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Structure of mesozooplanktoncommunity in the Barents Sea andadjacent waters in August 2009Vladimir G. Dvoretsky a & Alexander G. Dvoretsky aa Murmansk Marine Biological Institute (MMBI) , Vladimirskaya St.17, Murmansk , 183010 , RussiaPublished online: 18 Jun 2013.

To cite this article: Vladimir G. Dvoretsky & Alexander G. Dvoretsky (2013) Structure ofmesozooplankton community in the Barents Sea and adjacent waters in August 2009, Journal ofNatural History, 47:31-32, 2095-2114, DOI: 10.1080/00222933.2013.772670

To link to this article: http://dx.doi.org/10.1080/00222933.2013.772670

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Journal of Natural History, 2013Vol. 47, Nos. 31–32, 2095–2114, http://dx.doi.org/10.1080/00222933.2013.772670

Structure of mesozooplankton community in the Barents Seaand adjacent waters in August 2009

Vladimir G. Dvoretsky* and Alexander G. Dvoretsky

Murmansk Marine Biological Institute (MMBI), Vladimirskaya St. 17, Murmansk 183010,Russia

(Received 26 March 2012; final version received 30 January 2013; first published online 18 June 2013)

Strong climatic fluctuations have been documented in the Arctic in recent years.To detect possible impacts of the climatic variability on the pelagic ecosystemwe investigated mesozooplankton communities collected in the summer of 2009.Oithona similis dominated in terms of total abundance while Calanus species con-tributed a major part of the total biomass. The total mesozooplankton abundanceranged from 143 to 6145 individuals m−3. The highest average mesozooplanktonbiomasses were found in the frontal zone of Atlantic waters (AW) located southof the Svalbard archipelago and in Arctic waters (ArW), while the minimum wasregistered in Murmansk coastal waters (MCW). The spatial distributions of themesozooplankton communities were strongly related to latitude and hydrologicalconditions. A possible impact of the recent cooling registered in the Barents Seasince 2007 was detected as a decrease in the total mesozooplankton biomass withinMCW in the summer of 2009.

Keywords: Arctic shelf; Barents Sea; mesozooplankton; distribution; communitystructure

Introduction

The Barents Sea is one of the largest shelf regions of the Arctic Ocean (Sakshaug et al.2009). The area is characterized by varying environmental conditions and high pri-mary production (Wassmann et al. 2006; Loeng and Drinkwater 2007). The southern,western and central parts of the sea are influenced by warm Atlantic waters (Loenget al. 1997; Matishov et al. 2004). Therefore, pelagic communities in these regions dis-play boreal features including taxon composition and the proportions of dominantspecies (Timofeev 2000). At the same time, the northern and eastern Barents Sea isstrongly affected by waters from the Arctic Ocean (Loeng et al. 1997; Matishov et al.2004). As a result, the biota of these zones is dominated by coldwater taxa (Timofeev2000).

Mesozooplankton transfer energy from primary producers to the higher trophiclevels (Raymont 1983). In the Barents Sea, production of zooplankton communities isused by fish, many of which have commercial value (capelin, cod, herring) (Wassmannet al. 2006; Sakshaug et al. 2009). Hence, the current status of zooplankton may beused to estimate possible food stock for commercial species. At the same time, someregions of the Barents Sea and adjacent waters are still poorly studied (northern and

*Corresponding author. Email: vdvoretskiy@mmbi.info

© 2013 Taylor & Francis

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2096 V.G. Dvoretsky and A.G. Dvoretsky

eastern zones), despite recent progress in their investigations (e.g. Daase and Eiane2007; Blachowiak-Samolyk et al. 2008a, 2008b; Dvoretsky and Dvoretsky 2009a,2009b, 2010a, 2010d; Dvoretsky 2011). New data may help us to better understandthe structure and functioning of mesozooplankton assemblages across these areas.

In addition, plankton is often considered to be an indicator of climatic impact(Dalpadado et al. 2003; Brierley and Kingsford 2009). Because of their short life spansand high rates of growth, zooplankton communities respond rapidly to warming orcooling processes in the sea (Richardson 2008). Russian scientists use values of thetemperature anomaly in the Kola section (69◦–74◦ N, 33◦30′ E) as indicators of cli-matic changes in the Barents Sea (Matishov et al. 2012). Based on recent observations,the period 2000–2008 was characterized by positive temperature anomalies in this sec-tion for the upper 200 m. However, some degree of cooling has been noted since 2007(Matishov et al. 2012), and the temperature anomalies recorded in 2009 were similarin magnitude to multi-year values.

