Progress in Oceanography 186 (2020) 102391

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Progress in Oceanography
journal homepage: www.elsevier.com/locate/pocean

Review of spatial and inter-annual changes in the zooplankton community
structure in the western Arctic Ocean during summers of 2008–2017

T⁎

Yoshiyuki Abea,b, , Kohei Matsunoc,d, Amane Fujiwarae, Atsushi Yamaguchic,daResearch Development Section, Oﬃce for Enhancing Institutional Capacity, Hokkaido University, Kita 21, Nishi 10, Kita-ku, Sapporo, Hokkaido 001-0021, Japan
Atmosphere and Ocean Research Institute, The University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa, Chiba 277-8564, Japanc
Graduate School of Fisheries Science, Hokkaido University, 3-1-1 Minatomachi, Hakodate, Hokkaido 041-8611, Japand
Arctic Research Center, Hokkaido University, Kita-21 Nishi-11 Kita-ku, Sapporo, Hokkaido, 001-0021, Japane
Japan Agency for Marine-Earth Science and Technology, 2−15 Natsushima-cho, Yokosuka, Kanagawa 237-0061, Japanb

A R T I C LE I N FO

A B S T R A C T

Keywords:
Western Arctic Ocean
Mesozooplankton
Copepods
Spatial distribution
Community structure
Pelagic ecosystem

Reduction in summer sea ice coverage has recently been observed in the western Arctic Ocean. Changes in the
coverage and timing of sea ice retreat are expected to have a great impact on the marine ecosystem. In this study,
we evaluated inter-annual changes in the spatial distribution of zooplankton communities in the western Arctic
Ocean, during the summers of 2008, 2010, 2012–2017. A total of 339 casts were conducted to collect zooplankton by vertical hauls at 22–63 stations per year in the western Arctic Ocean, between August 26 andOctober 13, 2008, 2010, 2012–2017. Based on cluster analysis, four zooplankton communities (basin, slope,
shelf, and new-shelf) were identiﬁed. Horizontal distribution of the zooplankton communities corresponded withthe depth of the sea ﬂoor. No signiﬁcant interannual variability in zooplankton and copepod abundance wasobserved in the Canada basin; however, a decline in the abundance of dominant copepods associated with anenhanced freshening of seawater was suggested by a General Linear Model analysis. The shelf assemblage wascharacterized by a high abundance of Paciﬁc species that was predicted by the length of the open water period.
The new-shelf assemblage, located between the shelf and the slope, showed low species diversity and abundance
and was observed only in 2012, 2015, 2016 and 2017 when the melting day of sea ice was signiﬁcantly earlier
than in the other years. Our study indicates that diﬀerent changes in each region can be expected in response to
the possible environmental changes in the Paciﬁc Arctic.

1. Introduction

2006; Woodgate et al., 2010). It has been reported that the increased
Paciﬁc summer water (PSW) inﬂow not only aﬀects the reduction of sea
ice, but also causes changes in the marine environment, such as theoccurrence of a large warm-core eddy within the shelf break area of the
Chukchi Sea and the enhancement of the Beaufort Gyre (Kwok et al.,2013; Nishino et al., 2011a). These changes in the coverage and retreat
timing of sea ice are expected to have a great impact on the marine
environment (Grebmeier et al., 2006; Hunt and Drinkwater, 2007)
making it increasingly important to study the lower trophic levels in thewestern Artic Ocean, in order to evaluate the eﬀects of sea ice reduction
on marine ecosystems.
Environmental changes caused by sea ice reduction in the Paciﬁc
Arctic are thought to have a relatively early impact on the plankton
communities that have a shorter life cycle than organisms at higher
trophic levels. Accurate evaluations and predictions of the plankton
community structures are becoming increasingly important to understanding marine ecosystem dynamics in the western Arctic Ocean.

Recently, atmospheric warming in the Arctic has been progressing
at twice or thrice the rate in other parts of the globe (Trenberth et al.,2007). A reduction in sea ice coverage during summer has also beenreported for the Arctic Ocean (Duarte et al., 2012). The Paciﬁc Arctic(western Arctic Ocean, Fig. 1), consisting of a shallow continental shelfextending from northern Bering Sea to the Chukchi Sea and the Canada
Basin, is one of the areas showing the highest sea ice reduction (Comiso
et al., 2008; Markus et al., 2009; Shimada et al., 2001, 2006; Stroeve
et al., 2007). In reality, because of an earlier sea ice melt timing and alater autumn freeze-up, it has been reported that the melt season in the
Chukchi Sea has increased at a rate of 13.2 days decade–1, from 1979 to2013 (Stroeve et al., 2014). Although there are numerous processes that
can accelerate the reduction of sea ice in summer (Kashiwase et al.,2017; Stroeve et al., 2012), the Western Arctic reduction in sea ice isrelated to an increased inﬂow of warm Paciﬁc waters (Shimada et al.,⁎Corresponding author.
E-mail address: y.abe@aori.u-tokyo.ac.jp (Y. Abe).

https://doi.org/10.1016/j.pocean.2020.102391
Received 1 November 2019; Received in revised form 4 March 2020; Accepted 7 June 2020
Available online 20 June 2020
0079-6611/ © 2020 Elsevier Ltd. All rights reserved.

