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The mean home range size of female polar bears (Ursus maritimus; 125 100 km2 ± 11 800; n = 93) is substantially larger than the predicted value (514 km2) for a terrestrial carnivore of similar weight. To understand this difference, we correlated home range size and sea ice characteristics. Home range size was related to (i) the ratio of land vs. sea within a given home range (42% of explained variance), and (ii) seasonal variation in ice cover (24%). Thus, bears using land during the ice-free season had larger home ranges and bears living in areas of great seasonal variation in ice cover also had larger home ranges. In another analysis we investigated how variation in a bear’s environment in space and time affects its choice of home range. We found that polar bears adjusted the size of their home range according to the amount of annual and seasonal variation within the centre of their home range. For example, polar bears experiencing unpredictable seasonal and annual ice tended to increase their home range size if increasing home range size resulted in reducing variation in seasonal and annual ice. Polar bears make trade-offs between alternate space-use strategies. Large home ranges occur when variable ice cover is associated with more seals but also a more unpredictable distribution of those seals.
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Determinants of Home Range Size for Polar Bears
(Ursus maritimus)
Abstract
The mean home range size of female polar bears (Ursus maritimus; 125 100 km
2
+11
800; n= 93) is substantially larger than the predicted value (514 km
2
) for a terrestrial
carnivore of similar weight. To understand this difference, we correlated home range
size and sea ice characteristics. Home range size was related to (i) the ratio of land vs.
sea within a given home range (42% of explained variance), and (ii) seasonal variation
in ice cover (24%). Thus, bears using land during the ice-free season had larger home
ranges and bears living in areas of great seasonal variation in ice cover also had larger
home ranges. In another analysis we investigated how variation in a bear's
environment in space and time affects its choice of home range. We found that polar
bears adjusted the size of their home range according to the amount of annual and
seasonal variation within the centre of their home range. For example, polar bears
experiencing unpredictable seasonal and annual ice tended to increase their home
range size if increasing home range size resulted in reducing variation in seasonal and
annual ice. Polar bears make trade-offs between alternate space-use strategies. Large
home ranges occur when variable ice cover is associated with more seals but also a
more unpredictable distribution of those seals.
Keywords
Allometry, Arctic, body size, home range, polar bears, predictability, sea ice,
seasonality, Ursus maritimus, variation
Ecology Letters (1999) 2 : 311±318
INTRODUCTION
Environmental variation can have profound influences on
population processes (Southwood 1988; Abrams 1997;
Johst & Brandl 1997). Animals attempt to reduce
variation in their life processes through space use (e.g.
Wauters & Dhondt 1992) assuming that they can
accurately assess environmental variation (Lima &
Zollner 1996). Reducing variation in life processes can
afford greater fitness provided that geometric mean fitness
is greater than stochastic tracking of environmental
perturbations (Yoshimura & Jansen 1996). This environ-
mental unpredictability would explain the evolution of
homeostatic adaptations by animals to reduce detrimental
environmental variation on survival and reproduction.
Similarly, animals may change behaviour through differ-
ential movement patterns and range use (e.g. seasonal
movements) in an effort to control environmental
heterogeneity and create more stable life history responses
to external perturbations. This pattern of controlling
environmental influences is likely more pronounced in
large animals because of their size.
Recent analyses suggest that polar environments are
highly variable in both time and space (Ferguson &
Messier 1996; Smith et al. 1998), but the implications of
that variability for population processes are basically
unknown. The sea-ice landscape is not only highly
variable seasonally but also highly variable spatially
(Walsh et al. 1979; Smith et al. 1998; Ferguson et al.
1999). Spatial variability, annual fluctuations, and extreme
seasonality of sea ice coverage are linked to inherent
variability characteristic of marine polar ecosystems
(McGowan et al. 1998). External physical forces may play
a more dominant role in causing variability in marine
ecosystems compared to terrestrial ecosystems (Steele
1991; Underwood 1996; Smith et al. 1998). The annual
advance and retreat of sea ice affects all levels of Arctic
marine ecosystems, including the timing and magnitude of
seasonal primary production, the abundance, distribution
and recruitment of zooplankton, and the demography and
#1999 Blackwell Science Ltd/CNRS
Steven H. Ferguson,
1
Mitchell K.
Taylor,
2
Erik W. Born,
3
Aqqalu
Rosing-Asvid,
3
and FrancËois
Messier
1
1
Department of Biology,
University of Saskatchewan, 112
Science Place, Saskatoon, SK,
S7N 5E2, Canada.
E-mail: fergusons@sask.usask.c.
2
Department of Sustainable
Development, Government of
Nunavut, Bag 1340, Iqaluit, NT,
X0 A 0H0, Canada.
3
Greenland Institute of Natural
Resources, PO Box 570, DK-3900
Nuuk, Greenland.
Ecology Letters, (1999) 2: 311±318
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space-use patterns of top predators (Vibe 1967; Smith
et al. 1995).
Polar bear (Ursus maritimus) is an apex predator living
among the Arctic sea ice (Stirling & Derocher 1992). Polar
bears may react to environmental fluctuations or environ-
mental predictability with large home range size (e.g.
Amstrup 1986; Garner et al. 1990). Here, we test whether
large home range sizes of polar bears are due to spatial and
temporal variation in sea ice. We assume that animals
attempt to reduce variation in their life processes through
space and time, and that they can accurately assess
environmental variation. Thus, we predict that polar bears
will adjust home range size to reduce environmental
variation in space and time. For example, if the centre of
their home range shows low temporal variation in ice
characteristics relative to surrounding areas then we predict
smaller home range size. This would include a space-use
strategy whereby polar bears maintain a small home range
within a predictable environment. In contrast, if the centre
of their home range includes high temporal variation in ice
characteristics relative to the surrounding area then we
predict larger home range size. This would include a space-
use strategy whereby polar bears extend their home range
to reduce environmental variation in space and time.
