S. HRG. 110–1236 

EXAMINING THREATS AND PROTECTIONS FOR 

THE POLAR BEAR 

HEARING 

BEFORE THE

COMMITTEE ON ENVIRONMENT AND 

PUBLIC WORKS 

UNITED STATES SENATE 

ONE HUNDRED TENTH CONGRESS 

SECOND SESSION 

JANUARY 30, 2008 

Printed for the use of the Committee on Environment and Public Works 

( 

EXAMINING THREATS AND PROTECTIONS FOR THE POLAR BEAR 

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82–737 PDF 2014

S. HRG. 110–1236 

EXAMINING THREATS AND PROTECTIONS FOR 

THE POLAR BEAR 

HEARING 

BEFORE THE

COMMITTEE ON 

ENVIRONMENT AND PUBLIC WORKS 

UNITED STATES SENATE 

ONE HUNDRED TENTH CONGRESS 

SECOND SESSION 

JANUARY 30, 2008 

Printed for the use of the Committee on Environment and Public Works 

( 

Available via the World Wide Web: http://www.access.gpo.gov/congress.senate 

(II) 

COMMITTEE ON ENVIRONMENT AND PUBLIC WORKS 

ONE HUNDRED TENTH CONGRESS 

FIRST SESSION 

BARBARA BOXER, California, Chairman 

MAX BAUCUS, Montana 

JOSEPH I. LIEBERMAN, Connecticut 

THOMAS R. CARPER, Delaware 

HILLARY RODHAM CLINTON, New York 

FRANK R. LAUTENBERG, New Jersey 

BENJAMIN L. CARDIN, Maryland 

BERNARD SANDERS, Vermont 

AMY KLOBUCHAR, Minnesota 

SHELDON WHITEHOUSE, Rhode Island 

JAMES M. INHOFE, Oklahoma 

JOHN W. WARNER, Virginia 

GEORGE V. VOINOVICH, Ohio 

JOHNNY ISAKSON, Georgia 

DAVID VITTER, Louisiana 

JOHN BARRASSO, Wyoming 

LARRY E. CRAIG, Idaho 

LAMAR ALEXANDER, Tennessee 

CHRISTOPHER S. BOND, Missouri 

BETTINA POIRIER, Majority Staff Director and Chief Counsel 

ANDREW WHEELER, Minority Staff Director 

(III) 

C O N T E N T S 

Page 

JANUARY 30, 2008 

OPENING STATEMENTS 

Boxer, Hon. Barbara, U.S. Senator from The State of California ....................... 1 

Inhofe, Hon. James M., U.S. Senator from the State of Oklahoma .................... 3 

Lautenberg, Hon. Frank, U.S. Senator from the State of New Jersey ............... 14 

Barrasso, Hon. John, U.S. Senator from the State of Wyoming .......................... 148 

Lieberman, Hon. Joseph., U.S. Senator from the State of Connecticut .............. 148 

Craig, Hon. Larry, U.S. Senator from the State of Idaho .................................... 150 

WITNESSES 

Hall, H. Dale, Director, U.S. Fish And Wildlife Service, Department of The 

Interior .................................................................................................................. 151 

Prepared statement .......................................................................................... 154 

Kelly, Brendan P., Ph.D., Associate Professor of Marine Biology, Associate 

Vice President For Research, University of Alaska .......................................... 175 

Prepared statement .......................................................................................... 178 

Williams, Margaret, Managing Director, Kamchatka/Bering Sea Ecoregion 

Program, World Wildlife Fund ............................................................................ 183 

Prepared statement .......................................................................................... 185 

Glenn, Richard, Alaskan Arctic Resident, Sea Ice Geologist ............................... 237 

Prepared statement .......................................................................................... 239 

Responses to additional questions from Senator Boxer ................................ 243 

Armstrong, J. Scott, Ph.D., Professor of Marketing, The Wharton School, 

University of Pennsylvania ................................................................................. 243 

Prepared statement .......................................................................................... 245 

Wetzler, Andrew E., Director, Endangered Species Project, Natural Resources 

Defense Council .................................................................................................... 296 

Prepared statement .......................................................................................... 298 

ADDITIONAL MATERIAL 

Statements: 

Jamie Rappaport Clark, Executive Vice President Defenders of Wildlife ... 340 

Jack Lentfer, Alaskan Wildlife Biologist, Alaskan Conservation Foundation ................................................................................................................. 351 

Mary Simon, President Inuit Tapiriit Kanatami ........................................... 354 

Artic Slope Regional Corporation .................................................................... 358 

Congressional Research Service, CRS Report for Congress, Polar Bears: Proposed Listing Under the Endangered Species Act ............................................ 407 

Articles: 

Science Direct, Polar Bears of Western Hudson Bay and Climate Change: 

Are Warming Spring Air Temperatures the ′′Ultimate′′ Survival Control 

Factor ............................................................................................................. 421 

International Arctic Research Center University of Alaska Fairbanks: 

Is the Earth Still Recovering from the ‘‘Little Ice Age’’? ........................... 433 

World Wildlife Fund: Facts and Fallacies About Polar Bears ...................... 456 

National Research Council: Cumulative Environmental Effects of Oil and 

Gas Activities on Alaska’s North Slope ....................................................... 464 

Department of Interior: Five-Nation Conference on Polar Bears ................. 467 

(1) 

EXAMINING THREATS AND PROTECTIONS 

FOR THE POLAR BEAR 

WEDNESDAY, JANUARY 30, 2008 

U.S. SENATE, COMMITTEE ON ENVIRONMENT AND PUBLIC WORKS, Washington, DC. 

The full committee met, pursuant to notice, at 10 a.m. in room 

406, Dirksen Senate Office Building, Hon. Barbara Boxer (chairman of the full committee) presiding. 

Present: Senators Boxer, Inhofe, Lieberman, Lautenberg, 

Klobuchar, Warner, Barrasso, Craig. 

OPENING STATEMENT OF HON. BARBARA BOXER, 

U.S. SENATOR FROM THE STATE OF CALIFORNIA 

Senator BOXER. Good morning, everyone. Very happy to be here 

with my distinguished Ranking Member, Senator Inhofe, my 

friend. We don’t agree on everything, but we are good friends. 

The Committee today is going to examine threats and protections 

for one of the most magnificent creatures in the world, the polar 

bear. I am just going to show a couple of charts, just how beautiful 

this creature is, and the next one as well, which shows the mama 

bear. Let’s just put that up there for a minute. 

There are an estimated 20,000 to 25,000 polar bears in 19 populations in the Arctic. But scientists are greatly concerned about 

their future, due to global warming and melting sea ice, which they 

depend on to hunt and den. So I am going to show a picture, this 

is the denning that goes on in the ice. Also, we have a picture of 

the polar bear getting ready to hunt its prey, standing on the ice 

and getting the necessary traction to make his or her move. 

In December 2006, George W. Bush’s Interior Secretary, our 

former Republican colleague and friend, Dirk Kempthorne, said 

‘‘Polar bears’ habitat may literally be melting.’’ So I want to reiterate that. This is the Bush administration’s Secretary of the Interior: ‘‘Polar bears’ habitat may literally be melting.’’ And then we 

are going to show you what this looks like when the ice begins to 

melt. If you look at the very top, that is what is left of the ice. We 

start in 1980, then 2005 and then 2007. You can see the shrinking 

of the ice. 

It is a sad statement on the health of the planet when such a 

majestic species as the polar bear could be lost due to human activities. I view this as a moral issue, because I think the polar bear 

is one of God’s most magnificent creatures. Thankfully, we have an 

important law to help protect imperiled species. It is called the Endangered Species Act, which helps preserve species and the places 

2 

they live. For the polar bear, that includes the sea ice. As Secretary 

Kempthorne said, that sea ice is literally melting away. 

However, in general, the Endangered Species Act and its protections begin when a species is listed as threatened or endangered. 

Unfortunately, this Administration, has utterly failed to do what it 

is supposed to do to save the polar bear. I look at today as a moment of truth: are they going to do it or not do it in time? 

Unfortunately, we have seen the Administration fail to take 

other steps to combat global warming. This is just one. 

Oversight is about accountability. It is about seeing whether any 

administration, Democratic, Republican, this one, the next one and 

the ones after that, whether they are living up to their obligations 

to the American people. I intend to continue to shine a spotlight 

on the Administration’s actions. 

Director Hall, on some things we certainly do agree. On January 

17th, 2008 you said, ‘‘We need to do something about climate 

change, starting yesterday, and there needs to be a serious effort 

to look at greenhouse gases.’’ But sir, with all due respect, you 

were also supposed to do something specific about the polar bear 

yesterday. In fact, you were obligated under the Endangered Species Act to list or withdraw your proposed listing for the polar bear 

by no later than January 9th, 2008. 

The Fish and Wildlife Service got off to a slow start. It was only 

after being sued by conservation groups that it even began the 

process of considering whether to list the polar bear. And I want 

to thank those groups. Without you, we would be nowhere. 

However, I find it curious that while our agency in the Interior 

Department is dragging its feet to list the polar bear, another agency in the Interior Department is moving quickly. The Minerals 

Management Service is charging full speed ahead to allow new oil 

and gas drilling activities in one of the biological hearts of the 

polar bear’s domain, the Chukchi Sea, and we will show you the 

Chukchi Sea and the neighboring Beaufort Sea are home to nearly 

one-fifth of the world’s polar bears. 

Despite this, nearly 30 million acres of the Chukchi Sea will likely be opened to oil and gas leasing on February 6th. Had the polar 

been listed on the day it was supposed to have been listed, the 

MMS would have been required to consult with Fish and Wildlife 

Service. Because the listing is already long overdue, there should 

be no further delay. And I would like for you today to give us a 

firm commitment to take immediate action to protect the polar 

bear. 

The American people want their grandchildren to share in the 

wonder of the polar bear. It is our moral obligation to protect God’s 

creatures on earth. I look forward to hearing your testimony and 

that of the other witnesses, and I hope you will give us a really 

good surprise today. I hope you will say you are ready to do this 

listing before this lease starts, so that Fish and Wildlife can have 

input into this drilling. 

Senator Inhofe. 

[The prepared statement of Senator Boxer follows:] 

3 

STATEMENT OF HON. BARBARA BOXER, U.S. SENATOR FROM THE

STATE OF CALIFORNIA

Today, this Committee examines threats and protections for one of the most magnificent creatures in the world: the polar bear. There are an estimated 20,000– 

25,000 polar bears in 19 populations in the Arctic. But scientists are greatly concerned about their future, due to global warming and melting sea ice, which they 

depend on to hunt and den. 

As a matter of fact, in December 2006, George W. Bush’s Interior Secretary, our 

former Republican colleague, Dirk Kempthorne said: ‘‘polar bears’ habitat may literally be melting.’’ These pictures help demonstrate this more than Secretary 

Kempthorne’s or my words ever could. It is a sad statement on the health of the 

planet when such a majestic species as the polar bear could be lost due to human 

activities. 

Thankfully, we have an important law to help protect imperiled species—the Endangered Species Act, which helps preserve species and the places they live. For the 

polar bear, that includes sea ice. And it is literally melting away. 11However, in 

general, the ESA and its protections begin when a species is ‘‘listed’’ as threatened 

or endangered. Unfortunately, this Administration has utterly failed to do what it 

is supposed to do to save the polar bear. 

Just as it has failed to take the necessary steps to combat global warming. Oversight is about accountability; it is about seeing whether any Administration—Democratic or Republican—is living up to its obligations to the American people and I 

intend to continue to shine a spotlight on the Administration’s actions. 

Director Hall, on some things we agree. On January 17, 2008 you said: ‘‘We need 

to do something about climate change starting yesterday, and there needs to be a 

serious effort to look at greenhouse gases.’’ But sir, with all due respect, you were 

also supposed to do something about the polar bear yesterday—in fact, you were obligated under the Endangered Species Act to list, or withdraw your proposed listing 

for the polar bear by no later than January 9, 2008. 

The Fish and Wildlife Service got off to a slow start. It was only after being sued 

by conservation groups that it even began the process of considering whether to list 

the polar bear. However, I find it curious that while your agency in the Interior Department is dragging its feet to list the polar bear, another agency in the Interior 

Department—the Minerals Management Service is charging full speed ahead to 

allow new oil and gas drilling activities in one of biological hearts of the polar bear’s 

domain—the Chukchi Sea. 

The Chukchi Sea and the neighboring Beaufort Sea are home to nearly 1/5th of 

the world’s polar bears. Despite this, nearly 30 million acres of the Chukchi Sea will 

likely be opened to oil and gas leasing on February 6th. Had the polar bear been 

listed on the date the Fish and Wildlife Service was obligated to list, the MMS 

would have been required to consult with the Fish and Wildlife Service. 

Because this listing is already long overdue, there should be no further delay. I 

would like a firm commitment to take immediate action to protect the polar bear. 

The American people want their grandchildren to share in the wonder of the polar 

bear. It is our moral obligation to protect God’s creatures on earth. I look forward 

to the testimony of the witnesses. 

OPENING STATEMENT OF HON. JAMES M. INHOFE, 

U. S. SENATOR FROM THE STATE OF OKLAHOMA 

Senator INHOFE. Thank you, Madam Chairman. Before I start 

my time, I have three things to put into the record. I note that Senator Stevens, from Alaska, has been very involved in this issue. He 

wanted to be here today, Madam Chairman, and could not do it. 

So without objection, I would like to have his statement in the 

record, and would encourage our colleagues to read it. 

Along with that, the comments I received from the American 

Farm Federation and the Alaska Native Regional Corporation, all 

three in the record. 

Senator BOXER. We will be happy to do that at your request, sir. 

[The referenced statements from the American Farm Federation 

and the Alaska Native Regional Corporation was not submitted in 

time for print.] 

[The referenced statement of Senator Stevens follows:] 

4 


82737.153

Senator Ted Stevens 

Statement for Senate Environment and Public Works Committee 

"Examining Threats and Protections for the Polar Bear" 

January 30, 2008 

As a Senator for the State of Alaska for the past 39 years, I possess 

a deep professional and personal interest in the status of our wildlife. 

Wildlife provides basic subsistence for many of the approximately 

120,000 native Alaskans. Consequently, Alaskans take great pride in 

the sustainable management of our natural resources. 

The U.S. Fish and Wildlife Service's (USFWS) proposed listing of the 

polar bear as threatened under the Endangered Species Act (ESA) is 

unprecedented. None of the almost 1,900 previously listed species 

were occupying their entire geographic range at the time of listing, yet 

the polar bear is readily found throughout the Arctic. 1 None of the 

previously listed species had rising populations at the time of listing, 

yet the global population of polar bears has been steadily increasing 

for 40 years.2 This proposed listing is unique because it is based on 

mathematical models as opposed to biological observations. 

Although these models can be a useful scientific tool, I have deep 

concerns about how the USFWS used certain data in its decision 

making process. Most models assume that sea ice will continue to 

j Servheen C (1990) The Status and Conservation of the Bears of the World. International 

Conference on Bear Research and Management Monograph Series No.2. 32 pages. 

2 Maksimov LA, Sololov VK (1965) Polar bear: distribution and status of stocks; problems of 

conservation and research. pp 39-43 In: Proceedings First International Meeting on Polar 

Bear. University of Alaska. 
5 


82737.154

melt over the next 100 years, but there is vast uncertainty as to how 

polar bears will respond to a changing climate3

. In September 2007 

the U.S. Geological Survey (USGS) released 9 technical reports on 

habitat changes, including sea ice decline, which may impact the 

polar bear population. These reports did not study the size of polar 

bear populations but examined sea ice decline models and the 

impact of sea ice decline on polar bear populations. 

The key mathematical models in the reports are based on only five 

years of data. Three of the years were "good", meaning that sea ice 

coverage was normal and there was a high number of polar bear 

births, but USGS seized upon two bad years in 2004 and 2005, when 

the ice coverage declined slightly and birth rates were slightly lower, 

to create their pessimistic projections of polar bear numbers around 

the Arctic. The relatively small differences between the five years are 

not enough to make such drastic projections far into the future. 

In the proposed rule, USFWS has favored one hypothesis and 

ignored contradictory data and theories. Polar bear experts at the 

Alaska Department of Fish and Game (ADFG) have shared with 

USFWS their observations of polar bears feeding on salmon, bearded 

seals, and other southerly-distributed species that have moved into 

areas where sea ice has receded. Considering the tremendous 

socio-economic impact of the proposed listing for the state of Alaska 

3 Stempniewicz L (2006) Polar bear predatory behaviour toward molting barnacle geese and 

nesting glaucous gulls on Spitsbergen. Arctic 59: 247-251 
6 


82737.155

and our Nation, I am extremely concerned that USFWS failed to 

meaningfully consider other theories and information. 

It appears that interest groups are clamoring for sea ice to be 

designated as critical habitat in order to end oil and gas exploration in 

the North Slope and curtail the use of fossil fuels throughout the 

country. This would only increase our reliance upon volatile, less 

environmentally sensitive foreign sources of oil and gas. Such a 

result would neither reduce greenhouse gas emissions, nor improve 

polar bear habitat. It is clear that the polar bear may be only the first 

in a long line of Arctic species to be the subject of a petition for listing 

under the ESA. My concern, as a Senator, is the crippling effect this 

will have on Alaskans, the national economy, as well as the ESA 

itself. 

The polar bear is a vital resource for the 13,000 Alaskans who live on 

the North Slope. Polar bears are an important traditional food source 

for native Alaskans. Eskimo artisans may use polar bear body parts 

in handicrafts - further increasing the economic value of each polar 

bear. The polar bear harvest provides both sustenance and 

substantial economic benefits for these isolated northern 

communities. Unfortunately, listing the polar bear could provide the 

legal means for special interest groups to curtail subsistence hunting 

by native Alaskans, even though USFWS has stated that Alaskans 

are harvesting polar bears below the population's maximum 

sustainable yield. 
7 


82737.156

Polar bears and energy development have co-existed in Alaska since 

oil was discovered in the Arctic in 1967. Under the Marine Mammal 

Protection Act, industry's activities have been closely monitored and 

permits have been issued to allow for incidental take. Existing 

regulations have been extremely effective - no polar bears have been 

killed by industry since the permitting process began. 4 Indeed, in 

Range-wide Status Review of the Polar Bear, 5 USFWS found there to 

be a negligible impact of oil and gas activities on the polar bear. 

Nonetheless, the proposed listing could subject oil and gas 

development in the North Slope to onerous, if not devastating 

regulatory oversight. Center for Biological Diversity v. Kempthorne6 

clearly illustrated the consequences that Alaskan industry can expect 

from the listing of the polar bear. Activities such as seismic 

exploration; sub-sea sediment sampling; construction and use of 

drilling structures; construction and use of roads, pipelines, runways 

and camps; well drilling; transportation of materials; and oil 

production and transportation could all be presumed to have harmful 

ecological consequences; and, therefore, the vast majority of 

industrial activities could require separate reviews with respect to the 

ecological consequences for polar bear denning, hunting, migration, 

and contaminant load, in addition to the consequences for species 

fed upon by the polar bear. 

4 Schliebe S, Evans T, Johnson K, Roy M, Miller S, Hamilton C, Meehan R, Jahrsdoerfer S (2006) 

Range-wide status review of the polar bear (Ursus maritimus). US Fish and Wildlife Service 

Anchorage, AK. 5 ,d. 

6 Center for Biological Diversity v. Kempthorne, (filed Feb 13, 2006, N.D. California.). 
8 


82737.157

Heightened regulatory burden on industry will depress oil and gas 

development. The State of Alaska receives well over $1 billion per 

year in the form of oil and gas revenue, which contribute to more than 

50 percent to the State's annual operating budget. It is clear that an 

ESA listing could place Alaska's fiscal health in jeopardy. 

Perhaps the most ironic aspect of the proposed listing is the potential 

for it to undermine the ESA - our nation's most celebrated tool for 

species conservation. Models of climate change predict that global 

biodiversity may decline by 35 percent by 2050. 7 Does this mean 

that we should list, in addition to the polar bear, the multitude of 

species that are currently abundant but may decline as a result of a 

changing climate? This is an unwarranted expansion in the 

interpretation of the ESA which could open the door for potential 

abuse of this law, to the detriment of species that would be affected 

by a weakened ESA and deviates from my original intent when I 

voted for this Act. The ESA, when used properly, is a tool to assist in 

the recovery of a species, but with the listing of the polar bear as 

threatened, the ESA would be used as a tool to curtail or eliminate 

the use of fossil fuels - not a goal of the ESA. 

Even if the population of polar bears were to decline in response to 

melting sea ice, an ESA listing would not halt the loss of the bears' 

critical habitat. Arctic sea ice has been declined for the past 200 

7 Thomas CD, Cameron AC, Green RE, Bakkenes M, Beaumont LJ, Collingham YC, Erasmus 

BF, De Siqueria MF, Grainger A, Hannah L, Hughes L, Huntley B, Van Jaarsveld AS, Midgley 

GF, Miles L, Ortega-Huerta MA, Peterson AT, Phillips OL, Williams SE (2004) Extinction risk 

from climate change. Nature 427: 145-148. 
9 


82737.158

years - well before modern industrial activity.8 Moreover, Dr. SyunIchi Akasofu of the International Arctic Research Center has found 

that the rate of melting has not changed despite recent increases in 

the concentration of carbon dioxide in the atmosphere. 9 Even if one 

were to accept the premise that Greenhouse Gases (GHG) are the 

main contributor to melting sea ice, the ESA cannot control the 

worldwide emission of GHGs. Regardless of whether the polar bear 

is listed as threatened, industrialization and deforestation in other 

nations will continue to add carbon dioxide to the atmosphere. Listing 

the polar bear as threatened in order to slow the melting of sea ice is 

a misguided effort and abuse of the ESA. Furthermore, it ignores the 

need to gain international support and coordination to address our 

changing climate. In the meantime, Alaskans would be needlessly 

subjected to severe economic and cultural consequences by agenda 

and publicity-driven special interest groups. 

The ESA was created to provide the means to restore depleted 

species and their habitat. Not only does the proposed listing fail to 

address the fundamental problems causing a potential loss of polar 

bear sea ice habitat, but it threatens the rights and livelihoods of 

Alaskans. We must look for a better approach to protect Arctic 

wildlife. 

8 Vinje (2001) Anomalies and trends of sea-ice extent and atmospheric circulation in the Nordic 

Seas during the period 1864-1998. Journal of Climate, 14:255-267. 

9Akasofu Sl (2006) Is the Earth still Recovering from the "Little Ice Age"? International Arctic 

Research Center University of Alaska Fairbanks. 
10 

Senator INHOFE. A lot has been said about the polar bear, the 

threats it allegedly faces and what should be done about it. In 

2006, the United States Fish and Wildlife Service, under force of 

litigation, proposed to list the polar bear as a threatened species 

under the Endangered Species Act, based on concerns over retreating Arctic sea ice. The Service asserts that the reason for the decline in one or two bear populations is climate change. To make 

that assertion, they rely on hypothetical computer models showing 

massive loss of ice, including a recent U.S. Geological Survey modeling prediction that shrinking sea ice could eliminate two-thirds of 

the world’s polar bears by 2050. Now, again, these are computer 

models which are constantly a problem. 

This is a classic case of reality versus unproven computer models. I look forward to the testimony of Scott Armstrong, an Ivy 

League professor and the Nation’s leading expert on forecasting 

methodology, who along with an Arctic climate change expert, authored a paper that challenges the USGS modeling. 

The decision on whether or not to list the bear rests currently on 

computer models. Those models are invalid and any decision based 

on them is not justified. 

Ironically, physical observation of the bear tells a much different 

story. The Fish and Wildlife Service estimates that there are currently, as the Chairman said in her opening statement, 20,000 to 

25,000 polar bears. In the 1950’s and 1960’s, there were somewhere 

between 5,000 and 10,000 polar bears. So we are talking about an 

increase of somewhere between doubling and four times the number of polar bears there were just a few years ago. Canadian biologist, Dr. Mitchell Taylor, the director of wildlife research at the 

Arctic Government of Nunavut, dismisses these fears with evidence-based data on polar bear populations in Canada, where twothirds of the world’s bears reside. 

Of the 13 polar bear populations out there, all but 2 are either 

growing or are stable. And the two I think are in the area, the 

western Hudson Bay area. A lot of that is due to regulations, hunting regulations that are being changed at this time. Just last 

month, researchers discovered an ancient polar bear jaw that dates 

back more than 100,000 years, to a time far warmer than it is at 

the present time. One award-winning geologist and professor from 

the University of Iceland said about the discovery, he said that 

‘‘Despite the ongoing warming in the Arctic today, maybe we don’t 

have to be quite so worried about the polar bear.’’ 

I would like to enter into the record actually three things. First 

of all a fact sheet that I have prepared with statements from biologists and wildlife scientists who have taken issue with the predictions of the demise of the polar bear. Also to put into the record 

separate statements from Dr. Susan Crockford, a Canadian evolutionary biologist and Dr. Matthew Cronin, a professor of animal genetics at the University of Alaska, Fairbanks. 

Senator BOXER. We will be happy to put that in. 

[The referenced fact sheet was not submitted at time of print.] 

[The referenced statements of Susan Crockford and Matthew 

Cronin follows:] 

11 

STATEMENT OF SUSAN J. CROCKFORD, PH.D., EVOLUTIONARY BIOLOGIST/ 

ARCHAEOZOOLOGIST

What we know about polar bears is fundamentally incomplete. The nature of the 

beast and the habitat in which it lives combine to make the kind of scientific study 

that is routinely applied to other species virtually impossible. There is a profound 

uncertainty in polar bear evolutionary history, population numbers (both past and 

current), and details regarding most life history features, not to mention the uncertainties surrounding past, present and future conditions of its habitat. We also know 

very little about its primary prey, the ringed seal. In my opinion, these uncertainties 

are not adequately acknowledged in the hypothesis currently being used to predict 

a grim future for polar bear populations over the next few decades. I contend that 

we do not know nearly enough about polar bears or their environment to predict, 

with any degree of certainty, precisely how they will respond to a few degrees of 

warming. 

What we do know, with absolute certainty, is that about 10,000 years ago the 

polar bear survived a period of significant warming that lasted about 2,000 years. 

During that time, temperatures in Arctic regions rose to at least 2.50C warmer than 

today and sea ice above western North America retreated much further in summer 

than it has even in the last few years. There is no evidence to suggest that sea ice 

disappeared entirely during this extended warm period or that polar bears disappeared; none of the ice-dependent prey species of polar bears, including ringed 

and bearded seals, disappeared either. Present numbers of polar bears are hard 

proof that the population which lived 8,000 years ago did not drop to catastrophic 

levels: indeed, the archaeological record of prehistoric peoples of the Arctic tells us 

that for the last 1,000 years at least, and probably much longer, polar bears, ringed 

seals and bearded seals were as well distributed across the North American arctic 

as they are today. 

STATEMENT OF MATTHEW A. CRONIN, PH.D., PROFESSOR OF ANIMAL GENETICS AT

THE UNIVERSITY OF ALASKA, FAIRBANKS

1. It is critical to separate science and management/policy. Science can tell us the 

status of wildlife populations, like polar bears, and make inference regarding the 

causes of impacts and predictions of change. The science presented on both sides 

of the polar bear issue is generally valid. The information presented by the fieldexperienced biologists in Alaska and Canada should be given special consideration 

because of their first-hand knowledge. This applies to all experienced biologists 

whether they agree or disagree with an ESA listing. However, science does not dictate policy. Science can help achieve a given policy but does not decide what the 

policy should be. Our elected representatives do. 

2. Don’t discredit scientists because of their funding source or because their interpretation of data doesn’t agree with yours. This is prejudice. Be fair and judge 

science based on its merit. Blind acceptance or rejection is not acceptable in science. 

3. The polar bear ESA listing is based on prediction, not the current status of the 

species worldwide. It is also based on apparent impacts to a limited number of populations. The science documenting population status, potential causative factors, and 

predicted future status has been done by qualified scientists and has credibility. So 

does work presenting alternatives. 

4. It is critical to decide if the ESA is appropriate for a threat based on predictive 

models. Polar bears will be threatened with extinction if the climate, sea ice, and 

population model predictions are realized. The model results are legitimate predictions, but as predictions they should be considered hypotheses in need of testing 

with data in the future. 

5. My opinion is that it is not appropriate to base an ESA decision on predictions. 

I would reserve the use of ESA to cases where threatened or endangered status is 

verified. If prediction is allowed as a standard for ESA, the number of species subject to ESA regulation will be limitless. Our entire natural resource industry and 

government management system will be overwhelmed with legal and regulatory 

burdens instead of focusing efforts on practical management in the field. Consider 

the extensive use of the ESA for groups that are not even species. Subspecies and 

populations (which are scientifically subjective designations) comprise more than 70 

percent of the mammals and more than 50 percent of the birds listed in the U.S. 

Expanding the ESA to include populations that might be endangered in the future 

seems like a additional expansion beyond the intent and jurisdiction of the ESA. 

6. The problem of human caused global warming should be explicitly dealt with 

as a specific issue. Use of the ESA for one species is not the proper way to deal 

with such a problem. 

12 

7. Please consider whether the polar bear ESA listing process has complied with 

Executive Order 13211 of 18 May 2001, which requires agencies to prepare ‘‘Statements of Energy Effects’’ for Federal actions. 

8. Please seriously consider the proper role of the Federal Government as defined 

in the U.S. Constitution: 

‘‘The powers not delegated to the United States by the Constitution, nor prohibited by it to the States, are reserved to the States respectively, or to the people.’’ 

(10th Amendment to the U.S. Constitution). 

I believe that wildlife management is the role of states, not the Federal Government. I believe use of the InterState Commerce Clause of the Constitution to justify 

the ESA is contrived. Regardless, polar bears occur in only one State (Alaska) so 

this justification is not relevant in the case at hand. Dealing with global climate 

change directly is appropriate for the Federal Government. ESA listing of individual 

species is a distraction from this critical issue. 

Thank you for your consideration. 

Senator INHOFE. The fact is that the polar bear is simply a pawn 

in a much bigger game of chess. Listing the polar bear as a threatened species is not about protecting the bear, but about using the 

ESA to achieve global warming policy that special interest groups 

cannot otherwise achieve through the legislative process. These 

groups have made their agenda clear in comments filed with the 

Fish and Wildlife Service. Greenpeace and the Center for Biological 

Diversity urged the Service to force greenhouse gas-emitting 

projects, even those not in Alaska, to account for potential effects 

on the bear before they can go forward. 

They wrote, ‘‘It is simply not possible to fully discuss the threat 

to the polar bear from global warming without regulatory mechanism to address greenhouse gas emissions.’’ But the people who 

will suffer first under the ESA listing are the local indigenous people of Alaska and Canada. For example, Alaska’s shipping and 

highway construction and fishing activities will have to be weighed 

against the bear. 

Furthermore, the decision to list the polar bear would irreparably 

damage a culture. On January 14th, two groups representing the 

Canadian Inuit people asserted that ‘‘Environmental groups are 

using the polar bear for political reasons against the Bush administration over greenhouse gas emissions.’’ That was a quote. According to the president, Mary Simon of ITK in Canada, ‘‘The polar 

bear is a very important subsistence, economic, cultural, conservation, management and rights concern. It is a complex, multi-level 

concern. But it seems the media, environmental groups and the 

public are looking at this in overly simplistic black and white 

terms.’’ 

I would like to enter a statement into the record and I look forward to the testimony of Richard Glenn, an Inupiaq Eskimo Naive 

from Alaska, who is a sea ice geologist and a subsistence hunter. 

The bear is also being used as a tool to stop or slow natural resource development in Alaska. Last week of the House side, witnesses supporting the listing of the polar bear stated that no oil 

and gas leases should be allowed until the bear is listed, its critical 

habitat designated and a recovery plan put in place. As we know, 

that could take, judging from the past, a long, long time. We have 

species that have been on the ESA list for decades and still don’t 

have a recovery plan. 

Oil and gas—this is very significant—oil and gas exploration in 

Alaska accounts for 85 percent of the State’s revenue and 25 percent of the Nation’s domestic oil production. The price of crude oil 

13 

is nearly $100 a barrel. Eliminating a quarter the U.S. production 

could be just absolutely devastating. I would have to ask the question of anyone who is testifying or anyone on this panel, are we 

concerned at all about the price of fuel, about the energy crisis we 

are under and about the possibility of eliminating 25 percent of our 

domestic production? 

Thank you, Madam Chairman. 

[The prepared statement of Senator Inhofe follows:] 

STATEMENT OF HON. JAMES M. INHOFE, U.S. SENATOR FROM THE

STATE OF OKLAHOMA

Good morning. Much has been said about the polar bear, the threats it allegedly 

faces and what should be done about it. In 2006, the United States Fish and Wildlife Service, under force of litigation, proposed to list the polar bear as a threatened 

species under the Endangered Species Act based on concerns over retreating Arctic 

sea ice. 

The Service asserts that the reason for a decline in one or two bear populations 

is climate change. To make that assertion, they rely on hypothetical computer models showing massive loss of ice, including a recent US Geological Survey modeling 

predicting that shrinking sea ice could eliminate 2/3 of the world’s polar bears by 

2050. 

This is a classic case of reality versus unproven computer models. I look forward 

to the testimony of Scott Armstrong, an Ivy League professor and the nation’s leading expert in forecasting methodology, who, along with an arctic climate change expert, authored a paper that challenges the USGS modeling. The decision on whether 

or not to list the bear rests entirely on computer models. If those models are invalid, 

then any decision based on them is not justifiable. 

Ironically, physical observation of the bear tells a much different story. The Fish 

and Wildlife Service estimates that there are currently 20,000 to 25,000 polar bears. 

In the 1950’s and 1960’s, estimates were as low as 5,000–10,000 bears. Canadian 

biologist Dr. Mitchell Taylor, the director of wildlife research with the Arctic government of Nunavut, dismisses these fears with evidence based data on polar bear populations in Canada , where 2/3 of the world’s bears reside. ‘‘Of the 13 populations 

of polar bears in Canada , 11 are stable or increasing in number. They are not going 

extinct, or even appear to be affected at present.’’ 

Just last month, researchers discovered an ancient polar bear jaw that dates back 

more than 100,000 years, to a time far warmer than the present. One award-winning geologist and professor from the University of Iceland said about the discovery 

‘‘that despite the on-going warming in the Arctic today, maybe we don’t have to be 

quite so worried about the polar bear.’’ I would like to enter into the record a fact 

sheet I prepared with statements from biologists and wildlife scientists who have 

taken issue with the predictions of the demise of the polar bear. I would also like 

to put in the record separate statements from Dr. Susan Crockford a Canadian Evolutionary Biologist and Dr. Matthew Cronin a Professor of Animal Genetics at the 

University of Alaska Fairbanks . 

The fact is that the polar bear is simply a pawn in a much bigger game of chess. 

Listing the bear as a threatened species is not about protecting the bear but about 

using the ESA to achieve global warming policy that special interest groups cannot 

otherwise achieve through the legislative process. These groups have made their 

agenda clear. In comments filed with the Fish and Wildlife Service, Greenpeace and 

the Center for Biological Diversity urged the Service to force greenhouse-gas-emitting projects, even those not in Alaska , to account for potential affects on the bear 

before they can go forward. They wrote, ‘‘It is simply not possible to fully discuss 

the threat to the polar bear from global warming without regulatory mechanisms 

to address greenhouse gas emissions.’’ 

But the people who will suffer first under an ESA listing are the local, indigenous 

people in Alaska and Canada . For example, Alaska ’s shipping, highway construction and fishing activities will have to be weighed against the bear. Furthermore, 

the decision to list the polar would irreparably damage a culture. On January 14, 

two groups representing Canadian Inuit people asserted that environmental groups 

are ‘‘using the Polar Bear for political reasons against the Bush administration over 

greenhouse gas emissions.’’ According to President Mary Simon of ITK in Canada 

, ‘‘The Polar Bear is a very important subsistence, economic, cultural, conservation, 

management, and rights concern. It’s a complex and multilevel concern. But it 

seems the media, environmental groups, and the public are looking at this in overly 

14 

simplistic black and white terms.’’ I would like to enter the statement into the 

record and I look forward to the testimony of Richard Glenn, an Inupiaq Eskimo 

native from Alaska , who is a sea ice geologist and a subsistence hunter. 

The bear is also being used as a tool to stop or slow natural resource development 

in Alaska . Last week, on the House side, witnesses supporting the listing of the 

polar bear stated that no oil and gas leases should be allowed until the bear is listed, its critical habitat designated and a recovery plan put in place. That could be 

a very long time. We have species that have been on the ESA list for decades and 

still don’t have a recovery plan. Oil and gas exploration in Alaska accounts for 85 

percent of the state’s revenue and 25 percent of the nation’s domestic oil production. 

The price of crude oil is nearing $100 a barrel. Eliminating a quarter of the US oil 

production will make us more dependent on foreign sources of oil, not less. 

The bottom line is that the attempt to list the polar bear under the ESA is not 

based on any current polar bear decline but is founded entirely on computer climate 

models and predictions that are fraught with uncertainties. Unfortunately, the bear 

is being used as a back door to climate change regulation. I look forward to hearing 

from our witnesses. 

Senator BOXER. Thanks, Senator. 

The early bird rule applies, so we will go to Senator Lautenberg 

and then Senator Lieberman. Senator Lautenberg? 

OPENING STATEMENT OF HON. FRANK LAUTENBERG, 

U. S. SENATOR FROM THE STATE OF NEW JERSEY 

Senator LAUTENBERG. Thank you, Madam Chairman. I really appreciate the fact that you do take the leadership role in viewing 

and analyzing questions that are before us about in some ways the 

almost very existence of the world as we know it. 

When I listen to our friend from Oklahoma, who is the skeptic 

here, about the things that we see in front of us, about computer 

modeling, I happen to have come out of the computer business, I 

spent only 30 years of my life there. But computer modeling is 

what we do when we send people up in space shuttles. We do a lot 

of computer modeling to see whether or not we are prepared to do 

that. We use it certainly in the military. We certainly use computer 

modeling in determining what kind of medication is going to be effective against various of the diseases and illnesses that man sees. 

So with all due respect, Senator Inhofe’s skepticism about the 

use of computer modeling certainly presents, as far as I am concerned, a serious challenge to what the world is right in front of 

our eyes. 

We see the Bush administration valuing oil over our environmental protections for future generations. And when we hear about 

the price of oil and we think about what is causing oil prices to behave as they do, well, it is our friends in Saudi Arabia and places 

like that who are engaged in a conspiracy to raise prices to whatever they can extract from a dependent world. And the difference 

is not in Alaska. That is only a very small part of the whole thing. 

We in this Committee saw first-hand on our visit to Greenland 

global warming already significantly damaging our natural world. 

We saw green where there was recently complete ice coverage. We 

are seeing that melting trend repeat itself across the world. 

I took the trouble to go to Antarctica and the South Pole half a 

dozen years ago and meet with the National Science Foundation 

and see what they were able to develop in terms of warnings about 

ice melt. Now we see that pace accelerating. The Arctic Ocean, for 

example, could be devoid of ice in the summertime by 2040, according to the latest science. Since polar bears are totally dependent on 

15 

sea ice to live, hunt, breed, two-thirds of the world’s polar bears are 

on a path toward extinction. It is a sign of things to come. It is not 

only a precious species, but a harbinger of what the future might 

look like. According to the U.S. Geological Survey, as the sea ice 

goes, so goes the polar bear. 

As most people in the room know, polar bears have been in trouble for a long time. Between 1981 and 2004, the average female 

polar bear’s weight dropped from 650 pounds to 510 pounds. That 

is a substantial difference in the ability of the species to adjust. 

During a similar period, an average polar bear litter shrunk by 15 

percent. 

Science alone makes it clear that the polar bear should be considered a threatened species and should be protected. But our concerns are not limited to the polar bear. It is one of the more visible 

examples of the toll that global warming is taking on our whole 

ecosystem. Our world is changing. But instead of listening to 

science, the Bush administration is more concerned with satisfying 

the oil industry. 

This month, despite the science, the Administration announced 

that it needed more time to determine whether or not to protect 

the dying polar bear. At the same time, the Administration announced that it would allow companies to drill in the same habitat 

where polar bears currently live. And I find it hard to believe that 

delaying the polar bear decision so that it occurs after the oil drilling was not simply a coincidence. To me there is no clearer example than this of the Administration valuing oil over existence, over 

life. Science has proven that the polar bear is threatened, and instead of acting swiftly to protect it, the Administration is promoting the interests of the oil companies. 

Madam Chairman, it is wrong. Global warming is the biggest environmental threat our world and human existence faces. It threatens our food supply, the air we breathe, and the well-being of future generations. If we continue down this path as we are, we endanger the existence of countless species and ignore our planet’s 

cry for help. When we saw here an example of the change in the 

ecology here in the neighborhood, in the Potomac River, when male 

fish carried female eggs, doesn’t that tell us all something, that 

this world is on a path toward, if not reshaping, perhaps lack of 

existence? We dare not wait any longer for our children and grandchildren and potentially mankind. We must take bold and aggressive action to reduce greenhouse gases. I am glad that this Committee and our colleagues have taken this step to do just that. 

Thank you, Madam Chairman. 

Senator BOXER. Thank you so much, Senator. 

Before I call on Senator Barrasso, then we will go to Senator 

Lieberman and Senator Craig, I wanted to place a couple of things 

in the record to compete with what Senator Inhofe put in the 

record. A 2007 USGS study, scientists conclude that by 2050, twothirds of all polar bears could be lost if we don’t take protective action. Then the World Conservation Union report of 2006, some of 

the premier scientists in the world and experts from this organization say the polar bear is threatened. These are peer-reviewed articles, so they will appear in the record following the articles put in 

by my esteemed Ranking Member. 

16 

[The referenced World Conservation Union report of 2006 was 

not submitted at time of print.] 

[The referenced 2007 USGS study follows.] 

17 


82737.245

= USGS science for a changing world 

USGS Science Strate!lY to Support U.S. Fish and Wildlife Service Polar Bear Listin!l 

Decision 

Forecasting the Range-wide Status of Polar 

Bears at Selected Times in the 21 st Century 

By Steven C. Amstrup', Bruce G. Marcot', and David C. Douglas' 

Administrative Report 

U.S. Department of the Interior 

U.S. Geological Survey 
18 


82737.246

U.S. Department of the Interior 

DIRK KEMPTHORNE, Secretary 

U.S. Geological Survey 

Mark D. Myers, Director 

U.S. Geological Survey, Reston, Virginia: 2007 

U.S. Geologica! Survey Administrative Reports are considered to be unpublished and may not be cited or 

quoted except in fo!low·up administrative reports to the same federal agency or unless the agency releases 

the report to the public. 

Any use of trade, product, affirm names is for descriptive purposes only and does not imply 

endorsement by the U.S. Government 

Author affiliations: 

• U,S. Geological Survey, Alaska Science Center, Anchorage 

lUSDA Forest Service, PaCIfic Northwest Research Station, Portland. Oregon 

3 U.S. Geological Survey, A!aska Science Center, Juneau 
19 


82737.247

Contents 

Abstract"""",,, ,,,""",,,"",,,"', .. ,',,.,"",.,,",,.,,",, .. """''''''''''"."''''''''''".,, ".""".",,,.,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,.,,.,,.1 

Introduction "'"'''''''''''''''''''''''''''''''''''''''''''''''''''''''' ,,,,,,,,,,,,,,,,,,,,,,,,.,,,,,,,,,,,,,,,. """".",,,.,,,,.,,.,,,,,,,,,,,,,,.,,,,,.,,,,,.,,,,,.,,,,,,,,,2 

Stu d y 0 bje ctive "'" '" "".,' " .. , ".," ,",,' """ ..... ,' "" ''''''', .... "",,,., "." ,,,., ",,,,,,., ""''''', .. "''" .. ",, .... ,' "' ... " .. ,,, .. ""., .... " .... """.,2 

B a c k g ro u n d b io 10 gy ,," ". '''''' "",. "" .. " .. '"".,,''' , .... "'''''" .. ,, .. ,,, ... """. ,,,. """ """" ... ,,,.,'" """ ". "." "" ... , "'"'''''' ,,,,,,,,,,,.,, .. 2 

M etho d s " ... "" "". "" ... ,,' "."", ". ".,,"","",', " .. ,,, ... ,,," ""'" ,,,,,,,.,,,,.,,,.,, .. ",," """ .... "." '" ". ''''', .... , '" '''''" ... "." .. ".," ...... ,,' ", .. ,. 5 

Pol arB ear E core g ion s"., .. ". """ ",.""." .. """ "". " .. ""'" ... ,, ".,,' '''' '"'''' '" ''''''''''', .. """"'" "" ,,",,", ... , ""'" "" .. ,""" .... """ 6 

Modeling",,,.,,,,,.,, .. ,,,,,,,,,,,,,,, .. ,,,,,,,,,,,,.,,,,,,,,.,,,, ... ,, ... ,,,,,,,,,,,,,,.,,.""" .. "" ... """" .. ".""""" .. "." ... " ..... """, ... """",, .. ,,,,,,,,,8 

Overview,,,.,,,,,,,,, ... ,,,, ... ,,,,,.,,,.,,,,,,,,,,,, .. ,,,,,.,,,,,,,,.,,,,""".,"""""""""''''''''''''''''''''''''''''''''''''''''''','''',,'', .. """""",,,,,,,.8 

Sea-ic e ha bitat va ria bles """"'"".,'''''''" .. "''.' .. , .. ,,,.,,,,''',, .... ,, ..... , ...... ,,.,,, .. ,,, ... ,,''''' .. " ..... " .. ""'''''" .. "".,'''''" ... "".,, 8 

Ca rryin g Ca pa city Mod el., .... " ... ".""""".""".""""'''" .. " .. ,,'''''''''''',, .. ,,',,.,'',,. ".,''''"''""., .. ''"''".'',, .... ,,.,,'', ... ,''''''', 9 

Habitat amount .. ,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,.,,,,,.,,,,,,,,,,,,,.,,,,,, .. ,,,,,,,,,"""."",,.,,'"'''''''''''',.,,''''''''''''''''',,'',,''''''''' 10 

Cha ng e in habitat amount." .. "".,,,.,, ... ,,,,,.,,,,,,.,,,,,,,,,,,,,,,,,.,,,,,,,,.,,,, .. ,,,,.,,,,.,,,,"."".",,,,,,, .. ,,,,,,, ... ,,,,,.,,.,,,,,,,,,,,,.,, 1 0 

Pola r bear d ensities,,,,,,,,,,,,,,,,.. "'"'''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''' """'"'''' 11 

Polar bear carrying ca pacity """""""""""""""""""""""'''''''''''''''"."'',,. "" .... " ",," "". """ " " .. """ .. ,,,.,, .. ,,,,,, 11 

Percent change in carrying capacity """ .......... ''' .... '''' ......... ''''' .. " "" .. , .... ,,, .. ,,,.,, ....... " .... "'''" .. " .. " .... "",, ... ,," 12 

Assigning Status Categories Based on Carrying Capacity Change .. ".,." ..... "."." ........ " .. "", .. "" .. ,",,, ... ,, .. 12 

Bayesian Network Population Stressor Model." ... ,,,,,,,,.,,,,,,, ... ,,,,, .. ,,.,,,,,.,, ... ,,.,, .. ,,,,,,,,,,,,,., .. ,," .. ""." .. ""." .. "." 12 

What are Bayesian network models? " .. "". " .. "",,, ''' ......... " .. "" ... "" .. " .... " ...... " " .. " '''''''', .... "'''" .......... " .. ".",13 

Use of Bayesian networks in ecological modeling .. " ... , .. ,""." .. """ .. "".""" ... " ... "", .. "" .. " .. ,,,, .... ,,""",, .. " ... 13 

Structuring the Bayesian network population stressor model for polar bears """"."" .. " .. " ... ""."" ... " ... 14 

Parameterizing the Bayesian network model ........... " ... ""."""""", .. " .... """''', .. ,,, .... , ...... ,, ...... , .. , .... , ....... " .... 15 

Bayesian network model output states , .... "'" ... "" ..... , .... ,, .. """ ............ ''', ............................ " ... , ..................... 16 

Node C4: Numerical Response ... , .. " ...... "." ........... , ............. , .......... , ...... " .. , .. ,'" .... ", .... "., ... ,'''" ............ "" ...... 16 

Node C3: Distribution Response .' .. " ....... " .... ,,,",",",, .... ,,',", .. ,,', .... ,,', .. ,,.,, ..... , .... , ..... " ........ " .. ,"""" ... ,", .... ," 17 

Node 01: Overall Population Outcome"",,, ...... ,, .. , .. ,, ...... ,, ..... ,,,, .. ,, .... ,,,, .. , ... ,,,,.,, .. ,,,, ... ,, ....... ,, ....... " ............. 17 

Re suits " .. , .. ,,' , .... " ... " .... " .. ,." .... "', ... "' .. " .. ,, ........ , ..... "" .... , .. " .. '" .... " ..... ,,, ..... ",, .. , ,,, .. ,, ......... "" .. ' .... " .. , .... ,' " .. "",,, "'" .,,' , .. , 19 

Forecasted 21st Century Polar Bear Carrying Capacity , .... "" .... , ...... ,,, .. ,, .. ,,, ... ,, .. ,,',, .... ,,",, .. ,, .. ,"",, .... ,,''''',, ........ 19 

Habitat area and change ............... ,,"...... .. ... " .. """" ....... " ... " ... " ... " ..... "'" ... " .......... "." .... ,, ............ ,," ..... 19 

Pola r b ea r c arryin g ca pa city " .......... ""'''" ... " .. "''''' .. , .... " .... "'"." .... ''" .. " ... ,,, .. ,,,, .. , .... '"'" ... """ .. "', .. ' .... ,,, ..... ,,'"'' 20 

Bayesian Network Model Forecast of the 21st Century Status of Polar Bears .. " ....... "" .. "." .. , .. "" ................. 20 

Sensitivity Structure of the Bayesian Network PopUlation Stressor Model. .. " ...... " .. " .. "" .. "" .... " ... " .. , ..... 21 

Dis c ussion ......... " .... " ... , .. , .. ', ." ..... " ...... ,,, .. , .. , ...... ,, ...... ,''',. .,"' .. " ..... " .. , ..... " .... ,,, ... , ......... ,, ... ,, ... ,, ..... ,,,,', .. , ,.,,,.22 

Types and Implications of Uncertainty ,.. " ..... , .. " ... ", .. , "'''" .... " " ,,, ........... , .. , .... ,"' ...... "" .... """ .... " 22 

Forecasted 21st Century Polar Bear Carrying Capacity", .... " ... "", .... "."'''" ..... "''".", ...... " .... ".""." .. ,, .. ,,, .. ,, ... " .. 24 

Bayesian Network Model Forecast of the 21st Century Status of Polar Bears .. " .. "", .. " .. ", .... "" .. " .. "" ..... ",,,27 

Next steps in the BN model development"."" .. "" ........ " ... " .... " .. , ........ , .. "" ... , ..... , .. "" .. " ............ " .... " .............. ,,27 

BN model projected outcomes ... " ........ " ..... , .... " .. " ........ ,.. , .... " .. " ........ " .. " .... " .... , ...... , ............ 28 

Sensitivity a na lyses " .. ", .. ", .... ".,"'"."" .... " ....... ".. . .... , .......... ,,, .. ,,, .. ,,",,.,,, ...... ,,, ..... ,, .. ,,,,,,,,.29 

Strength of evidence of BN model projections" .. ", ..... "" ......... , .... """"" ... " ............. " ......... ,, ................... " .... " .... ,32 

Conclusion .. "." .. "' .. ,',, ........ ,'"'' ... " .... ,' .... ' .. ,'''''''''', .. " .. , ... ,,, ... ' .. , .. , .. ,.' ... ,', ........ ,, .. ,, .... ,,.,, .... , ...... ,,.,, ....... ,, ... ,, .. ," .... 35 

Acknowledgements .,", ........ "", ........ , .. " ... " ... ", .. "", ......... ,, ....... ,, .. , .......... , .. ,,, ... ,",, .. ,, ......... ,,, ....... ,",, .... ,,.,,,, ...... , ........ ,,,37 

Refe re n c e s Cite d ... ,., .. , .. , """" "" .. , .. " .... , .... ' ,,, .. '" "." "". " .. ,,"" ,,,. "" .. ", .. "" .. ", .. '''' '"'''' ' ........ " .. " .. ," """'" , ........ " " .. " ... ",37 

Appendix 1. Results of sensitivity analyses ofthe Bayesian network population stressor model.""" .. , .. " .. " .. 97 

Appendix 2. Documentation of the Bayesian network polar bear population stressor model.. .." .. " .. 100 

Appendix 3. Probability ta bles for each node in the Bayesian network model " ...... " .. " ... " .... " ..... ,"" ........... ,," 109 
20 


82737.248

Figures 

Figure 1. Map of four polar bear ecoregions to which we refer in this report. Ecoregions were established 

by grouping recognized subpopulations which share seasonal patterns of ice motion and distribution ....... 82 

Figure 2. Linkages followed in this report, from availablc information on sea icc polar bears and other 

environmental correlates, and leading to projections of future polar bear carrying capacity and overall 

population outcomc ...................................................................................................................................................... 83 

Figure 3. (a) Average summer and winter sea icc extent in the cntire polar basin (divergent and 

convergent regions) expressed in square km (left) and as a percent change relative to each model's 1990-

1999 mean for 20th ccntury hindeasts (right). (b) Average RSF habitat values for summcr and winter 

expressed in raw RSF units (left) and perccnt change to each model's 1990-1999 mean for the 20th century 

hindcasts (right) ................................................................................................................................................................ 84 

Figure 4. The basic influence diagram for the Baycsian network polar bear population stressor modcl 

showing thc role of 4 listing factor categories used by U.S. Fish and Wildlifc Service ................................... 85 

Figure 5. Thc full Bayesian network population stressor model dcveloped to evaluate overall population 

outcome ................................................ , ............................................................................................................................. 86 

Figure 6. Annual (12-month sum) polar bcar habitat area H,.c at I years -10 and () from satellite data and 0, 

45,75, and 100 from minimum, ensemble mcan. and maximum global change model (GCM) runs, in four 

geographic regions G and all regions combined (sce Table 4) .............................................................................. 87 

Figure 7. Pcrcent change in polar bear habitat amounts CH,.c at t years -10 and 0 from satellite data and 0, 

45,75, and 100 from minimum, cnsemble mean, and maximum global change model (GCM) runs, in four 

geographic regions G and all regions combined, normalizcd to 0% ehangc at year 0 (see Table 4) ............. 88 

Figure 8. Normalized polar bear carrying capacity at t years -10 and 0 based on habitat amount 

from satellite data at year -10, empirical bear counts at ycar 0, and habitat amounts at years 0, 45, 75, and 

100 from minimum, cnsemble mcan, and maximum global change model (GeM) runs. in four geographic 

rcgions G and all regions combined (see Table 6) .................................................................................................... 89 

Figure 9. Polar bcar carrying capacity trends CK,c at t years -10 and 0 based on carrying capacity values 

from Figure 8, in four geographic regions G and all regions combincd, normalized to 0% change at year 0 

(see Table 6) .................................................................... " .............. " ........................................................................... ".90 

Figure 10. Projected polar bear popUlation outcomes of Bayesian nctwork model for 4 ecoregions at 5 

time periods relative to prcsent.. ................................. .................... . ............... 91 

Figure 11. Projected probabilities ofthc "extinct" overall population outcome (node DI in Fig. 5), from 

thc Bayesian network population stressor modeL .............................................. " ..................................................... 92 

Figure 12. Cumulative sensitivity of overall popUlation outcome (nodc D I, Fig. 5) to all input variables 

(yellow boxes. Fig. 5), in the Bayesian network population stressor model. .................................. " .................. 93 

Figure 13. Mean (SE) arca of optimal RSF polar bear habitat in the polar basin by scason and decadal 

time period (top). and percentage change in the samc values (bottom), from enscmble mean of 10 IPCC 

AR-4 general circulation modcls ..... " ................................................................................................. " ........................ 94 

Figure 14. Probability of "extinct" outcomes projected by a Bayesian network (BN) polar bear population 

stressor model. Projections includc 4 ecoregions, and 3 future time periods relative to present... ................. 95 

Figure 15. Area of sea ice extcnt (>50% ice concentration) on August 23, 2007, compared to 10 IPCC 

AR-4 GCM mid-century projections of ice extent for September 2045-2054 (mean ± lsd, n ~ 10 years) . 

........................ " ............................................................................................................................................................ 96 
21 


82737.249

Tables 

Table 1. Ten IPCC AR-4 GCMs whose sea icc simulations and projections were used to definc ice 

covariates for polar bear RSF models: IPCC model 10, country of origin, approximate grid resolution 

(degrees), forcing scenario, and the number of runs used lor the polar bear studies ........................................ 46 

Table 2. Composite summary categories of polar bear carrying capacity change from present levels, based 

on categories of composite habitat change and composite carrying capacity change ...................................... .47 

Table 3. Input data used in the Bayesian network population stressor model (Figure 5) ............................... .48 

Table 4. Amount, percent change, and summary of change in polar bear habitat forecasted by the 

deterministic polar bear carrying capacity model. ................................................................................................... 56 

Table 5. Numbers and densities of polar bears by ecorcgion, based on habitat amount at year 0 (Table 4) . 

.............................................................................................................................................................................................. 59 

Table 6. Polar bear carrying capacity forecast lor each ecoregion, time period, and modeling basis, by the 

deterministic polar bear carrying capacity model... .. ................................................................................. 61 

Table 7. Overall summary of change in total polar bear carrying capacity from present levels (based on 

applying results of carrying capacity calculations in Table 6 to the rule set in Table 2) ................................. 64 

Table 8. Results of the Bayesian network popUlation stressor model, showing the most probablc outcome 

state, and probabilities of each state (larger. samc as now, smaller, rare, and extinct), for overall population 

outcome (node 01; see Figure 5) ................................................................................................................................ 66 

Table 9. Results of the Bayesian network population stressor model, showing the most probable outcome 

states, and probabilities of each state. for the distribution response and numerical response outcomes 

(nodes C3, C4; see Figure 5) ......................................................................................................................................... 68 

Table 10. Results of the Bayesian network population stressor model, showing the most probable outcome 

states, and probabilities of each state, for habitat threats and director mortalities summary variables (nodes 

F2 and A 1; see Fig. 5) ............................................................................................. , ....................................................... 70 

Table 11, Results of the Bayesian network population stressor model, showing the most probable outcome 

states, and probabilities of each state, for changes in foraging habitat distribution (node 0; see Figure 5).72 

Table 12. Results of the Bayesian network population stressor model, showing the most probable outcome 

states, and probabilities of each state, for disease/predation and other disturbance factors variables (nodes 

A4, A6; see Figure 5) ................................................................................................................................................... 74 

Table 13, Results of the Bayesian network population stressor model, showing the most probable outcome 

states, and probabilities of each state, for reproduction and vital rates (nodes U, L2; see Figure 5) ............. 76 

Table 14. Projected outcomes from Bayesian network population stressor model showing probabilities of 

overall outcome states resulting when all human factors were f1xed at 'same as now' or' fewer than now.' 

................................................ ................................. . ............................................ , ......... 78 

Table 15. Projected outcomes from Bayesian network population stressor model showing probabilities of 

overall outcome states resulting when all human factors were tlxed at uniform ............................................... 80 
22 


82737.250

Abbreviations, Acronyms, and Symbols 

Abbreviations, Acronvms, and Meaning 

Svmbols 

AR-4 JPCC Fourth Assessment Report 

Bn l3affin Bay Il]CN polar bear suhpopulation unit 

BN Bayesian Network 

BS Barents Sea IUCN polar bear subpopulation unit 

CS Chukchi Sea leeN polar hear sUbpopulation unit 

OS Davis Strait IUCN polar bear suhpopulation unit 

EG East Greenland IUC~ polar bear subpopulation unit 

FB Foxe Basin IUeN polar bear sUbpopulation unit 

GI3 Gulf ofI3oothia IUCN polar bear sUbpopulation unit 

GeM General Circulation Model 

HAD I SST Hadley Center sea icc and temperature data set 

IBCAO International Huthymetric Chart of the Arctic Ocean 

IPee International Panel on Climate Change 

IUCN International Union for the Conservation of Nature 

KB Kane Basin IUer...; polar bear subpopulation unit 

KS Kara Sea IUCN polar bear suhpopulation unit 

LS Lancaster Sound lUCN polar bear suhpopulation unit 

LVS Laptev Sea IUCN polar bear suhpopulation unit 

Me M'C!intock Channel iUCN polar bear subpopuJntion unit 

;\;ASA National Space and Aeronautics Administration 

NBS Northern Beaufort {UCN polar bear subpopulation unit 

NW Norwegian Bay TUCN polar bear subpopulation unit 

PBSG Polar Bear 

PMW Passive Miero\.vave 

QE Queen Elizabeth islands IUCN polar hear suhpopulation unit 

RSF Resource Selection Function 

SBS Southern Beaufort Sen IUCN polar bear suhpopulation unit 

SHB Southern Hudson Bay IUCN polar bear subpopuJation unit 

SRES Special Report on Emissions Scenarios 

SRES A IS SRES. greenhouse gas f()rciflg scenario that assumes "business as usual" 

CSFWS U.S. Fish & Wildlife Service 

VM Viscount Melville Sound IUCN poJar bear subpopulation unit 

WIfE 'A/estern Hudson Bay IUCN polar bear subpopulation unit 
23 


82737.251

Forecasting the Range-wide Status of Polar 

Bears at Selected Times in the 21 st Century 

By Steven C, Amstrup, Bruce G, Marcot, and David C, Douglas 

Abstract 

To inform the U,S, Fish and Wildlife Service 

decision, whether or not to list polar bears as 

threatened under the Endangered Spccies Act 

(ESA), we forecast the status of the world's 

polar bear (Ursus marilimus) populations 45, 75 

and 100 years into the future, We applied the 

best available information about predicted 

changcs in sea ice in the 21 st ccntury to current 

knowledge of polar bear populations and their 

ecological relationships to the sea ice to 

understand how the range-wide population of 

polar bears might change. We combined the 

world's 19 polar bear subpopulations into 4 

ecological regions based on current and 

projected sea ice conditions. These "ecoregions" 

are the (I) Seasonal lee Ecoregion which 

includes Hudson Bay, and occurs mainly at the 

southern extreme of the polar bear range, (2) the 

Archipelago Ecoregion of the Canadian Arctic, 

(3) the Polar Basin Divergent Eeoregion where 

ice is formed and then adveeted away from 

near-shore areas, and (4) the Polar Basin 

Convergent Eeoregion where sea ice formed 

elsewhere tends to collect against the shore, We 

incorporated projections of future sea icc in 

each ecoregion, based on 10 general circulation 

models (GCMs), into two models of polar bear 

habitat and potential population response, First, 

we used a deterministic model of past, current, 

and future polar bear carrying capacity which 

assumed a linear relationship between bear 

density and annual average sea ice extent. 

Because this approach did not include seasonal 

changes in icc availability or other possible 

popUlation stressors. it provided an optimistic 

view of the potential magnitude of and change 

in population carrying capacity by ecoregion 

and time step, Second, we developed a Bayesian 

network (BN) model structured around 

population stressors that could affect the factors 

considered in ESA decisions. The BN model 

combined empirical data, interpretations of data, 

and professional judgment into a probabilistic 

framework, Although BN models can be based 

on the collective judgment of multiple experts, 

time constraints in this project allowed input 

from only one expert, Therefore, we consider 

our BN model a prototype, and we provide 

guidance regarding next steps necessary to 

further refine the model. The BN model 

incorporated information about annual and 

seasonal sea icc trends as well as potential 

effects of other population stressors such has 

harvest, disease, predation, and effects of 

increasing human activity in the north due to ice 

retreat. Under both modeling approaches, polar 

bear populations were forecasted to decline 

throughoLlt all oflheir range during the 21" 

century. In projections based upon ensemble 

mean ice predictions, the carrying capacity 

model forecasted potential extirpation of polar 

bears in the Polar Basin Divcrgent Ecoregion in 

75 years. Projections llsing minimal ice levels 

forecasted potential extirpation in this ecoregion 

by year 45, whereas projections llsing maximal 

ice levels forecasted steady declines but not 

extirpation by year 100, Populations of polar 

bears in the other ecoregions were projected to 

decline at all time stcps, with severity of decline 

dependent upon whether minimum, maximum 

or mean ice projections were used, Dominant 

outcomes of the BN model were for extinction 

of polar bear populations in the Seasonal Ice 
24 


82737.252

and Polar Basin Divergent Ecoregions by 45 

years from present, and in the Polar Basin 

Convergent Ecoregion by 75 ycars from 

present. The BN model projected high non-zero 

probabilities that Archipelago polar bears could 

occur at smaller numbers than now through the 

end ofthc century. Declines in ice habitat were 

the overriding factors determining all model 

outcomes. Although management of human 

activities could forestall extinction in the 

Archipelago and Polar Basin Convergent 

ecoregions, it could not qualitatively alter the 

prognosis of extinction for the Polar Basin 

Divergent and Seasonal Ecoregions. Similarly, 

model results indicated that sea ice conditions 

would have to be substantially better than even 

the most conservative GCM projections to 

result in a qualitatively different outcome for 

any of the ecoregions. Our modeling suggests 

that realization of the sea ice future which is 

currently projected, would mean loss of'" 2/3 of 

the world's current polar bear population by 

mid-century. 

Introduction 

Study Objective 

Polar bears depend upon sea icc for acccss to 

thcir prcy and for other aspects of their life 

history (Stirling and Oritsland 1995; Stirling 

and Lunn 1997; Amstrup 2003). Observed 

declines in sea icc availability have been 

associated with reduced body condition, 

reproduction, survival, and population size for 

polar bears in parts of their range (Stirling et al. 

1999; Obbard et al. 2006; Stirling and 

Parkinson 2006; Regehr et al. 2007b). Observed 

(Comiso 2006) and projected (Holland et al. 

2006) sea ice declines have led to the 

hypothesis that the future welfare of polar bears 

range-wide may be diminished, and to the U.S. 

Fish and Wildlife Service (FWS) proposal to list 

the polar bear as a threatened species under the 

Endangered Species Act (U.S. Fish and Wildlife 

Service 2007). The classification as a 

"threatened spccies" requires determination that 

it is likely the polar bear will become an 

endangered species within the "foresceable 

future" throughout all or a significant portion of 

its range. An "endangered species" is any 

species that is in danger of extinction 

throughout all or a significant portion of its 

range. To help inform the final listing decision, 

the FWS requested that the U.S. Geological 

Survey (USGS) conduct additional analyses of 

polar bears and their sea ice habitats. Between 

February and August 2007, USGS and 

collaborators developed nine reports targeting 

specific questions considered especially 

informative to the final decision. This report, 

one of the nine, builds upon the other eight 

reports and uses other current information on 

polar bears to forecast the status of polar bears 

occurring in different parts of the Arctic at three 

future periods in the 21 st-century. 

We use the best available information and 

knowledge, including that derived from new 

studies requested by the FWS, to forecast the 

future status of polar bears in each of 4 

ecoregions (Figure I). We present our forecast 

in a "compared to now" setting where 

projections for the decade of2045-2055, 2070-

2080, and 2090-2100 arc compared to the 

"present" period of 1996-2006. For added 

perspective we also look back to the decade of 

1985-1995. Hence, we examined five time 

periods in total. Our view of the present and 

past are based on sea ice conditions derived 

from satellite data. Our future forecasts are 

based largely on information derived from 

general circulation model (GCM) projections of 

the extent and spatiotemporai distribution of sea 

ice. 

Background biology 

Polar bears occur throughout portions of the 

Northern Hemisphere where the sea is icecovcrcd for all or much of the year. Polar bear 

genetics indicate that the species branched off 

from brown bears (Ursus arctos) and invaded 
25 


82737.253

an open niche on the surface of the sea ice 

during maximal extent of the continental ice 

sheets in the very late Pleistocene. Molecular 

genetic techniques suggest this could have 

occurred as long ago as 250,000 years (Amstrup 

2003).Very few polar bear fossils are known, 

however, and those that have been discovered 

arc relatively recent. They appear for the first 

time in the fossil record only 40 to 50 thousand 

years ago (Thcnius 1953; Kurten 1964). During 

their short evolutionary history, polar bears 

have diverged substantially from brown bears, 

apparently under selective pressurcs stemming 

from their specialization for capturing seals 

from the surface of the icc. Stanley (1979) 

dcscribed the many recently-evolved traits of 

polar bears as an example of "quantum 

speciation." The dearth of polar bear fossils 

reflects their specialty of living on the sea ice. 

Remains of dead animals on the sea icc would 

tend to accumulate on the sea floor rather than 

on land where they are more acccssible to 

human discovery. 

Since moving offshore, behavioral and 

physical adaptations have allowed polar bears to 

increasingly specialize at hunting seals from the 

surface of the ice (Stirling 1974; Smith 1980; 

Stirling and 0ritsland 1995). Polar bears derive 

essentially all of their sustenance from marine 

mammal prey and have evolved a strategy 

designed to take advantage of the high fat 

content of marine mammals (Best 1984). Ovcr 

half of the calories in a seal carcass are located 

in the layer of fat between the skin and 

underlying muscle (Stirling and McEwan 1975). 

Polar bears show their prcference for fat by 

quickly removing the fat layer from beneath the 

skin after they catch a seal. The high fat intake 

that can be achieved by specializing on marine 

mammal prey has allowed polar bears to thrive 

in the harsh Arctic environment and to become 

the largest of the extant Ursids (Stirling and 

Derocher 1990; Amstrup 2003). 

Over much of their range, polar bears are 

dependent on onc species of seal, the ringed seal 

(Phoca hispida). Polar bears occasionally catch 

belugas (Delphinapterus leucas), narwhals 

(Monodon monocerns), walrus (Odobenus 

rosmarus), and harbor seals (P. vilulina) (Smith 

1985; Calvert and Stirling 1990; Smith and 

Sjare 1990; Stirling and 0ritsland 1995; 

Derocher et al. 2002). Walruses can be 

seasonally important in some parts of the polar 

bear range (Parovshchikov 1964; Ovsyanikov 

1996). Bearded seals (Erignathus barbatus) can 

be a large part of their diet where they are 

common and are probably the second most 

common prey of polar bears (Derocher et al. 

2002). Throughout most of their range, 

however, polar bears arc most dependent upon 

ringed seals (Smith and Stirling 1975; Smith 

1980). The relationship between ringed seals 

and polar bears is so close that the abundance of 

ringed seals in Some areas appears to regulate 

the density of polar bears, while polar bear 

predation in turn, regulates dcnsity and 

reproductive success of ringed seals (Hammill 

and Smith 1991; Stirling and 0ritsland 1995). 

Across much of the polar bear range, their 

dependence on ringed seals is close enough that 

the abundances of ringed seals can be estimated 

by knowing the abundances of polar bears 

(Stirling and 0ritsland 1995; Kingsley 1998). 

Polar bears rarely can catch seals on land or 

in open water (Fumell and Oolooyuk 1980); 

rather, they consistently catch seals and other 

marine mammals only at the air-ice-water 

interface. This dependence of polar bears on 

hunting at the ice surface, where aquatic 

mammals must come to breathe, is evident in 

the behavior of ringed seals. Steady predation 

pressure li'om polar bears over thousands of 

years has led ringed seals to use subnivian 

(below the snow) birthing lairs and to interrupt 

spring and summer basking with frequent 

periods of scanning their surroundings for bears. 

This is in contrast with Weddell seals 

(Leptonycholes weddelli), the southern 

hemisphere equivalent of ringed seals, which 

bask and give birth in the open (Stirling 1977) 

and can be approached by humans without 

reaction. 
26 


82737.254

Although there are local exceptions, it 

appears that polar bears gain little overall 

benefit from alternate foods. Evcn in Hudson 

Bay where polar bears are forced onto land for 

extended periods with aeeess to a variety of 

foods including human refuse, little terrestrial 

food is incorporated into polar bear tissues 

(Ramsay and Hobson 1991). In short, 

maintenance of polar bear populations is 

dependent upon marine prey, largely ringed 

seals, and they arc tied to the surface of the ice 

for effective access to those prey. 

Polar bears occur in most ice-covered 

regions of the northern hemisphere, including 

the center of the polar basin (Stefansson 1921). 

They are not evenly dispersed throughout this 

area, however. Polar bears have been observed 

most frequently in shallow-water areas near 

shore and in other areas where currents and 

upwellings keep the winter ice cover from 

becoming too solidified. These shore leads and 

polynyas create a zone of active unconsolidated 

sea ice that is small in geographic area but 

contributes -SO% of the (otal productivity in 

Arctic waters (Sakshaug 2004). Polar bears, are 

most commonly observed in or near these ncar 

shore zones where ice is constantly moving, 

opening up and reconsolidating, rather than 

pelagic areas which are of lower productivity 

(Stirling and Smith 1975; Pomeroy 1997; 

Stirling 1997), and have been shown to focus 

their annual activity areas over thesc regions 

(Stirling et a!. 1981; Amstrup and OeM aster 

1988; Stirling 1990; Stirling and 0ritsland 

1995; Stirling and Lunn 1997; Amstrup et al. 

2000, 2004a, 200S). Not surprisingly, ice over 

shallow waters less than 300m deep has now 

been shown to be the most prefcrred habitat of 

polar bears throughout the polar basin (Durner 

et al. 2007). 

Given their wide geographic distribution, 

polar bears inhabit regions with very different 

sea ice conditions. Thc southern reaches of their 

range includes areas where sea ice is seasonal. 

There, polar bears are forced onto land where 

they are food deprived for extended periods 

each year. Polar bears of Hudson Bay are the 

best known example of this situation, but bears 

in Foxe Basin, Davis Strait, and Baffin Bay also 

are "stuck" on land for a portion of the year 

when the sea ice in their area melts entirely. 

Other polar bears live in some of the harshest 

and most northerly climes of the world where 

the ocean is icc-covered year-round. This 

includes northerly regions of the Canadian 

Arctic archipelago and northern Grcenland 

(Janke I et al. 1976). Others live in the pelagic 

regions of thc polar basin where there are strong 

seasonal changes in the character of the ice. 

There polar bears historically have remained on 

the advancing and retreating icc pack 

throughout the year, despite the sometimes very 

long seasonal movements required to do so 

(Amstrup 1986; Amstrup and DeMaster 1988; 

Amstrup et al. 2000). For example, sea-iee 

extends as much as 400 km south of the Bering 

Strait that separates Asia from North America, 

and polar bears extend their range to thc 

southernmost cxtreme of the ice (Ray 1971). 

Because sca ice disappears from most of the 

Bering and Chukchi seas in summer, however, 

polar bears occupying these areas must move as 

far as 1000 km northward to stay on the 

retreating ice (Garner et a!. 1990, 1994). In the 

Chukchi Sea and elsewhere, polar bears spend 

their summers concentrated along the edge of 

thc persistent pack ice. Significant northerly and 

southerly movements appear to be dependent 

upon seasonal melting and refreezing of ice near 

shore (Amstrup ct al. 2000). 

Telemetry data have shown that polar bears 

do not wander aimlessly on the ice, nor are they 

carried passively with the ocean currents as 

previously thought (Pedersen 1945). Rather, 

they occupy multi-annual activity areas from 

which they seldom leave. Tracking data show 

that polar bears use seasonally preferred or 

"core" regions every year, despite variation in 

annual activity area boundaries (Amstrup et a!. 

2000,2001, 2004a, 200S). This suggests that 

activity areas of polar bears, when viewed over 

multi-year periods, could be called home 
27 


82737.255

ranges. All areas of the home range, however, 

will not be used each year. Sea-icc habitat 

quality varies temporally as wcll as 

geographically (Stirling and Smith 1975; 

DeMaster et al. 1980; Ferguson et al. 1997, 

1998, 2000a, 2000b; Amstrup et al. 2000). In 

areas where sea ice cover and character are 

seasonally dynamic, a large multi-year home 

range, of which only a portion may be used in 

anyone season or year is an important part of 

the polar bear life history strategy. In other 

regions where ice is less dynamic, smaller and 

less variable activity areas are common 

(Mcssier et al. 1992; Ferguson et al. 2001). 

The seasonal movement patterns of polar 

bears serve to emphasize the role of sea-ice in 

their life cycle. In the Beaufort Sea, the largest 

monthly activity areas and highest movement 

ratcs are during June-July and NovemberDecember. This matches the temporal patterns 

of ice melt and freeze in the area (Gloerscn et 

al. 1992). Polar bears catch seals mainly by 

still-hunting (Stirling and Latour 1978). The 

dynamic summer and autumn ice must 

minimize predictability of seal hunting 

0ppOltunity. Unpredictable icc distributions 

could require longer bear movements and larger 

bear activity areas during freeze-up and 

break-up. From May-August, measured net 

monthly movements of polar bears in the 

Beaufort Sea were significantly to the north for 

all bcars, and in October they moved back to the 

south (Stirling 1990; Amstrup et al. 2000). 

October has historically been the month of 

freeze-up in the southern Beaufort Sea. In recent 

years, especially, October has been the first time 

in months when ice is availablc over the 

shallow water near-shore. Polar bears 

summering on the persistcnt pack iee quickly 

move into shallow water areas as soon as new 

ice forms in autumn, and they disperse easterly 

and westerly along near shore unconsolidated 

ice zones during winter. Mauritzen et a!. (2001, 

2002) also found movement patterns that were 

closely tied to seasonal ice cycles in other parts 

ofthe polar basin. Polar bears, in fact, have 

adapted their movement strategies to 

accommodatc a broad range of sea ice 

characteristics (Messier et al. 1992; Ferguson et 

al. 1997, 1999). 

The common denominator is that polar bears 

make seasonal movements to maximize their 

foraging time on sea ice that is suitable for 

hunting (Amstrup 2003). Polar bears appear to 

requirc relatively high concentrations of sea ice 

for effective hunting. Recent obscrvations 

indicate that during most ofthc year, these 

preferred hunting habitats are sea-ice areas 

where the ice cover is 2:50% . (Stirling et al. 

1999; Durner ct al. 2004, 2006, 2007). 

Methods 

We took two approaches to forecast how the 

future range-wide population of polar bears 

might be different than it is now. Our first 

method provided estimates of the maximum 

potential sizes of polar bear populations based 

on climate modeling projections of the quantity 

of their habitat but in the absence of effects 

of any additional stressors or knowledge about 

changes in habitat distribution. OUf second 

method provided estimates of how the presence 

of multiple stressors, including changes in the 

quantity of sea ice as well as its spatiotemporal 

distribution, may affect polar bears. 

Thc first approach was a deterministic 

calculation of polar bear habitat amount and 

carrying capacity in each ecoregion. We used 

estimated numbers of polar bears currently 

occupying each of the world's subpopulations, 

and the amount of sca-ice habitat currently in 

each area, to estimate the present-day polar bear 

density in each of 4 defined ecoregions (Figure 

1). Then we multiplied the densities by the 

projected future (or empirically determined 

historic) amount of polar bear habitat in each 

ecoregion at various time periods, to derive the 

maximum potential number of bears that habitat 

could support. This is an estimate of polar bear 

carrying capacity, given the assumptions that 

current popUlations are at or near carrying 
28 


82737.256

capacity, that polar bear densities (number of 

bears per unit area) do not change, and that 

quality of the future habitat is equivalent to that 

at present. Of course, we recognize that such 

calculations oversimplify the eventuality. Yet, 

these simple calculations provide approximate 

numerical references of polar bear numbers that 

help place other discussions offuture change 

into perspective. 

Our second approach, a Bayesian network 

(BN) population stressor model, addressed 

many shortcomings of the carrying capacity 

model by incorporating probabilistic 

calculations of potential effects from multiple 

stressors on polar bear populations. The BN 

model used the same projections of habitat 

change as in the carrying capacity model, but it 

also included seasonal habitat changes as well 

as anticipated likelihoods of changes in several 

other stressors (Figure 2). The BN model 

accommodated scenarios of whether availability 

of food for polar bears would likely change and 

whether bears might redistribute themselves 

because of changes in habitat. Also considered 

was whether changes in hunting, oil and gas 

development, contaminants, parasites, disease 

agents and other potential anthropogenic 

(human-caused) stressors could become more or 

less influential than they are now. The BN 

model parameterized knowledge about the 

effects of observed habitat changes on polar 

bear distribution, demography and physical 

condition. This included understandings gained 

from other studies by the USGS relative to the 

listing decision, and expert judgment on the 

effects of a variety of other factors which might 

alter the future for polar bears. Construction of 

the BN model allowed us to integrate qualitative 

judgments, regarding how polar bears interact 

with their environment, with quantitative habitat 

prcdietions in a synthetic model to provide 

relative probabilities of potential future 

outcomes. Forecasts of the future status of polar 

bears were based on comparisons between 

current and future sea ice, and on other salient 

changes in the polar bear's environment that 

may change as the ice diminishes. Current ice 

conditions were extracted from data sets derived 

from passive microwave satellite imagery, 1979 

- 2006 (http://nsidc.org/datalnsidc-0051.html). 

Future ice conditions were extracted from GCM 

projections (https:llesg.llnl.gov:8443). In 

addition to sea ice extent and distribution data 

from satellite images and GCMs, we used 

resource sclection functions (RSFs) to identify 

preferred, optimal polar bear habitat. The RSFs 

allowed us to evaluate whether preferred sea ice 

habitats may changc at diffcrent rates than the 

overall sea ice cover. 

We made forecasts of the future for polar 

bears in each of four ecoregions. We dcfined the 

ecoregions based on observed and GCMprojected differences in sea ice, and how polar 

bears respond or may respond to those changes. 

In the following section, we provide detailed 

descriptions of the four polar bear ecoregions. 

Next, we describe the process we used to make 

projections of the amount and distribution of 

future sea icc habitat. Finally we provide details 

of the modeling methods we used to project the 

future status of polar bears. 

Polar Bear Ecoregions 

Polar bears are distributed throughout 

regions of the Arctic and subarctic where the 

sea is ice covered for large portions of the year. 

Although movements of individual polar bears 

overlap extensively, telemetry studies have 

demonstrated spatial segregation among groups 

or stocks of polar bears in different regions of 

their circumpolar range (Schweinsburg and Lee 

1982; Amstrup 1986,2000; Garner et a!. 1990, 

1994; Messier et a!. 1992; Amstrup and Gardner 

1994; Ferguson et a!. 1999; Carmack and 

Chapman 2003). Patterns in spatial segregation 

suggested by telemetry data, along with 

information from survey and reconnaissance, 

marking and tagging studies, and traditional 

knowledge, have resulted in recognition of 19 

partially discrete polar bear groups (Aars et a!. 

2006). There is considerable overlap in areas 

occupied by members of these groups (Amstrup 
29 


82737.257

et al. 2004a, 2005), and boundaries separating 

the groups are adjusted as new data are 

collectcd. Nonetheless, these boundaries are 

thought to be ecologically meaningful, and the 

19 units they describe and are managed as 

subpopulations (Figure I). 

In this report, we adhere largely to these 

group designations as they are used by 

International Union for the Conservation of 

Nature (IUCN) Polar Bear Specialist Group 

(PBSG) describcd in Aars et al. (2006). Our 

descriptions digress somewhat from thosc ofthc 

PBSG in regions of the polar basin where 

current knowledge of sea ice conditions and 

polar bear habitat preferences suggest that 

digression makes sense. We first redefined a 

Queen Elizabeth Islands suhpopulation (QE). 

This subpopulation had historically been 

identified for the continental shelf region and 

inter-island channels betwecn Prince Patrick 

Island and the northeast corner of Ellesmere 

Island. This unit was originally a geographic 

catchall population to account for the remainder 

of northern Canada (Aars et al. 2006). This area 

is characterized by heavy multi-year (old age) 

ice, except for a recurring lead system that runs 

along the Queen Elizabeth Islands from the 

northeastern Beaufort Sea to northern 

Greenland (Stirling 1980), Approximately 200 

polar bears could be resident here and somc 

bears from other regions have been recorded 

moving through the area (Durner and Amstrup 

1995; Lunn et al. 1995). In 2003, the Canadian 

Polar Bear Technical Committee and the 

Canadian Polar Bear Administrative Committee 

agreed not to identify the QE sUbpopulation, 

Rather, they concluded it should be included as 

an undifferentiated portion of the central Arctic 

Basin (Lunn et al. 2006, page 10 I), Here, we 

reinstated QE as an important ecological unit. 

We also formally extended the QE boundary to 

include northern Greenland, based upon 

observed and predicted behavior of sea ice. Like 

the Northern Beaufort Sea sUhpopulation, QE 

occurs in a region of the polar basin that recruits 

ice as it is advected from other portions of the 

polar basin (Comiso 2002; Rigor and Wallace 

2004; Belchansky et al. 2005; Holland et al. 

2006; Durner et al. 2007; Ogi and Wallace 

2007; Scrreze et aI. 2007), 

We also do not incorporate the Arctic Basin 

subpopulation into our analyses, This 

subpopulation was defined by the IUCN in 2001 

(Lunn et aL 2002) to recognize bcars which may 

reside outside the territorial jurisdictions of the 

polar nations, The Arctic Basin region is 

characterized by very dcep water which is 

known to be unproductive (Pomeroy 1997). 

Available data are conclusive that polar bears 

prefer sea-ice over shallow water «300m deep) 

(Amstrup et aL 2000, 2004a; Dumer et al. 

2007), and it is thought that this preference 

reflects increased hunting opportunities over 

more productive waters. Indeed, polar bears 

from coastal regions will use the central Arctic 

Basin seasonally, but tracking studies indicate 

that few if any bears are ycar-round residents of 

the central Arctic Basin, 

Although each of the areas where the 19 

individuallUCN subpopulations occur have 

unique characteristics, we pooled them into four 

ecological regions (Figure I), We defined 

"ecoregions" on the basis of observed temporal 

and spatial patterns of ice formation and 

ablation (melting or evaporation), obscrvations 

of how polar bears respond to those patterns, 

and how general circulation models (GCMs) 

forecast future ice patterns. We defined these 

four ecoregions as: 1) Seasonal Ice (or 

Seasonal) Ecoregion; 2) the Canadian Arctic 

Archipelago (Archipelago Ecoregion); 3) the 

Polar Basin Divergent Ecoregion; and 4) the 

Polar Basin Convergent Ecoregion, Splitting the 

polar basin into 2 ecoregions was based upon 

their diffcrent patterns of sea ice formation, 

ablation and advection (transport by the wind or 

currents) (Rigor et al. 2002; Rigor and Wallace 

2004; Maslanik et al. 2007; Meier et aL 2007; 

Ogi and Wallace 20(7), The Polar Basin 

Divergent Ecoregion is characterized by 

extensive formation of annual sea icc which is 

then advected into the center ofthc polar basin 
30 


82737.258

or out of the polar basin through Fram Strait. 

The Polar Basin Divergent Ecoregion lies 

between -127' W longitude and 10' E longitude 

and includes the southern Beaufort, Chukchi, 

East Siberian-Laptev, Kara, and Barents seas. 

The Polar Basin Convergcnt Ecoregion is the 

remainder of the polar basin ineluding the east 

Greenland Sea, the continental shelf areas 

adjacent to northern Greenland and the Queen 

Elizabeth Islands, and the northern Beaufort Sea 

(Figure I). 

Modeling 

Overview 

We projected the futurc status of polar bear 

populations in each of the four ecoregions, 

which collectively encompass the entire range 

of polar bear distributions range-wide. Both the 

carrying capacity and the BN models wcre 

applied to each of the four ecoregions at five 

time periods relative to present (years -10,0,45, 

75, and 100). Analyses included historic and 

current habitat conditions from the satelliteobservcd ice data for years -10 and 0, and future 

habitat conditions from GCM ice projections for 

years 45,75, and 100. Because multiple GCM 

model runs were not available, we did not have 

samples from which true process variation 

could be estimated. To capture the full range of 

variation, however, we developed estimates 

from: I) the multi-model (cnsemble) means of 

the 10 GCMs, 2) the GCM that projected the 

minimum ice extent, and 3) the GCM that 

projected the maximum ice extent-for each 

ecoregioll in each time period. Sec De Weaver 

(2007) and Durner et al. (2007) for a thorough 

discussion of the range in values among GCMs. 

Sea-ice habitat variables 

Our forecast of future carrying capacity of 

polar bears was based entirely on historic and 

current observations, and future GCM 

projections offuture sea ice habitat for polar 

bears. Our BN model then incorporated changes 

in sea-ice habitat distribution as one of the 

"stressors" which might help predict the future 

of polar bears. Hence both approaches depended 

upon an assessment of polar bear habitat and 

projections of how future habitat might be 

different than now (Figure 2). For modeling. we 

needed consistent metrics of polar bear habitat 

that would facilitate temporal comparisons. We 

defined two such metrics: I) polar bear habitat 

as simply the area of sea ice over the continental 

shelf; and 2) optimal sea icc habitat----<lefined as 

ice with characteristics shown to be preferred by 

polar bears through development and 

application of resource selections functions 

(RSFs). 

Durner et al. (2007) used polar bear satellite 

tracking data and monthly icc concentration 

observations derived from passive microwave 

satellite imagery (Cavalieri et al. 1999) to 

develop RSFs that estimated relative 

probabilities of habitat usc in the two pelagic 

ecoregions orthe polar basin. RSFs were built 

only for the polar basin where radiolocation 

data had sufficicnt sample size. Durner et al. 

(2007) constructed four seasonal RSF models 

(wintcr, spring, summer, and autumn) using 

data collected during 1985-1995. Durner et al. 

(2007) then extrapolated the RSF models using 

sea ice projections from each of 10 GCMs 

(Table I) that were selected for analysis because 

their 20th century simulations were betler 

aligned with the observational ice record 

(De Weaver 2007). 

For each season, Durner et al. (2007) 

calculated the average 1985-1995 RSF 

threshold that separated the upper 20% from the 

lower 80% of the RSF-valued habitat area, and 

termed the upper 20% "optimal habitat" because 

those areas were occupied by over 70% of the 

bear locations. These 1985-1995 thresholds 

were used to extract thc area of optimal habitat 

in all months of the 2 I "-century RSF 

extrapolations from all 10 GCMs. Using the 

1985-1995 period to define the thresholds 

provided Durner et al. a foundation that allowed 

them to examine whether futurc ice projections 
31 


82737.259

indicated increases, decreases, or stability in the 

cumulative annual area of optimal polar bear 

habitat. 

We used three types of monthly maps from 

the Durner et a!. (2007) study: I) Arctic-wide 

observed sea ice concentrations (1979-2006); 2) 

Arctic-wide 21 Sl-century sea ice projections by 

10 GeMs; and 3) both observed and projected 

areas of optimal polar bear sea-icc habitat in the 

two pelagic polar basin ecoregions. From the 

observed and projected Arctic-wide sea ice 

concentration maps, we defined and extracted 

"total available ice habitat" as the annual 12-

month sum of sea icc cover over the continental 

shelves of the two polar basin ecoregions. lee 

cover was defined as the aerial extent (km2

) of 

all pixels with 2:50% ice concentration. Since 

deep water is uncommon in the archipelago and 

seasonal ice ecoregions, we considered those 

entire areas to effectively reside over the 

continental shelf, meaning total ice habitat 

equated to total ice cover. 

We note that expressing changes in sea-ice 

habitat over time on the basis of annual km2

_ 

months tends to minimize the potential effects 

of sea ice habitat changes projccted for the 

future as well as those that have been observed 

may have on polar bears. Whereas the yearly 

average sea ice extent has declined at a rate of 

3.6% per decade, the mean September sea ice 

extent has declined at a rate of 8.4% per decade 

(Meier et al. 2007). Further, all GeMs project 

extensive winter sea ice through the end of the 

21 s( century in most ecoregions (Durner et al. 

2007). Therefore the severity of summer periods 

offood deprivation may be hidden by extensive 

sea ice in winter. Although polar bears are well 

adapted to a feast and famine diet (Watts and 

Hansen 1987), there apparently are limits to 

their ability to sustain long periods of food 

deprivation (Regehr et al. 2007b). We recognize 

that our measure of change in km2

-months will 

be largely insensitive to seasonal effects. 

We used the baseline period 1985-1995 to 

define high-value (optimal) habitat because 

during this early period of our studies, yearround polar bear movements were less restricted 

than they were in recent years when sea ice 

extent was more spatially reduced. The 4 

seasonal RSF thresholds, derived from the 

1985-1995 period, remained fixed for all time 

steps in our projections. Thus. when we 

extracted the area of optimal habitat from RSF 

maps generated from outputs of GeMs, the 

threshold values for optimal habitat were those 

observed in 1985-1995. This approach created a 

foundation that allowed us to examine whether 

future ice projections indicated increases, 

decreases, or stability in the cumulative annual 

area of optimal polar bear habitat relative to our 

earliest decade of empirical observations. 

Inherently, this approach assumes that polar 

bears in the future will select habitats in the 

same way they did between 1985-1995 despite 

seasonal changes in ice extent and distribution. 

Other key sea icc factors of interest included 

how climate warming may produce changes in 

the duration and distance that ice retreats from 

the continental shelf regions. Using the 

observed and projected ice concentration maps, 

we extracted and summed the annual number of 

icc-free months in each ecoregion. An ice-free 

month occurred when the proportion of icc 

cover (defincd above) over the continental shelf 

dropped below 50% (again, the archipelago and 

seasonal ecoregions were considered entirely 

shelf waters). In other words, we considered the 

availability of lolal habitat to be compromised 

if less than half of the shelf-waters were icecovered; hence the respective month was 

classified as icc-tree. Also for each year, for the 

month of minimum ice extent, we ealeulated the 

mean distance from every pixel in an eeoregion 

to the nearest sea icc. 
32 


82737.260

Carrying Capacity Model 

We developed deterministic calculations of 

polar bcar carrying capacity for each 

combination of ccoregion, time step, and future 

minimum, maximum, and multi-model mean 

GCM projections. Deterministic projections 

were calculated in Microsoft Excel®. 

Calculations in the model components are 

described below. 

Habitat amount 

First, we compiled the amount of total ice 

habitat and optimal habitat from the observcd 

sea ice record and from the GCM projections. 

Specifically, thc total annual (1: 12 months) 

habitat amount HI.G was expressed for each of 

the four ecoregions G and each ofthe five 

yearly time periods t as km2 -months. For the 

two polar basin ecoregions (where thc RSF 

study was conducted) we subtracted the optimal 

habitat area from the estimatcs of total icc 

habitat to provide an area of non-optimal 

habitat. 

Change in habitat amount 

Despite overall agreement in the direction of 

change in sea ice extent, there is considerable 

variability among the GCMs in their 

simulations of present-day ice extent, as well as 

disparity with the observed sea icc record 

(Figure 3). These disparities rcflect aspects of 

GCM model uncertainties that are introduced by 

many factors (De Weaver 2007). Disparities of 

GCM model predictions with known conditions 

arc not surprising bccause GCMs are 

constructed to cmulate natural climate 

variability (Wang ct al. 2007). Amounts of icc 

predicted by thc GCM model might not 

perfectly match amount observed bccausc the 

observed climate is but one realization of the 

possiblc modeled outcomes. 

When comparing modeled futures to the 

present, it would make no sense to project the 

trends forward from a baseline that "could havc 

been." Rather, the sensible approach is to use 

the GCM's projccted rates of habitat change, 

and apply those rates of change to the actual 

observed baseline. To this end, we compared 

the habitat projections at cach time step to each 

model's "time zero" value, and calculated the 

percent change in habitat projected by each 

model relative to itself. This calibrating or 

normalizing of the estimates of available habitat 

provided all model results with a common 

beginning or baseline value in year 0, and took 

full advantagc of the rate of change projected by 

each model. 

We calculated the percent change in habitat 

amount 11 at time t with rcspect to year 0, for 

each geographic rcgion G, as 

CH,p 100 * -=--~'-

One outcome of the calculation of CHI.G was 

that estimates at year 0 varied among GCM 

runs. Another outcome of these calculations is 

that compared to the observed ice extent, the 

GCM ensemble mean, and most individual 

models, overcstimated icc extent in the study 

area in both the late-20th century simulations 

and the early-21 st century proje~tions. 

Furthermore, the recent rate of summer icc 

dccline in the observed data shows a trajectory 

that is steeper than that of the GCM ensemble 

mean during the early 21 st century. This is a 

reflection of Stroeve et a!.' s (2007) conclusion 

that Arctic sea icc may be disappearing at a rate 

that is "faster than forecasted". 

Our normalized CH',G was furthcr interpreted 

into catcgories of direction of change, 

magnitude of change, and a composite summary 

of magnitude and direction. Dircction was 

categorizcd into "contracting" if CHw < ° or 

"expanding or stable" ifCH"G ~ 0, Magnitude 

was categorizcd into "fast" if ICH"GI > 30.0, 

"moderate" if 15,0 < ICH,,GI::; 30,0, and "slow 

or none" if ICH"r;1 15,0. We also make 

available the specific results for CFhG so that 
33 


82737.261

alternative cutoff values for such categories 

could be examined if desired. The summary 

category for habitat change was then based on 

the habitat change direction category and the 

magnitude category, as shown in Table 4. 

Polar bear densities 

We used the most recent estimated 

population size for each IUCN subpopulation 

(Aars et a!. 2006, Tablc 5) to calculate polar 

bear densities. Because estimates were not 

provided for the East Grecnland and Kara Sea 

subpopulations, we surmised numbers that 

seemed appropriate bascd upon the area of 

habitat and records of harvest where available. 

Accuracy of the year 0 density estimates is not 

critical because our goal was to express the 

relative changes that are likely to occur. In other 

words, although the numbers of bears in many 

of the world's subpopulations are poorly 

known, our projections of trends in those 

numbers in this model are valid to the extent 

that sea ice quantity alone determines polar bear 

carrying capacity. 

We calculated polar bear densities based on 

observcd total ice habitat in each of the four 

ecoregions. We also calculated polar bear 

densities based on optimal habitat in each orthe 

two polar basin ecoregions. Following examples 

in the ecological literature, we refer to the 

densities estimated from total and optimal 

habitat as "crude" and "ecological," respectively 

(Rinkevieh and Gutierrez 1996; Diller and 

Thome 1999). We calculated densities as 

follows. First we tallied present-day (year 0) 

polar bear population sizes No.G in each of the 

four ecoregions G. We then calculated polar 

bear densities as 

Do 

IVO,u 

expressed as habitat area (km2 -months x 1000) 

per bcar, using the estimates of habitat at year 0 

from satellite data. We expressed density in 

terms of habitat area per bear to avoid the 

excessively small values that would result from 

expressing density in terms of bears per area. 

We calculated total densities based on total 

ice habitat area for the Seasonal and 

Archipelago ecoregions, and we calculated 

"ecological" and "crude" densities based on 

optimal habitat and and non-optimal habitat 

area, respectively, for the Polar Basin Divergent 

and Convergent ecoregions. Empirical 

observations indicated that polar bears spend 

70% of their time in the portion of the habitat 

that we called optimal (Dumer et al. 2007). We 

extrapolated this to mean that at any snapshot in 

time, 70% of the bears in the two polar basin 

ecoregions werc within the identiiied optimal 

habitat. We used 70% to estimate an ecological 

density in the optimal habitat. The remaining 

30% of bears in each ecoregion were assigned 

to the non-optimal habitat to calculate a crude 

density. All polar bear density calculations were 

based on year 0 numbers of bears and habitat 

area, and thcn applied to other past and future 

time periods. This assumed that densities are 

invariant over time in terms of describing 

potcntial carrying capacity levels. 

Polar bear carrying capacity 

We applied year 0 polar bear densities to 

habitat area in each time period to calculate 

polar bear carrying capacity K,.G for each 

combination of time period I, ecoregion G, and 

minimum, maximum, and ensemble mean GCM 

habitat values. The calculation was: 

K,P H, / Dc' 

We used thc normalized perccnt change in 

habitat to derive values for available habitat at 

each time step. This assured that our estimates 

of changes in carrying capacity coincided with 

the projected estimate of available habitat at 

each time step. Speciiically, we calculated 

percent change CK,.G in K,.G trom year 0 values, 

as 

CK,p 100*':"'-~-~c:. 

KO,G 

This was done for all habitats in the Seasonal 

Ice and Archipelago ecoregions, and separately 
34 


82737.262

for optimal habitat and non-optimal habitat in 

the Divergent and Convergent ecoregions. Wc 

then applied each of the percent changc values 

CK,.G to the estimate of carrying capacity at year 

o Kn.G (based on the observed data), to 

recalculate a normalized value of carrying 

capacity as 

K"",,n = K * [1 + CKt.

G } 

t,G up 100' 

In this way, the values of normalized carrying 

capacity K;:;=' can be compared over time 

periods (historic, currcnt, and future) for each of 

thc GCM model run scenarios (minimum, 

cnsemble mean, and maximum) in parity. 

Percent change in carrying capacity 

We divided the values of change in carrying 

capacity CK,G into categories of direction, 

magnitude, and composite outcomes. Direction 

was categorized into "decreasing'" if CKt,G < 0 

or "stable or increasing'" ifCKt,G ~ O. 

Magnitude was categorized into "high" if 

ICK'.GI > 30.0, "moderatc" if 

15.0 < ICK,,c1 ~ ;10.0, and "low to none" if 

ICKwl < 15.0. We make available the specific 

results for CK,G so alternative cutolTvalues can 

be examined if desired. The summary categories 

of carrying capacity change were then derived 

from the direction and magnitude categories, as 

shown in Table 6. 

Assigning Status Categories 

Based on Carrying Capacity 

Change 

We categorized outcomes of habitat change 

and carrying capacity change into 4 composite 

summary categories to describe the status of 

polar bear populations: enhanced, maintained. 

decreased. and toward extirpation (Table 2). 

The composite summary categories express 

very general classes of carrying capacity Icvcls 

as compared with current levels, and basically 

constitute a simple rule set for cxpressing 

outcomes in ordinal scale classes. We provide 

categorical outcomes to depict future polar bear 

carrying capacity levels in a simple, 

understandable manner that is relatively 

insensitive to the accuracy of specific 

calculations or assumptions. We started these 

computations with the bcst cstimates available 

of sea ice habitats and polar bear numbers, and 

we applied those estimates to the best available 

GCM projections. 

As mentioned previously, many polar bear 

popUlation estimates were crude, and thc 

assumption that polar bear density would not 

change over time is almost certainly not valid. 

Collapsing the numerical outcomes of this 

process into intuitive categories of qualitative 

results, howevcr, converts the actual numbers to 

only four gencral classes. The carrying capacity 

model is not a dcmographic model, nor is it an 

estimation of actual, expected popUlation sizcs 

of polar bears. It is a calculation only of 

possible carrying capacity and changes thercof, 

assuming no effects from anthropogenic 

stressors or environmental factors other than the 

losses of habitat forccasted by GCMs. 

Bayesian Network Population Stressor 

Model 

Our second method of forecasting thc status 

of polar bears in the 21'( century involved the 

development of a prototype Bayesian network 

(BN) model that accommodates thc potential 

effccts of multiple stressors on polar bear 

populations. Inputs to ollr BN model included 

various categorics of natural and anthropogenic 

stressors (Barrett 1981; Anderson et al. 2000), 

and key cnvironmental factors that affect polar 

bear popUlations. Anthropogenic stressors 

included various human activities that could 

affect the distribution or abundance of polar 

bears, such as harvest, pollution, oil and gas 

development. shipping. direct bear-human 

interactions. and others. Natural stressors on 
35 


82737.263

polar bears included changes in thc availability 

of primary and alternate prey and foraging 

areas, and occurrence of parasites, disease, and 

predation (Ramsay and Stirling 1984; Amstrup 

et al. 2006). Other key environmental factors 

included projected changes in total ice and 

optimal habitat, changes in thc distance that ice 

retreats from traditional autumn or winter 

foraging areas, and changes in the number of 

months per year that ice is absent in thc 

continental shelf regions. Collectively. the 

anthropogenic stressors, natural disturbances. 

and other key environmental factors were 

structured in a BN model in terms of how they 

affect polar bear demography and use of 

foraging areas, and ultimately, how they atTect 

polar bear distribution and abundance. 

Below, wc provide a general description of 

BN models and their usc in ecological 

applications. W c then describe how we 

developed the population strcssor model for 

polar bears, how results from the model were 

analyzed, how we analyzed the model results, 

and how we conducted sensitivity analyses. 

What are Bayesian network models? 

A Bayesian network is a graphical model 

that represents a set of variables that are linked 

by probabilities 1 (Neopolitan 2003; McCann et 

I In BNs, input nodes contain unconditional 

prior probabilities of their states. The states are 

assumed to be mutually exclusive and the 

probabilities sum to one. Prior probabilities are 

distributed as discontinuous Dirichlet functions 

in the form of D(x)~ lim limcos"(m!IIT), which is 

a multivariate, n-state generalization of the twostate Beta distribution with statc probabilities 

being continuous within [0, Ij, States S of output 

nodes contain posterior probabilities that are 

calculated conditional upon nodes Hthat 

directly affect them, using Bayes Theorem, as 

P(S' fi) P(III S)1'(S) (see Jensen 200 I and , P(H) 

Marcot 2006 for furthcr explanation of the 

statistical basis of BNs). 

al. 2006). BNs are comprised of variable nodes 

and their links, Nodes can represent correlates 

or causal variables that affect some outcome of 

interest, and the links define which specific 

variables directly affect which other specific 

variables. A BN defines a causal web with 

probabilistic links, whereby specifying the 

conditions of some variables can predict the 

outcome of some other variables. In this way, 

BNs constitute what are callcd influence 

diagrams (Marcot et al. 2006). BNs provide an 

efficient way to represent and summarize 

understanding of a system, and can combine 

expert knowledge and empirical data into the 

same modeling structure, Crafting a BN allows 

one to better undcrstand the relationships and 

sensitivities among the elements of the causal 

web, and to provide insights into the workings 

of the system that otherwise would not have 

been evident. 

Each node in a BN model typically is 

depicted with two or more mutually exclusive 

states. BN nodes can represent categorical, 

ordinal. or continuous variable states or constant 

(scalar) values, Each node typically has an 

associated probability table that describes either 

its prior (unconditional) probabilities of each 

state for input nodes, or its conditional 

probabilities of each state for nodes that directly 

depend on other nodes (see Marcot et al. 2006) 

for a description of the underlying statistics). 

ENs arc "solved" by specifying the values of 

input nodes and having the model calculate 

postcrior probabilities ofthe outcome node(s) 

through standard "Bayesian learning," which is 

the application of Bayes' theorem (Jensen 200 I; 

see a Iso footnote 1), 

Use of BayeSian networks in ecological 

modeling 

BNs are being increasingly used in 

ecological and natural resource modeling. 

Examples include use of BNs to model 

population viability of salmonid fishes (Lee and 

Rieman 1997), habitat restoration potential for 

rare wi Idlife species (Marcot et al. 200 I; 
36 


82737.264

Wisdom et a!. 2002), effects of habitat alteration 

on populations of native ungulates (McNay et 

a!. 2006), and many other applications (Marcot 

2007). BNs are useful for modeling systems 

where cmpirical data are lacking, but variable 

interactions and their uncertaintics can be 

depicted based on expert judgment (Das 2000). 

They are also particularly useful in efforts to 

synthesize large amounts of divergent 

quantitative and qualitativc information to 

answer "what it'· kinds of questions. Their 

ability to examine "what if' questions has led to 

insights regarding the prognosis for how global 

warming may impact coral reefs, and the degree 

to which local management actions may be able 

to offset some effects of rising temperatures 

(Wooldridgc and Done 2004; Wooldridge et ai. 

2005). 

Structuring the Bayesian network population 

stressor model for polar bears 

Developing a BN model entails depicting the 

"causal web" of interacting variables (nodes) in 

an influence diagram (that is, describing the 

general structure of the model). assigning states 

to each node, and assigning probabilities to each 

node that define the conditions undcr which 

each state would result. BNs can be built from a 

combination of empirical data and expert 

judgment, and can be built using commerciallyavailable modeling shells. We uscd the 

modeling shell Netica® (Norsys, Inc.), and 

followed guidelines for developing BN models 

developed by Jensen (200 I), Cain (200 I) and 

Marcot et ai. (2006). 

The BN model we developcd for polar bears 

depicted the potential population influenccs 

from mUltiple stressors and environmental 

conditions that were not captured in the simple 

carrying capacity model described earlier. Our 

BN stressor model was based on the knowledge 

of one polar bear expert (S. Amstrup) who 

established the model structure and probability 

tables according to expected influences among 

variables. B. Marcot served as a "knowledge 

engineer" or model engineer, and provided 

guidance to help structure the expert's 

knowledgc into an appropriate BN format. An 

initial list of ecological correlates was compiled 

by the expert, which were then organizcd into 

an influence diagram (Figure 4). Through 

discussion and questioning, the model engineer 

guided the expert through several stages to a 

final structure. The interactive sessions were 

useful in exploring altcrnative means of 

depicting influences among variables, ways to 

summarize influences into categories of 

numerical and distribution responses which 

could be useful to managers, and ways of 

representing some variables with proxies. 

The BN modcl structure was divided into 

three kinds of nodes: (I) input nodes that werc 

the anthropogenic stressor or environmental 

variables and used unconditional probabi lities to 

parameterize their states; (2) summary nodes 

that collected and summarized effects of 

multiple input nodes and used conditional 

probabilities to calculate their states; and (3) 

output nodes that represented numerical, 

distribution, and overall population responses to 

the suite of stressors and environmental 

conditions. Tbe output nodes used Bayesian 

learning to calculate posterior probabilities of 

their final outcome states. Summary nodes in 

the model served to "gathcr" and depict the joint 

influence of several inputs, and constituted what 

are sometimes called latent variables in the 

ecological modeling literature (e.g., Bollen 

1989). Including latent variable nodes in the BN 

model was also helpful in establishing 

probability tables in each node and for 

characterizing general categories of the input 

(stressor) nodes. We went through many 

iterations of the model structure to ensure that it 

responded to particular input conditions in ways 

that paralleled responses of polar bear 

popUlations which have been observed, or for 

which there are strong prevailing hypotheses in 

the biological community. 

The overall outcome of our BN model was a 

statement of the relative probabilities that the 
37 


82737.265

population in each ecoregion would be larger 

than now, same as now, smailer, rare, or extinct. 

The overall outcome was dctermined by nodes 

which summarized the likely numerical and 

distribution response of polar bears to projected 

changes in their environment. Responses of 

polar bears to projected habitat changes and 

other potential stressors could affect polar bear 

distribution or polar bear numbers 

independently in some cases, or they could 

affect both distribution and numbers 

simultaneously. Our approach allowed for 

independent or linked numerical and 

distributional responses. The factors influencing 

numerical and distribution responses were, in 

turn, further defined in terms of more specific 

human stressor, natural disturbance, or key 

environmental correlate variables (Figurc 5). 

Because our purpose was to inform the 

decision of whether to list polar bears as a 

threatened species, we designed the summary 

nodes in the BN model to include four of the 

five major listing factors used to determine a 

species' status according to the Endangered 

Species Act (U.S. Fish and Wildlifc Service 

2007). We included summary nodcs for Factor 

A-habitat threats; Factor B-overutilization; 

Factor C-disease and predation; and Factor 

E--{)ther natural or man-made factors. We did 

not include Factor D-inadequacy of existing 

regulatory mechanisms, because our model 

focused on ecosystem effects; however, 

regulatory aspects could be seamlessly added at 

a future time. Inclusion of these summary nodes 

recognized the listing factors as important 

potential stressors and also acknowledged the 

work done by the FWS during development of 

the proposal to list polar bears. Structuring the 

BN model in this way, therefore, helps assure 

its relevance to the listing process. This 

structure also anticipates that our BN stressor 

model could provide a foundation fl)r a decision 

model specific to Endangered Species Act 

listing criteria for this species. 

Parameterizing the Bayesian network model 

Model input nodes were parameterized with 

data on ice extent, length of time that icc was 

projected to be away from identified foraging 

areas, and the distance of ice retreat from such 

areas Crable 3). Other nodes incorporated 

qualitative descriptions of possible states of 

important environmental correlates. Because we 

were interested in forecasting changes from 

current conditions, states of each node were 

exprcssed categorically as "compared to now." 

That is, they could be in a condition similar to 

present, they could be in better condition than 

present, or they could be in worse condition. 

We set prior probabilities of all input nodes to 

uniform distributions (complete uncertainty), 

but before the model was run, we specified thc 

states that seemed most probable (Table 3). 

States of environmental correlatcs were 

established under each combination of time 

step, ecoregion, and GCM model outputs. Wc 

parameterized the conditional probability tables 

to assure that node structures were specified in 

accordance with available polar bear data or 

expert understanding of data. After initially 

populating and inspecting the conditional 

probability tables, we used three different 

methods to arrive at final values: I) sensitivity 

analyses of subparts of the model, 2) solving the 

model backwards by specifying outcome states 

and evaluating if the most likely input states 

tbat were returned were plausible according to 

what we know about polar bears now, and 3) 

running the model (and subparts) forward to 

ascel1ain if the summary and outcome nodes 

responded as expected given the states of the 

input nodes. These approaches constituted 

initial calibration of the model to the expert's 

knowledge about polar bears and bow polar 

bears are likely to respond to various 

circumstances. In sum, the goals of this firstgeneration BN model were to ensure that input 

conditions matched the current understanding of 

polar bear biology ecology and responses to 

observed changes, and that it responded to 

particular input conditions in ways that 
38 


82737.266

paralleled observed responses of polar bear 

popUlations. 

As fully specified, the BN model included 

probability tables for each node (Figure 5, 

Appendix 2,3). The BN model ultimately 

consisted of 38 nodes, 44 links, and 1,667 

conditional probability values specified by the 

modelers. The model was solved for each 

combination of 4 ecoregions, 5 time periods, 

and 3 future GeM scenarios (ensemble mean, 

maximum, and minimum). Specifically, for 

each ecoregion and time period, the three future 

GeM scenarios were: 1) results projected by the 

ensemble mean of all 10 GeMs; 2) results 

projected by the GeM that forecasted the 

greatest retention of sea ice; and 3) results 

projected by the GeM that forecasted the lowest 

retention of sea ice. Only one data source (the 

observed record of sea ice) was examined for 

the historic (1985-1995) and current (1996-

2006) time periods. In total, we examined 44 

unique combinations. We evaluated correlations 

among input nodes and between input and 

output nodes, to assure that eolinearity among 

inputs was not unduly affecting outcome states. 

The input data to run each combination were 

specified by summarizing the respective GCMderived habitat variables, and by best 

professional judgment of polar bear expert S. 

Amstrup (Table 3). Because BN models 

combine expert judgment and interpretation 

with quantitative and qualitative empirical 

information, inputs from mUltiple experts arc 

usually incorporated into the structure and 

parameterization of a "final" model. Due to time 

constraints, however, we were not able to seek 

and incorporate the input of multiple polar bear 

experts. Therefore, the model presented here 

should be viewed as a first-generation 

prototype. The model will be refined through 

formally developed processes (see Discussion) 

at a future time. 

Bayesian network model output states 

Principal results ofthe BN model are levels 

of relative probabilities for the potential states at 

outcome nodes. In the polar bear BN population 

stressor model, outcomes of greatest interest 

were 1) those related to listing factors used by 

the FWS, 2) the distribution responses, 3) 

numerical responses, and 4) the overall 

population response. We evaluated the BN 

outcomes in terms ofthe most probable 

outcome at each of the time steps, and the 

dispersion of probabilities among all outcomes. 

Probabilities are presented for each ecoregion 

and for each of the GeM scenarios we 

examined. We assessed results from the BN 

model in the statistical software package 

SYSTAT 11 (SYSTA T 2004). 

We defined our principal outcome nodes 

(shown in Figure 5) and their possible states as 

follows: 

Node C4: Numerical Response 

This node represents the anticipated 

numerical response of polar bears in an 

ecoregion based upon the sum total of the 

identified factors which are likely to have 

affected numbers of polar bears in any 

particular area. Such factors include net 

reproduction as affected by icc habitat 

conditions. and influences of disease, predation, 

intentional' takes, and human disturbances and 

stressors. Numerical response outcome states 

were defined as follows: 

increased density = polar bear density 

greater than that at Year 0 (year 2000); the 

density level could be determined 

empirically to be significantly greater than 

that at Year 0; density can be expressed in 

terms of number of polar bears per unit area 

of optimal habitat (thus expressing 

"ecological density") or of total (optimal 

plus suboptimal) habitat (thus expressing 

"crude density"); 
39 


82737.267

same as now ~ polar bear density as above 

but equivalent to the density at Year 0; the 

density level could bc determined 

empirically to not be different from that at 

Year 0; 

• reduced density ~ polar bear density less 

than that at Year 0 (year 2000) but greater 

than one-half ofthe density at Year 0; the 

density level could be determined 

empirically to be significantly less than that 

at Year 0 and also significantly greater than 

one-half of the density at Year 0; 

rarc polar bear density less than half of 

that at Y car 0 (year 2000); the density level 

could be determined empirically to be 

significantly less than that one-half that at 

Year 0; 

• absent ~ polar bears are not demonstrably 

present; polar bear density is not 

significantly different than zero. 

Node C3: Distribution Response 

This is the sum total of ccological and human 

factors that predict the future distribution of 

polar bears in the ecoregion. Distribution refers 

here to the functional response of polar bears 

(viz., movement and spatial redistribution of 

bears) to conditions of ice habitat quantity. 

quality, and temporal distribution; availability 

of prey and foraging areas; and human 

disturbances and stressors. Distribution 

response outcome states were defined as 

follows: 

same as now ~ polar bear distribution 

equivalent to that at Year 0; distribution 

could be determ ined empirically to not be 

different from that at Year 0; 

reduced but resident = a condition in which 

habitat or prey availability have changed in 

a way that would likely lead to a 

significantly reduced spatial distribution 

(e.g. due to avoidance of a human 

development, or sea ice is still present in the 

area but in more limited quantity). Bears 

would still occur in the area. but their spatial 

distribution would be more limited than at 

Year 0; 

transient visitors ~ a condition in which 

habitat or prey availability are seasonally 

limited or human activities have resulted in 

a situation where available ice is precluded 

from use by polar bears on a seasonal basis; 

• extirpated ~ a condition in which habitat or 

prey availability have declined and human 

stressors have increased in such a way as to 

render the area essentially unusable by polar 

bears, and have lead to a complete or 

effective deaJ1h of polar bears in the area. 

Node 01: Overall Population Outcome 

Overall popUlation outcome refers to the 

collective influence of both numerical response 

and distribution response. It incorporates the 

full suite of effects trom all anthropogenic 

strcssors, natural disturbances, and 

environmental conditions on thc expected 

occurrence and levels of polar bear populations 

in the ecoregion. Overall population outcome 

states were defined as follows: 

• larger polar bear populations have a 

numerical response greater than at present 

(Year 0) and a distribution response at least 

the same as at present (that is, able to use 

available habitat, to relocate ifpossible and 

needed, and to withstand anthropogenic 

stressors); 

same as now ~ polar bear populations have 

a numerical response essentially the same as 

at present (Year 0) and a distribution 

response at least the same as at present; 

smaller polar bear popUlations have a 

reduced density and a distribution response 

the same as at present or reduced but 

resident; or havc a density same as at 

present but occur as reduced but resident or 

transient visitors; 
40 


82737.268

rare polar bears are numerically rare and 

have a distribution response same as at 

present, or occur as reduced but resident or 

transient visitors; or have a reduced density 

and occur as transient visitors; 

• extinct = polar bears are numerically absent 

or clistributionally extirpated. 

Here, the "extinct" state refers to conditions 

of: (1) complete absence of the species (N=O) 

from an ecoregion; or (2) numbers and 

distributions below a "quasi-extinction" level, 

that refers to a non-zero population level at or 

below which the population is ncar cxtinction 

(Ginzburg et al. 1982; Otway et al. 2004); or (3) 

functional extinction, that refers to being so 

scarce as to be near extinction and contributing 

negligibly to ecosystem processes (Sekercioglu 

et al. 2004; McConkey and Drake 2006). 

Our final BN model was structured to makc 

maximum use of thc data and GCM outcomcs 

describing observed and projectcd changes in 

the sea ice. Knowledge of polar bears. their 

dependence on sea icc, and the ways in which 

sea icc changes have been obscrved to affect 

polar bcars, were used to populate the 

conditional probability tables. The BN model 

also incorporatcd professional judgment 

regarding how othcr ccological and human 

factors may change if sea icc changes occur as 

projccted. Bccause our prototype model was 

paramcterized by the best professional judgment 

of only one polar bear expert, it is reasonable to 

ask how robust the results might be to input 

probabilities which could vary among othcr 

experts. It also is appropriate to ask whether it is 

likely that future sea ice change, to which model 

outcomes are very sensitive, could fall into 

ranges that would result in qualitatively 

different outcomes than our BN model projects. 

Finally, it is appropriate to ask the extent to 

which model outcomes may be altered by active 

management of the states of nodes which 

represent variables which are under human 

control. 

We addressed questions about the ability of 

changes in human activities to alter the BN 

output states by fixing inputs which humans 

could control and examining differences in the 

overall outcomes. We evaluated the extent to 

which sea ice projections would have to differ 

to make qualitative differences in outcomes by 

holding all non-ice variables at uniform priors 

and allowing ice variables only to vary at future 

time steps. Comparing those results to the range 

of ice conditions available from GCMs provides 

a sense of just how much the realized future ice 

conditions would have to change from those 

projected to make a difference in population 

outcomes. Finally. although we cannot second 

guess how other polar bear experts may 

recommend parameterizing and structuring the 

model, comparison of model runs with presct 

values providcs some sense of how much 

differently the model would have to be 

parameterized to project patterns qualitatively 

different than those we observed. 

Aftcr the BN population stressor model was 

finalized, we ran overall sensitivity analyses to 

dctcrmine the degrce to which each input and 

summary variable intlueneed the population 

outcome variables. We used results of 

sensitivity analysis to determine the potential 

effect of cach stressor variable on the 

anticipated polar bear numerical response, 

distribution response, and overall population 

outcome. 

For discrete and categorical variables, 

sensitivity was calculated in the modeling shell 

Nctica as the dcgree of entropy reduction 

(reduction in the disorder or variation) at one 

node relativc to the information rcpresented in 

other nodes of the model. That is, the sensitivity 

tests indicate how much of the variation in the 

node in question, is explained by each of the 

other nodes eonsidcred. That is. "node X 

explains this much ofthe variation in node Y." 

[See chapter 2 in Burnham and Anderson 

(1998) for a summary discussion of the entropy 

concept.] The degree of entropy reduction, I, is 

the expected reduction in mutual information of 
41 


82737.269

an output variable Q with q states due to a 

finding of an input variable F with f states. For 

discrete variables, I is measured in terms of 

information bits and is calculated as: 

I H(q) - H(Q I P) I: I: P(q,J) log,IP(q,J)] 

q! P(q)P(f) 

where H(Q) is the entropy of Q before new 

findings are applied to input node P, and 

H(QIP) is the entropy of Q after new findings 

are applied to P. In Netica, entropy reduction is 

also termed mutual information. 

For continuous variables, sensitivity is 

calculated as variance reduction VR, which is 

the expected reduction in variation, V(Q), of the 

expected real value of the output variable Q due 

to the value of input variable F, and is 

calculated as 

VR = V(Q) - V(Q I P), 

where 

V(Q) = I: q P(q)[Xq - E(Q)]' , 

V(Q I P) '" P(q I niX E(Q I f)]', 0 q q 

and 

and where Xq is the numeric real value 

corresponding to state q, E(Q] is the expected 

real value of Q before new findings are applied, 

E(QIF) is the expected real value or Q after new 

findings! are applied to F, and V(Q) is the 

variance in the real value of Q before any new 

findings (Marcot et al. 2006) 

The greater the values of lor VR, the greater 

is the influence of input variable F on output 

variable Q. In this way, we were able to assign 

an order to the potential influence of each input 

and summary node on the popUlation outcome 

nodes, and thereby describe the overall 

sensitivity structure of the model. 

Results 

In this section we tirst present the projection 

of carrying capacities for polar bears in each 

ecoregion based on a presumed linear 

relationship between sea ice extent and polar 

bear numbers. That projection, which does not 

include seasonal changes in the sea ice, or other 

factors which could be popUlation stressors, 

provides an upper bound on polar bear 

populations that could be supported by sea ice 

habitat available in the future. We next present 

projections based on the BN population stressor 

model. Because it incorporated many of the 

factors not included in the projection of carrying 

capacity, it provides a more thorough 

assessment of the future of polar bears in each 

ecoregion. 