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CanadaBasin

ChukchiSea
Siberia
Alaska2008 (54, 29 Aug.í4 Oct.)

2014 (22, 10í23 Sep.)

2010 (63, 4 Sep.í13 Oct.)

2015 (25, 5í29 Sep.)

2012 (51, 13 Sep.í3 Oct.)

2016 (31, 29 Aug.–22 Sep.)

2013 (36, 31 Aug.í4 Oct.)

2017 (57, 26 Aug.í19 Sep.)(number of station, period)
Fig. 1. Location of the sampling stations in the western Arctic Ocean during August–October 2008 and 2017. For the generalized linear model (GLM) analysis, we
extracted the abundance data from a gridded area (72°N–75°N, 150°W–170°W), where net sampling was conducted every study year.

2000, when sea ice reduction became rapid, covering broader areas.
In this study, we ﬁrst evaluated inter-annual changes in the horizontal distribution of zooplankton assemblages, derived from zooplankton abundance, biomass, and species diversity data collected fromthe northern Bering Sea and the southern Chukchi Sea to the Canada
Basin in the western Arctic Ocean, during the summers of 2008, 2010,
and 2012–2017. We then explored the characteristics of each group by
cluster analysis to reveal further the inter-annual changes in the zooplankton assemblages of each group. In the shelf break and slope area,
where sampling was possible every year, we evaluated the parameters
governing the standing stock of the Arctic copepod Calanus glacialis, a
key species in the western Arctic Ocean, in addition to predicting their
future abundance using a statistical model.

Phytoplankton communities exhibit major seasonal and spatial variations (Codispoti et al., 2005; Springer and McRoy, 1993), and Matsuno
et al. (2014) reported that the distribution of microplankton communities, including organisms from phytoplankton to ciliates, varies withthe latitude. Furthermore, environmental changes, such as earlier sea
ice retreat, can inﬂuence the phytoplankton community structure, e.g.,
haptophytes dominate the surface layer in the northern Chukchi Sea
with earlier melt year (Fujiwara et al., 2014; Lee et al., 2019).
Zooplankton, the secondary producers in the marine ecosystem,
connect the lower and upper trophic levels and are an important foodsource for pelagic ﬁshes, seabirds, and whales (Ashjian et al., 2010;
Lowry et al., 2004; Wassmann et al., 2006). Zooplankton communities
show great spatial variations, corresponding to the water masses of thenorthern Bering Sea and the southern Chukchi Sea (Ershova et al.,2015a; Hopcroft et al., 2010; Sasaki et al., 2016; Xu et al., 2018), theeastern Chukchi Sea (Ashjian et al., 2017; Pinchuk and Eisner, 2017;
Spear et al., 2019), and the Beaufort Sea (Smoot and Hopcroft, 2017). It
also has been shown that the yearly strength of PSW advection inﬂuences zooplankton community structure, resulting in diﬀerences intheir interannual horizontal distribution during summer in the Chukchi
Sea (Matsuno et al., 2011; Pinchuk and Eisner, 2017; Spear et al.,2019). Despite numerous studies of zooplankton community structurein the western Arctic Ocean, the majority of past studies have focusedon limited regions and years, with only a few long-term studies since

2. Materials and methods
2.1. Field sampling
A total of 339 vertical hauls of a NORPAC net (mouth diameter
45 cm, mesh size 335 um) from 150 m (for stations with > 150 m
depth) or 5 m above the sea bottom (for stations with < 150 m depth)
up to the sea surface were conducted to collect zooplankton (Table S1;
Fig. 1). Sampling was conducted from the RCGC Amundsen in 2014 andfrom the R/V Mirai in other years. The volume of water ﬁltered through2

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the net was estimated using a ﬂow-meter (Rigosha Co. Ltd.) mounted on
the mouth of the net. Once onboard, zooplankton samples were immediately preserved in 5% v/v borax buﬀered formalin. At each station,
the temperature and salinity were measured with a rosette mounted
CTD sampler (Sea-Bird Electronics Inc., SBE 911 Plus). Seawater samples were collected from 4 to 9 discrete depths as well as at 5 m and at
150 m (for stations in > 150 m bottom depth) or 10 m above the sea
bottom (for stations with < 150 m depth), using Niskin bottles
mounted on a rosette. Nutrient concentrations (NO2, NO3, NH4, PO4
and Si(OH)4) in the water samples were analyzed onboard using an
auto-analyzer. Chlorophyll a (Chl. a) concentrations were also determined ﬂuorometrically by the non-acidiﬁcation technique(Welschmeyer, 1994), using a 10-AU ﬂuorometer (Turner Designs Inc.,San Jose, CA, USA). All hydrographic datasets were provided by Japan
Agency for Marine-Earth Science and Technology (JAMSTEC).