The aims of the present study were (1) to describe mesozooplankton communitystructure in the southern, western, and northern Barents Sea and adjacent areas inrelation to different water masses, and (2) to compare our data with previous inves-tigations to detect possible impacts of temperature change on the abundance andbiomass.

Material and methods

Water samples for zooplankton analysis were collected at 29 stations during a cruisein the Barents Sea and surrounding areas in August 2009 (Table 1, Figure 1) onboardR/V Dalnie Zelentsy (MMBI). Vertical hauls (100–0 m or bottom–0 m) were per-formed with a Juday net (mesh size 168 µm, mouth opening 0.11 m2). The sampleswere preserved in 4% formalin immediately after collection. In the laboratory, twoor three subsamples containing 200–500 individuals were taken from each sam-ple with a pipette to analyse mesozooplankton species (<3–5 mm); larger animals(>5 mm) were sorted from the entire sample volume. Organisms were identified,measured and counted under an MBS-10 stereomicroscope equipped with an ocularmicrometer according to standard techniques (e.g. Dvoretsky and Dvoretsky 2009a,2009b, 2010a, 2010c). Abundance data were expressed as individuals per cubic metre(ind. m−3). On average, 20–50 individuals of each species were measured from asample.

Copepods of the genus Calanus were distinguished on the basis of their morphol-ogy and data on the prosome lengths of individual copepodite stages (Kwasniewskiet al. 2003; Weydmann and Kwasniewski 2008). We calculated the biomass by com-bining our abundance data with estimates of individual masses (wet, dry or carbon)based on published sources, length–mass equations or nomograms (Chislenko 1968;Richter 1994; Blachowiak-Samolyk et al. 2008b, and references therein). All valueswere computed as milligrams dry mass (DM) per cubic metre using the relationship:1 mg wet weight = 0.16 mg dry weight = 0.064 mg C (Vinogradov and Shushkina1987). In our study we used a rather coarse net, which may under-sample the smalltaxa (Nielsen and Andersen 2002). Therefore, real values of the total mesozooplank-ton abundance and biomass would be higher than those reported below. All the meansare given as values ± standard error.

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Table 1. List of sampling stations with information on the date, sampling time, depth, samplinglayer, averaged water temperature (Temp, ◦C) and salinity (Sal) in the sampling layer, dominat-ing type of water mass, mesozooplankton biodiversity (Shannon index H′) and evenness (E) inthe Barents Sea and adjacent waters in August 2009.

No. Date(Aug 2009)

Localtime

Depth Layer Temp Sal Water H′ E

4 01 14:19 293 100–0 7.6 ± 0.1 34.77 ± 0.02 MCW 1.31 0.497 01 22:48 287 100–0 7.4 ± 0.1 34.79 ± 0.01 MCW 1.54 0.5179 16 10:35 260 100–0 6.0 ± 0.1 34.84 ± 0.01 MCW 1.98 0.6185 17 07:25 151 100–0 7.2 ± 0.1 34.51 ± 0.02 MCW 1.49 0.5686 19 08:40 261 100–0 7.1 ± 0.1 34.30 ± 0.03 MCW 1.51 0.4917 03 06:16 69 60–0 2.2 ± 0.0 34.22 ± 0.00 BW 2.05 0.6611 02 12:58 441 100–0 6.2 ± 0.1 35.07 ± 0.00 AW 1.28 0.3814 02 23:41 455 100–0 5.6 ± 0.2 34.97 ± 0.01 AW 1.95 0.6327 04 21:48 145 100–0 5.5 ± 0.1 34.87 ± 0.02 AW 1.84 0.5929 05 11:07 186 100–0 5.9 ± 0.1 34.92 ± 0.03 AW 1.86 0.6270 13 14:03 309 100–0 3.7 ± 0.1 34.96 ± 0.01 AW 1.73 0.5372 13 22:44 143 100–0 2.4 ± 0.1 34.91 ± 0.01 AW 2.01 0.6576 15 23:53 211 100–0 4.9 ± 0.1 34.99 ± 0.00 AW 1.96 0.6221 03 21:21 135 100–0 4.0 ± 0.1 34.84 ± 0.01 AWF 2.05 0.6523 04 04:17 322 100–0 4.9 ± 0.0 34.8 ± 0.02 AWF 1.95 0.6125 04 12:27 41 35–0 1.0 ± 0.2 33.55 ± 0.06 SCW 2.14 0.6926 04 16:35 60 50–0 3.1 ± 0.1 33.71 ± 0.06 SCW 1.41 0.4432 05 17:33 268 100–0 3.1 ± 0.1 33.87 ± 0.06 SCW 1.98 0.6235 07 03:08 249 100–0 2.5 ± 0.2 34.23 ± 0.06 SCW 2.13 0.6944 08 03:42 81 70–0 1.3 ± 0.1 34.03 ± 0.05 ArW 1.63 0.5747 08 18:52 309 100–0 −0.8 ± 0.1 34.02 ± 0.05 ArW 1.41 0.4850 09 06:36 154 100–0 −0.4 ± 0.2 34.29 ± 0.03 ArW 1.76 0.6053 09 18:41 386 100–0 0.5 ± 0.1 34.43 ± 0.02 ArW 1.71 0.5956 10 02:28 311 100–0 0.6 ± 0.1 34.37 ± 0.03 ArW 1.81 0.6358 10 10:50 54 48–0 0.6 ± 0.1 33.94 ± 0.02 ArW 1.82 0.5860 10 19:15 31 25–0 −0.4 ± 0.0 34.21 ± 0.01 ArW 1.65 0.5762 11 01:08 394 100–0 −0.7 ± 0.1 34.45 ± 0.02 ArW 2.00 0.6266 12 21:52 186 100–0 −0.5 ± 0.2 34.36 ± 0.03 ArW 1.85 0.6868 13 05:52 161 100–0 0.0 ± 0.2 34.45 ± 0.03 ArW 1.49 0.51

