arctic Marine Synthesis—Atlas of the Chukchi and Beaufort Seas: Audubon Alaska and Oceana, Anchorage)]
272 An Evaluation of the Science Needs to Inform Decisions on Outer Continental Shelf Energy Development in the Chukchi and Beaufort Seas, Alaska Map title Data quality rating (Good, Fair, Poor) Data sources for individual maps Birds—Continued Ivory Gull Poor Audubon Alaska. 2009. Ivory Gull. GIS feature class (based on Portenko 1981; Benter 2009). Benter, B./USFWS. 2009. Personal communication with M. Smith/Audubon Alaska. 21 August. Drew, G.S., and J.F. Piatt. 2003. North Pacific pelagic seabird database, version 1.0. Alaska Science Center, USGS, Anchorage. Mallory, M.L., I.J. Stenhouse, G. Gilchrist, G. Robertson, J.C. Haney, and S.D. Macdonald. 2008. Ivory Gull (Pagophila eburnea). In The birds of North America Online. A. Poole, editor. Cornell Lab of Ornithology, Ithaca, New York. <http://bna.birds.cornell.edu/bna/ species/175>. Accessed June 2009. Portenko, L.A. 1981. Birds of the Chukchi Peninsula and Wrangel Island (translated from Russian). Published for the Smithsonian Institution and the National Science Foundation, Washington, D.C. Amerind, Springfield, Virginia. Kittlitz’s Murrelet Poor Arctic Ocean Diversity. 2009. Kittlitz’s Murrelet known nest locations in Alaska (based on Day et al. 1999). <http://www.arcodiv.org/ Database/Birds_datasets.html>. Accessed June 2009. Audubon Alaska. 2009. Important Bird Areas. GIS feature class. Day, R.H., K.J. Kuletz, and D.A. Nigro. 1999. Kittlitz’s Murrelet (Brachyramphus brevirostris). In The birds of North America online. A. Poole, editor. Cornell Lab of Ornithology, Ithaca, New York.<http://bns.birds.cornell.edu/bna/species/435>. Accessed January 2010. Drew, G.S., and J.F. Piatt. 2003. North Pacific pelagic seabird database, version 1.0. Alaska Science Center, USGS, Anchorage. Ridgely, R.S., T.F. Allnutt, T. Brooks, D.K. McNicol, D.W. Mehlman, B.E. Young, et al. 2007. Digital distribution maps of the birds of the Western Hemisphere, version 3.0. NatureServe, Arlington, Virginia. USFWS. 2009. Kittlitz’s Murrelet nesting areas. USFWS, Anchorage Field Office. Northern Fulmar Fair Drew, G.S., and J.F. Piatt. 2003. North Pacific pelagic seabird database, version 1.0. Alaska Science Center, USGS, Anchorage. NOAA. 1988. Bering, Chukchi, and Beaufort seas coastal and ocean zones strategic assessment data atlas. USFWS. 2008. Beringian seabird colony catalog. Microsoft Excel spreadsheet. Short-Tailed Shearwater Fair Drew, G.S., and J.F. Piatt. 2003. North Pacific pelagic seabird database, version 1.0. Alaska Science Center, USGS, Anchorage. Larned, W.W. 1999. Ledyard Bay survey. August. USFWS, Anchorage, Alaska. NOAA. 1988. Bering, Chukchi, and Beaufort seas coastal and ocean zones strategic assessment data atlas. Seabird Colonies Fair USFWS. 2008. Beringian seabird colony catalog. Microsoft Excel spreadsheet. Important Bird Areas Fair Audubon Alaska. 2009. Important Bird Areas. GIS feature class. BirdLife International. 2009. Important Bird Areas. GIS feature class. Bird Studies Canada and Canadian Nature Federation. 2004. Important Bird Areas of Canada database. Bird Studies Canada, Port Rowan, Ontario. Table E–1. Listing of maps, data sources, and data quality ratings as compiled from “The Arctic Marine Synthesis: Atlas of the Chukchi and Beaufort Seas” by Audubon Alaska in partnership with Oceana (Smith, 2010)—Continued Good: provides a complete geographic picture of the resource or species; data are consistent and of decent quality for mapping at the scale used (1:5,000,000); this rating does not indicate that fine-scale, project level data are available; Fair: provides a partial geographic picture of the resource or species; data are variable, some portions of the map are represented by reliable, high-quality data and data for other portions of the map are outdated, opinion-based, or missing data altogether; some key features, such as concentrations areas, may be missing. Poor: provides an incomplete geographic picture of the resource or species; information is missing, outdated, or deficient, but it is the best known data available (Smith, M.A., 2010, Arctic Marine Synthesis—Atlas of the Chukchi and Beaufort Seas: Audubon Alaska and Oceana, Anchorage)]
Appendix E 273

