The Cryosphere, 10, 2027–2041, 2016
www.the-cryosphere.net/10/2027/2016/
doi:10.5194/tc-10-2027-2016
© Author(s) 2016. CC Attribution 3.0 License.
Sea-ice indicators of polar bear habitat
Harry L. Stern1 and Kristin L. Laidre1,2
1Polar Science Center, Applied Physics Laboratory, University of Washington, 1013 NE 40th Street,
Seattle, WA 98105, USA
2Greenland Institute of Natural Resources, Box 570, 3900 Nuuk, Greenland
Correspondence to: Harry L. Stern (harry@apl.washington.edu)
Received: 5 May 2016 – Published in The Cryosphere Discuss.: 24 May 2016
Revised: 18 August 2016 – Accepted: 24 August 2016 – Published: 14 September 2016
Abstract. Nineteen subpopulations of polar bears (Ursus
maritimus) are found throughout the circumpolar Arctic, and
in all regions they depend on sea ice as a platform for traveling,
hunting, and breeding. Therefore polar bear phenology
– the cycle of biological events – is linked to the timing of
sea-ice retreat in spring and advance in fall. We analyzed the
dates of sea-ice retreat and advance in all 19 polar bear subpopulation
regions from 1979 to 2014, using daily sea-ice
concentration data from satellite passive microwave instruments.
We define the dates of sea-ice retreat and advance in
a region as the dates when the area of sea ice drops below
a certain threshold (retreat) on its way to the summer minimum
or rises above the threshold (advance) on its way to the
winter maximum. The threshold is chosen to be halfway between
the historical (1979–2014) mean September and mean
March sea-ice areas. In all 19 regions there is a trend toward
earlier sea-ice retreat and later sea-ice advance. Trends
generally range from −3 to −9 days decade−1 in spring and
from +3 to +9 days decade−1 in fall, with larger trends in
the Barents Sea and central Arctic Basin. The trends are not
sensitive to the threshold. We also calculated the number of
days per year that the sea-ice area exceeded the threshold
(termed ice-covered days) and the average sea-ice concentration
from 1 June through 31 October. The number of icecovered
days is declining in all regions at the rate of −7 to
−19 days decade−1, with larger trends in the Barents Sea and
central Arctic Basin. The June–October sea-ice concentration
is declining in all regions at rates ranging from −1 to
−9 percent decade−1. These sea-ice metrics (or indicators of
habitat change) were designed to be useful for management
agencies and for comparative purposes among subpopulations.
We recommend that the National Climate Assessment
include the timing of sea-ice retreat and advance in future
reports.
1 Introduction
The International Union for Conservation of Nature (IUCN)
Polar Bear Specialist Group (PBSG) recognizes 19 subpopulations
of polar bears (Ursus maritimus; Obbard et al., 2010;
Fig. 1 and Table 1). They are found throughout the sea-icecovered
areas of the circumpolar Arctic, especially over the
continental shelf and inter-island channels. Polar bears depend
on sea ice as a platform for hunting ice seals, their
primary prey. Sea ice also facilitates their seasonal movements,
mating, and, in some areas, maternal denning (Wiig
et al., 2015). Some polar bears remain on sea ice year-round,
but in more southerly areas where the ice melts completely,
all bears are forced to spend up to several months on land,
largely fasting until freeze-up allows them to return to the
ice again (e.g., Stirling et al., 1999; Stirling and Parkinson,
2006). The global population size of polar bears is roughly
estimated to be about 25 000 (Obbard et al., 2010). Genetic
analysis shows that gene flow occurs among the various
subpopulations, which are considered to be semi-discrete
(Paetkau et al., 1999; Peacock et al., 2015; Wiig et al., 2015).
Multiple approaches have been taken to construct sea-ice
metrics for studies of survival and body condition in specific
polar bear subpopulations (Table 2). These have generally focused
on subpopulation-specific metrics such as the number
of ice-free or ice-covered days per year (Obbard et al., 2007;
Regehr et al., 2010, 2015; Hamilton et al., 2014), the dates
of spring sea-ice breakup and/or fall sea-ice freeze-up (Stirling
and Parkinson, 2006; Regehr et al., 2007; Lunn et al.,
Published by Copernicus Publications on behalf of the European Geosciences Union.
2028 H. L. Stern and K. L. Laidre: Sea-ice indicators of polar bear habitat
Table 1. Polar bear subpopulation region names, abbreviations, and areas. See Fig. 1 for a map of the regions. The area of each region
includes the marine portion only, not land. The number of cells is the number of SSM/I grid cells. The percent of total area is with respect
to all regions (last row). The percent of area shallower than 300 m and deeper than 300 m are given in the last two columns. The pole hole
(second to last row) is the circular area around the North Pole excluded from analysis due to the satellite orbits. The Arctic Basin region (AB)
surrounds the pole hole but does not include it. All regions includes all 19 subpopulation regions plus the pole hole.
Abbreviation Subpopulation Number of Area % of total % %
cells (103 km2) area ≤ 300 m > 300 m
KB Kane Basin 81 53 0.3 68 32
BB Baffin Bay 1042 656 4.3 28 72
LS Lancaster Sound 380 243 1.6 73 27
NW Norwegian Bay 108 70 0.5 84 16
VM Viscount Melville 157 101 0.7 64 36
NB Northern Beaufort 1055 677 4.4 23 77
SB Southern Beaufort 529 333 2.2 59 41
MC M’Clintock Channel 224 140 0.9 100 0
GB Gulf of Boothia 100 62 0.4 99 1
FB Foxe Basin 883 528 3.4 97 3
WH Western Hudson Bay 326 188 1.2 100 0
SH Southern Hudson Bay 744 417 2.7 100 0
DS Davis Strait 2416 1367 8.9 40 60
EG East Greenland 2237 1387 9.0 27 73
BS Barents Sea 2379 1540 10.0 63 37
KS Kara Sea 1645 1054 6.9 87 13
LP Laptev Sea 2169 1393 9.1 84 16
CS Chukchi Sea 1840 1117 7.3 98 2
AB Arctic Basin 4307 2813 18.3 15 85
Pole hole 1799 1193 7.8 0 100
All regions 24 421 15 332 100.0 50 50
2014; Laidre et al., 2015a; Obbard et al., 2016), or the seaice
concentration (Rode et al., 2012; Peacock et al., 2012,
2013). Sea-ice metrics have mainly been selected based on
the specific region under study or developed for single studies
or data sets. There is a need to develop standardized circumpolar
metrics of polar bear habitat based on the satellite
record of sea ice that allow for regional comparisons of habitat
change and for tracking changes into the future, e.g., as
in Vongraven et al. (2012). Thus the objective of this study is
to propose and produce metrics of polar bear sea-ice habitat
that are also relevant to other Arctic marine mammal (AMM)
species.
In this study we used daily sea-ice concentration data to
calculate several sea-ice metrics for each of the 19 polar bear
subpopulation regions for the period 1979–2014. The metrics
are date of spring sea-ice retreat, date of fall sea-ice advance,
average sea-ice concentration from 1 June to 31 October, and
the number of ice-covered days per year. We calculated each
metric for the total marine area of each region and for the
shallow depths only (≤ 300 m). Shallow depths are more biologically
productive and are considered to be better polar
bear habitat (Durner et al., 2009).
Several previous studies have divided the Arctic into distinct
regions and calculated the sea-ice area trend in each
region (e.g., Stroeve et al., 2012; Perovich and RichterMenge,
2009; Parkinson and Cavalieri, 2008). While this is
a straightforward and useful way to document changes in sea
ice, other metrics of sea-ice habitat are more relevant to marine
mammals whose life history events, such as hunting and
breeding, depend on the annual retreat of sea ice in the spring
and advance in the fall. Many ecologically important regions
of the Arctic are ice covered in winter and ice free in summer
and will probably remain so for a long time into the future.
Therefore the dates of sea-ice retreat in spring and advance
in fall, and the interval of time between them, are key indicators
of climate change for ice-dependent marine mammals
(Stirling et al., 1999; Stirling and Parkinson, 2006).
2 Data
As in Laidre et al. (2015a) we used the Sea Ice Concentrations
from Nimbus-7 SMMR and DMSP SSM/I-SSMIS Passive
Microwave Data (Cavalieri et al., 1996) data set available
from the National Snow and Ice Data Center (NSIDC)
in Boulder, CO. This product is designed to provide a consistent
time series of sea-ice concentrations (the fraction, or
percentage, of ocean area covered by sea ice) spanning the
coverage of several passive microwave instruments. The seaice
concentrations are produced using the NASA Team algoThe
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H. L. Stern and K. L. Laidre: Sea-ice indicators of polar bear habitat 2029
Table 2. Recent literature where sea-ice metrics were used for analysis of polar bear habitat. Note that these studies examined habitat for a
single polar bear subpopulation (or geographically close set of subpopulations). Bold text gives names of sea-ice metrics. Abbreviations: PM
(passive microwave), SIC (sea-ice concentration), CIS (Canadian Ice Service).