Forecasted 21st Century Polar Bear 

Carrying Capacity 

Habitat area and change 

Total habitat area, expressed as the annual 

sum of km2 -months of sea ice extent, was 

projected by the GCM models to be reduced 

(Figure 3) from present-day conditions, at each 

time step in each ecoregion and for all 

ecoregions combined (global). Proportional 

declines in available total babitat ranged from 

relatively modest (less than 15% decline from 

present) at year 45 in the Seasonal Ice 

Ecoregion, to large (more than 47% decline) by 

year 100 in the Polar Basin Divergent 

Ecoregion (Table 4, Figures 6, 7). For all 

combinations of time steps, GeM runs, and 

ecoregions, both total and optimal habitat were 

projected to be less abundant than present 

amounts (Table 4, Figures 6, 7). Globally, 

projected habitat declines were 24%, 18%, and 

15% for the minimum, mean, and maximum 

GCM model inputs, respectively, by year 45. 

Equivalent global values at year 100 were 40%, 

32%, and 23% for minimum, mean, and 

maximum ice projections, respectively. Using 

the satellite observed sea ice record, total habitat 
42 


82737.270

area during the previous decade (year -I 0) 

varied among ecoregions and was bctween 3% 

and 17% more abundant than at present. 

Globally, total habitat in thc last decade was 7% 

more abundant than it is now (Figures 6, 7). 

Polar bear carrying capacity 

Current estimated polar bear densities ranged 

from a high of 0.923* 1 oj km2 -months per bear 

in the Polar Basin Convergent Ecoregion, to a 

low of 7.695* I 0.1 km2

-months per bear in the 

non-optimal portion of the Polar Basin 

Divergent Ecorcgion (Table 5). Estimates of 

polar bear carrying capacity (K,.G) based upon 

these densities, as well as percent change in 

carrying capacity from present (eK,.G). and 

carrying capacity normalized to present 

(K:'~""). are presented in Table 6, and Figures 8 

and 9. As with total habitat, total historical 

carrying capacity (year -I 0) ranged from 3 to 

17% grcater than at present in the Archipelago 

and Seasonal Ice Eeoregions, respcctively. and 

8% globally (Figure 9). 

In the Seasonal fce Ecoregion, we projected 

total carrying capacity to declinc 7-10% from 

present levels by year 45,21-32% by year 75, 

and 22-32% by year 100 (ranges of percentages 

depending on habitat amount predicted by the 

GCM maximum and GCM minimum results. 

respectively; Table 6, Figures 8, 9). In the 

Archipelago Ecoregion, we projected total 

carrying capacity to declinc 3-14% from present 

levels by year 45, 18-21 % by year 75. and 21-

24% by year 100. In thc Polar Basin Divergent 

Ecorcgion. total carrying capacity dropped 19-

35% from present levels by year 45. 29-43% by 

year 75, and 23-48% by year 100. In thc Polar 

Basin Convergent Ecoregion, total carrying 

capacity ranged from -24% to +4% of present 

levcls by year 45, and dropped 8-28% by year 

75. and 3-3 I % by year 100. 

F or the two polar basin ccoregions, model 

data also were available on amount of optimal 

habitat and carrying capacity within optimal 

habitat (Tables 2,4; Figs. 7,8). In the Polar 

Basin Divergent Ecoregion, we projected 

carrying capacity of optimal habitat to drop 17-

36% at year 45,31-45% at ycar 75, and 21-49% 

at year 100, again because of relatively greatcr 

loss of optimal habitat. Convcrsely, the Polar 

Basin Convergent Ecoregion appeared to 

largely maintain non-optimal habitat, although 

there was considerable variation among models 

and time periods. The increasing proportion of 

non-optimal habitat along with corresponding 

increase in its carrying capacity (by as much as 

49% by year 45 under the GCM maximum 

scenario), howcver, was insufficient to prevent 

overall declines in total carrying capacity, in 

most modcl runs. This was caused by strong 

declines in the carrying capacity of optimal 

habitat in latter years of the projections. 

Nonctheless, projected habitat losscs in the 

Polar Basin Convergent Ecoregion were more 

modest and morc variable among all model runs 

than in the Polar Basin Divergent Ecoregion. 

The optimal habitat-based carrying capacity 

showed dcclines ranging up to 31 % loss by year 

100, with no gains in any time period. In all 

ecoregions, trends consistently suggestcd 

moderate to large decreases in total carrying 

capacity by year 75, and moderate decreases in 

all ecoregions beginning in year 45. Globally, 

total carrying capacity across all ecoregions was 

projected to drop 10-22% from present levels by 

year 45,22-32% from present levels by year 75. 

and 20-37% from present Icvels by ycar 100 

(Figure 9). 

Overall, total carrying capacity was projected 

to decrease at all time steps wc examined in the 

21 st century. Models which projccted minimal 

ice extcnt projected trends toward extirpation of 

bears from the Polar Basin Divergent Ecoregion 

by ycar 45 and from the Seasonal Ecoregion by 

year 75. Under ensemble mean ice conditions, 

we projected likely extirpation of bears in the 

Polar Basin Divergent Ecoregion by year 75 and 

in the Polar Basin Convergcnt Ecoregion by 

year 100 (Table 7). 
43 


82737.271

Bayesian Network Model Forecast of 

the 21st Century Status of Polar 

Bears 

Overall outcomes projected by our BN 

model which included the considcration of 

population stressors in addition to sea ice area 

effects were ranked according to rclative 

probability in Tablc 8. In all but the 

Archipelago Ecoregion, the dominant outcomc 

state was "extinct" at all future time periods 

(Figure 10). Probabilities ofthc "extinct" statc 

for future time periods varied from a low of 8% 

in the Archipelago Ecoregion at year 45 undcr 

the GCM maximum scenario, to a high of87% 

in the Polar Basin Divergent Ecoregion at year 

45 under the GCM minimum ice scenario 

(Table 8, Figure 11). 

In the Archipelago Ecoregion. a smallcr 

population was the dominant outcome at year 

45 undcr all GCM scenarios, and at year 75 

only for the GCM maximum scenario. Even in 

the Archipelago Ecorcgion, "extinct" was 

sometimes the dominant outcome for other 

combinations of time periods and GCM 

modeling sccnarios (Figure 10). 

[n the Seasonal and Polar Basin Divergent 

ecoregions, "extinct" was by far the most 

dominant outcome with very low probabilities 

forecast for all other outcome states in all time 

pcriods. The low probability afforded to 

outcome states other than extinct suggested a 

clear trend in these ecoregions toward probable 

extirpation by mid century. At year 45 in the 

Polar Basin Convergent Ecoregion, and at all 

future time steps in the Archipelago Ecoregion, 

considerable probability fell into outcome states 

other than extinct (Figure 10). Even when 

extinct was the most probable outcome, other 

outcomes sometimes had large non-zero 

probabilities. 

The general trends of the overall population 

outcome (node 0 I) from the BN model (Table 

8. Figure 10 and 11) can be viewed as follows. 

In each ecoregion, the polar bear population was 

very likely larger or at least incurred a far lower 

likelihood of multiple stressors in the past than 

compared to present. In the future, however, 

multiple strcssors will likely play important and 

deleterious roles on all polar bear populations, 

even starting at year 45, and generally increase 

in their effect through ycar 100. Effects of 

multiple stressors appear to have a composite 

influence on thc overall populations at more or 

less the same intensities regardless of the GCM 

modeling scenario (Table 8). 

When the overall population outcome is 

broken down into its component influences, 

some fWiher diffcrences among ecoregions, 

time steps, and GCM modeling scenarios 

become apparent. For instance, there seems to 

be a greater adverse influence from future 

conditions on polar bear distribution response 

(node C3) than on polar bear numerical 

response (node C4) (Table 9). In part this is 

bccausc of salient adverse future outcomes of 

habitat threats (node F2; Table 10) and foraging 

habitat distribution, especially in the Seasonal 

and Polar Basin Divergent ecoregions (Table 

II). The BN model also represents worsening 

future conditions of natural disturbances 

including disease and predation (Table 12) and 

overall adverse inlluences on reproduction and 

vital rates (Table 13). 

Sensitivity Structure of the Bayesian 

Network Population Stressor Model 

We conducted 10 tests on the BN population 

stressor model to determine its sensitivity 

structure (Appcndix I). In general, the BN 

model seemed well balanced in terms of its 

underlying probability tables, in that sensitivity 

of the tinal outcome variable (node 01, overall 

popu lation outcome) was distributed among all 

arms of the model. In other words, no single 

input variable or small clique of input variables 

unduly dominated the overall population 

outcome (sec Appendix I, sensitivity test I). 

Some 91 % of the variation in overall 

population outcome (node Dl) was explained 

by the top six variables (Appendix I, Figure 

12). Four of those top six variables were sea ice 
44 


82737.272

related, including our quantitative data on 

spatiotemporal change, The ecoregion of 

consideration and the level of intentional takes 

rounded-out the top six variables with influence 

on overall population outcome, In essence, 

ecoregion also is a habitat variable because 

ecoregions were specified on the basis of their 

differences in sea ice, In that context, 5 of the 

top six variables explaining variation in overall 

outcome related to the nature of the sea ice, 

The primary importance of sea ice change 

and lesser but complementary importance of 

anthropogenic stressors carried through to 

determinations of which FWS listing factors 

explained the most variation in overall outcome, 

Relative to the FWS listing factors, overall 

population outcome was by far most influenced 

by stressors related to Factor A (habitat threats), 

Influences from Factor B (overutilization), 

Factor E (other natural or man-made factors), 

and Factor C (disease and predation) provided 

progressively less influence (Appendix I, 

sensitivity test 2), 

Subsections of the BN model ("sub mod cis") 

also were tested for sensitivity (Appendix I. 

sensitivity tests 5-10), Notable among these 

tests was that foraging habitat value (node A, a 

composite "Iatent variable" created to 

summarize effects of several key environmental 

factors), was most sensitive to foraging habitat 

character, which is a subjective assessment of 

the quality of sea ice used for foraging by polar 

bears (Appendix I, sensitivity test 8), Foraging 

habitat character (node S 1) was included in the 

ON model to reflect observations that recent 

changes in the sea ice have included increased 

roughness and rafting among ice floes that arc 

thought to reduce foraging effectiveness of 

polar bears (Stirling ct aL 2008). 

Discussion 

We begin this section with a discussion of 

uncertainty as it pertains to our objectives and 

our outcomes. We follow a treatment of general 

uncertainty with a discussion of our carrying 

capacity model outcomes. Then, we describe 

the state of development in our ON polar bear 

population stressor model. That description 

includes identification of caveats regarding the 

current stage of development of the model and 

next steps necessary to address those caveats. 

Finally, we assess the BN model outcomes with 

regard to existing knowledge about polar bears 

and with respect to observed and projected 

changes in their sea ice habitats on which they 

depend, 

Types and Implications of 

Uncertainty 

Analyses in this report contain three main 

categories of uncertainty: (I) uncertainty in our 

understandings of the biological, ecological, and 

climatological systems; (2) uncertainty in the 

representation of those understandings in 

models and statistical descriptions; and (3) 

uncertainty in model predictions, 

First, uncertainty in our understanding of 

complex ecosystems is virtually inevitable, 

particularly for one as extensive and remote as 

the circumpolar Arctic, We have however, 

incorporated a broad sweep of knowledge 

regarding polar bears and their environment 

which is available from published literature, 

from other reports informing the listing process, 

and from expert interpretations of that available 

information, 

How to best represent our understanding of 

the system in models can be structured in 

various ways, In this report, we captured and 

represented expert understanding of polar bear 

habitats and populations in a manner that can be 

reviewed, tested, verified, calibrated, and 
45 


82737.273

amended as appropriate. We have attempted to 

open the "black box" so to speak, and fully 

expose all formulas and probabilities used in the 

polar bear carrying capacity and the EN 

popUlation stressor models. We also used 

sensitivity testing to help convey thc rcliability 

of EN model depictions (Johnson and 

Gillingham 2004) (Appendix I). After BN 

models of this type are modified through pccr 

review, or revised with knowledge from more 

than one expert, any variation in resulting 

models can represent the divergence (or 

convergence) of expertise and judgment among 

mUltiple specialists. 

Also included in the second category of 

uncertainty are uncertainties associatcd with 

statistical estimation of parameters such as the 

extent of sea ice or size of polar bear 

populations. Statistical cstimation typically 

includes systematic measurement error and 

random error, for example, as partitioned in 

general linear models and as may arise in 

classification functions such as assigning 

categories to map areas. In this case, we have 

minimal opportunity to address these estimation 

errors. The sea ice parameters we used in our 

polar bear models were derived from GeM 

outputs, which possess their own wide margins 

of uncertainty (DeWeaver 2007). Hence, the 

magnitude and distribution of errors associated 

with our sea ice parameters were unknown. 

To compensate for thcse unknowns, we 

accommodated a broad range of sea ice 

uncertainties by analyzing the IO-member 

cnsemble GeM mean, as well as the minimum 

and maximum GeM ice forecasts. In the case of 

polar bear popUlation estimates, many arc 

known so poorly that the best we have are 

cducated guesses. Pooling subpopulations 

where numbers are merely gucsses, with those 

where precise cstimatcs are available, to gain a 

range-wide perspective prevents meaningful 

specific calculation and incorporation of error 

terms. We recognize that difficulty, but because 

our projections are expressed in the context of a 

comparison to present conditions. we largely 

avoid the issue. That is, whatever the population 

size is now, the future size is expressed relative 

to that and all errors are carried forward. 

The third category of uncertainty pertains to 

modcl predictions. Predictions from models of 

spccies abundance and distribution can be 

subject to at least three sources of error: error 

due to spatial autocorrelation, dispersal and 

movement of organisms, and biotic and 

environmental interactions (Guisan et a!. 2006). 

We addressed these error sources in the 

following ways. The estimates of ice habitat 

area were derived separately for each ecoregion 

from the GeM models bccause the ccoregions 

behave independently in terms of sea ice 

advection. The EN population stressor model 

accounted explicitly for potential movement of 

polar bears (e.g., use of alternative foraging 

areas) and for biotic and environmental 

interactions (as exprcssed in the conditional 

probability tables; see Appendix 3). 

Deterministic models, such as the 

spreadsheet carrying capacity model, present 

calculations and predictions essentially as point 

values with no variance or error. In the absence 

of empirical measures of variation, one could 

presume a Gaussian error distribution around 

such calculated predictions. However, in our 

polar bear carrying capacity model there was no 

means of determining the magnitude of that 

error (nor did we have empirical estimates of 

variation surrounding polar bear popUlation 

sizes by eeoregion). Hence, we did not attempt 

to estimate error levels for the carrying capacity 

calculations, although we acknowledge there is 

uncertainty surrounding those values. 

Probabilistic or stochastic models, such as 

the EN population stressor model, can 

inherently display results as probabilities of 

various states or potential outcomes. The spread 

and magnitude of probability values across the 

outcome states in the BN model renect the 

combination of uncertainties in statcs across all 

other variables, as reflected in each of their 

conditional probability tables. More 

sophislicatcd means of estimating variance of 
46 


82737.274

the probabilities of outcome slales can also be 

undertaken (e.g. calculating their standard 

deviation and standard error from bootstrapping 

random subsets of the input values (Guisan and 

Zimmermann 2000) or from random subsets of 

simulated output cases). These additional steps 

arc laborious, however, and better undertaken 

after the BN model has been through additional 

peer review and established as at least a beta 

level model (see below). 

The spread of probabilities among the BN 

outcome states is itself an expression of 

uncertainty and important information for the 

decision-maker who may wish to weigh 

alternative outcomes in a risk assessment. When 

predictions result in high probability of one 

population outcome state and low to zero 

probabilities of all other states, there is low 

overall uncertainty of predicted results, 

presuming that the other categories of 

uncertainty (in our understanding of the system 

and our representation of that understanding in 

the modeling) are taken into account. In some 

cases, however, the BN model predicts nearly 

equivalent probabilities of more than one 

population outcome state. In these cases, 

uncertainty of the outcomes is greater, and the 

decision-maker may wish to weigh the 

probabilities according to his or her risk attitudc 

and decision criteria. 

Finally, model uncertainty also entails 

addressing model credibility, acceptability, and 

appropriatencss of the model structure. We 

made every effort to ensure that the model 

structure was appropriate and credible, and that 

the inputs were parameterized according to best 

available knowledge on polar bears and their 

environment. We have explored the logic and 

structure of our BN model through sensitivity 

analyses, running the model backwards from 

particular states to sec if it returns us to the 

appropriate starting point, and performing 

particular "what if' experiments (e.g., by fixing 

values in some nodes and watching how values 

at other nodes respond). We are as confident as 

we can be at this point in model development 

that the model is performing correctly and 

providing outcomes that can be useful in 

qualitatively forecasting the potential future 

status of polar bears. Because the model has 

been structured and parameterized by only one 

polar bear expert, however, there are additional 

criteria of model validation that must be 

addressed through subsequent peer review and 

model revision (Mareot et al. 1983; Marcot 

1990, 2006). 

Forecasted 21 st Century Polar Bear 

Carrying Capacity 

All 10 of the GCMs we analyzed project a 

downward trend in sea icc extent in the 21 st 

century (De Weaver 2007). Those dcelines are 

paralleled by projected declines in both total 

and optimal polar bear habitat at all time steps 

(Figure 3, Durner et al. 2007). The wide range 

of outcomes in each region and time period 

represents the spread of values from the GCM 

model runs, even when normalized to presentday conditions. Despite the range of outcomes, 

however, deelines in available polar bear habitat 

translate to lower carrying capacity for polar 

bears in all ecoregions at all future time steps 

(Figures 8, 9). 

Our projected rates of decline in habitat and 

polar bear carrying capacity are generally 

slower than rates that have actually been 

observed during the past two decades. This is 

most notable in the Seasonal Icc Ecoregion 

where the rate of sea ice decline has been 

among the most profound of any in the Arctic 

(Meier et al. 2007). Yet, data derived from 

GCM forecasts appeared to suggest slow rates 

of future declines in the Seasonal Eeoregion 

(Figures 7, 9). This inconsistency in the 

Seasonal Eeoregion is apparently caused, at 

least in part, by some GCM projections that 

consistently put large amounts of sea ice over 

the continental shelf habitats in Davis Strait and 

Baffin Bay. Whereas the analyses ofGCM 

outputs suggest decreases of 15-45% in sea ice 

coYer in Hudson Bay through the next century. 

the same models forecast more ice remaining 
47 


82737.275

over the continental shelves of Davis Strait than 

was actually observed in that region between 

1996 and 2006. Similarly. GCMs predict only a 

7% decrease of sea ice in Baffin Bay by 2100. 

In contrast, satellite observations verify that 

Baffin Bay sea ice extent declined over 10% 

between the 1985-1995 period and the 1996-

2006 period. Between those same periods the 

sea ice extent over the continental shelves of 

Davis Strait declined 51 %. 

The rapid rate of observed ice loss in the 

Seasonal Ice Ecoregion suggests that modeled 

persistence of ice there in the future is probably 

not realistic. This concept is corroborated by 

observations that show this ecoregion has seen 

as much warming as almost any other location 

in the Arctic (Comiso and Parkinson 2004). If 

anything, sea ice declines in the Seasonal Ice 

Ecoregion are likely to be hastened in the future 

if temperatures continue to increase (Stirling 

and Parkinson 2006). Therefore, our projected 

gradual declines in polar bear carrying capacity 

in the Seasonal Ice Ecoregion are probably 

optimistic and biased on the high side. 

In most other regions, the differences 

between observed and projected ice loss arc 

smalicr, but still variable. For example. the 

Polar Basin Divergent Ecoregion has seen a 

4.5% loss in total habitat during the 

observational period. The ensemble mean 

forecast for ice loss in the ecoregion is 9% 

during the next 50 years and 26% by the end of 

the century. In contrast, individuallUCN 

subpopulation areas within the Polar Basin 

Divergent Eeoregion were forecast to have up to 

95% decline in iee habitat. Nonetheless, the 

range of values in our projections appears to 

capturc a general trend of large ice losses, large 

losses of optimal habitat, and large losses of 

carrying capacity for polar bears in the Polar 

Basin Divergent Ecoregion. 

In contrast to the Seasonal and Polar Basin 

Divergent Ecoregions, we forecast more modest 

changes in habitat and polar bear carrying 

capacity for the Archipelago and Polar Basin 

Convergent Ecoregions. These more modest 

habitat losses appear consistent with modest 

losses during the observational period and with 

the forecasted changes in the individuallUCN 

subpopulation areas. These results parallel 

recent sea ice observations that show minimal 

decl ines in these ecoregions (Meier et a1. 2007). 

Although thc pattern of projected carrying 

capacity varied greatly among regions. the 

bottom line was for an overall range-wide 

decline in polar bear carrying capacity of 

bctween 10% and 22% by year 45 and between 

20% and 37% by year 100 (Table 6, Figure 9). 

The carrying capacity model forecasted that 

polar bears could be extirpated from the Polar 

Basin Divergent Ecoregion as early as year 45. 

Projections from this modeling approach are 

deterministic projections based on current 

estimated densities of polar bears. They depend 

upon the extent of the sea ice and optimal sea 

ice habitat only and do not account for possible 

changes in rclative carrying capacity as the 

amount of ice changes. For example. if thinner 

ice for shorter periods of time rcsults in more 

insolation penetrating thc water column and 

greater productivity of the remaining ice habitat, 

carrying capacity per unit area may rise. If on 

the other hand. declines in the areal extent of the 

undcr icc (cpantic) community, which currently 

provides much of the productivity in Arctic seas 

(Sakshaug 2004) is not compensated by benefits 

of increased insolation, carrying capacity could 

decline. More open water in summer means 

more new ice forming in winter, which could 

increase brine expulsion (Fisher et al. 2006) 

with a variety of potential effccts on cpontic 

productivity. Even if overall productivity 

increases, if the character of the sca ice is 

dramatically different, polar bears may be illsuited to foragc thcre. The carrying capacity 

model cannot accommodate such scenarios, nor 

can it account for adverse effects of stressors 

other than changes in sea ice extent. 

Just as the carrying capacity model cannot 

capture possible changes in marine productivity, 

it also cannot capture the importance of 

scasonal variation in sea ice. Durner et al. 
48 


82737.276

(2007) illustrated that although the annual trend 

in km2-months of optimal habitat is useful for 

comparing large scale patterns, it overlooks the 

importance of seasonal variation. Whereas the 

GCM ensemble forecasts a polar basin-wide 

decline of 36% in annually available optimal 

habitat, it suggests declines of nearly 80% 

during summer (Figure 13). This reflects the 

fact that all GCMs forecast sea ice will continue 

to cover the whole polar basin during the winter 

through most of the 21 st century. So, the 

realized future changes in ice habitats are 

seasonally dependent. This is important 

because seasonal fluctuations in sea ice cover 

include changes in the location of sea ice as 

well as its total quantity. 

Among the most substantive spatial changes 

is the retreat of icc from the continental shelves 

of the polar basin (Comiso 2002; Rigor and 

Wallacc 2004; Belchansky ct at. 2005; Holland 

et al. 2006; Ourner et at. 2007; Ogi and Wallace 

2007; Scrreze et at. 2007). Hence, not only is 

the sea ice declining in this region on an annual 

basis, there will bc little or no ice in the region 

at all in summer. The continental shelves of the 

polar basin are far more productive than the 

deep polar basin regions offshore (Pomeroy 

1997; Sakshaug 2004). Observations show that 

polar bears spend most of their time foraging on 

sea-ice over shallow water «300m deep) 

(Amstrup et at. 2000, 2004a; Ourner et al. 

20(7), where it is thought that they hunt most 

effectively (Stirling et al. 1981; Stirling 1997). 

Seasonal absence of sea ice from the shelf 

regions of the polar basin, therefore, can be 

expected to have a greater effect on foraging 

than the annual changes in sea ice quantity 

might suggest. 

The length of time that ice is absent from 

important foraging areas is another variable that 

our carrying capacity model cannot 

accommodate. Polar bears are well adapted to 

survive periods of food deprivation. Those 

adaptations that have allowed them to 

successfully exploit the Seasonal Ice ecoregion 

(Watts and Hansen 1987). There. marine 

productivity is high enough that polar bears can 

gain sufficient mass before the ice melts to 

sustain a long summer and autumn fast. 

The polar basin, in contrast to most of the 

seasonal ice regions, is relatively low in 

productivity (Sakshaug 2004). Whereas polar 

bears in the Seasonal Ecoregion reach peak 

body weights before the icc melts in summer; 

polar bears in the polar basin do not reach peak 

body weight until late autumn or early winter 

(Ourner and Amstrup 1996). This suggests they 

have a different temporal pattern of weight gain 

to compensate for the relatively low 

productivity of the polar basin seas. Polar bears 

in the polar basin simply need more time to 

reach the weight necessary to survive the 

winter. Another indication of the low 

productivity, with which polar bears contend in 

the polar basin, is the observation that polar 

bears in the polar basin reach sexual maturity 

later in life than they do in other portions of 

their range. In the polar basin, polar bears 

producc their first young at age six. This is in 

contrast to much of the Canadian Arctic where 

they breed for the first time at age 4 and 

produce their first cubs at 5 years of age 

(Stirling et at. 1977, 1980, 1984; Ramsay and 

Stirling 1982. 1988; Furnell and Schweinsburg 

1984; Amstrup 2003). Polar basin bears, 

therefore, may not be able to accommodate 

extended seasonal absence of sea icc from their 

preferred toraging habitats. Indeed, recent 

analyses suggest that the length of time that ice 

is absent from continental shelf foraging areas 

may be related to certain measures of physical 

stature and cub survival (Rode et at. 2007) as 

well as a predictor of survival (Hunter et at. 

2007; Regehr et al. 2007a) in polar bears of the 

Beaufort Sea. 

As noted earlier, most GCMs project that ice 

will return to much orthe Arctic in winter, even 

late in the century. This fact is reflected in the 

relatively modest changes in sea ice extent we 

report on an annual basis--the seasonal absence 

is to great extent masked by the recurrence of 

ice in winter. Our carrying capacity model 
49 


82737.277

therefore does not account of these seasonal 

aspects of sea ice change. The impact of periods 

of food deprivation which are too long for polar 

bears to accommodate is just not represented by 

the changes in sea ice extent expressed as km2-

months. This shortcoming is another reason 

that the carrying capacity 1110dellikely 

underestimates the effects future sea ice change 

will have on polar bears. 

Even with all of the caveats that accompany 

the carrying capacity modeling, however. the 

conclusion that polar bear populations will face 

major declines over large portions of their 

currcnt range seems sOllnd if the sca ice declines 

as predicted. The carrying capacity model 

suggests the greatest declines will be in the 

Polar Basin Divergent Ecoregion where 

extirpation could occur by mid-century and 

seems very likely by latc-century. Using the 

recent observational sea ice record to qualify the 

carrying capacity projections for the Seasonal 

Ice Ecoregion, it seems more likely that 

extirpation will occur thcre despite the fact that 

that outcome was forecasted from only the 

GCM minimum ice projections. The carrying 

capacity model further suggests that polar bears, 

in reduced numbers, are likely to persist in the 

Polar Basin Convergent Ecoregion and the 

Archipelago Ecoregion through the end of the 

21" century. 

Bayesian Network Model Forecast of 

the 21st Century Status of Polar 

Bears 

Next steps in the BN model 

development 

Before we discuss outcomes of our BN 

model, we provide a detailed description of its 

current state of development and the next steps 

in that development. Because BN models 

combine expert judgment and interpretation 

with quantitative and qualitative empirical 

information, inputs from multiple experts (if 

available) are necessary before a model can be 

considered final. Due to time constraints, 

however, we were not able to seek and 

incorporate the input of multiple polar bear 

experts into our BN model. Therefore, the 

model presented here should be viewed as a 

first-generation "alpha" level prototypc (Marcot 

et al. 2006). It captures and depicts judgment of 

one subject matter expert. It is therefore, in a 

general sense, an expert system (Martin et al. 

2005; McCann ct al. 2006), but still must be 

vetted through other polar bear experts. 

The next model development steps, including 

the vetting necessary to advance development of 

our prototype "alpha" levcl modcl, have been 

described in detail by (Marcot et al. 2006), and 

include: 

further peer review of the alpha model by 

other subject-mattcr experts; 

reconciliation of the peer reviews by the 

initial expert, and updating the model to a 

bela level that incorporates the reviews; 

testing of the beta level model for accuracy 

with existing data (e.g., determining if it 

matches historic or current known 

conditions); and 

updating the model to the next "gamma" 

level with existing data, or even to a delta 

level through incorporation of additional 

validation data from new field work or new 

analyses if available. 

Throughout this process, sensitivity testing 

can be used to veri fy model performancc and 

structure. This framework has been used 

successfully for developing a number of BN 

models of rare species of plants and animals 

(Marcot et al. 200 I, 2006; Raphael et a!. 2001; 

Marcot 2006). 

The next step in the development process of 

the polar bear BN population stressor model is 

the review of the current prototype by pcers--in 

this case by other polar bear experts. The 

process of review of the model by other polar 

bear experts is akin to the peer review of a 

manuscript sent to a journal. The initial model 
50 


82737.278

engineer can serve as an "editor" to present the 

alpha-level model to one or more other experts 

in the field; to elicit and compile their critique 

and comments on overall model structure (the 

variable used and their connections) and 

probabilities; and then to return to the initial 

expert with the reviews. The review by pcers 

could result in revision of the alpha-level 

model, producing a variant(s) of the model that 

more adequately represents the reviewer's own 

expert knowledge and judgment. The initial 

expert develops a "reconciliation" of the 

reviews that annotates how each review 

comment was addressed in modifying the model 

(or not). The result is modification, or perhaps 

retention, of the alpha-level model structure. to 

produce the beta-level model which 

incorporates inputs from more than one expert. 

Model variants that may havc emerged in the 

review process would represent the range of 

expcrt opinions and experiences, and this range 

could be important information for decisionmaking. 

Further advancing of the model beyond a 

beta-level, depends on whether new analysis 

results or new empirical data are available. 

Because BN models are best viewed as working 

tools useful to project outcomes, and to guide 

monitoring and data collection this becomes an 

interactive process. The model sensitivities can 

indicate which monitoring efforts will provide 

the information most useful to future decisions. 

The full model or portions of the model can be 

tested for performance against new data 

generated by that monitoring. The model is then 

validated and updated. This advantage of the 

BN modeling approach which allows new field 

data or new empirical observations to be 

incorporated into the model as they come along, 

allows for continual tests of model performance 

and provide new inputs which can be, in turn, 

used to improve model performance. Every new 

piece or data and new relevant observation 

allows further refinement of the performance of 

the model (Marcot 2006). 

Because these additional steps in 

development of our prototype model have not 

yet been completed, it is important to view 

probabilities of outcome states in terms of their 

general direction and overall magnitudcs rather 

than focusing on the exact numerical 

probabilities of the outcomes. When predictions 

result in high probability of one population 

outcome state and low or zero probabilities of 

all other states, there is low ovcrall uncertainty 

of predicted results. When projected 

probabilities of various states are more equally 

distributed, however, careful consideration 

should be given to large nonzero probabilities 

representing particular outcomcs even if those 

probabilities are not the largest. Consistency of 

pattern among scenarios (e.g., different GCM 

runs) also is important to note. If the most 

probable outcome has a much higher probability 

than all of the other states, and if the pattern 

across time frames and GCM models is 

consistent, it is most likely important to note 

that outcome and pattern. If on the other hand, 

probabilities are more uniformly spread among 

different states, and if the pattern varies among 

scenarios, the importance of the most probable 

outcome may not be as great. This approach 

takes advantage of the information available 

from the model while recognizing that it is still 

in development. It also conforms to the concept 

of viewing the model as a tool describing 

relative probabilistic relationships among major 

levels of population response under mUltiple 

stressors. 

BN model projected outcomes 

In the BN model, for each scenario run, the 

spread of population outcome probabilities (or 

at least non-Zero possibilities) represented how 

individual uncertainties propagate and 

compound across multiple stressors. Bcyond 

year 45, "extinct" was the most probable state 

into which polar bear populations in all 

ecoregions moved, except those in the 

Archipelago Eeoregion (Figure 10, Table 8). 
51 


82737.279

Distribution changes driven by changes in the 

sea ice appeared to be a major factor leading to 

these predictions. The sea ice extents of the 

Polar Basin Divergent Ecoregion and Seasonal 

Ice Ecoregion have declined more rapidly than 

other places in the Arctic (Meier et aL 2007). 

The loss of sea ice habitats in the Polar Basin 

Divergent Ecoregion is projected to continue, 

and possibly to accelerate (Holland ct aL 2006; 

Stroeve et aL 2007; Durner et aL 2007). 

Because polar bears are tied to the sea ice for 

obtaining food, major changes in the quantity of 

and distribution of sea ice must result in similar 

changes in polar bear distribution. In this sense, 

our carrying capacity model incorporates an 

element offoraging efficiency, even though it 

cannot directly account for other potential 

stressors per se. 

The BN model suggested that polar bear 

populations in the Seasonal lee Ecoregion 

moved into the extinct category rapidly in 

contrast to outcomes projected by the carrying 

capacity model. This may have been because 

the BN model incorporated aspects of the 

spatiotemporal distribution of the sea ice that 

are consistent with recent analyses (Hunter et aL 

2007; Regehr et aL 2007a) suggesting that long 

periods without ice habitats over continental 

shelf foraging areas may be associated with 

decreased survival of polar bears. In addition to 

variables representing the availability of sea ice 

over the continental shelves, Our BN model 

incorporated other potential stressors not 

included in our projection of carrying capacity 

which could have resulted in the different 

forecasts for the Seasonal lee Eeoregion. The 

BN model projection for the Seasonal Ice 

Ecoregion also seems more in line with the 

observational record (Stirling and Parkinson 

2006; Meier et at 2007) and provides added 

cause for reconsideration of the results of the 

carrying capacity model in the Seasonal Ice 

Ecoregion. 

Overall outcomes projected for polar bears 

appeared to be driven more by distributional 

effects than numerical effects. The most 

probable outcomes for Factor A (Habitat 

Threats) of the Proposal to list polar bears as a 

threatened species were "major restriction" 

Crable 10), Numerical responses of polar bcars 

to future circumstances were forecast to be 

morc modest than changes in distribution. In all 

regions, reduced density was the most probable 

outcome (Table 9), One way to interpret that 

outcome may be that where habitat remains, 

polar bears will remain even if in reduced 

numbers. This is consistent with our BN model 

results suggesting that polar bear populations 

may remain in the Archipelago Eeoregion at 

least into the middle of the 21st century. 

Corresponding with our carrying capacity 

projection, declines in distribution and number 

arc likely to be faster and more profound in the 

Polar Basin Divergent Eeoregion and the 

Seasonal Ecoregion than elsewhere. 

Imp0l1antly, our results suggest that a core of 

polar bear habitat and some number of polar 

bears is likely to persist in and around the 

Archipelago Ecoregion at least into mid 

century. 

Sensitivity analyses 

Sensitivity analyses otTcr an oppol1unity to 

interpret model outcomes at every level. The 

overall popUlation outcome was most sensitive 

to change in habitat quantity (node 8) and 

temporal habitat availability (node C). The other 

major habitat variable, change in distance 

between ice and the continental shelf (node N) 

was the 6th most influential factor on the overall 

popUlation outcome. Change in distance 

between ice and the continental shelf may have 

been ranked much lower than the other two 

quantitative sea ice variables because it was a 

measurement which only applied to the two 

polar basin ecoregions. This variable was not 

calculated in the Archipelago or Seasonal Icc 

Ecoregions because waters there are all (or 

essentially all) over the continental shelf 

Nonetheless, the combination of these three 

habitat variables explained 64% of the 
52 


82737.280

uncertainty in the overall population outcome. 

Ecoregion was the 3'd most influential node on 

overall outcome. We constructed the model 

recognizing that the four ecoregions differed in 

the nature of the sea ice which occurred there 

and in how polar bears utilize that ice. The fact 

that ecoregion explained 15% of the variation in 

overall population outcome is further evidence 

of the importance of sea ice habitat and its 

regional differences, to polar bear responses to 

projected habitat change. This is an important 

resu It helpful in understanding that, for 

example, polar bears appear to be facing much 

greater restriction in the Polar Basin Divergent 

and Seasonal lee ecoregions than they do 

elsewhere. 

Another habitat variable, "sea icc character" 

(node S I), was ranked 5th among variables 

having influence on the overall population 

outcome. This qualitative variable relating to 

sea icc character was included to allow for the 

fact that in addition to changes in quantity and 

distribution of sea ice, more subtle changes in 

the sea ice could affect polar bears. For 

example, longer open water periods and warmer 

winters have resulted in thinner icc in the polar 

basin region (Lindsay and Zhang 2005; Holland 

et al. 2006; Belchansky et al. 2008). Fischbach 

et al. (2007) hypothesized that thinning and the 

associated greater extent of marginal icc 

stability in autumn has resulted in reduced sea 

icc denning among polar bears of the southern 

Bcaufort Sea. 

Obscrvations during polar bear field work 

suggest that the thinning oflhe sea ice also has 

resulted in increased roughness and rafting 

among ice floes. Compared to the thicker icc 

that dominated the polar basin decades ago, 

thinner ice is more easily deformed, cven late in 

the winter. Although highly deformed ice 

composed of blocks of thin and rafted ice may 

bc satisfactory for seals, thcy may not be well 

suited to polar bear foraging. These changes 

appear to reduce foraging effectiveness of polar 

bears and it is suspected the changes in ice 

conditions may have contributed to recent 

cannibalism and other unusual foraging 

behaviors (Stirling et al. 2008). 

Recognizing these recent observations of 

nutritionally stressed individuals prompted us to 

include the "sea ice character" variable to 

qualitatively summarize a variety of changes in 

sea ice which may affect polar bears. States for 

this variable were entered based upon the 

observations that habitat quality already had 

been changing in a negative way in the Polar 

Basin Divergent Ecoregion. States, however, 

were entered differently to reflcct that warming 

which has caused thinning of ice in the polar 

basin, could actually improve habitat for polar 

bears in other ecoregions. That flexible 

parameterization resulted in this variable 

explaining 6% of the variation in overall 

population outcome. The sensitivity of overall 

population outcome to this node confirms that 

the nature of the sea ice as well as its 

spatiotemporal distribution will continue to 

have an important influence on the future of 

polar bears. 

The 4th ranked potential stressor to which 

overall population outcome was sensitive was 

intentional takes. Historically, the direct killing 

of polar bears by humans, for subsistence or for 

sport, has been thc biggcst challcnge to polar 

bear welfare (Amstrup 2003). Our model 

suggests that harvest of polar bears remains an 

important factor in their population dynamics, 

as sea ice retreats. Retreating sea ice will make 

the arctic habitats of polar bears more accessible 

and it is likely to result in increased numbers of 

bears occupying terrestrial habitats, at least 

seasonally. These factors will increase the 

potential vulnerability of bears to direct human 

kills. As the regions of the Arctic, which are 

currently unsettled due to the harshness of the 

climate, become warmer, human settlements 

and developments are likely to expand into 

them. This will increase the likelihood of takes 

in areas where direct mortalities by humans had 

not previously been an issue. The fact that 

intentional takes ranked so importantly in our 

outcomes suggests that of the potential human 
53 


82737.281

effects on polar bears, management of hunting 

will continue to be important (but see below). 

The remainder of the variables ranking in the 

top ten with regard to their influence on overall 

population outcome were bear-human 

interactions (node B I), parasites and disease 

(node T), and hydrocarbon contamination (node 

R4). Although these and the remainder of the 

variables which exerted intluence on overall 

outcome cumulatively explained only 9% of the 

variation in outcome, some of them result 

directly from human behavior. I-Ience, noting 

their influence may be of management value. 

Bear-human interactions, number 7 on the list 

of factors to which overall outcome was 

sensitive, are likely to increase as bears lose 

their traditional sea ice habitats. Our direct 

observations indicate these interactions already 

are increasing in Alaska as larger numbers of 

bears remain on land in summer. Longer 

summers They also have increased in frequency 

in portions of the Seasonal Ice Ecoregion where 

increased periods of ice absence have resulted 

in more bears in poor condition appearing in 

settlements as they apparently seck alternate 

foods (Regehr et al. 2007b). According to our 

model, management of bear-human interactions 

eould influence the future status of polar bears 

at least on the local level. 

The influence of parasites and disease 

agents, number 8 on the sensitivity list, on polar 

bears would likely increase if the climate 

continues to warm. Historically, polar bears 

have had few parasite and disease agents with 

which to contend (Amstrup 2003) but this may 

change as warming continues. Parasitic agents 

which have developmental stages outside the 

bodies of warm-blooded hosts (e.g., nematodes) 

will likely benefit from the warmer and wetter 

weather forecast for the Arctic (Macdonald et 

al. 2005). Improved conditions for such 

parasites already have had significant impacts 

on some terrestrial mammals (Klitz et al. 200 l. 

2004). Bacterial parasites also are likely to 

benefit from a warmer and weUer Arctic. In 

general, the distribution and abundance of a 

variety of pathogens is dependent upon climate 

inlluences (Dobson and Carper 1993; Powell et 

al. 1996; Cook et al. 1998). Although increases 

in disease and parasite agents have not yet been 

reported in polar bears, a warming climate has 

been associated with increases in pathogens in a 

variety of other marine organisms (Kuiken et al. 

2006). Similar increases in disease and parasite 

agents in the polar bear's environment are 

anticipated, however, if temperatures continue 

to warm as projected. 

Human activities related to oil and gas 

exploration and development are very likely to 

increase with disappearance of sea ice from 

many northern areas. At the same time, less sea 

ice will facilitate offshore developments. More 

offshore development will increase the 

probability of hydrocarbon discharges into polar 

bear environments (Stirling 1990). The record 

of over 30 years of oil and gas development in 

Alaska suggests that with proper management, 

potential negative effects of these activities on 

polar bears can be minimized (Amstrup 1993, 

2000,2003; Amstrup et a1. 2004b). Increases in 

marine developments, however, and the 

associated increases in shipping (etc.) will 

require new monitoring methods and may 

require increased diligence to maintain the 

positive track record. I-Ience, restricted sea ice 

could lead to greater probabilities oflocalized 

contaminant discharges. 

Long range marine and atmospheric 

transport of contaminants also is likely to 

increase (Macdonald et a!. 2003, 2005). 

Increased rainfall in northern regions already 

has increased river discharges into the arctic 

seas. Many of these north flowing rivers 

originate in heavily industrialized regions and 

carry heavy contaminant burdens (Macdonald et 

al. 2005). Considering the potential for 

increases in both local and long range transport 

of contaminants to the arctic. with warmer 

climate and less sea ice, the influence these 

activities have on polar bears is likely to 

increase. 
54 


82737.282

Strength of evidence of BN model 

projections 

The overall outcomes projectcd by our BN 

population stressor model are consistent with 

conclusions of the International Union for the 

Conservation of Nature (IUCN) polar bear 

specialist group (PI3SG) which recommendcd, 

based mainly on projccted changes in sca ice, 

that polar bears should be reclassified as 

vulnerable (Aars et al. 2006). It is also 

consistent with the increasing volume of data 

continning negative relationships between polar 

bear welfare and sea ice decline (Stirling and 

Derocher 1993; Stirling et al. 1999,2007,2008; 

Ainley et al. 2003; Derocher et al. 2004; 

Ferguson et al. 2005; Aars et al. 2006; Amstrup 

et al. 2006; Stirling and Parkinson 2006; Hunter 

ct al. 2007). In summary, our prototype I3N 

population stressor model projects that sea ice 

and sea ice rclated factors will be the dominant 

driv ing force affecting future distributions and 

numbers of polar bears through the 21" century. 

Our model also projects that if sea ice patterns 

change as projected by currently available 

climate models, polar bears wili be absent from 

2 major portions of their range by mid century. 

Despite caveats regarding the early stage of 

dcvclopment of our BN model, there are 

reasons, in addition to its consistency with the 

conventional wisdom of the polar bear 

community, to believe the directions and 

general magnitudes of its outcomes are 

reasonable. Sea icc related variables, including 

our 3 nodes (13, C, and N) which were derived 

from GCM outputs, were in the top 6 variables 

to which overall outcome was sensitive, and 

explained 70% ofthc variation in that outcome 

(Figure 12, Appendix I). This, while appearing 

to corroborate the well established link betwcen 

polar bears and sea icc, prompted us to ask 2 

questions. First, is there is anything that humans 

could do, short of bringing back more icc, that 

would qualitatively alter our projeetcd 

outcomes. Second. how much ditfcrent would 

sea ice need to be to cause a qualitative change 

in our overall outcomes. 

Could on the ground management affect our 

outcomes?--To address the first question, we 

fixed the input states far all nodes over which 

humans might be able to exert control (e.g., 

harvest, contaminants, oil and gas development) 

first to same as now, and then to improved 

conditions as compared to now, We reran the 

BN population stressor modcl under both 

conditions for other nodes and at all future time 

periods and with all 3 GCM scenarios for sea 

ice. 

Despite fixing human influences, outcomes 

of these runs were not qualitatively different 

from prcvious runs for the Polar Basin 

Divergent and Seasonal Ecoregions. Projected 

probabilities of extinction were lower at every 

time step, but the most probable outcome state 

for these two ecoregions was still "extinct" at 

nearly every time step and for every GCM 

sccnario. The only exception to this statement 

was for the Seasonal Ecoregion at year 45, the 

most probable outcome from the maximum ice 

GCM scenario being "smaller" rather than 

"extine!." In that case, however. the probability 

of extinct was just slightly below that of 

smaller. Probabilities of extinction in these two 

fixed runs of the model were lower at each time 

step and for each GCM scenario than during the 

general runs of the model (Figure 14). 

indicating that more probability was being 

spread across other outcome states (Table 14). 

However, at all time steps (except for year 45 in 

the Seasonal Icc Ecoregion), the predicted 

probability of extinction was around twice that 

of any other outcome state. The conclusion for 

the Seasonal Ice and Polar Basin Divergent 

Ecoregions is that management of localized 

human activities can have no qualitative effect 

on the future of polar bears in the Seasonal Jee 

and Polar l3asin Divergent Ecoregions if sea ice 

continues to decline as projected. Polar bears of 

both ecoregions are projected to move toward 

extinction by 45 years from now. 

There were greater differences between our 

fixed runs and our general runs in the other 

ccorcgions. The most probable outcome state 
55 


82737.283

for the Archipelago Ecoregion was smaller at all 

time steps and for all GCM scenarios when 

human factors were set to same as now. When 

human factors were set to fewer than now, the 

most probable state of the Archipelago 

Ecoregion was same as now through the 45 year 

time step and smaller thereafter. Probabilities of 

other outcome states in the Archipelago 

Ecoregion were rather evenly distributed on 

either side of the "smaller" outcome (Table 14). 

Probabilities of extinction were substantially 

lower than in our general model runs when 

human influences were either same as now or 

better then now, and with the GCM maximum 

scenario they were essentially 0 through year 75 

(figure 14). Also, there was even a relatively 

large probability of increase in some of the runs. 

This indicates that management of human 

factors could be important for polar bears in the 

Archipelago Ecoregion. 

In the Polar Basin Convergent Ecoregion, 

"smaller" rather than "extinct" was the most 

probable outcome at year 45 for all GCM 

scenarios when human factors were either same 

as now or improved. Under the scenario where 

human factors were fixed as fewer in the Polar 

Basin Convergent Ecoregion, "smaller" was the 

most probable outcome through year 75 in the 

maximum GCM scenario. Probabilities of 

extinction were lower (Figure 14), and 

probabilities were spread through other outcome 

states. Unlike the Archipelago Ecoregion, 

however, extinct was the most probable 

outcome at most time steps for the majority of 

GCM sccnarios Crable 14, Figure 14). 

The conclusion from these fixed runs of the 

model is that management of human activities 

has the potential to qualitatively improve the 

welfare of polar bears in the Archipelago 

Ecoregion through the 21 st century and in Polar 

Basin Convergent Ecoregion through midcentury. Conversely, it appears that there is little 

that management of localized human activities 

can do, assuming spatiotemporal extent of the 

sea ice continues to decline as expected, to 

qualitatively improve the outcomes projected 

for polar bears in the Polar Basin Divergent and 

Seasonal lee Ecoregions. Polar bears in those 

two ecoregions, which include approximately 

2/3 of the current range-wide population, are 

projected to become extinct by mid century 

regardless of local management actions that 

would eliminate or mitigate anthropogenic 

stressors. 

Could future sea ice be different enough to 

affect outcomes? --Fixing the effects in our 

model, which humans might be able to manage, 

illustrated that sea ice effects prevail in 

determining the future of polar bears, and that 

only in some regions could those effects be 

compensated by on the ground human activities. 

But what would it take in the way of different 

sea ice projections to qualitatively change our 

forecasted population outcomes? To answer that 

question we must turn to the presumptions built 

into our model. 

We populated the conditional probability 

tables, in nodes of our model which reflect sea 

ice extent and distribution, in recognition of the 

established reliance of polar bears on the 

surface of the sca icc (Table 3, Appendix 3). 

Evidence for the polar bear's reliance on sea ice 

is replete. Although they are opportunistic and 

wil! take terrestrial foods, including human 

refuse, when available, and may benefit from 

such activity (Lunn and Stirling 1985; Derocher 

et al. J 993), polar bears are largely dependent 

on the productivity of the marine environment. 

Refuse, for example, is of limited availability 

throughout the polar bear range, and could at 

best benefit relatively few individuals. Also, 

polar bears are poorly equipped to consume and 

digest most plant parts (Chapin et a!. 2006), and 

they are, for the most part, inefficient in preying 

on terrestrial animals (Brook and Richardson 

2002; Stempnicwicz 2006). Perhaps most 

importantly, polar bears have evolved a strategy 

designed to take advantage of the high fat 

content of marine mammals (Best 1984). 

Available terrestrial foods are, with few 

exceptions, not rich enough or cannot be 

gathered efficiently enough to support polar 
56 


82737.284

bears, which are the largest of the bears, in any 

numbers (Wclch et al. 1997; Rode et al. 2001; 

Robbins ct al. 2004). Although there are 

localized exceptions, polar bears appcar to gain 

little overall bcncfit at the population level, 

from alternate foods (Ramsay and Hobson 

1991). Polar bcars, it appears, are obligately 

dcpendent on the surface of the sca ice for 

capture of the prey necessary to maintain their 

populations. 

Based upon this wcll established reliance on 

sea ice for foraging wc assumed that continued 

dcclines, in regions where sea ice declines 

already have had significant deleterious effccts, 

would be negative for polar bears and we built 

that assumption into the conditional probability 

tables of our models. Wc also assumed that in 

some ecoregions, polar bears might benefit from 

changes in the sea ice - at least temporarily - or 

would at least not be as greatly affected as in 

other regions. We built that assumption into our 

models as well. These assumptions, in short, 

mean that if sea ice continues to decline it 

ultimately will havc a negative effect on polar 

bears but that those effects will not be equal in 

all ecoregions nor will they occur at the same 

times in all regions. 

So, the question "how would the ice need to 

change in order to produce outcomcs 

qualitatively different than our current model 

outcomes Crable 8 and figures 10 and II)" is 

reasonable. We explored this question in our 

BN model by setting the values for all non-ice 

inputs to uniform prior probabilities. That is we 

didn't make any assumptions about whether 

they would change in ways that were better or 

worse for polar bears. We assumed complete 

uncertainty with regard to futurc food 

availability, oil and gas activity, contaminants 

and disease etc. Then, we ran the model to 

determine how changes in the sea ice states 

alone, specified by our ensemble of GCMs, 

givcn complete uncertainty with rcgard to all 

else, would affect our outcomes. 

This exercise illustrated that for the Seasonal 

Ice Ecoregion, and the Polar Basin Divergent 

Ecoregion, sea ice would have to decline 

substantially less than is predicted by our 

maximum ice GCM scenario to make any 

qualitative difference in our outcomes. At all 

time steps and for all GCM runs, the most 

probable outcome is "extinct" (Figure 14), and 

by far the greatest probability falls into the 

extinct state Crable 15). The most probable 

outcomc in the Polar Basin Convergent 

Ecoregion also is "extinct" at all time steps 

under this fixed modeling sitllation. Overall 

probabilities of extinction are lower, and more 

probability is forecast for other outcome states, 

but extinction holds more than twice the 

probability of any other state at all timc frames. 

We do not know just how much more ice it 

would take to prevent this outcome, but it would 

necd to be much more than any of our models 

suggest if' it were to result in a qualitative 

improvement of'the general model outcome. 

Even in the Archipelago Ecoregion there is 

no substantial change. There, the most probable 

outcomes are in the same patterns as in our 

general model runs. The difference is that the 

probability of extinct is slightly lower in most 

cases, and more probability is spread throughout 

other possible states. 

In conclusion, to see any qualitative change 

in the probability of cxtinction in any of the 

ecoregions, even in year 45, sea ice projections 

would nced to leave more sea ice than the 

maximum GCM projection wc used. This 

eventuality may be unlikely in light of the fact. 

as shown in Figures 3, 6, and 7, that most sea 

ice models tended to predict more ice than there 

actually was during the observational record 

betwcen 1979 and present (Durner et al. 2007; 

Stroeve et al. 2007). It also may seem unlikely 

in light of rccent observations. As of 23 August 

2007 declines in Arctic sea ice extent in 2007 

have set a new record for the available time 

scrics from 1979-2006. This record minimum is 

400,000 km2 below the previous record which 

occurred in 2005 (National Snow and Ice Data 

Center, http://nsidc.org/news/press/2007_seaice 

minimum120070810 _index.html). Because this 
57 


82737.285

new record has occurred 25-83 days before the 

summer melt season will end in different parts 

of the polar basin (Stroeve et a!. 2006), much 

more melting and greater sea ice rcduction 

seems likely. The more rapid decline in 

observed sea ice than in modeled sea ice 

(Stroeve et al. 2007) appears to be continuing. 

By exploring outcomes of our BN model by 

fixing certain parameters, we determined that 

future sea ice would have to be more extensive, 

at all time steps, than is projected by our most 

conservative models (the models forecasting the 

most sea icc remaining). But, the sea ice in 2007 

already has declined below the level projected 

for mid century by the 4 most conservative 

models in our ensemble (Figure 15). This seems 

to be compelling evidence that we are not likely 

to see more ice than our models have suggested 

at any of the future time steps we evaluated. 

Another aspect of the 2007 summer ice melt 

is pertinent to our discussion. Our analyses of 

GeM outputs has suggested that sea ice is likely 

to remain in the Archipelago Ecoregion through 

the end of the century. Based upon this 

projection, our carrying capacity model and our 

BN model both suggested that the Archipelago 

Ecoregion would provide refuge to polar bears 

well into the century. The southern portion of 

the Archipelago Ecoregion, however, was clear 

of sea ice by 23 August 2007 (Figure 15). This 

recent observation then calls into question a 

main conclusion of our modeling effort: that 

polar bears in the Archipelago Ecoregion may 

be insulated from sea ice change for many 

decades. True, this is just one yearly data point. 

But it is a data point that fits a recent pattern of 

sea ice declining at an aecelerating rate that is 

faster than sea ice forecasters have projected. 

And, it is One piece of evidence suggesting that 

it may not be at all reasonable to expect that 

future spatiotemporal distribution of sea iee will 

exceed the maximum values projected by our 

model ensemble. 

We do not know how other polar bear 

experts might differ in how they would structure 

and parameterize a BN polar bear population 

stressor model. Several factors, however, 

suggest that a polar bear model would have to 

be structured and parameterized very differently 

to project qualitatively ditTerent outcomes. First, 

the great sensitivity in our model to sea ice 

habitat changes is consistent with hypothesized 

effects of global warming on polar bears 

(Derocher et a!. 2004). Second, this sensitivity 

to sea ice change parallels recent observations 

of how decreasing spatiotemporal distribution 

of sea ice has affected polar bears (Stirling et a!. 

1999.2007; Hunter et al. 2007; Regehr et al. 

2007a, 2007b; Rode et al. 2007). Third, it 

appears that future sea ice patterns would have 

to be fundamentally different than is projected 

tor the apparent direction in polar bear 

popUlations we project to be altered. Finally, 

with sea ice trends continuing to decline at rates 

that are faster than forecast, the relationship of 

polar bears to sea ice change would have to be 

fundamentally different than the range-wide 

body of polar bear data suggests it is. All of 

these would have to be very different for trends 

in polar bears distrubution and numbers to take 

a fundamentally different path than our BN 

model projects. 

In short, although it is highly likely that other 

polar bear experts might structure a model 

differently and populate conditional probability 

tables differently than we have, it seems 

unlikely that those differences would be great 

enough to make a qualitative difference in the 

outcomes projeeted by our prototype mode I. 

Conclusion 

We took two approaches to forecast the 

range-wide future status of polar bears. First, we 

built a simple deterministic model of future 

polar bear carrying capacity. This model 

depended on a linear relationship between sea 

ice area and polar bear density. It was easy to 

understand and provided some sense of how 

numbers of polar bears might change over time 

in different regions of the Arctic. However, 

because it only addressed annual average sea ice 

extent, the carrying capacity model could not 
58 


82737.286

account for contribution of changes in the 

nature or spatiotemporal distribution of sea ice. 

It also could not account for other population 

stressors which could accompany changes in the 

sea ice and which could exacerbate the effects 

due to habitat loss. Hence, this simple 

deterministic model provided a conservative 

outlook for polar bears. Second, we built a 

Bayesian network population stressor (BN) 

model. This model incorporated changes in 

spatiotemporal distribution of sea ice as well as 

other potential population stressors which the 

deterministic carrying capacity model did not 

include. The BN model incorporated 

quantitative information regarding changes in 

habitat as well as qualitative information 

regarding other potential stressors in a 

probabilistic setting. The BN model had the 

ability to more thoroughly assess the extent of 

changes which might occur and to describe 

outcome states in terms of their relative 

probabilities. 

Our forecasts suggested that declines in the 

spatiotemporal distribution of sea ice habitat 

along with other potential stressors will severely 

impact future polar bear populations. Outcomes 

varied geographically and by time step, and 

included the following: 

I. Polar bear populations in the Polar Basin 

Divergent and Seasonal lee ecorcgions will 

most likely be extirpated by mid century. 

Approximately 2/3 of the world's current 

polar bear population resides in the 

combined area of these two ecoregions. 

2. Polar bear populations in the Archipelago 

Ecoregion appear likely to persist through 

the middle of the century. Some modeling 

scenarios suggest persistence of polar bears 

in this ecoregion toward the end of the 

century. The number of bears in this 

ecoregion will likely be less than at present 

due to the reduced amount of habitat and 

other factors. 

3. Polar bears in the Polar Basin Convergcnt 

Ecoregion may persist through mid-century, 

but they most probably will be extirpated at 

and beyond year 75. 

4. A declining habitat base, coinciding with 

FWS Listing Factor A (habitat threats), was 

the overriding factor in forecasts of 

declining numbers and distribution of polar 

bears. 

5. Other factors which correspond with FWS 

listing Factors B, C, and E, and which could 

result in additional population stress on 

polar bears, are likely to exacerbate effects 

of habitat loss. 

6. Management of localized human activities 

such as hunting, release of contaminants, 

and direct bear-human interactions etc., 

qualitatively increased the probability of 

persistence of polar bears in the Archipelago 

ecoregion through the end of the century 

and increased the probability that polar 

bears could persist in the Polar Basin 

Convergent Ecoregion through mid-century. 

7. Management of localized human activities 

did not appear able to changc the probability 

of extinction in the Polar Basin Divergent or 

Seasonal Ice ecoregions in any qualitative 

way. Holding all model inputs for localized 

human activities to represent fewer impacts 

than now made no qualitative change in the 

probability of extinction. 

8. Because recently observed deelincs in sea 

ice extent continue to outpace most GCM 

projections, more extensive sea ice seems an 

increasingly unlikely future. Yet, to 

qualitatively alter outcomes projected by our 

models and head off the projected loss of 

2/3 of the world's current polar bears, future 

sea ice would have to be far more extensive 

than is projccted by even conservative 

General Circulation Models. 
59 


82737.287

Acknowledgements 

Principal funding for this project was 

provided by the U.S. Geological Survey. We 

thank G.S. York, K.S. Simac, for logistical 

support on this project and for keeping the 

offiee going while we were preoccupied. We 

thank G. M. Durner and E. V. Regehr, M. 

Runge, and S. Morey for valuable discussions 

and K. Oakley for effective and insightful 

project management. We are grateful to W. L. 

Thompson, T. Starfield, N. Lunn, and B. Taylor 

for helpful reviews of earlier versions of this 

report. 

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68 


82737.296

Table 1. Ten fPCC AR-4 GCMs whose sea ice simulations and projections were used to define ice 

covariates for polar bear RSF models: IPCC model ID, country of origin, approximate grid resolution 

(degrees), forcing scenario, and the number of runs used for the polar bear studies. 

We treated the mean of the 8 ncar_ ccsm3 _ 0 model runs as a single output to be consistent with the other 

models which had only one run. 

Grid Resolution Forcin!l Number 

MODEL ID Count!}' (Iatx Ion) Scenario .of Runs 

ncar_ccsm3_0 USA 1.0 x 1.0 20c3m 8 

SRES AlB 8 

cccma_cgcm3_1 Canada 3.8 x 3.8 20c3m 

SRES Al B 

cnrm_cm3 France 1.0 x 2.0 20c3m 

SRES AlB 

gfdl_cm2_0 USA 0.9 x 1.0 20c3m 

SRES AlB 

giss_aom USA 3.0 x 4.0 20c3m 

SRES AlB 

ukmo _ hadgem 1 UK 0.8 x 1.0 20c3m 

SRES AlB 

ipsl_cm4 France 1.0 x 2.0 20c3m 

SRES AlB 

miroc3_2_ medres Japan LOx 1.4 20c3m 

SRES AlB 

miub_echo_g Germany/Korea 1.5 x 2.8 20c3m 

SRES AlB 

mpi_ccham5 Germany 1.0 x 1.0 20c3m 

82737.297

Table 3. Input data used in the Bayesian network population stressor model (Figure 5). 

Data for model node B was derived from the spreadsheet carrying capacity model (Table 6); data for model nodes C and N 

derived from the global circulation mode! (GCM) results; and data for all other model nodes were specified as best professi

judgment by one polar bear expert (S. Amstrup). 

BBN node name 

Variable name 

Unit of measure 

Allowable values 

Time 

Period Basis 

Year -10 Year 0 Year 45 Year 75 Year 100 Year 45 

Year 75 Year 100 Year 45 Year 75 Year 100 

Satellite data Satellite data 

GCM minimum 

GCMminimum GCMminimum 

Ensemble mean Ensemble mean Ensemble mean 

GCM maximum GCM maximum 

GCMmaximum 

B 

Foraging 

habitat 

quantity 

change 

% change 

from "now" 

C 

Foraging 

habitat 

absence 

change 

#of 

Months 

DitTerent 

than now 

N 

Shelf 

distance 

change 

km 

SI 

Foraging 

habitat 

character 

discrete state 

M 

Geographic area 

discrete stnte 

Polar __ Basin _ Di vergent 

any value < any value any value morc_optimal Polar_Basin_Convergent 

or > or = > or = same._as_now Archipelago 

+20% _I .200 less._ optimal Seasonal_Ice 

17.14% 

0.00% 

-10.36% -31.89% -32.11% -14.62% -25.75% 

.27.83% 

-6.71% 

-21.16% -21.69% 

-0.7 

0.0 

1.0 

2.5 

2.7 

1.0 

1.6 

1.8 

0.7 

1.3 

1.7 

* * 

Seasonal Ice Ecoregion 

more_optimal 

same _as_now 

same_as_now 

less_optimal 

less_optimal 

same_<1s_now 

less_optimal 

less_optimal 

same._ as_now 

same as now 

Seasonal_lee 

Seasonal_Ice Seasonal_Ice Seasonal_Ice Seasonal_Ice Seasonal_Ice Seasonal_Ice Seasonal_lee 

Seasonal_Ice 

Seasonal_lee 

Seasonal Ice 

R3 

Alternative 

prey 

availability 

discrete state 

increase 

same_as_now 

decrease 

decrease 

R2 

Relative 

ringed seal 

availability 

discrete state 

increase 

same_as_now 

decrease 

increase 

Al

a

d

Y

samc_as_novv Y

decrease decrease Y

decrease decrease Y decrease decrease Ydecrease 

decrease decrease decrease decrease decrease 

decrease 

dccrcase decrease decrease decrease decrease 

YYYYYY
70 


82737.298

Table 2. Composite summary categories of polar bear carrying capacity change from present levels. 

based on categories of composite habitat change and composite carrying capacity change. 

Composite habitat change 

summary category 

Expanding fast 

Expanding fast 

Expanding fast 

Expanding moderate 

Expanding moderate 

Expanding moderate 

Stable 

Stable 

Stable 

Stable 

Stable 

Stable 

Contracting slow 

Contracting slow 

Contracting slow 

Contracting slow 

Contracting moderate 

Contracting moderate 

Contracting moderate 

Contracting moderate 

Contracting fast 

Contracting fast 

Contracting fast 

Contracting fast 

Composite carrymg capacity 

change summary category 

Increasing high 

Increasing moderate 

Stable 

Increasing high 

Increasing moderate 

Stable 

Decreasing high 

Decreasing moderate 

Decreasing low 

Increasing high 

Increasing moderate 

Stable 

Decreasing high 

Decreasing moderate 

Decreasing low 

Stable 

Decreasing high 

Decreasing moderate 

Decreasing low 

Stable 

Decreasing high 

Decreasing moderate 

Decreasing low 

Stable 

Composite summary category 

of carrying capacity change 

Enhanced 

Enhanced 

Enhanced 

Enhanced 

Enhanced 

Enhanced 

Decreased 

Decreased 

Decreased 

Enhanced 

Enhanced 

Maintained 

Decreased 

Decreased 

Decreased 

Decreased 

Toward extirpation 

Decreased 

Decreased 

Decreased 

Toward extirpation 

Toward extirpation 

Decreased 

Decreased 

82737.299

Table 3. continued. 

BBi'i node name JI BI RI R4 TI E T 

Variable name Bear-human 0,1 & gas Hydrocarbons I oil Intentional Parasites Tourism mteractlons actJv,ty Shipping spill Contaminants takes & disease P

Unit of measure 

discrete discrete 

discrete state discrete state state discrete state discrete state discrete state discrete state state 

increased increased Increase Increased_occurrence elevated increased 

Allowable values same as now Increased same_as _now same_as_now same as now influential i

decrca;ed decreased decrease same as now decreased occurrence reduced dec-;:ea'S"cd not 

Time 

I.!eriod Basis 

Seasonal Ice Ecoregion 

Year-IO Sateillte data decreased decreased no change same_as _ nmv same_as _now reduced decrea<;ed not 

Year 0 Satellite data same_as_now same __ as_now no_change same as_now same_as_no\v samc_as_now same_as_now not Year 45 GeM minimum increased increased no_change increased same_a "i_now elevated decreased inllucntial 

Year 75 GCM mmimum increased increased no_change increased increased_occurrence elevated decreased mlluential 

Year 100 GeM minimum increased increased no .... change increased Increased_occurrence elevated decreased influential 

Year 45 Ensemble mean increased Increased no_change increased same __ as_now elevated decrcased influential Year 75 Ensemble mean increased increased no_change increased increased_occurrence elevated decreased influential 

Year 100 Ensemble mean increased increascd .. change increased Increased_occurrence elevated decreased influential Year 45 GCM maximum increased increased nOJhange increascd __ now elevated decreased intlucnt1al 

Year 75 GeM maximum increased increased no_change increased increased_occurrence elevated decreased influential 

Year 100 GeM maximum IIlcreased mcreased no_change increased increased __ occurrence elevated decreased intluential 

82737.300

Table 3 continued. 

Time 

Period 

Year -10 

YearO 

Year 45 Year 75 

Year 100 Year 45 Year 75 Year 100 

Year 45 Year 75 Year 100 

BBN node name 

Variable name 

lInit of measure 

Allowable values 

Basis 

Satellite data Satellite data 

GCMminimum GCMminimum 

GCMminimum 

Ensemble mean Ensemble mean Ensemble mean 

GCMmaximum GCMmaximum 

GCM maximum 

B 

Foraging 

habitat 

quantity 

change 

% change 

C 

Foraging 

habitat 

abseflce 

change 

#7T 

Months 

Different 

from Hnow" than now 

any value < any value 

N 

Shelf 

distance 

change 

SI 

Foraging 

habitat 

character 

km discrete 

any value more_optimal 

M 

Geograpbic area 

discrete state 

or = > or = > or::= same_3s_now 

Polar _Basin_Divergent 

Polar __ Basin _Convergent 

Archipelago 

+20% -)00 less_optimal Seasonal Ice 

3.21% 

0.00% 

-13.79% 

-20.7\% 

-24.30% 

-11.93% 

-20.06% -22.16% 

-3.43% 

-18.02% -20.85% 

-0.5 

0.0 

l.l 

2.0 

2.3 

1.5 

2.4 2.5 

0.0 

2.7 

2.3 

.. 

Archipelago Ecoregion 

less_optimal 

same_as_now 

more_optimal 

same _ as_now 

same_as _now 

more_optimal 

same_as_now 

same _ as._Dow 

morc_optimal 

more_optimal 

Archipelago 

Archipelago Archipelago Arcbipelago 

Archipelago 

Archipelago Archipelago Archipelago 

Archipelago 

Archipelago 

same as_Il()\_,_' ____ Archipelago 

R3 R2 

Alternative 

prey 

availability 

Relative 

ringed seal 

availability 

Al

r

av

discrete state 

increase 

sarne_as_oow 

decrease 

discrete state 

increase 

same_as _now 

decrease 

d

same _ as_now decrease N

same_as_now same_as_,now N

increase increase N

decrease decrease Ndecrease de crease N

increase increase N

increase decrease N

decrease decrease N

increase 

increase 

decrease 

increase increase 

decrease 

N

N

N

82737.301

Table 3 continued. 

B BN node na me II Bl RI R4 TI E T 

Variable name Bear-human Oil & gas Hydrocarbons I oil Intentional Parasites Tourism interactions acttvlIY Shipping spill ContamInants lakes & disease P

discrete discrete Unit of measure discrete state dlscrete state state discrete state discrete state discrete state discrete state state 

increased increased increase increased_occurrence elevated increased 

Allowable values same as now same_as_now no_change increased same_as_now same_as _now same as now influential i

decrea;ed decreased decrease same as now decreased occurrence reduced decreased not 

TI= . 

period Basis Archipelago Ecoregl()D 

Year -10 Sate I lite data decreased increased no_change same_as_now reduced same_3s_noW not 

Year 0 Salellite data same_3s_now same_as_now no_chaoge same_as_now same_as_now same_as_now same_as_now not 

Year 45 GCM minimum Increased increased no_change same_as_now same_as_now elevated increased influential 

Year 75 GCMmmimum increased increased increase increased increased_occurrence elevated influential 

Year 100 GCM minimum increased increased increase increased increased_occurrence elevated decreased influential 

Year 45 Ensemble mean increased increased no_change same_as now same_as_Hnow elevated increa'ied influential 

Year 75 Ensemble mean increased increased mcrease same_a5_flOW increased_occurrence elevated same_as_now influential 

Year 100 Ensemble mean increased increased mcrease increased 1ncreased _occurrence elevated decreased influential 

Year 45 GCM maximum increased increased no_change same _ samc_as_now elevated increased influential 

Year 75 GCMmax,mum increased increased mcrease same_as._now increased_occurrence elevated increased influential 

Year 100 GeM maximum increased increa'led increase same as now increased occurrence elevated decreased influential 

82737.302

Table 3 continued. 

BBN node name B C N SI M R3 R2 

Foraging Foraging 

habitat habitat Shelf Foraging Variable name quantity absence distance habitat A lIe mati ve Relative Al

prey ringed seal r

change change change character Geographic area availabilitL availability av

# of 

Unit of measure 

Momhs 

% change Different d

from "now" than now km discrete stare discrete state discrete state discrete state 

Polar_Basin _Divergent 

increase increase 

same_as_now same ... as_now 

Allowable values any value < any value any value more_optima! Polar_Basin_Convergent 

or= >or= >or= same_as_now Archipelago 

+2fi% -200 SeasonaUce decrease decrease 

Time 

Period Basis 

Polar Basin Divergent Ecoregion 

Year -10 Satellite data 5.33% -0.3 ·83 more_optimal Polar _Basin_Divergent same_us_now increase YYear 0 Satellite data 0.00% 0.0 0 same_as_now Polar _Basin_Divergent same_as_now same_us_now Y

Year 45 GCMminimum ·36.15% 2.1 1359 less_optimal Polar_Basin _Divergent same_as_now decrease Y

Year 75 GCMminimum -44.64% 2.9 2006 less_optimal Polar_Basin_Divergent same_as_now decrease Y

Year 100 GCMminimum ·49.46% 3.2 2177 less_optimal Polar._Basin_Divergent same_as_now decrease Y

Year 45 Ensemble mean -19.31% 1.8 631 less_optimal Polar_Basin_Divergent same_as_now decrease Y

Year 75 Ensemble mean ·31.68% 2.6 1034 less, .. optimal Polar _Basin_Divergent same_as_now decrease Y

Year 100 Ensemble mean -35.77% 3,0 1275 less_optimal Polar _Basin_Divergent same_as_now decrease Y

Year 45 GCM maximum -16.68% 2.2 234 less_optimal Polar _Basin_Divergent same_us_now decrease Y

Year 75 GeM maximum ·31.16% 2.4 233 less_optimal Polar _Basin_Divergent same_as_flow decrease Y

Year 100 GCM maximum ·21.33% 2.7 315 less_optitnal Polar Basin_Divergent same_as now decrease Y

82737.303

Table 3 continued. 

BBN node name JI BI RI E T 

Variable name Bear-human Oil & gas Hydrocarbons I oil Intentional Parasites Tourism interactions activity Shipping spill Contaminants takes & disease P

Unit of measure 

discrete 

discrete stale discrete state state state discrete state discrete state discrete state state 

increased increat;;ed mcrease inaeased _occurrence elevated increased 

Allowable values same as now same as now no_change increased Same as now same_3s_now same as now influential i

dec-;eaScd decrease same as now decreased o;;currence reduced not 

Time 

eeriod Basis 

Polar Basin Divergent Ecoregion 

Year -10 Satel! tte data decreased decreased decrease samc_as_now same_as _now reduced decreased not 

Year 0 Satell ite data same_3s_now samc_as_now no_change same_as _now samc_as_now samc_as_now sarnc_as_now not 

Year 45 GeM minimum increased increased increase increased increased_occurrence elevated decreased inlluential 

Year 75 GCMminimum decreased increased increase increased increased_occurrence elevated decreased influential 

Year 100 GCMminimum decreased increased decrease increased increased_occurrence elevated decreased intluential 

Year 45 Ensem ble mean increased increased increase increased increased_occurrence elevated decreased influential 

Year 75 Ensemble mean same _ 3S._now increased increase increased increased_occurrence elevated decreased influential 

Year 100 Ensemble mean decreased increased decrease increased increased_occurrence elevated decreased inlluential 

Year 45 GeM maximum increased increased increa,e increased elevated decreased inlluential 

Year 75 GCMmaximum same_as_now increased increase increased increased_occurrence elevated decreased influential 

Year lOa GCM maximum same as now increased decrease increased increased occurrence elevated decreased influential 

82737.304

Table 3 continued. 

Time 

Period 

Year -10 Year 0 

Year 45 

Year 75 

Year 100 

Year 45 

Year 75 

Year 100 

Year 45 Year 75 

Year JOO 

BBN node name 

Variable name 

lInit of measure 

Allowable values 

Basis 

Satellite data Satellite data 

GCMminimum 

GCMminimum 

GCM minimum 

Ensem ble mean 

Ensemble mean 

Ensemble mean 

GCMma)(imum GCM maximum GCM maximum 

B 

Foraging 

habitat 

quantity 

change 

% change 

from lInow" 

C 

Foraging 

habitat 

absence 

change 

'#'";;f 

Months 

Dillerent 

than now 

N SI M 

Shelf Foraging 

distance habitat 

change character Geographic area 

km discrete state discrete state 

Polar_Basin _Divergent 

any value < any value any value more_optimal Polar_Basin_Convergent 

or= > or > or= same_asyow Archipelago 

+ 20% Jess_optimal 

Polar Basin Convergent Ecoregion 

4.34% -0.5 -41 same_as_now Polar _ Basin __ Convergent 

0.00% 0.0 0 same_as_now Po lar _Basin_Convergent 

-1.77% 0.9 831 same_as_now Polar _ Basin_ .. Convergent 

-23.19% 1.9 1542 less_optimal Polar_Basin_ Convergent 

-30.33% 2.5 1478 less_optimal Polar _Basin .. Convergent 

-13.85% 2.0 464 same_as_now Polar_B as in_ Convergent 

-22.65% 3.0 847 less_optimal Polar _Basill_ Convergent 

-25.02% 3.3 795 less_optimal Polar_Basin _Convergent 

-24.28% 2.9 334 same_us_now Polar .. Basin_Convergent 

-30.23% 3.5 434 less_optimal Polar _ Basin .. Convergent 

·31.20% 3.7 510 less_optimal Polar_ Basin_Convergent 

R3 R2 

Altemative Relative Al

prey ringed seal r

avaiiabili!L,. availability a

d

discrete state discrete state 

increase increase 

same_as_now same _ as __ now 

decrease decrease 

same_as_now same_as_now N

same_as_now samc .. 3s_now N

increase same_as_now N

decrease decrease Ndecrease decrease N

increase increase N

decrease samc_as_now N

decrease decrease N

increase increase N

increase increase N

decrease same as now N

82737.305

Table 3 continued. 

BBN node name JI BI RI R4 T! E T 

Variable name Bear·human Oil & gas Hydrocarbons / oil Intentional Parasites Tourism interactions activity Shipping spill Contaminants takes & disease 

U nil of measure discrete 

discrete state discrete slzlte state discrete state discrete state discrete state discrete state state 

increased increas,ed increase increased_occurrence elevated 

Allowable values same as now same as noW no_change increased same _,as_now same_as_now same as now influential i

decrease same as now decreased occurrence reduced not 

Time 

I!<riod Basis 

Polar Basin Convergent Ecoregion 

Year-lO Satellite data decreased decrease same_as now samc._as_now reduced same_a8_tlOW not 

Yearu Satellite data same _.as _now samc_as_now no_change same_as_now same_as._now same_3s_now same_as_now not 

Year 45 GCMminimum increased increased increase increased increased_occurrence elevated decreased influential 

Year 75 GCMminimum increased Increased increase increased increased ... occurrence elevated decreased influential 

Year 100 GCMminimum increased increased increase increased increased_occurrence elevated decreased influential 

Year 45 Ensemble mean increased 1ncreased increase increased increased_occurrence elevated decreased influential 

Year 75 Ensemble mean increased increased increase increased increased_occurrence elevated decreased influential 

Year 100 Ensemble mean increased increased mcrease increased increased_occurrence elevated decreased influential Year 45 GCMmaximum increased increased increase increased increased_occurrence elevated decreased influential 

Year 75 GCMmaximum increased increa')ed increase increased increased_occurrence elevated decreased influential 

Year 100 GCM maximum increased increased increase increased increased occurrence elevated decreased influential 

82737.306

Table 4. Amount, percent change, and summary of change in polar bear habitat forecasted by the deterministic polar bear carr

capacity model. 

x = not calculated or data not available. 

Habitat amount % change in habitat 

{km' -montbs x 1000) from year 0 Change in Tota! Habitatfrorn Year 0 

Time Period Oata basis Total habitat RSF habit.t habitat RSF habitat Total habitat Directionl Sum

Seesonallce EcoreQion 

Year -10 Satellite data i6258.70 17% Expanding or stable Moderate Expanding 

Year 0 Satelhte data \3.879.60 0% Expanding or stable Slow to none Stable 

Year 0 GeM minimum 11,217.33 0% Expanding or stable Slow to none Stable 

Year 45 GCMminimum 10,054.93 Contracting SIQW to none Contmctltlg 

Year 75 GeM minimum 7,640.68 ·32% Contracting Fast Contracting 

Year 100 GeM minimum 7,615.55 ·32% Contracting Fast Contracting 

Year 0 Ensemble mean 16.340.56 0% Expandmg or slable Slow to none Stable Year 45 Ensemble mean 13,952.36 -15% Contracting Slow to none Contracting 

Year 75 Ensemble mean 12,132.32 Contracting Moderate Contracting 

Year 100 Ensemble mea.n 11,793.25 ·28% Contracting Moderate Contracting 

Year 0 GCMmaximum 20,178.76 0% Expanding or stable Slow to none- Stable Year 45 GeM maXimum 13,823.83 -7% Contractmg SJowto none Contracting Year 75 GeM maximum 15,909.29 ·21% Contractmg Moderate Contracting 

Year 100 OCMmaximum 15,802.l(; Contracting Moderate Comracting 

I Direction was categorized into "contracting" if CH"u < 0 or "expanding or stable" if CH"e; 2: O. 

2 Magnitude was categorized into "fast" if ICH""I > 30.0, "moderate" if 15,0< ICHu;l::; 30.0, and "slow or none" if ICH,.ui < 

82737.307

Table 4 continued. 

Habitat amount % cbange in babitat 

(krnl-months x 1000) fram yeaJO Change in Total Habitat from Year D 

Non·RSF 

fimll"Perind Data basis Tatal habitat RSF habitat habitat RSF habitat Tnlal haMtat Direction Magnitude Sum

Archie_lago 

Year-tO Satellite data 6,90H9 3% Expanding or stable Siowto none Stabl' Year 0 Satellite data 6,689.17 0% Expanding.of stable Slow to none Stable 

Year 0 GeM tnInimum 5,784.55 0% ExpandU'lg Of stable Slow to none Stable 

Year 45 GCMmmimum 4,986.82 x -14% Contracting Slow to none Conrr-acting 

Year 75 GeM minimum 4,586,46 ·21% Contracting Moderate Contracting Year 100 GCMminimum 4,378.68 Contracting Moderate Contrnctmg 

Year 0 Ensemble mean 7,158.84 0% Expanding or stable Slow to none Stable 

Year45 Ensemble mean 6305.10 -12% Contracting Slowto none Contracting Year 75 Ensemble mean 5,722.95 -20% ContractH1g Moderate Contractmg 

Year 100 Ensemble mean 5,572.14 -22% Contracting Moderate Contracting 

Year 0 GeM maximum 8,298.05 0% Expanding Or stable Slow to none Stable 

Year 45 GCMmaximum 8,013.84 HJ% Contracting Slow to none Contractmg Year 75 GCMmaximum 6,802.87 -18% Contracting Moderate ContractlOg 

Year 100 GeM maximum 6.568.13 -2\% Contracting Moderate 

Polar Basin OiveT2ent EcoreDion 

Year -to Satellite data 3\066.08 12,253.30 22,812,78 5% 4% Expanding or stable Slow to none Stable 

VearO Satellite data 33,563.40 11,633.44 21,929.96 0% 0% Expanding or stable Slow to none Stable 

Year 0 GCMmimmum 31)41.23 11,032.20 20,709.03 0% (P/o Expandir,g or stable Slow to none Stable 

Year 45 GCMmmimum 21,207.61 7,043.79 14,163.82 "36% ·33% Contracttng Fast Contracting 

Year 75 GCMminimllm 18,50341 6,107.96 12,395.45 -45% -42% Contracting Fast Contracting 

Year 100 GCMminimum 16,871.39 5,575.40 11,295.99 -47% Contracting fast Contracting 

Year 0 Ensemble mean 38,753.63 12,56031 26,193.32 0% 0% Expandmg or ;,;table Slow to none Stable 

Year 45 Ensemble mean 30,582.79 10,135.02 20,447.77 ·21% Contracting Mcderate Contracting 

Year 75 Ensemble mean 26,399.58 8,580.94 17,818.64 -32% -32% Contracting Fast Contracting 

Year 100 Ensemble mean 24,992.14 8,067.62 16,924.52 -36% -36%· Contracting Fast Contracting 

Year 0 GCMmaximum 45,672.05 14,591.97 31,080.08 0% 0% Expanding or stable Slow to none Stable 

Year 45 GeM maximum 36,092.83 12,158.61 23,934.22 ·17% Contracting ModerQtc Contracting 

Year 75 GeM max.imum 33,66481 10,045-76 23,619.05 -31% Contracting Moderate Contracting Year 100 GeM maximum 34,293.06 11.479.88 n,81318 ·21% -25% Conuacting Moderute Contracting 

82737.308

Table 4 continued, 

Habitat amount OIl! change in babitat 

(km2-months x 1000) hom yeerO ____ in Total Habitat from Year 0 

N.n,RSf 

Time Period Data basis Total habitat RSf habitat habitat RSF habitat Total habitat Direction Magnitude Sum

Polar Basin Convergent Ecoragion 

YC<Lr-lO Satellite data 6,063.56 5.44034 623.22 4% 4% Expanding or stable Slow to none 

Year 0 Satellite data 5,823 36 5.21413 609.23 0% 0% Expandmg or stable Slow to none Stable 

Year 0 GCMm1l'limum 4,945.44 4,136.50 808.94 0% 0% Expanding or stable Slow to none Stable 

Year45 GeM minimum 4,42439 4,063.23 361.16 -1% -It% Contractmg Slow to none Contracting 

Year 75 GCMminimum 4,042.15 3,177.04 865.11 -23% -18% Contracting Moderate Contracting 

Year 100 GeM minimum 3,539.31 2,881.99 657.32 -30% -28% COJltracting Moderate Contracting 

Year 0 Ensemble mean 6,305.23 5,158.01 1,147.22 0% 0% Expanding or stable Slow to none Stahle 

Year45 Ensemble mean 5,334.67 4,443.39 891.28 -14% Contractmg Moderate Contractmg 

Year 75 Ensemble mean 4,739.31 3,989.57 749.74 Contracting Moderate:: Contracting 

Year toO Ens.emble mean 4,566.56 3,867.34 699.22 -28% Contracting Moderate Contracting 

Year 0 GCM maximum 7,068.41 6,023.03 1,045.38 0% 0% Expanding or stable Slow to none Stable 

Year45 GCM maximum 6,115.28 4,560.71 1,55457 -24% -13% Contractmg Slow to none Contracting 

Year?5 GeM maximum 5,538.43 4,202.13 1,336.20 -30% -22% Contracting Moderate Contracting 

Year 100 GCMmaximum 5.625.88 4.143.95 1,48193 -31% -20% Contractins Moderate Contracting 

Global (aU ecoregions combined I 

Year -10 Satellite data 64,292.03 7% Expanding or stable Slow to none Stable 

Year 0 Satellite data 59,955.53 0% txpandmg or stable Slow to none Stable 

Year 0 GCMminimum 53,68855 0% Expanding or s.table Slow to none Stable 

Year45 GCMminimum 40,673.75 -24% Contracting Moderate Contracting 

Year 75 GCMminimum 34,772,70 Contracting Fast Contr"dcting 

Year 100 GCM minimum 32,40493 -4()% Contracting Fast Contractmg 

Year 0 Ensemble mean 68,558.26 x 0% Expanding or stable SloW to nOne Stable 

Year 45 Ensemble mean 56,174.92 Contracting Moderate Contracting 

Year 75 Ensemble mean 48.994.16 Contracting Moderate Contracting 

Year 100 Ensemble mean 46.924.09 Contracting Fast Contracting 

Year 0 GCM maximum 81,217.27 D% Expanding or stable Slow to none Stable 

Year 45 GCM maximum 69,045.78 -15% Contracting Slow to none Contracting 

Year 75 GeM maximum 61,915.40 Contracting Moderate Contractmg 

Year 100 GeM maximum 62,28933 -23% Contracting Moderate C:'(;Jl1tfilcting 
81 


82737.309

Table 5. Numbers and densities of polar bears by ecoregion, based on habitat amount at year 0 (Table 

4). 

x = not calculated or data not available. 

Numbers 

of polar 

bears 

Polar bear density ____________ ~(~km~'-m~on=thsxl000,=xp~er~b~e~a~r) ____________ __ 

Ecoregion Seasonal Ice 

Archipelago 

Polar Basin Divl!rgcnt 

Polar Basin Convergent 

7800 

5000 

9500 

2200 

Crude density, based on non-RSF habitat 

x 

7.695 

0.923 

Ecological density, based on RSF habitat 

x 

x 

1.749 

3.386 

Total density, based on total habitat 1.779 

1.338 

82737.310

Table 6. Polar bear carrying capacity forecast for each ecoregion, time period, and modeling basis, by the deterministic polar bea

carrying capacity model. 

x not calculated or data not available. 

Carrying capacity (K) expressed as polar 

bear population size (no, bears'. not 

nonnalized to year 1) 

BaSRd 

Based Based (In nonon all on RSF RSF 

0/(1 change in carrying capacity 

___ ,,-fro::.:m year 0 

Based 

Based Based on 

on all 011 RSf RSf 

Carrying capacity Change in total carrying capaci

nonnalized to year 0 fromyear() 

Based on 

Time RSf 

Period Data basis habitat habitat habitat TOTAL habitat habjtat ha,,,b.,,,·taoot_..cT,,,O,,,TA,,,L,--,,==_-,-,=,--,==",--_-,,,, Su

Seasonal Ice Ecoregion 

Year-to Satellite data 9,137 9)37 17% 17% 9,J37 stab_Inef moderate increaslO

Year 0 Satellite data 7,800 7,800 0% 0"/(1 7,800 stabjncr Low to none Stable Year 0 GCMminimum 6,304 6,304 0% 0% 7,800 stab_iner Low to none Stable 

Year 45 GCMmmimum 5,651 5,651 -10% -10% 6,992 Decreasing Low to none Decreasi

Year 75 GCMminimum 4294 4,29' -32% ¥32% 5,313 Decrea<;ing high Decreasi

Year 100 GCMmmimum 42SO 4,280 ·32% -32% 5,295 Decreasing high DecreasiYeilrD Ensemble mean 9.183 9,183 0% 0% 7,800 stab_incr Low to none Stable Year 45 Ensemble mean 7,841 7,841 -15% 6.660 Decreasmg Low to none Dec-reasl

Year 75 Ensemble mean 6,81& 6,818 ·26% ·26% 5,791 Decreasmg modefilU! Decreasi

Year 100 Ensemble mean 6,628 6.628 ·28% -2&% 5,629 Decreasmg moderate Decreasi

Year 0 GeM maxImum I J,340 1/,340 0% 0% 7,800 stab_mer Low to none Stable 

Year 45 GeM maximum 10,579 10,579 ·7% ·7% 7,276 Decreasing Low to none Decreasm

Year 75 GeM maxImum 8.941 8,941 -21% -21% 6,150 Decreasing moderate Decreasi

Year 100 GCJ::1 maXlmum 8,880 8,880 -22% -22% 6.108 Decreasing moderute pecreasi

4 Direction was categorized into "decreasing" if CK"r; < 0 or "stable or increasing" if CK,.G ;;: 0 . 

5 Magnitude was categorized into "high" if ICK,.,,! > 30.0, "moderate" if 15.0 < ICK,.G! ::; 30.0, and "low to none" if iCK"" I < 15.

82737.311

Table 6 continued, 

Carrying capacity (K) expretlsed 8S polar 

bear population sile (no. bears), not 

n.ormafized to year 0 

Bas.ed 

Based Based on nonOR aU on RSf RSF 

% change in carrying capacity Carrying capacity 

from year 0 _ Itormaliud to year 0 

Based 

eased Based 011 non" 

on aU on RSF RSF 

Change in total carrying capaci

from yearO 

Time 

Period Data basis habitat habitat habitat TOTAL habitat habitat habitat TOTAL 

Based 011 

RSf 

habitat TOTAL Direction Magnitude Su

Ye-ar·1O Satellite data Year 0 Satellite data Year 0 GeM rninimum Year 45 GeM minimum Year 75 GeM minimum 

Year 100 GeM minimum Ycar 0 Ensemble mean 

Year 45 Ensemble mean Year 75 Ensemble mean 

Year 100 Ensemble mean 

Year 0 GeM maximum Year 45 ('.rCM maxImum 

Year 75 GCMmaxlmull1 Year 100 GeM maximum 

5,160 

5,000 

4,324 

3,728 3,428 

3,273 

5,351 

4,713 

4,278 

4,165 

6,203 

5,990 

5,085 

4,910 

x 

5,160 5,000 

4)24 

3,728 

3,428 

3,273 

5,351 

4,713 4.278 4,165 

6,203 

5,990 

5,085 

Year-lO 

YcarO 

Year 0 

Year 45 

Year?5 

Year 100 YearO 

Year 45 Year 75 Year 100 Year 0 

Year 45 

Year 75 

Satclitte data 7,004 2,965 9,969 

SatelUte data 6,650 2,850 9,500 

GeM mimmum 6,306 2,691 8,998 GeM mmimum 4,026 1.841 5,867 GeM mimmum 1,491 1,611 5,102 

GeM mmimum 3,1.87 1,468 4,655 

Ensemble mean 7,.1-30 3,404 10,5&4 

Ensemble mean 5,793 2,657 8A51 Ensemble mean 4,905 2,316 7,221 Ensemble mean 4,612 2,199 6.811 

GeM maximum 8,341 4,039 12,3&0 

GeM maximum 6,950 3)10 10,061 

GeM maximum 5,742 3,070 8,812 

Year 100 GeM maximUm 6,562 2,965 9,527 

Archipelago Ecoregion 

3% 

0%. 

0% 

-14%_ 

-21% 

-24% 

0% 

-12% -20% 

-22% 

0% 

-3% 

x 

5% 

0% 0% 

¥36% 

-45% -49% 

0% 

-19% 

0% 

-17% 

-31% 

-21% 

4% 

0% 0% 

,32% 

-40% 

-45% 

0% 

-22% -32% 

-35% 

0% 

-23% 

-24% -27% 

3% 

0% 

09/0 

-14% 

-21% 

-24% 

0% 

-12% 

·200h 

-22% 

0% 

-3% 

-18% 

5% 

0% 0% 

·35% 

-43% 

A8% 

0% 

-20"10 

·32% 

-36'% 

0% 

-29% 

·23% 

7,004 

6,650 

6,650 

4,246 

3,6B2 

3,361 

6,650 

5.366 

4,543 

4,271 

6,650 

5,541 

4,578 

5,232 

5,1(,0 stab_incr Low to none Stable 

5,000 stab_Iocr Low to none Stable 

5,000 stab_incr l.ow to oooe Stable 

4,310 Decreasing Low to none Decreasi

3,%4 Decreasing Moderate Decreasi3,785 Decreasing Moderate Decreasi

5,000 Stable-Intr Low to none Stabie 

4,404 Decreasing Low to none Decfl!asi

3,997 Decreasing Moderate Decreasm

3,892 Decreasing Moderate Decreasi

),000 Stable-lncr Low 10 n'lne Stable 

4,829 Decreasing Low to none Decreasm4,099 Decreasing Moder.ate Decreasi

9,969 Low to none 

9,500 Stable-incr L.(lw to none 

9,500 Stable-lncr Low to none 

6,\95 Decreasing High 

5)87 Decreasing High 

4,915 Decreasing High 

9,500 Slllble-tncr Low to none 

7,585 Decreasing Moderate 

6,481 Decreasing High 

6.114 Decreasing thgh 

9,500 Low to none 

7"720 Decreasing Moderate 

6,762 Decreasmg Moderate 

7,311 Decreasmg Moderate 

Stable 

Stable 

Stable 

DecreasmDecreasiDecreasi

5mble 

Decreasi

DecreasiDecreas

Stable 

Decreas

Decreasi

Decreas

82737.312

Table 6 continued. 

Time 

Peri.od Data basis 

Year Satellite data Yet:lf 0 Satellite data Year 0 GeM minimum 

Year 45 GeM minimum Year 75 GeM minimum 

Year 100 GeM mmimum 

Year 0 mean 

Year 45 Ensemble mean 

Year 75 Ensemble mean 

Year 100 Ensemble mean 

Year 0 GeM maxImum 

Year 45 GeM maximum 

Year 75 GeM maximum Year 100 GeM maxImum 

Year -JO Satellite data Year 0 Satellite data 

Year 0 GeM mimmum 

Year 45 GeM minimum 

Year 75 GCM minimum 

Year lOG GeM minimum 

Year 0 Ensemble mean Year 45 Ensemble mean 

Year 75 Ensemble mean Year 100 Ensemble mean 

Year 0 GCM maximum 

Year 45 GeM maximum 

Yea! 75 GeM maximum 

Year 100 GeM maximum 

Carrying capacity (K} upressed as polar 

bear population size (mt bears). not 

normalized to year 0 

% change in carryin.g capacity 

from year 0 

Catrying c.apaeity 

normalized tD year 0 

Change in total carlYing capac

ffl)m vearO 

Based 

ODan 

habilat 

Based 

Based on 

on RSF RSF 

habitat habitat 

I,W7 

1,540 

1,222 

1,200 

938 

851 

1,523 

],312 

1,178 1.142 1,779 

1.347 

1.241 

1,224 

675 660 

876 

391 9J7 

712 

1)43 

966 

812 

757 

1,132 

1,684 1.448 1,605 

Bas:ed 

Based Based UR no1'lon all on RSF RSF Based Oh RSF 

TOTAL habitat habitat habilal TOTAL habitat 

Polar Basin Convergent Ecoregion 

2)82 

2,200 2.098 

1,591 

1,876 

1.563 

2.766 

2,27& 

1,991 

1,900 

2,911 

3,031 

2.689 

4% 

1),% 

0% 

-2% 

-23% 

,JO% 

0% 

_\4% 

-23% -25% 

0% 

·24% 

-30% 

2% 

0% 0% 

-55% 

7% 

-19% 

0% 

-22% 

-35% 

,39% 

0% 

49% 

28% 

4% 

0% 

0°/(1 

-24% 

-11% 

-25% 

0% 

-28% 

0% 

4% 

-8% 

1.607 1.540 

1.540 1.513 1,183 

1,073 

1540 1.327 

1.191 

1,155 

1,540 

{,1M 

1.074 

2,829 -31% 42% 1,060 

Globallall ecoregions combined, 

26,54& 

24,500 

21.723 

16,837 

14,700 

1),771 

27.884 23.283 20,307 

19.503 

32,834 

29,,661 

25.526 26,146 

8% 

0% 

0% 

-32% -37% 

0% 

-11% -27% 

-30% 

0% 

-22% 

TOTAL Direction Magnitude 

2,282 Stable-lner Low to none 2)00 Stable-Incr Low to none 2,200 Stable·lncr Low to none 

1,669 Decreasing Moderate 

1,967 Decreasing Low to none 

1,639 Decre::ssing Moderate 

2,200 Low 1O none 

1,8 12 Decreasing Moderate 

1,5&3 Decreasing Moderate 

1,511 Decreasing High 

2,200 Stable·lner Low to nOf/e 2,290 StableM lncr Low to none 

2,032 Decrcasmg Low to none 

Slable 

Slable 

Stable 

S

DecreasDecreasDecreas

Stable 

De-creas

Decreas

Decreas

Stable 

Stable 

Decrea')

2,J38 Decreasmg Low to none Decreas

26,548 Stable-Incr Low to ntlne 

24,500 Low to none 

24,500 Stable¥lncr Low to none 

JS,989 Decreasmg Modemte 

16,579 Decreasing High 

15,53 i Decreasing High 

24,500 Low to none 20,457 Decreasing Moderate 

17,843 Decreasmg Moderate 

17,136 Decreasing High 

24,5(}O Stable· Iocr Low to none 

22,132 Decreasmg Low to none 

19.047 Decreasmg Moderate 

19,510 Decreasing Moderate. 

Stable 

Stable 

Stable 

Decreas

Decreas

Decreas

5t<Jblc 

Decreas

Decreas

Decreas

Stable 

Decreas

Decreas

Decreasi
85 


82737.313

Table 7. Overall summary of change in total polar bear carrying capacity from present levels (based on 

applying results of carrying capacity calculations in Table 6 to the rule set in Table 2). 

Year 0 GCMminimum 

Year 45 GCMminimum 

Year 75 GCMminimum 

Year 100 

Year 0 Ensemble mean 

Year 45 Ensemble mean 

Year 75 Ensemble mean 

Year 100 Ensemble mean 

Year 0 GCMmaximum maintained 

Year 45 GCM maximum decreased 

Year 75 decreas~d 

Year 100 

Year -10 

Year 0 

Year 0 GCMminimum maintained 

Year 45 GCMminimum decreased 

Year 75 GCMminimum decreased 

Year 100 GCMminimum 

Year 0 Ensemble mean maintained 

Year 45 Ensemble mean decreased 

Year 75 Ensemble mean deerellSed 

Year 100 Ensemble mean 

Year 0 GeM maximum 

Year 45 GCM maximum 

Year 75 

Year 100 

Year -10 

Year 0 Satellite data 

Year 0 

Year 45 

Year 75 GCM minimum 

Year 100 GeM minimum 

Year 0 Ensemble mean 

Year 45 Ensemble mean 

Year 75 Ensemble mean 
86 


82737.314

Time Period Data basis 

Year 100 Ensemble mean 

Year 0 GCM maximum 

Year 45 GCMmaximum 

Year 75 GCM maximum 

Year 100 

Year -10 

Year 0 Satellite data 

Year 0 GCM minimum 

Year 45 GCM minimum 

Year 75 

Year 100 GCM minimum 

Year 0 Ensemble mean 

Year 45 Ensemble mean 

Year 75 Ensemble mean 

Year 100 Ensemble mean 

Year 0 GCM maximum 

Year 45 GCM maximum 

Year 75 GCM maximum 

Year 100 GCM maximum 

Glob 

Year -10 maintained 

Year 0 maintained 

Year 0 GCM minimum maintained 

Year 45 GCM minimum 

Year 75 GCMminimum 

Year 100 GCM minimum 

Year 0 Ensemble mean 

Year 45 Ensemble mean 

Year 75 Ensemble mean 

Year 100 Ensemble mean 

Year 0 GCM maximum maintained 

Year 45 GCM maximum decreased .. 

Year 75 GCM maximum . decreased 

Year 100 GCM maximum 
87 


82737.315

Table 8. Results of the Bayesian network population stressor model, showing the most probable 

outcome state, and probabilities of each state (larger, same as now, smaller, rare, and extinct), for 

overall population outcome (node Dl; see Figure 5). 

Node 01: Overalll)opulation Outcome 

P(01= 

Time Most probable P(Ot= same as P(OI= 1'(01= P(Ot= 

eeriod Basis outcome larger) nowl smaUcrl rare} extinctl 

Seasonal Ice Ecoregion 

Year-IO Satellite data larger 93.92% 575% 0.30% 0.02% 0.00% 

Year 0 Satellite data -same_as._now 2185% 43.72% 1898% 8.37% 707% 

Year 45 OCMminimum extinct 0.05% 0.61% 9.79% 12.36% 77.19% 

Year 75 GeM minimum extinct 000% 0.09% 348% 828% 88 15~/o 

Year 100 GCMminimum extinct 0.00% 0.09% 3.48<1/0 8.28°/(1 88.15% 

Year 45 Ensemble mean extinct 0,05% 0.61% 9.79% 1236% 77.19% 

Year 75 Ensemble mean extinct 0.00% 0.09% 3.48% &.28% 88.15%, 

Year 100 Ensemble mean extinct 000% D.09% 3A8% 8.28% 88.15% 

Year 45 GCMmaximum extinct 0.24% 2.20% 24.37% !9.35% 5385% 

Year 75 OCMmaximum extinct 001% 0,18% 5.17% 9,52% 85.11% 

Year 100 GCMmaximum extinct 0.01% OJ8~/(I 5.17% 9.52% SS.l!% 

Archieclago Ecoregion 

Ycar-IO Sate!llte data same_as_now 22.5!'.l/~ 34.73'% 31.48% 872% 2.56% 

YearO Satel!ite data larger 69.4&% 29,26% \.O6~/(). 0.19'% 0000/0 

Year 45 GCMminimum smaller 457% 12.93~/0) 51.34% 20.60~/[J 10 56% 

Year 75 GCMmmimwn extmct 089% 3.16% 32,07';;';0) 19.34% 4454% 

Year 100 GCMminimulll extinct 138% 4.65% 33.38% 19.51% 4107% 

Year 45 Ensemble mean smaller 4.57% 12.93% 51.34% 20.60% 10.56% 

Year 75 Ensemble mean extinct 1.05% 334% 32.25% 26.07% 37301

% 

Year 100 Ensemble mean extinct 1.38% 4.65% 3338% 19.51% 4107% 

Year 45 GCMmaximllm smaller 5.83% 15.93% 5235% 18.01% 7.88% 

Year 75 GCMmllximum smaller 4.42% 12.40% 4"9.36% 22.96% 10.85% 

Year 100 GeM maxImum extinct 1.38% 4.65% 33.38% 1951% 4107il/(} 
88 


82737.316

Table 8 continued. 

Node Dl: Overall Population Outcome 

P(Dl= 

Time Most probable PlOl= same as P(I)l= P(Ol= P(Ol= 

I!criod Basis outcome larger) nowl .maller) rare} extinctl 

Polar Basin Divergent Ecoregion 

Year ·10 Satellite data larger 99,78% 0.22% 0,00% o.oo~/o 0.00% 

Year 0 Satellite data same_as _ nQw 24.16% 56,60% 13.36% 4.73% t 14% 

Year 45 GeM minimum extmct O.OO%} 0.00% 286% 1058% 86.5.5% 

Year 75 GCMminimum extmct 0.00% 000% 3.07% 1091% 86.02~'n 

Year 100 GeM minimum extlOct 0.00% 0,00% 188'V(l 12.23% 83,89% 

Year 45 Ensemble mean extinct 0.00% 0.18% 6.16% 1134% 80.33%. 

Year 75 Ensemble mean extinct 000% 0.00% 2.86% 1058% 86.55% 

Year 100 Ensemble mean cxtmct o OOIVO 0,00% 388% 12.23% 83.89% 

Yea.r45 GeM maximum extinct 0.00% 0,18% 6.16% 13.34% 80.33% 

Year 75 GeM maximum extinct 000% 0.07% 4.46!}f, 12.00YI;I 83.47% 

Year 100 GCM maximum extinct 0.00% 0,09% 5.73% J184% 80.33% 

Polar Basin Conyer~ent Ecore~ion 

Year -10 Satellite data larger 98.39% 1.61% 000% 0.00% 000% 

Year 0 Satellite data larger 7L69% 27.49%) 063% 0.19% 0,00% 

Year 45 GeM minimum extinct 026% 2.30% 27.98% 3159% 37,87'% 

Year 75 GeM minimum exlmct 0.00% 0.39% 9.68% 13.24<% 76,70% 

Year 100 GCMminimum extinct 000% 0.39% 968% 13.24% 76.70% 

Year 45 Ensemble mean extinct 0.48% 2.72% 29.27% 32.46% 35,06% 

Year 75 Ensemble m~an extmct 0.00% 027% 8.40% 15.10% 7623% 

Year 100 Ensemble mean extmct 0.02% 044% 9.49% 12.75% 77.30% 

Year 45 GCMma.-ximum extinct 0.14% 1.24% 2U5% 30.71% 46.77% 

Year 75 GeM maximum extinct 002% 0.46% 12.64% 24,46% 62.41% 

Year 100 GeM maximum extmct 0.02% 044% 10.51% 16.52% 72,52% 

82737.317

Table 9 continued. 

Node C3: Distribution Response Node C4: Numerical Response 

P(C3= 

P(C3= reduced P(C3= P(C4= P(C4= P(C4= 

Time Most probable same as but transient P(C3= Most probable increased same as reduced P(C4= 

rare) 

periodllllsis outcome nowl residenl) " outcol11l> density) now) density) 

Satellite data 

Year 0 Satell ite data 

Year 45 GeM minimum 

Year 75 GeM minimum 

Year 100 GeM minimum 

Year 45 Ensemble mean Year 75 Ensemble mean 

Year 100 Ensemble mean 

Year 45 GeM maximum 

Year 75 

Year 100 

GeM maximum GeM maximum 

Year 10 Satellite data 

Y car a Satellite data 

Year 45 GeM minimum 

Year 75 GeM minimum 

Year 100 GeM minimum 

Year 45 Ensemble mean 

Year 75 Ensemble mean 

Year 100 Ensemble mean 

Year 45 GeM maximum 

Year 75 GeM maximum 

Year 100 GeM maximum 

same_as _now 

same_as _now 

extirpated extirpated 

extirpated 

extirpated 

extirpated 

extirpated 

extirpated 

100.00% 

85.66% 

0.00% 0.00% 

a.OO% 

2.14% 

0.1)0% 

0"00% 

2.14% 

0.00% 

837% 

0"00% 0.30% 

1.50% 

2.99% 

0.00% 

1.50% 

2.99% 

Polar Basin Divergent Ecoregion 

0,00% 

4.82% 

1&.00% 

18.27% 

19,35% 

{9,98% 

18,00% 

1935°/0-

t9.98% 

0.00% 

1.14% 

82"00% 8L43% 

79.15% 

74.89% 

82,00% 

79J5% 

74,89% 

increas:ed _density 

reduced_density 

reduced_density 

reduced _ delisity reduced_density reduced_density reduced_density reduced_density 

9V8% 

24.16% 

0.00% 

0.00% 0.00% 0.00% 

0.00% 

0.00% 0.00% 

022% 

59.71% 

0.00% 

0.00% 0.00% 

0.56% 

0.00% 0.00% 0.56% 

0.00% 

16.12% 

5300% 

53.33% 

54.65% 53,90% 

53.00%) 

54.65% 

53.90% 

0.00% 

(tOO% 

3100% 30,91% 

30.55% 30.04% 31.00% 

30.55% 

30.04% 

extirpated 1.02% 1.50% 19.04% 78A4% reduced_density 0.00% 0.26% 53.42% 30.55% 

extirpated J 11% 330% 20A4.%____ }:5._J5% _ 0.00% .. _

same_as_now 

transient_visitors 

extirpated extirpated 

translcnt_ Ylsitors 

extirpated exttrtyJled 

transient_visitors 

extirpated 

100.00% 

99.40% 

l7Jl% 

4.72% 

4.72% 

18.56% 

3.53% 

4.55% 

11.44% 

5.32% 

0.00% 

0.43% 

14.07% 

8.32% 8.32% 

13.79% 

5.29% 

8.08% 

10.51% 

5.39"10 

Polar Basin Convergent Ecoregion 

0.00% 

0.18% 

40.63 D/a 

15.48% 

1548% 

42.66% 

20.93% 

15.05% 

41.&8% 

36,12% 

0.00% 0.00% 

27,59%. 

71.48% 7L48% 

24.99% 

70.24% 

72.32% 

3617% 

53.17% 

increased_density 

Increased_density 

reduced_density 

reduced_density reduced_density reduced _ denslty 

reduced_density reduced_density reduced_density 

extirpated 4 . .80% 7.22% 21 82'Vo 66J6% 

98.39% 

71.69% 

0,31% 0.00% 

0.00% 0.69% 

0.00% 

0.04% 023% 

0,05% 0.05% 

27,65% 

5,23% 

1.27% 

1.27% 

6.01% 

0.95% 

\.34% 

3.51% 

1.58% 1.42% 

0,00% 

0.66% 

60.81% 

55.04% 

55.04% 

61.31% 

54.53% 

55.0B!)/o 

58.19% 

55.44% 55.19% 

0.00% 

0.00% 

22,19% 28.82% 

28"82% 21.10% 29.37% 28,72% 25"11% 

28.31% 28.59% 

82737.318

Table 9. Results of the Bayesian network population stressor model, showing the most probable outcome states, and probabilities of 

each state, for the distribution response and numerical response outcomes (nodes C3, C4; see Figure 5). 

Node C3: Distribution Response 

P(C3= 

P(C3= reduced P(C3= 

Time Most probable same as but transient P(CJ= 

Jl!!iod 8asls __ . _____ ._. outcome now) resident) visitors) extirpated) 

Year-IO Satel!!tedata 

Y car 0 Satellite data 

Year 45 GeM mimmum Year 75 GeM mInimum 

Year 100 GeM minimum 

Year 45 Ensemble mean 

Year 75 Ensemble mean 

Year 100 Ensemble mean 

Year 45 GeM maximum 

Year 75 GeM maximum 

samc_as_oow sumc_3,'Ul0W 

extirpated extirpated 

extirpated 

extirpated 

extlfpated extIrpated 

extirpated 

extirpated 

99.79% 

72.47% 

4.69% 

0.94% 0.94% 

4,69D/o 

0.94%· 

0.94% 

14.8]% 

1.96% 

021% 

11.59% 

8.13% 

L66% J.66{l/(1 

8.13% 

1.66% 1.66% 

20.97% 

352% 

Seasonal Ice Ecoregion 

0.00% 

8.88% 

14.51% 

12.70% 

12.70% 

14.51% 

12.70% 

12.70% 

16,84% 

13.30% 

0.00% 

707% 

72.;;8% 

84.70% 84.70% 

72.68% 

84.70% 

8470% 

4735% 

81.22% 

Most probable 

outcome 

increased_density 

samc)l.s_now 

reduced_density redu\.:cd_density reduced_density 

_density 

reduced_density reduced_density reduced _density reduced_densitY 

Year 100 GCMmaximum extirpated 196% 352% 13,30% 81.22% reduced .. _density 

YearMIO Satell!tedara 

Year 0 SateHite data 

Year 45 GeM minimum Year 75 GeM mmimum Year 100 GeM minimum 

Year 45 Ensemble mean 

Year 75 El1scmble mean Year 100 Ensemble mean 

Year 45 GeM maximum 

Ye-ar 75 GeM maxiI1lUm 

Year 100 GeM maxlmum 

"Same_as _now 

same_as _now same _as _,now 

extu-P3ted extirpated 

same_as_oow 

transient_visitors 

extirpated 

same_as. ,now same_3s_noW 

extirpated 

71.72% 99,40%1 

56.09% 

23.49% 

23.49% 

561l9"/o 

24,66% 23.49% 

61.02% 

51.08% 

23.49% 

18.29% 

0.43% 

16.39% 

25.05% 

25.05% 

1639% 

1746% 

2505% 

15.59% 

16.90% 

25.05% 

Archipelago Ecoregion 

8.74% 

0.18% 

24.50% 

16,32% 

16.32% 

24.50% 

32,64(1/0-

16.32% 

21.31% 

28,65% 

1632% 

J 25% 

0.00% 

3.03% 

35.14% 

35,14% 

3.03% 

25.25% 

35.t4% 

2.08% 

3.37% 

35.14% 

same_aSjlQW 

Increased _ demlty 

reduced_density reduced_density 

r-educed _ densl.ty 

reduced __ density 

reduced_density 

reduced_density 

reduced_density 

reduced density 

Node C4: Numerical Response 

P{C4= 

increased 

density) 

93.93% 

21.90% 

0.09% 0.01% 

001% 

0.09% 0.01% 

0.01% 

0.35% 

0.02% 

0.02% 

2436% 

69.49% 

536% 

114% 

1.76% 

5.36% 

1.34% 

\.76% 

6,81% 5.36% 

1.76% 

P{C4= 

same as 

now) 

5.83% 

47.20% 

1.40% 

027% 

0.27% 

140% 

0,27% 0.27% 

4.54% 

0.57% 

0.57% 

41.18% 

2941% 

15.63% 

4.99% 

7.92% 

15.63% 

5.39% 

7.92% 

18.88% 

15.63% 

7.92% 

P(C4= 

reduced 

density) 

024% 

30.90% 

56.27% 53.42% 

53.42% 

56.27% 53.42% 53.42% 

60,16% 

5388% 

5388% 

31.17% 

1.11% 

63.62% 

55.92% 

62.24% 

63.62% 56.47% 

62.24% 

62.63% 

63.62% 62.24% 

P{C4= 

rare) 

0.00% 

0.00% 

28.3&% 

30.54% 

3054% 

2838% 

3(),54% 3054% 

23,40% 

30.03% 

3003% 

2.19% 

0.00% 

8.32% 

21.22% 

18.53% 

8.32% 

20.)8% 

18.53% 

6.32% 

832% 

18.53% 

82737.319

Table 10. Results of the Bayesian network population stressor model, showing the most probable outcome states, and probab

each state, for habitat threats and director mortalities summary variables (nodes F2 and A I; see Fig. 5). 

Node F2: Factor A: Habitat Threats Node At: Factor B: Direct Mortalities 

P(F2= P(AI,. 

Time Most probable improve- P(F2=no P(F2= minor P(F2= major Most probable P(AI: same as P

I!eriod Basis outcome ment) effect) restriction I restrictionl outcome fewer) now) m

Seasonal Ice Ecoregion 

Year -10 Satellite data improvement 94.60% 5.00% 0.40% 0.00% fewer 100.00% 0.00"/0 

Year 0 S atell ite data no_effect 26.41% 36.84% 23.02% 13.72% same 0.00% 100.00% 

Year 45 GCMminimum major_restriction 0.08% 2.00% 16.64% 81.28% same_as_floW 0.00% 62.60% 3

Year 75 GCM minimum major 0.00% 0.00% 4.72% 95.28% same_as_now 0.00% 60.00% 4

Year 100 GCMminimum major_restriction 0.00% 0.00% 4.72% 95.28% same_as_oow 0.00% 60.00% 4Year 45 Ensemble mean major_restriction 0.08% 2.00% 16.64% 81.28% same_aS_flOW 0.00% 62.60% 3

Year 75 Ensemble mean majorJestriction 0.00% 0.00% 4.72% 95.28% same_as_now 0.00% 60.00% 4

Year 100 Ensemble mean major_restriction 0.00% 0.00% 4.72% 95.28% same_as_now 0.00% 60.00% 4

Year 45 GCMmaximum major_restriction 0040% 9.68% 43.60% 46.32% same.as_now 0.00% 62.60% 3

Year 75 GCM maximum major_restriction 0.00% 0.08% 9.60% 90.32% samc_as_now 0.00% 60.00% 4

Year 100 GCMmaximum maior restriction 0.00% 0.08% 9.60% 90.32% same as now 0.00% 60.00% 4

Archipelago Ecoregion 

Year -10 Satellite data no_etIect 39.00% 44.60% 16.40% 0.00% same_as_Ilow 4.80% 53.00% 4

Year 0 S atell ite data improvement 88.56% 10.43% 1.01% 0.00% same_as_oow 0.00% 100.00% 

Year 45 GCMminimum no_effect 32.48% 41.28% 22.30% 3.94% more 0.00% 0.00% 1Year 75 GCMminimum minor_restriction 4.08% 24.32% 40.32% 31.28% more 0.00% 30.00% 7

Year 100 GCMminimum minor Jestriction 4.08% 24.32% 40.32% 31.28% same_as_now 0.00% 60.00% 4

Year 45 Ensemble mean no_effect 32.48% 41.28% 22.30% 3.94% more 0.00% 0.00% 1

Year 75 Ensemble mean minor_restriction 4.96% 25.44% 39.84% 29.76% more 0.00% 30.00% 

Year 100 Ensemble mean minor_restriction 4.08% 24.32% 40.32% 31.28% same_as now 0.00% 60.00"/0 4

Year 45 GCMmaximum improvement 41.92% 38.40% 17.06% 2.62% more 0.00% 0.00% 1

Year 75 GCMmaximum no_effect 32.48% 41.28% 22.30% 3.94% more 0.00% 0.00"/0 1

Year 100 GCMmaximum minor restriction 4.08% 24.32% 40.32% 31.28% same as now 0.00% 60.00% 4

82737.320

Table 10 continued. 

Node F2: Factor A: Habitat Threats Node AI: Factor B: Direct Mortalities 

P(F2= P(AI: 

Time Most probable improve- P(F2= no P(F2= minor P(F2=major Most probable PIAl: same as 

period Basis outcome menl) effect! restriction) restriction) outcome fewer) now) P(A

Polar Basin Divergent Ecoregion 

Year -10 Satellite data improvement 99.68% 0.32% 0.00% 0.00% fewer 100.00% 0.00% 

Year 0 Satellite data no_effect 30.20% 47.24% 20.54% 2.02% same_as_now 0.00% 100.00% 

Year 45 GCMminimum major_restriction 0.00% 0.00% 0.00% 100.00% same_as_now 0.00% 60.00% 

Year 75 GCMminimum major Jestriction 0.00% 0.00% 0.00% 100.00% same_as_now 0.00% 60,60% 

Year 100 GCMminimum major_restriction 0.00% 0.00% 0.00% 100.00% same_as_now 0.00% 63.00% 

Year 45 Ensemble mean major_restriction 0.00% 0.36% 9.80% 89.84% same_as_.now 0.00% 60.00% 

Year 75 Ensemble mean major_restriction 0.00% 0.00% 0.00% 100.00% same_as_now 0.00% 60.00% 

Year 100 Ensemble mean major_restriction 0.00% 0.00% 0.00% 100.00% same_as_now 0.00% 63.00% 

Year 45 GCMmaximum major_restriction 0.00% 0.36% 9,80% 89.84% same __ as_now 0.00% 60.00% 

Year 75 GCMmaximum major_restriction 0.00% 0.00% 5.08% 94.92% O.OOO/O 60.00% 

Year 100 GCM maximum major restriction 0,00% 0.00% 5.08% 94.92% saIne as now 0.00% 63.60% 

Polar Basin Convergent Ecoregion 

Year -10 Satellite data improvement 97.48% 2.52% 0.00% 0.00% fewer 100.00% 0.00% 

Year 0 Satellite data improvement 88.56% 10.43% 1.01% 0.00% same_as_now 0.00% 100.00% 

Year 45 GCMminimlim minor_restriction 1.10% 14.38% 48.19% 36.32% same_as_now 0.00% 60.00% 

Year 75 GCMminimum major_restriction 0.00% 0.00% 23.60% 76.40% same_as_now 0.00% 60.00% 

Year 100 GCMminimum major Jestriction 0.00% 0.00% 23.60% 76.40% same_as_now 0.00% 60.00% 

Year 45 Ensemble mean minor Jestriction 1.25% 15.49% 49.10% 34.16% samc_as_now 0.00% 60.00% 

Year 75 Ensemble mean major_restriction 0.00% 0.00% 17.65% 82.35% same_as_now 0.00% 60.00% 

Year 100 Ensemble mean major_restriction 0,00% 0.24% 22.16% 77.60% same_as_now 0.00% 60.00% 

Year 45 GCMmaximum majof.Jestriction 0.29% 4.22% 45.49% 50.00% same_as_now 0.00% 60.00% 

Year 75 GCMmaximum maj(}r _restriction 0.00% 0.58% 25.18% 74.24% same_as_now 0.00% 60.00% 

Year 100 GCM maximum majorJestriction 0.00% 0.35% 23.l3% 76.52% same_as. now 0.00% 60.00% 

82737.321

Table 11. Results of the Bayesian network population stressor model, showing the most probable outcome states, and probab

each state, for changes in foraging habitat distribution (node D; see Figure 5). 

Node D; Change in Foraging Habitat Distribution 

P(D= P(D= greatly 

improved P{D=same P(D: reduced reduced PID: 

Time period Basis Most erobable outcome availabililyt as now} availability) availability} unavailable} 

Seasona! Ice Ecoregion 

Year-IO Satellite data 50.00% 50.00% 0.00% 0.00% 0.00% 

Year 0 Satellite data reduced_avail 20.00% 60.00% 20.00% 0.00% 

Year 45 GCMminimum Gr_reduced.avail 0.00% 0.00% 20.00% 40.00% 40.00% 

Year 75 GCMminimum Or -,educed. avail 0.00% 0.00% 20.00% 40.00% 40.00% 

Year 100 GCMminimum Or_reduced_avail 0.00% 0.00% 20.00% 40.00% 40.00% Year 45 Ensemble mean Or.reduced_avail 0.00% 0.00% 20.00% 40.00% 40.00% 

Year 75 Ensemble mean Or _reduced_avail 0.00% 0.00% 20.00% 40.00% 40.00% Year 100 Ensemble mean Gr.}educed.avail 0.00% 0.00% 20.00% 40.00% 40.00% 

Year 45 GCMmaximum reduced_avail 0.00% 20.00% 60.00% 20.00% 0.00% 

Year 75 GCMmaximum Gr -,educed. avail 0.00% 0.00% 20.00% 40.00% 40.00% 

Year 100 GCM maximum Gr reduced avail 0.00% 20.00% 40.00% 40.00% 

Year -10 Satellite data same_as _now 0.00% 100.00% 0.00% 0.00% 0.00% Year 0 Satellite data improved_availability 60.00% 40.00% 0.00% 0.00% 0.00";Year 45 GCMminimum samc_as_now 40.00% 60.00% 0.00% 0.00% 0.00% 

Year 75 GCM minimum. same_as_now 40.00"1. 60.00% 0.00% 0.00% 0.00"1. 

Year tOO GCMminimum same_as._now 40.00"1. 60.00% 0.00% 0.00% 0.00% 

Year45 Ensemble mean same_as _now 40.00% 60.00% 0.00% 0.00% 0.00% Year 75 Ensemble mean same_as_now 40.00% 60.00% 0.00% 0.00% 0.00% 

Year 100 Ensemble mean same_as_now 40.00";' 60.00% 0.00% 0.00% 0.00% Year 45 GCM maximum improved_availability 60.00% 40.00% 0.00% 0.00% 0.00% 

Year 75 GCMmaximum 40.00"1. 60.00% 0.00% 0.00% 0.00% Year 100 GCMmaximum same as now 40.00% 60,00% 0.00% 0.00% 0.00% 

82737.322

Table 11 continued. 

