[Federal Register: May 15, 2008 (Volume 73, Number 95)]
[Rules and Regulations]               
[Page 28211-28303]
From the Federal Register Online via GPO Access [wais.access.gpo.gov]
[DOCID:fr15my08-18]                         


[[Page 28211]]

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Part II





Department of the Interior





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Fish and Wildlife Service



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50 CFR Part 17



Endangered and Threatened Wildlife and Plants; Determination of 
Threatened Status for the Polar Bear (Ursus maritimus) Throughout Its 
Range; Final Rule


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DEPARTMENT OF THE INTERIOR

Fish and Wildlife Service

50 CFR Part 17

[FWS-R7-ES-2008-0038; 1111 FY07 MO-B2]
RIN 1018-AV19

 
Endangered and Threatened Wildlife and Plants; Determination of 
Threatened Status for the Polar Bear (Ursus maritimus) Throughout Its 
Range

AGENCY: Fish and Wildlife Service, Interior.

ACTION: Final rule.

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SUMMARY: We, the U.S. Fish and Wildlife Service (Service), determine 
threatened status for the polar bear (Ursus maritimus) under the 
Endangered Species Act of 1973, as amended (Act) (16 U.S.C. 1531 et 
seq.). Polar bears evolved to utilize the Arctic sea ice niche and are 
distributed throughout most ice-covered seas of the Northern 
Hemisphere. We find, based upon the best available scientific and 
commercial information, that polar bear habitat--principally sea ice--
is declining throughout the species' range, that this decline is 
expected to continue for the foreseeable future, and that this loss 
threatens the species throughout all of its range. Therefore, we find 
that the polar bear is likely to become an endangered species within 
the foreseeable future throughout all of its range. This final rule 
activates the consultation provisions of section 7 of the Act for the 
polar bear. The special rule for the polar bear, also published in 
today's edition of the Federal Register, sets out the prohibitions and 
exceptions that apply to this threatened species.

DATES: This rule is effective May 15, 2008. The U.S. District Court 
order in Center for Biological Diversity v. Kempthorne, No. C 08-1339 
CW (N.D. Cal., April 28, 2008) ordered that the 30-day notice period 
otherwise required by the Administrative Procedure Act be waived, 
pursuant to 5 U.S.C. 553(d)(3).

ADDRESSES: Comments and materials received, as well as supporting 
scientific documentation used in the preparation of this rule, will be 
available for public inspection, by appointment, during normal business 
hours at: U.S. Fish and Wildlife Service, Marine Mammals Management 
Office, 1011 East Tudor Road, Anchorage, AK 99503. Copies of this final 
rule are also available on the Service's Marine Mammal website: http://
alaska.fws.gov/fisheries/mmm/polarbear/issues.htm.

FOR FURTHER INFORMATION CONTACT: Scott Schliebe, Marine Mammals 
Management Office (see ADDRESSES section) (telephone 907-786-3800). 
Persons who use a telecommunications device for the deaf (TDD) may call 
the Federal Information Relay Service (FIRS) at 1-800-877-8339, 24 
hours a day, 7 days a week.

SUPPLEMENTARY INFORMATION: 

Background

    Information in this section is summarized from the following 
sources: (1) The Polar Bear Status Review (Schliebe et al. 2006a); (2) 
information received from public comments in response to our proposal 
to list the polar bear as a threatened species published in the Federal 
Register on January 9, 2007 (72 FR 1064); (3) new information published 
since the proposed rule (72 FR 1064), including additional sea ice and 
climatological studies contained in the Intergovernmental Panel on 
Climate Change (IPCC) Fourth Assessment Report (AR4) and other 
published papers; and (4) scientific analyses conducted by the U.S. 
Geological Survey (USGS) and co-investigators at the request of the 
Secretary of the Department of the Interior specifically for this 
determination. For more detailed information on the biology of the 
polar bear, please consult the Status Review and additional references 
cited throughout this document.

Species Biology

Taxonomy and Evolution

    Throughout the Arctic, polar bears are known by a variety of common 
names, including nanook, nanuq, ice bear, sea bear, isbj[oslash]rn, 
white bears, and eisb[auml]r. Phipps (1774, p. 174) first proposed and 
described the polar bear as a species distinct from other bears and 
provided the scientific name Ursus maritimus. A number of alternative 
names followed, but Harington (1966, pp. 3-7), Manning (1971, p. 9), 
and Wilson (1976, p. 453) (all three references cited in Amstrup 2003, 
p. 587) subsequently promoted the name Ursus maritimus that has been 
used since.
    The polar bear is usually considered a marine mammal since its 
primary habitat is the sea ice (Amstrup 2003, p. 587), and it is 
evolutionarily adapted to life on sea ice (see further discussion under 
General Description section). The polar bear is included on the list of 
species covered under the U.S. Marine Mammal Protection Act of 1972, as 
amended (16 U.S.C. 1361 et seq.) (MMPA).
    Polar bears diverged from grizzly bears (Ursus arctos) somewhere 
between 200,000 and 400,000 years ago (Talbot and Shields 1996a, p. 
490; Talbot and Shields 1996b, p. 574). However, fossil evidence of 
polar bears does not appear until after the Last Interglacial Period 
(115,000 to 140,000 years ago) (Kurten 1964, p. 25; Ingolfsson and Wiig 
2007). Only in portions of northern Canada, Chukotka, Russia, and 
northern Alaska do the ranges of polar bears and grizzly bears overlap. 
Cross-breeding of grizzly bears and polar bears in captivity has 
produced reproductively viable offspring (Gray 1972, p. 56; Stirling 
1988, p. 23). The first documented case of cross-breeding in the wild 
was reported in the spring of 2006, and Wildlife Genetics International 
confirmed the cross-breeding of a female polar bear and male grizzly 
bear (Paetkau, pers. comm. May 2006).

General Description

    Polar bears are the largest of the living bear species (DeMaster 
and Stirling 1981, p. 1; Stirling and Derocher 1990, p. 190). They are 
characterized by large body size, a stocky form, and fur color that 
varies from white to yellow. They are sexually dimorphic; females weigh 
181 to 317 kilograms (kg) (400 to 700 pounds (lbs)), and males up to 
654 kg (1,440 lbs). Polar bears have a longer neck and a proportionally 
smaller head than other members of the bear family (Ursidae) and are 
missing the distinct shoulder hump common to grizzly bears. The nose, 
lips, and skin of polar bears are black (Demaster and Stirling 1981, p. 
1; Amstrup 2003, p. 588).
    Polar bears evolved in sea ice habitats and as a result are 
evolutionarily adapted to this habitat. Adaptations unique to polar 
bears in comparison to other Ursidae include: (1) White pelage with 
water-repellent guard hairs and dense underfur; (2) a short, furred 
snout; (3) small ears with reduced surface area; (4) teeth specialized 
for a carnivorous rather than an omnivorous diet; and (5) feet with 
tiny papillae on the underside, which increase traction on ice 
(Stirling 1988, p. 24). Additional adaptations include large, paddle-
like feet (Stirling 1988, p. 24), and claws that are shorter and more 
strongly curved than those of grizzly bears, and larger and heavier 
than those of black bears (Ursus americanus) (Amstrup 2003, p. 589).

Distribution and Movements

    Polar bears evolved to utilize the Arctic sea ice niche and are 
distributed throughout most ice-covered seas of the Northern 
Hemisphere. They occur throughout the East Siberian, Laptev, Kara, and 
Barents Seas of Russia; Fram Strait (the narrow strait between northern 
Greenland and Svalbard),

[[Page 28213]]

Greenland Sea and Barents Sea of northern Europe (Norway and Greenland 
(Denmark)); Baffin Bay, which separates Canada and Greenland, through 
most of the Canadian Arctic archipelago and the Canadian Beaufort Sea; 
and in the Chukchi and Beaufort Seas located west and north of Alaska.
    Over most of their range, polar bears remain on the sea ice year-
round or spend only short periods on land. However, some polar bear 
populations occur in seasonally ice-free environs and use land habitats 
for varying portions of the year. In the Chukchi Sea and Beaufort Sea 
areas of Alaska and northwestern Canada, for example, less than 10 
percent of the polar bear locations obtained via radio telemetry were 
on land (Amstrup 2000, p. 137; Amstrup, USGS, unpublished data); the 
majority of land locations were bears occupying maternal dens during 
the winter. A similar pattern was found in East Greenland (Wiig et al. 
2003, p. 511). In the absence of ice during the summer season, some 
populations of polar bears in eastern Canada and Hudson Bay remain on 
land for extended periods of time until ice again forms and provides a 
platform for them to move to sea. Similarly, in the Barents Sea, a 
portion of the population is spending greater amounts of time on land.
    Although polar bears are generally limited to areas where the sea 
is ice-covered for much of the year, they are not evenly distributed 
throughout their range on sea ice. They show a preference for certain 
sea ice characteristics, concentrations, and specific sea ice features 
(Stirling et al. 1993, pp. 18-22; Arthur et al. 1996, p. 223; Ferguson 
et al. 2000a, p. 1,125; Ferguson et al. 2000b, pp. 770-771; Mauritzen 
et al. 2001, p. 1,711; Durner et al. 2004, pp. 18-19; Durner et al. 
2006, p. pp. 34-35; Durner et al. 2007, pp. 17 and 19). Sea-ice habitat 
quality varies temporally as well as geographically (Ferguson et al. 
1997, p. 1,592; Ferguson et al. 1998, pp. 1,088-1,089; Ferguson et 
al.2000a, p. 1,124; Ferguson et al.2000b, pp. 770-771; Amstrup et al. 
2000b, p. 962). Polar bears show a preference for sea ice located over 
and near the continental shelf (Derocher et al. 2004, p. 164; Durner et 
al. 2004, p. 18-19; Durner et al. 2007, p. 19), likely due to higher 
biological productivity in these areas (Dunton et al. 2005, pp. 3,467-
3,468) and greater accessibility to prey in near-shore shear zones and 
polynyas (areas of open sea surrounded by ice) compared to deep-water 
regions in the central polar basin (Stirling 1997, pp. 12-14). Bears 
are most abundant near the shore in shallow-water areas, and also in 
other areas where currents and ocean upwelling increase marine 
productivity and serve to keep the ice cover from becoming too 
consolidated in winter (Stirling and Smith 1975, p. 132; Stirling et 
al. 1981, p. 49; Amstrup and DeMaster 1988, p. 44; Stirling 1990, pp. 
226-227; Stirling and [Oslash]ritsland 1995, p. 2,607; Amstrup et al. 
2000b, p. 960).
    Polar bear distribution in most areas varies seasonally with the 
seasonal extent of sea ice cover and availability of prey. The seasonal 
movement patterns of polar bears emphasize the role of sea ice in their 
life cycle. In Alaska in the winter, sea ice may extend 400 kilometers 
(km) (248 miles (mi)) south of the Bering Strait, and polar bears will 
extend their range to the southernmost proximity of the ice (Ray 1971, 
p. 13). Sea ice disappears from the Bering Sea and is greatly reduced 
in the Chukchi Sea in the summer, and polar bears occupying these areas 
move as much as 1,000 km (621 mi) to stay with the pack ice (Garner et 
al. 1990, p. 222; Garner et al. 1994, pp. 407-408). Throughout the 
polar basin during the summer, polar bears generally concentrate along 
the edge of or into the adjacent persistent pack ice. Significant 
northerly and southerly movements of polar bears appear to depend on 
seasonal melting and refreezing of ice (Amstrup 2000, p. 142). In other 
areas, for example, when the sea ice melts in Hudson Bay, James Bay, 
Davis Strait, Baffin Bay, and some portions of the Barents Sea, polar 
bears remain on land for up to 4 or 5 months while they wait for winter 
and new ice to form (Jonkel et al. 1976, pp. 13-22; Schweinsburg 1979, 
pp. 165, 167; Prevett and Kolenosky 1982, pp. 934-935; Schweinsburg and 
Lee 1982, p. 510; Ferguson et al. 1997, p. 1,592; Lunn et al. 1997, p. 
235; Mauritzen et al. 2001, p. 1,710).
    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 
any one season or year, is an important part of the polar bear life 
history strategy. In other regions, where ice is less dynamic, home 
ranges are smaller and less variable (Ferguson et al. 2001, pp.51-52). 
Data from telemetry studies of adult female polar bears show that they 
do not wander aimlessly on the ice, nor are they carried passively with 
the ocean currents as previously thought (Pedersen 1945 cited in 
Amstrup 2003, p. 587). Results show strong fidelity to activity areas 
that are used over multiple years (Ferguson et al. 1997, p. 1,589). All 
areas within an activity area are not used each year.
    The distribution patterns of some polar bear populations during the 
open water and early fall seasons have changed in recent years. In the 
Beaufort Sea, for example, greater numbers of polar bears are being 
found on shore than recorded at any previous time (Schliebe et al. 
2006b, p. 559). In Baffin Bay, Davis Strait, western Hudson Bay and 
other areas of Canada, Inuit hunters are reporting an increase in the 
numbers of bears present on land during summer and fall (Dowsley and 
Taylor 2005, p. 2; Dowsley 2005, p. 2). The exact reasons for these 
changes may involve a number of factors, including changes in sea ice 
(Stirling and Parkinson 2006, p. 272).

Food Habits

    Polar bears are carnivorous, and a top predator of the Arctic 
marine ecosystem. Polar bears prey heavily throughout their range on 
ice-dependent seals (frequently referred to as ``ice seals''), 
principally ringed seals (Phoca hispida), and, to a lesser extent, 
bearded seals (Erignathus barbatus). In some locales, other seal 
species are taken. On average, an adult polar bear needs approximately 
2 kg (4.4 lbs) of seal fat per day to survive (Best 1985, p. 1035). 
Sufficient nutrition is critical and may be obtained and stored as fat 
when prey is abundant.
    Although seals are their primary prey, polar bears occasionally 
take much larger animals such as walruses (Odobenus rosmarus), narwhal 
(Monodon monoceros), and belugas (Delphinapterus leucas) (Kiliaan and 
Stirling 1978, p. 199; Smith 1980, p. 2,206; Smith 1985, pp. 72-73; 
Lowry et al. 1987, p. 141; Calvert and Stirling 1990, p. 352; Smith and 
Sjare 1990, p. 99). In some areas and under some conditions, prey other 
than seals or carrion may be quite important to polar bear sustenance 
as short-term supplemental forms of nutrition. Stirling and 
[Oslash]ritsland (1995, p. 2,609) suggested that in areas where ringed 
seal populations were reduced, other prey species were being 
substituted. Like other ursids, polar bears will eat human garbage 
(Lunn and Stirling 1985, p. 2,295), and when confined to land for long 
periods, they will consume coastal marine and terrestrial plants and 
other terrestrial foods (Russell 1975, p. 122; Derocher et al. 1993, p. 
252); however the significance of such other terrestrial foods to the 
long-term welfare of polar bears may be limited (Lunn and Stirling 
1985, p. 2,296; Ramsay and Hobson 1991, p. 600; Derocher et al. 2004, 
p. 169) as further expanded under the section entitled ``Adaptation'' 
below.