Hence, environmental variability affects decisions on the
parts of the environment that a polar bear incorporates into
its home range and the time that it is used.
METHODS
The arctic environment under study extends south
(608N), north (808N), east (658W), and west (1108W;
Fig. 1). Of the study area (2.3 610
6
km
2
), 55% is covered
by sea ice for at least 6 months of the year. More open
water occurs in the Baffin Bay-Davis Strait area than other
regions. The Arctic region of Canada and Greenland is
dominated by a cycle of almost total ice cover in late
winter and minimum ice extent in September (Collin &
Dunbar 1964; Ferguson et al. 1999).
We used satellite telemetry (Argos Data Collection &
Location System, Fancy et al. 1988) to obtain polar bear
locations (1989±97) every 4 or 6 days (Messier et al. 1994)
from 110 adult female bears equipped with radio collars
(Telonics, Inc., Mesa, Arizona; Messier et al. 1992;
Ferguson et al. 1997). Bears were captured from helicopter
using darting equipment (Stirling et al. 1989) either in
spring (April±May) or autumn (September±October) of
1989±96. The latitude-longitude coordinates received via
satellite were transformed to Universal Transverse
Mercator coordinates using SPANS
TM
GIS (Intera Tydac
Technologies, Inc. 1994).
Nonparametric estimators (e.g. kernel contouring) are
less influenced by outliers than other estimators of home
range size (Silverman 1986; Worton 1989; Seaman &
Powell 1996) which is a concern with nomadic animals
such as polar bears. We chose to use the 95% adaptive
kernel method with varying band width (CALHOME;
Kie et al. 1996). CALHOME uses an adaptive Epanech-
nekov kernel with smoothing done by minimizing least-
squares cross-validation scores. For comparative purposes
we also calculated the 95% fixed kernel estimates of home
range using ``The Home Ranger'', Version 1.5 (F.W.
Hovey, British Columbia Forest Service, Research
Branch, Columbia Forest District, PO Box 9158, R.P.O.
no. 3, Revelstoke, BC, V0E 3K0, Canada). The choice of
home range estimator is probably not important as we
compare home ranges among polar bears. Still, we
considered the adaptive kernel to better represent the
biological home range of a polar bear. Therefore, the
adaptive kernel perimeter estimates were used in sub-
sequent spatial analyses.
We refer to the estimated annual range as ``home
range''. As few as 20 locations are generally required for
dependable kernel estimates of home range (Powell et al.
1997), although all home range estimators remain
sensitive to increasing sample size up to at least n= 500
(Robertson et al. 1998). As a result, we restricted our
analyses to a range in number of locations per bear-year
from 25 to 100 (mean +SD: 61 +25, n= 93) and to
bears that provided more or less continuous locations
(48 days between locations). Thus, denning bears were
excluded (17 of 110 collared bears). As a check for sample
#1999 Blackwell Science Ltd/CNRS
312 S.H. Ferguson et al
Figure 1 Arctic study area showing two examples of home
ranges (95% kernel) of female polar bears in the Arctic
Archipelago (left) and Baffin Bay region (right). Also shown
are various radii (50, 100, 200, and 400 km) that circle the median
location of bear home ranges.
Paper 090 Disc
size bias affecting the observed effects, we included the
number of locations as a covariate in analyses and found
no effect (P40.35). In 13 instances we estimated a
separate home range for the same bear. If the same bear
provided two or three estimates of home range, we
ensured that at least 1 year separated the calculated home
ranges and that family status (e.g. with cubs or solitary)
had changed to avoid dependence.
The perimeter coordinates for each kernel home range
were overlaid upon monthly ice maps to determine
percentage cover of the following habitat characteristics:
land, annual ice (annually melts and reforms), multi-year
ice (survives 41 year), and water. The resolution of
habitat (1 km
2
) matched the resolution of telemetry
locations (Garner et al. 1990; Arthur et al. 1996; Ferguson
et al. 1999). Ice characteristics were derived from ice maps
(1:4 million) to assess seasonal variation (January to
December 1994, n= 12) and annual variation (1987±97,
n= 10). To assess the characteristics of available ice
throughout the study area, we systematically sampled the
intersection points of a 100 6100 km grid (n= 186
points). Coastline habitat represents the relative amount of
coastline within a home range and was measured as the
distance of coastline (1 km wide) divided by the home
range area.
First, we used SD as our variance descriptor and PROC
REG of the Statistical Analysis System (SAS Institute,
Inc. 1991) to compare annual home range size to
environmental factors by multiple linear regression. We
used stepwise selection with entry and exit criteria and
model acceptance set at P50.05. Ten factors considered
important as determinants of home range size included
percentage cover of land, percentage cover of annual ice,
percentage cover of multi-year ice, seasonal variation in
three ice cover characteristics (SD within 12 months of a
year), annual variation in three ice cover characteristics
(SD within 10 years), and amount of coastline habitat. To
avoid data dependence we eliminated percentage water
cover from the sum of habitat proportions (see Aibischer
et al. 1993). All data were log-transformed to meet model
assumptions of normality and uniform variances. Data are
presented as mean +standard error.
Next, we tested whether polar bears adjusted home
range size to reduce unpredictability in sea-ice character-
istics over time and space. We measured spatial variation
using four distances (radii of buffers) from the centre of
each polar bears' home range. We calculated habitat cover
within buffers around the centre (i.e. median longitude
and latitude values) of the home range of female polar
bears (Fig. 1). Radius distances were 50 km (7900 km
2
),
100 km (31 400 km
2
), 200 km (125 700 km
2
) and 400 km
(502 700 km
2
). Temporal variation was measured within
each of these distance buffers as the SD in ice
characteristics (% annual ice, multi-year ice, open water)
over seasons (n= 12 months, year = 1994) or years
(n= 10, years 1987±97). To avoid data-dependence we
did not use the percentage land habitat proportion and
thus habitat proportions do not sum to unity (Aibischer
et al. 1993).