To evaluate the relationship between the abundance of dominant
species/taxa and environmental parameters, Generalized Linear Models(GLM) were constructed in R version 3.4.3, using the glm2 package(Marschner, 2011; R Development Core Team, 2017). Abundances wereused as response data for each group separated by the cluster analyses.
Five explanatory variables obtained from CTD data, integrated meanwater column temperature (IMT), integrated mean water column salinity (IMS), integrated mean water column chlorophyll a concentration(IMC), sea surface temperature (SST), and sea surface Chl. a (SSC), andfour explanatory variables obtained from the satellite datasets (collected daily, 72 km resolution; Fujiwara et al., 2014, 2016, 2018), including annual median Chl. a (AMchl), annual median temperature(AMtemp), annual primary production (APP) and open period of sea ice(OpenPeriod) were included in the GLM. Backward stepwise model
selection using the “MASS” package was done to ﬁt the models. The
most appropriate models were selected using the Akaike Information
Criterion (AIC) (Yamaoka et al., 1978).

2.2. Samples and data analyses

3. Results

In the laboratory, zooplankton samples were split using a Motoda
box splitter (Motoda, 1959). An aliquot from each sample was weighed
for wet mass (WM), with a precision of 0.01 g, using an electronicbalance (Mettler PM4400). The sample remaining was used for theidentiﬁcation and enumeration of zooplankton under a dissecting microscope. Calanoid copepods were identiﬁed to the species level, following mainly Brodskii (1967) and Frost (1989) for Pseudocalanus spp.
(P. acuspes, P. mimus, P. minutus and P. newmani), and Miller (1988) for
Neocalanus spp. Because Calanus glacialis and C. marshallae are morphologically very similar, the two species were not diﬀerentiated andwere pooled as C. glacialis. For the early copepodid stages of Calanus
spp. (C. glacialis and C. hyperboreus), we used the prosome length for
species identiﬁcation (Hirche et al., 1994; Kosobokova and Hirche,2016). For Pseudocalanus spp., species identiﬁcation was done for late
copepodid stages (C5F/M and C6F/M), and the early copepodid stages
were integrated as Pseudocalanus spp. For C. glacialis, the Mean Copepodid Stage (MCS) was calculated using the following equation:

3.1. Hydrography
Integrated mean temperature ranged between −1.4 and 7.8 °C
during the study period, and was high in the shelf but low in the basin,
particularly in the western part of the basin (Fig. 2). Integrated meansalinity during the study period ranged from 29.4 to 33.2 and was low
in the eastern basin and on the shelf only in 2012. Chlorophyll a ranged
from 8 to 290 mg m−2, and was high on the shelf particularly oﬀ of thecoast of Utqiagvik in 2008 and around the Bering Strait in 2015 and2016.
3.2. Zooplankton abundance and biomass
Zooplankton abundance during the study period ranged between
2889 and 274,021 ind.m−2, and was greater on the shelf than in thebasin (Fig. 3). Zooplankton biomass ranged from 1 to 263 g WM m−2,
and showed a spatial pattern similar to that of the abundance distribution.

6

MCS =

∑i = 1 i × Ai
6∑i = 1 Ai(1)−2

where i is the copepodid stage (1–6 indicates C1–C6), and Ai (ind.m )is the abundance of the ith copepodid stage (cf. Marin, 1987). A species
diversity index (H′) was calculated using the following equation:

H ' = − ∑ (ni/ N ) × ln(ni/ N )3.3. Community structure
Sixty-nine species/taxa of zooplankton and 36 species belonging to
25 genera of calanoid copepods were identiﬁed (Table 1). Based oncluster analysis of zooplankton community composition, four groups ofstations: basin (n = 47 stations), slope (n = 166 stations), shelf(n = 80 stations) and new-shelf (n = 36 stations) were identiﬁed at
57% and 62% similarity levels (Fig. 4A).
Zooplankton abundance varied greatly depending on the stationgroup. The basin stations had the second-lowest mean abundances andlow species diversity, with averages of 14,029 ind.m−2 and 1.80, respectively (Fig. 4C). For the species/taxa composition in abundance, thepercentage of other copepods in the basin assemblage (13.1%) was
higher than that of other groups (6.6–8.1%). The slope assemblage hadintermediate abundance and species diversity, with averages of 48,329
ind.m−2 and 1.95, respectively. In the slope assemblage, the averageabundance of C. glacialis (14,703 ind.m−2) was the highest within thefour groups. The shelf assemblage had the highest abundance andspecies diversity, with averages of 73,022 ind.m−2 and 2.19, respectively. The shelf assemblage was characterized by a high abundance ofPaciﬁc species, especially the copepod Metridia paciﬁca (9%) that hadpresumably been transported from the Bering Sea. In the new-shelfassemblage, the species composition was similar to that of the slope
assemblage, but it had the lowest abundance and species diversity of
the groups, with averages of 13,815 ind.m−2 and 1.75, respectively.
According to the results of SIMPER analysis, the top four species that
contributed most to the dissimilarity in the community structure of the(2)−2