Subpopulation Data Years Methods for sea-ice metric Reference
Western
Hudson Bay
Daily
PM SIC
1979–2004 Calculated daily percent sea-ice cover in the region.
Date of spring sea-ice breakup is the
date when the ice cover fell below 50 %.
Stirling and Parkinson (2006)
Western
Hudson Bay
Daily
PM SIC
1984–2004 Date of spring sea-ice breakup is the date
when the ice cover fell below 50 %
(same as Stirling and Parkinson, 2006).
Regehr et al. (2007)
Southern
Hudson Bay
Daily
PM SIC
1984–2003 Date of spring sea-ice breakup is the date
when the ice cover fell below 50 % (same as
Stirling and Parkinson, 2006).
Date of fall sea-ice freeze-up is the date when
the ice cover rose above 50 %.
Ice-free period is the number of days between
breakup and freeze-up.
Obbard et al. (2007)
Southern
Beaufort
Sea
Daily
PM SIC
2001–2005 Calculated the daily percent sea-ice cover for
the continental shelf only (depth < 300 m).
Number of ice-free days is the number of days
per calendar year with ice cover < 50 %.
Regehr et al. (2010)
Northern
Beaufort
Sea
Daily
PM SIC
1979–2006 Mean annual number of grid cells with seaice
concentration > 50 %, calculated for continental
shelf only (depth < 300 m) and excluding
a buffer of one ocean grid cell along all coastlines.
Second sea-ice covariate is derived from
the resource selection functions of Durner et
al. (2009).
Stirling et al. (2011)
Baffin Bay,
Davis Strait
Mean
weekly
SIC
(CIS)
1977–2010 Mean weekly sea-ice concentration from 15
May to 15 October.
Rode et al. (2012)
Chukchi
Sea, Southern
Beaufort
Sea
Daily
PM SIC
1985–1993,
2007–2010
Reduced-ice days per year is the number of
days with sea-ice area < 6250 km2 (continental
shelf of each region only, depth < 300 m).
Distance to ice edge is the daily minimum distance
from continental shelf to pack ice, averaged
over all days in September. When pack ice
is over the continental shelf the distance is set
to zero.
Rode et al. (2014)
Baffin Bay Daily
PM SIC
1979–2009 Sea-ice concentration in April, May,
and June for the continental shelf only
(depth < 300 m). (Note that the continental
shelf consists of two parts: Baffin Island in the
west and Greenland in the east.)
Peacock et al. (2012)
Davis Strait Mean
weekly
SIC
(CIS)
1974–2007 Mean weekly sea-ice concentration from 14
May to 15 October.
Peacock et al. (2013)
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2030 H. L. Stern and K. L. Laidre: Sea-ice indicators of polar bear habitat
Table 2. Continued.
Subpopulation Data Years Methods for sea-ice metric Reference
Canadian
Arctic
Archipelago
MIT
general
circulation
model
(GCM)
2006–2100 Future projections of sea ice were made using the
MIT GCM with 18 km grid size and monthly output,
forced by “business as usual” RCP8.5 emission sce-
nario.
Month of spring sea-ice breakup is the first month
in a given year with sea-ice concentration < 50 %.
Month of fall sea-ice freeze-up is the first month after
breakup with sea-ice concentration ≥ 10 %.
Ice-free season is the time from breakup to freezeup.
If all months of the year have sea-ice concentration
< 10 % then the ice-free season is 12 months.
Hamilton et al. (2014)
Western
Hudson Bay
Daily PM
SIC
1979–2012 Calculated daily percent sea-ice cover in the region.
Date of spring sea-ice breakup is the date when
the ice cover fell below 50 % (same as Stirling and
Parkinson, 2006) and stayed below 50 % for at least
3 consecutive days.
Date of fall sea-ice freeze-up is the date when the
ice cover rose above 50 % and stayed above 50 % for
at least 3 consecutive days.
Ice decay is the rate of sea-ice loss from 1 May until
the date of complete disappearance of sea ice, calculated
as the absolute value of the slope of the ordinary
least squares regression line of ice concentration vs.
time.
Lunn et al. (2014)
East Green-
land
Daily PM
SIC
1979–2012 Calculated the daily sea-ice area in the region. Defined
threshold area A as halfway between mean
March ice area and mean September ice area, where
the means are calculated over the baseline period
1979–1988.
Date of spring sea-ice breakup is the date when ice
area fell below threshold area A.
Date of fall sea-ice freeze-up is the date when ice
area rose above threshold area A.
Laidre et al. (2015a)
Chukchi
Sea, Southern
Beaufort
Sea
Daily PM
SIC
1979–2013 Calculated the daily sea-ice area in each region. Defined
threshold area A as halfway between mean
March ice area and zero area, where the mean March
area is calculated over the baseline period 1979–
2013.
Ice-covered days is the number of days each year
with ice area > threshold area A.
Calculated the mean number of ice-covered days for
1994–2013 and then projected the number of icecovered
days forward in time.
Regehr et al. (2015)
Southern
Beaufort
Sea
2001–2010 Summer habitat is the sum of monthly indices of
the area of optimal polar bear habitat over the continental
shelf for July through October each year (from
Durner et al., 2009).
Melt season is the time between melt onset and
freeze onset (“inner melt length” from Stroeve et al.,
2014).
Bromaghin et al. (2015)
Southern
Hudson Bay
Daily PM
SIC
1980–2012 Date of spring sea-ice breakup is the date when
mean ice concentration falls below 5 %.
Date of fall sea-ice freeze-up is the date when mean
ice concentration rises above 5 %.
Obbard et al. (2016)
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H. L. Stern and K. L. Laidre: Sea-ice indicators of polar bear habitat 2031
Figure 1. Map of the 19 PBSG polar bear subpopulation regions,
with shallow depths (≤ 300 m) in blue. See Table 1 for subpopulation
names corresponding to the abbreviations on the map.
rithm, and are provided in a polar stereographic projection
(true at 70◦ N) with a nominal grid cell size of 25 × 25 km
(cell size varies slightly with latitude). Temporal coverage is
every other day from 26 October 1978 through 9 July 1987,
then daily through 31 December 2014.
Concerning the accuracy of the sea-ice concentration data,
the product documentation states that it is within ±5 % of
the actual sea-ice concentration in winter and ±15 % in summer
when melt ponds are present on the sea ice and that the
accuracy is best for thick ice (> 20 cm) and high ice concentration
(NSIDC, 2015). This means that accuracy is less in
the marginal ice zone – the band of low ice concentration
between open water and consolidated pack ice. Ivanova et
al. (2015) found that all passive microwave sea-ice retrieval
algorithms underestimated sea-ice concentration in the presence
of melt ponds and thin ice. Thus our estimates of daily
sea-ice area in each region are undoubtedly biased low, but
a consistent bias over time would not affect trends computed
from the data.
The spatial coverage of the sea-ice concentration data excludes
a small circle around the North Pole, due to the satellite
orbits. This “pole hole” is entirely surrounded by the Arctic
Basin region (AB in Fig. 1 and Table 1). Although the size
of the pole hole became smaller in 1987 with the advent of
a new satellite and instrument, we use the larger pre-1987
pole hole for consistency of calculations throughout the period
1979–2014. Our Arctic Basin region does not include
the pole hole; it surrounds the pole hole.
To identify shallow depths (≤ 300 m) we used bathymetry
from ETOPO1, a 1 arcmin global relief model of Earth’s surface
that integrates land topography and ocean bathymetry,
built from numerous global and regional data sets (Amante
and Eakins, 2009). We averaged the ETOPO1 data over each
SSM/I grid cell to obtain the mean ocean depth for each
cell, which we then used to distinguish the continental shelf
(≤ 300 m depth) from the deeper ocean. Table 1 gives the marine
area of the 19 subpopulation regions, as well as the percent
of the area shallower than 300 m and deeper than 300 m.
3 Methods
3.1 Preliminary data processing
Sea-ice area is defined as sea-ice concentration × grid cell
area summed over cells with sea-ice concentration greater
than 15 %. For each region, we calculated the daily (or everyother-day
prior to 1987) sea-ice area over two sets of grid
cells: (1) all cells in the region and (2) those cells in which the
mean ocean depth is ≤ 300 m. We note that the 15 % threshold
is standard in the sea-ice literature for identifying the
presence of sea ice (e.g., Parkinson, 2014) and is not based
on ice concentration preferences of polar bears, which can be
higher or lower depending on season (Cherry et al., 2013).