Notes: MCW, Murmansk coastal waters; AW, Atlantic waters; AWF, Atlantic waters (frontalzone); SCW, Svalbard coastal waters; ArW, Arctic waters; BW, Bear Island waters.

Stations were referred to different water masses based on data from the literatureand on vertical profiles of temperature and salinity, which were recorded at each sam-pling location with an SBE 19 plus SEACAT CTD. General properties of the mainwater masses are summarized in Table 2 (for boundaries of water masses see alsoFigure 1).

Multivariate analysis of the mesozooplankton was performed using PRIMER5.0 software (Clarke and Warwick 1994). Abundance data (ind. m−3) were square-roottransformed. Cluster analysis based on the Bray–Curtis similarity index (group aver-age linkage) was applied to test similarities in the mesozooplankton community amongstations. Analysis of similarities (ANOSIM) based on Bray–Curtis similarity matrices

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2098 V.G. Dvoretsky and A.G. Dvoretsky

Figure 1. Barents Sea and adjacent waters. Location of sampling stations in 2009 and generalscheme of main water masses (Ozhigin and Ivshin 1999): MCW, Murmansk coastal waters; AW,Atlantic waters; SCW, Svalbard coastal waters; ArW,– Arctic waters; BW, Bear Island waters;NCW, Norwegian coastal waters; TAW, Transformed Atlantic waters (Barents Sea waters);WCW, White Sea coastal waters; PCW, Pechora coastal waters; NZCW, Novaya Zemlya coastalwater.

of mesozooplankton abundance was used to test for differences between water masses(Bray and Curtis 1957; Clarke and Gorley 2001). ANOSIM uses the test statistic R,which is calculated from average rank similarities among pairs of samples within eachof the groups minus average rank similarity of samples between groups. R values canvary from – 1 to 1. The higher the R value the larger the difference between groups.Negative values show that difference within groups is larger than that between groups(Clarke and Warwick 1994). We used the SIMPER procedure to reveal the contribu-tion (in %) of each mesozooplankton taxon to the total similarity within the differentwater masses. The BIOENV test based on Spearman rank correlations between Bray–Curtis similarity matrices of mesozooplankton abundances and Euclidean distancesof environmental factors (time of sampling, latitude, longitude, depth of station, sam-pling layer, averaged temperature and salinity in the sampling layer) was applied toestimate the influence of these abiotic factors on the mesozooplankton community

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Journal of Natural History 2099

Table 2. Oceanographic characteristics of water masses in the Barents Sea (Ozhigin and Ivshin1999; Hop et al. 2006) within the study area.