Node D: Change in Foraging Habitat Distribution 

PID: PID: greatly 

improved P(D=same PID", reduced reduced 

Timel!eriod Basis Most outcome availabili!l} as now) availabili!I) availability} una

Polar Basin Divergent Ecoregion 

Year -10 Satellite data improved_availability 100.00% 0.00% 0.00% 0.00% 

Year 0 Satellite data reduced_avail 0.00% 20.00% 80.00% 0.00% 

Year 45 OCMminimum unavailable 0.00% 0.00% 0.00% 20.00% Year 75 OCMminimum unavailable 0.00% 0.00% 0.00% 20.00% 

Year 100 GCM minimum unavai lable 0.00% 0.00% 0.00% 0.00% 

Year 45 Ensemble mean Gr _reduced_avail 0.00% 0.00% 20.00% 40.00% 

Year 75 Ensemble mean unavailable 0.00% 0.00% 0.00% 20.00% 

Year 100 Ensemble mean unavailable 0.00% 0.00% 0.00% 0.00% 

Year 45 GCMmaximum GrJeduced_avail 0.00% 0.00% 20.00% 40.00% 

Year 75 GCMmaximum Gr_reduced_avail 0.00% 0.00% 20.00% 40.00% 

Year 100 GCMmaximum Or reduced avail 0.00% 0.00"10 20.00% 40.00% 

Polar Basin Convergent Ecoregion 

Year -10 Satellite data improved_availability 100.00% 0.00% 0.00% 0.00% 

Year 0 Sate Ilite data improved_availability 60.00% 40.00% 0.00% 0.00"/. 

Year 45 GCM minimum reduced_avail 0.00% 20.00% &0.00% 0.00"10 

Year 75 GCMminimum reduced_avail 0.00% 0.00% 100.00% 0.00% 

Year 100 GCM minimum reduced_avail 0.00% 0.00% 100.00% 0.00"10 

Year 45 Ensemble mean reduced_avail 0.00% 30.00% 70.00% 0.00% 

Year 75 Ensemble mean reduced_avail 0.00% 0.00% 70.00% 30.00% 

Year 100 Ensemble mean reduced_avail 0.00% 20.00% 60.00% 20.00% 

Year 45 GCMmaximum reduced_avail 0.00% 30.00% 70.00% 0.00% 

Year 75 GCMmaximum reduced_avail 0.00% 20.00% 60.00% 20.00% 

Year 100 GCM maximum reduced avail 0.00% 20.00% 60.00% 20.00% 

82737.323

Table 12. Results of the Bayesian network population stressor model, showing the most probable outcome states, and probab

each state, for disease/predation and other disturbance factors variables (nodes A4, A6; see Figure 5). 

Node A4: factor C: Disease. predation Node A6: Factor E: Other lactors (natural or man-made) 

P(A4= P(A6= 

Most probable same as P(A4= Most probable improve- P(A6=no P(A6=minor P(A

Time period Basis outcome now) worse) outcome ment) effect) restriction) res

Seasonal Ice Ecoregion 

Year ·10 Satellite data same __ a<:j_TIOW 100.00% 0.00% improvement 84.80% 15.20% 0.00% 

Year 0 Satellite data same_as_now 100.00% 0.00% no_effect 0.00% 100.00% 0.00% 

Year 45 GCMminimum worse 0.00% 100.00% major_restriction 0.00% 0.00% 13.00% Year 75 GCMminimum worse 0.00% 100.00% major_restriction 0.00% 0.00% 0.00% 

Year 100 GCMminimum worse 0.00% 100.00% major_restriction 0.00% 0.00% 0.00% 

Year 45 Ensemble mean worse 0.00% 100.00% major_restriction 0.00% 0.00% 13.00% 

Year 75 Ensemble mean worse 0.00% 100.00% major_restriction 0.00% 0.00% 0.00% 

Year 100 Ensemble meaIl worse 0.00% 100.00% major_restriction 0.00% 0.00% 0.00% Year 45 GCM maximum worse 0.00% 100.00% major_restriction 0.00% 0.00% 13.00% Year 75 GCMmaximum worse 0.00% 100.00% major_restriction 0.00% 0.00% 0.00% 

Year 100 GCM maximum worse 0.00% 100.00% major restriction 0.00% 0.00% 0.00% 

Archipelago Ecoregion 

Year -10 Satellite data same_as_now 100.00% 0.00% major_restriction 4.80% 20.00% 34.80% Year 0 Satellite data same_a5_now 100.00% 0.00% no_effect 0.00% 100.00% 0.00% 

Year 45 GCMminimum worse 30.00% 70.00% major_restriction 0.00% 0.00% 28.00% Year 75 GCMminimum worse 0.00% 100.00% major_restriction 0.00"10 0.00% 0.00% 

Year 100 GCMminimum worse 0.00% 100,00% major_restriction 0.00% 0.00% 0.00% 

Year 45 Ensemble mean worse 30.00% 70.00% major_restriction 0.00% 0.00% 28.00% 

Year 75 Ensemble mean worse 0.00% 100.00% major_restriction 0.00% 0.00% 0.00% Year 100 Ensemble mean worse 0.00% 100.00% major_restriction 0.00% 0.00% 0.00% Year 45 GCMmaximum worse 30.00% 70.00% major_restriction 0.00% 0.00% 28.00% 

Year 75 GCMmaximum worse 30.00% 70.00% major_restriction 0.00% 0.00% 0.00% 

Year 100 GCMmaximum worse 0.00"10 100.00% 0.00% 0.00% 0.00% 

82737.324

Table 12 continued. 

Node A4: Factor C: Disease, predati()fl Node A6: Factor E: Other factors (natural or man-made) 

P(A4= P{A6= 

Most probable same as P(A4 .. Most probable improve- P(A6=no P(A6:minor P(A

Timeeeriod Basis outcome now) worse) outcome ment) effect) restriction) res

Polar Basin Divergent Ecoregion 

Year-IO Satellite data 100.00% 0.00% improvement 100.00% 0.00% 0.00% Year 0 Satellite data same_as_now 100.00% 0.00% no_.elTecl 0.00% 100.00% 0.00% 

Year 45 GCMminimum worse 0.00% lOO.OO% majof_ restriction 0.00% 0.00% 0.00% 

Year 75 GCMminimum worse 0.00% 100.00% ml\ior_.restriction 0.00% 0.00% 3.00% 

Year 100 GCMminimum worse 0.00% 100.00% major_restriction 0.00% 0.00% 15.00% Year 45 Ensemble mean worse 0.00% 100.00% majof_}estriction 0.00% 0.00% 0.00% Year 75 Ensemble mean worse 0.00"10 100.00% major_restriction 0.00% 0.00% 0.00% 

Year 100 Ensemble mean worse 0.00% 100.00% major_restriction 0.00% 0.00% 15.00% 

Year 45 GCM maximum worse 0.00% 100.00% major Jestriction 0.00% 0.00% 0.00"10 

Year 75 GCM maximum worse 0.00% 100.00% major.Jestriction 0.00% 0.00% 0.00% 

Year 100 GCM maximum worse 0.00% 100.00% maior restriction 0.00% 0.00% 18.00% 

Polar Basin Convergent Ecoregion 

Year ·10 Satellite data same._us..Jlow 100.00% 0.00% improvement 100.00% 0.00% 0.00% Year 0 Satellite data same_as now 100.00% 0.00% no_effect 0.00% 100.00% 0.00% 

Year45 GCM minimum worse 0.00% 100.00% majorJestriction 0.00% 0.00% 0.00% 

Year 75 GCMminimum worse 0.00% 100.00% major _re;;triction 0.00% 0.00% 0.00% 

Year 100 GCMminimum worse 0.00% 100.00% major •. restriction 0.00% 0.00% 0.00% Year 45 Ensemble mean worse 0.00% 100.00% majo(Jestriction 0.00% 0.00% 0.00% Year 75 Ensemble mean worse 0.00% 100.()0% major Jestfiction 0.00% 0.00% 0.00% Year toO Ensemble mean worse 0.00% 100.00"/0 major_restriction 0.00% 0.00% 0.00% 

Year 45 GCMmaximum worse 0.00% 100.00% major Jestriction 0.00% 0.00% 0.00% 

Year 75 GCMmaximum worse 0.00% 100.00% major Jestfiction 0.00% 0.00% 0.00% 

Year 100 GCMmaximum worse 0.00% 100.00% majorJestriction 0.00% 0.00% 0.00% 

82737.325

Table 13. Results of the Bayesian network population stressor model, showing the most probable outcome states, and probab

each state, for reproduction and vital rates (nodes U, L2; see Figure 5). 

Node U: Reproduction Node ll: Vital Rates 

P(I2: 

Most probable P(U= P(U=same P(u= Most probable P(12 same as 

Time period Basis outcome increased) as now) decreasedl outcome =imerove) now) d

Seasonal Ice Ecoragion 

Year -10 Satellite dala increased 59.68% 33.42% 6.90% improve 92.53% 7.00% 

Year 0 Satellite data same_us_flow 25.59% 41.59% 32.82% same_as_now 27.38% 41.72% 

Year 45 GCMminimum decreased 1.78% 23.47% 74.75% decline 0.25% 7.04% Year 75 GCMminimum decreased 0.38% 20.76% 78.87% decline 0.03% 1.47% Year 100 GCMminimum decreased 0.38% 20.76% 78.87% decline 0.03% 1.471% 

Year 45 Ensemble mean decreased 1.78% 23.47% 74.75% decline 0.25% 7.04% Year 75 Ensemble mean decreased 0.38% 20.76% 78.87% decline 0.03% 1.47% 

Year 100 Ensemble mean decreased 0.38% 20.76% 78.87% decline 0.03% Year 45 GCM maximum decreased 5.67% 30.90% 63.43% decline 1.01% 22.54% 

Year 75 GCMmaximum decreased 0.78% 21.57% 77.65% decline 0.05% 3.07% Year 100 GCMmaximum decreased 0.78% 21.57% 77.65% decline 0.05% 3.07% 

Archipelago Ecoregion 

Year ·10 Satellite data same __ as_now 34.41% 45.14% 20.44% 39.94% 47.09% 

Year 0 Satellite data increased 57.07% 34.96% 7.96% improve 86.86% 12.04% Year 45 GCMminimum same __ as_now 30.18% 43.98% 25.84% same_as_now 33.47% 45.72% 

Year 75 GCMminimum decreased 10.62% 36.67% 52.71% decline 5.17% 35.07% 

Year 100 GCMminimum decreased 10.62% 36.67% 52.710/0 decline 5.17% 35.07% Year 45 Ensemble mean 30.18% 43.98% 25.84% same __ as_now 33.47% 45.72% Year 75 Ensemble mean decreased 11.35% 37.15% 51.50% decline 6.07% 35.97% 

Year 100 Ensemble mean decreased 10.62% 36.67% 52.71% decline 5.17% 35.07% 

Year 45 GCMmaximum same_as_now 35.03% 43.12% 21.85% improve 42.54% 41.66% Year 75 GCMmaximum same_as_now 30.18% 43.98% 25.84% same_as _now 33.47% 45.72% Year 100 GCMmaximum decreased 10.62% 36.67% 52.71% decline 5.17% 35,07% 

82737.326

Table 13 continued. 

Node U; Reproduction Node Ll; Vila I Rates 

P(Ll: 

Most probable P(U= P(U=same P(U= Most probable PIll same as 

Time period Basis outcome increased) as now) decreased) outcome =improve) nowl 

Polar Basin Divergent Ecoregion 

Year ·10 Satellite data increased 90.93% 9.07% 0.00% improve 99.72% 0.28% 

Year 0 Sate Il ite data same_as_now 10.57% 77.96% 11.47% same_as_now 30.20% 53.67% 

Year 45 GCMminimum decreased 0.00% 0.00% 100.00% decline 0.00% 0.00% 

Year 75 GCMminimum decreased 0.00% 0.00% 100.00% decline 0.00% 0.00% 

Year 100 GCMminimum decreased 0.00% 0.00% 100.00% decline 0.00% 0.00% 

Year 45 Ensemble mean decreased 0.00% 98.72% decline 0.00% 3.09% 

Year 75 Ensemble mean decreased 0.00% 0.00% 100.00% decline 0.00% 0.00% 

Year 100 Ensemble mean decreased 0.00% 0.00% 100.00% decline 0.00% 0.00% 

Year 45 GCM maximum decreased 0.00% 1.28% 98.72% decline 0.00% 3.09% 

Year 75 GCM maximum decreased 0.00% 0.61% 99.39% decline 0.00% 1.44% 

Year 100 GCMmaximum decreased 0.00% 0.61% 99.39% decline 0.00% 1.44% 

Polar Basin Convergent Ecoragion 

Year -10 Satellite data increased 100.00% 0.00% 0.00% improve 97.98% 2.02% 

YearO Satellite data increased 68.30% 31.34% 0.36% improve 89.62% 9.73% 

Year 45 GCMminimum decreased 0.15% 30.35% 69.49% decline 0.91% 27.51% 

Year 75 GCMminimum decreased 0.00% 22.83% 77.17% decline 0.00% 7.04% 

Year 100 GCMminimum decreased 0.00% 22.83% 77.17% decline 0.00% 7.04% 

Year 45 Ensemble mean decreased 7.45% 40.74% 51.81% decline 2.03% 29.91% 

Year 75 Ensemble mean decreased 0.00% 22.12% 77.88% decline 0.00% 5.26% 

Year 100 Ensemble mean decreased 1.82% 32.73% 65.45% decline 0.13% 7.24% 

Year 45 GCMmaximum decreased 4.58% 36.77% 58.65% decline 0.68% 18.32% 

Year 75 GCM maximum decreased 2.13% 33.19% 64.68% decline 0.16% 8.51% 

Year 100 GCMmaximum decreased 1.92% 32.88% 65.20% decline 0.14% 7.65% 

82737.327

Table 14. Projected outcomes from Bayesian network population stressor model showing probabilities of overall outcome stales 

resulting when all human factors were fixed at 'same as now' or 'fewer than now.' 

"Influence Run" #1 

Outcome lorcing Node AI = "same as now" and 

________ N_o_de_A_.6 = "no ellect", for Vears 45, 75, 100 

Node Dl: Overall Population Outcome 

"Influence Run" #2 

Outcome forcing Node AI ,,"fewer" and 

_______ Node = "improvement", lor Vears 45, 75, 100 

Node 01: Overall Population Outcome 

Time P(OI: PID1= same P(OI= P(OI= PI01= PI01= PI01= same P(01= PI01" 

_ . .Jl!'riod Basis most·prob 01 __ as now} 

Year Year 0 

Year 45 

Year 75 

Year 100 

Year 45 

Year 75 Year 100 

Year 45 

Ycar 75 

Year 100 

VearO Yoar 45 

Year 75 

Year 100 Year 45 

Year 75 

Year 100 

Year 45 

Year 75 Year 100 

Satellite data Satellite data 

GCMminimum 

GCMminimum 

GCMminimum 

Ensemble mean 

Ensemble mean Ensemble Oll;arl 

GCMmaximum 

GeM maximum 

GCMmaximum 

Satellite data SatellIte data 

GCMmimn1um 

GCMmmimum 

GCMminimum 

Ensemble mean Ensemble mean 

Ensemble mean 

GCMmaximum 

GeM maximum GeM maximum 

larger 

same_aS_llOW 

extmct extinct extmct extinct 

extmct 

extinct 

smaller 

extinct 

extmct 

.. as.,J1QW 

larger 

smaller smaller smaller smaller smaller smaller 

smaller 

smaller smaller 

93.92% 

21.85% 

0.10% 

0,01% 0.01% 0,10% O.Ol% 0.01% 0.45% 

0.02% 

0.02% 

22.5l%t 

69AS% 

19,70% 

2.54% 

2,54% 

19.70% 

2.99% 

254% 

25.10% 

1970% 

254% 

5.75% 

43.72% 

1.46% 

0.24''/0 

0.52% 

1.46% 

024% 0.24% 

5.16% 

0.52% 052% 

34.73% 

29.26% 29.40% 

l{UO% 

)0.10% 

29.40% 

10.50% 10,10% 

29.90"/0 29.40% 

10.[0% 

smaller) rare) extinct) most·p.ob D1 la.!ll!;.l 

Seasonall.ce Ecoregion 

030% 

18.98% 

22.80% 

16.20% 

18.60% 

22,80% 

16.20% 

16.20% 

39.50% 

18.50% 18.50:% 

0,02% 

8.37% 

21.20% 

2020% 

1870% 

21.20% 20.20% 2020% 22.80% 20.80% 20.80% 

0,00% larger 7.07% samc_as_oow 

54 40% extmct 

6330% extinct 

62,20% extinct 

54.40% extinct 

63.30% extinct 

63 30% extinct 

32.000/0 smaller 

60.20% extlI'1ct 

60.20% extmct 

Archipelago Ecoregion 

31.48% 

1.06% 

3970% 

46.40% 

46.40% 

3970% 

46.50% 

46.40% 

36.80% 39.70% 

46.40% 

8.72% 

0.19% 

K90% 

19.00% 

19.t1O% 

890% 

2350% 

19.00% 

6.72% 

8-90% 

19.00% 

2.56% same_fts_oow 

0.00% iarger 

2.261)/" same._as_oQw 

22.00% smaller 

22,00% smaller 

2.26% same_tis_now 

16.50% smal!er 

22.00% smaller 

1.55% 

2.26% 

22 00% smaller 

93.92% 

21.85% 

0.11% 

0,01% 

0.10% 

0.11.% 

0.01% 

0.01% 0.415% 0.02% 0.02% 

22.51% 

6948% 

24.30% 

255% 2.55% 

24.30% 

2.99% 255% 

30.00% 

24.30% 

255% 

as ".owl smaller) rare) 

5.75% 

43.72% 

8.43% 

].89% 

4.98% 

8.43% 

3.89% 

3.89% 

2L10% 

5.20% 5.10% 

34.73% 

2926% 

44.10% 

31.8.0% 

31.80% 

44,10% 

32.10% 

31.80% 

42.10% 

44.10% 

31.80% 

030% 

18.98% 

31.70% 

27.90% 

28JO% 

31.70% 

27.90% 

27.90% 

40.30% 

29.50%. 

29.50% 

11A8% 

1.06% 

25.40% 

38.50% 

38,50% 

25.40% 

38.90% 38.50% 

23.40% 25.40% 

38.50% 

0.02% 

837% 

14.00% 

14.70% 

13.30'%, 

14.00% 

14.70% 

14.70()/1l 

11.90% 14.50% 

14.50% 

8.72% 

019% 

4.62% 

9.30% 

9.30% 

4.62% 

13.20% 

930% 

3A3%, 

4,62% 

9.30% 

82737.328

Table 14 continued. 

i(lnfluence Run" #1 

Outcome forcing Node AI = "same as now" and 

Node A6 = "no effecf', for Vears 45, 75. 100 

Node 01: Overall Population OUICOm! 

Time P(OI: PIOI= same P(DI: P(OI: P(OI= 

_ Basis most-prob 01 larger) as no",) smaller) rare) extinct) _ "",st:prob 01 

Year 10 

Year 0 Year 45 

Year 75 Year 100 

Year 45 

Year 75 

Year 100 

Year 45 Year 75 Year 100 

Year 0 

Year 45 

Year 75 Year 100 

Year 45 Year 75 

Year 100 

Year 45 

Year 75 Year 100 

Satellite data Satellite data 

GCMminimum 

GCMmmimum 

GeM minimum 

En:semble mean 

Ensemble mean Ensemble mean 

GCMmaximum 

GeM maximum GeM maximum 

Satellite data 

Satellite data 

GCMminimum 

GCMmlnimum 

GeM minimum 

Ensemble mean 

Ensemble mean 

Ensemble mean 

GCMmaximum 

GCMmaximum 

GeM maximum 

larger 

same_as_now 

extinct 

extinct eXlinct 

extmct 

extinc:t 

extmct 

extinct 

extmct 

extmct 

larger 

larger 

smaller 

extinct 

extinct 

smaller 

extmct 

extmct 

s.maller 

rare 

extinct 

99-78% 

24.16% 

O.W/Q 

0.00% 000% 

0.00% 

OJ)()% 

OJ)O'1o 

0,00% 

0.00% 

0_00"10 

98.39% 

7'-69% 

0.46% 0.00% 0.00% 

0.95% 

0.00% 0.04% 

028% 

0.05% 0.04% 

0.22% 

56.60% 

0,00% 

0_00% 

0.00% 

0.53% 0.00% 

(WO% 

0.53% 

0,22% 

0_22% 

1.61% 

27.49% 

6.31% 

Ll3% 

1.13% 

7.12% 

0_82% 

1.24% 

3.47% 

13&% 

1.28% 

Polar Basin Divergent £coregion 

0.00% 

13.36% 1).90% 15,90% 

15.90% 

20.10% 

15.90% 15.90% 

20.10% 

IS.OOO/I;) 

1800% 

0.00% 

473% 

25.30% 2530% 

25.30% 26.00% 

2530% 25 . .30% 26.00% 

25.70{l/1) 

2570% 

0.00% larger 

1.14% samc_as_now 

58.80% extinct 58.80% extinct 58.80% extinct 53 40% extmct 

58.80% extinct 

58.80"% extm<;t 

53.40% extinct 

56 10% extinct 56 10% extinct 

Polar Basin Convergent [con:gio-o 

0.00% 

0,63% 

44. \0% 

24.60% 24.60% 

44.70% 

23-00% 24.30% 

37.70% 

28.50% 2560% 

0_00% 

0.19% 

30.70% 

22.30% 22.30% 

30.40% 

26.10% 

22.10% 

34.60% 

35.60% 

2640% 

0.00% larger 

0.00% larger 

lS.40% smaller 

51 90% extinct 

51.90% extmct 

16.80% smaller 

50.00% extinct 

52.4ifla extinct 

24.00% smaller 

34.50% smaller 

46.60% extmct 

"Innuence Run" #2 

Outcome forcing Node A I = "ewe" and 

Node A6 = "improvement". for Vear. 45.15. 100 

Node 01: Overall Population Outcome 

P(OI= 

larger) 

99,78% 

2416% 

0.00% 0.00% 0.00% 

O.c}()% 

0.00% 

000% 

000% 

D.OO% 

0.00% 

98.3go/o 

71.69% 

O.4ti% 0.00% 

O.DO% 

0.96% 

000% 

0,04% 

0,29% 

0()5% 

0.05% 

P(DI=same 

as now) 

0.22% 

56.60% 

2.70% 2.70% 

2-70% 

5.28% 

2.70% 

2.70% 

5.28% 

3.91% 

391% 

1.61% 

27A9% 

24.70% 

8.56% 

8.56% 

26.10% 

6.98% 

8.54% 

16_70% 

9.12% 

8.73% 

P(OI= 

smalle., 

0.00% 

13.36% 

29.20% 29.20% 

29.20% 

31.90% 

29.20% 29.20% 

3L90% 30.60% 30.60% 

0.00% 

0.63% 

4J,20% 

33.90% 33.90% 

42.70% 

3J90% 

33.40% 

4330% 

39.40% 

3540% 

P(OI: 

rare) 

0.00% 

4.73% 

19.10% 19.1O% 

19.10% 18.50% 19.10% 

1'f.IO% 

1850% 

18.80% 18.80% 

0.00% 

0.19% 

17.80% 14_00% 

14.00% 

17.S0% 

11-70% 14.00% 

2L40% 

24.30% 

17.30% 

82737.329

Table 15. Projected outcomes from Bayesian network population stressor model showing probabilities of overall outcom

resulting when all human factors were fixed at uniform. 

This means we made no assumptions about whether human factors would have more or less influences on polar bears in t

We allowed total uncertainty in these nodes. 

Time Qcriod 

Year YearO 

Year 45 

Year 75 

Year 100 

Year 45 

Year 75 Year 100 Year 45 

Year 75 

Year 100 

Year Year 0 Year 45 

Year 75 

Year 100 Year 45 

Year 75 

Year 100 

Year 45 Year 75 

Year 100 

ftlntluence Run ll #3 

Outcome f()rcing all input nodes to uniform (default prior) probabilities, except ice nodes 

N, B & C. and Ecoregion node M, for Years 45, 75.100 

Node D I: Overall Population Outcome 

P(D!= P(D!= P(D!= P(Dl= P(Dl= 

. __ == ___ ..:m,",o",s"t--"p::.r",ob"-,,D,-,l __ same as now) smaller) rare) extinct) 

Satellite data 

Satellite data 

GeM minimum 

GeM minimum 

GCMminiml,lm 

Ensemble mean 

Ensemble mean 

Ensemble mean 

GCMtnax!mum GeM maximum GeM maximum 

Satellite data 

Sate!lite data 

GCMmintmum GCMmitlimum 

GeM mimmum 

Ensemble mean Ensemble mean 

Ensemble rotan 

GeM maximum GCMmaximum 

GeM maXImum 

larger 

same_os_now 

extmct extinct extinct 

extinct 

extrnct 

extinct 

extinct 

extinct 

extmct 

same _now 

larger 

smaller 

extinct 

extinct 

smaller 

extmct 

extinct 

smaUer smaller 

exttnct 

Seasonal Ice Ecoregion 

93,92% 

21.85% 

0.25% 

0.05% 0.05% 

025% 

0.05% 0.05% 

1.06% 

0.05% 

005% 

Al"chiVflago E(Ofegion 

22,51% 

69.48% 

6.34% 

2.86% 

2.86% 

6.34% 

2.86% 

2.&6% 

S.55% 

6)4% 

2.86% 

5.75% OJO% 0.02% 0.00% 

43.72% 18.98% 8.37% 7.07%) 

2.61% 14.70% 13.30% 69.10% 

1.42% 11.90% 12.70% 74.00% 1.42% 11.90% 12.70% 74.00% 

2,61% 14/0% 1330% 69.10% 

1.42% J 1.900/<} 12.70% 74.00% 

1.42% Jt.90% 12.70'10 74.00% 

7.63% 27.20% 16.50% 47.60% 

tA2% 11.90% 12.70% 74.00% 

1.42%1 1190% 1270% 7400% 

34.73% 3148% 8.72% 2.56% 

29.26% L06% 0.19% 0.00% 

17.20% 39.80% 15.30% 2t.40"lo 12.50% 34.00% 16.00% 34.60% 

12.50% 34.00% 16.00% 34.60% 

17.20% 39.80% 15.30% 21.40% 

12.50% 34.00% 16.00% 34.60% 

12.50% 34.00% 16.00% 34.60% 

19.90% 41.60% 13.70% 16.20% 17.20% 39.80'10 15.30% 2L40% 

1250% 3400% 1600% 3460% 

82737.330

Table 15 continued. 

Time period Basis 

Year -10 Satellite data 

Year 0 Satellite data 

Year 45 GCMmmimum 

Year 75 GCMmimmum 

Year 100 GeM minimum Year 45 Ensemble mean 

Year 75 Ensemble mean 

Year 100 Ensemble mean 

Year 45 GCMmaximum Year 75 GCMmaxlmum 

Year 100 GeM maximum 

Year-IO Satellite data Year 0 Satellite data 

Year 45 GCMminimum 

Year 75 GCM minimum Year 100 GCMminimum 

Year 45 Ensemble mean 

Year 75 Ensemble mean Year 100 Ensemble mean Year 45 GCMmaxlmum Year 75 GCMmaximum 

Year 100 GeM maximum 

"Influence Run" #3 

Outcome forcing all input nodes to uniform (default prior) probabilities, excep

N, B & C, and Ecoregion nod-e M, for Years 45, 75, JOO 

!'iode 01: Overall Population Outcome 

P(Ot= P(D1= P(D1= P(OI= 

most-I!rob 0 t same as now) smaller) rare) 

Polar Basin Divergent 

larger 99.78% 0.22% 0,00% 0.00% 

samc_as_now 24.(6% .56.60% 1136% 4.73% 

extmct a.DO'VI) 0.59% 8,78% 11.30% 

extmct 0.00% 0.53% 8.53% 11.20% 

exttnct 0.00% 0.53% 8.53% 11.20% 

extmct 0.17% 2A7% 14.70% 13.50% 

extinct 0.00% 0.59% 8.78% 11.30% 

extmct 0.00% 0.53% 8.53% 11.20% extinct 0.17% 2.47% 14.70% 13.50% 

extinct 0,03% 1.36% 11.80% 12.70% 

extmct 136% 11.80% 1270% 

Polar Dear 

larger 98.39% 1.61% 0.00% 0.00% 

larger 71.69% 27.49% 0.63% 0.19% 

extmct 091% 8.60rr/Q ],0.20% 17.50% 

extmct 0.14% 4.15% 22.60% 17.40% extinct 0.14% 4.l5(l/o 22.60% 17.40% 

extmct 1.31'% 9.28% 30.90% 17.30% 

extinct 0.10% 3.16% 18.80% 15.70% 

extinct 0.34% 4.29%· 2Ll0% 16.00% extmct 0.46% 5.31'% 24.10% 17.00% 

extinct 0.34% 4.29% 21.10% 16.00% 

extmct 0.)4% 4.29% 21.10% 16.00% 

82737.331

Divergent ice 

El Convergent ice 

·300 m isobath 

Figure 1. Map of four polar bear ecoregiQl1s to which we refer in this report. Ecoregions were established by grouping recognized subpopulations wh

seasonal pattems of ice motion and distribution. 

The polar basin Divergent Ice Ecoregion (purple) includes: Southern Beaufort Sea (SBS), Chukchi Sea (CS), Laptev Sea (LV

Sea (KS), and the Barents Sea (BS). The polar basin Convergent Ice Ecoregion (blue) includes: East Greenland (EG), Queen 

(QE), Northern Beaufort Sea (NBS). The Seasonal Ice Ecoregion (Green) includes: Southern Hudson Bay (SHB), Western H

Bay (WHB), Foxe Basin (FB), Davis Strait (OS), and Baffin Bay (BB). The Archipelago Ecoregion (yellow) includes: Gulf 

Boothia (GB), M'Clintock Channel (MC), Lancaster Sound (LS, orange), Viscount-Melville Sound (VM), Norwegian Bay (

Kane Basin (KB). 
104 


82737.332

Climate 

Models 

(General Circulation 

Models, GCMs) 

Current estimates of Projected Se.9 ice habitat ExpCftjudgment: 

polar bear population area and distribution: • key stressors & threats, size: • for years 45, 75, 100 • and their po/ential 

• byecoregion • byecoregion 

Polar Bear 

Carrying Capacity 

Model 

(deterministic 

spreadsheet) 

Polar bear carrying capacity 

extrapolated from: 

• projected habitat area, and 

• estimated present.day density 

• by ecoregion and time period 

future conditions 

/ 

Polar Bear 

Population 

Stressor Model 

(probabilistic Bayesian 

network) 

Probability of polar bear 

population response to: 

• anthropogenic stressors 

• sea ice habitat changes 

• other environmental fae/ors 

• by ecoregion and time period 

Figure 2. Linkages followed in this report. from available information on sea ice potar bears and other 

environmental correlates, and leading to projections of future polar bear carrying capacity and overall 

population outcome. 

82737.333

a) lee Extent 

E 

C. 

I 

2 

o 

Summer 

lDI5 2000 2025 

12 

Winter 7·. _.-

1975 2000 2025 2050 2075 2100 

b) RSF Habitat Value 

la -

f 

1!i 12 

" i 

on 

, 

fu 

"' Summer 

25 

g 

" 

2 t3 .75-

o '" _ _ _ _ _ 

j975 20M 2025 2050 2075 2100 1975 2000 2025 2050 

25, 

l! 

!1 

'" -

ID 

.3 

,. 

j 

Winter 

·100 220' Winter 

1975 2000 2025 2050 2075 2100 1975 2000 2025 20SC 2075 2100 

___ ensembte -- cgcm3_t47 gL'lS_OOIll 01Iroc32_medres 

ccsn 13 e,:nrfH ctn3 -- hadgem'f rniub acl'Iu 

ccsm3JJ41 ipslp"" mpL;;"ham5 

_ 5dteUite olr.iervecJ 

25 

8: 

?j i 

u. 

:5l" 00 Winter 

1915 2000 2025 2050 

Figure 3. (a) Average summer and winter sea ice extent in the entire polar basin (divergent and convergent regions) express

square km (left) and as a percent change relative to each model's 1990-1999 mean for 201h century hindcasts (right). (b) Av

habitat values for summer and winter expressed in raw RSF units (left) and percent change to each model's 1990-1999 mea

201h century hindcasts (right). 

Black line is the PMW satellite record of actual observations. Numbers in brackets are seasonal mean ofvalucs for 1990-19

most hindcast model results overestimated the amount of habitat available during the observation period. 
106 


82737.334

Figure 4. The basic influence diagram for the Bayesian network polar bear population stressor model 

showing the role of 4 listing factor categories used by U.S. Fish and Wildlife Service. 

The final ourput node, overall population outcome, represents expected the joint polar bear population 

nLlmerical and distribution responses to multiple stressors and environmental conditions. 

82737.335

Figure 5. The full Bayesian network population stressor model developed to evaluate overall population outcome. 

Input nodes are set to initial uniform probabilities. The model is solved by specifying input node values for each combinatio

geographic regions, 5 time periods, and 4 global climate modeling scenarios or data sources (input data are specified in Tab
108 


82737.336

Figure 6. Annual (12-month sum) polar bear habitat area H,,e; at f years -10 and ° from satellite data and 0, 45, 

75, and laO from minimum, ensemble mean, and maximum global change model (GeM) runs, in four geographic 

regions G and all regions combined (see Table 4). 

Optimal (selected) habitat areas (from resource selection function [RSF] models) are shown for the two Polar 

Basin regions. 

Total Habitat Area 

Optimal (RSF) Habitat Area 

Divergent Ewtcgion 

j--C-GCM maximum I l-o-Ensernble meanj 

l-:::>-GCM miOlmum 1 

i ~_~ate:!.'!".d."!"._~J 
109 


82737.337

Figure 7. Percent change in polar bear habitat amounts CH,.G at l,Years·1O and 0 from satellite data and 

0,45,75, and 100 from minimum, ensemble mean, and maximum global change model (GCM) runs, in 

four geographic regions G and all regions combined, normalized to 0% change at ,Year 0 (see Table 4). 

Total Habitat Percent Change 

Afl geographlc regioM 

Optimal (RSF) Habitat Percent Change 

Divergent Ecoreg1on 

Year5 from preS€nt 

i':.o-GCM maXimu:] 

_Ensemble meaol 

-GCM minimum 

-:?-sa!ellit~~~.J 

Archipelago Ecoregfon 

Corwergent Ecoregion 

Years from present 
110 


82737.338

Figure 8. Normalized polar bear carrying capacity K;;"" at I years· I 0 and 0 based on habitat amollnt from sateilite 

data at year·1 0, empirical bear counts at year 0, and habitat amounts at years 0, 45, 75, and 100 [TOm minimum, 

ensemble mean, and maximum global change model (GCM) runs, in four geographic regions G and all regions 

combined (see Table 6). 

GCM·based values are normalized to year ° empirical counts. Note that all graphs are plotted on the same y·axis scale 

for comparison. 

Total Carrying Capacity 

Optimal (RSF) Carrying Capacity 

Years {rom pres'I'ot 

r:;;:(icM'~~';i;;~<l 

l

-D-Ensemble mean! 

-<>-GCM. rnlnIOlu.' .. ll I 

_Satellite data ! 

Convergerr! Ecol'eglon 

" 

Ye~f5 hom present 
111 


82737.339

Figure 9. Polar bear carrying capacity trends CKt,G at t years -10 and 0 based on carrying capacity 

values from Figure 8, in four geographic regions G and all regions combined, normalized to 0% change 

at year 0 (see Table 6), 

Total Carrying Capacity Percent Change 

r::;::GCM~~~l , , I-o-Ens.mble mean: 

j-<>-GCM minimum 

t~~<~.~~~.~i~~ "~!!~"._,. 

Archlpeiago Ec:oreglon 

Optimal (RSF) Carrying Capacity Percent Change 

Convergent £cmeglon 

Years from present Years fram pres-em 
112 


82737.340

Figure 10. Projected polar bear population outcomes of Bayesian network model for 4 ecoregions at 5 

time periods relative to present. 

Present and prior decade (years 0 and -10) sea ice conditions were from observed record. Future ice 

conditions were based on the ensemble mean of 10 GeMs, and the 2 GeMs that forecasted maximum 

and minimum ice extent in each ecoregion at each time period. Note that strength of dominant outcomes 

(tallest bars) is inversely proportional to heights of competing outcomes. Outcome definitions: larger = 

more abundant than present (Year 0) plus distribution at least the same as at present; same = numerical 

and distribution responses similar to present; smaller = reduced in numbers and distribution; rare = 

numerically rare but occupying similar distribution, or reduced numerically but spatially represented as 

transient visitors, extinct =are numerically absent or distributionally extirpated. 
113 


82737.341

Seas.onal lee Ecoregion 

E 100% 

§ 

~ 

~ ~ ~%+-___________ ~k-____ , __ • ____ __ 

1i 

~ :c 

Jl 

e 

Cl. 

E "

0 

S 

a 

1:1 

" 

~ 1i 

~ :is 

Jl 

£ 

75% 

50% 

..20 211 40 00 BO 100 1211 

Polar Basin Divergent Ice Emregion 

·20 20 40 60 110 100 12Q 

Years from Present 

<i> S.temt. Observed 

o En>emble Menn 

.2{) 20 40 tiO 80 100 120 

·20 211 40 60 80 100 120 

Years from Present 

a GeM Minimum 

/1; GCM Maximum 

Figure 11. Projected probabilities of the "extinct" overall population outcome (node D 1 in Fig. 5), from 

the Bayesian network population stressor model. 

Projections include 4 ecoregions, and 5 time periods relative to present. Present and prior decade (years 

o and -10) sea ice conditions were from observed record. Future ice conditions were based on the 

ensemble mean of 10 GCMs, and the 2 GCMs that forecasted maximum and minimum ice extent in 

each ecoregion at each time period. 
114 


82737.342

Cumulative sensitivity (entropy reduction) 

a 0.2 0.4 0.6 0.8 1 

, 8:Foraging habitat quantity change , 

C:Foraging habitat absence change 

M:Geographic area 

E:lntentional takes - S 1 :Foraging habitat character 

N:Shelf distance change 

81:8ear-human interactions 

T:Parasites and disease 

R4:Hydrocarbons and oil spills 

Rl :011 and gas activity 

J:Shipping 

T2:Predation 

T1 :Contaminants 

Jl:Tourism 

F:Altemate regions available 

R3:Alternate prey availability 

R2:Relative ringed seal availability .•..... ,.,. ',"" . .. "' ..... -.. ' ..... , .. , .... , .. , 

Figure 12. Cumulative sensitivity of overall population outcome (node 0 I. Fig. 5) to all input variables 

(yellow boxes, Fig. 5). in the Bayesian network population stressor modeL 

The 17 input variables on the venita I axis are listed, top to bottom, in decreasing order of their 

individual influence on overall population outcome (see Appendix I, Sensitivity Test 1). The horizontal 

axis represents the cumulative proportion of total entropy reduction (mutual information) from the input 

variables. For example, the first two variables. foraging habitat quantity change and foraging hahitat 

ahsence change, together account for 58% of all explainable entropy reduction. 

82737.343

a) Full Study Area 

1,8 

'" 

1.2 

'" 2i j lUi 

;;; 

is 0.0 

" 4e 

i 

_ 

4" 

j 

.$l 

.JlO 

Saa..4Hte otr-A."IveU 

III 8 

19%-lt1<J6 204;:;-20:>4 2090-2099 

b) Alaska-Eu rasia 

u 

'" 

'i; 

1.2 

<Il 

!! 

m 

,. 

0,6 

.t:; 

'a 

o 0.0 

.. ·20 

"1'-

., 

"-

-60 

.00 

film D III 

JrJ9!).Ifr:R 

c) Canada-Greenland 

,.8 

<D5! 

N 

..... 'L2 

OJJ 

1 

a 0.0 

it< 

l<' 

{l 

20 

II ->0 

-40 

-00 

WINTER SPRlkG SUMMER AutuMN 

42)if

J'.;:J..M 

El III 

1985"1995 199t'i o 2005 lfJ'lO··1;fl7'g 

Figure 13. Mean (SE) area of optimal RSF polar bear habitat in the polar basin by season and decadal time period (top), and 

percentage change in the same values (bottom), from ensemble mean of 10 IPCC AR-4 general circulation models. 

Note the modest changes in annual values which were used in our carrying capacity model in comparison to the spring and s

values. 
116 


82737.344

~ 100% 

fi ::E 3 15% ::.> ? ;§ j Z 

~ 

:;; '0 

l5 l:- ZS-,4 :B 

-8 

~ 0"-

~ 100% 

F Z @ ~ ? 15% ::; 

co 

~ .~ $O"l .. ::; ~ .... 

w '0 Vl g ~ 15 ~5% 

Jl 

£ 0% 

SEASONAL 1([ 

Final !:IN mode!: 

ARC1l1PElAGO 

......... :,,7} .. ~ ..... ~.:.~~ .i._._.~o~e!:",::<J.'-: ___ ~., 

Y~MS. from P;e~ent 

...... Pwj('(tcopala1be,)tst.)tu;; 

OlVERGENT lC[ CONV[RG[NT l(E 

Vears from Pr'1;'sent 

Hyp{'lth~tk;o\l "(f>nilrio<;-t~; (O!1lfJ.2lfi<OlY 

¢ 0 S~t!11~"~I"lO'W 

---. !f,'P'DYl:d 

"::' Of)(Prt,1inly 

Figure 14. Probability of "extinct" outcomes projected by a Bayesian network (BN) polar bear 

population stressor model. Projections include 4 ecoregions, and 3 future time periods relative to 

present. 

Future ice conditions were based on the ensemble mean of 10 GCMs, and the 2 GCMs that forecasted 

maximum and minimum ice extent in each ecoregion at each time period. General BN runs (thick red 

lines, Table 8, Figure II) are compared to results obtained by 3 scenarios in which certain inputs were 

fixed: "Same" = direct mortalities (BN node A I, Figure 5) fixed at "same as now" and other human 

factors (node A6) at "no effect" (open circles); "Fewer" node A I fixed at "fewer" and node A6 at 

"improvement" (solid circles); and "Uncertain" = all input nodes other than those expressing 

quantitative sea ice conditions held at their uniform, prior probabilities (complete uncertainty) with the 

three ice-related nodes (N, B, and C) varying the same as the original runs (open squares). 

82737.345

CNRMCM3 

CCSM3 

HadGEM1 

IPSLCM4 

M1UBECHO 

GISSAOM 

M!CR032MED 

MPI ECHAM5 

GFOLCM2 

CGCM3 T47 

o 2 3 4 5 

lee Extent (km2x 106) 

Figure l5. Area of sea ice extent (>50% ice concentration) on August 23,2007, compared to 10 lPCC AR·4 GCM mid-centur

projections of ice extent for September 2045-2054 (mean ± 1 sd, n = 10 years). 

Note that the 4 models which project the greatest remaining sea ice extent at mid century forecast more perennial sea ice than 

at present. Ice extent for August 23,2007, was calculated using near-real-time ice concentration estimates derived with the NA

Team algorithm and distributed by the NSIDC (http://nsidc.org). 
118 


82737.346

Appendix 1. Results of sensitivity analyses of the Bayesian 

network population stressor model 

This appendix presents the results of conducting a series of 

sensitivity analyses of the Bayesian network population stressor 

model discussed in the text (also see Fig. 5). Sensitivity analysis 

reveals the degree to which selected input or summary variables 

influence the calculated values of a specified output variable. 

Presented here are results of 10 sensitivity tests on various summary 

and output nodes in the model (see text for explanation of 

calculations). Note that mutual information is also called entropy 

reduction. All tests were conducted using the Bayesian network 

modeling software package Netica (Norsys, Inc.). 

SENSITIVITY GROUP 1: SENSITIVITY OF OVERALL POPULATION OlJ'TCOME 

Sensitivity Test 1. Sensitivity of node Dl:Overal1 Population Outcome to all input node$ 

Node 

B 

C 

M 

51 

N 

B1 

T 

R4 

R1 

J 

T2 

Tl 

J1 

F 

R3 

R2 

Mutual 

Info 

0.11624 

0.04591 

0.04003 

0.01837 

0.01569 

0.01325 

0.00939 

0.00546 

0.00302 

0.00289 

0.00224 

0.00100 

O. D0082 

0.00046 

0.00000 

0.00000 

o.oooeo 

Node title 

Foraging Habitat Quantity Change 

Foraging Habitat Absence Change 

Geographic Area 

Intentional Takes 

Foraging habitat chara.cter 

Shelf Distance Change (km) 

Bear-human interactions 

Parasites & Disease 

Hydrocarbons/Oil Spill 

Oil &. Gas Activity 

Shipping 

Predation 

Contaminants 

Tourism 

Alternate Regions Available 

Alternate Prey Availability 

Relative Ringed Seal Availability 

Sensitivity Test 2. Sensitivity of node Dl:0verall Population Outcome to Listing Factor nodes 

Mutual 

Node Info Node title 

-------- ~ -------------- F2 0.60174 Factor A, Habitat Threats 

Al 0.06391 Factor B. Direct Mortalities 

A6 0.03659 Factor E. Other factors {natural or man-made) 

A4 0.01123 Factor C. Disease l predation 
119 


82737.347

Sensitivity Test 3. Sensitivity of node Ol:Overall Population Outcome to intermediate nodes 

This does NOT includes the Listing Factor nodes included in Sensitivity Test 2/ above. 

Mutual 

Node Info Node title 

L2 0.57024 Vital Rates 

L1 0.53323 Adult Female survival 

L 0.53295 Juvenile Survival 

K 0.51522 Adult Body Condi t ion 

V1 0.42691 Cub production per event 

U 0.23368 Reproduction 

D 0,18791 Change in Poraging Habitat Distribution 

A o. 02592 Foraging habitat value 

Cl 0 .02114 Human disturbance 

G .00000 Relocation possible 

H . 00000 Crowding Tolerance 

C2 0.00000 Pollution 

Sensitivity Test 4. Sensiti1fity of node Dl;OveJ:all populatit;)n Outcome to sele-c:ted 

intermediate nodeS 

This includes all {6} nodes that are two links distant from the outcome node. 

Mutual 

Node Info Node t.it.le 

- ----- -- --------- -- -- -- -- ------- FO 0.60174 Factor A: Habitat Threats 

L2 0.57024 Vital Rates 

Al 0.06391 Factor B. Direct Mortalities 

G 0.00000 Relocation Possible 

A6 0.03659 Factor E., Other factors (natural or man-made) 

A4 0.01123 Factor C. Disease, predation 

SENSITIVITY GROUP 2: SENSITIVITY OF SUBMODELS 

Sensitivity Test 5. Sensitivity of node A4:Factor C. Disease r predation 

Node 

Mutual 

Info Node title 

TO. 3 9016 Parasites & Disease 

T2 0.06593 Predation 

Sensitivity Test 6. Sensitivity of node C2: Pollution 

Mutual 

Node Info Node title 

R4 0.69005 Hydrocarbons/Oil Spill 

T1 0.13542 Contaminants 
120 


82737.348

Sensitivity Test 7. Sensitivity of node Cl:Human disturbance 

Node 

Mutual 

lnto Node title 

Bl 0.45796 Bear-human interactions 

Rl 0.12450 Oil & Gas Activity 

J 0.08941 Shipping 

Jl 0.01729 Tourism 

Sensitivity Test 8. Sensitivity of node A,Foraging habitat value 

Node 

81 

F 

R3 

R2 

Mutual 

lnto 

0.63429 

0.00000 

0.00000 

0.00000 

Node title 

Foraging habit.at character 

Alternate Regions Available 

Alternate Prey Availability 

Relative Ringed Seal Availability 

Sensitivity Test 9. Sensitivity of node D:Change in Foraging Habitat Distribution 

Node 

Mutual 

Info Node title 

M 0.33239 Geographic Area 

C 0.32674 Foraging Habitat Absence Change 

N 0.06131 Shelf Distance Change (km) 

Sensitivity Test 10. Sensitivity of node L2:Vita1 Rates 

Node 

L1 

L 

F2 

K 

VI 

U 

M 

N 

Mutual 

Info 

1.09792 

1.09537 

0.99215 

0.97559 

0.69213 

0.36497 

0.04728 

0,01955 

Node title 

Adult Female Survival 

Juvenile Survival 

Factor A: Habitat Threats 

Adult Body Condition 

Cub production per event 

Reproduction 

Geographic Area 

Shelf Distance Change (km) 
121 


82737.349

Appendix 2. Documentation of the Bayesian network polar bear 

population stressor model 

This appendix documents the structure of the Bayesian network (BN) 

population stressor model. We used the BN modeling shell Netica® 

(Norsys, Inc.) to create a model that represents potential influences 

on distribution response, numerical response, and overall population 

response of polar bears under multiple stressors, which include 

anthropogenic stressors, natural disturbances, and other key 

environmental correlates to polar bear population amount and 

distribution. 

The BN population stressor model was created to represent the 

knowledge and judgment of one polar bear biologist (S. Amstrup) with 

guidance from an ecologist modeler (B. Marcot). See the text for a 

brief explanations of Bayesian modeling and statistics. The general 

underlying influence diagram for the BN model is shown in Figure 4, 

and the full model is in Figure 5. A BN model consists of a series of 

variables represented as "nodes" (boxes in Fig. 5) that interact 

through links (arrows in Fig. S). Nodes that have no incoming arrows 

are "input nodes" (the yellow boxes in Fig. 5, e.g., node T Parasites 

& Disease). Nodes with both incoming and outgoing arrows are summary 

nodes (or latent variables, e.g., node L2 Vital Rates). In our model, 

we also specified four of the summary nodes as listing factors used 

by USDI Fish and Wildlife Service (S. Morey, pers. comm.). Nodes with 

incoming arrows but no outgoing arrows are outcome nodes (node Dl 

Overall Population Outcome) . 

Each node in this model consists of a short node name (e.g., node 

Dl), a longer node title (e.g., Overall population Outcome), a set of 

states (e.g, larger, same as now, smaller, rare, and extinct), and an 

underlying probability table. The probability tables consist of 

unconditional (or prior) probabilities in the input nodes, or 

conditional probabilities in all other nodes, the latter representing 

probabilities of each state as a function of (conditional upon) the 

states of all nodes that directly influence it. 

The following table presents a complete list of all nodes in the 

model with their short code letter names, their fuller titles, a 

description, their states, and the group (Node Set, in Netica 

parlance) to which it belongs (input nodes, output node, summary 

node, or summary listing factor node) . 

82737.350

Node I Node title 

y--- Parasites & 

Disease 

T2 I Predation 

Node description 

Input nodes 

As the climate warms, regions of the arctic arc hospitable to parasites and disease agents which fomedy didn't 

survive there. Polar bears have ahvays been free of most disea'ie and parasite agents. Trichinella is one notable 

exception, but even rabies, common in the Arctic has had no significance to polar bears. Changes in other species 

disease vulnerability suggest that similar changes could occur in polar bears so that they could move from a position 

where parasites and disease are not influential on a population level to where they are influentiaL 

/

" Predation on polar bears by other species is very uncommon partly because bears spend almost all ofthejr time on 

the icc. With more time on land, polar bears, especially young will be subject to increased levels of predation from 

wolves, and perhaps grizzly bears. 

This wm vary by region as some regions where polar bears occur have few other predators. 

Intraspecific predation is one behavior which is knmvn to occur in bears. It has rarely been observed in polar bears 

and historically IS not thought 10 have been infiuentiaL 

Recent observations of predation on other bears by large males, in regions where it has not been observed before, 

arc consistent with the hypothesis that this sort of behavior may increase in frequency if polar bears arc nutritionally 

stressed. At present. intraspecific predation is not thought to be influential at the population level anywhere in the 

polar bear range. It appears, however, that its frequency may be on the increase. At some point. it therefore could 

States 

influential 

not 

influential 

not 

inHucntiaL At very low population levels. even a miner increase in predation could be influential. 

E Intentional This node represents direct mortalities including hunting, and collection for zoos, and managt:ment actions. It also increased 

Takes. includes research deaths even though they are not intentionaL samc_as._now 

---t- These arc mortality sources that are very much controllable by re ulatioR decreased 

TI I Contaminants Increased precipitation and glacial melt have recently resulted in greater influx of contaminants into the Arctic elevated 

R4 I Hydrocarbons 

/OilSpill 

Jl I Tourism 

region from the interior of Eurasia via the iarte. northward flowing rivers. Similarly, differing atmospheric same_as_now 

circulation pattems have altered potential pathways for contaminants tram lower latitudes. This node reflects the reduced 

possible increase or decrease of contamination in the Arctic as a result of modified pathways. 

These contaminants can act to make habitat f¢ss suitable and directly affect things like survival and reproduction. 

The grcatest likelihood seems to be that such contaminants will increase in Arctic regions (and indeed worldwide) 

as increasing numbers of chemicals. are developed and as their persistence in the environment is belatedly 

determined, Some contaminants have been reduced and we have the ability to reduce others, bur the record of 

reduction and the persistence of many of these chemicals in the environment suggests the greatest likelihood is for 

elevated levels in the short to medium term with some pt9bability of or even declines far in the future. 

This refers to the release oroil or oil related products into polar bear habitat. Such action would result in direct 

mortality or bears direct mortality of prey, and cOllld result in displacement of bears from areas they fonneriy 

occupied. Hence, it has ramifications for both habitat quality and population dynamics directly. 

Hydrocarbon exploration and development are expanding and proposed to expand further in the Arctic. Greater 

levels of such activity are most likely to increase the probability of oil spills. 

Also. increased shippjI}g will result in higher levels of hydrocarbon release into Arctic waters. 

As sea ice extent declines spatially and temporally access and opportunities for Arctic Tourism also will increu5e. 

Increased tourism could lead to direct disturbances of polar bears as well as to increased levels of contamination. 

Here, we address only the physical presence of more tourism and the conveyances used by tourists land 

vehicles, aircraft). 

The greatest likelihood seems to be that tourism wiU increase. It couid decline. however, if governments take 

actions to reduce interactions with increasingly stressed polar bears. However, as tourism currently accounts Cor 

increased occu

same._as_now 

occu

increased 

same as now 

'-_-' ______ iL:::es"'se"'n"'t"'ia"'iI,L'"no"-"lim""itation to polar bears this effect only comes into play when it is noted to increase, 

82737.351

Node Node title 

name 

1 Node description j States 

I I believe that tourism will increase in all area.,') of the Ar<:-tic until such time as fuel becomes too expensive for 

I people to venture to such remote areas or 10 the polar basm dlYergen1 umt, when It IS essentIally devOid of Ice, It 

I 

mllY not attract many tourists and such activity may slirge and then decline in that region. The arctic areas with 

I

· -L more interesting coastlines etc .. however will probably see nothing but increases in tourism. 

Contamination that may accompany such activities, and biological effect.s from introduced organisms that may 

compele with residents of the food web or cause disease are covered under the nodes for contamination and 

_" __________ -'--_parasi!es and disease. 1 -.c---;-

Bl includes takes which may increase as a result of increased human-bear interactions due to food I increased 

RI 

F 

interactions ! stressed bears more frequently entering Arctic communities. Such takes can displace beElI"S from their preferred same_as_now 

Oil&Gas 

Activity 

Shipping 

AltemHle 

Regions 

Available 

locations and reduce habitat quality. decreased 

This is separate from the similar interactions that may occur around oil and gas or other industrial sites which also 

can displace bears and lower habitat quality. 

These interactions also. however. can result in deaths as when ploblem bears are shot in defense of life and 

property So. this node includes a component of both habitat quality and direct mortality. 

I believe that bear-human interaction..') will increase until such time a,cas are devoid of bea,s or climate cools again 

amI ice returns. 

This refers to the spatial effects of oil and gas activity. It refers to activities and infrastructure \vhich may physically 

displace bears from habitat that wa.s formally available 10 them. It also, can result in direct killings of bears which 

become a persistent safety problem around industrial 

Oil companies etc. have great leSQurces 10 prevent these events from leading to mortalities, but such monalities 

cannot be totally avoided and are likely to increase as habitat base shrinks. 

I think oil and gas acti'lity will increase in the polar basin region through mid century and then decline becau-se 

resources will have been tapped. We may see some increase in exploration and development in the 

increase 

no change 

de-;;rease 

however, as it becomes increasingly ____ +c--_-,-__As sea ice extent declines spatially and temporally it is predicted that shipping in Arctic regions will increase. increased 

Increased shipping, could lead to direct disturbances of polar bears as well as to increased levels of contamination. same _as_.now 

Her.e, we address only the physical presence of more vessel traffic. Contamination (bilge 

oil etc.), and biological effects from intwduced organisms that may compete with residents of the food web O{ cause 

disease are covered under the nodes for contamination and parasites and disease. 

We allow only two stales here: increased and same as now, because we can think of no reason why shipping will 

in the foreseeable future. Even if international shipping does not increase, local shipping will because 

barges and vessels arc more efficient ways to move fuel and freight into remote Arctic locatjons than I 

Are there geographic regions to which bears from the subject region may eftectivdy be able to relocate. Yes 

rhis ability is contingent on othel regions with suitable habitats being contiguous with regions where habitat No 

quantity or quality have degraded to the point they won't support polar bea,s on a seasonal or annual basis. For 

example, if the sea ice is deteriorating throughout the polar basin including the Beaufort Sea and the last ve:')1iges of 

ice are along the Alaskan Coast, there may no where else to go if the ice deteriorates to an unsatisfactory state. If, 

however, the ice re(rcates to the northeast as its extent reduces, bears remaining on the ice may have access to 

suitable habitats in the- archipelago or in NE Gwenland. 

I believe that bears in the seasonal ice region and in the polar bastn will he able to collapse into the archipelago. lee 

patterns suggest that the remaining ice in the arctic is likely to converge on the archipeJage rather than fonn disjunct 

chunks of ice (although some GeMs do predict the latter, this is contrary to the historical recold and the paleo 

record). Yes = other suitable areas are contiguous 

No = other suimble regions arc not contiguous 

82737.352

I Node title 

name 

R2 Relative 

Ringed Sea! 

Availability 

Prey 

Availability 

51 Foraging 

habitat 

character 

Node description States 

This node expresses changes in prey availability that arc likely to occur as sea ice cover declines and its character I increase 

changes. I same as noW 

This node specifically includes only the possibility that ringed seals, the mainstay of polar bears over most of their decre-;:serange might change in abundance and availability. This is specine to the amount of remaining ice, That is, as sea ice 

declines in coverage (which is the only way it seems possible for it to go) will the remaining habitat be more 

producti 'le. 

Availability here refers to the combined effects of abundance and accessibility recognizing that seals may occupy 

areas that make them less available to polar bears even if the seals are still relativelY abundant. Examples of this are 

the recent observations of failed bear attempts to dig through solid ice (a result orthe thinner ice that deforms and 

rans more easily) that predominates now, and the fa-ct that seals may simply stuy in open water all summer and not 

be available to bears even if the seal numbers arc stable, 

My opiniotl is that only in the northern part of the ice convergent zone ofthc polar basin and in portions of the 

archipelago are conditions to improve: for ringed seal availability. And) there, such improvements are likely to be 

transient perhaps through mid century. 

increase =- greater abundance or availability of ringed seals same as now 

decrease = !ess or availab",i1",ity'-c;:;== 

This node expresses changes in prey availability that arc likely to occur as sea ice cover decline.') and its character increase 

changes. This is largely expert opinion because there is little to go on to suggest prey base change possibilities in S3me._.as _now 

the fulure. With very different ice and other ecological differences that may accoml:lUny global warming things 

could occur which arc totally unforeseen. Today's experience, however. suggests that little in the way of significant 

alternate prey is likely to emerge to allow bears to replace traditional prey that may be greatly reduced in the future. 

Where alterna.te prey could become importa.nt is in the seasonal ice regions and the archipelago. Now, harp and 

hooded seals have become important to polar bears as they have moved farther north than historically, As the ice 

retreats into the archipelago it is reasonable to expect that these animals may penetrate deeper into the archipelago 

and provide at !east a transient improvement in alternate prey. It is unclear, however, that such changes could 

persist as bears prey on these seals which arc forced onto smaller an smaller areas of icc. So, I projett only transient 

improvements follo\ved by decline. 

fhis node specifically addresses the possibility that alternate prey either marine or terrestrial might change in a way 

rhat would allow polar bears to take advantage of it. 

increase = greater availability of alternate prey same as now 

decrease = fess opportunity for access to prey items other than ringed seals 

This node expresses a subjective assessment of the quality of sea ice for foraging by polar bears. Recent I morc_optimal 

observations of the changes in sea ice chara(..1er in the s.outhern Beaufort Sea suggest that the later fTeeze up warmer same_us_now 

winters, and earlier ice retreat in summer h<we resulted in thinner ice that more easily deforms and more frequently less_optimal 

rafts over itself. These changes have reduced the quality of ice as a denning and may have reduced its 

quality as a foraging substrate since the extensive ice deformation can result in icc -covered refugia for ringed scals 

which aTe less likely for polar bears to get into. Also, it can result in very rough sharp pressure ridges that arc 

hugely expansive compared to earlier years. This rough ice may also provide refuge for seals, and it also is surely 

difficult for polar bear cays to negotiate as they attempt to move out onto the ice after den emergence in spTing. 

More optimal icc is somewhat heavier not as rough, with pressure ridges comp<:lsed of larger ice blocks. However, 

it can go the other way now. Very heavy stable ice in the Beaufort Sea in the past may have been limiting polar 

bears. This is also prohably currently true in pon:ions of the Canadian Archipelago and in the northern part of 

the Ice convergent zone ofthc polar basin, So, in those areas,l expect that ice quality wilt at first improve with 

global warming and theo decline. 

Because my only sense orthis ice quality is in the polar basin, I am leaving all priors uniform for the other ice 

82737.353

Node I Node title 

name 

Node desc.-iption 

c Foraging 

Habitat 

Absence 

Change 

regions. 

This node expresses the length in months of icc absence from the continental shelf regions currently preferred by 

polar bears. It correspondes to the value "proportional ice free months" from Dave Douglas' calculations. based on 

GeMs. This is [he number of months during which the continental shelf waS icc free where ice free is defined as 

fewer than 501J/1I of the pixels over the shelf having less tha.n 50% ice cover. 

We express this as a change from now. S() the figures in this node represent the difference in months between the 

forecasted number of ice free months for three future time periods and the number of icc free months for the present 

. which is defined as the GeM model outputs Cor the period 200 l·20W. 

I 

The bears in some regions already experience protracted ice free periods, In other regions they don't. The impact of 

the length of the ice free period is dependent mainly upon the productivity of the environment, and has a different 

impact in the Beaufort Sea for example than it does in the currently seasonal icc environments which are, for the 

most part, very productive. 

I 

For example, in the archipelago and PH convergence regions the mean time expressed in teh table must be 

interpreted with regard to thl': fact tbat in large parts of these areas even at a mean months of increased absence, 

actual absence in some parts of these regions would still be 0, An abseMe difference ofGT 3 months meaos 11. mean 

abs.ence of7 or 8 months in the PH divergent wnet and 8 9 or 10 months in the seasonal ice zone, but only] + 

I I 1 months in portions of the archipelago or the PD convergence region. B Foraging I This node expresses the proportional change in the area of polar bear habitat over time. 

11abitat Polar bear habitat is expressed as the number of square km months of optimal RSF habitat in the two polar basin 

Quantity geographic units, and as square km months of ice over continental shelf in the other regions. Because the other 

Change regions are almost entirely shallow water areas, tbe habitat in those areas boils down to essentially the ice extent 

months over each regi<ln. 

We further express this as the percent change in quantity of these icc habitats, from the baseline now which is 

defined as the period 

lnlerpreting the percent difference must take into account that a given percent change in the archipelago or the PB 

convergent region is a very different thing than it might be in the other two units. The absolute -change in the 

I archipelago, for example may be vel)' small. but bc()ause it is measured from essentially 0, it may look like a great 1%. 

These measurements arc derived from the satellite record for the observational period and from the GeM outputs 

States 

·1100 

Oto 1 

I t03 

>=3 

01020 

·20100 ·40 to ·20 

I of sea ice for __ -,, __ =_.,-_---c---,-__ ___ 77'-;-___ +='-'7"-

N Shelf Distance I This node expresses the distance that the ice retreats from traditional autumn/winter foraging areas which.are oVl::r to 0 

L._ 

Change (k.m) ,the continental shelves and other shallow water areas within the polar basin. It is ()a!cuLated by extracting the largest 0 to 200 

contiguous chunk orice whose pixels have >50% concentration and detennining the mean of the measured 20010800 

distances between aU cells in the subpopularion unit and the nearest point within that ()hunk of icc. It is expressed as >= 800 

the difference bct\\'een this mean distance calculated for the pedod and the same mean distance 

calculated for the other rime periods of interest. These distances are derived from the satellite record for the 

observational period and from the GeM outputs of sea ice for future periods. 

Expressing this value as a change from the current time allows the model to show that conditions improve in a hind 

cas.t back to the period of 1985·1995. 

This measurement is available only from the polar basin management units because all other management units 

occur in areas that aTe essenl:ially aU shelf. lienee, the measurement of distance to shelf means nothing. How far has 

the ice retreated from snore .areas where polar bears traditionally have f-oraged in autumn and winter. Caniwill bears 

makt: the trip from remaining summer refugia to these areas. 

Thb node also could be expressed simply as accessible or inaccessible as in denning Meas above. 

This may not apply to regions other than the polar basin, because we don't have reliable assessments of where the 

82737.354

Nod. t N ode title Node description 

I name t-sea ice will be at maximum retreat Need to look at this question more closc-!y. 

Geographic 

Area 

NOTE that we need to revisit how these values are calculated because the July values put in don't really seem to 

reflect reat distances in for example the Archipelago where the ice is not expected to be away from the shelf for a 

long time to come. 

NOTE also that this difference change means a very different think in the divergent unit than it does in teh 

convergent unit. The mean distance to the shelf in the archipelago unit at future times will incorporate regions 

where there is no ice retreat at all and some regions where the change may be quite great (like the northem 

Beaufort). 'Ine overall change in the unit will actually be much more modest than the mean value suggests. In the 

divergent unit, however. a large mean distance means that the ice is unifonnly a long way from the continental 

,helf. 

Geographic region used for combining populations of polar bears. 

States 

Polar Basin DPolar-Basin--C

Archipelago -

Seasonal Ice 

f-n.--. 

___ Output Nodes \a 

o i IOverall i'ompoSitc influence of numerical response and distribution response. larger 

Population same as now 

Outcome -

C4 

C3 

Numerical 

Response Distribution Response 

This node represents the anticipated numerical response of polar bears based upon the sum total of the identified 

factors which are likely to have affected numbers of polar bears in any pan:icular areu. 

This -is the sum total of ecological and human factors that predict the future distribution of polar bears. 

but Resident habitat has changed in a way that would likely lead to a reduced spatial distribution (e.g, 

dut! to avoidance of a human development, or sea ice js still prescnt in the area but in more limited quantity). Bears 

would still occur in the area, but their distribution would he more limited. Transient"'" habitat is seasonally limited 

f--_-'_. ____ -'i...:o"r ..::h"'um=an='c""i.;..vi"'ti=es !lave resulted in a situation where available ice is precluded from use on a seasonal basis, 

Summl!':Y. Nodes 

C2 Pollution fhis is the sum of pollution effects from hydrocarbon discharges directly into arctic waters. and from other 

pollutants brought to the Arctic from other parts orthe world. 

Tbe FWS listing proposal included Pollution as One of the "other factors" along with direct human bear interactions 

that may displace bears or otherwise make habitats less satisfactory, J vie ....... ed the main effect of pollution as a 

potential effect on population dynamics. Clearly, severe pollution as in an oil spill for example, could make habitats 

unsatisfactory and result in direct displacement. The main eftec1,. however, is likely to be how pollution affects 

immune systems. reproductive perfonnance, and survival. Hence, I have included input from this node as: well a5 

from the human disturbance node into both the habitat and the ahundancc side of the network by including input 

rare 

extinct 

increased_dens

same as now 

reduced it

rare 

absent 

same as now 

reduc-;d -but rtransient visito

extjrputed 

reduced 

same as now 

eievattd -

greatly_elevate

____ __ ______ ___ __ 

-4 

__ ____

Cl This node expresses the combination of the changes in "oth!;!r" direct human disturbances to polar bears. This does 

not include changes in sea ice habitat. Nor does it include the contamination possibilities from hydrocarbon 

exploration. Those arc c()vered elsewhere. It cover the direct bear-human intl!ractions that can occur in 

! association with industrial development. 

82737.355

I 

Node I Node title 

name 

H 

G 

A 

Crowding 

Tolerance 

I Relocation 

Possible 

! Foragmg 

habitat value 

l-l.., Foraging 

Habitat 

Distribution 

Node description 

The degree to which polar bears may tolerate increased densities that may result from migration of bears from 

presently occupied regions that become unsuitable to other regions already occupied by polar bears. 

In essence, this is the tolerance of bears to live in more crowded conditions than those at which they presently Jive. 

And, it is a function of fuod availability 

I believe that bears have a reasonable tolerance of crowding iffood is abundant or if they are in good condition 

while waiting for sea ice to return etc. Examples of these situations include 1) porticDs of the high arctic like ncar 

resolute. where bear densities on the sea ice in spring are apparently much higher than {hey are in most of the polar 

basin, and 2) the high densities at which polar bears occur on land in Hudson Bay in summer when they arc loafing 

and waiting for the sea ice to return. 

I assumed that crowding tolerance has little or no effect -on outcome likelihoods until habitat quantity was reduced 

substantially requiring bears from one area to either perish or find some place else to go on at least a seasonal basis. 

Thereafter, if relocations of members of some subpopulations mcant invading the areas occupied by other bears 

crowding tolerance entered an assessment of or not rElocation was a practical solution. I 

Is it likely that polar bears displaced from one region could either seasonally or pennanently relocate to another ", 

region in order to persist 

This is a function of foraging effects (e.g. prey availability) in the alternative area (here I am specifically focusing 

on prey availability in the .alternative area rather than the arca from which the bears may have been displaced) I crowding and contiguity of habitats. 

This node expresses the sum total of things which may work to alter the quality of habitats available to polar bears 

in the future. The idea here that sea ice is retreating spatially and temporally, but is the ice that remains of 

comparable. better or worse quality as polar bear habitat Our RSF values are projected into the with the 

assumption that a piece of ice in 2090 that looks the same as piece of ice in 1985 has the same value to a po\ar bear. i Perhaps because of responses we cannot foresee. it may be better seal habitat, or it may be habitat fOf an alternate I prey. Ccnverseiy, it may be worse because of atmospheric and oceanic processes (e.g. the epontic community is 

less vibrant due to thinner ice which is not around for as long each year). Or it may be worse habitat because of oil 

etc. 

This node expresses the combination of the quantitative ways the retreat of sea ice may affect use of continental 

shelf habitats. 

Our analyses indicate, in addition to reductions of total icc (and RSF Optimum ice) extent (expressed under habitat 

quantity), we will sec seasoMI retreats of the sea ice away from coastal areas now preferred by polar bears, and 

these retreats are projected to progressively become longer. 

These changes wilt affect polar bears by reducing the total availability of ice substrate for bears. They also will 

make ice unavailable for extended periods in many regions bears now occur year round. This will result in the 

opportunity for seasonal occupancy but not year-round occupancy as they have had in the past 

Note that in the PB CDnvergent unit because it includes the NB and QE and EG each of which has different starting 

pOints, the values in the CPT express kind of an average. SimilarlY, in the Seasonal region, there is a huge 

difference between HBay and Foxe Basin or BB. so, again the CPT values are a sort of an average, trying to reflect 

these differences. Ultimately, we need to subdivide these regions a bit more to really reflect what is going on. 

improved_avai

same 8S now 

reduc-;;d -avail 

Or av

Un-;'vailableAlso note that the "same as now" category doesn't really work very well for the seasonal ice environment where 

now is seasonal. The only way to go fi'om here is to better than now or to sporadic. Having a step between now and 

S oradic is not useful. In fact, all ofthese categories need to be changed. r.L'Z--hV-;'i"ta71 "R::atCCescc. --t,""r;!;h"'is"'e"'xZ.pre=ss"'es"'t"'h"'c' combined effect of changes in survival ofaduU females and of),oung and re-productive patterns. improve 

The probabilities assigned each of the states reflects the relative importance to polar bear population dynamics of 

each of these vital rates to the growth of the population, 

This node does not reflect human influences on population growth such as hunting. or mortalities resulting from 

same as now 

-

82737.356

Node I Node title 

U I Reproduction 

VI Cub 

production per 

event 

:=ruvcnile 

Survival 

L I Adult FeUl<u,,; 

Survival 

Node description 

interactions. Those things, along with effects of parasites, contaminants. etc. are brought in as 

modifiers at the level of the next node. 

The sum of trends in numbers of cubs produced and the effect of retreating sea ice on the ability of females to reach 

traditional denning areas. 

This node describes the number of cubs produced per denning attempt. 

States 

increased 

same as now 

decreased 

Fewer_than __ no

same as now 

I more now 

Annual natural survival rate of cubs and yearlings_ Note that this is conditional on survival of the mother. This is the increase 

survival rate for juveniles that would occur in absence of hunting or other anthropogenic factors. Those no_change 

'I anthropoecnic factors that would influence survival are included in node F. decrease 

K I Auu" DUUY 

Annual natural survival rate of sexually mature females. This is the survival rate for adult females that would occur I increase I in absence of hunting or other anthropogenic fh.ctors. Those anthropogenic factors that would influence survival arc no_change 

.-;:-;;--;-_-tI-:i:;c"C",<if-ud=.c,d in node F. decrease 

Body mass index or other indicator ofahllity ofbcars to secure resources. Our analysis suggests body condition has increa.')c 

Condition been declining in the SBS and is inversely correlated ·with ice extent. Also recent analyses indicate that body same_as_.now 

condition is an important predictor of survival ofpoiar bears in SHR 

Summary Nodes - USFWS Listing Factors \b 

1 C'm.' I This node summarizes the combined information about changes in habitat quantity and quaJity. It approximately improvement 

Habitat reflects factor A of the proposal to list polar bears as: threatened. no_.effect 

Threats 

Al I Factor B. 

OverutlIization 

minor.Jestrictimaior restricti

rhis node approximates the FWS Iistlng Factor B. h includes the combination of hunting (harvest), take tor II fewer 

scientific purposes, and take for zoos. It also includes mortalities from bear-human interactions etc. brought in from sume_as_now 

Factor E. These aU are factors which serve to modify the population changes that would be brought about without more 

the direct local interference of humans. 

t-A:"4TFactor C. II This node expresses probability of changing VUlnerability of pol at bear!; to 'diseases and parasites, and to potential 

Disease, , ofintiJspecific predation/cannibalism. WOrse 

1edation 

A6 I Factor [, 

Other factors 

(natural or 

man-made) 

This node approximately corresponds to Factor E of the listing proposal. 1t includes factors (other than [he changes 

in sea ice quality and quantity) which may affect habitat suitability for polar bears. Also. its effects can be directly 

on population dynamics features. I'fence, it applies directly to both the habitat and population sides of our netwwk. 

lncluded here arc effects of a variety of contaminants, including: petroleum hydrocarbons, persistent organic 

pollutants, and metals. Although we don't know much quantitatively aoout effects of these contaminants at the 

population level, we know qualitatively that effects on immune systems and steroid levels etc. will ultimately have 

such effects. We also know thal0il spills will have immediate and dire effects. 

It also includes eftects of hUman activities and developments which may directly affect habitat quality, including: 

shipping and transportation activities, habitat change, noise, spills, ballast discharge, and ecotourism. This includes 

disturbance but not direct killing of bears by humans as a result of DLP cases (direct killing is included under node 

AI), 

I viewed human disturbances as the most predictable in their negative effects until pollution levels reached their 

improvement 

no_cffect 

minor_restrictimajor Jestricti

greatly elevated stage at which time, their import.!to"-"fu",tu"r,,,e ",po",p",u",la",ti",on",s,-w",u",s.",iu",d",g",eci",t",o"b",cJ:g,"r<"'a,,1. _______ '-____

82737.357

Node Node title Node description States 

name 

Descriptive (Disconnected) Nodes \c 

Q Time Period The states forthis node correspond to years -10 (historic), 0 (now), 45 (mid-century), 75 (late century), and 100 historic (1985-199

(end of century). now (1996-2006) 

mid-century (2045

late century (2070

end of century (20

2099) 

R CGM run The states for this node correspond to the data source (either "satellite" for year -10 and 0 runs) and GCN modeling GeM_minimum I scenario (minimum, ensemble mean, or maximum) basis for a given condition. Ensemble_mean 

GCM._maximum 

SateHite 

\a Output nodes here include the Numerical Response and Distribution Response nodes 

provide summary output conditions. 

\b USDI Fish and Wildlife Service (USFWS) lists 5 Listing Factors. Listing factor D 

pertains to inadequacy of existing regulatory mechanisms, and was not included in th

population stressor model because it does not correspond to any specific environmen

stressor. 

\c These two nodes are included in the model to help denote the basis for a given mo

run. They are not included as environmental stressors per se. 
130 


82737.358

Appendix 3. Probability tables for each node in the Bayesian 

network model 

Following are probability tables for each node in the BN model. (These were generated in the Netica 

software.) Not included here are all input nodes (yellow coded nodes in Fig. 5) because each of their 

prior probability tables was set to uniform distributions. 

node H - "Crowding Tolerance" 

Node R2- Node R3-

Alternative prey Relative ringed seal 

availability availability 

increase increase 

increase same as now 

increase decrellse 

same as now increase 

same as now same as now 

same as now decrease 

decrease increase 

decrease same as now 

node G - "Relocation Possible" 

Node FAlternative 

regions available 

Yes 

Yes 

Yes 

No 

No 

Node HCrowding 

tolerance 

none 

moderate 

high 

none 

moderate 

Level of Crowding Tolerance 

none moderate high 

0.0 0.2 0.8 

0.0 OA 0.6 

0.1 0.5 0.4 

0.0 0.4 0.6 

0.1 0.8 0.1 

0.3 0.6 0.1 

0.1 0.5 0.4 

0.3 0.5 0.2 

Possibilty of relocation 

Yes No 

0.0 1.0 

0.8 0.2 

1.0 0.0 

0.0 1.0 

0.0 1.0 
131 


82737.359

node A - "Foraging habitat value" 

Node SI - Node G- Value offoraging habitat 

Foraging habitat Relocation same as 

character possible better now worse 

more optimal Ye.s 0.7 OJ 0.0 

more optimal No 0.2 0.6 0.2 

same as now Yes 0.1 0.8 0.1 

same as now No 0.0 0.8 0.2 

less optimal Yes 0.0 0.3 0.7 

less optimal No 0,0 0.0 1.0 

node N - "Shelf Distance Change (km)" 

Distance of shelf change 

-200 to a 0 to 200 200 to 800 >=800 

0.25 0.25 0.25 0.25 

82737.360

node D - "Change in Foraging Habitat Distribution" 

Node M- NodeC - NodcN - Distribution of foraging habitat 

Geographic area Foraging habitat Shelf distance improved same as reduced Gr reduced un

absence change change availab now avail avail 

Polar Basin Dive -I to 0 -200 to 0 1.0 0.0 0.0 0.0 0.0 

Polar Basin Dive -1 to 0 o to 200 . 0.8 0.2 0.0 0.0 0.0 

Polar Basin Dive -I to 0 200 to 800 0.2 0.6 0.2 0.0 0.0 

Polar Basin Dive -I to 0 >= 800 0.0 0.4 0.6 0.0 0.0 

Polar Basin Dive o to I -200 to 0 0.5 0.5 0.0 0.0 0.0 

Polar Basin Dive Oto I o to 200 0.0 0.2 0.8 0.0 0.0 

Polar Basin Dive Oto I 200 to 800 0.0 0.0 0.5 0.5 0.0 

Polar Basin Dive o to I >=800 0.0 0.0 0.25 0.5 0.2

Polar Basin Dive I to 3 -200 to 0 0.2 0.4 0.4 0.0 0.0 

Polar Basin Dive I to 3 o to 200 0.0 0.0 0.5 03 0.2 

Polar Basin Dive I to 3 200 to 800 0.0 0.0 0.2 0.4 0.4 

Polar Basin Dive I to 3 >= 800 0.0 0.0 0.0 0.2 0.8 

Polar Basin Dive >=3 -200 to 0 0.0 03 0.5 0.2 0.0 

Polar Basin Dive >=3 o to 200 0.0 0.0 0.2 0.4 0.4 

Polar Basin Dive >=3 200 to 800 0.0 0.0 0.0 0.1 0.9 

Polar Basin Dive >=3 >=800 0.0 0.0 0.0 0.0 1.0 

Polar Basin Conv -I to 0 -200 to 0 1.0 0.0 0.0 0.0 0.0 

Polar Basin Conv -1 to 0 o to 200 0.8 0.2 0.0 0.0 0.0 

Polar Basin Conv -I to 0 200 to 800 0.6 0.4 0.0 0.0 0.0 

Polar Basin Conv -I to 0 >= 800 0.4 0.6 0.0 0.0 0.0 

Polar Basin Conv o to I -200 to 0 1.0 0.0 0.0 0.0 0.0 

Polar Basin Conv o to I o to 200 0.6 0.4 0.0 0.0 0.0 

Polar Basin Conv o to I 200 to 800 0.2 0.4 0.4 0.0 0.0 

Polar Basin Conv Oto I >= 800 0.0 0.2 0.8 0.0 0.0 

Polar Basin Cony I to 3 -200 to 0 0.6 0.4 0.0 0.0 0.0 

Polar Basin Con v I to 3 o to 200 0.1 0.5 0.4 0.0 0.0 

Polar Basin Conv I to 3 200 to 800 0.0 03 0.7 0.0 0.0 

Polar Basin Conv I to 3 >=800 0.0 0.0 1.0 0.0 0.0 

Polar Basin Conv >=3 -200 to 0 0.4 0.6 0.0 0.0 0.0 

Polar Basin Conv >= 3 o to 200 0.1 03 0.5 0.1 0.0 

82737.361

Polar Basin Cony >= 3 200 to 800 0.0 0.2 0.6 0.2 0.0 

Polar Basin Cony >=3 >= 800 0.0 0.0 0.7 0.3 0.0 

Archipelago -1 to 0 -200 to 0 0.0 1.0 0.0 0.0 0.0 

Archipelago -1 to 0 o to 200 0.0 1.0 0.0 0.0 0.0 

Archipelago -I to 0 20010800 0.0 1.0 0.0 0.0 0.0 Archipelago -1 to 0 >=800 0.0 1.0 0.0 0.0 0.0 Archipelago o to I -200 to 0 0.6 0.4 0.0 0.0 0.0 

Archipelago o to I o to 200 0.6 0.4 0.0 0.0 0.0 

Archipelago o to I 200 to 800 0.6 0.4 0.0 0.0 0.0 

Archipelago o to I >=800 0.6 0.4 0.0 0.0 0.0 

Archipelago 1 to 3 -200 to 0 0.4 0.6 0.0 0.0 0.0 

Archipelago I to 3 o to 200 0.4 0.6 0.0 0.0 0.0 

Archipelago 1 to 3 200 to 800 0.4 0.6 0.0 0.0 0.0 

Archipelago I to 3 >=800 0.4 0.6 0.0 0.0 0.0 

Archipelago >= 3 -200 to 0 0.0 0.6 0.4 0.0 0.0 

Archipelago >=3 o to 200 0.0 0.6 0.4 0.0 0.0 

Archipelago >= 3 200 to 800 0.0 0.6 0.4 0.0 0.0 

Archipelago >= 3 >= 800 0.0 0.6 0.4 0.0 0.0 

Seasonal Ice -I to 0 -200 to 0 0.5 0.5 0.0 0.0 0.0 

Seasonal Ice -1 to 0 o to 200 0.5 0.5 0.0 0.0 0.0 

Seasonal Ice -I to 0 200 to 800 0.5 0.5 0.0 0.0 0.0 

Seasonal Ice -I to 0 >= 800 0.5 0.5 0.0 0.0 0.0 

Seasonal Ice o to I -200 to 0 0.0 0.2 0.6 0.2 0.0 

Seasonal lee o to I o to 200 0.0 0.2 0.6 0.2 0.0 

Seasonal Ice o to I 200 to 800 0.0 0.2 0.6 0.2 0.0 

Seasonal Ice o to I >= 800 0.0 0.2 0.6 0.2 0.0 

Seasonal Ice I to 3 -200 to 0 0.0 0.0 0.2 0.4 0.4 

Seasonal Ice I to 3 o to 200 0.0 0.0 0.2 0.4 0.4 

Seasonal Ice I to 3 200 to 800 0.0 0.0 0.2 0.4 0.4 

Seasonal Ice 1 to 3 >= 800 0.0 0.0 0.2 0.4 0.4 

Seasonal Ice >= 3 -200 to 0 0.0 0.0 0.0 0.1 0.9 

Seasonal Ice >= 3 o to 200 0.0 0.0 0.0 0.1 0.9 Seasonal Ice >= 3 200 to 800 0.0 0.0 0.0 0.1 0.9 Seasonal lee >= 3 >=800 0.0 0.0 0.0 0.1 0.9 

82737.362

node F2 "Factor A: Habitat Threats" 

D- Node A- Level of habitat threat 

Foraging habitat Change in foraging Foraging habitat minor major 

change habitat distribution value no effect restriction restric

o to 20 improved availab better 1.0 0.0 0.0 0.0 o to 20 improved availab same as now 1.0 0.0 0.0 0.0 o to 20 improved availab worse 0.8 0.2 0.0 0.0 o to 20 same as now better 1.0 0.0 0.0 0.0 o to 20 same as now same as now 0.8 0.2 0.0 0.0 

o to 20 same as now worse 0.3 0.5 0.2 0.0 o to 20 reduced avail better 0.4 0.4 0.2 0.0 o to 20 reduced avail same as now 0.2 0.6 0.2 0.0 

o to 20 reduced avail worse 0.0 0.2 0.6 0.2 

o to 20 Gr reduced avail better 0.0 0.2 0.4 0.4 

o to 20 Gr reduced avail same as now 0.0 0.0 0.4 0.6 

o to 20 Gr reduced avail worse 0.0 0.0 0.2 0.8 

o to 20 unavailable better 0.0 0.0 0.0 1.0 o to 20 unavailable same as now 0.0 0.0 0.0 1.0 

o to 20 unavailable worse 0.0 0.0 0.0 1.0 

-20 to 0 improved availab better 0.8 0.2 0.0 0.0 

-20 to 0 improved availab same as now 0.2 0.6 0.2 0.0 

-20 to 0 improved availab worse 0.2 0.4 0.4 0.0 

-20 to 0 same as now better 0.2 0.6 0.2 0.0 

-20 to 0 same as now same as now 0.0 0.2 0.6 0.2 

-20 to 0 same as now worse 0.0 0.0 0.6 0.4 

-20 to 0 reduced avail better 0.1 0.5 0.2 0.2 

-20 to 0 reduced avail same as now 0.0 0.1 0.5 0.4 

-20 to 0 reduced avail worse 0.0 0.0 0.4 0.6 

-20 to 0 Gr reduced avail better 0.0 0.0 0.5 0.5 

-20 to 0 Gr reduced avail same as now 0.0 0.0 0.2 0.8 

-20 to 0 Gr reduced avail worse 0.0 0.0 0.0 1.0 

82737.363

-20 to 0 unavailable better 0.0 0.0 0.0 1.0 -20 to 0 unavailable same as now 0.0 0.0 0.0 1.0 -20 to 0 unavailable worse 0.0 0.0 0.0 1.0 -40 to -20 improved availab better 0.4 0.4 0.2 0.0 

-40 to -20 improved availab same as now 0.1 0.5 0.4 0.0 

-40 to -20 improved availab worse 0.0 0.3 0.5 0.2 

-40 to -20 same as now better 0.1 0.4 0.4 0.1 

-40 to -20 same as now same as now 0.0 0.1 0.4 0.5 

-40 to -20 same as now worse 0.0 0.0 0.4 0.6 

-40 to -20 reduced avail better 0.0 0.1 0.6 0.3 

-40 to -20 reduced avail same as now 0.0 0.0 0.5 0.5 

-40 to -20 reduced avail worse 0.0 0.0 0.2 0.8 -40 to -20 Gr reduced avail better 0.0 0.0 0.3 0.7 

-40 to -20 Gr reduced avail same as now 0.0 0.0 0.0 1.0 

-40 to -20 Gr reduced avail worse 0.0 0.0 0.0 1.0 -40 to -20 unavailable better 0.0 0.0 0.0 1.0 

-40 to -20 unavailable same as now 0.0 0.0 0.0 1.0 

-40 to -20 unavailable worse 0.0 0.0 0.0 1.0 

< -40 improved availab better 0.2 0.6 0.2 0.0 

< -40 improved availab same as now 0.0 0.2 0.6 0.2 

<-40 improved availab worse 0.0 0.0 0.5 0.5 

< -40 same as now better 0.0 0.1 0.6 0.3 

<-40 same as now same as now 0.0 0.0 0.3 0.7 

< -40 same as now worse 0.0 0.0 0.2 0.8 

<-40 reduced avail better 0.0 0.1 0.2 0.7 

< -40 reduced avaH same as now 0.0 0.0 0.1 0.9 

<-40 reduced avail worse 0.0 0.0 0.0 1.0 

<-40 Gr reduced avail better 0.0 0.0 0.0 1.0 

< -40 Gr reduced avail same as now 0.0 0.0 0.0 1.0 

< -40 Gr reduced avail worse 0.0 0.0 0.0 1.0 < -40 unavailable better 0.0 0.0 0.0 1.0 

<-40 unavailable same as now 0.0 0.0 0.0 1.0 

< -40 unavailable worse 0.0 0.0 0.0 1.0 

82737.364

node C 1 - "Human disturbance" 

Node B1 • Node J- Node Rl - Node JI- Level of human disturbance 

Bear-human Oil & gas same 

interactions ShiEEing Tourism reduced as now elevated 

increased increased increase increased 0.0 0.0 0.0 increased increased increase same as now 0.0 0.0 0.0 

increased increased increase decreased 0.0 0.0 0.1 

increased increased no change increased 0.0 0.0 0.0 

increased increased no change same as now 0.0 0.0 0.1 

increased increased no change decreased 0.0 0.0 0.2 

increased increased decrease increased 0.0 0.0 0.3 

increased increased decrease same as now 0.0 0.0 0.6 

increased increased decrease decreased 0.0 0.0 0.5 increased same as now increase increased 0.0 0.0 0.0 

increased same as now increase same as now 0.0 0.0 0.2 

increased same as now increase decreased 0.0 0.0 0.3 

increased same as now no change increased 0.0 0.0 0.5 

increased same as now no change same as now 0.0 0.0 0.7 

increased same as now no change decreased 0.0 0.2 0.6 

increased same as now decrease increased 0.0 0.0 0.7 

increased same as now decrease same as now 0.0 0.2 0.7 

increased same as now decrease decreased 0.0 0.4 0.6 

same as now increased increase increased 0.0 0.0 0.2 

same as now increased increase same as now 0.0 0.0 0.5 

same as now increased increase decreased 0.0 0.2 0.6 

same as now increased no change increased 0.0 0.2 0.8 

same as now increased no change same as now 0.0 0.3 0.7 

same as now increased no change decreased 0.0 0.5 0.5 

same as now increased decrease increased 0.0 0.3 0.7 

same as now increased decrease same as now 0.0 0.5 0.5 

82737.365

same as now increased decrease decreased 0.0 0.6 0.4 0

same as now same as now increase increased 0.0 0.2 0.8 0

same as now same as now increase same as now 0.0 0.4 0.6 0

same as now same as now increase decreased 0.0 0.5 0.5 0

same as now same as now no change increased 0.0 0.8 0.2 0

same as now same as now no change same as now 0.0 1.0 0.0 0

same as now same as now no change decreased 0.1 0.9 0.0 0

same as now same as now decrease increased 0.3 0.7 0.0 0

same as now same as now decrease same as now 0.5 0.5 0.0 0

same as now same as now decrease decreased 0.6 0.4 0.0 0

decreased increased increase increased 0.0 0.0 0.6 0

decreased increased increase same as now 0.0 0.2 0.6 0

decreased increased increase decreased 0.0 0.3 0.7 0

decreased increased no change increased 0.1 0.6 0.3 0

decreased increased no change same as now 0.2 0.6 0.2 0

decreased increased no change decreased 0.3 0.5 0.2 0

decreased increased decrease increased 0.2 0.6 0.2 0decreased increased decrease same as now 0.3 0.7 0.0 0decreased increased decrease decreased 0.4 0.6 0.0 0

decreased same as now increase increased 0.0 0.5 0.5 0

decreased same as now increase same as now 0.2 0.6 0.2 0

decreased same as now increase decreased 0.3 0.6 0.1 0

decreased same as now no change increased 0.5 0.5 0.0 0decreased same as now no change same as now 0.7 0.3 0.0 0decreased same as now no change decreased 0.8 0.2 0.0 0

decreased same as now decrease increased 0.9 0.1 0.0 0

decreased same as now decrease same as now 1.0 0.0 0.0 0

decreased same as now decrease decreased 1.0 0.0 0.0 0
138 


82737.366

node C2 "Pollution" 

Node R4- Node Tl - Level of pollution 

Hydrocarbons I oil same greatly 

sQili Contaminants reduced as now elevated elevated 

increased occurI' elevated 0.0 0.0 0.0 1.0 

increased occurr same as now 0.0 0.0 0.6 0.4 

increased occurr reduced 0.0 0.4 0.4 0.2 

same as now elevated 0.0 0.3 0.7 0.0 

same as now same as now 0.0 1.0 0.0 0.0 

same as now reduced 0.4 0.6 0.0 0.0 

decreased occurr elevated 0.3 0.5 0.2 0.0 

decreased occurI' same as now 0.8 0.2 0.0 0.0 

decreased occurr reduced 1.0 0.0 0.0 0.0 

node A6 - "Factor E. Other factors natural or man-made" 

Node CI - Node C2- Level of other factors 

minor major 

CI C2 imQrovement no effect restrictio restrictio 

._------ reduced reduced 1.0 0.0 0.0 0.0 

reduced same as now 1.0 0.0 0.0 0.0 

reduced elevated 0.3 0.4 0.3 0.0 

reduced greatly elevated 0.0 0.3 0.3 0.4 

same as now reduced 0.6 0.4 0.0 0.0 

same as now same as now 0.0 1.0 0.0 0.0 

same as now elevated 0.0 0.4 0.6 0.0 

same as now greatly elevated 0.0 0.2 0.2 0.6 

elevated reduced 0.0 0.2 0.5 0.3 

elevated same as now 0.0 0.0 0.5 0.5 

elevated elevated 0.0 0.0 0.4 0.6 

elevated greatly elevated 0.0 0.0 0.3 0.7 

greatly elevated reduced 0.0 0.0 0.3 0.7 

greatly elevated same as now 0.0 0.0 0.2 0.8 

greatly elevated elevated 0.0 0.0 0.1 0.9 

greatl~ elevated greatl~ elevated 0.0 0.0 0.0 1.0 
139 


82737.367

node C3 "Distribution Response" 

Node F2- Node A6- Node G- Distribution response 

Factor A. Habitat Factor E. Other factors Relocation same reduced transient 

Threats (natural or man-made) Qossible as now but resi visito extirQated 

improvement improvement Yes 1.0 0.0 0.0 0.0 

improvement improvement No 1.0 0.0 0.0 0.0 

improvement no effect Yes 1.0 0.0 0.0 0.0 

improvement no effect No 1.0 0.0 0.0 0.0 

improvement minor restrietio Yes 0.9 0.1 0.0 0.0 

improvement minor restrictio No 0.9 0.1 0.0 0.0 

improvement major restrictio Yes 0.8 0.1 0.1 0.0 

improvement major restrlctio No 0.8 0.2 0.0 0.0 

no effect improvement Yes 1.0 0.0 0.0 0.0 

no effect improvement No 1.0 0.0 0.0 0.0 

no effect no effect Yes 1.0 0.0 0.0 0.0 

no effect no effect No 1.0 0.0 0.0 0.0 

no effect minor restrictio Yes 0.8 0.1 0.1 0.0 

no effect minor restrictio No 0.8 0.2 0.0 0.0 

no eiTect major restrictio Yes 0.5 0.2 0.3 0.0 

no effect major restrictio No 0.5 0.5 0.0 0.0 

minor restrictio improvement Yes 0.5 0.25 0.25 0.0 

minor restrictio improvement No 0.5 0.5 0.0 0.0 

minor restrlctio no effect Yes 0.4 0.3 0.3 0.0 

minor restrictio no effect No 0.4 0.6 0.0 0.0 

minor restrictio minor restrictio Yes 0.3 0.3 0.4 0.0 

minor restrictio minor restrictio No 0.3 0.6 0.0 0.[ 

minor restrictio major restrictio Yes 0.2 0.2 0.6 0.0 

minor restrietio major restdetio No 0.2 0.5 0.0 0.3 

major restrictio improvement Yes 0.0 0.3 0.35 0.35 

major restrictio improvement No 0.0 0.3 0.0 0.7 

major restrietio no effect Yes 0.0 0.2 0.4 0.4 

major restrictio no effect No 0.0 0.2 0.0 0.8 

major rcstrictio minor rcstrictio Yes 0.0 0.1 0.45 0.45 

major restrietio minor restrictio No 0.0 0.1 0.0 0.9 

major restrictio major rcstrictio Yes 0.0 0.0 0.3 0.7 

major restrietio maior restrictio No 0.0 0.0 0.0 1.0 
140 


82737.368

node K "Adult Body Condition" 

Node F2- Quality of adult body condition 

Factor A. Habitat Threats increase same as now decrease 

improvement 

no effect 

minor restrictio 

major restrictio 

node L 1 - "Adult Female Survival" 

Node KAdult Body 

Condition 

increase 

increase 

increase 

increase 

same as now 

same as now 

same as now 

decrease 

decrease 

decrease 

decrease 

1.0 0.0 0.0 

QO 1.0 O~ 

0.0 0.5 0.5 

O~ O~ I~ 

Node F2- Adult Female Survival 

Factor A. no 

Habitat Threats increase change decrease 

improvement 1.0 0.0 0.0 

no effect 0.8 0.2 0.0 

minor restrictio 0.1 0.6 0.3 

major restrictio 0.0 0.5 0.5 

no effect 0.5 0.5 0.0 

minor restrictio 0.0 0.6 0.4 

major restrietio 0.0 0.3 0.7 

improvement 0.0 0.4 0.6 

no effect 0.0 0.2 0.8 

minor restrictio 0.0 0.1 0.9 

major restrictio 0.0 0.0 1.0 
141 


82737.369

node L - "Juvenile Survival" 

Node K- Node Ll - Juvenile Survival 

Adult Body Adult Female no 

Condition Survival increase change decrease 

increase increase 1.0 0.0 0.0 

increase no change 0.7 0.3 0.0 

increase decrease 0.0 0.4 0.6 

same as now increase 0.8 0.2 0.0 

same as now no change 0.0 l.0 0.0 

same as now decrease 0.0 0.2 0.8 

decrease increase 0.0 0.6 0.4 

decrease no change 0.0 0.3 0.7 

decrease decrease 0.0 0.0 LO 

node VI "Cub production per event" 

Node F2- Cub Production per event 

Fewer than same as more than 

Factor A. Habitat Threats now now now 

improvement 0.0 0.3 0.7 

no effect 0.0 1.0 0.0 

minor restrictio 0.6 0.4 0.0 

major restrictio l.0 0.0 0.0 

82737.370

node U "Reproduction" 

NodcM - Node VI- NodeN Rate of reproduction 

Cub production per Shelf Distance same as 

GeograQhic Area event Change increased now dec

Polar Basin Dive Fewer than now -200 to 0 0.0 0.3 0.7 

Polar Basin Dive Fewer than now o to 200 0.0 0.2 0.8 

Polar Basin Dive Fewer than now 200 to 800 0.0 0.0 1.0 

Polar Basin Dive Fewer than now >;800 0.0 0.0 1.0 Polar Basin Dive same as now -200 to 0 0.7 0.3 0.0 

Polar Basin Dive same as now o to 200 0.0 1.0 0.0 

Polar Basin Dive same as now 200 to 800 0.0 0.3 0.7 

Polar Basin Dive same as now >= 800 0.0 0.0 1.0 

Polar Basin Dive more than now -200 to 0 1.0 0.0 0.0 

Polar Basin Dive more than now o to 200 0.5 0.5 0.0 

Polar Basin Dive more than now 200 to 800 0.0 0.5 0.5 

Polar Basin Dive more than now >; 800 0.0 0.0 1.0 

Polar Basin Cony Fewer than now -200 to 0 0.0 0.5 0.5 

Polar Basin Cony F ewer than now o to 200 0.0 0.4 0.6 

Polar Basin Cony Fewer than now 200 to 800 0.0 0.3 0.7 Polar Basin Cony Fewer than now 800 0.0 0.2 0.8 

Polar Basin Cony same as now -200 to 0 1.0 0.0 0.0 

Polar Basin Cony same as now o to 200 0.5 0.5 0.0 

Polar Basin Cony same as now 200 to 800 0.2 0.6 0.2 

Polar Basin Cony same as now >=800 0.0 0.5 0.5 

Polar Basin Cony more than now -200 to 0 1.0 0.0 0.0 

Polar Basin Cony more than now o to 200 0.8 0.2 0.0 

Polar Basin Cony more than now 200 to 800 0.4 0.4 0.2 Polar Basin Cony more than now >;800 0.2 0.4 0.4 

Archipelago Fewer than now -200 to 0 0.0 0.2 0.8 

Archipelago Fewer than now o to 200 0.0 0.2 0.8 

Archipelago Fewer than now 200 to 800 0.0 0.2 0.8 

Archipelago Fewer than now >= 800 0.0 0.2 0.8 

Archipelago same as now -200 to 0 0.2 0.6 0.2 

Archipelago same as now o to 200 0.2 0.6 0.2 

82737.371

Archipelago same as now 200 to 800 0.2 0.6 0.2 

Archipelago same as now >= 800 0.2 0.6 0.2 

Archipelago more than now -200 to 0 0.8 0.2 0.0 

Archipelago more than now o to 200 0.8 0.2 0.0 

Archipelago more than now 200 to 800 0.8 0.2 0.0 Archipelago more than now >=800 0.8 0.2 0.0 

Seasonal Ice Fewer than now -200 to 0 0.0 0.2 0.8 

Seasonal Ice Fewer than now o to 200 0.0 0.2 0.8 

Seasonal lee Fewer than now 200 to 800 0.0 0.2 0.8 

Seasonal lee Fewer than now >= 800 0.0 0.2 0.8 

Seasonal lee same as now -200 to 0 0.2 0.6 0.2 

Seasonal lee same as now o to 200 0.2 0.6 0.2 

Seasonal Ice same as now 200 to 800 0.2 0.6 0.2 

Seasonal Ice same as now >= 800 0.2 0.6 0.2 

Seasonal Ice more than now -200 to 0 0.8 0.2 0.0 

Seasonal Ice more than now o to 200 0.8 0.2 0.0 

Seasonal Ice more than now 200 to 800 0.8 0.2 0.0 

Seasonal Ice more than now >= 800 0.8 0.2 0.0 
144 


82737.372

node L2 - "Vital Rates" 

Node LI - Node L- Node U- Vital Rates 

Adult Female Juvenile same 

Surival Survival Re2roduction im2rove as now decline 

increase increase increased 1.0 0.0 0.0 

increase increase same as now 1.0 0.0 0.0 

Increase increase decreased 0.6 0.4 0.0 

increase no change increased 0.9 0.1 0.0 

increase no change same as now 0.8 0.2 0.0 

increase no change decreased 0.7 0.2 0.1 

increase decrease increased 0.3 0.5 0.2 

increase decrease same as now 0.2 0.5 0.3 

increase decrease decreased 0.0 0.4 0.6 

no change increase increased 0.7 0.3 0.0 

no change increase same as now 0.6 0.4 0.0 

no change increase decreased 0.2 0.5 0.3 

no change no change increased 0.2 0.8 0.0 

no change no change same as now 0.0 1.0 0.0 

no change no change decreased 0.0 0.8 0.2 

no change decrease increased 0.0 0.6 0.4 

no change decrease same as now 0.0 0.5 0.5 

no change decrease decreased 0.0 0.3 0.7 

decrease increase increased 0.2 0.4 0.4 

decrease increase same as now 0.0 0.6 0.4 

decrease increase decreased 0.0 0.5 0.5 

decrease no change increased 0.1 0.5 0.4 

dccrease no change same as now 0.0 OA 0.6 

decrease no change decreased 0.0 0.3 0.7 

decrease decrease increased 0.0 0.2 0.8 

decrease decrease same as now 0.0 0.0 1.0 

decrease decrease decreascd 0.0 0.0 1.0 
145 


82737.373

node Al - "Factor B. Overutilization" 

Node E- Node A6- Level of Overutilization 

Intentional Factor E. Other factors same as 

Takes (natural or man-made) fewer now more 

increased improvement 0.0 0.4 0.6 

increased no effect 0.0 0.0 1.0 

increased minor restrictio 0.0 0.0 1.0 

increased major restrictio 0.0 0.0 1.0 

same as now improvement 1.0 0.0 0.0 

same as now no etTect 0.0 1.0 0.0 

same as now minor restrictio 0.0 0.6 0.4 

same as now major restrictio 0.0 0.3 0.7 

decreased improvement 1.0 0.0 0.0 

decreased no effect 1.0 0.0 0.0 

decreased minor restrictio 0.0 0.8 0.2 

decreased major restrictio 0.0 0.6 0.4 

node A4 - "Factor C. Disease, predation" 

Node T- Node T2- Level of disease, predation 

Parasites & 

Disease Predation same as now worse 

influential influential 0.0 1.0 

influential not 0.3 0.7 

not influential 0.7 0.3 
146 


82737.374

node C4 "Numerical Response" 

Node L2. Node Al • Node A4- Numerical Response 

Factor B. Factor C. Disease, increased same reduced 

Vital Rates Overutilization Predation dens it as now density rare absent 

improve fewer same as now 1.0 0.0 0.0 0.0 0.0 

improve fewer worse 0.5 0.25 0.25 0.0 0.0 

improve same as now same as now 0.8 0.2 0.0 0.0 0.0 

improve same as now worse 0.5 0.25 0.25 0.0 0.0 

improve more same as now 0.3 0.35 0.35 0.0 0.0 

improve more worse 0.1 0.4 0.5 0.0 0.0 

same as now fewer same as now 0.2 0.8 0.0 0.0 0.0 

same as now fewer worse 0.0 0.8 0.2 0.0 0.0 

same as now same as now same as now 0.0 1.0 0.0 0.0 0.0 

same as now same as now worse 0.0 0.3 0.7 0.0 0.0 

same as now more same as now 0.0 0.2 0.8 0.0 0.0 

same as now more worse 0.0 0.0 1.0 0.0 0.0 

decline fewer same as now 0.0 0.5 0.5 0.0 0.0 

decline fewer worse 0.0 0.3 0.7 0.0 0.0 

decline same as now same as now 0.0 0.0 l.0 0.0 0.0 

decline same as now worse 0.0 0.0 0.75 0.25 0.0 

decline morc same as now 0.0 0.0 0.4 0.4 0.2 

decline more worse 0.0 0.0 0.2 0.4 0.4 
147 


82737.375

node DI "overall population outcome" 

Node C4- Node C3- Overall population outcome 

same 

Numerical resEonse Distribution resEonse larger as now smaller rare extinct 

increased densit same as now 1.0 0.0 0.0 0.0 0.0 

increased densit reduced but resi 0.3 0.5 0.2 0.0 0.0 

increased densit transient visito 0.1 0.3 0.3 0.3 0.0 

increased densit extirpated 0.0 0.0 0.0 0.0 1.0 

same as now same as now 0.0 1.0 0.0 0.0 0.0 

same as now reduced but resi 0.0 0.3 0.7 0.0 0.0 

same as now transient visito 0.0 0.0 0.6 0.4 0.0 

same as now extirpated 0.0 0.0 0.0 0.0 1.0 

reduced density same as now 0.0 0.0 1.0 0.0 0.0 

reduced density reduced but resi 0.0 0.0 0.7 OJ 0.0 

reduced density transient visito 0.0 0.0 0.3 0.7 0.0 

reduced density extirpated 0.0 0.0 0.0 0.0 1.0 

rare same as now 0.0 0.0 0.0 1.0 0.0 

rare reduced but resi 0.0 0.0 0.0 0.8 0.2 

rare transient visito 0.0 0.0 0.0 0.7 0.3 

rare extirpated 0.0 0.0 0.0 0.0 1.0 

absent same as now 0.0 0.0 0.0 0.0 1.0 

absent reduced but res! 0.0 0.0 0.0 0.0 1.0 

absent transient visito 0.0 0.0 0.0 0.0 1.0 

absent extirQated 0.0 0.0 0.0 0.0 1.0 
148 

OPENING STATEMENT OF HON. JOHN BARRASSO, 

U.S. SENATOR FROM THE STATE OF WYOMING 

Senator BARRASSO. Thank you, Madam Chairman. I appreciate 

the opportunity to be here today and I appreciate the witnesses 

coming to testify. 

I am just going to be very brief, if I could. It is just that when 

we last met before Christmas for the markup of the LiebermanWarner bill in that long, marathon session, the final amendment, 

and I think they played that on C-SPAN all over the Christmas 

holidays. One night I went to bed and it was on and I woke up and 

the Committee meeting was still on C-SPAN. 

[Laughter.] 

Senator BARRASSO. It was something. 

The final amendment that I offered, and we didn’t get into a discussion, had to do with if Lieberman-Warner would be tied to the 

Endangered Species Act. I was assured that that was nowhere the 

intention, I believed that. Then I saw an article in the Baltimore 

Sun by the staff attorney at the Center for Biological Diversity. 

And she writes: ‘‘Once protection for the polar bear is finalized, 

Federal agencies and other large greenhouse gas emitters will be 

required by law to ensure that the emissions do not jeopardize the 

species. And the only way to avoid jeopardizing the polar bear is 

to reduce emissions.’’ 

So I would ask if I could make this article from the Baltimore 

Sun a part of the record, and I look forward to the discussion. 

Thank you. 

[The referenced material was not submitted at time of print.] 

Senator BOXER. Sure, and Senator, I just would point out to you 

that that is exactly what the ESA would require, it has nothing to 

do with any other law that we would pass. Unless we weaken the 

ESA, that may well be one of the things that is required. But it 

has nothing to do with Lieberman-Warner. 

Senator Lieberman, I just wanted to point out that you do head 

the subcommittee that has within its jurisdiction the protection of 

wildlife. You have already held hearings on this, but I am just 

thrilled to have you here today. 

OPENING STATEMENT OF HON. JOSEPH LIEBERMAN, 

U.S. SENATOR FROM THE STATE OF CONNECTICUT 

Senator LIEBERMAN. Thanks, Madam Chairman. 

Correct, in fact, that marathon that Senator Barrasso, at least in 

the C-SPAN version, slept through, he was wide awake when it actually happened, was preceded in the process that led to the adoption of the Climate Security Act in December and reporting by a 

majority of members of Committee to the floor actually began at a 

hearing almost a year ago to this day that Senator Warner and I 

convened in our subcommittee on the impacts of global warming on 

wildlife. 

In that hearing, we heard of the ways in which unchecked global 

warming is already harming, and of course in the absence of further action, will increasingly harm species and entire ecosystems 

that are integral to our way of life and the well-being of human societies around the world. And of course, these species and ecoVerDate Aug 31 2005 12:30 Jan 15, 2014 Jkt 000000 PO 00000 Frm 00154 Fmt 6633 Sfmt 6633 S:\_EPW\DOCS\82737.TXT VERN
149 

systems themselves have an inherent worth, in my belief structure, 

as part of God’s creation, so that the impact on the well-being of 

human societies is important. But it is important to remember that 

these species have value within themselves. If I might just go on 

a moment, inspired, which is to say that I was raised in a tradition 

that reminded us that in the Bible, in Genesis, God says to Adam 

and Eve in the garden of Eden, from which we were unfortunately 

banned, that they have a responsibility to both work, which is to 

say enjoy, reap the benefits of, but also to guard and protect the 

garden and all that is in it, the implication being for future generations. 

We hard in that hearing nearly a year ago quite a remarkable 

accumulation of testimony. In that hearing, the Fish and Wildlife 

Service Director, Mr. Hall, who we are privileged to have with us 

today, identified a warming climate and the resulting melting of 

sea ice as the primary reason that polar bears were threatened as 

a species. So we have both the indication of a threat to the species, 

but also if you will, the polar bear may be to global warming what 

the canary in the coal mine has been to danger for coal miners in 

the mine. 

I would say parenthetically that we also had riveting testimony 

that day from a trout fisherman from Montana who testified to the 

fact that the warming of the planet has begun to warm the streams 

and waters in which the trout live, and it has made them sluggish, 

because they are—forgive me for what may be an overstatement, 

but I think it is not scientifically—they are essentially suffocating 

as a result of the warming of the water. 

Dr. Hall, 2 weeks ago you testified before a House committee 

that ‘‘We need to do something about climate change starting yesterday, and it needs to be a serious effort to try and control greenhouse gases.’’ I want to thank you now for that clear statement 

about the urgent need to take substantive action to address climate 

change, and I hope it resonates here in the Senate. 

Many of us here on this Committee, obviously, and beyond, want 

to see the Service expeditiously issue the conclusion that we personally believe science and the Endangered Species Act dictate 

with regard to the polar bear. Studies commissioned by Interior 

Secretary Kempthorne from the USGS concluded, as Chairman 

Boxer said a moment ago, that two-thirds of the world’s polar bear 

population could be lost by the middle of this century. These studies go on to State that that may in fact be a conservative prediction 

as we are watching Arctic sea ice now disappear at a faster rate 

than the computer models have projected. 

I think we are also, many of us, concerned by the last-minute 

delay in taking final action on the listing decision. And some, Director Hall, and I hope you will testify to this, are troubled by the 

coincidence between that delay and the sale of some drilling leases 

that would affect the polar bear. I think this is an opportunity both 

for you, Mr. Director, to clarify those matters, and for us to ask you 

further questions. 

I thank you for your presence here, and again, Madam Chairman, I thank you for convening this hearing. 

[The prepared statement of Senator Lieberman follows:] 

150 

STATEMENT OF HON. JOSEPH LIEBERMAN, U.S. SENATOR FROM THE

STATE OF CONNECTICUT

Thank you, Madame Chairman. 

Many here will recall that the first hearing Senator Warner and I held in our subcommittee last February was on the impacts of global warming on wildlife. In that 

hearing, we heard of the ways in which unchecked global warming is harming and, 

in the absence of action, will increasingly harm species and entire ecosystems that 

are integral to our way of life and the wellbeing of human societies around the 

world. We heard in that hearing, nearly a year ago today, that Fish and Wildlife 

Service Director Hall had identified a warming climate, and the resulting melting 

of sea ice, as the primary reason that polar bears were threatened as a species. 

I am glad that the process that in some sense began with that February hearing 

culminated last month in our committee reporting the Lieberman-Warner Climate 

Security Act to the full Senate. I am proud that this committee showed the leadership take the first step toward protecting all wildlife and ecosystems from the damaging effects of catastrophic climate change. 

Director Hall, 2 weeks ago, you testified in the House that ‘‘We need to do something about climate change starting yesterday, and it needs to be a serious effort 

to try and control greenhouse gases.’’ 

I want to express my deep appreciation to you now for that clear statement about 

the urgent need to take substantive action to address climate change. I hope it resonates here in the Senate. 

We are here today in part because many of us up here want to see the Service 

expeditiously issue the conclusion that science and the Endangered Species Act 

clearly dictate with regard to the polar bear. Studies commissioned by Interior Secretary Kempthorne from the USGS concluded that two-thirds of the world’s polar 

bear population could be lost by the middle of this century. They go on to State that 

this may be a conservative prediction as we are watching Arctic sea ice disappear 

at a faster rate than models had predicted. 

And, in part, we are here because many of us are concerned by the last-minute 

delay in taking final action on the listing decision, and the troubling coincidence between that delay and the sale of some drilling leases that would affect the polar 

bear. I look forward to hearing Director Hall’s testimony, and to asking him some 

questions. 

Thank you, Madame Chairman. 

Senator BOXER. Thank you so much. 

Senator Craig. 

OPENING STATEMENT OF HON. LARRY CRAIG, 

U.S. SENATOR FROM THE STATE OF IDAHO 

Senator CRAIG. Madam Chair, I will be brief. 

I am just beginning to acquaint myself with this issue, and I 

have not read all of these studies, to be thorough in my examination of it. I am looking at some obvious things. And one of the 

trend lines that I watch, living in the Pacific Northwest, relates to 

the Marine Mammals Protection Act that we passed in 1972 and 

the consequence of that. In my home area, the consequence, of 

course, of seals, sea lion populations almost exploding up and down 

the Pacific Coast have resulted in where we now have seals and 

sea lions contributing substantially to the depletion of salmon runs, 

or the damage of young fish and all of that, because it is a natural 

prey base. 

It is also true that during that time we did something else. We 

reduced the human take of the polar bear, and numbers within 

polar bear populations have moved up substantially from 1965, a 

guesstimated 8,000 to 10,000, to today 20,000 to 25,000 polar 

bears. So the polar bear itself, at least in the current environment, 

is, population-wise, if these figures are accurate, doing quite well 

in part because of an action this Congress took some time ago. 

I also understand the climate change movement, the emotion involved and all that. I know that it is very difficult to predict the 

151 

future and therefore to extrapolate out of it therefore what will become of these populations. I also have watched over the years as 

different organizations have used the Endangered Species as a 

wedge or a sledgehammer to change and modify human action and/ 

or activity within certain areas. That is a given. If you are going 

to do something within an area that is relatively pristine, you will 

probably get, somebody will find a species to file to stop you. That 

is a new tool in the tool kit of human interest that is a part of the 

public policy we have here. 

So I am here to listen and, Director, I am glad you are with us 

to see where we are in all of this. I hope, as a government, we don’t 

rush to judgment. At the same time, I think we are moving expeditiously now and appropriately in the climate change area. And history will only say, was it us or was it mother nature? Because that 

question still is on the books. 

Thank you. 

Senator BOXER. Senator, thank you very much. 

I wanted to point out that you were right about the numbers, because we used to allow hunting of polar bears. And therefore 

the—— 

Senator CRAIG. Yes, the take was down substantially. 

Senator BOXER. Dramatically down. And then when we said only 

subsistence, that brought them up. What we are talking about 

today is not hunting, we are talking about the natural environment. 

Senator CRAIG. Well, we also did something else, Madam Chair, 

with the Marine Mammals Act. We increased, we populated their 

prey base substantially more with seals and sea lions. Those things 

that the polar bear hunts, we increased those numbers. So obviously their food base was up, their take was down. Mother nature 

did the math. Thank you. 

Senator BOXER. Well, thank you. I think we are in agreement as 

to the history, which is very important. Because today we are looking at this other threat, not the hunting threat, but the habitat 

threat. 

So I think everybody has spoken, so we will now go to you, Mr. 

Hall. Welcome, and we look forward to your remarks. 

STATEMENT OF H. DALE HALL, DIRECTOR, U.S. FISH AND 

WILDLIFE SERVICE, DEPARTMENT OF THE INTERIOR 

Mr. HALL. Thank you, Chairwoman Boxer, and Ranking Member 

Inhofe, and good friend, and other members of the Committee who 

are also friends. 

It is really a pleasure to be here with you today and I ask that 

my full written statement be entered into the record. 

Senator BOXER. Without objection, so ordered. 

Mr. HALL. As you are aware, the Service proposed to list the 

polar bear as a threatened species throughout its range on January 

9th, 2007. This proposal was based upon scientific review which indicated that the polar bear populations may be threatened by receding sea ice. Sea ice is used by polar bears for platforms for activities essential to their life functions, but especially hunting for 

ice seals, their main prey. 

152 

At the time Secretary Kempthorne announced the proposal, he 

had directed us to work with USGS, the public, pertinent sectors 

of the scientific community to broaden understanding of what factors affect the species and to gather additional information to form 

the final listing decision basis. To assist in that effort, we opened 

a 3-month public comment period and held public hearings in Anchorage and Barrow, Alaska, and in Washington, DC. We then 

hosted a meeting in June 2007 of all the range states around the 

circumpolar, with official representatives from all the countries. 

The meeting provided a forum for the exchange of scientific, management and technical information among all the range nations. 

Then in September 2007, USGS scientists supplied nine new research reports to the Service, updating population information on 

polar bears in the southern Beaufort Sea of Alaska, and provided 

new information on the status of two other polar bear populations 

as well. USGS studies provided additional data on Arctic climate 

and sea ice trends and projected effects to polar bear numbers 

throughout the species range. As a result of the new USGS research findings, we reopened the comment period and later extended a second comment period to allow the public time to review 

and respond to this USGS science. 

We expect to provide a final recommendation to the Secretary 

and to finalize a decision on the proposal to list the polar bear as 

a threatened species within the very near future. 

I would like to discuss current, ongoing efforts to conserve the 

polar bear as well. While much attention has been focused on the 

proposed listing of the polar as threatened under the ESA, it is important to realize that the polar bear is currently protected under 

a number of statutes, treaties and agreements, including the Marine Mammal Protection Act, CITES, or the Convention on International Trade in Endangered Species of Wild Fauna and Flora, 

under the Endangered Species Act, the 1973 agreement between all 

five range states, and the Inupiat-Inuvialuit Agreement. These protections, which address take, trade and management, remain in 

place regardless of the final listing decision. 

In addition, the Service has been and is continuing to work a 

wide range of partners, including the State of Alaska, Alaska Natives, the oil and gas industry and other Federal agencies, scientific 

organizations, foreign countries, all within the range of the polar 

bear, and the sporting and conservation communities on a number 

of efforts to conserve polar bears. The Service and its partners are 

working on coordinated efforts to conserve the bear under existing 

authorities, even if we do not move forward with listing. But if we 

do move forward with the listing, it would be in addition to these 

existing authorities. 

This broad, landscape level effort focuses on polar bear management coordination, polar bear conservation planning, range-wide 

implementation of the U.S.-Russia bilateral agreement, and research and monitoring. The polar bear is a messenger of the changing conditions in the Arctic. If we listen and work together, we can 

help enhance the survival of the polar bear for the long term. 

I will also mention today, quickly, that I am sending out today 

an employee’s scientific code of conduct. This sets out standards 

that includes me and the Fish and Wildlife Service to follow sound 

153 

scientific codes of conduct as we approach scientific information. 

That will be the basis, the science in front of us and our code of 

ethics to follow that science will be the basis for the decision. 

I thank you for allowing me to be here today and I would be glad 

to answer any questions that you might have. 

[The prepared statement of Mr. Hall follows:] 

154 


82737.001

TESTIMONY OF H. DALE HALL, DIRECTOR, U.S. FISH AND WILDLIFE 

SERVICE, DEPARTMENT OF THE INTERIOR, BEFORE THE SENATE 

ENVIRONMENT AND PUBLIC WORKS COMMITTEE ON EXAMINING 

THREATS AND PROTECTIONS FOR POLAR BEARS 

January 30, 2008 

Chairman Boxer, Ranking Member Inhofe, and Members of the Committee, I am H. Dale 

Hall, Director of the U.S. Fish and Wildlife Service (Service), and I appreciate the 

opportunity to testify before you today regarding both the proposal to list the polar bear 

as a threatened species under the Endangered Species Act (ESA) and the current 

protections provided for polar bears under Federal laws such as the Marine Mammal 

Protection Act (MMP A). 

Under the ESA, a species may be determined to be either an endangered species, defined 

as one which is in danger of extinction throughout all or a significant portion of its range, 

or a threatened species, deflned as any species which is likely to become an endangered 

species within the foreseeable future throughout all or a significant portion of its range, 

based on one or more of the following five factors: 

• Present or threatened destruction, modification or curtailment of its habitat or 

range; 

• Overutilization for commercial, recreational. scientific or educational purposes; 

• Disease or predation; 

• Inadequacy of existing regulatory mechanisms; or 

• Other natural or manmade factors affecting its continued existence. 