Appendix E

Map title

Data quality 

rating 

(Good, Fair, Poor)

Data sources for individual maps

MammalsPolar Bear Fair ADFG. 1997. Most Environmentally Sensitive Area (MESA) Data. GIS shapefiles. Habitat and Restoration Division.

Amstrup, S.C., G.M. Durner, I. Stirling, and T.L. McDonald. 2005. Allocating harvests among polar bear stocks in the Beaufort Sea. Arctic 

58:247-259.

Kalxdorff, S. 1997. Collection of local knowledge regarding polar bear habitat use in Alaska. Technical report MMM 97-2. USFWS, 

Marine Mammal Management, Anchorage, Alaska.

Kochnev, A.A., V.M. Etylin, V.I. Kavry, E.B. Siv-Siv, and I.V. Tanko. 2003. Traditional knowledge of Chukotka Native peoples regarding 

polar bear habitat use. Prepared for U.S. National Park Service by The Chukotka Association of Traditional Marine Mammal Hunters, The Alaska Nanuuq Commission, The Pacific Fisheries Research Center (Chukotka Branch). 

McDonald, L.L., and D.G. Robertson. 2000. Polar bear maternity den surveys in the Russian Arctic: development of protocols and 

standard operating procedures. Western EcoSystem Technologies, Cheyenne, Wyoming.

MMS. 2008. Bowhead whale aerial survey program. Microsoft Access database.NOAA. 1988. Bering, Chukchi, and Beaufort seas coastal and ocean zones strategic assessment data atlas.NOAA. 2002. Environmental sensitivity index, version 3.0. NOAA, Seattle, Washington.North Slope Science Initiative. 2008. Polar bear locations. GIS shapefile. <http://www.gina.alaska.edu/projects/nssi-catalog>. Accessed 

October 2008.

Stishov, M.S. 1991. Results of aerial counts of the polar bear dens on the Arctic coasts of the extreme Northeast Asia. In Polar bears: 

proceedings of the tenth working meeting of the IUCN/SSC Polar Bear Specialist Group. S.C. Amstrup and O. Wiig, editors. October 25-29. Sochi, USSR.

USFWS. 2009. Polar bear proposed critical habitat. GIS shapefiles.USFWS (U.S. Fish and Wildlife Service) and MMS. 1994. Conservation plan for the polar bear in Alaska. June. USFWS, Anchorage, 

Alaska.

USGS (U.S. Geological Survey). 2002. Confirmed polar bear den locations, 1919-2002. GIS shapefile. Biological Resources Division.

Table E–1. Listing of maps, data sources, and data quality ratings as compiled from “The Arctic Marine Synthesis: Atlas of the Chukchi and Beaufort Seas” by AudubonAlaska in partnership with Oceana (Smith, 2010)—ContinuedGood: provides a complete geographic picture of the resource or species; data are consistent and of decent quality for mapping at the scale used (1:5,000,000); this rating does not indicate that fine-scale, project level data are available; Fair: provides a partial geographic picture of the resource or species; data are variable, some portions of the map are represented by reliable, high-quality data and data for 

other portions of the map are outdated, opinion-based, or missing data altogether; some key features, such as concentrations areas, may be missing. Poor: provides an incomplete geographic picture of the 