We next looked for outliers in each time series: excessively
large or small values that may be the result of erroneous
sea-ice retrievals due to extreme weather events or other errors.
Outliers were identified by comparing each value in the
time series with a five-point median-filtered version of the
time series. If the difference between the actual value and the
median-filtered value exceeded a certain threshold (15 % of
the mean March sea-ice area), then the actual value was replaced
by the median value. The outlier rate was less than
three values per 10 000. This procedure also led to the identification
of an anomaly on 14 September 1984 that turned out
to be an error in the passive microwave source data, which
was subsequently re-processed by NSIDC.
We next used linear interpolation to fill in the every-otherday
gaps up to 9 July 1987. We also used linear interpolation
to span a data gap from 3 December 1987 to 13 January 1988.
The end result was a complete time series of daily sea-ice
area for each region, 1979–2014.
3.2 Dates of spring sea-ice retreat and fall sea-ice
advance
The date of spring sea-ice retreat is defined here as the date
when the sea-ice area drops below a certain threshold on its
way to the summer minimum. The date of fall sea-ice advance
is defined as the date when the sea-ice area rises above
the threshold on its way to the winter maximum. These dates
may or may not occur in what is normally considered to be
spring or fall; they are meant to mark the transitions between
winter and summer sea-ice conditions.
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2032 H. L. Stern and K. L. Laidre: Sea-ice indicators of polar bear habitat
Figure 2. Daily sea-ice area in Baffin Bay (all depths), January–
December, 1979–2014 (gray curves). The colored curves are
decadal averages, as indicated in the legend. The upper horizontal
dotted line (at 613 × 103 km2) is the average sea-ice area in March
(1979–2014); the lower horizontal dotted line (at 9 × 103 km2) is
the average sea-ice area in September. The middle horizontal dotted
line, halfway between the upper and lower lines, is the threshold for
determining the spring and fall transition dates in Baffin Bay. See
Fig. S1 for similar plots for other subpopulation regions.
Arctic sea ice typically reaches its maximum area in
March and its minimum area in September. Accordingly,
we chose the transition threshold for each region as follows.
We calculated the mean March sea-ice area over the period
1979–2014, and the mean September sea-ice area over the
same period, and then chose the transition threshold to be
halfway between these means. This is illustrated for the Baffin
Bay region in Fig. 2 and for the other regions in Supplement
Fig. S1. (Figs. 2–9 use Baffin Bay as a sample region
for purposes of illustration).
Figure 3 illustrates the method for finding the dates of
spring retreat and fall advance in Baffin Bay in one particular
year. The daily sea-ice area (gray curve) exhibits small daily
fluctuations that can be attributed to the uncertainty in the
underlying sea-ice concentration data. We smooth the daily
values with a low-pass Gaussian-shaped filter in which 87 %
of the weight is within ±1 week of the central value (black
curve). Then, starting from the minimum sea-ice area in summer,
we search forward and backward in time for the first
intersections of the smoothed time series with the threshold.
The backward search gives the spring date (red vertical line)
and the forward search gives the fall date (blue vertical line).
Occasionally the smoothed sea-ice area time series may
cross the threshold more than once in spring and/or fall. Our
method always chooses the crossing date that is closest in
time to the summer minimum. In practice, out of 2736 crossing
dates (36 years × 2 seasons × 19 regions × 2 time series
per region), only 131 dates (4.8 %) had any potential for ambiguity.
In more than 95 % of the cases there was clearly only
a single crossing date.
Figure 3. Determination of the spring and fall transition dates for
the year 2005 in Baffin Bay. The gray curve is the daily sea-ice area;
the black curve is a smoothed version. The horizontal dotted line (at
311 × 103 km2) is the threshold. The intersection of the threshold
with the smoothed (black) curve determines the spring (red) and
fall (blue) transition dates.
3.3 Summer sea-ice concentration
For each region we calculated the mean sea-ice concentration
for 1 June–31 October for each year, from 1979 to 2014.
While it has already been established that the sea-ice concentration
in every region of the Arctic except the Bering Sea
is declining in every month of the year (e.g., Perovich and
Richter-Menge, 2009), the winter sea-ice cover will likely
continue to provide suitable polar bear habitat for at least
several more decades (especially in the Canadian high Arctic;
Amstrup et al., 2008; Hamilton et al., 2014), whereas the
summer sea-ice cover may not. A summer sea-ice metric,
therefore, measures the change in polar bear habitat during
the season when that habitat is most vulnerable to change.
3.4 Number of ice-covered days per year
We calculated the number of days per year that the sea-ice
area in each subpopulation region exceeded the threshold defined
in Sect. 3.2 (i.e., 50 % of the way from mean September
to mean March sea-ice area). For example, in Fig. 3, the seaice
area in Baffin Bay was greater than the 50 % threshold for
220 days in the year 2005. This sea-ice metric was used as a
measure of polar bear habitat in the IUCN Red List assessment
of polar bears (Wiig et al., 2015).
4 Results
4.1 Sea-ice metrics
In all 19 regions, the date of spring sea-ice retreat is trending
earlier and the date of fall sea-ice advance is trending later.
Along with this, the length of the summer season is increasing,
the summer sea-ice concentration is decreasing, and the
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H. L. Stern and K. L. Laidre: Sea-ice indicators of polar bear habitat 2033
Figure 4. Dates of sea-ice retreat (red) and sea-ice advance (blue)
in Baffin Bay (all depths) for 1979–2014. The red and blue lines are
least-squares fits. The vertical green lines indicate the time interval
between retreat and advance (i.e., length of summer season). See
Table 3 for trends. See Fig. S2 for similar plots for other regions.
number of ice-covered days per year is decreasing, for the period
1979–2014 (Table 3). Nearly all the trends (88 of 95) are
statistically significant. Trends in the date of spring sea-ice
retreat are on the order of −3 to −9 days decade−1 (negative
being earlier), with the largest trend (−16 days decade−1) in
the Barents Sea. Trends in the date of fall sea-ice advance
are on the order of +3 to +9 days decade−1 (positive being
later), with the largest trend (+18 days decade−1) again in
the Barents Sea. This means that over the 3.5 decades of this
study, the time interval from the date of spring retreat to the
date of fall advance has lengthened by 3 to 9 weeks in most
regions and by 17 weeks in the Barents Sea. The summer
(June–October) sea-ice concentration is declining at a rate of
−1 to −9 percent decade−1, depending on region. The number
of ice-covered days is declining in all regions at the rate
of −7 to −19 days decade−1, with larger trends in the Barents
Sea and central Arctic Basin. Results for the shallow
(≤ 300 m) portions of each region are similar (Table 4). Note
that some regions consist almost entirely of shallow depths
(see Fig. 1 and Table 1).
Figure 4 illustrates results for the Baffin Bay region (see
Fig. S2 for similar plots for other regions). Sea-ice retreat
in spring is changing by −7.3 days decade−1 (red) and
sea-ice advance in fall is changing by +5.4 days decade−1
(blue), both statistically significant. The time interval between
the spring and fall transition dates is changing by
+12.7 days decade−1 (Fig. 5; see Fig. S3 for similar plots for
other regions). The summer sea-ice concentration is changing
by −4.1 percent decade−1 (Fig. 6; see Fig. S4 for similar
plots for other regions). The number of ice-covered days is
changing by −12.7 days decade−1, which is the negative of
the fall-minus-spring trend: the loss of every ice-covered day
occurs between the time of spring sea-ice retreat and fall seaice
advance.
Figure 5. Length of the summer season (from spring sea-ice retreat
to fall sea-ice advance) vs. year for Baffin Bay (all depths), with
least-squares line in red (slope: +12.7 days decade−1). See Fig. S3
for similar plots for other regions.
Figure 6. Summer (June through October) sea-ice concentration vs.
year for Baffin Bay (all depths), with least-squares line in red (slope:
−4.1 percent decade−1). See Fig. S4 for similar plots for other re-
gions.
We also calculated the number of ice-covered days based
on a 15 % threshold of sea-ice area, as illustrated in Figs. 7
and 8 (see Fig. S5 for similar plots for other regions). The 15
and 50 % thresholds intersect the annual cycle of sea-ice area
at different levels and therefore contain information about
the shape of the annual cycle. In Baffin Bay, the rate of decline
in the number of ice-covered days is about the same for
both thresholds (Fig. 8). However, in the Chukchi Sea region
(Fig. S5) the rate of decline is faster for the 15 % threshold,
meaning that the rise and fall of the annual cycle of sea-ice
area is steepening, leading to faster transitions between summer
and winter sea-ice coverage. In the Barents Sea (Fig. S5)
the opposite is occurring. Further analysis of changes in the
shape of the annual cycle of sea-ice area is possible but is
beyond the scope of the present study.
