FISHERIES OCEANOGRAPHY
Fish. Oceanogr. 17:5, 396–410, 2008
Density-independent and density-dependent factors affecting
temporal changes in spatial distributions of eastern Bering Sea
flatfish
PAUL D. SPENCER*
Alaska Fisheries Science Center, 7600 Sand Point Way NE,
Bldg 4, Seattle, WA 98115, USA
ABSTRACT
The general warming of the eastern Bering Sea (EBS)
and the wide range of abundance exhibited by several
eastern Bering Sea flatfish motivated an examination
of how density-dependent and density-independent
factors may influence the spatial distributions of EBS
flatfish. In this study, EBS trawl survey data from 1982
to 2006 were used to examine how temporal changes in
the distributions of six flatfish species groups [yellowfin
sole (Limanda aspera), rock sole (Lepidopsetta sp.),
flathead sole (Hippoglossoides sp.), Alaska plaice
(Pleuronectes quadrituberculatus), arrowtooth flounder
(Atheresthes sp.), and Greenland turbot (Reinhardtius
hippoglossoides)] are related to temporal changes in the
location of the ‘cold pool’ (bottom water < 2C), and
how the area occupied by flatfish are related to the cold
pool and population abundance. Rock sole and flathead
sole distributions have generally moved northwest
since 1982 and are significantly correlated with the
movement of the cold pool, whereas arrowtooth
flounder avoid the cold pool and their area occupied is
inversely related to the size of the cold pool. The area
occupied by arrowtooth flounder and rock sole are also
significantly related to stock abundance. Multivariate
statistical models indicate that the location of rock sole
is more strongly related to stock abundance than to the
cold pool, whereas the area occupied by arrowtooth
flounder is more strongly related to the area of the cold
pool rather than abundance. The temperatures occupied by several flatfish stocks indicate a substantial
variability in suitable temperatures. These results
suggest that a complex suite of density-dependent
and density-independent factors may determine the
*Correspondence. e-mail: paul.spencer@noaa.gov
Received 14 January 2008
Revised version accepted 28 June 2008
396
response of EBS flatfish spatial distributions to
increasing temperatures.
Key words: Alaska plaice, arrowtooth flounder, cold
pool, density-dependent habitat selection, eastern
Bering Sea, flathead sole, Greenland turbot, rock
sole, spatial distributions, temperature, yellowfin sole
INTRODUCTION
The study of distributional shifts in marine fish species
has long been a topic of interest to fisheries oceanographers, with Cushing’s (1982) ‘dramatic decade’ of
1925–35 providing classic examples such as the
expansion of Icelandic Atlantic cod (Gadus morhua)
to west Greenland and the reappearance of cod and
haddock (Melanogrammus aeglefinus) in the Barents
Sea. A common approach has been to focus upon
density-independent environmental factors underlying
changes in fish distributions, and this perhaps explains
the renewed interest in this topic given the general
warming of marine systems. For example, Perry et al.
(2005) found that 21 of 36 demersal North Sea fish
stocks showed recent distribution shifts, with 13 stocks
moving northwards. Similarly, Mueter and Litzow
(2008) observed a community-wide northward shift of
eastern Bering Sea (EBS) fish and invertebrates from
1982 to 2006.
Alternatively, density-dependent interactions may
also result in changes in fish distributions. Under the
classic theory of density-dependent habitat selection,
increases in population size would be expected to
increase competition, reduce habitat suitability, and
lead to an expansion of area occupied (Fretwell and
Lucas, 1970; MacCall, 1990). The expansion would be
expected to be directional if equally suitable habitats
are not evenly distributed around the margin of a
population. For example, Swain and Wade (1993)
found that Atlantic cod in the southern Gulf of St.
Lawrence expanded its distribution to the east as
abundance increased. Similarly, Marshall and Frank
(1995) found that the distribution of Scotian Shelf
juvenile haddock expanded to the east of Browns Bank
doi:10.1111/j.1365-2419.2008.00486.x
2008 The Author.
Spatial distributions of eastern Bering Sea flatfish
as population increased. In many systems, fish distributions would be expected to respond to both densityindependent and density-dependent processes (Swain,
1999). Thus focusing only on either density-independent or density-dependent mechanisms may lead to an
incomplete interpretation of distributional shifts.
EBS flatfish exist in an ecosystem with rapidly
changing environmental conditions and have also
experienced substantial population changes, thus
raising the potential for both density-independent and
density-dependent processes to affect distributions.
The effects of global warming would be expected to be
pronounced in the EBS, which appears to be in
transition from an Arctic to a sub-Arctic system. A
subsurface ‘cold pool’, a body of water < 2C
(Wyllie-Echeverria and Wooster, 1998), substantially
affects the demersal environment and is formed from
the melting of sea ice and trapping of cold water
during spring stratification (Stabeno et al., 2001). The
total amount of EBS sea ice and its southern extent
has diminished since the early 1970s (Stabeno et al.,
2001; Overland and Stabeno, 2004) and from 1997 to
2004 the timing of ice melt has shifted about 3 weeks
earlier (Grebmeier et al., 2006). Northward shifts in
the distributions of snow crabs (Chinoecetes opilio; Ernst
et al., 2005) and grey whale feeding grounds (Moore
et al., 2003) have also been observed, although for
grey whales the depletion of amphipod prey may be a
factor (Coyle et al. 2007). Wyllie-Echeverria and
Wooster (1998) have also observed that the distributions of walleye pollock (Theragra chalcogramma) and
Arctic cod (Boreogadus saida) are significantly affected
by the cold pool.