resource or species; information is missing, outdated, or deficient, but it is the best known data available (Smith, M.A., 2010, Arctic Marine Synthesis—Atlas of the Chukchi and Beaufort Seas: Audubon Alaska and Oceana, Anchorage)]
274 An Evaluation of the Science Needs to Inform Decisions on Outer Continental Shelf Energy Development in the Chukchi and Beaufort Seas, Alaska Map title Data quality rating (Good, Fair, Poor) Data sources for individual maps Mammals—Continued Arctic Fox Poor Audubon Alaska. 2009. Arctic fox. GIS feature class (based on Pelletier 2000; Nowacki et al. 2001; Patterson et al. 2007; Pamperin 2008; Northwest Territories Environment and Natural Resources Wildlife Division 2009; IUCN 2009). IUCN (International Union for Conservation of Nature). 2009. Arctic fox (Alopex lagopus) range map. Species Survival Commission Canid Specialist Group.<http://www.canids.org/species/Alopex_lagopus.htm>. Accessed June 2009. Northwest Territories Environment and Natural Resources Wildlife Division. 2009. Arctic fox distribution. Digital map. <http://www. nwtwildlife.com/NWTwildlife/foxes/arcticfox/distribution.htm>. Accessed June 2009. Nowacki, G., P. Spencer, T. Brock, M. Fleming, and T. Jorgenson. 2001. Ecoregions of Alaska. GIS shapefile. USGS, Reston, Virginia. Pamperin, N.J. 2008. Winter movements of Arctic foxes in northern Alaska measured by satellite telemetry. University of Alaska Fairbanks. Patterson, B.D., G. Ceballos, W. Sechrest, M.F. Tognelli, T. Brooks, L. Luna, et al. 2007. Digital distribution maps of the mammals of the Western Hemisphere, version 3.0. NatureServe, Arlington, Virginia. Pelletier, B.R. 2000. Environmental atlas of the Beaufort coastlands. Geological Survey of Canada. <http://gsc.nrcan.gc.ca/beaufort index_ ephp>. Accessed June 2009. Pacific Walrus Fair ADFG (Alaska Department of Fish and Game). 1986. Alaska habitat management guide. Division of Habitat, Juneau, Alaska. AOOS. 2009. 1 km topographic/bathymetric map of Alaska. Raster dataset. <http://ak.aoos.org/aoos/tools.htm>. Accessed February 2009. Audubon Alaska. 2009. Bathymetric contour lines. GIS feature class (based on AOOS 2009). Audubon Alaska. 2009. Chukchi Sea shoals. GIS feature class (based on AOOS 2009). Audubon Alaska. 2009. Pacific walrus. GIS feature class (based on NOAA 1988; MMS 2008). MMS. 2008. Bowhead whale aerial survey program. Microsoft Access database. NOAA. 1988. Bering, Chukchi, and Beaufort seas coastal and ocean zones strategic assessment data atlas. Robards, M., A. Kochnev, and S. Deming. 2007. Sharing knowledge about Pacific walrus. Published map. Ribbon Seal Fair AOOS. 2009. 1 km topographic/bathymetric map of Alaska. Raster dataset. <http://ak.aoos.org/aoos/tools.htm>. Accessed February 2009. Angliss, R.P., and R.B. Outlaw. 2008. Alaska marine mammal stock assessments, 2007. U.S. Department of Commerce. Report Technical Memo NMFS-AFSC-180. Audubon Alaska. 2009. Bathymetric contour lines. GIS feature class (based on AOOS 2009). Boveng, P.L., J.L. Bengtson, T.W. Buckley, M.F. Cameron, S.P. Dahle, B.A. Megrey, J.E. Overland, and N.J. Williamson. 2008. Status review of the ribbon seal (Histriophoca fasciata). U.S. Department of Commerce, NOAA. NOAA. 1988. Bering, Chukchi, and Beaufort seas coastal and ocean zones strategic assessment data atlas. Table E–1. Listing of maps, data sources, and data quality ratings as compiled from “The Arctic Marine Synthesis: Atlas of the Chukchi and Beaufort Seas” by Audubon Alaska in partnership with Oceana (Smith, 2010)—Continued Good: provides a complete geographic picture of the resource or species; data are consistent and of decent quality for mapping at the scale used (1:5,000,000); this rating does not indicate that fine-scale, project level data are available; Fair: provides a partial geographic picture of the resource or species; data are variable, some portions of the map are represented by reliable, high-quality data and data for other portions of the map are outdated, opinion-based, or missing data altogether; some key features, such as concentrations areas, may be missing. Poor: provides an incomplete geographic picture of the resource or species; information is missing, outdated, or deficient, but it is the best known data available (Smith, M.A., 2010, Arctic Marine Synthesis—Atlas of the Chukchi and Beaufort Seas: Audubon Alaska and Oceana, Anchorage)]
Appendix E 275