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Reproduction

    Polar bears are characterized by late sexual maturity, small litter 
sizes, and extended parental investment in raising young, all factors 
that contribute to a low reproductive rate (Amstrup 2003, pp. 599-600). 
Reproduction in the female polar bear is similar to that in other 
ursids. Females generally mature and breed for the first time at 4 or 5 
years and give birth at 5 or 6 years of age. Litters of two cubs are 
most common, but litters of three cubs are seen sporadically across the 
Arctic (Amstrup 2003, p. 599). When foraging conditions are difficult, 
polar bears may ``defer'' reproduction in favor of survival (Derocher 
et al. 1992, p. 564).
    Polar bears enter a prolonged estrus between March and June, when 
breeding occurs. Ovulation is induced by mating (Wimsatt 1963, p. 72), 
and implantation is delayed until autumn. The total gestation period is 
195 to 265 days (Uspenski 1977, cited in Amstrup 2003, p. 599), 
although active development of the fetus is suspended during most of 
this period. The timing of implantation, and therefore the timing of 
birth, is likely dependent on body condition of the female, which 
depends on a variety of environmental factors. Pregnant females that 
spend the late summer on land prior to denning may not feed for 8 
months (Watts and Hansen 1987, p. 627). This may be the longest period 
of food deprivation of any mammal, and it occurs at a time when the 
female gives birth to and then nourishes new cubs.
    Newborn polar bears are helpless and have hair, but are blind and 
weigh only 0.6 kg (1.3 lb) (Blix and Lentfer 1979, p. 68). Cubs grow 
rapidly, and may weigh 10 to 12 kg (22 to 26 lbs) by the time they 
emerge from the den in the spring. Young bears will stay with their 
mothers until weaning, which occurs most commonly in early spring when 
the cubs are 2.3 years of age. Female polar bears are available to 
breed again after their cubs are weaned; thus the reproductive interval 
for polar bears is 3 years.
    Polar bears are long-lived mammals not generally susceptible to 
disease, parasites, or injury. The oldest known female in the wild was 
32 years of age and the oldest known male was 28, though few polar 
bears in the wild live to be older than 20 years (Stirling 1988, p. 
139; Stirling 1990, p. 225). Due to extremely low reproductive rates, 
polar bears require a high survival rate to maintain population levels 
(Eberhardt 1985, p. 1,010; Amstrup and Durner 1995, pp. 1,313, 1,319). 
Survival rates increase up to a certain age, with cubs-of-the-year 
having the lowest rates and prime age adults (between 5 and 20 years of 
age) having survival rates that can exceed 90 percent. Amstrup and 
Durner (1995, p. 1,319) report that high survival rates (exceeding 90 
percent for adult females) are essential to sustain populations.

Polar Bear--Sea Ice Habitat Relationships

    Polar bears are distributed throughout the ice-covered waters of 
the circumpolar Arctic (Stirling 1988, p. 61), and rely on sea ice as 
their primary habitat (Amstrup 2003, p. 587). Polar bears depend on sea 
ice for a number of purposes, including as a platform from which to 
hunt and feed upon seals; as habitat on which to seek mates and breed; 
as a platform to move to terrestrial maternity denning areas, and 
sometimes for maternity denning; and as a substrate on which to make 
long-distance movements (Stirling and Derocher 1993, p. 241). Mauritzen 
et al. (2003b, p. 123) indicated that habitat use by polar bears during 
certain seasons may involve a trade-off between selecting habitats with 
abundant prey availability versus the use of safer retreat habitats 
(i.e., habitats where polar bears have lower probability of becoming 
separated from the main body of the pack ice) of higher ice 
concentrations with less prey. Their findings indicate that polar bear 
distribution may not be solely a reflection of prey availability, but 
other factors such as energetic costs or risk may be involved.
    Stirling et al. (1993, p. 15) defined seven types of sea ice 
habitat and classified polar bear use of these ice types based on the 
presence of bears or bear tracks in order to determine habitat 
preferences. The seven types of sea ice are: (1) stable fast ice with 
drifts; (2) stable fast ice without drifts; (3) floe edge ice; (4) 
moving ice; (5) continuous stable pressure ridges; (6) coastal low 
level pressure ridges; and (7) fiords and bays. Polar bears were not 
evenly distributed over these sea ice habitats, but concentrated on the 
floe ice edge, on stable fast ice with drifts, and on areas of moving 
ice (Stirling 1990 p. 226; Stirling et al. 1993, p. 18). In another 
assessment, categories of ice types included pack ice, shore-fast ice, 
transition zone ice, polynyas, and leads (linear openings or cracks in 
the ice) (USFWS 1995, p. 9). Pack ice, which consists of annual and 
multi-year older ice in constant motion due to winds and currents, is 
the primary summer habitat for polar bears in Alaska. Shore-fast ice 
(also known as ``fast ice'', it is defined by the Arctic Climate Impact 
Assessment (2005, p. 190) as ice that grows seaward from a coast and 
remains in place throughout the winter; typically it is stabilized by 
grounded pressure ridges at its outer edge) is used for feeding on seal 
pups, for movement, and occasionally for maternity denning. Open water 
at leads and polynyas attracts seals and other marine mammals and 
provides preferred hunting habitats during winter and spring. Durner et 
al. (2004, pp. 18-19; Durner et al. 2007, pp. 17-18) found that polar 
bears in the Arctic basin prefer sea ice concentrations greater than 50 
percent located over the continental shelf with water depths less than 
300 m (984 feet (ft)).
    Polar bears must move throughout the year to adjust to the changing 
distribution of sea ice and seals (Stirling 1988, p. 63; USFWS 1995, p. 
4). In some areas, such as Hudson Bay and James Bay, polar bears remain 
on land when the sea ice retreats in the spring and they fast for 
several months (up to 8 months for pregnant females) before fall 
freeze-up (Stirling 1988, p. 63; Derocher et al. 2004, p. 163; Amstrup 
et al. 2007, p. 4). Some populations unconstrained by land masses, such 
as those in the Barents, Chukchi, and Beaufort Seas, spend each summer 
on the multi-year ice of the polar basin (Derocher et al. 2004, p. 163; 
Amstrup et al. 2007, p. 4). In intermediate areas such as the Canadian 
Arctic, Svalbard, and Franz Josef Land archipelagos, bears stay on the 
sea ice most of the time, but in some years they may spend up to a few 
months on land (Mauritizen et al. 2001, p. 1,710). Most populations use 
terrestrial habitat partially or exclusively for maternity denning; 
therefore, females must adjust their movements in order to access land 
at the appropriate time (Stirling 1988, p. 64; Derocher et al. 2004, p. 
166).
    Sea ice changes between years in response to environmental factors 
may have consequences for the distribution and productivity of polar 
bears as well as their prey. In the southern Beaufort Sea, anomalous 
heavy sea ice conditions in the mid-1970s and mid-1980s (thought to be 
roughly in phase with a similar variation in runoff from the Mackenzie 
River) caused significant declines in productivity of ringed seals 
(Stirling 2002, p. 68). Each event lasted approximately 3 years and 
caused similar declines in the birth rate of polar bears and survival 
of subadults, after which reproductive success and survival of both 
species increased again.

Maternal Denning Habitat

    Throughout the species' range, most pregnant female polar bears 
excavate

[[Page 28215]]

dens in snow located on land in the fall-early winter period (Harington 
1968, p. 6; Lentfer and Hensel 1980, p. 102; Ramsay and Stirling 1990, 
p. 233; Amstrup and Gardner 1994, p. 5). The only known exceptions are 
in western and southern Hudson Bay, where polar bears first excavate 
earthen dens and later reposition into adjacent snow drifts (Jonkel et 
al. 1972, p. 146; Ramsay and Stirling 1990, p. 233), and in the 
southern Beaufort Sea, where a portion of the population dens in snow 
caves located on pack and shore-fast ice. Successful denning by polar 
bears requires accumulation of sufficient snow for den construction and 
maintenance. Adequate and timely snowfall combined with winds that 
cause snow accumulation leeward of topographic features create denning 
habitat (Harington 1968, p. 12).
    A great amount of polar bear denning occurs in core areas 
(Harington 1968, pp. 7-8), which show high use over time (see Figure 
8). In some portions of the species' range, polar bears den in a more 
diffuse pattern, with dens scattered over larger areas at lower density 
(Lentfer and Hensel 1980, p. 102; Stirling and Andriashek 1992, p. 363; 
Amstrup 1993, p. 247; Amstrup and Gardner 1994, p. 5; Messier et al. 
1994, p. 425; Born 1995, p. 81; Ferguson et al. 2000a, p. 1125; Durner 
et al. 2001, p. 117; Durner et al. 2003, p. 57).
    Habitat characteristics of denning areas vary substantially from 
the rugged mountains and fjordlands of the Svalbard archipelago and the 
large islands north of the Russian coast (L[oslash]n[oslash] 1970, p. 
77; Uspenski and Kistchinski 1972, p. 182; Larsen 1985, pp. 321-322), 
to the relatively flat topography of areas such as the west coast of 
Hudson Bay (Ramsay and Andriashek 1986, p. 9; Ramsay and Stirling 1990, 
p. 233) and north slope of Alaska (Amstrup 1993, p. 247; Amstrup and 
Gardner 1994, p. 7; Durner et al. 2001, p. 119; Durner et al. 2003, p. 
61), to offshore pack ice-pressure ridge habitat (Amstrup and Gardner 
1994, p. 4; Fischbach et al. 2007, p. 1,400). The key characteristic of 
all denning habitat is topographic features that catch snow in the 
autumn and early winter (Durner et al. 2003, p. 61). Across the range, 
most polar bear dens occur relatively near the coast. The main 
exception to coastal denning occurs in the western Hudson Bay area, 
where bears den farther inland in traditional denning areas (Kolenosky 
and Prevett 1983, pp. 243-244; Stirling and Ramsay 1986, p. 349).

Current Population Status and Trend

    The total number of polar bears worldwide is estimated to be 
20,000-25,000 (Aars et al. 2006, p. 33). Polar bears are not evenly 
distributed throughout the Arctic, nor do they comprise a single 
nomadic cosmopolitan population, but rather occur in 19 relatively 
discrete populations (Aars et al. 2006, p. 33). The use of the term 
``relatively discrete population'' in this context is not intended to 
equate to the Act's term ``distinct population segments'' (Figure 1). 
Boundaries of the 19 polar bear populations have evolved over time and 
are based on intensive study of movement patterns, tag returns from 
harvested animals, and, to a lesser degree, genetic analysis (Aars et 
al. 2006, pp. 33-47). The scientific studies regarding population 
bounds began in the early 1970s and continue today. Within this final 
rule we have adopted the use of the term ``population'' to describe 
polar bear management units consistent with their designation by the 
World Conservation Union-International Union for Conservation of Nature 
and Natural Resources (IUCN), Species Survival Commission (SSC) Polar 
Bear Specialist Group (PBSG) with information available as of October 
2006 (Aars et al. 2006, p. 33), and to describe a combination of two or 
more of these populations into ``ecoregions,'' as discussed in 
following sections. Although movements of individual polar bears 
overlap extensively, telemetry studies demonstrate spatial segregation 
among groups or stocks of polar bears in different regions of their 
circumpolar range (Schweinsburg and Lee 1982, p. 509; Amstrup et al. 
1986, p. 252; Amstrup et al., 2000b, pp. 957-958.; Garner et al. 1990, 
p. 224; Garner et al. 1994, pp.112-115; Amstrup and Gardner 1994, p. 7; 
Ferguson et al. 1999, pp. 313-314; Lunn et al. 2002, p. 41). These 
patterns, along with information obtained from survey and 
reconnaissance, marking and tagging studies, and traditional knowledge, 
have resulted in recognition of 19 relatively discrete polar bear 
populations (Aars et al. 2006, p. 33). Genetic analysis reinforces the 
boundaries between some designated populations (Paetkau et al. 1999, p. 
1,571; Amstrup 2003, p. 590) while confirming the existence of overlap 
and mixing among others (Paetkau et al. 1999, p. 1,571; Cronin et al. 
2006, p. 655). There is considerable overlap in areas occupied by 
members of these groups (Amstrup et al. 2004, p. 676; Amstrup et al. 
2005, p. 252), and boundaries separating the groups are adjusted as new 
data are collected. These boundaries, however, are thought to be 
ecologically meaningful, and the 19 units they describe are managed as 
populations, with the exception of the Arctic Basin population where 
few bears are believed to be year-round residents.

[[Page 28216]]

[GRAPHIC] [TIFF OMITTED] TR15MY08.002

    Population size estimates and qualitative categories of current 
trend and status for each of the 19 polar bear populations are 
discussed below. This discussion was derived from information presented 
at the IUCN/SSC PBSG meeting held in Seattle, Washington, in June 2005, 
and updated with results that became available in October 2006 (Aars et 
al. 2006, p. 33). The following narrative incorporates results from two 
recent publications (Stirling et al. 2007; Obbard et al. 2007). The 
remainder of the information on each population is based on the 
available status reports and revisions given by each nation, as 
reported in Aars et al. (2006).
    Status categories include an assessment of whether a population is 
believed to be not reduced, reduced, or severely reduced from historic 
levels of abundance, or if insufficient data are available to estimate 
status. Trend categories include an assessment of whether the 
population is currently increasing, stable, or declining, or if 
insufficient data are available to estimate trend. In general, an 
assessment of trend requires a monitoring program or data to allow 
population size to be estimated at more than one point in time. 
Information on the date of the current population estimate and 
information on previous population estimates and the basis for