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2034 H. L. Stern and K. L. Laidre: Sea-ice indicators of polar bear habitat
Table 3. Trend in date of spring sea-ice retreat (days decade−1), trend in date of fall sea-ice advance (days decade−1), trend in length of
summer season (days decade−1), trend in June–October sea-ice concentration (percent concentration decade−1), trend in number of icecovered
days (days decade−1), and correlation of de-trended dates of spring retreat and fall advance (dimensionless). All quantities are
computed from the total marine area of each region, regardless of depth (compare Table 4), for the period 1979–2014. The trend in the length
of the summer season (fall–spring trend) is equal to the fall trend minus the spring trend. Statistical significance is indicated by * (95 % level)
or ** (99 % level) according to a two-sided F test (for trends) or a two-sided t test (for correlations).
Subpopulation Spring Fall Fall−spring Jun–Oct Ice-covered Correlation of
trend trend trend ice concentration days dates
Kane Basin −6.8 * 5.6 ** 12.4 ** −5.4 ** −14.1 ** −0.55 **
Baffin Bay −7.3 ** 5.4 ** 12.7 ** −4.1 ** −12.7 ** −0.64 **
Lancaster Sound −5.4 * 4.7 ** 10.1 ** −4.4 ** −10.6 ** −0.11
Norwegian Bay −1.2 4.3 5.5 −1.6 −7.1 * −0.21
Viscount Melville −4.0 7.9 11.8 * −4.7 ** −12.3 ** 0.36 *
Northern Beaufort −6.0 * 3.1 9.0 * −4.3 ** −9.3 * −0.40 *
Southern Beaufort −9.0 ** 8.8 ** 17.8 ** −9.3 ** −17.5 ** −0.50 **
M’Clintock Channel −4.1 ** 5.9 ** 10.0 ** −5.1 ** −11.1 ** −0.74 **
Gulf of Boothia −8.6 ** 7.6 ** 16.2 ** −8.9 ** −18.6 ** −0.57 **
Foxe Basin −5.3 ** 5.7 ** 11.0 ** −3.3 ** −11.4 ** −0.58 **
Western Hudson Bay −5.1 ** 3.5 ** 8.7 ** −2.9 ** −8.6 ** −0.25
Southern Hudson Bay −3.0 * 3.6 * 6.6 ** −1.8 * −6.8 ** −0.35 *
Davis Strait −7.4 ** 9.2 ** 16.6 ** −1.0 ** −17.1 ** −0.35 *
East Greenland −5.7 ** 4.8 * 10.5 ** −1.4 * −10.4 ** −0.34 *
Barents Sea −16.4 ** 18.2 ** 34.6 ** −3.8 ** −41.0 ** −0.46 **
Kara Sea −9.2 ** 7.3 ** 16.5 ** −7.9 ** −16.9 ** −0.49 **
Laptev Sea −6.9 ** 7.0 ** 13.9 ** −9.4 ** −13.5 ** −0.78 **
Chukchi Sea −4.0 ** 5.3 ** 9.3 ** −4.0 ** −8.9 ** −0.39 *
Arctic Basin −11.9 ** 15.2 ** 27.1 ** −6.0 ** −24.6 ** 0.35 *
Figure 7. Sea-ice area in Baffin Bay (all depths), 1979–2014. Top green line is mean March sea-ice area; bottom green line is mean September
sea-ice area. Two thresholds are shown: 15 and 50 % of the way from the mean September area to the mean March area.
4.2 Correlation of de-trended dates
Figure 4 shows that there is year-to-year variability about the
trend lines in the dates of spring sea-ice retreat and fall seaice
advance. Subtracting out the trend lines leaves residuals.
We calculated the correlation of the spring residuals with the
fall residuals (Table 3, last column). The correlation is negative
in most regions, often significantly so. This means that
an early spring sea-ice retreat (relative to the trend line) tends
to be followed by a late fall sea-ice advance (relative to the
trend line), and vice versa. The de-trended spring and fall
dates for Baffin Bay are shown in Fig. 9. The negative correlations
are likely the result of the ice–albedo feedback, discussed
in Sect. 5.4.
In regions with a strong negative correlation, this suggests
a method for predicting the date of fall sea-ice advance, once
the date of spring sea-ice retreat has been observed. (1) Find
the slope (S) of the least-squares fit of the de-trended fall
dates vs. the de-trended spring dates (as in Fig. 9, red line).
(2) Calculate the projected date of retreat (Dr) and date of
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H. L. Stern and K. L. Laidre: Sea-ice indicators of polar bear habitat 2035
Figure 8. Number of ice-covered days in Baffin Bay (all depths),
1979–2014, based on two thresholds: 15 % (blue) and 50 % (red)
(see also Fig. 7). Least-squares lines are also shown. See Fig. S5 for
similar plots for other regions.
advance (Da) for the current year by extrapolating the historical
trends (Table 3). (3) In the current year, once the date
of spring sea-ice retreat has been observed (Dobs
r ), predict
the date of fall sea-ice advance as Da + S × (Dobs
r − Dr).
This is the date projected by the trend line plus the anomaly
predicted by the historical correlation of the spring and fall
dates. This method should give several months of lead time
for the predicted date of fall sea-ice advance, with a higher
degree of skill than simply predicting a continuation of the
fall linear trend, in those regions where the spring and fall
dates are significantly correlated.
4.3 Spatial patterns
The spatial pattern of trends in the date of spring sea-ice retreat
(Fig. 10) shows that all trends over shallow depths are
statistically significant except in the Northern Beaufort, Viscount
Melville, and Norwegian Bay regions. Otherwise, the
continental shelves around the Arctic show significantly earlier
spring retreat, generally −3 to −9 days decade−1, with
faster retreat in the northern Chukchi and East Siberian seas,
Kane Basin, and especially the Barents Sea. For the date of
fall sea-ice advance (Fig. 11), all regions have positive trends,
but the trends are not statistically significant in some parts of
the Canadian Arctic Archipelago. The rest of the continental
shelf regions around the Arctic show significantly later fall
advance, generally 3 to 9 days decade−1, with larger rates in
the northern Chukchi and East Siberian seas and in the Barents
Sea, similar to the spring pattern. The increase in the
length of the summer season (Fig. 12) shows the same pattern,
with roughly double the rate (since it equals the fall rate
minus the spring rate).
Note that in this analysis, the Chukchi Sea region extends
south of Bering Strait into the northern Bering Sea. We know
from other analyses (e.g., Laidre et al., 2015a; Parkinson,
2014) that there has been a slight increase in sea ice in the
Bering Sea. Therefore the negative trends for the Chukchi
Sea reported here, while still statistically significant, are relatively
small because of the inclusion of the northern Bering
Sea within the Chukchi Sea region. Similarly, the trends for
the Arctic Basin region are relatively large because that region
includes the northern Chukchi Sea, where summer sea
ice has been rapidly disappearing (e.g., Frey et al., 2015;
Parkinson, 2014).
4.4 Sensitivity to threshold
The calculation of the spring and fall transition dates is based
on a sea-ice area threshold that is halfway between the mean
September sea-ice area and the mean March sea-ice area for
each region. Different thresholds would lead to different transition
dates. How sensitive are the transition dates to the actual
choice of threshold? The answer can be seen in Fig. 2
(and Fig. S1). The rate of change of sea-ice area (i.e., its
slope) is relatively steep at the times of threshold crossing,
indicating that sea ice diminishes quickly in spring and grows
back quickly in fall compared to the rate of change in winter
and summer. Therefore the transition dates are relatively insensitive
to the threshold, in the sense that a small change in
the threshold would lead to a small change in the transition
dates.
5 Discussion
5.1 Previous studies of the timing of Arctic sea-ice
advance and retreat
Many studies in the last 10 years have considered changes
in the timing of sea-ice advance and retreat in the context
of polar bear ecology. Stirling and Parkinson (2006)
used daily sea-ice concentration from satellite passive microwave
data to calculate the date of sea-ice breakup (50 %
concentration) in spring in Baffin Bay for each year from
1979 through 2004, finding a statistically significant trend
toward earlier breakup (−6.6 ± 2.0 days decade−1). The timing
of polar bear onshore arrival in western Hudson Bay
was previously shown to be significantly related to the 50 %
sea-ice concentration threshold (Stirling et al., 1999). Other
studies of sea-ice timing and polar bears include Regehr et
al. (2007), Obbard et al. (2007), Hamilton et al. (2014), Lunn
et al. (2014), Laidre et al. (2015a), and Obbard et al. (2016).