Appendix E

Map title

Data quality 

rating 

(Good, Fair, Poor)

Data sources for individual maps

Mammals—ContinuedSpotted Seal Fair ADFG. 1997. Most Environmentally Sensitive Area (MESA) Data. GIS shapefiles. Habitat and Restoration Division.

AOOS. 2009. 1 km topographic/bathymetric map of Alaska. Raster dataset. <http://ak.aoos.org/aoos/tools.htm>. Accessed February 2009.Angliss, R.P., and R.B. Outlaw. 2008. Alaska marine mammal stock assessments, 2007. U.S. Department of Commerce. Report Technical 

Memo NMFS-AFSC-180.

Audubon Alaska. 2009. Bathymetric contour lines. GIS feature class (based on AOOS 2009).Audubon Alaska. 2009. Spotted seal. GIS feature class (based on NOAA 1988; ADFG 1997; Rugh et al. 1997; Lowry et al. 1998; 

Eningowuk 2002; NOAA 2002; Oceana 2008).

Eningowuk, J. 2002. Spotted seal (based on local and traditional knowledge).Lowry, L.F., K.J. Frost, R. Davis, D.P. DeMaster, and R.S. Suydam. 1998. Movements and behavior of satellite-tagged spotted seals 

(Phoca largha) in the Bering and Chukchi seas. Polar Biology 19:221-230.

NOAA. 1988. Bering, Chukchi, and Beaufort seas coastal and ocean zones strategic assessment data atlas.NOAA. 2002. Environmental sensitivity index, version 3.0. NOAA, Seattle, Washington.Oceana. 2008. Spotted seal. GIS feature class (based on local and traditional knowledge).Rugh, D.J., K.E.W. Shelden, and D.E. Withrow. 1997. Spotted seals, Phoca largha, in Alaska. Marine Fisheries Review 59:1-18.

Ringed Seal Fair ADFG (Alaska Department of Fish and Game). 1986. Alaska habitat management guide. Division of Habitat, Juneau, Alaska.

Angliss, R.P., and R.B. Outlaw. 2008. Alaska marine mammal stock assessments, 2007. U.S. Department of Commerce. Report Technical 

Memo NMFS-AFSC-180.

AOOS. 2009. 1 km topographic/bathymetric map of Alaska. Raster dataset. <http://ak.aoos.org/aoos/tools.htm>. Accessed February 2009.Audubon Alaska. 2009. Bathymetric contour lines. GIS feature class (based on AOOS 2009).Audubon Alaska. 2009. Ringed seal. GIS feature class (based on NOAA 1988; Harwood and Stirling 1992; MMS 2008).Bengtson, J.L., L.M. Hiruki-Raring, M.A. Simpkins, and P.L. Boveng. 2005. Ringed and bearded seal densities in the eastern Chukchi Sea, 

1999–2000. Polar Biology 28:833-845.

Frost, K./Retired biologist. 2010. Personal communication with M. Smith/Audubon Alaska. 3 January.Harwood, L.A., and I. Stirling. 1992. Distribution of ringed seals in the southeastern Beaufort Sea during late summer. Canadian Journal of 

Zoology 70:891-900.