[[Page 28217]]

those estimates is detailed in Aars et al. (2006, pp. 34-35). In some 
instances a subjective assessment of trend has been provided in the 
absence of either a monitoring program or estimates of population size 
developed for more than one point in time. This status and trend 
analysis only reflects information about the past and present polar 
bear populations. Later in this final rule a discussion will be 
presented about the scientific information on threats that will affect 
the species within the foreseeable future. The Act establishes a five-
factor analysis for using this information in making listing decisions.
    Populations are discussed in a counterclockwise order from Figure 
1, beginning with East Greenland. There is no population size estimate 
for the East Greenland polar bear population because no population 
surveys have been conducted there. Thus, the status and trend of this 
population have not been determined. The Barents Sea population was 
estimated to comprise 3,000 animals based on the only population survey 
conducted in 2004. Because only one abundance estimate is available, 
the status and trend of this population cannot yet be determined. There 
is no population size estimate for the Kara Sea population because 
population surveys have not been conducted; thus status and trend of 
this population cannot yet be determined. The Laptev Sea population was 
estimated to comprise 800 to 1,200 animals, on the basis of an 
extrapolation of historical aerial den survey data (1993). Status and 
trend cannot yet be determined for this population.
    The Chukchi Sea population is estimated to comprise 2,000 animals, 
based on extrapolation of aerial den surveys (2002). Status and trend 
cannot yet be determined for this population. The Southern Beaufort Sea 
population is comprised of 1,500 animals, based on a recent population 
inventory (2006). The predicted trend is declining (Aars et al. 2006, 
p.33), and the status is designated as reduced. The Northern Beaufort 
Sea population was estimated to number 1,200 animals (1986). The trend 
is designated as stable, and status is believed to be not reduced. 
Stirling et al. (2007, pp. 12-14) estimated long-term trends in 
population size for the Northern Beaufort Sea population. The model-
averaged estimate of population size from 2004 to 2006 was 980 bears, 
and did not differ in a statistically significantly way from estimates 
for the periods of 1972 to 1975 (745 bears) and 1985 to 1987 (867 
bears), and thus the trend is stable. Stirling et al. (2007, p. 13) 
indicated that, based on a number of indications and separate annual 
abundance estimates for the study period, the population estimate may 
be slightly biased low (i.e., might be an underestimate) due to 
sampling issues.
    The Viscount Melville Sound population was estimated to number 215 
animals (1992). The observed or predicted trend based on management 
action is listed as increasing (Aars et al. 2006, p. 33), although the 
status is designated as severely reduced from prior excessive harvest. 
The Norwegian Bay population estimate was 190 animals (1998); the 
trend, based on computer simulations, is noted as declining, while the 
status is listed as not reduced. The Lancaster Sound population 
estimate was 2,541 animals (1998); the trend is thought to be stable, 
and status is not reduced. The M'Clintock Channel population is 
estimated at 284 animals (2000); the observed or predicted trend based 
on management actions is listed as increasing although the status is 
severely reduced from excessive harvest. The Gulf of Boothia population 
estimate is 1,523 animals (2000); the trend is thought to be stable, 
and status is designated as not reduced. The Foxe Basin population was 
estimated to number 2,197 animals in 1994; the population trend is 
thought to be stable, and the status is not reduced. The Western Hudson 
Bay population estimate is 935 animals (2004); the trend is declining, 
and the status is reduced. The Southern Hudson Bay population was 
estimated to be 1,000 animals in 1988 (Aars et al. 2006, p. 35); the 
trend is thought to be stable, and status is not reduced. In a more 
recent analysis, Obbard et al. (2007) applied open population capture-
recapture models to data collected from 1984-86 and 1999-2005 to 
estimate population size, trend, and survival for the Southern Hudson 
Bay population. Their results indicate that the size of the Southern 
Hudson Bay population appears to be unchanged from the mid-1980s. From 
1984-1986, the population was estimated at 641 bears; from 2003-2005, 
the population was estimated at 681 bears. Thus, the trend for this 
population is stable. The Kane Basin population was estimated to be 
comprised of 164 animals (1998); its trend is declining, and status is 
reduced. The Baffin Bay population was estimated to be 2,074 animals 
(1998); the trend is declining, and status is reduced. The Davis Strait 
population was estimated to number 1,650 animals based on traditional 
ecological knowledge (TEK) (2004); data were unavailable to assess 
trends or status. Preliminary information from the second of a 3-year 
population assessment estimates the population number to be 2,375 bears 
(Peacock et al. 2007, p. 7). The Arctic Basin population estimate, 
trend, and status are unknown (Aars et al. 2006, p. 35).
    On the basis of information presented above, two polar bear 
populations are designated as increasing (Viscount Melville Sound and 
M'Clintock Channel-both were severely reduced in the past and are 
recovering under conservative harvest limits); six populations are 
stable (Northern Beaufort Sea, Southern Hudson Bay, Davis Strait, 
Lancaster Sound, Gulf of Bothia, Foxe Basin); five populations are 
declining (Southern Beaufort Sea, Norwegian Bay, Western Hudson Bay, 
Kane Basin, Baffin Bay); and six populations are designated as data 
deficient (Barents Sea, Kara Sea, Laptev Sea, Chukchi Sea, Arctic 
Basin, East Greenland) with no estimate of trend. The two populations 
with the most extensive time series of data, Western Hudson Bay and 
Southern Beaufort Sea, are both considered to be declining.
    As previously noted, scientific information assessing this species 
in the foreseeable future is provided later in this final rule.

Polar Bear Ecoregions

    Amstrup et al. (2007, pp. 6-8) grouped the 19 IUCN-recognized polar 
bear populations (Aars et al. 2006, p. 33) into four physiographically 
different functional groups or ``ecoregions'' (Figure 2) in order to 
forecast future polar bear population status on the basis of current 
knowledge of polar bear populations, their relationships to sea ice 
habitat, and predicted changes in sea ice and other environmental 
variables. Amstrup et al. (2007, p. 7) defined the ecoregions ``on the 
basis of observed temporal and spatial patterns of ice formation and 
ablation (melting or evaporation), observations of how polar bears 
respond to those patterns, and how general circulation models (GCMs) 
forecast future ice patterns.''
    The Seasonal Ice Ecoregion includes the Western and Southern Hudson 
Bay populations, as well as the Foxe Basin, Baffin Bay, and Davis 
Strait populations. These 5 IUCN-recognized populations are thought to 
include a total of about 7,200 polar bears (Aars et al. 2006, p. 34-
35). The 5 populations experience sea ice that melts entirely in 
summer, and bears spend extended periods of time on shore.

[[Page 28218]]

[GRAPHIC] [TIFF OMITTED] TR15MY08.003

    The Archipelago Ecoregion, islands and channels of the Canadian 
Arctic, has approximately 5,000 polar bears representing 6 populations 
recognized by the IUCN (Aars et al. 2006, p. 34-35). These populations 
are Kane Basin, Norwegian Bay, Viscount Melville Sound, Lancaster 
Sound, M'Clintock Channel, and the Gulf of Boothia. Much of this region 
is characterized by heavy annual and multi-year ice that fills the 
inter-island channels year round and polar bears remain on the sea ice 
throughout the year.
    The polar basin was split into a Convergent Ecoregion and a 
Divergent Ecoregion, based upon the different patterns of sea ice 
formation, loss (via melt and transport) (Rigor et al. 2002, p. 2,658; 
Rigor and Wallace 2004, p. 4; Maslanik et al. 2007, pp. 1-3; Meier et 
al. 2007, pp. 428-434; Ogi and Wallace 2007, pp. 2-3).
    The Divergent Ecoregion is characterized by extensive formation of 
annual sea ice that is transported toward the Canadian Arctic islands 
and Greenland, or out of the polar basin through Fram Strait. The 
Divergent ecoregion includes the Southern Beaufort, Chukchi, Laptev, 
Kara, and Barents Seas populations, and is thought to contain up to 
9,500 polar bears. In the Divergent Ecoregion, as in the Archipelago 
Ecoregion, polar bears mainly stay on the sea ice year-round.
    The Convergent Ecoregion, composed of the Northern Beaufort Sea, 
Queen Elizabeth Islands (see below), and East Greenland populations, is 
thought to contain approximately 2,200 polar bears. Amstrup et al. 
(2007, p. 7) modified the IUCN-recognized population boundaries (Aars 
et al. 2006, pp. 33,36) of this ecoregion by redefining a Queen 
Elizabeth Islands population and extending the original boundary of 
that population to include northwestern Greenland (see Figure 2). The 
area contained within this boundary is characterized by heavy multi-
year ice, except for a recurring lead system that runs along the Queen 
Elizabeth Islands from the northeastern Beaufort Sea to northern 
Greenland (Stirling 1980, pp. 307-308). The area may contain over 200 
polar bears and some bears from other regions have been recorded moving 
through the area (Durner and Amstrup 1995, p. 339; Lunn et al. 1995, 
pp. 12-13). The Northern Beaufort Sea and Queen Elizabeth Islands 
populations occur in a region of the polar basin that accumulates ice 
(hence, the Convergent Ecoregion) as it is moved from the polar basin 
Divergent Ecoregion, while the East Greenland population occurs in area 
where ice is transported out of the polar basin through the Fram Strait 
(Comiso 2002, pp. 17-18; Rigor and Wallace 2004, p. 3; Belchansky et 
al. 2005, pp. 1-2; Holland et al. 2006, pp. 1-5; Durner et al. 2007, p. 
3; Ogi and Wallace 2007, p. 2; Serreze et al. 2007, pp. 1,533-1536).
    Amstrup et al. (2007) do not incorporate the central Arctic Basin 
population into an ecoregion. This population was defined by the IUCN 
in 2001 (Lunn et al. 2002, p.29) to recognize polar bears that may 
reside outside the territorial jurisdictions of the polar nations. The 
Arctic Basin region is characterized by very deep water, which is known 
to be unproductive (Pomeroy 1997, pp. 6-7). Available data indicate 
that polar bears prefer sea ice over shallow water (less then 300 m 
(984 ft) deep) (Amstrup et

[[Page 28219]]

al. 2000b, p. 962; Amstrup et al. 2004, p. 675; Durner et al. 2007, pp. 
18-19), and it is thought that this preference reflects increased 
hunting opportunities over more productive waters. Also, tracking 
studies indicate that few if any bears are year-round residents of the 
central Arctic Basin, and therefore this relatively unpopulated portion 
of the Arctic was not designated as an ecoregion.

Sea Ice Environment

    As described in detail in the ``Species Biology'' section of this 
rule, above, polar bears are evolutionarily adapted to life on sea ice 
(Stirling 1988, p. 24; Amstrup 2003, p. 587). They need sea ice as a 
platform for hunting, for seasonal movements, for travel to terrestrial 
denning areas, for resting, and for mating (Stirling and Derocher 1993, 
p. 241). Moore and Huntington (in press) classify the polar bear as an 
``ice-obligate'' species because of its reliance on sea ice as a 
platform for resting, breeding, and hunting, while Laidre et al. (in 
press) similarly describe the polar bear as a species that principally 
relies on annual sea ice over the continental shelf and areas toward 
the southern edge of sea ice for foraging. Some polar bears use 
terrestrial habitats seasonally (e.g., for denning or for resting 
during open water periods). Open water is not considered to be an 
essential habitat type for polar bears, because life functions such as 
feeding, reproduction, or resting do not occur in open water. However, 
open water is a fundamental part of the marine system that supports 
seal species, the principal prey of polar bears, and seasonally 
refreezes to form the ice needed by the bears (see ``Open Water 
Habitat'' section for more information). Further, the open water 
interface with sea ice is an important habitat used to a great extent 
by polar bears. In addition, the extent of open water is important 
because vast areas of open water may limit a bear's ability to access 
sea ice or land (see ``Open Water Swimming'' section for more detail). 
Snow cover, both on land and on sea ice, is an important component of 
polar bear habitat in that it provides insulation and cover for young 
polar bears and ringed seals in snow dens or lairs (see ``Maternal 
Denning Habitat'' section for more detail).

Sea Ice Habitat

Overview of Arctic Sea Ice

    According to the Arctic Climate Impact Assessment (ACIA 2005), 
approximately two-thirds of the Arctic is ocean, including the Arctic 
Ocean and its shelf seas plus the Nordic, Labrador, and Bering Seas 
(ACIA 2005, p. 454). Sea ice is the defining characteristic of the 
marine Arctic (ACIA 2005, p. 30). The Arctic sea ice environment is 
highly dynamic and follows annual patterns of expansion and 
contraction. Sea ice is typically at its maximum extent (the term 
``extent'' is formally defined in the ``Observed Changes in Arctic Sea 
Ice'' section) in March and at its minimum extent in September 
(Parkinson et al. 1999, p. 20,840). The two primary forms of sea ice 
are seasonal (or first year) ice and perennial (or multi-year) ice 
(ACIA 2005, p. 30). Seasonal ice is in its first autumn/winter of 
growth or first spring/summer of melt (ACIA 2005, p. 30). It has been 
documented to vary in thickness from a few tenths of a meter near the 
southern margin of the sea ice to 2.5 m (8.2 ft) in the high Arctic at 
the end of winter (ACIA 2005, p. 30), with some ice also that is 
thinner and some limited amount of ice that can be much thicker, 
especially in areas with ridging (C. Parkinson, NASA, in litt. to the 
Service, November 2007). If first-year ice survives the summer melt, it 
becomes multi-year ice. This ice tends to develop a distinctive 
hummocky appearance through thermal weathering, becoming harder and 
almost salt-free over several years (ACIA 2005, p. 30). Sea ice near 
the shore thickens in shallow waters during the winter, and portions 
become grounded. Such ice is known as shore-fast ice, land-fast ice, or 
simply fast ice (ACIA 2005, p. 30). Fast ice is found along much of the 
Siberian coast, the White Sea (an inlet of the Barents Sea), north of 
Greenland, the Canadian Archipelago, Hudson Bay, and north of Alaska 
(ACIA 2005, p. 457).
    Pack ice consists of seasonal (or first-year) and multi-year ice 
that is in constant motion caused by winds and currents (USFWS 1995, 
pp. 7-9). Pack ice is used by polar bears for traveling, feeding, and 
denning, and it is the primary summer habitat for polar bears, 
including the Southern Beaufort Sea and Chukchi Sea populations, as 
first year ice retreats and melts with the onset of spring (see ``Polar 
Bear-Sea Ice Habitat Relationships'' section for more detail on ice 
types used by polar bears). Movements of sea ice are related to winds, 
currents, and seasonal temperature fluctuations that in turn promote 
its formation and degradation. Ice flow in the Arctic often includes a 
clockwise circulation of sea ice within the Canada Basin and a 
transpolar drift stream that carries sea ice from the Siberian shelves 
to the Barents Sea and Fram Strait.
    Sea ice is an important component of the Arctic climate system 
(ACIA 2005, p. 456). It is an effective insulator between the oceans 
and the atmosphere. It also strongly reduces the ocean-atmosphere heat 
exchange and reduces wind stirring of the ocean. In contrast to the 
dark ocean, pond-free sea ice (i.e., sea ice that has no meltwater 
ponds on the surface) reflects most of the solar radiation back into 
space. Together with snow cover, sea ice greatly restricts the 
penetration of light into the sea, and it also provides a surface for 
particle and snow deposition (ACIA 2005, p. 456). Its effects can 
extend far south of the Arctic, perhaps globally, e.g., through 
impacting deepwater formation that influences global ocean circulation 
(ACIA 2005, p. 32).
    Sea ice is also an important environmental factor in Arctic marine 
ecosystems. ``Several physical factors combine to make arctic marine 
systems unique including: a very high proportion of continental shelves 
and shallow water; a dramatic seasonality and overall low level of 
sunlight; extremely low water temperatures; presence of extensive areas 
of multi-year and seasonal sea-ice cover; and a strong influence from 
freshwater, coming from rivers and ice melt'' (ACIA 2005, p. 454). Ice 
cover is an important physical characteristic, affecting heat exchange 
between water and atmosphere, and light penetration to organisms in the 
water below. It also helps determine the depth of the mixed layer, and 
provides a biological habitat above, within, and beneath the ice. The 
marginal ice zone, at the edge of the pack ice, is important for 
plankton production and plankton-feeding fish (ACIA 2005, p. 456)

Observed Changes in Arctic Sea Ice

    Sea ice is the defining physical characteristic of the marine 
Arctic environment and has a strong seasonal cycle (ACIA 2005, p. 30). 
There is considerable inter-annual variability both in the maximum and 
minimum extent of sea ice, but it is typically at its maximum extent in 
March and minimum extent in September (Parkinson et al. 1999, p. 20, 
840). In addition, there are decadal and inter-decadal fluctuations to 
sea ice extent due to changes in atmospheric pressure patterns and 
their associated winds, river runoff, and influx of Atlantic and 
Pacific waters (Gloersen 1995, p. 505; Mysak and Manak 1989, p. 402; 
Kwok 2000, p. 776; Parkinson 2000b, p. 10; Polyakov et al. 2003, p. 
2,080; Rigor et al. 2002, p. 2,660; Zakharov 1994, p. 42). Sea ice 
``extent'' is normally defined as the area of the ocean with at least 
15 percent ice coverage, and sea ice ``area'' is normally defined as 
the integral sum of areas actually covered by sea ice

[[Page 28220]]

(Parkinson et al. 1999). ``Area'' is a more precise measure of the 
areal extent of the ice itself, since it takes into account the 
fraction of leads (linear openings or cracks in the ice) within the 
ice, but ``extent'' is more reliably observed (Zhang and Walsh 2006). 
The following sections discuss specific aspects of observed sea ice 
changes of relevance to polar bears.