Flatfish constitute a large portion of the EBS fish
community, accounting for 44% of the estimated total
biomass of Bering Sea/Aleutian Islands federally
managed fish species in 2007 (NPFMC, 2006). Thus
any effect of EBS temperature trends on the distributions of the overall fish community will likely affect
flatfish species. Changes in the EBS environment
could affect flatfish distributions via a number of
mechanisms, including altering migration pathways
and areas of benthic production. Several EBS flatfish
species migrate between separate winter and summer
distributions; for example, the movement of yellowfin
sole (Limanda aspera) to deeper offshore areas in winter
is thought to be related to avoidance of ice cover and
colder temperatures (Wilderbuer et al., 1992). Additionally, changes in the amount of sea ice and timing
of ice retreat not only affect the location of the cold
pool, but also the timing of the spring bloom and level
of benthic production (Walsh and McRoy, 1986).
Under the Oscillating Control Hypothesis (OCH;
2008 The Author, Fish. Oceanogr., 17:5, 396–410.
397
Hunt et al., 2002) early ice retreats are associated with
delayed blooms in warm water in late spring when
stratification occurs, and the warm temperatures lead
to rapid zooplankton population growth which provides prey for piscivorous fish. Conversely, late ice
retreats are associated with earlier spring blooms in
cold water, where the primary production sinks to the
benthic community because the cold water delays
zooplankton production. Thus, earlier ice retreats
would be expected to favor piscivorous fish such as
walleye pollock, Pacific cod (Gadus macrocephalus),
and arrowtooth flounder (Atheresthes sp.), which now
dominate the system rather than benthic-feeding
species. If the general warming trends affect the spatial
pattern of benthic production, then it is plausible that
the spatial pattern of some flatfish species may also be
affected.
Several EBS flatfish have shown marked changes in
population size in recent decades. For example, yellowfin sole abundance increased fivefold from the early
1970s to early the 1980s and has declined since then,
and both rock sole (Lepidopsetta sp.) and flathead sole
(Hippoglossoides sp.) abundance increased 10-fold from
the 1970s to the mid-1990s and have declined
since then (Stockhausen et al., 2006; Wilderbuer and
Nichol, 2006a,b). Walters and Wilderbuer (2000)
observed density-dependent reductions in size at age
for rock sole during the population expansion of the
1980s, and also noted that the center of the distribution shifted to the northwest (NW) during this period.
McConnaughey (1995) found significant relationships
between a dispersion index and population size for
several flatfish species.
EBS flatfish provide a unique opportunity to
examine the influence of density-dependent and density-independent factors on spatial distributions
because of recent changes in population size and the
linkages between environmental variability and their
population dynamics. The purpose of this study was to
examine changes in EBS flatfish distributions and their
relationship with temperature and population abundance. First, I describe temperature variability and
changes in fish distributions since 1982. Secondly, I
examine the extent to which flatfish spatial distributions reflect temperature preferences and are related to
changes in the size and location of the cold pool, and
use a randomization test (Syrjala, 1996) to examine
whether significant changes in fish distributions
occurred between pairs of specified years. Thirdly,
I examine whether the area occupied by a stock is
significantly related to abundance and the area of the
cold pool, and test for regional differences in rates of
local density as a function of overall population size
398
P.D. Spencer
(Swain and Morin, 1996). Finally, for stocks in which
both environmental variability and abundance are
related to distributional changes, I use simple multivariate models to assess the relative importance of
these factors.
METHODS
Data from the EBS summer trawl survey conducted
by the Alaska Fisheries Science Center were used to
obtain spatial information on flatfish density and
temperature (Lauth and Acuna, 2007). Although the
survey extends back to the mid-1970s, a gear change
in 1982 to the 83–112 eastern otter trawl prompted
selection of data from 1982 to 2006; a map of survey
strata sampled consistently since 1982 is shown in
Fig. 1. The survey region is divided into 10 strata
bounded primarily by the 50-, 100-, and 200-m isobaths, and two geographic areas that bisect the EBS
into NW and SE strata. The NW shelf consists of
Strata 20, 41, 42, 43, 61, and 62, and the SE shelf
consists of Strata 10, 31, 32, and 50 (Fig. 1). The
standardized survey is conducted annually during
the spring and summer, with approximately 356
fixed survey stations located within a systematic grid
having 37 · 37-km grid cells. Each survey station is
trawled for approximately 30 min at 3 knots, and the
number and weight of each species is recorded.
Numbers caught for each of the six flatfish species
groups of interest (arrowtooth flounder, flathead sole,
rock sole, Alaska plaice (Pleuronectes quadrituberculatus), Greenland turbot (Reinhardtius hippoglossoides),
and yellowfin sole), area swept by the trawl,
temperature, and depth were obtained for each survey
station, and catch-per-unit-effort (CPUE) was defined
as numbers per km2. Because of the degree to which
closely related species have been separately identified
in trawl surveys has varied since 1982, the arrowtooth flounder group includes Kamchatka flounder
(Atheresthes evermanni), the flathead sole group
includes Bering flounder (Hippoglossoides robustus),
and the rock sole group includes both northern rock
sole (Lepidopsetta polyxystra) and southern rock sole
(Lepidopsetta bilineata).
The survey data were used to describe environmental variability and fish distributions, and to evaluate the following hypotheses concerning how fish
distributions may depend upon environmental factors
and population abundance:
• the temperatures experienced by fish populations
reflect strong temperature preferences;
• temporal changes in the location of fish distributions are related to the location of the cold pool;
• fish distributions differ between warm and cold
years;
• temporal changes in the area occupied by fish
populations are related to the area occupied by the
cold pool;
• temporal changes in the location of fish populations
are related to population size;
• temporal changes in the area occupied by fish
populations are related to population size, and;
• the relationship between local density and overall
population size differs between EBS survey strata.
Environmental variability was described by mean
temperature and several descriptors describing the
Figure 1. The eastern Bering Sea shelf,
with strata used for the groundfish trawl
survey. SE strata are 10, 31, 32, and 50,
whereas NW strata are 20, 41, 42, 43, 61,
and 62.