If variation in time increases over distance then we
predict polar bears will maintain relatively small home
ranges. In contrast, we predicted larger home ranges if
variation in ice characteristics decreased over distance (i.e.
more predictable variation with larger buffers). We used
the slope of the relationship between variation (SD) in ice
characteristics and distance from the centre of the home
range as a measure of predictability of ice characteristics.
We assessed the variability in ice characteristics at the
centre of a bears' home range as the y-intercept of this
relationship. The calculated slope and intercept for the
sample of bears was then correlated with home range size.
For example, an increasing home range size with
decreasing slope indicated that bears responded to greater
temporal variability with larger home ranges and the
result of a large home range was greater predictability (i.e.
less seasonal and annual variation in ice characteristics).
An increasing home range size with increasing intercept
indicated that bears living in unpredictable ice over
seasons and years had larger home ranges.
RESULTS
Home range size
Female polar bears had a mean home range size of 125
500 +11 800 km
2
(n= 93) and showed considerable
variation in home range size (range 940±540 700 km
2
,
SD = 43 900; Fig. 2). Polar bears showed differences in
home range size among populations (Table 1). For
example, bears from the Kane Basin region had smaller
home ranges (19 400 km
2
+4200, n= 11, range = 5300±
32 100 km
2
) than bears from the Baffin Bay region (192 000
km
2
+16 500, n= 14, range = 63 300±332 500 km
2
;
t=5.1, P50.001). Data from 10 bears with more than
one estimated home range showed that polar bears tended
not to maintain similar sizes of annual home ranges from
year to year (r
2
=0.23, n= 13, year 1 vs. year 2, P=0.10).
Home range size of polar bears estimated from
telemetry data was significantly larger than predicted
based on allometric regression of mammalian carnivore
species living in terrestrial environments. We used 256 kg
as the mean female polar bear weight (Cattet et al. 1997;
n= 255). Polar bear home ranges estimated using
adaptive or fixed kernel methods were almost two orders
of magnitude greater than predicted by Lindstedt et al.
1986) allometric equation (Fig. 3). Estimated home range
#1999 Blackwell Science Ltd/CNRS
Polar bear home range size 313
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sizes using fixed kernel estimators were 26 +6.9%
smaller than adaptive kernel estimates of home range size
(see also Powell et al. 1997).
Environmental correlates of home range size
The amount (% cover) of land, seasonal variation in
annual ice, and coastline habitat contributed significantly
to variation of home range size (Table 2). The amount of
land in a polar bears' home range explained 42% of the
variation in home range size. Polar bears living in areas
where ice ablation occurred during late summer and
autumn were forced to live on land for 2±3 months while
awaiting the return of ice (e.g. Baffin Bay). In other areas
where multi-year ice was available during summer, polar
bears were able to use ice all year (e.g. Arctic
Archipelago). Bears that lived on land during the late
summer ice-free period had the largest home range sizes as
indicated by the strong positive correlation between
percentage land and home range size. The amount of
seasonal variation in sea ice explained 24% of the
variation in home range size. Bears living in areas of
great seasonal variation in ice cover had larger home
ranges. The amount of coastline habitat explained 5% of
the variation in home range size of polar bears. Bears
living in areas with more coastline had smaller home
ranges than bears living in areas of less coastline.
Sea-ice predictability and home range size
Seasonal variation in amount of annual ice, multi-year ice,
and water varied with distance from the centre of home
ranges of polar bears (Table 3). For example, polar bears
with larger home ranges had greater seasonal variation in
#1999 Blackwell Science Ltd/CNRS
314 S.H. Ferguson et al
Table 1 Home range size (km
2
) for female polar bears by population 1989±97 (ANOVA test:
F
6,91
= 6.73, P50.001)
Population nMean Standard error Significance*
Davis Strait 5 228300 59400 a
Baffin Bay 32 192000 16500 a
Queen Elizabeth Islands 4 144800 109600 abc
Parry Channel 29 107700 20100 abc
Viscount-Melville Sound 9 53300 18700 bc
Gulf of Boothia 7 32500 8000 bc
Kane Basin 7 19400 4200 c
Total 93 125500 11800
*Means with the same letter do not differ significantly from each other using Tukey's multiple
comparison test (P40.050). Names of populations as per Taylor & Lee (1995).
Figure 2 Frequency distribution of polar bear home ranges
(n= 93) by intervals of 50 000 km
2
in the Canadian Arctic,
including Baffin Bay and Davis Strait regions 1989±97.
Figure 3 Regression of home range area on body mass for
terrestrial carnivores (*) (Lindstedt et al. 1986) showing 95%
prediction interval relative to polar bear home range size
calculated using adaptive kernel method (^) and fixed kernel
method (26% smaller). Both axis are presented in log-scales.
Paper 090 Disc
ice-free cover near the centre of their home range (i.e.
high intercept value; P= 0.04). Also, polar bears with
large home ranges tended to have a negative relationship
between variation in ice-free cover and distance (i.e. high
negative slope value; P= 0.07). This relationship indi-
cates that by increasing home range size bears decreased
unpredictability in ice-free cover.
A similar pattern was evident for seasonal variation in
annual ice (Table 3), although the slope and home range
size relationship was not significant (P= 0.17). A positive
relationship between the intercept and seasonal variation
in annual ice (P= 0.02) suggests that bears with a
relatively small amount of variation near the centre of
their home range (i.e. small intercept value) had smaller
home range size. In contrast, bears with unpredictable
annual ice at the centre of their home range were likely to
have larger home ranges. Larger home ranges had the
effect of reducing seasonal variation in ice cover (i.e.
reducing unpredictability).