Water mass Stratum (m) Temperature Salinity

MCW 0 8.0–10.0 33.50–34.5550 5.5–6.5 34.35–34.55

100 4.0–4.5 34.45–34.55AW 0 nd nd

50 3.0–5.0 34.95–34.98100 2.0–4.0 34.95–35.01

BW 0 2.5–3.5 34.00–34.8050 1.5–3.5 34.15–34.80

100 1.0–2.5 34.15–34.80SCW (Surface Water) 0 Variable 28.00–34.40SCW (Intermediate Water) 50 Variable 33.00–34.70SCW (Transformed Atlantic Water) 100 >1.0 >34.70ArW 0 2.0–5.0 33.00–34.50

50 −0.5 to +1.5 34.50–34.75100 −0.5 to +1.0 34.70–34.75

Notes: MCW, Murmansk coastal waters; AW, Atlantic waters; SCW, Svalbard coastal waters;ArW, Arctic waters; BW, Bear Island waters; nd, not detected.

structure (Clarke and Gorley 2001). The Shannon diversity index (H′) was appliedto mesozooplankton for the estimation of community diversity (Shannon 1948): H =−�pilog2pi, where pi is the proportion of the total number of specimens i expressed as aproportion of the total number of species for all species in the sample. The species even-ness index (E) was calculated according to the formula of Pielou (1977): E = H/log2S,where S is the total number of species in the sample.

Results

Vertical profiles of water temperature and salinity indicated considerable differencesin the upper layer among the five water masses (Figure 2). In general, the maxi-mum temperature was recorded at stations of MCW (Table 3), where it varied from4.6 to 10.7◦C. The minimum temperature (from – 1.7 to 3.5◦C) was found within ArW(Table 3). The highest salinity (up to 35.14) was registered at stations of AW (Table 3).The lowest values (30.87) occurred in Isfjorden (St. 32, 35), where SCW dominatedthe system. There was a distinct pycnocline and thermocline at 15–35 m within AW,BW, SCW and ArW (Figure 2). Stations of MCW and AWF were characterized bya low-temperature sub-surface layer between 50 and 60 m (Figure 2). Figure 3 repre-sents a T-S plot for each water mass. In general, T-S curves corresponded well to theclassification of water masses presented in Table 2.

Altogether, 68 taxa were identified in the water samples (Table 3). Holoplanktonicanimals dominated in terms of the total abundance, accounting for 95.6 ± 3.4%.Cluster analysis indicated that mesozooplankton communities were strongly related tothe different water masses (Figure 4). This result was confirmed by ANOSIM analysis,

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2100 V.G. Dvoretsky and A.G. Dvoretsky

Figure 2. Vertical profiles of temperature and salinity in the upper layer at the five water massesin the Barents Sea and adjacent waters in August 2009.

where the value of the Global R statistic was 0.633 (p = 0.001). Pairwise compar-isons showed that there were significant differences between the mesozooplanktoncommunities of MCW and other water masses (except for BW) as well as for the

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Journal of Natural History 2101

Tab

le3.

Com

posi

tion

,m

ean

(±st

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The

mis

tolib

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la−

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0.1

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The

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2102 V.G. Dvoretsky and A.G. DvoretskyT

able

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7±

0.6

1.8

±1.

8−

<0.

1−

8.57

nsB

ival

via

(juv

.)6.

6±

3.4

68±

15.8

49.8

±29

.3−

17.4

±13

.24.

8±

3.6

15.8

8<

0.05

Bry

ozoa

larv

ae−

0.8

±0.

8−

−−

−n.

a.E

umed

usa

biru

lai

−<

0.1

−−

−<

0.1

0.70

nsC

irri

pedi

ana

uplii

1.6

±1.

6−

−−

3.1

±3.

10.

6±

0.5

0.91

nsD

imop

hyes

arct

ica

−−

−−

−0.

1±

0.1

n.a.

Eup

hysa

flam

mea

−−

−1.

10.

1±

0.1

<0.

14.

35<

0.05

Eup

hysa

spp.

<0.

10.

5±

0.5

−2.

80.

1±

0.1

−3.

72ns

(Con

tinu

ed)

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] at

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Journal of Natural History 2103

Tab

le3.

(Con

tinu

ed).

Hal

itho

lus

cirr

atus

−−

−−

0.1

±0.

1−

n.a.

Asc

idia

larv

ae−

−−

−−

0.8

±0.

6n.

a.A

uric

ular

iala

rvae

−−

−−

0.6

±0.

6−

n.a.

Ant

hozo

ala

rvae

−−

−−

0.1

±0.

1−

n.a.

Ech

inop

lute

us0.

2±

0.2

15.5

±4.

98.

1±

1.2

−3.

1±

1.4

10±

5.7

13.3

5<

0.05

Gas

trop

oda

larv

ae−

0.7

±0.

7−

−1.

2±

1.2

1.6

±1.

10.