2008 The Author, Fish. Oceanogr., 17:5, 396–410.
Spatial distributions of eastern Bering Sea flatfish
location and extent of the cold pool. Mean temperature by year, t, was computed as
t ¼
ni
h X
X
wi
i¼1 j¼1
ni
ð1Þ
xji ;
where wi is the proportion of the survey area in strata i,
ni is the number of hauls in strata i, xij is bottom
temperature in haul j and strata i, and h is the number
of strata. The central location of the cold pool was
determined from the average latitude and longitude of
stations containing bottom water defined as being in
the cold pool. Prior to all analyses involving spatial
data, the latitude and longitude locations were projected onto an x–y grid with correct distances between
pairs of data points and the results from spatial analyses were then reconverted to latitude and longitude.
The proportion of the survey area within a given
temperature range for each year was obtained from the
cumulative distribution function (CDF),
fðtÞ ¼
ni
h X
X
wi
i¼1 j¼1
ni
Iðxji Þ where Iðxji Þ ¼
1; if xji t
;
0; otherwise
ð2Þ
and t ranges between the lowest and highest temperatures measured; for example, the proportion of the
survey area covered by the cold pool is f (t = 2.0)
(Perry and Smith, 1994). Finally, the proportion of the
cold pool located within the SE strata in each year was
used as an index of areal changes in cold pool coverage, and was computed as the proportion of f (t = 2.0)
that occurred in the SE shelf.
Fish distributions were described using several
methods, including ellipses, the proportion of the
distribution occurring in the SE shelf, and the temperatures occupied for a fish population. Ellipses were
computed by fitting a bivariate normal distribution in
which survey CPUE data are a function of latitude and
longitude, and then obtaining the contour corresponding to a probability of 50%.
The hypothesis that fish distributions reflect temperature preferences was evaluated by comparing the
CDF of temperature in the EBS (eqn 2) with catchweighted CDFs that identify the proportion of a fish
distribution that occupied a given temperature range
each year. The catch-weighted CDFs were computed
as
gðtÞ ¼
ni
h X
X
wi yji
1; if xji t
;
Þ
where
Iðx
Þ
¼
Iðx
ji
ji
0; otherwise
ni Y
i¼1 j¼1
ð3Þ
2008 The Author, Fish. Oceanogr., 17:5, 396–410.
399
yij is the CPUE for haul j in strata i and Y is the
stratified mean CPUE for the entire survey; scaling by
Y ensures that the distribution sums to 1.
Statistical models relating fish distributions to
environmental variability
The hypothesis that temporal changes in the locations
of fish distributions and the cold pool are related to
each other was evaluated with correlation analysis
between the proportion of the cold pool occurring in
the SE strata (from eqn 2) and the proportion of the
fish distribution occurring in the SE strata; the latter
was computed as
Pse ¼
hse X
ni
X
wi yij
;
n Y
ð4Þ
i¼1 j¼1
where the summation is over the hse strata in the SE
shelf. Because the proportion values are bound
between 0 and 1, an arcsin transform was applied to
the data, and the transformed data were then normalized. Critical values for significance at the 0.05
level were adjusted for autocorrelation using the
method described in Kope and Botsford (1990), and
the Wilks–Shapiro test was used to test for normality.
Greenland turbot were excluded from this analysis
because they were only found near the northwest
boundary of the survey area and the proportion in the
SE strata is not a meaningful measure.
The hypothesis that spatial differences exist
between pairs of years were evaluated with a modified
Cramer–von Mises test (Syrjala, 1996). This nonparametric test is analogous to a Kolmogorov–Smirnov
test, but is less sensitive to small numbers of unusually
large density observations which may arise from patchy distributions but may not necessarily indicate true
spatial differences in distributions. For each species,
the analysis was conducted for each pairwise comparison between the warmest and coldest 6 years since
1982. The CPUE data from all stations in each year
are expressed as a CDF, and the test proceeds from one
corner of the survey area and systematically covers the
survey area, producing the sum of the squared differences between the two CDFs. Because the CDFs vary
with the corner one chooses to initiate the analysis,
the final test statistic averages the sum of squared
differences obtained from initiating the analysis in
each of the four corners. A distribution for the test
statistic was obtained by making 2000 random pairings
of years and CPUE data and recomputing the
test statistic, and statistical significance was inferred
by comparing the observed test statistic to this
distribution.
400
P.D. Spencer
Preliminary graphs suggest that for some stocks,
the area occupied by the stock is related to the area of
the cold pool. This hypothesis was evaluated with the
statistical model
model relating local (i.e. stratum) density and population size over all years:
D95 ¼ a1 eb1 A þ e
where lti is the mean CPUE in stratum i and t is year.
A Gamma error model was used because the variance
of lti increases as a square of lti, and exploratory plots
of the survey CPUE data suggests that this variance
structure is appropriate. In the model above, a b of 1
indicates that local abundance increases at the same
rate as overall abundance, and a b of 1 for all strata
would indicate density-independent habitat selection
(Marshall and Frank, 1995; Swain and Morin, 1996).
In contrast, a b larger than 1 indicates marginal
habitats where local abundance increases more rapidly
than overall abundance, whereas a b smaller than 1
indicates optimal habitats where local abundance increases less rapidly than overall abundance (Swain and
Morin, 1996); thus with density-dependent habitat
selection b would be expected to differ between strata.
Differences in bi between strata were assessed with an
analysis of deviance comparing a model with b of 1 for
all strata to a model with a separate b for each strata.
Note, however, that in the presence of density-independent changes in the location of fish distribution,
differences in b between strata do not necessarily
indicate density-dependent habitat selection. For
example, a stock could occupy the same amount of
area but shift its location and change the relative
distribution across strata as the overall population size
was changing. In this case, the relationship between
local abundance and overall abundance would clearly
differ between strata even though the stock would not
correspond to the basin model of DDHS. For this
reason, the test for differences in b between strata was
only applied to those stocks where a significant relationship was found between area occupied and stock
size.