MMS. 2008. Bowhead whale aerial survey program. Microsoft Access database.NOAA. 1988. Bering, Chukchi, and Beaufort seas coastal and ocean zones strategic assessment data atlas.NOAA. 2002. Environmental sensitivity index, version 3.0. NOAA, Seattle, Washington.

Table E–1. Listing of maps, data sources, and data quality ratings as compiled from “The Arctic Marine Synthesis: Atlas of the Chukchi and Beaufort Seas” by AudubonAlaska in partnership with Oceana (Smith, 2010)—ContinuedGood: provides a complete geographic picture of the resource or species; data are consistent and of decent quality for mapping at the scale used (1:5,000,000); this rating does not indicate that fine-scale, project level data are available; Fair: provides a partial geographic picture of the resource or species; data are variable, some portions of the map are represented by reliable, high-quality data and data for 

other portions of the map are outdated, opinion-based, or missing data altogether; some key features, such as concentrations areas, may be missing. Poor: provides an incomplete geographic picture of the 

resource or species; information is missing, outdated, or deficient, but it is the best known data available (Smith, M.A., 2010, Arctic Marine Synthesis—Atlas of the Chukchi and Beaufort Seas: Audubon Alaska and Oceana, Anchorage)]
276 An Evaluation of the Science Needs to Inform Decisions on Outer Continental Shelf Energy Development in the Chukchi and Beaufort Seas, Alaska Map title Data quality rating (Good, Fair, Poor) Data sources for individual maps Mammals—Continued Bearded Seal Fair Angliss, R.P., and R.B. Outlaw. 2008. Alaska marine mammal stock assessments, 2007. U.S. Department of Commerce. Report Technical Memo NMFS-AFSC-180. AOOS. 2009. 1 km topographic/bathymetric map of Alaska. Raster dataset. <http://ak.aoos.org/aoos/tools.htm>. Accessed February 2009. Audubon Alaska. 2009. Bathymetric contour lines. GIS feature class (based on AOOS 2009). Audubon Alaska. 2009. Bearded Seal. GIS feature class (based on NOAA 1988; Bengtson et al. 2005; Angliss and Outlaw 2008; MMS 2008; Boveng 2009). Audubon Alaska. 2009. Chukchi Sea shoals. GIS feature class (based on AOOS 2009). Bengtson, J.L., L.M. Hiruki-Raring, M.A. Simpkins, and P.L. Boveng. 2005. Ringed and bearded seal densities in the eastern Chukchi Sea, 1999–2000. Polar Biology 28:833-845. Boveng, P./NOAA Alaska Fisheries Science Center. 2009. Personal communication with M. Smith/Audubon Alaska. June. Frost, K./Retired biologist. 2010. Personal communication with M. Smith/Audubon Alaska. 3 January. MMS. 2008. Bowhead whale aerial survey program. Microsoft Access database. NOAA. 1988. Bering, Chukchi, and Beaufort seas coastal and ocean zones strategic assessment data atlas. NOAA. 2002. Environmental sensitivity index, version 3.0. NOAA, Seattle, Washington. Bowhead Whale Fair ADFG. 2009. Summary maps of fall movements of bowhead whales in the Chukchi Sea. <http://www.adfg.alaska.gov/static/home/about/ management/wildlife/management/marinemammals/pdfs/bow_move_chukchi_sea.pdf>. Accessed February 2009. Audubon Alaska. 2009. Bowhead whale. GIS feature class (based on North Slope Borough 2003; ADFG 2009; Quakenbush 2009). Moore, S.E., and K.L. Laidre. 2006. Trends in sea ice cover within habitats used by bowhead whales in the Western Arctic. Ecological Applications 16(3):932-944. NOAA. 1988. Bering, Chukchi, and Beaufort seas coastal and ocean zones strategic assessment data atlas. NOAA. 2002. Environmental sensitivity index, version 3.0. NOAA, Seattle, Washington. Noongwook, G., H.P. Huntington, and J.C. George. 2007. Traditional knowledge of the bowhead whale (Balaena mysticetus) around St. Lawrence Island, Alaska. Arctic 60:47-54. North Slope Borough. 2003. Bowhead whale subsistence sensitivity. (The map incorporates data from Moore and Reeves 1993 and Richardson 1999.) In Barrow, Alaska: North Slope Borough. Department of Planning and Community Services, Geographic Information Systems Division. Oceana. 2008. Bowhead whale. GIS feature class (based on local and traditional knowledge). Quakenbush, L./ADFG. 2009. Personal communication with M. Smith/Audubon Alaska. February. Table E–1. Listing of maps, data sources, and data quality ratings as compiled from “The Arctic Marine Synthesis: Atlas of the Chukchi and Beaufort Seas” by Audubon Alaska in partnership with Oceana (Smith, 2010)—Continued Good: provides a complete geographic picture of the resource or species; data are consistent and of decent quality for mapping at the scale used (1:5,000,000); this rating does not indicate that fine-scale, project level data are available; Fair: provides a partial geographic picture of the resource or species; data are variable, some portions of the map are represented by reliable, high-quality data and data for other portions of the map are outdated, opinion-based, or missing data altogether; some key features, such as concentrations areas, may be missing. Poor: provides an incomplete geographic picture of the resource or species; information is missing, outdated, or deficient, but it is the best known data available (Smith, M.A., 2010, Arctic Marine Synthesis—Atlas of the Chukchi and Beaufort Seas: Audubon Alaska and Oceana, Anchorage)]
Appendix E 277