where ni is the abundance (ind.m ) of the ith species, and N is theabundance of total calanoid copepods in the group (Shannon andWeaver, 1949). The abundance datasets (X, ind.m−2) for each species
were log-transformed (log10[X + 1]). The community analysis performed for log-transformed abundance using the all of the station data
across all years. Similarity between samples were calculated using the
Bray-Curtis similarity index (Bray and Curtis, 1957). For grouping thesamples, similarity indices were coupled with hierarchical agglomerative clustering, using a complete linkage method (UPGMA: Unweighted Pair Group Method using Arithmetic mean) (Field et al.,1982). A similarity percentage analysis (SIMPER) was conducted todetermine the percent contribution of each species/taxa to the observed
similarity between groups. Nonmetric Multi-Dimensional Scaling(NMDS) ordination was employed to delineate the sample groups on a
two-dimensional map. The NMDS plots and the hydrographic data
(latitude, longitude, depth, integrated mean temperature, integrated
mean salinity, integrated mean Chl. a) were subjected to multiple-regression analyses. All these analyses were performed in the PRIMER v7
software (PRIMER-E Ltd., Plymouth, UK). Diﬀerences in zooplankton
and copepod abundance and environmental parameters, between years
and sampling days were compared using two-way ANOVA, performed
using the Stat View v5 software (SAS Institute Inc.).
3

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Fig. 2. Spatial changes in the integrated mean temperature, integrated mean salinity, and integrated chlorophyll a in the western Arctic Ocean during
August–October 2008 and 2017.

4

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Table 1
List of mesozooplankton species identiﬁed in the western Arctic Ocean during
2008–2017.
Species/taxa

Grand mean (ind.m−2)

Calanoid coepods
Calanus glacialis
Pseudocalanus newmani
Pseudocalanus spp. (C1–C4)
Pseudocalanus acuspes
Pseudocalanus minutus
Metridia paciﬁca*
Pseudocalanus mimus
Acartia longiremis
Metridia longa
Centropages abdominalis
Microcalanus pygmaeus
Eucalanus bungii*
Calanus hyperboreus
Eurytemora herdmani
Paraeuchaeta glacialis
Calanus marshallae
Acartia hadsonica
Neocalanus ﬂemingeri*
Scolecithricela minor
Neocalanus plumchrus*
Chiridius obtsifrons
Spinocalanus lomgicornis
Heterorhabdus norvegicus
Temotites brevis
Neocalanus cristatus*
Aetideopsis multiserrata
Gaetanus tenuispinus
Gaidius brevispinus
Epilabidocera amphitrites
Scaphocalanus magnus
Tortanus discaudatus
Aetideopsis rostrata
Heterorhabdus compactus
Rincalanus nasutus
Undinella oblonga
Racovitzanus antarcticus
Lucicutia anomala

10,309
4921
4603
4373
2785
1370
988
897
847
549
362
268
96
73
62
37
33
30
22
18
16
13
13
10
8
6
5
4
3
2
1
1
0.5
0.4
0.3
0.2
0.1

Other taxa
Barnacle larvae
Echinodermata larvae
Appendicularians
Cyclopoid copepods
Hydrozoans
Polychaetes
Chaetognaths
Bivalvia larvae
Pteropods (Limacina helicina)
Cladocerans (Podon spp.)
Euphausiids
Ostracods
Cladocerans (Evadne spp.)
Amphipods
Pteropods (Clione limacina)
Eubrachyura zoea
Isopods
Poecilostomatoid copepods
Harpacticoid copepods

2895
2626
2395
2194
1193
1026
934
399
264
138
121
52
37
32
19
8
8
5
0.7

* Paciﬁc species.

slope and the new-shelf were M. paciﬁca, barnacle larvae, Centropages
abdominalis, and polychaetes, with a cumulative contribution rate of
22.7% (Table S2). Each assemblage was also clearly separated in the
NMDS plot (Fig. 4B). For the ordination of NMDS plots, several environmental parameters (temperature, salinity, Chl. a, latitude, anddepth) were signiﬁcant (r2 = 0.14–0.62).
The horizontal distributions of the zooplankton communities wereseparated and corresponded with the depth (Fig. 5). Interannual variation in horizontal distribution was observed every year, except 2015,
for the slope assemblage, and in the basin assemblage, variation wasFig. 3. Horizontal distribution of zooplankton abundance and biomass in thewestern Arctic Ocean during August–October of 2008–2017.

5

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Fig. 4. Results of cluster analysis based on zooplankton abundance by Bray-Curtis similarity connected UPGMA. Four assemblages were identiﬁed with the similarity
at 57% and 62%, respectively (dashed lines) (A). Non-metric multidimensional scaling plots of each group (B). For various environmental parameters, their directions
and coeﬃcients of determination (%) are shown. Sal.: salinity, Chl. a.: chlorophyll a, Tem.: temperature, Lon.: longitude, Lat.: latitude, Dep.: sampling depth. The
mean abundance, species diversity and taxonomic composition of each group (C).