For species where univariate tests indicated that
population size and the location of the cold pool were
related to the location of the population, a linear
multiple regression model was used to assess the relative significance of these two independent variables.
Similarly, for species where univariate tests indicated
that the area of the cold pool and population size were
related to the area of the population, the following
nonlinear model was applied:
ð5Þ
where D95 is a minimum estimate of the area covered
by 95% of the stock, A is the area covered by the
cold pool, a1 and b1 are parameters, and e is a normally distributed error term. The area of the cold
pool is the sum of the area for survey stations £ 2C,
where the area of each survey station is defined as
wi/ni times the total survey area. The minimum
estimate of the area covered by the stock was
obtained from the total area of survey stations for
which the cumulative CPUE was equal to 95% of the
cumulative CPUE for all stations (Swain and
Sinclair, 1994). Greenland turbot were excluded from
this analysis because they were only found near the
northern boundary of the survey area and temporal
changes in area occupied could reflect movement
beyond the survey area.
Statistical models relating fish distribution to population
density
Under density-dependent habitat selection, changes in
population size may also affect the central location and
areal extent of fish distributions. The hypothesis that
the location of fish populations is related to abundance
was evaluated using linear correlations between
abundance and the proportion of the population in the
SE strata.
The hypothesis that the area occupied is related to
population size was evaluated with the asymptotic
regression model
D95 ¼ a2 b2 ecN þ e
ð6Þ
where N is the population abundance obtained from
recent stock assessment models, and e is a normally
distributed error term. Density-dependent habitat
selection would occur if the area occupied changes
with abundance (i.e. c „ 0) (Marshall and Frank,
1995). As with the test of the cold pool area upon the
fish distribution area (Eqn 5), Greenland turbot were
excluded from this analysis because they were only
found near the northern boundary of the survey area.
For stocks that demonstrated significant relationships between area occupied and stock size, one would
expect some areas to represent optimal habitats in
which the stock occurred irrespective of population
size, and other areas to represent marginal habitat
which is utilized during periods of high abundance.
This process was modeled using a generalized linear
E½yti ¼ lti ¼ eðai þbi ln Nt Þ ;
D95 ¼ a2 b2 ecN þ a1 eb1 A þ e
ð7Þ
ð8Þ
In each case, partial r2 values for each independent
variable were computed by dividing the type II sum of
squares for the variable by the total sum of squares; this
2008 The Author, Fish. Oceanogr., 17:5, 396–410.
Spatial distributions of eastern Bering Sea flatfish
quantity indicates the relation of the dependent variable to each independent variable after adjusting for
the effect of the other variable. The unexplained
portion of the r2 was obtained by subtracting the sum
of the two partial r2 from the total r2 for the model,
and indicates the portion of the variance explained by
the full model that cannot be uniquely attributed to
either independent variable.
RESULTS
The mean bottom temperature on the EBS shelf has
varied substantially from 1982 to 2006 (Fig. 2). The
six warmest years in this time series occurred in 1996,
1998, and 2002–2005, and the average temperature for
these years was 3.43C. In contrast, the six coldest
years occurred in 1986, 1992, 1994–95, 1999, and
2006 and the average temperature for these years was
1.64C. The average temperature for 1999 was 0.83C,
substantially below the average temperature of the
next coldest year, 1994, of 1.57C. The proportion of
the cold pool in the SE strata has varied inversely with
the mean temperature, ranging from 0% in warm years
to approximately 60%. This range corresponds to
Figure 2. Time series (a) and scatterplot (b) of mean bottom temperature (C) and percentage of the cold pool in the
SE survey strata.
2008 The Author, Fish. Oceanogr., 17:5, 396–410.
401
dramatic changes in the location and areal coverage of
the cold pool. For example, in 1998 the cold pool was
limited to only the most northwestern stations of the
middle shelf, whereas in 1999 the cold pool occupied
the entire middle and inner shelf, extending as far
south as the Alaska Peninsula; a similar change
occurred between 2005 and 2006 (Fig. 3).
Ellipses characterizing flatfish distributions indicate
that flathead sole and rock sole are generally located
farther to the north or northwest during the six
warmest years as compared to the six coldest years,
whereas Alaska plaice and yellowfin sole distributional
ellipses had moved slightly but do not show a correspondence with environmental conditions (Fig. 4). In
particular, the northern boundaries of the distribution
ellipses for rock sole in each of the cold years (with the
exception of 2006) are located farther south than the
northern boundaries from the warm years. The 1998
flathead sole distribution is located farther to the
northwest than in other years, and arrowtooth flounder distributions moved noticeably toward the inner
shelf in the warm years of 2003, 2004, and 2005. The
centroid of the cold pool in the survey area is also
shown in Fig. 4; in warm years the centroid is located
just south of St. Lawrence Island at approximately
60N, whereas in cold years the centroid is located at
approximately 59N.
Catch-weighted temperature distributions indicate
that arrowtooth flounder avoid the cold pool, whereas
other flatfish do not reveal particularly strong temperature preferences. The CDFs can be summarized
over all years by plotting the 10th and 90th percentiles
of catch-weighted temperature against the 10th and
90th percentiles of available temperature in the survey
area; data that fall on a 1 : 1 line indicate species
where the temperatures of areas occupied do not differ
from the available temperatures over the survey area
(Fig. 5). Species preference (or avoidance) of the cold
pool would occur if the catch-weighted temperature
data are below (or above) 2C. Arrowtooth flounder
show avoidance of the cold pool, as the 10th percentile of arrowtooth flounder temperature distributions
are generally higher than 2C even in years of low
available temperatures. The temperatures occupied by
Greenland turbot showed less variability than those
recorded over the entire EBS shelf, being lower during
warm periods and higher during cold periods. In contrast, rock sole and yellowfin sole occupied temperatures slighter warmer than those recorded over the
entire survey area, whereas Alaska plaice occupied
temperatures very similar to those seen for the entire
survey area. Note also that in 1999 the temperature
experienced by rock sole, yellowfin sole and Alaska
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P.D. Spencer
Figure 3. Eastern Bering Sea trawl survey stations within the cold pool (solid
circles) in 1998, 1999, 2005 and 2006.
plaice were much colder than other years, as the 90th
percentile for catch-weighted temperature (which is
the only 90th percentile data point <2C) was similar
to the 10th percentile for most other years.