Appendix E

Map title

Data quality 

rating 

(Good, Fair, Poor)

Data sources for individual maps

Mammals—ContinuedBeluga Whale Fair ADFG. 1997. Most Environmentally Sensitive Area (MESA) Data. GIS shapefiles. Habitat and Restoration Division.

Angliss, R.P., and R.B. Outlaw. 2008. Alaska marine mammal stock assessments, 2007. U.S. Department of Commerce. Report Technical 

Memo NMFS-AFSC-180.

Huntington, H. P., and the communities of Buckland, Koyuk, Point Lay, and Shaktoolik. 1999. Traditional knowledge of the ecology of 

beluga whales (Delphinapterus leucas) in the eastern Chukchi and northern Bering seas, Alaska. Arctic 52:49-61.

NOAA. 1988. Bering, Chukchi, and Beaufort seas coastal and ocean zones strategic assessment data atlas.NOAA. 2002. Environmental sensitivity index, version 3.0. NOAA, Seattle, Washington.Suydam, R., and ADFG. 2004. Bowhead whale feeding areas. In North Slope Borough. 2006. North Slope Borough Area Wide 

Comprehensive Plan. Barrow, Alaska.

Gray Whale Fair Angliss, R.P., and R.B. Outlaw. 2008. Alaska marine mammal stock assessments, 2007. U.S. Department of Commerce. Report Technical 

Memo NMFS-AFSC-180.

Audubon Alaska. 2009. Gray whale. GIS feature class (based on NOAA 1988; MMS 2008).MMS. 2008. Bowhead whale aerial survey program. Microsoft Access database.NOAA. 1988. Bering, Chukchi, and Beaufort seas coastal and ocean zones strategic assessment data atlas.

PeopleEnergyDevelopment andProtected Areas

Good Alaska Center for the Environment. 2009. Oil and gas infrastructure. GIS geodatabase.

Alaska Department of Natural Resources. 2008. Surface holes. GIS shapefile.Alaska Department of Natural Resources. 2009. Oil and gas leases. GIS shapefile.Alaska Oil and Gas Conservation Commission. 2009. Oil and gas wells. GIS shapefile.Alaska State Geospatial Data Clearinghouse. 2008. Base data. GIS shapefiles. <http://www.asgdc.state.ak.us/>. Accessed June 2008.