Seasonal variation in multi-year ice over distance
showed the opposite pattern relative to annual ice (Table
3). Polar bears with variation in multi-year ice that
decreased with distance from the centre of their home
range had smaller home ranges (P= 0.04).
Annual variation in ice characteristics was also
correlated with distance (radius) from the centre of home
ranges (Table 3). The same patterns observed for seasonal
variation with distance were observed for annual varia-
tion. Polar bears had larger home ranges if they
experienced (i) greater unpredictability in water/annual
ice cover at the centre of their home range, or (ii) lower
variation in water/annual ice cover with distance from the
centre of their home range. Again, the opposite pattern
was evident for multi-year ice.
DISCUSSION
Home range size of polar bears was larger than other
mammalian carnivores which are adapted to terrestrial
environments. To explain this discrepancy, we tested for
determinants of home range size. Landscape, measured as
the amount of land cover, contributed most (42%) of the
variation in home range sizes. Previously, we showed
#1999 Blackwell Science Ltd/CNRS
Polar bear home range size 315
Table 2 Multiple regression analysis of the relationship of mean
and standard deviation of various sea-ice types on home range
size of polar bears (n= 93) in the Canadian Arctic, including
Baffin Bay and Davis Strait regions 1989±97. Partial correlations
(r
2
) express the unique contribution of a given factor
(independent variable) as a proportion of the total variance
explained on polar bear home range
Proportion
variation FSignificance
Parameter explained value (p)
Permanent attributes:
Land cover (+)* 0.42 62.1 50.001
Coastline habitat (±) 0.05 14.1 50.001
Seasonal variability:
Annual ice (+) 0.24 60.3 50.001
Complete Model 0.71 68.6 50.001
*(+) positive correlation, (±) negative correlation.
Table 3 Relationship between (i) the slope or intercept of the correlation between sea-ice
parameter and distance from centre of polar bear home ranges, and (ii) home range size of polar
bears from the Canadian Arctic, including the Baffin Bay and Davis Strait regions 1989±97
(n= 93). A significant negative correlation between home range and slope indicates that greater
temporal variability in ice characteristics results in large home range size whereas a significant
positive correlation between home range and intercept indicates that greater unpredictability in
ice characteristics results in larger home range size
Slope Intercept
ÐÐÐÐÐÐÐÐÐ ÐÐÐÐÐÐÐÐ
Ice characteristics r*p{r*p{
Seasonal variability:
Water ±0.21 0.07 +0.27 0.04
Annual ice ±0.17 0.17 +0.25 0.02
Multi-year ice +0.24 0.04 ±0.06 0.61
Annual variability:
Water ±0.19 0.09 +0.28 0.03
Annual ice ±0.35 0.001 +0.19 0.09
Multi-year ice +0.22 0.04 ±0.29 0.01
*Pearsons product moment correlation coefficient.
{Probability of slope different from zero.
Paper 090 Disc
that polar bear movements were constrained by landscape
pattern (Ferguson et al. 1998). Polar bears living in areas
with many islands, such as the Arctic Archipelago, had
more irregular movements and smaller seasonal home
range sizes. In contrast, polar bears that lived in seasonal
environments characterized by the annual ablation of ice
during late summer had the largest home range sizes (e.g.
Baffin Bay and Davis Strait populations). Larger home
ranges may result from use of land during the ice-free
period because bears remain with the ice as long as
possible, resulting in large distances separating winter
and summer range. Seasonal changes in the amount of
annual ice explained a large amount (24%) of the
variation in home range size of female polar bears.
Annual ice is critical to the food base for arctic marine
food webs and directly controls the availability and
accessibility of food for polar bears (Savidge et al. 1996;
Arrigo et al. 1997; Nicol & Allison 1997). In contrast,
multi-year ice and zones of open water provide few seal
hunting opportunities for polar bears (Stirling et al.
1993). Relative amount of coastline habitat contributed to
an explanation of polar bear home range size. Polar bear
home ranges that had more coastline likely encompassed
a greater proportion of highly productive coastline
habitat (Sakshaug et al. 1994; Arrigo et al. 1997; Stirling
1997) and, as a result, home ranges were smaller than
many offshore home ranges.
The proportion of ice cover (e.g. annual ice) likely
affects polar bear home range size but predictability of
sea-ice characteristics across time and space ultimately
affects the area required by polar bears to maintain life.
Polar bears control for spatial and temporal variation in
ice characteristics by making large-scale movements
and selecting sea-ice landscape favourable for seal
hunting (Garner et al. 1990; Ferguson et al. 1999). We
found evidence that polar bears adjusted their home
range size to reduce annual and seasonal variation in ice
characteristics. For example, home ranges with un-
predictable ice characteristics across seasons or years
were larger than those associated with more predictable
ice features.
Three factors important to polar bear predation of seals
and home range size are the dispersion of land, the
seasonal flux of ice, and the amount of edge habitat. At
one extreme, bears living in areas with many large islands,
multi-year ice, and extensive shoreline habitat (e.g. Arctic
Archipelago) have more predictable access to seals,
particularly in spring during seal pupping. Here, we
predict a lower annual return on their hunting efforts but
an annual return that is more constant year-to-year. The
greater proportion of multi-year ice in these habitats
provides for fewer seals, and hunting success by polar
bears is likely lower. As a result these bears tend to have
smaller home ranges and their space-use strategy involves
a trade-off between the mean availability of food (low)
and the temporal and spatial variability associated with
this food (low). At the other extreme, bears living in areas
characterized by large expanses of ice and large seasonal
flux of annual ice (e.g. Baffin Bay) have large home
ranges. The space-use strategy adopted by these bears is to
take greater risks to find patches of prey in a more
variable environment. As a result, they move extensively
and exploit larger home ranges. These bears travel far
offshore searching the moving pack ice for concentrations
of seals. The density of seals is greater offshore, but their
distribution is more spatially and temporally unpredict-
able. Also, offshore bears have access to other food
sources for a greater part of the year [e.g. narwhals
(Monodon monoceros), beluga whales (Delphinapterus leu-
cas), bearded (Erignathus barbatus) and hooded seals
(Cystophora cristata; Stirling 1997)]. Therefore, some bears
trade off greater food availability (high mean) for more
variable food over time and space (greater unpredict-
ability), whereas other bears live with lower but more
constant food availability. Bears will adopt a strategy
along this continuum that fits their local environment.