Summer Sea Ice

    Summer sea ice area and sea ice extent are important factors for 
polar bear survival (see ``Polar Bear-Sea Ice Habitat Relationships'' 
section). Seasonal or first-year ice that remains at the end of the 
summer melt becomes multi-year (or perennial) ice. The amount and 
thickness of perennial ice is an important determinant of future sea 
ice conditions (i.e., gain or loss of ice) (Holland and Bitz 2003; Bitz 
and Roe 2004). Much of the following discussion focuses on summer sea 
ice extent (rather than area).
    Prior to the early 1970s, ice extent was measured with visible-band 
satellite imagery and aircraft and ship reports. With the advent of 
passive microwave (PM) satellite observations, beginning in December 
1972 with a single channel instrument and then more reliably in October 
1978 with a multi-channel instrument, we have a more accurate, 3-decade 
record of changes in summer sea ice extent and area. Over the period 
since October 1978, successive papers have documented an overall 
downward trend in Arctic sea ice extent and area. For example, 
Parkinson et al. (1999) calculated Arctic sea ice extents, areas, and 
trends for late 1978 through the end of 1996, and documented a decrease 
in summer sea ice extent of 4.5 percent per decade. Comiso (2002) 
documented a decline of September minimum sea ice extent of 6.7 percent 
plus or minus 2.4 percent per decade from 1981 through 2000. Stroeve et 
al. (2005) analyzed data from 1978 through 2004, and calculated a 
decline in minimum sea ice extent of 7.7 percent plus or minus 3 
percent per decade. Comiso (2006, p. 72) included observations for 
2005, and calculated a per-decade decline in minimum sea ice extent of 
up to 9.8 percent plus or minus 1.5 percent. Most recently, Stroeve et 
al. (2007, pp. 1-5) estimated a 9.1 percent per-decade decline in 
September sea ice extent for 1979-2006, while Serreze et al. (2007, pp. 
1,533-1,536) calculated a per-decade decline of 8.6 percent plus or 
minus 2.9 percent for the same parameter over the same time period. 
These estimates differ only because Serreze et al. (2007, pp. 1,533-
1,536) normalized the trend by the 1979-2000 mean, in order to be 
consistent with how the National Snow and Ice Data Center \1\ 
calculates its estimates (J. Stroeve, in litt. to the Service, November 
2007). This decline translates to a decrease of 60,421 sq km (23,328 sq 
mi) per year (NSIDC Press Release, October 3, 2006).
---------------------------------------------------------------------------

    \1\ The NSIDC is part of the University of Colorado Cooperative 
Institute for Research in Environmental Sciences (CIRES), is funded 
largely by the National Aeronautics and Space Administration (NASA), 
and is affiliated with the National Oceanic and Atmospheric 
Administration (NOAA) National Geophysical Data Center through a 
cooperative agreement. A large part of NSIDC is the Polar 
Distributed Active Archive Center, which is funded by NASA.
---------------------------------------------------------------------------

    The rate of decrease in September sea ice extent appears to have 
accelerated in recent years, although the acceleration to date has not 
been shown to be statistically significant (C. Bitz, in litt. to the 
Service, November 2007). The years 2002 through 2007 all exceeded 
previous record lows (Stroeve et al. 2005; Comiso 2006; Stroeve et al. 
2007, pp. 1-5; Serreze et al. 2007, pp. 1,533-1,536; NSIDC Press 
Release, October 1, 2007), and 2002, 2005, and 2007 had successively 
lower record-breaking minimum extent values (http://www.nsidc.org). The 
2005 absolute minimum sea ice extent of 5.32 million sq km (2.05 
million sq mi) for the entire Arctic Ocean was a 21 percent reduction 
compared to the mean for 1979 to 2000 (Serreze et al. 2007, pp. 1,533-
1,536). Nghiem et al. (2006) documented an almost 50 percent reduction 
in perennial (multi-year) sea ice extent in the East Arctic Ocean (0 to 
180 degrees east longitude) between 2004 and 2005, while the West 
Arctic Ocean (0 and 180 degrees west longitude) had a slight gain 
during the same period, followed by an almost 70 percent decline from 
October 2005 to April 2006. Nghiem et al. (2007) found that the extent 
of perennial sea ice was significantly reduced by 23 percent between 
March 2005 and March 2007 as observed by the QuikSCAT/SeaWinds 
satellite scatterometer. Nghiem et al. (2006) presaged the extensive 
decline in September sea ice extent in 2007 when they stated: ``With 
the East Arctic Ocean dominated by seasonal ice, a strong summer melt 
may open a vast ice-free region with a possible record minimum ice 
extent largely confined to the West Arctic Ocean.''
    Arctic sea ice declined rapidly to unprecedented low extents in 
summer 2007 (Stroeve et al. 2008). On August 16-17, 2007, Arctic sea 
ice surpassed the previous single-day (absolute minimum) record for the 
lowest extent ever measured by satellite (set in 2005), and the sea ice 
was still melting (NSIDC Arctic Sea Ice News, August 17, 2007). On 
September 16, 2007 (the end of the melt season), the 5-day running mean 
sea ice extent reported by NSIDC was 4.13 million sq km (1.59 million 
sq mi), an all-time record low. This was 23 percent lower than the 
previous record minimum reported in 2005 (see Figure 3) (Stroeve et al. 
2008) and 39 percent below the long-term average from 1979 to 2000 (see 
Figure 4) (NSIDC Press Release, October 1, 2007). Arctic sea ice 
receded so much in 2007 that the so-called ``Northwest Passage'' 
through the straits of the Canadian Arctic Archipelago completely 
opened for the first time in recorded history (NSIDC Press Release, 
October 1, 2007). Based on a time-series of data from the Hadley 
Centre, extending back before the advent of the PM satellite era, sea 
ice extent in mid-September 2007 may have fallen by as much as 50 
percent from the 1950s to 1970s (Stroeve et al. 2008). The minimum 
September Arctic sea ice extent since 1979 is now declining at a rate 
of approximately 10.7 percent per decade (Stroeve et al. 2008), or 
approximately 72,000 sq km (28,000 sq mi) per year (see Figure 3 below) 
(NSIDC Press Release, October 1, 2007).

[[Page 28221]]

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[GRAPHIC] [TIFF OMITTED] TR15MY08.005


[[Page 28222]]


    In August 2007, Arctic sea ice area (recall that ``area'' is a 
different metric than ``extent'' used in the preceding paragraphs) also 
broke the record for the minimum Arctic sea ice area in the period 
since the satellite PM record began in the 1970s (University of 
Illinois Polar Research Group 2007 web site; http://
arctic.atmos.uiuc.edu/cryosphere/). The new record was set a full month 
before the historic summer minimum typically occurs, and the record 
minimum continued to decrease over the next several weeks (University 
of Illinois Polar Research Group 2007 web site). The Arctic sea ice 
area reached an historic minimum of 2.92 million sq km (1.13 million sq 
mi) on September 16, 2007, which was 27 percent lower than the previous 
(2005) record Arctic ice minimum area (University of Illinois Polar 
Research Group 2007 web site). In previous record sea ice minimum 
years, ice area anomalies were confined to certain sectors (North 
Atlantic, Beaufort/Bering Sea, etc.), but the character of the 2007 
summer sea ice melt was unique in that it was both dramatic and covered 
the entire Arctic Basin. Atlantic, Pacific, and the central Arctic 
sectors all showed large negative sea ice area anomalies (University of 
Illinois Polar Research Group 2007 web site).
    Two key factors contributed to the September 2007 extreme sea ice 
minimum: thinning of the pack ice in recent decades and an unusual 
pattern of atmospheric circulation (Stroeve et al. 2008). Spring 2007 
started out with less ice and thinner ice than normal. Ice thickness 
estimates from the ICESat satellite laser altimeter instrument 
indicated ice thicknesses over the Arctic Basin in March 2007 of only 1 
to 2 m (3.3 to 6.6 ft) (J. Stroeve, in litt. to the Service, November 
2007). Thinner ice takes less energy to melt than thicker ice, so the 
stage was set for low levels of sea ice in summer 2007 (J. Stroeve, 
quoted in NSIDC Press Release, October 1, 2007). In general, older sea 
ice is thicker than younger ice. Maslanik et al. (2007) used an ice-
tracking computer algorithm to estimate changes in the distribution of 
multi-year sea ice of various ages. They estimated: that the area of 
sea ice at least 5 years old decreased by 56 percent between 1985 and 
2007; that ice at least 7 years old decreased from 21 percent of the 
ice cover in 1988 to 5 percent in 2007; and that sea ice at least 9 
years old essentially disappeared from the central Arctic Basin. 
Maslanik et al. (2007) attributed thinning in recent decades to both 
ocean-atmospheric circulation patterns and warmer temperatures. Loss of 
older ice in the late 1980s to mid-1990s was accentuated by the 
positive phase of the Arctic Oscillation during that period, leading to 
increased ice export through the Fram Strait (Stroeve et al. 2008). 
Another significant change since the late 1990s has been the role of 
the Beaufort Gyre, ``the dominant wind and ice drift regime in the 
central Arctic'' (Maslanik et al. 2007). ``Since the late 1990s * * * 
ice typically has not survived the transit through the southern portion 
of the Beaufort Gyre,'' thus not allowing the ice to circulate in its 
formerly typical clockwise pattern for years while it aged and 
thickened (Maslanik et al. 2007). Temperature changes in the Arctic are 
discussed in detail in the section entitled ``Air and Sea 
Temperatures.''
    Another factor that contributed to the sea ice loss in the summer 
of 2007 was an unusual atmospheric pattern, with persistent high 
atmospheric pressures over the central Arctic Ocean and lower pressures 
over Siberia (Stroeve et al. 2008). The skies were fairly clear under 
the high-pressure cell, promoting strong melt. At the same time, the 
pattern of winds pumped warm air into the region. While the warm winds 
fostered further melt, they also helped push ice away from the Siberian 
shore.

Winter Sea Ice

    The maximum extent of Arctic winter sea ice cover, as documented 
with PM satellite data, has been declining at a lower rate than summer 
sea ice (Parkinson et al. 1999, p. 20,840; Richter-Menge et al. 2006, 
p. 16), but that rate appears to have accelerated in recent years. 
Parkinson and Cavalieri (2002, p. 441) reported that winter sea ice 
cover declined at a rate of 1.8 percent plus or minus 0.6 percent per 
decade for the period 1979 through 1999. More recently, Richter-Menge 
et al. (2006, p. 16) reported that March sea ice extent was declining 
at a rate of 2 percent per decade based on data from 1979-2005, Comiso 
(2006) calculated a decline of 1.9 plus or minus 0.5 percent per decade 
for 1979-2006, and J. Stroeve (in litt. to the Service, November 2007) 
calculated a decline of 2.5 percent per decade, also for 1979-2005.
    In 2005 and 2006, winter maximum sea ice extent set record lows for 
the era of PM satellite monitoring (October 1978 to present). The 2005 
record low winter maximum preceded the then-record low summer minimum 
during the same year, while winter sea ice extent in 2006 was even 
lower than that of 2005 (Comiso 2006). The winter 2007 Arctic sea ice 
maximum was the second-lowest in the satellite record, narrowly missing 
the March 2006 record (NSIDC Press Release, April 4, 2007). J. Stroeve 
(in litt. to the Service, November 2007) calculated a rate of decline 
of 3.0 plus or minus 0.8 percent per decade for 1979-2007.

Cumulative Annual Sea Ice

    Parkinson et al. (1999) documented that Arctic sea ice extent for 
all seasons (i.e., annual sea ice extent) declined at a rate of 2.8 
percent per decade for the period November 1978 through December 1996, 
with considerable regional variation (the greatest absolute declines 
were documented for the Kara and Barents Sea, followed by the Seas of 
Okhotsk and Japan, the Arctic Ocean, Greenland Sea, Hudson Bay, and 
Canadian Archipelago; percentage declines were greatest in the Seas of 
Okhotsk and Japan, at 20.1 percent per decade, and the Kara and Barents 
Seas, at 10.5 percent per decade). More recently, Comiso and Nishio 
(2008) utilized satellite data gathered from late 1978 into 2006, and 
estimated an annual rate decline of 3.4 percent plus or minus 0.2 
percent per decade. They also found regions where higher negative 
trends were apparent, including the Greenland Sea (8.0 percent per 
decade), the Kara/Barents Seas (7.2 percent per decade), the Okhotsk 
Sea (8.7 percent per decade), and Baffin Bay/Labrador Sea (8.6 percent 
per decade). Comiso et al. (2008) included satellite data from 1979 
through early September 2007 in their analyses. They found that the 
trend of the entire sea ice cover (seasonal and perennial sea ice) has 
accelerated from a decline of about 3 percent per decade in 1979-1996 
to a decline of about 10 percent per decade in the last 10 years. 
Statistically significant negative trends in Arctic sea ice extent now 
occur n all calendar months (Serreze et al. 2007, pp. 1,533-1,536).