AMchl), however, no signiﬁcant inter-annual diﬀerences were observed
for zooplankton and copepod abundance. There was a signiﬁcant difference in the inter-annual variability and seasonal changes in the integrated mean Chl. a, and zooplankton and copepod abundance of the
shelf assemblage.

observed in all years when observation in this area was possible. The
new-shelf assemblage, located between the shelf and slope, occurred forthe ﬁrst time in 2012 and was then observed mainly in 2015, 2016 and2017.
We performed two-way ANOVA analyses to determine if there weresigniﬁcant annual variability or seasonal changes in environmental
variables, and copepod and zooplankton abundance within each assemblage (Table 2). The new-shelf assemblage was not included due tothe insuﬃcient number of samples. In the basin assemblage, signiﬁcantinter-annual variability was observed for salinity and Chl. a, however,no signiﬁcant diﬀerence in seasonal changes was observed. No signiﬁcant diﬀerences were observed in inter-annual and seasonal changes
for zooplankton and copepod abundance in the basin assemblage. In theslope assemblage, located mainly in the shelf break and slope areas,signiﬁcant inter-annual variability and seasonal changes were observed
for all environmental parameters (IMT, IMC, OpenPeriod, AMtemp, and3.4. GLM analyses
The results of the relationship between environmental variables andthe abundance of species/taxa, which showed a high contribution in the
SIMPER analysis, in each group, determined using the GLM analysis,
are shown in Table 3. In the basin assemblage, every three species andthe total copepod abundance had a signiﬁcant positive or negative relationship with the variation of IMS. The slope assemblage showed amore distinct relationship with the sea surface satellite data than thebasin assemblage. In the basin assemblage, C. glacialis showed a6

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2008

2010

2012

2013

2014

2015

2016

Basin
Slope
Shelf
New-Shelf
Out

2017

Fig. 5. Horizontal distribution of the four groups (Basin, Slope, Shelf, New-Shelf) identiﬁed from the Bray-Curtis similarity index based on abundances data in thewestern Arctic Ocean during summers of 2008–2017.

between the predicted data and the observed data, at ﬁrst, we extracted
C. glacialis abundance data from a gridded area (72°N–75°N,
150°W–170°W) where net sampling was conducted every study year
(Fig. 1). The GLM analysis was performed using the extracted abundance data of C. glacialis as the response variable and the environmental
parameters (72 km grid resolution including sampling station) derived
from the satellite data (OpenPeriod, AMtemp, AMchl, APP) as explanatory variables (Table S3). Since models including OpenPeriod andAMtemp showed the best ﬁt based on AIC, we used the GLM analysis
including these two parameters. We simulated the entire time series ofsigniﬁcant positive relationship with OpenPeriod and IMS, and a signiﬁcant negative relationship with AMtemp. Pseudocalanus spp. had asigniﬁcant positive relationship with AMtemp, and a negative relationship with APP.
The abundance of C. glacialis, the most abundant species, in theslope assemblage had a signiﬁcant relationship with the satellite data
based on the GLM analysis (cf. Table 3). If the annual variability in thepredicted abundance close to the annual changes in the observed
abundance data, the prediction model based on the satellite data would
become available as a good model. To evaluate the relationship7

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Table 2SIMPER analyses showing diﬀerences in species/taxa assemblage between the groups, species/taxa (with % contribution) contributing to the dissimilarities between
pair of groups.
Group

A (Basin)B (Slope)

C (shelf)

B (Slope)
Centropages abdominalis (5.0%)
M. longa (4.6%)
Pseudocalanus spp. (4.6%)
M. paciﬁca (4.5%)
C (shelf)
Pseudocalanus spp. (11.5%)
Acartia longiremis (5.6%)
Barnacles nauplii (5.5%)
Polychaetes (4.9%)

M. longa (6.0%)
M. paciﬁca (5.9%)
Centropages abdominalis (5.8%)
Eucalanus bungii (4.7%)

M. longa (6.9%)
M. pygmaeus (6.4%)
P. glacialis (5.8%)
C. hyperboreus (5.6%)

M. longa (7.7%)
Barnacles nauplii (5.7%)
M. pygmaeus (5.4%)
Pseudocalanus spp. (5.2%)D
M. paciﬁca (5.9%)
Barnacles nauplii (5.6%)
Centropages abdominalis (5.6%)
Polychaetes (5.6%)

Table 3
Variance analyses (two-way ANOVA) on year to year and day to day diﬀerencesin environmental parameter and abundance of zooplankton and copepod ofgroup A (Basin), group B (Slope) and group C (Shelf) during summers of
2008–2017. IMT: integrated mean temperature (0–150 m or 0–bottom-5 m),
IMS: integrated mean salinity (0–150 m or 0–bottom–5 m), IMC: Integrated
mean chl. a (0–150 m or 0–bottom–5 m), OpenPeriod: Open period of sea ice,
AMtemp: Annual median temperature, AMchl: Annual median chl. a, APP:
Annual Primary Production, Zooplankton: zooplankton abundance, Copepods:
copepod abundance.
Group