For flathead sole and rock sole, significant correlations were found between the proportion of the fish
distributions located in the SE strata and the proportion of the cold pool located in the SE strata, whereas
non-significant relationships were found for yellowfin
sole, Alaska plaice, and arrowtooth flounder (Fig. 6).
Reduced proportions of the flathead sole and rock sole
distributions were found in the SE strata during recent
warm years, suggesting that these populations had
redistributed to the northwest as the cold pool also
shifted to the northwest. In the cold year of 1999 the
proportion of the cold pool and the rock sole and
flathead sole distributions in the SE strata were dramatically increased as compared to 1998; this increase
was also noted for yellowfin sole, although the overall
relationship was non-significant.
Randomization tests comparing flatfish distributions
between the six warm and cold years indicated patterns of significant distributional differences for rock
sole, flathead sole, and arrowtooth flounder that were
driven largely by particular years (Table 1). For rock
sole and flathead sole, 30 and 12, respectively, of the
36 possible comparisons were statistically significant
(P < 0.05). Four of the six non-significant pairwise
comparisons for rock sole involved the 2006 distribu-
tion. The distribution of flathead sole in 1998 was
significantly different than the distributions in four of
the cold years (all except 1999 and 2006), whereas the
distribution in 1986 was significantly different than
the distributions in five of the warm years (all except
1996). Distributions of arrowtooth flounder in 2003
and 2005 were significantly different from the distributions in each cold year, and the 2004 distribution
was significantly different from the distributions in
four of the cold years. Some of these distributions, such
as flathead sole in 1986 and 1998 and arrowtooth
flounder from 2003–2005, were also significantly different from several other distributions within the sets
of warm and cold years (not shown), indicating the
uniqueness of these years.
The area occupied by arrowtooth flounder is
inversely related to the area of the cold pool
(P < 0.01), whereas this relationship was not significant for the other flatfish stocks. The area occupied by
arrowtooth flounder is largest during the warm years
from 2003 to 2005 when the area of the cold pool is
lowest; when the area of the cold pool increases during
the cold year of 2006 the area occupied by arrowtooth
flounder is reduced (Fig. 7a).
The proportion of rock sole and arrowtooth flounder in the SE strata were each significantly correlated
(P < 0.05) with their stock abundance. The correlations were )0.65 and 0.49 for rock sole and arrowtooth
flounder, respectively, indicating that as abundance
2008 The Author, Fish. Oceanogr., 17:5, 396–410.
Spatial distributions of eastern Bering Sea flatfish
Figure 4. Ellipses representing 50% probability contours of
bivariate normal distribution fit to EBS survey CPUE data
for six flatfish species during the six warmest (red) and
coldest years (blue) from 1982 to 2006; the centroids of the
cold pool for the 12 years are plotted in panel (a).
increases, the proportion of the stock in the SE strata
decreases for rock sole and increases for arrowtooth
flounder.
Additionally, the area occupied by 95% of the
rock sole and arrowtooth stocks significantly
increased with stock size (P < 0.001) (Fig. 7). For
arrowtooth flounder there was approximately a
2.4-fold difference between the largest and smallest
amounts of area covered during the 1982–2006
period, whereas for rock sole this factor was approximately 2.0. Although the overall relationship
between area occupied by rock sole and stock
2008 The Author, Fish. Oceanogr., 17:5, 396–410.
403
Figure 5. Scatterplot of bottom temperatures (C) corresponding to the 10th (s) and 90th (+) percentiles of survey
temperature CDFs and CPUE-weighted temperature distributions from 1982 to 2006. Points along the 1 : 1 line
indicates the temperature occupied by the species is identical
to the overall temperature in the EBS survey area. Points
below the horizontal line indicate CPUE-weighted temperatures within the cold pool.
abundance is significant, this relationship is driven by
the strong increases in both area occupied and stock
size from 1982 to 1989 (Fig. 7c). Since 1990, stock
size has varied substantially, although the area
occupied has not increased.
For rock sole and arrowtooth flounder, the b
parameter of Eqn 7 was significantly different
between strata, indicating differential responses of
local density to overall population size (Table 2). For
each species, b was < 1 in strata with high abundance, indicating core areas where strata abundance
increased more slowly than overall abundance, and b
was > 1 in strata with low abundance, indicating
marginal areas where the strata abundance increased
more rapidly than overall abundance. For example,
the bulk of the rock sole biomass occurred in the SE
strata in shallow and intermediate depths (i.e., the
middle shelf), and b was 0.85 and 0.47 for Strata 10
and 31, respectively (Fig. 8). As rock sole abundance
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P.D. Spencer
Figure 6. Time series of the proportion
of a stock (solid line) and cold pool
(dashed line) occurring within the SE
survey strata, based upon EBS survey
data; P-values indicate significance of
correlation tests.
increased, its distribution expanded onto the NW
shelf and Strata 20, 41, and 42 showed b values of
1.51, 1.58, and 1.15, respectively. Arrowtooth
flounder largely occur in the middle and outer shelf,
and the b values for outer shelf Strata 50 and 61
were 0.80 and 0.84, respectively. As the arrowtooth
flounder abundance increased, its distribution
expanded primarily onto the middle shelf and b
increased with distance from the outer shelf area.