Sea Ice Thickness

    Sea ice thickness is an important element of the Arctic climate 
system. The sea ice thickness distribution influences the sea ice mass 
budget and ice/ocean/atmosphere exchange (Holland et al. 2006a). Sea 
ice thickness has primarily been measured with upward-looking sonar on 
submarines and on moored buoys; this sonar provides information on ice 
draft, the component of the total ice thickness (about 90 percent) that 
projects below the water surface (Serreze et al. 2007, pp. 1,533-
1,536). Rothrock et al. (1999, p. 3,469) compared sea-ice draft data 
acquired on submarine cruises between 1993 and 1997 with similar data 
acquired between 1958 and 1976, and concluded that the mean sea-ice 
draft at

[[Page 28223]]

the end of the melt season (i.e., perennial or multi-year ice) had 
decreased by about 1.3 m (4.3 ft) in most of the deep water portion of 
the Arctic Ocean. One limitation of submarine sonar data is sparse 
sampling, which complicates interpretation of the results (Serreze et 
al. 2007, pp. 1,533-1,536). Holloway and Sou (2002) noted concerns 
regarding the temporal and spatial sampling of ice thickness data used 
in Rothrock et al. (1999), and concluded from their modeling exercise 
that ``a robust characterization over the half-century time series 
consists of increasing volume to the mid-1960s, decadal variability 
without significant trend from the mid-1960s to the mid-1980s, then a 
loss of volume from the mid-1980s to the mid-1990s.'' Rothrock et al. 
(2003, p. 28) conducted further analysis of the submarine-acquired data 
in conjunction with model simulations and review of other modeling 
studies, and concluded that all models agree that sea ice thickness 
decreased between 0.6 and 0.9 m (2 and 3 ft) from 1987 to 1996. Their 
model showed a modest recovery in thickness from 1996 to 1999. Yu et 
al. (2004, p. 11) further analyzed submarine sonar data and concluded 
that total ice volume decreased by 32 percent from the 1960s and 1970s 
to the 1990s in the central Arctic Basin.
    Fowler et al. (2004) utilized a new technique for combining 
remotely-sensed sea ice motion and sea ice extent to ``track'' the 
evolution of sea ice in the Arctic region from October 1978 through 
March 2003. Their analysis revealed that the area of the oldest sea ice 
(i.e., sea ice older than 4 years) was decreasing in the Arctic Basin 
and being replaced by younger (first-year) ice. The extent of the older 
ice was retreating to a relatively small area north of the Canadian 
Archipelago, with narrow bands spreading out across the central Arctic 
(Fowler et al. 2004, pp. 71-74). More recently, Maslanik et al. (2007) 
documented a substantial decline in the percent coverage of old ice 
within the central Arctic Basin. In 1987, 57 percent of the ice pack in 
this area was 5 or more years old, with 25 percent of this ice at least 
9 years old. By 2007, only 7 percent of the ice pack in this area was 5 
or more years old, and ice at least 9 years old had completely 
disappeared. This is significant because older ice is thicker than 
younger ice, and therefore requires more energy to melt. The reduction 
in the older ice types in the Arctic Basin translates into a reduction 
in mean ice thickness from 2.6 m in March 1987 to 2.0 m in March 2007 
(Stroeve et al. 2008).
    Kwok (2007, p. 1) studied six annual cycles of perennial (multi-
year) Arctic sea ice coverage, from 2000 to 2006, and found that after 
the 2005 summer melt, only about four percent of the thin, first-year 
ice that formed the previous winter survived to replenish the multi-
year sea ice area (NASA/JPL News Release, April 3, 2007). That was the 
smallest amount of multi-year ice replenishment documented in the 
study, and resulted in perennial ice coverage in January 2006 that was 
14 percent smaller than in January 2005. Kwok (2007, p. 1) attributed 
the decline to unusually high amounts of ice exported from the Arctic 
in the summer of 2005, and also to an unusually warm winter and summer 
prior to September 2005.

Length of the Melt Period

    The length of the melt period (or season) affects sea ice cover 
(extent and area) and sea ice thickness (Hakkinen and Mellor 1990; 
Laxon et al. 2003). In general terms, earlier onset of melt and 
lengthening of the melt season result in decreased total sea ice cover 
at the end of summer (i.e., the end of the melt season) (Stroeve et al. 
2005, p. 3). Belchansky et al. (2004, p. 1) found that changes in 
multi-year ice area measured in January were significantly correlated 
with duration of the intervening melt season. Kwok found a correlation 
between the number of freezing and melting temperature days and area of 
multi-year sea ice replenished in a year (NASA/JPL News Release, April 
3, 2007).
    Comiso (2003, p. 3,506), using data for the period 1981-2001, 
calculated that the Arctic sea ice melt season was increasing at a rate 
of 10 to 17 days per decade during that period. Including additional 
years in his analyses, Comiso (2005, p. 50) subsequently found that the 
length of the melt season was increasing at a rate of approximately 
13.1 days per decade. Stroeve et al. (2006 pp. 367-374) analyzed melt 
season duration and melt onset and freeze-up dates from satellite 
passive microwave data for the period 1979 through 2005, and found that 
the Arctic is experiencing an overall lengthening of the melt season at 
a rate of about 2 weeks per decade.
    The NSIDC documented a trend of earlier onset of the melt season 
for the years 2002 through 2005; the melt season arrived earliest in 
2005, occurring approximately 17 days before the mean date of onset of 
the melt season (NSIDC 2005, p. 6). In 2007, in addition to the record-
breaking September minimum sea ice extent, NSIDC scientists noted that 
the date of the lowest sea ice extent shifted to later in the year 
(NSIDC Press Release, October 1, 2007). The minimum sea ice extent 
occurred on September 16, 2007; from 1979 to 2000, the minimum usually 
occurred on September 12. This is consistent with a lengthening of the 
melt season.
    Parkinson (2000) documented a clear decrease in the length of the 
sea ice season throughout the Greenland Sea, Kara and Barents Seas, Sea 
of Okhotsk, and most of the central Arctic Basin. On the basis of 
observational data, Stirling et al. (cited in Derocher et al. 2004) 
calculated that break-up of the annual ice in Western Hudson Bay is 
occurring approximately 2.5 weeks earlier than it did 30 years ago. 
Consistent with these results, Stirling and Parkinson (2006) analyzed 
satellite data for Western Hudson Bay for November 1978 through 2004 
and found that, on average, ice break-up has been occurring about 7 to 
8 days earlier per decade. Stirling and Parkinson (2006) also 
investigated ice break-up in Foxe Basin, Baffin Bay, Davis Strait, and 
Eastern Hudson Bay in Canada. They found that ice break-up in Foxe 
Basin has been occurring about 6 days earlier each decade and ice 
break-up in Baffin Bay has been occurring 6 to 7 days earlier per 
decade. Long-term results from Davis Strait were not conclusive, 
particularly because the maximum percentage of ice cover in Davis 
Strait varies considerably more between years than in western Hudson 
Bay, Foxe Basin, or Baffin Bay. Conversely, Stirling and Parkinson 
(2006) documented a negative short-term trend from 1991 to 2004 in 
Davis Strait. In eastern Hudson Bay, there was not a statistically 
significant trend toward earlier break-up.

Understanding Observed Declines in Arctic Sea Ice

    The observed declines in the extent of Arctic sea ice are well 
documented, and more pronounced in the summer than in the winter. There 
is also evidence that the rate of sea ice decline is increasing. This 
decline in sea ice is of great importance to our determination 
regarding the status of the polar bear. Understanding the causes of the 
decline is also of great importance in assessing what the future might 
hold for Arctic sea ice, and, thus, considerable effort has been 
devoted to enhancing our understanding. This understanding will inform 
our determination regarding the status of the polar bear within the 
foreseeable future as determined in this rule.
    In general terms, sea ice declines can be attributed to three 
conflated factors: warming, atmospheric changes (including circulation 
and clouds), and changes in oceanic circulation (Stroeve and Maslowski 
2007). Serreze et al.

[[Page 28224]]

(2007, pp. 1,533-1,536) characterize the decline of sea ice as a 
conflation of thermodynamic and dynamic processes: ``Thermodynamic 
processes involve changes in surface air temperature (SAT), radiative 
fluxes, and ocean conditions. Dynamic processes involve changes in ice 
circulation in response to winds and ocean currents.'' In the following 
paragraphs we discuss warming, changes in the atmosphere, and changes 
in oceanic circulation, followed by a synthesis. It is critically 
important that we understand the dynamic forces that govern all aspects 
of sea ice given the polar bear's almost exclusive reliance on this 
habitat.

Air and Sea Temperatures

    Estimated rates of change in surface air temperature (SAT) over the 
Arctic Ocean over the past 100 or more years vary depending on the time 
period, season, and data source used (Serreze et al. 2007, pp. 1,533-
1,536). Serreze et al. (2007, pp. 1,533-1,536) note that, although 
natural variability plays a large role in SAT variations, the overall 
pattern has been one of recent warming.
    Polyakov et al. (2003) compiled SAT trends for the maritime Arctic 
for the period 1875 through 2000 (as measured by coastal land stations, 
drifting ice stations, and Russian North Pole stations) and found that, 
since 1875, the Arctic has warmed by 1.2 degrees Celsius (C), an 
average warming of 0.095 degree C per decade over the entire period, 
and an average warming of 0.05  0.04 degree C per decade 
during the 20th century. The increases were greatest in winter and 
spring, and there were two relative maxima during the century (the late 
1930s and the 1990s). The ACIA analyzed land-surface air temperature 
trends as recorded in the Global Historical Climatology Network (GHCN) 
database, and documented a statistically significant warming trend of 
0.09 degree C per decade during the period 1900-2003 (ACIA 2005, p. 
35). For periods since 1950, the rate of temperature increase in the 
marine Arctic documented in the GHCN (ACIA 2005, p. 35) is similar to 
the increase noted by Polyakov et al. (2003).
    Rigor et al. (2000) documented positive trends in SAT for 1979 to 
1997; the trends were greatest and most widespread in spring. Comiso 
(2006) analyzed data from the Advanced Very High Resolution Radiometer 
(AVHRR) for 1981 to 2005, and documented an overall warming trend of 
0.54  0.11 degrees C per decade over sea ice. Comiso noted 
that ``it is apparent that significant warming has been occurring in 
the Arctic but not uniformly from one region to another.'' The Serreze 
et al. (2007, pp. 1,533-1,536) assessment of data sets from the 
National Centers for Environmental Prediction and the National Center 
for Atmospheric Research indicated strong surface and low-level warming 
for the period 2000 to 2006 relative to 1979 to 1999, consistent with 
the observed sea ice losses.
    Stroeve and Maslowski (2007) noted that anomalously high 
temperatures have been consistent throughout the Arctic since 2002. 
Further support for warming comes from studies indicating earlier onset 
of spring melt and lengthening of the melt season (e.g., Stroeve et al. 
2006, pp. 367-374), and data that point to increased downward radiation 
toward the surface, which is linked to increased cloud cover and water 
vapor (Francis and Hunter 2006, cited in Serreze et al. 2007, pp. 
1,533-1,536).
    According to the IPCC AR4 (IPCC 2007, p. 36), 11 of 12 years from 
1995 to 2006 (the exception being 1996) were among the 12 warmest years 
on record since 1850; 2005 and 1998 were the warmest two years in the 
instrumental global surface air temperature record since 1850. Surface 
temperatures in 1998 were enhanced by the major 1997-1998 El 
Ni[ntilde]o but no such large-scale atmospheric anomaly was present in 
2005. The IPCC AR4 concludes that the ``warming in the last 30 years is 
widespread over the globe, and is greatest at higher northern latitudes 
(IPCC 2007, p. 37).'' Further, the IPCC AR4 states that greatest 
warming has occurred in the northern hemisphere winter (December, 
January, February) and spring (March, April, May). Average Arctic 
temperatures have been increasing at almost twice the rate of the rest 
of the world in the past 100 years. However, Arctic temperatures are 
highly variable. A slightly longer Arctic warm period, almost as warm 
as the present, was observed from 1925 to 1945, but its geographical 
distribution appears to have been different from the recent warming 
since its extent was not global.
    Finally, Comiso (2005, p. 43) determined that for each 1 degree C 
increase in surface temperature (global average) there is a 
corresponding decrease in perennial sea ice cover of about 1.48 million 
sq km (0.57 million sq mi).

Changes in Atmospheric Circulation

    Links have also been established between sea ice loss and changes 
in sea ice circulation associated with the behavior of key atmospheric 
patterns, including the Arctic Oscillation (AO; also called the 
Northern Annular Mode (NAM)) (e.g., Thompson and Wallace 2000; 
Limpasuvan and Hartmann 2000) and the more regional, but closely 
related North Atlantic Oscillation (NAO; e.g., Hurrell 1995). First 
described in 1998 by atmospheric scientists David Thompson and John 
Wallace, the Arctic Oscillation is a measure of air-pressure and wind 
patterns in the Arctic. In the so-called ``positive phase'' (or high 
phase), air pressure over the Arctic is lower than normal and strong 
westerly winds occur in the upper atmosphere at high latitudes. In the 
so-called ``negative phase'' (or low phase), air pressure over the 
Arctic is higher than normal, and the westerly winds are weaker.
    Rigor et al. (2002, cited in Stroeve and Maslowski 2007) showed 
that when the AO is positive in winter, altered wind patterns result in 
more offshore ice motion and ice divergence along the Siberian and 
Alaskan coastlines; this leads to the production of more extensive 
areas of thinner, first-year ice that requires less energy to melt. 
Rigor and Wallace (2004, cited in Deweaver 2007) suggested that the 
recent reduction in September ice extent is a delayed reaction to the 
export of multi-year ice during the high-AO winters of 1989 through 
1995. They estimated that the recovery of sea ice to its normal extent 
should take between 10 and 15 years. However, Rigor and Wallace (2004) 
estimated that the combined winter and summer AO-indices can explain 
less than 20 percent of the variance in summer sea ice extent in the 
western Arctic Ocean where most of the recent reductions in sea ice 
cover have occurred. The notion that AO-related export of multi-year 
ice from the Arctic is the principal cause of observed declines in 
Arctic sea ice extent has been questioned by several authors, including 
Overland and Wang (2005), Comiso (2006), Stroeve and Maslowski (2007), 
Serreze et al. (2007, pp. 1,533-1,536), and Stroeve et al. (2008) who 
note that sea ice extent has not recovered despite the return of the AO 
to a more neutral state since the late 1990s. Overland and Wang (2005) 
noted that the return of the AO to a more neutral state was accompanied 
by southerly wind anomalies from 2000-2005 which contributed to 
reducing the ice cover over time and ``conditioning'' the Arctic for 
the extensive summer sea ice reduction in 2007 (J. Overland NOAA, pers. 
comm. to FWS, 2007). Maslanik et al. (2007) reached a similar 
conclusion that despite the return of the AO to a more neutral state, 
wind and ice transport patterns that favor reduced ice cover in the 
western and central Arctic continued to play a role in the loss of sea 
ice in those regions. Maslanik et al.