Parameter

F-valueYear

Day

Year × Day

IMT
IMS
IMC
OpenPeriod
AMtempAMchl
APP
Zooplankton
Copepods

0.495ns
4.318**
4.901**
0.832ns
0.476ns0.579ns–0.419ns
0.329ns

0.011ns
0.448ns
0.918ns
0.337ns
0.345ns0.188ns–
0.060ns
0.051ns2.466ns4.308**
4.713**
0.800ns0.550ns
0.620ns–
0.436ns
0.391ns

IMT
IMS
IMC
OpenPeriod
AMtempAMchl
APP
Zooplankton
Copepods

5.572***
2.746*
2.154*
9.910***
10.085***14.092***
7.939***
1.332ns
1.823ns

10.766**1.016ns
6.230*
7.581**
9.027**
62.684***0.006ns
4.088*
2.552ns5.415***
2.395*
2.159*
9.740***
9.954***
13.629***7.737***
1.327ns
1.815ns

IMT
IMS
IMC
OpenPeriod
AMtempAMchl
APP
Zooplankton
Copepods

1.208ns
1.205ns
6.400***
0.457ns
0.538ns
1.555ns
1.538ns2.795*
4.381**

3.704ns0.226ns
20.246***0.104ns
0.343ns
0.852ns
0.115ns9.639**
14.877**1.258ns
1.138ns
6.310***
0.459ns
0.574ns
1.573ns
1.457ns2.789ns
4.400**A (Basin)B (Slope)

Fig. 6. Inter-annual variability of the observed data and GLM predicted data ofC. glacialis abundance in the gridded area (cf. Fig. 1) (A). Inter-annual variability of the selected explanatory variables in the GLM. OpenPeriod: a period of
open water, AMtemp.: annual median temperature from the satellite data.

C (Shelf)

observed abundance data with the predicted data (Fig. 6A). Inter-annual changes in the two parameters are shown in Fig. 6B. A similarvariation was observed in both observed and predicted data; however,
the observed data showed lower variation than the predicted data in2015 and 2016.
4. Discussion

ns

Not signiﬁcant.
* p < 0.05.
** p < 0.01.
*** p < 0.001.

4.1. Horizontal distribution
Four major groups of stations were identiﬁed based on faunal assemblages. In previous studies, it had been suggested that such a distribution is related to biogeographic variations and the presence ofseveral water masses in the western Arctic Ocean (Ershova et al.,C. glacialis abundance from the satellite data (OpenPeriod and AMtemp)
in the grid area (72°N–75°N, 150°W–170°W), and compared the8Progress in Oceanography 186 (2020) 102391

Y. Abe, et al.

Pseudocalanus spp. so that high abundances are expected when thesetwo parameters increase. It has been established that there is a direct
relation between the number of larvae ejected by barnacles, bivalves,and polychaetes and the phytoplankton density (Ambrose and Renaud,
1997; Clare and Walker, 1986; Graf et al., 1982). Hence, the highabundance of Pseudocalanus spp., the Paciﬁc copepods and the benthic
larvae in the shelf assemblage might have been caused by the highintegrated mean temperature, integrated mean salinity, and annual
primary production from the inﬂow of the warm Paciﬁc water.