These studies are summarized in Table 2, along with eight
other studies where sea-ice metrics were used for analysis of
polar bear habitat.
Other researchers have considered changes in the timing
of sea-ice advance and retreat without specific emphasis on
polar bears. Stammerjohn et al. (2012) used daily sea-ice
concentration from satellite passive microwave data (1979–
2007) to calculate trends in the dates of sea-ice retreat and
advance at every 25 × 25 km grid cell. Then they identified
two regions where the trends were particularly large, encomwww.the-cryosphere.net/10/2027/2016/
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2036 H. L. Stern and K. L. Laidre: Sea-ice indicators of polar bear habitat
Figure 9. Date of fall sea-ice advance (de-trended) vs. date of spring
sea-ice retreat (de-trended) for Baffin Bay (all depths). The detrended
dates have correlation −0.64. This suggests that the date
of fall sea-ice advance can be predicted from the date of spring seaice
retreat with more skill than simply extrapolating the fall trend.
See Table 3 for correlations in all regions. The red line is the leastsquares
fit.
passing parts of the East Siberian/Chukchi/Beaufort seas and
the Kara/Barents seas. Dates of sea-ice retreat in these regions
trended earlier by 15–18 days decade−1, and dates of
sea-ice advance trended later by 10–13 days decade−1, with
correlations of de-trended dates on the order of −0.8. Their
results are slightly more extreme than ours (Table 3) because
their regions were specifically tailored to include the largest
trends, but our results are nevertheless generally consistent
with theirs.
Parkinson (2014) used daily passive microwave data
(1979–2013) to calculate and map the number of days per
year with sea-ice concentration ≥ 15 %, finding that most
of the Arctic seasonal ice zone (roughly all regions in
Fig. 1 except the Arctic Basin) is experiencing a loss of 10–
20 days decade−1, with the most rapid loss in the Barents
Sea. They also found that the trends are not sensitive to the
15 % threshold, with similar trends obtained using 50 %. The
results are consistent with ours (Table 3) that show a decrease
in the number of ice-covered days.
Frey et al. (2015) used daily passive microwave data
(1979–2012) to study the timing of sea-ice breakup, freezeup,
and persistence in the Beaufort, Chukchi, and Bering
seas, finding trends toward earlier breakup and later freezeup
in the Beaufort and Chukchi seas, with steeper trends
since 2000. They also used wind and air temperature data
to determine that for the localized areas that are experiencing
the most rapid shifts in sea ice, those in the Beaufort Sea
are primarily wind driven, while those offshore in the Canada
Basin are primarily thermally driven.
Figure 10. Trend map of the date of spring sea-ice retreat for the
shallow parts of each PBSG region. Trends are also given in Table 4.
Steele et al. (2015) looked at the timing of sea-ice retreat in
the southeastern and southwestern Beaufort Sea using daily
sea-ice concentration data (1979–2012). They found no trend
in the date of retreat in the southeastern Beaufort Sea but did
find a trend toward earlier retreat in the southwestern Beaufort
Sea. Furthermore, an increase in monthly mean easterly
winds of ∼ 1 m s−1 during spring was associated with an earlier
summer sea-ice retreat of 6–15 days, offering predictive
capability of sea-ice retreat with 2 to 4 months of lead time.
Our methods in the present study are based on our previous
work. Laidre et al. (2015a) calculated the timing of
sea-ice advance and retreat in 12 Arctic regions (1979–2013)
for the Conservation of Arctic Flora and Fauna (CAFF) Arctic
Biodiversity Assessment (ABA). Laidre et al. (2015b)
focused on polar bear habitat in East Greenland, including
changes in the timing of sea-ice advance and retreat. Laidre
et al. (2012) examined narwhal sea-ice entrapments and the
timing of fall sea-ice advance in six narwhal summering areas
of Baffin Bay. Heide-Jørgensen et al. (2013) considered
changes in the timing of spring sea-ice retreat in the North
Water Polynya. All these studies found trends toward earlier
spring sea-ice retreat and later fall sea-ice advance from the
1980s to present.
Our sea-ice metrics are currently being used in the
IUCN PBSG Status Table (http://pbsg.npolar.no/en/status/
status-table.html), the primary source of scientific information
for managers, nongovernmental organizations, and the
public on the status of the world’s polar bears. The Status Table
includes trends in the dates of spring sea-ice retreat, fall
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H. L. Stern and K. L. Laidre: Sea-ice indicators of polar bear habitat 2037
Figure 11. Trend map of the date of fall sea-ice advance for the
shallow parts of each PBSG region. Trends are also given in Table 4.
sea-ice advance, and summer (June–October) sea-ice concentration
for each of the 19 polar bear subpopulations, as
reported here, and will be updated accordingly. The IUCN
Red List assessment of polar bears (Wiig et al., 2015) used
the number of ice-covered days per year as its sea-ice metric,
as presented here in Sect. 3.4.
5.2 Relevance to other Arctic marine mammal species
While the metrics reported here were tailored specifically to
polar bears and polar bear ecology, they can be considered
relevant for a range of other AMM species. Besides the polar
bear, AMMs are typically considered to be three cetacean
species (the narwhal, Monodon monoceros; beluga, Delphinapterus
leucas; and bowhead whale, Balaena mysticetus)
and seven pinniped species (the ringed seal, Pusa hispida;
bearded seal, Erignathus barbatus; spotted seal, Phoca
largha; ribbon seal, Phoca fasciata; harp seal, Pagophilus
groenlandicus; hooded seal, Cystophora cristata; and walrus,
Odobenus rosmarus) (Laidre et al., 2008; Laidre et al.,
2015a). These species all occur north of the Arctic Circle for
most of the year and depend on the Arctic marine ecosystem
for all aspects of life. In a few cases some may live outside
the Arctic for part of the year. All depend on the timing of
sea-ice advance and retreat for different aspects of their life
history, and thus the metrics in this study may be relevant
to understanding changes in the regions where these AMMs
occur.
Figure 12. Trend map of the length of the summer season for the
shallow parts of each PBSG region. Trends are also given in Table 4.
5.3 Variability in the timing of sea-ice advance and
retreat
The dates of sea-ice advance and retreat, as shown in Figs. 4
and S2, vary about the trend lines. Some regions such as East
Greenland have high year-to-year variability, while other regions
such as Foxe Basin have low year-to-year variability
(as measured, for example, by the standard deviation of the
residuals about the trend line). The high variability is likely
due to advection of sea ice through the region due to wind
and currents, while the low variability indicates a lack of such
advection, as noted by Laidre et al. (2012), who found that
three sheltered sites on the western side of Baffin Bay had
low variability in fall freeze-up dates, while sites near the
North Water Polynya in northern Baffin Bay, and in the East
Greenland Current, had high variability. In regions where
sea-ice advance and retreat are primarily driven by thermodynamics,
the year-to-year variability will be lower than in
regions where wind and currents are strong.
5.4 Correlation of dates of sea-ice retreat and advance
The negative correlations between the de-trended dates of
sea-ice retreat and advance (Tables 3 and 4) are likely the result
of the ice–albedo feedback, noted also by Stammerjohn
et al. (2012). When sea ice retreats earlier than average in
spring, the ocean has more time to absorb heat from the sun.
The extra heat is stored in the upper ocean through the summer,
and must be released to the atmosphere in the fall before
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2038 H. L. Stern and K. L. Laidre: Sea-ice indicators of polar bear habitat
Table 4. Same as Table 3 but for the shallow (≤ 300 m) portions of each region.