This determination is to be based solely on the best scientific and commercial data 

available and after taking into account any efforts being made by any state or foreign 

nation, or any political subdivision of either, to protect such species. The determination 

may be based on any of these factors or a combination ofthc factors. The ESA does not 

distinguish between natural or manmade causes. 
155 


82737.002

As Committee Members are aware, on January 9, 2007, the Service proposed to list the 

polar bear under the ESA as a threatened species throughout its range aller a scientific 

review of the polar bear found that populations may be threatened by decreasing sea ice 

extent and coverage and inadequate regulatory mechanisms to address sea ice recession, 

Polar bears use sea ice as a platform for many activities essential to their life cycle, 

especially hunting for their main prey, ice seals. The polar bear listing proposal was 

based on both observed and projected future elfect of the expected modification or 

curtailment of polar bear habitat or range, specifieally from receding sea ice, and the 

absence of any known regulatory mechanisms at the national or international level 

effectively addressing this threat to polar bear habitat. As pmt of the scientific review for 

the listing proposal, the Service also considered the possibility of effects from oil and gas 

development, hunting, and subsistence harvest and determined, based on a review of 

various factors, that these activities do not threaten the polar bear rangewide. 

At the time Secretary of the Interior Dirk Kempthorne announced the proposal, he 

directed the U.S. Geological Survey (USGS) to perform new research aimed at providing 

additional analysis designed to assist our process of moving from a proposed rule to a 

final rule. The Secretary also directed the Service to work with the public and pertinent 

sectors of the scientific community to broaden our understanding of what factors affect 

the species and to gather additional information to inform the final decision on whether 

the species warrants Federal protection under the ESA. The Service opened a threemonth public comment period and held public hearings in Anchorage and Barrow, 

Alaska and Washington D.C. In June 2007, the Service hosted a meeting of countries 

that are part of the polar bear's range that included official representatives from the 

United States, Canada, Norway and Russia. Greenland, which is part of Denmark, was 

also represented. The meeting provided a forum for the exchange of scientific, 

management and technical information among the range nations. 

In September 2007, USGS scientists provided the results of their new research to the 

Service. This research included an evaluation of polar bears occupying similar 

physiographic ecoregions and a determination of how the observed and projected changes 
156 


82737.003

in sea ice translate into changes in polar bcar habitat availability and status. It updated 

population information on polar bears of the Southcrn Beaufort Sea of Alaska, and 

provided new information on the status of two other polar bear populations (Northern 

Beaufort Sea and Southern Hudson Bay). USGS studies also provided additional data on 

arctic climate and sea ice trends and modeled probabilities of change to polar bear 

numbers throughout the species' range over various time periods. 

As a result of the new USGS research findings, the Service reopened and later extended a 

second comment period, which closed on October 22,2007. to allow the public time to 

review and respond to the USGS findings. At the time the decision was made to reopen 

and extend the comment period, I aletted the Department that the Service might need 

extra time to adequately evaluate and incorporate results from the comments received. 

The Service received numerous comments on the USGS reports and has been working to 

incorporate the USGS findings, as well as to analyze and respond to the information 

provided during this extended comment period. 

The Service expects to provide a final recommendation to the Secretary of the Interior 

and to finalize a decision on the proposal to list the polar bear as a threatened species 

under the ESA in the near future. 

POLAR BEAR CONSERVATION 

The Service working with key partners including the State of Alaska, Alaska Natives, the 

oil and gas industry, other Federal agencies, science organizations. foreign countries 

within the range of the polar bear and the sporting and conservation communities, has a 

number of programs or efforts in plaee which provide conservation benefits to the polar 

bear. 

The polar bear is currently protected under the Marine Mammal Protection Act (MMPA). 

The MMPA, enacted in 1972. places an emphasis on habitat and ecosystem protection 

and sets forth a national policy to prevent marine mammal species or population stocks 

from diminishing to a point where they are no longer a significant functioning element of 
157 


82737.004

the ecosystem. The Secretaries of Commerce and the Interior have primary responsibility 

for implementing the MMP A. The Department of the Interior, through the U.S. Fish and 

Wildlife Service, manages polar bears, walruses, manatees and sea otters. The 

Department of Commerce has responsibility for whales, porpoises, seals and sea lions. 

The incidental take provisions of the MMPA ensure that any population-level effects on 

the polar bear will be negligible and will not have an unmitigable negative effect on the 

availability of the species for subsistence use by Alaska Natives. 

The Service and its partners have also started working on coordinated efforts to conserve 

polar bears under our existing authorities. These elTolis will focus on polar bear 

management and coordination; polar bear conservation planning, range-wide; 

implementation of the U.S.-Russia Bilateral Agreement I; and research and monitoring, 

and represent an ongoing approach to utilizing and depending upon the expertise, 

authorities, and support of our State, Federal, Alaska Native, and non-governmental 

partners. International collaboration will also be fundamental to the success of efforts to 

address polar bear conservation in the near and long term, using a broad, landscape-level, 

inter-disciplinary approach. 

In addition to the MMPA and the proposed status under the ESA, the polar bear is 

protected under the Convention on International Trade in Endangered Species of Wild 

Fauna and Flora (CITES). the 1973 Agreement between all five range states, and the 

Inupiat-Inuvialuit Agreement. This latter agreement is a voluntary agreement between 

two Native groups - one Alaskan and one Canadian - that harvest polar bears for cultural 

and subsistence purposes. The Agreement covers the Southern Beaufort Sea population, 

and harvest under the agreement is monitored by the Service's marking and tagging 

program. Illegal take or trade in Alaska is monitored by the Service's law enforcement 

program. All of these protections remain in place regardless of the final listing decision 

under the ESA. 

I Agreement between the Government oflhe United Stales of America and the Government of the Russian 

Federation on the Conservation and Management of the Alaska-Chukotka Polar Bear Population. 
158 


82737.005

CONCLUSION 

In conclusion, I look forward to working with you as we move forward on this important 

issue. The Service recognizes that the polar bear faces significant challenges across its 

range, but we will continue to work with all stakeholders, including the State of Alaska, 

Alaska Natives, industry, the sporting and conservation communities and foreign 

governments to conserve the polar bear throughout its range. Rest assured, we are 

actively utilizing our resources to make an informed decision, based on the best available 

scientific and commercial data available. I appreciate the opportunity to be here today 

and am happy to answer any questions you may have. 
159 

Senator BOXER. Thank you very much, Director Hall. 

Did your staff present a recommendation to you on the listing of 

the polar bear? 

Mr. HALL. We have received the first draft and now the second 

draft that we are working on that includes the staff’s recommendations. 

Senator BOXER. So you have received the staff recommendations? 

Mr. HALL. Yes, ma’am. 

Senator BOXER. OK, then why haven’t you acted? 

Mr. HALL. Because I am working with staff to get the document 

in the proper mode, so that it clearly explains all of the questions 

that we received. We had 670,000 comments, both pro and con, people that argued for and against. 

Senator BOXER. Right. 

Mr. HALL. And it is not just making the decision. It is being able 

to have the Congress and the public understand the decision—— 

Senator BOXER. Right, but you do understand that there is a 

timeliness associated with this because of the lease sale, right? 

Mr. HALL. Yes, ma’am, I do. And I want to say that this delay 

is my responsibility. 

Senator BOXER. Well, let me just say, I wouldn’t want to have 

that responsibility on my shoulders, to think that these polar bears 

could lose a huge among of their population because you are delaying. I just want to say this. Look at Mr. Johnson. Mr. Johnson of 

EPA denied a California waiver. He hasn’t given us one ounce of 

paperwork to support it. He is working on it now. 

The fact is, it is not unprecedented. So it seems like when it is 

a delay, that allows special interests to move forward, there is a 

delay. But when it is the reverse, we don’t get the paperwork. 

According to Bruce Woods, an agency spokesman in Anchorage, 

Alaska, the completed work on the decision by the polar bear scientists in the Alaska field office was sent to headquarters December 14th. What was the conclusion of the listing recommendation 

that was transmitted from the Alaska field office on December 

14th? 

Mr. HALL. Madam Chair, it would be inappropriate for me to 

share recommendations internal until the Secretary has made a 

final decision. Then all of that is part of the public record that 

would be available. But in the internal workings, the recommendations is to me, then I put together my recommendation for the Secretary and then we move forward from that. 

Senator BOXER. But you do understand the timeliness? 

Mr. HALL. Yes, ma’am, I do. 

Senator BOXER. You do understand that there is a lease sale? 

You do understand that that is going to move forward, and you do 

understand that you are late under the law in this decision? 

Mr. HALL. Yes, ma’am, I do. 

Senator BOXER. The Endangered Species Act allows for a delay 

in noticing a listing beyond the 1-year deadline only in situations 

of substantial scientific uncertainty. Am I correct that you have not 

filed a notice with the Federal Register that this is the reason for 

your delay? 

Mr. HALL. That is correct. 

Senator BOXER. What is the reason for your delay? 

160 

Mr. HALL. The reason for the delay really started back when we 

received the USGS reports and we went out for public review. I 

alerted the Department at that time that it was quite possible that 

our staff would not be able to work through all of that volume of 

information and put the packages together to get all the information—— 

Senator BOXER. So your delay is because there was a lot of public 

comment? 

Mr. HALL. The delay is because of not just the public comment. 

It is the quality of the answer that is important, too. We received 

public comments and we owe those public comments the opportunity to really be evaluated and then reported back on. 

Senator BOXER. Was there an overwhelming feeling in those public comments whether to list or not list? 

Mr. HALL. The public comments are really to ask about the 

science. And there was good support, I don’t have a percentage 

breakdown, but the vast majority of the support of the comments 

came in, supported the science that would support a listing. 

Senator BOXER. I understand. So there weren’t that many diverse views expressed in the public comments? They essentially fell 

under the category of list it because the science is on your side to 

do so? 

Mr. HALL. We did not believe that, referring to your first question, we did not believe that there was ample scientific disagreement to warrant using that clause of the Act. 

Senator BOXER. But you do understand that what you are doing 

is outside what the law requires you to do. And you do understand 

that there are many people who suspect some kind of situation 

going on here between MMS. Have you been in communication 

with anyone at the White House about the listing rule, anyone at 

all? 

Mr. HALL. No, ma’am. 

Senator BOXER. Has anyone contacted you about the timing of 

your decision from the White House or the Vice President’s office? 

Mr. HALL. No, ma’am. I notified the Secretary, the Secretary notified the White House that we were going to be late. And that was 

the extent of the comments. 

Senator BOXER. Director Hall, is it true that as of today, it has 

been 630 days since Fish and Wildlife Service has listed a single 

species in the U.S. under the Endangered Species Act? 

Mr. HALL. I don’t have that number in front of me, so I don’t 

know. 

Senator BOXER. That is our understanding. And if that is correct, 

it is the longest delay in the history of the Act. You are delaying 

the listing of the polar bear, saying there is more work to do. You 

have legal obligations to protect imperiled natural heritage. So 

again, I don’t quite get it. I appreciate your taking blame for the 

delay. But your answer is disturbing. Because while you say you 

care about the science, it looks like there is a lot of science. 

I just put in the record USGS report, peer-reviewed. And as a result of your delay, this isn’t just, oh, you know, I will wait for a 

sunny day to make my decision. There is going to be a drilling in 

an area where 20 percent of these magnificent creatures reside. 

161 

So again, I would hope that you would reconsider this. Because 

everything we do has consequences. And this consequence is something that is going to be pretty disastrous for all of us. 

Mr. HALL. Please understand, Madam Chair, I do not take this 

lightly. But I am committed to having a quality decision out that 

answers all of the questions. Because this is a very high profile decision. And we will move as fast as we possibly can. But I don’t 

want to over-push our staff. And that is an honest answer. 

Senator BOXER. Can you do this before February 6th? 

Mr. HALL. That is the projected date that—we had a press conference and said it would probably take us in the neighborhood of 

an additional 30 days, and we are still pushing to make that. 

Senator BOXER. Can you do it by February 6th? 

Mr. HALL. The only answer I can give is that we are pushing to 

try and get there. 

Senator BOXER. Well, I would urge you, because even if you have 

to work overtime, and I will be happy to, if you needed some staff 

assistants who would work, this Committee would help you, if you 

needed just some more hands to do this. 

It would mean a lot to me as Chairman and I know to many of 

my colleagues as well. 

Mr. HALL. Our staff has worked very, very hard. 

Senator BOXER. I understand, and we are willing to give you 

more resources if you need those. 

Senator Inhofe. 

Senator INHOFE. Thank you, Madam Chairman. 

Let me first of all exchange Scriptures with my good friend, Senator Lieberman. It is Romans 1:25, ‘‘Who exchanged the truth of 

God for a lie and worshiped the creation rather than the Creator.’’ 

Senator LIEBERMAN. Well, I was about to say amen, brother, but 

I think this may lead to a longer theological discussion. 

[Laughter.] 

Senator INHOFE. I will accept the amen. 

Senator LIEBERMAN. I think we honor the Creator by honoring 

and protecting His creation. But I am glad to be engaged at this 

level of dialog. It is a good one. Good source. 

Senator INHOFE. All right. Administrator Hall, there seems to be 

a lot of concern about the halting of gas production and all that. 

You heard my opening statement. 

In your proposal to list the polar bear, the Fish and Wildlife 

Service found no impact on polar bears, due to oil and gas activities. Now, I can remember so well back in the old Alaska Pipeline 

days when they said the effect this was going to have on the caribou. It has been my experience, particularly in the summer 

months when I go up there, that the caribou are using the pipeline 

as the only shade around. So would you elaborate on why these activities would not affect the polar bear, oil and gas production? 

Mr. HALL. In our proposed rule of January 9th, 2007, we go 

through the five-factor analysis. There are five factors in the Endangered Species Act that start with habitat and go down to other 

man-made or natural causes. One of those activities that we reviewed was oil and gas operation on the North Slope. We looked 

back over 30 years of operation up there. And especially since the 

implementation of the Marine Mammal Protection Act regulations, 

162 

and about 1993, we have been able to document no mortality of the 

polar bears as a result of oil and gas operations. 

So our conclusion in that draft was that oil and gas operations 

was not in and of itself a significant factor threatening the species. 

Senator INHOFE. That is good. I read that, and it is much more. 

So I would like to ask you to elaborate on that for the record and 

get into some more of the details. That is very good, I appreciate 

it. 

Now, there is a great deal of concern about the ramifications of 

the listing on activities elsewhere in the Country. For example, 

could the emissions of a new power plant in my State of Oklahoma, 

Oklahoma City, contribute to sea ice decline in the Arctic and 

therefore harming the bears’ habitat. The environmental groups 

have made it clear that they want to force these associations so 

that they can regulate greenhouse gases elsewhere. 

In last week’s House hearing, you disputed that. Could you kind 

of walk us through that one? 

Mr. HALL. Thank you, Senator, because this is one of those areas 

that I believe that there is some misunderstanding about what the 

law can and cannot do. When I say the law I mean the Endangered 

Species Act. 

When we talk about consultation between two Federal agencies 

under Section 7, the first question that is asked is, and the agency 

does this, is may this, the proposed action, may it affected a listed 

species. And if the answer is yes, and that determination is usually 

made by the action agency. Then the next question that they have 

to ask is, is it likely to adversely affect the species. And if the answer to that question is yes, then that leads you into formal consultation, as most people understand it. 

The problem that we face, and Madam Chair was correct a while 

ago in saying that if you have the scientific evidence then you 

would have to consult. The issue here, though, for the Endangered 

Species Act, is both in law and in science. In order for, and I will 

go with the law first, both the Supreme Court of the United States 

in the Sweet Home case, and the Ninth Circuit flowing that and 

the Arizona Cattle Growers Association case, directed that yes, we 

may implement take for the destruction of habitat. Take means to 

harm a species, and we have to authorize that. 

But in doing so, we must make, as Justice O’Connor called it, the 

proximal cause case. We must be able to say that this action leads 

to this take. And but for that action, take would not have occurred. 

That is a burden that is on us in regulating under the Endangered 

Species Act. And the Ninth Circuit told us that we could not speculate, that we clearly had to have that chain of evidence that led 

from this particular action to this particular take. 

Now, with that said about the law side, the science today as we 

know it would not allow us, it doesn’t allow us to segregate out specific point source emissions of greenhouse gases and track those to 

a specific take of a polar bear. And that is the problem that we face 

in the presumption that is out there, that we would be able to regulate all of this and tie it to the polar bear. 

Senator INHOFE. Yes. And I appreciate that, I am sorry to rush 

you. I do have one more question. It appears to me, and I hate to 

interject logic into this, but it would seem to me that if we were 

163 

not to be able to have this, if the connection were made between 

a power plant in Oklahoma City, therefore something would happen that would be, to halt it in some way, then we would be more 

dependent upon China and places where they don’t have the controls that we have. 

Last, and if it is all right, Madam Chairman, since we will take 

the time off from our scriptural exchange—— 

Senator LIEBERMAN. But I thought it was timeless. 

Senator INHOFE. Very good. 

This is a quote: ‘‘There is no evidence to suggest that ice in the 

Arctic Basin disappeared entirely during either of these two warming periods.’’ Now, the two warming periods we are talking about 

were the Glacial Maximum, about 8,000 to 9,000 years ago in the 

mid-Holocene warm period, 10,000 to 11,000 years ago. In any of 

these warming periods, which were of equal or greater warming 

than predicted by the IPCC’s climate warming modelers, nor did 

any ice-dependent species become extinct. Will this factor into your 

decision? 

Mr. HALL. We are factoring in all historic data that we are able 

to calculate, including the speed of the warming, along with the 

end result of the warming temperature. Because we are analyzing 

for a species, for a living animal and how it might or might not be 

able to adjust to that. And there are differences in the length of 

time that it took for the warming to occur in those earlier periods 

than the length of time that it appears to be taking today. 

Senator INHOFE. Thank you. 

Senator BOXER. Thank you. 

Senator Lautenberg? 

Senator LAUTENBERG. Madam Chairman, it feels like we are on 

the precipice here, it feels like we are on the edge of the precipice, 

the race between getting the protection for the polar bear in place 

and the rush to start the process for drilling. I would like to see 

if we can’t make certain that the drilling permits are contingent 

upon the outcome, Mr. Hall, of the report that you have on polar 

bears. 

I heard some exchange between you and the Chairman, have you 

said that February 6th is not possible? 

Mr. HALL. I have not said that. 

Senator LAUTENBERG. I heard the language, but I didn’t understand the outcome. 

Mr. HALL. No, sir. I have said that on January 7th, when I came 

out and had the news release and alerted people that it would take 

us approximately another 30 days, my answer is that that is still 

my goal. That is still the effort that I want to meet. 

Senator LAUTENBERG. Well, why couldn’t you issue a report that 

says whatever delays you might have in front of you, that no drilling, that your recommendation, there is no process that begins the 

drilling exercise should take place? 

Mr. HALL. I am not aware that what has come up with MMS is 

a drilling. It is a lease sale exercise. So—— 

Senator LAUTENBERG. It is not an insignificant exercise. 

Mr. HALL. No, sir, I am not trying to say that it isn’t. But under 

that exercise, our staff in Alaska did work with the Minerals ManVerDate Aug 31 2005 12:30 Jan 15, 2014 Jkt 000000 PO 00000 Frm 00169 Fmt 6633 Sfmt 6633 S:\_EPW\DOCS\82737.TXT VERN
164 

agement Service using the guidelines of the Marine Mammal Protection—— 

Senator LAUTENBERG. I heard you say that. 

Mr. HALL [continuing].—to make sure, which, the Marine Mammal Protection Act is actually a little more stringent in the take 

prohibition than the ESA is. But they did work with them on that. 

Senator LAUTENBERG. Right. But I want to get down to the nub 

of things and ask, you are a person of some significant respect in 

the community, the environmental community. Why we can’t get 

an assurance from you that delays that you generously took responsibility for says to me that the Department is not equipped, I 

mean, you are not the person who is doing the work, you have a 

team there. 

So for whatever reason, you are not guaranteed a finish by February 6th. And I would urge you to use the influence that you have 

as the Director of Fish and Wildlife to say, you recommend that 

nothing be done in that area, that you are close to having a report 

delivered and you would like the opportunity from the other agencies to hold up on anything until we complete. Is this an important 

study that we are looking at? 

Mr. HALL. The important study being? 

Senator LAUTENBERG. On the polar bear, on the important species. 

Mr. HALL. Yes. 

Senator LAUTENBERG. OK. 

Mr. HALL. It is an important study. 

Senator LAUTENBERG. So if you could give us the assurance that 

some of us are looking for, that you understand that what you are 

doing will make a difference in the way we approach the leases. We 

need your help. 

Mr. HALL. I understand your concern. 

Senator LAUTENBERG. You have taken responsibility boldly for 

the delay, so we need your help now to protect the situation as we 

would like it done. 

Now, you said before that you introduced a new code of conduct 

for the scientists on your staff? 

Mr. HALL. Yes, sir. It is not new, it is a followup to the Office 

of Management and Budget encouragement that we establish scientific codes of conduct. 

Senator LAUTENBERG. And what did we do before this? Was the 

conduct arbitrary, left to the individual? 

Mr. HALL. What this one does is it clearly identifies who is in 

the scientific arena and who isn’t. 

Senator LAUTENBERG. Was that a question? 

Mr. HALL. There were questions in the past about involvement 

and discussions, and the Secretary wanted to make clear that, I am 

one of those oddities. My job requires that I have scientific credentials and fish and wildlife experience, so that I am a scientist. At 

the same time, I am the first leg of the policy development within 

the Department. So I wanted to make sure, this is something personally important to me, that we make sure that everyone understands that whatever you see coming from the Fish and Wildlife 

Service is of the highest scientific regard and as much as possibly 

be done without emotion. 

165 

Senator LAUTENBERG. That was not clear before, apparently, otherwise it wouldn’t need a review and a restatement? 

Mr. HALL. There is also question about our scientific findings. 

Senator LAUTENBERG. Last question, please, Madam Chairman. 

Could an oil spill in that area, what would the effect perhaps of 

an oil spill in the region that we are talking about the polar bear, 

do you have any view of what kind of a condition might result to 

the bear population? 

Mr. HALL. In my discussion with our polar bear experts, it is expected that if a polar bear were to get oiled, that mortality would 

occur because of the natural grooming, the conditioning that the 

bear goes through, it would ingest the oil. And our polar bear experts assumed that any single bear that would be oiled would likely end up in mortality. 

Senator LAUTENBERG. Thank you. Thank you, Madam Chairman. 

Senator BOXER. Thank you. 

Senator BARRASSO. 

Senator BARRASSO. Thank you, Madam Chairman. 

Director Hall, thank you very much for being here today. I will 

get to the polar bear in a second. I wanted to first, there was a letter that the Wyoming delegation sent to Secretary Kempthorne in 

December. One has to do with the sage grouse. We felt that the 

right decision was made when it chose not to list the sage grouse. 

Subsequently, the people of Wyoming, who have always been interested in protecting the sage grouse and its habitat, have formed 

working groups, developed and implemented community-based 

plans to work with the sage grouse, and with habitat. The game 

and fish department has limited the hunting season, doing the 

kinds of things we want to do to help with recovery. 

There has been a lawsuit, the Western Watersheds Project, and 

a court ruling. And we understand that requests for documents 

have been made. The Wyoming delegation has, in this letter, asked 

that we could please get copies of all the documentation used to 

support these decisions. We have not received those yet, it has been 

about 6 weeks. I am just asking that if you could make a note of 

that and get a look, and we can get a copy of this letter to you 

again requesting some of those helpful documents. 

Mr. HALL. OK. 

Senator BARRASSO. But we appreciate the decision that was 

made regarding this and agree with it. We just want to make sure 

that we get to see what else is going on there, because we are doing 

everything we can as a State to help protect this. 

Mr. HALL. And the States are doing a very good job of working 

with us on this, and we do appreciate it. 

Senator BARRASSO. Thank you very much. 

With regard to the polar bear, and Senator Inhofe had a question 

about a hypothetical case of what the impacts would be if there is 

a project in Oklahoma, we have similar questions in Wyoming; how 

far does this go with potential greenhouse gas emissions and what 

impact they may have in contributing to these issues. If we are 

building a road and that is going to allow more cars to be driven 

with emissions, how far does this go and what can the impact be 

with all activity which may contributing to the issues of global climate change? 

166 

Mr. HALL. How far it goes, in my narrow view of the world, in 

implementing the Endangered Species Act, I have to stay within 

those legal decisions that I cited a minute ago. We have to stay 

within the strength and the maturity of the science. 

As I was explaining earlier, I don’t believe that it is possible for 

us to meet the legal standard of having the proximal cause, cause 

and effect to reach take for emissions done somewhere else on the 

globe and be able to use the science that cannot make that connection for us. Right now, the greenhouse gas concentrations discussions are really discussions from all sources. They do talk about 

general breakdowns. 

But to be able to track something from the action, which is what 

we must analyze for an agency, to a point of effective, we have to 

have the science that makes that clear bridge and tracks that 

there. My response is, we can’t get there today with the level and 

maturity of the science that we have. 

So when you reach out into CAFE standards or into industry or 

other things, other aspects, including our own homes, we don’t 

know yet how to break that down and make that connection and 

have that be responsible for the loss of polar bears, or any other 

species that we might have listed. That is the requirement under 

the law for us to be able to do that. 

Senator BARRASSO. Thank you, Director Hall. Thank you very 

much, Madam Chairman. 

Senator BOXER. Thank you, Senator Barrasso. 

Senator LIEBERMAN. Senator LIEBERMAN. Thanks, Madam Chairman. 

Thanks, Mr. Hall. It strikes me, I don’t know whether we should 

put this in the record, but you are a career Fish and Wildlife Service person. You come to the directorship from that. So you have 

spent your life in this work, and I appreciate that. To me, that 

gives you some credibility as you testify before us. 

I mentioned in my opening remarks the study commissioned by 

Senator Kempthorne from the U.S. Geological Survey that concluded that two-thirds of the world’s polar bear population could be 

lost by the middle of this century. I just want to ask you, not at 

great length, but generally, whether you viewed the USGS survey 

as a credible survey? 

Mr. HALL. We do view the USGS science as credible science. And 

the prediction that they made in that science was not necessarily 

that two-thirds of the polar bears would be gone, but that twothirds of the habitat that they need to survive would be gone. 

Senator LIEBERMAN. Right. 

Mr. HALL. That was the prediction they made there. And then 

they stepped that over into other studies and talked about the bear 

population. 

Senator LIEBERMAN. Got it, OK. I appreciate that. So it has some 

credibility. We had a series of questions about the timing of the oil 

and gas leases and the Chukchi Sea, as related to the decision 

about whether to list the polar bear in the ESA. I just wanted, for 

the record, to ask you if you would describe the additional, to the 

best of your ability in this testimony, the additional steps the Federal Government would need to take in examining the proposed 

Chukchi Sea lease sale, if the polar bear were first to be listed as 

167 

a threatened species under the ESA. I understand, as you alluded 

to earlier, that there are other laws, notwithstanding the ESA, that 

require some steps to be taken with regard to wildlife. 

But what additionally would be required if the ESA listing occurs? 

Mr. HALL. The only thing additional that would be required 

would be a formal Section 7 consultation that would be added to 

the Marine Mammal Protection Act consultation and the OCS Act 

requirements. If the lease sales went forward, then the next steps 

would be industry proposals. And they start to get very specific. 

Then we would consult under each of those laws again for each of 

those steps along the way. 

So the only additional thing would be a Section 7 consultation on 

top of the Marine Mammal Protection Act and on top of the other 

things that are there. 

Senator LIEBERMAN. Right. Just briefly, what does the Section 7 

consultation involve? 

Mr. HALL. The Section 7 consultation is under, obviously, Section 

7 of the Act that requires that no Federal agency undertake an activity that might jeopardize the continued existence of a species. 

Senator LIEBERMAN. OK, that is important. Finally, the work 

done by the Minerals Management Service in considering the 

Chukchi Sea leases included some environmental impact statements. In the EIS that the MMS obtained, there was a recognition 

that there was a 40 percent chance of a large crude oil spill, 26 percent for a pipeline spill and 19 percent for a platform spill as a result of the Chukchi Sea activities. The Minerals Management Service acknowledges that, predicts, I suppose, that between 750 and 

1,000 oil spills are likely from its proposal to open up the Chukchi 

Sea to oil and gas development. 

The reason I mention this is that while, in my opinion, clearly 

the most significant threat to the existence of polar bears today is 

the loss of the sea ice habitat and as has been said, access to prey, 

it does seem to me that the oil and gas development that were 

being, or leases that were being talked about and relevant development, is also a source of some danger of a different sort to the polar 

bears. Would you agree? 

Mr. HALL. Yes, sir. 

Senator LIEBERMAN. Thank you. Thank you for your testimony. 

Thanks, Madam Chair. 

Senator BOXER. Thank you, Senator. 

Senator CRAIG. 

Senator CRAIG. Dale, again, thank you very much for your testimony. This is one Senator that is not going to ask you to rush the 

science. Get it right, as best you possibly can. I am amazed that 

there is even an implication or a suggestion by any Senator that 

the science ought to be rushed. Because we have questioned the 

science of your agency over time. Was it political science or was it 

good biological science? 

I am also always a little disturbed when U.S. Geological gets into 

the biological business instead of the geological business as to their 

credibility. Your credibility is important here, and the work you do 

is important. I recognize you and the Secretary for establishing a 

168 

protocol for your science and reinforcing it. Credibility in that process is very, very important. 

So get the science right. I don’t want to use it as a block, I don’t 

want you to rush it to stop a lease sale, because you have just mentioned to Senator Lieberman the process. And there is a process. 

Because it is clearer that there are some Senators who want to use 

this as a blocking tactic. That is pretty clear by the line of questioning that has gone on here today. 

Once the lease sale is released and leases are bought, there is 

a process, the application for a Federal permit to drill. That is 

where Section 7 comes into play, it is my understanding. And everything must be done within that process by the company to meet 

the standards that you set down in that process, to mitigate as best 

they can against any degradation to the environment and/or to the 

species that might be involved, is that not correct? 

Mr. HALL. It is, sir, and it happens at each step, from the seismic 

activity to the expiration to the development. 

Senator CRAIG. In other words, all human activity that might result from a lease sale in the Chukchi Sea would require that kind 

of process, would it not? 

Mr. HALL. Yes, sir, at each step of the way. 

Senator CRAIG. Would your agency, during that process, have 

people in place to observe and to participate in those activities, if 

a lease sale went through, if a permit to drill were allowed, and 

if those standards were developed, how would you monitor those? 

Mr. HALL. Historically, and we have worked with the National 

Marine Fisheries Service for observers to be present in areas where 

we had overlapping jurisdiction, in this case marine mammals. The 

National Marine Fisheries Service has most of the marine mammals and we have four or five of them. So the National Marine 

Fisheries Service does generally have observers out on ships for 

fishing and we would expect that there may be that case here for 

oil and gas development. 

Senator CRAIG. You would expect that that might be the case, or 

you would believe that that would be the case? 

Mr. HALL. I don’t know the answer to that yet. We would have 

to wait until, as we move forward into the process. 

Senator CRAIG. Thank you very much. 

Senator BOXER. Senator Klobuchar. 

Senator KLOBUCHAR. Thank you, Chair. 

It is good to see you again, Director Hall. I thank you for traveling to Minnesota on a very cold day to attend our national Pheasants Forever convention. We were excited to have 10,000 people 

there. I spoke, I think you spoke. 

Mr. HALL. Yes, ma’am. 

Senator KLOBUCHAR. It was very good. 

I was actually also surprised at the number of hunters and wildlife people there that mentioned climate change to me. As you 

know, I talked about cellulosic ethanol in my speech, and our concern about the effect that the changing world is having on our 

lands and their sport. So I just wanted to mention that for the 

record as well. 

But today we are talking about the polar bear. I will say I am 

concerned, having not been here for too long, but realizing that the 

169 

first petition to list polar bears was made in February 2005. And 

here we are, 3 years later, now still being told that a decision is 

in the future. With the Intergovernmental Panel on Climate 

Change predicting a total loss of summer sea ice in as soon as 30 

years, the USGS study mentioned by Senator Lieberman, which is 

predicting a loss, as you clarified, of habitat by two-thirds, I just 

don’t think we can afford to keep delaying. 

My questions are about, first of all, the listing. Some people 

claim that a threatened listing for polar bears would create some 

kind of patchwork of regulation, when taken together with the Marine Mammal Protection Act and international agreements on polar 

bear conservation. What are your views on this? Are there ways to 

simplify this? I am just trying to figure out why this would create 

a problem. 

Mr. HALL. I think the way I would like to answer that, because 

I am not exactly sure of the patchwork, but let me just say that 

the standards for marine mammals, under both the Endangered 

Species Act and the Marine Mammal Protection Act for the protective standards are very close. And as a matter of fact, in some 

cases, the Marine Mammal Protection Act that is in place is more 

protective. 

So obviously, if a species were listed, that is a marine mammal, 

if it were listed under the Endangered Species Act, one of the first 

things we would want to do is synchronize the Marine Mammal 

Protection Act and the Endangered Species Act operations and reviews so that—— 

Senator KLOBUCHAR. Would there be additional protections that 

would come into effect if you were to list it? 

Mr. HALL. I am not sure. And the reason that I say that is under 

the Marine Mammal Protection Act, the standard, for example, the 

oil and gas operations that were just being talked about, the standard under the Marine Mammal Protection Act is no negligible 

harm. And under the Endangered Species Act, an agency would be 

able to move forward and avoid jeopardizing the species. Those 

standards are obviously very far apart. 

So in that regard, the Marine Mammal Protection Act is far more 

protective. 

Senator KLOBUCHAR. Could you describe the impact that this 

polar bear listing, if it happens, will have on Federal and State climate change initiatives? The argument has been made that if a 

listing compels the Government to protect habitat and the habitat 

loss has been caused by global warming, then a listing might compel Government to take action. Do you think that is true? 

Mr. HALL. I think that the polar bear, as I said in my oral comments as I opened, is that the polar bear is a message for us here. 

But I think it would be a mistake to hang too much on, even if we 

list or don’t list, it’s too much to hang it on any given species. If 

climate change is an issue that we want to address, and I believe 

that all Americans want to make sure that we don’t do something 

that we can’t reverse, that will leave harm for our future generations, then I think we need to address it as a societal world issue 

as well. 

Symbols like the polar bear help to galvanize and help to get people to understand the significance. But the Endangered Species Act 

170 

simply is not the vehicle, I do not believe, to reach out and demand 

all the things that need to happen after a good, common discussion 

about what should happen. 

Senator KLOBUCHAR. Our State doesn’t have a lot of polar bears, 

but we have trout and other freshwater fish that, I think there are 

some good arguments to be made, are going to be threatened by climate change. Is there work being done to look at other animals and 

fish that may be affected by this? 

Mr. HALL. Yes, ma’am. Senator, it is a very good question, I am 

glad you brought it up. Because it does tend to get lost in the discussion. I think most Federal agencies, almost all State agencies, 

game and fish agencies that I am aware of, and a lot of foreign nations that we work with are all trying to address the issue of climate change and not tie it to a species, but tie it to a complete type 

of ecosystem. 

For example, I firmly believe that we should be looking at the 

Arctic as an ecosystem and what will happen? There will be winners and there will be losers as ecosystems change. How do we deal 

with that? And coming down into the sub-Arctic, but it sure felt 

like I was in the Arctic when I was in Minnesota, but when you 

come down into those areas, all of us are working to try and understand much larger questions than a species. I think if we are going 

to make real progress, that is the way we have to look at it, what 

can we really learn that will help us understand how species and 

whole ecosystems will respond to these changes. I really believe 

that is where the effort should be. 

Senator KLOBUCHAR. Thank you. 

Senator BOXER. I noted that we have been joined by Senator 

Warner, who is Ranking Member of the subcommittee that deals 

with wildlife. I wonder if you would like to make an opening statement and ask Mr. Hall some questions before we move to our next 

panel. 

Senator WARNER. Thank you. I would just like to be listed as one 

supporting listing as an endangered species, and let’s get on with 

it. I will just put a short statement into the record. I am very envious of the job you have, which is about the only job I would take 

in trading this one. 

[The prepared statement of Senator Warner was not submitted 

at time of print.] 

Senator BOXER. This could be very exciting. 

Mr. HALL. Our staffs are still trying to figure out how to get us 

fishing together, Senator. 

Senator WARNER. That is correct, we had that fishing trip 

planned. Thank you very much. 

Senator CRAIG. Come to Idaho, will you two come to Idaho and 

fish? I’ll take you fishing, how is that. 

Senator BOXER. Senators, thank you very much. 

What I want to do, just in concluding this, is to put a few things 

in the record and also give to my colleagues a picture that I won’t 

put up here, because it is a very sad picture of a starving polar 

bear. There are many of us who believe if we don’t take action, this 

is what we will be looking at instead of these magnificent pictures 

that we have shared today. 

171 

So this is what I want to do, I want to put into the record and 

I want to clear the record on something as well, your mission statement, sir. The mission of the U.S. Fish and Wildlife Service is 

working with others to conserve, protect and enhance fish, wildlife 

and plants and their habitats for the continuing benefit of the 

American people. So I think focusing on the ethics, the science and 

your mission, I think is very, very important. 

[The referenced material follows:] 

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173 

Senator BOXER. I also, because one of our Senators told you, do 

not rush, I have to take issue with that. There is a law, and the 

law says you must act. This isn’t about one Senator saying, I think 

this is really important, this isn’t about one Senator saying, don’t 

rush or rush. This is about the law. The law says that you needed 

to act by January 9th of this year. You took full responsibility for 

the delay, which I appreciate, I really do. You didn’t blame anyone 

else. But the fact is, you didn’t file the appropriate papers you were 

supposed to under the Act. 

So you are not obeying the law. That is serious. SO it is not a 

question of rush or don’t rush. You need to obey the law. And as 

Chairman of this Committee, I urge you to obey the law. 

Now, you are delinquent, but the quicker you act now, and again, 

if you need to work overtime, a lot of us will help you with, go 

through these comments, whatever it is you need, we will make 

available to help you. 

But I think it is really key, and I want to put into the record the 

citing of this section of the law that requires you to act. It is the 

Endangered Species Act, 16 U.S.C. 1533(b)(6). So again, if you or 

I broke the law outside of this, just a law outside of the Senate, 

there would be consequences. We wouldn’t just sit there and say 

to the judge, I am sorry, I am not obeying the law. There would 

be consequences. 

Now, the consequences for taxpayers is, you are going to be sued. 

There has already been an intent filed, because you didn’t follow 

the law. So I think this is key. 

And then just to lighten it up a little, I thought I would put into 

the record another very interesting quote, made in the year 500 

A.D. in a commentary on Genesis. One of the great rabbis said, 

‘‘See my handiwork, how beautiful and choice. Be careful not to 

ruin and destroy my world, for if you ruin it, there is no one to repair it afterward.’’ 

So I think this is something that we all feel strongly about. Now, 

we may come at it in different ways. But I think we all feel strongly about it. I think this has been a very important hearing. Mr. 

Hall, I just want you to know, I am completely at your disposal to 

help you move forward on this. 

Was there anything else? 

Senator CRAIG. Madam Chair, in a sense of fair play, may I take 

just a moment? 

Senator BOXER. Yes. 

Senator CRAIG. Certainly when I suggested to the Director that 

he get the science right, I was not suggesting and I must ask that 

the record show that he violate the law to do so. You implied that 

I might be suggesting that by your statement. I did not do that. 

I believe that when we do good science, then we can create good 

policy. And if this is a question of getting it right, get it right. But 

it was not my intent, Madam Chair, to suggest that he violate the 

law to do so. Thank you. 

Senator BOXER. Well, I am really glad, because you did say, 

‘‘don’t rush.’’ And the point is—— 

Senator CRAIG. And then I said, ‘‘Get the science right.’’ 

Senator BOXER. Yes, well, we all want that. 

Senator CRAIG. Thank you. Let’s keep it in context. 

174 

Senator BOXER. No, no, no. I am very happy you clarified it. I 

just wanted to make the point that there is a date certain. Mr. Hall 

took responsibility for the delay. I am encouraging him to use 

whatever resources at his disposal to save this creature. And I 

think it is very important, because while we are delaying here, we 

are rushing on a lease sale here. There is, in many people’s minds, 

a connection to the two. 

Thank you very much. We are going to move forward. Yes, of 

course. 

Senator WARNER. I won’t take but a minute. Any of us who were 

fortunate to raise a family of young children, as I did, know that 

at some point in their life, the house is scattered with panda bear 

toys. In a way this is the panda bear for the Atlantic region, count 

it on down. There is a great fascination about this magnificent 

beast. 

I would just ask, are there other things we could do, apart from 

putting it back on the species list, or keeping it on, whatever the 

case may be, are there other Federal policies that could be invoked 

to help? 

Mr. HALL. Well, sir, as I alluded to a minute ago—— 

Senator WARNER. Well, if you have already covered it—— 

Mr. HALL. No, no, I only alluded to it with the other question. 

And that is that this is a much larger issue. The bills that you 

have in Congress looking at ways to approach greenhouse gas management and making sure that we are doing what we can to control, those are larger issues than the Endangered Species Act. That 

was really the point that I wanted to try and make, is that to rely 

on the Endangered Species Act to make those kinds of decisions, 

in my opinion, takes it out of the realm of this discussion, where 

it really needs to be. 

Senator WARNER. Last, are there any other species of animals 

that are similarly in peril in the Arctic region? 

Mr. HALL. We will be looking at the Arctic. There are questions 

about the movements there as well. But climate change has regional impacts. It may be sea level rise on the Gulf Coast and in 

your part of the world. It may be droughts in the Southwest. It 

may be floods in other areas and rain instead of snow in the mountains for that summer water that is so important out west. 

We need to address this, I believe, on a regional basis, working 

together. 

Senator WARNER. I thank the witness and thank the Chair. 

Senator BOXER. Thank you. Yes, we thank you, sir. We will be 

in close touch. 

We will call up panel two, Margaret Williams, Director, Bering 

Sea Ecoregion and Russia projects, from the World Wildlife Fund; 

Andrew Wetzler, Director, Endangered Species Project, from the 

NRDC; Brendan Kelly, Ph.D., Associate Vice President for Research, University of Alaska; Richard Glenn, Alaskan Arctic resident and sea ice geologist; J. Armstrong, Ph.D., Professor of Marketing, The Wharton School, University of Pennsylvania. 

We welcome all of you. I know you have been very, very patient. 

We really are happy, and we are going to start right in, if you can 

take your seats quickly. 

175 

Ladies and gentlemen, I am going to ask you to do what we 

didn’t too well here, which is to keep your opening remarks to the 

5-minutes. My Ranking Member, I really want him to be here to 

question, and he has a tight schedule. 

So we will start with you, Dr. Kelly. We are very happy you are 

here representing the World Wildlife Fund. 

STATEMENT OF BRENDAN P. KELLY, PH.D., ASSOCIATE PROFESSOR OF MARINE BIOLOGY, ASSOCIATE VICE PRESIDENT 

FOR RESEARCH, UNIVERSITY OF ALASKA 

Mr. KELLY. Thank you. Senator Boxer, Senator Inhofe, members 

of the Committee, I appreciate the opportunity to share with you 

my assessment of the threats posed to polar bears by climate 

change. 

The Fish and Wildlife Service brings bad news that none of us 

wants to hear. I must confess that when I was asked to review 

their proposed listing and the supporting documents, I was looking 

forward to finding some critical flaw in their analysis or the conclusions. That is not what I found, however. Instead, I found that they 

have carefully assembled the best available information and conducted a thorough and thoughtful analysis. 

For over 30 years, I have studied the marine mammals that inhabit Arctic seas. During those three decades, I have witnessed 

dramatic changes in the sea ice environment that provides essential habitat to seven species of seals, to walruses and to polar 

bears. Most dramatic has been the decease in the seasonal duration 

and extent of sea ice. I have seen in the graphic—can we put that 

graphic back up that shows the ice retreat? As seen in this graphic, 

the summer ice extent has been reduced almost by one half. The 

Intergovernmental Panel on Climate Change, the American Geophysical Union and the vast majority of sea ice physicists predict 

that there will be no summer sea ice in the Arctic within this century, possibly within 30 years. 

The loss of over 8 million square kilometers of summer sea ice 

will endanger many plants and animals that are adopted to that 

once extensive habitat. Polar bears will be especially negatively impacted, as they are adapted to a narrow niche; namely, hunting 

seals on sea ice. 

Polar bears began to separate from the brown bear population 

several hundred thousand years ago. Eventually, and I stress eventually, that new line of bears began to specialize on hunting seals 

and walruses that were abundant on the Arctic sea ice. 

A key feature of that specialization was the evolution of teeth 

specialized for meat-eating, quite different from the brow bear’s 

teeth, which reflect a more generalist diet. Thus polar bears, like 

the seals they prey upon, and many Arctic organisms, are specifically adapted to the sea ice environment. In the absence of summer 

sea ice, such specialized species will be threatened by competition 

from other species, by the disappearance of prey, by the loss of 

breeding habitat and by potential hybridization or inter-breeding 

with other species. 

Without summer sea ice, polar bears will overlap for longer periods with brown bears in habitat to which brown bears are better 

adapted, putting the polar bears at a competitive disadvantage. 

176 

Food will be less available to polar bears, as populations of their 

ice-associated prey decline. Their main prey, the ring seal, depends 

on spring snow cover to successfully raise their pups. And increasingly early snow melts associated with climate change are exposing 

those seal pups to predation at extreme temperatures. 

Emergence of female and young polar bears from dens in the 

spring coincides with the seals’ birthing season and the newly 

emerged bears depend on catching and consuming young seals to 

recover from months of fasting. The match in timing between polar 

bear emergence and the availability of young seals may be disrupted by changes in the timing and duration of snow and ice 

cover. 

The polar bear’s ability to capture seals depends critically on the 

presence of ice. Hunting on the ice, bears take advantage of the 

fact that the seals must surface to breathe in limited openings in 

the ice. They have evolved complex behaviors for locating and capturing the seals on the ice. 

On the open ocean, however, bears lack a hunting platform. 

Seals are not restricted in where they can surface, and successful 

predation is exceedingly rare. Only in ice-covered waters are bears 

regularly successful at hunting seals. When restricted to shorelines, 

bears feed little, if at all. 

The most obvious change to the breeding habitat is the reduction 

in snow cover on which successful denning depends. Female polar 

bears hibernate for four to 5 months each year in dens in which 

they give birth to cubs, each weighing about one pound. Those 

small cubs depend on the snow cover to insulate them from the 

cold. 

Some criticisms of the proposal to list polar bears as threatened 

reflects misconceptions about the predictions of climate models and 

the predictions of population models. There are fewer and fewer serious critics of climate models, and that is not surprising when you 

consider the marked consistency of the 23 major models and their 

abilities to reconstruct past climates. 

While models developed in different laboratories vary from one 

another in terms of the exact amount of warming predicted in the 

coming century, they all predict warming. None predict cooling or 

even a stable climate. The reliabilities of the models is also seen 

in their tremendous power to accurately reconstruct global temperatures for the past 750,000 years, as recorded in ice cores. Models that can accurately hindcast for a million years are a good bet 

for forecasting. Thus, it is the that pronounced future climate 

warming and melting of ice is the overwhelming consensus view in 

the scientific community. 

While climate models can be validated in using temperature 

records and ice cores, population models do not have a comparable 

record for validation. 

Senator BOXER. Sir, you are going to have to finish, because you 

are going way over time. 

Mr. KELLY. OK. I will just finish by saying that the approaches 

used by the Fish and Wildlife Service and the USGS have been 

well tried and evidence their efficacy in other species. I don’t think 

we need to wait for a body count to know that these reductions are 

177 

happening. The most recent IPCC reports that the resilience of 

many ecosystems is likely to be exceeded by the year 2100. 

[The prepared statement of Mr. Kelly follows:] 

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82737.006

Testimony submitted to 

Senate Committee on Environment and Public Works 

Hearing on 

Examining Threats and Protections for the Polar Bear 

Wednesday, 30 January 2008 

Dr. Brendan P. Kelly 

Associate Professor of Marine Biology 

Associate Vice President for Research 

University of Alaska 

Juneau, Alaska 9980 I 

telephone: 907-209-653 I 

email: Brendan.kelly(@uas.alaska.edu 

Observed reductions of Arctic sea icc 

For over thirty years, I have studied the marine mammals that populate the Gulf of 

Alaska as well as the Bering, Chukchi, and Beaufoli seas. During those three decades, I 

have witnessed dramatic changes in the sea ice that 

provides esscntial habitat to 7 species of seals, walruses, 

and polar bears. Eleven of the 12 warmest years sinee 

1850 were recorded between 1994 and 2006. and one 

result has been that the seasonal duration and extent of 

the ice decreased substantially. As seen in the figure on 

the next page, the summer sea ice extent has been 

reduced by almost one halL The Intergovernmental Panel 

on Climate Change, the American Geophysical Union, and the vast majority of sea ice 

physicists predict that there will be no summer sea ice in the Arctic Ocean before the 

current century is over, perhaps within the next 30 years. 

Polar bears are specialists, adapted to bunting on sea ice 

The loss of over 8,O()O,()()O km2 of summer sea ice will endanger many species of plants 

and animals adapted to that once extensive habitat. Polar bears especially will be 

negatively impacted as they are adapted to a narrow niche, namely hunting seals from the 

sea icc. 

The narrow niche occupied by polar bcars can be contrasted to that of brown bears who 

occupy a greater range of habitats and whose diet is much broader. Genetic data indicate 

that polar bears began to separate f1'om a brown bear population (probably in southern 

Alaska) I SO,OO() to 250,000 years ago. Molecular biology does not tell us when that new 

line of bears began to specialize in hunting Arctic seals. but the oldest fossils showing the 
179 


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180 


82737.008

specialized meat-eating teeth that distinguish today's polar bears from brown bears are as 

recent as 20,000 years old. 

Specialization to preying on ice-inhabiting seals was not without its costs, and the polar 

bear's feeding success is strongly related to ice conditions; when stable ice is over 

productive shelf waters, polar bears can feed throughout the year on their primary prey, 

ringed seals. When the ice is absent, however, the bears lack a platform from which to 

capture surfacing seals. 

Today, an estimated 20,000 to 25,000 polar bears live in 19 apparently discrete 

populations distributed around the circumpolar Arctic. Their overall distribution largely 

matches that of ringed seals, which inhabit all seasonally ice-covered seas in the Northern 

Hemisphere, an area extending in wintcr to approximately 15,000,000 km2

• The broad 

distribution of their seal prel is reflected in the home ranges of polar bears which -

averaging over 125,000 km- - are 200 times larger than the averages for brown bears. 

Most polar bear populations expand and contract their range seasonally with the 

distribution of sea ice, and they spend most of year on the ice. Most populations, 

however, retain their ancestral tie to the terrestrial environment for denning, although 

denning on the sea ice is common among the bears of the Beaufort and Chukchi seas. 

Dens on land and on ice are excavated in snow drifts, the stability and predictability of 

which are essential to cub survival. 

Loss of sea ice too rapid for successful adaptation 

The rapid rates of warming in the Arctic observed in recent decades and projected for at 

least the next century are dramatically reducing the snow and ice covers that provide 

denning and foraging habitat for polar bears. These changes to their environment will 

exert new, strong selection pressures on polar bears. Adaptive traits reflect selection by 

past environments, and the time needed to adapt to new environments depends on genetic 

diversity in populations, the intensity of selection, and the pace of change. Genetic 

diversity among polar bears is evident in the 19 putative popUlations, suggesting some 

scope for adaptation within the species as a whole even if some populations will be at 

greater risk than others. On the other hand, the nature of the environmental change 

affecting critical features of polar bears' breeding and foraging habitats. and the rapid 

pace of change relative to the bears' long generation time (about 15 years) do not favor 

successful adaptation. 

Threats from changes in breeding habitat 

The most obvious change to breeding habitats is the reduction in the snow cover on 

which successful denning depends. Female polar bears hibernate for four to five months 

per year in snow dens in which they give birth to cubs, typically twins, each weighing 

just over 1 lb. The small cuhs depend on snow cover to insulate them from the cold. 
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82737.009

Threats from changes in foraging habitat .......... . 

Changes in the foraging habitat that will entail new selection pressures include seasonal 

mismatches between the energetic demands of reproduction and prey availability; 

changes in prey abundance; changes in access to prey; and changes in community 

structure . 

...... mismatches in timing 

Emergence offemale and young polar bears from dens in the spring coincides with the 

ringed seal's birthing season, and the newly emerged bears depend on catching and 

consuming young seals to recover from months of fasting. The match in timing between 

bear emergence and the availability of young seals may be disrupted by changes in timing 

and duration of snow and ice cover. Such mismatches between reproductive cycles and 

food availability are increasingly recognized as a means by which a variety of animal 

populations are impacted by climatc change . 

...... reduced prey abundance 

Recognized as the most abundant of north em seals, ringed seal populations also are likely 

to decline as the sea ice habitat changes. Like polar bears, ringed seals depend on snow 

caves for rearing their young, and increasingly early snow melts have led to high rates of 

seal mortality due to hypothermia and predation. Walruses and bearded seals also are 

preyed upon by polar bears, and feeding and reproduction of those animals likewise is 

tightly coupled to the sea ice environment . 

...... reduced access to prey 

The polar bear's ability to capture seals depends on the presence of icc. In that habitat, 

bears take advantage of the fact that seals must surface to breathe in limited openings in 

the ice cover. In the open ocean, however, bears lack a hunting platform, seals are not 

restricted in where they can surface. and successful predation is exceedingly rare. Only in 

ice-covered waters are bears regularly successful at hunting seals. When restricted to 

shorelines, bears feed little if at all, and terrestrial foods generally are of little significance 

to polar bears . 

...... changes in biological community 

Seal and other prey populations also will be impacted by fundamental changes in the fate 

of primary production. For example, in the Bering and Chukchi seas, the reduction in sea 

ice cover alters the physical oceanography in ways that diminish nutrient flow to bottomdwelling organisms and increases nutrient recycling closer to the ocean surface. The 

resultant shift in the composition of the biological community will impact all branches of 

the food web, including polar bears. The exact composition of future biological 
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communities in the Arctic Ocean is not known, nor is it known how effectively polar 

bears might exploit those communities. 

Projected population reductions and possible extinctions 

The rapid rate at which snow and ice cover is declining, will work against successful 

adaptation by polar bears. Populations are likely to be reduced and extinction could result 

from mortality outpacing production and/or from hybridization with brown bears. 

The U.S. Fish and Wildlife has made a careful analysis of the threats and prudently 

recommended listing polar bears as threatened. They accurately summarized the 

preponderance of evidence that the loss of sea ice will threaten polar bears. They have 

used the best available information to project likely changes in population levels. We 

cannot expect those projections to be precise in terms of actual numbers, but we have 

every reason to believe that population changes will be large and downward given the 

magnitude of sea ice loss. 

The impacts of small changes in habitat can be difficult to predict, but the impacts of 

whole-sale loss of critical habitat are more obvious. I f a lake shrinks, its fish population 

likely will be stressed but survival of the population is quite possible. If the lake dries up 

completely - even if only seasonally - the fish population will not survive. Sea ice is 

essential habitat to polar bears just as lake water is to fish, and the U. S. Fish and Wildlife 

Service's proposal to list polar bears as threatened is appropriate and timely. 
183 

Senator BOXER. We’re going to have to stop you there. Because 

we just told everyone to stick with 5 minutes. 

So next is Margaret Williams, of the World Wildlife Fund. Welcome. 

STATEMENT OF MARGARET WILLIAMS, MANAGING DIRECTOR, 

KAMCHATKA/BERING SEA ECOREGION PROGRAM, WORLD 

WILDLIFE FUND 

Ms. WILLIAMS. Thank you, Madam Chair, and members of the 

Committee. It is an honor to speak to you on the subject of protecting polar bears and their habitat. 

My name is Margaret Williams, and I represent the World Wildlife Fund, WWF, an international conservation organization with 1 

million members in the U.S. and 5 million members worldwide. For 

more than 20 years, World Wildlife Fund has been an active player 

in the Arctic, and polar bears and other Arctic species have been 

a major focus of our work. 

I have submitted my full written testimony for the record, but in 

the next few minutes, I would like to speak about the history of 

polar bear protection and recommend actions to protect the species. 

Many of those who oppose the listing of the polar bear under the 

ESA, the Endangered Species Act, State that polar bears today are 

more numerous than they were 40 years ago. That is correct. This 

is because polar bears were over-harvested by trophy hunters into 

the middle of the 20th century, when numbers dipped to the low 

thousands. 

Fortunately, the U.S. took action with the passage of the Marine 

Mammal Protection Act in 1972. A year later, the U.S. took further 

action for polar bears, signing on to the International Agreement 

for the Conservation of Polar Bears, committing our Nation to 

‘‘take appropriate actions to protect the ecosystems in which polar 

bears live.’’ 

The U.S. is also party to another international treaty, which is 

aimed specifically at conserving a polar bear population which we 

share with Russia, the Alaska-Chukotka, also known as the 

Chukchi population. While the MMPA and these international 

agreements provide an important framework for conservation, 

today more is needed to protect polar bears. The leading threat to 

the species is climate change, and we have heard a lot of the data 

this morning. In the last three decades, the Arctic has undergone 

a major transformation. Arctic summer sea ice has shrunk by approximately 10 percent per decade since 1979, the equivalent of the 

area the size of California and Texas combined. 

For a species whose life cycle entirely depends on the ice, this 

means less time to hunt and eat, leading to declines in body condition, reproduction and ultimately declines in survival. These facts 

have been well documented in hundreds of peer-reviewed scientific 

papers, including a report by the Nobel prize-wining Intergovernmental Panel on Climate Change. 

A compelling body of work explaining the relationship of polar 

bears to sea ice was complemented last fall by a series of comprehensive reports by the U.S. Geological Survey. And again, we 

have heard it, the USGS shows that two-thirds of the world’s polar 

bears, including America’s two populations, could be lost by midVerDate Aug 31 2005 12:30 Jan 15, 2014 Jkt 000000 PO 00000 Frm 00189 Fmt 6633 Sfmt 6633 S:\_EPW\DOCS\82737.TXT VERN
184 

century. Based on this unequivocal science and based on the requirements of the Endangered Species Act, the polar bear must be 

listed as threatened. 

While climate change is the primary threat, other factors must 

also be considered. As the health of the species is compromised, we 

must eliminate other sources of stress and disturbance. One such 

factor is oil and gas development, concern over which was expressed by the Polar Bear Specialist Group in 2001, and this is the 

world’s preeminent body on polar bears, when it reported that industrial development of oil and gas resources and consequent increases in shipping are major concerns as future threats for polar 

bears and their habitats. 

The issue is now very pertinent, because in 2 weeks, the Minerals Management Service, MMS, will conduct a lease sale for oil 

and gas in 29 million acres in the Chukchi sea, the home range of 

a species whose future is already tenuous. MMS has acknowledged 

a huge lack of information about the wildlife in this marine area, 

home not just to polar bears, but seals, whales, walrus, and remarkable numbers of birds. In fact, MMS ignored the advice of the 

National Marine Fisheries Service, which recommended removing 

the Chukchi Sea entirely from the MMS 5-year program. 

In regard to the delay—— 

Senator BOXER. Say that one more time. 

Ms. WILLIAMS. The National Marine Fisheries Service recommended removing the Chukchi Sea from the MMS 5-year plan 

on oil and gas development, the plan from 2007 to 2012, which just 

went into effect in July. 

In regard to the delay in its decision on listing the polar bear, 

the U.S. Fish and Wildlife Service explained that additional time 

was needed to conduct necessary data analyses. Yet MMS is not 

following the same example, instead, rushing forward for no clear 

reason on the Chukchi sale. Just as the U.S. took action 30 years 

ago to help the polar bear, we must do the same today. In addition 

to listing the species under the ESA on a global scale, this means 

drastically reducing CO2 emissions and other greenhouse gases 

and on a regional scale, delaying the lease sale on the Chukchi Sea 

until there is adequate information and until adequate measures 

have been put in place to protect polar bears and their habitat. 

In closing, I would like to say that on nearly a daily basis I am 

in contact with scientists and conservation colleagues from around 

the Arctic. They are eagerly waiting to see how and whether the 

U.S. will protect polar bears and their Arctic habitat. Indeed, the 

world is watching us. I urge the Secretary of Interior to do the 

right thing for the polar bear and for the planet. I applaud this 

Committee’s attention to this important species. 

Thank you. 

[The prepared statement of Ms. Williams follows:] 

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\ij 

WWF 

Testimony of Margaret Williams 

Managing Director 

Kamchatka/Bering Sea Ecoregion Program 

World Wildlife Fund 

before the 

Committee on the Environment and Public Works 

U.S. Senate 

"Examining Threats and Protections for the Polar Bear" 

January 30,2008 

Chairwoman Boxer, Ranking Member Inhofe, and Members of the Committee: on behalf of the 

World Wildlife Fund (WWF), I am pleased to provide you with comments on this very important 

topic -- the future of polar bears and polar bear habitat, patticularly of oLir polar bear populations 

here in the United States. 

WWF is an international conservation organization with 1.2 million members in the US and over 

5 million members worldwide. WWF has been involved in Arctic conservation for over 20 years, 

and we have offices and field programs in all of the circumpolar Arctic countries. 

My own educational and professional background is in conservation biology and policy and for 

ten years I have been director of WWF's Bering Sea Ecoregion Program, which involves work 

on both the Alaskan and Russian coasts of this region. In the last several years! have been 

working closely with Alaska and Russian polar bear biologists and community members to 

address changes in bear distributions and increasing human-bear interaction, particularly in the 

Russian Arctic. I am a member of the Council on Foreign Relations and also formerly the chair 

ofWWF's international Arctic team. 

Polar bears, the charismatic icon of the polar environment, have long been a focus in WWF's onthe-ground research and conservation projects in the Arctic. Polar bears are an essential part of 

the Arctic ecosystem: as an apex predator, polar bears also serve as bell weathers for the state of 

their northern surroundings, an indicator of health for the Arctic. 
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Polar bears also comprise a central part of Arctic indigenous cultures. For example, Chukchi 

native people in the Russian Arctic for years practiced ancient rituals and celebrations honoring 

the polar bear, and today the species remains part of the subsistence cultures of people of Alaska, 

Greenland and Canada. 

Polar bears - and the issue that brings us together today at this hearing -- are also important for 

their ability to captivate the public's attention. During the public input period for the USFWS' 

proposed listing of polar bears, hundreds of thousands of comments were generated - a 

staggering number- indicating the intense interest in the fate of this species. 

I. Threats to Polar Bears 

Today polar bears face a very serious threat. Analyses recently published by the US Geological 

Survey show that by mid 21 st century, two-thirds of the world's polar bear population could be 

lost, mainly due to loss of sea ice. As this sea ice habitat decreases, the entire food chain will be 

affected - from the tiniest plankton to the forage fish, the ringed seal, and the king of the north, 

the polar bear. 

The impacts of global vvarming on polar bears have been well-documented and are described in 

World Wildlife Fund's public comments regarding the proposed listing, included as an appendix 

to this document. In summary. climate change will impact polar bear habitat, polar bear prey, 

and the reproduction and survival of polar bears. Some of those impacts are as follows: 

A. Climate Impacts on Polar Bear Habitat 

The most fundamental characteristic of polar bears in relation to their ecology is their utter 

dependence on sea ice habitats (Derocher et al. 2004). Anything that significantly changes the 

distribution and abundance. let alone the very existence of sea ice will have profound effects on 

the persistence of polar bears on Earth. Such habitat loss or fragmentation is well documented to 

be a primary cause of extinctions (Beissinger 2000, Ceballos and Ehrlich 2002). 

Experts agree that the once-characteristic ecotype of the far north is undergoing an 

unprecedented and accelerating warming trend (ACIA 2004, Serreze et al 2000, Parkinson and 

Cavalieri 2002, Comiso 2002a, 2002b, 2003), shifting from arctic to subarctic conditions, and in 

some cases profoundly altering the fundamental biological components that are usually 

associated with the Arctic realm (e.g. Grebmeier et al. 2006). This consensus confirms what has 

been known for some time by Native peoples inhabiting this region (e.g. ACtA 2004, WWF 

Climate Witness Program testimony www.panda.org/arctic ). 

B. Climate Impacts on Polar Bear Prey 

Sea ice also is the preferred habitat for polar bears' main prey: ringed and bearded seals (Smith 

1980). Polar bears are specialists on these phocid seals, only rarely and opportunistically taking 

other prey, like walrus, small whales, or other seals (Derocher et al. 2002). Of concern is how 

accessible prey species will be in an altered sea icc environment. Sea ice is the physical platform 
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from which polar bears hunt; they only rarely capture prey successfully in open water (Furnell 

and Oolooyuk 1980). The emerging warmer climate regime is likely to negatively impact polar 

bears both by reducing the duration, thickness, and extent of available hunting habitat (as 

described above) and also by reducing populations of these two obligate prey species, which, like 

polar bears, are sensitive to perturbations in the sea ice environment and related changes in 

primary productivity (Derocher ct al. 2004). In illustration of this, changes in ice characteristics 

have been documented to have a significant negative effect on population size and recruitment of 

ringed seals and subsequently of polar bears (Stirling 2002). Thus, predicted and obscrved 

changes in its distribution, characteristics, and timing of sea ice certainly have the potential to 

profoundly and negatively affect the species at the population level (Stirling and Derocher 1993, 

Derochcr et al. 2004). 

C. Climate Impacts on Polar Bear Reproduction and Survival 

Changes to ice habitats also affect polar bear denning opportunities, ultimately reducing 

population reproductive success. For pregnant bears that den on land, ice must freeze early 

enough in the fall to allow them to walk or swim to the coast. As the distance from ice edge to 

coasts incrcases, it will become progressively more diHicult for them to reach their preferred 

locations (Derocher et al. 2004). For females that den on multiyear ice rather than stable land, 

increased drift rates of this habitat could mean longer distances to travel with new cubs to reach 

the core of their normal home range (Derocher et a I. 2004). 

Such increased energy expenditure by individual polar bears could result in both lower survival 

and reproductive rates in the long term (Derocher et al. 20(4) by reducing stores of fat tissue, 

thereby impacting body condition. 

D. Other Threats to Polar Bears 

1. Oil and Gas Development and Ti'ansport 

Active oil and gas exploration, extraction, and transportation activities are increasing throughout 

the Arctic. As bear populations arc compromised due to climate-related stress, the increase of 

offshore oil activities reprcsents a particular concern. Polar bears are sensitive to oiling in the 

event of a spill (Stirling 1990), and their behaviors can be affected by disturbances related to 

hydrocarbon development (such as seismic blasting and infrastructure development; Derocher et 

al. 1998). Currently proposed offshore extraction activities pose the greatest threat to polar 

bears, especially if a spill occurred near a polar bear denning site (Isaksen et al 1998). Also, 

spills in frozen or partially frozen Arctic waters are hard to detect and no method has proven 

effective for clean up in this environment. 

Finally, should climate warming lead to an open northern shipping routc, the threat of a spill 

would be presented to more northerly polar bear populations, such as Alaska's bears in the 

Chukchi Sea. Recent accidents and near-misses in Alaska's Aleutian Islands. such as the 

grounding of the cargo freighter Selendang Ayu in 2004, have dcmonstrated the challenges in 

responding to such incidents in remote and rough waters of the north. 
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2, Pollutants and Disease 

Many persistent organic pollutants (POPs), as well as heavy metals and radioactive elements, can 

reach high levels in polar bears due to their high fat diet and high trophic position (Norstrom et al 

1998), Studies have demonstrated that such chemicals can negatively impact endocrine function 

(Skaare et aL 2001), immune function (Bernhoft et al 2000), and subsequent reproductive 

success (Derocher et aL 2003), Immune-compromised, not to mention hungry, bears may be 

more susceptible to disease or parasites. The northern expansion if range of disease organisms 

and the nearly complete lack of such organisms in polar bears' evolutionary past also make them 

vulnerable to novel pathogens (Derocher et aL 20004). Finally, environmental pollutants can 

cause pseudo-hermaphroditism in female bears, as has been observed in Svalbard, further 

reducing population reproductive rates. 

3. increased Aggressive Human-Bear interactions 

It has been predicted that human-bear interactions would increase as a result of climate-induced 

changes to polar bear habitat (Stirling and Derocher (993). There is a documented correlation 

between date of ice break-up in spring and number of "problem" bears reported in some 

communities (Stirling et al 1999). More bears on land, especially if they are hungry, can lead to 

more attacks on humans and, correspondingly, more "defense of life and property" killings of 

bears. Just this year, in a remote village on Russia's Chukotka Pcninsula, a young woman was 

killed by an unusually aggrcssivc bear; this was the third reported bear shooting in Russia this 

winter. 

4. Illegal Harvest of Polar Bears 

Harvesting of polar bears has historically bcen the main threat to the species, but this has been 

largely mitigated through various management regimes (Prestrud and Stirling 2002). However, 

in some parts of the bears' range, poaching is still a problem that can have profound effects on 

population persistence. For example, the unregulated harvest of Chukchi Sea polar bears in 

Russia appears to be significant and raises concern about the status of this population. Notably, 

large numbers of polar bear hides have been offered for sale on the internet in Russia. Although 

it has not been proven that the source of these hides is Chukotka, we do know this population is 

vulnerable to illegal hunting. Although actual harvest levels are unknown, an estimated 250-300 

polar bcars were illegally takcn on Russia's Chukotka Pcninsula in 2002. Experts believe this 

harvest was at least twice the level expericnced in previous years and likely resulted from the 

large number of bears that were stranded on land by an early ice rctreat (Ovsyanikov 2003). A 

recent population viability analysis indicated that, even at a harvest level of 180 bears/year, there 

would likely be a 50% reduction in this population (which is shared with the U.S.) size within 18 

years (Schlicbe 2003). 

II, Protecting the Polar Bear 

This section examines protective measures in place domestically and internationally to protect 

the polar bear, points out our shortcomings, and demonstrates how listing the polar bear under 

the Endangered Species Act could help the polar bear. 
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A. Existing Protections 

Currently, polar bears in the United States are protected under the Marine Mammal Protection 

Act ('·MMPA"). enacted in 1972. The primary focus of this legislation, with respect to polar 

bears, has been the management and reporting of the limited legal harvest of polar bears by 

Alaska Natives. The MMPA also sets the conditions for specific activities in polar bear habitats, 

such as oil and gas exploration, development, and production. The MMPA protects the right of 

Alaskan natives to conduct subsistence harvest of polar bears. MMPA regulations played an 

important role in curbing rampant trophy hunting that was decimating polar bears throughout 

their range in the Arctic. 

Elsewhere in the Arctic, other protective measures are in place. In Russia, polar bears have been 

included in the Red Data Book of Rare and Endangered Species and important polar bear habitat 

has been protected. Wrangell Island, known as the "polar bear nursery" for its large 

concentration of maternity dens, was designated in 1976 as a federally protected strict nature 

reserve, and surrounded with a 30-mile marine bulTer zone. Russia continues to protect polar 

bear habitat, as evident in the establishment of regional sanctuaries, national parks, and 

community-managed areas in the Arctie. In Norway, hunting is prohibited and large protected 

areas have been established around polar bear habitat. In Canada, the species is under 

consideration for addition to the Species At Risk Act (SARA) list. 

There are two international legal instruments to which the US is a party that commit the US 

government to protecting the polar bear and its habitat. The first is the 1973 International 

Agreement on the Conservation of Polar Bears. This treaty, like the MMPA, grew out of 

concern in the I 950s and 1960s about the increase in sport hunting of polar bears and the decline 

in polar bear populations throughout their range. High numbers of bears were being hunted as 

trophies for their hides. Those opposed to listing the bear under the ESA correctly point out that 

today polar bears are more numerous than they were 40 years ago. Throughout the 20th century, 

across the Arctic, from Canada to Russia, bears were being ovcr-hunted. One scicntist estimated 

that more than 150,000 polar bears had been taken in Eurasia between the late 18th Century and 

the late 1970s (Stirling, I, 2002). However, action was taken to recover polar bears. 

Ironically, considering the State of Alaska's position against listing the polar bear (See "Bearing 

Up, New York Times editorial by Alaska Governor Sarah Palin, Jan. 5, 2008), the move to 

protect polar bears 40 years ago was in large part due to the efforts of an Alaskan leader. In 

1965 Secretary of Interior Stewart Udall credited Alaska's Senator Bartlett with "awakening the 

public interest in the preservation of the polar bear" (see attached FWS press release). It was 

thanks to Senator Bartlett that the first international meeting of polar bear experts was convened 

- and hosted at the University of Alaska, Fairbanks-to address the problem of declining polar 

bear populations. Out of this first international event held in September, 1965, grew the Polar 

Bear Specialist Group (PBSG) (Young and Osherenko 1993). Formed in 1968, the PBSG today 

is considered the preeminent scientilic body regarding polar bears. 

Following two more meetings of the new Polar Bear Specialist Group and a series of draft 
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protocols on protecting polar bears, four nations agreed to meet in Oslo, and representatives of 

Canada, the US, Norway, and Denmark sign the International Agreement on the Conservation of 

Polar Bears. (Later the Soviet Union would sign). In 1981 the five range states agree to extend 

the agreement indefinitely, and today this agreement is still in force. 

Most notable for today's discussion is Article II of the Agreement, which states that "Each 

Contracting Party shall take appropriate aClion to protect the ecosystems o(which polar bears 

are a part, with special attention to habitat components. such as denning and feeding sites and 

migration patterns, and shall manage polar bear populations in accordance with sound 

conservation practices based on the best available scientific data. " 

Further reinforcing this point, Article IV states that "Each Contracting Party shall enact and 

en(orce such legislation and other measures as may be necessary for the purpose olgiving eilect 

to this agreement." Protecting the polar bear under the Endangered Species Act constitutes one 

of those necessary measures. 

Another international agreement, which was negotiated over many years, is the US-Russia 

Agreement on the Conservation and Management of the Alaska-Chukotka Polar Bear 

Population. The agreement was signed by both countries in 2000, then ratified by the US Senate 

in 2003 and went into effect in 2007. As a preamble to the agreement, both parties affirmed 

"that the United States and the Russian Federation have a mutual interest in and responsibility 

for the conservation of the Alaska-Chukotka polar bear population" and recognized that 

"reliable biological inlormation, including scientific data and traditional knowledge of native 

people, serves as the basis for development ol an eflective strategy for the conservation and 

management of this population." At1icle 1II describes that area as being affected by the treaty as 

"the waters and adjacent coastal areas subject to the national jurisdiction of the Contracting 

Parties in that area of the Chukchi, East Siberian and Bering Seas.. . . " The US-Russia polar bear 

agreement requires both countries to protect and sustainably manage the shared population of 

polar bears, whose home range includes both Russian and Alaskan portions of the Chukchi Sea. 

While these treaties represent important milestones in polar bear conservation, there are some 

shortcomings. For example, there have been few meetings of the Parties since the signing of the 

treaty. Until the US hosted a meeting in June of2007, the last conference of the parties had been 

in 1981. The treaty lacks a mechanism to adequately monitor the effectiveness of its overarching 

goal, and there is an insufficient connection between the Polar Bear Specialist Group and the 

Agreement (I3ankes and Clark, 2007). Finally, there is currently no range-wide, internationally 

agreed-upon species action plan. 

While the US works with its international partners to strengthen this treaty, it should take a 

stronger stand by listing the polar bear and activating the necessary measures under the ESA. 

Today, polar bears face a new threat - climate change - and action is needed just as it was forty 

years ago. 

B. The Next Step in Protecting Polar Bears: Listing Under the ESA 
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The Endangered Species Act (ESA) was intended by Congress to provide a means to protect 

endangered and threatened species as well as the ecosystems on which they depend. Listing the 

polar bear under the ESA rcquires the federal government to take actions not available under 

other regulatory mechanisms for the protection of listed species. 

For example, if the polar bear is listed, the US Fish and Wildlife Scrvice will be required to 

identify and protect critical habitat for the polar bear. The Servicc will also bc obligated to 

develop a recovery plan, which provides a scicnce-bascd "road map" that guides managcrs 

responsible for the species. A recovery plan should includc site-specific actions, estimatcs of 

time and cost of the recommended mcasures, and criteria for "de-listing" the spccies. 

Additionally, if the polar bear is listcd as threatened, the federal government will be required to 

identify and designate "critical habitat" for the polar bear. The Endangered Species Act defines 

"critical habitat" as "specific areas within the geographical area occupied by the species" which 

contain "physical or biological features (I) essential to the conservation of the species and (II) 

which may require special management considerations or protection. Critical habitat can also 

include "specific areas outside the geographical area occupied by the species." 

Finally, the listing of the polar bear under the ESA will prohibit any federal action from 

jeopardizing the continued existence of the species, or adversely modifying its critical habitat. 

WWF supports the USFWS recommcndation to list the polar bear as threatened under the ESA. 

This position is based on: 

1) The preponderance of scientific, peer-reviewed papers and studies on the impacts of 

climate change to the Arctic sea ice 

2) The numerous reports over several years from the Polar Bear Specialists Group 

indicating concerns about the status of polar bears, and the series of reports by our own federal 

agency, the llS Geological Survey, that two-thirds of the world's polar bears could be lost if 

current climate trends continue. 

3) The legal mandate of the Endangered Species Act to protect a species "threatened" or 

"endangered" species when any of the following criteria are met: 

(l) The present or threatened destruction, modification, or curtailment of its habitat or 

range; 

(2) Over-utilization for commercial, recreational, scientific, or educational purposes; 

(3) Disease or predation; 

(4) The inadequacy of existing regulatory mechanisms; 

(5) Other natural or manmade factors affecting its continued existence. 

The volume and gravity of scientific, peer-reviewed papers and studies on the impacts of climate 

change to the Arctic have increased significantly in the last several years and provide a 

compelling body of science to justify the listing of the polar bears as threatened under the 

Endangered Species Act. 

In the last two ycars alone, several major studies including the Noble Prize-winning report by 

the Intergovernmental Panel on Climate Change (fPCC, 2007), have been co-authored and peer-
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reviewed by hundreds of well-respected scientists that document evidence of global climate 

change, These experts have reached widespread agreement that (l) climate change is real; (2) 

human-caused pollution is the main contributing factor; and that (3) the Arctic is one of the 

regions experiencing climate change most acutely, 

One widely accepted scientific study suggests that abrupt reductions in the extent of summer ice 

are likely to occur over the next few decades, and that near ice-free September conditions may be 

reached as early as 2040, In December, 2007, Dr. Jay Zwally of NASA predicted that summer 

sea ice may be gone as early as 2012 (Associated Press 2007), 

Besides diminishing sea ice, other impacts in the Arctic that are already being observed include: 

shrinking glaciers, thawing permatrost, and Arctic "greening" (encroachment of shrubs and trees 

into tundra ecosystems) validate -- and in many cases -- exceed predictions made regarding 

temperature trends, reductions to annual sea ice during the summer and winter periods, 

reductions to multi-year pack ice and reductions to ice thickness, 

For several years, polar bear scientists have recognized these changes and have been warning us 

about the potential impacts to polar bear habitat from climate changed-induced loss of sea ice, 

In 2004, Canada's leading polar bear biologists wrote that: "" ,polar bears are constrained in that 

tbe very existence of their habitat is changing and there is limited scope for a northward sbift in 

distribution, Due to the long generation time of polar bears and the current pace of climate 

warming, we believe it unlikely that polar bears will be able to respond in an evolutionary sense, 

Given the complexity of tbe ecosystem dynamics, predictions are uncertain but we conclude that 

the future persistence of polar bears is tenuous" (Derocher et aL, 2004), 

In 2005, polar bear biologists from throughout the world recommended that the World 

Conservation Union (IUCN) reclassify tbe polar bear from Least Concern to Vulnerable (one of 

the categories which describes species that are "threatened with global extinction"), and the 

following year, lliCN did indeed add the polar bear to this category, 

In 2007, scientists of the US Geological Survey produced a series of compelling reports 

indicating that if global climate trends continue, two-thirds of the world's polar bear populations 

could be lost. Among those popUlations that could witness localized extinctions are the Chukchi 

and Beaufort Sea populations, 

The weight of scientific evidence supports the contention that polar bears' habitat is fast 

disappearing and that predicted individual and population level effects are already occurring, In 

the two best-studied polar bear populations in the world, the Western Hudson Bay and the 

Southern Beaufort Sea, we have witnessed population dcclines that correlate directly with the 

decline in Arctic Sea ice, 

The sad and undeniable truth is that we are rapidly losing the polar bear's most important key to 

survival- its sea icc habitat. And there is unequivocal evidence for this: federal agencies have 

documented late summer Arctic sea ice declining by 7,7 percent pCI' decade, and the perennial 

sea ice area declining up to 9,8 percent per decade since 1978. In some places, the Arctic sea 

ice has been shown to be thinning by 32 percent or more from the 1960's and 1970's to the 
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1990's. These figures are presented in peer-reviewed published data to which Alaska scientists 

had substantial input. So when Alaska government representatives and other opponents to the 

listing say that the proposed listing is "based on uncertain modeling of possible effects" 

(Compass, December 18, 2007) it is surprising to biologists and climatologists around the world. 

The facts are no longer "uncertain" or "possible" - we are seeing the impacts along the Bering 

Sea coast from Alaska to Russia. 

It is clear that the listing of the polar bear as a threatened species is warranted chiefly because of 

the "threatened destruction. modification. or curtailment" of polar bear habitat or range, i.e. the 

sea ice. This is the primary Endangered Species Act standard that counsels listing of the polar 

bear. 

Alaska has some of the world's best polar bear scientists. including one of the leading authors of 

the now-famous US Geological Survey (USGS) study that was released in September 2007. 

Based on the status of sea ice and polar bears, the USGS report warns that two-thirds of the 

world's polar bear populations could be lost by 2050. Other peer-reviewed research has shown 

negative impacts of declining sea ice. In the western Hudson Bay population. which is not 

"stable" but decreasing, the ice breaks up three weeks earl ier than it did 20 years ago. Scientists 

have recorded nutritionally stressed bears, lower survival in the population, and a 22 percent 

popUlation decline. 

In another dramatic example of the consequences of shrinking sea ice to polar bears, scientists in 

2004 found four dead polar bears floating in the ocean 60 miles offshore of northern Alaska, at a 

time when the polar ice cap had retreated a record 160 miles north of Alaska's coast. This led a 

marine biology professor at the University of Alaska to state: "For anyone who has wondered 

how global warming and reduced sea ice will affect polar bears. the answer is simple - they 

die . .. 

C. Potential for Adverse Impacts to Polar Bears and their Habitat 

Currently, as the USFWS deliberates over whether to list the polar bear as threatened under the 

ESA, another federal agency, the Minerals Management Service, is weighing an important 

decision which could have some signiticant impacts on polar bear habitat: the conducting of 

Lease Sale 193, nearly 30 million acres offshore in Alaska's Chukchi Sea, for oil and gas 

development. 

1. The Chukchi Sea: Why It Matters 

Until recently, few people in the American public knew where the Chukchi Sea is located, or 

why it matters. Yet this Arctic body of water, nestled north of the Bering Strait between Russia 

and Alaska, is one of the world's most productive seas. Fed by nutrient-rich currents from the 

Bering Sea and the Arctic Ocean, the Chukchi Sea supports a diverse and dynamic web of life. 

At the base of food chain are prodigious plankton communities that thrive along the ice edge. 

They, in turn, support ocean bottom shelltish, and crustaceans, and forage fish, which provide 

important prey for sea ducks, seabirds, walrus. ice seals, whales, and other marine species. 

These include populations of ringed and bearded seals which provide a high-energy food source 

for the ultimate predator at the top of this food chain -- the polar bear. 
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In addition to polar bears, numerous whale species, walrus, seals, birds and fish exist in the 

Chukchi Sea, For example, bowhead whales, including mothers and calves, migrate through the 

Chukchi lease sale area, Gray whales summer in the lease sale area, parts of which (e,g, the 

Hannah Shoal) contain important feeding habitat. Gray whale use of the Chukchi Sea is 

increasing, likely as a result of changing prey regimes due to climate change. 

The Chukchi Sea provides the "main feeding grounds" for walrus, which are a "species of 

special concern." This is due to "the importance of offshore habitats within the Chukchi, the 

documented sensitivity of walruses to anthropogenic disturbances, and the significance of walrus 

hunting to the economy and culture of indigenous communities in Alaska and Chukotka." 

The sea is also home to the Stellar and Spectacled Eider, both of which are protected under the 

Endangered Species Act (ESA). A portion of the Chukchi Sea. Ledyard Bay, is so important to 

continued survival of the NOith Slope breeding population of spectacled eider - the majority of 

which molt in the bay each summer - that it has been designated as critical habitat under the 

ESA. 

2. Leasing in the Chukchi Sea: a Cause for Concern 

WWF joins the conservation community in its grave concern over plans by Minerals 

Management Service (MMS) to conduct Sale 193 in the Chukchi Sea. This concern is based on 

several factors: 

(i) A series of scientific comments provided by numerous federal agency experts who believe 

that the Chukchi Sea - and another important place for marine life, the North Aleutian Basin 

(otherwise known as Bristol Bay) -- should not have been included in the 2007-2012 MMS' Five 

Year Program for oil and gas development of the Outer Continental Shelf. 

(ii) Minerals Management Service's own recognition of the high probabilities of oil spills that 

could result from development of the Chukchi Lease sale area. Specifically, MMS states that 

there is a 40% chance of a large crude oil spill; 26% lor a pipeline spill; and 19% for a platform 

spill. MMS also estimates that 179 small crude oil spills could occur, totaling 1,214 barrels, or 

over 50,000 gallons of oil. in this region (Final Environmental Impact Statement for Oil and Gas 

Lease Sale 193 and Seismic Surveying Activities in the Chukchi Sea). 

(iii) The USFWS in its proposed ruling to list the polar bear stated that although there have been 

few direct mortalities associated with oil and gas activities. '·the greatest concern for future oil 

and gas development is the effect of an oil spill or discharges in the marine environment 

impacting polar bears or their habitat." 

(iv) To date, there is no proven technology to contain oil spills in the Arctic ice environment. 

And, unfortunately. there have been thousands of spills already on the North Slope - on land. 

Over 4,000 spills totaling 1.9 million gallons of toxic substances occurred during a nine-year 

period, according to the Alaska Department of Environmental Conservation (Alaska Department 

of Environmental Conservation spill database 1996-2004 (no villages, DEWlines). If this record 
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is any indication of what is to be expected in terms of oil spills and environmental 

contamination, offshore development in the Chukchi Sea would be highly irresponsible. Indeed, 

the infrastructure and preparedness in place to address even small spills in the icy, Arctic 

environment of the Chukchi Sea do not even exist. 

3. Overview of the Threat of Oil and Gas to Polar Bears in/he Chukchi Sea 

Given the importance of the Chukchi Sea to polar bears and the growing climate-induced threats 

to this species, WWF is concerned about the proposed oil and gas leasing in the region. These 

concerns are bolstered by the following facts: 

(i) A series of scientific comments were provided to MMS by numerous federal agency experts 

who believe that the Chukchi Sea and another important place for marine life, the North 

Aleutian Basin (otherwise known as Bristol Bay) -- should not have been included in the MMS 

Five Year Plan for the OCS. 

For example, in two separate formal written submissions to MMS, the National Marine Fisherics 

Service (NMFS) raised concerns about MMS's lack of scientific data about how drilling in these 

Arctic waters could affect wildlife and Native cultures. In comments dated April 10, 2006, 

NMFS recommended that MMS remove the Chukchi Sea entirely from its proposed 5-year plan 

due to the critical lack of science: 

"The NMFS Alaska Region believes the proposed leasing schedule is unrealistically ambitious 

and would not allow jor necessary environmental research . .. This is particularly true for the 

North Aleutian Basin (Bristol Bay) and Chukchi Sea proposed sales. The NMFS Alaska Region 

recommends deletion of these areas and initiation of a comprehensive research program to 

support future plans subsequent to the 2007-2012 plan . .. For instance. MMS states repeatedly 

that lillie is known about the distribution, abundance, behavior, and habitat use oj' marine 

mammals in the Chukchi Sea, and the [eH' existing studies are very dated. It is extremely 

important to gain a beller understanding of'these issues prior to any exploration, leasing, or 

development. The needfiJr baseline data on the distribution o.fmarine mammals in the Chukchi 

Sea is particularly urgent" (NMFS Comments on Department of the Intcrior's Minerals 

Management Service (MMS) Draft Proposed Outer Continental Shelf (OCS) Oil and Gas 

Leasing Program 2007-2012, dated April 10.2006). 

Again on January 30, 2007, NMFS raised its concerns with MMS about MMS' lack of scientific 

understanding of the potential impacts on polar bears, whales, walrus, sea lions and other 

wildlife from drilling in the Chukchi Sea. NMFS also pointed out serious issues with potential 

impacts on Native cultures and traditional ways of life: 

"We remain very concerned about potential impacts to living marine resources and their 

habitats. fisheries, and subsistence uses of marine resources as a result o.f' lease sales, 

exploration. and development in the Chukchi Sea Planning Area. The individual and cumulative 

e)fects o.f development in these relatively pristine environments could be significant. , . [Yet 

MMS's] data to describe marine mammals within the sale area and their habitat use are lacking 

or inadequate. , . Some of these [scientific datal gaps are striking given the ecological, social 

and cultural importance of the marine mammals in question" (Comments of the National Marine 
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Fisheries Service on the Minerals Management Service (MMS) Draft Environmental Impact 

Statement for the Chukchi Sea Planning Area, January 30, 2007). 

(ii) MMS's EIS recognized that there is a 40% chance of a large crude oil spill; 26% for a 

pipeline spill; and 19% for a platform spill (Final Environmental Impact Statement for Oil and 

Gas Lease Sale 193 and Seismic Surveying Activities in the Chukchi Sea). 

MMS admits that 750-1,000 oil spills are likely from its proposal to open-up the Chukchi Sea to oil and 

gas development (MMS's Environmental Assessment for the Proposed Oil and gas Lcase Sale 20, 

l3eaufort Sca Planning Area, p. 97 and MMS's Chukchi Sea Planning Area Oil and Gas Lease 

Sale 193 and Seismic Surveying Activities Draft Environmental Impact Statement. 2006. 

http://www.mms.gov/alaska/ref/EIS%20EA/Chukchi_DEIS_193/DEIS_193.htm ). 

While clearly the overwhelming threat to polar bears today is the loss of sea ice habitat and 

access to prey, we must consider other sources of stress to the species. Oil and gas development 

is certainly one of those sources. 

a) Oil and Gas as a Threat to Polar Bears 

Polar bears are sensitive to oiling in the event of a spill (Stirling 1990), and their behaviors can 

be affected by disturbances related to hydrocarbon development, such as seismic blasting and 

infrastructure development (Derocher ct al 1998). In 200 I, the Polar Bear Specialist Group, in 

its final proceedings, stated that "Industrial development of oil and gas resources and a 

consequent increase in shipping are main concerns as future threats for polar bears and their 

habitats (Isaksen et al 1998). 

At its next international meeting in 2005, the IUCN Polar Bear Specialist Group cautioned that 

"Expansion of winter-time petroleum exploration and development in the Arctic has increased 

concerns that oil and gas activities could disturb denning polar bears, resulting in premature den 

abandonment and cub mortality" (IUeN Polar Bear Specialists Group 2005). Sources of 

disturbance include noise and vibration from exploratory drilling, construction of ice roads and 

ice pads, aircraft and ground traffic. Although some experiments have been conducted testing 

noise levels inside artificial dens, the experts concluded that "there is currently a lack of pertinent 

information that is necessary to determine how industrial noise and vibration effects on polar 

bears should be mitigated." Currently the petroleum industry is required to avoid a one-mile 

buffer around known polar bear den sites. However, the PBSG has pointed out that this distance 

was arbitrarily established and the required buffer can be overridden if the USFWS provides 

authorization for "incidental taking" OUCN Polar Bear Specialists Group 2005). 

Also, spills in frozen or partially frozen Arctic waters are hard to detect and no method has 

proven effective for clean up in this environment. Finally, should climate warming lead to an 

open northern shipping route, the threat of a spill would be presented to more northerly polar 

bear populations, such as Alaska's bears in the Beaufort and Chukchi Seas alike. 

b) Oil and Gas as a 'fhreat to Other Wildlife Species 
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Oil threatens nearly all arctic wildlife, and as an apex predator, the polar bear can be harmed if 

other wildlife is oiled. This section summarizes some of the impacts that oil activities can have 

on other wildlife. 

Oil spills can affect wildlife in numerous ways, depending on location, timing, and weather at 

time of spill, as well as the type of oil spilled. As oil "weathers" it can adhere to wildlife even 

more. Marine wildlife will not necessarily avoid an oil spill and in fact may be attracted to slicks 

that can appear like floating food. 

Known impacts resulting from oil, usually crude and bunker fuels, include but are not limited to: 

• hypothermia in birds by reducing or destroying the insulation and waterproofing 

properties of their feathers; 

• hypothermia in seal pups by reducing or destroying the insulation of their fur; 

• marine mammals such as fur seals become easy prey if oil sticks their flippers to their 

bodies, making it hard for them to escape predators; 

• birds sink or drown because oiled feathers weigh more and their feathers cannot trap 

enough air to keep them buoyant; 

birds lose body weight as their metabolism tries to combat low body temperature; 

• marine mammals lose body weight when they can not feed due to contamination of their 

environment by oil; 

• disguise of scent that seal pups and mothers rely on to identify each other, leading to 

rejection, abandonment and starvation of seal pups; 

• damage to the insides of animals and birds bodies, for example by causing ulcers or 

bleeding in their stomachs if they ingest the oil by accident. 

Other types of less direct impacts of spills can be felt by wildlife. For example, oil persisting in 

the environment or oil that is ingested can cause: 

poisoning of wildlife higher up the food chain if they eat large amounts of other 

organisms that have taken oil into their tissues; 

• interference with breeding by making the animal too ill to breed, interfering with 

breeding behavior such as a bird sitting on their eggs, or by reducing the number of 

eggs a bird will lay; 

damage to the airways and lungs of marine mammals: 

• damage to and suppression of a marine mammal's immune system, sometimes 

causing secondary bacterial or fungal infections; 

damage to red blood cells; 

organ damage and failure such as a bird or marine mammal's liver; 
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• damage to a bird's adrenal tissue which interferes with a bird's ability to maintain 

blood pressure, and concentration of fluid in its body; 

• damage to fish eggs. larvae and young fish; 

interference with a baleen whale's feeding system by tar-like oil, as this type of whale 

feeds by skimming the surface and filtering out the water. 

(From the Australian Maritime Safety Authority: 

http://www.amsa.gov.au/marine _ env ironment_protection/education ai_resources _and_in f 

ormation/teachers/the _effects_of... oil_on _ wildlife.asp). 

iii) In its proposed ruling to list the polar bear the USfWS stated that although to date there have 

been few direct mortalitics associated with oil and gas activities, "the greatest concern for 

future oil and gas development is the effect of an oil spill or discharges in the marine 

environment impacting polar bears or their habitat." (US fish and Wildlife Servicc Proposed 

Rule pp 1079-1080. Federal Register Voln, No 5. Jan 9,2007]) 

USFWS noted in its ruling that such activity is "increasing as development continues to expand 

throughout the United States Arctic and internationally, including in polar bear terrestrial and 

marine habitats. 

Echoing the cautions expressed by the National Academy of Science when it issued a rcport on 

cumulative impacts of oil development on Alaska's north slope, the USFWS noted that "A major 

spill in the Beaufort sea would have major impacts on polar bears and ringed seals. (US Fish and 

Wildlife Service Proposed Rule pp 1079-1080. Federal Register voln. No 5. Jan 9, 2007). 

iv) To date. there is no proven technology to contain oil spills in the Arctic ice environment. 

Of great concern in the Chukchi Sea is the lack of known technology to contain and recover oil 

spilled in the marine environment. In a rcport resulting from an expert pancl examining 

cumulative impacts of oil development on the North Slope, the National Academies of Science 

publication concluded that: "no current cleanup methods remove more than a small fraction of 

oil spilled in marine waters. especially in the presence of broken ice." (NRC 2003) 

This message has been repeated in other parts of the world, as well, such as in Norway. A 2006 

study cxamining methods to recover spilled oil in the Barents Sea pointed to the difficulty of 

operating in ice conditions. citing the usual long distance to infrastructure; increased viscosity of 

the oil; migration of the oil in the ice; spillage in pools and channels between ice noes, and even 

under the ice; difficulty in detection and monitoring spills; and other challenges. (Evers, K, 

Sorheim. KR and Singsaas, I , 2006). 

One year ago. in examining the risks of oil development around Sakhalin Island in Russia, World 

Wildlife released a report called Offshore Oil Spill Response in Dynamic Sea Ice Conditions. 

(DeCola et ai, 2006) The report is co-authored by a petroleum engineer with extensive 

experience on Alaska's North Slope; an Alaskan biologist with years of experience in the field of 

environmental compliance and drilling operations in Alaska, and a founding member of the Oil 

Spill Prevention and Response within the Prince William Sound Regional Citizens Advisory 
199 


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Council. The report focuses on the Sea of Ohkotsk, an area where dynamic seas and long ice 

seasons make it in many ways similar to the Chukchi Sea. The bottom line is: "mechanical 

recovery is extremely difficult in ice-infested waters; dispersants are an unproven 

technology; and in-situ burning has not been demonstrated in actual field tests to be 

effective in ice coverage above 30% or below 70%." Where ice concentration exceeds 70%. 

the ice may provide natural containment, although the sea ice may transport oil great distances so 

that it is unavailable for response once spring break up occurs. At higher ice concentrations, 

significant logistical, technical, and safety challenges remain in tracking, assessing, and igniting 

the oil slicks and recovering burn residues." 

Recently, the lack of capacity to respond to and contain spills has been quite evident, even highly 

developed, technologically sophisticated nations. For example, just last month in the North Sea, 

a large oil spill occurred in the cold waters of the North Sea, resulting in what may be the second 

largest spill in Norway's history. The incident occurred during the transfer of crude oil from a 

loading buoy to a tanker ncar an offshore oil platform known as Statfjord A and resulted in 4,000 

cubic meters being spilled into the sea. 

D. Other Concerns: Is the Race for Oil Leading to "Shortcuts" at the Expense of 

Our Environment? 

As noted above, in pursuing the Chukchi Lease Sale 193, MMS disregarded expert opinions of 

other US agencies. In the past week, information released by the Public Employees for 

Environmental Responsibility (PEER) points out that MMS has also ignored the advice of its 

own experts in Alaska in its effort to expedite the permitting processes necessary to conduct 

lease sales. The agency ignored strong cautions of one biologist who warned about the potential 

for the introduction of invasive species into Alaskan waters by exploration activities. Rather, the 

agency "directed its scientists to exclude any assessments of the high likelihood that offshore oil 

drilling would introduce invasive species into Arctic waters." 

"While MMS contends that it has done complete environmental assessments of its Arctic 

offshore drilling permits, its own specialists many of whom have left in recent months -

vehemently disagree. After he was removed from any role on invasive species issues and his 

work on native fish populations was altered, [the employee] resigned from MMS in disgust. In 

addition, MMS chose to ignore state and federal experts who seconded the warnings from MMS 

staff scientists." (PEER press release). 

As the MMS Five Year Program unfolds in Alaska and throughout the US, such reports of 

internal pressure to expedited development at the cost of the best available science are alarming 

and must be further investigated. 

III. Summary 

World Wildlife Fund appreciates the efforts of this Committee and Congress more generally to 

investigate current and future protections for the polar bear. 

In closing, I would like to say that listing this species under the Endangered Species Act is a last 
200 


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resort, and in essence, signifies a failure of policy and management. We have known for some 

time of dangers of global warming, and should have acted more expediently to address them. 

Had we done so, perhaps we would not be faced with the need to list this species. Before we are 

faced with similarly difficult decisions for other species, we should enact legislation directly 

dealing with global warming, such as policies that will require the energy sector to rapidly and 

dramatically reduce C02 emissions. In the short term, we need to closely scrutinize and prevent 

all actions that may add further stress to the polar bear, including conducting oil and gas leasing 

in prime polar bear habitat. 

Finally to summarize the points in this testimony; 

• The overwhelming body of peer-reviewed science regarding the relationship of declining 

Arctic sea ice to declines in polar bear populations meets the statutory criteria requiring a 

listing as threatened under the Endangered Species Act. 

• While listing the polar bear would be a very important step, the US will have to also take 

dramatic steps to decrease C02 emissions, the source of global warming that is melting 

polar bear habitat and transforming the Arctic. 

• The US has an obligation to heed the science and to uphold its international commitments 

to protcct polar bears and their habitat. 

The US has only two polar bear populations, inhabiting the Beaufort and Chukchi Sea. 

We must reduce all known sources of stress to these populations, including offshore oil 

and gas development. 

• Global experience tells US that the technology to effectively contain and clean up such 

spills does not exist at this time and the risks to marine life posed by offshore oil and gas 

development are too great. 

• We must do ever}1hing possible to allow for the polar bear to persist, and to leave future 

generations of Americans with a chance of knowing that polar bears and other Arctic 

wildlife exist in the wild. Listing the polar bear will be the first step in the right direction. 

Thank you for your consideration. 
201 


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References 

ACIA. 2004. Impacts of a warming climate: Arctic climate impact assessment. Cambridge 

University Press. Available at http://amap.no/acia/. 

Alaska Department of Environmental Conservation spill database 1996-2004 (DEWlines). 

Associated Press. Ominous Arctic Melt Worries Experts. Deccmber 11,2007 

Australian Maritime Safety Authority: 

http://www.amsa.gov.au/marinc environment protection/educational resources and inform 

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Bankcs, Nigel and Clark, Douglas. 2007. Time for Action. WWF Arctic Bulletin, No.1, 2007. 

Beissinger, S.R. 2000. Ecological mechanisms of extinction. Proc. Nat. Acad. Sci. 

U.S.A. 97: 11688-11689. 

Ceballos, G. and P.R. Ehrlich. 2002. Mammal population losses and the extinction crisis. 

Science 296: 904-907. 

Comiso, J.e. 20020. Correlation and trend studies of the sea-ice cover and surface temperatures 

in the Arctic. Ann. Glaciol. 34: 420-428. 

Comiso, J.e. 2002b. A rapidly declining perennial sea icc cover in the Arctic. Geophys. Res. 

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DeCola, Robertson, T., Fletcher, S. Harvey, S. 2006. Offshore Oil Spill Response in Dynamic 

Icc Conditions: A Report to WWF on Considerations for the Sakhalin II Project. Alaska, 

Nuka Research. 

Derocher, A.E., N.J. Lunn. and I. Stirling. 2004. Polar bears in a warming climate. Integr. 

Compo BioI., 44: 163-176. 

Evers, K, Sorheim. KR and Singsaas, I. 2006. Oil Spill Contingency Planning in the 

Arctic - Recommendations. Arctic Operational Platform (ARCOP). Also available: 

http://www.arcop.fi/reports/D4224.pdf (See page 37) 

Final Environmental Impact Statement for Oil and Gas Lease Sale 193 and Seismic Surveying 

Activities ill the Chukchi Sea ("FEIS") at Ill-51 (the full FEIS is available at 

http://www.mms.gov/alaskalref/EIS%20EA/Chukchi leis Sale 193/feis 193.htm.) 
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Furnell, DJ" and 0. Oolooyuk. 1980. Polar bear predation on ringed seals in icc-free water. 

Can. Field-Nat. 94: 88-89. 

Grebmeier, J.M., J.E. Overland, S.E. Moore, E.Y. Farley, E.C. Carmack, L. W. Cooper, K.E. 

Frey, J.H. Helle, F.A. McLaughlin, and S.L. McNutt. 2006. A major ecosystem shift in 

the northern Bering Sea. Science 311: 1461-1464. 

Isaksen, K., Y. Bakken, and 0. Wiig. 1998. Potential effects on seabirds and marine mammals of 

petroleum activity in the northern Barents Sea. Norsk Polarinst. Medd. 154,66 pp. 

IUCN Polar Bear Specialists Group. 2001. Polar Bears: Proceedings of the 13th Working 

Meeting of the IUCN/SSC Polar Bear Specialist Group. 223-28 June, 200 I, Nuuk, 

Greenland. 

IUCN Polar Bear Specialists Group. 2005. Polar Bears: Proceedings of the 14h Working 

Meeting of the IUCN/SSC Polar Bear Specialist Group. 20-24 June, 2005, Seattle, 

Washington. 

Minerals Management Service Environmental Assessment for the Proposed Oil and gas Lease 

Sale 20, Beaufort Sea Planning Area, p. 97 and MMS's Chukchi Sea Planning Area Oil 

and Gas Lease Sale 193 and Seismic Surveying Activities Drat( Environmental Impact 

Statement. 2006. 

http://www.mms.gov/aiaskaJref/EIS%20EA/Chukchi_DEIS_I93/DEIS_193.htm 

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Draft Environmental Impact Statement for the Chukchi ea Planning Area, January 30, 

2007. 

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Management Service (MMS) Draft Proposed Outer Continental Shelf(OCS) Oil and Gas 

Leasing Program 2007-2012, dated April 10,2006. 

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Ovsyanikov, N. 2003. Dark Times for Chukotka Polar Bears. WWF Arctic Bulletin 2.03:13-

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Palin, Sarah. 2008. Bearing Up: Letter to the New York Times. Jan. 5, 2008. 
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Parkinson, C.L. and 0.1. Cavelieri. 2002. A 21 year record of Arctic sea-ice extents and their 

regional, seasonal and monthly variability and trends. Ann. Glaciol. 34: 

Prestrud, P. and l. Stirling. 1994. The International Polar Bear Agreement and the current status 

of polar bear conservation. Aquat. Mamm. 20. 3: 113-124. 

Public Employees for Environmental Responsibility. January 24, 2008. Press Release: 

INVASIVE SPECIES THREAT FROM ARCTIC OFFSHORE DRILLING IGNORED: 

Interior Purged Scientific Concerns about Introduction of Exotics in Arctic Waters 

Schliebe, S. 2003. Chukchi sea polar bears: A population concern. USFWS Factsheet. U.S. 

Fish & Wildlife Service, Anchorage, AK. 

Serreze, M.C., lE. Walsh, F.S. Chapin, Ill, T. Osterkamp, M. Dyurgerov, V. Romanovsky, W.e. 

Oechel, J. Morison, T. Zhang, and R.G. Barry. 2000. Observational evidence of recent 

change in the nOl1hern high-latitude environment. Clim. Change 46: 159-207. 

Smith, T.G. 1980. Polar bear predation of ringed and bearded seals in the land-fast sea ice 

habitat. Can. 1. Zoo!. 58: 2201-2209. 

Stirling, I. 1990. Polar bears and oil: Ecological perspectives. In 1. R. Geraci and D. 1. St. 

Aubin (eds.), Sea mammals and oil: confronting the risks, pp. 223-234. Academic Press, 

San Diego. 

Stirling, l. 2002. Polar bears and seals in the eastern Beaufort Sea and Amundsen Gulf; A 

synthesis of population trends and ecological relationships over three decades. Arctic 55: 

59-76. 

Stirling, l. And A.E. Derocher. 1993. Possible impacts of climatic warming on polar bears. 

Arctic 46: 240-245. 

US Fish and Wildlife Service Proposed Rule pp 1079-1080. Federal Register Vol 72, No 5. Jan 

9,2007 

Young, 0 and Osherenko, G (eds.): Polar Politics: Creating International Environmental 

Regimes. 1993. Cornell University 
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Attachments 

Facts and Fallacies about Polar Bears: Polar Bear Listing - Dispelling Fallacies with 

Facts 

WWF Comments to the Fish and Wildlife Service on the Proposed Listing of the Polar 

Bear April 10, 2006 

WWF Comments to the Fish and Wildlife Service on the Proposed Listing of the Polar 

Bear April 1,2007 

WWF Comments to the Fish and Wildlife Service on the Proposed Listing of the Polar 

Bear October 22, 2007 [Comment Period Reopened] 

1965 USFWS Press Release: "Five-Nation Conference on Polar Bears Scheduled for 

September in Alaska" 
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October 22, 2007 

Dr. Rosa Meehan 

Supervisor 

U.S. Fish and Wildlife Service 

Marine Mammals Management Office 

10 II East Tudor Road 

Anchorage, AK 99503 

Attn: Polar Bear Finding 

Dear Dr. Meehan: 

~ WWF 

World Wildlife Fund (WWF) appreciates the opportunity to comment on the recently published 

U.S. Geological Survey (USGS) reports which present a comprehensive analysis of the world's 

polar bear (Ursu.\' maritimus) population status and threats. WWF understands that these 

scientific reports will be used by the U.S. Fish and Wildlife Service (Service) in conjunction with 

other information gathered in the process to make a final decision on whether to protect the polar 

bear as a "threatened" species under the Endangered Species Act. 

In the previous comment period on this subject, WWF supported the listing ofthis species as 

Threatened. Now, based on the rigorous and in-depth set of analyses provided by USGS, we feel 

there is even more compelling evidence to make such a decision. The stark conclusion of the 

USGS research reports is that "projected changes injiJlure sea ice conditions, ifrealized. will 

result in loss of approximately 2/3 of the world's current polar bear population by the mid 21" 

century. Because the observed traiectOl)' of Arctic sea ice decline appears to be underestimated 

by currently available models. this assessment offiJture polar bear status may be conservative. " 

The plain facts in these USGS research reports speak for themselves in favor of a listing. The 

reports' 18 key findings point out that: 

Arctic sea ice decline is likely underestimated by the available models; 

• It is now possible to relate declines in the availability of sea ice to declines in metrics of 

population status for two subpopulations of polar bears (including the Southern Beaufort 

Sea [SBS] sUbpopulation inhabiting Arctic Alaska): 

• Under a range of future sea ice scenarios for the 21 sl century, and modeling approaches, 

the SBS sUbpopulation of polar bears is projected to decline severely by the end of the 

century, and in many scenarios, by the mid-century; 
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• Optimal habitat in the polar basin declined between 1985 and 2006 based on the 

observational record of sea ice, and the most pronounced polar bear habitat loss in the 

past decade has occurred in the Chukchi Sea and Barents/Greenland Seas; 

• The USGS has projected losses of polar bear habitat within the polar basin to be greatest 

for peripheral seas of the polar basin (e.g., the Chukchi Sea and Barents Sea); 

• The largest reductions in habitat in the polar basin are predicted for spring and summer; 

• The USGS projects a 42% loss of optimal polar bear habitat during summer in the polar 

basin by mid century; 

• Polar bears could be extirpated in the divergent ice ecoregion (including Arctic Alaska) 

within 75 years assuming that sea ice decline follows the mean trajectory predicted by the 

10 models used by USGS in their analysis; 

• Polar bears could be extirpated in the same ecoregion within 45 years, if sea ice decline 

follows the minimum trajectory prediction. 

• Using the carrying capacity model. the USGS projected populations of polar bears in all 

other ecoregions to decline at all time steps, with severity of decline dependent upon 

whether minimum, maximum or mean ice projections were used; 

• The USGS forecasts the extirpation of polar bear populations in the seasonal sea ice and 

polar basin divergent ecoregions (including Arctic Alaska) by 45 years from the present 

(based on a first-generation Bayesian Network model); 

Polar bear populations in the polar basin convergent ecoregion are forecasted by the 

USGS to be extirpated 75 years from the present; and 

• The USGS specitically notes that sea ice conditions would have to be substantially better 

than even the most conservative GCM projections to result in qualitatively different 

outcomes for polar bears in any of the ecoregions. 

The federal ESA requires the protection of a species as "Threatened" if it "is likely to become an 

endangered species within the foreseeable future throughout all or a significant portion of its 

range." [16 U.S.C. § 1532(20)]. A species is considered "endangered" when it "is in danger of 

extinction throughout all or a signiticant portion of its range." [16 U .S.C. § 15320(6)J. 

The USGS science reports represent the best available science and unambiguously show that the 

polar bear is threatened with extinction in the foreseeable future chiefly due to ongoing climate 

warming in the Arctic. WWF strongly believes that the current situation for polar bcars clearly 

relates to ESA Section 4(a)( I) and therefore supports formal listing and protection measures for 

the polar bear as a Threatened species under the ESA. 

Thank you for your consideration. 

Sincerely, 

Margaret Williams 

Director, Kamchatka/ Bering Sea ecoregion Program 
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~ WWF 

April I, 2007 

Rosa Meehan 

Supervisor, Marine Mammals Management 

U.S. Fish and Wildlife Service 

Marine Mammals Management Office 

1011 East Tudor Road 

Anchorage, AK 99503 

Attn: Polar Bear Finding 

Dear Ms. Meehan: 

On behalf of the World Wildlife Fund, thank you for this opportunity to comment on the 

recommendation by the U.S. Fish and Wildlife Service to list the polar bear (Ursus 

marifimus) as "Threatened" under the U.S. Endangered Species Act (ESA). 

WWF is an international conservation organization with 1.2 million members in the US. 

WWF works around the world, including in all of the Arctic countries inhabited by polar 

bears. One of our priority ecoregions is the Bering Sea, where we have been actively 

involved in conservation of the Alaska-Chukotka polar bear population. 

Last year, WWF strongly supported formal listing and protection measures for thc polar 

bear as a Threatened species under the ESA, for reasons outlined herein and with the 

support of the best available science. Our position has not changed. In fact, additional 

data pointing to climate change impacts on the Arctic sea ice only further reaffirm the 

conclusions that listing is warranted. 

The federal ESA requires the protection of a species as "Threatened" if it "is likely to 

become an endangered species within the foreseeable future throughout all or a 

significant portion of its range." [16 U.S.c. § 1532(20)]. A species is considered 

"endangered" when it "is in danger of extinction throughout all or a significant portion of 

its range." [16 U.S.C. § I 5320(6)J. The factors that are used to determine whether a 
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species is threatened or endangered are enumerated in Section 4(a)(I) of the Act (16 

U.S.c. § 1533(a)(J)(A)-(E»). Of the five factors listed in that section, three weigh most 

heavily in determining the status of polar bears: 

A. the present or threatened destruction, modification or curtailment of its habitat or 

range; 

D. the inadequacy of existing regulatory mechanisms; and 

E. other natural or manmade factors affecting its continued existence. 

wwr believes that polar bears in the U.S. meet the statutory criteria cited above for 

protection as Threatened under the ESA, based on the now substantial and growing body 

of peer-reviewed and published scientific data (discussed below) and the numerous 

observations of Arctic community members (i.e. Local & Traditional Knowledge). These 

sources strongly suggest that current and projected global warming is and will continue to 

negatively and severely impact polar bears' habitat, prey. behavior, reproduction, and 

survival such that the species faces probable dramatic population declines by the end of 

this century. 

Finally, WWF fully endorses precautionary and proactive conservation principles and 

argues for application of strong protective measures for this species sooner rather than 

later. as the observed rate of Arctic ecosystem change (especially reductions in sea ice 

cover, extent, and duration) is accelerating well beyond that projected by early climate 

models. 

Evidence l that the polar bear warrants listing in under the ESA as "Threatened". and that 

fulfill the listing criteria that the species "is likely to become an endangered species 

within the foreseeable future throughout all or a significant portion of its range" 

according to 16 U .S.C. § 1532(20), include: 

I. Climate Impacts on Polar Bear Habitat 

The most fundamental characteristic of polar bears in relation to their ecology is their 

strong aiTinity for sea ice (Derocher et al. 2004). Polar bears are almost completely 

dependent on sea ice for sustenance. Their preferred habitat is the annual sea ice over the 

continental shelf and inter-island archipelagos that encircle the polar basin. Polar bears 

depend on ice for hunting and feeding on the seals that usc the ice as a platform for 

parturition and lactation, and for hauling out to rcst and molt (Iverson et al. 2006; see also 

Ferguson et al. 1998,2000). Iverson et al. (2006) further state: 

Those bears that live on the pack ice all year round, such as in the Beaufort Sea, 

move north with the receding floe edge in summer and south again in winter 

I Scientific data are better tor some regions/populations (han lor others. However. remote sensing has allowed 

more homogenous high quality data (0 be compiled across the Arctic marine ecosystem; these data include crucial 

sea-ice habitat data and projections relating to polar bear survival prospects across the entire species range. 
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(citing Amstrup et a!. 2(00). The southernmost populations live year-round in the 

Hudson and James bays, Canada, where ice is completely absent for at least 4 

months during summer and autumn each year, and all bears are forced ashore to 

fast until freeze-up, while pregnant females fast for 8 months (citing Stirling et al. 

1977, Ramsay and Stirling 1988). Thus the presence of sea-ice is critical to polar 

bears and changes in its distribution and duration will have a profound impact on 

their foraging patterns and population ecology (citing Stirling and Derocher 1993, 

Stirling et a!. 1999). 

Derocher et al. (2004) similarly note that anything that significantly changes the 

distribution, abundance or existence of sea ice will have profound cffects on the 

persistence of polar bears .. Such habitat loss or fragmentation is well documented to be a 

primary cause of extinctions (Bcissinger 2000, Ceballos and Ehrlich 2002). 

Climate changes appear to threaten the sea ice itself - the floating platform upon which 

polar bears depend for nearly all of their life history needs (Amstrup 2006). Experts 

agree that the Arctic Region is undergoing an unprecedented and accelerating warming 

trend (Serrcze et al 2000; Parkinson and Cavalieri 2002; Comiso 2002a, 2002b, 2003; 

ACIA 2004; IPCC 2007), shifting from arctic to subarctic conditions, in some cases 

profoundly altering the fundamental biological components that are usually associated 

with the Arctic realm (e.g. Grebmeier et al. 2006). This consensus confirms what has 

been known for some time by Native peoples inhabiting this region (e.g. ACIA 2004, 

WWF Climate Witness Program testimony www.pandll.org/arctic ). 

Acrtic sea ice is melting at an unprecedented rate as a result of increased global 

temperatures, very likely caused by anthropogenically based atmospheric pollution 

accumulating since 1750 (IPCC, 2007) (Meier et a!. 2005, NSIDC 2005, Overpeck et a!. 

2005, Stroeve 2005). Scientists estimate that in just the last three decades, the avcrage 

annual sea ice extent has decreased by nearly 1.3 million square kilometers or 500,000 

square miles (twice the size of Texas), at a rate of about 8-9% per decade (Comiso 2002b, 

NSIDC 2005). It appears that the warming/ melting trend is accelerating (ACIA 2004, 

NSIDC 2005). Eleven of the last twelve years (1995 -2006) rank among the 12 warmest 

years in the instrumental record of global surface temperature (since 1850) (IPCC 2007). 

Current predictions in the scientific literature are that, by the end of this century, annllal 

temperatures in the Arctic will likely rise by 7 degrees C (13.6 degrees F) over oceans 

(ACIA 2004) and that summer Arctic sea ice might decline by 50-100% (ACIA 2004, 

Comiso 2003, Gough and Wolfe 2001, NSIDC 2005, Overpeck et a!. 20(5). 

The latest satellite information from the National Snow and Ice Data Center and NASA 

indicates that the observed temperature increases and ice declines are not anomalies but 

signal a new and ominous trend: 2005 marked the fourth consecutive year exhibiting the 

lowest amount of ice cover in more than a century. Mean temperatures in 2001-2005 

were 20% warmer than the average of 1978-2000 and the winter recovery of sea ice in 

2004-2005 was the smallest on satellite rccord. These organizations concluded that 

Arctic sea ice, home to all polar bears on Earth, "is likely on an accelerating, long-term 

decline" (NSIDC 2005). 
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During most seasons polar bears prefer mixed ice habitats ncar ice edges in shallow 

waters over the continental shelf (Durner et a!. 2006b). In past decades, this habitat use 

pattern was maintained during summer because of persistent near shore ice. The summer 

distribution of polar bears, however, has changed in recent years because of extensive ice 

melt that forces most polar bears to summer in deep water ice habitat> 200 km from the 

mainland coast while a smaller segment of the population is forced to use shoreline 

habitat. 

Further evidence of climate change impact upon polar bear habitat is manifest in a 

landward shift in polar bear denning. Polar bears in the northern Alaska region den in 

coastal areas and on offshore drifting pack ice. Fischback et a!. (2006) reported find that 

the proportion of dens on pack icc between 137° Wand 167 0 W longitude declined from 

62% in 1985-1994 to 37% in 1998-2004. Fischbaek et a!. (2006) hypothesize that this 

landward shi ft was a response to reductions in stable old ice, increases in unconsolidated 

ice, and lengthening of the melt season, which have likely reduced the availability and 

quality of pack icc denning habitat. They note that if these sea ice trends continue, as 

predicted, they expect the proportion of polar bears denning on coastal habitats will 

continue to increase, until such time as the autumn icc retreat precludes otTshore pregnant 

females from reaching the Alaska coast in advance of denning. One must thcn ask, how 

might climate change alter coastal landscapes and terrestrial denning habitat, particularly 

in light of ACIA (2004) predictions of rising sea levels, rising river flows, declining snow 

cover, and thawing permafrost, and then how might such habitat alterations influence 

polar bear reproduction, survival, and population dynamics. 

2. Climate Impacts on Polar Bear Prey 

Sea ice also is the preferred habitat for polar bears' main prey: ringed and bearded seals 

(Smith 1980). Polar bears are specialists on thesc phocid seals, though sometimes 

opportunistically taking other prey, like walrus or small whales, ( e.g., Derocher et a!. 

2002). 

Recently, Iverson et al (2006) reported on their study examining polar bear diets, where 

they used quantitative fatty acid signature analysis of polar bear adipose tissue to estimate 

their diets in the 1980s-1990s across three major regions of the Canadian Arctic. Their 

result show that polar bears consumed ringed and bearded seals throughout their range, 

however, diets differed greatly among regions. Other species shown to be substantive in 

the diet of sampled polar bear populations include harp and hooded seals, and walrus, 

depending on region. Changes in diet were also associated with environmental variation 

(e.g., periodicity of ice breakup). Polar bear diets also varied spatially within a 

subpopulation as a function of latitude. 

Of concern is how accessible prey will be as sea ice diminishes in the Arctic region. 

Rosing-Avid (2006) studied and modeled the ShOlt- and medium-term effects of climate 

change on mortality or ringed seal pups and polar bear cubs olT east Greenland. Iverson et 

a!. (2006) noted that during the 19905 in the western Hudson Bay, the trend towards 
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progressively earlier sea ice breakup dates was accompanied by significant decreases in 

ringed seals in polar bear diets .... and that all species [of ice seals] are mainly only 

available to bears on the ice so these changes in diet, especially reduction in ringed scals, 

compliment evidence that during the same period bears camc ashore earlier and in 

progressivcly poorer condition, with a decline in both physical and reproductive 

characteristics (Iverson et al. 2006 citing Stirling et al. 1999). 

Thc emerging warmer climate regime is likely to negatively affcct polar bears in two 

ways: (I) by reducing the duration, thickness, and extent of available ice platforms used 

for hunting (as described above); and (2) by reducing populations of ringed and bearded 

seals, which, like polar bears, are dependent on, and sensitivc to, perturbations to sea ice 

habitat and related changes in primary productivity (Derocher et al. 2004). Winter and 

spring distribution of ringed seals reflects the gcneral distribution of polar bears. During 

summer, while some ringed seals may track the ice edge as it retreats north, others may 

have an open water life style and thus would be unavailable to polar bears. Bearded seals, 

duc to their benthic feeding habits, have not been available to polar bears during recent 

summers. Changes in ice characteristics have been documented to havc a significant 

negative cffect on population sizc and recruitment of ringed seals (Ferguson ct al. 2005) 

and subsequently of polar bears (Stirling 2002). Thus, predicted and observed changes in 

the distribution. characteristics, and timing of sea ice cet1ainly have the potential to 

profoundly and negatively affect the ice-associated species at the population levcl 

(Stirling and Derocher 1993, Derocher et al. 2004). 

3. Climate Impacts on Polar Bear Reproduction and Survival 

Changes to ice habitats also affect polar bear denning opportunities, ultimately reducing 

population rcproductive success. For pregnant bears that den on land, ice must frecze 

early enough in the fall to allow them to walk or swim to the coast. As the distancc from 

the ice edge to the coast increases, it will become progressively more difficult for them 

to reach their preferred locations (Derocher et al. 2004). For females that den on 

multiyear ice rather than stable land, increased drift rates of this habitat could mean 

longer distances to travel with new cubs to reach the core of their normal homc range 

(Derocher et al. 2004). 

Such increased energy expenditure by individual polar bears could result in both lower 

survival and reproductivc ratcs in the long tcrm (Derocher et al. 2004) by rcducing stores 

of adipose tissue, thereby impacting body condition. Much of the life history of polar 

bears, particularly reproductive females, is tied to storing large quantities of adipose 

tissue when hunting conditions are favorable and subsequently using these stores whcn 

conditions do not allow for hunting (Ramsay and Stirling 1988), such as during the fourmonth fast that occurs in many populations during summer when sea ice is in retreat. 