Also, some bears likely switch strategies as indicated by
the weak correlation between home range sizes comparing
the same bears from year to year.
What is the cause of the large home range sizes
characteristic of this species (see also Amstrup 1986;
Garner et al. 1990; Wiig 1995; Born et al. 1997)? We
propose that large home range size of polar bears is due
to the distribution of their prey within the three-
dimensional water environment and the ever-changing
ice layer that their primary prey (ringed seals; Phoca
hispida) live under. Sea-ice, like all interfaces, not only
creates ecological diversity but it also selects for
organisms adapted to environments that vary consider-
ably with space and time (Holling 1992; Naiman &
De camps 1997). Polar bear morphology is that of a
terrestrial mammal and they rely on the two-dimensional
terrestrial-like platform of sea ice to move about and prey
on ringed seals (Stirling & Archibald 1977). Large home
range sizes have been documented for marine fish (Zeller
1997), marine turtles (Renaud & Carpenter 1994), marine
otters (Bowyer et al. 1995), seals (Stewart & DeLong
1993), and whales (Whitehead 1996). Similarities that
polar bears have with marine mammals, relative to
terrestrial carnivores, include large size, long-distance
travel, lack of territoriality, and physiological adaptations
to extremes in seasonal fluctuations in food availability
(e.g. periods of fasting). Thus, selection pressure to
capture marine prey has resulted in polar bear adaptations
that include movement patterns similar to a marine
mammal living in a three-dimensional environment.
#1999 Blackwell Science Ltd/CNRS
316 S.H. Ferguson et al
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ACKNOWLEDGEMENTS
We thank all the field personnel that helped with capture
surveys. This study was supported by Heritage Canada
Parks Service, Polar Continental Shelf Project, Greenland
Institute of Natural Resources, Nunavut Wildlife Manage-
ment Board, Nunavut & Inuvialuit Hunters & Trappers
Organizations, and the Department of Resources, Wildlife,
& Economic Development, Government of the North-
west Territories. We are also grateful for the valuable
comments provided by three anonymous reviewers.
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Editor, N. Perrin
Manuscript received 3 June 1999
First decision made 16 June 1999
Manuscript accepted 9 July 1999
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BIOSKETCH
Steven Ferguson has research interests in evolution of life-
history traits and population biology, with particular
emphasis on predator±prey relations.
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... × 10 6 km 2 ) and minimum in September (e.g., 1999-2016, x = 5.1 × 10 6 km 2 ) (Fetterer et al. 2017), which requires polar bears to adjust their distribution in response. Given their dependence on sea ice, polar bears have larger home ranges than would be predicted for similar-sized terrestrial carnivores (Ferguson et al. 1999, Auger-Méthé et al. 2016. However, polar bears also exhibit dramatic differences in annual home range size in different regions of the Arctic, ranging from a mean of 19,400 km 2 in Kane Basin (KB) (Ferguson et al. 1999) to 353,557 km 2 in Western Hudson Bay (McCall et al. 2015). ...
... Given their dependence on sea ice, polar bears have larger home ranges than would be predicted for similar-sized terrestrial carnivores (Ferguson et al. 1999, Auger-Méthé et al. 2016. However, polar bears also exhibit dramatic differences in annual home range size in different regions of the Arctic, ranging from a mean of 19,400 km 2 in Kane Basin (KB) (Ferguson et al. 1999) to 353,557 km 2 in Western Hudson Bay (McCall et al. 2015). This regional variation suggests that responses to sea ice declines and fragmentation are likely to differ among the 19 recognized polar bear subpopulations (Stern and Laidre 2016). ...
... Our estimated mean annual home range size for SB polar bears that summered on land (27,000 km 2 , 1999-2016) most closely matched annual home ranges in the Viscount Melville Sound, Gulf of Boothia, and KB subpopulations (19,400-53,300 km 2 ; Ferguson et al. 1999), which are some of the smallest polar bear home ranges ever estimated. These small home ranges are within the Canadian Arctic Archipelago ecoregion (Amstrup et al. 2008) and appeared to be influenced by the high number of islands and coastlines, persistent summer sea ice, and abundance of multi-year ice relative to areas where ice melts completely during the summer and coastline habitat is less abundant (Ferguson et al. 1999). ...
Article
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Animals responding to habitat loss and fragmentation may increase their home ranges to offset declines in localized resources or they may decrease their home ranges and switch to alternative resources. In many regions of the Arctic, polar bears (Ursus maritimus) exhibit some of the largest home ranges of any quadrupedal mammal. Polar bears are presently experiencing a rapid decline in Arctic sea ice extent and a change in sea ice composition. For the Southern Beaufort Sea subpopulation of polar bears, this has resulted in a divergent movement pattern where most of the subpopulation remains on the sea ice in the summer melt season while the remainder move to land. We evaluated the effects of summer land use and maternal denning on the annual and seasonal utilization distribution size (i.e., home range) of adult female polar bears in the Southern Beaufort Sea subpopulation over 30 yr (1986–2016) during a period of rapid sea ice decline. For bears that remained on the summer sea ice, model‐derived mean annual utilization distributions were 64% larger in 1999–2016 (x̄ = 176,000 km2) relative to 1986–1998 (x̄ = 107,000 km2). This increase was primarily driven by increases in summer utilization distributions that encompassed increased amounts of open water and decreased amounts of preferred sea ice. The mean centroid of summer utilization distributions for bears that remained on the sea ice was 193 km further north‐northeast in 1999–2016. In contrast, bears that summered on land during 1999–2016 exhibited 88% smaller mean annual utilization distribution sizes (x̄ = 22,000 km2) relative to bears that remained on the summer sea ice during the same period. Our findings highlight the impacts of sea ice declines on polar bear space use and the increasing importance of land as an alternative summer refuge.