[[Page 28225]]

(2007) believe that circulation patterns such as the Beaufort Gyre, 
which in the past helped to maintain old ice in the Arctic Basin, are 
now acting to export ice, as the multi-year ice is no longer surviving 
the transport through the Chukchi and East Siberian Seas.
    According to DeWeaver (2007): ``Recognizing the need to incorporate 
AO variability into considerations of recent sea ice decline, Lindsay 
and Zhang (2005) used an ocean-sea ice model to reconstruct the sea ice 
behavior of the satellite era and identify separate contributions from 
ice motion and thermodynamics. Similar experiments with similar results 
were also reported by Rothrock and Zhang (2005) and Koberle and Gerdes 
(2003).'' Rothrock and Zhang (2005, cited in Serreze et al. 2007, pp. 
1,533-1,536), using a coupled ice-ocean model, argued that although 
wind forcing was the dominant driver of declining ice thickness and 
volume from the late 1980s through the mid-1990s, the ice response to 
generally rising air temperatures was more steadily downward over the 
study period (1948 to 1999). ``In other words, without wind forcing, 
there would still have been a downward trend in ice extent, albeit 
smaller than that observed'' (Serreze et al. 2007, pp. 1,533-1,536). 
Lindsay and Zhang (2005, cited in Serreze et al. 2007, pp. 1,533-1,536) 
came to similar conclusions in their modeling study: ``Rising air 
temperature reduced ice thickness, but changes in circulation also 
flushed some of the thicker ice out of the Arctic, leading to more open 
water in summer and stronger absorption of solar radiation in the upper 
(shallower depths of the) ocean. With more heat in the ocean, thinner 
ice grows in autumn and winter.''

Changes in Oceanic Circulation

    According to Serreze et al. (2007, pp. 1,533-1,536), it appears 
that changes in ocean heat transport have played a role in declining 
Arctic sea ice extent in recent years. Warm Atlantic waters enter the 
Arctic Ocean through the Fram Strait and Barents Sea (Serreze et al. 
2007, pp. 1,533-1,536). This water is denser than colder, fresher (less 
dense) Arctic surface waters, and sinks (subducts) to form an 
intermediate layer between depths of 100 and 800 m (328 and 2,624 ft) 
(Quadfasel et al. 1991) with a core temperature significantly above 
freezing (DeWeaver 2007; Serreze et al. 2007, pp. 1,533-1,536). 
Hydrographic data show increased import of Atlantic-derived waters in 
the early to mid-1990s and warming of this inflow (Dickson et al. 2000; 
Visbeck et al. 2002). This trend has continued, characterized by 
pronounced pulses of warm inflow (Serreze et al. 2007, pp. 1,533-
1,536). For example, strong ocean warming in the Eurasian Basin of the 
Arctic Ocean in 2004 can be traced to a pulse entering the Norwegian 
Sea in 1997-1998 and passing through Fram Strait in 1999 (Polyakov et 
al. 2007). The anomaly found in 2004 was tracked through the Arctic 
system and took about 1.5 years to travel from the Norwegian Sea to the 
Fram Strait region, and an additional 4.5-5 years to reach the Laptev 
Sea slope (Polyakov et al. 2007).
    Polyakov et al. (2007) reported that mooring-based records and 
oceanographic surveys suggest that a new pulse of anomalously warm 
water entered the Arctic Ocean in 2004. Further Polyakov et al. (2007) 
stated that: ``combined with data from the previous warm anomaly * * * 
this information provides evidence that the Nansen Basin of the Arctic 
Ocean entered a new warm state. These two warm anomalies are 
progressing towards the Arctic Ocean interior * * * but still have not 
reached the North Pole observational site. Thus, observations suggest 
that the new anomalies will soon enter the central Arctic Ocean, 
leading to further warming of the polar basin. More recent data, from 
summer 2005, showed another warm anomaly set to enter the Arctic Ocean 
through the Fram Strait (Walczowski and Piechura 2006). These inflows 
may promote ice melt and discourage ice growth along the Atlantic ice 
margin (Serreze et al. 2007, pp. 1,533-1,536).
    Once Atlantic water enters the Arctic Ocean, the cold halocline 
layer (CHL) separating the Atlantic and surface waters largely 
insulates the ice from the heat of the Atlantic layer. Observations 
suggest a retreat of the CHL in the Eurasian basin in the 1990s (Steele 
and Boyd 1998, cited in Serreze et al. 2007, pp. 1,533-1,536). This 
likely increased Atlantic layer heat loss and ice-ocean heat exchange 
(Serreze et al. 2007, pp. 1,533-1,536), which would serve to erode the 
edge of the sea ice on a year-round basis (C. Bitz, in litt. to the 
Service, November 2007). Partial recovery of the CHL has been observed 
since 1998 (Boyd et al. 2002, cited in Serreze et al. 2007, pp. 1,533-
1,536), and future behavior of the CHL is an uncertainty in projections 
of future sea ice loss (Serreze et al. 2007, pp. 1,533-1,536).

Synthesis

    From the previous discussion, surface air temperature warming, 
changes in atmospheric circulation, and changes in oceanic circulation 
have all played a role in observed declines of Arctic sea ice extent in 
recent years.
    According to DeWeaver (2007): ``Lindsay and Zhang (2005) propose a 
three-part explanation of sea ice decline,'' which incorporates both 
natural AO variability and warming climate. In their explanation, a 
warming climate preconditions the ice for decline as warmer winters 
thin the ice, but the loss of ice extent is triggered by natural 
variability such as flushing by the AO. Sea ice loss continues after 
the flushing because of the sea-ice albedo feedback mechanism which 
warms the sea even further. In recent years, flushing of sea ice has 
continued through other mechanisms despite a relaxation of the AO since 
the late 1990s. The sea-ice albedo feedback effect is the result of a 
reduction in the extent of brighter, more reflective sea ice or snow, 
which reflects solar energy back into the atmosphere, and a 
corresponding increase in the extent of darker, more absorbing water or 
land that absorbs more of the sun's energy. This greater absorption of 
energy causes faster melting, which in turn causes more warming, and 
thus creates a self-reinforcing cycle or feedback loop that becomes 
amplified and accelerates with time. Lindsay and Zhang (2005, p. 4,892) 
suggest that the sea-ice albedo feedback mechanism caused a tipping 
point in Arctic sea ice thinning in the late 1980s, sustaining a 
continual decline in sea ice cover that cannot easily be reversed. 
DeWeaver (2007) believes that the work of Lindsay and Zhang (2005) 
suggests that the observed record of sea ice decline is best 
interpreted as a combination of internal variability and external 
forcing (via GHGs), and raises the possibility that the two factors may 
act in concert rather than as independent agents.
    Evidence that warming resulting from GHG forcing has contributed to 
sea ice declines comes largely from model simulations of the late 20th 
century climate. Serreze et al. (2007, pp. 1,533-1,536) summarized 
results from Holland et al. (2006, pp. 1-5) and Stroeve et al. (2007, 
pp. 1-5), and concluded that the qualitative agreement between model 
results and actual observations of sea ice declines over the PM 
satellite era is strong evidence that there is a forced component to 
the decline. This is because each of these models would be in its own 
phase of natural variability and thus could show an increase or 
decrease in sea ice, but the fact that they all show a decrease 
indicates that more than natural variability is involved, i.e., that 
external forcing by GHGs is a factor. In addition, the model results do 
not show a decline if they are not forced with the observed GHGs. 
Serreze et al.

[[Page 28226]]

(2007, pp. 1,533-1,536) concluded: ``These results provide strong 
evidence that, despite prominent contributions of natural variability 
in the observed record, GHG loading has played a role.''
    Hegerl et al. (2007) used a new approach to reconstruct and 
attribute a 1,500-year temperature record for the Northern Hemisphere. 
Based on their analysis to detect and attribute temperature change over 
that period, they estimated that about a third of the warming in the 
first half of the 20th century can be attributed to anthropogenic GHG 
emissions. In addition, they estimated that the magnitude of the 
anthropogenic signal is consistent with most of the warming in the 
second half of the 20th century being anthropogenic.

Observed Changes in Other Key Parameters

Snow Cover on Ice

    Northern Hemisphere snow cover, as documented by satellite over the 
1966 to 2005 period, decreased in every month except November and 
December, with a step like drop of 5 percent in the annual mean in the 
late 1980s (IPCC 2007, p. 43). April snow cover extent in the Northern 
Hemisphere is strongly correlated with temperature in the region 
between 40 and 60 degrees N Latitude; this reflects the feedback 
between snow and temperature (IPCC 2007, p. 43).
    The presence of snow on sea ice plays an important role in the 
Arctic climate system (Powell et al. 2006). Arctic sea ice is covered 
by snow most of the year, except when the ice first forms and during 
the summer after the snow has melted (Sturm et al. 2006). Warren et al. 
(1999, cited in IPCC 2007 Chapter 4) analyzed 37 years (1954-1991) of 
snow depth and density measurements made at Soviet drifting stations on 
multi-year Arctic sea ice. They found a weak negative trend for all 
months, with the largest being a decrease of 8 cm (3.2 in) (23 percent) 
in May.

Precipitation

    The Arctic Climate Impact Assessment (2005) concluded that 
``overall, it is probable that there was an increase in arctic 
precipitation over the past century.'' An analysis of data in the 
Global Historical Climatology Network (GHCN) database indicated a 
significant positive trend of 1.4 percent per decade (ACIA 2005) for 
the period 1900 through 2003. New et al. (2001, cited in ACIA 2005)) 
used uncorrected records and found that terrestrial precipitation 
averaged over the 60 degree to 80 degree N latitude band exhibited an 
increase of 0.8 percent per decade over the period from 1900 to 1998. 
In general, the greatest increases were observed in autumn and winter 
(Serreze et al. 2000). According to the ACIA (2005) calculations: (1) 
during the Arctic warming in the first half of the 20th century (1900-
1945), precipitation increased by about 2 percent per decade, with 
significant positive trends in Alaska and the Nordic region; (2) during 
the two decades of Arctic cooling (1946-1965), the high-latitude 
precipitation increase was roughly 1 percent per decade, but there were 
large regional contrasts with strongly decreasing values in western 
Alaska, the North Atlantic region, and parts of Russia; and (3) since 
1966, annual precipitation has increased at about the same rate as 
during the first half of the 20th century. The ACIA report (2005) notes 
that these trends are in general agreement with results from a number 
of regional studies (e.g., Karl et al. 1993; Mekis and Hogg 1999; 
Groisman and Rankova 2001; Hanssen-Bauer et al. 1997; F[oslash]rland et 
al. 1997; Hanssen-Bauer and F[oslash]rland 1998). In addition to the 
increase, changes in the characteristics of precipitation have also 
been observed (ACIA 2005). Much of the precipitation increase appears 
to be coming as rain, mostly in winter and to a lesser extent in autumn 
and spring. The increasing winter rains, which fall on top of existing 
snow, cause faster snowmelt. Increased rain in late winter and early 
spring could affect the thermal properties of polar bear dens (Derocher 
et al. 2004), thereby negatively impacting cub survival. Increased rain 
in late winter and early spring may even cause den collapse (Stirling 
and Smith 2004).
    According to the IPCC AR4 (2007, pp. 256-258), distinct upward 
trends in precipitation are evident in many regions at higher 
latitudes, especially from 30 to 85 degrees N latitude. Winter 
precipitation has increased at high latitudes, although uncertainties 
exist because of changes in undercatch, especially as snow changes to 
rain (IPCC 2007, p. 258). Annual precipitation for the circumpolar 
region north of 50 degrees N has increased during the past 50 years by 
approximately 4 percent but this increase has not been homogeneous in 
time and space (Groisman et al. 2003, 2005, both cited in IPCC 2007, p. 
258). According to the IPCC AR4: ``Statistically significant increases 
were documented over Fennoscandia, coastal regions of northern North 
America (Groisman et al. 2005), most of Canada (particularly northern 
regions) up until at least 1995 when the analysis ended (Stone et al. 
2000), the permafrost-free zone of Russia (Groisman and Rankova 2001) 
and the entire Great Russian Plain (Groisman et al. 2005, 2007).'' That 
these trends are real, extending from North America to Europe across 
the North Atlantic, is also supported by evidence of ocean freshening 
caused by increased freshwater run-off (IPCC 2007, p. 258).
    Rain-on-snow events have increased across much of the Arctic. For 
example, over the past 50 years in western Russia, rain-on-snow events 
have increased by 50 percent (ACIA 2005). Groisman et al. (2003) 
considered rain-on-snow trends over a 50-year period (1950-2000) in 
high latitudes in the northern hemisphere and found an increasing trend 
in western Russia and decreases in western Canada (the decreasing 
Canadian trend was attributed to decreasing snow pack). Putkonen and 
Roe (2003), working on Spitsbergen Island, where the occurrence of 
winter rain-on-snow events is controlled by the North Atlantic 
Oscillation, demonstrated that these events are capable of influencing 
mean winter soil temperatures and affecting ungulate survival. These 
authors include the results of a climate modeling effort (using the 
earlier-generation Geophysical Fluid Dynamics Laboratory climate model 
and a 1 percent per year increase in CO2 forcing scenario) 
that predicted a 40 percent increase in the worldwide area of land 
affected by rain-on-snow events from 1980-1989 to 2080-2089. Rennert et 
al. (2008) discussed the significance of rain-on-snow events to 
ungulate survival in the Arctic, and used the dataset European Center 
for Medium-range Weather Forecasting (ECMWF) European 40 Year (ERA40) 
Reanalysis (Uppala et al. 2005) to create a climatology of rain-on-snow 
events for thresholds that impact ungulate populations and permafrost. 
In addition to contributing to increased incidence of polar bear den 
collapse, increased rain-on-snow events during the late winter or early 
spring could also damage or eliminate snow-covered pupping lairs of 
ringed seals (the polar bear's principal prey), thereby increasing pup 
exposure and the risk of hypothermia, and facilitating predation by 
polar bears and Arctic foxes. This could negatively impact ringed seal 
recruitment.