Warming trcnds will force polar bears to come ashore earlier in the season, which means 

that they will have less opportunity to store fat, with the potential to decrease polar bear 

survival, depending on life stage and condition (e.g., Regehr et al. 2006b). Adult fcmale 

polar bears lose approximately 4.71 kg/day during fasts (the rate may be 4-fold higher for 

pregnant females; Derocher and Stirling 1995). Because females apparently cannot 
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reproduce when they drop below 189 kg, and at current rates of ice decline, it has been 

calculated that most females in the southerly Hudson Bay population will be unable to 

reproduce as soon as 2012 (Derocher et al 1992). Compromised females will also likely 

produce fewer, smaller cubs with lower survival rates (Derocher and Stirling 1996, 

Derocher and Stirling 1998). 

Regehr et al. (2006a) examincd cub production between the early (1967-89) and latter 

(1990-2006) time periods and found evidence of a decrease in the survival of polar bear 

cubs of the Southern Beaufort Sea population during their first 6 months of life. 

For polar bears captured during the autumn, the number of cubs of the year per adult 

female declined significantly from a mean of 0.61 in the early period to a mean of 0.25 in 

the latter period. This decline can only be explained by lower survival of cubs after den 

emergence. In contrast to the autumn data, the numbers of cubs of the year per adult 

female captured in the spring increased between the two periods. This reflects a shortened 

inter-birth interval for the recent period. Apparently, more females are losing their cubs 

shortly after den emergence, breeding again shortly after losing their cubs, denning again 

the following autumn, and emerging with another litter the following spring. In short, 

numerous cubs are currently being born in the Southern Beaufort Sea region, but many of 

them are not being recruited into the population (Regehr et aI., 2006a). 

Reduced hunting success as a result of compromised habitat integrity will likely result in 

reduced fat stores because of the increased energy output associated with traveling on 

more labile ice or swimming across open water for longer distances when ice retreats 

(Mauritzen et al 2003). If ice conditions are particularly poor, cub mortality may 

increase as they are forced to swim greater distances in cold water (Derocher et al 2004). 

Adult mortality can also result from changes in ice condition, timing, and extent: 

recently, there have been documented accounts of adult polar bears drowning in the 

Alaskan Beaufort Sea, and scientists suggest that mortalities due to offshore swimming 

during late-ice (or mild ice) years may be an important and unaccounted source of natural 

mortality given energetic demands placed on individual bears engaged in long-distance 

swimming (Monnett and Gleason 2006). Also suggested is that drowning-related deaths 

of polar bears may increase in the future if the observed trend of regression of pack ice 

and/or longer open water periods continues [as climate models project]. Increased adult 

mortality has also been observed in recent years on Wrangellsland in the Chukchi Sea, 

home (with nearby Herald Island) to 80% of the region's breeding female polar bears. In 

2002, a year of exceptionally early ice retreat, the Island's resident polar bear biologist 

reported the highest proportion of skinny bears ever and a very high mOltality rate 

(Ovsyanikov 2003) . 

Case Study: Southwestern Hudson Bay Population 

In southwestern Hudson Bay, increasing temperatures have already increased the 

duration of the ice-free period (thus increasing the fast) by approximately 2.5 weeks 

(Stirling et al. 1999). A recent study of this well-known population, which alone 

constitutes roughly 5-10% of the total estimated world population, has established, for the 

first time, a negative population-level effect of climate change on polar bears (Regehr et 

al. 2005). The study documented that the size of this population had declined from 
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approximately 1200 bears in 1987 to fewer than 950 bears in 2004. The authors also 

established a statistical correlation between earlier summer ice break-up and decreased 

survival for all but prime-aged bears. 

It is widely recognized, based on sea ice remote sensing and oceanographic monitoring, 

that similar rapid reductions of sea ice (and hence polar bear feeding and denning 

opportunities) are probably affecting other populations (such as the Alaska-Russia 

population), although these have not been as intensely studied as those in southwest 

Hudson Bay. 

4. Thrcats to Polar Bears Due to Their Life History and Distribution 

Polar bears are a classic K-selected species, exhibiting delayed maturation, sma!llitters, 

and high adult survival rates (Bunnell and Tait 1981). Potential extinction risk for polar 

bears is heightened because of these characteristic features of their life history, and other 

traits such as their specialized diet, large body size, long life span, and low genetic 

diversity (McKinney 1997, Beissinger 2000). Also, because of thcir long generation time 

(mean 12-17 years in most regions), polar bears are not well suited to rapid evolution and 

therefore are unlikely to adapt successfully to the rapidly changing climate and the 

related effects on habitat and prey. 

5. Other Threats to Polar Bears 

The existence of polar bcars is further threatened by a number of other factors, many of 

which are likely to be exacerbated by the effects of climate change. 

a. Oil and Gas Development and Transport 

Active oil and gas exploration, extraction, and transportation occur throughout the range 

of the polar bear and projected to increase. Polar bears are sensitive to oiling in the event 

of a spill (Stirling 1990), and their behaviors can be affected by disturbances relatcd to 

hydrocarbon development (such as seismic blasting and infrastructure development; 

Derocher et aL 1998). Currently proposcd offshore extraction activities pose the greatest 

threat to polar bears, especially if a spill occurred near a polar bear denning site (Isaksen 

et al 1998). Also, spills in frozen or partially frozen Arctic waters are hard to detect and 

no method has proven effective for clean up in this environment. Finally, should climate 

warming lead to an open northern shipping route, the threat of a spill would be presented 

to more northerly polar bear populations, such as Alaska's bears in the Chukchi Sea. 

b. Pollutants and Disease 

Many persistent organic pollutants, such as heavy metals, radioactive elements, and 

persistent organic pollutants, can reach high levels in polar bears due to their high fat diet 

and high trophic position (Norstrom ct al 1998). Studies have demonstrated that such 
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chemicals can negatively impact endocrine function (Skaare et al. 200 1). immune 

function (Bernhoft et al 2000), and subsequent reproductive success (Derocher et at. 

2003). It is possible that endocrine disrupting chemicals affect behavior and cognitive 

abilities in polar bears such that they are less able to cope with changes in ice-coverage 

caused by climate change (Jenssen 2006). Also, environmental pollutants can cause 

pseudohermaphroditism in female bears, as has becn observed in Svalbard (Wiig et al 

1998) further reducing population reproductive rates. 

Immune compromised, not to mention hungry, bears may be more susceptible to disease 

or parasites. A study of free ranging populations of polar bears in northern Alaska has 

been initiated to establish clinical (health) baseline data in order to monitor potential 

change in health status, using multiple hematologic endpoints and infectious agents 

exposure measures (Kirk et al. 2006). A relatively high prevalence of serum antibodies 

to four morbilliviral species [canine distemper (COY), dolphin morbillivirus (DMY), 

phocine distemper (PDY), and porpoise morbillivirus (PMY)] were identified. This group 

of viruses can cause significant disease and mortality in populations of some marine 

mammals as well as interfere with differentiation and specialization of lymphocytes in 

vitro. Moreover, the northern range expansion of disease organisms and the nearly 

complete lack of such organisms in polar bears' evolutionary past also make them 

vulnerable to novel pathogens (Derocher et al. 20004). 

c. Increased Aggressive Human-Bear Interactions 

It has been predicted that human-bear interactions would increase as a result of climateinduced changes to polar bear habitat (Stirling and Derocher 1993). There is a 

documented correlation between date ofiec break-up in spring and number of "problem" 

bears reported in some communities (Stirling et aI 1999). Churchill and other 

communities along the western coast of Hudson Bay, Canada have experienced an 

increase in the number of human-polar bear interactions in recent years (Regehr et al. 

2006b). Earlier sea ice breakup is believed to have resulted in a larger number of 

nutritionally-stressed polar bears, which are encroaching upon human habitations in 

search of supplemental food. More bears on land, especially if they are hungry, can lead 

to more attacks on humans and, correspondingly, more "defense of life and property" 

killings of bears. Just this year, in a remote village on Russia's Chukotka Peninsula, a 

young woman was killed by an unusually aggressive bear; this was the third reported bear 

shooting in Russia this winter. 

Stirling and Iverson (2006) examined possible effects of climate warming on five 

populations of polar bears in the Canadian Arctic. Inuit hunters in the areas of four polar 

bear popUlations in the eastern Canadian Aretic (including Western Hudson Bay) have 

reported seeing more bears near settlements during the open-water period in recent years. 

In a fifth ecologically similar population, no changes have yet been reported by Inuit 

hunters. These observations, interpreted as evidence of increasing population size, have 

resulted in increases in hunting quotas. However, long-term data on the population size 

and body condition of polar bears in Western Hudson Bay, as well as population and 

harvest data from Baffin Bay, make it clear that those two populations at least are more 

likely to be declining, not increasing. 
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While the ecological details vary in the regions occupied by the five different populations 

examined, analysis of passive-microwave satellite imagery beginning in the late 1970s 

indicates that the sea iee is breaking up at progressively earlier dates, so that bears must 

fast tor longer periods during the open-water season. Thus, at least part of the explanation 

for the appearance ofmorc bears near coastal communities and hUllting camps is likely 

that they are searching for alternative food sources in years when their stored body fat 

depots may be depleted before freeze-up, when they can return to the sea ice to hunt seals 

again. Stirling and Iverson (2006) hypothesize that, if the climate continues to warm as 

projected by the Intergovernmental Panel on Climate Change (IPCC), then polar bears in 

all five populations examined will be increasingly food-stressed, and their numbers are 

likely to decline eventually, probably significantly so. As these populations decline, 

problem interactions between bears and humans will likely continue, and possibly 

increase, as the bears seek alternative food sources. 

d. Illegal Harvest of Polar Bears 

Harvesting of polar bears has historically been the main threat to the species, but this has 

been largely mitigated through various management regimes (Prestrud and Stirling 20(2). 

However, in some parts of the bears' range, poaching is still a problem that can have 

profound effects on population persistence. For example, the unregulated harvest of 

Chukchi Sea polar bears in Russia appears to be significant and raises concern about the 

status of this popUlation. Notably, large numbers of polar bear hides have been offered 

for sale on the internet in Russia. Although it has not been proven that the source of 

these hides is Chukotka, we do know this population is vulnerable to illegal hunting. 

Although actual harvest levels are unknown, an estimated 250-300 polar bears werc 

illegally taken on Russia's Chukotka Peninsula in 2002. Experts believe this harvest was 

at least twice the level experienced in previous years and likely resulted from the large 

number of bears that were stranded on land by an early ice retreat (Ovsyanikov 2003). A 

recent population viability analysis indicated that, even at a harvest level of 180 

bears/year, there would likely be a 50% reduction in this popUlation (which is shared with 

the U.S.) size within 18 years (Schliebe 20(3). 

6. Insufficient Current Protections for Polar Bears Under U.S Legislation. 

Currently, polar bears in the U.S. are protected under regulations of the Marine Mammal 

Protection Act ("MM PA"). The primary focus of this legislation, with respect to polar 

bears, has been the management and reporting of the limited legal harvest of polar bears 

by Alaska Natives. The MMPA also sets the conditions for specific activities in polar 

bear habitats, such as oil and gas exploration, development, and production. The MMPA 

regulations have led to a marked decline in the harvest of bears in the U.S.; this Act does 

not address the take from this same population by poachers in Russia, nor does it address 

habitat loss caused by human-induced climate warming. A "Threatened" listing under 

ESA corresponds to, and would automatically result in, the listing of polar bears as 

"Depleted" under MMPA. 
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A potential form of additional protection for U.S. polar bears will be the "Agreement on 

the Conservation and Management of the Alaska-Chukotka Polar Bear Population". This 

treaty was signed by the governments of the U.S. and Russia in October of 2000, but now 

awaits the reconciliation and passage of implementing legislation by the U.S. Senate 

Commerce Committee and the House Resources Committee. Under the terms of the 

Agreement, an international U.S.-Russia Polar Bear Commission (with both federal and 

native representatives) will be formed to oversee a polar bear conservation program. The 

primary focus of this Agreement is the regulation of the limited subsistence hunt (e.g. 

setting harvest limits), which the group will have the authority to enforce as a matter of 

law. While the group will also address habitat issues related to oil and gas development, 

shipping, and other human activities, its role in this regard will be consultative and 

advisory only and will not carry the force of law. The Agrcement will not explicitly 

address the mitigation of threats related to global warming. 

Polar Bear Critical Habitat 

As part of the request for comments on the proposal to list the species (i.e., polar bear), 

the Service is also seeking information regarding measures to consider and reasons why 

any habitat should or should not be determined to be critical habitat for the polar bear if 

the listing becomes final. 

Section 1IJ(5)(A)(i) of the Endangered Species Act (ESA) defines "critical habitat" for 

threatened or endangered species to mean the specific areas within the geographical area 

occupied by the species, at the time it is listed in accordance with the provisions of 

section 4 of the ESA, on which are found those physical or biological features (I) 

essential to the conservation of the species and (II) which may require special 

management considerations or protection. Section IIl(5)(C) specifies that "except in those 

circumstances determined by the Secretary, critical habitat shall not include the entire 

geographical area which can be occupied by the threatened or endangered species." 

USFWS states that "the primary threat to polar bears is the decrease of sea ice coverage. 

Although some females use snow dens on land for birthing cubs, polar bears are almost 

completely dependent upon sea ice for their sustenance. Any significant changes in the 

abundance, distribution, or existence of sea ice will have effects on the number and 

behavior of these animals and their prey" 

http://alaska.fws.gov/fisherics/mml11/polarbear/issues.htm). As noted throughout WWF's 

comments in the proceeding pages. this statement is strongly supported by a rigorous 

body of peer-reviewed science. 

Based on this information and on guidance from the ESA, WWF recommends that the 

critical habitat for polar bears be defined as all Arctic region sea ice capable of 

supporting a polar bear; all known maternal denning areas; and all of those areas likely 

to support maternal denning areas on land and sea, based on projected changes in sea ice 

dynamics. 
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Sea ice is a physical feature essential to the conservation of polar bears. Schliebe et a1. 

(2006) note that polar bear distributions are not uniform throughout the Arctic, but 

depend upon the type of sea ice and its location and extent over time, availability of prey, 

and reproductive status. In their review of the existing information, Sehliebe et a1. (2006) 

note that data indicate that population distribution may not be solely a reflection of prey 

availability, but instead other factors may operate to influence distributions. 

The sea ice environment is highly dynamic and follows annual patterns of expansion and 

contraction (see Schliebc et a1. 2006). Movements of sea ice are related to winds, 

currents, and seasonal temperature fluctuations that promote its formation and 

degradation. Sea ice is generally catcgorized by the stage of development, form, 

concentration, and type of ice and may include stable fast ice with drifts; stable fast ice 

without drifts; floe edge ice; moving ice; continuous stable pressure ridges; coastal low 

level pressure ridges; and fiords and bays. Alternatively, sea ice may be characterized as 

pack ice; shore-fast ice; transition zone ice; and polynyas and leads. 

It is evident there are a variety of forms of sea ice for which polar bears may (or may not) 

show a preference. Schliebe et a1. (2006) noted from the scientific literature that 

predictable sea-ice conditions could help bears in hunting success and sheltering. 

However, sea ice conditions are not necessarily predictable in all areas, as evident in the 

fluctuating sea-ice condition in regions like the Beaufort Sea or Baffin Bay, and possibly 

requiring modifications of foraging strategy from month to month or even day to day 

during break-up, freeze-up, or periods of strong winds. Given the day-to-day and monthto-month dynamic changes of sea ice forms in the Arctic, and our inability to accurately 

predict such changes to sea ice forms in the days, weeks, months, years, and decades 

ahead because of climatic warming in the Arctic, it is prudent to designate all Arctic 

region sea ice capable of supporting a polar bear as critical habitat. 

As noted above, polar bears' life history is intricately linkcd to the Arctic sea ice. 

However, it would be impracticable and unrealistic to accurately predict (with the current 

information) how polar bears will respond to the diminishment of one or several sea ice 

forms (e.g., stable fast ice with drifts, shore-fast ice) relative to other forms (e.g., coastal 

low level pressure ridges, transition zone ice) as climatic warming progresses in the 

Arctic. Thus WWF would caution USFWS against attempting to identify just one or 

even several forms of sea ice as critical habitat while excluding other sea ice forms also 

necessary for polar bear survival now or in the future. 

Maternal Denning Habitat as Polar Bear Critical Habitat 

Throughout their range, most pregnant female polar bears excavate dens in snow located 

on land in the fall- early winter period with exceptions in Hudson Bay and the southern 

Beaufort Sea (Schliebe et a1. 2006). Successful denning by polar bears requires 

accumulation of sufficient snow for den construction and maintenance. Adequate and 

timely snowfall combined with winds to cause snow accumulation leeward of 
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topographic features create denning habitat (Schliebe et al. 2006). Denning areas are both 

physical and biological features necessary for the conservation of polar bear populations. 

The IPCC (2007) notes that snow cover is projected to contract in the decades ahead. 

Widespread increases in thaw depth are projected over most penna frost regions. 

Coincident with decreasing snow fall and permafrost thawing, global sea levels are 

projected to continue rising during the 21 st century. Decreased snowfall, permafrost 

thawing, increased precipitation, and the inundation of Arctic coastal areas due to rising 

sea level, appear likely to diminish maternal denning sites currently used on land, while 

at the same time, the current and future loss of sea ice may force a landward shift in 

maternal denning as observed by Fischback et al. (2006). How future snow melt, 

pennafrost thawing, and rising sea lcvels in the Arctic might influence maternal polar 

bear denning habitat appears poorly understood or modeled, but may synergistically 

interact to form a confiuence of factors that collectively diminish maternal denning 

habitat on Arctic lands and on sea ice. Therefore WWF believes that a prudent measure 

would be to identify maternal denning areas on sea ice and land as polar bear critical 

habitat. 

Best Scientific Data Available 

Section IV (b)(2) of the ESA specifies the basis for critical habitat determinations-the 

Secretary shall designate critical habitat, and make revisions thereto, under subsection 

(a)(3) on the basis of the best scientific data available and after taking into consideration 

the economic impact, the impact on national security, and any other relevant impact, of 

specifying any particular area as critical habitat. The Secretary may exclude any area 

from critical habitat if he determines that the benefits of such exclusion outweigh the 

benefits of specifying such area as part of the critical habitat, unless he determines, based 

on the best scientific and commercial data available, that the failure to designate such 

area as critical habitat will result in the extinction of the species concerned. 

Assertions have been made publicly suggesting that polar bears do not strongly depend 

on sea ice for their sustenance; that polar bears are adaptable to foraging on terrestrial 

sources of protein (instead of icc seals); and that polar bears can den in earthen tunnels. 

Such assertions are extrapolations taken from the scientific literature, but are not regarded 

as being of strong scientific merit or the best scientific information available. It is more 

likely that such assertions are hype, and intended to mislead policy makers and wildlife 

administrators from the fundamental task of conserving polar bear populations as climatic 

warming in the Arctic diminishes their habitat. 

The scientific literature reviewed by Schliebe et al. (2006) clearly establishes that Arctic 

sea ice and maternal denning habitat on land and sea are necessary to maintaining healthy 

polar bear populations; that refiects the best available science. Furthermore, the !PCC 

(2007), upon extensive study, debate, and review of the best available science, 

determined that sea ice is projected to shrink in the Arctic under all IPCC Special Report 

emission scenarios, and that in some projections, Arctic late-summer sea ice disappears 

almost entirely by the latter part of the 21 st century. Additionally, the !PCC notes that 

anthropogenic warming and sea level rise will continue for centuries due to the 
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timescales associated with climate processes and feedbacks, even if greenhouse gas 

concentrations are stabilized. The !PCC (2007) and the ACIA (2004, 2005) reflects the 

best available science on climate change, particularly in the Arctic. 

Concurrent Designation of Critical Habitat with Listing Polar Bears 

Section 4(a)(3) of the ESA requires that the Secretary, by regulation promulgated in 

accordance with subsection (b) and to the maximum extent prudent and determinable-

(A) shall, concurrently with making a determination under paragraph (I) that a 

species is an endangered species or a threatened species, designate any habitat of 

such species which is then considered to be critical habitat; and 

(B) may, from time-to-time thereafter as appropriate, revise such designation. 

The scientific literature, as well as the professional opinions of many polar bear experts, 

clearly reflect the critical necessity of sea ice habitat and maternal denning habitat for 

conservation of healthy polar bear populations. Climatic warming in the Arctic threatens 

to diminish both sea ice and maternal denning habitats. Therefore, WWF recommends 

that Arctic sea ice habitat and maternal denning habitat (terrestrial and on sea ice) be 

designated as polar bear critical habitat concurrently with making a determination under 

paragraph (i) that the polar bear is an endangered species or a threatened species. 

Conclusion 

Taylor et al. (2007) assessed scientists' ability to detect declines of marine mammal 

stocks based on recent levels of survey effort, when the actual decline is precipitous. The 

percentage of precipitous declines that would not be detected as declines was 55% for 

polar bears/sea otters, given the frequency and precision of recent monitoring effort. This 

study highlights the need for accurate stock estimates, and the strong likelihood of not 

accurately detecting declines in polar bear subpopulations. For this reason, WWF 

recommends listing the polar bear as Threatened. We believe protection under the ESA 

will benefit and augment conservation of the polar bear as it faces diminishing sea ice 

habitat due to climatic warming. 

The IUCN/Polar Bear Specialist Group concluded that the IUCN Red List classification 

of the polar bear should be upgraded from "Least Concern" to "Vulnerable" based on the 

likelihood of an overall decline in the size of the total population of more than 30% 

within the next 35 to 50 years (Aars et aI., 2006). The principal cause of this decline is 

climatic warming and its consequent negative affects on the sea ice habitat of polar bears. 

In some areas, contaminants may have an additive negative influence. 

The weight of scientific evidence supports the contention that polar bears' habitat is fast 

disappearing and that predicted individual and population level effects are already 

occurring. According to Derocher et a!. (2004): 
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" ... polar bears are constrained in that the very existence of their habitat is 

changing and there is limited scope for a northward shift in distribution. 

Due to the long generation time of polar bears and the current pace of 

climate warming, we believe it unlikely that polar bears will be able to 

respond in an evolutionary sense. Given the complexity of the ecosystem 

dynamics, predictions are uncertain but we conclude that the future 

persistence of polar bears is tenuous." 

Due to the well-documented and accelerating warming of the Arctic and subsequent loss 

of polar bear habitat, the potential for such changes to negatively impact polar bear 

reproduction and survival, and the existing gaps in protection under current polar bear 

management regulations, WWF supports immediate listing of the polar bear as 

Threatened under the ESA. 

Sincerely, 

Margaret D. Williams 

Director, Bering Sea Ecoregion Program 

World Wildlife Fund 

406 G Street, Ste 303 

Anchorage, AK 99501 

Enclosures: 

• Literature Cited 

• CV for Margaret Williams 
221 


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The Wildlife Society 13'h Annual Conference. Anchorage, Alaska. September 23-27. 

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135. 

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Grebmeier, J.M., J.E. Overland, S.E. Moore, E.V. Farley, E.C. Carmack, L.W. Cooper, 

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http://www.ipcc.ch/SPM2feb07.pdf 

Iverson, S.1., l. Stirling, and S.L.e. Lang. 2006. Spatial and temporal variation in the 

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populations and environment. Pp. 98-117. In: Top Predators in Marine 

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Jenssen, B.M. 2006. Endocrine-disrupting chemicals and climate change: a worst-case 

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Perspectives 114:76-80. 

Kirk, C.M., R. Sworl, D. Holcomb, S. Amstrup, and T. O'Hara. 2006. Recent efforts to 

assess Beaufort Sea polar bear health. Abstracts of The Wildlife Society 13th Annual 

Conference, Anchorage, Alaska. September 23-27,2006. The Wildlife Society. Bethesda, 

MD. 

Mauritzen, M., A.E. Derocher, O. Pavlova, and O. Wiig. 2003. Female polar bears, 

Ursus maritimus, on the Barents Sea drift ice: Walking the treadmill. Anim. 

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McKinney, M.L. 1997. Extinction vulnerability and selectivity: Combing ecological 

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Meier, W., J. Strieve, F. Fetterer, and K. Knowles. 2005. Reductions in Arctic sea ice 

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Monnett, C., and J.S. Gleason. 2006. Observations of mortality associated with extended 

open-water swimming by polar bears in the Alaskan Beaufort Sea. Polar Biology 

29:681-687. 

NISDC, NASA, and University of Washington. 2005. Sea ice decline intensifies. Press 

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Norstrom, R.1., S.E. Belikov, E.W. Born, G.W. Garner, B. Malone, S. Olpinski, M.A. 

Ramsay, S. Schliebe, I. Stirling, M.S. Stishov, M.K. Taylor, and O. Wiig. 1998. 
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America, Greenland and Svalbard. Arch. Envir. Cont. Toxicol. 35: 354-367. 

Ovsyanikov, N. 2003. Dark Times for Chukotka Polar Bears. wwr Arctic Bulletin 

2.03:13-14. 

Overpeck, J., M. Sturm, J. Francis, D. Perovich, et al. 2005. Arctic system on trajectory 

to new, seasonally ice-free state. EOS 86: 309-313. 

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their regional, seasonal and monthly variability and trends. Ann. Glacial. 34: 

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Prestrud. P. and l. Stirling. 1994. The International Polar Bear Agreement and the 

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bears (Urusu maritimus) . .I. Zool., London 214: 601-634. 

Regehr, E.V., N.J. Lunn. S.C. Amstrup. and l. Stirling. 2005. Population decline of 

polar bears in western Hudson Bay in relation to climactic warming. Abstract 

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San Diego, California. 

Regehr, E.V., S.C. Amstrup, and I. Stirling. 2006a, Polar bear population status in the 

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Rosing-Avid, A. 2006. The intluence of climate variability on polar bear (Ursus maritimus) and 

ringed seal (Pusa hispida) population dynamics. Can. J. Zoo I. 84:357-364. 

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Jahrsdoerfer. 2006. Range-wide status review of the polar bear (Ursus maritimus). U.S. 

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Serreze, M.e., J.E. Walsh, F.S. Chapin, III, T. Osterkamp, M. Dyurgerov, V. 

Romanovsky, W.C. Oechel, J. Morison, T. Zhang, and R.G. Barry. 2000. 

Observational evidence of recent change in the northern high-latitude 

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Skaare, J.U., A. Bernhoft, O. Wiig, K.R. Norum, E. Haug, D.M. Eide, and A.E. 

Derocher. 2001. Relationships between plasma levels of organochlorines, retinol 

and thyroid hormones from polar bears (Ursus marilimus) at Svalbard. J. Envir. 

Health Tox. 62: 227-241. 

Smith, T.G. 1980. Polar bear predation of ringed and bearded seals in the land-fast sea 

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Stirling, I. 1990. Polar bears and oil: Ecological perspectives. In J. R. Geraci and D. 1. 

St. Aubin (eds.), Sea mammals and oil: conlronting the risks, pp. 223-234. 

Academic Press, San Diego. 

Stirling, I. 2002. Polar bears and seals in the eastern Beaufort Sea and Amundsen Gulf: 

A synthesis of population trends and ecological relationships over three decades. 

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April 10,2006 

Scott Schliebe 

Polar Bear Project Leader 

U.S. Fish and Wildlife Service 

Marine Mammals Management Office 

1011 East Tudor Road 

Anchorage, AK 99503 

Re: Polar Bear 90-day petition finding 

Dear Scott: 

~ WWF 

On behalf of the World Wildlife Fund, thank you for this opportunity to comment on the recent 

determination by the U.S. Fish and Wildlife Service that formal listing and protection of the 

polar bear (Ursus maritimus) under the U.S. Endangered Species Act (ESA) may be warranted. 

WWF is an international conservation organization with 1.2 million members in the US. WWF 

works around the world, including in all of the Arctic countries inhabited by polar bears. One of 

our priority ecoregions is the Bering Sea, where we have been actively involved in conservation 

of the Alaska-Chukotka polar bear population. 

WWF strongly supports fonnallisting and protection measures for the polar bear as a Threatened 

species under the ESA, for reasons outlined herein and with the support of the best available 

science. 

The federal ESA requires the protection of a species as 'Threatened" if it "is likely to become an 

endangered species within the foreseeable future throughout all or a signiticant portion of its 

range." r 16 U.S.C. § 1532(20)]. A species is considered "endangered" when it "is in danger of 

extinction throughout all or a significant portion of its range." [16 U.S.c. §J5320(6)]. We 

believe that the current situation for polar bears clearly relates to ESA Section 4(a)(1). Factors 

weighted heavily as listing evaluation criteria that apply to polar bears include: 
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A. the present or threatened destruction, modification or curtailment of its habitat or range; 

D. the inadequacy of existing regulatory mechanisms; and 

E. other natural or manmade factors affecting its continued existence. 

[See Title 6 Us. Code. Section /533(a)(/}(A-E)} 

WWF believes that polar bears in the U.S. meet the statutory criteria cited above for protection 

as Threatened under the ESA. based on the now substantial and growing body of peer-reviewed 

and published scientific data (discussed below) and the nUmerous observations of Arctic 

community members (i.e. Local & Traditional Knowledge). These sources strongly suggest that 

current and projected global warming is and will continue to negatively and severely impact 

polar bears' habitat, prey, behavior, reproduction. and survival such that the species faces 

possible global extinction by the end of this century. 

Finally, WWF fully endorses precautionary and proactive conservation principles and argues for 

application of strong protective measures for this species sooner rather than later, as the observed 

rate of Arctic ecosystem change (especially reductions in sea ice cover, extent, and duration) is 

accelerating well beyond that projected by early climate models. 

Evidence' that the polar bear warrants listing in under the ESA as "Threatened", and that fulfill 

the listing criteria that the species "is likely to become an endangered species within the 

foreseeable future throughout all or a significant portion of its range" according to 16 USc. § 

1532(20), include: 

I. Climate Impacts on Polar Bear Habitat 

The most fundamental characteristic of polar bears in relation to their ecology is their utter 

dependence on sea ice habitats (Derocher et aJ. 2004). Anything that significantly changes the 

distribution and abundance, let alone the very existence of sea ice will have profound effects on 

the persistence of polar bears On Earth. Such habitat loss or fragmentation is well documented to 

be a primary cause of extinctions (Beissinger 2000, Ceballos and Ehrlich 2002). 

Experts agree that the once-characteristic ecotype of the far north is undergoing an 

unprecedented and accelerating warming trend (ACIA 2004, Serreze et al 2000, Parkinson and 

Cavalieri 2002, Comiso 2002a, 2002b, 2003), shifting from arctic to subarctic conditions, in 

some cases profoundly altering the fundamental biological components that are usually 

associated with the Arctic realm (e.g. Grebmeier et a!. 2006). This consensus confirms what has 

been known for some time by Native peoples inhabiting this region (e.g. ACIA 2004. WWF 

Climate Witness Program testimony www.panda.org/arctic ). 

Because of increased global temperatures thought to result from accumulated atmospheric 

pollution, Arctic sea ice is melting at an unprecedented ratc (Meicr et al. 2005, NSIDC 2005, 

1 Scientific data are octter for some regions/populations than for others. However, remote sensing has allowed more 

homogenous high quality data to be compiled across the Arctic marine ecosystem; these data include crucial sea-ice habitat 

data and projections relating to polar bear survival prospects across the entire species range. 
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Overpeck et al. 2005, Stroeve 2005). Scientists estimate that injust the last three decades, the 

average annual sea icc extent has decreased by nearly 1.3 million square kilometers or 500,000 

square miles (twice the size of Texas), at a rate of about 8-9% per decade (Comiso 2002b, 

NSIDC 2005). It appears that the warming/ melting trend is accelerating (ACIA 2004, NSIDC 

2005). Current predictions in the primary literature are that, by the end of this century, annllal 

temperatures in the Arctic will likely rise by 7 degrees C (13.6 dcgrees F) over oceans (ACIA 

2004) and that summer Arctic sea ice might decline by 50-100% (ACIA 2004, Comiso 2003, 

Gough and Wolfe 2001, NSIDC 2005, Overpeck et al. 2005). 

The latest satellite information from the National Snow and lee Data Center and NASA indicates 

that the observed temperature increases and ice declines are not anomalies but signal a new and 

ominous trend: 2005 marked the fourth consecutive year exhibiting thc lowest amount of ice 

cover in more than a century. Mean temperatures in 200 I -2005 were 20% warmer than the 

average of 1978-2000 and the winter recovery of sea ice in 2004-2005 was the smallest on 

satellite record. These organizations concluded that Arctic sea ice, home to all polar bears on 

Earth, "is likely on an accelerating, long-term decline" (NSIDC 2005). 

2. Climate Impacts on Polar Bear Prey 

Sea ice also is the preferred habitat for polar bears' main prey: ringed and bearded seals (Smith 

1980). Polar bears are specialists on these phocid seals, only rarely and opportunistically taking 

other prey. like walrus, small whales, or other seals (Derocher et a!. 2002). Of concern is how 

accessible prey spccies will be in an altered sea ice environment. Sea ice is the physical platform 

from which polar bears hunt; they only rarely capture prey successfully in open water (Furnell 

and Oolooyuk 1980). The emerging warmer elimate regime is likely to negatively impact polar 

bears both by reducing the duration, thickncss. and extent of available hunting habitat (as 

described above) and also by reducing populations of these two obligate prey species, which, like 

polar bears, are sensitive to perturbations in the sea ice environment and related changes in 

primary productivity (Derocher et a!. 2004). In illustration of this, changes in ice characteristics 

have been documented to have a significant negative effect on popUlation size and recruitment of 

ringed seals and subsequently of polar bears (Stirling 2(02). 

Thus, predicted and observed changes in its distribution. characteristics, and timing of sea ice 

certainly have the potential to profoundly and negatively affect the species at the population level 

(Stirling and Derocher 1993, Derocher et al. 2004). 
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82737.055

3. Climate Impacts on Polar Bear Reproduction and Survival 

Changes to ice habitats also affect polar bear denning opportunities. ultimately reducing 

population reproductive success. For pregnant bears that den on land, icc must freeze early 

enough in thc fall to allow them to walk or swim to the coast. As the distance from ice edge to 

coasts increases, it will become progressively more difficult for them to reach their preferred 

locations (Derocher et al. 2004). For females that den on multiyear ice rather than stable land, 

increased drift rates of this habitat could mean longer distances to travcl with new cubs to reach 

the core of their normal home range (Derocher et al. 2004). 

Such increased energy expenditure by individual polar bears could result in both lower survival 

and reproductive rates in the long tcrm (Derocher et al. 2004) by reducing stores of adipose 

tissue, thereby impacting body condition. Much of the life history of polar bears, particularly 

reproductive females, is tied to storing large quantities of adipose tissue when hunting conditions 

are favorable and subsequently using these stores when conditions do not allow for hunting 

(Ramsay and Stirling 1988), such as during the 4-month fast that occurs in many popUlations 

during summer when sea ice is in retreat. The earl ier bears are forced to come ashore, the less 

fat they have been able to store. Adult female polar bears losc approximately 4.71 kg/day during 

fasts (the rate may be 4-fold higher for pregnant females; Derocher and Stirling 1995). Because 

femalcs apparently cannot reproduce when they drop below 189 kg, and at current rates of ice 

decline, it has been calculated that most females in the southerly Hudson Bay popUlation will be 

unable to reproduce as soon as 2012 (Derocher et al 1992). Compromised females will also 

likely produce fewer, smaller cubs with lower survival rates (Derocher and Stirling 1996. 

Derocher and Stirling 1998). 

Reduced hunting success as a result of compromised habitat integrity will likely result in reduced 

fat stores becausc of the increased energy output associated with traveling on more labile ice or 

swimming across open water for longer distances when ice retreats (Mauritzen et aI2003). If 

ice conditions arc particularly poor, cub mortality may increase as they are forced to swim 

greater distances in cold water (Derocher et al 2004). Adult mortality can also result from 

changes in ice condition, timing, and extent: recently, there have been documentcd accounts of 

adult polar bears drowning in the Alaskan Bcaufort Sea, presumably while swimming unusually 

long distances across open water in unusually rough weather (Monnett et al. 200S); the authors 

suggest that such drowning events may increase in the future, as icc continues to melt. Increased 

adult mortality has also bcen observed in recent years on Wrangel Island in the Chukchi Sea, 

home (with nearby Herald Island) to 80% of the region's breeding female polar bears. In 2002, a 

year of exceptionally early icc retreat, the Island's resident polar bear biologist reported the 

highest proportion of skinny bears ever and a very high mortality rate (Ovsyanikov 2003) . 

Case Study: Southwestern Hudson Bay Population 

In southwestern Hudson Bay, increasing temperatures have already increased the duration of the 

ice-free period (thus increasing the fast) by approximately 2.S weeks (Stirling et al. 1999). A 

recent study of this well-known population, which alone constitutes roughly 5-10% of the total 

estimated world population, has established, for the first time, a negative population-level efl'ect 

of climate change on polar bears (Regehr ct al. 200S). The study documented that the size of this 

population had declined from approximately 1200 bears in 1987 to fewer than 9S0 bears in 2004. 
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The authors also established a statistical correlation between earlier summer ice break-up and 

decreased survival for all but prime-aged bears. 

Some experts believe that, at the current rate of decline and unless climate change trends and 

impacts are swiftly reversed, this self-sustaining population of wild polar bears could become 

extirpated by 2050 (i.e., only 3 polar bear generations from now using the IUCN-recognized 

range for polar bear mean generation time of 12-17 ycars). It is widely recognized, based on sea 

ice remote sensing and oceanographic monitoring, that similar rapid reductions of sea ice (and 

hence polar bear fceding and denning opportunities) are probably affecting other populations 

(such as the Alaska-Russia population), although these have not been as intensely studied as 

those in southwest Hudson l3ay. 

4. Threats to Polar Bears Due to Their Life History and Distribution 

Polar bears are a classic K-selected spccies, exhibiting delayed maturation, small litters, and high 

adult survival rates (Bunnell and Tait 1981). Potential extinction risk for polar bears is 

heightened because of these characteristic features of their life history, and other traits such as 

their specialized diet, large body size, long life span, and low genetic diversity (McKinney 1997, 

Beissinger 2000). Also, because of their long generation time (mean 12-17 years in most 

regions), polar bears are not well suited to rapid evolution and therefore are unlikely to adapt 

successfully to the rapidly changing climate and the related effects on habitat and prey. Finally, 

although polar bears occupy virtually all available sea ice habitats throughout the vast 

circumpolar Arctic and number between 21,500-25,000 individuals worldwide (the IUCN/SSC 

Polar Bear Specialist Group recognizes 20 distinct subpopulations), the species is neveltheless 

vulnerable to the effects of disappearing and/or fragmented habitat because it occupies a range 

that, with few exceptions, cannot simply expand further nOlth. 

5. Other Threats to Polar l3ears 

The existence of polar bcars is further threatened by a number of other factors, many of which 

are likely to be exacerbated by the effects of climate change. 

a. Oil and Gas Development and Tramport 

Active oil and gas exploration, extraction, and transportation occur throughout the range of the 

polar bear. Polar bears are sensitive to oiling in the event of a spill (Stirling 1990), and their 

behaviors can be affected by disturbances related to hydrocarbon development (such as seismic 

blasting and infrastructure development: Derocher et al. 1998). Currently proposed offshore 

extraction activities pose the greatest threat to polar bears, especially if a spill occurred near a 

polar bear denning site (Isaksen et al 1998). Also, spills in frozen or partially frozen Arctic 

waters are hard to detect and no method has proven effective for clean up in this environment. 

Finally, should climate warming lead to an open northern shipping route, the threat of a spill 

would be presented to more northerly polar bear populations, such as Alaska's bears in the 

Chukchi Sea. 
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b, Pollutants and Disease 

Many persistent organic pollutants, such as heavy metals, radioactive elements, and persistent 

organic pollutants, can reach high levels in polar bears due to their high fat diet and high trophic 

position (Norstrom et al 1998), Studies have demonstrated that such chemicals can negatively 

impact endocrine function (Skaare et aL 200 I), immune function (Bernhoft et al 2000), and 

subsequent reproductive success (Derocher et aL 2003). Immune compromised, not to mention 

hungry, bears may be more susceptible to disease or parasites. The northern expansion if range 

of disease organisms and the nearly complete lack of such organisms in polar bears' cvolutionary 

past also make them vulnerable to novel pathogens (Derocher et aL 20004). Finally, 

environmental pollutants can cause pseudohermaphroditism in female bears, as has been 

observed in Svalbard (Wiig et al 1998) further reducing population reproductive rates. 

c, Increased Aggressive Human-Bear Interactions 

It has been predicted that human-bear interactions would increase as a result of climate-induced 

changes to polar bear habitat (Stirling and Derocher 1993). There is a documented correlation 

between date of ice break-up in spring and number of "problem" bears reported in some 

communities (Stirling et al 1999), More bcars on land, especially if they are hungry, can lead to 

more attacks on humans and, correspondingly, more "defense of life and property" killings of 

bears, Just this year, in a remote village on Russia's Chukotka Pcninsula, a young woman was 

killed by an unusually aggressive bear; this was the third reported bear shooting in Russia this 

winter. 

d !Ilegal Harvest of Polar Bears 

Harvesting of polar bears has historically been the main threat to the species, but this has been 

largely mitigated through various management regimes (Prestrud and Stirling 2002). However, 

in some parts of the bears' range, poaching is still a problem that can have profound effects on 

population persistence, For example, the unregulated harvest of Chukchi Sea polar bears in 

Russia appears to be significant and raises concern about the status of this population. Notably, 

large numbers of polar bear hides have been offered for sale on the internet in Russia. Although 

it has not been proven that the source of these hides is Chukotka, we do know this population is 

vulnerable to illegal hunting. Although actual harvest levels are unknown, an estimated 250-300 

polar bears were illegally taken on Russia's Chukotka Peninsula in 2002. Experts believe this 

harvest was at least twice the level experienced in previous years and likely resulted from the 

large number of bears that were stranded on land by an early ice retreat (Ovsyanikov 2003). A 

reccnt population viability analysis indicated that, even at a harvest level of 180 bears/year, there 

would likely be a 50% reduction in this population (which is shared with the U ,S,) size within 18 

years (Schliebe 2003), 
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6. Insufficient Current Protections for Polar Bears Under U.S Legislation. 

Currently, polar bears in the U.S. are protected under regulations of the Marine Mammal 

Protection Act ("MMPA"). The primary focus of this legislation, with respect to polar bears, has 

been the management and reporting of the limited legal harvest of polar bears by Alaska Natives. 

The MMPA also sets the conditions for specific activities in polar bear habitats, such as oil and 

gas exploration, development, and production. The MMPA regulations have led to a marked 

decline in the harvest of bears in the U.S.; this Act does not address the take from this same 

population by poachers in Russia, nor does it address habitat loss caused by human-induced 

climate warming. A "Threatened" listing under ESA corresponds to and would automatically 

result in the listing of polar bears as "Depleted" under MMPA. 

A potential form of additional protection for U.S. polar bears will be the "Agreement on the 

Conservation and Management of the Alaska-Chukotka Polar Bear Population". This treaty was 

signed by the governments ofthc U.S. and Russia in October of2000, but now awaits the 

reconciliation and passage of implementing legislation by the U.S. Senate Commerce Committee 

and the House Resources Committee. Under the terms of the Agreement, an international U.S.-

Russia Polar Bear Commission (with both federal and native representatives) will be formed to 

oversee a polar bear conservation program. The primary focus of this Agreement is the 

regulation of the limited subsistence hunt (e.g. setting harvest limits), which the group will have 

the authority to enforce as a matter ofiaw. While the group will also address habitat issues 

related to oil and gas development, shipping, and other human activities, its role in this regard 

will be consultative and advisory only and will not carry the force oflaw. The Agreement will 

not explicitly address the mitigation of threats related to global warming. 

Conclusion 

In light of the documented uncertainties in the face of a warming Arctic, in 2005, the IUCN/SSC 

Polar Bear Specialist Group concluded that the IUCN Red List classification oftbe polar bear 

should be upgraded from "Least Concern" to ·'Vulnerable". These experts based their 

reclassification on their projection for a 30% overall decline in the size of the total population 

within the next 35 to 50 years. The principal cause of this decline, according to their own 

experts, is climatic warming and its consequent negative affects on the sea ice habitat of polar 

bears. 

The weight of scientific evidence supports the contention that polar bears' habitat is fast 

disappearing and that predicted individual and population level effects are already occurring. 

According to Derochcr et al. (2004): 

" ... polar bears arc constrained in that the very existence of their habitat is 

changing and there is limited scope for a northward shift in distribution. Due to 

the long generation time of polar bears and the current pace of climate warming, 

we believe it unlikely that polar bears will be able to respond in an evolutionary 

sense. Given the complexity of the ecosystem dynamics, predictions are 

uncertain but we conclude that the future persistence of polar bears is tenuous." 
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Due to the well-documented and accelerating warming of the Arctic and subsequent loss of polar 

bear habitat, the potential for such changes to negatively impact polar bear reproduction and 

survival, and the existing gaps in protection under current polar bear management regulations, 

WWF supports immediate listing of the polar bear as Threatened under the ESA. 

Sincerely, 

Margaret D. Williams 

Director, Bering Sea Ecoregion Program 

World Wildlife Fund 

Lara J. Hansen, Ph.D. 

Chief Scientist, Climate Change Program 

World Wildlife Fund 

Enclosures: 

CY for Margaret Williams 

CY for Lara Hansen 

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237 

Senator BOXER. Thank you so much, Margaret. You were right 

on target, you made all your points. Very good. 

I am happy to call on Richard Glenn, an Arctic resident, Alaskan 

Arctic resident and a sea ice geologist. Welcome, sir. 

STATEMENT OF RICHARD GLENN, ALASKAN ARCTIC 

RESIDENT, SEA ICE GEOLOGIST 

Mr. GLENN. Thank you, Madam Chair. Thank you, Senator 

Inhofe and members of the Committee. Thank you for the opportunity to provide comments. 

My name is Richard Glenn, and I am the board present of the 

Barrow Arctic Science Consortium. This is an organization dedicated to bringing visiting researchers together with Arctic residents. I am an officer of the Arctic Slope Regional Corporation, 

which is a corporation for the Native people of Alaska’s North 

Slope. I am here today as an Alaskan resident who studies sea ice, 

as a subsistence hunter, a whaling crew co-captain and a geologist. 

This issue is very important to me. 

I have only 5 minutes an my oral comments will summarize the 

most important points of my more detailed written testimony. I 

have studied sea ice for university-level work and have assisted 

many others in the sea ice environment. We Inupiaq hunters hunt 

on the ice each year, and our lives depend and the safety of our 

people depends on our knowledge of changing ice conditions. 

Along with many of our people, I am concerned about changing 

sea ice conditions. However, I question whether the loss of multiyear sea ice equals the loss of polar bear habitat. The most prominent point made by the Fish and Wildlife Service is about receding 

multi-year sea ice cover and its equivalence to the loss of polar 

bear habitat. There is little mention of the marginal ice zone, that 

area of ice that freezes and melts within a given year, mixed with 

open water and older ice. It is in this area that it grows at the expense of the loss of multi-year ice. 

The polar bear does not live only on the multi-year ice pack. 

Polar bears thrive in many settings. In late spring, polar bears 

come to the near-shore land-fast ice to hunt newborn seal pups located in dens beneath snow drifts. In summer, we observe polar 

bears hunting farther offshore in the marginal ice zone. Other 

polar bears will stay on the coast, not trapped there by the absence 

of sea ice, but to feed on living or dead animals along the shoreline. 

Groups of bears have even been seen by our villagers establishing 

an over-wintering circle around a carcass, such as dead gray whale. 

My point is, none of the above hunting environments is on the 

multi-year ice pack. There is a year-long and varied cycle of habitats for polar bears. It is wrong to ignore them and focus only on 

how far the ice has receded. To do so is to ignore the polar bear’s 

use of other habitats. Even the Fish and Wildlife Service study acknowledges that the increase of marginal ice cover may be beneficial for ice seals and polar bears. 

The proposed listing is not based on polar bear population levels 

or trends. There is not enough observational data for a listing. 

Polar bears are hard to count, and ice conditions are not so easy 

to predict form models or satellites. The proposed rule correlates a 

decline of sea ice cover with a decline of ring seals. The data is inVerDate Aug 31 2005 12:30 Jan 15, 2014 Jkt 000000 PO 00000 Frm 00243 Fmt 6633 Sfmt 6633 S:\_EPW\DOCS\82737.TXT VERN
238 

sufficient to support even this conclusion. Right now, in the 

Chukchi Sea, the satellites will tell you that our ocean is covered 

with new, young ice, and not the multi-year ice pack. Nevertheless, 

our hunters are reporting abundant and healthy ring seals as well 

as polar bears. 

There are many international mechanisms set up to conserve and 

protect the polar bear. In moving to the Endangered Species Act, 

let us not ignore those, such as the Marine Mammal Protection 

Act. If we really want to protect the species, let’s do something 

about poaching, poaching by other countries. Alaskan Inupiaq people annually take about 45 to 50 bears from the Chukchi stock. Yet 

the same stock is suffering from poaching on the Russian side, with 

catch numbers around 200 per year. 

Our traditional knowledge is built upon thousands of years of experience in the Arctic environment. I encourage Congress to use 

our experience and science before taking action to list the polar 

bear as threatened. This is common sense and required by law. 

Senator BOXER. You have more time, if you want to go on. 

Mr. GLENN. Oh, I heard a buzzer. I thought you were—— 

Senator BOXER. Not at all. You have another 45 seconds. Go 

right ahead. 

Mr. GLENN. A threatened listing for the polar bear, Madam 

Chair, will do little to aid the polar bear’s existence. It will not create more sea ice cover. It will not change their ability to locate dens 

or prey. But it will disproportionately affect the lives of Inupiaq Eskimos who live along the Arctic coast. While America sleeps better 

at night falsely believing they have assisted this iconic species, 

they will still fly planes, drive cars and power their homes. We are 

very concerned about changes in climate changes in the Arctic, and 

have more reason than others to be aggressive. The proper methods 

to address those issues are to deal with climate change causes directly and not twist the Endangered Species Act listing of the polar 

bear into action directed at climate change. 

Thank you. 

[The prepared statement of Mr. Glenn follows:] 

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Statement of Richard Glenn 

To the Committee on Environment and Public Works 

United States Senate 

On 

Examining Threats to and Protections of Polar Bear 

January 30, 2008 

Madam Chair, Senator Inhofe, and Members of the Committee, thank you for the 

opportunity to appear here today. I appreciate your effort to hear from Alaskan Arctic 

residents and Alaska's Inupiaq people on these most important issues. 

Introduction 

My name is Richard Glenn. I am here today as an Alaskan Arctic resident who studies 

sea ice, a subsistence hunter and whaling crew co-captain, and a geologist. I am also an 

incorporator and the board President of the Barrow Arctic Science Consortium, which is 

an organization that fosters the ongoing productive relationship between visiting 

researchers and local experts within our Native community. I am also a board member 

and officer of the Arctic Slope Regional Corporation (ASRC), the Alaska Native 

Regional Corporation for the Native people of Alaska's North Slope. While I wear many 

hats, I am appearing here today as an Inupiaq resident of Alaska's Arctic. 

I have studied sea ice for years, studied it for University-level work and have assisted 

many others in the sea ice environment, including ice scientists, Navy dive teams, 

journalists and biologists. We Inupiaq hunters live and hunt on the ice each year, so our 

lives and safety depend on our knowledge of ever-changing ice conditions. 

Ice Conditions and Relation to Polar Bear 

T, along with many of our people, am concerned about the changing sea ice conditions 

that we have experienced in the last few years. We are watching it closely, on a day to 

day basis, as well as seasonally, to understand what is occurring in our ocean 

environment, and, most significantly for us, what those changes mean for the resources 

on which we depend for our way of life. 

The most prominent point made by the Fish and Wildlife Service in its proposal to list the 

polar bear as a threatened species under the ESA is about receding perennial ice pack and 

its equivalence as a "loss of habitat". It also mentions increased fetches of open water, 

and its effects on denning and feeding. There is little mention of the marginal ice zone 

which must grow at the expense of a receding perennial pack. The marginal ice zone is 

comprised of ice that freezes and melts within a given year, and may contain fragments of 

older multiyear ice as well as areas of open water. 
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In addition to hunting at breathing holes and wind-driven lead edges in winter, polar 

bears thrive in many settings. In waters offshore of Barrow, for example we hunters see 

polar bears come closer to shore in late spring when the ringed seals give birth to pups 

beneath stable snowdrifts on landfast sea ice. The bears smell the odor of dens of 

newborn seal pups beneath snowdrifts. 

In summer we observe polar bears hunting in the marginal ice zone. This coincides with 

the arrival of the walrus herds, and bears hunt them along with seals on and around 

drifting ice floes. I believe this is where polar bears thrive, because they can catch 

napping prey on ice floes, or use the floes for cover to catch animals in the water. 

Some polar bears will also stay on the coast in the summer months, not trapped there by 

the absence of ice, but to feed on dead grey whales that have washed ashore, or on walrus 

and seals basking on the beach. 

In autumn and winter some bears continue to feed on the remains of dead animals that 

have washed ashore. Groups of bears have been seen by our villagers establishing an 

over-wintering circle around a carcass, such as a grey whale. And yes, as the Fish and 

Wildlife Service notes, they also feed on the remains of bowhead whales harvested by 

fall-time whale hunters of the three eastern North Slope villages. Much has been written 

about the presence of bears around bowhead remains, but it is simply a part of their 

natural feeding cycle. 

None of the above hunting environments is on the multi-year ice "pack". My point is 

there is a yearlong and varied cycle of habitat, ice environment, prey animals and food 

sources for polar bears in our region, including marginal ice zones, shorelines, inland 

areas, leads, and multi-year ice. As you consider receding ice, it is very important to also 

consider the other aspects of the polar bear's habitat---it is wrong to ignore these aspects 

and focus only on how far the ice has receded in recent summers. To do so, is to ignore 

polar bear behavior and use of other habitats. 

The Fish and Wildlife Service acknowledges that the increase of marginal ice and 

corresponding reduction of multi-year ice cover may even be beneficial for ice seals and 

polar bears. 

Polar Bear Populations 

The proposed listing of the polar bear, is not based on polar bear population levels or 

trends, but based on the art of modeling. There is not on enough observational data as 

there should be for a listing. I am concerned that the listing is directed at being used as a 

legal tool to address climate change issues well away from the Arctic, not as a means to 

conserve a species. 

Polar bears are hard to count. For example, the population of the polar bears of the 

Chukchi Sea region is estimated to be 2,000, based "on extrapolation of aerial den 

surveys", but these surveys are not sufficiently reliable to provide an accurate population 
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count. Polar bear population researchers do not appear to take into account migrating 

animals within a population. Scientists have documented bear denning on the pack ice in 

the central Beaufort Sea and those dens, subsequently, drifting with the pack ice. As just 

one example, in the span of several months, a den had drifted from the central Beaufort 

Sea to the Wrangel Island vicinity, offshore of the Russian Far East. The mother and 

cub(s) emerged from the den there and made a beeline back to the Beaufort. What does 

this imply? That bears and dens can drift great distances, and that there may be flux 

between population stocks. 

The accuracy of current population counts is a threshold issue in an ESA listing, and 

should be determined with a greater degree of certainty than that exhibited in the 

proposed rule. 

The proposed rule correlates a decline of multi-year ice cover with a decline in the 

abundance and distribution of ringed seal, a primary prey of the polar bear. Yet the data 

used by USFWS is insufficient to support this key conclusion. For example, right now in 

the Chukchi Sea, the satellites will tell you that our ocean is covered with new, young ice 

and not the multi-year pack. Nevertheless, our hunters are finding abundant and healthy 

ringed-seals as well as polar bears. 

Existing National and International Regulatory Mechanisms 

There are many international mechanisms, laws and commissions set up to conserve and 

protect the polar bear. Some of these have been strengthened in recent years. In moving 

to the Endangered Species Act, let us not ignore those groups and activities and laws such 

as the Marine Mammal Protection Act. The actions that work best in the Arctic are the 

actions that respect and work with the Native people of the Arctic. Please do not skip 

over these means and measures to protect polar bear. These actions and forums, several 

of which have recently been strengthened, have not been thoroughly acknowledged by 

USFWS in its proposed listing. These actions and forums should be better understood in 

Congress, and not glossed in focusing on the Endangered Species Act. The ESA is only 

one means of protecting polar bears, not the only means. 

Federal harvest data show that the take of polar bears by Inupiat people is sustainable. 

Inupiat Eskimos take about 45-50 bears from the Chukchi stock, for example. Yet the 

same stock is suffering from poaching on the Russian side, with catch numbers thought to 

be around 200 per year. [fwe really want to protect the species, let's do something about 

polar bear poaching by other countries. 

Traditional Knowledge and Consultation 

Our knowledge is both traditional and scientific as many Inupiaq people are involved in 

conducting and supporting scientific research on wildlife, sea ice conditions and climate 

change. Our traditional knowledge is built upon thousands of years of experience with 

the polar bear and its habitat. We monitor environmental changes closely because they 

are critical to our subsistence way of life and our culture. I encourage the federal 
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government, and the Congress, to seek and use the breadth of knowledge and year-round, 

first hand traditional knowledge held by the lnupiaq people before taking action to list the 

polar bear as threatened under the ESA. This type of consultation with the most 

knowledgeable and affected Native people of the region is both common sense and 

required by law and federal policy. 

ESA Listing of Polar Bear as a Means to Affect Climate Change Policies 

I believe that a threatened listing for the polar bear will do little to aid the polar bears' 

existence. It will not create more sea ice cover. It will not change their ability to locate 

dens or prey. But it will negatively and disproportionately affect the lives of the people, 

the Inupiat Eskimos, who co-exist with the polar bear in the Alaskan Arctic. Our small, 

isolated communities will run the risk of becoming included in "Critical Habitat", even 

though we have no measurable impact on polar bear. What few playgrounds, gravel pits, 

airstrips, landfills, campsites, hunting areas, and village expansions that we have 

scattered along Alaska's northern arctic coast may be limited by the subjective process 

invoked by the Endangered Species Act. While America sleeps better at night, falsely 

believing they have assisted this iconic species, they will still fly planes, drive cars, and 

power their homes. 

We are very concerned about changes in climate conditions in the Arctic and have more 

reason than others to be aggressive about addressing climate change; however, the proper 

methods to address those issues are to deal with climate change conditions and causes 

directly, not to twist the ESA listing of the polar bear into an action directed at climate 

change. 

Conclnsion 

Madam Chair, the Arctic is a beautiful, and yes, changing environment. It has been the 

home of the Inupiat for thousands of years. We appreciate the effort that you and Senator 

Inhofe have made to hear the concerns from those of us that have the most experience 

with the Arctic's unique climate, which is home to our people and the polar bear. 

Thank you for the opportunity to testify here today. I would be happy to answer any 

questions that you or the members of the Committee may have. 
243 

RESPONSE BY RICHARD GLENN TO AN ADDITIONAL QUESTION

FROM SENATOR BOXER

Question. The Committee has received a statement for Ihere cord from groups representing Canadian Inuit peoples indicating that Ihe U.S. Fish and Wildlife Service 

has failed to sufficienlly consider Inuit Traditional Knowledge of Ihe polar bears 

during Ihe rulemaking process. They also state that USFWS does not consider or 

even examine the polar bear’s abilily to adapt to changing and ice-free conditions. 

Do you agree that the USFWS is relying too much on computer models to determine 

the behavior, movement and overall health of polar bear populations? Could you 

provide some additional comment on this from the Alaska Inupiaq perspective? 

Response. In large part, the Canadian and Alaskan Inuit are in agreement. As 

I spent time in our villages discussing this issue with residents, I was repeatedly 

asked, ‘‘Why doesn’t Fish and Wildlife come to our villages and ask us?’’ Inupiat 

hunters, our experts in the ice and animal sciences, have not been consulted 

throughout this process-specifically the USFWS has not sought our input or expert 

observations. 

The policymaking arm of the USFWS has little regard for input from the Native 

traditional knowledge. USFWS scientists have worked, over time, in places with 

local Native experts in very field-specific expeditions such as at Barter Island and 

Barrow. However, USFWS fail to incorporate traditional knowledge when they take 

their field research and attempt to synthesize it into publications that have farreaching interpretations. 

Further, USFWS substitutes polar bear researchers for ice experts when talking 

about the future of the Arctic Ocean ice environment. 

Senator BOXER. Thank you, sir. Right on the nose. 

Dr. Armstrong, we welcome you. You are a Professor of Marketing at the Wharton School. Welcome. 

STATEMENT OF J. SCOTT ARMSTRONG, PH.D., PROFESSOR OF 

MARKETING, THE WHARTON SCHOOL, UNIVERSITY OF 

PENNSYLVANIA 

Mr. ARMSTRONG. Thank you, Madam Chair, and thank the Committee for hearing me today. 

My name is Scott Armstrong, I am a Professor at the Wharton 

School at the University of Pennsylvania. 

As stated, the primary problem we are looking at today is what 

might happen to polar bears in the future. So I am addressing this 

Committee as an expert on forecasting. I have been working in the 

field for 48 years now. 

Please direct your attention to Exhibit 1. It is also in the report 

at the end. It is an unlabeled exhibit. The dots represent data 

points. As you look at that, assume you had the forecast for the 

rest of the 21st century. Is it going up, down, staying the same, or 

what is happening? I will come back to that later in the talk. 

In the mid–1990’s, I started a project, the Principles of Forecasting Project. The idea was to summarize all of the knowledge 

that we had about forecasting and transform these into scientific 

principles. Here is an example. Be conservative in situations involving uncertainty. The project led to my handbook, ‘‘Principles of 

Forecasting,’’ in which 39 authors and 123 reviewers participated. 

Along with Dr. Kesten Green and Dr. Willie Soon, I examined 

two of the reports we have been talking about today. These are the 

reports by Amstrup and Hunter. We looked at those, because they 

are the ones most closely related to forecasting. We asked, ‘‘Did the 

authors’ procedures follow scientific principles?’’ We made independent ratings, discussed them over followup rounds and reached 

agreement. 

244 

Here is an example: keep the forecast independent of organizational politics. We all rated that as a contravention of the principle. 

Why? Because if you look at the front page of all these reports, 

they say that the purpose of the report is to support the polar bear 

listing decision. 

The reports involve a complex set of assumptions. In effect, they 

made assumptions where they should have made forecasts. The assumptions lacked validity, and we judged the reports to be invalid 

on that basis. 

But we went further. We said, what if all those assumptions 

were true? Did they at least use the proper methods to arrive at 

a polar bear forecast? 

I would like you to look at Exhibit 2. This shows the results of 

our audit. We found that the Amstrup report contravened 41 of the 

principles, the Hunter report contravened 61, and so on down the 

line. What is most important to look at is how many principles did 

they really follow? And it turns out that they properly applied, in 

the case of Amstrup, 17, and in the case of Hunter, 10. 

Now, on a percentage basis, that means they followed 12 percent 

of the relevant principles. I wonder how many occupations there 

are in our Country where you can follow only 12 percent of the recommended policy and procedures? 

The forecasts in those reports rested heavily on unaided judgment. By unaided, expert judgment, I mean unaided by scientific 

principles. Now, consider this. Unaided experts’ forecasts are of no 

value when the situation is complex and uncertain. It is an astounding finding. I will repeat: unaided expert forecasts are of no 

value when the situation is complex and uncertain. I ran across 

this in my long-range forecasting book in 1978. Dr. Tetlock recently 

came out with a massive 20-year study supporting this. His study 

involved over 80,000 forecasts. 

Please look again at the original unlabeled graph. I am now 

going to show you how the administrative report forecast that polar 

bear population would decrease rapidly. The graph relates to icefree days and it comes from one of the Administration reports. 

They forecasted a sharp increase in ice-free days. How is that possible from the data? It is not possible. It only happened because 

they ignored the data. Instead, they relied on climate models. 

The climate models do not provide forecasts. They provide socalled scenarios. Now, let’s examine the graph with labels. The 

filled-in dots that you will see show the data that were used to determine the relationship between ice-free days and the polar bear 

population, 5 years. Now, is it possible to estimate this causal relationship with 5 years of observations? The answer is no. 

The above analysis indicated contraventions of principles such 

as, use all available important data, use the most recent data, use 

simple forecasting methods and be conservative in cases of high uncertainty. 

I would like to end on a very positive note. We know how to approach this problem in a scientific way. 

Senator BOXER. OK, but you have to be positive in just a few seconds. But go ahead. 

Mr. ARMSTRONG. I have six recommendations for approaching 

this in a scientific matter. 

245 

Senator BOXER. Just give one sentence for each one of them, and 

then you have gone over. 

Mr. ARMSTRONG. Use a variety of forecasting methods; generate 

a list of alternative solutions and prepare forecasts; commission 

forecasts by independent teams; promote collaboration among polar 

bear climate experts along with forecasting experts; require forecasts be based on audited methods and don’t tolerate any contraventions; combine all forecasts based on procedures that pass 

the audit. 

Thank you, Madam Chairman. 

[The prepared statement of Mr. Armstrong follows:] 

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Polar Bear Population Forecasts: A Public-Policy Forecasting Audit 

Working Paper Version 44: January 27, 2008 

J. Scott Armstrong, The Wharton School, University of Pennsylvania 

747 Huntsman, Philadelphia, PA 19104, USA. 

armstrong(dlwharton.upenn.edu; jscottarmstrong.com; T 610-622-6480 

Kesten C. Green, Business and Economic Forecasting, Monash University, Vic 3800, Australia. 

Contact: PO Box 10800, Wellington 6143, New Zealand. 

kesten@kestencgreen.com; T +6449763245; F +64 4 976 3250 

Willie Soon, Harvard-Smithsonian Center for Astrophysics, Cambridge MA 02138, USA. 

wsoon@cfa.harvard.edu 

Abstract 

The extinction of polar bears by the end of the 21" century has been predicted and calls have been made to 

list them as a threatened species under the U.S. Endangered Species Act. The decision on whether or not to 

list rests upon forecasts of what will happen to the bears over the 21" Century. 

Scientific research on forecasting, conducted since the 1930s, has led to an extensive set of 

principles-evidence-based procedures-that describe which methods are appropriate under given 

conditions. The principles of forecasting have been published and are easily available. We assessed polar 

bear population forecasts in light of these scientific principles. 

Nine government reports were prepared " ... to Support U.S. Fish and Wildlife Service Polar Bear 

Listing Decision." None of the papers referred to works on scientific forecasting methodology. Of the nine 

papers, two appeared to be the most relevant to the listing decision: A mstrup, Marcot and Douglas (2007), 

which we refer to as AMD; and Hunter et al. (2007), which we refer to as H6 to represent the six authors. 

AMD's and H6's forecasts were each products of complex sets of assumptions. Both incorrectly 

assumed first that General Circulation Models (GCMs) are valid tools for forecasting summer sea ice in the 

regions inhabited by polar bears. In fact, GCMs did not even provide reliable good fits of summer sea ice 

when estimated and run over historical periods. A primary assumption of both AMD and H6 therefore lacks 

support. We nevertheless audited their conditional forecasts of what would happen to the polar bear 

population assuming as they did that the extent of summer sea ice will decrease substantially in the coming 

decades. 

AMD could not be rated against 26 relevant forecasting principles because the paper did not contain 

enough information. In all, AMD contravened 73 of the 90 forecasting principles we were able to rate. In 

fact, they properly applied only 15% ofthe relevant principles. They used two un-validated methods and 

relied on only one polar bear expert to specify variables, relationships, and inputs into their models. The 

same expert then adjusted tbe models until the outputs conformed to his expectations. In effect, the 

forecasts were the opinions of a single expert unaided by forecasting principles. Based on research to-date, 

approaches based on unaided expert opinion are inappropriate for forecasting in situations with high 

complexity and much uncertainty. 

Our audit of the second paper, H6, found that like AMD, the authors' forecasting procedures 

contravened many forecasting principles. For example, they relied heavily on five years of data to forecast 

polar bear populations over the remainder of the 21" Century. They properly applied only 10% of the 

relevant principles. 

In summary, experts' forecasts that are unaided by evidence-based forecasting procedures, should not 

be used for forecasting in this situation. The decision of whether to list polar bears should be based on 

scientific forecasts of their popUlation and forecasts of net benefits from feasible policies arising from 

listing polar bears. We recommend the use ofthe forecasting audits to ensure that the forecasts are properly 

done. 

Key words: adaptation, bias, climate change, decision making, endangered species, expert opinion, 

evaluation, evidence-based principles, expert judgment, extinction, forecasting methods, global warming, 

habitat loss, matbematical models, scientific method, sea ice. 
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Introduction 

Polar bears have been described by some as the "canaries of climate change," and concerns have 

been expressed over the survival of some sub-populations. We assessed the validity of long-term 

forecasts of selected polar bear populations by asking "Are the forecasts derived from accepted 

scientific procedures?" 

We first examined the references in the nine unpublished government reports written to 

support listing polar bears under the Endangered Species Act. Second, we examined the 

forecasting methods employed in two of those nine reports by assessing the procedures described 

in the reports against forecasting principles. We use the term "forecasting principles" to refer to 

guidelines on the selection offorecasting methods. The principles are based on evidence from 

scientific research that has revealed which methods provide the most accurate forecasts for a 

given situation. 

Scientific forecasting procedures 

Scientific research on forecasting has been conducted since the 1930s; important findings from 

the extensive literature on forecasting were first summarized in Armstrong (1978, 1985). 

In the mid-1990s, the Forecasting Principles Project was established with the objective of 

summarizing all useful knowledge about forecasting. The evidence was codified as principles, or 

condition-action statements, to provide guidance on which methods to use under different 

circumstances. The project led to the Principles o/Forecasting handbook (Armstrong 2001). 

These principles were formulated by 40 internationally-recognized experts on forecasting 

methods and were reviewed by 123 leading experts on forecasting methods. The summarizing 

process alone was a four-year effort. We refer to the evidence-based methods as scientific 

forecasting procedures. 

The strongest form of evidence is that which is derived from empirical studies that compare 

the performance of alternative methods. Ideally, "performance" is assessed by the ability of the 

selected method to provide useful ex ante forecasts. The weakest form of evidence is based on 

received wisdom about proper procedures. However, some of these principles seem self-evident 

(e.g., "Provide complete, simple and clear explanations of methods") and, as long as they were 

unchallenged by the available evidence, they were included. Some important principles are 

counter-intuitive: as a consequence, forecasts derived in ignorance of forecasting principles have 

no scientific st(lnding. 

The forecasting principles are available on forecastingprinciples.com, a site sponsored by the 

International Institute of Forecasters. The site claims to provide "all useful knowledge about 

forecasting" and asks visitors to submit any missing evidence. The Forecasting Principles site has 

been at the top of the list of sites in Internet searches for "forecasting" for many years. 

A summary of the principles, currently numbering 140, is provided as a checklist in the 

Forecasting Audit software available on the site. The strength of evidence is summarized briefly 

for each principle, and details are provided in Armstrong (200 I) as well as in papers posted on the 

site. 

General Assessment of Long-Term Polar Bear Population Forecasts 

We examined the references cited in the nine unpublished USGS Administrative Reports posted 

on the Internet at http://usgs.gov/newsroom/special/polar bears/. They were: Amstrup et a1. 

(2007); Bergen et al (2007); DeWeaver (2007); Durner et aI. (2007); Hunter et a!. (2007); Obbard 

et al. (2007); Regehr et al. (2007); Rode et a1. (2007); and Stirling et aI. (2007). The USGS 

Administrative Reports included 444 unique references in total. We were unable to find any 

references that related to the validation of forecasting methods. 
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Forecasting Audit of Two Key Papers Prepared to Support an Endangered Listing 

We audited the forecasting procedures used in what we judged to be the two most crucial of the 

nine papers commissioned by the U. S. Department of the Interior to support the petition to 

classify polar bears as an endangered species. 

The evidence-based principles upon which our audit was based were derived from many 

areas, including management, psychology, economics, politics, and weather, with the intention 

that they would apply to any type of forecasting problem. Some reviewers of our research have 

suggested that the principles do not apply to the physical sciences. We have asked reviewers for 

evidence to support that viewpoint, but have been unable to obtain usefut'responses. Readers can 

examine the principles and form their own judgments on this issue. For example, might one argue 

that the principle, "Ensure that information is reliable and that measurement error is low," does 

not apply when forecasting climate? 

In conducting the audits, each of the three authors read the paper and independently rated the 

forecasting procedures described in it by using the Forecasting Audit software at 

forecastingprinciples.com. The rating scale runs from -2 to +2, with the former indicating the 

procedures contravene the principle and the latter signifying that it is properly observed. After the 

initial round of ratings, we examined differences in our ratings in an attempt to reach consensus. 

To the extent that we had difficulty in reaching consensus, we moved ratings toward "0". 

Clearly forecasting audit ratings involve some subjectivity. Despite this, for each of the 

papers our ratings after the first round were in substantial agreement. Furthermore, we had little 

difficulty in reaching consensus by the third round. 

In some cases, the two papers did not provide sufficient details to allow for ratings. To 

resolve this issue, we contacted the authors ofthe two papers and requested further infonnation. 

In addition, we asked them to review our ratings and to tell us whether they disagreed with any of 

them. In their reply, they refused to provide any responses to our requests. (See Note 2 at the end 

of our paper.) 

At various points in our audit report, we cite studies that provide relevant evidence. To ensure 

that we cited them properly, we sent a copy of our paper to all authors that we cited in a 

substantive manner in December 2007 asking them to inform us if we had not properly referred to 

their findings. None of the authors objected to the way that we summarized their research. We 

also invited them to review the paper. 

Audit ofAMD 

We audited Amstrup, Marcot, and Douglas (2007), which we will refer to as AMD. That paper 

made forecasts of polar bear populations for 45, 75, and 100 years from the year 2000. 

AMD implicitly made many assumptions: (I) global warming will occur; (2) this will both 

reduce the extent of and thin the summer sea ice; (3) polar bears will obtain less food by hunting 

from the sea ice platform than they do now; (4) they will not obtain adequate supplementary food 

using other means or from other sources; (5) the bear population will decline; (6) the designation 

of polar bears as an endangered species will solve the problem and will not have serious 

detrimental effects; and (7) there are no other policies that would produce better outcomes than 

those based on an endangered species classification. 

AMD assumed that the general circulation models (GCMs) provide scientifically valid 

forecasts of global temperature and the extent and thickness of sea ice. They stated (AMD 2007, 

p. 2 and Fig 2 p. 83): "Our future forecasts are based largely on information derived from general 

circulation model (GCM) projections of the extent and spatiotemporal distribution of sea ice." 

That is, their forecasts are conditional on long-term global warming forecasts leading to a 
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dramatic reduction in Arctic sea ice during maximum melt-back periods in spring, late summer 

and fall. 

Green and Armstrong (2007) examined long-term climate forecasting efforts and were unable 

to find a single forecast of global warming that was based on scientific methods. The climate 

modelers' procedures did not follow many forecasting principles and some of the contraventions 

were critical. This formal auditing result is consistent with earlier cautions. For example, Soon et 

al. (200 I) found that the current generation of GeMs is unable to meaningfully calculate the 

climatic effects of added atmospheric carbon dioxide given the severe limitations from both the 

uncertainties and unknowns in representing all relevant physical processes. 

The fact that the AMD forecasts rest on the GeM forecasts and that these forecasts lack a 

scientific basis puts their assumptions into question. Indeed, some climate modelers state that the 

GeMs do not provide forecasts. Furthermore, the GeM models have not been designed for 

analysis at a regional level in the way they are used by AMD and H6 (see the discussion of 

Principle 9.2 in H6 below). 

We audited AMD's polar bear population forecasting procedures to assess whether they 

would produce valid forecasts assuming valid climate and sea ice forecasts were available as 

inputs. Of the 140 forecasting principles, we agreed that 24 were irrelevant to the forecasting 

problem. We then examined principles on which our ratings differed. After two rounds of 

consultation (i.e., the process required three rounds in all), we were able to reach consensus on all 

116 relevant principles. We found that AMD's procedures contravened 41 principles (Table 1) 

and apparently contravened 32 principles (Table 2). We were unable to rate 26 relevant principles 

(Table 3) due to a lack of information. 
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Table 1: Principles contravened in AMD 

Setting Objectives: 

1.2 Prior to forecasting, agree on actions to take 

assuming different possible forecasts. 

1.3 Make sure forecasts are independent of politics. 

1.4 Consider whether the events or series can be 

forecasted. 

1.5 Obtain decision makers' agreement on 

methods. 

Identify Data Sources: 

3.5 Obtain information from similar (analogous) 

series or cases. Such information may help 

to estimate trends. 

Collecting Data: 

4.2 Ensure that information is reliable and that 

measurement error is low. 

Selecting Methods: 

6.1 List all the important selection criteria before 

evaluating methods. 

6.2 Ask unbiased experts to rate potential methods. 

6.7 Match the forecasting method(s) to the situation 

6.8 Compare track records of various forecasting 

methods. 

6.10 Examine the value of alternative forecasting 

methods. 

Implementing Methods: General 

7.3 Be conservative in situations of high uncertainty 

or instability. 

Implementing Judgmental Methods: 

8.1 Pretest the questions you intend to use to elicit 

judgmental forecasts. 

8.2 Frame questions in alternative ways. 

8.5 Obtain forecasts from heterogeneous experts. 

8.7 Obtain forecasts from enough respondents. 

8.8 Obtain multiple forecasts of an event from each 

expert. 

Implementing Quantitative Methods: 

9.1 Tailor the forecasting model to the horizon. 

9.3 Do not use "fit" to develop the model. 

9.5 Update models frequently. 

Implementing Methods: Quantitative Models with 

Explanatory Van'ables: 

10.6 Prepare forecasts for at least two alternative 

environments. 

10.8 Apply the same principles to forecasts of 

explanatory variables. 

10.9 Shrink the forecasts of change if there is high 

uncertainty for predictions of the explanatory 

variables. 

Combining Forecasts: 

12.1 Combine forecasts from approaches that 

differ. 

12.2 Use many approaches (or forecasters), 

preferably at least five. 

12.3 Use formal procedures to combine forecasts. 

12.4 Start with equal weights. 

Evaluating Methods: 

13.6 Describe potential biases of forecasters. 

13.10 Test assumptions for validity. 

13.32 Conduct explicit cost-benefit analyses. 

Assessing Uncertainty: 

14.1 Estimate prediction intervals (Pis). 

14.2 Use objective procedures to estimate explicit 

prediction intervals. 

14.3 Develop prediction intervals by using empirical 

estimates based on realistic representations 

of forecasting situations. 

14.5 Ensure consistency over the forecast horizon. 

14.7 When assessing Pis, list possible outcomes 

and assess their likelihoods. 

14.8 Obtain good feedback about forecast accuracy 

and the reasons why errors occurred. 

14.9 Combine prediction intervals from alternative 

forecasting methods. 

14.10 Use safety factors to adjust for 

overconfidence in the Pis. 

14.11 Conduct experiments to evaluate forecasts. 

14.13 Incorporate the uncertainty associated with 

the prediction of the explanatory variables in 

the prediction intervals. 

14.14 Ask for a judgmental likelihood that a 

forecast will fall within a pre-defined 

minimum-maximum interval 
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Table 2: Principles apparently contravened in AMD 

Structuring the problem: 

2.1 Identify possible outcomes prior to making 

forecasts. 

2.7 Decompose time series by level and trend. 

Identify Data Sources: 

3.2 Ensure that the data match the forecasting 

situation. 

3.3 Avoid biased data sources. 

3.4 Use diverse sources of data. 

Collecting Data: 

4.1 Use unbiased and systematic procedures to 

collect data. 

4.3 Ensure that the information is valid. 

Selecting Methods: 

6.4 Use quantitative methods rather than qualitative 

methods. 

6.9 Assess acceptability and understandability of 

methods to users. 

Implementing Methods: General 

7.1 Keep forecasting methods simple. 

Implementing Quantitative methods: 

9.2 Match the model to the underlying phenomena. 

9.4 Weight the most relevant data more heavily. 

Implementing Methods: Quantitative Models with 

Explanatory Variables: 

10.1 Rely on theory and domain expertise to select 

causal (or explanatory) variables. 

10.2 Use all important variables. 

10.5 Use different types of data to measure a 

relationship. 

Combining Forecasts: 

12.5 Use trimmed means, medians, or modes 

12.7 Use domain knowledge to vary weights on 

component forecasts. 

12.8 Combine forecasts when there is uncertainty 

about which method is best. 

12.9 Combine forecasts when you are uncertain 

about the situation. 

12.10 Combine forecasts when it is important to 

avoid large errors. 

Evaluating Methods: 

13.1 Compare reasonable methods. 

13.2 Use objective tests of assumptions. 

13.7 Assess the reliability and validity of the data. 

13.8 Provide easy access to the data. 

13.17 Examine all important criteria. 

13.18 Specify criteria for evaluating methods prior 

to analyzing data. 

13.27 Use ex post error measures to evaluate the 

effects of policy variables. 

Assessing Uncertainty: 

14.6 Describe reasons why the forecasts might be 

wrong. 

Presenting Forecasts: 

15.1 Present forecasts and supporting data in a 

simple and understandable form. 

15.4 Present prediction intervals. 

Leaming That Will Improve Forecasting 

Procedures: 

16.2 Seek feedback about forecasts. 

16.3 Establish a formal review process for 

forecasting methods. 
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Table 3: Principles not rated 

due to lack of information in AMD 

Structuring the problem: 

2.5 Structure problems to deal with important 

interactions among causal variables. 

Collecting data: 

4.4 Obtain all of the important data 

4.5 Avoid the collection of irrelevant data 

Preparing Data: 

5.1 Clean the data. 

5.2 Use transformations as required by 

expectations. 

5.3 Adjust intermittent series. 

5.4 Adjust for unsystematic past events. 

5.5 Adjust for systematic events. 

5.6 Use multiplicative seasonal factors for trended 

series when you can obtain good estimates 

for seasonal factors. 

5.7 Damp seasonal factors for uncertainty 

Selecting Methods: 

6.6 Select simple methods unless empirical 

evidence calls for a more complex approach. 

Implementing Methods: General 

7.2 The forecasting method should provide a 

realistic representation of the situation 

Implementing Judgmental Methods: 

8.4 Provide numerical scales with several 

categories for experts' answers. 

Implementing Methods: Quantitative Models with 

Explanatory Variables: 

10.3 Rely on theory and domain expertise when 

specifying directions of relationships. 

10.4 Use theory and domain expertise to estimate 

or limit the magnitude of relationships. 

Integrating Judgmental and Quantitative Methods: 

11.1 Use structured procedures to integrate 

judgmental and quantitative methods. 

11.2 Use structured judgment as inputs to 

quantitative models. 

11.3 Use pre-specified domain knowledge in 

selecting, weighting, and modifying 

quantitative methods. 

11.4 Limit subjective adjustments of quantitative 

forecasts. 

Evaluating Methods:. 

13.4 Describe conditions associated with the 

forecasting problem. 

13.5 Tailor the analysis to the decision. 

13.9 Provide full disclosure of methods. 

13.11 Test the client's understanding of the 

methods. 

13.19 Assess face validity. 

Assessing Uncertainty: 

14.12 Do not assess uncertainty in a traditional 

(unstructured) group meeting. 

Leaming That Will Improve Forecasting 

Procedures: 

16.4 Establish a fomnal review process to ensure 

that forecasts are used properly. 

We describe some ofthe more serious problems with the AMD forecasts below: 

Match the forecasting method(s) to the situation (Principle 6.7) 

The forecasts in AMD rely on the opinions of an expert who is knowledgeable in the domain. The 

opinions were transformed into a complex set offormulae, but were unaided by evidence-based 

forecasting principles. 

Some studies (e.g., Tetlock 2005) suggest that judgmental forecasts by researchers who 

ignore accepted forecasting principles have little value in complex and uncertain situations. This 
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apparently applies whether the opinions are expressed in words, spreadsheets, or mathematical 

models. It also applies regardless of how much scientific information is used by the experts. 

Among the reasons for this are: 

a) Complexity: Individuals cannot assess complex relationships through unaided 

observations. 

b) Coincidence: Individuals confuse correlation with causation. 

c) Feedback: Individuals making judgmental predictions typically do not 

receive unambiguous feedback they can use to improve their 

forecasting. 

d) Bias: Individuals have difficulty in obtaining or using evidence that 

contradicts their initial beliefs. This problem is especially serious 

among individuals who view themselves as experts. 

Despite the lack of validity of unaided forecasts by experts, many public policy decisions are 

based on such forecasts. Research on persuasion has shown that people have substantial faith in 

the value of such forecasts and that faith increases when experts agree with one another. Although 

they may seem convincing at the time, expert forecasts can, a few years later, serve as important 

cautionary tales. Cerf and Navasky's (1998) book contains 310 pages of examples, such as Fermi 

Award-winning scientist John von Neumann's 1956 prediction that "A few decades hence, 

energy may be free". Examples of expert climate forecasts that turned out to be wrong are easy to 

find, such as UC Davis ecologist Kenneth Watt's prediction in a speech at Swarthmore College 

on Earth Day, April 22, 1970 that "If present trends continue, the world will be about four 

degrees colder in 1990, but eleven degrees colder in the year 2000. This is about twice what it 

would take to put us into an ice age." 

Are such examples merely a matter of selective perception? The first author's review of 

empirical research on this problem led him to develop the "Seer-sucker Theory," which can be 

stated as "No matter how much evidence exists that seers do not exist, seers will find suckers" 

(Armstrong 1980). The amount of expertise does not matter beyond a basic minimum level. There 

are exceptions to the Seer-sucker Theory: experts can improve their forecasting when they 

receive well-summarized feedback on the accuracy of their forecasts and reasons why their 

forecasts were or were not accurate. This situation applies for short-term (up to five day) weather 

forecasts, but we are not aware of any such regime for long-term global climate forecasting. Even 

if there were such a regime, the feedback would trickle in over many years before it became 

useful for improving forecasting. Moreover, experts typically resist negative feedback and prefer 

to provide excuses for inaccurate forecasts (Tetlock 2005). 

Research since 1980 has added support to the Seer-sucker Theory. In particular, Tetlock 

(2005) recruited 284 people whose professions included "commenting or offering advice on 

political and economic trends." He asked them to forecast the probability that various situations 

would or would not occur, picking areas (geographic and substantive) within and outside their 

areas of expertise. By 2003, he had accumulated over 82,000 forecasts. The experts barely if at all 

outperformed non-experts and neither group did well against simple rules. 

Many comparative empirical studies have concluded that judgmental forecasting by experts is 

the least accurate of the methods available to make forecasts. For example, Ascher (1978, p. 200), 

in his analysis of long-term forecasts of electricity consumption, found that that was the case. 

AMD also implicitly forecast-that is, they used their judgment unaided by scientific 

forecasting procedures-that a policy to classify polar bears as a threatened species would save 

the bears from future possible extinction. AMD did not include forecasts of the costs, planned and 

unintended, of such a policy. 
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Be conservative in situations of high uncertainty or instability (Principle 7.3) 

Forecasts should be conservative when a situation is unstable, complex or uncertain. Being 

conservative means moving forecasts towards "no change" or, in cases that exhibit a well 

established long-term trend and where there is no reason to expect the trend to change, being 

conservative means moving forecasts toward the trend line. A long-term trend is one that has 

been evident over a period that is much longer than the period being forecast. Conservatism is a 

fundamental principle in forecasting. 

The interaction between polar bears and their environment in the Arctic is complex and there 

is much uncertainty. For example, AMD associated warm temperatures with lower polar bear 

survival rates, yet cold temperatures have also been associated with similar outcomes, as this 

quote illustrates: "Abnormally heavy ice covered much of the eastern Beaufort Sea during the 

winter of 1973-1974. This resulted in major declines in numbers and productivity of polar bears 

and ringed seals in 1975" (Amstrup et al. 1986, p. 249). Stirling (2002, p. 68 and 72) further 

expanded on the complexity of polar bear-sea-ice interactions: 

"In the eastern Beaufort Sea, in years during and following heavy ice conditions in 

spring, we found a marked reduction in production of ringed seal pups and consequently 

in the natality of polar bears ... The effect appeared to last for about three years, after 

which productivity of both seals and bears increased again. These clear and major 

reductions in productivity of ringed seals in relation to ice conditions occurred at decadalscale intervals in the mid-1970s and 1980s ... and, on the basis of less complete data, 

probably in the mid-1960s as well ... Recent analyses of ice anomalies in the Beaufort 

Sea have now also confirmed the existence of an approximately 10-year cycle in the 

region '" that is roughly in phase with a similar decadal-scale oscillation in the runoff 

from the Mackenzie River ... However, or whether, these regional-scale changes in 

ecological conditions have affected the reproduction and survival of young ringed seals 

and polar bears through the 1990s is not clear." 

Regional variability adds to uncertainty. For example, Antarctic ice mass extent has been growing 

while sea and air temperatures have been increasing (e.g. Zhang 2007). At the same time, depthaveraged oceanic temperatures around the Southeastern Bering Sea (Richter-Menge et at. 2007) 

have been cooling in 2006. Despite the warming of local air temperature by 1.6±0.6°C, there was 

no sharp decline in the area over the continental shelf of the Canadian Beaufort Sea that was icecovered for the 36 years from 1968 to 2003 (Melling et al. 2005). 

Despite the uncertainty, instability, and complexity of the situation, AMD made predictions 

based on assumptions that we view as questionable. They also used little historical data. 

Obtain forecasts from heterogeneous experts (Principle 8.5) 

AMD's polar bear population forecasts were the product of a single expert. Experts vary in their 

knowledge and the way they approach problems, and bringing more information and different 

approaches to bear on a forecasting problem improves accuracy. When sufficient information is 

not available, forecasting can not be assumed valid. Also, in situations where experts might be 

biased, it is important to obtain forecasts from experts with different biases. Failing to follow this 

principle increases the risk that the forecasts obtained will be extreme when, in this situation, 

forecasts should be conservative (see Principle 7.3, above). 

Use all important variables (Principle 10.2) 

Dyck et al. (2007) recently noted that scenarios of polar bear decline grossly oversimplity the 

complex ecological relationships of the situation. In particular, AMD did not adequately consider 

the adaptability of polar bears. They mentioned the fact that polar bears evolved trom brown 
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bears 250,000 years ago (p. 2) but they appear to have ignored the fact that polar bears probably 

experienced much warmer conditions in the Arctic over that extended time period, with periods 

when sea ice habitat was less than those expected over the next century according to the GeM 

projections AMD have used. Several studies (Hamilton and Brigham-Grette 1991; BrighamGrette and Hopkins 1995; Norgaard-Pedersen et al. 2007) have documented the dramatic 

reduction of sea ice in both the Northwest Alaskan coast and Northwest Greenland part of the 

Arctic Ocean during the very warm Interglacial of marine isotope stage 5e ca. 130,000 to 120,000 

years ago. Brigham-Grette and Hopkins (1995, p. 159) noted that the "winter sea-ice limit was 

north of Bering Strait, at least 800 km north of its present position, and the Bering Sea was 

perennially ice-free" and that "[the more saline) Atlantic water may have been present on the 

shallow Beaufort Shelf, suggesting that the Arctic Ocean was not stratified and the Arctic sea-ice 

cover was not perennial for some period." On the face ofit, the nature and extent of polar bear 

adaptability seem crucial to any forecasts that assume dramatic changes in the bears' 

environment. 

AMD's forecasts were commissioned to inform public policy decisions, but they do not 

explicitly forecast the effects of different policies. For example, in the event of the polar bear 

popUlation coming under stress due to inadequate summer food, what would be the costs and 

effects of protecting areas by prohibiting marine and land-based activities at critical times? In 

addition, what would be the costs and benefits of a smaller but stable population of polar bears in 

some polar sub-regions? And how would the net costs of such alternative policies compare with 

the net costs of listing polar bears? 

Make sure forecasts are independent of politics (Principle 1.3) 

By politics, we mean any type of organizational biases or pressures. While different stakeholders 

may prefer particular forecasts, ifforecasters are influenced by such considerations, forecast 

accuracy will suffer. The Executive Summary documentl noted that "the Secretary of the Interior 

asked the U.S. Geological Survey (USGS) to generate new scientific data, models, and 

interpretations on polar bears and their sea ice habitats, to support the "U.S. Fish and Wildlife 

service polar bear listing decision" (http://www.doLgov/news/06 News Releases/06I227.html). 

The authors ofthe AMD administrative report are all employees of the U.S. government agencies 

that are trying to support this decision. 

Audit of Hunter et at (H6) 

Hunter et al. (2007), which we refer to here as H6, forecasted polar bear numbers in the southern 

Beaufort Sea for 45,75, and 100 years from 2000. To do so, they implicitly assumed the 

following: (I) global warming will occur; (2) frequent "bad years" will be a consequence of 

global warming; (3) polar bears will not adapt to "bad years"; (4) the popUlation of polar bears 

will decline dramatically from negative effects of "bad years" alone; (5) the designation of polar 

bears as an endangered species will solve the problem and will not have serious detrimental 

effects; and (6) there are no other policies that would produce better outcomes than those based 

on listing polar bears under the Endangered Species Act. 

Like AMD, H6 accepted GeM forecasts of global warming and reduced extent and thickness 

of sea ice. They stated that "we extracted forecasts of the availability of sea ice for polar bears in 

the SB [southern Beaufort Sea) region, using monthly forecasts of sea ice concentrations from 10 

!pee Fourth Assessment Report (AR4) fully-coupled general circulation models" (p. II ofH6). 

That is, their forecasts are conditional on long-term forecasts of global warming producing 

dramatic effects. However, Green and Armstrong (2007) were unable to find any forecasts made 

1 http://www.usgs.gov/newsroom/specialipo\ar bears/docs/executive summary. pdf 
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in accordance with scientific forecasting principles that support the hypothesized predictions of 

global wanning throughout the 21 st Century. 

We nevertheless audited H6's polar bear population forecasting procedures to assess 

whether they would produce valid forecasts if valid climate and sea ice forecasts were available 

as inputs. 

Each of the authors read H6 and independently rated the forecasting procedures described in 

it using the Forecasting Audit software at forecastingprinciples.com. Of the 140 forecasting 

principles, we agreed that 35 were irrelevant to the forecasting problem. We then examined 

principles on which our ratings differed, and after three rounds of consultation we were able to 

reach consensus on all 105 relevant principles. To the extent that we had difficulty in reaching 

consensus, we moved ratings toward "0". 

We found that H6's procedures could clearly be improved for 6) principles (Appendix Table 

A) and probably be improved for an additional 19 principles (Appendix Table B). We were 

unable to rate 15 relevant principles (Appendix Table C) due to a lack of infonnation. 

Many of the contraventions in H6 were similar to those in AMD and we provide the H6 audit 

details in the appendix. Here are some examples of contraventions, some of which are, on their 

own, raise serious questions about the value of the H6 forecasts: 

Decisions, actions, and biases (Principles 1.1 1.3) 

The H6 authors did not describe alternative decisions that might be taken (1.1), nor did they 

propose relationships between possible forecasts and alternative decisions (1.2). For example, 

what decision would be implied by a forecast that bear numbers will increase to the point where 

they become a threat to existing human settlements? These problems relate to the biased manner 

in which the problem was stated: "USGS science strategy to support U.S. Fish and Wildlife 

Service polar bear listing decision" (1.3). Research is often prone to bias, sometimes due to 

unknown preferences or interests, but it is nevertheless important to try to avoid it, and it is 

clearly improper to undertake a research project on the understanding that there is a desired 

finding. 

Ensure that information is reliable and that measurement error is low (Principle 4.2) 

Long-tenn forecasts require enonnous amounts of valid and reliable data. Annstrong (1985, p. 

166) refers to two rules of thumb for how much data are needed for extrapolating h years ahead. 

One calls for 4hV, years of historical data and the other calls for h years. These rules imply that H6 

should have based any extrapolations on 40 to 100 years of historical data. 

H6 relies heavily on five years of data with unknown measurement errors. Furthennore, did 

the capture data on which they rely provide representative samples of bears in the southern 

Beaufort Sea given the vast area involved and difficulties in spotting and capturing the bears? 

Bears wander over long distances and do not respect administrative boundaries (Amstrup et at. 

2004). The validity ofthe data is likely to be compromised further by imposing a speculative 

demographic model on the raw capture-recapture data (Amstrup et at. 200 I; Regehr et at. 2006). 

Be conservative in situations of high uncertainty or instability (Principle 7.3) 

The situation regarding polar bears in the southern Beaufort Sea is complex and there is much 

uncertainty. For example, on the basis of five years of data, H6 associated warm temperatures 

with lower polar bear survival rates, yet as noted earlier, cold temperatures have also been 

associated with similar outcomes: "Abnormally heavy ice covered much of the eastern Beaufort 

Sea during the winter of 1973-1974. This resulted in major declines in numbers and productivity 

of polar bears and ringed seals in 1975" (Amstrup et at. 1986, p. 249). 
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82737.078

As noted above, regional changes add to uncertainty, noting the Antarctic ice extent has been 

growing at the same time that sea and air temperatures have been increasing (e.g. Zhang 2007) 

while depth averaged oceanic temperatures around the southeastern Bering Sea have been 

undergoing relative cooling in 2006 (Richter-Menge et aJ. 2007). Despite the warming of local air 

temperature by 1.6±0.6°C, there was no sharp decline in the area over the continental shelf of the 

Canadian Beaufort Sea that was covered in ice for the 36 years from 1968 to 2003 (Melling et al. 

2005). 

Given all of the uncertainties, the H6 forecasts did not strike us as being conservative. 

Tailor the forecasting model to the horizon (Principle 9.1) 

When forecasting over the long term, as in H6, forecasting models should be based on long-term 

trends. However, the H6 authors built models based entirely on estimates derived from only five 

years of recent data. 

Update frequently (Principle 9.5) 

H6 did not include the most recent year, 2006, when estimating their model. From the 

supplementary information provided in Figure 3 of Regehr et al. (2007), one finds that the 

number ofice-free days for the 2006 season was about 105: close to the mean of the "good" ice 

years. 

The latest "Alaska Marine Mammal Stock Assessment, 2006" report by Angliss and Outlaw 

(2007, p. 218), states that 

"The Southern Beaufort Sea [polar bear] Stock is not classified as 'depleted' under the 

MMPA or listed as 'threatened' or 'endangered' under terms of the Endangered Species 

Act. This stock is assumed to be within optimum sustainable population levels." 

Use all important variables (Principle 10.2) 

With causal models, it is important to incorporate policy variables if they might vary or if the 

purpose is to decide what policy to implement. H6 did not include policy variables such as 

seasonal protection of bears' critical habitat, or changes to hunting rules. 

Other variables should also be included, such as migration, snow, and wind conditions. For 

example Holloway and Sou (2002), Ogi and Wallace (2007), and Nghiem et al. (2007) suggested 

that large-scale atmospheric winds and related patterns play an important role in causing - in 

some situations with significant time delays - both the decline in extent and thinning of Arctic sea 

ice; those effects were not correctly included in the GCM forecasts of sea ice (and hence the 

quality of polar bear habitat). 

In addition, Dyck et al. (2007) recently noted that future scenarios of polar bear decline 

oversimplify the complex ecological relationships of the situation. This is why the extent and 

kind of polar bear adaptability is crucial to any forecasts that assume dramatic changes in the 

bears' environment. 

Use different types of data to measure a relationship (Principle 10.5) 

This principle is important when there is uncertainty about the relationships between causal 

variables (such as ice extent) and the event being forecast (polar bear population) and when large 

changes are expected in the causal variables. In the case of the latter condition, H6 accepted the 

GCM model predictions oflarge declines in summer ice throughout the 21" century, so their 

forecasts were sensitive to their estimate the quantitative effect of ice extent on polar bear 

populations. Yet H6 base their estimate of this important relationship on only five years of data 
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with a limited range of climatic-ecological responses sampled. They might, for example, have 

independently estimated the magnitude ofthe relationship by obtaining estimates of polar bear 

populations during much warmer and much colder periods in the past. The supplementary 

information from Figure 3 of Regehr et al. (2007) shows that 1987, 1993 and 1998 were 

exceptional seasons with the number of ice-free days longer than 150 days (Le., substantially 

above the 135 ice-free days documented for 2004-2005) in the southern Beaufort sea, yet there 

were no apparent negative impacts on the polar bear population and wellbeing - see for example, 

Amstrup et al. 2001). 

Match the model to the underlying phenomena (Principle 9.2) 

It is important for the readers to know what is meant by "Southern Beaufort Sea" (SB) in the H6 

report because of the poor spatial resolution of the GCMs. H6 states: "Because GCMs do not 

provide suitable forecasts for areas as small as the SB, we used sea ice concentration for a larger 

area composed of 5 IUCN polar bear management units (Aars et al. 2006) with ice dynamics 

similar to the SB management unit (Barents Sea, Beaufort Sea, Chukchi Sea, Kara Sea and 

Laptev Sea; see Rigor and Wallace 2004, Durner et a!. 2007). We assumed that the general trend 

in sea ice availability in these 5 units was representative of the general trend in the Southern 

Beaufort region." (p. 12). Given the unique ecological, geographical, meteorological, and 

climatological conditions in each of the five circumpolar seas, we did not find this assumption to 

be convincing. 

When assessing prediction intervals (PIs), list possible outcomes and assess their likelihoods 

(Principle 14.7) 

To assess meaningful PIs, it helps to think of diverse possible outcomes. The H6 authors did not 

appear to consider, for example, the possibility that polar bears might adapt to terrestrial life over 

summer months by finding alternative food sources (such as is the case in the Southern Hudson 

Bay populations, or elsewhere; see references in Stempniewicz 2006; Dyck and Romberg 2007) 

or by successfully congregating in smaller or localized ice-hunting areas. Consideration of these 

and other possible adaptations and outcomes would have likely led the H6 authors to be less 

confident (provide wider prediction intervals) about a bad outcome for bears. Extending this 

exercise to the forecasts of climate and summer ice extent would have further widened the range 

of other outcomes. 

Summary and conclusions 

We examined the nine administrative reports that were commissioned by the USGS with the 

stated purpose of supporting the listing of polar bears under the Endangered Species Act. Since 

the current population of bears is not at a level that causes concern, the case for listing depends 

upon forecasts of serious declines in bear numbers in decades to come. 

We found that the two reports most relevant to the listing decision made some questionable 

assumptions. Even if these assumptions had been valid, the bear population forecasting 

procedures contravened many important forecasting principles. Table 4 summarizes our audits: 

Table 4: Summary ratings from the forecasting audits 

Principles AMD H6 

Contravened 41 61 

Apparently contravened 32 19 

Not auditable 26 15 

Properly applied 17 10 
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To provide credible scientific forecasts, forecasting procedures should properly apply all 

evidence-based principles. In other words, there should be no contraventions. 

Decision makers and the public should expect to see scientific forecasts of both the polar bear 

population and the net benefits from feasible policies before any decision is made on whether to 

list polar bears as threatened or endangered. We recommend that important forecasting efforts 

such as this should observe all relevant principles and that their procedures be audited to ensure 

that they do so. 

Appendix 

Table A: Principles contravened in H6 

Setting Objectives: 

1.3 Make sure forecasts are independent of politics. 

1.4 Consider whether the events or series can be 

forecasted. 

Structuring the problem: 

2.6 Structure problems that involve causal chains. 

Identify Data Sources: 

3.4 Use diverse sources of data. 

3.5 Obtain information from similar (analogous) 

series or cases. Such information may help 

to estimate trends. 

Collecting Data: 

4.4 Obtain all of the important data 

Preparing Data: 

5.2 Use transformations as required by 

expectations. 

5.4 Adjust for unsystematic past events. 

5.5 Adjust for systematic events. 

Selecting Methods: 

6.1 List all the important selection criteria before 

evaluating methods. 

6.2 Ask unbiased experts to rate potential methods. 

6.6 Select simple methods unless empirical 

evidence calls for a more complex 

approach. 

6.7 Match the forecasting method(s) to the 

situation. 

6.8 Compare track records of various forecasting 

methods. 

6.10 Examine the value of alternative forecasting 

methods. 

Implementing Methods: General 

7.1 Keep forecasting methods simple. 

7.2 The forecasting method should provide a 

realistic representation of the situation. 

7.3 Be conservative in situations of high uncertainty 

or instability. 

7.4 Do not forecast cycles. 

Implementing Quantitative Methods: 

9.1 Tailor the forecasting model to the horizon. 

9.2 Match the model to the underlying phenomena. 

9.3 Do not use "fit' to develop the model. 

9.5 Update models frequently. 

Implementing Methods: Quantitative Models with 

Explanatory Variables: 

10.2 Use all important variables. 

10.5 Use different types of data to measure a 

relationship. 

10.7 Forecast for alternate interventions. 

10.9 Shrink the forecasts of change if there is high 

uncertainty for predictions of the explanatory 

variables. 

Integrating Judgmental and Quantitative Methods: 

11.1 Use structured procedures to integrate 

judgmental and quantitative methods. 

11.2 Use structured judgment as inputs to 

quantitative models. 

11.3 Use pre-specified domain knowledge in 

selecting, weighting, and modifying 

quantitative methods. 
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Combining Forecasts: 

12.1 Combine forecasts from approaches that 

differ. 

12.2 Use many approaches (or forecasters), 

preferably at least five. 

12.3 Use formal procedures to combine forecasts. 

12.8 Combine forecasts when there is uncertainty 

about which method is best. 

12.9 Combine forecasts when you are uncertain 

about the situation. 

12.10 Combine forecasts when it is important to 

avoid large errors. 

Evaluating Methods: 

13.1 Compare reasonable methods. 

13.2 Use objective tests of assumptions. 

13.3 Design test situations to match the forecasting 

problem. 

13.5 Tailor the analysis to the decision. 

13.6 Describe potential biases of forecasters. 

13.7 Assess the reliability and validity of the data. 

13.8 Provide easy access to the data. 

13.10 Test assumptions for validity. 

13.12 Use direct replications of evaluations to 

identify mistakes. 

13.13 Replicate forecast evaluations to assess their 

reliability. 

13.16 Compare forecasts generated by different 

methods. 

13.17 Examine all important criteria. 

13.18 Specify criteria for evaluating methods prior 

to analyzing data. 

13.26 Use out-of-sample (ex ante) error measures. 

13.27 Use ex post error measures to evaluate the 

effects of policy variables. 

13.31 Base comparisons of methods on large 

samples of forecasts. 

Assessing Uncertainty: 

14.3 Develop prediction intervals by using empirical 

estimates based on realistic representations 

of forecasting situations. 

14.5 Ensure consistency over the forecast horizon. 

14.9 Combine prediction intervals from alternative 

forecasting methods. 

14.10 Use safety factors to adjust for 

overconfidence in the Pis. 

14.11 Conduct experiments to evaluate forecasts. 

14.13 Incorporate the uncertainty associated with 

the prediction of the explanatory variables in 

the prediction intervals. 

14.14 Ask for a judgmental likelihood that a 

forecast will fall within a pre-defined 

minimum-maximum interval (not by asking 

people to set upper and lower confidence 

levels). 

Presenting Forecasts: 

15.1 Present forecasts and supporting data in a 

simple and understandable form. 

15.2 Provide complete, simple, and clear 

explanations of methods. 
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Table B: Principles apparently contravened in H6 

Setting Objectives: 

1.1 Describe decisions that might be affected by 

the forecasts. 

1.2 Prior to forecasting, agree on actions to take 

assuming different possible forecasts. 

Structuring the problem: 

2.1 Identify possible outcomes prior to making 

forecasts. 

2.3 Decompose the problem into parts. 

Identify Data Sources: 

3.2 Ensure that the data match the forecasting 

situation. 

3.3 Avoid biased data sources. 

Collecting Data: 

4.2 Ensure that information is reliable and that 

measurement error is low. 

4.3 Ensure that the information is valid. 

Preparing Data: 

5.3 Adjust intermittent series. 

5.7 Damp seasonal factors for uncertainty 

5.8 Use graphical displays for data. 

Implementing Methods: General 

7.6 Pool similar types of data. 

Implementing Methods: Quantitative Models with 

Explanatory Variables: 

10.4 Use theory and domain expertise to estimate 

or limit the magnitude of relationships. 

10.8 Apply the same principles to forecasts of 

explanatory variables. 

Evaluating Methods: 

13.4 Describe conditions associated with the 

forecasting problem. 

13.9 Provide full disclosure of methods. 

Assessing Uncertainty: 

14.6 Describe reasons why the forecasts might be 

wrong. 

14.7 When assessing Pis, list possible outcomes 

and assess their likelihoods. 

14.8 Obtain good feedback about forecast accuracy 

and the reasons why errors occurred. 
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Table C: Principles not rated 

due to lack of information in H6 

Setting Objectives: 

1.5 Obtain decision makers' agreement on methods 

Structuring the problem: 

2.7 Decompose time series by level and trend 

Identify Data Sources: 

3.1 Use theory to guide the search for information 

on explanatory variables 

Collecting Data: 

4.1 Use unbiased and systematic procedures to 

coUect data 

4.5 Avoid the collection of irrelevant data 

Preparing Data: 

5.1 Clean the data 

Selecting Methods: 

6.4 Use quantitative methods rather than qualitative 

methods 

6.5 Use causal methods rather than naive methods 

if feasible 

6.9 Assess acceptability and understandability of 

methods to users 

Evaluating Methods: 

13.11 Test the client's understanding of the 

methods 

13.19 Assess face validity 

Presenting Forecasts: 

15.3 Describe your assumptions 

Learning That Will Improve Forecasting 

Procedures: 

16.2 Seek feedback about forecasts 

16.3 Establish a formal review process for 

forecasting methods 

16.4 Establish a formal review process to ensure 

that forecasts are used property 

Notes 

I) Our interest in the topic of this paper was piqued when the State of Alaska hired us as 

consultants in late-September 2007 to assess forecasts that had been prepared "to Support U.S. 

Fish and Wildlife Service Polar Bear Listing Decision." We were impressed by the importance 

of the issue and, after providing our assessment, we decided to continue working on it and to 

prepare a paper for publication. These latter efforts have not been funded. We take 

responsibility for all judgments and for any errors that we might have made. 

2) On November 27,2007, we sent a draft of our paper to the authors of the U.S. Geological 

Survey administrative reports that we audited and stated: 

"As we note in our paper, there are elements of sUbjectivity in making the audit 

ratings. Should you feel that any of our ratings were incorrect, we would be grateful if 

you would you provide us with evidence that would lead to a different assessment. 

The same goes for any principle that you think does not apply, or to any principles that 

we might have overlooked. There are some areas that we could not rate due to a lack 

of information. Should you have information on those topics, we would be interested. 
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82737.084

Finally, we would be interested in peer review that you or your colleagues could 

provide, and in suggestions on how to improve the accuracy and clarity of our paper." 

We received a reply from Steven C. Amstrup on November 30, 2007 that said: "We all decline 

to offer preview comments on your attached manuscript. Please feel free, however, to list any 

of us as potential referees when you submit your manuscript for publication." 

3) We invite others to conduct forecasting audits of AMD, H6, any of the other papers prepared 

to support the endangered species listing, or any other papers relevant to long-term forecasting 

of the polar bear population. Note that the audit process calls for two or more raters. The audits 

can be submitted for publication on pubicpolicyforecasting.com along with the auditors' bios 

and any information relevant potential sources of bias. 

4) We seek information about scientifically developed forecasting studies, published or 

unpublished, that are relevant to polar bear forecasting. 

5) We seek further peer review on this paper. 

Acknowledgments 

We thank Don Esslemont, Milton Freeman, Paul Goodwin, and Torn Stewart for their reviews on 

earlier drafts. Janice Dow and Kelly Jin provided editorial assistance. 

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GLOBAL WARMING: FORECASTS BY SCIENTISTS 

VERSUS SCIENTIFIC FORECASTS* 

Kesten C. Green! and J. Scott Armstrong2t 

997 

IBusiness and Economic Forecasting Unit, Monash University, Victoria 3800, Australia. 

Contact: PO Box 10800, Wellington 6143, New Zealand. kesten@kestencgreen.com; 

T +6449763245; F +64 4 976 3250 

2The Wharton School, University of Pennsylvania 747 Huntsman, 

Philadelphia, PA 19104, USA. armstrong@wharton.upenn.edu 

ABSTRACT 

In 2007, the Intergovernmental Panel on Climate Change's Working Group One, a 

panel of experts established by the World Meteorological Organization and the 

United Nations Environment Programme, issued its Fourth Assessment Report. 

The Report included predictions of dramatic increases in average world 

temperatures over the next 92 years and serious harm resulting from the predicted 

temperature increases. Using forecasting principles as our guide we asked: Are 

these forecasts a good basis for developing public policy? Our answer is "no". 

To provide forecasts of climate change that are useful for policy-making, one 

would need to forecast (1) global temperature, (2) the effects of any temperature 

changes, and (3) the effects of feasible alternative policies. Proper forecasts of all 

three are necessary for rational policy making. 

The IPCC WGI Report was regarded as providing the most credible long-term 

forecasts of global average temperatures by 31 of the 51 scientists and others involved 

in forecasting climate change who responded to our survey. We found no references 

in the 1056-page Report to the primary sources of information on forecasting methods 

despite the fact these are conveniently available in books, articles, and websites. We 

audited the forecasting processes described in Chapter 8 of the IPCC's WG 1 Report 

to assess the extent to which they complied with forecasting principles. We found 

enough information to make judgments on 89 out of a total of 140 forecasting 

principles. The forecasting procedures that were described violated 72 principles. 

Many of the violations were, by themselves, critical. 

The forecasts in the Report were not the outcome of scientific procedures. In 

effect, they were the opinions of scientists transformed by mathematics and 

obscured by complex writing. Research on forecasting has shown that experts' 

predictions are not useful in situations involving uncertainly and complexity. We 

have been unable to identify any scientific forecasts of global warming. Claims that 

the Earth will get warmer have no more credence than saying that it will get colder. 

Keywords: accuracy, audit, climate change, evaluation, expert judgment, 

mathematical models, public policy. 

--------------------- 'Neither of the authors received funding for this paper. 

tin formation about J. Scott Armstrong can be found on Wikipedia. 
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998 

"A trend is a trend, 

But the qucstion is, will it bcnd? 

Will it alter its course 

Through some unforeseen force 

And come to a premature end?" 

Alec Cairncross, 1969 

Energy & Environment· Vol. 18, No. 7+8,2007 

Research on forccasting has been conducted since thc 1930s. Empirical studies that 

compare methods in order to determine which ones provide the most accurate 

forecasts in specified situations are the most useful source of cvidence. Findings, along 

with the evidence, were first summarized in Armstrong (1978, 1985). In the mid1990s, thc Forecasting Principles Projcct was established with the objective of 

summarizing all useful knowledge about forecasting. The knowledge was codified as 

cvidence-based principles, or condition-action stateme,nts, in ordcr to provide 

guidance on which mcthods to use when. The projcct led to the Principles of 

Forecasting handbook (Armstrong 2001): the work of 40 internationally-known 

experts on forecasting methods and 123 reviewers who wcre also leading experts on 

forccasting methods. Thc summarizing process alone required a four-ycar effort. 

The forecasting principles are easy to find: They are freely available on 

forecastingprincip\cs.com, a sitc sponsored by the International Institute of 

Forecasters. The Forecasting Principles site has been at the top of the list of sites in 

Internet searchcs for "forecasting" for many years. A summary of the principlcs, 

cUITently numbering 140, is provided as a checklist in the Forecasting Audit software 

available on thc site. The site is often updated in order to incorporate new evidence on 

forecasting as it comes to hand. A recent review of new evidence on some of the key 

principles was published in Armstrong (2006). Thcre is no other source that provides 

evidence-based forecasting principles. 

Thc strcngth of evidence is different for different principles, for example some 

principles are based on common sense or received wisdom. Such principles are 

included when there is no contrary evidence. Other principles havc some empirical 

support, while 31 are strongly supported by empirical evidence. 

Many of the principles go beyond common sense, and some are counter-intuitivc. 

As a result, those who forecast in ignorance of the forecasting research literature are 

unlikely to produce useful predictions. Here are some well-establishcd principles that 

apply to long-term forecasts for complex situations where the causal factors are 

subject to uncertainty (as with climatc): 

• Unaided judgmental forecasts by experts have no value. This applies whether 

the opinions are expressed in words, spreadsheets, or mathematical models. It 

applies regardless of how much scientific evidence is possessed by the experts. 

Among the reasons for this are: 

a) Complexity: Pcoplc cannot asscss complex relationships through 

unaided observations. 

b) Coincidcnce: People confuse correlation with causation. 

c) Feedback: People making judgmental predictions typically do not 
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Global Warming: Forecasts by Scientists versus Scientific Forecasts 999 

receive unambiguous feedback they can use to improve 

their forecasting. 

d) Bias: People have difficulty in obtaining or using evidence that 

contradicts their initial beliefs. This problem is especially 

serious for people who view themselves as experts. 

• Agreement among experts is weakly related to accuracy. This is especially true 

when the experts communicate with one another and when they work together 

to solve problems, as is the case with the IPCC process. 

• Complex models (those involving nonlinearities and interactions) harm 

accuracy because their errors multiply. Ascher (1978), refers to the Club of 

Rome's 1972 forecasts where, unaware of the research on forecasting, the 

developers proudly proclaimed, "in our model about 100,000 relationships are 

stored in the computer." Complex models also tend to fit random variations in 

historical data well, with the consequence that they forecast poorly and lead to 

misleading conclusions about the uncertainty of the outcome. Finally, when 

complex models are developed there are many opportunities for errors and the 

complexity means the errors are difficult to find. Craig, Gadgil, and Koomey 

(2002) came to similar conclusions in their review of long-term energy forecasts 

forthe US that were made between 1950 and 1980. 

• Given even modest uncertainty, prediction intervals are enormous. Prediction 

intervals (ranges outside which outcomes are unlikely to fall) expand rapidly as 

time horizons increase, for example, so that one is faced with enormous intervals 

even when trying to forecast a straightforward thing such as automobile sales for 

General Motors over the next five years. 

• When there is uncertainty in forecasting, forecasts should be conservative. 

Uncertainty arises when data contain measurement errors, when the series are 

unstable, when knowledge about the direction of relationships is uncertain, and 

when a forecast depends upon forecasts of related (causal) variables. For 

example, forecasts of no change were found to be more accurate than trend 

forecasts for annual sales when there was substantial uncertainty in the trend 

lines (Schnaars and Bavuso 1986). This principle also implies that forecasts 

should revert to long-term trends when such trends have been firmly established, 

do not waver, and there are no firm reasons to suggest that they will change. 

Finally, trends should be damped toward no-change as the forecast horizon 

increases. 

THE FORECASTING PROBLEM 

In determining the best policies to deal with the climate of the future, a policy maker 

first has to select an appropriate statistic to use to represent the changing climate. By 

convention, the statistic is the averaged global temperature as measured with 

thermometers at ground stations throughout the world, though in practice this is a far 

from satisfactory metric (see, e.g., Essex et a!., 2007). 

It is then necessary to obtain forecasts and prediction intervals for each of the 

following: 
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1. Mean global temperature in the long-term (say 10 years or longer). 

2. Effects of temperature changes on humans arui other living things. 

If accurate forecasts of mean global temperature can be obtained arui the 

changes are substantial, then it would be necessary to forecast the effects of the 

changes on the health of living things and on the health and wealth of humans. 

The concerns about changes in global mean temperature are based on the 

assumption that the earth is currently at the optimal temperature and that 

variations over years (unlike variations within days and years) are undesirable. 

For a proper assessment, costs and benefits must be comprehensive. (For 

example, policy responses to Rachel Carson's Silent Spring should have been 

based in part on forecasts of the number of people who might die from malaria 

if DDT use were reduced). 

3. Costs and benefits offeasible alternative policy proposals. 

lfvalid forecasts of the effects of the temperature changes on the health of living 

things and on the health and wealth of humans can be obtained and the forecasts 

are for substantial harmful effects, then it would be necessary to forecast the 

costs and benefits of proposed alternative policies that could be successfully 

implemented. 

A policy proposal should only be implemented ifvalid and reliable forecasts of the 

effects of implementing the policy can be obtained and the forecasts show net benefits. 

Failure to obtain a valid forecast in any of the three areas listed above would render 

forecasts for the other areas meaningless. We address primarily, but not exclusively, 

the first of the three forecasting problems: obtaining long-term forecasts of global 

temperature. 

But is it necessary to use scientific forecasting methods? In other words, to use 

methods that have been shown by empirical validation to be relevant to the types of 

problems involved with climate forecasting? Or is it sufficient to have leading 

scientists examine the evidence and make forecasts? We address this issue before 

moving on to our audits. 

ON THE VALUE OF FORECASTS BY EXPERTS 

Many public policy decisions are based on forecasts by experts. Research on 

persuasion has shown that people have substantial faith in the value of such forecasts. 

Faith increases when experts agree with one another. 

Our concern here is with what we refer to as unaided expert judgments. In such 

cases, experts may have access to empirical studies and other information, but they use 

their knowledge to make predictions without the aid of well-established forecasting 

principles. Thus, they could simply use the information to come up with judgmental 

forecasts. Alternatively, they could translate their beliefs into mathematical statements 

(or models) and use those to make forecasts. 

Although they may seem convincing at the time, expert forecasts can make for 

humorous reading in retrospect. Cerf and Navasky's (1998) book contains 310 pages 

of examples, such as Fermi Award-winning scientist John von Neumann's 1956 

prediction that "A few decades hence, energy may be free". Examples of expert 
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climate forecasts that turned out to be completely wrong are easy to find, such as UC 

Davis ecologist Kenneth Watt's prediction in a speech at Swarthmore College on Earth 

Day, April 22, 1970: 

If present trends continue, the world will be about four degrees colder in 1990, but 

eleven degrees colder in the year 2000. This is about twice what it would take to 

put us into an ice age. 

Are such examples merely a matter of selective perception? The second author's 

review of empirical research on this problem led him to develop the "Seer-sucker 

theory," which can be stated as "No matter how much evidence exists that seers do not 

exist, seers will find suckers" (Armstrong 1980). The amount of expertise does not 

matter beyond a basic minimum level. There are exceptions to the Seer-sucker Theory: 

When experts get substantial well-summarized feedback about the accuracy of their 

forecasts and about the reasons why their forecasts were or were not accurate, they can 

improve their forecasting. This situation applies for short-term (up to five day) 

weather forecasts, but we are not aware of any such regime for long-term global 

climate forecasting. Even if there were such a regime, the feedback would trickle in 

over many years before it became useful for improving forecasting. 

Research since 1980 has provided much more evidence that expert forecasts are of 

no value. In particular, Tetlock (2005) recruited 284 people whose professions 

included, "commenting or offering advice on political and economic trends." He 

asked them to forecast the probability that various situations would or would not 

occur, picking areas (geographic and substantive) within and outside their areas of 

expertise. By 2003, he had accumulated over 82,000 forecasts. The experts barely if at 

all outperformed non-experts and neither group did well against simple rules. 

Comparative empirical studies have routinely concluded that judgmental 

forecasting by experts is the least accurate of the methods available to make forecasts. 

For example, Ascher (1978, p. 200), in his analysis of long-term forecasts of electricity 

consumption found that was the case. 

Experts' forecasts of climate changes have long been newsworthy and a cause of 

worry for people. Anderson and Gainor (2006) found the following headlines in their 

search of the New York Times: 

Sept. 18, 1924 

March 27, 1933 

May 21,1974 

Dec. 27, 2005 

MacMillan Reports Signs of New Ice Age 

America in Longest Warm Spell Since 1776 

Scientists Ponder Why World's Climate is Changing: 

A Major Cooling Widely Considered to be Inevitable 

Past Hot Times Hold Few Reasons to Relax About New 

Warming 

In each case, the forecasts behind the headlines were made with a high degree of 

confidence. 

In the mid-1970s, there was a political debate raging about whether the global climate 

was changing. The United States' National Defense University (NDU) addressed this 

issue in their book, Climate Change to the Year 2000 (NDU 1978). This study involved 
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nine man-years of effort by the Department of Defense and other agencies, aided by 

experts who received honoraria, and a contract of nearly $400,000 (in 2007 dollars). The 

heart of the study was a survey of experts. The experts were provided with a chart of 

"annual mean temperature, 0-80° N.latitude," that showed temperature rising from 1870 

to early 1940 then dropping sharply until 1970. The conclusion, based primarily on 19 

replies weighted by the study directors, was that while a slight increase in temperature 

might occur, uncertainty was so high that "the next twenty years will be similar to that 

of the past" and the effects of any change would be negligible. Clearly, this was a 

forecast by scientists, not a scientific forecast. However, it proved to be quite influential. 

The report was discussed in The Global 2000 Report to the President (Carter) and at the 

World Climate Conference in Geneva in 1979. 

The methodology for climate forecasting used in the past few decades has shifted 

from surveys of experts' opinions to the use of computer models. Reid Bryson, the 

world's most cited climatologist, wrote in a 1993 article that a model is "nothing more 

than a formal statement of how the modeler believes that the part of the world of his 

concern actually works" (p. 798-790). Based on the explanations of climate models 

that we have seen, we concur. While advocates of complex climate models claim that 

they are based on "well established laws of physics", there is clearly much more to the 

models than the laws of physics otherwise they would all produce the same output, 

which patently they do not. And there would be no need for confidence estimates for 

model forecasts, which there most certainly are. Climate models are, in effect, 

mathematical ways for the experts to express their opinions. 