... Only 28% of the data points occurred in years with low ice concentration, suggesting that the observed area of the UD may be a conservative estimate. A similar negative relationship with sea ice concentration and home range size was found in several polar bear populations (Ferguson and Taylor, 1999;Amstrup et al., 2000;Hamilton et al., 2015;Durner et al., 2019;Pagano et al., 2021). However, other work showed home range to increase with an extended ice season and greater extent (Parks et al., 2006;Laidre et al., 2018). ...
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Change in behavior is one of the earliest measurable responses to variation in habitat suitability, making the study of factors that promote behaviors particularly important in areas undergoing environmental change. We applied hidden Markov models to remote movement data of 14 polar bears, Ursus maritimus , from Western Hudson Bay, Canada between 2011 and 2021 during the foraging season (January--June) when bears inhabit the sea ice. The model incorporated bear movement and orientation relative to wind to classify three behaviors (stationary/drifting, area-restricted search, and olfactory search), and investigated 11 factors to identify conditions that may promote these behaviors. In contrast to other polar bear populations, we found high levels of evening activity, with active behaviors peaking around 20:00. We identified an increase in activity as the ice-covered season progressed. This apparent shift in foraging strategy from still-hunting to active search corresponds to a shift in prey availability (i.e., increase in haul-out behavior from early winter to the spring pupping and molting seasons). Last, we described spatial patterns of distribution with respect to season and ice concentration that may be indicative of variation in habitat quality and segregation by bear age that may reflect competitive exclusion. Our observations were generally consistent with predictions of the marginal value theorem, and differences between our findings compared to other populations could be explained by variation in regional or temporal variation in resource abundance or distribution. Our findings and methodology can help identify periods, locations, and environmental conditions associated with habitat quality and can improve our understanding polar bear behavioral ecology and aid conservation.
... On morphological perspective, the bear family have all the carnivores' characteristics (Sienkiewicz et al. 2019). The brown bear, the American black, the Asiatic black, sun, giant panda, spectacled and sloth bears are the representatives of the Ursidae (Ferguson et al. 1999 ...
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The purpose of the present research is to investigate the major arteries, veins, and nerves of the crus in the brown bear through macro anatomical dissection and contrast radiography. The pelvic limbs of 4 bears were included in the study. The limbs were removed from the trunk and the vessels and nerves were dissected and photographed. For the radiography barium sulfas solution was introduced through the femoral artery and images in cranio-caudal and medio-lateral projection were made. The main arteries, veins and nerves and their branches supplying the structures of the crural region were identified and compared to the dog, cat and human.
... Furthermore, to mitigate recapture heterogeneity in genetic sampling conducted in 2011−2013, we defined sampling strata to guide effort and improve survey coverage and ef ficiency. Stratification was primarily based on satellite telemetry data ob tained from adult female polar bears collared during fall and spring along eastern Baffin Island (1993− 1995, 1997) and in spring in W and NW Greenland in 2009 and 2010 (Ferguson et al. 1999, 2000, Born et al. 2011b. We summarized location data by proximity to the coastline and used the proportion of locations in different inland zones to inform stratification. ...
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Changes in sea-ice dynamics are affecting polar bears Ursus maritimus across their circumpolar range, which highlights the importance of periodic demographic assessments to inform management and conservation. We used genetic mark-recapture-recovery to derive estimates of abundance and survival for the Baffin Bay (BB) polar bear subpopulation—the first time this method has been used successfully for this species. Genetic data from tissue samples we collected via biopsy darting were combined with historical physical capture and harvest recovery data. The combined data set consisted of 1410 genetic samples (2011-2013), 914 physical captures (1993-1995, 1997), and 234 harvest returns of marked bears (1993-2013). The estimate of mean subpopulation abundance was 2826 (95% CI = 2284-3367) in 2012-2013. Estimates of annual survival (mean ± SE) were 0.90 ± 0.05 and 0.78 ± 0.06 for females and males age ≥2 yr, respectively. The proportion of total mortality of adult females and males that was attributed to legal harvest was 0.16 ± 0.05 and 0.26 ± 0.06, respectively. Remote sensing sea-ice data, telemetry data, and spatial distribution of onshore sampling indicated that polar bears were more likely to use offshore sea-ice habitat during the 1990s sampling period compared to the 2010s. Furthermore, in the 1990s, sampling of deep fjords and inland areas was limited, and no offshore sampling occurred in either time period, which precluded comparisons of abundance between the 1993-1997 and 2011-2013 study periods. Our findings demonstrate that genetic sampling can be a practical method for demographic assessment of polar bears over large spatial and temporal scales.
... The spatial clusters (i.e., hot spots and cold spots) we identified were generally associated with Inuit communities. Polar bears have large home ranges (Amstrup et al., 2000;Ferguson et al., 1999;Mauritzen et al., 2001;McCall et al., 2015) and the relationship between where a bear was harvested and where it foraged is to some extent uncertain. However, polar bears are often philopatric and differential space use strategies have led to genetic differentiation within subpopulations (Crompton et al., 2014Maduna et al., 2021;Viengkone et al., 2016). ...