Audubon Alaska. 2009. MMS program areas, 2010–2015. GIS feature class (based on MMS 2009).BLM. 2008. Oil and gas infrastructure. GIS shapefiles.ESRI. 2009. StreetMap premium: North America. GIS feature class.MMS. 2009. Draft proposed Outer Continental Shelf (OCS) oil and gas leasing program, 2010–2015. January.World Wildlife Fund. 2009. Arctic-wide human infrastructure. GIS geodatabase.World Wildlife Fund. 2010. Protected areas in eastern Russia. GIS shapefile.

Human Impact Good Alaska Department of Natural Resources. 2008. Surface holes. GIS shapefile.

Halpern, B., S. Walbridge, K. Selkoe, C. Kappel, F. Micheli, C. D’Agrosa, et al. 2008. A global map of human impact on marine 

ecosystems. Science 319:948-952.

Table E–1. Listing of maps, data sources, and data quality ratings as compiled from “The Arctic Marine Synthesis: Atlas of the Chukchi and Beaufort Seas” by AudubonAlaska in partnership with Oceana (Smith, 2010)—ContinuedGood: provides a complete geographic picture of the resource or species; data are consistent and of decent quality for mapping at the scale used (1:5,000,000); this rating does not indicate that fine-scale, project level data are available; Fair: provides a partial geographic picture of the resource or species; data are variable, some portions of the map are represented by reliable, high-quality data and data for 

other portions of the map are outdated, opinion-based, or missing data altogether; some key features, such as concentrations areas, may be missing. Poor: provides an incomplete geographic picture of the 

resource or species; information is missing, outdated, or deficient, but it is the best known data available (Smith, M.A., 2010, Arctic Marine Synthesis—Atlas of the Chukchi and Beaufort Seas: Audubon Alaska and Oceana, Anchorage)]
278 An Evaluation of the Science Needs to Inform Decisions on Outer Continental Shelf Energy Development in the Chukchi and Beaufort Seas, Alaska Map title Data quality rating (Good, Fair, Poor) Data sources for individual maps People—Continued Predicted Climate Change Fair Audubon Alaska. 2009. Predicted climate change: increase in air temperature at surface, mean for June - August, 2000–2009 versus 2090 2099. GIS raster dataset (based on NCAR 2009; SNAP 2009). NCAR (National Center for Atmospheric Research). 2009. Global CCSM data: Scenario A1B –ensemble average for air temperature at surface. GIS shapefile. Geographic Information Systems (GIS) Initiative. <http://www.gisclimatechange.org/CCSMDownloadWizard. htm>.Accessed March 2009. SNAP (Scenarios Network for Alaska Planning). 2009. A1B GCM dataset: air temperature – 5-model composite. GIS raster dataset. <http://www.snap.uaf.edu/downloads/alaska-climate-datasets>. Accessed March 2009. Table E–1. Listing of maps, data sources, and data quality ratings as compiled from “The Arctic Marine Synthesis: Atlas of the Chukchi and Beaufort Seas” by Audubon Alaska in partnership with Oceana (Smith, 2010)—Continued Good: provides a complete geographic picture of the resource or species; data are consistent and of decent quality for mapping at the scale used (1:5,000,000); this rating does not indicate that fine-scale, project level data are available; Fair: provides a partial geographic picture of the resource or species; data are variable, some portions of the map are represented by reliable, high-quality data and data for other portions of the map are outdated, opinion-based, or missing data altogether; some key features, such as concentrations areas, may be missing. Poor: provides an incomplete geographic picture of the resource or species; information is missing, outdated, or deficient, but it is the best known data available (Smith, M.A., 2010, Arctic Marine Synthesis—Atlas of the Chukchi and Beaufort Seas: Audubon Alaska and Oceana, Anchorage)]
For more information, contact:

Energy Resources Program Coordinator

U.S. Geological Survey, MS 915A

Reston, VA 20192

Regional Executive, Alaska

U.S. Geological Survey

4210 University Drive

Anchorage, AK 99508
Holland-Bartels and Pierce— An Evaluation of the Science Needs to Inform Decisions on Outer Continental Shelf Energy Development in the Chukchi and Beaufort Seas, Alaska—Circular 1370