To our knowledge, there is no empirical evidence to suggest that presenting 

opinions in mathematical terms rather than in words will contribute to forecast 

accuracy. For example, Keepin and Wynne (1984) wrote in the summary of their study 

of the International Institute for Applied Systems Analysis's "widely acclaimed" 

projections for global energy that "Despite the appearance of analytical rigor. .. [they 1 

are highly unstable and based on informal guesswork." Things have changed little 

since the days of Malthus in the 1800s. Malthus forecast mass starvation. He expressed 

his opinions mathematically. His mathematical model predicted that the supply of food 

would increase arithmetically while the human population grew at a geometric rate 

and went hungry. 

International surveys of climate scientists from 27 countries, obtained by Bray and 

von Storch in 1996 and 2003, were summarized by Bast and Taylor (2007). Many 

scientists were skeptical about the predictive validity of climate models. Of more than 

1,060 respondents, 35% agreed with the statement, "Climate models can accurately 

predict future climates," and 47% percent disagreed. Members of the general public 

were also divided. An Ipsos Mori poll of 2,031 people aged 16 and over found that 

40% agreed that "climate change was too complex and uncertain for scientists to make 

useful forecasts" while 38% disagreed (Eccleston 2007). 

AN EXAMINATION OF CLIMATE FORECASTING METHODS 

We assessed the extent to which those who have made climate forecasts used 

evidence-based forecasting procedures. We did this by conducting Google searches. 

We then conducted a "forecasting audit" of the forecasting process behind the IPCC 
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forecasts. The key tasks of a forecasting audit are to: 

• examine all elements of the forecasting process, 

• use principles that are supported by evidence (or are self-evidently true and 

unchallenged by evidence) against which to judge the forecasting process, 

• rate the forecasting process against each principle, preferably using more than 

one independent rater, 

• disclose the audit. 

To our knowledge, no one has ever published a paper that is based on a forecasting 

audit, as defined here. We suggest that for forecasts involving important public 

policies, such audits should be expected and perhaps even-required. In addition, they 

should be fully disclosed with respect to who did the audit, what biases might be 

involved, and what were the detailed findings from the audit. 

REVIEWS OF CLIMATE FORECASTS 

We could not find any comprehensive reviews of climate forecasting efforts. With the 

exception of Stewart and Glantz (1985), the reviews did not refer to evidence-based 

findings. None of the reviews provided explicit ratings of the processes and, again 

with the exception of Stewart and Glantz, little attention was given to full disclosure 

of the reviewing process. Finally, some reviews ignored the forecasting methods and 

focused on the accuracy of the forecasts. 

Stewart and Glantz (1985) conducted an audit of the National Defense University 

(NDU 1978) forecasting process that we described above. They were critical of the 

report because it lacked an awareness of proper forecasting methodology. Their audit 

was hampered because the organizers of the study said that the raw data had been 

destroyed and a request to the Institute for the Future about the sensitivity of the 

forecasts to the weights went unanswered. JUdging from a Google Scholar search, 

climate forecasters have paid little attention to this paper. 

In a wide-ranging article on the broad topic of science and the environment, Bryson 

(1993) was critical of the use of models for forecasting climate. He wrote: 

... it has never been demonstrated that the GCMs [General Circulation Models] are 

capable of prediction with any level of accuracy. When a modeler says that his 

model shows that doubling the carbon dioxide in the atmosphere will raise the 

global average temperature two to three degrees Centigrade, he really means that a 

simulation of the present global temperature with current carbon dioxide levels 

yields a mean value two to three degrees Centigrade lower than his model 

simulation with doubled carbon dioxide. This implies, though it rarely appears in 

the news media, that the error in simulating the present will be unchanged in 

simulating the future case with doubled carbon dioxide. That has never been 

demonstrated-it is faith rather than science." (pp. 790-791) 

Balling (2005), Christy (2005), Frauenfeld (2005). and Posmentier and Soon 

(2005) each assess different aspects of the use of climate models for forecasting and 
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each comes to broadly the same conclusion: The models do not represent the real 

world sufficiently well to be relied upon for forecasting. 

Carter, et aI. (2006) examined the Stern Review (Stem 2007). They concluded that 

the authors of the Review made predictions without reference to scientific validation 

and without proper peer review. 

Pilkey and Pilkey-Jarvis (2007) examined long-term climate forecasts and 

concluded that they were based only on the opinions of the scientists. The scientists' 

opinions were expressed in complex mathematical terms without evidence on the 

validity of chosen approach. The authors provided the following quotation on their 

page 45 to summarize their assessment: "Today's scientists have substituted 

mathematics for experiments, and they wander off through equation after equation and 

eventually build a structure which has no relation to reality (Nikola Telsa, inventor and 

electrical engineer, 1934)." While it is sensible to be explicit about beliefs and to 

formulate these in a model, forecasters must also demonstrate that the relationships are 

valid. 

Carter (2007) examined evidence on the predictive validity of the general 

circulation models (GCMs) used by the IPCC scientists. He found that while the 

models included some basic principles of physics, scientists had to make "educated 

guesses" about the values of many parameters because knowledge about the physical 

processes of the earth's climate is incomplete. In practice, the GCMs failed to predict 

recent global average temperatures as accurately as simple curve-fitting approaches 

(Carter 2007, pp. 64 - 65). They also forecast greater warming at higher altitudes in 

the tropics when the opposite has been the case (p. 64). Further, individual GCMs 

produce widely different forecasts from the same initial conditions and minor changes 

in parameters can result in forecasts of global cooling (Essex and McKitrick, 2002). 

Interestingly, when models predict global cooling, the forecasts are often rejected as 

"outliers" or "obviously wrong" (e.g., Stainforth et aI., 2005). 

Roger Pielke Sr. (Colorado State Climatologist, until 2006) gave an assessment of 

climate models in a 2007 interview (available via http://tinyurl.com/2wpk29): 

You can always reconstruct after the fact what happened if you run enough model 

simulations. The challenge is to run it on an independent dataset, say for the next 

five years. But then they will say "the model is not good for five years because 

there is too much noise in the system". That's avoiding the issue then. They say you 

have to wait 50 years, but then you can't validate the model, so what good is it? 

... Weather is very difficult to predict; climate involves weather plus all these 

other components of the climate system, ice, oceans, vegetation, soil etc. Why 

should we think we can do better with climate prediction than with weather 

prediction? To me it's obvious, we can't! 

I often hear scientists say "weather is unpredictable, but climate you can predict 

because it is the average weather". How can they prove such a statement? 

In his assessment of climate models, physicist Freeman Dyson (2007) wrote: 

I have studied the climate models and I know what they can do. The models solve 
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the equations of fluid dynamics, and they do a very good job of describing the fluid 

motions of the atmosphere and the oceans. They do a very poor job of describing 

the clouds, the dust, the chemistry and the biology of fields and farms and forests. 

They do not begin to describe the real world that we live in. 

Bellamy and Barrett (2007) found serious deficiencies in the general circulation 

models described in the IPCC's Third Assessment Repor!. In particular, the models (1) 

produced very different distributions of clouds and none was close the actual 

distribution of clouds, (2) parameters for incoming radiation absorbed by the 

atmosphere and for that absorbed by the Earth's surface varied considerably, (3) did 

not accurately represent what is known about the cffects of CO2 and could not 

represent the possible positive and negative feedbacks about which there is great 

uncertainty. The authors concluded: 

The climate system is a highly complex system and, to date, no computer models 

are sufficiently accurate for their predictions of future climate to be relied upon. (p. 

71) 

Trenberth (2007), a lead author of Chapter 3 in the IPCC WG I report wrote in a 

Nature.com blog H ••• the science is not done because we do not have reliable or 

regional predictions of climate." 

Taylor (2007) compared seasonal forecasts by New Zealand's National Institute of 

Water and Atmospheric Research (NIWA) with outcomes for the period May 2002 to 

April 2007. He found NIWA's forecasts of average regional temperatures for the 

season ahead were 48% correct, which was no more accurate than chance. That this is 

a general result was confirmed by New Zealand climatologist Jim Renwick, who 

observed that NlWA's low success rate was comparable to that of other forecasting 

groups worldwide. He added that "Climate prediction is hard, half of the variability in 

the climate system is not predictable, and so we don't expect to do terrifically well." 

Renwick is a co-author with Working Group I of the IPCC 4th Assessment Report, and 

also serves on the World Meteorological Organization Commission for Climatology 

Expert Team on Seasonal Forecasting. His expert view is that current GCM climate 

models are unable to predict future climate any better than chance (New Zealand 

Climate Science Coalition 2007). 

Similarly, Vizard, Anderson, and Buckley (2005) found seasonal rainfall forecasts 

for Australian townships were insufficiently accurate to be useful to intended 

consumers such as farmers planning for feed requirements. The forecasts were 

released only 15 days ahead of each three month period. 

A SURVEY TO IDENTIFY THE MOST CREDIBLE LONG· TERM 

FORECASTS OF GLOBAL TEMPERATURE 

We surveyed scientists involved in long-term climate forecasting and policy makers. 

Our primary concern was to identify the most important forecasts and how those 

forecasts were made. In particular, we wished to know if the most widely accepted 

forecasts of global average temperature were based on the opinions of experts or were 
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derived using scientific forecasting methods. Given the t1ndings of our review of 

reviews of climate forecasting and the conclusion from our Google search that many 

scientists are unaware of evidence-based t1ndings related to forecasting methods, we 

expected that the forecasts would be based on the opinions of scientists. 

We sent a questionnaire to experts who had expressed diverse opinions on global 

warming. We generated lists of experts by identifying key people and asking them to 

identify others. (The lists are provided in Appendix A) Most (70%) of the 240 experts 

on our lists were IPCC reviewers and authors. 

Our questionnaire asked the experts to provide references for what they regarded as 

the most credible source of long-term forecasts of mean global temperatures. We 

strove for simplicity to minimize resistance to our request. Even busy people should 

have time to send a few references, especially if they believe that it is important to 

evaluate the quality of the forecasts that may influence major decisions. We asked: 

"We want to know which forecasts people regard as the most credible and how 

those forecasts were derived ... 

In your opinion, which scientific article is the source of the most credible 

forecasts of global average temperatures over the rest of this century?" 

We received useful responses from 51 of the 240 experts, 42 of whom provided 

references to what they regarded as credible sources of long-term forecasts of mean 

global temperatures. Interestingly, eight respondents provided references in support of 

their claims that no credible forecasts exist. Of the 42 expert respondents who were 

associated with global warming views, 30 referred us to the IPCC's report. A list of 

the papers that were suggested by respondents is provided at 

publicpolicyforecasting.com in the "Global Warming" section. 

Based on the replies to our survey, it was clear that the IPCC's Working Group 1 

Report contained the forecasts that are viewed as most credible by the bulk of the 

climate forecasting community. These forecasts are contained in Chapter 10 of the 

Report and the models that are used to forecast climate are assessed in Chapter 8, 

"Climate Models and Their Evaluation" (Randall et aL 2007). Chapter 8 provided the 

most useful information on the forecasting process used by the IPCC to derive 

forecasts of mean global temperatures, so we audited that chapter. 

We also posted cal1s on email lists and on the forecastingprinciples.com site asking 

for help from those who might have any knowledge about scientific climate forecasts. 

This yielded few responses, only one of which provided relevant references. 

Does the IPCC report provide climate forecasts? 

Trenberth (2007) and others have claimed that the IPCC does not provide forecasts but 

rather presents "scenarios" or "projections." As best as we can tell, these terms are 

used by the IPCC authors to indicate that they provide "conditional forecasts." 

Presumably the IPCC authors hope that readers, especially policy makers, will find at 

least one of their conditional forecast series plausible and will act as if it will come 

true if no action is taken. As it happens, the word "forecast" and its derivatives 

occurred 37 times, and "predict" and its derivatives occurred 90 times in the body of 
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Chapter 8. Recall also that most of our respondents (29 of whom were IPCC authors 

or reviewers) nominated the IPCC report as the most credible source of forecasts (not 

"scenarios" or "projections") of global average temperature. We conclude that the 

IPCC does provide forecasts. 

A FORECASTING AUDIT FOR GLOBAL WARMING 

In order to audit the forecasting processes described in Chapter 8 of the IPCC's report, 

we each read it prior to any discussion. The chapter was, in our judgment, poorly 

written. The writing showed little concern for the target readership. It provided 

extensive detail on items that are of little interest in judging the merits of the 

forecasting process, provided references without describing what readers might find, 

and imposed an incredible burden on readers by providing 788 references. In addition, 

the Chapter reads in places like a sales brochure. In the three-page executive summary, 

the terms, "new" and "improved" and related derivatives appeared 17 times. Most 

significantly, the chapter omitted key details on the assumptions and the forecasting 

process that were used. If the authors used a formal structured procedure to assess the 

forecasting processes, this was not evident. 

We each made a formal, independent audit of IPCC Chapter 8 in May 2007. To do 

so, we used the Forecasting Audit Software on the forecastingprinciples.com site, 

which is based on material originally published in Armstrong (200l). To our 

knowledge, it is the only evidence-based tool for evaluating forecasting procedures. 

While Chapter 8 required many hours to read, it took us each about one hour, 

working independently, to rate the forecasting approach described in the Chapter using 

the Audit software. We have each been involved with developing the Forecasting 

Audit program, so other users would likely require much more time. 

Ratings are on a 5-point scale from -2 to +2. A rating of +2 indicates the forecasting 

procedures were consistent with a principle, and a rating of -2 indicates failure to comply 

with a principle. Sometimes some aspects of a procedure are consistent with a principle 

but others are not. In such cases, the rater must judge where the balance lays. The Audit 

software also has options to indicate that there is insufficient information to rate the 

procedures or that the principle is not relevant to a particular forecasting problem. 

Reliability is an issue with rating tasks. For that reason, it is desirable to use two or 

more raters. We sent out general calls for experts to use the Forecasting Audit 

Software to conduct their own audits and we also asked a few individuals to do so. At 

the time of writing, none have done so. 

Our initial overall average ratings were similar at -1.37 and -1.35. We compared our 

ratings for each principle and discussed inconsistencies. In some cases we averaged 

the ratings, truncating toward zero. In other cases we decided that there was 

insufficient information or that the information was too ambiguous to rate with 

confidence. Our final ratings are fully disclosed in the Special Interest Group section 

of the forecastingprinciples.com site that is devoted to Public Policy 

(publicpolicyforecasting.com) under Global Warming. 

Of the 140 principles in the Forecasting Audit, we judged that 127 were relevant 

for auditing the forecasting procedures described in Chapter 8. The Chapter provided 

insufficient information to rate the forecasting procedures that were used against 38 of 
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Table 1. Clear Violations 

Setting Objectives 

Describe decisions that might be affected by the forecast. 

Prior to forecasting, agree on actions to take assuming 

different possible forecasts. 

Make sure forecasts are independent of politics. 

Consider whether the events or series can be forecasted. 

Identifying Data Points 

Avoid biased data sources. 

Collecting Data 

Use unbiased and systematic procedures to collect data. 

Ensure that information is reliable and that measurement 

error is low. 

Ensure that the information is valid. 

Selecting Methods 

List all important selection criteria before selecting 

methods. 

Ask unbiased experts to rate potential methods. 

Select simple methods unless empirical evidence calls for a 

more complex approach. 

Compare track records of various forecasting methods. 

Assess acceptability and understandability of methods to 

users 

Examine the value of altemative forecasting methods. 

Implementing Methods: General 

Keep forecasting methods simple. 

Be conservative in situations of high uncertainty or 

instability. 

Impienumling Quantitative Methods 

Tailor the forecasting model to the horizon. 

Do not use "fit" to develop the model. 

Implemenring Methods: Q1Iantitative Models with Ripianatory 

Variables 

Apply the same principles to forecasts of explanatory 

variables. 

Shrink the forecasts of change if there is high uncertainty 

for predictions of the explanatory variables. 

Integrating Judgmental and Quantitative Methods 

Use structured procedures to integrate judgmental and 

quantitative methods. 

Usc structured judgments as inputs of quantitative models. 

Use prespecified domain knowledge in selecting. weighing, 

and modifying quantitative models. 

Combining Forecasts 

Combine forecasts from approaches that differ. 

Use trimmed means, medians, or modes. 

Use track records to vary the weights on component 

forecasts. 

Evaluating Methods 

Compare reasonable methods. 

Tailor the analysis to the decision. 

Describe the potential biases of the forecasters. 

Assess the reliability and validity of the data. 

Provide easy access to the data. 

Provide full disclosure of methods. 

Test assumptions for validity. 

Test the client's understanding of the methods. 

Use direct replications of evaluations to identify mistakes. 

Replicate forecast evaluations to assess their reliability. 

Compare forecasts generated by different methods. 

Examine all important criteria. 

Specify criteria for evaluating methods prior to analyzing 

data. 

Assess face validity. 

Use error measures that adjust for scale in the data. 

Ensure error measures are valid. 

Use error measures that are not sensitive to the degree of 

difficulty in forecasting. 

Avoid error measures that are highly sensitive to outliers. 

Use out of sample (ex-ante) error measures. 

(Revised) Tests of statistical significance should not be 

used. 

Do not use root mean square error (RMSE) to make 

comparisons among forecasting methods. 

Base comparisons of methods on large samples of forecasts. 

Conduct explicit cost-benefit analysis. 

Assessing Uncertainty 

Use objective procedures to estimate explicit prediction. 

Develop prediction intervals by using empirical estimates 

based on realistic representations of forecasting situations. 

When assessing Pis, list possible outcomes and assess their 

likelihoods. 

Obtain good feedback about forecast accuracy and the 

reasons why errors occurred. 

Combine prediction intervals from altemative forecast 

methods. 

Use safety factors to adjust for overconfidence in PIs. 

Presenting Forecasts 

Present forecasts and supporting data in a simple and 

understandable form. . 

Provide complete, simple, and clear explanations of methods. 

Present prediction intervals. 

Learning That Will Improve F orecasling Procedures 

Establish a formal review process for forecasting methods. 

Establish a formal review process to ensure that forecasts 

are used properly. 
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these 127 principles. For example, we did not rate the Chapter against Principle 10.2: 

"Use all important variables." At least in part, our difficulty in auditing the Chapter 

was due to the fact that it was abstruse. It was sometimes difficult to know whether the 

information we sought was present or not. 

Of the 89 forecasting principles that we were able to rate, the Chapter violated 72. 

Of these, we agreed that there were clear violations of 60 principles. Principle 1.3 

"Make sure forecasts are independent of politics" is an example of a principle that is 

clearly violated by the IPCC process. This principle refers to keeping the forecasting 

process separate from the planning process. The term "politics" is used in the broad 

sense of the exercise of power. David Henderson, a former Head of Economics and 

Statistics at the OECD, gave a detailed account of how the IPCC process is directed 

by non-scientists who have policy objectives and who believe that anthropogenic 

global warming is real and dangerous (Henderson 2007). The clear violations we 

identified are listed in Table 1. 

We also found 12 "apparent violations". These principles, listed in Table 2, are ones 

for which one or both of us had some concerns over the coding or where we did not 

agree that the procedures clearly violated the principle. 

Table 2. Apparent Violations 

Setting Objectives 

• Obtain decision makers' agreement on methods. 

Structuring the Problem 

• Identify possible outcomes prior to making forecast. 

• Decompose time series by level and trend. 

Identifying Data Sources 

• Ensure the data match the forecasting situation. 

• Obtain infonnation from similar (analogous) series or cases. Such infonnation may help to 

estimate trends. 

Implementing Judgmental Methods 

• Obtain forecasts from heterogeneous experts. 

Evaluating Methods 

• Design test situations to match the forecasting problem. 

• Describe conditions associated with the forecasting problem. 

• Use multiple measures of accuracy. 

Assessing Uncertainty 

• Do not assess uncertainty in a traditional (unstructured) group meeting. 

• Incorporate the uncertainty associated with the prediction of the explanatory variables in the 

prediction intervals. 

Presenting Forecasts 

• Describe your assumptions. 

Finally, we lacked sufficient information to make ratings on many of the relevant 

principles. These are listed in Table 3. 
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Table 3. Lack of Information 

Structuring the Problem 

• Tailor the level of data aggregation (or segmentation) to the decisions. 

• Decompose the problem into parts. 

• Decompose time series by causal forces. 

• Structure problems to deal with important interactions among causal variables. 

• Structure problems that involve causal chains. 

Identifying Data Sources 

• Use theory to guide the search for information on explanatory variables. 

Collecting Data 

• Obtain aU the important data. 

• Avoid collection of irrelevant data. 

Preparing Data 

• Clean the data. 

• Use transformations as required by expectations. 

• Adjust intermittent series. 

• Adjust for unsystematic past events. 

• Adjust for systematic events. 

• Use graphical displays for data. 

Implementing Methods: General 

• Adjust for events expected in the future. 

• Pool similar types of data. 

• Ensure consistency with forecasts of related series and related time periods. 

Implementing Judgmental Methods 

• Ask experts to justify their forecasts in writing. 

• Obtain forecasts from enough respondents. 

• Obtain multiple forecasts of an event from each expert. 

Implementing Quantitative Methods 

• Match the model to the underlying phenomena. 

• Weigh the most relevant data more heavily. 

• Update models frequently. 

Implementing Methods: Quantitative Models with Explanatory Variables 

• Use aU important variables. 

• Rely on theory and domain expertise when specifying directions of relationships. 

• Use theory and domain expertise to estimate or limit the magnitude of relationships. 

• Use different types of data to measure a relationship. 

• Forecast for alternative interventions. 

Integrating Judgmental and Quantitative Methods 

• Limit subjective adjustments of quantitative forecasts. 

Combining Forecasts 

• Use formal procedures to combine forecasts. 

• Start with equal weights. 

• Use domain knowledge to vary weights on component forecasts. 
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Table 3. continued 

Evaluating Methods 

• Use objective tests of assumptions. 

• Avoid biased error measures. 

• Do not use R-square (either standard or adjusted) to compare forecasting models. 

Assessing Uncertainty 

• Ensure consistency of the forecast horizon. 

lOll 

• Ask for a judgmental likelihood that a forecast will fall within a pre-defined minimummaximum interval. 

Learning That Will Improve Forecasting Procedures 

• Seek feedback about forecasts. 

Some of these principles might be surprising to those who have not seen the 

evidence-"Do not use R-square (either standard or adjusted) to compare forecasting 

models." Others are principles that any scientific paper should be expected to 

address-HUse objective tests of assumptions." Many ofthese principles are important 

for climate forecasting, such as "Limit subjective adjustments of quantitative 

forecasts." 

Some principles are so important that any forecasting process that does not adhere 

to them cannot produce valid forecasts. We address four such principles, all of which 

are based on strong empirical evidence. All four of these key principles were violated 

by the forecasting procedures described in IPCC Chapter 8. 

Consider whether the events or series can be forecasted (Principle 1.4) 

This principle refers to whether a forecasting method can be used that would do better 

than a naIve method. A common naiVe method is to assume that things will not 

change. 

Interestingly, naIve methods are often strong competitors with more sophisticated 

alternatives. This is especially so when there is much uncertainty. To the extent that 

uncertainty is high, forecasters should emphashe the naive method. (This is illustrated 

by regression model coefficients: when uncertainty increases, the coefficients tend 

towards zero.) Departures from the naiVe model tend to increase forecast error when 

uncertainty is high. 

In our judgment, the uncertainty about global mean temperature is extremely high. 

We are not alone. Dyson (2007), for example, wrote in reference to attempts to model 

climate that "The real world is muddy and messy and full of things that we do not yet 

understand." There is even controversy among climate scientists over something as 

basic as the current trend. One researcher, Carter (2007, p. 67) wrote: 

... the slope and magnitude of temperature trends inferred from time-series data 

depend upon the choice of data end points. Drawing trend lines through highly 

variable, cyclic temperature data or proxy data is therefore a dubious exercise. 

Accurate direct measurements of tropospheric global average temperature have 

only been available since 1979, and they show no evidence for greenhouse 

warming. Surface thermometer data, though flawed, also show temperature stasis 

since 1998. 
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Global climate is complex and scientific evidence on key relationships is weak or 

absent. For example, does increased CO2 in the atmosphere cause high temperatures or 

do high temperatures increase CO2? In opposition to the major causal role assumed for 

CO2 by the IPCC authors (Le Treut et al. 2007), Soon (2007) presents evidence that the 

latter is the case and that CO2 variation plays at most a minor role in climate change. 

Measurements of key variables such as local temperatures and a representative 

global temperature are contentious and subject to revision in the case of modern 

measurements because of inter alia the distribution of weather stations and possible 

artifacts such as the urban heat island effect, and are often speculative in the case of 

ancient ones, such as those climate proxies derived from tree ring and ice-core data 

(Carter 2007). 

Finally, it is difficult to forecast the causal variables. Stott and Kettleborough 

(2002, p. 723) summarize: 

Even with perfect knowledge of emissions, uncertainties in the representation of 

atmospheric and oceanic processes by climate models limit the accuracy of any 

estimate of the climate response. Natural variability, generated both internally and 

from external forcings such as changes in solar output and explosive volcanic 

eruptions, also contributes to the uncertainty in climate forecasts. 

The already high level of uncertainty rises rapidly as the forecast horizon increases. 

While the authors of Chapter 8 claim that the forecasts of global mean temperature 

are well-founded, their language is imprecise and relies heavily on such words as 

"generally," "reasonable well," "widely," and "relatively" [to what?). The Chapter 

makes many explicit references to uncertainty. For example, the phrases " ... it is not 

yet possible to determine which estimates of the climate change cloud feedbacks are the 

most reliable" and "Despite advances since the TAR, substantial uncertainty remains in 

the magnitude of cryospheric feedbacks within AOGCMs" appear on p. 593. In 

discussing the modeling of temperature, the authors wrote, "The extent to which these 

systematic model errors affect a model's response to external perturbations is unknown, 

but may be significant" (p. 608), and, "The diurnal temperature range ... is generally too 

small in the models, in many regions by as much as 50%" (p. 609), and "It is not yet 

known why models generally underestimate the diurnal temperature range." The 

following words and phrases appear at least once in the Chapter: unknown, uncertain, 

unclear, not clear, disagreement, not fully understood, appears, not well observed, 

variability, variety, unresolved, not resolved, and poorly understood. 

Given the high uncertainty regarding climate, the appropriate naIve method for this 

situation would be the "no-change" model. Prior evidence on forecasting methods 

suggests that attempts to improve upon the naiVe model might increase forecast error. 

To reverse this conclusion, one would have to produce validated evidence in favor of 

alternative methods. Such evidence is not provided in Chapter 8 of the IPCC report. 

We are not suggesting that we know for sure that long-term forecasting of climate 

is impossible, only that this has yet to be demonstrated. Methods consistent with 

forecasting principles such as the naIve model with drift, rule-based forecasting, wellspecified simple causal models, and combined forecasts might prove useful. The 
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methods are discussed in Armstrong (2001). To our knowledge, their application to 

long-term climate forecasting has not been examined to date. 

Keep forecasting methods simple (Principle 7.1) 

We gained the impression from the IPPC chapters and from related papers that climate 

forecasters generally believe that complex models are necessary for forecasting 

climate and that forecast accuracy will increase with model complexity. Complex 

methods involve such things as the use of a large number of variables in forecasting 

models, complex interactions, and relationships that employ nonlinear parameters. 

Complex forecasting methods are only accurate when there is little uncertainty about 

relationships now and in the future, where the data are subject to little error, and where 

the causal variables can be accurately forecast. These conditions do not apply to 

climate forecasting. Thus, simple methods are recommended. 

The use of complex models when uncertainty is high is at odds with the evidence 

from forecasting research (e.g., Allen and Fildes 2001, Armstrong 1985, Duncan, Gorr 

and Szczypula 2001, Wittink and Bergestuen 2001). Models for forecasting variations 

in climate are not an exception to this rule. Halide and Ridd (2007) compared 

predictions of EI Nino-Southern Oscillation events from a simple univariate model 

with those from other researchers' complex models. Some of the complex models 

were dynamic causal models incorporating laws of physics. In other words, they were 

similar to those upon which the IPCC authors depended. Halide and Ridd's simple 

model was better than all eleven of the complex models in making predictions about 

the next three months. All models performed poorly when forecasting further ahead. 

The use of complex methods makes criticism difficult and prevents forecast users 

from understanding how forecasts were derived. One effect of this exclusion of others 

from the forecasting process is to reduce the chances of detecting errors. 

Do not use fit to develop the model (Principle 9.3) 

It was not clear to us to what extent the models described in Chapter 8 (or in Chapter 9 

by Hegerl et al. 2007) are either based on, or have been tested against, sound empirical 

data. However, somc statements were made about the ability of the models to fit 

historical data, after tweaking their parameters. Extensive research has shown that the 

ability of models to fit historical data has little relationship to forecast accuracy (See 

"Evaluating forecasting methods" in Armstrong 200 I.) It is weB known that fit can be 

improved by making a model more complex. The typical consequence of increasing 

complexity to improve fit, however, is to decrease the accuracy of forecasts. 

Use out-of-sample (ex ante) error measures (Principle 13.26) 

Chapter 8 did not provide evidence on the relative accuracy of ex ante long-term 

forecasts from the models used to generate the IPCC's forecasts of climate change. It 

would have been feasible to assess the accuracy of alternative forecasting methods for 

medium- to long-term forecasts by using "successive updating." This involves 

withholding data on a number of years, then providing forecasts for one-year ahead, 

then two-years ahead, and so on up to, say, 20 years. The actual years could be 

disguised during these validation procedures. Furthermore, the years could be reversed 
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(without telling the forecasters) to assess back-casting accuracy. If, as is suggested by 

forecasting principles, the models were unable to improve on the accuracy of forecasts 

from the naIve method in such tests, there would be no reason to suppose that accuracy 

would improve for longer forecasts. "Evaluating forecasting methods" in Armstrong 

2001 provides evidence on this principle. 

SUMMARY OF AUDIT FINDINGS 

Our ratings of the processes used to generate the forecasts presented in the IPCC report 

are provided on the Public Policy Forecasting Special Interest Group Page at 

forecastingprinciples.com. These ratings have been posted since the time that our 

paper was presented at the International Symposium on Forecasting in New York in 

late June 2007. 

Prior to the publication of this paper, we invited other researchers, using messages 

to email lists and web sites, to replicate our audit by providing their own ratings. In 

addition, we asked for information about any relevant principles that have not been 

included in the Forecasting Audit. At the time of writing, we have received neither 

alternative ratings nor evidence for additional relevant principles. 

The many violations provide further evidence that the IPCC authors were unaware 

of evidence-based principles for forecasting. If they were aware of them, it would have 

been incumbent on them to present evidence to justify their departures from the 

principles. They did not do so. We conclude that because the forecasting processes 

examined in Chapter 8 overlook scientific evidence on forecasting, the IPCC forecasts 

of climate change are not scientific. 

We invite others to provide evidence-based audits of what they believe to be 

scientific forecasts relevant to climate change. These can be posted on web sites to 

ensure that readers have access to the audits. As with peer review, we will require all 

relevant information on the people who conduct the audits prior to posting the audits 

on publicpolicyforecasting.com. 

Climate change forecasters and their clients should use the Forecasting Audit early 

and often. Doing so would help to ensure that they are using appropriate forecasting 

procedures. Outside evaluators should also be encouraged to conduct audits. The audit 

reports should be made available to both the sponsors of the study and the public by 

posting on an open web site such as publicpolicyforecasting.com. 

CLIMATE FORECASTERS' USE OF THE SCIENTIFIC LITERATURE ON 

FORECASTING METHODS 

Bryson (1993) wrote that while it is obvious that when a statement is made about what 

climate will result from a doubling CO2 it is a forecast, "I have not yet heard, at any 

of the many environmental congresses and symposia that I have attended, a discussion 

of forecasting methodology applicable to the environment" (p. 791). 

We looked for evidence that climate modelers relied on scientific studies on the 

proper use of forecasting methods. In one approach, in April and June 2007, we used the 

Advanced Search function of Google Scholar to get a general sense of the extent to 

which climate forecasters refer to scientific studies on forecasting. When we searched 

for "global wanning" and "forecasting principles," we found no relevant sites. Nor did 
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we find any relevant citations of "forecastingprinciples.com" and "global warming." Nor 

were there any relevant citations of the relevant-sounding paper, "Forecasting for 

Environmental Decision-Making" (Armstrong 1999) published in a book with a relevant 

title: Tools to Aid Environmental Decision Making. A search for "global warming" and 

the best selling textbook on forecasting methods (Makridakis et al. 1998) revealed two 

citations, neither related to the prediction of global mean temperatures. Finally, there 

were no citations of research on causal models (e.g., Allen and Fildes 2001). 

Using the titles of the papers, we independently examined the references in Chapter 

8 of the IPCC Report. The Chapter contained 788 references. Of these, none had any 

apparent relationship to forecasting methodology. Our examination was not difficult as 

most papers had titles such as, "Using stable water isotopes to evaluate basin-scale 

simulations of surface water budgets," and, "Oceanic isopycnal mixing by coordinate 

rotation." 

Finally, we examined the 23 papers that we were referred to by our survey 

respondents. These included Chapter 10 of the IPCC Report (Meehl et al. 2007). One 

respondent provided references to eight papers all by the same author 

(Abdussamatov). We obtained copies of three of those papers and abstracts of three 

others and found no evidence that the author had referred to forecasting research. Nor 

did any of the remaining 15 papers include any references to research on forecasting. 

We also examined the 535 references in Chapter 9. Of these, 17 had titles that 

suggested the article might be concerned at least in part with forecasting methods. 

When we inspected the 17 articles, we found that none of them referred to the 

scientific literature on forecasting methods. 

It is difficult to understand how scientific forecasting could be conducted without 

reference to the research literature on how to make forecasts. One would expect to see 

empirical justification for the forecasting methods that were used. We concluded that 

climate forecasts are informed by the modelers' experience and by their models-but 

that they are unaided by the application of forecasting principles. 

CONCLUSIONS 

To provide forecasts of climate change that are useful for policy-making, one would 

need to prepare forecasts of (1) temperature changes, (2) the effects of any temperature 

changes, and (3) the effects of feasible proposed policy changes. To justify policy 

changes based on climate change, policy makers need scientific forecasts for all three 

forecasting problems. If governments implement policy changes without such 

justification, they are likely to cause harm. 

We have shown that failure occurs with the first forecasting problem: predicting 

temperature over the long term. Specifically, we have been unable to find a scientific 

forecast to support the currently widespread belief in "global warming." Climate is 

complex and there is much uncertainty about causal relationships and data. Prior 

research on forecasting suggests that in such situations a naIve (no change) forecast 

would be superior to current predictions. Note that recommending the naIve forecast 

does not mean that we believe that climate will not change. It means that we are not 

convinced that current knowledge about climate is sufficient to make useful long-term 

forecasts about climate. Policy proposals should be assessed on that basis. 
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Based on our literature searches, those forecasting long-term climate change have 

no apparent knowledge of evidence-based forecasting methods, so we expect that 

similar conclusions would apply to the other two necessary parts of the forecasting 

problem. 

Many policies have been proposed in association with claims of global warming. It 

is not our purpose in this paper to comment on specific policy proposals, but it should 

be noted that policies may be valid regardless of future climate changes. To assess this, 

it would be necessary to directly forecast costs and benefits assuming that climate does 

not change or, even better, to forecasts costs and benefits under a range of possible 

future climates. 

Public policy makers owe it to the people who would be affected by their policies 

to base them on scientific forecasts. Advocates of policy changes have a similar 

obligation. We hope that in the future, climate scientists with diverse views will 

embrace forecasting principles and will collaborate with forecasting experts in order 

to provide policy makers with scientific forecasts of climate. 

ACKNOWLEDGEMENTS 

We thank P. Geoffrey Allen, Robert Carter, Alfred Cuzan, Robert Fildes, Paul 

Goodwin, David Henderson, Jos de Laat, Ross McKitrick, Kevin Trenberth, Timo van 

Druten, Willie Soon, and Tom Yokum for helpful suggestions on various drafts of the 

paper. We are also grateful for the suggestions of three anonymous reviewers. Our 

acknowledgement does not imply that all of the reviewers agreed with all of our 

findings. Rachel Zibelman anq Hester Green provided editorial support. 

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1020 Energy & Environment· Vo!' 18, No. 7+8, 2007 

APPENDIX A: PEOPLE TO WHOM WE SENT OUR QUESTIONNAIRE 

(* indicates a relevant response) 

IPCC Working Group 1 

Myles Allen, Richard Alley, Ian Allison, Peter Ambenje, Vincenzo Artale, Paulo 

Artaxo, Alphonsus Baede, Roger Barry, Terje Berntsen, Richard A. Betts, Nathaniel 

L. Bindoff, Roxana Bojariu, Sandrine Bony, Kansri Boonpragob, Pascale Braconnot, 

Guy Brasseur, Keith Briffa, Aristita Busuioc, Jorge Carrasco, Anny Cazenave, 

Anthony Chen*, Amnat Chidthaisong, Jens Hesselbjerg Christensen, Philippe Ciais*, 

William Collins, Robert Colman*, Peter Cox, Ulrich Cubasch, Pedro Leite Da Silva 

Dias, Kenneth L. Denman, Robert Dickinson, Yihui Ding, Jean-Claude Duplessy, 

David Easterling, David W. Fahey, Thierry Fichefet*, Gregory Fiato, Piers M. de F. 

Forster*, Pierre Friedlingstein, Congbin Fu, Yoshiyuki Fuji, John Fyfe, Xuejie Gao, 

Amadou Thierno Gaye*, Nathan Gillett*, Filippo Giorgi, Jonathan Gregory*, David 

Griggs, Sergey Gulev, Kimio Hanawa, Didier Hauglustaine, James Haywood, 

Gabriele Hegerl* , Martin Heimann* , Christoph Heinze, Isaac He1d*, Bruce Hewitson, 

Elisabeth Holland, Brian Hoskins, Daniel Jacob, Bubu Pateh Jallow, Eystein Jansen*, 

Philip Jones, Richard Jones, Fortunat Joos, Jean Jouzel, Torn Karl, David Karoly * , 

Georg Kaser, Vladimir Kattsov, Akio Kitoh, Albert Klein Tank, Reto Knutti, Toshio 

Koike, Rupa Kumar Kolli, Won-Tae Kwon, Laurent Labeyrie, Rene Laprise, Corrine 

Le Quere, Herve Le Treut, Judith Lean, Peter Lemke, Sydney Levitus, Ulrike 

Lohmann, David C. Lowe, Yong Luo, Victor Magana Rueda, Elisa Manzini, Jose 

Antonio Marengo, Maria Martelo, Valerie Masson-Delmotte, Taroh Matsuno, Cecilie 

Mauritzen, Bryant Mcavaney, Linda Mearns, Gerald Meehl, Claudio Guillermo 

Menendez, John Mitchell, Abdalah Mokssit, Mario Molina, Philip Mote*, James 

Murphy, Gunnar Myhre, Teruyuki Nakajima, John Nganga, Neville Nicholls, Akira 

Noda, Yukihiro Nojiri, Laban Ogallo, Daniel Olago, Bette Otto-Bliesner, Jonathan 

Overpeck*, Govind Ballabh Pant, David Parker, Wm. Richard Peltier, Joyce Penner*, 

Thomas Peterson * , Andrew Pitman, Serge Planton, Michael Prather*, Ronald Prinn, 

Graciela Raga, Fatemeh Rahimzadeh, Stefan Rahmstorf, Jouni Raisanen, Srikanthan 

(S.) Ramachandran, Veerabhadran Ramanathan, Venkatachalam Ramaswamy, 

Rengaswamy Ramesh, David Randall*, Sarah Raper, Dominique Raynaud, Jiawen 

Ren, James A. Renwick, David Rind, Annette Rinke, Matilde M. Rusticucci, 

Abdoulaye Sarr, Michael Schulz*, Jagadish Shukla, C. K. Shum, Robert H. Socolow*, 

Brian Soden, Olga Solomina*, Richard Somerville*, Jayaraman Srinivasan, Thomas 

Stocker, Peter A. Stott*, Ron Stouffer, Akimasa Sumi, Lynne D. Talley, Karl E. 

Taylor*, Kevin Trenberth*, Alakkat S. Unnikrishnan, Rob Van Dorland, Ricardo 

Villalba, Ian G. Watterson*, Andrew Weaver*, Penny Whetton, Jurgen Willebrand, 

Steven C. Wofsy, Richard A. Wood, David Wratt, Panmao Zhai, Tingjun Zhang, De'er 

Zhang, Xiaoye Zhang, Zong-Ci Zhao, Francis Zwiers* 

Union of Concerned Scientists 

Brenda Ekwurzel, Peter Frumhoff, Amy Lynd Luers 
295 


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Global Warming: Forecasts by Scientists versus Scientific Forecasts 1021 

Channel 4 "The Great Global Warming Swindle" documentary (2007) 

Bert Bolin, Piers Corbyn*, Eigil Friis-Christensen, James Shitwaki, Frederick Singer, 

Carl Wunsch* 

Wikipedia's list of global warming "skeptics" 

Khabibullo Ismailovich Abdusamatov*, Syun-Ichi Akasofu*, Sallie Baliunas, Tim 

Ball, Robert BaIling*, Fred Barnes, Joe Barton, Joe Bastardi, David Bellamy, Torn 

Bethell, Robert Bidinotto, Roy Blunt, Sonja Boehmer, Andrew Bolt, John Brignell*, 

Nigel Calder, Ian Castles*, George Chilingarian, John Christy*, Ian Clark, Philip 

Cooney, Robert Davis, David Deming*, David Douglass, Lester Hogan, Craig Idso, 

Keith Idso, Sherwood Idso, Zbigniew Jaworowski, Wibjorn Karlen, William 

Kininmonth, Nigel Lawson, Douglas Leahey, David Legates, Richard Lindzen*, Ross 

Mckitrick*, Patrick Michaels, Lubos Motl*, Kary Mullis, Tad Murty, Tim Patterson, 

Benny Peiser* , Ian Plimer, Arthur Robinson, Frederick Seitz, Nir Shaviv, Fred Smith, 

Willie Soon, Thomas Sowell, Roy Spencer, Philip Stott, Hendrik Tennekes, Jan Veizer, 

Peter Walsh, Edward Wegman 

Other sources 

Daniel Abbasi, Augie Auer, Bert Bolin, Jonathan Boston, Daniel Botkin*, Reid 

Bryson, Robert Carter*, Ralph Chapman, Al Gore, Kirtland C. Griffin*, David 

Henderson, Christopher Landsea*, Bjorn Lomborg, Tim Osborn, Roger Pielke*, 

Henrik Saxe, Thomas Schelling*, Matthew Sobel, Nicholas Stern*, Brian Valentine*, 

Carl Wunsch*. Antonio Zichichi. 
296 

Senator BOXER. Thank you very much. 

And now, last but not least, by any means, is Andrew Wetzler, 

Director, Endangered Species Project for the Natural Resources Defense Council. Welcome, sir. 

STATEMENT OF ANDREW E. WETZLER, DIRECTOR, ENDANGERED SPECIES PROJECT, NATURAL RESOURCES DEFENSE 

COUNCIL 

Mr. WETZLER. Thank you for having me, Madam Chairman, 

thank you, members of the Committee. 

You have my written statement, and rather than reiterating it 

now, I thought that I could just briefly respond to three of the 

points that we have heard in testimony from panelists, and I think 

questions from the Senators throughout the day. 

The first is with regard to the role of modeling. Now, modeling 

is obviously a very important part of the Fish and Wildlife Service’s 

conclusion that polar bears are threatened with extinction because 

of global warming. But it is not by any means the only basis. In 

fact, there are two separate, empirical, peer-reviewed bases for 

coming to that conclusion. 

First are literally dozens of published papers observing behavioral and population changes in polar bear populations around the 

world. These include population declines, increased pup and young 

polar bear mortality, starvation in some populations, male polar 

bears turning to cannibalism in some populations, an increase in 

spike in drownings during storm events, and alterations in essential polar bear behavior, such as the location of maternal dens. 

Now, all of those empirical observations are completely consistent with and indeed, are predicted by the decline of sea ice 

caused by global warming. 

Second, a lot of the declining sea ice, as has been pointed out, 

and as is illustrated by the exhibit showing the decline of sea ice 

from 1980 to 2007, is in fact empirical. Those pictures are not forecasts, they are not models. That is observed sea ice loss. That is 

a sea ice loss that represents a million square miles of polar bear 

habitat. That is six Californias. 

The second point I wanted to make very briefly was to respond 

to some of the testimony that we have heard about the Marine 

Mammal Protection Act. Now, there is no doubt that the Marine 

Mammal Protection Act is an important, landmark law in protecting marine mammals around the world. But the suggestion that 

the Endangered Species Act does not provide any additional or special protections for the polar bear if the polar bear was to be listed 

I think is just false. 

And just very briefly, there is no equivalent of the Section 7 consultation procedure that we have heard so much about today in the 

Marine Mammal Protection Act. There is no requirement in the 

Marine Mammal Protection Act to protect habitat essential to the 

conservation of the species. That is an explicit requirement under 

the Critical Habitat Provisions of the Endangered Species Act. And 

there is no requirement in the Marine Mammal Protection Act 

which is present in the Endangered Species Act to prepare a recovery plan for a species, which would be a very important part of savVerDate Aug 31 2005 12:30 Jan 15, 2014 Jkt 000000 PO 00000 Frm 00302 Fmt 6633 Sfmt 6633 S:\_EPW\DOCS\82737.TXT VERN
297 

ing the polar bear in the long term, as the obligation under the Endangered Species Act to prepare a recovery plan for the polar bear. 

Finally, I just wanted to briefly address, I think, the coincidence 

and timing between the delay that the U.S. Fish and Wildlife Service took, the extra legal delay, and the proposed lease sale that is 

going to go forward in the Chukchi Sea on February 6th. Senator 

Boxer, I think that you were right to point out that this has raised 

suspicions in many people’s minds. I think given the history of this 

Administration, those suspicions are well-founded. 

But even if we want to give Director Hall the benefit of the 

doubt, and the Fish and Wildlife Service, and assume that the 

delay was simply caused by bureaucratic reasons, I think it is essential to recognize that there is absolutely no reason on the other 

side of the equation, on the Minerals Management Service side of 

the equation, to move ahead with this lease sale now. There is 

nothing preventing the Secretary of the Interior form simply reopening the decision to proceed with the lease sale and hold it in 

abeyance until the Fish and Wildlife Service makes a considered 

decision about whether or not to list the polar bear. At a minimum, 

I would urge the Administration to take that very common sense 

step, which I think would defuse a lot of these suspicions. 

Thank you. 

[The prepared statement of Mr. Wetzler follows:] 

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~DC NATURAL RESOURCES DEFENSE COUNCIL 

Statement of 

Andrew E. Wetzler 

Direetor, Endangered Speeies Project 

Natural Resources Defense Council 

Before the 

Committee on Environment and Public Works 

United States Senate 

January 30, 2008 
299 


82737.118

Introduction 

Good morning Madam Chairman and Members ofthe Committee. My name is Andrew Wetzler 

and I am the Director ofthe Endangered Species Project for the Natural Resources Defense 

Council (NRDC). NRDC is a not-for-profit environmental advocacy organization with over I 

million members and activists served from offices in New York, Washington, D.C., Los 

Angeles, San Francisco, Chicago, and Beijing. NRDC's mission is to safeguard the Earth: its 

people, its plants and animals, and the natural systems on which all life depends. I thank the 

Committee for inviting me to testify today about threats and protections for the polar bear, one of 

the world's most spectacular and well-recognized animals. 

Sadly, today polar bears stand on the brink of extinction. Threatened by a combination of factors 

ranging from toxic contamination to oil and gas pollution but, most importantly, global warming, 

polar bears are seeing the sea ice habitat on which they depend disappear at an alarming rate. 

There is now overwhelming scientific agreement that sea ice loss in the Arctic threatens polar 

bears with extinction. The International Union for the Conservation of Nature's Polar Bear 

Specialist Group has officially categorized the polar bear as a "vulnerable" species, defined as a 

species "facing a high risk of extinction in the wild." 1 Based on the "best scientific and 

commercial data available," the United States Fish and Wildlife Service has proposed c1assitying 

the polar bear as a threatened species under the federal Endangered Species Act, 16 U.S.C. §§ 

1531, et seq., and, after an extensive review, the United States Geological Survey has concluded 

I IUCN (2001). 
300 


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that two-thirds of the worlds polar bears, including all polar bears in Alaska, are likely to be 

extirpated by 2050. 2 

As grim as the situation facing polar bears is, it is not hopeless. Prompt action now to increase 

protection for polar bears throughout their range, combined with concerted action by Congress to 

control and reduce greenhouse gas emissions is needed ifpolar bears are to survive. Indeed, the 

best available science clearly indicates that future sea ice extent could be significantly affected 

by reductions in the emission of global warming pollution. 3 By stabilizing and gradually 

reducing carbon dioxide concentrations and significantly reducing concentrations of shorterlived greenhouse gases, it should be possible to stabilize arctic sea ice extent and eventually 

allow for it to recover. While the situation confronting polar bears is critical, it is not too late if 

we act now. 

It is thus particularly disturbing that the Fish and Wildlife Service has repeatedly delayed making 

a final decision about whether to protect polar bears under the Endangered Species Act. A 

formal petition to protect the polar bear was filed under the Endangered Species Act in February, 

2005. Yet, despite the Endangered Species Act's clear requirement that the Fish and Wildlife 

Service make a final determination about the polar bear's status no later than two years after such 

a petition is filed, 16 U.S.C. § 1533(b), almost three years later the polar bear is still not 

protected. In January, the Fish and Wildlife Service announced that it would delay making a 

2 Amstrup et al. (2007). 

3 Dumer et a!. (2007). 
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82737.120

final decision about whether to protect the polar bear for at least another month. 4 This 

announcement came on the heels of the U.S. Mineral Management Service's plans to lease 

46,000 square miles of key polar bear habitat in the Chukchi Sea for oil and gas development, 

home to between 1,500 and 2,000 bears, on February 6, 2008. 5 

Global Warming Threatens the Polar Bear With Extinction 

The Endangered Species Act requires that decisions to list a species as either "endangered" or 

"threatened" be made "solely on the basis ofthe best scientific and commercial data available." 

16 U.S.C. § 1533(b)(l)(A). Even a cursory review of the available scientific literature leaves 

little doubt that polar bears are threatened by global warming. 

Polar bears (Ursus maritimus) are pagophilic ("ice-loving") mammals whose preferred habitat is 

the annual sea ice over the continental shelf and inter-island archipelagoes of the Arctic basin. 

Polar bears are almost completely dependent on sea-ice for hunting and migrating, and also rely 

on sea-ice to find mates and, in some populations, to provide dens for pregnant females. 6 The 

current global population of polar bears is estimated to be between 20,000 and 25,000 

individuals, divided into 19 sub-populations, all of which are located in the Arctic. Polar bear 

populations are not found outside of areas that have significant sea ice coverage for much of the 

year. 

The greatest threat to polar bears is the effect of warming and sea ice declines on the availability 

4 Slalemenl for Polar Bear Decision (January 7, 2008) (available at: 

http://www.fws.gov/newslNewsReleases/showNews.cfm?newsld=54D2A6BD·E928·94E6-6BA905F3F540B8F7) 

, Lunn el al. (2002). 

, Regehr el al. (2007); Derocher el al. (2004). 
302 


82737.121

and abundance of polar bear's main prey, ringed seals (Phoca hispida) and bearded seals 

(Erignathus barbatus).l These seal species use sea-ice as resting places, haul-out sites, feeding 

grounds and habitat to raise their cubs. Changes in sea-ice will likely impact the availability and 

abundance of seals as prey for polar bears thereby reducing polar bear fat stores, resulting in 

longer fasting periods and decreasing successful reproductive rates. As three of the world's 

leading polar bear authorities concluded in 2004, when assessing the potential impact of 

widespread changes in sea ice on the polar bear: "anything that significantly changes the 

distribution, abundance, or even the existence of sea icc will have profound etTects on polar 

bears.',8 

Based on ten climate models that have done the best job of simulating current ice conditions and 

are thus expected to do the best job of simulating future ice conditions, and using the 

Intergovernmental Panel on Climate Change ("IPCC") A I B "business as usual" scenario of 

future emissions. the U.S. Geological Survey (USGS) recently evaluated the future range-wide 

status of the polar bear.9 

The USGS divided the range of the polar bear into four "ecoregions" based on major ditTerences 

in current and projected sea ice conditions. (See Figure I, below.) These ecoregions, which 

include all 19 polar bear subpopulations, are as follows: 

7 Derocher et al. (2004); Ferguson. ct al (2005). 

S Derocher, et al. (2004), p. 164. 

9 Amstrup. et al. (2007). In the A I B scenario, atmospheric carbon dioxide concentrations reach 717 parts per 

million by 2100. 
303 


82737.122

• Seasonal Ice Ecoregion, which includes Hudson Buy, and occurs mainly at the 

southern extreme oftbe polar bear range; 

• Archipelagic Ecoregion of the Canadian Arctic: 

• Polar Basin Divergent Ecoregion, where ice is formed and then drawn away from 

near-shore areas, especially during the summer minimum ice season; and 

• Porar Basin Convergent Ecoregion, where sea ice formed elsewhere tends to 

collect against the shore. 

Figure I--Polar Bear Hubitut Ecoregiolls 

_~ ___ ~.~_._. ___ ._~.LSollrcc..:.,~nstrtl~~U29.QD,Ijg~I.I"J) __ ~ ___ '~"_~' ___ ~_' __ 

Polar Basin: 

Divergent 

Convergent 

-300 In 
304 


82737.123

Based on this modeling, USGS concluded that polar bears will completely disappear from the 

Seasonal and Divergent lee Ecoregions by the middle of this century. Polar bears may survive in 

the Archipelago Ecoregion and portions of the Convergent lee Ecoregion through the end of this 

century, however, even in these regions, the probability of extinction by century's end is still 

extremely high: over 40% in the Archipelago Ecoregion and over 70% in the Convergent Ice 

Ecoregion, under any of the sea ice projections. Table I, below. expresses the most likely 

outcome for polar bear populations in each region in a forty-five and one hundred year timeframe. 

Ecorcgion 

Seasonal Ice 

Divergent Ice 

Convergent Ice 

Archipelago 

Table I--Most Likely Modeled Outcome 

of the Four Polar Bear Ecoregions 

(Source: Amstrup et al. (2007) (Table 8». 

Time Period Most Likely Outcome Probability of Extinction 

Year 45 F\: IT\( r 177.19% 

Year 100 1 '\ I !\{ l 88.15% 

Year 45 jX !I',( T 80.33% 

Year 100 i LX 1I\ll 83.89% i 

Year 45 EX!!\( T 35.06% 

Year 100 EXI j ',CT 77.30% 

Year 45 SMALLER 10.56% 

Year 100 1\. H\(T 41.07% 

When assessing these predictions it is extremely important to bear in mind that the USGS's 

projections must be viewed as conservative. as the actual observed role of sea ice loss has 
305 


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exceeded these models predictions. This is noted throughout the USGS report (e.g. Amstrup c( 

al. (2007), pp. 34, 36). 

Indeed, as shown in Figure 2, after the USGS report was released. scientists reported that a new 

record summer sea ice minimum had been reached in 2007. The new reported record low of 

1.59 million square miles is far less than the previous record low of 2.05 million square miles 

and 50% lower than conditions in the 19505 to the J 9705. 10 The 2007 record low is also I 

million square miles-an area approximately six times the size ofCalif()rnia-less than the longterm average minimum of 2.60 million square miles. I I 

Figurc 2--Sea ice concentration for Septembcr 2007, along with median extcnt from1953 to 

2000 (red curve), from 1979 to 2000 (orange curve), and for September 2005 (grcen curve). 

September ice extent time series from 1953 to 2007 is shown at the bottom. 

(Solfrce: Stroeve et al. (2008) (Figure J ). 

10 NSIDC 2007a,b; Stroeve et al. (2008). 

II NSIDC 2007a,b. 
306 


82737.125

This record low is far below that predicted by any of the ten climate models used by the USGS. 

Moreover, as illustrated by Figure 3, below. the 2007 minimum sea icc extent is below that 

predicted by the ensemble mean of the Stroeve et al. (2007) models for 2050. Tn other words, 

there was less ice in the Arctic in 2007 than over climate models predictedfbr 2050. 12 

Leading sea icc researchers now believe that the Arctic could be completely ice free in the 

summer as early as 2030. IJ 

Figure 3--Actual Observed Sea Ice Extent (in Red) Compared to Model ProJections 

(Sollrce: After DeWeaver (2007): Stroeve ot al. 2007.) 

It is also worth noting that the carbon dioxide concentrations cited for these scenarios in 2100 are just the level 

projected to be attained in that year, not the level at which C02 concentrations wonld be stabilized. Indeed, under all 

of these scenarios C02 concentrations would continue to rise indefinitely after 2100. 

13 Stroeve et a1. (2008). 
307 


82737.126

The effects of the decline of sea ice can already be seen in many polar bear populations around 

the world, and are paliicularly pronounced in the Western Hudson Bay, the polar bear's 

southern-most population. 

Over the past two decades the condition of adult polar bears in the Hudson Bay has deteriorated 

and this has been reflected in the reproductive cycle offemales and in total population levels. In 

1987 there were 1,194 polar bears in the Western Hudson Bay. In 2004 only 935 were recorded, 

a drop of 22%.14 This decline is reflective of reduced breeding success and lower survival of 

senescent-adult polar bears (less than 20 years in age) and can be attributed to a combination of 

overharvest and "increased natural mortality associated with earlier sea ice breakup:' 15 

Scientists now predict that "more northerly polar bear populations will experience declines in 

demographic parameters similar to those observed in western Hudson Bay" in light of the "long 

term and severe'" forecasts of ice break up in the Arctic. II> 

And, in fact, the Western Hudson Bay population is not the only one that is already suffering 

from the effects of climate change. The Southern Beaufort Sea population is now also classified 

by the Polar Bear Specialist Group as declining. 17 In addition to an overall population decline, 

the Southern Beaufort Sea population has experienced statistically significant declines in cub 

survival, cub skull size, and adu It male weight and skull size-·the same types of declines 

observed in Western Hudson Bay prior to the decline of that population. IS Other signs of poor 

" Aars et a!. (2006). 

" Regehr et 31. (2007), p. 2681. 

'6 Id,p. 268l. 

Aars et 31. (2006). 

IB Regehr ot 31. (2007). 
308 


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nutrition have been recorded in the Southern Beaufort Sea, where multiple female polar bears 

and their young have starved to death, 19 

There are also indications that adult male polar bears may be turning to cannibalism as a means 

to supplement their diet, Amstrup (2006) reports three instances of intraspecific predation and 

cannibalism of polar bears in the Beaufort Sea, including the unprecedented killing ofa 

parturient female in her maternal den, The authors hypothesize that these killings-which are 

the first reported in 24 years of research on polar bears in the southern Beaufort Sea and 34 years 

in northwestern Canada-may be caused by nutritional stress due to longer ice-free seasons, A 

similar incident was recently reported among polar bears on Phippsoya. in Norway's Svalbard 

Islands. 20 

The retreat of sea ice may also result in significant behavior changes in polar bears, some of 

which put bears at increased risk of mortality. Most female polar bears, for example. exhibit a 

preference for den locations that are on land. As sea-ice extent declines, and hence the sea-ice 

edge moves northwards. polar bears will have to travel greater distances, and expend more 

energy, to reach their preferred den areas or they will have to change den locations. Sometimes 

this can have catastrophic consequences. For example. in Alaska's Southern Beaufort Sea. 

survey results reported by the Minerals Management Service reveal that in September 2004 at 

least four polar bears, and up to twenty-seven, drowned off the north coast of Alaska where the 

sea-ice retreated a record 160 miles from the coast, 21 As an alternative to traveling long 

19 Regehr et al. (2006). 

20 Stone and Derocher (2007). 

Monnett et al. (2005). 
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distances, some female polar bcars may choose to leave thc ice at break-up and summer in the 

location of their den. Although this avoids additional energy expended during travel, it will 

instead require an additional fasting period because females will leave the sea-ice feeding 

grounds earlier than preferred, possibly resulting in fasting of up to eight months. 22 

Some polar bear populations also den in snow and changes in the proportion of precipitation 

falling as snow compared to rain will affect such denning behavior. Thc Arctic Council and the 

International Arctic Science Committee reports that den collapses due to increased frcquency and 

intensity of spring rains has already occurred in some cases, resulting in the death of some 

females and their cubs.2J In addition to an increase in unseasonable rains, global warming is 

expected to increase the frequency, extent, and season for fires in Arctic regions which, in turn, 

may significantly reduce availability of suitable denning habitat on land 24 

In short, global warming thus poses an immediate, accelerating, and mortal threat to polar bear 

populations around the world. 

Other threats to polar bears 

As polar bear populations continue to be affected by the loss, retreat, and earlier break up of sea 

ice, it is extrcmely important to minimize other stresses on the population. In particular 

continued and expanded oil and gas exploration and development, toxic contamination and, in 

Derocher et al. (2004), 

2l AC[A (2004), 

24 Richardson (2007). 
310 


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some populations, over-harvesting are all additional sources of disruption, injury, and mortality 

to polar bears. Some of these threats are expected to be exacerbatcd by global warming. 

Oil and Gas Exploration 

Oil and gas exploration can have a significant effcct on polar bear populations. Oil and gas 

activities can alter important onshore and offshore polar bear habitat and is often accompanied 

by air traffic, vessel traffic and other supporting infrastructure. A large oil spill could havc 

catastrophic consequences for polar bear populations. In addition, anthropogenic noise pollution, 

generated by seismic exploration and oil and gas development activities, may also have a 

negative effect on polar hears. Denning polar bears, for example, are likely to be susceptible to 

disturbance from activities related to oil and gas exploration and development. Noise 

disturbance from seismic activities of oil exploration as well as ground and air transportation can 

be heard within 300 meters ofdens. 25 A recent study of auditory evoked potentials found that 

polar bears hear acutely across an unexpectedly wide frequency range and, on this basis, the 

authors expressed caution over the introduction of noise into their environment. 26 Exposure to 

noise from drilling and vehicles may cause bears to abandon their dens.27 In other 

circumstances, den disturbance has been linked to lower birth weight in female cubs. 28 

Of particular concern is pending Lease Sale 193 in the Chukchi Sea. Polar bears in the Chukchi 

Sea are thought to number between 1,500 and 2,000 individuals (although much about the 

population still remains uncertain). Lease Sale 193 would open up 46,000 square miles of polar 

" Blix and Lentfer (1992). 

Nacthingall (2007). 

27 Amstrup (1993); Linnell et al. (2000). 

28 Lunn et al. (2004). 
311 


82737.130

bear habitat in the Chukchi Sea to oil and gas development. As can be seen from Figure 4 and 

Figure 5, below, polar bears are widely distributed throughout the Chukchi Sea, as are polar bear 

denning sites. 29 

Figure 4--Chuckchi Sea polar bear distribution 

(Source: Durner et al (2007)) 

Figure 1. Boundar! of the full Chukchi Sea study area (intermediate gray) as defined by a 25 

km x 25 km rasterized polygon that encompassed offshore t>25 km) waters between 170"E156'"W and 66"N-80~N. Dot symbols denote all polar bear satellite relocations vvlthin 170?E156'W and 66"N--80'N that were collected during the autumn months (SeptemberNovember), mostly from an early.vintage field study (1987-1994) of the Chukchi Sea bear 

population (red), and exclUSively from a recent-vintage field study (1997-2005) of the Beaufort 

Sea bear population (blue). 

Fischbach ct a1. (2007). 
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82737.131

Figure 5--Distributiou of polar bear den entrance locations 

(Sollrce: Fischbach ef aJ. (2007)) 

As illustrated in Figure 5, there has been an apparent shift in denning locations in response to 

changing sea ice stability and the lengthening of tile Arctic melt season. Significantly, 

researchers are also beginning to observe large scale polar bear movements, including the 

movement of bears from the Canadian portion of the Southern Beaufort Sea population into the 

Chukchi Sea (see Figure 6, below). As conditions in the Southern Beaufort Sea decline, the 

Chukchi Sea's habitat may become increasingly impOliant. 
313 


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Figure 6--Selected Locations of Bears 35496 and 35568 through 12 January 2008 

(Source: Andrew Derocher, unpub!. data.) 

Polar Bear Locations - January, 2008 

In addition to the risks that accompany any oil development, Lease Sale 193 also poses an 

unacceptable risk ofa large oil spill. The Mineral Management Service's Final Environmental 

Impact Statement for Chukchi Sea Planning Area Oil and Gas Lease Sale 193 and Seismic 

Surveying Activities (FEIS) estimates that there is at least a 40%, and as much as a 54%, chance 

of a large spill if the sale areas are developed. 3o Bears who come in contact with oil generally 

attempt to clean themselves, ingesting the oil, which can be fatal. 

JO Minerals Management Service (2007), p. IV-2; Table A.I-27. 
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82737.133

Toxic Contamination 

In addition to threats from global warming and oil and gas development, the polar bear, as one of 

the Arctic's apex predators. is particularly vulnerable to biocontamination from a range of 

substances, including persistent organic pollutants (or "POPs") and heavy metals. Its 

vulnerability is exacerbated by certain aspects of its biology, such as its long annual fast, which 

tends to elevate its toxicity levels at a time when the animal is under greatest stress. Moreover, 

global warming stands to create new pathways for concentration of pollutants in the region, with 

the remobilization oftoxics from melting permafrost and the rise of industrial activity as the 

climate warms. 

In general, pollutant levels in the Arctic remain high and in some cases arc increasing. Sampling 

taken from 1996 to 2002 indicates that regional concentrations of certain chlorinated 

hydrocarbon contaminants (CHCs) did not decline as might have been expected in response to 

reduced produetion. J1 Based on their CHC loads, the East Greenland and Svalbard polar bcar 

populations are at greatest risk of health effeets.12 Perfiuorochemieals (PFOS), whose worldwide circulation was only recently discovered, are considered important contaminants in 

Greenland, with biomagnilication of PFOS observed in the polar bear populations there and in 

South Hudson Bay.3J Some perfiuorochemieals are reported to have rapidly increased in the 

Canadian Arctic as well J4 and have been found in signilicant concentrations in polar bears of the 

Beaufort and Chukchi Seas, though at lower levels than in North Atlantic populations. 35 

31 Verreau It et al. (2005a) 

12 [d. 

13 Bossi et al. (2005), Smithwick et 31. (2005). 

J4 Braune et al. (2005): see also Prevedouros et al. (2005). 

35 Kannan et al. (2005), Smithwick et al. (2005). 
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82737.134

Concentrations of Polybrominated diphenyl ethers (PBDEs) have for the first time been reported 

in Alaskan bears.J6 In addition, according to the Arctic Monitoring and Assessment Programme 

("A MAP"). the region as a whole remains highly vulnerable to the effects ofradionuclides. 37 

Several recent studies provide further indication of the health impacts of contaminants. Some 

congeners have been shown to significantly affect lymphocyte production in polar bears, leaving 

the animals susceptible to infection.)H On the basis of that study and others, a number of 

Canadian and Norwegian researchers have concluded that organochlorines could already be 

having population-level impacts on the species.J9 A separate study on East Greenlandic polar 

bears correlated liver innammation with long-term exposure to organohalogens, such as PBDEs, 

which have also been linked to renallesions. 4o 

Additional research that has emerged, particularly on brominated name retardants like PBDEs, 

which are rising in the Arctic due to long-range transport from western Europe, eastern North 

America, and other industrial regions. 41 Studies have demonstrated slow biodegradation42 and 

high biomagnification 43 of certain PBDEs in a number of polar bear subpopulations, and a study 

of the food web in the Norwegian Arctic indicates that some congeners already exceed detection 

thresholds even in zooplankton and biomagnify specifically through the trophic system. 44 

PBDEs and other organohalogens were shown to adversely affect the male and female genitalia 

36 Kannan et al. (2005). 

J7 AMAP (2004). 

38 Lie et al. (2004); see also AMAP (2005). 

" Fisk et al. (2005). 

40 Sonne ct al. (2005). 

" de Wit et al. (2006). 

42 Dietz et al. (2007). 

;] Muir et al. (2006) . 

. " Serino et al. (2006). 
316 


82737.135

of East Greenland polar bears, reducing their size and robustness and potentially compromising 

reproduction in these animals. 45 The past year also saw further evidence on the health impacts of 

other contaminants. Organochlorines, for example, were found to alter hormone production in 

both male and female polar bears; modeling indicates that even low levels of chronic exposure to 

these chemicals can impair the reproduction and immune system function oftheir offspring.46 

Of particular note is the possible increase in global mercury deposition, despite emission 

reductions adopted in the 1980s by North America and Europe. 47 Rising concentrations in the 

Northwest Atlantic and other parts of the Arctic have been attributed to long-range transport 

from Asia, which now accounts for roughly half of the world's mercury pollution48 

Concentrations are substantially higher in the Canadian Arctic than elsewhere, and there is strong 

evidence that levels in Canadian polar bears have increased substantially since the beginning of 

the industrial age. 49 The higher levels that have been reported in the Canadian Arctic may be 

due, in part, to global warming. 5o Indeed. the increased precipitation that climate change is 

expected to bring is likely to make the Arctic a more efTective trap for heavy metals. 51 While 

mercury concentrations have declined in East Greenlandic polar bears, consistent with emission 

reductions from European coal plants. levels remain about 11 times higher than the pre-industrial 

baseline. 52 

45 Sonne et al. (200Gb). 

46 Ropstad et al. (2007). 

47 AMAP (2005). 

4' Dietz et al. (2006). 

49 Braune et al. (2005). 

50 Braune et al. (2005 l. 

SI Macdonald et al. (2005). 

" Dietz et al. (2006). 
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82737.136

I would note that this Committee is now considering impoltant legislation, the Mercury Export 

Ban Act of2007, which will help stem global mercury pollution, by banning the export of 

elemental mercury from the United States. Elemental mercury is still used in a number of 

commercial products and industrial processes worldwide. While the US has become increasingly 

vigilant about managing mercury within its borders, much of our mercury is sold on the global 

market, where it is used in highly polluting industries, mainly in developing countries. Because 

mercury is a global pollutant, mercury emitted in those countries can travel around the world, 

and end up in Arctic waters and fish and wildlife, including polar bears. By preventing the sale 

of United States mercury overseas, the Mercury Export Ban Act of 2007 will help limit the US 

contribution to the overall global mercury contaminant pool. I urge the committee to consider 

and pass this important legislation as quickly as possible. 

Overharvest 

While sports hunting of polar bears is currently prohibited in the United States, Russia, and 

Norway, some polar bear populations are subject to unsustainable harvest levels either as the 

result of poaching (as is the case in Russia) or hunting practices (as is the case in Greenland and 

some parts of Canada). Over-harvest of polar bears thus has a concentrated, but potentially 

severe, effect on several polar bear populations, some of which have already been classified as 

"declining" by the Polar Bear Specialist Group.53 

Poaching of polar bears in the Russian Federation continues to be a serious problem. In 2002, 

for example, experts estimate that poachers took between 250 and 300 bears on the north coast of 

53 Aars el aJ. (2006). 
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Chukotka. 54 Poaching may be exacerbated by receding sea ice, which forces polar bears onto 

shore carly. And more polar bear skins and other commercial products are being advertised on 

web sites than ever before. 55 However, the Agreement between the United States of America 

and the Russian Federation on the Conservation and Management of the Alaska-Chukotka Polar 

Bear Population, which was recently ratified by the U.S. Senate, is an important tool whose 

implementation may help to alleviate illegal harvest of polar bears in Russia. 

In Canada and Greenland, the levels of legal harvest of some polar bear populations are far too 

high and, in and of themselves, may threaten the continued existence of these populations. For 

example, despite the scientific evidence, discussed above, that the western Hudson Bay 

population is experiencing severe declines, the Fish and Wildlife Service has noted that, while 

this population has a maximum sustained yield of only 44 bears, Canada allows 62 bears to be 

removed from the western Hudson Bay. 56 A recent study also concluded that selective harvest 

of male polar bears by SPOlts hunters could lead to a "sudden and rapid reproductive collapse" 

due to a combination of reduced population density and altered female-to-male ratios. 57 

Moreover, receding sea icc, caused by global warming, may bring more polar bears in contact 

with people, increasing hunting opportunities and potentially leading to misperceptions of polar 

bear abundance. 58 

54 Ovsiyanikov (2003). 

55 Jd. 

56 72 Fed. Reg. al 1084. 

S7 Molnar ct al (2008). 

58 Stirling and Parkinson (2006). 
319 


82737.138

When discussing hunting, it is important to emphasize, however, that protecting the polar bear 

under the Endangered Species Act will not affect subsistence harvest by native Alaskans. 

Section 9(e) of the Endangered Species Act provides that the Act's prohibition against "taking" a 

listed species does not apply to Alaskan Natives (or non-native residents of Native villages) if 

such taking is primarily for subsistence purposes. 16 U.S.C. § 1539( e). The Act also exempts 

"authentic native article of crafts and clothing" produced t1'om listed species . .!Q, Significantly, 

the Marine Mammal Protection Act, which already regulates native harvest of polar bears in 

Alaska, contains a nearly identical provision. See 16 U.S.C. § 1371(b) ("Exemptions for 

A laskan natives"). 

Prompt Action is Needed to Save the Polar Bear 

Congress Must Pass Legislation to Control Global Warming Pollution 

The situation facing polar bears is undeniably grim. But it is not hopeless. The USGS Reports 

illustrate this very point. As discusses above, in its reports the USGS considered several 

scenarios developed by the IPCC in implementing its models. These scenarios indicate that 

arctie sea ice eonditions during the eoming century will be sensitive to future emission levels. 

Scientists have noted, for example, that the ensemble-mean summer minimum sea ice extent is 

reduced by 65% in the highest emission scenario considered (A2) and by 45.8% in the lowest 

scenario considered (B I), thus suggesting that reducing global warming emissions can 

substantially affect future reductions of sea ice in polar bear habitat. 59 In fact, the USGS reports 

themselves note that: 

59 DeWeaver (2007); Zhang and Walsh (2006). 
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82737.139

"Differences between the AlB and B I scenarios (for the CCSM3 model) in 

timing and relative magnitude of projected sea ice extent are remarkably similar 

to the inverse of their imposed C02 loadings ... ,,60 

The U.S. government as well as many other governments and independent researchers have 

developed climate mitigation scenarios that would stabilize greenhouse gas concentrations well 

helow the levels considered in the scenarios used by the USGS reports. For example. the US. 

Climate Change Technology Program Strategic Plan (DOE/PI-OOOS. 2006: 3S) considers a "Very 

High Constraint" scenario in which total radiative forcing from greenhouse gases is stabilized at 

less than 3.S W/m2, corresponding to stabilizing C02 concentrations at approximately 4S0 parts 

per million (ppm). The Union of Concerned Scientists recently reviewed scenarios designed to 

limit total global warming to no more than 2 degrees Celsius, concluding that this is feasible if 

the United States reduces its emissions hy 4 percent per year starting in 20 I 0, assuming other 

countries also take appropriate action. 51 Finally, Dr. James Hansen, Director of NASA's 

Goddard Institute for Space Studies, has proposed an "alternative" scenario aimed at keeping 

additional global warming well below I degree Celsius. 52 His recent review of current trends 

concludes that it is still possihle to achieve this objective. 6

] Thus, by stabilizing and gradually 

reducing C02 concentrations while significantly reducing concentrations of shorter-lived 

greenhouse gases, it should be possible to stabilize arctic sea ice extent and eventually allow for 

it to recover. This observation is particularly impoliant given the possihility that some polar 

bear refugia may continue to exist in the Arctic through the end of the century. 

60 Durner, et al (2007), p. 16. See also Holland el al. (2006) (finding that periods of rapid decline in arctic sea ice 

are less likely under the 131 scenario than under the A IB or A2 scenarios). 

61 Luers el al. (2007). 

62 Hansen, et .1 (2000). 

63 Hansen and Sato (2007). 
321 


82737.140

In order to accomplish this goal, it is crucial for Congress to enact comprehensive legislation to 

reduce global warming pollution. The Lieberman-Warner Climate Security Act of2008 is one 

of the strongest global warming bills currently being considered by Congress and I would like to 

thank Senator Boxer and other members of the Committee for their leadership in both 

strengthening and moving this bill through the Committee last year. NRDC urges you to move 

the Lieberman-Warner bill to the Senate floor as soon as possible and we stand ready to assist 

you to help further strengthen the bill. NRDC will also work to prevent any amendments from 

passing that would weaken the emission limits, which will make it much more challenging to 

stablalize atmospheric concentrations of C02 at a level that is sufficient to save the polar bear 

and the thousands of other species that are threatened by global warming. 

Protecting the Polar Bear Under the Endangered Species Act Will Help Save the Species 

Protecting the polar bear under the Endangered Species Act will also provide crucial long and 

short-term protections to the species. Listing the polar bear under the Endangered Species Act 

will have the following immediate benefits. 

First, once a species is listed as threatened or endangered, federal agencies must ensure, through 

a process known a "consultations" with the Fish and Wildlife Service, that any action they 

authorize, fund, or carry out will not 'jeopardize the continued existence" of the species or 

"result in the destruction or adverse modification" of that habitat. 16 U.s.c. § I 536(a)(2). 

While the Section 7(a)(2) duty not to "jeopardize the continued existence" of listed species helps 
322 


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to ensure their survival, the critical habitat duty allows these species to recover so that they may 

eventually be delisted,64 

The consultation process, which can be informal or formal in nature, almost never stops projects 

from going forward. 65 That is because the Fish and Wildlife Service is required to provide 

federal agencies with a list of "reasonable and prudent measures" that can be implemented to 

reduce the impact of proposed federal actions and allow the action to proceed. 16 U.S.C. § 

1536(b)(4). Thus, in practice, the consultation process will provide an important safety net (or 

polar bears, by requiring federal agencies to implement additional safeguards to the species, 

while allowing them to go forward. Significantly, this consultation requirement will apply to 

many of the threats facing polar bears, from toxic pollution, to oil and gas development, and, 

most importantly, sources of global warming pollution that require a fedcral permit. 

Second, the Fish and Wildlife Serviee will be required to designate "critical habitat" for the polar 

bear. 16 U.S.c. § I 533(a)(3)(A)(i). Critical habitat is defined in Section 3 of the ESA as: 

(i) the specific areas within the geographical area occupied by a species, at the 

time it is listed in accordance with the [Endangered Species Act], on which are 

found those physical or biological features (I) essential to the conservation of the 

species and (II) that may require special management considerations or 

protection; and (ii) specific areas outside the geographical area occupied by a 

species at the time it was listed .... upon a determination by the Secretary that such 

areas are essential for the conservation of the species." 

64 Sec Gifford Pincho/ Task Force v. 

Fish and Wildlife Serv .. 245 F.3d 434 

fish and Wildlile Sal'. , 378 F.3d 1059 (9'" Cir. 2004); Sierra ('fub v. US 

Cir. 2001). 

"j According the Endangered Species Coaliton, a study by the Fish and Wildlife Service found that between 1987 

and 1992 the consultation process only resulted in the cancellation of .05% of proposed federal actions. See 

Endangered Species Coalition, "ESA Agenc)' Action Facts" (available at: 

hl!J2:.!!WWw.slopextitlD12n,()!Q/sitelsffilt2hXQ)l.lsQLl1J§ 1809!k.C6EOIESA Agency Actions.hlm) 
323 


82737.142

16 U.S.C. § 1532(5)(A). As discussed above, designating critical habitat will provide additional 

protections to essential polar bear habitat, including both onshore habitat used for maternal 

denning and sea ice habitat used for most of the bears' essential biological functions. 

Third, protecting the polar bear under the Endangered Species Act will impose a prohibition 

against any individual "taking" of a polar bear without a permit. It should be noted, however, 

that, while the Endangered Species Act prohibits the "take" of a species listed as endangered, 

this same prohibition does not apply to threatened species. except by regulation. 16 U.S.C. § 

1533(d). Thus, under certain circumstances, the Service may issue regulations under Section 

4(d) of the ESA (these regulations are generally referred to as "special rules") that authorize 

activities that result in the take of threatened species that could not be authorized for endangered 

species. While NRDC believes that the scientific evidence now warrants an "endangered" rather 

than a "threatened" listing, it is important to note that if the Fish and Wildlife Service does list 

the polar bear as a threatened species, that designation will provide the agency with the ability to 

modify the Endangered Specics Act's taking requiremcnts for the species. Given this 

Administration's history of undercutting environmental protections, particularly when it comes 

to thc energy industry, we would urge that any such regulations be subject to vigilant oversight 

by this Committee. 

Fourth, protecting the polar bear under the Endangered Species Act will require the Fish and 

Wildlife Service to prepare a "recovery plan" for the polar bear. Recovery plans are required to 

include (I) "site specific management actions as may be nccessary to achieve the plan's goal for 

the conservation and survival of the species"; (2) "objective, measurable criteria" for 
324 


82737.143

determining a species to be recovered; and (3) "estimates of the time required" to carry out the 

recovery plan. 16 U.S.C. § 1533(1)(1 )(8). Preparing a recovery plan for the polar bear will not 

only be of enormous benefit to the species, by forcing the Fish and Wildlife Service to precisely 

confront the various threats that it faces and put the species on the road to recovery, but it will 

also force the Bush Administration to deal directly and quantifiably with the climate change 

science in a way it has mostly resisted to date. 

Finally, listing the polar bear under the Endangered Species Act will be a powerful 

acknowledgement of the toll that global warming is taking not just on polar bears, but on the 

entire Arctic ecosystem and, indeed, on wildlife around the world. Polar bears may be the first 

species listed under the Endangered Species Act principally because of global warming, but if 

we do not act soon to stabilize and reduce greenhouse gas emissions, they will be far from the 

last. 

The Fish and Wildlife Service's History of Delays in Protecting Polar Bears 

Given the overwhelming evidence that polar bears are facing extinction because of global 

warming, the need for prompt action to protect the polar bear, and the many benefits that 

Endangered Species Act protections would provide, it is particularly dismaying that the Fish and 

Wildlife Service has continually sought to delay making a final decision about whether to list 

polar bears. 

The Endangered Species Act allows "any person" to petition the Secretary of the Interior or 

Secretary of Commerce to list a species as either "endangered'" or "threatened.'" 16 U.S.c. § 
325 


82737.144

1533(a). An "endangered species" is defined as any species "which is in danger of extinction 

throughout all or a significant portion of its range." 16 U.S.C. § 1532(6). A "threatened species" 

is defined as any species "which is likely to become an endangered species within the 

foreseeable future." 16 U.S.c. § 1532(20). 

When making listing determinations, the Service must consider five statutory listing criteria: (I) 

the present or threatened destruction. modification. or curtailment of its habitat or range; (e) 

overutilization for commercial, recreational, scientific, or educational purposes; (3) disease or 

predation; (4) the inadequacy of existing regulatory mechanisms; or (5) other natural or 

manmade factors affecting its continued existence. 16 U.S.c. § 1533(a)(I). Ira species meets 

the definition of threatened or endangered because it is imperiled by anyone or more of these 

five factors, the Service must list the species. 16 U.S.c. § 1533(1). The Service must base all 

listing determinations "solely on the basis ofthe best scientific and commercial data available." 

ld. at § 1533(b)(I)(A). 

On February 16,2005, the Center for Biological Diversity petitioned the Fish and Wildlife 

Service to list the polar bear as a threatened species. The Petition was principally based on the 

threat that global warming poses to the polar bear's sea ice habitat, but also discussed ongoing 

threats from toxic contamination, oil and gas development, and overhunting. NRDC and 

Greenpeace USA formally joined the petition in July 2005. 

After a petition to list a species is filed. the Fish and Wildlife Service (acting on behalf of the 

Secretary) has ninety days to make an initial finding whether the petition presents "substantial 
326 


82737.145

scientific or commercial information indicating that the petitioned action may be warranted" (this 

is known as a "90-day finding"). 16 U.S.C. § 1533(b). If the Service answers this question in 

the affirmative, it has twelve months from the date the petition was fi led to decide whether to 

grant the petition and, if so, issue a proposed rule listing the species (known as a "I 2-month 

finding"). & 

As is typically the case, however, we received no official response (other than an 

acknowledgement of receipt) to our Petition. Accordingly, on December 15,2005, the Center 

for Biological Diversity, NRDC, and Grecnpeace sued the Fish and Wildlife Service for failing 

to respond to the Petition within the time required by the ESA.6ii In response to the lawsuit, the 

Service issued a positive 90-day tinding on February 9, 2007, and initiated a status review of the 

species. N RDC and the other petitioners, and numerous conservation groups, filed comments 

with the Fish and Wildlife Service during a public comment period that followed this finding. 

The parties also entered into a Settlement Agreement and Consent Decree that requircd the 

Service to make a preliminary decision about whether to propose the polar bear for protection 

under the ESA by the end of the year. 

On December 27,2006, the Fish and Wildlife Service issued a proposed rule to list the polar bear 

as a threatened species under the ESA, which was published in the Federal Register on January 

9,2007. 67 The proposed rule triggered another public comment period, which the Fish and 

Wildlife Service subsequently reopened twice, once to allow for the official submission of new 

GO Center/or Biological Diversity v. Kemplhorne, Civ. 05-5191 JSW (N. Dis!. Cal. Dec. 15 2005) (Complaint). 

67 Proposal to List the Polar Bear as a Threatened Species, 72 Fed. Reg. 1064·1099 (Jan. 9, 2007). 
327 


82737.146

information and once to allow public comment on the USGS studics discussed abovc. During 

these various public comment periods over 600,000 people submitted comments to the Fish and 

Wildlife Service, the overwhelming majority supporting the listing of the polar bear. Almost 

400,000 of these comments were submitted by NRDC members and activists. 

The Endangered Species Act requires that "[w]ithin the one-year period beginning on the date on 

which" a proposed rule to list a species is published in the Federal Registcr, the Fish and Wildlife 

Service must either issuc a fInal rule listing the species or withdraw it's proposed rule." 16 

U.S.C. IS33(b)(6)(A). The Fish and Wildlife Service may extend this mandatory deadline for 

six months if it tlnds that there is "a substantial disagreement regarding the sufficiency or 

accuracy of the available data relevant to the determination." 16 U.S.C. §1536(b)(6)(B)(i). 

Thus, in the absence of such a substantial disagreement, the Fish and Wildlife Service was 

required to make a final decision about whether to protect the polar bear under the Endangered 

Species Act no later than January 9th, 2008. 

On January on January 7,2008, the Fish and Wildlife Service announced that the listing decision 

would be delayed 68 While the agency did not givc a fIrm datc for publication ofthc final listing 

determination, it stated that it "expected" to make a final decision "within the next month." The 

Fish and Wildlife Service did not claim that thcre was any substantial disagreemcntjustifying a 

delay of the final listing determination. 

68 Statement for Polar Bear Decision (January 7, 2008) (available at 

http://www.t\vs.gov/news/NewsRele.'hQes!sh9WNev'C'i&fm"newsld· 54D2A6BD-E928-94E6-@A905FlE.~±QJ}jU'7.l 
328 


82737.147

It is worth noting, however, that a delay of a month is precisely long enough to allow the 

Minerals Management Service to proceed with Lease Sale 193 in the Chukchi Sea. Despite this, 

however, the Mineral Management Service has refused to delay Lease Sale 193. NRDC believes 

that it is thus incumbent upon Congress to ensure that the Department of Interior withdraw its 

Record of Decisions on Lease Sale 193 and that the sale not be allowed to proceed until the 

Mineral Management Service fully accounts for the risk that it poses to the Chukchi Sea polar 

bear population under the Endangered Species Act. including any impacts that oil and gas 

development would have on polar bear critical habitat. 

Thank you for this opportunity to address the Committee on the conservation of polar bears. 
329 


82737.148

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Dietz, R., F.F. Rigct, C. Sonne, R..I. Letcher, S. Backus, E. W. Born, M. Kirkegaard, and D.C.G. 

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Derocher, A.E., N.J. Lunn, and I. Stirling. 2004. Polar bears in a warming climate. Integrated 

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Durner, G,M" et al. 2007, Predicting the future distribution ()f polar bear habitat in the polar 

basin Fom resource selection .limctions applied 10 21st century general circulation model 

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334 

Senator BOXER. Thank you so much, Mr. Wetzler. 

I am going to have my Ranking Member question first, because 

he needs to leave, and then I will finish up. But I did want to recognize students in the back there from James Logan High School, 

Union City, California. I am very proud that you came in and that 

you care about the environment. We are very pleased that you are 

here. 

Senator Inhofe. 

Senator INHOFE. Thank you, Madam Chairman. 

Dr. Armstrong, when you were talking, this chart up here, first 

of all, did you say that you had a paper that you wrote in 1978? 

Mr. ARMSTRONG. I was writing books on long-range forecasting 

then. 

Senator INHOFE. You were writing books in 1978? 

Mr. ARMSTRONG. Well, I have been in this field for 48 years now. 

Senator INHOFE. Wow. I thought maybe I heard wrong. You are 

the forecasting expert, I recognize that. 

When I saw this before your testimony, the fact that they’re 

using the 5-years, it is my understanding that three of those years 

showed normal sea ice coverage with high numbers of polar bear 

births and only two showed receding with a slightly less births. But 

the USGS used the 2-years. Is this correct? Or is my information 

wrong? 

Mr. ARMSTRONG. I know there are a lot of questions about the 

quality of the data. My major point is, you cannot possibly use 5 

years of data to estimate a causal relationship. 

Senator INHOFE. But even with those 5 years of data, you cherrypicked the two worst years, that would be even more egregious? 

Mr. ARMSTRONG. Yes. 

Senator INHOFE. And I want to get back with another question. 

Richard Glenn, it is kind of interesting, your background, I understand you were at the University of Alaska and University of Nebraska, San Jose State and also a subsistence hunter. So you have 

been on the ground for quite some time. 

In your testimony, you take issue with the FWS focus on the 

multi-year pack ice, and their neglect of the bears’ activity on marginal ice. You also discuss how polar bears travel great distances 

to move between populations. Could you elaborate a little bit on 

that, why that is significant? 

Mr. GLENN. The polar bear is an opportunistic hunter. It will follow its nose wherever it can find food. And the scientists have documented, for example, a polar bear denning in the Beaufort Sea, 

in the central Beaufort Sea, and that polar bear then drifting with 

the ice pack as far as the Wrangell Island area. Then as soon as 

the polar bear gave birth, the mother and cubs made a beeline back 

to the Beaufort Sea. 

Now, this shows that polar bears can migrate between what you 

see as wedges on the map as population stocks. And it shows that 

part of their lifestyle is to move great distances. So how do you 

count polar bear population stocks when you have this flux between these different areas? 

Senator INHOFE. That is interesting. In the testimony, and I 

don’t remember whose it was, we talked about the number of 

things that are there for protection today, the Marine Mammal Act 

335 

has been referred to several times, there are several international 

conservation agreements, educational outreach efforts. What are 

some of the ways in which the bear is protected already, and do 

you think we really need this ESA listing in addition to those that 

are already in place. 

Mr. GLENN. Right, thank you. Several of the presenters today 

have talked about the various agreements and acts that are currently in place for protection of the polar bear. And they include 

the organizations of the Native people across the circum-Arctic and 

agreements that they have made about the harvest. What is lacking, though, is the ability, for example, to stop the poaching of 

polar bears by the Russians, where so many of the bears that live 

in our area are suffering from today. The agreements in place 

today are doing things like limiting to sustainable numbers the 

number of polar bears that are taken by subsistence hunters, by 

my people, the people that live along coastal Alaska and Arctic 

Canada. 

So the list is long. There is the Alaska Chukotka polar bear population studies, United States-Russian Polar Bear Conservation 

and Management Act, there is of course the Marine Mammal Protection Act. 

Senator INHOFE. You think those are adequate, that are there 

right now? 

Mr. GLENN. Yes. 

Senator INHOFE. And Dr. Armstrong, in your, well, first of all, 

you probably don’t know this, I have been critical of computer modeling for quite some time and the deficiencies that are there, not 

just insofar as polar bears are concerned, but insofar as anthropogenic gases and what effect they actually have on climate change. 

In your testimony, you point out that the USGS study included 

various assumptions. Can you briefly outline those assumptions? 

Mr. ARMSTRONG. Yes. There were five assumptions. The first assumption is that global warming will occur. The second assumption 

is that polar bears will obtain less food by hunting from reduced 

sea ice platform. The third is that bears will not be able to adequately obtain supplementary food, using other means from other 

sources. 

Four, the designation of polar bears as an endangered species 

will solve the problem and will not have any detrimental effects. 

And five, and I think probably the most important one, is that 

there are no other policies that would produce a better outcome 

than those based on the endangered species classification. 

Senator INHOFE. Well, I might disagree, I think your first one is 

more significant. But that is fine. 

I appreciate that very much. I regret that I won’t be able to stay 

afterwards, to come and thank you individually for coming. But you 

have come a long way, and I appreciate all five of you being here 

and your testimony. Thank you for allowing me to go first, Madam 

Chairman. 

Senator BOXER. Senator, thank you so very much. 

Well, I think if we heard some of this testimony way back when 

from people like Dr. Armstrong and Mr. Glenn, we never would 

have saved the bald eagle. And I am going to pursue that. 

336 

Mr. Glenn, you said in your statement that you are an officer of 

the Arctic Slope Regional Corporation. And I read what that organization does, so I think we will put it in the record. The Arctic 

Slope Regional Corporation is committed to developing the resources and bringing to market, meaning oil, gas, coal and base 

metal sulfides. And bringing them to market in a manner that respects the Inupiaq subsistence values while ensuring proper care 

of the environment. 

I think it is important to note that everybody who comes here 

has a certain background. When you come to this table to come to 

the polar bear and you belong to a corporation that wants to develop the resources, I just think it needs to be placed in the record. 

So I am going to place in the record what this Arctic Slope Regional Corporation does. 

[The referenced material follows:] 

Senator BOXER. Now, Dr. Scott, you are a Ph.D. in what? Dr. 

Armstrong. 

Mr. ARMSTRONG. I went to MIT, so I basically had three areas, 

one was economics, another was social psychology and the other 

was marketing. 

Senator BOXER. Economics, social psychology and marketing. Are 

you a biologist? 

Mr. ARMSTRONG. No. 

Senator BOXER. Are you a polar bear expert? 

Mr. ARMSTRONG. No. 

Senator BOXER. Are you an expert in wildlife of any sort? 

Mr. ARMSTRONG. No. 

Senator BOXER. Are you an ecologist? 

Mr. ARMSTRONG. Pardon me? 

Senator BOXER. Are you a climatologist? 

Mr. ARMSTRONG. No, I am not. 

Senator BOXER. So you are bringing your marketing experience 

here. 

Mr. ARMSTRONG. No, I am bringing my forecasting methods experience. 

Senator BOXER. But you are not, I just want to say for the 

record, an expert on the polar bear, you have never studied the 

polar bear, you have never gone out to see what is going on. Have 

you read the USGS report that talks about the polar bear? 

Mr. ARMSTRONG. That is what we analyzed. But I think that is 

an advantage for me—— 

Senator BOXER. Whoa, whoa, whoa. No, no, no. I am not asking 

what you analyzed. I am asking you if you read the USGS report 

on the polar bear—— 

Mr. ARMSTRONG. Well, we read—— 

Senator BOXER [continuing].—before you made your statement 

that there is a high degree of uncertainty? Did you read the USGS 

report that says that two-thirds of the world’s current polar bear 

population will be gone by mid-century if the ice continues to be 

lost at the rate it is now? 

Mr. ARMSTRONG. That is what we did our audit on. That was 

what I reported on. 

Mr. ARMSTRONG. I did. It is all marked up here. 

337 

Senator BOXER. You did. OK, very good. So I would like to ask 

Dr. Kelly and the other members of the panel, Mr. Wetzler and Ms. 

Williams do you feel that there is a high degree of uncertainty or 

instability about the information you are looking at on what is happening with the polar bears? I will start with Dr. Kelly. 

Mr. KELLY. No. It is a remarkable amount of information on 

those populations, due to the efforts, primarily, of USGS biologists 

over a number of years. There are always uncertainties in any kind 

of data. I think it is important to recognize that there is a bit of 

a culture difference, I think, going on here between the way social 

scientists approach modeling and the way biologists and ecologists 

do. 

Senator BOXER. Yes. 

Mr. KELLY. I was a dean for several years in a school of arts and 

sciences. I struggled regularly with this difference in culture and 

language between economics and natural scientists. They both have 

their developed theories and approaches to modeling. As Senator 

Lautenberg so well put it, models are valuable and used in many, 

many different arenas. But there are these different disciplines 

that use them differently, they have different languages and they 

typically don’t talk together very well. 

So if you go through the literature in ecology, you won’t find a 

lot of references to Dr. Armstrong’s book and that approach, which 

isn’t to say it is not a good approach. 

Senator BOXER. OK, so just to sum it up, because we don’t have 

a lot of time to have professorial back and forths, you find the information not to be confusing in terms of the threats? You don’t 

find it to be uncertain at this point? Your research shows that the 

polar bear is threatened and will continue to be if the ice loss continues, is that correct? 

Mr. KELLY. That is correct. 

Senator BOXER. OK. Do you agree with that, Ms. Williams? 

Ms. WILLIAMS. Yes, Senator Boxer, we are fortunate to have had 

several major reports in the last few years published that show 

great certainty on changes in the ice, on changes in the climate. 

These include the Intergovernmental Panel on Climate Change, the 

Arctic Climate Impact Assessment, they all show tremendous 

changes, increases in temperature, loss of sea ice, and the Arctic 

is changing at the fastest rate. The Arctic is the most vulnerable 

to climate change impacts throughout the world. 

I also want to bring attention to a series of reports that the 

IUCN Polar Bear Specialist Group has been issuing on a regular 

basis. In 2004 and 2005 and 2006, IUCN, again, the world’s preeminent body of polar bear specialists, have drawn attention to 

their concern on the future of the polar bear. In 2005, IUCN reclassified, actually it was 2006, the polar from least concern to vulnerable. In 2004, Andy Derocher, one of the leading polar bear scientists from Canada, said that predictions are uncertain, but we 

conclude that the future persistence of polar bears is tenuous. 

So for years now, we have been hearing the concerns of people 

who are out there studying and observing the changes in body condition, and there is empirical evidence and it is quite certain that 

polar bears are suffering as a result of lost time on the sea ice. 

338 

Senator BOXER. Mr. Wetzler, I assume you agree with that. I do 

have a question about the drilling. There is a report I am going to 

place in the record published by the National Academy’s Press 

called Cumulative Environmental Effects of Oil and Gas Activities 

on Alaska’s North Slope. In there, in that report, and it is done 

with a whole consortium of groups, they say climate warming at 

predicted rates in the Beaufort Sea region is likely to have serious 

consequences for ring seals and polar bears, and those affects will 

accumulate with the effects of oil and gas activities in the region. 

And therefore, when you raised the issue of this lease sale, I understand, as representing the Endangered Species Project of 

NRDC, you see that this has a consequence and you are concerned, 

as I am, about this situation where we see a rush to a lease sale 

and a delay to a listing. I wanted you to expand on that. 

I feel very strongly that when bureaucrats break the law, there 

ought be consequences. I think the consequences should be a lawsuit, and I am wondering whether you have heard if there would 

be that possibility. Because this thing is a nightmare. 

Suppose they issue this lease and it has no conditions to protect 

the polar bear and the lease is good for many years. We know how 

that goes. And then we find out 2 weeks later that in fact, there 

is a finding made that this is true, that there is in fact a connection. It would be a disaster, and we would have to now go, I guess 

you would, I would try to overturn it legislatively, that is hard. You 

would try to overturn it, I am sure, in a lawsuit. But what are the 

chances that we could see some lawsuits here because of this outrageous missing of the deadline, and then this strange, miraculous 

timing of this oil lease? 

Mr. WETZLER. I think, Senator, you are very like to see lawsuits 

on both issues. The Natural Resources Defense Council and the 

Center for Biological Diversity and Greenpeace have already informed Secretary Hall that if he does not rectify his illegal action 

by missing the deadline, we are going to sue him. We have to wait 

60 days before we can file that lawsuit. But in the first week of 

March, if there is not a decision, we are going to take him to court. 

And as far as the lease sale goes, I think that there will also be 

legal action by a broad coalition of groups in Alaska who are opposed to the lease sale, which is not just conservationists, but also 

Native groups and some government groups as well. 

Senator BOXER. Well, I think that is very important. Because, 

and I just want to say to the environmental organizations who are 

here or who may be in the audience or supporters, you are really 

the wind at my back. I don’t know what I would do with this Administration and this tough Senate right now in terms of living up 

to the letter of the law. This is not a question of oh, gee, I will wait 

until tomorrow. The law says the decision should have been made, 

and there is this connection. 

So in closing, I want to take another look at the polar bear in 

all its glory and just say, this is pretty straightforward deal here. 

I guess, Mr. Glenn, when you say the polar bear can live on thin 

ice, which is essentially what you are saying, because if you go 

back to the loss of ice, I don’t think anyone here is disputing, I 

don’t even think Dr. Armstrong or Mr. Glenn are disputing the fact 

339 

that the ice has been lost, but Mr. Glenn says, oh, the polar bear 

can live on this thin ice. 

I guess I would like to ask you, Mr. Wetzler, since you are in 

charge of this project, what your response is to that. Can this polar 

bear live the way this polar bear has lived on thin ice that may 

or may not come back because of the climate 1 year or another? 

Mr. WETZLER. If I can answer that by saying, and this goes back 

to your earlier question that, I have reviewed a lot of Endangered 

Species Act petitions and a lot of decisions by the U.S. Fish and 

Wildlife Service under the Endangered Species Act. This petition is 

remarkable for the unanimity and the strength of the scientific evidence supporting it. I don’t think that there is any scientific question that the polar bears are endangered under the Endangered 

Species Act. 

I think to answer your specific question about the difference between seasonal and permanent ice pack that Dr. Kelly would be a 

more appropriate person to ask. 

Senator BOXER. OK, I will ask Dr. Kelly that question. The difference between the permafrost, or the living on the sea ice, the 

thin ice that might come 1 year or the next for the polar bear. 

Mr. KELLY. Well, the question is not just a matter of the thickness, but it is also the regional extent. And the ice is retracting 

such that their habitat is shrinking at an alarming rate and will 

be gone during the summer before the century is over. 

Senator BOXER. So let’s take a look at the polar bear on the thick 

snow there, just looking to go in to get its prey, is what we pretty 

much think is happening, that one, yes. And I think we should 

keep this in our mind. I think that we all believe, because we are 

at the top of the chain, that nothing else matters. That is not true. 

And we all know this is not true. And we could have so much hubris that at the end of the day, we are the ones who are threatened. 

I feel my work is not only about saving God’s creation, but also 

about protecting human beings. Because at the end of the day, it 

is just all connected. 

So I just want to thank all of our witnesses, regardless of their 

perspectives, for coming here today. And this Committee is dedicated to dealing with the issue of global warming. We are having 

a very important briefing this afternoon. Everyone is invited to 

come. We have the chair of the IPCC who will be before us, and 

he is going to go into what the IPCC has found about this. 

So we really appreciate your being here and we stand adjourned. 

[Whereupon, at 12:15 p.m., the committee was adjourned.] 

340 


82737.159

TESTIMONY OF 

JAMIE RAPPAPORT CLARK 

EXECUTIVE VICE PRESIDENT 

DEFENDERS OF WILDLIFE 

FOR THE ENVIRONMENT AND PUBLIC WORKS COMMITTEE 

UNITED STATES SENATE 

HEARING ON 

"EXAMINING THREATS AND PROTECTIONS FOR THE POLAR BEAR" 

JANUARY 30, 2008 

l\Iadam Chairwoman and Members of the Select Committee, I am Jamie Rappaport 

Clark, Executive Vice President of Defenders of Wildlife. Founded in 1947, Defenders of 

Wildlife has over 1 million members and supporters across the nation and is dedicated to [he 

protection and restoration of native animals and plants in their natural communities. 

Thank you for the opportunity to submit testimony for the record. This hearing 

highlights the misguided and conflicting priorities of [he current administration. There is a 

tragic irony to the situation today and a need to assess both the urgent importance of the 

proposal pending in the Department of the Interior to take action to prevent the extinction 

of the polar bear and the simultaneous proposal by the Minerals Management Service 

(NIMS) in the same Interior Department to open to large-scale offshore oil and gas 

operations nearly 30 million acres of core habitat critical to the survival of polar bears. 

There is something dreadfully wrong with this picture. 
341 


82737.160

On the one hand, it ha~ to be abundantly clear to the Interior Department that global 

warming due to human activities threatens the sUlvival of well documented, dwindling 

numbers of polar bears, and yet they arc irre~ponsibly dragging their feet on listing polar 

bears as a threatened species under the Endangered Species Act. On the other hand, the 

same Department is now irresponsibly and unnecessarily rushing forward to sell oil and gas 

leases in the Chukchi Sea, in the heart of critically important and essential polar bear habitat. 

Not only would leasing increase the risk to polar bears from oil spills, pollution, and habitat 

destruction and further disturb already stressed populations, but also it would lead to even 

more burning of fossil fuels and even greater emissions of greenhouse gas pollution, 

exacerbating global warming and the melting of polar bears' Arctic ice habitat. 

Defenders of Wildlife strongly believes the administration is wrong on both counts. 

As we have stated in comments to the U.S. Pish and Wildlife Service (FWS), testimony 

before rhe House of Representatives and as we reiterate here polar bears should be listed as 

a threatened species under the Endangered Species Act, without further delay. Furthelmore, 

as a matter of law, once polar bears are listed, the administration must not proceed with any 

new oil and gas leasing in the Chukchi Sea or other areas of polar bear habitat until it has 

fully complied with the Endangered Species l\ct's consultation requirements to ensure that 

such leases will not jeopardize the continued existence of polar bears and other listed 

species. Consequently, it is the height of irresponsibility for the administration to try to 

evade consultation requirements by appro\'ing new oil and gas leasing in this region before 

polar bears are listed. 

Madam Chairwoman, the administration's delay in listing polar bears on the one 

hand while, on the other hand, pushing forward with new oil and gas leasing in the heart of 

polar bear habitat, at the very least creates an appearance of, once again, allowing politics to 
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trump science in endangered species decision-making. J\s a longtime career biologist with 

the federal government before becoming director of FWS, I know the difficulties faced by 

the dedicated professionals in r:WS, the Nationall\hrine Fisheries Service, and other federal 

agencies implementing the Endangered Species Act. Consequently, I am reluctant to 

criticize them. However, I cannot ignore what this administration's political appointees have 

done to the administration of the Endangered Species Act and our other conservation laws. 

This administration has repeatedly engaged in political manipulation of science and 

conservation. For example, former Deputy Assistant Secretary of the Interior Julie 

McDonald was found by the Interior Department's own Inspector General to have 

inappropriately interfered politically with the professional assessments, conclusions, and 

recommendations of the Department's biologists, scientists, and wildlife managers in 

endangered species listing and critical habitat decisions--decisions which the Department has 

now been forced to revisit. Moreover, this administration has consistently starved 

endangered species and other conservation programs, reducing staff and budget to untenable 

levels. Thus, when the administration delays listing polar bears under the Endangered 

Species Act while, at the same time, promoting new oil and gas leasing in polar bear habitat, 

it is reasonable to suspect that it is once again putting political interests before conservation. 

For this reason, Defenders of Wildlife welcomes today's hearing and urges the Members of 

the Environment and Public Works Committee to make clear that such political interference 

with conservation will not be tolerated, in the Arctic or elsewhere. 

Defenders of \\Tildlife has been particularly concerned with the Arctic and the fate of 

polar bears. The Arctic has become "ground zero" for the most visible adverse early effects 

of global warming, a place where dramatic coastal erosion threatens human communities and 

where the accelerating disappearance of sea icc has become emblematic of the underlying 
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problems directly attributable to our society's destructive dependence on carbon-based fossil 

fuels. Polar bears are the most ,-isible, and most poignant, symbol of the devastating impact 

global warming is already having on wildlife. It is no accident that the world's leading soft 

drink seller, Coca-Cola, has adopted polar bears as a marketing image. People respond to 

these magnificent creatures. Thus, as reports of melting Arctic sea icc proliferate and images 

of polar bears starving or drowning find their way into the public consciousness, polar bears 

are awakening us all to the threat from global warming. Or almost all of us. 

IJnfortunately, there is still ongoing denial by the Bush administration. By continuing 

to delay listing polar bears as threatened, and at the same time pushing forward new oil and 

gas leases in essential polar bear habitat, the Bush administration is continuing its outrageous 

pattern of denial and foot-dragging in response to global warming, while actually promoting 

the burning of fossil fuels that will only make the problem worse -- for wildlife and humans. 

Quite simply, it is past time for this administration to list polar bears as a threatened 

species, to follow the requirements of the Endangered Species Act and carefully review 

proposed oil and gas leases and other federal actions to ensure tha t they will not jeopardize 

the continued existence of polar bears, and to refrain from any new oil and gas leasing in the 

Chukchi Sea and other polar bear habitat until adequate measures are in place to prevent 

harm from such activity to polar bears and their habitat. If the administration will finally 

show responsible leadership, the polar bear can serve not just as a symbol of the harmful 

impacts of global warming, but as a beacon of hope for helping all wildlife survive global 

warming. 

I. Polar Bears Should Be Listed as Threatened Under the Endangered Species 

Act, Without Further Delay. 

Responding [() a petition flied by the Center for Biological Diversity, Greenpeace, 

and the Natural Resources Defense Council, FWS has proposed listing polar bears as a 
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threatened species. FWS has received more than 600,000 comments on the proposal, nearly 

all of which favor listing. Defenders of\'Vildlife submitted comments in support of the 

proposed listing, in .Apri12006 and October 2007. 

As we have stated in our comments on the proposed listing, there are numerous 

factors that support listing polar bears as threatened. These include the continued hunting 

of polar bears and international trade in polar bear parts, potential for increased vulnerability 

to disease and parasites resulting from habitat shifts due to global warming, increased 

exposure to human-caused disturbance and pollution, and the inadequacy of existing 

regulatory mechanisms to respond to the threat from global warming. Above all other 

factors contributing to the need to list polar bears as threatened, however, is the unequivocal 

and extensive loss of polar bear habitat due to global warming. 

The Arctic sea ice which provides habitat for polar bears is literally melting away. 

Research conducted by experts at the U.S. National Snow and Icc Data Center in Colorado 

shows that for the second year in a row Arctic sea ice has failed to re-form after the summer 

melt. Last September, satellite images showed Arctic ice cover to be at its lowest extent 

since monitoring began in 1978, a reduction of 8.7 percent per decade. Scientists confirmed 

that summer sea ice retreated even more during summer 2007. 

The extent of sea icc on the Arctic Ocean, of course, fluctuates with the season. The 

icc melts during the six months of daylight, reaching its minimum point in September. 

Normally, during the winter, sea ice forms to compensate for what was lost over the 

summer, but last winter the ;\rctic experienced warmer than usual temperatures preventing 

ice from forming and causing the ice that did form to be thinner. Reduction of the extent of 

sea ice in both the winter and summer is an indicator that the i\rctic is experiencing a 

positive feedback effect, whereby warmer temperatures melt sea icc, causing more open 
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water that absorbs sunlight, which, in turn, causes more ice to melt. In addition, emissions 

of black carbon, or soot, also may be accelerating the melting of sea ice by reducing its 

reflectivity. If this cycle continues as predicted, models indicate that there will be no sea ice 

left by 2070, or earlier. Already parts of the Arctic Ocean remain ice-free year round, such as 

a large area in the Barents Sea, home to an estimated 2,000-5,000 polar bears. 

Loss of sea ice results in dire consequences for polar bears. Sea ice provides a 

platform from which polar beats hunt for ringed seals and other prevo [\s seals follow the 

receding sea ice, they may be too far from land for polar bears to reach them. Polar bears, 

though good swimmers over short distances, are not able to traverse large open expanses of 

water. In 2004, MYv[S found four bears that had drowned off the northern coast of 1\laska 

where the ice cap had retreated 160 miles north of land. Unable to reach the sea icc, polar 

bears that remain on land will likely come into conflict with humans, leading to killing of socalled nuisance bears. 

In particular, lack of sea ice will have a negative impact on female bears. MMS has 

found that, in the last ten years, 60 percent of female polar bears were denning on land and 

40 percent were denning on ice, where previously the percentages were reversed. Polar 

bears that den on land have more difficulty traveling between land and icc, forcing them to 

leave the icc and stop hunting earlier before the ice has retreated too far for them to find 

their preferred denning areas on land. Less and thinner ice may also disrupt the rearing of 

polar bear cubs for those populations that den on the icc. 

Here is the most dire warning of all: Reductions in Arctic sea ice and increases in the 

rate at which J\rctic sea icc is disappearing led the U.S. Geological SUlyey to conclude that 

U.S. populations of polar bears will be extirpated by 2050. The government's o\vn scientists 

predict that, if we continue with business as usual in emitting greenhouse gas pollution, by 
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mid-century, polar bears will no longer exist in Alaska. Case closed. Polar bears must be 

listed as threatened under the Endangered Species Act. In addition, immediate steps must 

be taken to halt their downward spiral. These include refraining from oil and gas leasing in 

the Chukchi Sea and changing our energy policy to reduce greenhouse gas pollution. If we 

act now, there is hope for polar bears, the Arctic ecosystem, and ourselves and our children. 

II. The Bush Administration Should Refrain From Oil and Gas Leasing in the 

Chukchi Sea and Any Other Polar Bear Habitat Until It Has Fully Complied 

With the Endangered Species Act to Protect Polar Bears and Their Habitat 

Once a species is listed under the Endangered Species Act, it is entitled to a number 

of important protections. First, it is illegal for anyone to take an individual of the species. 

Take means "to harass, harm, pursue, hunt, shoot, wound, kill, trap, capture or collect, or to 

attempt to engage in any such conduct." 1G U.S.c. § 1532(19). Prohibited take includes 

habitat desu-uction which actually kills or injures indi,oiduals of a listed species. So, for 

example, oil and gas development in the Chukchi Sea which results in an oil spill that kills or 

injures polar bears would be an illegal take under the Endangered Species Act, unless 

incidental take has been authorized pursuant to Section 7 of the Act. 

In addition to the prohibition against take, listed species receive the additional 

protection provided by the consultation requirements of Section 7 of the Endangered 

Species Act. Section 7 requires federal agencies to consult with either the Secretary of the 

Interior, acting through FWS, Of, in the case of certain marine species, the Secretary of 

Commerce acting through the National Marine Fisheries Service, to ensure that any action 

"authorized, funded, or carried out" by a federal agency "is not likely to jeopardize the 

continued existence" of a listed species or adversely modify or destroy its designated critical 

habitat. 1G U.S.c. § 153G(a)(2). Consequently, once polar bears arc listed, any proposed oil 

and gas leases in the Chukchi Sea or other polar bear habitat \vould have to undergo Section 
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7 consultation frrst, to ensure that the leases are not likely to jeopardize the continued 

existence of polar bears or any other listed species in the region. 

Even before polar bears are listed, Section 7 requires federal agencies to confer with 

FWS on possible impacts of federal actions which are likely to jeopardize polar bears or any 

other species proposed for listing. 16 U.S.c. § 1536(a)(4). Thus, since listing of polar bears 

has been proposed, MMS and FWS must determine whether oil and gas leasing in the 

Chukchi Sea is likely to jeopardize polar bears and, if so, confer on the leasing and its 

impacts. Once polar bears are listed, l\IMS must consult with FWS to ensure that the leasing 

is not likely to jeopardize the continued existence of polar bears. In other words, the 

Endangered Species Act requires federal agencies to stop and think about the effect of their 

actions on listed species and species proposed to be listed. It would flv in the face of the 

precautionary purpose of the Endangered Species i\ct if the Interior Department is able to 

take advantage of its own delay in making a listing decision on polar bears to expedite oil and 

gas leasing in the Chukchi Sea, without first fully evaluating the potential harm to polar 

bears. At minimum, given the proximity of the listing decision and the leasing proposal, the 

Bush administration should delay any oil and gas leasing in the Chukchi Sea or anv other 

polar bear habitat until the listing decision has been made and, assuming polar bears are 

listed, Section 7 consultation requirements are fully met. 

The potential for harm to polar bears from oil and gas leasing in the Chukchi Sea is 

substantial. MMS is proposing to open nearly 30 million acres of core habitat critical to the 

survival of polar bears to oil and gas development. Such development is highly risky and 

detrimental to polar bears and other Arctic wildlife. Oil and gas development routinely 

produces massive air pollution emissions, including increased emissions of greenhouse gases 

that cause global warming. The sensitive Arctic marine environment is subject to serious 
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damage, from activities ranging from seismic survey blasts to routine toxic discharges of 

spent drill muds, borehole cuttings, and wastewater, dumped directly into one of the most 

pristine and biologically sensitive marine environments on the planet. The risk of damage 

from oil spills, leaks, fires, and other accidents, exacerbated by an industry history oflax 

oversight and enforcement, poses a serious threat to Arctic wildlife. 

Most disturbing of all, no technology presently exists that can even begin to 

successfully clean up spilled oil at sea in the meteorological and sea-state conditions 

prevalent in the Arctic. Furthermore, no oil spill technology currently exists to adequately 

respond to a spill in broken-sea-ice conditions such as those prevailing in the Chukchi Sea. 

Once an oil spill moves under the ice sheet, which is essential to the breeding, feeding, and 

sheltering of polar bears and the entire Arctic marine life community, there is no way to even 

track its mOYements. Oil will not biodegrade but will remain highly toxic for up to a century 

or more, continually leaking out at unpredictable intervals to poison our wildlife and foul 

delicate lagoons and hundreds of miles of inaccessible shorelines. For polar bears, as well as 

the resident walrus and shorebird populations, and for the migrating bowhead and beluga 

whales in the Chukchi Sea, the consequences are unthinkable. 

In addition to the potential for direct harm to polar bears and their habitat from oil 

and gas development in the Chukchi Sea and elsewhere, there is the indirect, but e(]ually 

devastating, impact of promoting additional burning of fossil fuels, which increases 

greenhouse gas pollution that causes global warming. We have reached a point, 1'v[ister 

Chairman, where we cannot continue business as usual. We cannot continue to promote the 

burning of fossil fuels if we are going to stabilize atmospheric greenhouse gas concentrations 

and stop human-caused global warming. The plight of polar bears is a warning to us that we 
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must act now to reduce our use of fossil fuels and consequent production of greenhouse gas 

pollution. 

This is so much bigger than a singular focus on the polar bear, regardless of the 

importance of this species itself. Given what '.ve now clearly know about the drastic 

implications of global warming for human society worldwide, it is clear that the 

administration's stumbling approach to making these decisions concerning the polar bear 

and the Chukchi Sea are emblematic of something biggcr and very troubling. Enn with all 

the evidence out there on the seriousness of global warming, this administration stillincomprehensihly-refuses to believe it. Or, they do believe it and yet still will not take 

responsible action hecause of their commitment to serve private and political interests that 

are not in the best interests of the country or the future. Either way, it is a poor reflection 

on this administration and the £\merican people are ill-served by it. 

Conclusion 

In conclusion we have come to a crossroads--for the polar bear, for all life in the 

Arctic seas, and for our own global climate future. It is long past time to begin seriously 

addressing global warming. The Bush administration should move forward immediately to 

list the polar bear as a threatened species and to fully comply with the requirements of the 

Endangered Species Act. The administration should also withdraw the proposed oil and gas 

leases in the Chukchi Sea, while it fully complies with the consultation requirements of the 

Endangered Species Act. The administration should also refrain from any further oil and gas 

leasing in the Chukchi Sea or other polar bear habitat until adequate measures are in place to 

protect polar bears and their habitat from the harmful effects of such development. Most 

importantly, this administration or, more likely, the next one, should work with the Congress 

to develop an energy policy that will reduce our use of fossil fuels, our production of 
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greenhouse gas pollution, and that will protect polar bears, other imperiled wildlife, and, 

ultimately, ourselves and future generations from the harmful impacts of global warming. 

Thank you again for the opportunity to submit testimony for the record on this 

important issue. 
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WRITTEN TESTIMONY FOR 

THE SENATE COMMITTEE ON THE ENVIRONMENT AND PUBLIC WORKS 

HEARING ON EXAMINING THREATS AND PROTECTIONS 

FOR THE POLAR BEAR 

JANUARY 30, 2008 

Jack Lentfer 

PO Box 2617 

Homer. Alaska 99603 

lcntfcr@gg.net 

As an Alaskan wildlife biologist with extensive polar bear experience, I am 

especially concerned about the threat of global warming to polar bears. I have directed 

polar bear research and management programs for the State of Alaska and the U.S. Fish 

and Wildlife Servicc, served as a member of the international Polar Bear Specialist 

Group, and helped negotiate the international Polar Bear Agreement. I have served on 

the Scientific Advisory Committee and also as a Commissioner of the U.S. Marine 

Mammal Commission. During my time with the Marine Mammal Commission, it dealt 

with a number of polar bear issues, all of which I was involved with. I have published 

peer-reviewed articles for scientific journals and popular articles on polar bears 

The U.S. Fish and Wildlife Service and the U.S. Geological Survey (USGS) have 

made a comprehensive and science-driven case to list polar bears as threatened under the 

terms of the Endangered Species Act because global warming is destroying their sea ice 

habitat. Sea ice is essential habitat for ringed and bearded seals, the primary prey of 

bears, and provides a platform for hunting them. Ice facilitates seasonal movements for 

bears, provides a platform for most mating, and in some areas provides maternity denning 

habitat. The overall conclusion of the USGS research effort is that projected changes in 

future sea ice conditions, if realized. will result in the loss of approximately 2/3 of the 

world's current polar bear population by the mid 21 st century. This assessment of future 

polar bear status may be conservative because the observed trajectory of Arctic sea ice 

decline appears to be underestimated by currently available models. 
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Modeling indicates sea ice reductions will occur across the range of polar bears. 

Some of the best data for assessing popUlation change are for the southern Beaufort Sea 

popUlation off Alaska's north coast. The body condition of bears, recruitment of cubs, 

and demographic trends of this population are all declining as sea ice decreases. Other 

signs of population stress include a shift toward land-based denning, abandonment of 

areas with high rates of ice degradation, and starved and cannibalized bears. The USGS 

predicts that if ice conditions observed since 1979 continue, this population can be 

expected to decline about 1 percent per year and be at 1 to 10 percent of present numbers 

by 2100. If ice conditions remain similar to those of 2004 and 2005, the population 

would decline severely within 45 years. Various forecasts of sea ice conditions predict 

that this population could be extirpated within the next 50 to 100 years. 

The U.S. Marine Mammal Commission (MMC), charged with making 

recommendations to the Secretary of Interior regarding the Endangered Species Act, has 

reviewed listing documents. One of the members of the Scientific Advisory Committee 

to the MMC is a preeminent Canadian polar bear scientist. The MMC states that USGS 

modeling to predict reductions in sea ice constitute the best scientific information 

available and that a strong legal justification exists for listing under the Endangered 

Species Act at the present time. Based on sea ice modeling projections, the MMC 

believes that the southern Beaufort Sea population should, at a minimum, be listed as 

threatened. If nothing were to occur to reverse the projected trend in sea ice loss, the 

MMC believes the population is already close enough to extinction to walTan! listing as 

endangered. MMC believes the other Alaskan population (Chukchi Sea) faces risks 

similar to those of the southern Beaufort Sea population and also merits an endangered 

status listing. 

Another issue of immediate concem is pending action in the Department of 

Interior for an oil and gas lease sale in the Chukchi Sea outer continental shelf before 

taking action to list under the Endangered Species Act. Polar bears could be affected by 

oil and gas activities as follows: (I) damage or destruction of essential habitat; (2) contact 
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with and ingestion of oil from acute and chronic oil spills; (3) contact with and ingestion 

of other contaminants; (4) attraction to and disturbance by industrial noise and 

harassmcnt by aircraft, over-ice vehicles, icebreakcrs, and other vehicles; (5) death, 

injury, or harassment resulting from interactions with humans; (6) increascd hunting 

pressure; and (7) potential injury, mortality, and stress resulting from handling and 

interaction designed to evaluate and/or investigate all of the above. Before oil and gas 

leasing is approved for the Chukchi Sea each of these aspects should be considered 

thoroughly and include an evaluation of how global warming and development interact in 

conjunction to affect polar bears and thc marine food web that supports them. lt is of 

special concern that no method has been developed to remove spilled oil from ice 

covered water. 