Subpopulation Spring Fall Fall–spring Jun–Oct Ice-covered Correlation of
trend trend trend ice concentration days dates
Kane Basin −9.7 ** 5.5 ** 15.2 ** −6.9 ** −15.1 ** −0.36 *
Baffin Bay −8.4 ** 9.7 ** 18.1 ** −3.3 ** −19.8 ** −0.54 **
Lancaster Sound −7.6 ** 4.6 ** 12.2 ** −4.3 ** −11.2 ** −0.35 *
Norwegian Bay −1.3 4.2 5.5 −1.6 −7.0 ** −0.21
Viscount Melville −4.3 6.9 11.2 * −4.3 ** −11.7 ** 0.31
Northern Beaufort −5.6 3.5 ** 9.1 * −3.6 * −8.5 * −0.62 **
Southern Beaufort −7.3 ** 8.6 ** 15.9 ** −7.9 ** −15.5 ** −0.53 **
M’Clintock Channel −4.1 ** 5.8 ** 10.0 ** −5.2 ** −11.0 ** −0.74 **
Gulf of Boothia −8.6 ** 7.6 ** 16.2 ** −9.0 ** −18.8 ** −0.57 **
Foxe Basin −5.2 ** 5.6 ** 10.9 ** −3.2 ** −11.3 ** −0.57 **
Western Hudson Bay −5.1 ** 3.5 ** 8.7 ** −2.9 ** −8.6 ** −0.25
Southern Hudson Bay −3.0 * 3.6 * 6.6 ** −1.8 * −6.8 ** −0.35
Davis Strait −6.9 ** 8.0 ** 14.9 ** −1.9 ** −14.7 ** −0.26
East Greenland −4.5 ** 4.6 ** 9.0 ** −3.0 * −9.4 ** −0.30
Barents Sea −17.0 ** 21.0 ** 37.9 ** −4.2 ** −44.6 ** −0.46 **
Kara Sea −8.8 ** 7.0 ** 15.8 ** −7.3 ** −16.2 ** −0.47 **
Laptev Sea −6.8 ** 6.5 ** 13.3 ** −9.1 ** −13.2 ** −0.77 **
Chukchi Sea −4.1 ** 5.4 ** 9.5 ** −4.1 ** −9.1 ** −0.39 *
Arctic Basin −9.4 ** 16.8 ** 26.1 ** −9.0 ** −29.3 ** −0.18
sea ice can begin to form, thus delaying fall freeze-up. Conversely,
a late spring sea-ice retreat prevents the ocean from
absorbing as much heat, allowing sea ice to form earlier in
the fall (e.g., Perovich et al., 2007). The negative correlations
are not perfect because other factors contribute to the timing
of sea-ice retreat and advance, such as short-term weather
events and long-term climate patterns. This is also discussed
in more detail by Blanchard et al. (2011), who attributed the
“re-emergence of memory” in the fall to the several-month
persistence of sea surface temperatures (SSTs) over the summer,
enhanced by the ice–albedo feedback. We calculated the
correlation of the date of fall sea-ice advance in year n with
the date of spring sea-ice retreat in year n + 1, but the correlation
was not significant in any region, suggesting that SST
anomalies do not persist through the winter.
5.5 Sea-ice area vs. extent
Some sea-ice studies use sea-ice extent, rather than sea-ice
area, to characterize sea-ice coverage. Sea-ice extent is the
total area of all grid cells with sea-ice concentration greater
than 15 %, i.e., not weighted by the sea-ice concentration.
If the sea-ice concentration in a grid cell exceeds 15 %, the
entire area of the grid cell counts toward the sea-ice extent.
This is useful in some contexts, but we believe that sea-ice
area is a better measure of how much usable sea ice is actually
present for polar bears. Also, sea-ice extent is a highly
nonlinear function of sea-ice concentration, which leads to
more abrupt jumps in its time series than sea-ice area.
5.6 Melt onset and freeze-up
Some investigators have approached the idea of seasonal
transitions in the Arctic by examining the dates of melt onset
in the spring and freeze-up in the fall, based on the presence
of liquid water in the surface layer of the ice or snow (Winebrenner
et al., 1994, 1996; Smith, 1998; Belchansky et al.,
2004; Markus et al., 2009; Stroeve et al., 2014). In these studies,
melt onset and freeze-up are closely tied to the surface
air temperature, but they are not indicators of sea-ice coverage
or condition. For example, at the SHEBA station in the
Beaufort Sea in 1997–1998 (Perovich et al., 1999), melt onset
occurred on 29 May when rain fell, but the sea ice did not
actually break up until the end of July when a storm passed
through. Similarly in fall, melt ponds on the surface of the ice
began to freeze in mid-August but the sea ice did not actually
consolidate into winter-like pack ice until early October
(Stern and Moritz, 2002). Melt onset and freeze-up dates are
useful as climate metrics, but for ice-dependent marine mammals,
transition dates between seasons are best measured by
the sea-ice coverage itself, rather than proxies tied to air tem-
perature.
5.7 National Climate Assessment (NCA)
The NCA summarizes the impacts of climate change across
the United States, now and into the future, with the goal
of better informing public and private decision-making at
all levels. The third NCA report was released in May 2014
(Melillo et al., 2014). It documents the decline of Arctic seaice
extent, thickness, and volume, but not changes in the timing
of sea-ice advance and retreat. One of the motivations of
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H. L. Stern and K. L. Laidre: Sea-ice indicators of polar bear habitat 2039
the present study was to develop a sea-ice climate metric (or
indicator) with relevance to marine mammals that could be
used in future NCA reports. The timing of sea-ice advance
and retreat satisfies all the qualifications for climate indicators
put forward by the NCA (NCA, 2011).
6 Conclusions
It is well established that the area of Arctic sea ice is declining
in all months of the year, based on satellite passive microwave
data from 1979 to the present (Fetterer et al., 2016;
IPCC, 2013). In this study we looked instead at the timing of
sea-ice retreat in spring and advance in fall, because the duration
of the sea-ice season (or equivalently the ice-free season)
is important for polar bears. We found that there has been a
consistent and large loss of habitat for polar bears across the
Arctic. In 17 of the 19 subpopulation regions there are significant
trends toward earlier spring sea-ice retreat, mostly
ranging from −3 to −9 days decade−1. In 16 of the regions
there are significant trends toward later fall sea-ice advance,
mostly ranging from +3 to +9 days decade−1. Over the 3.5
decades of this study, the time interval from the date of spring
retreat to the date of fall advance has lengthened by 3 to 9
weeks in most regions.
General circulation models (GCMs) predict ice-free Arctic
summers by mid-century or sooner (IPCC, 2013; Overland
and Wang, 2013). Spring sea-ice retreat will continue
to arrive earlier and fall sea-ice advance will continue to arrive
later, with no reversal in sight. Barnhart et al. (2015)
used daily sea-ice output from a 30-member GCM ensemble,
driven by the business-as-usual emissions scenario (RCP
8.5), to map the annual duration of open water in the Arctic
through 2100. They found that by 2050 the entire Arctic
coastline and most of the Arctic Ocean will experience an
additional 1 to 2 months of open water per year, relative to
present conditions, which is consistent with extrapolation of
the trends in Table 3.
What are the implications of these physical changes for
the global population of polar bears? Their dependence on
sea-ice means that climate warming poses the single most
important threat to their persistence (Stirling and Derocher,
2012; USFWS, 2013). Changes in sea ice have been shown to
impact polar bear abundance, productivity, body condition,
and distribution (Stirling et al., 1999; Durner et al., 2009;
Regehr et al., 2010; Rode et al., 2012, 2014; Bromaghin et
al., 2015; Obbard et al., 2016). Furthermore, population and
habitat models predict substantial declines in the distribution
and abundance of polar bears in the future (Durner et al.,
2009; Amstrup et al., 2008; Castro de la Guardia et al., 2013;
Hamilton et al., 2014). This study offers standardized metrics
with which to compare polar bear habitat change across the
19 subpopulations and provides a starting point for including
sea-ice habitat change in circumpolar polar bear management
and conservation plans.
The Supplement related to this article is available online
at doi:10.5194/tc-10-2027-2016-supplement.
Author contributions. Harry L. Stern carried out the sea-ice calculations
in consultation with Kristin L. Laidre; Harry L. Stern and
Kristin L. Laidre prepared the manuscript.
Acknowledgements. This work was supported by NASA under
the programs Development and Testing of Potential Indicators
for the National Climate Assessment, grant NNX13AN28G (PI:
Harry L. Stern), and Climate and Biological Response, grant
NNX11A063G (PI: Kristin L. Laidre). We also acknowledge
support from the Greenland Institute of Natural Resources. We
thank the National Snow and Ice Data Center in Boulder for sea-ice
concentration data, and NOAA for bathymetry data (ETOPO1).
We thank Eric Regehr, Steve Amstrup, and Cecilia Bitz for
conversations about sea-ice metrics. We thank the PBSG for input
during the development of the metrics. We thank Andy Derocher
and one anonymous reviewer for comments that helped to improve
the paper.
Edited by: C. Haas
Reviewed by: two anonymous referees
References
Amante, C. and Eakins, B. W.: ETOPO1 1 Arc-Minute Global
Relief Model: Procedures, Data Sources and Analysis, NOAA
Technical Memorandum NESDIS NGDC-24, National Geophysical
Data Center, NOAA, doi:10.7289/V5C8276M, 2009.
Amstrup, S. C., Marcot, B. G., and Douglas, D. C.: A Bayesian network
modeling approach to forecasting the 21st century worldwide
status of polar bears, in: Arctic Sea Ice Decline: Observations,
Projections, Mechanisms and Implications, edited by:
DeWeaver, E. T., Bitz, C. M., and Tremblay, L. B., Geophysical
Monograph Series 180, American Geophysical Union, Washington,
DC, USA, 213–268, 2008.