Article
Climate warming and associated physical and biological changes will likely force widespread species redistribution, particularly in polar environments. However, tracking such distributional shifts is difficult. The dietary habits of apex predators, like polar bears (Ursus maritimus), may provide early signals of distributional change in prey populations. We used harvest-based sampling to investigate the spatial feeding patterns of polar bears across Nunavut from 2010 to 2018 (n = 1570) and identify spatiotemporal clusters of different prey based on predator diet estimates. Quantitative fatty acid signature analysis and the Getis-Ord Gi* statistic identified spatial clusters of high or low dietary proportions (i.e., “hot spots” and “cold spots”) reflecting seasonal and spatial availability of prey. Ringed seal (Pusa hispida) was the primary prey of bears throughout Nunavut followed by bearded seal (Erignathus barbatus), although proportional consumption varied spatially. A consistent ringed seal consumption hot spot was found in Gulf of Boothia indicating the importance of year-round availability of ringed seals. Spatial clusters of bearded seal and Atlantic walrus (Odobenus rosmarus rosmarus) throughout Foxe Basin suggested overlapping seasonal distributions and high regional abundance. Bears had consistently high dietary levels of harbour seal (Phoca vitulina) around Southampton Island and along the western coast of Hudson Bay suggesting a possible year-round concentration of this prey. Hot spots of harp seal (Pagophilus groenlandicus) consumption were evident throughout Davis Strait and a spring-summer hot spot around Jones Sound was consistent with harp seal migratory patterns. Year-round beluga whale (Delphinapterus leucas) hot spots were found along eastern Baffin Island and southern Viscount Melville Sound providing new knowledge of local conditions that promote polar bear predation or scavenging. Narwhal (Monodon monoceros) were less susceptible to predation with only one spatial cluster of high consumption appearing during spring-summer in Barrow Strait. Bowhead whale (Balaena mysticetus) hot spots occurred around south-western Foxe Basin and seasonally in southern Viscount Melville Sound suggesting carcasses are locally accessible to bears and may act as a supplemental food source in particular areas and seasons. The congruence of polar bear feeding habits and known prey distribution suggests polar bears serve as ecological indicators and ongoing monitoring of their diets may reveal regional and broad-scale changes in prey population distributions and Arctic ecosystem functioning.
... Polar bears travel long distances on the sea ice in search of seals and in response to sea ice conditions. As a result, their home ranges are often larger than those of most terrestrial mammals (see Chap. 14;Ferguson et al. 1999;Tucker et al. 2014). Polar bear foraging success varies considerably among seasons (Table 13.1). ...
Chapter
Otters are a semiaquatic clade that stands out among carnivorans. Of 13 otter species, only three are known to cooperate, although most species exhibit some form of sociality. The observed variation in social structure among species, especially those in marine environments, makes this taxon suitable for studying the proximate and ultimate factors underpinning sociality. Here we review evidence for social behavior in otters with an emphasis on two species: the North American river otter (an inland and coastal generalist) and the sea otter (a marine specialist). In addition, we provide new information on a marine population of river otters in coastal Alaska using telemetry, camera traps, and social network analysis. Our results provide new insight into the contexts for river otter social behavior, confirm previous observations on individual variation in social behavior, and highlight differences between males and females. We additionally review the published data on sea otter social behavior. We discuss potential directions for hypothesis testing in otter social systems with an emphasis on drivers of individual variation in social behavior, especially potential insights from the fields of sociogenomics and proteomics.
... Polar bears travel long distances on the sea ice in search of seals and in response to sea ice conditions. As a result, their home ranges are often larger than those of most terrestrial mammals (see Chap. 14; Ferguson et al. 1999;Tucker et al. 2014). Polar bear foraging success varies considerably among seasons (Table 13.1). ...
Chapter
Polar bears forage in the marine environment, primarily on the sea ice over the shallow waters of the continental shelf. They are solitary, ambush hunters that catch ringed and bearded seals when they surface to breathe in ice holes or haul out on the ice to rest and molt. In most parts of their range, polar bears experience dramatic seasonal variability in their ability to catch seals, with foraging success peaking in late spring and early summer when seal pups are weaned. During this time, the body mass of polar bears can nearly double, especially in pregnant females, such that body composition may reach 49% body fat. The accumulation of body fat is vital for these bears to survive through the autumn and winter when seals are less accessible or when pregnant adult female bears enter dens and fast. When the sea ice retreats in summer, some bears exhibit a temporary switch to omnivory, feeding on a variety of terrestrial food. However, the energetic benefit of most terrestrial food is small relative to their marine mammal prey and, in some regions, increased land use has been associated with declines in body condition. Reduced accessibility of seal prey to polar bears as a result of global climate change threatens the long-term sustainability of this Arctic predator.
Article
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Background Change in behavior is one of the earliest responses to variation in habitat suitability. It is therefore important to understand the conditions that promote different behaviors, particularly in areas undergoing environmental change. Animal movement is tightly linked to behavior and remote tracking can be used to study ethology when direct observation is not possible. Methods We used movement data from 14 polar bears ( Ursus maritimus ) in Hudson Bay, Canada, during the foraging season (January–June), when bears inhabit the sea ice. We developed an error-tolerant method to correct for sea ice drift in tracking data. Next, we used hidden Markov models with movement and orientation relative to wind to study three behaviors (stationary, area-restricted search, and olfactory search) and examine effects of 11 covariates on behavior. Results Polar bears spent approximately 47% of their time in the stationary drift state, 29% in olfactory search, and 24% in area-restricted search. High energy behaviors occurred later in the day (around 20:00) compared to other populations. Second, olfactory search increased as the season progressed, which may reflect a shift in foraging strategy from still-hunting to active search linked to a shift in seal availability (i.e., increase in haul-outs from winter to the spring pupping and molting seasons). Last, we found spatial patterns of distribution linked to season, ice concentration, and bear age that may be tied to habitat quality and competitive exclusion. Conclusions Our observations were generally consistent with predictions of the marginal value theorem, and differences between our findings and other populations could be explained by regional or temporal variation in resource availability. Our novel movement analyses and finding can help identify periods, regions, and conditions of critical habitat.