Projected Changes in Arctic Sea Ice

Background

    To make projections about future ecosystem effects that could 
result from climate change, one must first make projections of changes 
in physical

[[Page 28227]]

climate parameters based on changes in external factors that can affect 
the physical climate (ACIA 2005). Climate models use the laws of 
physics to simulate the main components of the climate system (the 
atmosphere, ocean, land surface, and sea ice) (DeWeaver 2007), and make 
projections of future climate scenarios-plausible representations of 
future climate-that are consistent with assumptions about future 
emissions of GHGs and other pollutants (these assumptions are called 
``emissions scenarios'') and with present understanding of the effects 
of increased atmospheric concentrations of these components on the 
climate (ACIA 2005).
    Virtually all climate models use emissions scenarios developed as 
part of the IPCC effort; specifically the IPCC's Special Report on 
Emissions Scenarios (SRES) (IPCC 2000) details a number of plausible 
future emissions scenarios based on assumptions on how societies, 
economies, and energy technologies are likely to evolve. The SRES 
emissions scenarios were built around four narrative storylines that 
describe the possible evolution of the world in the 21st century (ACIA 
2005, p.119). Around these four narrative storylines the SRES 
constructed six scenario groups and 40 different emissions scenarios. 
Six scenarios (A1B, A1T, A1FI, A2, B1, and B2) were then chosen as 
illustrative ``marker'' scenarios. These scenarios have been used to 
estimate a range of future GHG emissions that affect the climate. The 
scenarios are described on page 18 of the AR4 Working Group I: Summary 
for Policymakers (IPCC 2007), and in greater detail in the SRES Report 
(IPCC 2000).
    The most commonly-used scenarios for current-generation climate 
modeling are the B1, A1B, and A2 scenarios. In the B1 scenario, 
CO2 concentration is around 549 parts per million (ppm) by 
2100; this is often termed a `low' scenario. In the A1B scenario, 
CO2 concentration is around 717 ppm by the end of the 
century; this is a 'medium' or `middle-of-the-road' scenario. In the A2 
scenario, CO2 concentration is around 856 ppm at the end of 
the 21st century; this is considered a `high' scenario with respect to 
GHG concentrations. It is important to note that the SRES scenarios 
include no additional mitigation initiatives, which means that no 
scenarios are included that explicitly assume the implementation of the 
United Nations Framework Convention on Climate Change (UNFCC) or the 
emission targets of the Kyoto Protocol.
    Of the various types of climate models, the Atmosphere-Ocean 
General Circulation Models (AOGCMs, also known as General Circulation 
Models (GCMs)) are acknowledged as the principal and most rapidly-
developing tools for simulating the response of the global climate 
system to various GHG and aerosol emission scenarios. The climates 
simulated by these models have been verified against observations in 
several model intercomparison programs (e.g., Achuta Rao et al. 2004; 
Randall et al. 2007) and have been found to be generally realistic 
(DeWeaver 2007). Additional confidence in model simulations comes from 
experiments with a hierarchy of simpler models, in which the dominant 
processes represented by climate models (e.g., heat and momentum 
transport by mid-latitude weather systems) can be isolated and studied 
(DeWeaver 2007).
    For projected changes in climate and Arctic sea ice conditions, our 
proposed rule (72 FR 1064) relied primarily on results in the IPCC's 
Third Assessment Report (TAR) (IPCC 2001b), the Arctic Climate Impact 
Assessment (ACIA 2005, p. 99), and selected peer-reviewed papers (e.g., 
Johannessen et al. 2004; Holland et al. 2006, pp. 1-5). The IPCC TAR 
used results derived from 9-AOGCM ensemble (i.e, averaged results from 
9 AOGCMs) and three SRES emissions scenarios (A2, B2, and IS92a). The 
ACIA (2005, p. 99) used a 5-AOGCM ensemble under two SRES emissions 
scenarios (A2 and B2); however, the B2 emissions scenario was chosen as 
the primary scenario for use in ACIA analyses (ACIA 2005). These 
reports relied on ensembles rather than single models, because ``no one 
model can be chosen as 'best' and it is important to use results from a 
range of models'' (IPCC 2001, Chapter 8). The other peer-reviewed 
papers used in the proposed rule (72 FR 1064) tend to report more-
detailed results from a one or two model simulations using one SRES 
scenario.
    After the proposed rule was published (72 FR 1064), the IPCC 
released its Fourth Assessment Report (AR4) (IPCC 2007), a detailed 
assessment of current and predicted future climates around the globe. 
Projected changes in climate and Arctic sea ice conditions presented in 
the IPCC AR4 have been used extensively in this final rule. The IPCC 
AR4 used results from state-of-the-art climate models that have been 
substantially improved over the models used in the IPCC TAR and ACIA 
reports (M. Holland, NCAR, in litt. to the Service, 2007; DeWeaver 
2007). In addition, the IPCC AR4 used results from a greater number of 
models (23) than either the IPCC TAR or ACIA reports. ``This larger 
number of models running the same experiments allows better 
quantification of the multi-model signal as well as uncertainty 
regarding spread across the models, and also points the way to 
probabilistic estimates of future climate change'' (IPCC 2007, p. 761). 
Finally, the IPCC AR4 used a greater number of emissions scenarios (4) 
than either the IPCC TAR or ACIA reports. The emission scenarios 
considered in the AR4 include A2, A1B, and B1, as well as a ``year 2000 
constant concentration'' scenario; this choice was made solely due to 
the limited computational resources for multi-model simulations using 
comprehensive AOGCMs, and ``does not imply any preference or 
qualification of these three scenarios over the others'' (IPCC 2007, 
p.761). For all of these reasons, there is considerable confidence that 
the AOGCMs used in the IPCC AR4 provide credible quantitative estimates 
of future climate change, particularly at continental scales and above 
(IPCC 2007, p. 591), and we have determined that these results are 
rightly included in the category of best available scientific 
information upon which to base a listing decision for the polar bear.
    In addition to the IPCC AR4 results, this final rule utilizes 
results from a large number of peer-reviewed papers (e.g., Parkinson et 
al. 2006; Zhang and Walsh 2006; Arzel et al. 2006; Stroeve et al. 2007, 
pp. 1-5; Holland et al. 2006, pp. 1-5; Wang et al. 2007, pp. 1,093-
1,107; Overland and Wang 2007a, pp. 1-7; Chapman and Walsh 2007) that 
provide more detailed information on climate change projections for the 
Arctic.

Uncertainty in Climate Models

    The fundamental physical laws reflected in climate models are well 
established, and the models are broadly successful in simulating 
present-day climate and recent climate change (IPCC 2007, cited in 
DeWeaver 2007). For Arctic sea ice, model simulations unanimously 
project declines in areal coverage and thickness due to increased GHG 
concentrations (DeWeaver 2007). They also agree that GHG-induced 
warming will be largest in the high northern latitudes and that the 
loss of sea ice will be much larger in summer than in winter (Meehl et 
al. 2007, cited in DeWeaver 2007). However, despite the qualitative 
agreement among climate model projections, individual model results for 
Arctic sea ice decline span a considerable range (DeWeaver 2007). Thus, 
projections from models are often expressed in terms of the typical

[[Page 28228]]

behavior of a group (ensemble) of simulations (e.g., Arzel et al. 2006; 
Flato et al. 2004; Holland et al. 2006, pp. 1-5).
    DeWeaver (2007) presents a detailed analysis of uncertainty 
associated with climate models and their projections for Arctic sea ice 
conditions. He concludes that two main sources of uncertainty should be 
considered in assessing Arctic sea ice simulations: uncertainties in 
the construction of climate models and unpredictable natural 
variability of the climate system. DeWeaver (2007) states that while 
most aspects of climate simulations have some degree of uncertainty, 
projections of Arctic climate change have relatively higher 
uncertainty. This higher level of uncertainty is, to some extent, a 
consequence of the smaller spatial scale of the Arctic, since climate 
simulations are believed to be more reliable at continental and larger 
scales (Meehl et al. 2007, IPCC 2007, both cited in DeWeaver 2007). The 
uncertainty is also a consequence of the complex processes that control 
the sea ice, and the difficulty of representing these processes in 
climate models. The same processes which make Arctic sea ice highly 
sensitive to climate change, the ice-albedo feedback in particular, 
also make sea ice simulations sensitive to any uncertainties in model 
physics (e.g., the representation of Arctic clouds) (DeWeaver 2007).
    DeWeaver (2007) also discusses natural variability of the climate 
system. He states that the atmosphere, ocean, and sea ice comprise a 
``nonlinear chaotic system'' with a high level of natural variability 
unrelated to external climate forcing. Thus, even if climate models 
perfectly represented all climate system physics and dynamics, inherent 
climate unpredictability would limit our ability to issue highly, 
detailed forecasts of climate change, particularly at regional and 
local spatial scales, into the middle and distant future (DeWeaver 
2007).
    DeWeaver (2007) states that the uncertainty in model simulations 
should be assessed through detailed model-to-model and model-to-
observation comparisons of sea ice properties like thickness and 
coverage. In principle, inter-model sea ice variations are attributable 
to differences in model construction, but attempts to relate simulation 
differences to specific model differences generally have not been 
successful (e.g., Flato et al. 2004, cited in DeWeaver 2007). A 
practical consequence of uncertainty in climate model simulations of 
sea ice is that a mean and spread of an ensemble of simulations should 
be considered in deciding the likely fate of Arctic sea ice. Some 
model-to-model variation (or spread) in future sea ice behaviors is 
expected even among high-quality simulations due to natural 
variability, but spread that is a consequence of poor simulation 
quality should be avoided. Thus, it is desirable to define a selection 
criterion for membership in the ensemble, so that only those models 
that demonstrate sufficient credibility in present-day sea ice 
simulation are included. Fidelity in sea ice hindcasts (i.e., the 
ability of models to accurately simulate past to present-day sea ice 
conditions) is an important consideration. This same perspective is 
shared by other researchers, including Overland and Wang (2007a, p. 1), 
who state: ``Our experience (Overland and Wang 2007b) as well as others 
(Knutti et al. 2006) suggest that one method to increase confidence in 
climate projections is to constrain the number of models by removal of 
major outliers through validating historical simulations against 
observations. This requirement is especially important for the 
Arctic.''

Projection Results in the IPCC TAR and ACIA

    This section briefly summarizes the climate model projections of 
the IPCC TAR and the ACIA, the principal reports used in the proposed 
rule (72 FR 1064), while the following section presents detailed 
results published subsequent to those reports, including in the IPCC 
AR4.
    All models in the IPCC TAR predicted continued Arctic warming and 
continued decreases in the Arctic sea ice cover in the 21st century due 
to increasing global temperatures, although the level of increase 
varied between models. The TAR projected a global mean temperature 
increase of 1.4 degree C by the mid-21st century compared to the 
present climate for both the A2 and B2 scenarios (IPCC 2001b). Toward 
the end of the 21st century (2071 to 2100), the mean change in global 
average surface air temperature, relative to the period 1961-1990, was 
projected to be 3.0 degrees C (with a range of 1.3 to 4.5 degrees C) 
for the A2 scenario, and 2.2 degrees C (with a range of 0.9 to 3.4 
degrees C) for the B2 scenario. Relative to glacier and sea ice change, 
the TAR reported that ``The representation of sea-ice processes 
continues to improve, with several climate models now incorporating 
physically based treatments of ice dynamics * * *. Glaciers and ice 
caps will continue their widespread retreat during the 21st century and 
Northern Hemisphere snow cover and sea ice are projected to decrease 
further.''
    The ACIA concluded that, for both the A2 and B2 emissions 
scenarios, models projected mean temperature increases of 2.5 degrees C 
for the region north of 60 degrees N latitude by the mid-21st century 
(ACIA 2005, p. 100). By the end of the 21st century, Arctic temperature 
increases were projected to be 7 degrees C and 5 degrees C for the A2 
and B2 scenarios, respectively, compared to the present climate (ACIA 
2005, p. 100). Greater warming was projected for the autumn and winter 
than for the summer (ACIA 2005, p. 100).
    The ACIA utilized projections from the five ACIA-designated AOGCMs 
to evaluate changes in sea ice conditions for three points in time 
(2020, 2050, and 2080) relative to the climatological baseline (2000) 
(ACIA 2005, p. 192). In 2020, the duration of the sea ice freezing 
period was projected to be shorter by 10 days; winter sea ice extent 
was expected to decline by 6 to 10 percent from baseline conditions; 
summer sea ice extent was expected to decline such that continental 
shelves were likely to be ice free; and there would be some reduction 
in multi-year ice, especially on shelves (ACIA 2005, Table 9.4). In 
2050, the duration of the sea ice freezing period was projected to be 
shorter by 15 to 20 days; winter sea ice extent was expected to decline 
by 15 to 20 percent; summer sea ice extent was expected to decline 30 
to 50 percent from baseline conditions; and there would be significant 
loss of multi-year ice, with no multi-year ice on shelves. In 2080, the 
duration of the sea ice freezing period was projected to be shorter by 
20 to 30 days; winter sea ice extent was expected to decline such that 
there probably would be open areas in the high Arctic (Barents Sea and 
possibly Nansen Basin); summer sea ice extent was expected to decline 
50 to 100 percent from baseline conditions; and there would be little 
or no multi-year ice.
    According to ACIA (2005, p. 193), one model indicated an ice-free 
Arctic during September by the mid-21st century, but this model 
simulated less than half of the observed September sea-ice extent at 
the start of the 21st century. None of the other models projected ice-
free summers in the Arctic by 2100, although the sea-ice extent 
projected by two models decreased to about one-third of initial (2000) 
and observed September values by 2100.

Projection Results in the IPCC AR4 and Additional Projections

    The IPCC AR4, released a few months after publication of our 
proposed listing

[[Page 28229]]

rule for the polar bear (72 FR 1064), presents results from state-of-
the-art climate models that are substantially improved over models used 
in the IPCC TAR and ACIA reports (M. Holland, NCAR, in litt. to the 
Service FWS, 2007; DeWeaver 2007). Results of the AR4 are presented in 
this section, followed by discussion of several key, peer-reviewed 
articles that discuss results presented in the AR4 in greater detail or 
use AR4 simulations to conduct additional, in-depth analyses.
    In regard to surface air temperature changes, the IPCC AR4 states 
that the range of expected globally averaged surface air temperature 
warming shows limited sensitivity to the choice of SRES emissions 
scenarios for the early 21st century (between 0.64 and 0.69 degrees C 
for 2011 to 2030 compared to 1980 to 1999, a range of only 0.05 
[deg]C), largely due to climate change that is already committed (IPCC 
2007, p. 749). By the mid-21st century (2046-2065), the choice of SRES 
scenario becomes more important for globally averaged surface air 
temperature warming (with increases of 1.3 degree C for the B1 
scenario, 1.8 degree C for A1B, and 1.7 degree C for A2). During this 
time period, about a third of that warming is projected to be due to 
climate change that is already committed (IPCC 2007, p. 749).
    The ``limited sensitivity'' of the results is because the state-of-
the-art climate models used in the AR4 have known physics in connecting 
increases in GHGs to temperature increases through radiation processes 
(Overland and Wang 2007a, pp. 1-7, cited in J. Overland, NOAA, in litt. 
to the Service, 2007), and the GHG levels used in the SRES emissions 
scenarios are relatively similar until around 2040-2050 (see Figure 5). 
Because increases in GHGs have lag effects on climate and projections 
of GHG emissions can be extrapolated with greater confidence over the 
next few decades, model results projecting out for the next 40 to 50 
years (near-term climate change estimates) have greater credibility 
than results projected much further into the future (long-term climate 
change) (J. Overland, NOAA, in litt. to the Service, 2007). Thus, the 
uncertainty associated with emissions is relatively smaller for the 45-
year ``foreseeable future'' for the polar bear listing. After 2050, 
uncertainty associated with various climate mechanisms and policy/
societal changes begins to increase, as reflected in the larger 
confidence intervals around the trend lines in Figure 5 beyond 2050.
[GRAPHIC] [TIFF OMITTED] TR15MY08.006


[[Page 28230]]