After several decades into the future, polar bears may occur only as a remnant 

population in the high Canadian Arctic. Protective measures now, that include listing 

under the Endangered Species Act and the Recovery Plan that follows, may help the 

species survive and recover if global warming and loss of sea ice habitat can be reversed. 
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Il.JJ/:l CAn..c bQ.Cr 

INUIT TAPIRIIT KANATAMI 

Written Statement on: 

Examining Threats and Protections/or the Polar Bear 

Prepared for: 

U.S. Senate Committee on Environment and Public Worl.s 

Washington D.C. 

Submitted by: 

Ms. Mary Simon, President 

Inuit Tapiriit Kanatami 

Ottawa Canada 

February 6, 2008 
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82737.174

Dear Senate Committee Members 

On behalf of Inuit in Canada, we are thankful to be given the opportunity to provide for 

you a written statement for the record in regard to your current deliberations on the 

examination of threats and protections for the Polar Bear in light of the proposed listing 

of the Polar Bear as Threatened throughout its range under the Endangered Species Act 

(ESA). 

I am celtainly hopeful that your Committee wiU consider our concerns from a Canadian 

Inuit perspective as we, along with our fellow Indigenous Alaskans, Greenlanders, and 

Russians, share in our own respective ways a vcry close, enduring, and important 

relationship and cultural link (0 the Polar Bear. 

Please do appreciate in context that we as a people in Canada's Arctic have similar 

important on-going subsistence, cultural, livelihood, and spiritual links to many other 

terrestrial and marine mammals, fish, birds, and plant life. The Polar Bear (called Nanuq 

in our language) is one among many species impoltant to us, and if we felt it was 

incumbent upon us to defend and promote our rights, our interests, and perspectives on 

any other species impOitant to us, we would not hesitate to do so. 

When we are concerned about our Arctie environment and ecosystems in the face of 

global warming, we are concerned for our wildlife and for our very own lives and way of 

life as Inuit because these elements are inseparable. As a result, we must approach 

emerging issues and changes in as much of a balanced way as we can from the 

perspective of our past and current state of affairs, and to examine and determine the best 

solutions and options as ways forward. This is an impOltant way in which we arrive at 

our decisions and directions given thc complexitics and challenges we face in the Arctic, 

the successes we have (hus far achieved, and the need to sustain Ollr culture and way of 

life for our future generations. 

OUf organization, Inuit Tapiriit Kanatami (ITK), is the national organization that 

represents and advocates on behalf of Inuit in Canada. Similarly, our associated 

organization, the IIlUit Circumpolar Council (ICC), Canada, represents and advocates on 

behalf of Inuit in Canada but on an international level along with other ICC associated 

organizations in Alaska, Russia, and Greenland. 

On April 4, 2007, our two organizations jointly provided a written submission to the US 

Fish and Wildlife Service indicating our disagreement with the proposed listing of the 

Polar Bear as Threatened 011 the U.S. Endangered Species Act. 

With some emphasis or rephrasing, we essentially had expressed the following: 

The Polar Bear is integral to Inuit because it has value culturally, spiritually, 

subsistence and nutritionally, for knowledge, for clothing, and for livelihood; 
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• Inuit have signed Land Claims Agreements with Canada and have a suite of 

Constitutionally pmtected rights under which we can continue the sustainable 

harvest and use of Polar Bears; 

Inuit in Canada have conserved and continue to conserve the Polar Bear at 

healthy population levels through proper and responsible wildlife management, 

co-management, research, monitoring, as well as through our sustainable 

harvesting measures and practices as a hunting culture; 

There are numerous sub-national, national, international, and user-to-user 

agreements, bodies, and processes that serve to conserve, manage, monitor, and 

regulate Polar Bear populations-it would be fair to say that the Polar Bear is 

among the most managed species in Canada's north, and the majority of the 

world's Polar Bears are in Canada; 

There is insufficient inclusion of Inuit Traditional Knowledge of Polar Bears in 

the proposed rule's considerations; 

There is no consideration or examination of the Polar Bear's ability to adapt to 

changing and ice-free conditions-the proposed rule focuses on the projected 

future demise of the species; 

Using long-term projections (i.e. the 45-year model) regarding the fate of our 

wildlife in relation to ice is an exercise in speculation and we see this as one 

precautionary projection which cannot be substantiated and do not support the 

use of such long term and uncertain predictions to base current high-impact 

decisions on the management and use of our critical wildlife resources; 

It is our concern that elevating the listing of the Polar Bear to Threatened will 

impose arbitrary, and scientifically unfounded, penalties and hardships upon 

Inuit; 

• As a part of our responsibility for conserving and managing Polar Bears, we will 

take appropriate measures if and when the popUlations or subpopulations do 

become adverscly affected for one reason or another; 

The environmental organizations and petitioners to the propose rule are using the 

Polar Bear and the ESA to apply public and political pressure on the cUl1'ent US 

Administration to address greenhouse gas emissions; 

• Using the Polar Bear and the ESA for political and public campaigning pUlJloses 

is, in our view, misguided and short-sighted; 

• We see no conclusive or convincing evidence which demonstrates that a broad 

Polar Bear regulatory restriction will in fact reduce greenhouse gas emissions or 

become a practical solution to mitigate climate change-if anything that will be 

celtain, Inuit will be the most adversely affected. 

As an organization that represents Inuit and the realities of living in the Arctic, which 

includes the necessity of hunting, fishing, trapping, using the reSOllIces of the land and 

ocean, and observing and experiencing the changes that are happening as a result of 

global warming, we are very careful not to become alarmist and to be wary of those who 

pelpetrate alarmist messages or campaigns for their own interests or causes. 

During the course of the deliberations and discussions surrounding the proposed rule for 

the past year OJ' so, even we were thinking of the motivations behind the need to up list 
357 


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the Polar Bear to Tlueatened on the ESA. Is it to stop Amcrican hunters from sport 

hunting in the Canadian Arctic? Is it some method to curb global warming? Is it meant 

for the cnvironmental organizations to increase their publieity and financial rcturn and 

test the hook of using the Polar Bear as an icon species that is already secn in zoos and 

coca cola commercials? Or is it a regulatory mcans for environmental organizations to 

legally stop drilling in the Alaskan off-shore? 

The real issue fOf us in the Arctic is climate change that has the potential to alIect us all, 

including our wildlife. Thercfore, we continue to call for regulation and mitigation 

measurcs at the national and international levels in order to directly address greenhollse 

gas emissions and to find new technologies, hal'l1ess new forms of clean energy and 

energy production, and for environmentally friendly alternatives to such things as vehicle 

engines that burn fossil fuels. 

In closing, I want to thank the Committee for accepting our written submission at this 

time as you deliberate the issue of the threats and protections for the Polar Bear. 

Sincerely, 

Mary 

tA.~ Simon 

President 

Inuit Tapiriit Kanatami 
358 


82737.177

Arclic S!or~ R~gitln;\l Corporation 

Company Prome 

ASRC Companies 

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LMd'14 

WUlltOfl1 Arctic CM! 

Stock 

PrtJS$ R;j!c<ls\lS 

Documents 

Employment 

Contact 

P~tfO Star lnc. 

PETj:.:IO 
359 


82737.178
360 


82737.399

Corporals Headquartms .. P.O. Box 129 .. Bartow" A1asl(a .. 99723-0129 • (907) 852,8533 or (907) 852-8833 .. FAX {907} 858-5733 • 1.800.770-2772 

ql - arctic ~Iope 

reqional corp. 

October 22, 2007 

VUl email 10 Polar_Bear_ Finding@fws.goy 

Attn: Polar Bear Finding 

U.S. Fish lUld Wildlife Service 

Marine Mammals Management Office 

1011 East Tudor Road ' 

Anchorage, Alaska 99503 

Re: Comments of the Arctic Slope Regional Corporation on the New Information 

Contained in United States Geological Swvey Reports and the Proposed Rule to 

List the Polar Bear (Ursus maritimus) as Threatened Throughout Its Range 

To Whom It May Concern: 

On behalf of the Arctic Slope Regional Corporation (ASRC), I respectfully submit the 

following comments in response to the Notice of Av.Hability of New Information issued by the 

U.S. Fish and Wildlife Service (USFWS) requesting comment on nine United States Geological 

Survey (USGS) reports concerning sea ice conditions and the effect of habitat change on the 

polar bear (Ursus maritimus). 72 Fed. Reg. 56979 (October 5, 2007). ASRC seeks a continued 

dialogue with the USFWS regarding the information contained in these reports and the proposed 

listing of polar bear as a threatened species under the Endangered Species Act (ESA), and greater' 

appropriatc peer review of the sludi~s and reports in the USGS reports. 

As noted in our comments on April 9, 2007, responding to the request for comments on 

the proposed listing of the polar bear as a threatened species, ASRC has an obligation to protect 

our Inupiat shareholders' interests by ensuring that USFWS's proposed rule is objective, based 

on the best available science, draws on all relevant scientific disciplines Wld is informed by-and 

respects--Inupiat traditional knowledge of our environment.' As discussed further'below, 

ASRC is deeply concerned about the recent apparent decision by USFWS to rely heavily on the 

new, previously unpublishcil or uncirculated USGS reports in the final listing rule. Such a 

reliance on significant new scientific data assessments, which differ substantially from the 

previously available scientific information, forecasts and conclusion used to support the 

proposed listing rule, is not warranted unless greater peer review and consultation are provided. 

See ASRC, Comments of Arctic Slope Regional Corporation on the Proposed Rule to List the Polar Bear 

(UrsWI maririmus) as Threatened Throughout Its Range (April 9, 2001). 
361 


82737.400

A very limited public comment period for such significant reports which were largely assembled 

outside of public scrutiny does not meet the tests of fairness or the law for listing. 

1. Listing ofthe polar bear under the ESA should not be used as a land management 

tool or to drive climate change policy. 

At the outset, ASRC continues to believe that the proposed listing on the basis of 

forecasted habitat loss arguably caused by human activities across the globe is an inappropriate 

use of the ESA. The agency will not be able to engage in any meaningful section 7 consultations 

fonowing a listing, because to do so arguably would require that all anthropogenic activities 

contributing to the release of greenhouse gas emissions anywhere within the jurisdictional reach 

of the ESA be subjected to a section 7 consultation whenever the requisite federal nexus is 

present. This would be a virtually impossible task, and require an aimost herculean 

determination of whether those particular activities, whether occurring on the east coast, the west 

coast, the midwest, Alaska or Hawaii, are likely to contribute to the loss of a certain percentage 

of the habitat of the polar bear and, jf so (absent a critical habitat designation). how that loss of 

habitat will affect the polar bear. An aimost identical impossible task will be required with 

respect to any judgments regarding the potential "take" of the polar bear as a consequence of 

activities that allegedly contribute to the loss of the polar bear's habitat. We are quite conceme.d 

about changes in climate conditions in the Arctic and have more reason than others to be 

aggressive about addressing climate change; however, the proper methods to address those issues 

are to deal with climate change conditions and causes directly, not to twist the ESA listing of the 

polar bear into an action directed at climate change. 

2. The USGS reports lack meaningful observational data, including data 

incorporating the use ofInuoiat traditional ecological knowledge. 

Next, the USGS reports focus intensely on statistical analysis and modeling approaches 

to make key detenninations regarding polar bear mortality .. Many of these determinations, in the 

form of forecasts upon which the listing would tum, do not appear to factor in much, if any, 

observational data and are far more detenninative than previously used scientific information. 

We believe that the USGS reports rely too exclusively on the use of models to identify the 

likelihood of polar bear survival (e.g., modeling to identifY the relationship between ice 

conditions and cub recruitment). While we agree that the use of modeling is necessary and 

beneficial, models should be tested with other data, particularly observational data that happens 

to be available in this instance. ASRC requests that the USFWS's final listing rule discuss both 

the USGS reports based on modeling and reports based on previously used observational data. If 

there are conflicts between the two types of reports, then USFWS should discuss the conflicts 

and how those were resolved in the agency's final decision. 

ASRC is also concerned that, in compiling these reports, USFWS and USGS have not 

made any concerted effort to gather traditional ecological knowledge from the Inupiat people. 

We yield to no one in our desire to protect and conserve the natural resources of the Arctic. Our 

people have vigilantly monitored, guarded and lived with those resources for centuries. There is 

no other group in the country with as much current and historical knowledge of the polar bear 

and its habitat as our Inupiat people, Our traditional knowledge encompasses wildlife, sea ice 
362 


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conditions and climate change and is built upon thousands of years of experience with the polar 

bear and its habitat. The importance of traditional ecological knowledge is recognized by the 

USFWS; for instance, the draft Stalus Assessment of polar bear was subject to peer review by 

independent experts in many fields including traditional ecological knowledge. See 72 Fed. Reg. 

at 1065. In providing for the co-management of species under the Marine Mammals Protection 

Act (which includes polar bear), USFWS "considers traditional ecological knowledge a 

significant contribution to our understanding of polar bears and other species and their habitat.'" 

We believe that the USGS reports, and any final listing rule, should incorporate traditional 

ecological knowledge and that ASRC should be consulted and work with the agency in 

compiling that knowledge. 

3. The CQlllI!lent period for the USGS reports is insufficient for adequate review, 

analysis and comments on the major changes in scientific conclusions on the polar 

bear's viability from previous studies. . 

Climate change and reducing greenhouse gas emissions is not something that will be 

changed overnight, or in a year for that matter, and so ASRC is concerned with the USFWS's 

desire to proceed quickly without ensuring a meaningful opportunity for parties to participate 

and comment on this proposed listing. The amount oftime provided by USFWS for review and 

comment on the USGS reports is wholly unsatisfactory. While we appreciate the granting of a 

limited extension of the comment period, the short review period that was provided is inadequate 

for such a volume of information. These USGS reports mark a significant departure from 

conclusions on the polar bear's population trend from that set forth in the USFWS's Proposed 

Rule and Notice of 12-month Finding published on January 7,2007. 72 Fed. Reg. 1064 (January 

7, 2007). In the proposed listing rule, USFWS' s predicted population trend showed that for 

seven populations the trend could not be determined, for five populations the trend was stable, 

for five populations the trend was declining, and for two populations the trend was increasing. 

72 Fed. Reg. at 1070. The new USGS reports, however, paint a far bleaker picture of the polar . 

bears survival, based on modeling and forecasting, to predict the loss of approximately 213 of the 

world's current polar bear population by the mid-21st century and, within that time frame, the 

extirpation the Southern Beaufort Sea subpopulation. As a policy matter, this significant change 

in the polar bear's population trend deserves appropriate peer review and a thorough review by 

all stakeholders, who are to be provided a "meaningful" opportunity to participate in the . 

rulemaking process.' Access to information without time to review and comment does not allow 

for a ''meaningful'' participation. 

Neither USFWS nor the USGS consulted with ASRC or the Inupiat people, in general, 

prior to the consideration of or publication of the reports. We were not granted an opportunity to 

request peer review or an independent third party review. Because the USGS reports are such a 

departure from the prior reasoning regarding the polar bear's population trends and sea ice 

condition in the Arctic and, as noted in the Notice of Availability of New Information, will be 

relied upon by USFWS in making the final listing decision, it is important that adequate review 

of the reports be completed. 

USFWS, A Co-management Vision for the Sustainable Use of Sea oner, Polar Bear, and Walrus In Alaska, 

1997 - 2000, 5 (2{)OO). 

, Idaho Faun Bure!lll Fed'n y. B.bbitt, 58 F.3d 1392. 14()4 (91h Cir. 1995). 
363 


82737.402

4 ASRC has significant concerns regarding the methodology used in the USGS re.ports. 

We believe that the USGS reports, as presented. may not meet the standard for the best 

scientific and commercial data available, which Congress has directed that the Secretary use as a 

basis for ESA listing detenninations, since there has been little opportunity to review the major 

assumptions and methodology contained in the reports" ASRC joins in the comments filed by 

the State of Alaskawith respect to the distinctions used to classifY the polar bear into 

subpopulations as well as other specific disagrcements over the methodology used in the USGS 

reports including the methodology used in modeling and forecasting. 

In particular, we question the division of the range of polar bear into four ecoregions and 

the use of subpopulations in the latest USGS reports. There is simply no demonstrated basis in 

the proposed listing rule or the USGS reports to appropriately distinguish, within the levels of 

scientific accuracy required for listing. between polar bears fOWld in different locations. As we 

noted in our previous comments, polar bear are highly migratory. Given the wide movement of 

the polar bear between areas, we do not see a sufficient, current and clear basis to determine thata member of a "subpopulation" is in fact distinct from the remainder of the polar bear species. If 

USFWS wishes to identify "distinct population segments" (DPS) for purposes of the ESA listing, 

there are specific principles to determine if a DPS exists.5 There has been no decision by 

USFWS to identify polar bear DPS, and therefore it seems inappropriate that the USGS reports 

would rely on subpopulations. 

The State of Alaska has also noted that there is substantial disagreement regarding the 

sufficiency and accuracy of the available information in the USGS reports, especially regarding 

the validity and predictive value of climate modeling, but also regarding population modeling 

based on modeled environmental changes. For example, there are models and studies of the 

likely timing and extent of sea ice recession that differ significantly with the conclusion of the 

USGS reports and USFWS's determination in the proposed listing rule. Use of models and 

conclusions drawn from those models should involve commentary from a wide spectrum of 

disciplines including other polar bear experts, climatologists, and statisticians over a sufficient 

length oftime to allow proper scientific debate and reciprocal discussion. 

We join with the State of Alaska in our concerns regarding the accuracy of the modeling' 

and forecasting on which the USGS reports depend for their conclusions on the viability of the 

polar bear populations. As the State notes, looking more than ten years into the future is pushing 

climate change models beyond their ability to produce reasonable approximations oflikely 

conditions. Claiming to foretell the effects of climate change 45 years into the future, as the 

USGS reports do, invites the use of highly speCUlative and Wlcertain assumptions and forecasts 

regarding climate change, ice modeling and Wlcertain possible impacts on the species which are 

too speculative to be used in the £SA listing decision. Such speculation, using highly uncertain 

icc and climate modeling, is not an appropriate basis to support listing a species whose 

population numbers are currently not in decline. 

16U.S.C. § 1533(bXI)(A}; SOC.F.R §424.11(b). 

See 61 Fed. Reg. 4,721 (1996). 
364 


82737.403

The ESA listing decision is to be based "solely on the basis of Ihe best scientific and 

commercial data available.'" Another statute, the Infonnation Quality Act (section SIS, P.L. 

106-554), imposes requirements to ensure the quality and utility ofinfunnationdissemlnated by 

federal agencies. These statutory requirements are not met in the issuance of the USGS reports. 

Policy guidelines further direct the USFWS to ensure appropriate data is used in the listing 

process.7 ASRC has significant concerns regarding the methodology used in the USGS reports, 

but an appropriately through review of the methodology used in the reports requires a degree of 

technical expertise not readily available to stakeholders such as ASRC, in part because the 

reports conclusions were based primarily on modeling. USFWS has provided insufficient time 

for ASRC to assess the reports and provide substantive comments. 

5. The USGS reports do not indicate any impact to the polar bear populations from 

local or state activities or oil and gas activity. 

As a comment on the USFWS's proposed rule listing the polar bear as threatened under 

the ESA, ASRC would like to reiterate that local and state activities and oil and gas activity in 

the Arctic have not been linked to a decrease in the polar bear population. In reviewing the five 

factors for listing a species under the ESA, the USFWS did not identify local or state activities as 

baving an impact on polar bear popUlations. Oil and gas activity was also found to pose no 

threat to the viability of the polar bear population. As noted in the proposed listing rule, 

"[ d]ocurnented impacts on polar bears by the oil and gas industry during the past 30 years are 

minimal." 72 Fed. Reg. at 1079. In fact, "[nJo lethal take associated with [the oil and gas] 

industry has occurred during the period covered by incidental take regulations." 72 Fed. Reg. 

at 1080. The proposed rule concluded that oil and gas activities "do not threaten the species 

throughout all or a significant portion of its range:' 72 Fed. Reg. at 1080. The USGS reports do 

not change this finding, as no mention of local or state activities or oil and gas activity were . 

made in the reports. In making the final listing decision, ASRC requests the USFWS reafTmn 

this point in the final listing rule, since it is not contradicted in the USGS reports in any manner. 

6. USFWS has failed to adequately consult with Alaska Natives. 

As noted in Executive Order 13175 (April 29, 1994), USFWS has an obligation to 

communicate on a Govennnent-to-Oovemment basis with the Alaska Native entities recognized 

by the Secretary of Interior on Federal policies that have tribal implications.' The eight Villages 

represented by ASRC are included on the Secretary of Interior's list of Indian Entities . 

Recognized and Eligible to Receive Services from the United States Bureau of Indian Affairs 

and should be afforded the consultation benefits described in Executive Order 13175. USFWS 

even acknowledged this responsibility in the proposed listing rule, stating that "we readily 

aclmowledge our responsibility to communicate meaningfully with recognized Federal Tribes on 

a govemment-to-govemment basis." 72 Fed. Reg. at 1099. In assembling the scientific 

ld 

S9Fed. Reg. 34,271 (1994). 

"Policies that have tribal implications" refers to regulations, legislative comments or proposed legislation, 

and other policy statements or actions thaI have substantial direct effects on lndian tribes, on the relationship 

between the Federal Government and Indian tribes, or on thc distribution of power and responsibilities between the 

Federal Government and Indillll tribes. 
365 


82737.404

information and assessments contained in the nine USGS reports, we believe that the agencies 

(USGS and USFWS) have not met these requirements to establish regular and meaningful 

consultation and collaboration with Alaska Natives. 

In addition to the Executive Order requirement for consultation, it is the policy of the 

federal government to consult with Alaska Natives regarding ESA listing of subsistence species, 

such as polar bear. See Secretarial Order 3225 (2001). Under this policy, Alaska Native 

organizations have the opportunity to participate in tbe management of subsistence species that 

are proposed or listed species under the ESA. The management includes, but is not limited to: 

forming recommendations for management actions, plans or regulations; population and harvest 

monitoring projects; law enforcement activities; education programs; research, design, data 

collection and use of traditional knowledge; habitat protection programs; and recovery projects: 

ASRC is concerned that USFWS has made no apparent attempt to consult with affected 

Alaska Native groups on the new USGS reports or the effect of those reports on the proposed 

listing or potential management of the species. The Inupiat, with our traditional knowledge of 

the Arctic and our wildlife, already playa large role in conserving the polar bear; a role which 

should be increased, not diminished, if the species is in peril. Traditional and common-sense 

knowledge is, as history shows, very important in the conservation and rehabilitation of a 

species. In addition, as noted in our previous comments, our people are active in polar bear 

conservation organizations such as the Alaska Nanuuq Commission.9 ASRC encourages 

USFWS to seek full access to the breadth of knowledge and year-round, first hand traditional 

knowledge held by the Inupiat people before completing scientific reports such as the USGS 

reports and before taking action to list the polar bear as threatened under the ESA. 

CQnclusion 

ASRC strongly believes that a listing as threatened for the polar bear, based on scientific 

information that has not been properly reviewed, does not meet scientific, legal or regulatory 

requirements of the ESA is not justified. Ultimately, a listing under these circumstances, would 

have very little impact on the population status of the polar bear yet, a listing under the ESA 

would negatively and disproportionately affect the Inupiat Eskimos who co-exist with the polar 

bear in the Alaskan Arctic. As such, we are gravely concerned with the USFWS reliance on 

USGS reports that have not been thoroughly reviewed, rely on untested modeling and forecasting 

which has been subject to limited peer review, and are substantially different in conclusion than . scientifie reports issued this year with the proposed listing rule. 

ASRC continues its request to USFWS that rather than a rusbed ESA listing of the 

species, that we work together to understand the polar bear and its habitat, and specifically work 

toward understanding the consequences of how development and greenhouse gas emissions 

generated far away from our lands·and waters affect the habitat we share with the polar bear. 

ASRC reminds USFWS that under both Executive Order 13 i 75 and Seeretarial Order 3225 the 

agency is requlred to consult with Alaska Natives, a consultation that has not occurred to date. 

S.ee ASRC. Comments of Arctic Slope Regional COlporation on the PropDSed Rule to List me Polar Bear 

(Ur.fWJ maT/timus) as Threatened Throughout Its Range, 19 and Appendix A (Aprll9, 2001). 
366 


82737.405

ASRC looks forward to establishing regular and meaningful consultation and collaboration with 

USFWS and continuing this discussion at that time. 

Sincerely, 

~<-~""~, ~~ Roberta Quintavell 

President and Chief Executive Officer for 

ASRC 
367 


82737.179

Anchorage Omes • 3900 C StrBet • SUIte 801 • Pmchorage • Alaska 99503-5963 • (907) 339-6000 • fAX (907) 3...19-6028 • 1-800·770-2772 

-J o~o>oP' reqional corp. 

January 30, 2008 

The Honorable Barbara Boxer 

Chair, Environment and Public Works Committee 

United States Senate 

Room 456 

Dirksen Senate Olliee Building 

Washington, D.C. 20510 

The Honorable James Inhofe 

Ranking Minority Member, Environment and Public Works Committee 

United States Senate 

Room 456 

Dirksen Senate Ollice Building 

Washington, D.C. 20510 

Dear Senators Boxer and Inhofe: 

ASRC represents the interests of its 10,000 Inupiat Eskimo shareholders who live on Alaska's 

North Slope. Because this proposed listing under the Endangered Species Act presents potential 

changes, problems, costs, and uncertainties for our shareholders and the communities and 

villages in whieh they live, ASRC has previously submitted comments and testimony on the 

Administration's proposed polar bear listing. I am enclosing copies of these comments and I 

would appreciate it if they were made a part of the Committee's record of this hearing. 

Sincerely, 

ARCTIC SLOPE REGIONAL CORPORATION 

~ Director, Goverrunent Affairs 
368 


82737.180

CmI'O"'.H.adq_~ S'" . ~- . -.. "'"'" . ~~~"~O~·~ . --~ . 

6retic .)Iope 

reqlonal corp. 

April 9,2007 

Vw emtJil to Polar Bear Findlnfil(ji)[ws.gov 

Attn: Polar Bear Finding 

U.S. Fish and Wildlife Service 

Marine Mamrnals Management Office 

1011 East Tudor Road 

Anchorage, Alaska 99503 

Re: Comments of Arctic Slope Regional Corporation on the Proposed Rule to List the 

Polar Bear (Ursus maritimus) as Threatened Throughout Its Range 

To Whom It May Concern: 

On behalf of Arctic Slope Regional Corporation (ASRC), I enclose and transmit the 

following comments and recommendations regarding the United Slates Fish and Wildlife 

Service's (USFWS) proposed rule to list polar bear (Ursus maritimus) as threatened throughout 

its range under the Endangered Species Act (ESA). 72 Fed. Reg. 1064 (January 9, 2007). ASRC 

looks forward to a continued dialogue with USFWS regarding this proposed listing and the many 

impacts it could have, if adopted, upon the Inupiat Eskimo people. 

Our formal comments foeus on the biological, scientific and commercial data associated 

with this proposed rule, as well as our people's tm,ditional knowledge of the polar bear. 

The Introduction and Background sections of our comments provide infonnation about 

ASRC, its Inupiat shareholders, their traditional knowledge about the polar bear and the legal 

basis for USFWS to address our shareholders' concerns. 

The balance of this transmittal letter will touch upon a few important matters associated 

with the proposed listing which are !!Q1 exclusively science based, but which provide important 

and relevant information for understanding our comments. We have separated this information, 

from our formal comments to he in accord with what we understand are USFWS's guidelines for 

science-based comments on proposed listings. 
369 


82737.181

L Pmaration of an EIS Would Benefit the Listing Proposal 

The proposed listing of the polar bear as threatened constitutes "a major Federal action" 

which should be subject to the preparation of an Environmental Impact Statement (EIS) under 

the National Environmental Policy Act. This has not been done, however, Pecause the 

Department ofInterior concluded in 1983 that ESA listings do not legally require the preparation 

of EIS dOCUJnents. This is unfortunate because this listing action, if implemented, bas the 

potential to significantly impact ASRC and its shareholders. The potential for a negative impact 

on the local commuuity from an ESA listing has been seen in other ESA listings such as the 

sp.otted owl and various salmon listings in the Pacific Northwest. The potential negative impacts 

from listing the polar bear under the ESA could affect: 

• the thousands of Inupiat Eskimo people who live in Villages and commuuities on 

Alaska's North Slope; 

• local community needs for infrastructure by imposing increased costs and 

permitting delays for Villages and their local government in their efforts to 

provide essential public services for their residents; 

• the flow of tax revenues to the North Slope Borough and the State of Alaska 

which support our schools and many other basic public services; 

• our people's subsistence taking of wildlife species in the North Slope's marine 

and onshore environments; 

• the continued and expanded exploration and production of needed domestic ail 

reserves on the North Slope and their costs; and 

• the viability and timing of the proposed Alaska natural gas pipeline which, if 

constructed, would deliver large volrunes of needed gas reserves to United States 

consruners. 

Preparation of an EIS would go a long way towards providing information on the many 

socio-economic issues and questions presented. An EIS would include a review of all available 

and reasonable alternatives to the proposed polar bear listing, thus determining the most 

constructive way to benefit the polar bear population. Further, for USFWS, moving more 

deliberately and preparing an EIS would permit a better evalnation of the applicable science, the 

root ca~s of the problems presented, an analysis of available remedies, a determination oithe 

costs of unintended socio-economic in;J.pacts and gcnerally lead to a more informed policy 

decision. 

2. Impact of the Listin~ on all Alaska Natives 

USFWS should be aware that the proposed listing of the polar bear, if implemented, may 

have signifiCl!llt impacts on ASRC and on the cleven other Alaska Native Regional Corp@rations 

(ANC's) in Alaska and their shareholders, most of whom are located outside the range of the 

pol~. bear. This is because under the provisions of Section 7(i) of Alaska Native Claims 

Settlement Act of 1971 (ANCSA), all ANC's are required to share 70 percent of the revenues 

derived from their lands with each of the other eleven ANC's. ASRC is a majol'provider of 7(i) 

revenues. If revenues to ASRC decline because of an ESA listing (e.g., new regulatory 

requirements, delays in permitting, restrictions on oil and gas developments or for other related 
370 


82737.182

reasons), this will reduce the level of7(i) payments. We understand that such economic 

conceplS are not a factor in USFWS's decision to list a species under the ESA. However, 

economics are a factor in the designation of critical habitat for a listed species and d~cisions to 

limit or curtail activities in areas designated as critical habitat. 

3. ASRC's Recommendationoll the Proposed Rule 

Based uWn our review of the proposed rule. ASRC recommends that USFWS should 

withdraw the proposed listing of the polar bear as threatened under the ESA as the evidence 

presented does not justify such a listing. The proposed listing does not meet the ESA's 

prescribed criteria because: I) the available scientific data does not support the conclusion that 

polar bear populations are declining; 2) traditional Eskimo knowledge does not support the 

conclusion that polar bear are negatively impacted by "Arctic warming" or that polar bear 

populations are declining; 3) assuming that global climate change causes sea ice in the Arctic to 

recede, the immediate and foreseeable impacts of receding sea ice on polar bears is not ~ely to 

cause the species to be threatened with extinction; and 4) even if receding sea ice has some 

negative impacts on the polar bear, there are sufficient existing regulatory mechanisms to prevent 

the species from being threatened with extinction. 

As noted further in our comments, USFWS has an obligation to consult with the Alaska 

Native Villages represented by ASRC regarding development of the rule to list polar bear under 

the ESA and with ASRC regarding management of the polar bear, a subsistence species. We 

look forward to the fulfillment of this consultation requirement, and an opportunity to discuss 

with USFWS the comments set forth below. 

fl. I! ~A.ls;. Roberta Quintavell __ 

President and Chief Executive Officer for 

ASRC 
371 


82737.183

Comments of Arctic Slope Regional Corporation on the Proposed Rule to List the Polar 

Bear (Ursus maritimusl as Threatened Throughout Its Range 

I. INTRODUCTION 

Thank you for affording Arctic Slope Regional Corporation (ASRC) the opportunity to 

comment on the United States Fish and Wildlife Service's (USFWS) proposed rule to list the 

polar bear (Ursus maritimus) as threatened throughout its range under the Endangered Species 

Act (ESA).' 72 Fed. Reg. 1064 (January 9, 2007). For thousands of years, the Inupiat people 

have lived off the Arctic Ocean and on lands within the Nortb Slope of Alaska. Inupiat culture, 

society and economy have coexisted with the polar bear. Because of our special relationship 

with the polar bear, ASRC and its Inupiat shareholders have a unique interest in this ESA listing 

decision. 

ASRC has an obligation to protect our Inupiat shareholders' interests by ensuring that 

USFWS's proposed rule is objective, based on good science, draws on all relevant scientific 

disciplines and is informed by-and respects---Inupiat traditional knowledge of our 

environment, including the use of sea ice' by polar bears. In our view, the proposed rule to list 

the polar bear falls short. 

Based upon our review of the proposed rule, the listing of polar bears as threatened under 

the ESA is not warranted at this time because: 1) the available scientific data do not support the 

Richard Glenn, Vice-President of Lands for ASRC, has been authorized to coordinate ASRC's comments 

regarding USFWS's proposed rule. Mr. Glenn testified before USFWS at the March 7, 2007 hearing in Barrow, 

Alaska (testimony attached as Appendix A). Points made in Mr. Glenn's testimony have been endorsed by ASRC 

and incorporated within this comment document. 

, In the proposed rule, USFWS uses the generic tenn "sea ice" when discussing the pDlar bears' habitat. As 

noted in these comments, there are several different types of sea ice which are used by the polar bear, for example, 

landfast ice (or fast ice), marginal ice, or perennial ice pack. The different types ofsea ice have different 

characteristics which should be noted by USFWS. For purposes of our comments, Jandfast ice means sea ice that is 

immobile due to its attachment to a coast, usually extending offshore to about the 20-m isobath; marginal ice (or the 

marginal ice zone) is delimited by the influence oflow density meltwater and scattered ice flows from the receding 

pack ice and by the penelJation of ocean swell into the pack ice; and perennial ice pack includes sea ice that is 

capable of substantial motion and deformation. II is inaccurate for the agency to refer solely to "sea ice" in 

discussing polar bear habitat in the Arctic. 
372 


82737.184

conclusion that polar bear populations are declining; 2) traditional Eskimo knowledge does not 

support the conclusion that polar bear are negatively impacted by "Arctic wanning" or that polar 

bear populations are declining; 3) assuming that global climate change causes sea ice in the 

Arctic to recede, the immediate and foreseeable impacts of receding sea ice on polar bears is not 

likely to cause the species to be threatened with extinction; and 4) even if receding sea ice 

negatively impacts the polar bear, there are sufficient existing regulatory mechanisms to prevent 

the species from being threatened with extinction. 

The polar bear is, of course, an iconic species of the United States, ifnot ofall nations. 

Making the charismatic polar bear a "poster child" in the national and international climate 

change debates-without demonstrating that climate change is in/act adversely impacting polar 

bear populations-does not serve the interest of the polar bear, the ESA or the United States. 

IL BACKGROUND 

A. ASRC and its Inupint Shareholders 

ASRC is a private, for profit, Alaska Native owned corporation created at the direction of 

Congress under the terms of the Alaska Native Claims Settlement Act of 1971 (ANCSA). ASRC 

represents the interests of its more than 9,000 Inupiat shareholders. ASRC is committed to 

preserving the Inupiat subsistence way of life, culture and traditions that strengthen both our 

shareholders and ASRC. Adhering to the traditional values of protecting the land, the 

environment, the wildlife and the culture of the Inupiat is the foundation of ASRC's mission. 

ASRC represents eight villages on the North Slope of Alaska: Point Hope, Point Lay, 

Wainwright, Atqasuk, Barrow, Nuiqsut, Kaktovik and Anaktuvuk Pass. As a corporation, ASRC 

employs 6,000 people and bas a growing shareholder population. ASRC was granted, and holds 

legal title to, approximately five and a halfmHlion acres of the 56 million acres ofland on 
373 


82737.185

Alaska's North Slope which the Inupiat people used and claimed under aboriginal title. ASRC'g 

subsidiaries offer oompanies doing business on Alaska's North Slope engineering, consulting 

services, civil construction and oil and gas field support services. ASRC is also engaged in 

petroleum refining and distribution, aerospace engineering services, communications, venture 

capital management and facilities management services. 

B. Traditional Knowledge 

There is no other group in the oountry with as much historical knowledge on the polar 

bear and its habitat as our Inupiat shareholders. Our knowledge is both traditional and, in some 

cases, scientific as many Inupiat people are involved in conducting and supporting scientific 

research on wildlife, sea ice conditions and climate change. Fundamentally though, our 

knowledge is traditional and built upon thousands of years of experience with the polar bear and 

its habitat. 

C. Shared Concerns 

The Inupiat people in general are just as ooncemed as members of the American public, 

perhaps even more so, about the changes in sea ice oonditions over time and the potential impact 

of these changes on polar bear and other wildlife species in the Arctic. We monitor these 

changes closely because they are critical to our subsistence way of life and our culture. The 

Mayor of the North Slope Borough spoke eloquently on this point in his remarks at the hearings 

in Barrow, Alaska on March 7, 2007. We ask that those remarks be acoorded careful attention 

byUSFWS. 

D. ASRC's Inupiat Shareholders and Our History 

ASRC represents both the individual Inupiat and their cultural and traditional interest in 

the polar bear and its corporate interest as a major landholder and provider of services to 
374 


82737.186

companies involved in North Slope oil and gas exploration, development and production. The 

officers of ASRC, acting pursuant to our Board's policy decisions, have an obligation to present 

our judgment on state and federal issues which impact ASRC' s business interests and our 

shareholders' cultural and traditional interests.3 

The Inupiat people have a unique standing on this proposed rule. We have lived for 

thousands of years as the only residents of the American Arctic in a difficult environment that 

demanded pragmatic study and understanding of all Arctic wildlife species, including the polar 

bear. Much of our early interaction with the outside world has had negative aspects: 

exploitation by early commercial whalers; the introduction of diseases, alcohol and drugs; the 

taking of 50 million acres of our lands by the federal government for the State of Alaska and for 

mineral, oil and gas development; and the past subversion of our culture, language and traditions 

by government agencies. Our concerns about change in the Arctic and our lives are well 

grounded in our historical experiences. ASRC respectfully requests that USFWS consult directly 

with officials at ASRC and other North Slope native entities to address our concerns before 

proceeding further in this matter. 

E. Basis for Addressing ASRC's Concerns 

ASRC has many direct interests in USFWS's proposed rule to list the polar bear as a 

threatened species under the ESAand significant concerns about the science and other related 

matters advanced to justify the proposed rule. USFWS should spend additional time and 

resources to focus on these issues and concerns. As noted in Executive Order 13175 (April 29, 

1994), USFWS has an obligation to communicate on a government-to-government basis with the 

Alaska Native entities recognized by the Secretary of Interior. The eight Villages represented by 

ASRC respects the views of all our shareholders and has encouraged local ViHage leaders to present their 

individual views to USFWS on thi$ importWlt matter. To this end, ASRC has made an effon to bring USFWS's 

proposed polar bear listing to the attention oflocal Village leaders. 
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ASRC are included on the Secretary of Interior's list of Indian Entities Recognized and Eligible 

to Receive Services from the United States Bureau ofIndian Affairs and should be afforded the 

consultation benefits described in Executive Order 13175. We ask that USFWS fulfill its 

requirement to have regular and meaningful consultation and collaboration with officials in the 

development of this federal action that will have substantial implications for the VUIages. 

III. COMMENTS 

A. Issues with the Scientific Studies and Data 

1. The proposed listing's documentation and study of polar bear population 

levels and treruis do not support a listing at this time. 

The polar bear species is comprised of 19 relatively discrete populations located in the 

Arctic's vast expanse, with popUlations in several different countries including the United States, 

Canada, Greenland, Norway and Russia The proposed rule notes both the status and a trend 

assessment for each polar bear population. 72 Fed. Reg. at 1070. The current population 

numbers used in the proposed rule indicate that, of the 19 world-wide popUlation projections 

analyzed, two-thirds are described as not detenninable or not declining. Of the 19 populations, 

the status of seven populations cannot be detennined, six populations are "not reduced", four 

populations are "reduced" and two populations are identified as "severely reduced from prior 

excessive harvest". 72 Fed. Reg. at 1070. 

With respect to the predicted population trend, the proposed rule states that for seven 

populations the trend cannot be detennined, for five populations the trend is stable, for five 

popUlations the trend is declining, and for two populations the trend is increasing. 72 Fed. Reg. 

at 1070. ASRC appreciates the effort being made, particularly over the past decade, by dedicated 

scientists to establish a solid count of polar bears. However, the population data and projected 
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trends included in the proposed rule do not support a listing at this time. The data do, however, 

indicate that more intensive polar bear population research and study should become a priority. 

ASRC is familiar with the case of the Southern Beaufort Sea population (the population 

with the most extensive data and life history), which the proposed rule states has a "predicted 

trend [of] declining and the status is designated as reduced". 72 Fed. Reg. at 1070. Yet in 

another portion of the proposed rule the current population numbers for the Southern Beaufort 

Sea population are described as "not statistically different" than previous population counts of 

prior decades. 72 Fed. Reg. at 1076. These statements on the Southern Beaufort Sea population 

are inconsistent. It appears that USFWS determined that the population's trend is declining due 

to a study showing a variation in survival rates, weights and skull sizes for cubs and not based on 

a decline in the numerical population. 72 Fed. Reg. at 1076. Based on information presented in 

the proposed rule, it is not reasonable for the agency to project that the population will decline or 

that the population status is reduced given that the current population is consistent with 

population counts of past decades. 

USFWS's data regarding the number of animals in a discrete polar bear population has 

other significant gaps which may result in an under-reporting of the animals comprising a polar 

bear population. For example, the population number for the Chukchi Sea population is 

estimated to be 2,000 based "on extrapolation of aerial den surveys", 72 Fed. Reg. at 1070. 

USFWS acknowledges that the status and trend for this population cannot be determined based 

on existing data. However, we question whether even the 2,000 population number should be 

used because it is based on aerial den surveys, which are not sufficiently reliable to provide an 

accurate population count. This type of population estimate is insufficient to support a listing 

under the ESA. 
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The data on the munber of animals comprising a polar bear population also does not 

appear to have taken into account migrating animals within a population. Polar bears migrate 

and are in flux between locations. Scientists and Alaska Natives have documented polar bear 

denning on the pack ice in thc central Beaufort Sea; those dens subsequently have drifted with 

the pack ice. This observation is significant because in the Arctic, as noted in the proposed 

listing, polar bears denning on pack ice may travel with the ice outside their usual locations. As 

described by Mr. Glenn in his testimony in Barrow, Alaska on March 7, 2007 (see Appendix A), 

in the span of several montbs a den drifted from the central Beaufort Sea to the Wrangell Island 

vicinity, offshore of the Russian Far East. The mother and cub emerged from the den there and 

traveled back to the Beaufort Sea area This shows that dens can drift, and polar bear from onc 

population may exist in different areas of the Arctic. In this instance, the mother and cub 

traveled through approximately three different polar bear populations' areas in thc space of a few 

seasons. By not taking into account migrating polar bears, a population's numbers are likely to 

have been IUlder-reported by USFWS in the proposed rule. The accuracy of current population 

COlUlts is a threshold issue in an ESA listing, and should be determined with a greater degree of 

certainty than that exhibited in the proposed rule. 

Also, the data on polar bear populations' levels and trends in the proposed rule were 

largely extrapolated from cursory data and not derived from focused, in-depth studies. Rather 

than relying upon peer-reviewed studies and data to determine the potential effects of climate 

change on polar bear populations' levels and trends, USFWS relied upon projections and 

modeling. Even the authors ofkey studies relied upon by USFWS have described a "high degree 

of uncertainty" in the use ofprojections to determine the impact of climate change on polar bear 

populations' levels and trends. Derocher et aI. 2004, p. 173. USFWS's decision to base the 
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proposed listing on data with a "high degree of uncertainty" is not consistent with the level of 

scientific information required to support a listing under the ESA. 

Finally, the proposed listing is based primarily on climate change and the loss of sea ice 

habitat, not a statistical decline in polar bear populations' numbers. In the proposed rule, 

USFWS focused more on the data provided by projections of climate change impacts on sea ice 

than on the current numerical status of the polar bear. Without a clear understanding of the 

number of animals comprising each polar bear population, how can USFWS determine whether 

or not the polar bear population levels are declining? Projections and modeling provide a "high 

degree of uncertainty" and should not be the basis for a determination that polar bear popUlations 

will exhibit declines in the future. There is too much uncertainty in the proposed rule regarding 

the current number of animals within each of the 19 polar bear populations and the lack of peerreviewed scientific studies and data regarding polar bear populations levels and trends to support 

a listing of the entire species at this time. 

2. The proposed listing lacks suffICient documentation and study of the 

impact of sea ice conditions and climate change on polar bear population 

levels and trends. 

USFWS found that the current and anticipated changes to the polar bear's sea ice habitat 

will result in decline of polar bear populations' levels significant enough to warrant listing for 

the entire species under the ESA. However, the studies cited by USFWS in the proposed listing 

are hesitant to predict future polar bear population trends. The 2004 Derocher study, which is 

cited throughout the proposed rule, states: "[i]t is not possible to confidently predict whether a 

reduction in sea ice area would necessarily result in a corresponding reduction in the size of polar 

bear populations .•. in some areas polar bear popUlations may increase if the changes [result in} 
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increased seal populations." Derocher et al. 2004, p. 171. The report also concludes that there is 

a "hlgh degree of uncertainty" about many of its own predictions. Derocher et al. 2004, p. 173. 

The proposed rule hypothesizes that a potential decline in abundance and distribution of 

ringed seal, considered by USFWS as the primary prey of the polar bear, due to changes in the 

sea ice habitat would cause a corresponding decline in the polar bear populations' levels. 72 

Fed. Reg. at 1074-75. Yet the data used by USFWS is insufficient to support this key 

conclusion. The agency's conclusions regarding the potential impacts of projected sea ice 

changes on ringed seals arc speculative. The proposed rule contains no data showing a 

population decline of ringed seal populations in the Arctic, despite the current reduced summer 

ice conditions. Without supporting data, the proposed rule concludes that a "reduction in sea ice 

is likely to result in a net reduction in abundance of ringed seals", citing only one study, ACIA 

2005, at p. 520. In the absence of reduced or declining ringed seal population nwnbers-at a 

time when the summer sea ice is receding, it is not reasonable for USFWS to conclude that 

changes in sea ice (due to global climate change) will cause ringed seal abundance and 

distribution to decline, thereby significantly affecting the polar bear populations' levels leading 

to a threat of extinction. 

3. The proposed listing lacks adequate review of existing studies and data on 

climate change and the causes of sea ice recession in the Arctic. 

USFWS's proposed rule references scientific studies and data written by a relatively 

small group of polar bear researchers and scientists, and does not reflect the views of the larger 

scientific c.ommunity which has stuilied the Arctic and the potential impacts of global climate 

change on that environment While there is a consensus among researchers and scientists about 

warming in the Arctic, there is little sci entific consensus as to the causes of this condition, how 

long this warming trend will continue, and its long-term impacts on the polar bear. USFWS has 
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detennined that the wanning trend is caused by climate change-- primarily human actions 

creating COz-and the greenhouse effect. The agency then concludes that the impact of climate 

change has resulted in a receding of sea ice, threatening the habitat of polar bear and 

necessitating a listing of the species under the ESA. 72 Fed. Reg. at 1094. However, USFWS's 

proposed role does not acknowledge, much less address, the lack of consensus among the 

scientific community regarding the relative causes for warming in the Arctic. The agency's 

failure to review existing scientific studies on warming in the Arctic. climate change and the 

impact on sea ice which conflict with the view set forth in the proposed listing is a significant 

shortcoming in the proposed listing. 

a. Questions about Science and the Understanding a/Climate 

Change in the Arctic 

USFWS detennined that global climate change was causing habitat modification in the 

Arctic. endangering the polar bear populations. 72 Fed. Reg. at 1095. However, the proposed 

rule failed to address several issues related to the impact of climate change in the Arctic and the 

impact such a change would have on the polar bear. The following issues should be addressed 

by USFWS before finalizing the proposed rule: 

• Are the climate changes in the Arctic natural and are the climate changes cyclical and 

transitory? 

• How long will wanning in the Arctic occur before the trend flattens or reverses? 

• Have polar bears experienced similar climate changes in prior Arctic history"? 

In the last 10,000 years, polar bear have survived at least two periods of significant climate wanning, 

including a period when temperatures were much warmer than present. CRS Report 2001, p. 9·10 (available at 

http://www.opellCfs.comlrpts/RL33941 7oo10327.pd!». During this time, the sea ice above North America 

retracted substantially allowing Arctic species to reach areas they cannot reach today. CRS Report 2007 at p. 9. 

While USFWS mentions historic warming periods in the proposed rule, the agency has not provided a detailed 

examination of the climate record for the Arctic. See 72 Fed. Reg. at 1081. By not reviewing the climate change 

record and the ability of polar bear to survive similar (ifnot more sever) periods of climate warming, USFWS has 
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• Can polar bears adapt to climate changes and have they successfully adapted to such 

changes in the past (e.g., in previous ice ages and other more recent cooling trends 

followed by wanning trends)? 

• What are other likely contributory causes of observed changes in nearshore ice 

recession? To what extent are changes to nearshore ice caused by the introduction of 

greenhouse gases (CCh) in the atmosphere, and to what extent do the changes to 

nearshore ice reflect a normal cycle of warming after what some scientists refer to as 

the recent "Little Ice Age" of 1500 to 1800? 

• Does USFWS have sufficient understanding of climate change history in the Arctic to 

conclude that the sea ice changes which are currently occurring actually "threaten" 

the polar bear populations? 

The answers to these questions are vital to provide a supportive record for the proposed 

polar bear listing, and to support additional management and regulatory initiatives for 

conservation of the polar bear. 

b. Studies Regarding Global Climate Change and the Arctic 

i. Study a/the Impacta/"Natural" Warming in the Arctic 

Dr. Syun-Ichl Akasofu, a leading and long-time Arctic scientific researcher and Founding 

Director of the International Arctic Research Center, has recently published a recent paper which 

focuses on the causes of warming in the Aretic! USFWS stated that a significant factor in the 

listing of the polar bear is the threat of habitat loss due to sea ice recession caused by climate 

change. Dr. Akasofu's paper reviews the current warming trend in the Arctic and whether or not 

created a gap in the scientific data for the proposed listing, and failed to consider the "best scientific and commercial 

data available." 

, Dr. Akasofu, "Is the Earth Still Recovering from the 'Little Ice Age'?" (2007) available at 

<http://www·iare.uaf.edulhighlightsl2007/a!casofu 3 07lEarth recovering from UA.pdf.> (attached as Appendix 

B). 
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such a warming trend has a historical basis. Dr. Akasofu concludes that the majority of wanning 

in the Arctic-two-thirds-is the result of "natural" warming, and a third of the warming can be 

traced to CO2 and greenhouse gas climate change caused by human activity. USFWS should 

review this and other studies and data which specifically review the impact of climate change in 

the Arctic, because a final decision on the proposed rule is driven by the effect of global climate 

change on polar bear habitat. Dr. Akasofu is a respected scientist who has an understanding of 

the Arctic and has specifically looked at the warming of the Arctic and potential causes. 

USFWS should review studies such as Dr. Akasofu's which look at the various potential causes 

of warming in the Al'ctic. 

ii. Study on the Impact of Advection on Sea Ice 

In reviewing the forces leading to a loss of sea ice in the Arctic, USFWS should include 

studies that explore whether the reduction in sea ice is due in part to a combination of the ice 

pack melting and advection (ice leaving the Arctic via the Greenland Strait (between Greenland 

and Iceland). As noted in an article by Walter B. Tucker III et al, "[w]ben the [North Atlantic 

Oscillation] index is strongly positive, as in the 19905, a weakened or non-existent Arctic 

anticyclone suppresses the Beaufort Gyre. This regime causes ice to be advected rapidly out of 

the western Arctic, which, along with increased melting, inhibits the development, accumulation, 

or incorporation oflarge amounts of thicker deformed ice.'" The reduction in sea ice due to 

advection is not likely to be permanent, although it may take many years to increase the 

thickness of the ice. The study found that "a shift back to the anticyclonic circulation pattern 

(proshutinsky and J olmson, 1997) would again increase ice thickness in the western Arctic, 

although a number of years may be required to substantially increase thickness." Id As required 

Walter B. Tucker III et at, "Evidence for rapid thinning 0 f sea ice in the western Arctic Ocean at the end of 

the 1980s", Geophysical Research Letters, Vol. 28, No. 14,2851, at 2854 (July 15,2001). 
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by the ESA, USFWS should review the "best scientific and commercial data available" and the 

study of advection and its impact on sea ice in the Arctic would fit that designation, particularly 

since the reduction of sea ice is cited as the main reason for the proposed listing of polar bear. 

B. Use of Traditional Knowledge in the Proposed Listing 

1. Traditional knowledge indicates thai a marginal ice zone does not 

negatively impact polar bear. 

A significant factor in USFWS's decision to list the polar bear was thc impact ofthe 

receding perennial ice pack and the agency's determination that this equates to a "habitat loss". 

72 Fed. Reg. at 1095. USFWS also mentions increased fetches of open water, and its negative 

effects ondenning and feeding. 72 Fed. Reg. at 1075-76. There is little mention of the marginal 

ice zone which must, and does, grow at the expense of a receding perennial ice pack. It is in this 

marginal ice zone that Inupiat subsistence hooters consistently see polar bears efficiently hooting 

ringed and bearded seals and walrus in the summer months. 

In waters offshore of ASRC's coastal villages, from mid-July to mid-AUgust, Inupiat 

people observe polar bears hunting in the marginal ice zone. This coincides with the arrival of 

the walrus herds, ringed seals and bearded seals on and aroood drifting ice floes. 11Us is an 

important habitat in which polar bears thrive because they can catch napping prey on ice floes, or 

use the floes for cover to catch animals in the water. As noted in Appendix A, blood-stained ice 

and feeding remnants on the drifting floes are numerous at this time of year. 

Derocher, whose 2004 study is frequently quoted by USFWS, notes that "if the multiyear 

ice ... is largely replaced by annual ice ... and the polynyas in the area [become) more 

numerous and larger it is likely that biological productivity might increasSl ... and the area 

would become better habitat for polar bears." Derocher et al. 2004, p. 169 (emphasis added). 

USFWS's proposed rule fixates on the "pack ice" as essential polar bear habitat but does not 
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adequately explore or acknowledge the extensive use of the marginal ice zone by polar bear. 

USFWS's lack of study and focus on this significant polar bear habitat is a major omission, 

which should be reconsidered before proceeding with the proposed listing. 

1. Eskimollnupiat observations conflict with information supplied by USFWS 

in the proposed role. 

As detailed below, the Inupiat people have many observations, experiences and 

traditional knowledge which are at odds with statements put forth by USFWS in the proposed 

rule. We ask that USFWS work with ASRC and other Inupiat institutions to clarify and resolve 

these differences before making a final decision on the proposed rule. 

a. Observations from Polar Bear Hunting 

In the proposed rule, USFWS dowoplays the use of the marginal ice zone by polar bear 

as part of the species habitat. It is our experience that polar bears frequent the marginal ice zone 

due to the hunting opportunities. Our hunters have seen polar bears come closer to shore in late 

spring from mid-May to early June when the ringed seals give birth to pups beneath stable 

snowdrifts on landfast sea ice. The polar bears smell the odor of a den of newborns seal pups 

beneath snowdrifts. Appendix A notes Inupiat observations made while following bear tracks in 

the spring and watching how and where the polar bear hunt the seal pups. Inupiat hunters and 

others have also accompanied scientists and trained dogs to the seal dens, which are not visible 

frOID the surface, but which have an odor that polar bears, foxes, and these trained dogs can 

detect. 

b. Instances of Polar Bear Cannibalism 

In the proposed rule, USFWS emphasizes that three instances of polar bear cannibalism 

were observed in 2004, leading to the conclusion that the interaction of environmental factors 

and nutritional stress are causing unusual behavioral events. 72 Fed. Reg. at 1076. However, the 
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Inupiat have observed and been taught by Elders and by traditional knowledge that a male polar 

bear will eat anything-including a female bear or cub-even when alternative food sources 

exist. This behavior cannot be ascribed to starvation when it is part of the polar bears' intrinsic 

character. 

c. Polar Bear Use a/Terrestrial Habitat 

The proposed rule concludes that reductions in sea ice have forced polar bears to utilize 

terrestrial habitat which contributes to nutritional stress. 72 Fed. Reg. at 1073-74. However, the 

Inupiat people who live along the Arctic coastline have observed this behavior for many years. 

Some polar bears will stay on the coast in the summer months, not necessarily because they are 

trapped there by the absence of ice, but because that is the season for them to feed on dead grey 

whales that the waves have brought ashore, or on beached walrus pups, or seals basking on the 

beach. The Inupiat who live along the Arctic coastline see this every year along the Alaskan 

coast; and it has also been documented at Wrange\ Island. Contra 72 Fed. Reg. at 1073. 

d. Polar Bears as Scavengers 

In September to October, polar bears feed on the remains of gray whales, walrus and 

other dead animals that have washed ashore during the fall-time storms. Groups of polar bears 

have been seen by our villagers establishing an over-wintering circle around any large carcass, 

such as a grey whale, that can sustain them through the winter. In the fall-time, polar bears also 

prey on walrus and seals that are resting on the beach. The bears also feed on the remains of 

bowhead whales harvested by fall-time whale hunters of the three eastern North Slope villages. 

While much has been written about the presence of polar bears around bowhead whale remains, 

traditional knowledge indicates this is simply a part of their natural feeding cycle. There are 

many naturally occurring carcasses that wash ashore that would sustain the polar bears in the 
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absence of the bowhead whale remains created by subsistence hunting. The proposed rule 

largely ignores these natural food sources of the polar bear without affording them appropriate 

consideration. These sources of food deserve further consideration, particularly in light of 

USFWS's uncertainty regarding the potential decline of ringed seals population and/or ringed 

seal availability as prey to polar bears. 

e. Alternative Polar Bear Habitat 

None of the hunting environments described above are on tlle multi-year "ice pack", but 

instead are located in the "marginal ice zones" and nearshore lands of the Beaufort and Chukchi 

Sea. This conflicts with USFWS's findings that sea ice is an essential platform from which polar 

bears meet life functions. 72 Fed. Reg. at 1080. The proposed rule also describes sea ice as 

"primary" polar bear habitat, but provides an insufficient analysis of these alternative habitats in 

which the Inupiat consistently observe polar bear. 72 Fed. Reg. at 1067. Alternative habitat for 

polar bear requires further analysis, particularly for a highly adaptive species such as polar bear, 

when that species is undergoing a potential change in habitat. 72 Fed. Reg. at 1066. The 

proposed rule should not ignore the existing, non-pack ice habitat of polar bear. As noted in 

Appendix A, the polar bear is an opportunistic animal and will eat whatever it can find. Polar 

bear have been known to be more than sixty miles inland, even with ice conditions that would 

have readily allowed them offshore perennial ice pack without swimming great distances. Polar 

bear hunt seals, belugas, and walrus from breatlring holes, and leads in both the pack ice and 

marginal ice zones. A polar bear is at home in the water, on the ice, and on the land. Polar bears 

adapt to the environment at hand and are not limited to the perennial ice pack as habitat. 

Inupiat hunters, using traditional knowledge and observation, know that a polar bear can 

swim better than it can walk-it is definitely a marine mammal. Although there must be a finite 
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distance for the polar bear's swimming range, it is considerable. In the proposed rule, USFWS 

concluded that a recent incident involving the drowning of polar bears is an indication of the 

hannful impacts of climate change and sea ice regression. 72 Fed. Reg. at 1077. However, 

USFWS provided no information that the instance of polar bear drowning is a recent 

phenomenon. Because the incident was recently observed does not mean that the event is unique 

or a recent development. Polar bears have adapted in the past, and adapt over time to changing 

habitat, prey and other food sources. There are changing and varied cycles of habitat, ice 

environment, prey animals and food sources for the polar bear in our region, including marginal 

ice zones, shorelines, inland areas, leads and multi-year ice. 

3. ASRC officials. Elders and other Inupiat Shareholckrs • observations and 

traditional knowledge of the polar bear do not support a polar bear listing 

under the ESA althis time. 

ASRC has made the Federal Register proposed rule available to elected officials, Elders 

and other ASRC shareholders who live in our North Slope Villages together with the testimony 

of the North Slope Borough Mayor Itta, Richard Glenn and others at the March 7, 2007 hearing 

in Barrow. A summary of some of the observations and the traditional knowledge of the Inupiat 

people who live in our Villages on this proposed listing of the polar bear as threatened are set 

forth below. 

Our North Slope village residents would support greater conservation protection for the 

polar bear if a case were made that the polar bear and its habitat are threatened by any conditions 

that the Inupiat people, or our units of government, can act to control. Observation over decades 

by Village people, however, identifies no such specific conditions threatening the polar bear that 

can be addressed by either USFWS or our people. Indeed, our people see and interact with more 

polar bears in recent years than they did 10,20 or even 40 years ago, indicating that existing 
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conservation regulations for polar bear at the local, state, federal and intcrnationallevels are 

working well. The species is healthy and overall the populations appear to be relatively stable. 

Our Village people agree that we are seeing wanning in the Arctic. Many of our Elders 

say, however, that this change is part of a normal and re-occurring cyeIe. Every year, and every 

generation, our weather is different; sometimes warmer, sometimes colder. Weather and ice 

conditions in the Arctic change annually and over the decades. Our Elders say these changes are 

cyclical over the generations. The Inupiat people have adapted to these changes over hundreds 

of years. So have the Arctic's wildlife species, including the polar bear. Our traditional 

knowledge tells us that environmental change is constant and dynamic in the Arctic, much more 

than in other climatic regions. That the Arctic wanning is a natural, cyclical climate change 

should be fully considered by USFWS. 

4. The proposed listing o/polar bear is similar to the attempt to list the 

bowhead whale in the 1970 's, in which the lnupiat demonstrated by 

traditionnl Native knowledge and science that the whale was not 

endangered 

Our Inupiat leaders say that this proposed listing of the polar bear reminds them of the 

efforts in the early 1970's to declare the bowhead whale as an "endangered species." This led to 

a major effort to prohibit the Inupiat people's traditional subsistence whale hunts. The Inupiat 

people went to court, initiated scientific studies, conducted popUlation counts and eventually won 

this debate. With the assistance of hard work, traditional Native knowledge and good science, 

the Inupiat proved that the bowhead whale species was, in fact, growing, not declining. As a 

result, we were able to save our whaling tradition, our Inupiat culture and our traditional 

subsistence way of life. This important lesson from the history of international and national 

government agencies acting on the basis of inadequate study and science should be examined in 

the context of this proposed polar bear listing. 
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Based on our bowhead whale experience of the 1970's, the lnupiat people developed and 

implemented a program of whale conservation and self regulation. Our Whaling Captains' 

Associations acted to study, monitor, conserve and regulate the lnupiat's traditional taking of the 

bowhead whale. This program has proven very successful. It has been copied for other species 

in the Arctic and Alaska as well as by indigenous people in many other parts of the world for the 

conservation of their wildlife. 

One option, not addressed by USFWS in the proposed rule, is that the Inupiat, with our 

traditional knowledge of the Arctic and our wildlife, should playa larger role in conserving the 

polar bear. USFWS could begin by employing experienced Eskimo hunters and whalers to 

observe, study and monitor the polar bear as the Inupiat did for the bowhead whale studies, 

popUlation counts and assessments in the \970's. Traditional and common·sense knowledge is, 

as history shows, very important USFWS and Department of Interior (DOl) should seek full 

access to this breadth ofknowleclge and year-round, firsthand traditional knowledge before 

taking premature action to list the polar bear as threatened. 

C. Existing Regulatory Mechanisms in the Proposed Listing' 

1. The proposed listing did not adequately consider existing regulatory 

mechanisms regarding polar bear conservation. 

USFWS has not fully taken into account current available conservation measures for 

polar bear. One key listing factor in the listing of species under the ESA is the consideration of 

the "inadequacy of exiting regulatory mechanisms" to conserve the species. 16 U.S.C. § 

1533(a)(I)(D). Polar bear conservation is governed by a number offederal and international 

measures, including: the work of the Alaska Nanuuq Commission, the 1973 Agreement on the 

Conservation of Polar Bears, the 2000 bilateral Agreement between the Government of the 

For additional infonnation on the international, federal, state and local regulatory mechanisms descnbed in 

Section C. of these comments, see Appendix C. 
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United States of America and thc Government ofthc Russian Federation on the Conservation 

and Management of the Alaska-Chukotka Polar Bear Population, the United States-Russia Polar 

Bear Conservation and Management Act of 2006, the Inuvialuit-Inupiat Polar Bear Management 

Agreement in the Southern Beaufort Sea and, more generally, the Marine Mammal Protection 

Act and the Convention on International Trade in Endangered Species of Fauna and Bora. 

These actions and forums, several of which have recently been strengthened, should be more 

thoroughly considered by USFWS. The agency should consider in particular the recent changes 

that were hard-won and international in scope, and usc significant indigenous resources to 

protect the very species that is the focus of the proposed listing. A thorough consideration of 

these mechanisms is required by law, but such a consideration is not cvidcnt in the proposed rule. 

In their focus on receding sea ice, USFWS has not properly considered existing polar bear 

conservation mechanisms, which consider both the polar bear as a species and the habitat upon 

which it is dependent. 

In particular, two key mechanisms for polar bear conservation have been recently 

strengthened. The Inuvialuit-Inupiat Polar Bear Management Agreement in the Southern 

Beaufort Sea, adopted in 2000, is a major agreement for polar bear conservation among 

indigenous people of the circumpolar north. The agreement is intended "to maintain a healthy, 

viable population of polar bears in the southern Beaufort Sea in perpetuity", and includes 

provisions for habitat conservation, take limits and identification of key research tasks. This 

agreement has led to a higher degree of international cooperation over the conservation of this 

important population. Actions authorized under this agreement include habitat protection 

recommendations (Article VIII, (7) (e». 
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Congress has expressly recognized the need for increased polar bear conservation in 

enacting new conservation measures just this past year in the United States-Russia Polar Bear 

Conservation and Management Act of2006. The Act significantly strengthens the mission of the 

Alaska Nanuuq Commission, focusing on the Alaska-Chukotka polar bear population, and 

establishes a formal international mechanism for polar bear conservation for this population. 

Importantly, both of these mcchanisms span international borders in three key countries for polar 

bears, the only three for which polar bear populations from the United States can reasonably 

travel. 

The benefit to conservation of polar bears in Alaska. Canada and Russia found in these 

regulatory mechanisms have significant value to the conservation of the species. There is little 

evidence in the proposed listing that the conservation benefit of these newly adopted 

mechanisms has been adequately considered by USFWS. 

2. The proposed listing did not adequately review existing local, state and 

international mechanisms designed expressly to reduce human causes of 

climate change (identified by USFWS as having a significant impacting on 

sea ice). 

Climate change has been identified by USFWS as a major contributor to changes in sea 

ice habitat. 72 Fed. Reg. at 1071. There is no cvidence that, in the proposed rule, USFWS 

considered rccently adopted or strengthened local, state or international initiativcs designed to 

reduce the man-made causes of climate change which contribute to warming in the Arl,.1ic. 

impacting sea ice, which in tum is cited as the primary factor for the determination that polar 

bear are a threatened species. 72 Fed. Reg. at 1082. The proposed rule contains incomplete 

information on existing regulatory systems and mechanisms to address climate change. 
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82737.204

a. international Regulatory Mechanisms 

The impact of climate change on the Arctic, and conservation of species in the Arctic, has 

been addressed by a high-level intergovernmental forum, the Arctic Council. Formed to ensure 

environmental, social and economic sustainable development in the Arctic region, current 

council members include the United States, Canada, Denmark, Finland, Iceland, Norway, Russia 

and Sweden. Six Arctic indigenous conununities are Permanent Participants on the Council. 

The Arctic Council has five expert working groups focusing on monitoring, assessing and 

providing scientific work regarding specific issues in the Arctic. The working groups and the 

scientific data they produce are a valuable resource and should be consulted by USFWS 

regarding polar bear and the impact of climate change on habitat in the Arctic. 

The proposed rule should also note international climate change policy such as the United 

Nations Framework Convention on Climate Change (UNFCCC), which regulates greenhouse gas 

emissions. 189 nations, including the United States, have ratified the UNFCCC, agreeing to the 

conunon objective of stabilizing greenhouse gas emissions "at a level that would prevent 

dangerous anthropogenic (human induced) interference with the climate system." UNFCCC at 

Art. 2. 

h. Federal Regulatory Mechanisms 

While the United States federal government has no existing active climate change policy, 

there are numerous bills currently pending in Congress that should be noted in the proposed rule. 

Introduced bills regarding climate change include: the Climate Stewardship and Innovation Act, 

S. 280; the Global Warming Pollution Reduction Act, S. 309; the Electric Utility Cap-and-Trade 

Act, S. 317; a draft Bingaman-Specter Bill; the Global Warming Reduction Act Bill, S.485; the 

Climate Stewardship Act, HR 620; and the Safe Climate Act, HR 1590. 
393 


82737.205

Additionally, on April 2, 2007, the United States Supreme Court decided its first climate 

change case, Massachusetts v. EPA, Case No. 05-1120, in which the court determined that the 

Environmental Protection Agency (EPA) has the statutory authority under the Clean Air Act to 

issue a rule regulating greenhouse gas emissions from new motor vehicles. Greenhouse gas 

emissions are a known contributor to climate change. This indicates the policy of the United 

States' with respect to addressing the causes of climate change through existing statutes and 

regulatory mechanisms may be undergoing significant change. 

c. State and Local Regulatory Mechanisms 

While USFWS was correct in noting that the United States lacks a comprehensive federal 

climate change policy, it failed to note significant state and local measures which have been 

adopted to reduce greenhouse gas emissions. The Regional Greenhouse Gas Initiative is an 

example of multiple states engaging in a state-level emissions cap-and-trade program. Also, the 

California Legislature has adopted an economy-wide cap on carbon dioxide emissions to reduce 

the state's greenhouse gas emissions, which rank at 12th-largest in the world, by 25 percent by 

the year 2020. Several other states have adopted or are considering similar measures to reduce 

their contribution to global climate pollution, such as Washington and Oregon. In addition, the 

West Coast Governors have adopted a Western Regional Climate Change Initiative through 

which Washington, Oregon, California, New Mexico and Arizona will work together on climate 

protection. 

Local governments have adopted climate change regulations as well. While the United 

States is not party to the Kyoto Protocol, 435 mayors from 50 states representing a total 

population of over 61 million citizens have agreed to meet or exceed the Kyoto Protocol targets 
394 


82737.206

in their own co=unities, including a 7% reduction from 1990 greenhouse gas emission levels 

by 2012. 

d. The Proposed Rule Should Reflect These Regulatory Mechanisms 

USFWS's statement in the proposed rule that "{t]here are no known regulatory 

mechanisms effectively addressing reductions in sea ice habitat at thls time" is disingenuous. 

72 Fed. Reg. at 1086. The agency has clearly made a detennination in the proposed rule that 

climate change (Arctic warming) is affecting sea ice, and polar bear populations are being 

affected by changes in the sea ice habitat. Yet in reviewing the factor on "existing regulatory 

mechanisms" USFWS ignores the vast amount of international, state and local regulatory 

mechanisms directly addressing climate change-even those directly addressing climate change 

in the Arctic. While these regulatory mechanisms may not specifically address "sea ice", 

because they address climate change (which the agency identifies as a major threat to polar bear) 

USFWS should review the adequacy of these regulatory mechanisms as required by section 

4(b){1){A) of the ESA. 

D. Consultation with Alaska Native Organizations on Subsistence Activities 

Section 10 of the ESA allows Alaska Natives to take any endangered or threatened 

species if the taking is primarily for subsistence purposes. USFWS retains the ability to 

prescribe regulations limiting the take of such species by Alaska Natives, but only if such taking 

''materially and negatively affects" the species at issue. 16 U.S.C. § 1529(e)(4). Before issuing 

subsistence hunting-limiting regulations, USFWS must provide notice and conduct hearings in 

the affected judicial districts of Alaska, and must also consult with the Alaska Native 

organizations (including ASRC). See Secretarial Order 3225 (2001). The consultation 

requirement states that the agency must provide technical. financial and other assistance to the 
395 


82737.207

Alaska Native organizations as is appropriate. Secretarial Order 3225 also provides that Alaska 

Native organizations have the opportunity to participate in the management of subsistence 

species that are candidate, proposed or listed species under the ESA. The management includes, 

but is not lirrrlted to: forrrring recommendations for management actions, plans or regulations; 

population and harvest monitoring projects; Jaw enforcement activities; education programs; 

research, design, data collection and use of traditional knowledge; habitat protection programs; 

and recovery projects. Therefore ASRC requests that USFWS consult with ASRC regarding the 

management of the polar bear, a subsistence species that is proposed for listing under the ESA. 

E. Critical Habitat Designation 

In the proposed rule, USFWS did not designate critical habitat for the polar bear, instead 

stating that a careful assessment of the designation of critical habitat would require additional 

time and evaluation. 72 Fed. Reg. at 1096. USFWS does, however, specifically requests 

infonnation regarding critical habitat in comments on the proposed rule. The designation of 

critical habitat should be "on the basis of the best scientific data available and after taking into 

considemtion the probable econorrrlc and other impacts of making such a determination •... " 

50 C.F.R. § 424.12(a). The request for critical habitat data, during the process for the polar bear 

ESA listing, creates some difficulty for ASRC. First, as noted in our comments, ASRC does not 

believe that, based on the data and reasoning set forth in the proposed rule, polar bear should be 

listed under the ESA or that critical habitat should be designated for the species. Second, 

economic data may not be used in determining if a species should be listed under the ESA. 

However, USFWS is required to take into account such data in the designation of critical habitat. 

Submittal of such data by ASRC in these comments could be seen as improper with regards to 

the potential ESA listing, thus limiting the utility of our comments on the proposed rule. 
396 


82737.208

Since USFWS requested such information, however, the letter oftraDsmittal to these comments 

provides an overview of some of the economic impacts the proposed listing and designation of 

critical habitat would have on both the Inupiat people and the Alaska Native community as a 

whole. IfUSFWS fmalizes the proposed rule and lists the poJar bear under the ESA, then ASRC 

requests that it be consulted and provided a separate opportunity to comment on critical habitat, 

including presentation of data on the economic impact of specifying areas in the North Slope as 

critical habitat. Third, USFWS has not presented any indication of which of the immense areas 

in the range of the polar bear might be listed as critical habitat. Does the agency expect 

comments on every area potentially traversed by polar bear? If so, the comment period for this 

proposed rule is far too short for any meaningful data to be gathered or put in a useable format. 

If USFWS proceeds to finalize the proposed rule and lists the polar bear, the agency should 

specify the areas under consideration for critical habitat and provide an opportunity for comment 

at such time. 

F. ASRC's Recommendation regarding the Proposed Rule 

ASRC proposes that DOl and USFWS withdraw the proposed rule to list the polar bear 

as threatened. DOl and USFWS should conduct further research on polar bear and prey 

population data and on the potential effects of sea ice change on the polar bear. In addition, the 

DOl and USFWS should work with existing regulatory mechanisms to strengthen polar bear 

conservation. This action would bring needed focus and practical experience to protect the polar 

bear while expanding our understanding of the polar bear populations and their habitat. It would 

also mean that the effort for a factual and science based evaluation is now beginning and not 

concluding. This would create momentum for new studies and research initiatives supported by 

local governments, the State of Alaska, federal agencies, and international organizations. 
397 


82737.209

This greater emphasis on polar bear conservation and study that ASRC proposes 

acknowledges that polar bear populations' statistics are uncertain and require additional study, 

and addresses the need for research on receding ice conditions and the impact of climate change 

in the Arctic. This action by DOl and USFWS will also spur needed actions by the other Arctic 

nations on whom the long term well-being of the polar bear is dependant. There are no more 

than approximately 3,500 of the world's total of20,000 to 25,000 polar bears within the United 

States' claimed territory and subject to the United States' jurisdiction. Greater domestic 

conservation and study by the United States followed by meaningful efforts by the federal 

government to engage other nations in cooperative evaluations, study and research could-and 

should-lead to productive bilateral and multilateral efforts to address polar bear conservation 

and the international problem of climate change in the Arctic. The challenge of dealing with the 

polar bear's future well-being is very important to the Inupiat people and requires a better 

understanding of the polar bear populations, their habitat and the causes and effects and the 

evolving science of climate change as it applies to the unique habitat within the Arctic. 

F. Review of the ESA's Five Criteria for Listing a Species 

Section 4 of the ESA, and its implementing regulations, prescribe five criteria for 

USFWS to consider when determining whether to list a species. 16 U.S.C. § 1533(a); 50 C.F.R. 

§ 424.11. Those criteria include: (1) the present or threatened destruction, modification or 

curtailment of a species habitat or range; (2) overutilization for commercial, recreational, 

scientific, or educational purposes; (3) disease or predation; (4) the inadequacy of existing 

regulatory mechanisms; or (5) other natural or manmade factors affecting the species continued 

existence. ASRC believes that polar bear do not meet any ofthc five criteria. As noted above, 

data do not show that current and anticipated ehanges to polar bears' sea iee habitat are causing a 
398 


82737.210

decline of polar bear populations or pose an increasing risk to polar bear populations. ASRC 

agrees with USFWS's conclusion that overutilization as a singular factor does not threaten the 

polar bear. 72 Fed. Reg. at 1085. ASRC also agrees with USFWS that there are no indications 

that disease or cannibalism will have an effect on the population levels of the polar bear. 72 Fed. 

Reg. at 1086. ASRC agrees with USFWS that threats to polar bear from direct take, disturbance 

by humans and incidental or harassment take are adequately addressed through range state laws, 

statutes and other regulatory mechanisms. 72 Fed. Reg. at 1091. As discussed above, ASRC 

believes USFWS failed to consider existing regulatory mechanisms at the international, state and 

local level that address the impact of climate change on the Arctic and the polar bear's habitat. 

Finally, ASRC agrees with USFWS's conclusion that natural or manmade factors, specifically 

contaminants, ecotourism and shipping, do not threaten the existence of the polar bear. 72 Fed. 

Reg. at 1094. 

IV. CONCLUSION 

ASRC strongly believes that a threatened listing for the polar bears does not meet 

scientific, legal or regulatory requirements and, ultimately, would have very little impact on the 

polar bears well-being. It will not create more ice cover. It will not change the polar bear's 

ability to locate dens or prey. But a listing under the ESA will negatively and disproportionately 

affect the lives of the people, the Inupiat Eskimos, who co-exist with the polar bear in the 

Alaskan Arctic. Our communities will run the risk of becoming "critical habitaf'. Playgrounds, 

gravel pits, airstrips, landfills. campsites, hunting areas, village expansions-all of these may be 

limited by the subjective process invoked prematurely and unfairly in the name of the ESA. 

ASRC instead recommends that we work together to understand the polar bear and its habitat, 

and specifically work toward understanding the consequences of how development and 
399 


82737.211

greenhouse gas emissions generated far away from our lands and waters affect the habitat we 

share with the polar bear. 
400 


82737.212

APPENDIX A 
401 


82737.213

655 

Microsatellite DNA and mitochondrial DNA 

variation in polar bears (Ursus maritimus) from the 

Beaufort and Chukchi seas, Alaska 

M.A. Cronin, S.C. Amstrup, and K.T. Scribner 

Abstract: Radiotelemetry data have shown thut polar be,lfs (Ursus maritimus Phipps. 1774) occur in separate subpopulations in the Chukchi Sen and the southern B..:aufort Sea, However. segregation is not absolute, and there is overlap of 

ranges of animals in each subpopulation. We u<;ed genetic variution at eight microsatellite D~A loci and mitochondria! 

DNA (IlltDNA) to further asses,> the degree of <;patial structure of polar bears from the Chukchi and southern Beaufort 

seas. Microsute!1itc aU de frequencies and mtDNA haplotype frequencies of bears from the southern Beaufort and Chukchi 

seas did not differ significantly. Lack of differentiation at both maternally inherited rntD.'JA and bi-parentally inherited 

microsatellite IOel LhaL noV. between the two areas is mediated by both sexes. The genetic data indicate that 

polar be,lrs in the and Chukchi seas compose one interbreeding population. However, there is comiderable fidelity to ranges in each area, particularly by adult females. The combined genetic and movement data suggest that 

polar bear~ could be managed ali BC':H1fort SC'~l and Chukchi Sea subpopu!ntions of a combined ~oulhern Beaufort Sea and 

ctlllkchi Sea population. 

Resume: Des donnees de radiotelemetric montrent que les ours polaircs (Ursus maritimus Phipps, 1774) de la mer de 

Chukchi ct du >.ud de la mer de Beaufort formen! des sous-populations serarees. La segregation n'csl cependant, absolue, ct il a un chevauchemcnt d'aires d'anlmaux de chague sou<;~popu!aliol1. Nous utili7.0ns la g6netique a huH locus ct' ADN et dans I' ADl',' mitochondrial (ADNml) pour Ie degn~ de structure spatia!e chel 

les ours pol aires de la mer de Chukchi et du sud de la mer de Beaufort Les des ulleles microsatclliles ct des 

haplotypes d'ADNmt chez les ours polnir~s de In mer de Chukchi et du sud de mer de Beaufor1 ne different signifiea{ivemcnl. Le manque de diftcrenciation tant dans I'ADNmt d'origine mmemcJle dans lc~ locus herites des deux parents montre que !e nux gcnetiquc entre les deux region;, e,t par les Jcux sexes. Lcs donnees 

gcnctiques indiquen! que jes Ol!r~ poiaires du sud de la mer de Beaufort et de la mer de Chukchi formenl une seule popula!ion reproducfivc. l! existe, llcanmoins, une forte fidclitc <lUX aires vitales dans chaqlle region, particulierement chel les 

femelles adultes. Les donnees combinecs sur la gcn6tiquc el les d6placemcnts lais'\ent croire que la gc')tion des ours polnires pourrail bien se fmre nu nlveau des sous-populations de la mer de Oeaufor! el de la mcr de Chukchi au sdn d'une 

population conjointc du sud de la mer de Beaufort et de In mer de Chukchi. 

lTraduit par la Redaction J 

Introduction 

Polar hears (Ursus marilimus Phipps, 1774) in northern 

Alaska primarily occur in two SUbpOplllations (Fig. 1; 

Amstrup et al. 2000, 200S), Amstrup et al. (2004, 2005) 

showed that polar bears occurring hetween the McKenzie 

River (Canada) and the Colville River, Alaska, compose a 

southern Beaurort Sea suhpopulation. Similarly, polar hears 

west of Cape Lisburne. Alaska, represent a Chukchi Sea 

Received 18 August 2005. Accepted 2 March 2006. Publi"hcd 

on the NRC Research Pres~ Web site at htt[J://cjl .. nrc.ca on 25 

May 2006, 

M.A. Cronin.l University of Alaska Fairbanks, School of 

~atural Resources and Agricultural Science~, Palmer Research 

Center. 533 Firewced Avenue, Palmer, AK 99645, USA. 

S.C. Amstrup. U.S. Geological Survey, Alaska Science Center, 

1011 East Tudor Road, Anchorage, AK 99503. tJSA. 

K.T. Scribner. Department,> of Fi<;heries and Wildlife and 

Zoology, Michigan State University, 13 .'Jatural Resources 

Building. East Lansing. MI -l8824-1222. GSA. 

ICorrc'\ponding author (e-mail: ffmad QvuaLedu). 

subpopuJmion. On an annual has is, more than 90% of the 

bear~ in the southern Beaufort Sei] sUhpopu!ation occur between the Colville River in Alaska and the M<lckenzie River 

in Canada. Similarly, more than 90% of the hears in the 

Chukchi Sea subpopulation occur west of Cape Lishurne. 

This high level of fidelity of polar bears to adjacent ranges 

in the Beaufort and Chukchi seas has led to their manage~ 

ment as separate s.ubpopulations. although Amstrup ct al. 

(2005) showed an area of overlap around Barro\v (Fig. 1). 

Previous analyses suggested there may be some genetic 

differentiation of hears from the southern Beaufort and 

Chukchi seas. An analysis of 16 microsatcllite loci of 30 

hears from each region showed a low level (FST 0.01) of 

differentiation of allele frequencies between the suhpopulations in the southern Beau fon and Chukchi seas (Paetkau et 

a1. 1999). An analysis of mitochondrial DNA (J1ltDNA) restriction fragment length polymorphisms from 10 bears cap~ 

tured in the Chukchi Sea and IS hears captured in the 

Beaufort Se<'l identified three haplotypes, with one prcdomi~ 

nating (70%-737r) in both ,ucas (Cronin et al. 1991). 

These genetic results were preliminary bccullse of small 

sample sizes compared with the numbers of hears in the 

Carl. J. Zoo!. R4: 6S5~660 (2006) do!: IO.! j ~9iZ06-()39 1:: 2(l06 NRC Canada 
402 


82737.214

656 Con. J. ZooL Vol. 811, 2006 

Fig. 1. ?vlap of the geographic arca of the :.ouihcm Beaufort Sea llnJ Chukchi Sea polar bear (UrSIIS marilimus) ,uhoopuiatioll' showing 

place names used in the lext Point Bamm, Alaska, is on the houndary hdwcl..'n the Chukchi and BCHufort The of 

overlap is shown (Amstrup aL 2005). 

[E5E~~W--~ 

we quantify the variations 

DNA from larger numbers or bears captured in the 

Chukchi and southern Beaufort seas. mtDNA is 

inherited and reflects only female~mediated gene flow, 

nuclear DNA (e.g., micro satellites) is inherited. 

and tlow 

8eaufort Sea 

variance of allele frequenWeir Cock~rham 19R4) \>vlth program 

information abo llseu the Bayesian dustcring: method of 

Materials and methods 

Blood and tissue were collected from bears CliP~ 

tured in the southern Sea, ea~t of Point Barrow, 

Alaska, and in the Chukchi Sea, \Ii~st of Point Barrmv, hct\veen 1985 and 1995 (Amstrup 20(0). Bears were assigned 

to the southern Beaufort or Chukchi 

Pritchard et itl. (2000), implemented in program STRUC 

TURE to asseSs structure, The STRUCTURE proto infer structure and 

based on post~rior prohathat bears 

for 

kov chain Monte Carlo iterations f-ollowing a burn-in 

rioJ of 100000 iterations. and repetitions of ew:h 

of K 

of mtDN1\ were as JescribcJ by Cronin ct a1. 

i~olation of DN A, restriction el1¥ 

ele,etrr'nh'oresi" Southern b!ot~ 

labeled mtDNA 

2(JO() NRC Cmmla 
403 


82737.215

Cronin et al. 

Table 1. Mlcrosatellite ullele frequencies, allelic richness (AR), observed heterozygosity (H,,), cxpcctcu 

heterozygosity (He). and FST in polur bear:, (UrSlI.\' 

maritimus) captured in the southern Beaufort Sea and 

Chukchi Sea of northern Alaska, USA Sample sin's 

were 116 bears for the Beaufort Sea samples and 127 

bears for the Chukchi Sea samples, 

Locus and allele Beaufort Sea Chukdll S\Cu 

GlOe 

101 0.017 0.043 

10J 0.737 0.732 

IDS 0.194 0.161 

107 O.OD 0.012 

109 0.013 0.035 

III 0.009 0 

113 0.01] 0.012 

liS 0.004 0.004 

ARfHiJHC 8.010.4510.42 6.9/0.44/0.44 

FSl --D.OOI 

GI.4 

188 0.012 

190 0.461 O.4G5 

192 0.10] 0.154 

194 0.138 0.146 

196 0.203 0.157 

198 0.047 0.028 

200 0.047 0.039 

ARlHJH, 6.0/0.7310.72 7.010.78/0.72 

Fs"] 0.000 

GlOM 

200 0.065 0.063 

206 0.026 0.008 

208 0.297 0.272 

210 0.289 0.378 

212 0.08G 0.114 

214 0.19 0.142 

216 0.043 0.02 

218 0.004 0.004 

ARll/ollIe 8.010.7310.78 7.9/0.7410.75 

FST 0.004 

GlOB 

142 0.164 0.22 

150 0.069 0.071 

152 0.039 0.051 

154 0.461 0.421 

156 0.159 0.154 

158 0.103 O.OS3 

162 0.004 

ARIH,'/H, 7.0/0.7210.72 6.010.7210.74 

FST 0000 

GlOP 

145 0.478 0.492 

147 0.022 0.055 

149 0.052 0.035 

lSI 0.O4.l (1.1)39 

657 

Table 1 (conclllded). 

Lncus and allele Beaufort Sea Chukchi Sea 

!53 0.207 0.244 

155 0.134 0.114 

157 0.034 il.012 

[59 0.009 0.004 

161 0.022 0.004 

AR/H(JH,> 9.010.73/0.71 8.410.69/0.68 

F"T -0.001 

GID 

180 0.034 0.008 

lS2 0.552 0.543 

184 0.246 0.276 

186 0.056 0.083 

188 0.047 0.OJ9 

190 0.065 0.043 

]92 0 O.OOS 

ARlHJH, 6.0/0.64/0.63 6.910.6110.62 

Fs! -0.002 

GIOX 

133 0.!25 0.118 

135 0.116 0.098 

137 n.121 oms 139 0 0.004 

141 0.138 0.169 

143 0.362 0.398 

145 0.056 0.051 

147 0.082 0.087 

ARIH,/H, 7.010.8210.80 7.9/0.79/0.78 

FSi -0.001 

O/OL 

145 0.772 0.768 

147 0.147 0.173 

149 0.034 0.051 

151 0.047 (WOS 

AH.IHjH~ 4.010.3910.38 4.0/0.35/0.38 

FSl -(l.Otll 

Over all 8 loci 

AR/llJlfc 6.9/0.6510.64 6.9/0.6410.64 

Fs! -0.0002 

pro he. We identified mtDNA haplotypes of polar bears from 

the Beaufort and Chukt:hi seas with 2 (HindIII and ClaI) 

of the 11 restriction enzymes previously used to assess 

mtDNA variation. Each enzyme results in a llltDNA fragment pattem, and (he patterns for the two enzymes compose 

a haplotype for each hear. The hap]otypes have a low Jevel 

of DNA sequence divergence (0.003-·0.006 suhstitutionsl 

nucleotide). A test for variance in haplotype frequency 

among subpopulations was conducted using a molecular 

analysis of variance (AMOYA) to calculate ¢ST using program Arlcquin ver.'.lon 2.0 (Schneider et al. 2000). We also 

compared the numbers of each haplotype in the Beaufort 

and Chukchi seas for males and females separately with 

X"2 contingency tests. 

CD 2006 NRC Canada 
404 


82737.216

658 

Table 2. Mitochondrial DNA (mtDNA) haplotype frequencies 

and allelic richness (AR) of polar bean captured in the southern Beaufort Sea and Chukchi Sea of northern Alaska. 

Beaufort Sea (N = 51) Chukchi Sea (tV;::: 47) 

mtDNA 

PBI 0.7647 0.7872 

PD2 0.2157 0.1489 

PBl 0.0196 O.06J8 

AR 1.0 3.0 

Results 

Genotypes were ahtained at eight microsatellite DNA loci 

for 116 bears captured in the southern Beaufort Sea and 127 

bears captured in the Chukchi Sea (Table 1). We observed 

4-9 alleles at the eight microsatellite loci, with an average 

of 6.9 alleles per locus in the southern Beaufort Sea and 7.0 

alleles per locus in the Chukchi Sea, Allelic richness was 6.9 

alleles per locus in both areas. Overall observed heterozygosity was 0,652 in the southern Beaufort samples and 0.639 in 

the Chukchi samples. and overall expected heterozygosity 

was 0.641 in the southern BeaufOJ1 samples and 0.637 in the 

Chukchi samples. Silmplcs from both areas were in HardyWeinberg equilibrium at each locus (P > 0.06) and at allloc! 

combined (P > 0.3334). Hardy-Weinberg equilibrium also 

was apparent at each locus (P > 0.1 193) and at all loci combined (P > 0,5115) when all of the Chukchi and Beaufort sea 

samples were pooled into one group. We found no significant associations of loci (P > 0.0646), suggesting that the 

microsutellite loci are not !inked (Paetkau ct at 1999). 

Microsatellite allele frequencies in the Cbukchi and so lIthem Beaufort sea samples were not significantly different. 

The eight-locus FST value was not significantly different 

from zero (FST = -0.0002) and the tests of heterogeneity 

showed that the allele frequencies did not differ significantly 

(P 0.0827) between the southern Beaufort and Chukchi 

samples over the eight loci combined (Table I). Results of 

the Bayesian analysis without a priori assignment of individual" to populations indicated that the number of genetic populations most consistent with the data was K = I. 

We obtained mtDNA restriction fragment patterns for the 

HindIIl and Clal restriction enzymes for 51 bears from the 

southern Beaufort Sea and 47 bears from the Chukchi Sea. 

Three mlDNA haplotypes were identified in polar bears 

from the Beaufort and Chukchi seas (Table 2), as in previous 

analyses (Cronin et al. 1991). Haplotype PBI predominated 

in both areas (76%-79%), haplotype PB2 was the second 

most abundant in both areas (15%-22%), and haplotype 

PH3 was the least common in both areas (2o/c-6%). mtD:\,A 

haplotype frequencies did not differ significantly between 

the southern Beaufort and Chukchi seas (~~( = -0.(06). Of 

the 51 bears from the southern Beaufort Sea for which 

mtDN A haplotypes were determined ~Hld the sex was 

known, 12 were males and 30 were females. The sex was not 

known for nine of the southern Beaufort Sea bears. Of the 47 

bears from the Chukchi ~ea for which mtDNA haplotypes 

were determined, 6 were males and 41 were females. mtDNA 

haplotype frequencies did not differ significantly between 

the Beaufort and Chukchi sellS for males (P = 0.6775) or 

femules (P = 0.2294). 

Can. J. Zool. Vol. 84, 2006 

Discussion 

The frequencies of microsatellite. nllc1es and mtD~A haplotypes of polar bears captured in the Chukchi Sea and sOllthern Beaufort Sea were not significantly different, and the 

microsatellite genotypes of the combined samples from the 

two ureas were consistent with expected Hardy-Weinberg 

proporlions (i.e., no WahJund effect). This suggests that 

there is no genetic ~lIbdivision, and bears from the Chukchi Sea and southern Beaufort Sea can be considered to 

be one interbreeding population. This result corroborates 

previolls studies, based upon smaller sample sizes, that 

suggested little genetic differentiation between bears from 

the southern Beaufort and Chukchi seas (Cronin et a1. 

1991; Scribner et <II. 1997; Paetkau et al. 1999), 

There are three geographic scales of interest regarding the 

popUlation gendic structure of polar bears: adjacent subpopulutions, subpopulations across the north polar ba~in, and 

subpopulations acros;; the worldwide distrihution of polar 

bears. At the scale of geographically adjacent subpopulations, our data indicate no genetic differentiation between 

bears from the sOllthern Beaufort and Chukchi seas. There 

is more differentiation of microsatellite allele frequencies 

across the larger geographic scale of the north polar basin. 

The avcrage pairwise FST (0.013) for 16 microsmelhte loci 

among polar bears from six Arctic locations across the north 

palm ba'iin (including the northern and southern Beauforl 

seas, the Chukchi Sea, the Siberian Arctic, Svalbard archipelago, and eastern Greenland; Puetkau et al. 1999) was higher 

than our FST (-0.0002) between the adjacent Beaufort and 

Chukchi SCQ sUbpopulations. On the worldwide geographic 

scale, there is considerable genetic differentiation among polar bears in four major geographic regions; the north polar 

basin; the Norwegiflll Bay area of northern Canada; the 

Canadian Arctic arcbipel;lgo; and areas in Canada and 

Greenland south of tbe Canadian Arctic archipelago, including Hudson Bay. Davis Strait, and the Foxe Basin (Pactkau 

et aI. 1999). Average pairwise FST between these regions 

w~\s higher (0.05(}) than the average pairwise FST within 

these regions (0.013), Thesc patterns of genetic differentiation are thought to be due primarily to differences in the 

seasonal distribution of sea-lee habiwt between the high 

Arctic land rna~ses (Paetk<lll et aL 1999). Across the north 

polar basin, including the Chukchi and Beauforl seas, sea 

ice is continuous and there are no ban'jers to movement of 

polar bcars. In contrast, differing patterns of distribution of 

ice and land masses may c;onstitute barriers to gene flow 

among tbe four regions thQt show a higher degree of genetic 

differentiation. 

Our data show that polar bears <tre not genetically differentiated between the Chukchi and Beaufort seas, despite 

movement data showing high range fidelity, The combined 

genetic and field data indicate the potential for discordance 

between direct (animal movements) and indirect (molecular 

genetic) measur~s of gene tlow (Slatkin 1987), Genetic homogeneity may result from relmively low level of continuous gene flow. episodic gene now, or recent common 

ancestry of cun'ently segregated subpoputations, The range 

overlap and movements of polar bears between the B~aufort 

and Chukchi seas suggests that there is probably enough 

continuous gene tlow to maintain genetic homogeneity over 

© 2006 NRC Cwnda 
405 


82737.217

Cronin et al. 

these areas. Lack of genetic differentiation as revealed by 

both maternally inherited mtDNA and bi~parentally inherited 

microsatellite DNA suggests that gene flow hetween the 

Chukchi and southern Beaufort seas is mediated by both 

sexes. This is consistent with radiotelemetry and tag-recov~ 

ery data showing that male and female polar bears have similar range sizes and movement patterns in these areas 

(Amstrup et al. 2000, 2001), 

The discrepancy between genetic and movement data may 

also be due to collection of movement data primarily from 

adult femaJe hears, which exhibit high fidelity to ranges. 

Therefore, the radiotelemetry data would not record dispersal and gene flow between subpopulations. However, some 

of the adults sampled for genetic analysis may have immi~ 

grated as suhadults prior to being captured and radio-collared. The genetic analysis would thus include adults born 

in the sub population and adults that immigrated into the 

subpopulation as sub~\dults, and thus rencct gene flow 

over time. Subadult bears might disperse more than adult 

females, as Taylor et al. (2001) found that suhadult polar 

bears of both sexes truvel more widely than adults, 

although they usually return to near their natal area by the 

time they reach sexual maturity. Additional research is 

needed to understand the movements of adult and subadult 

polar hears and the resulting gene flow in the Beaufort and 

Chukchi seas. 

In the context of management and conservation, our re~ 

suits suggest that problems associated with small, isolated 

sUhpopulations are not manifested in polar bears in the 

southern Beaufort Sea and Chukchi Sea. It appears that im~ 

migration and emigration between the southern Beaufort and 

Chukchi seas facilitate gene Dow and maintain genetic di~ 

versity. These data also suggest that reductions in numhers 

of bears in one area could be compensated by immigration 

from the adjacent area, and the bears in our study areas 

could be considered to be one population. However, factors 

other than genetics need to be considered in identifyi ng 

units for management (Cronin 1993, 2(06). For example 

adult females have high fidelity to ranges, and me critical 

from a management standpoint bCC<'Hlse of the importance 

of production and recruitment of new hears (Taylor et al. 

1987). Therefore, it is appropriate to manage polar bears in 

the Beaufort and Chukchi seas as separate suhpopulations 

despite the genetic homogeneity. Other factors that differ 

between the bear ranges in the southern Beaufort Sea and 

Chukchi Sea, such as seasonal movements of sea ice, also 

suggest that they should he treated as separate management 

units (Amstrup et al. 20(X). Considering the comhined ge~ 

netic and movement dara, it is approprime to consider the 

polar bears from the southern Beaufort Sc .. \ and Chukchi 

Sea as subpopulations of a eomhined southern Beaufort and 

Chukchi popUlation. 

Acknowledgements 

Principal funding for this study was provided by the U.S, 

Geological Survey (USGS), Alaska Science Center. Addi~ 

tiona! support was provided by BP Exploration Alaska, Inc., 

the Canadian \Vildlife Service, the Northwest Territories 

Wildlife Service. the Alaskan ~orth Slope Borough, the 10-

uvialuit Game Council of Canada, Co naco-Phillips, Inc., and 

the ExxonMobil Production Company Tnc, Capture protocols 

659 

were approved by the USGS Alaska Science Center animal 

care and welfare committee, and by the U.S. Marine Mam~ 

mals Commission. Thanks are extended to R. Fields who 

conducted much of the laboratory work; B. Pierson, K. Den~ 

ning, and S. Kavanaugh for help in the laboratory; K. Simac 

for help with manuscript formatting and literature searches; 

G. Durner for help making the figure: and D. Paetkau for 

useful insights on polar bear genetics. The efforts of G.W. 

Garner (deceased), who collected some of the samples used 

in thb study. are greatly appreciated. 

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© 2006 NRC Canada 
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Order Code RL33941 

CRS Report for Congress 

Polar Bears: Proposed Listing Under the 

Endangered Species Act 

~ 

~ ~. Congressional 

Rese~rch • ~Servlce 

Updated March 30, 2007 

Eugene H. Buck 

Specialist in Natural Resources Policy 

Resources, Science, and Industry Division 

Prepared for Members and 

Committees of Congress 
408 


82737.220

Polar Bears: Proposed Listing Under the 

Endangered Species Act 

Summary 

The proposed listing of polar bears as threatened under the Endangered Speeies 

Aet (ESA; 16 U.S.C. §§ 1531 et seq.) highlights the interscction of two significant 

issues currently before Congrcss - climate change and species protection. 

According to the ESA, this listing decision rests solely on an interprctation of thc 

best available scicntific understanding of the spccics and how it may be affccted by 

changes in its habitat. 

Polar bears depend on Arctic sea icc, which most scicntists acknowledge will 

be affected by climate warming causing, at minimum, an earlier annual or seasonal 

thaw and a later frecze of coastal sea ice. Globally, less than onc-third of the 19 

known or recognized polar bear populations are declining, morc than one-third arc 

increasing or stable, while the remaining third have insufficient data available to 

estimatc population trends and thcir status has not been assesscd. Two of these polar 

bcar populations occur within u.s. jurisdiction. 

Polar bears are affected by climate change, contaminants, and subsistencc and 

sport hunting. Environmental organizations have voiced public concern that polar 

bears were threatened by climatc change. Scientists havc confirmed that, in recent 

decades, the extent of Arctic sea ice has declined significantly as the result of climate 

warming: annual ice break-up in many arcas is occurring earlier and freeze-up later, 

Arctic sea ice is experiencing a continuing decline that cannot easily be reversed, and 

some models project that Arctic sea ice will disappear completcly by thc second half 

of this century. Three main groups of contaminants are implicated as potcntially 

threatening polar bears - pctrolcum hydrocarbons, persistent organic pollutants, and 

heavy mctals. The United States allows limited subsistence harvest of polar bears by 

Alaska Natives. In Canada, Nativc huntcrs arc permittcd to allocatc a limited portion 

ofthc subsistence harvest to sport hunters. Under 1994 amcndments to the MMPA, 

U.S. citizens may obtain permits to import sport-harvestcd polar bear trophies from 

Canada. 

Thc Fish and Wildlifc Scrvice (FWS) has proposed listing polar bears as a 

threatened species undcr ESA, acknowledging the increasing thrcats to their 

existencc. The FWS listing decision must bc bascd solely on the bcst available 

scientific and commcrcial information regarding five factors: habitat destruction, 

overutilization, disease or predation, inadequacy of othcr rcgulatory mechanisms, and 

other natural or manmade factors. 

Controversy exists ovcr how great a threat the changing climatc might be to 

polar bears and whether they might be ablc to adapt to these changing conditions. 

Some point out that polar bears today are not coping with changing climate alone, but 

also face a host of other human-induced factors - including shipping, oil and gas 

exploration, contaminants, and reduced prey popUlations - that compound the threat 

to their continued existcnce. There is also considerable uncertainty in estimates of 

polar bear popUlation numbers and trends as well as in our understanding of polar 

bear habitat. 
409 


82737.221

Contents 

Background ...................................................... 1 

Circumstances Affecting Polar Bears .................................. 4 

Climate Change ............................................... 4 

Contaminants ................................................. 6 

Subsistence and Sport Harvest .................................... 7 

Protection Efforts .................................................. 8 

Controversy ...................................................... 9 

List of Figures 

Figure I. Distribution of Polar Bear Populations Throughout the 

Circumpolar Basin ............................................. 2 
410 


82737.222

Polar Bears: Proposed Listing Under the 

Endangered Species Act 

The proposed listing of polar bears as threatened under the Endangered Species 

Act (ESA; 16 V.S.c. §§ 1531 et seq.) highlights the intersection of two significant 

issues currently before Congress - climate change and species protection. This 

listing decision rests solely on an interpretation of the best available scientific 

understanding of the species and how it may be affected by changing habitat. 

Background 

The polar bear, Ursus maritimus, is the largest terrestrial carnivore and a top 

predator, inhabiting cireumpolar Arctic regions wherever sea ice is present for a 

substantial part of the year. Nineteen known or identified populations of polar bears 

have an estimated total abundance of20,000 to 25,000 animals (Figure 1). Two of 

these populations occur within V.S. jurisdiction - the Southern Beaufort Sea 

population (shared about equally with Canada) is estimated at 1,526 animals, 1 while 

the Chukchi/Bering Seas population (shared with Russia) is estimated at about 2,000 

animals.2 Polar bear populations are in decline in Western Hudson Bay and may be 

starting to decline in the Southern Beaufort Sea. Simulations suggest that polar bear 

populations are also declining in Baffin Bay, Kane Basin, and Norwegian Bay. 

Globally, less than one-third of the 19 populations are declining, and more than onethird arc increasing or stable, while the remaining third have insufficient data 

available to estimate population trends and their status has not been assessed.] The 

status of the polar bear in the Central Arctic Basin, the largest population, is 

unknown. Large carnivorous mammals arc generally considered to be most at risk 

of population declines and extinctions,4 and the minimum viable total population of 

polar bears has been estimated at 4,961 individuals 5 

! E. V. Regehr, S. C. Amstrup, and T. Stirling, Polar Bear Population Status in the Southern 

Beaufort Sea, U.S. Geological Survey, Open File Report 1337 (2006). 

2 This abundance estimate, by the Polar Bear Specialist Group (see footnote 3). has low 

confidence, with no estimate of precision or bias. 

J Polar Bear Specialist Group, Proceedings o/rhe i4,h Working Meeting o/the JUCNISSC 

Polar Bear Specialist Group, Occasional Paper of the IUCN Species Survival Commission 

No. 32 (2006), p. 34-35, available at [http://pbsg.npolar.no/docs/PBSGl4proc.pdl]. 

4 M. Cardillo ct aI., "Multiple Causes of High Extinction Risk in Large Mammal Species," 

Science, v. 309, no. 5738 (Aug. 19,2005): 1239-1241. 

5 D. H. Reed et aI., "Estimates of Minimum Viable Population Sizes for Vertebrates and 

Factors Influencing Those Estimates," Biological Conservation, v. 113, no. I (September 

2003): 23-34. 
411 


82737.223

CRS-2 

Figure 1. Distribution of Polar Bear Populations 

Throughout the Circumpolar Basin 

Source: Polar Bear Specialist Group, J 4'" Working Meeting olthe 

IUCNISSC Polar Bear Specialist GroIlP, p. 33. Southern Beaufort Sea, NB 

Northern Beaufort Sea, VM = Viscount Melville, NW = Norwegian Bay, LS Lancaster 

Sound, MC McClintock Channel, GB Gulf of Boothia, FB Foxe Basin, WH 

Western Hudson Bay, SH = SOllthern Hudson Bay, KB Kane Basin, BB Baffin Bay, 

OS Davis Strait. 

The primary prey of polar bears is the ringed seal a polar bear may stalk a 

seal by waiting quietly for it to emcrge from an opening in the ice that seals make to 

breathe or climb out of the watcr to rcst. Ringed scals havc a circumpolar 

distribution and are associated with ice ycar-round, Much of ringed seal habitat 

(cspecially in offshorc drifting sea icc) has not been surveyed, leading to much 

uncertainty regarding population size and status. Current estimates of the global 

population numbers for ringed seal range from more than 2 million to as many as 7 

million animals. Other prey include bearded and harp seals, juvenile walrus, beluga 

whales, narwhal, fish, and seabirds and their eggs. Over most of their range, polar 

bears remain on the sea ice year-round or spend at most only short periods on land. 

In October and November, male polar bears head out onto sea ice where they spcnd 

the winter. 
412 


82737.224

CRS-3 

Polar bears have one of the lowest reproductive rates of any mammal, with 

mature females reproducing once every three years. Pregnant females either seek 

sites on the sea icc ("pelagic bears") or on mainland areas ("nearshore bears") to dig 

large dens in snow where they give birth and spend the winter." Females do not 

require mainland sites for denning, but some individuals seem to prefer them. Both 

pelagic and nearshore individuals are known in all subpopulations studied.' 

Currently, polar bears are protected and managed under domestic law and 

several international agreements. Because the primary habitat of the polar bear is sea 

ice and this species is evolutionarily adapted to life at sea, it is managed as a marine 

mammaL In the United States, polar bears are protected under the Marine Mammal 

Protection Act (MMPA; 16 U.S.c. §§1361 et seq.), with the Fish and Wildlife 

Service (FWS) in the Department of the Interior as the federal management agency. 

The Alaska Nanuuq Commission, a Native organization representing villages in 

northern and northwestern Alaska, has a co-management agreement with the FWS 

to provide input on matters related to the conservation and sustainable use of polar 

bears.s 

Internationally, the multilateral 1973 Agreement on the Conservation of Polar 

Bears9 and the 2000 bilateral Agreement Between the Government of the United 

States of America and the Government of the Russian Federation on the 

Conservation and Management of the Alaska-Chukotka Polar Bear Population lO 

provide a basis for cooperation on polar bear management. In addition, Alaska and 

Canada exercise joint cross-border management through the Inuvialuit-Inupiat Polar 

Bear Management Agreement for the Southern Beaufort Sea. II The International 

Union for the Conservation of Nature (ruCN) classifies the polar bear as vulnerable 

on the IUCN Red List of Threatened Species. The ruCN elassifieation of vulnerable 

represents a judgment that the species is facing a high risk of extinction in the wild. 12 

In addition, polar bears are listed on Appendix II of the Convention on 

International Trade in Endangered Species of Fauna and Flora (CITES). Appendix 

II contains species not necessarily threatened with extinction but requiring controlled 

6 U.S. Dept. of the Interior, Fish and Wildlife Service, "Polar Bear Fact Sheet," available at 

[http://www.fws.gov/home/feature/2006/polarbeaLpdf], and "Polar Bear Questions and 

Answers," available at [http://www.fws.govihome/feature/2006/PolarbearFAQ.pdf]. 

7 Mette Mauritzen, Andrew E. Derocher, and Oystein Wiig, "Space-Use Strategies of 

Female Polar Bears in a Dynamic Sea Ice Habitat:' Canadian Journal (~rZoo/()gy, v. 79 

(Sept. 2001): 1704-1713. 

S See [http://www.nanuuq.info/index.html). 

9 Parties to this agreement are Canada, Denmark, Norway, the Russian Federation, and the 

United States. See [http://sedac.ciesin.org/entriitextsipoIaLbears.1973.html). 

10 See [http://alaska. fws.govimediaipbsigning/agreement.html). 

II See [http://pubs.aina.ucalgary.caiarcticiArctic55-4-362.pdf]. 

12 This assessment is based on a suspected population decline of more than 30% within three 

generations (45 years) due to decline in area of occupancy, extent of occurrence, and habitat 

quality. 
413 


82737.225

CRS-4 

trade to prevent population declines, as well as other species whose body parts are 

diffieult to distinguish by visual inspection (the so-called "look-alike" problem, in 

this case in controlling trade in bear gall bladders).13 ESA implements CITES 

provisions domestically. As such, ESA affords protection to endangered species and 

wildlife of global coneell1. To complement CITES, ESA specifically prohibits 

interstate and foreign commerce in ESA-listed species. FWS agents and inspectors 

work to control any illegal trade and intell1ational movement of CITES- and ESAlisted species, since some species found in other countries may be brought into the 

United States by activities that could threaten their long-term survival. ESA is 

applicable to activities within U.S. jurisdiction, as well as activities by U.S. citizens 

anywhere, including the high seas. 

Circumstances Affecting Polar Bears 

Climate Change 14 

Climate change is widely believed to be one of the most significant 

contemporary threats to biodiversity worldwide. 's A May 2002 report by the World 

Wildlife Fund raised public concell1 that polar bears were threatened by climate 

change. '6 Scientists have confirmed that, in recent decades, the extent of Arctic sea 

ice has declined significantly as the result of climate warming: annual ice break-up 

in many areas is occurring earlier and freeze-up later, Arctic sea ice is experiencing 

a continuing decline that it is thought may not easily be reversed, 17 and some models 

project that Arctic sea ice could disappear completely by the second half of this 

century. IS 

Distribution pattell1s of some polar bear populations have changed in recent 

years. Greater numbers of bears are being found onshore ncar the Bering Sea, 10 and 

13 For additional background on CITES, see CRS Report RL3275J, The Convention on 

International Trade in EndangeredSpecies of Wild Fauna and Flora (CITES): Background 

and Issues, by Pervaze A. Sheikh and M. Lynne Com. 

14 For background on climate change, see CRS Report RL33849, Climate Change: Science 

and Policy Implications, by Jane Leggett. 

!5 C. D. Thomas et aI., "Extinction Risk from Climate Change," Nature, v. 427, no. 6970 

(Jan. 8,2004): 145-148; Arctic Climate Impact Assessment, Impacts of a Warming Arctic: 

Arctic Climate Impact Assessment (Cambridge University Press, 2005), 144 p. 

16 Stefan Norris, Lynn Rosentrater, and Pal Martin Eid, Polar Bears at Risk (World Wildlife 

Fund, May 2002), available at [http://www.ngo.grida.no/wwfap/polarbears/risk/PolarBears 

AtRisk.pdf]. 

17 R. W. Lindsay and 1. Zhang, "The Thinning of the Arctic Sea Ice, 1988-2003: Have We 

Passed a Tipping Point?" Journal of Climate, v. 18, no. 22 (2005), pp. 4879-4894. 

IS Intergovernmental Panel on Climate Change, Climate Change 2007: The Physical Science 

Basis, Summary for Policymakers (Geneva, Switzerland: Fehruary 2007), 21 pp. 

19 S. L. Schliebe, T. Evans, S. Miller, and J. Wilder, "Fall Distribution of Polar Bears along 

(continued ... ) 
414 


82737.226

CRS-5 

in some parts of Canada,2° with Inuit hunters reporting more bears present on land 

during summer and fall. 2J There may be several reasons for the observed changes, 

including changes in sea ice; those who conduct population censuses of polar bears 

will need to be cautious in interpreting whether apparent population variations are 

indicative of different habitat use (e.g., greater numbers of bears onshore) or actual 

changes in population abundance. 

The projected loss of sea ice could affect survival and reproduction of polar 

bears by: 

• shortening the season during which ice is available to serve as a 

platfom1 for hunting seals/2 

• increasing the distance between the ice edge and land, thereby 

making it more difficult for nearshore female bears that prefer to den 

on land to reach preferred denning areas; 

• reducing the availability of sea ice dens for gestating pelagic female 

bears; 

• requiring nearshore bears to travel through fragmented sea ice and 

open water, which uses more energy than walking across stable ice 

fonnations;2J 

• reducing the availability and accessibility of ice-dependent prey, 

such as ringed seals, to nearshore populations;24 and 

19 ( ... continued) 

Northern Alaska Coastal Areas and Relationship to Pack Ice Position," in Collection oj 

SCientific Papers from the 41h international Conference 0/ Marine Mammals oj the 

Holarctic, V. M. Belkovich, ed. (St. Petersburg, Russia: 2006), p. 559. 

20 E. K. Parks, et al., "Seasonal and Annual Movement Patterns of Polar Bears on the Sea 

Ice of Hudson Bay," Canadian Journal o/Zoology, v. 84, no. 9 (September 2006): 1281-

1294. 

21 Unpublished reports in 2005 by M. Dowsley and M. Taylor, as cited in the FWS polar 

bear status assessment report (see footnote 4 I ). 

22 For evelY week earlier the sea ice breaks up, bears come ashore 10 kilograms lighter in 

weight, on average. See Ian Stirling and A.E. Derocher, "Possible Impacts of Climatic 

Warming on Polar Bears," Arctic, v. 46 (1993): 240-245. 

23 Loss of sea ice forces polar bears to cross large expanses of water and increases risk of 

drowning. In 2004, scientists documented polar bears swilmning as far as 60 miles offshore 

and observed 4 drowned bears. See C. Monnett and J.S. Gleason, "Observation of Mortality 

Associated with Extended Open-Water Swimming by Polar Bears in the Alaskan Beaufort 

Sea," Polar Biology, v. 29, no. 8 (July 2006): 681-687. 

24 1. Stirling and C. L. Parkinson, "Possible Effects of Climate Warming on Selected 

Populations of Polar Bears (Ursus maritimus) in the Canadian Arctic," Arctic, v. 59, no. 3 

(September 2006): 261-275; S. H. Ferguson,!. Stirling, and P. McLoughlin, "Climate 

Change and Ringed Seal (Phoca hispida) Recruitment in Western Hudson Bay," Marine 

Mammal Science, v. 21, no. I (Janaury 2005): 121-135. 
415 


82737.227

CRS-6 

• requiring nearshore bears to spend more time on land, thereby 

inereasing the potential for adverse human-polar bear interaetions.2s 

In addition to changing sea ice conditions, climate change might affect the integrity 

of polar bear den sites, as rain can destroy ice dens, exposing young polar bears to the 

elements prematurely.26 

Although some scientists predict the extinction of polar bears under potential 

climate change scenarios, not all sea-ice changes would harm polar bears. For 

example, reduced sea ice thickness and coverage in far northern regions is likely to 

improve polar bear habitat, by increasing the availability and accessibility of icedependent prey, such as ringed seals.27 Others remind biologists that climate-related 

changes to a species' distribution docs not neccssarily result in changes in 

abundance. 2x 

Contaminants 

Three main groups of contaminants are implicated as potentially threatening 

polar bears - petroleum hydrocarbons, persistent organic pollutants, and heavy 

metals. Polar bears are particularly vulnerable to oil spills, because oil damagcs polar 

bear fur (decreasing the bears' ability to themloregulate) and because of oil ingestion 

(poisoning) via grooming and/or eating contaminated prey.29 Although elevated 

concentrations of some persistent organic pollutants have becn discovered in polar 

bears, it has been difficult to determine what biological effects these chemicals might 

have on polar bears; weakened immune systems and reduced reproductive success 

are among the concerns.JO Some persistent organic pollutants are endocrine 

disruptors and are thought to cause pseudo-hermaphrodism and aberrant genital 

morphology in polar bears.JI Mercury is a particular concern because of its toxicity 

at low concentration, and its magnification and accumulation through the food web. 

However, polar bears appear able to demethylate (i.c., alter the chemical form and 

biological reactivity of) mercury and accumulate somewhat elevated levels of 

25 Marine Mammal Commission. Annual Report to Congress, 2005 (Bethesda, MD: July IS, 

2006), p. 52. 

26 Stefan Norris, Lynn Rosentratcr, and Pal Martin Eid, Polar Bears a/ Risk (World Wildlife 

Fund, May 2002). 

27 A. E. Derocher, N. J. Lunn, and 1. Stirling, "Polar Bears in a Warming Climate," 

Integrative and Comparative Biology, v. 44, no. 2 (ApriI2004): 163-176. 

2' C. J. Krebs and D. Berteaux, "Problems and Pitfalls in Relating Climate Variability to 

Population Dynamics," Climate Research, v. 32 (2006): 143-149. 

29 D. 1. St. Aubin, "Physiologic and Toxic Effects on Polar Bears," in Sea Mammals and Oil: 

Confronting the Risks, J. R. Geraci and D. J. St. Aubin, cds. (New York, NY: Academic 

Press, Inc., 1990), p. 235-239; N. A. Oritsland, et aI., Effect o{Crude Oil on Polar Bears, 

Environmental Studies No. 24, Northern Affairs Program, Northern Environmental 

Protection Branch, Jndian and Northern Affairs, Canada (1981),268 pp. 

JO J. U. Skarre et aI., "Ecological Risk Assessment of Persistent Organic Pollutants in the 

Arctic," Toxicology, v. 181-182 (2002): 193-197. 

31 C. M. Fossi and L. Marsili, "Effects of Endocrine Disruptors in Aquatic Matmnals," Pure 

and Applied Chemislly, v. 75, nos. 11-12 (Nov.-Dec. 2003): 2235-2247. 
416 


82737.228

CRS-7 

mercury without harn1.]2 Climate change may alter contaminant pathways through 

increased precipitation, increasing the potential threat to polar bears.]] 

Subsistence and Sport Harvest 

The United States allows limited subsistence harvest of polar bears by Alaska 

Natives. Subsistence harvest of depleted, threatened, and endangered marine 

mammals can be managed in different ways. Due to concerns for depleted beluga 

whales in Cook Inlet, AK, subsistence harvest by Alaska Natives has been severely 

restricted (0 to 2 animals annually) since 1999.34 On the other hand, a substantial 

Alaska Native subsistence harvest of endangered bowhead whales continues, with 75 

whales permitted to be struck in 2006. 35 Tn the year from July 1,2004, through June 

30,2005, Alaska Natives harvested 27 polar bears from the Southern Beaufort Sea 

population and 33 polar bears from the Chukchi/Bering Seas population. Tn addition, 

there is particular concern for the ChukchilBering Seas population due to anecdotal 

evidence that unregulated harvest by Russian Natives on the Chukotka Peninsula may 

be reaching unsustainable levels.J6 

In Canada, Native hunters are permitted to allocate a limited portion of the 

subsistence harvest to sport hunters. 37 Under 1994 amendments to the MMP A, U. S. 

citizens may obtain permits to import sport-harvested polar bear trophies from 

Canada, taken under scientifically sound quotas ensuring the maintenance of the 

affected population at a sustainable level. 3s Tn 2006, FWS issued 72 permits for 

importing polar bear trophies from Canada, with more than half taken from the 

Lancaster Sound population. 

Habitat damage from climate change may interact with subsistence and sport 

harvest to increase polar bear mortality. For example, large adult male bears, more 

likely to be targeted by hunters, may also be more at risk from the effect of climate 

change on prey availability since larger bears require greater amounts of food. Tn 

addition, male bears also disperse greater distances than females and thus could be 

more affected by the necessity to swim increasing distances. 

32 Arctic Monitoring and Assessment Programme, AMAP Assessment 2002: Persistent 

Organic Pollutants in the Arctic (Oslo, Norway: 2005), p. 123. 

33 R. W. Macdonald, T. Harner, and J. Fyfe, "Recent Climate Change in the Arctic and Its 

Impact on Contaminant Pathways and Interpretation of Temporal Trend Data: Review 

Article," Science a/The Total Environment, v. 342, no. 1-3 (Apr. 1,2005): 5-86. 

34 71 Fed. Reg. 15697-15698 (Mar. 29, 2006). 

35 71 Fed. Reg. 7539 (Feb. 13,2006). 

36 Marine Mammal Conunission.Annual Report to Congress, 2005 (Bethesda, MD: July 15, 

2006), p. 50-51. 

37 M. M. R. Freeman and G. W. Wenzel, "The Nature and Significance of Polar Bear 

Conservation Hunting in the Canadian Arctic," Arctic, v. 59, no. I (2006): 21-30. 

JB P.L. 103-238, §§4, 5; 16 U.S.C. §1371(a)(I); 16 USc. §1374(c)(5). 
417 


82737.229

CRS-8 

Protection Efforts 

On February 17,2005, FWS received a petition from the Center for Biological 

Diversity requesting that FWS list the polar bear as threatened under ESA throughout 

its range and that it designate critical habitat for this species. 39 Thc Natural 

Resources Defense Council and Greenpeacc, Inc., joined as petitioners on July 5, 

2005. On December 15,2005, the pctitioncrs filcd a complaint, challenging FWS's 

failure to issue a 90-day finding on the petition. On February 7, 2006, FWS 

announced a finding that the petition presented substantial scientific information 

indicating that listing the polar bear might be warranted, and subsequently announced 

the initiation of a formal status review:o 

In a settlement agreement, approved on July 5, 2006, FWS agreed to submit a 

12-month finding on the petition by December 27,2006. On January 9, 2007, FWS 

announced its 12-month finding on the petition - concluding that, after a review of 

scientific and commercial information, listing the polar bear as a threatened species 

under ESA was warranted - and formally proposed such listing.41 This proposed 

rule does not designate critical habitat for the polar bear. A 90-day period (through 

April 9, 2007) was announced to receive data and comments, with requests for a 

public hearing accepted for 45 days (through February 23, 2007). A decision on 

whether to list polar bears is due from FWS in January 2008. 