Barnhart, K. R., Miller, C. R., Overeem, I., and Kay, J. E.: Mapping
the future expansion of Arctic open water, Nature Climate
Change, 6, 280–285, doi:10.1038/NCLIMATE2848, 2015.
Belchansky, G. I., Douglas, D. C., and Platonov, N. G.: Duration of
the Arctic Sea Ice Melt Season: Regional and Interannual Variability,
1979–2001, J. Climate, 17, 67–80, 2004.
Blanchard, E., Armour, K. C., and Bitz, C. M.: Persistence
and Inherent Predictability of Arctic Sea Ice in a
GCM Ensemble and Observations, J. Climate, 24, 231–250,
doi:10.1175/2010JCLI3775.1, 2011.
Bromaghin, J. F., McDonald, T. L., Stirling, I., Derocher, A. E.,
Richardson, E. S., Regehr, E. V., Douglas, D. C., Durner, G. M.,
Atwood, T., and Amstrup, S. C.: Polar bear population dynamics
in the southern Beaufort Sea during a period of sea ice decline,
Ecol. Appl., 25, 634–651, doi:10.1890/14-1129.1, 2015.
www.the-cryosphere.net/10/2027/2016/ The Cryosphere, 10, 2027–2041, 2016
2040 H. L. Stern and K. L. Laidre: Sea-ice indicators of polar bear habitat
Castro de la Guardia, L., Derocher, A. E., Myers, P. G., Terwisscha
van Scheltinga, A. D., and Lunn, N. J.: Future sea ice conditions
in Western Hudson Bay and consequences for polar bears in the
21st century, Glob. Change Biol., 19, 2675–2687, 2013.
Cavalieri, D. J., Parkinson, C. L., Gloersen, P., and Zwally, H. J.: Sea
Ice Concentrations from Nimbus-7 SMMR and DMSP SSM/ISSMIS
Passive Microwave Data, Version 1, Boulder, Colorado
USA, NASA National Snow and Ice Data Center Distributed
Active Archive Center, doi:10.5067/8GQ8LZQVL0VL, updated
yearly, 1996.
Cherry, S. G., Derocher, A. E., Thiemann, G. W., and Lunn, N. J.:
Migration phenology and seasonal fidelity of an Arctic marine
predator in relation to sea ice dynamics, J. Animal Ecology, 82,
912–921, doi:10.1111/1365-2656.12050, 2013.
Durner, G. M., Douglas, D. C., Nielson, R. M., Amstrup, S. C.,
McDonald, T. L., Stirling, I., Mauritzen, Born, E. W., Wiig, Ø.,
DeWeaver, E. T., Serreze, M. C., Belikov, S. E., Holland, M. M.,
Maslanik, J., Aars, J., Bailey, D. A., and Derocher, A. E.: Predicting
21st-century polar bear habitat distribution from global climate
models, Ecol. Monogr., 79, 25–58, doi:10.1890/07-2089.1,
2009.
Fetterer, F., Knowles, K., Meier, W., and Savoie, M.: Sea Ice Index,
updated daily, Boulder, Colorado USA: National Snow and Ice
Data Center, doi:10.7265/N5QJ7F7W, 2016.
Frey, K. E., Moore, G. W. K., Cooper, L. W., and Grebmeier, J.
M.: Divergent patterns of recent sea ice cover across the Bering,
Chukchi, and Beaufort seas of the Pacific Arctic Region, Prog.
Oceanogr., 136, 32–49, 2015.
Hamilton, S. G., Castro de la Guardia, L., Derocher, A. E., Sahanatien,
V., and Tremblay, B.: Projected Polar Bear Sea Ice Habitat
in the Canadian Arctic Archipelago, PLoS ONE, 9, e113746,
doi:10.1371/journal.pone.0113746, 2014.
Heide-Jørgensen, M. P., Burt, M. L., Hansen, R. G., Nielsen, N. H.,
Rasmussen, M., Fossette, S., and Stern, H.: The Significance of
the North Water Polynya to Arctic Top Predators, AMBIO, 42,
596–610, doi:10.1007/s13280-012-0357-3, 2013.
IPCC: Climate Change 2013: The Physical Science Basis, in: Contribution
of Working Group I to the Fifth Assessment Report
of the Intergovernmental Panel on Climate Change, edited by:
Stocker, T. F., Qin, D., Plattner, G.-K., Tignor, M., Allen, S. K.,
Boschung, J., Nauels, A., Xia, Y., Bex, V., and Midgley, P. M.,
Cambridge University Press, Cambridge, United Kingdom and
New York, NY, USA, 1535 pp., 2013.
Ivanova, N., Pedersen, L. T., Tonboe, R. T., Kern, S., Heygster,
G., Lavergne, T., Sørensen, A., Saldo, R., Dybkjær, G.,
Brucker, L., and Shokr, M.: Inter-comparison and evaluation
of sea ice algorithms: towards further identification of challenges
and optimal approach using passive microwave observations,
The Cryosphere, 9, 1797–1817, doi:10.5194/tc-9-1797-
2015, 2015.
Laidre, K. L., Stern, H., Kovacs, K. M., Lowry, L., Moore, S.,
Regehr, E. V., Ferguson, S., Wiig, Ø., Boveng, P., Angliss, R.
P., Born, E. W., Litovka, D., Quakenbush, L., Lydersen, C.,
Vongraven, D., and Ugarte, F.: Arctic marine mammal population
status, sea ice habitat loss, and conservation recommendations
for the 21st century, Conserv. Biol., 29, 724–737,
doi:10.1111/cobi.12474, 2015a.
Laidre, K. L., Born, E. W., Heagerty, P., Wiig, Ø., Stern, H., Dietz,
R., Aars, J., and Andersen, M.: Shifts in female polar bear (Ursus
maritimus) habitat use in East Greenland, Polar Biol., 38, 879–
893, doi:10.1007/s00300-015-1648-5, 2015b.
Laidre, K., Heide-Jørgensen, M. P., Stern, H., and Richard, P.: Unusual
narwhal sea ice entrapments and delayed autumn freeze-up
trends, Polar Biol., 35, 149–154, doi:10.1007/s00300-011-1036-
8, 2012.
Laidre, K. L., Stirling, I., Lowry, L., Wiig, Ø., Heide-Jørgensen,
M. P., and Ferguson, S.: Quantifying the sensitivity of arctic marine
mammals to climate-induced habitat change, Ecol. Appl.,
18, S97–S125, 2008.
Lunn, N., Servanty, S., Regehr, E., Converse, S., Richardson, E.,
and Stirling, I.: Demography and population status of polar bears
in Western Hudson Bay, Environment Canada research report,
2014.
Markus, T., Stroeve, J. C., and Miller, J.: Recent changes in Arctic
sea ice melt onset, freezeup, and melt season length, J. Geophys.
Res., 114, C12024, doi:10.1029/2009JC005436, 2009.
Melillo, J. M., Terese, T. C. R., and Gary, W. Y. (Eds.): Climate
Change Impacts in the United States: The Third National Climate
Assessment, US Global Change Research Program, 841 pp.
doi:10.7930/J0Z31WJ2, 2014.
NCA: The United States National Climate Assessment, NCA Report
Series, Volume 5b, Monitoring Climate Change and its Impacts:
Physical Climate Indicators, 32 pp., 2011.
NSIDC: Documentation at: http://nsidc.org/data/docs/daac/
nsidc0051_gsfc_seaice.gd.html, 2015.
Obbard, M., McDonald, T. L., Howe, E. J., Regehr, E. V., and
Richardson, E. S.: Polar Bear Population Status in Southern Hudson
Bay, Canada, USGS Administrative report, 2007.
Obbard, M. E., Thiemann, G. W., Peacock, E., and DeBruyn, T.
D. (Eds.): Polar Bears: Proceedings of the 15th Working Meeting
of the IUCN/SSC Polar Bear Specialist Group, Copenhagen,
Denmark, 29 June–3 July 2009, IUCN, Gland, Switzerland and
Cambridge, UK, 235 pp., 2010.
Obbard, M. E., Cattet, M. R. L., Howe, E. J., Middel, K. R., Newton,
E. J., Kolenosky, G. B., Abraham, K. F., and Greenwood, C. J.:
Trends in body condition in polar bears (Ursus maritimus) from
the Southern Hudson Bay subpopulation in relation to changes
in sea ice, Arct. Sci., 2, 15–32, doi:10.1139/as-2015-0027, 2016.
Overland, J. E. and Wang, M.: When will the summer Arctic
be nearly sea ice free?, Geophys. Res. Lett., 40, 2097–2101,
doi:10.1002/grl.50316, 2013.
Paetkau, D., Amstrup, S. C., Born, E .W., Calvert, W., Derocher, A.