Strata 32 and 42, located on the outer edge of the
middle shelf, showed b values near 1, and Strata 31
and 41, located farther inshore, showed higher levels
of b of 1.71 and 1.93, respectively.
Because univariate correlations indicated that the
proportion of rock sole in SE strata was correlated with
both the proportion of the cold pool in the SE strata
and the total abundance, a multiple regression
was conducted to evaluate the relative importance of
these two factors. The overall r2 from the multiple
regression model was 0.54 (Table 3). The partial r2
values, which give the proportion of the variability
explained by a single independent variable after
adjusting for the other independent variables, was 0.35
and 0.12 for abundance and proportion of cold pool in
the SE strata, respectively. Approximately 0.07 of the
total r2 could not be attributed to either of the two
independent variables, indicating some confounding
between the independent variables. Similarly, a
multivariate model (eqn 8) indicates that the
variance in the area occupied by arrowtooth flounder
is more closely related to the area of the cold pool
rather than stock abundance (Table 3). The partial r2
values for abundance and area of the cold pool were
0.21 and 0.33, respectively, with a total r2 of 0.81.
2008 The Author, Fish. Oceanogr., 17:5, 396–410.
Spatial distributions of eastern Bering Sea flatfish
405
Table 1. P-values from randomization tests evaluating differences in flatfish distributions between cold years (rows) and warm
years (columns).
1996
1986
1992
1994
1995
1999
2006
1986
1992
1994
1995
1999
2006
1986
1992
1994
1995
1999
2006
1998
Yellowfin sole
0.07
0.31
0.52
0.67
0.61
0.06
0.25
0.02
0.06
0.46
0.23
0.14
Flathead sole
0.10
0.00
0.74
0.02
0.53
0.00
0.17
0.00
0.37
0.26
0.44
0.14
Greenland turbot
0.45
0.62
0.88
0.85
0.96
0.57
0.23
0.05
0.41
0.58
0.01
0.01
2002
2003
2004
2005
0.05
0.67
0.44
0.09
0.03
0.15
0.92
0.97
0.34
0.29
0.65
0.62
0.15
0.70
0.65
0.13
0.05
0.40
0.06
0.67
0.39
0.28
0.15
0.10
0.00
0.15
0.05
0.02
0.84
0.38
0.02
0.63
0.36
0.20
0.25
0.74
0.00
0.17
0.02
0.01
0.47
0.53
0.01
0.29
0.17
0.07
0.18
0.52
0.20
0.74
0.96
0.94
0.09
0.15
0.09
0.63
0.87
0.91
0.05
0.33
0.00
0.18
0.33
0.43
0.01
0.74
0.16
0.92
0.97
0.99
0.20
0.27
1996
1998
2002
Rock sole
0.00
0.00
0.00
0.00
0.05
0.09
0.00
0.00
0.03
0.00
0.00
0.01
0.00
0.00
0.00
0.87
0.05
0.06
Alaska plaice
0.55
0.53
0.07
0.42
0.25
0.33
0.89
0.34
0.17
0.38
0.09
0.02
0.19
0.08
0.88
0.13
0.01
0.96
Arrowtooth flounder
0.29
0.54
0.23
0.71
0.41
0.56
0.17
0.11
0.05
0.94
0.65
0.88
0.51
0.12
0.41
0.07
0.17
0.02
2003
2004
2005
0.00
0.21
0.02
0.00
0.00
0.00
0.00
0.04
0.00
0.00
0.00
0.05
0.00
0.00
0.00
0.00
0.00
0.11
0.35
0.24
0.10
0.18
0.03
0.00
0.87
0.82
0.72
0.29
0.35
0.05
0.33
0.16
0.33
0.05
0.42
0.17
0.02
0.01
0.02
0.01
0.00
0.05
0.07
0.02
0.01
0.00
0.00
0.09
0.01
0.00
0.00
0.00
0.00
0.00
Bold/italic values are significant at the P = 0.05 level.
DISCUSSION
Considerable variability occurs in how flatfish spatial
distributions have responded to the generally increasing temperatures of the EBS shelf, with both densityindependent and density-dependent factors emerging
as potential mechanisms. Some flatfish stocks, such as
yellowfin sole and Alaska plaice, do not show a significant correlation between their spatial distribution
and the spatial distribution of the cold pool; for Alaska
plaice, this may reflect the presence of a blood enzyme
that allows increased metabolic activity at low temperatures (Knight et al., 1991). Other stocks, such as
flathead sole and rock sole, show significant positive
relationships between the proportion of the stock in
the SE strata and the proportion of the cold pool in
the southeast, suggesting movement to the northwest
as the cold pool moves to the northwest. These results
are consistent with those of Mueter and Litzow (2008),
who also found significant northward movement
related to temperature for flathead sole and rock sole,
and non-significant results for Alaska plaice and
yellowfin sole. However, the changes in the spatial
distributions of rock sole and arrowtooth flounder are
also correlated to abundance, and expansion of
arrowtooth onto the middle shelf appears to be limited
2008 The Author, Fish. Oceanogr., 17:5, 396–410.
by the area of the cold pool. These results suggest that
the factors that determine temporal changes in EBS
flatfish distributions extend beyond solely temperature
and likely differ between species.