The Secretary of the Interior must decide whether to list polar bears under ESA 

based only on the best available scientific and commercial (i.e., trade) information,42 

after an extensive series of procedural steps to ensure public participation and the 

collection of relevant information. The listing decision considers information 

relating to five factors: habitat destruction, overutilization, disease or predation, 

inadequacy of other regulatory mechanisms, and other natural or manmade factors. 43 

At this point in the ESA process, the Secrctary may not consider the economic effects 

that listing may have. The listing detemlination is the only place in ESA where 

39 A species may be designated as either endangered or threatened, depending on the severity 

of its decline and threats to its continued survival. The prohibitions and penalties of ESA 

apply primarily to those species listed as endangered. Under § 4(d) ofESA, the Secretary 

may promulgate special regulations to address the plight of species listed as threatened. 

Protections and recovery measures for a particular threatened species can be tailored to 

particular situations. 50 C.F.R. §] 7.31 also affords threatened species for which a special 

rule has not been promulgated the same protections as endangered species. For additional 

background on ESA as well as regulatory procedures under this act, see CRS Report 

RL31654, The Endangered 5]7ecies Act: A Primer, by M. Lynne Com, Eugene H. Buck, and 

Pamela Baldwin. 

40 71 Fed. Reg. 6745 (Feb. 9, 2006). Information on the status of the polar bear was solicited 

from the public in this notice and again in 71 Fed. Reg. 28653 (May 17,2006). 

" 72 Fed. Reg. 1064-1099 (Jan. 9, 2007). The polar bear status assessment document is 

available at [http://alaska.fws.gov/fisheries/mmm/polarbear/pdf/Polar Bear %20Status 

Assessment.pdf]. - - -

" 16 U.S.c. § 1533(b)(1 )(A). 

43 16 U.S.c. §1533(a)(I). 
418 


82737.230

CRS-9 

economic considcrations are expressly forbidden; such considerations may enter in 

other stages, including critical habitat designation. 

Economic factors cannot be taken into account at this stage because Congress 

directed that ESA listing bc fundamentally a scientific question: is the continued 

existencc of the species threatened or endangered? If polar bears wcre listed under 

ESA, federal agencies would be required to ensure that anything the federal 

government authorized, funded, or carried out that is likely to affect polar bears or 

their habitat would not jeopardize the survival of thcse bears or destroy or adversely 

modify their habitat. 

The Committee on the Status of Endangered Wildlife in Canada (COSEWIC) 

is also reviewing the status of the polar bear in Canada. In addition, many would cite 

the multilateral 1973 Agreement on the Conservation of Polar Bears as a significant 

and substantive protection effort that provides international oversight of various 

national research and management programs. 44 

Controversy 

Supporters of increased protection for polar bears argue that polar bears are the 

most iconic Arctic specics, representing the Arctic as lions represent Africa. They 

further assert that it would be irrcsponsible to let the polar bear become extinct as a 

result of human action, and would be a terrible blow to the psyche of humankind. 

However, some critics suggest that the current proposal to list polar bears as 

threatened is premature, with this species bcing used as a "poster child" for the evils 

of climate change by thc popular prcss in recognition of polar bears' charismatic 

appeal; somc believe the less-glamorous walrus could be facing similar or greater 

immediate risk. 

Some scientists also point out that, since polar bears have survived at least two 

major warming periods over the last 10,000 years, including the intense warming 

event that ended the Last Glacial Maximum about 8,000 to 9,000 years ago (when 

temperatures were believed to have been much warmer than now), polar bears and 

other Arctic mammals could be capable of adjusting, adapting, and coping with the 

current climatic change. At the end of the last Ice Age, the Northcrn Hcmisphere 

entered an extended period of rapid warming, with temperatures in Arctic regions 

eventually reaching levels several degrees warmer than today. At that time, the sea 

ice above North America is known to have retreated substantially, allowing Arctic 

species such as bowhead whales and walrus to move northward into areas of the 

Canadian Arctic that thcy cannot reach today. The Mid-Holocene Warm Period 

peaked about 11,000-9,000 years ago near Alaska and about 8,000-5,000 years ago 

ncar Greenland and Northern Europe. In both areas, temperatures rose rapidly 10-15 

degrees Ccntigrade to a point significantly warmer than present (about 2.5 degrees 

Centigrade warn1er; but Jess than the temperatures projected by the 

44 P. Prestrud and 1. Stirling, "The International Polar Bear Agreement and the Current 

Status of Polar Bear Conservation," Aquatic Mammals, v. 20, no. 3 (J 994): 113-124. 
419 


82737.231

CRS-IO 

Intergovernmental Panel on Climate Change for 2100), and about 5-10 degrees 

Centigrade of that warming took place within 30 years or less 45 

Another significant but shorter warm period occurred about 1,000 years ago, 

when Arctic temperatures were slightly warmer than today. This warming also 

triggered sea ice reductions in Arctic regions and was accompanied by significant 

reductions in Greenland glaciers, creating so much arable land that Viking settlers 

established farms on the west coast of Greenland that were occupied for about 400 

years. 46 

There is no evidence to suggest that ice in the Arctic Basin disappeared entirely 

during either ofthese warm periods or that any icc-dependent species became extinct. 

Polar bears and their primary prey existed before thc last Icc Age and significant 

populations of them remain today. The tight association of polar bears and their prey 

species with moving sea icc gives them a flexibility that land-based carnivores do not 

have. 

Others counter that polar bears today are not coping with changing climate 

alone, but also face a host of other human-induced factors - including shipping, oil 

and gas exploration, contaminants, and reduced prey populations that compound 

the threat to their continued existence.47 In addition, the opportunity for a 

catastrophic disease event is greater in populations subject to mUltiple stressors. 

Furthermore, they emphasize that current climate wam1ing may be occurring at an 

accelerated rate, due to human influence, compared to past periods of climate 

warming, and species may be less capable of adapting to these more rapid changes. 

Others suggest that there is considerable ullceltainty in the estimates of polar 

bear population numbers and trends as well as in our understanding of polar bear 

habitat. Much of what we know about the polar bear habitat is confined to regions 

close to shore that have been studied during long summer days, with little known 

about what happens on drifting sea icc far from shore, especially in winter when there 

is little or no daylight. These critics also urge caution on interpreting studies of sea 

ice change that are based primarily on surveys of nearshore regions, rather than the 

drifting sea ice environment in the central Arctic Basin, where icc may be thickest. 

Recent studies conclude there is significantly more variability in ice thickness 

45 D. S. Kaufman etal., "Holocene Thermal Maximum in the Western Arctic (0-180 Degrees 

W," Quaternary Science Revie,vs, v. 23, nos. 18-19 (October 2004): 2059-2060; Arthur S. 

Dyke, et aI., "The Late Wisconsinan and Holocene Record of Walrus (Odobenus rosmarlls) 

from North America: A Review with New Data from Arctic and Atlantic Canada," Arctic, 

v. 52, no. 2 (June 1999): 160-181; Arthur S. Dyke and James M. Savelle, "Holocene History 

of the Bering Sea Bowhead Whale (Ba1aena myslicetlls) in its Beaufort Sea Summer 

Grounds off Southwestern Victoria Island, Western Canadian Arctic," QlIaternQlY 

Research, v. 55 (2001): 371-379. 

46 Willie Soon and Sallie Baliunas, "Proxy Climatic and Environmental Changes of the Past 

1000 Years," Cfimate Research, v. 23 (Jan. 31, 2003): 89-110. 

47 A. 5hi, A. M. Bell, and J. L. Kerby, "Two Stressors are Far Deadlier Than One," Trends 

in Ecology and Evolution, v. 19 (2004): 274-276. 
420 


82737.232

CRS-II 

bctwccn years and regions than is predicted by climate models, which means that icc 

thickness can increasc or decrease rapidly as well as diffcr among regions. 4R 

Under ESA, the Secrctary is requircd to take into account forcign polar bear 

conservation programs, including conservation hunting programs involving non-local 

(including U.S.) huntcrs. However, an ESA listing as "threatened" triggers an 

automatic listing as "depleted" under the MMPA, a listing that would prevent U.S. 

citizens from importing polar bear products into the United States. Such an import 

ban, effectively stopping U.S. participation in conservation hunting programs, is 

likely to seriously compromise successful Canadian community-based conscrvation 

programs.49 

4~ Seymour Laxon, Neil Peacock, and Doug Smith, "H igh Interannual Variability of Sea Ice 

Thickness in the Arctic Region," Nature, v. 425 (Oct. 30, 2003): 947-950. 

49 M. M. R. Freeman and G. W. Wenzel, "The NatLlre and Significance of Polar Bear 

Conservation Hunting in the Canadian Arctic," Arctic, v. 59, no. I (2006): 21-30. 
421 


82737.233

available at www.sciencedirect.com 

jou rnal h omepa ge; http://www,elsevier.comflocate/ecocom 

Viewpoint 

Polar bears of western Hudson Bay and climate change: 

Are warming spring air temperatures the "ultimate" 

survival control factor? 

M.G. Dyck a,., W. Soon b ... , R.K. Baydack 0, D.R. Legates d, S. Baliunas b, 

T.r. Ball e, L.G. Hancock! 

a Environmental Techno!ogy Program, Nunavut Arctic College, Box 600, Iqaluit, Nunavut XOA OBO, Canada 

bHarvard-Smithsonian Center for AstrophysicS, Cambridge, MA 02138, USA 

<;' Clayton IL Riddell Faculty oj Environment, Earth, and Resources, University of Manitoba, Winnipeg, Manitoba R3T 2N2, Canada 

dCenter for Climatic Research, University Of Delaware, Newark, DelawarE' 19116, USA 

"Climate and Environment Consulront, Victoria, British Columbia, Canada 

f MSN H-5-S03, 1818 H Street, NW, Washington, DC 20433, USA 

ARTICLE INFO 

Article history 

Received 1 March 2007 

Accepted 2 March 2007 

Published on line 16 April 2007 

Keywords 

Polar bear 

Climate change 

Hudson Bay 

Extinction 

doi:l0, 1016!j.ecocom.2007 .03.002 

ABSTRACT 

Long-term warming of late spring (April--June) air temperatures has been proposed by 

Stirling et a1. [Stirling, L, Lunn, N,J., lacozza, ]., 1999, Long-term trends in the population 

ecology of polar bears in western Hudson Bay in relation to climatic change. Arctic 52, 294-

306) as the "ultimate" factor causing earlier sea-ice break-up around western Hudson Bay 

(WH) that has, in tum, led to the poorer physical and reproductive characteristics of polar 

bears occupying this region. Derocher et a1. IDerocher, A.E" Lunn, N.]., Stirling, L, 2004, Polar 

be-ars in a warming climate, fntegr. Comp. Biol. 44, 163-176J expanded the discussion to the 

whole circumpolar Arctic and conduded that polar bears wiUunlikely survive as a species 

should the computer-predicted scenarios for total disappearance of sea-ice in the Arctic 

come true, We found that spring air temperatures ilTOund the Hudson Bay basin for the past 

70 years (1932~2002) show no signiflcant warming trend and are more likely idtmtifled with 

the large-amplitude, natural climatic variability that is characteristic of the Arctic, Any role 

of extem81 forcing by anthropogenic greenhouse gas.es remains dlfflcu]t to identify. We 

argue, therefore, that the extrapolation of polar bp.at disappearance is high1y premature 

Climate models ure simply not skilful for the projection of regional sea-ice changes in 

Hudson Bay or the whole Arctic. Alternative factors, :mch increased human-bear interaction, must be taken into account in a more realistic study and explanation of the 

population ecology of W1-I polar bears, Both scientific papers and public discussion that 

continue to fail to recogni2',e the inherent complexity in the adaptive interaction of polar 

bears with both human and nature will not likely offer ony usefu1, science-based, preservation and management strategies for the species, 

\: 2007 Elsevier n.v, All rights reserved 

of Environment, Government of Nunavllt, Box 209, 19lootik XOA OLD, Canada 

Dyck), wsoon@tf8.harvard.edu (W. Soon). 
422 


82737.234

74 ECOI.OG!CfI,L COMPLlXI'lY 4 (200n 73-84 

1. Introduction 

Polar bears (Ursus maritimus) are charismatic megafauna that 

symbolize the Arctic. They play an important cultural, 

spiritual, mystical, and traditional role in the lives of Canadian 

Inuit through hunting and subsequent sharing of meat and 

fur. Additionally, {nuit~guided sport hunts provide jrnportant 

revenue for the economically challenged communities (Lee 

and Taylor, 1994). The latest research findings suggest, 

however, that this multi-purpose natural resource faces 

threats from climatic change and environmental stress 

(Stirling and Derocher, 1993; Stirling et aI., 1999; World Wide 

Fund for Nature, 2002; Derocher et at, 2004) or from simply 

unsustainable harvests by human hunters (see recent discus" 

sion in Taylor et at, 2005). 

Unfortunately, polar bears and their shrinking ice habitat 

are commonly used rhetoric to argue for the possible severity 

of climate change and global warming to the general public 

(d., Washington Post, 2005). The polar bears that are most 

often cited are a specific population that inhabits the south" 

western Hudson Bay coast-l of 14 polar bear popuiations 

found in Canada (Derocher et at, 1998; Taylor et al., 2001). The 

area they occupy encompasses almost the southernmost 

extent of the species {only the southern Hudson Bay polar bear 

population reaches farther south; Derocher et aL, 199B}. 

Population stresses have been observed, which has led to 

the proposition that an earlier break-up of Hudson Bayice (and 

an associated increase in spring air temperatures) is the cause 

of decreases in reproduction, sub adult survival, and body 

mass of some of these bears {Stirling and Derocher, 1993; 

Stirling et a1., 1999}. A long"term warming trend of spring 

atmospheric temperatures was proposed, though not shown 

directly,l to be "the ultimate factor" (Stirling et a1., 1999, p. 

294). As a result, it is commonly believed that climatic changes 

(or "global warming") are the predominant factors leading to 

adverse conditions for the polar bear populations, although 

other factors have been acknowledged (e.g., density-dependent population responses; Derocher and Stirling, 1992), 

We argue that there are several related stress factors that can 

explain the observed patterns in polar bear population ecology. 

Global warming may indeed have an effect on the polar bears of 

western Hudson Bay (WH) but it must be assessed in a more 

renlistic framework that considers all the like1y stress factors 

and their cumulative impacts. In such a context, it is difficult to 

isolate one factor of predominant severity and, consequently, it 

is simply not prudent to overstate the certainty of any single 

factor. As emphasized in Li (2004) and Loehle (2004), a full 

scientific understanding of an issue as complex as the 

population ecology of polar bears must necessarily reqUires 

the combined assessment of both the natural and social 

systems rooted in the problem rather than consideration of 

either component in isolation (Le., warmer spring air temperatures and related sea-ice conditions in WH). 

In the next two sections, we examine some of the potential 

nondimatic causes of decreased reproduction, offspringsurvi" 

val, and body masses, including repeated bear-human inter" 

actions, food availability and competition. We then consider 

1 Stirling et a1. (1999) relied on the mean air temperature results 

of Skinner et a1. (1998). 

climatic factors by examiningavailabJe surface air temperature 

records and ice dynamics in the Hudson Bay basin. Finally we 

synthesize these findings to critically evaluate the forecasts of 

polar bear extinction in relation to model projected scenarios of 

global warming by Derocher et a1. (2004). 

2. Human-polar bear interactions in western 

Hudson Bay 

Western Hudson Bay polar bears have a long history of 

interactions and confrontations with humans. Stirling et a1. 

(1977) discusses interactions between humans and WH polar 

bears from Churchill at dump sites, in town, and adj<lcent 

town areas. Over the years, the three main sources of bearhuman interactions for the WH bears are activities related to 

(a) scientific research, (b) tourism, and (c) the Polar Bear Alert 

Program. 

Research activities for the WH area began in 1956, and 

continue today as a long-term ecological monitoring project in 

which over 80% of the bear population is marked (Stirlinget a1., 

1977; Lunn et a1., 2002), The majority of this field work has been 

carried out by the Canadian Wildlife Service (CWS), although 

universities also conduct research on polar bears in the area. 

Many bears are captured, marked, and eventually recaptured, 

sometimes within the same year, over a number of years (e.g., 

Calvert et a1., 1991a,b, 1995a,b, 1998). Forexample, from 1977 to 

1995, an estimated total of 2772 bears were captured (Derocher 

and Stirling, 1995, their Tables 2 and 3; Lunn et a1., 1997a, their 

Tables 2 and 3), with a minimum (i.e" since not all captures are 

dearly reported in publications and conflicting information 

exists) of about 1100 recaptures {recapture rates of between 52 

and 90%; mean number of bears captured/year between 1977 

and 1995 is about 145 bears; see summary total of columns 2 

and 3 in Table 1}. If one considers that the WH population 

estimate then was between 700 and 1200 bears (Amstrup and 

Wiig, 1991; Wiig et aL, 1995), and about 15-30% of the 

population was captured and recaptured due to high ftdelity 

to locations along the coast (Derocher and Stirling, 1990a,b), it 

is very likely that many bears were/are exposed to capture 

activities on a repeated basis. 

An assumption most frequently made by researchers is that 

their work (Le., capturing and handling wildlife repeatedly) has 

no significant effect on fitness, behaviour or survival of the 

wildlife species in question (Seber, 1973; Lehner, 1979). Longterm trends of handling polar bears were suggested by Ramsay 

and Stirling (1986) and induded the possible effects on females 

with cubs, Although their study did not find any statistically 

significant results, the trends they presented indicated that 

females may suffer from handling by being displaced from 

feeding sites, possibly resulting in lowered body mass. Note that 

female polar bear body mass is positively related to cub survival 

(Derocher and Stirling, 1996, 1998a). If females lose body mass 

due to handling, cubs will be adversely affected in their survival 

rates. Also, most polar bear capture work occurs either on 

family gmups in spring as they emerge from their dens, or 

during the ice-free period while bears are distributed along the 

southwestern shore of Hudson Bay-times when the bears are 

either stressed due to lactation (Arnould, 1990) or undergo a 

fasting period while living off their stored fat reserves {Watts 
423 


82737.235

Table 1 - Captures of polar bears for research (males and 

females). for the Polar Bear Alert Program (PBAP'), and 

total polar bear captures per year from 1977 to 1995 

Year Males3 Femalesu PBAP" Total captures! 

year 

1977 53 34 32 119 

1978 29 26 16 71 

1979 15 10 27 

1980 20 29 18 67 

1981 34 36 27 95 

19$2 68 42 32 

1983 95 95 92 282 

1984 96 63 18 177 

1985 9S 59 76 230 

1986 S, 53 26 163 

1987 115 149 30 294 

1988 140 152 35 327 

1989 168 163 51 382 

1990 107 92 64 263 

1991 86 68 18 172 

1992 57 74 5, 185 

1993 42 54 58 154 

19'94 63 64 79 206 

1995 86 58 33 177 

Total 1451 132"1 785 

Mean 76 69 41 187 

and Hansen, 1987). While the handling effect study of Ramsay 

and Stirling (1986) covered only 1967-1984, we suggest an 

additional analysis of capture-recapture data for handling 

effects that extends their time period to the present. 

Almost concurrently with research activities at WH, some 

of the bears in the WH population ar.e exposed to tourists and 

tourism activities during the fall. SiDce about 1980, polar bear 

viewing from large customized vehicles has been practiced 

near the town of ChurchilL Pol<J.r bears leave the ice during 

June/July and slowly migrate north to the shores of Hudson 

Bay (approximately 35 km east of Churchill) where they 

congregate and wait the early freezE'-up of the Bay, usually 

during November. Tour companies transport visitors into the 

congregation area (approximate coordinates are: 58 4SiN to 

58 '48'N, and 93' 38'W to 93 'SOW) during October/November to 

view the bears (Dyc:k, 2001.), Although the viewing period is 

short, usually between 1 October and IS November, it is very 

intense, with about 6000 tourists and 15 large tundra vehicles 

per day in the area (Dyck and Baydack, 2006), Bailing, 

harassment and chasing of bears have been documented to 

occur (Watts and Ratson, 1989; Herrero and Herrero, 1997), The 

(Calvertet aI., 1998). In the first baseline study conducted in the 

area to address tundra vehicle behaviour and vigilance (i.e" a 

motor act that corresponds to a head lift interrupting the 

ongoing activity) of resting polar bears, Dyck and Baydack 

(2004) found significant increases in Vigilance behaviour of 

resting male polar bears in the presence of' vehicles. The 

75 

authors speculated that increased vigilance could lead to 

increased heart rates and metabolic activity, subsequently 

adding other factors that possibly contribute to the negative 

energy balance of bears while on land. 

Another bear-human interaction occurs in the form of the 

Polar Bear Alert Program (PEAP) at Churchill. The Manitoba 

provincial management agency initiated the program in 1969 

to protect local residents from bears, and vice versa (Kearney, 

1989). The area around the town is patrolled, and bears that 

enter certain zones will either be deterred, captured, handled, 

or destroyed, From its inception up to 2000, an average of 48 

bears per year (<1 total of 1547 bears) have been handled 

(Kearney, 1989; Calvert etal., 1991b, 1995b; Lunn Et aI" 1998; for 

a detailed PBAP descriptiOD, see Kearney, 1989). Handling 

procedures are similar to those during research activities, and 

effects can be assumed to be similar. 

Considering CWS-relat€'d research activities and the PEAP 

activities bt;'tween 1977 and 1995, a total of 3558 bears (not 

including university-research handled bears) have been 

handled (last column In Table 1). This is about three times 

greater than the actual estimated WH popUlation of 1100 

(Derocher and Stirling, 1992), indicating that all bears are, on 

average, s'llbje('t to repeated handling. Moreover, these 

activities occur when bears are either fasting or leaving their 

dens and are already energetically stressed. It is plausible that 

these repeated bear-human interactions have advt;'rsely 

stressed the bears over the past 30 years. 

3. Food availability and competition 

Between 1978 and 1990, the WH palm bear population was 

estimated to be around 1100 bears (Derocher and Stirling, 1992). 

Derocher and Stirling (1995) estimated the mean size of the 

popUlation between 1978 ::md 1992 to be around 1000 bears, Up 

to 1997, the population did not change signiflcantly, and was 

estimated to be around 1200 bears (Lunn et a1., 1997a; fig. 6 in 

Stirling ct at, 1999). When pUblished yearly population 

estimates from Derocher and Stirling (1995) and Lunn et a1. 

(1997a) are examined, several tendencies are apparent. first, the 

DerQcher and Stirling (1995) data for 1977-1992 show an 

increasing trend (F "" 4.16, P '" 0.06, ~ "" 0.23), o.lthough that 

trend is not statistically Significant. Second, the Lunn et al 

(1997a) data from 1984 to 1995 indicate a stabl€' popUlation 

(F"'" 0.71, P '" 0.42, r2 "" 0.07). When both data sets are combined 

(i.e., the Derocher and Stirling (1995) data from 1977 to 1992 and 

the l,unn et aL {1997a) data for 1993-1995), a significant increase 

in the population size is implied (F", 6.40, P "" 0.02, r2 "" 0.27). 

Most recently, however, it was notE'd that the population since 

1995 has been declining to "less than 950 in 2004" (IUCN/Polar 

Bear Specialist Group, 2005). We clarify that the published 

combining Churchill and Cape 

bear popUlation of 1233 with a 95% confidence interva1 that 

ranges from 823 to 1643 bears, so the actuJ.l confidence in the 

"decline" ofthe WH polar bear population in 2004, relative to the 

1995 values, is difficult to confirm. 

been imprinted in the observed records of polar bears at WHo 1t 
424 


82737.236

76 

is important, however, to recognize the great difficulties in 

demonstrating density dependence in population studies (e.g., 

Ray and Hastings, 1996; Mayor and SchaefE.'r, 2005), among 

which is the sensitivity of the phenomenon on spatial scale 

covered by the population sampling techniques (e.g., Taylor 

et aL, 2001). We concur with Derocher and Stirling (1995) and 

Stirling et a1. (2004) that the WH population was at least stable 

during the 1984-1995 period (and likely up to 1997; see Stirling 

et aL, 1999, their Fig. 6). Prior to that the WH population was 

hunted heavily, which led to hunting restrictions (Stirling et aL, 

1977; Derocher and Stirling, 1995). After the population 

recovered, and then increased, bear body mass, reproductive 

parameters, cub survival, and growth declined (Derocher and 

Stirling, 1992, 1998b). Derocher and Stirling (1992, 1995, 1998b) 

considered whether these responses reflect density~dependent 

population control mechanisms. They discarded them either 

because no accurate popUlation estimates for WH existed, or no 

change in population size was detected. Typically, density-

(a) Winter (OJF) Temperature of Churchill, Manitoba 6·20 ~----------~---~-~~~~~ 

~'22~"." 1 

" r:·Z4 

~.26~ 

t_Z8 t 

~ -30 L[--:-;-;-;:---'---:o-;o;----=;;-----c=-' 

Year 

Sprin (MAM Tem erature of Churchill, Manitoba 

1960 2000 Year 

dependent responses, similar to those exhibited by WH polar 

bears, are detected in increasing popUlations (Eberhardt and 

Siniff, 1977; Fowler, 1990). By contrast, however, individuals ofa 

population near carrying capacity (given that the WHpopulation 

remained relatively stable for so long) can also exhibit traits that 

were observed for this polar bear population, namely poorer 

physical condition, lower survivorship, and lower rates of 

reproduction {Kie et aI., 1980, 2003; Stewart et a1., 2005}, It is 

possible that the WH population has been stable for so long 

because carrying capacity has been reached, and intraspecific 

competition increased with increasing polar bear density, 

resulting in the documented responses. 

It is important to note that the southern half of Hudson Bayis 

shared between polar bear popUlations of WH and southern 

Hudson Bay (SH) (Derocher et a1., 1998). Polar bears of SH have 

exhibited better body condition as compared to their WH 

counterparts (Stirling et aI., 1999, 2004) but prolonged ice 

conditions in that area seem not to be the explanation because 

(b) Late Spring (AMJ) Temperature of Churchill. Manitoba 

1940 1960 1980 2000 

Fa!! (SON) Temperature of Churchill, Manitoba 

1940 19PO 1980 2000 

Year 

Fig. 1-(a) Climatological winter (the average of December. January and February). spring (the average of March, April and May), 

summer (the average of June, July and August) and fall (the average of September, October and November) surface air 

temperatures of Churchill, Manitoba, which are assumed to be representative of temperatures around the western Hudson 

Bay from 1932 through 2002. (b) Late spring (defined as the average of April, May and June, following the discussion in Stirling 

et al., 1999; top panel) and fall (bottom panel) temperatures with statistically insignificant (Le., with p > 0.05j again chosen in 

order to fonow discussion in Stirling et at, 1999) trend lines (dotted) fitted through the 1932-2002 interval. The dashed trend 

line fitted through 1981-1999 verifies the late spring warming episode noted by Stirling et at (1999) for that limited period. 
425 


82737.237

recent updated analysis by Gagnon and Gough (2005a) 

suggested tendencies toward earlier ice break~up (hence 

shorter overall duration of sea-ice cover) in James Bay and 

along the southern shore of Hudson Bay. Population estimates, 

which have been conducted almost entirely via aerial surveys, 

indicate an increasing trend for this SH population from 1963 to 

1996 (i.e., see Table 2 and Fig. 4c of Stirling et aL, 2004). Although 

both populations are recognized as independent(e.g., Derocher 

and Stirling, 1990a,b; Kolenosky et a1., 1992; Taylor et al., 2001), 

possible overlap can occur on the sea-ice. If population density 

for SH has been increasing, whereas food supply has been 

insufficient due to increased competition, then some SH bears 

may have expanded their hunting forays, leading to competition for food with WH bears. Yet there has not been a drastic 

decline in the WH population detected. One reason may be that 

the bears have learned to hunt seals during the ice-free period 

along the shores in tidal flats. This phenomenon has been 

obseIVed for several years at Churchill in the polar bear viewing 

area (Dyck, personal observations). 

Data on the bear food supply is needed to draw more clear 

conclusions about the interplay between population densities 

and worsening physical attributes of polar bears. The main 

prey of polar bears are ringed (Phoca hispida) and bearded seals 

(Erignathus barbatus) (Stirling and Archibald, 1977; Smith, 

1980), but seal population data aTe too limited at present to 

resolve this issue (Lunn et a1., 1997b). 

4. Air temperature and climate variability 

around Hudson Bay 

Fig. 1a shows the surface air temperature records 2 of nearby 

Churchill, Manitoba (assumed here to be representative of 

WH) from 1932 to 2002 for the four climatological seasons. The 

large interannual variability of the seasonal temperatures 

suggests that establishing a meaningful long-term trend in 

any of these relatively short records would be difficult and that 

a trend determination, especially over short periods, will be 

highly sensitive to the time inteIVal considered (e.g., Fielke 

et aL, 2002; Cohen and Barlow, 2005). fig. lb attests that no 

statistically significant warming trend (dotted trend lines 

fi.tted over the full records in Fig. 1b) can be confirmed for 

either the late spring (defined here as the average of April, May 

and June, following discussion in Stirling et aL, 1999) or fall 

seasons when the full record from 1932 through 2002 is 

considered. Thus, the hypothesis that a warming trend is the 

principal causative agent for the supposed earlier spring melt 

and later fall freeze of the sea-ice around WH cannot be 

confirmed. Further, that the temperature trend is not 

statistically different from zero indicates it is not obviously 

forced by anthropogenic greenhouse gases as commonly 

2 Our data source is the quality-controlled version of records 

from the NASA Goddard Institute for Space Studies web site: 

http://www ,giss. nasa. gov I data/upd a tef gistem p!statlon . da tal. 

Churchill and Frobisher Bay data shown here are from the 

7~station- and 5·station~merged records, respectively. Missing 

Churchill temperatures from NASA GISS database for 1993-1996 

were replaced by data points from ChurchHl Airport given by 

CUMVIS Global Summary of the dCly available from the u.s. 

National Climatic Data Center. 

77 

assumed and extrapolated to suggest implications for polar 

bear ecology in future scenarios of climate change. Such 

extrapolations remain premature at best. 

An apparent tendency towards late spring warming can be 

derived by examining the period from 1981 to 1999, illustrated 

by the dashed trend curve in Fig. lb. Clearly, the choice of end 

points is very influential on the results. The trend fails to 

persist when data through 2002 are included and we make no 

inferences about any concurrent ecological responses. Thus, 

although our independent results for temperature change and 

variability over the WH do not contradict Stirling et a1. (1999) 

for the limited period from 1981 to 1999, the longer record 

reveals a fuller range of air temperature variability that argues 

against assuming a persistent warming trend. 

Gough et a1. (2004) recently identified snow depth as the 

primary governing parameter for the interannual variability of 

winter sea-ice thickness in Hudson Bay because of its direct 

insulating effect on ice surfaces. By contrast, the concurrent 

winter or previous summer air temperatures yield only weak 

statistical correlations with ice thickness. Detailed highresolution modelling efforts by Saucier et a1. (2004) that 

considers tides, river runoff and daily meteorological forcing, 

found tidal mixing to be critically important for ice-ocean 

circulation within, and hence the regional climate of, the 

Hudson Bay basin. 

We further examined records of winter and spring air 

temperatures at Frobisher Bay (now called IqaIuit, Nunavut) by 

the Hudson Strait and the respective winter and spring Arctic 

Oscillation (AO) circulation indices3 (Fig. 2) to better 

3 Arctic Oscillation (AO) is a natural, planetary-scale pattern or 

mode of atmospheric circulation variability that is characterized 

by a seaSllW of the air mass anomaly between the Arctic basin and 

the midlatitude zonal ring centered at about 45 'N. A high (positive) 

AO value is defmed as lower"than~normal atmospheric pressure 

over the Arctic and colder stratosphere, which are associated with 

strong subpolar westerlies. A low (negative) AO value represents 

higher-than-normal Arctic atmospheric pressure, less cold 

polar stratosphere and weak subpolar westerlies. The AO index 

is 3vailable from http://horizon.atmos.colostate.edu/ao/Data/ 

lndeX.html. Because of the relatively larger variability and stronger coupling of stratospheric and tropospheric air circulation 

during the cold season, AD is mainly a winteT phenomenon However,AD has been demonstrated to be relevant to temperature and 

precipitation fields in other seasons as well {Gong and Ho, 2003; 

Kryjov, 2002; Overland et nt., 2002}. please see Wal1<lce (2000), 

Baldwin (2001) and Thompson and Wallace (2001) for complete 

tutorials. Although there have been several suggestions that the 

post-1969 or post-1989 AD index remained in an 'unusual', highly 

positive phase as a result of forcing by anthropogenic carbon 

dioxide, the current generation of climate models and modelling 

efforts are not sufficiently mature to confirm or refute such a 

proposal (Soon etal., 2001; Soon and Baliunas, 2003). Furthermore, 

it has been pointed out that AO index has been mostly neutral or 

negative in the most recent 9 years (1996-2004) despite the notable 

high-positive AD phase during the 1989--1995 interval earlier (e.g., 

Cohen and Barlow, 2005; Soon, 2005). Cohen and Barlow (2005) 

argued that even though the AD may contribute to re.gional warming in the Arctic and even the Northern Hemisphere for a particular pe.riod, but th€ pattern and magnitude of temperature signal 

induced by AD are physically quite different from the large-scale 

features produced by global wanning trend in the last 30 years, 

thus disallowing any direct attribution of AD to radiative forcing 

by anthropogenic greenhouse gases. 
426 


82737.238

78 

1940 19S0 196() 1970 1900 1990 2000 

~ ~ C 

0 

" ~ 

;; ] ~ U ~ [ E 

~ if> 

~ 0 « if> 

Year 

Fig. 2 - Statistically significant (i.e., p <.<: 0.001) correlation 

between temperature (solid) at Frobisher Bay (now as 

lqaluit), Nunavut and the Arctic oscillation (AD) index 

(dotted) for winter (as averages of January, February and 

March; top panel) and spring (as averages of March, April 

and MaYi bottom panel). The axis for AD indices has a 

reversed scale such that high positive AD values mean 

colder temperatures at Frobisher Bay. 52% and 20% of the 

variance of the winter and spring temperatures for the 

1943-2002 interval are explained by the respective AD 

indices. Both the standard Pearson's r and non-parametric 

Kendall's r were computed, and statistical significance of 

the results are e5tablished based on both statistical 

measures. 

characterize the regional pattern of air temperature variability. 

Fig. 2 shows two important points. First, note the rather 

strong cooling trend (at a rate of about 0.4 C per decade 

since the 1950s) for the winter and spring temperatures of 

Frobisher Bay. Regional differences in the pattern of the 

temperature variability, especially on the multidecadal 

timescale, are large. This pattern of large temperature 

gradients between the southwestern and northeastern 

corners of the Hudson Bay oceanic basin has been well 

noted by Ball (1995), Catchpole (1995) and Skinner et al. 

(1998)-these authors also provided a comprehensive dis~ 

cussion on climate regimes around WH, including a broad, 

historical perspective on the range of natural variabilities. 

Among other things this indicates that a hypothesis of late 

spring warming negatively affecting the WH polar bear 

population ecology cannot be universally extended to other 

locations. 

The second point of Fig. 2 is that the air temperature and 

climatic conditions around the Hudson Strait and Hudson Bay 

areas have a close association with the AO circulation index. 

The correlations shown in Fig. 2 are statistically significant, 

with AO variability explaining up to 20-50% of the interannual 

temperature variances at Frobisher Bay. 

To examine the link between the AO index and Frobisher 

Bay air temperatures, both series were regressed on a matrix 

of monthly dummy variables to remove fixed seasonal 

effects. The residuals of these regressions (denoted AOr 

and FR1) were then tested in a vector autoregression to 

determine leading patterns of Granger causality (see Hamilton, 1994, Chapterl1). While AO r shows a significant Grangercausal pattern on FRr no such pattern exists in the other 

direction. This means the current value of the AO index 

significantly improves forecasts of monthly Frobisher Bay air 

temperatures, but the current air temperature does not 

improve forecasts of the AO. Finally, FRr was regressed on its 

first two lags, AOr and the first three lags of AOr to remove 

serial correlation in the mean. After a trend term that was 

insignificant was removed, the r2 from this regression was 

0.39 (with an adj-r2 of 0.38). A Wald test of the joint AOr terms 

yielded a chi-square (d.f. '" 4) statistic of 235.6. A p-value on 

the hypothesis of no influence of the current and lagged AO 

anomalies on the current monthly temperature anomaly is 

less than 0,00001. 

The AO circulation index appears to be physically 

relevant for two reasons. First, from an examination of 

the statistics of sea level pressure and sea-ice motion from 

the 1979 to 1998 data collected by the International Arctic 

Buoy Programme, Rigor et a1. (2002) confirmed that the AO 

circulation pattern can explain at least part of the thinning 

sea-ice trend observed over the Arctic Ocean. Polyakov and 

Johnson (2000) and Polyakov et a1. (2003a) further emphasized the importance of the relative phasing of the decadal 

and multidecadal (i.e., 50-80 years) oscillatory modes of 

Arctic atmospheric circulation variability in explaining the 

recent Arctic sea-ice areal extent and thickness trends. 

Rigor et a1. (2002) clarified that instead of assuming that the 

warming trend in surface air t<:>mperature caused the sea-ice 

to thin, it is the AO-induced circulation pattern that 

produces the tendencies for sea-ice to thin and sea-ice 

area to retreat (see further discussion on regional sea-ice 

trends and mechanisms in ZhRng et al., 2000; Kimura and 

Wakatsuchi, 2001; Poly aka v et aL, 2003b; S6derkvist and 

Bjork, 2004). In turn, it was the changes in sea-ice that 

caused the air temperature to warm because of an 

increasing heat flux from the interface with the ice~free 

ocean. Beyond atmospheric AO, Shimada et a1. (2006) 

recently documented and highlighted the key role played 

by the inflows of warm Paciflc summer water through the 

Bering Straits in causing the large sea-ice areal reduction in 

the Arcti, that began in the late 1990s. Thus, such a complex 

physical picture connecting oceanic and atmospheric 

processes with sea-ice variability is dramatically different 

from Stirling et a1. (1999)'s suggestion in which warm spring 

air temperature is considered to be the ultimate cause for 
427 


82737.239

rCOLOGiCAL COMPU-X:TY <1- (:007) 73 -84 79 

the earlier spring sea-ice break-up4 and poorer conditions of 

polar bears. 

The second reason to discuss the AQ indE'x is related to a 

recent fmding that climatic change effects associated with the 

AO index aTe propagated through two trophic levels within a 

high-arctic ecosystem (Aanes et aI., 2002). From the statistical 

analyses of the 1987-1998 growth series of Cassiope tetragona 

(Lapland Cassiope) and the 1978-1998 abundance series of an 

introduced Svalbard reindeer (Rangifer tarandus platyThynchus) 

population near Broggerhalvoya, on the NW coast of Svalbard, 

Aanes et at (2002) found that high positive values of the AO 

index are associated with decreased plant growth and 

reindeer population growth rate. Thus, the reindeer population at Svalbard, through the mediation of the climate 

modulated effects on plant growth, is plausibly connected 

to climate through a bottom~up sequence. But Aanes et a1. 

(2002) noted that the bottom-up scenario may be densitydependent in that at higher reindeer densities, a reverse topdown sequence of tTOphic interaction is becoming more 

important in which grazing has a dominating influence on the 

forage species and plant communities. The AO index is thus 

promising as a useful climatic variable for further exarnina~ 

tion of the dynamic of trophic interactions under various 

settings of the arctic ecosystem. 

It must also be asked whether natural climate oscillations 

as those described above - reducing sea-ice cover and 

changing the freeze-and-thaw cycles that affect the food 

sources of polar bears at higher latitudes are really as 

detrimental to biodiversity as suggested. These changes may 

create more polynyas, which are productive oases in the ice 

(Stirling, 1997), or increase marine productivity oVC'Tall (Fortier 

4 It should be noted that the tendency or trend for earlier spring 

sea ice break-up in WH from 1979 to 1998 pointed out by Stirling 

et a1. (1999) is not statistically significant (with p "" 0.07) under the 

authors' own criterion and admission. Houser and Gough (2003) 

was also unable to demonstrate statistical significance in the 

trend of timing of the spring sea ice retreat at the Hudson Strait 

over the full interval from 1971 through 1999; although they 

suggest that an earlier spring ice retreat or break-up seems clear 

for the data starting 1990. We argue that this nt::>w tendency may be 

related to the sustained positive phase for the AO circulation 

index since 1989 till 1995 or so (see footnote 3) and it remains 

to be confirmed if that the AD index might remain in that trend of 

high positive values or the AO variability might undergoes a shift 

toward the low (negative) AO-value phase as in the 1950$ and 

19605. Updated results shown by Gagnon and Gough (2005a) on 

trends in the timing of ice break-up, although now able to claim 

"statistical significance" under rigorous statistical testing for 

James Bay and western half of Hudson Bay {though it should be 

noted that in several records, threshold p-value ofless than 0.10, 

instead of the threshold of 0.05 adopted for example by Stirling 

et at (1999), is now used to claim signiflcance], point out that 

detecting surface air temperature trends is still sensitive to the 

time interval of data records (see e,g., Cohen and Barlow, 

Another real concern is the definition of spring ice break-up 

autumn freeze·up where we are not sure if the criterion of50% ice 

cover for the onset of melting and freezing seasons has been 

optimized for the understanding of polar bear population ecology 

(see Rigor et at, 2000 for other suggestions and threshold criteria), 

In general we wish to discourage the over reliance on statistical 

confidence that bypasses clear physical arguments or hypotheses 

(see e.g" Wunsch, 1999). 

et aL, 1996; Rysgaard et aI" 1999; Hansen et aI., 2003) primarily 

because of the modulation of the food web of the lower trophic 

levels by freshwater·Umiting and light·limiting processes. 

Bears do not feed year-round, but do feed during late spring 

when seal pups are abundant. More fat deposits may be 

accumulated during this time, and a "true hibernation state" 

like black (U. americanus) and brown bears (U. arctos) could 

become an evolutionary strategy for the remainder of the year 

for polar bears. This scenario could be very likely because polar 

bears evolved fTOm brown bears (Kurten, 1964). Alternatively, 

a supplementary feeding strategy could evolve where berries 

and vegetation are consumed in higher frequencies during the 

ice-free period, as has been observed for bears of Hudson Bay 

(Russell, 1975; Derocher et aI., 1993). 

s. Extrapolating polar bear populations 

In light of these considerations we do not consider it a sound 

methodology to assumE that local air temperature trends 

adequately explain WH population conditions and that 

ExtrapolatingWH results generates predictions for polar bears 

and their habitat over the circumpolar Arctic (e.g., Stirling and 

Derocher, 1993; World Wide Fund for Nature 2002; Derocher 

et aL, 2004). We take particular exception to the suggestion by 

Derocher et at (2004, p. 163) that polar bears will not likely 

survive "as a species"s if several computer· generated scenarios of air temperature-driven disappearance of sea-ice "by the 

middle of the present century" come true. The conjecture 

seems errant for two reasons, First, most climate models 

predict a complete disappearance of sea-ice over the central 

Arctic for only the late summer (I.e., September) while the 

whole Hudson Bay is always ice+free during this time 

regardless of the forcing by anthropogenic greenhouse gases 

(see for example Figs. 8 and 9 in Johannessen et a1., 2004). 

Second, in the cited climate model projections, sea-ice at the 

Hudson Bay for the late winter or early spring(Le., March) was 

never predicted to completely disappear by the end of this 

century, even under scenarios that posit greenhouse gas 

accumulations at rates considerably faster than currently or 

historical1y observed. In a recent mu1ti-model study of climate 

projection in the Hudson Bay region, Gagnon and Gough 

(200Sb, p. 291) concluded that "Hudson Bay is expected to 

remain completely ice covered in those five models by the end 

of this century for at least part of the year." 

It should also be noted that Gough et aL (2004) had earlier 

reported that the observed thickening of sea-ice cover during 

the last few decades on the western coast of Hudson Bay was 

5 However, it should not be too surprising to find somewhat 

contradictory or more restrictive statements by these same 

authors from what we faithfully quoted about polar bears facing 

extinction in the Arctic by Deroch!;.'r et a1. (2004), For example, Dr. 

Ian Stirling was quoted in WWF (2002) to have said that ''For every 

week earlier that break-up occurs in the Hudson Bay, bears will 

come ashore roughly 10 kg lighter and thus in poorer condition 

With reproductive success tied closely to body condition, jf temperatures continue to rise in response to increases in greenhouse 

gas emissions and the sea ice melts for longer periods, polar bear 

numbers will be reduced in the southern portions of their range 

and may even become loci.d!y [emphasis added] extinct." (p, 5). 
428 


82737.240

80 ECOlOGICAL COMPLEXITY 4- (2uo7173~84 

in direct contradiction to the thinning ice scenario that is 

posited by warming due to an enhanced CO2 atmosphere. 

Under these COr warming scenarios, the models predicted not 

only an earlier spring break-up of sea-ice but also later faU 

freeze-up at Hudson Bay (Gagnon and Gough, 2005b). Available 

observations from 1971 to 2003, by contrast, do not show any 

tendency for a later freeze-up of ice especially at WH or 

southwestern Hudson Bay (Stirling et a1., 1999; Gagnon and 

Gough, 2005a). Further to the north, Melling (2002, pp. 2-18), in 

his study of sea-ice around the northern Canadian Arctic 

archipelago, concluded that "[iJnterannual fluctuations in 

late-summer ice coverage obscure any evidence of trend [in 

the Sverdrup Basin]. A decadal cycle contributes variability to 

the times series of both total and multiyear ice concentrations. 

Because the reputedly extreme conditions of 1998 are similar 

to occurrences in 1962 and 1971, there is little basis on which to 

view them as evidence for anthropogenic change." 

We therefore conclude that it is highly premature to argue 

for the extinction of polar bear across the circumpolar Arctic 

within this century as incorrectly suggested in Derocher et a1. 

(2004). 

Finally, we wish to encourage a renewed archaeological 

search for information related to polar bear population 

ecology from 1760 to 1820, when historical evidence (based 

on early thermometers at trading posts of Churchill Factory 

and York Factory) suggests that the climatic regimes at WH 

had shifted from temperate to arctic conditions (see Ball, 

1995; Catchpole, 1995). Ball (1983, 1986) documented large 

changes and abrupt shifts in both floral (i.e., treeline 

boundary between the boreal forest and the tundra) and 

fauna (i.e., migration of wild geese) ecosystem responses of 

the Hudson Bay region that occurred naturally as a 

consequence of the varying mean locations of the Arctic 

Front (Bryson, 1966). Ball (1995) suggested that the three 

consecutive decades from 1770 to 1800 at York Factory 

consisted of very wet and variable winter conditions 

oscillating between extremes of heavy snow versus almost 

snow-free conditions, which made the thriving of wildlife 

populations difficult. Heavy late winter rains, for example, 

have been proposed as a cause of the collapse of maternity 

dens, suffocating the occupants (Stirling <Jnd Derocher, 

1993). Excessive snowfall was noted to alter oxygen flux 

through the snow layer of maternity dens nnd could 

negatively impacting survival rates of young altricial cubs 

that need to be nursed for 3 months before they are able to 

leave the den with their mothers (Derocher et al., 2004). The 

records compiled by Ball and Kingsley (1984) suggested an 

interval with a relatively warm late spring (April-May~June) 

at York Factory of about 2.9 ·C for 1779, 1780, and 1782 (no 

data for 1781) when monthly air temperature readings were 

available from the Hudson Bay's Company and Royal 

Society's archives. These data may be applied to assess 

the resiliency of polar bears under adverse climate conditions. The latest research by Scott and Stirling (2002) have 

successfully dated, through sophisticated timing and fingerprinting techniques of dendro-sciences, polar bear maternity 

dens and dens activities inland from the coast of WH, south 

of Churchill and north of York Factory, since at least 1795, 

while reports of polar bears have been recorded at least since 

1619. These authors concluded that "there does not appear 

to be a relationship between climate trends and the rates of 

den disturbance during the overall 1850-1993 period" and 

that "changes in the frequency and pattern of disturbances 

at den sites may be related to the pattern of hunting and 

trading of hides at York Factory during the 19th and early 

20th century" (p. 163). Thus, the reality of human activity 

impacting population ecology of polar bears at WH is clear 

while empirical evidence for polar bear resiliency under 

extended records of weather extremes and a wide range of 

climatic conditions may be stronger than previously 

thought, 

6. Conclusions 

The interactions among sea-ice, atmospheric and oceanic 

circulations, and air and sea temperatures are complex and 

our understanding of these issues in the Arctic context is 

limited, We suggest that large interannual variability, which 

we view as stochastic in nature (e.g., Wunsch, 1999), 

dominates the climatic changes in WH. Improved understanding of polar bear resiliency and adaptive strategy to 

climatic changes must consider human-bear interactions, 

natural popUlation dynamiCS, and the dominant components of variability of the Arctic ice, ocean a.nd atmosphere 

that operate naturally on decadal to multidecadal timescales (Vinje, 2001; POlyakov et aL, 2003a,b; Soon, 2005). The 

clear evidence for strong regional differences in the spatial 

pattern of historical climate change around the Hudson Bay 

region add a layer of uncertainty to the task of explaining 

empirical evidence. It is certainly premature, if not impossible, to tie recent regional climatic variability in this part of 

central Canada to anthropogenic greenhouse gases and, 

further, to extrapolate species-level conditions on this basis. 

These complex interactions of man-made and natural 

factors will ultimately bring about particular ecosystem 

responses (perhaps yet unintelligible to us) but we find that 

late spring air temperature has not emerged as a decisive 

causal [actor or reliable predictor. Such a complexity within 

the Hudson Bay's ecosystem clearly challenges the usefulness of the original proposal in considering polar bears as 

indicators of climatic warming made by Stirling and 

Derocher (1993). 

The broad claim for the sea-ice to be "gone by the middle 

of the present century" could be both misleading and 

confusing in that existing model predictions are for the 

complete disappearance of late summer, rather than spring, 

sea-ice over the central Arctic ocean. Climate models 

actually expected Hudson Bay to be fully covered with 

sea-ice at least part of the year (including early spring) even 

under rather extreme forcing assumptions by involving 

rapid increases in anthropogenic greenhouse gases by the 

end of this century. This is why extrapolation studies 

arguing for severe negative impacts of polar bears under a 

global warming scenario are neither scientifically convincing 

nor appropriate. 

The fate of the charismatic polar bear population is of 

considerable public concern, and rightly so. Science can best 

contribute to the goals of conservation by providing the most 

accurate possible understanding of the factors affecting the 
429 


82737.241

population ecology of these impressive animals. Our concern 

in this paper is that if attention is inappropriately confined to a 

single mechanism, namely greenhouse warming, opportunities to understand other relevant mechanisms behind 

changes in bear population and health parameters may be 

lost in the process. It is also abundantly clear that relying on 

such a strict single-variable-driven scenarios of global warming by increasing atmospheric carbon dioxide and related 

melting sea-ice in discussing an issue as complex as the 

population and well being of polar bears runs counter to the 

underlying realities and challenges of ecological complexity 

that emphasizes at least the six co-dimensions of spatial, 

temporal, structural, process, behavioural and geometric 

complexities (as e.g., outlined in viewpoints ofLi, 2004; Loehle, 

2004; Cadenasso et al., 2006). 

Therefore, we believe it is premature to make the "onedimensional" predictions about how climate change may 

affect polar bears in general and there is no ground for 

raising public alarm about any imminent extinction of 

Arctic polar bears. The multiple known and likely stresses 

interact dynamically and may contribute in an additive 

fashion to negative effects on polar bears. To quantify the 

severity of these stress co-factors, however, is very difficult, 

if not almost impossible, with current limitations on data. 

Areas of research we would particularly encourage include 

archaeological investigations, improved data on prey population dynamics, and examination of lower trophic levels to 

provide more insight into the proximate effects of climate 

change on Arctic species. We further suggest that the AO 

circulation index may be useful in tracking the propagation 

of climatic and meteorological signals through the coupled 

ecosystems of the Arctic land and sea that promises only 

the undeniable complexity of multi-trophic level interactions (Fortier et at, 1996; Steinke et at., 2002; Hansen et a1., 

2003). 

Acknowledgements 

We thank our colleagues (especially those sharing our 

concerns for the well beings of polar bears) for important 

conversations and lessons throughout the years about this 

topic. We further thank R. McKitrick for performing the 

Granger causality tests on statistical associations shown in 

Fig. 2 of this paper and other substantial contributions. We are 

grateful for the constructive comments on earlier versions of 

the manuscript from S. Polischuk, S.-L. Han, and A. Derocher, 

which were critical for the improvement of the finaJ version. 

(The open review on a 2002-2003 version of our manuscript by 

A. Derocher is available at http://cfa-www.harvard.edu/ 

,,-,wsoonJpolarbearclimate05-dJ.) All views and conclusions 

are strictly our own and do not reflect upon any of those 

acknowledged (especially A. Derocher) or any institutions with 

whom we are affiliated. 

M. Dyck and W. Soon initiated this scientific study around 

2002-2003 without seeking research fundings and both have 

contributed equally. W. Soon's effort for the completion of this 

paper was partially supported by grants from the Charles G. 

Koch Charitable Foundation, American Petroleum Institute, 

and Exxon-Mobil Corporation. The views expressed herein are 

81 

solely of the authors and are independent of sources providing 

support 

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Is the Earth still recovering from the "Little Ice Age"? 

A possible cause of global warming 

Syun-Ichi Akasofu 

International Arctic Research Center 

University of Alaska Fairbanks 

Abstrad 

There seems to be a roughly linear increase of the temperature from about 1800, or even much earlier, to 

the present. This warming freud is likely to be a natural change; a rapid increase of CO! began in about 

1940. This freud should be subtracted from the temperature data during the last 100 years. Thus, there is a 

possibility that only a fraction of the present warming trend may be attributed to the greenhouse effect 

resulting from human activities. This conclusion is contrary to the IPCC (2007) Report, which states that 

"most" of Ihe present wanning is due to Ihe greenhouse effect. One possible cause of the linear increase 

may be that the Earth is still recovering from the Little Ice Age. It is urgent that natural changes be 

correctly identified and removed accurately from the presently on-going changes in order to find the 

contribution of the greenhouse effect. 

1. Introduction 

There are many documents that suggest that the period between 1500 and 1900 was relatively 

cool, at least in Europe; the River Thames was frequently frozen in 1676 and in the later part of 

the 17th century (Lamb, 1982). Stories of the exploration of the Northwest Passage also hint that 

sea ice conditions in northern Canada in the latter part of the 1800s were much worse than 

conditions today. It is now possible to cruise the passage without much assistanee by icebreakers. 

Although there is some doubt about the exact timing of the "Little Ice Age," it is possible to infer 

that the period between 1500 and 1900 was relatively cool in many parts of the world, including" 

Alaska (cf. Lamb, 1982; Gribbin (ed.), 1978; Crowley and North, 1991; Burroughs, 2001; 

Serreze and Barry, 2005). 

Climate change during the last 100 years or so has been intensely discussed over the last few 

decades. However, it is important to recognize that as far as the basic global warming data for 

this period are concerned,.alI we have is what is illustrated in the top of the diagram of Figure 1. 

The IPCC Reports state that the global average temperature increased about O.6°C (-1°F) during 

the last 100 years. Their interpretation may be illustrated in the second diagram of Figure 1. 

Certainly, both the temperature and the amount of CO2 in the air have increased during the last 

100 years or so. Further, it is well known that ~ causes the greenhouse effect; therefore, it is 

natural to hypothesize that C~ is a cause of the present warming trend. 

However, there is so far no definitive proof that "most" of the present warming is due to the 

greenhouse effect, as is stated in the recently published IPCC Report (2007). In fact, the 

relationship between air temperature and C02 is not simple. For example, the temperature had a 
434 


82737.377

cooling trend from 1940 to about 1975, in spite of the fact that atmospheric C02 began to 

increase rapidly in about 1940, as can be seen in Figure L 

In this note, it is pointed out that it is not possible to determine the percentage contribution of the 

greenhouse effect that is a direct result of human activities, unless natural causes can be 

identified and subtracted from the present warming trend . 

. s·cr-----=:::...::=:..t:=.:::::..c:::.:..---......., 

BaslcDala 

~C~::::::::::::::::::::::::::~ ,s'crDifferent InlerprelaliOn (1) GreenhoUS:r 

effect L. 

O·C ..::.::;. __ ____ CJ'" ~~----_-

'Jl'C,"-::==========: Jl'Cr , Dlfferanllnleqll8talion (2) __ ,L_ .......... " 

__ ,FI_ ... ;-lIot ..... I"""_ 

O'C 

1Sao 1940 11160 1980 2000 YIO' 

Figure 1: From the top, the bask data on global warming: the ]PCC interpretation (indicating that 

the O.6°C increase is caused by the greenhouse effect), another interpretation, sugge$ting a bD$eline 

change of O.loCflOO years and additional fluctuations, and yet another interpretation, a linear 

natural change superposed by natural fluctuations. 

Actually, there are many other ways to interpret the temperature changes than what is shown in 

the second diagram of Figure 1. For example, the third diagram shows another interpretation. In 

this interpretation, it is assumed that there was a base increase of about O.2OC during the last 100 

years, which was superposed by fluctuations, such as multi-decadal oscillations. The fourth 

diagram shows yet another interpretation. In this interpretation, there was an almost linear 

increase of natural temperature change during the last 100 years, which is superposed by 

fluctuations, such as multi-decadal oscillations. The difference between the second and fourth 

diagrams is that the IPCe Report assumes that the wanning trend is mostly due to human 
435 


82737.378

activities, while the latter asSlUIles that a large fraction of the warming trend is caused by natural 

causes. 

It is somewhat surprising that there has, so far, been no debate on sucb, and many other 

possibilities. Indeed, it is doubtful that the IPCC conclusion of "mosf' is the consensus of 250 

experts in climatology. The greenhouse effect is a hypothesis to be proven quantitatively. 

Further, even if proven qualitatively, it is necessary to investigate, quantitatively, how large its 

effect is. At this stage in the development of modeling and simulation, one can test the 

hypothesis only qualitatively, not quantitatively, because there are too many uncertain 

parameters in the modelings. This point will be discussed later. 

Figure 2 shows both the global average temperature and the temperature from stations widely 

distributed along the coast of the Arctic Ocean (polyakov et aI., 2002) during the last 100 years 

or so. One can see that the magnitude of temperature changes is significantly larger in the Arctic. 

A similar result was shown in the ACIA Report (2004); see p. 23. In particular, fluctuations, 

including multi-decadal oscillations, are greatly "amplified" in the Arctic. There occurred two 

major fluctuations, one between 1910 and 1915, and one after 1975. The arctic data indicates that 

the two fluctuations in the global average data should not be treated as minor fluctuations to be 

ignored. Indeed, it is crucial to investigate the nature of the temperature rise between 1910·1940 

and also the one after 1975. As the top diagram in Figure 1 shows, C(h in the atmosphere began 

to increase rapidly after 1940, when the temperature decreased from 1940 to 1975. Thus, the 

large fluctuation between 1910 and 1975 can be considered to be a natural change. Therefore, 

unless the difference between the two changes can be understood, it is not possible to say tacitly 

that the rise after 1975 is mostly caused by the greenhouse effect. 

.... c 

1_ 1m 182:0 11140 1KO 'tin 2O:)C y", 

Fign.-e 2: Red - global average change (!pCC Reports). Blue - data from statious along the 

coastline ofthe Arctic Ocean (polyakov, et al., 2002.) 

In this note, we examine first the possibility of the last case in Figure 1 and then the nature of the 

fluctuations. 

2. Linear Increase 

The basis for drawing a linear line, in the last diagram in Figure 1, is weak without additional 

data. Fortunately, Frizsche et aI. (2006) obtained ice cores from Severnaya Zemlya, an island in 

the Arctic Ocean, and made the 0(18) analysis. Their results are reproduced here as Figure 3. It 
436 


82737.379

shows the 0(18) data at the top: It is possible to observe that an almost linear change is evident 

from about 1800 to the present in the ice core record; the red linear line is drawn by the present 

author; large fluctuations are also indicated as ''natural changes" also by the author, since it is 

unlikely that C02 caused any major temperature fluctuations before 1940. 

? 

1.5 

E ~ § ~ g ~ ~ ~ g ~ ~ ~ 

·17.5 

·19.00~ 

~ 

.2(1.5 0' 

·21.0 ~ 

Figure 3: Late Halocene ice core record from Akademii Nauk lee Cap, Severnaya Zemlya, Russian 

Arctic, together with temperatare records at Vardo. Norway, and along the artie coast stations 

(Polyakov et aL, 2002), the last one is the same as that In Figure 2 (blue). 

Their figure shows also a thermometer record from Vardo in Northern Norway. The bottom 

diagram is the same as the "Arctic" one of Figure 2. The credibility of the ice core record is 

supported by the similarity with the Norwegian temperature record and the data by Polyakov et 

al. (2002), or vice versa. 

The ACIA Report (2004) took the average of 100-year records as the baseline (their figure on 

page 23), namely, a line parallel to the horizontal axis, with the aVCIlIge value as the zero line. 

However, the ice-core record shows that such a practice may not be appropriate. There is clearly 

a linear increase of temperature from about 1800. Similar linear trends can be inferred in the 

Norwegian data and the data by Polyakov et a1. (2002) in Figure 3 based on the core record. 

There are several other supporting studies that suggest that there bas been a linear change from 

about 1800 or earlier. For example, Figures 4, 5, 6, and 7 suggest a roughly linear change of 

temperature from the earliest recordings by Burroughs (2001), Tarand and Norelli (2001), and 

van Egelen et a1. (2001). 
437 


82737.380

~L-__ .~ __ .. ~ __ ~ __ ~ __ .~ ____ L-__ ~ ___ ~_. __ -L ______ .~ __ ~~ __ .~ 

1110 1. I'" 1m UI4I 1m 1810 1111 _ I. 1110 11:111 1... I_ 

vFigure 4: The linear trends for the temperature of central England over the period 1660·1996 {or 

(a) tbe annual data, and (b) tbe winter montbs (December to February), show a marked warming. 

I.b both cases, tbiS warming is signlfica.nt, but althougb the temperature rise Is greater in winter, 

this trend Is less significant because the variance from year to year Is correspondingly greater 

(Burroughs, 2001). 

-2,00 +--+--I--I---!---I--1---I---I'---I--+I 

G' 

-, ::: -I---+.--.-+--+,....--H-j!i++-+-tl--t--llill+"'!r 

-5.00 ... ~,OO¥-~~~~-+--+~~-+--~~--4 

-7.00 .l-~_L--L---.J~..i..--'_-'--L_.J-......I 

1500 1550 1600 1650 1700 1750 1800 1850 1900 1950 2000 

I ...... Fllt.3 - Fllt.9 - Fllt.30 I 

Figure 5: Winter temperature (December.March) at Taillnn since 1500, whlch are based on ice 

break-up dates in Tallinn port. The series is smoothed by Gaussian filters of 3, 9, and 30 years as 

standard deviations in the Gaussian distributiOn (Tarand aud Nordl!, 2001). 
438 


82737.381

12+---~+-~--4-----~~---+~---+--~~ .. 

7+-----~--~-----+----~----~--~ 

1700 1750 1800 1850 1900 1950 

I . Summer temperature - FlIt. 9 - Trend I 

Figure 6: Summer temperature (April to July) for Tamnn, which is based on ice break-up and rye 

harvest data and of instrnmental observations. To ease the study of variations on a timescale oC 

approximately 30 hours, the observations are smootbed by a Gaussian filter with standard 

deviation of 9 years in its distribution (curve). A trend line for the wbole period Is also ShOWD; 

Torand and Nordli (2001) 

__ '_11 ... , .... ' .... '_1 .... ' .... "..,' .... , .... _ 

Figure 7: 2S-year meao winter (DJF) temperature at De Bllt; van Egelen, Bulsman and Ijnsen 

(2001). ThIs figure includes a longer period data tban Figures 4, 50 and 6. 

There is further supporting evidence of a continuous climate change from about 1800. Figure 8 

shows that the southern edge of sea ice in the Norwegian Sea bas been continuously receding 

from about 1800. Figure 9 shows examples of glaciers in Greenland and Alaska, which have 

been receding from the time of the earliest records (about 1800 for Greenland and 1900 for 

Alaska). There are a large number of similar records from the European Alps and elsewhere 

(Grove, 1982). Therefore, it can be assumed that many glaciers advanced during the Little lee 
439 


82737.382

Age and have been receding since then. Thus, the retreat is not something that happened only in 

recent years. 

August ice edge relative to the 1961 -1990 mean 

-5 

79.10 N 

~.;.;..:.=.:;:..<--

-4 

1980 Y ... 1990 2000 

Figure 8: Retreat of sea ice In the Norwegian Sea (VInJe, 2001). 

Figure 9: Retreat of glaciers in Glacier Bay (Alaska Geographic., 1993) 
440 


82737.383

The fact that an almost linear change has been progressing, without a distinct change of slope, 

from as early as 1800 or even earlier (about 1660, even before the Industrial Revolution), 

suggests that the linear change is natural change. As shown at the top diagram of Figure I, a 

rapid increase of CO:! began only after 1940. 

As far as the gradient of the linear change is concerned. it can roughly be estimated to be about 

O.soC/IOO years based on Figures 3, 4, S, 6, and 7. It is very interesting to recognize that this 

gradient is almost comparable with the IPCC's estimate of O.6°C/l00 years. Since the maximum 

decrease of temperature during the Little Ice Age is estimated to be about O.soC (Wilson et aI, 

2000) - 1.5°C (Crowley and North, 1991; Grove, 2005), it is worthwhile to speculate iliat the 

Earth is still recovering from it. Another possible additional cause may be changes in solar 

output (cf. Scafetta and West, 2006), which we did not investigate in this note. 

Therefore, the linear change, which is likely to be a natural change, should be subtracted from 

the top diagrnm of Figure 1 in order to identify and estimate the greenhouse effect. 

However, this note is not intended to evaluate an accurate estimate of the gradient of the linear 

change. There is a great uncertainty in obtaining early data corresponding to the accuracy of the 

top of Figure 1 in terms of the geographic distribution of the stations, seasons, etc. Here, I 

emphasize only that a significant part of the 0.6°C increase includes natural changes, contrary to 

the statement by the !PCC Report (2007). 

At this point, we encounter one of the fundamental problems in climatology and also 

meteorology. Is there any definitive evidence to conclude that the Little Ice Age ended by 19OO? 

More fundamentally, how can we determine the "normal" or "standard" temperature from which 

deviations (warming or cooling) are considered to be abnormal? At this time, there is no 

reference level to conclude iliat the Little Ice Age was over by about 1900. 

Further, the !PCC Report (2007) states that the present high temperature is "unusual" except for 

about 130,000 years ago (p. 10). However, if we examine the temperatures during all the other 

interglacial periods (240,000, 330,000, 400,000 years ago), each period was warmer than the 

present one. Thus, it could be said that the present interglacial period was abnormally a cool one. 

In fact, even during the present interglacial period, the temperature was a little warmer than the 

present one for a few thousand years at its beginning (cf. Wilson et aI .• 2000). 

3. How Linear is the Linear Change? 

It is reasonable to expcct that the linear change is only a rough first approximation. An accurate 

examination is expected to show deviations from the linear trend, if the greenhouse effect is 

significant, namely an upward deviation after 1940. However, this may be hard to examine 

because the linear change is superposed by large fluctuations. 

In this respect, it is interesting to note a recent study of sea level changes (Holgate, 2006); it is 

shown in Figure 10. Although the data covers only the period after 1910, it is sufficient to view 

any indication of accelerated increase of sea level after 1940. The sea level change should reflect 

the expected changes associated with the thermal expansion of seawater and glacier melting 
441 


82737.384

changes during the last half century that were mentioned in the lPee Reports. Figure 10 shows 

that there is no clear indication of an accelerated increase of sea level after 1940, even if some 

individual glaciers in the world show accelerated receding. 

As will be discussed in the nellt section. the most prominent warming during the last half of the 

last centwy has ceased during the last twenty years. In this connection. it might be added that 

both seawater (Lynn et a!., 2006) and permafrost temperatures (Richter-Menge et aI., 2006), as 

well as the amount of Cl:4, have ceased to increase from about 2000. It is puzzling why they do 

not show an accelerated increase if their increase before 2000 was due to the greenhouse effect; 

they may be temporallluctuations. 

.. _ ........... •.............. r c .. •··· .. ••• .... 

;1 ~ 

I 

/;\. 

, 

"" - ... .... Figure 10: The mean sea level record from the nine tide gauges over the period 1904-2003 based GD 

the decadal trend values for 1907-1999. The sea level curve bere Is the lotegral of tbe rates; 

(Holgate, 2007). 

4. Fluctuations 

As shown in Figure 2, two prominent tluctuations occurred during the last 100 years. The first 

one was a temperature rise from 1910 to 1940 and the subsequent decrease from 1940 to about 

1975 (Figures 1 and 2). The second one is the present rise after 1975. As stated earlier, it is 

crucial to examine if both rises are due to the same, similar, or entirely different causes. Until 

some study can provide convincing results on this problem, we should not claim that the rise 

after 1975 is mostly due to the greenhouse effect. 

It is interesting to note from the original paper from Jones (1987, 1994) that the first temperature 

change from 1910 to 1975 occurred only in the Northern Hemisphere, Further, it occurred in 

high latitudes above 50° in latitude (Serreze and Francis, 2006), The present rise after 1975 is 

also confined to the Northern Hemisphere, and is not apparent in the Southern Hemisphere; there 

may be a problem due to the lack of stations in the Southern Hemisphere, but the Antarctic 

shows a cooling trend during 1986-2005 (Hansen, 2006). 

Thus, it is not accurate to claim that the two changes are a truly global phenomenon. even if 

averaging the data from both hemispheres can provide Figure 1. Since the greenhouse effect is 

supposed to be global, the two prominent changes may be considered to be regional changes. 

Thus, there is a possibility that both increases are natural changes, unless it can be shown 

definitely that such regional changes are caused by the greenhouse effect, 
442 


82737.385

If so, it may not be vel)' difficult, after all, to remove the two prominent fluctuations from the 

changes during the last 100 years. As a very rough first approximation. fluctuations above and 

below the linear change can also be regarded as natural changes. 

It is important to note that the present global warming after 1975 is not uniform over the Earth. 

Although a single number, namely +O.6°C/lOO years, is used in discussing global warming. the 

geographic distribution of "warming" is quite complex. The upper part of Figure II shows the 

''warming'' pattern during the last half of the last centul)'. from about 1950 to about 2000 

(Hansen et aI., 2005). One can see that the most prominent change occurred in Siberia. Alaska, 

and Canada, namely in the continental arctic. In the continental arctic, the warming rate was 

several times more than the global average of 0.6°C/I 00 years (O.6°CI2=O.3°CI50 years). It may 

be also noted that rooling was in progress in Greenland over the same time period 

It is of great interest to ask if GeMs can reproduce this geographic distribution of the observed 

ehanges shown in the upper part of Figure 11. Thus, we asked the IPCC arctic group (consisting 

of 14 sub-groups headed by V. Kattsov) to "hindeast" geographic distribution of the temperature 

change during the last half of the last century. To ''hindcast'' means to ask whether a model can 

produce results that match the known observations of the past; if a model can do this, we can be 

much more confident that the model is reliable for predicting future conditions Their results are 

compiled by Bill Chapman, of the University oflllinois, and are shown in the right side of Figure 

12. The left side of the figure is taken from the ACIA Report (2004). which shows a similar trend 

as that of the upper part of Figure 11, namely the prominent warming in the continental arctie 

and cooling in Greenland. This comparison was undertaken to reduce differences between them. 

because both are expected to be imperfect. 

Figure 11: Upper - the geographic distribution of temperature change between 1950 and 1998 

(Hansen et at, 2005). Lower - the geographic distrlbntion of temperature change between 1986 and 

:Z005 (Hansen, 2006). 
443 


82737.386

We were surprised at the difference between the two diagrams in Figure 12. If both were 

reasonably accurate, they should look alike. Ideally, the pattern of change modeled by the GeMs 

should be identical or very similar 10 the pattern seen in the measured data. We assumed that the 

present GCMs would reproduce the observed pattern with at least reasonable fidelity. However, 

we found that there was no resemblance at aU. 

Figure 12: Comparison of the observed distribution of temperature £hanges (ACIA, 20(4) and the 

simulation ("blndeastlng") by the IPCC arctic group. 

Our first reaction to this surprising result was that GCMs are still not advanced enough for 

hindcasting. However, this possibility is inconceivable, because the increase of C(h measured in 

the past is correctly used in the hindcasting, and everything we know is included in the 

computation. The IPCC arctic group's result is the best result that is possible based on our 

present knOWledge. If the greenhouse effect caused the wanning. it should be reproducible to 

some extent by these models, even if the reproduction is not perfect. It took a week or so before 

we began to realize another possibility of this discrepancy: If 14 GCMs cannot reproduce 

prominent warming in the continental arctic, perhaps much of this warming is not caused by the 

greenhouse effect at all That is to say, because it is not caused by the greenhouse effect, the 

warming of the continental arctic cannot be reproduced by our GCMs. How do we examine that 

possibility? 

If the prominent warming in the continental arctic is due to the greenhouse effect, the prominent 

trend should continue after 2000. That is, we should observe an amplification of continental 

arctic warming in this century that will be even greater than the amplification that was observed 

during the last half of the last century, because the amount of C02 continues to increase at an 

exponential rate. Thus, we examined the wanniog trend during just the last 20 years or so, 

provided by Hansen (2006). To our surprise, the prominent continental arctic wanning almost 

disappeared in those results; the Arctic warmed at a rate about like that of the rest of the world, 

while Greenland showed a strong warming (the lower part of Figure 11). Actually, the 

temperature shows a cooling trend in Fairbanks between 1977 and 2001 (Hartman and Wendler, 

2005). Therefore, our conclusion at the present time is that much of the prominent continental 

arctic warming and cooling in Greenland during the last half of the last century is due to natural 
444 


82737.387

change, perhaps to multi-decadal oscillations like Arctic Oscillation, the Pacific Decadal 

Oscillation, and the EI Nino - Southern Oscillation. This trend is shown at the bottom of Figure 

1 as positive and negative fluctuations. 

5. Summary 

From the data provided in the earlier sections, it is quite obvious that the temperature change 

during the last 100 years or so includes significant natural changes, both the linear change and 

fluctuations. It is very puzzling that the IPCC Reports state that it is mostly due to the 

greenhouse effect Radiative and other forcings are considered to explain the present warming of 

0.6°C/IOO years, so that they cannot be a confirmation of the term "mosl." Further, 

unfortunately, computers are already incorrectly "taught" that the O.6°C rise during the last 

hundred years was caused by the greenhouse effect, so they cannot prove the greenhouse effect 

and cannot predict accurately the degree of future warming. 

It is suggested here that the linear change may be due to the fact that the Earth is slowly 

recovering from the Little Ice Age, although the cause of the Little Ice Age is unknown at the 

present time. 

It is urgent that natural changes should be correctly identified and removed accurately from the 

present on-going changes in order to find the contribution of the greenhouse effect Only then 

will an accurate prediction of future temperature changes become possible. 

One lesson here is that it is not posSlble to study climate change without long-term data. This is 

understandable from the fact that it is not possible to draw the linear line in the fourth diagram of 

Figure 1 without the data shown in Figures 3, 4, 5, 6, 7, and &.It is very easy to discredit the 

results of the traditional climate change studies (Figures 4, 5, 6, and 7) in terms of accuracy. 

However, this is what climatologists must face. In some sense, inaccurate data during the last 

few hundred years are more important than accurate satellite data after 1970 in our study of 

global warming. Unfortunately, at this time, many studies are foeused on climate change after 

1975, because satellite data have become readily available. A study of climate change based (In 

satellite data is a sort of "instant" climatology. 

6. References 

AClA (Arctic Climate ImpactAssessment), Cambridge Universisty Press, 2005. 

Burroughs, W.J., Climate Change, Cambridge Univ. Press, 2001. 

Crowley, T.1. and G.R. North, Paleoclimatology, Oxford Univ. Press, 1991. 

Cruikshank, J., Do Glaciers Listen?, University of Washington Press, 2005. 

Fagan, B., The Little Ice Age: How climate made history, 1300-1&50, Persns Books Group, 2000. 

Fritzsche, D., R Schutte, H. Meyer, H. Miller, F. Wilhelms, T. Opel. L.M. Savatyugin. Late 

Holocene ice core record from Akasemii Nauk ICe Cap. Severnaya Zemlya, J.W. 

Dowdeswell and I.C. Willis, eds., Annals of Glaciology, No. 42, AlSO, accepted, 2006. 
445 


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Gribbin, J. (ed.), Climate Change, Cambridge Univ. Press, 1978. 

Grove, J.M., Little Ice Age, in Encyclopedia of the Arctic (p. 477), Routledge, 2005. 

Grove, J.M., The Little Ice Ages, Methuen, 1982. 

Hansen, J., L. Nazarenko, Reto Ruedy, Makiko Sato, Josh Willis, Anthony Del Genio, Dorothy 

Koch, Andrew Lads, Ken Lo, Surabi Menon, Tica Novakov, Judith Perlwitz, Gary Russell, 

Gavin A. Schmidt, and Nicholas Tausnev, Earth's energy imbalance: Confinnation and 

implications, Science, 308, no. 5727, pp 1431-1435, 2005. 

Hansen, J., Private communication, 2006. 

Hartmann, B. and G. Wendler, The significance of the 1976 Pacific climate shift in the 

climatology of Alaska, J. Climate, 18, 4824, 2005. 

Holgate, S.J. On the decadal rates of sea level change during the twentieth century, Geophys. 

Res. Lett., 34, LOI602,2007. 

IPCC (Intergovernmental Panel on Climate Change), http://www.ipcc.ch. 

Jones, P.D., A.E.J. Ogilvie, T.D. Davies, and K.R. Britta, History and Climate: Memories o/the 

Future?, Kluwer AcademicIPlenum Pub., 2001. 

Jones, P .D., Early European instrumental records, History and Climate; Memories of the 

Future?, Kluwer Academic Plenum Pub., pg. 55,2001 

Jones, P.O., Hemisphere surface air temperature variations: a reanalysis and an update to 1993,.1. 

Climate, 1, 1794, 1994. 

Jones, P.D., Hemispheric surface air temperature variations; recent trends and update to 1987, J. 

Climate,t,654,1987. 

Lamb, H.H., Climate, history and the modern world, Methuen, 1982. 

Ogilvie, A.E. and T. Jonsson, The Iceberg in the Mist: Northern Research in Pursuit of a "Little 

lee Age, Kluwer Academic, 2001. 

Polyakov, I.V., Genrikh V. Alekseev, Roman V. Bekryaev, Uma Bhatt, Roger L. Colony, Mark 

A. Johnson, Varerii P. Karldin, Alexander P. Makshtas, David Walsh, and Alexander V. 

Yulin, Observationally based assessment of polar amplification of global warming, Geophys. 

Res. Lett., 29, No. 18,1878,2002. 

Richter-Menge, J., J. Overland, A. Proshutinsky, V. Romanovsky, lC. Gascard, M. Karcher, J. 

Maslanile, D. Perovich, A. Shiklomanov, and D. Walker, Arctic Report, pp. S46-S52, K.A. 

Shein (cd), in State of the Climate in 200.5, NOAAINESDISINCDC and American 

Meteorological Society Report, BAMS, 2006. 

Ruddiman, W.F., Earth's Climate: Past and Future, W.H. Freeman and Company, New York, 

2001. 

Scafetta, N. and B.J. West, Phenomenological solar signature in 400 years of reconstructed 

Northern Hemisphere temperature record, Geophys. Res. Lett., 33, Ll778, 2006. 

Serreze, M. and J.A. Francis, The arctic amplification debate, Climate Change, 76, 241, 2006. 

Serreze, M.C. and RG. Barry, TheArctic Climate System, Cambridge Univ. Press, 2005. 
446 


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Simpson, 1.1., F.S. Rowland, S. Meinard, and n.R. Blake, Influence of biomass burning during 

recent fluctuations in the slow growth of globallropospheric methane, Geophys. Res. Lett., 

33, L22808, 2006. 

Trand, A. and P.O. Nardli, The Tallinn temperature series reconstructed back half a millennium 

by use of proxy data, Climate Change, 48,189,2001. 

van Engelen, A.F.V., J. Buisman, and F. Ijnsen, History and Climate - Memories of the Future. A 

millennium of weather, winds. and water in the lower countries, Kluwer Academic Press, 

New York, Boston, London, 200l. 

Vinje, T., Anomalies and Trends of Sea-Ice Extent and Atmospheric Circulation in the Nordic 

Seas during the Period 1864-1998, J. Climate, 14, 255-267, 200 1. 

Wilson, R.C,L., SA Dnny, and J.L. Chapman, The Great Ice Age, Routledge, 2000. 
447 


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APPENDIXC 
448 


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APPENDIXC 

A. Existing Regularoty Mechanisms 

1. The proposed listing did not adequately consider existing regulatory 

mechanisms regarding polar bear conseTllation. ' 

a. United States-Russia Polar Bear Conservation and Management 

Act of 2006 

On January 12,2007, H.R. 5946 was signed into law as Public Law 109-479. Sections 

901 and 902 of the Public Law, titled the United States-Russia Polar Bear Conservation and 

Management Act of 2006 (Act). amended the Marine Mammal Protection Act (MMP A) to make 

it unlawful for a person subject to, or in waters or on lands under, United States jurisdiction to 

take, import, export, possess, transport, or sell any polar bear or polar bear products in violation 

of the Agreement Between the Government of the United States of America and the Government 

of the Russian Federation on the Conservation and Management of the Alaska-Chukctka Polar 

Bear Population (Agreement) or any annual taking limit or other restriction adopted by the 

United States-Russia Polar Bear Commission. 

The Act then sets forth requirements for designation and appointment of the United 

States members on the United States-Russia Polar Bear Commission, and requires the Secretary 

of the Interior to take all necessary actions to implement tile decisions and determinations of the 

United States-Russia Polar Bear Commission. MMPA § 507. The Secretary of the Interior is 

also required to administer and enforce the Agreement on behalf of the United States, and to 

share authority for the management of the taking of polar bears for subsistence purposes with the 

Alaska Nanuuq Commission. MMPA §§ 503, 504. 

As noted by the IUeN/SSC Polar Bear Specialist Group's 2005 Report, the principal 

threat to the Chukchi Sea polar bear population was unsustainable harvest levels in the absence 
449 


82737.392

of implementation of the United States-Russia treaty. Due to the enactment ofH.R. 5946, the 

treaty is now ratified and in effect, and sets in place sufficient regulatory mechanisms to address 

the most significant threat to the Chukchi Sea population. 

The Act also addresses poaching of polar bear by authorizing a government official to 

import a polar bear or a polar bear product for purposes of forensic testing or any other law 

enforcement purpose. MMP A § 502(b), Additionally, any polar bear or any part or product of a 

polar bear taken, imported, exported, possessed, transported, sold, received, acquired, purchased, 

exchanged, or bartered, or offered for sale or exchange in violation of this title is subject to 

seizure and forfeiture, without any showing that may be required for assessment of a civil 

penalty or for criminal prosecution. MMPA § 503(c), 

The proposed rule listing the polar bear under the ESA is very dismissive of the 

Agreement, noting that the Act "provides the necessary authority to regulate and manage the 

harvest of polar bears from the Chukchi Sea population, an essential conservation measure" but 

faulting the Act because "the Act does not provide authority or mechanisms to address ongoing 

loss of sea ice," 72 Fed. Reg. at 1087 (emphasis added). Contrary to USFWS's characterization, 

the Agreement requires that the United States and Russia adopt habitat conservation measures. 

Specifically, in Article IV, the Agreement states: 

The Contracting Parties shall undertake all efforts necessary to conserve 

polar bear habitats, with particular attention to denning areas and areas oj 

concentration oj polar bears during feeding and migration. To this end, 

they shall take steps necessary to prevent loss or degradation of such 

habitats that results in, or is likely to result in, mortality to polar bears or 

reduced productivity or long-tenn decline in the Alaska-Chukotka polar 

bear population. 

(Emphasis added). These habitat protection requirements are adopted by the recent MMP A 

amendment which requires that the Secretary "do all things necessary and appropriate ••• to 
450 


82737.393

implement, enforce, and administer the provisions of the Agreement. ... " MMPA § 503(a). 

This is a significant agreement which restricts harvesting and hunting of polar bear and commits 

both parties to the conservation of ecosystems and habitats. USFWS should recognize the 

Agreement as an existing regulatory mechanism to conserve the species, with the potential to 

help prevent the risk of extinction for polar bear. 

b. The Alaska N anuuq Commission 

The Alaska Nanuuq Commission (ANe) was formed in 1994 to represent the villages in 

North and Northwest Alaska on matters concerning the conservation and sustainable subsistence 

use of polar bear. The tribal council of each membervilJage passed a resolution to become a 

member, and to authorize the ANC to represent them on matters concerning polar bear at 

regional and international levels. In 2001, the ANC signed a co-management agreement with 

USFWS. The co-management agreement authorizes ANC to work on six major areas: 1) enter 

into co-management agreements; 2) participate in the Joint Commission under the United 

StatsiRussia Treaty regarding polar bear harvest; 3) document Traditional Knowledge of Polar 

Bear Cultural Values and Utilization practices in Alaska; 4) participate in, and facilitate the 

North Slope Polar Bear Studies Plan; 5) participate and facilitate the Strategic Plan for the 

Conservation, Management. and Research of Alaska Polar Bear Populations; and 6) provide for 

conservation, education and outreach. 

In reviewing existing regulatory mechanisms, the proposed rule fails to recognize the 

benefits provided by the ANC. and the potential for the ANC to provide additional conservation 

mechanisms if required to assist in polar bear conservation. 
451 


82737.394

c. Inuvialuit-Inupiat Polar Bear Management Agreement in the 

Southern Beaufort Sea 

While passage of the MMP A in 1972 banned polar bear hunting unless done by Alaska 

Natives for subsistence, the MMP A placed no restrictions on the numbers or composition of the 

subsistence hunt, leaving open the potential for an overharvest with no legal management 

response until the population was declared depleted. Recognizing that as a threat to the 

conservation of the shared polar bear population, the Inuvialuit Game Council from Canada and 

the North Slope Borough from Alaska negotiated and signed a user-to-user agreement, the "Polar 

Bear Management Agreement for the Southern Beaufort Sea" in 1988. The 1988 Agreement 

provides for: protection of cubs and their mothers and denning females; restrictions on hunting 

seasons; allocation guidelines; prohibitions on the use of aircraft or large motorized vessels to 

take polar bears; protection of the environment; and continued support fur polar bear research 

and data acquisition. 

In a review of the 1988 Agreement, the consensus was that it has been successful because 

both the total harvest and the proportion offemales in the harvest have been contained within 

sustainable limits. While noting that harvest monitoring needs to be improved in Alaska, and 

awareness of the need to prevent overharvest of females needs to be increased in both countries, 

it was concluded that the 1988 Agreement is a useful model for other user~to-user conservation 

agreements. See C.D. Brower, et. al., "The Polar Bear Management Agreement for the Southern 

Beaufort Sea: An Evaluation of the First Ten Years ofa Unique Conservation Agreement" (May 

2001). The ability for this existing regulatory mechanism to provide for the conservation of 

polar bear should be noted by USFWS in its ruling on the proposed listing. Because user-to-user 

conservation agreements have a history of working in Alaska, the 1998 Agreement provides yet 
452 


82737.395

another existing regulatory mechanism and potential avenue for polar bear conservation besides 

listing the species mder the ESA. 

2. The proposed listing did not adequately review eXisting local, state and 

international mechanisms designed expressly to reduce human causes of 

climate change (identified by USFWS as having a significant impacting on 

sea ice). 

Climate change has been identified by USFWS as a major contributor to sea ice habitat 

changes. 72 Fed. Reg. at 1071. There is no evidence that in the proposed rule USFWS 

considered recently adopted or strengthened loeal, state or international initiatives designed to 

reduce the man-made causes of climate change which contribute to wanning in the Arctic, 

impacting sea ice, which in tum is cited as the primary factor for the determination that polar 

bear are a threatened species. 72 Fed. Reg. at 1082. The proposed rule contains incomplete 

information on existing regulatory systems and mechanisms to address climate change. 

a. International Regulatory Systems and Mechanisms 

i. Arctic Council 

The impact of climate change on the Arctic, and conservation of species in the Arctic, has 

been addressed by a high-level intergovernmental forum, the Arctic Council. The Arctic Comcil 

was formed in 1996 to ensure environmental, social and economic sustainable development in 

the Arctic region. Current council members include the United States, Canada, Denmark, 

Finland, Iceland, Norway, Russia and Sweden. Six Arctic indigenous communities are 

Permanent Participants on the Council. The Arctic Council has five expert working groups 

focusing on monitoring, assessing and providing scientific Work regarding specific issues in the 

Arctic. The working groups which should be consulted regarding polar bear and the impact of 

climate change on habitat in the Arctic include: The Arctic Monitoring and Assessment 

Programme (which identifies pollution risks and their impact on the Arctic ecosystems and 
453 


82737.396

assesses the effectiveness ofintemational agreements on pollution control); the Protection of the 

Arctic Marine Environment (which reviews climatic and developmental pressures on the Arctic 

marine environment from shipping, dumping, offshore oil and gas development and land-based 

activities); and the Conservation of Arctic Flora and Fauna (which works for enhanced 

monitoring of biodiversity at the circumpolar level, fully utilizing traditional knowledge, to 

detect the impacts of global change on biodiversity and enable Arctic communities to effectively 

respond and adapt to those changes). 

Studies and actions by the Arctic CoWlCil should also be addressed in the proposed rule, 

including: the Protection of the Arctic Marine Environment workgroup's development of the 

Regional Programme of Action which addresses urgent pollution problems in the Arctic marine 

environment stemming from land-based activities and the Arctic Climate Impact Assessment, 

which notes the ongoing warming of the Arctic as well as possible adaptations and responses. 

ii. United Nations Framework Convention on Climate 

Change 

The proposed rule should also note international climate change policy such as thc United 

Nations Framework Convention on Climate Change (UNFCCC), which regulates greenhouse gas 

emissions. 189 nations, including the United States, have ratified the UNFCCC, agreeing to the 

common objective of stabilizing greenhouse gas emissions "at a level that would prevent 

dangerous anthropogenic (human induced) interference with the climate system." UNFCCC at 

Art. 2. 

iii. Kyoto Protocol 

The Kyoto Protocol is a binding addendum to the UNFCCC which requires industrialized 

countries that ratified the treaty to collectively reduce greenhouse gas emissions by about five 
454 


82737.397

percent compared to the 1990 levels between 2008 and 2012. As of Dece..'Ilber 2006, 169 

countries and other government entities are party to the Kyoto Protocol. 

b. State and Local Regulatory Systems and Mechanisms 

i. Kyoto Protocol adopted by Cities 

While the United States is not party to the Kyoto Protocol, 435 mayors from 50 states 

representing a total population of over 61 million citizens, have agreed to: meet or exceed the 

Kyoto Protocol targets in their own communities; urge their state governments, and the federal 

government, to enact policies and programs to meet or exceed the greenhouse gas emission 

reduction target suggested for the United States in the Kyoto Protocol- a 7% reduction from 

1990 levels by 2012; and urge the U.S. Congress to pass the bipartisan greenhouse gas reduction 

legislation, which would establish a national emission trading system. 

ii. Regional Initiatives 

The Regional Greenhouse Gas Initiative began on January 18, 2007, as eight 

Northeastern states initiated a state level emissions capping and trading program. Participating 

states include: Maine, New Hampshire, Vermont, Connecticut, New York, New Jersey, 

Delaware, and Massachusetts. Observer states and regions include: Pennsylvania, Maryland, 

District of Columbia, and the Eastern Canadian Provinces. In conjunction with their individual 

state emission cap programs, the West Coast Governors have adopted a Western Regional 

Climate Change Initiative through which Washington, Oregon, California, New Mexico and 

Arizona will work together on climate protection. 

iii. State Caps on Greenhouse Gas Emissions 

On August 31, 2006, California adopted AB 32, an economy-wide cap on carbon dioxide 

emissions. The aim of AB 32 is to reduce the state's greenhouse-gas emissions, which rank as 
455 


82737.398

the 12th-largest in the world, by 25 percent by the year 2020. Several other states have adopted 

similar measures to reduce their contribution to global climate pollution, including Washington 

and Oregon. 
456 


82737.406

f.a.~t~,i:jnd :F~Ui:H:;i~~ 

~iboill:t P,ol;tj:r iB~;!:lr~ 
457 


82737.407

World Wildlife Fund iYVWFj has worked around the 

world's Arctic regions for over 25 years to protect 

Arctic wildlife such as walrus, Whales, seals and 

polar bears. Today, many species are facing new 

threats as climate change warms and alters arctic 

habitats. In late 2006, the U.S. Fish and Wildlife 

Service (USFWS) proposed listing the polar bear as 

threatened under the Endangered Species Act of 

1 973, 8ecausethere is confusion and misinformation 

reported about polar bears and the effects of global 

warming on their habitat, WWF has compiled the 

following facts to clarify inaccuracies from truths. 

"There are still 20,000-25,000 polar bears in the wild. That's too large a number to allow for considering the 

species to be endangered." 

Facts: 

• The Endangered Species Act (ESA) specifies that the listing of a threatened or endangered species is 

justifiable when any of the following criteria are met: 

1. The present or threatened destruction, modification, or curtailment of its habitat or range; 

2. Overutilization for commercial, recreational, scientlfic, or educational purposes; 

3. Disease or predation; 

4. The inadequacy of existing regulatory mechanisms; 

5. Other natural or manmade factors affecting its continued existence. 

WWF believes that the proposal by the USFWS is based on a logical and science-based case, to which many 

respected experts from around the world have contributed. 

• The listing of the polar bear as a threatened species is warranted chiefly because of the "threatened 

destruction, modification, or curtailment" of polar bear habitat or range, i.e., the sea ice. Sea ice is 

anticipated to decrease significantly over the next 45 years. As of December 12, 2007 NASA climate 

scientist Jay Zwally predicts that summer sea ice may be entirely gone by 2012. 

"The listing should be made on the current status of the bear - not on the potential, future loss of habitat." 

Facts: 

• The life history of polar bears is intricately tied to the Arctic sea ice. While polar bears are found in most 

Ice-covered areas in the northern hemisphere, they appear to prefer annual sea ice in shaflow, productive 

waters. In recent decades, sea ice has been diminishing at an unprecedented rate. In fact, records for sea 

ice decline were broken in August. 2007, signaling a major loss of the polar bear's most important habitat. 

Although 20,000-25,000 seems like a big number, experts predict that based on projections of continued 

sea ice decline, as early as mid-century, two-thirds of the world's polar bears could be lost. 

• Under the Endangered Species Act, a threatened species is defined as "any species which is likely to 

become an endangered species within the foreseeable future throughout all or a significant portion of its 

range." Accordingly, USFWS is required to analyze not only the current status of a species but also its 

status Into the foreseeable future. 

lmages © 2007 V'lWF-Ganon I Sveln Be Oppegaard; Martin Harvey, Wlm van Passel, MiChel Terrettaz, Syfi.1a Rubli, Dan Guravicl'l, WwW.Jsgrove.Com. Kevin Schafer: 
458 


82737.408

"Usting won't really help the polar bear because it won't stop the melting of sea lce." 

Facts: 

• The ESA was intended by Congress to provide a means to protect endangered and threatened species as 

well as the ecosystems on which they depend. 

• Listing the polar bear under the ESA requires the federal government to take actions not available under 

other pertinent regulatory mechanisms for the protection of listed species. For example, if the polar bear 

is listed, USFWS will be rsqulred to identify and protect critical habitat for the polar bear. USFWS will also 

be obligated to develop a recovery plan, which provides a scienGe~based '~road map" that guide managers 

responsible for the species. A recovery plan should include site-specific actions, estimates of time and 

cost of the recommended measures and crlteria for "de-listing" the species. 

• Additionally, if the polar bear is listed as threatened, the federal government will be required to identify and 

designate "critical habitat" for the polar bear. The ESA defines "critical habitat" as "specific areas within 

the geographical area occupied by the species" ,,\!hich contain "physical or blological features Q} essential 

to the conselVatlon of the species and (Il) which may require special management considerations or 

protection. Critical habitat can also include "specific areas outside the geographical area occupied by the 

speCies." 

• In addition to these legal measures, the public discussion about listing the polar bear has attracted 

world-wide attention to the issue of sea ice decline and global climate change. Only through such broad 

awareness and engagement of the public wi!! it be possible to reduce the production of the "greenhouse 

gases" that have led to the current trends in warming that we are witnessing today. 
459 


82737.409

"If polar bears are listed as threatened under the ESA in the United States, 

all hunting of polar bears will be stopped, and local communities will be 

negatively impacted." 

Facts: 

• For thousands of years, indigenous peoples of the Arctic have 

harvested marine wildlife for sustenance as well as clothing and 

handicrafts. In Alaska, Canada and Greenland, indigenous people 

harvest polar bear for subsistence purposes. In Russia, a new 

U.S.- Russia treaty that was legally enacted in September 2007 opens 

the possibility for Russian native people to conduct a harvest, pending 

recommendations from scientists. In the United States, Alaskan 

native rights to harvest marine mammals for subsistence and use in 

handicrafts are protected under the Marine Mammal Protection Act 

(MMPA). This right will not be suspended if the bear is listed. 

• Currently the native harvest of polar bears in the Southern Beaufort 

Sea is managed by an international agreement between the Inupiat 

people of Alaska and the Inuvialuit people of Canada, who share a 

quota of polar bears. In Canada, a part of the quota is apportioned to 

recreational hunting permits. 

" The majority of recreational hunters in Canada are U.S. citizens, 

and in 1994 an amendment to the MMPA was made to allow these 

hunters to import their legally taken trophies into the United States. 

If the polar bear is listed as threatened, U.S. hunters who participate 

in such a sport hunt will not be able to import the hide of any polar 

bear harvested. The MMPA prohibits sport and commercial hunting of 

polar bears in Alaska. Greenland allows only full-time hunters living a 

subsistence lifestyle to hunt polar bears. 

"Canadian scientists and governments strongly oppose the listing of 

polar bears under the ESA." 

Facts: 

• The government of the Canadian province of Nunavu! and its 

biologists have gone on record in opposition to the listing of the polar 

bear as a threatened species. However, other Canadian scientists 

and governments support such protections as listing the polar bear 

as threatened. Two of the world's leading polar bear biologists, Dr. 

Ian Stirling and Dr. Andrew Derocher are supportive of additional 

protective measures for polar bear populations. The Minister of 

Natural Resources David Ramsay has warned that continued climate 

change may lead to the extinction of polar bears in southeastern 

Canada. 

• Canada currently lists the polar bear as a "species of concern" and in 

April of 2008, the government will determine whether to add the polar 

bear to the Canadian Species at Risk Act (SARA) list, which is similar 

to the ESA. 
460 


82737.410

"Legislation currently in place in the United States is adequate to protect 

the polar bear and therefore it is not necessary for the USFWS to list the 

polar bear under the ESA." 

Facts: 

• In its proposal to list the polar bear at threatened, the USFWS 

acknowledges that the regulatory mechanisms directed specifically 

at managing immediate threats to polar bears do exist in all of the 

range states where the species occurs. However, polar bears are most 

threatened by the accelerating loss of Arctic sea ice habitat as a result 

of climate warming. There are no existing regulatory mechanisms 

requiring the conservation of sea ice habitat in the Arctic and current 

energy policies in the countries, China and the U.S., which are the 

leading polluters, are inadequate to curb greenhouse gas emissions. 

• There is one avenue available to protect the principal habitat of polar 

bears -- the designation of "critical habitat" but this requires first listing 

the polar bear under the ESA. 

• Other measures that are not in place, but which WWF is promoting, 

include an Arctic-wide treaty that would help to protect the entire range 

of the polar bear and would regulate other threats to the polar bear and 

its habitat. Also, WWF joins many other conservation organizations in 

promoting a global reduction of C02 emissions. 

"Polar bears will be able to adapt to hunt and live on land, where 

alternative food sources can be found." 

Facts: 

• On average, an adult polar bear needs approximately 2 kg (4.4 100) of 

seal fat per day to survive. Sufficient nutrition is critical and is stored as 

fat that helps polar bears survive the harsh arctic winter. 

• Polar bears are carnivores, preying heavily throughout their range on ice 

seals, primarily ringed seals and bearded seals. Polar bears also have 

been known to kill much larger animals such as walruses, narwhal, and 

belugas. 

• As the Arctic Sea ice continues to deCline, polar bears wifl have less 

access and time to forage on these important food sources. In the 

western Hudson Bay, where the ice breaks up three weeks earlier than 

it did 20 years ago, scientists have recorded nutritionally stressed bears 

and lower survival in the population. 

III In some areas and under certain conditions, prey and carrion other 

than seals may supplement a polar bear's diet. Polar bears will eat 

human garbage, and when confined to land for long periods they will 

consume coastal marine and terrestrial plants and other terrestrial food 

if necessary. However, these sources are nutritionally poor compared 

to the high fat content of ice seals, and would not be adequate to 

replace the polar bears' preferred food. In addition the sea ice habitat 

is changing too rapidly for polar bears to evolve to a terrestrial life style. 

In summary, there Is no scientific evidence indicating that polar bears 

can suffiCiently adapt to a life without ice seals and maintain viable 

populations. 
461 


82737.411

"Polar bears survived warming periods before, and some warming may 

actually benefit polar bears," 

Facts: 

• As a species, polar bears have survived at least two warming periods in the 

past For example, 6,000 to 10,000 years ago, summer temperatures were 

two to three degrees Celsius warmer than today. However, there were also 

periods (140,000 and 20,000 years ago) when temperatures were much 

colder - as much as 10 degrees Celsius. 

• Although we do not know how polar bears survived those warming periods, 

we do know that the species' survival is closely dependent on Arctic sea 

ice, which is rapidly diminishing in much of the Arctic. 

• If any warming is to benefit bears, this may be for those which occupy the L northernmost regions where sea ice IS present year-round. But in places It where sea ice is receding, bears are forced to spend more time on land or 

on the remaining pack ice over the relatively deep and unproductive waters 

in centra! polar basin and thus are deprived from their key food sources for 

longer periods. 

• Unlike past warming periods, polar bears now face additional 

anthropogenic threats such as pollutants and various forms of human 

disturbance. 

"Climate modeling is speculative and there is a lack of agreement on 

climate warming." 

Facts: 

• In the last two years, several major studies have been co-authored and peerreviewed by hundreds of well-respected scientists that document evidence of 

global climate change. These experts have reached widespread agreement 

that: 

1. Climate change is real; 

2. Human-caused pollution is the main contributing factor and that; 

3. The Arctic is one of the regions to experience climate change most acutely. 

• Observations have shown a decline in late summer Arctic sea ice extent of 

7.7 percent per decade and in the perennial sea ice area of up to 9.8 percent 

per decade since 1978. In some places, a thinning of the Arctic sea ice of as 

great as 32 percent or more from the 1960's and 1970's to the 1990's has been 

shown. More importantly, the rate of sea ice decrease is accelerating, with 

record low minimum extents in the sea ice recorded in 2005 and even lower in 

2007. 

• One widely accepted scientific study suggests that abrupt reductions in the 

extent of summer ice are likely to occur over the next few decades, and that 

near ice-free September conditions may be reached as early as 2040, In 

December, 2007, Dr. Jay Zwally of NASA predicted that summer sea ice may 

be gone as early as 2012. 

• Besides diminishing sea ice, other impacts in the Arctic that are already being 

observed include: shrinking glaciers, thawing penmafrost, and Arctic "greening" 

(encroachment of shrubs and trees into tundra ecosystems) validate - and 

in many cases - exceed predictions made regarding temperature trends, 

reductions to annual sea ice during the summer and winter periods, reductions 

to multiyear pack ice and reductions to ice thickness. 
462 


82737.412

"Polar bears can breed with grizzly bears to avoid extinction." 

Facts: 

• Hybrid polar-grizzly bears are neither polar bears nor grizzly bears. Hybridization of the two bear species 

does not prevent one or the other from going extinct; rather it may actually facilitate extinction. 

"Polar bears can be moved --- to zoos or parks where they can be cared for, or even to Antarctica, where there 

is also snow and ice." 

Facts: 

• Although zoos can play an important role in captive breeding and reintroduction of animals into the wild, this 

measure would be largely impractical and over the long-term, is not likely to help polar bears survive in the wild. 

• The introduction of polar bears to Antarctica is also impractical. In addition to the unlikely potential of capturing 

polar bears and safely transporting an entire population to the southern hemisphere, such a measure would 

have great potential to significantly disrupt the existing ecosystem there. For example, introducing a predator 

such as the polar bear could jeopardize a variety of potential prey species such as penguins and seals. 

can be built in the Arctic Ocean that may be utilized by polar bears and ice seals in place 

of melting sea ice." 

Facts: 

• This is a possible mitigation deserving more study; however, any such platforms would need to effectively 

mimic the habitat characteristics and uses that sea ice serves for polar bears and ice seals. Realistically, this 

is not likely to work in the harsh seas and rough weather in the Arctic. 

• A fundamental fact is that polar bears catch seals, mainly at their breathing holes or birth lairs on the sea 

ice and seals could not make breathing holes in artificial/plastic sheeting covering thousands of km2 of 

arctic ocean. The arctic ecosystem that polar bears have evolved in is driven by the ice-water interface. 

Furthermore, WWF could not condone creating new sources of marine debris to an ocean which already 

suffers from pollution. 

"Oil and gas development poses no discernable threat to polar bears or their habitat." 

• The principal cause of climate change in the Arctic is global warming, which the scientific community has 

clearly linked to the increase of carbon dioxide into the atmosphere via human use of fossil fuels (e.g., coal, 

oil and gas). 

• Thus, oil and gas development does indeed pose a discern able threat to sea ice and indirectly to polar bears 

by virtue of the extraction and development of sequestered hydrocarbons that are subsequently used by 

people for energy. 

• Oil and gas exploration and development activities in the Arctic (e.g., Chukchi and Beaufort seas off Alaska 

and Canada) pose other hazards to polar bears, ice seals, and their sea ice habitats, the most notable threat 

being that of spilled oil which cannot be cleaned up effectively. Oiled bears and seals would likely suffer 

lethal and sub-lethal effects. Disturbances due to seismic exploration, construction, transportation and the 

operation of facilities, as well as contamination from oil spill cleanup operations, may negatively impact 

polar bears. Furthermore, exploration of oil and gas continues to add C02 into the atmosphere, which is the 

leading cause of the global wanming and the loss of the polar bear's sea ice habitat. 

• WWF urges individuals, corporations and governments to recognize the need for conservation and better 

use of fossil fuels in addition to the development of new cleaner air technologies to meet our ever increasing 

energy demands. 
463 


82737.413

World Wildlife Fund 

1250 24th Street, NW 

Washington, D.C. 20037 

Phone: (202) 778-9685 

Fax: (202) 293-9345 

World Wildlife Fund's Alaska Office 

40.6 G Street, Suite 303 

AQchorage, AK 99501 

Phone: (907) 279-5504 
464 


82737.414

(umuJ>livc r,nvi",nmcnalliff~. QfOil iln~ (l~.I\c'i.i(ie. Q.l\lnsto. NOt1h Slope (2003) t4fl~~~~l~MIIT.\'1ttlII~JJII/III.<'t"Y'qal:!lJD"'U·I"'~lIe;dec1yl'lfSc"m:a..II'Inpc.~ 

CUMULATIVE ENVIRON1\l1ENTAL EFFEcrs OF OIL AND GAS 

ACTIVITlES ON 

ALAsKAs NORTH SWPE 

CommiHee on Cumulcfive Environmental Effec::15 of 

Oil and Gas Activities on Alaska's North Slope 

Board on Environmental Studies and Toxicology 

Polar Research Board 

Division on Earth and Life 5lvdies 

NATIONAL RESEARCH COUNCIL Of 7H£ NAnONAI ACIDEMlES 

THE NA llONAl ACADEMIES PRESS 

Washington, D.C. 

_.n.p .• du 
465 


82737.415

(Umul:"livc: finvironmro.ntal nffc~a of Oil"nd Oll' Actjyiti(; ... ()fl Mauta s Nonb Slope (200)} ~~t1l.I',\am.lt.(tl1lfJ11Qj\iluN,(lWri,lJlI'lJ.lII'ill~ltIIlosW~f!I1''''~dl''.III'rt:Il'~t 

pol..- bears nod their habita's (FWS 1995b), no formal projeclioo, have been mllde of how likely effect5 on ringed seals 

Of pol..- bears from Mil ... 011 nod gM aotivitles .... to accumulate wllh effects of other human activities. For pIUpOses 

of milking su<:h • projection, the committee', scenario assumes that offsho ... exploration for 011 and gas. and posSible 

e,,""ction. will occur In the B .... fon S" from Banow 10 

F1axmlUllsland. and po>slbly 10 lhe Canadlnn border. Activity would occur mo.tIy Dear shore. adjaa:nl to onsho ... oil 

reserves. lIDd developmeDt would entail methods IUld struclwe. similar to those currently in use (gravel Islands or 

""ltom-founded struCIUreS, horizonUII drilling. buried pipelines. and an emphasis on working during wloter). 

Full'scale Industrialization of oe .... shore ueas would 

most llkely rewlt In at !eIlst plll1lDl dlsplw:ment of ringed 

seDls. The frequency with which polar bears come into con· 

tact with people IUld struoturesi. undoubtedly a fuoctlon of 

Ih. amount of activity In their habilau. EVen with the best 

possible mitigallon measures in place. it i. ""rtain thOl .ome 

bears will be hnrassed or I:IIled. More humllll aolivlty aloog 

the coast nod ncar sbore could reduce the I5UitabiUty of some 

orea.s for use by denoiDg female be ..... This effed is likely 10 

be greate't east of the ClUI/lhJg River, especio\1y within the 

1002 ArelI of the Arcdc National WlldHfe Refuge. wbere the 

highesl concentration of on-land deol i. found (Amstrup 

1993. Amstrup and Ganloer 1994). Bffort. to Identify areas 

wbere poilU' bears .... most likely 10 den In the eastern 1'"11 of 

Ihe Nonb Slope (Owner el aI. 2001). should improve the 

abIHty of regolators and induslJy to reducc d1stUl"bance of 

deMed bears. 

CODIlICI with spiUed oil or other conll!mlnants in the 

ocean would harm rioged seals and pol..- bears. and the llkeIihood of spills would increase with increased exploration 

and developmenL Amstrup and eoUeagoes (2000) modeled 

the spread of. hypothetical 5.900 bbl (939.000 1.. 248,000 

gol) oil spill from the Ubeny prospeel'lIS it might nffecl the 

sellSooal distribution and abundance of polar bears in the 

B""ufort Sea. The number of be .... potentiDlly offeded by 

.uch D .pill runged from 0 10 2S with summer open-Wilier 

conditioll5 and 0 to 61 with autumn brokeo-I"" conditions. 

In Its flndlngs permittJng the 011 and gos Industry to !like 

polar be ... in Alaska woters.the FWS .Ialed. "We conclude 

that If IUl oil spW were 10 occur during the fall or spring 

broken-j"" periods •• slgnificanl impacllo polat bears could 

occur" (M Federal Register 16833 (2000)). It seems likely 

that an all spin would affect rioged seals the $MIe way the 

E:aon Yaldez affected horbar seals (PIwca vlr.llna) (Fro,t 

el nI.l994o. Lowry el DI. 1994. Spmerel 111.1994). and the 

number of wmDls killed would depend latgely on the se.-

son IUld lb. size of the splU. Polar bears could be funber 

affected lfthey ateoil-eon!amloatedseals (51. Aubin 199Ob). 

CUmale change also wllIllffecl marine mllflUl\alB (Tynan 

and DeMosI.r 1997). S"" icc Is imponanl iD the life of aU 

lOS 

marine mammllls iD the arctlc and subllfolic reglous (Fay 

1974). Alreody. Ut .... have been dramatic decreases in the 

exlent IUld thickness of sea ice throughout lhe nortbern hemi· 

.pbere. and those trends .... eXj)e(:ted 10 cootlnue through 

th. next century (ViDnlkov et aI. 1999. Wener 2000). The 

distribution. abundance. and prodoctivlly of Alo.skan manne 

m8llllQal populations will likely be allered by the combined 

effects of changes In pbyslcal habllals. p ... y populations. and 

interspecles inleractlons (Lowry 2000). WannirJg is likely 10 

increase Ibe OCCUITeIIce nod resideDce times of .uban:tic species (spotted seals. walrus. beluga whales. bowhead wbales) 

in the region. 

Negative effects on populations of truly arctic speeles 

(poillf bears. riDged seals. lIDd bearded seals) pre likely 10 

resull from climate wcrmlng. Poiill' bears and rloged .eals 

depend on sea ice, lIDd reducUo06 In the extenl nod persislence of Ice in the Beaufon Sea wiD almost cenainly buve 

negallve effects 00 their populations (FWS 1 !l9Sb). Climate 

change has already affected pol..- beano in western Hudson 

Boy. wh .... beano hunt ringed seals on the sea I"" from N<>-

vember 10 July and spend Ibe open.water season on sho ... 

where they feed little. In aloDg-term study. SlirUng nod colle.go" (1999) documeDred decreased body condition and 

reproducdve performllllce In bears thlll conelOled with a 

trend toward earlier breakup of sea Ice in recenl Ye.ull. The 

carlier breakup glv .. beano a shorter feeding .... on. They 

.... leIUler when they come .. hore,and they must f .. 1 longer. 

Many rioged seal. give birth 10 and care for their pups on 

stable sho .... tost ice. and chllDges In the extent and slllbillty 

or the timing of breuIrup of the Ice could reduce pnx!uctivlty 

(Smith and Horwood 20(1). Because of the c1o.e predalorp ... y ... Iadonsblp between polar beano and ringed seal •• ere.. creos .. in ringed seal abundance con be expected to C8IIse 

decUne. in polar bear populations (SdrUng and 0ritsland 

1995). 

How theselndependeot factors mighl combine to Influence populations cannol be predicted with currenl knowledge. If cUmote wcrmlng lIDd subslliDtiDl oil spills did not 

occur. cumulative e~ aD riDged seals IUld polar bears in 

Ibe nexl2S ye.ull would likely be minor and nol =umulllle. 

CurrenUy there are no research plllRS or studies thOl spe· 

clfically address potential accumulating effects on polar 

bears or ringed seals of[ Ibe North Slope. Unle .. such studIes .... designed, funded. and cooduc1e4 over long periods 

(decodes). it will be impossible 10 verify whether lIIe effects 

occur. 10 measun: tbeIr magnitude. or 10 exploin their ..... s ... 

FindIngs 

• industrial activity in manne waters of the Beaufort 

Sea bllS been limited Md 5poJtIdio nod likely has 110\ caused 

serious =umulatlng effecu on ringed seals or polar bears. 

• C .... fI1I mitigation CIIII help 10 reduce the effects of 

North Slope aU lIDd gas developmenl and their accumulation. especially if there I. no major oU spiU. However. the 
466 


82737.416

('u.nul.lltivc I1p",ironlllcnu.1 fif(<<1-'1 of Oi11lnd 04.' I\criviri~ (Ill Ahu:1."U $: Nonh Slop!; (200~) 

M~.II.1,j\~~l~~~mMltIllVIl ... lltftll"lwn,hf2ltJ" . .)lIl1~N~~J(~~I",I\I'~ 

/0/1 

olT",,1S of fuD,scalo industrial d.velopm""l orthe waters olT 

the North Slope would aecwnulalC through displacement of 

poiIII' bears and ringed seals from their habitats. iftcteased 

molUlillY. aad deo;reased n:pro<Iutlivo .U<Xe5s. 

• A major 8 •• ufort Sea oil spill would b.v. major ef· 

f""lo 00 polar bears and ringed seals. 

• Climate worming at predicled niles in the BeaufOl1 

Sea region Is Ukely to buv. serious consequences tor ringed 

seals and poiIII' bean. aad those elTeclS will atC\llDulQle with 

Ih. effuts of oil and 805 octIvllies In the region. 

• Unless studies 10 address potential atCumulation of 

effects on North Slope poIIII' bears or ringed seals are deoigoed, funded, and condutled over long pcrioda, It will be 

Impossible to verify whether such effec:lS ocwr. 10 measure 

them. or to o~phun their emuses. 

CARIBOU 

InlmdulUon 

The effeclS of North Slope industrial development 00 

bam:n·ground coribou (RQIIg/f.r (arandus grant£) hen!.! bave 

boen conlentious. AItbough much research has been con· 

dueled on coribou in the region. researohers hove disagreed 

over the interpretation and n:lotivo impol1allee of some data 

nnd how serious data gaps are. The disagreements are espc • 

• laUy signifitaat bee.use coribou lIfO nulrltlooally and cui· 

tunlly important to North Slope residents and beeBUse <.:arl. 

boo are widely recognized as importaol symbols of the state 

nnd weD·being of North Slop: environments. For these rea· sons. the commillCe assembled information on <.:arlbou nnd 

evwualed conrucUng interprelatloos ofth. ioformatloluboul 

bow oil and gns development might have nffectedthelr popu· 

lallon dynaoUcs. The committee's consensus 011 effects 10 

dole, aad proj~tlons of probable future etrull, is the praduCI of this ~aret\JllllllllysJs aad deUberalion. 

As,essing theelTects of oil and gasdevolopmenlOflcari· 

boo i. nol straightforward betause mllny factors other thlln 

oil lind gns actlvlOes affect the sizes of North Slop: caribou 

herds-weather, yegetaOon, disease, and predators. for "". 

ample. Therefore, there Is no steady baseUne ngalnst whitlt 

10 identify and assess distwbanc\>olnduced cbanges. To 

evaluate the effects of p:troleum developmenl OD caribou, 

the committee eXaoUned changes in di.tribution and habitat 

use. and evaluated the nutritional and n:produc!ivelmpUca· 

lions of those thange. and how they altered populoUon 

dynaoUcs. 

BaakOfOund 

Caribou are ubiquitous on the North Slope. Four sepa. 

fIlle herds. flIOglng nearly 2O-fold in siz.o, .... recognized on 

the basis of distinctly diffetellt calving grounds (Skoog 1968, 

Figure 8·2). The extent of scasonallDlgralion varies with 

berd size (BergetUd 1979. Faacy ct aI. 1989. Skoog 1968). 

CUMUI.A71VE /fJo'I'IiCl'S 01' AlASKA NDX!lI SWPI: OIL AND GAS 

By far the llll'gesl is the Western Alelle Herd (WAH), esli· 

maled 01460,000 (in 20(1).11 calves in the Utukok uplaads 

south of BartOW and summm thrOughout the North Slope 

and Brooks Range wesl otthe ColviUeRiver. including most 

of tlte NaIloDIIl Petroleum Reserve-Alaska. Wintering IU'OU 

Intlude both the weslern North Slope aad Ibe southern 

foothiUs of tho Brooks Range. The annual IlIIIge of the 

Te.hekpuk Lake Herd ('lUI), numbering 27.000 (In 1999), 

Hes within the W AM SWDmer range. Calving and summer 

ranges are in the coastal zone lie4\' Tesbekpuk Lake; the win· 

ter range typically Is confined 10 the COIlSIaI pillin and nelllby 

foothills.l!stimaled 01123,000 (in 200 I). the Porcupine Cari· 

bou Herd (PCH) calves on the coastal plain aad lower 

uplands In northeastern Alaska within the AleUc N.lional 

Wildlife Refuge and adjocent Yukon Territory. During the 

summer. the PeH rnnges thrOugboul much of the eastern 

North 'Slop: ODd Brooks Ronge; Its winlering IU'OU Include 

the Ogilvie and RiChardSOD alOuotalns in western Canada 

and the southern Brooks Range in easlern A1oska. At 27.000 

(in 20(0). the Centnll AleUc Herd (CAll) is dlstribuled pri. 

marily within state lands between the Colvillo aad Canning 

rivers. CAM clllving and summer moges are on the coastal 

plain, aad the WiDlI:r ClllIj;e Iypically extends 50UthWard into 

the northern foothiUs of the Brooks Range. Durin8 the pnsl 

27 years. the size ot the PCH bas been nearly constant; the 

other three herds hove inCl'ellSed substantially (FiSUre 8·3). 

Canlral Amite Hard 

For the pasl 50 or 60 yean, all four berds (Figure 8·2) 

have been exposed 10 011 and gns exploratlon IICIivity, but 

only tho CAM has boen In n:gullll' aad dire<t COfll8Ot with 

sutface development reJlIIed 10 oil produttlon and tnmsport. 

Its calving ground and sWlllDer range He within the oil-field 

reglon = Prudhoe Bay; its autumn, winter, and spring 

rangO$ encompa.s the Dalton Highway (also called the Haul 

Road) and the area around the Trans·Alaska Pipeline 

(Cameron and Whitten I 979b). TheCAR has iftcteased from 

QlOVnd 5,000 anlmllls In tho laIC 19705 to its cu"",,1 (2000) 

size of 27,000 (FISU'" 8.3). 

Parturienl femules. along with most nonparturient females aad yearUng •• arrive 00 the collSta! l'alving grouod in 

IDId-May (Gavin 1978, SlDIth 01 aI. 1994). The exact timing 

depends on pll1tems of snowfall and snowmelt (CametOn el 

al. 1992. Gavin 1973). Most calving occurs within 50 kID 

(31 mI) of the Beaufort Sea (WbInen and Cameron 1985. 

Wolfe 20(0). Virtually all calves "'" born between late May 

and early lune (Cameron et aI. 1993) within two or Ihm> 

calving tonceDtr1Ition areas (WbIlten and Cameron 1985. 

Wolfe 2000). AI the landsempe level. selec:tinn and repealed 

use of a I'aIving ground is probably relalCd 10 both the distri· 

bution of predators, whlth lIfO less abundant on the coastal 

plain (Rausch 1953; Reynolds 1979; Shideler and HechlCl 

2000; Stephenson 11179; Youog el al. 1992, 2002) and the 

IIJceHbood of favomble foragJng COll<litions (Griffith 01 aI. 
467 


82737.417

UNITED STATES 

DEPARTMENT of the INTERIOR 

* * * * ** * * * * * * * * * * * * * * *news release 

OFFICE OF THE SECRETARY 

For Release to PM'. JULY 8. 1965 

FIVE-NATION CONFERENCE ON POLAR BEARS 

SCHEDULED FOR SEPTEMBER IN ALASKA 

Guinan ., 343-5634 

In a joint announcement with United States Senator E. L. uBobu 

Bartlett of Alaska, Secretary of the Interior Stewart L. Udall said 

today that a five-nat ton meeting of scientists concerned with polar 

bear conservation wlll be held at the Universlty of Alaska, Fairbanks, 

September 6-11, 1965. 

Secretary Udall aald Senator Bartlett has led in awakening public 

interest 1n the preservation of the polar bear and bas been closely 

concerned with planning the international conference. 

Fonnal invitations to the Fairbanks meeting have been sent to 

Canada, Norway, Denmark and the Soviet Union. Certain private conser ... 

vat10n organizations will be asked to send observers~ 

Secretary Udall said much remains to be learned about polar bears 

and that the scientists from the five nations will study factors concerning population. distribution) exploitation, reproduction, danger 

of elttinction, and related matters. He said the polar bear1s rang~ has. 

contracted considerably since 1930, but data to support s.toriee circulated that it is becoming a rare animal are not definitive. 

"It is time the. scientists got together to determine. how much fact 

and fancy there are In the various re.ports, u S~cretary Udall commented. 

Most of the United States research on polar bears has been done by 

State of Alaska scientists. These scientistB wil.l be among those partic" 

ipating in the international meeting. Secretary Udall. pointed out that 

Alaska is the only State where polar bears are found, and the State is 

vitally concerned with proper management of the resource. 
468 


82737.418

Sao~atary Udall .aid all .. allabla aeleatLfle infor.atlon will be 

pooled ad tben d1atributed to SO\fenmeDti concemad to determine 

futur.a aetu,a ad poUele. toward pola~ baar COD.anatlOD. The lairblDk. 

maatina 1. expaeted to propoae P~OI~'" for colleetiDa needed .eientLfle 

data aDd for intarnacLonal COllabo~atloD in polar bear re.earch vital to 

proper CDD.ervatlon. 

"It L. particularly flttiDI that .ucb a coaference taka place 

duriDi the International Coopa~at~ Yaar (ICY) DOW beLng observed arouad 

the VQ.t14." Seeretary Udall added. "It La in sueh forullI8 that exputs 

frOlll _y leu" Q.III dLacu88 conaarYation probl.s of mutual concern and 

establlah the fouadatlons fo~ lutue aet1oD. that eeu banefit all man." 

aaa 
469 

Æ