2015a; Hopcroft et al., 2010; Matsuno et al., 2011; Smoot and Hopcroft,
2017; Spear et al., 2019; Xu et al., 2018). Owing to the large coverageof the western Arctic Ocean region, in the present study, the coverage ofeach assemblage was larger than that of any previous study. Hence, we
did not observe small community variations in response to ﬁne watermass variability as observed in previous studies.
The basin assemblage had the lowest abundance of Pseudocalanus
spp., and a lower abundance of C. glacialis compared to the slope assemblage. Furthermore, this group exhibited the second-lowest zooplankton abundance (Fig. 5). A low zooplankton abundance has previously been documented in this area (Ashjian et al., 2003; Lane et al.,2008; Rutzen and Hopcroft, 2018). The low abundance of zooplankton
observed in the basin in the present study is consistent with the previous studies showing low abundances in the Canada Basin, inside of
the Beaufort Gyre. The basin assemblage was also characterized by thepresence of mesopelagic copepod species (Heterorhabdus norvegicus,
Paraeuchaeta glacialis, Spinocalanus longicornis, Temorites brevis), consistent with the basin location. Previous studies, with an approach similar to the present study, have reported the occurrence of mesopelagic
copepods and a reduction in the zooplankton abundance around the
deep pelagic stations in the western Arctic Ocean (Smoot and Hopcroft,
2017; Xu et al., 2018).
The slope assemblage was widely distributed across the slope andshelf-break regions and included the highest number of stations. The
slope assemblage was characterized by C. glacialis, which was mostabundant, Pseudocalanus spp. and appendicularians. The mean copepodid stage (MCS) of C. glacialis (3.57) in the slope assemblage waslower compared to other groups (basin: 4.20, shelf: 4.28, new-shelf:
4.51); in other words, the abundance of early copepodid stages washigh in this group. The mtCOI gene analysis revealed that the Bering
haplotype of C. glacialis dominated the shelf region of the Chukchi Sea
while the Arctic haplotype was dominant in the slope area (Ashjian
et al., 2017; Nelson et al., 2009). C. glacialis undergoes a diapause
period in the mesopelagic layer, requiring depths greater than that of
the shelves to complete their life cycle (Ashjian et al., 2003; Hirche,1991). As a result, low abundances of C. glacialis, especially early copepodid stages, are observed on the shallow (< 50 m) Chukchi Shelf(Matsuno et al., 2012b, 2016). The characteristic high abundance andlow MCS of C. glacialis in the slope assemblage suggest that it is a habitat of the Arctic haplotype population. Also, the presence of theBering haplotype indicates to its transport from the Bering Strait.
The shelf assemblage, with many stations in the northern Bering Sea
and the shelf region of the southern Chukchi Sea, was characterized bya high zooplankton abundance, and the occurrence of Paciﬁc andcoastal species, with a high species diversity in the slope region (Table
S2, Fig. 5). The SIMPER analysis revealed that M. paciﬁca was the mostfrequent Paciﬁc copepod in this assemblage with a higher contribution
to the total abundance (9%) compared to that in other assemblages.
Johnson (1963) has reported the occurrence of the Paciﬁc copepods
Neocalanus cristatus and Eucalanus bungii on the Chukchi Abyssal Plain(85°06′N, 168°40′W) in 1953. The major distribution of Paciﬁc copepods in the western Arctic Ocean has been described in Nelson et al.
(2014). The Paciﬁc zooplankton species seem to have arrived with theadvection of Paciﬁc water (Ershova et al., 2015a; Hopcroft et al., 2010;
Matsuno et al., 2011), which is warm and enriched with nutrients,
passing through the Bering Strait with several other water masses(Anadyr Water, Bering Sea Water and Alaskan Coastal Water)(Coachman et al., 1975; Danielson et al., 2017). The shelf assemblage
had the highest zooplankton abundance composed primarily of Pseudocalanus spp., Paciﬁc copepods, and benthic larvae. Based on morphological and molecular approaches, four species of the genus Pseudocalanus (P. minutus, P. acuspes, P. mimus, P. newmani) have been
documented in the western Arctic Ocean (Ershova et al., 2017); thepresence of these four species was conﬁrmed in this study. It was evident from the GLM that annual mean temperature and annual mean
primary production were signiﬁcant predictors of the abundance of

4.2. Inter-annual changes
Inter-annual changes in the zooplankton community structureduring summer in the western Arctic Ocean were diﬀerent for each
assemblage. Notwithstanding with some diﬀerences in the annual distribution of se-ice during the sampling years, it was evident that themelt day of sea ice in the study region was signiﬁcantly diﬀerent (oneway ANOVA, p < 0.05). The meldt day was clearly earlier than day
200 in 2012, 2015, 2016 and 2017, which corresponded with the appearance of the new-shelf assemblage with low average abundance andlow species diversity. Okkonen et al. (2019) found interdependent relationships between changes in seasonally regional winds and thetiming of sea ice retreat and water mass in the northwestern Chukchi
Sea. Changes in the phytoplankton community structure and a decreasein the abundance and distribution of phytoplankton has been reported
in summer, when the sea surface temperature increase and nutrient
depletion occurs in response to early sea ice retreat in the western
Arctic Ocean (Li et al., 2009; Fujiwara et al., 2014). The occurrence ofthe new-shelf assemblage, with low abundances and species diversity inthe northern Bering Sea and southern Chukchi Sea, might be due tochanging phytoplankton community structure due to early sea ice retreat correlated with seasonally-averaged regional winds.
Inter-annual variability or seasonal changes in the environmental
factors and zooplankton abundance were small in the basin assemblage
during our study period (Table 2). The low variability in the zooplankton community was expected due to the small changes in theenvironmental factors in the Canada Basin, which included almost all
stations of the basin group. However, low primary production is expected in the central Canada Basin, due to the intensiﬁcation of the
anticyclonic circulation, enhanced stratiﬁcation by the accumulation ofless saline meltwater at the surface, and deepening of the nutricline(Nishino et al., 2011b; Zhang et al., 2020). The eﬀects of changing
environmental conditions on lower trophic levels in the western Arctic
Ocean have also been reported, including a change in the size of thedominant phytoplanktons from nano to pico (Li et al. 2009), and adominance of haptophytes during the early sea ice retreat years(Fujiwara et al., 2014). The results of GLM analysis indicated that in thebasin, the abundance of dominant copepods is declining with decreasing salinity, except for the Microcalanus abundance. Althoughvariability has not been observed in the abundance of all zooplanktons,
Metridia longa abundance decreased signiﬁcantly from 2008 to 2014,
with the low salinity period (one-way ANOVA, p < 0.001). The
freshening of seawater has also been documented in the Canada Basin(Yamamoto-Kawai et al., 2009). Our results suggest that a decline in thestanding stock of zooplankton and changes in their community structure are expected as freshening of seawater increases, along with arecent increase in river discharge (Peterson et al., 2002) and changes in
the phytoplankton community structure in the western Arctic Ocean
basin.
Signiﬁcant variability was observed for Chl. a, and zooplankton andcopepod abundance in the shelf region (Table 2). An inter-annual
variability in the sea ice retreat rate and the sea ice melt season, which
depends on various factors (e.g., ice-albedo feedback, the inﬂow of PSW
and winds) (Serreze and Stroeve, 2015; Steele et al., 2015; Stroeve
et al., 2014), has also been observed. Such variability has a crucial
eﬀect on the community structure and size of phytoplankton that9