Under the classic basin model of density-dependent
habitat selection (Fretwell and Lucas, 1970; MacCall,
1990), stock expansion into marginal habitats may
occur at high densities (Swain and Wade, 1993;
Marshall and Frank, 1995; Swain, 1999), and directional shifts in the centers of distributions may occur
in cases where marginal habitat is not symmetrically
distributed around preferred habitat. For example,
arrowtooth flounder are generally located on the outer
EBS shelf and the steeper habitat of the EBS slope
likely constrains movement and forces any expansion
further toward the EBS shelf. Similarly, the center of
rock sole distribution in 1982 was located fairly close
to the Alaska Peninsula, thus forcing the area
expansion to the north and northwest. McConnaughey (1995) used a dispersion index (the CPUEweighted average distance of all tows from the
population centroid; Murawski and Finn (1988)) and
found significant positive relationships between
dispersion and abundance for flathead sole, Greenland
turbot and arrowtooth flounder, and a significant
negative relationship for Alaska plaice; rock sole
406
P.D. Spencer
Figure 7. Relationship between area occupied by arrowtooth flounder and area of the cold pool (a) and abundance
(b). The relationship between the area occupied by rock sole
and abundance (c) is shown for 1982–89 (squares; dotted
line) and 1990–2006 (triangles); the solid line and r and P
values are for all years.
Figure 8. Relationship between mean rock sole CPUE
within survey strata and overall population abundance from
1982 to 2006.
CPUE data (not shown) indicate that flatfish stocks
commonly have multimodal spatial distributions.
The pattern of density-dependent habitat selection
for rock sole exists largely from 1982 through 1989
(Fig. 8), a period which corresponds to declining
length at age (Walters and Wilderbuer, 2000) and
relatively high groundfish recruitments across the
North Pacific (Hare and Mantua, 2000). However,
from 1990 through 2006 the area occupied by 95% of
the stock does not show positive relationship with
dispersion was not found to be significantly related to
abundance. The difference in these results is likely
related to differing measures of spatial extent, as the
dispersion index used by McConnaughey (1995) can
confound changes in spatial extent with changes in
spatial pattern. For example, a stock with a multimodal spatial distribution will have a greater dispersion index than a stock with a single high density area
even if both stocks cover the same area, and maps of
Species
Model
Arrowtooth Null
flounder
Alternative
Rock sole
Null
Alternative
Residual Degrees
Scale
deviance of freedom parameter F-statistic P-value
87.37
63.29
96.03
84.97
216
207
240
230
0.53
0.60
0.46
0.42
4.44
<0.001
2.64
0.005
Table 2. Statistical models relating
strata CPUE and population size for
arrowtooth flounder and rock sole.
The F-statistic tests whether b is significantly different between strata (alternative
model) relative to the null model of b = 1 for all strata.
2008 The Author, Fish. Oceanogr., 17:5, 396–410.
Spatial distributions of eastern Bering Sea flatfish
Table 3. Multivariate models for the
location of rock sole and area occupied
by arrowtooth flounder.
Partial
r2
Dependent variable
Independent variables
Proportion of rock
sole in SE strata
Proportion of cold
pool in SE strata
Abundance
0.12
Abundance
0.21
Area of cold pool
0.34
Area occupied by
Arrowtooth flounder
407
Total
r2
Unaccounted
r2
0.54
0.07
0.81
0.26
0.35
The partial r2 indicates the variability explained after adjusting for the other
variable, and the unaccounted r2 is the total r2 minus the sum of the partial r2
values.
abundance. Walters and Wilderbuer (2000) observed
that the mean length of age-3 rock sole decreased from
1982 to 1990 and increased from 1990 to 1998. The
observations of decreasing length at age, increasing
abundance, and expanding population range during
the 1980s are consistent with the classic theory of
density-dependent habitat selection in which intraspecific competition results in range expansion.
Additionally, the identification of the 1989–90 period
as a breakpoint in the trends of range expansion and
age-3 rock sole size at age coincides with Hare and
Mantua’s (2000) identification of a 1989 regime shift,
after which declines in North Pacific groundfish
recruitment and salmon catches occurred. Rock sole
abundance has decreased through the 1990s, and the
decreasing trend in area occupied with population size
during this period may be attributable to changes in
population abundance occurring primarily in the highdensity areas.
Arrowtooth flounder also showed density-dependent habitat selection in which expansion to the
middle shelf is related to population increases, but this
movement is more strongly related to the reduction in
cold pool area in warm years (Table 3). While many
EBS flatfish species show movement along a northwest-southeast axis (motivating the use of the proportion in the SE strata as an index of movement),
arrowtooth flounder expand their populations through
onshelf movement (Fig. 4), which has a northward
component. Mueter and Litzow (2008) also observed a
significant northward movement related to temperature. Note that this movement does not necessarily
translate to increases in the proportion in the SE
strata, which increased in the early 1990s but has
shown little increase since then (Fig. 6). It is notable
that the 3 years in which arrowtooth flounder occupied the most area, 2003–2005, were also the 3 years
of the smallest cold pool area and very large popula 2008 The Author, Fish. Oceanogr., 17:5, 396–410.
tion sizes (Fig. 7). In 2006 some contrast is provided,
as the area occupied by arrowtooth flounder and area
of the cold pool both dramatically decreased, whereas
while the arrowtooth flounder population remained
very large.
The correlation of both density-dependent and
density-independent variables with EBS flatfish spatial
distributions leads to the question of the interaction
between these processes, or whether the temperature
selection of EBS flatfish is affected by population
density. For example, Swain (1999) found that
Atlantic cod in the Gulf of St. Lawrence are underrepresented in cold water in low abundance years and
over-represented in high abundance years. However,
the CPUE-weighted temperatures of EBS flatfish
do not reveal variation associated with abundance.