Article
Monitoring changes in the distribution of large carnivores is important for managing human safety and supporting conservation. Throughout much of their range, polar bears (Ursus maritimus) are increasingly using terrestrial habitats in response to Arctic sea ice decline. Their increased presence in coastal areas has implications for bear-human conflict, inter-species interactions, and polar bear health and survival. We examined observed trends in land use over three decades by polar bears in the southern Beaufort Sea (SB) and Chukchi Sea (CS) where bears have traditionally spent most of the year on the sea ice. Using data from 408 adult females fitted with satellite radio-collars, we examined trends in the annual proportion of bears coming onshore (hereafter referred to as “percent of bears”) during the summer for ≥21 days, arrival and departure dates, duration spent onshore and relationships with sea ice metrics. We then estimated future land use through 2040 by extrapolating trends and by combining observed relationships between land use and sea ice with projections of future sea ice from an ensemble of earth system models. The observed percent of bears summering onshore and their duration onshore was correlated with the percent of open water that occurred within their population’s range between July and October. As sea ice declined, the percent of bears summering onshore increased from ~5 to 30% in the SB and ~10 to 50% in the CS and duration onshore increased by >30 days to 60–70 days in both populations. Using a range of greenhouse gas emission scenarios and adjustments for faster than forecasted sea ice loss we estimated that 50-62% of SB and 79-88% of CS bears will spend 90–108 and 110–126 days onshore during summer in the SB and CS, respectively, by 2040. Sea ice projections varied little between greenhouse gas emission scenarios prior to 2040 but diverged thereafter. Observed and forecasted increases in polar bear land occupancy puts more bears in proximity to human activities and settlements for longer durations while extending the lack of access to their primary prey. Because human conflict is one of the primary factors affecting the conservation of large carnivores worldwide, mitigation of bear-human interactions on land will be an increasingly important component of polar bear conservation.
Article
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In natural environments, bear behavior follows seasonal patterns but the zoo environment differs from the natural environment in several ways, including the presence of zoo visitors. Although typically difficult to disentangle, we were able to tease apart the effects of seasonal changes and visitor density on the visibility and behavior of 10 bears representing five species housed at Cleveland Metroparks Zoo due to the disruption caused by COVID-19. We conducted a longitudinal bear behavior monitoring project from June, 2017-November, 2020. Bears were more visible in the spring and in the presence of visitors, locomoted more and were less inactive when large crowds were present, foraged and locomoted more when it was earlier in the day, and locomoted more at higher temperatures. There were limited differences in bear visibility to observers between 2020 (when the zoo was temporarily closed to visitors) and the previous three years. There were no differences in rates of stereotypy or social behavior across seasons, crowds, or daily attendance categories. Based on these limited differences, neither season nor visitor density seemed to have an apparent effect on bear behavior or welfare.
Article
1. Home-range indices, describing the area over which an animal moves or within which it concentrates its activity, are widely used in the analysis of animal movement, habitat selection, interaction and survival, the basic topics of applied animal ecology. However, the wide range of available indices and a poor understanding of their statistical properties limits their applicability, their interpretation and the ease by which comparisons can be made. These restrict many analyses to qualitative rather than quantitative assessments of home-range. We present an analysis of home-range indices under different conditions to assess their relative performance quantitatively, and we suggest a method of correcting for biases to allow quantitative comparisons between studies and techniques. 2. We compared the performance of a range of current home-range indices against the underlying animal trajectory. A moving animal describes a trajectory, a continuous line of movement through space and time. Home-range is redefined as an outline enclosing a specified proportion of the trajectory over a specified period. This definition allows the performance of different home-range indices to be compared quantitatively. 3. Detailed radiotracking data from a chaffinch Fringilla coelebs L. and a goshawk Accipiter gentilis L. were used to reconstruct trajectories. Intermittent radiotracking was simulated by randomly extracting 200 sets, each of 30, 100 and 500 fixes for each animal. Seven home-range indices were used to generate home-range outlines at nominal 20%, 30%, 40%, 50%, 60%, 70%, 80%, 85%, 90%, 95% and 100% cores. 4. The area estimates, mean/variance ratio of area, overlap, percentage inclusion of trajectory, and trajectory density within each outline were used to compare the effectiveness of techniques and their ability to provide quantitative measures of animal use. 5. No technique performed well under all criteria. There was a spectrum of performance from techniques producing outlines with high trajectory density, low spatial stability and high sensitivity to sample size; to low trajectory density, high spatial stability and low sensitivity to sample size. 6. The nominal percentage cores produced by the techniques did not reflect accurately the true percentage time spent within that outline. A jack-knifing technique was evaluated that calibrates the true percentage cores at each nominal level for any home- range index. Suggestions are made for the quantitative interpretation of current indices, the use of different indices for specific analyses, and the development of new fix- and trajectory-based indices.
Article
Covering the ecology and behaviour of North American black bears, this volume discusses such topics as: home ranges and home range estimators; predicting habitat quality and use of home ranges; food abundance and variation in home range size; and territories and home ranges.
Article
1. Variability in a measure of the feeding success of sperm whales, defecation rate, was calculated over temporal scales ranging from 5 h to 4 years, and spatial scales ranging from 100 to 5000 km. 2. Sperm whale feeding success was not obviously linked to any sub-annual environmental cycles, with the possible exception of time of day. 3. Variability in feeding success over temporal scales of 1-64 days, and spatial scales of 100 km, was about 60% of the long-term mean, but reached 130% of the long-term mean over time intervals of 2-4 years and distance intervals greater than 500 km. 4. During periods of days characterized by low feeding success groups of sperm whales moved greater distances. 5. Migration over ranges of about 300 1000 km allows sperm whales to maintain high biomass and low reproductive rates in an environment which, at any location, contains long, unpredictable periods of food shortage.