    However, even if GHG emissions had stabilized at 2000 levels, the 
global climate system would already be committed to a warming trend of 
about 0.1 degree C per decade over the next two decades, in the absence 
of large changes in volcanic or solar forcing. Meehl et al. (2006) 
conducted climate change scenario simulations using the Community 
Climate System Model, version 3 (CCSM3, National Center for Atmospheric 
Research), with all GHG emissions stabilized at 2000 levels, and found 
that the global climate system would already be committed to 0.40 
degree C more warming by the end of the 21st century.
    With respect to warming in the Arctic itself, the AR4 concludes: 
``At the end of the 21st century, the projected annual warming in the 
Arctic is 5 degrees C, estimated by the multi-model A1B ensemble mean 
projection'' (see IPCC 2007, p. 908, Fig. 11.21). The across-model 
range for the A1B scenario varied from 2.8 to 7.8 degrees C. Larger 
mean warming was found for the A2 scenario (5.9 degrees C), and smaller 
mean warming was found for the B1 scenario (3.4 degrees C); both with 
proportional across-model ranges. Chapman and Walsh (2007, cited IPCC 
2007, p. 904) concluded that the across-model and across-scenario 
variability in the projected temperatures are both considerable and of 
comparable amplitude.
    In regard to changes in sea ice, the IPCC AR4 concludes that, under 
the A1B, A2, and B1 SRES emissions scenarios, large parts of the Arctic 
Ocean are expected to be seasonally ice free by the end of the 21st 
century (IPCC 2007, p. 73). Some projections using the A2 and A1B 
scenarios achieve a seasonally ice-free Arctic by as early as 2080-2090 
(IPCC 2007, p.771, Figure 10.13a, b). Sea ice reductions are greater in 
summer than winter, thus it is summer sea ice cover that is projected 
to be lost in some models by 2080-2090, not winter sea ice cover. The 
reduction in sea ice cover is accelerated by positive feedbacks in the 
climate system, including the ice-albedo feedback (which allows open 
water to receive more heat from the sun during summer, the insulating 
effect of sea ice is reduced and the increase in ocean heat transport 
to the Arctic further reduces ice cover) (IPCC 2007, p. 73).
    While the conclusions of the IPCC TAR and AR4 are similar with 
respect to the Arctic, the confidence level associated with independent 
reviews of AR4 is greater, owing to improvements in the models used and 
the greater number of models and emissions scenarios considered (J. 
Overland, NOAA, in litt. to the Service, 2007). Climate models still 
have challenges modeling some of the regional differences caused by 
changing decadal climate patterns (e.g., Arctic Oscillation). To help 
improve the models further, the evaluation of AR4 models has been on-
going both for how well they represent conditions in the 20th century 
and how their predicted results for the 21st century compare (Parkinson 
et al. 2006; Zhang and Walsh 2006; Arzel et al. 2006; Stroeve et al. 
2007, pp. 1-5; Holland et al. 2006, pp. 1-5; Wang et al. 2007, pp. 
1,093-1,107; Chapman and Walsh 2007).
    Arzel et al. (2006) and Zhang and Walsh (2006) evaluate the sea ice 
results from the IPCC AR4 models in more detail. Arzel et al. (2006) 
investigated projected changes in sea ice extent and volume simulated 
by 13 AOGCMs (also known as GCMs) driven by the SRES A1B emissions 
scenario. They found that the models projected an average relative 
decrease in sea ice extent of 15.4 percent in March, 61.7 percent in 
September, and 27.7 percent on an annual basis when comparing the 
periods 1981-2000 and 2081-2100; the average relative decrease in sea 
ice volume was 47.8 percent in March, 78.9 percent in September, and 
58.8 percent on an annual basis when comparing the periods 1981-2000 
and 2081-2100. More than half the models (7 of 13) reach ice-free 
September conditions by 2100, as reported in some previous studies 
(Gregory et al. 2002, Johannessen et al. 2004, both cited in Arzel et 
al. 2006).
    Zhang and Walsh (2006) investigated changes in sea ice area 
simulated by 14 AOGCMs driven by the SRES A1B, A2, and B1 emissions 
scenarios. They found that the annual mean sea ice area during the 
period 2080-2100 would be decreased by 31.1 percent in the A1B 
scenario, 33.4 percent in the A2 scenario, and 21.6 percent in the B1 
scenario relative to the observed sea ice area during the period 1979-
1999. They further determined that the area of multi-year sea ice 
during the period 2080-2100 would be decreased by 59.7 percent in the 
A1B scenario, 65.0 percent in the A2 scenario, and 45.8 percent in the 
B1 scenario relative to the ensemble mean multi-year sea ice area 
during the period 1979-1999.
    Dumas et al. (2006) generated projections of future landfast ice 
thickness and duration for nine sites in the Canadian Arctic and one 
site on the Labrador coast using the Canadian Centre for Climate 
Modelling and Analysis global climate model (CGCM2). For the Canadian 
Arctic sites the mean maximum ice thickness is projected to decrease by 
roughly 30 cm (11.8 in) from 1970-1989 to 2041-2060 and by roughly 50-
55 cm (19.7-21.7 in) from 1970-1989 to 2081-2100. Further, they 
projected a reduction in the duration of sea ice cover of 1 and 2 
months by 2041-2060 and 2081-2100, respectively, from the baseline 
period of 1970-1989. In addition simulated changes in freeze-up and 
break-up revealed a 52-day later freeze-up and 30-day earlier break-up 
by 2081-2100.
    Holland et al. (2006, pp. 1-5) analyzed an ensemble of seven 
projections of Arctic summer sea ice from the Community Climate System 
Model, version 3 (CCSM3; National Center for Atmospheric Research, USA) 
utilizing the SRES A1B emissions scenario. CCSM3 is the model that 
performed best in simulating the actual observations for Arctic ice 
extent over the PM satellite era (Stroeve et al. 2007, pp. 1-5). 
Holland et al. (2006, pp. 1-5) found that the CCSM3 simulations 
compared well to actual observations for Arctic ice extent over the PM 
satellite era, including the rate of its recent retreat. They also 
found that the simulations did not project that sea ice retreat would 
continue at a constant rate into the future. Instead, the CCSM3 
simulations indicate abrupt shifts in the ice cover, with one CCSM3 
simulation showing an abrupt transition starting around 2024 with 
continued rapid retreat for around 5 years. Every CCSM3 run had at 
least one abrupt event (an abrupt event being defined as a time when a 
5-year running mean exceeded three times the 2001-2005 observed 
retreat) in the 21st century, indicating that near ice-free Septembers 
could be reached within 30-50 years from now.
    Holland et al. (2006, pp. 1-5) also discussed results from 15 
additional models used in the IPCC AR4, and concluded that 6 of 15 
other models ``exhibit abrupt September ice retreat in the A1B scenario 
runs.'' The length of the transition varied from 3 to 8 years among the 
models. Thus, in these model simulations, it was found that once the 
Arctic ice pack thins to a vulnerable state, natural variability can 
trigger an abrupt loss of the ice cover so that seasonally ice-free 
conditions can happen within a decade's time (J. Stroeve, in litt. to 
the Service, November 2007).
    Finally, Holland et al. (2006, pp. 1-5) noted that the emissions 
scenario used in the model affected the likelihood of future abrupt 
transitions. In models using the SRES B1 scenario (i.e., with GHG 
levels increasing at a slower rate), only 3 of 15 models show abrupt 
declines lasting from 3 to 5 years. In models using the A2 scenario 
(i.e., with

[[Page 28231]]

GHG levels increasing at a faster rate), 7 of 11 models with available 
data obtain an abrupt retreat in the ice cover; the abrupt events last 
from 3 to 10 years (Holland et al. 2006, pp. 1-5).
    In order to increase confidence in climate model projections, 
several studies have sought to constrain the number of models used by 
validating climate change in the models simulations against actual 
observations (Knutti et al. 2006; Hall and Ou 2006). The concept is to 
create a shorter list of ``higher confidence'' models by removing 
outlier model projections that do not perform well when compared to 
20th century observational data (Overland and Wang 2007a, pp. 1-7). 
This has been done for temperatures (Wang et al. 2007, pp. 1,093-
1,107), sea ice (Overland and Wang 2007a, pp. 1-7; Stroeve et al. 2007, 
pp. 1-5), and sea level pressure (SLP; defined as atmospheric pressure 
at sea level) and precipitation (Walsh and Chapman, pers. comm. with J. 
Overland, NOAA, cited in litt. to the Service, 2007).
    Overland and Wang (2007a, pp. 1-7) investigated future regional 
reductions in September sea ice area utilizing a subset of AR4 models 
that closely simulate observed regional ice concentrations for 1979-
1999 and were driven by the A1B emissions scenario. They used a 
selection criterion, similar to Stroeve et al. (2007, pp. 1-5), to 
constrain the number of models used by removing outliers so as to 
increase confidence in the projections used. Out of an initial set of 
20 potential models, 11 models were retained for the Arctic-wide area, 
4 were retained for the Kara/Laptev Sea area, 8 were retained for the 
East Siberian/Chukchi Sea, and 11 were retained for the Beaufort Sea 
(Overland and Wang 2007a, pp. 1-7). Using these constrained subsets, 
Overland and Wang (2007a, pp. 1-7) found that there is: ``considerable 
evidence for loss of sea ice area of greater than 40 percent by 2050 in 
summer for the marginal seas of the Arctic basin. This conclusion is 
supported by consistency in the selection of the same models across 
different regions, and the importance of thinning ice and increased 
open water at mid-century to the rate of ice loss.'' More specifically, 
Overland and Wang (2007a, pp. 1-7) found that ``By 2050, 7 of 11 models 
estimate a loss of 40 percent or greater of summer Arctic ice area. Six 
of 8 models show a greater than 40 percent ice loss in the East 
Siberian/Chukchi Seas and 7 of 11 models show this loss for the 
Beaufort Sea. The percentage of models with major ice loss could be 
considered higher, as two of the models that retain sea ice are from 
the same Canadian source and thus cannot be considered to be completely 
independent. These results present a consistent picture: there is a 
substantial loss of sea ice for most models and regions by 2050'' (see 
Figure 6). With less confidence, they found that the Bering, Okhotsk, 
and Barents seas have a similar 40 percent loss of sea ice area by 2050 
in winter; Baffin Bay/Labrador shows little change compared to current 
conditions (Overland and Wang 2007a, pp. 1-7). Overland and Wang 
(2007a, pp. 1-7) also note that the CCSM3 model (Holland et al. 2006, 
pp. 1-5) is one of the models with the most rapid ice loss in the 21st 
century; this model is also one of the best at simulating historical 
20th century observations (also see Figure 12 in DeWeaver (2007)).

[[Page 28232]]

[GRAPHIC] [TIFF OMITTED] TR15MY08.007

    DeWeaver (2007), applying a similar conceptual approach as Overland 
and Wang (2007a, pp. 1-7) and Stroeve et al. (2007, pp. 1-5), used a 
selection criterion to construct an ensemble of 10 climate models that 
most accurately depicted sea-ice extent, from the 20 models that 
contributed sea ice data to the AR4. This 10-model ensemble was used by 
the USGS for assessing potential polar bear habitat loss (Durner et al. 
2007). DeWeaver's selection criterion was to include only those models 
for which the mean 1953-1995 simulated September sea ice extent is 
within 20 percent of its actual observed value (as taken from the 
Hadley Center Sea Ice and Sea Surface Temperature (HadISST) data set 
(Raynor et al. 2003)). DeWeaver (2007) then investigated the future 
performance of his 10-model

[[Page 28233]]

ensemble driven by the SRES A1B emissions scenario. He found that: all 
10 models projected declines of September sea ice extent of over 30 
percent by the middle of the 21st century (i.e., 2045-2055); 4 of 10 
models projected declines September sea ice in excess of 80 percent by 
mid-21st century; and 7 of 10 models lose over 97 percent of their 
September sea ice by the end of the 21st century (i.e., 2090-2099) 
(DeWeaver 2007).
    Stroeve et al. (2007, pp. 1-5) compared observed Arctic sea ice 
extent from 1953-2006 with 20th and 21st century simulation results 
from an ensemble of 18 AR4 models forced with the SRES A1B emission 
scenario. Like Overland and Wang (2007a) and DeWeaver (2007), Stroeve 
et al. (2007, pp. 1-5) applied a selection criterion to limit the 
number of models used for comparison. Of the original 18 models in the 
ensemble, 13 were selected because their performance simulating 20th 
century September sea ice extent satisfied the selection criterion 
established by the authors (i.e., model simulations for the the period 
1953-1995 had to be within 20 percent of observations). The 
observational record for the Arctic by Stroeve et al. (2007, pp. 1-5) 
made use of a blended record of PM satellite-era (post November 1978) 
and pre-PM satellite era data (early satellite observation, aircraft 
and ship reports) described by Meier et al. (2007, pp. 428-434) and 
spanning the years 1953-2006 (Stroeve et al. 2007, pp. 1-5).
    Stroeve et al.'s (2007, pp. 1-5) results revealed that the observed 
trend of September sea ice from 1953-2006 (a decline of 7.8  0.6 percent per decade) is three times larger than the 13-model 
mean trend (a decline of 2.5  0.2 percent per decade). In 
addition, none of the 13 models or their individual ensemble members 
has trends in September sea ice as large as the observed trend for the 
entire observation period (1953-2006) or the 11-year period 1995-2006 
(Stroeve et al. 2007, pp. 1-5) (see Figure 7). March sea ice trends are 
not as dramatic, but the modeled decreases are still smaller than 
observed (Stroeve et al. 2007, pp. 1-5). Stroeve et al. (2007, pp. 1-5) 
offer two alternative interpretations to explain the discrepancies 
between the modeled results and the observational record. The first is 
that the ``observed September trend is a statistically rare event and 
imprints of natural variability strongly dominate over any effect of 
GHG loading'' (Stroeve et al. 2007, pp. 1-5). The second is that, if 
one accepts that the suite of simulations is a representative sample, 
``the models are deficient in their response to anthropogenic forcing'' 
(Stroeve et al. 2007, pp. 1-5). Although there is some evidence that 
natural variability is influencing the sea ice decrease, Stroeve et al. 
(2007, pp. 1-5) believe that ``while IPCC AR4 models incorporate many 
improvements compared to their predecessors, shortcomings remain'' 
(Stroeve et al. 2007, pp. 1-5) when they are applied to the Arctic 
climate system, particularly in modeling Arctic Oscillation variability 
and accurately parameterizing sea ice thickness.
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    The observational record indicates that current summer sea ice 
losses appear to be about 30 years ahead of the ensemble of modeled 
values, which suggests that a transition towards a seasonally ice-free 
Arctic might occur sooner than the models indicate (J. Stroeve, in 
litt. to the Service, November 2007). However, Stroeve et al. (2007, 
pp. 1-5) note that the two models that best match observations over the 
PM satellite era-CCSM3 and UKMO--HADGEM1 (Hadley Center for Climate 
Prediction and Research, UK)-incorporate relatively sophisticated sea 
ice models (McLaren et al. 2006 and Meehl et al. 2006, both cited in 
Stroeve et al. 2007, pp. 1-5). The same two models were mentioned by 
Gerdes and Koberle (2007) as having the most realistic sea ice 
thickness simulations. If only the results of CCSM3 are considered, as 
in Holland et al. (2006, pp. 1-5), model simulations compare well to 
actual observations for Arctic ice extent over the PM satellite era, 
including the rate of its recent retreat, and simulations of future 
conditio