Progress in Oceanography 186 (2020) 102391

Y. Abe, et al.

temperature, and the prediction models showed that their abundance
would increase with an increase in the aforementioned environmental
factors. In the shelf group, the period of open water was a signiﬁcantpredictor of the abundance of Paciﬁc copepods, with longer periods,
caused by an increase in the annual median temperature, increasing the
copepod abundance. These results suggest that earlier sea ice reductionand enhanced inﬂow of the warm Paciﬁc Water resulted in a higher
diversity of Paciﬁc species in the shelf region. This change can possibly
lead to an increase in the area of new-shelf, which showed a low species
diversity and zooplankton abundance. Our study suggests that environmental changes in the Paciﬁc Arctic will have varied eﬀects on thezooplankton communities in each region.

sustains the zooplankton in the lower trophic level (Fujiwara et al.,2016, 2014; Lee et al., 2019; Selz et al., 2018). Based on the long-term
observations, there is a trend of an increase in the zooplankton abundance in the shelf region (Ershova et al., 2015b; Matsuno et al., 2011),
and the increased inﬂow of the warm Paciﬁc water (Woodgate et al.,2010) can potentially lead to an increase in the zooplankton biomass(Matsuno et al., 2011, Matsuno et al., 2012a,b). Moreover, Sasaki et al.
(2016) tested the relationship between environmental variables and thezooplankton standing stock using statistical models and found thatzooplankton abundance increased with early sea ice melt in thenorthern Bering Sea and the southern Chukchi Sea. In the present study,
as OpenPeriod and AMtemp were selected as the explanatory variablesin the GLM, an increase in zooplankton and Paciﬁc copepod abundancemight result from an increase in these variables. Hence, the zooplankton standing stock might vary depending on the variation in therate of sea ice reduction and the extent of open areas formed due tovarious factors, such as an increase in the inﬂow of Paciﬁc water.
In the slope assemblage nestled between the basin and the shelf, asigniﬁcant variation in the environmental factors was detected (Table
S2, Fig. 5). In this region of the western Arctic Ocean, the environmentchanges considerably due to the variation in inﬂow of Paciﬁc water inthe subsurface layer (Pickart et al., 2019), inter-annual changes in thesea ice cover in summer (Kwok et al., 2009; Tivy et al., 2011; Wanget al., 2019), the occurrence of upwelling (Huﬀord, 1974; Lin et al.,2019; Schulze and Pickart, 2012), and the formation of a large warmcore eddy due to the inﬂow of Paciﬁc water and sea ice reduction(Nishino et al., 2011a). The high abundance of C. glacialis has previously been reported in the slope region of the Chukchi Sea (Matsuno
et al., 2016), as was observed in the present study. Since C. glacialis is ahighly dominant zooplankton species and has an important role inconnecting the lower and higher trophic levels, it is considered as a key
species in the shelf region (Hopcroft et al., 2010; Matsuno et al.,2012b). To determine the environmental factors aﬀecting the abundance of C. glacialis in the slope region, we performed a GLM analysis.
The best-ﬁt models included AMtemp and OpenPeriod as the explanatory variables (Table S3). The GLM showed that the abundance ofC. glacialis increased with increasing OpenPeriod and AMtemp in thegridded slope region. The OpenPeriod, in particular, was an important
predictor of C. glacialis abundance, and the observed abundance dataalso showed a similar increasing trend. Based on modeling studies,
Wassmann et al. (2015) have predicted that the main geographicaldistribution of C. glacialis will have shifted from the Atlantic to the
Paciﬁc Arctic by 2099. Taking this into account, it becomes very important to predict the abundance of C. glacialis in the slope region,
where they showed a high abundance during the present study. The
OpenPeriod has increased in the gridded area (Fig. 6B), and the summer
melt season in the western Arctic Ocean has lengthened at a rate of
13.2 days decade–1 (Stroeve et al., 2014). We predict that the abundance of C. glacialis might increase when the earlier sea ice reduction
increases the period of open water, increasing the temperature in theslope region. Such a change can potentially aﬀect the lower trophic
levels in the western Arctic Ocean.

Declaration of Competing Interest
The authors declare that they have no known competing ﬁnancial
interests or personal relationships that could have appeared to inﬂuence the work reported in this paper.
Acknowledgements
The authors are indebted to the captain, oﬃcers, and crews of the
R/V Mirai and CCGS Amundsen. This research was funded by the Japan
Society for the Promotion of Science (JSPS) (Grant-in-Aid for JSPS
Fellows), the GRENE Arctic Climate Change Research Project, and theArctic Challenge for Sustainability (ArCS) Project.
Appendix A. Supplementary material
Supplementary data to this article can be found online at https://doi.org/10.1016/j.pocean.2020.102391.
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