E., Garner, G. W., Messier, F., Stirling, I., Taylor, M. K., Wiig,
Ø., and Strobeck, C.: Genetic structure of the world’s polar bear
populations, Molecular Ecol., 8, 1571–1584, 1999.
Parkinson, C. L.: Spatially mapped reductions in the length of
the Arctic sea ice season, Geophys. Res. Lett., 41, 4316–4322,
doi:10.1002/2014GL060434, 2014.
Parkinson, C. L. and Cavalieri, D. J.: Arctic sea ice variability
and trends, 1979–2006, J. Geophys. Res., 113, C07003,
doi:10.1029/2007JC004558, 2008.
Peacock, E., Laake, J., Laidre, K. L., Born, E., and Atkinson, S.: The
utility of harvest recoveries of marked individuals to assess polar
bear (Ursus maritimus) survival, Arctic, 65, 391–400, 2012.
Peacock, E., Taylor, M. K., Laake, J., and Stirling, I.: Population
ecology of polar bears in Davis Strait, Canada and Greenland, J.
Wildlife Manage., 77, 463–476, 2013.
The Cryosphere, 10, 2027–2041, 2016 www.the-cryosphere.net/10/2027/2016/
H. L. Stern and K. L. Laidre: Sea-ice indicators of polar bear habitat 2041
Peacock, E., Sonsthagen, S. A., Obbard, M. E., Boltunov, A.,
Regehr, E. V., Ovsyanikov, N., Aars, J., Atkinson, S. N., Sage,
G. ., Hope, A. G., Zeyl, E., Bachmann, L., Ehrich, D., Scribner,
K. T., Amstrup, S. C., Belikov, S., Born, E. W., Derocher, A.
E., Stirling, I., Taylor, M. K., Wiig, Ø., Paetkau, D., and Talbot,
S. L.: Implications of the circumpolar genetic structure of polar
bears for their conservation in a rapidly warming Arctic, PLoS
ONE, 10, e11202, doi:10.1371/journal.pone.0112021, 2015.
Perovich, D. K. and Richter-Menge, J. A.: Loss of Sea Ice in the
Arctic, Annu. Rev. Mar. Sci., 1, 417–441, 2009.
Perovich, D. K., Light, B., Eicken, H., Jones, K. F., Runciman,
K., and Nghiem, S. V.: Increasing solar heating of the Arctic
Ocean and adjacent seas, 1979–2005: Attribution and role
in the ice-albedo feedback, Geophys. Res. Lett., 34, L19505,
doi:10.1029/2007GL031480, 2007.
Perovich, D. K., Andreas, E. L., Curry, J. A., Eiken, H., Fairall, C.
W., Grenfell, T. C., Guest, P. S., Intrieri, J., Kadko, D., Lindsay,
R. W., McPhee, M. G., Morison, J., Moritz, R. E., Paulson, C. A.,
Pegau, W. S., Persson, P. O. G., Pinkel, R., Richter-Menge, J. A.,
Stanton, T., Stern, H., Sturm, M., Tucker III, W. B., and Uttal, T.:
Year on Ice Gives Climate Insights, Eos, Transactions, American
Geophysical Union, 80, 41, 485–486, 1999.
Regehr, E. V., Lunn, N. J., Amstrup, S. C., and Stirling, I.: Effects of
earlier sea ice breakup on survival and population size of polar
bears in western Hudson Bay, J. Wildlife Manage., 71, 2673–
2683, doi:10.2193/2006-180, 2007.
Regehr, E. V., Hunter, C. M., Caswell, H., Amstrup, S. C., and
Stirling, I.: Survival and breeding of polar bears in the southern
Beaufort Sea in relation to sea-ice, J. Animal Ecol., 79, 117–127,
2010.
Regehr, E. V., Wilson, R. R., Rode, K. D., and Runge, M. C.: Resilience
and risk – A demographic model to inform conservation
planning for polar bears, US Geological Survey Open-File Report
2015–1029, 56 pp., doi:10.3133/ofr20151029, 2015.
Rode, K. D., Peacock, E., Taylor, M., Stirling, I., Born, E. W.,
Laidre, K. L., and Wiig, Ø.: A tale of two polar bear populations:
Ice habitat, harvest, and body condition, Population Ecology, 54,
3–18, doi:10.1007/s10144-011-0299-9, 2012.
Rode, K. D., Regehr, E. V., Douglas, D. C., Durner, G., Derocher,
A. E., Thiemann, G. W., and Budge, S. M.: Variation in the
response of an Arctic top predator experiencing habitat loss:
feeding and reproductive ecology of two polar bear populations,
Glob. Change Biol., 20, 76–88, 2014.
Smith, D. M.: Recent increase in the length of the melt season of
perennial Arctic sea ice, Geophys. Res. Lett., 25, 655–658, 1998.
Stammerjohn, S., Massom, R., Rind, D., and Martinson, D.:
Regions of rapid sea ice change: An inter-hemispheric
seasonal comparison, Geophys. Res. Lett., 39, L06501,
doi:10.1029/2012GL050874, 2012.
Steele, M., Dickinson, S., Zhang, J., and Lindsay, R.: Seasonal
ice loss in the Beaufort Sea: Toward synchrony
and prediction, J. Geophys. Res.-Oceans, 120, 1118–1132,
doi:10.1002/2014JC010247, 2015.
Stern, H. L. and Moritz, R. E.: Sea ice kinematics and surface
properties from RADARSAT synthetic aperture radar
during the SHEBA drift, J. Geophys. Res., 107, 8028,
doi:10.1029/2000JC000472, 2002.
Stirling, I. and Derocher, A. E.: Effects of climate warming on polar
bears: a review of the evidence, Glob. Change Biol., 18, 2694–
2706, doi:10.1111/j.1365-2486.2012.02753.x, 2012.
Stirling, I. and Parkinson, C. L.: Possible Effects of Climate Warming
on Selected Populations of Polar Bears (Ursus maritimus) in
the Canadian Arctic, Arctic, 59, 261–275, 2006.
Stirling, I., Lunn, N. J., and Iacozza, J.: Long-term trends in the population
ecology of polar bears in western Hudson Bay in relation
to climatic change, Arctic, 52, 294–306, 1999.
Stirling, I., McDonald, T., Richardson, E. S., Regehr, E. V., and Amstrup,
S.: Polar bear population status in the northern Beaufort
Sea, Canada, 1971–2006, Ecol. Appl., 21, 859–876, 2011.
Stroeve, J. C., Serreze, M. C., Holland, M. M., Kay, J. E., Malanik,
J., and Barrett, A. P.: The Arctic’s rapidly shrinking sea ice cover:
a research synthesis, Climatic Change, 110, 1005–1027, 2012.
Stroeve, J. C., Markus, T., Boisvert, M., and Barrett, A.: Changes
in Arctic melt season and implications for sea ice loss, Geophys.
Res. Lett., 41, 1216–1225, doi:10.1002/2013GL058951, 2014.
US Fish and Wildlife Service (USFWS): Endangered and Threatened
Wildlife and Plants; Special Rule for the Polar Bear Under
Section 4(d) of the Endangered Species Act, Federal Register 78,
34, 11766–11788, Washington, D.C., USA, 2013.
Vongraven, D., Aars, J., Amstrup, S., Atkinson, S. N., Belikov, S.,
Born, E. W., DeBruyn, T. D., Derocher, A. E., Durner, G., Gill,
M., Lunn, N., Obbard, M. E., Omelak, J., Ovsyanikov, N., Peacock,
E., Richardson, E., Sahanatien, V., Stirling, I., and Wiig,
Ø.: A circumpolar monitoring framework for polar bears, Ursus,
Vol. 23, Special Issue: Monograph Series Number 5, 1–66, 2012.
Wiig, Ø., Amstrup, S., Atwood, T., Laidre, K., Lunn, N., Obbard,
M., Regehr, E., and Thiemann, G.: Polar Bear (Ursus
maritimus), The IUCN Red List of Threatened Species 2015,
doi:10.2305/IUCN.UK.2015-4.RLTS.T22823A14871490.en,
2015.
Winebrenner, D. P., Holt, B., and Nelson, E. D.: Observation of autumn
freeze-up in the Beaufort and Chukchi Seas using the ERS
1 synthetic aperture radar, J. Geophys. Res., 101, 16401–16419,
1996.
Winebrenner, D. P., Nelson, E. D., Colony, R., and West, R. S.: Observation
of melt onset on multiyear Arctic sea ice using the ERS
1 synthetic aperture radar, J. Geophys. Res., 99, 22425–22441,
1994.
www.the-cryosphere.net/10/2027/2016/ The Cryosphere, 10, 2027–2041, 2016