Instead, with the exception of arrowtooth flounder and
Greenland turbot, the trends of temperature occupied
by most EBS flatfish in this study follow the trends in
available temperature, although with slightly higher
mean levels for yellowfin sole and rock sole. This
indicates some plasticity of EBS flatfish with respect to
water temperature, and their habitat selection on
summer feeding grounds may be more strongly influenced by prey availability and/or predator avoidance
than maintaining their populations within a water
mass with particular temperature characteristics. In
contrast, other studies of habitat use for EBS groundfish found that the distributions of Arctic cod and
walleye pollock respond strongly to temperature variability (Wyllie-Echeverria and Wooster, 1998), and
Atlantic cod on the Scotian shelf were associated with
a water mass associated with a particular temperature
and salinity range (Smith et al., 1991). The relative
plasticity of EBS flatfish may also reflect their residence in demersal habitats, whereas gadids in the
pelagic water column may be expected to adjust their
habitat more easily in response to either abundance or
408
P.D. Spencer
changing environmental conditions. Greenland turbot
and arrowtooth flounder both occur largely on the
outer shelf typically outside of the cold pool area, and
the association of these species with this particular
depth zone may drive habitat selection. Previous
studies have found that habitat selection of EBS flatfish reflects a complex suite of factors such as depth
(Swartzman et al., 1992) and sediment characteristics
(McConnaughey and Smith, 2000).
Although many EBS flatfish show plasticity to
water temperatures, spatial distributions can sometimes
show substantial inter-annual differences, presumably
reflecting inter-annual changes in temperature, benthic production, or other habitat variables. Temporal
trends in flatfish distributions may not occur smoothly
over time, but rather can be punctuated by some
particularly unusual years such as 1999, when the
proportion in the SE strata increased for several species including rock sole, yellowfin sole, and flathead
sole. The 1999 survey was conducted about 2½ weeks
earlier than most other years, leading to the possibility
that the change in observed temperature reflected a
change in survey timing. However, rerunning the
analyses after removing the effect of survey timing on
temperature and location of the cold pool produced
results similar to those presented here. For yellowfin
sole and flathead sole, the lack of statistical significance between the 1999 distribution and other years
may reflect the overall variability within the CPUE
data and the conservative nature of the modified
Cramer–van Mises test. Substantial inter-annual
temperature changes occurred from 1998 to 1999 and
from 2005 to 2006 (Fig. 2), although dramatic changes
in flatfish distributions occurred from 1998 to 1999 but
not from 2005 to 2006 (Fig. 6), again suggesting that
measurements of summer water temperature do not
reflect all factors influencing habitat selection. This
variability may illustrate the importance of the linkages between event-scale environmental variability
and biological productivity (Bond and Overland,
2004), and an important future research topic will be
to evaluate how environmental conditions during
critical seasons in 1998 and 1999 relate to flatfish
distributions.
Temperature variability can affect research trawl
surveys either through availability (from changes in
spatial distributions) or catchability (from changes in
the behavioral response of fish to survey gear), thus
posing significant management challenges. For example, Smith et al. (1991) found that the availability of
Scotian shelf Atlantic cod to a bottom trawl survey
was a function of the extent to which an intermediate
layer water mass extended to benthic habitats, thus
confounding interpretation of survey abundance estimates. EBS Greenland turbot are found at the northern boundary of the survey area, and any movement
northwards would have direct effects on availability to
the annual survey. Yellowfin sole spawn in inner shelf
areas outside the EBS survey area, and rock sole, yellowfin sole, and flathead sole also have juvenile nursery areas in inner shelf areas (Wilderbuer et al., 1992,
2002). Thus, if the timing of ontogentic and/or seasonal movement to inner shelf areas or deeper habitats
is a function of environmental conditions, then the
proportion available to the survey could vary with
water temperature. The ontogenetic changes in fish
distributions motivate separate analyses for particular
age and/or length groups (Swain and Wade, 1993).
However, in this study, separate analysis of only adult
fish (as defined by the length categories in McConnaughey and Smith, 2000) did not change the interpretation. Finally, several flatfish species have been
observed to be herded into trawl nets (Somerton and
Munro, 2001), and temperature could potentially
affect this process and survey catchability through
changes in fish behavior (i.e., swimming speed). The
survey catchabilities of flathead sole and yellowfin
sole, estimated from stock assessments, are significantly related to temperature (Stockhausen et al.,
2006; Wilderbuer and Nichol, 2006a).
Given the general warming trend observed in the
EBS, it is reasonable to suspect that fish distributions
would also move north. However, several EBS flatfish
revealed spatial distributions that are not completely
explained by patterns in bottom water temperature,
and the spatial distributions of rock sole and arrowtooth flounder also show evidence of density-dependent habitat selection producing expansion in area
occupied. These findings are consistent with those of
Mueter and Litzow (2008), who found that while
there has been a northward shift of the general EBS
fish and invertebrate community, a temporal trend in
the residual variance not explained by temperature
may reflect species interactions. Prediction for any
particular species will remain difficult until more
refined habitat models are developed. As in this
study, Mueter and Litzow (2008) found a range of
species responses in that 16 of the 46 species examined showed significant northward movement and the
remaining 30 showed non-significant patterns
(including 10 that moved south). Future studies
should examine the myriad of density-independent
(temperature, depth, salinity) and density-dependent
(local population size and prey availability) variables
to gain a more detailed understanding of the complex
factors influencing flatfish habitat selection. For
2008 The Author, Fish. Oceanogr., 17:5, 396–410.
Spatial distributions of eastern Bering Sea flatfish
example, the Oscillating Control Hypothesis (Hunt .
et al., 2002) provides a proposed framework for
understanding how sea ice extent and timing of ice
retreat may influence benthic production and timing
of the spring bloom. Further refinements may include
observations and models examining how temperature
variation may influence spatial patterns of benthic
production, and how these patterns correspond to
flatfish distributions.
ACKNOWLEDGEMENTS
I thank the Resource Assessment and Conservation
Engineering Division of the Alaska Fisheries Science
Center for collecting the EBS survey data. Anne
Hollowed, Tom Wilderbuer, William Stockhausen,
Jim Ianelli, Martin Dorn, Bob Lauth, Chris Rooper,
Franz Mueter, and Stephani Zador provided helpful
comments on earlier drafts of this manuscript.
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