69ns

Oph

iopl

uteu

s1

±1

39.8

±10

.133

±14

.4−

6.2

±2.

342

.5±

17.7

12.0

3<

0.05

Poly

chae

tala

rvae

2.6

±1.

68.

9±

5.5

16.3

±9.

8−

2±

1.6

0.8

±0.

65.

41ns

Rat

hkea

octo

punc

tata

6.0

±6.

016

.4±

14.7

−−

−−

2.66

nsS

arsi

asp

p.−

−−

−−

0.1

±0.

1n.

a.T

iaro

psis

mul

tici

rrat

a−

<0.

1−

−−

−n.

a.N

emer

tini

larv

ae−

<0.

1−

−−

−n.

a.B

oroe

cia

bore

alis

−−

−2.

6−

−n.

a.D

isco

conc

hoec

iael

egan

s−

0.9

±0.

90.

7±

0.7

−3.

1±

1.8

−3.

62ns

Tom

opte

ris

helg

olan

dica

−−

−0.

2−

−n.

a.P

isce

sla

rvae

−<

0.1

−−

−−

n.a.

Lim

acin

ahe

licin

a3.

6±

1.1

2±

24.

2±

4.2

−0.

2±

0.1

33.1

±17

.513

.54

<0.

05E

ukro

nia

ham

ata

−−

−−

−0.

1±

0.1

n.a.

Par

asag

itta

eleg

ans

0.2

±0.

14.

1±

1.2

3.8

±0.

64.

311

.2±

7.3

0.9

±0.

318

.03

<0.

001

Thy

ssan

oess

ara

schi

i<

0.1

−−

−−

−n.

a.T

hyss

anoe

ssa

larv

ae0.

6±

0.2

2.2

±2

3.5

±2.

31.

20.

3±

0.3

0.6

±0.

68.

35ns

Tota

l57

2.6

±27

7.7

1893

.5±

307.

327

99.8

±12

9.8

624.

228

48.7

±75

426

43.6

±52

7.5

13.0

3<

0.05

Cop

epod

a52

4.5±

266.

116

32.1

±27

0.8

2403

.7±

278.

459

0.4

2621

.4±

821.

525

13.6

±50

0.5

11.5

2<

0.05

Am

phip

oda

−0.

1±

0.1

−−

0.1

±0.

10.

1±

0.1

3.66

nsA

ppen

dicu

lari

a4.

4±

1.9

79±

29.4

265.

9±

203.

819

.117

4.6

±11

9.2

32.6

±16

14.6

7<

0.05

Cte

noph

ora

2.5

±1.

24

±2

0.9

±0.

91.

10.

4±

0.2

0.9

±0.

52.

64ns

Cla

doce

ra17

.7±

14.3

16.3

±13

.4−

1.1

−−

8.90

<0.

05P

tero

poda

3.6

±1.

12

±2

4.2

±4.

2−

0.2

±0.

133

.1±

17.5

13.5

4<

0.05

Cha

etog

nath

a0.

2±

0.1

4.1

±1.

23.

8±

0.6

4.3

11.2

±7.

31.

0±

0.4

6.83

<0.

05

(Con

tinu

ed)

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] at

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2104 V.G. Dvoretsky and A.G. Dvoretsky

Tab

le3.

(Con

tinu

ed).

Tax

on/P

aram

eter

Wat

erm

ass

Kru

skal

–Wal

liste

st

MC

WA

WA

WF

BW

SCW

ArW

Hp

Eup

hais

iace

a0.

7±

0.2

2.2

±2

3.5

±2.

31.

20.

3±

0.3

0.6

±0.

68.

35ns

Mer

opla

nkto

n+M

edus

ae18

.1±

10.6

151

±35

.211

5.2

±59

.94.

237

.2±

1261

.2±

23.8

11.4

4<

0.05

Oth

ers

1±

0.5

2.6

±1.

12.

5±

2.5

2.8

3.1

±1.

90.

4±

0.1

3.63

nsSh

anno

ndi

vers

ity

inde

x1.

57±

0.11

1.85

±0.

082.

00±

0.05

2.05

1.92

±0.

171.

71±

0.06

8.27

nsSp

ecie

sev

enne

ssin

dex

0.53

±0.

020.

59±

0.03

0.63

±0.

050.

660.

61±

0.06

0.58

±0.

026.

31ns

Oce

anog

raph

icva

riab

les

Tem

pera

ture

,◦ S7.

1±

0.3

4.9

±0.

54.

5±

0.5

2.2

2.4

±0.

50.

0±

0.2

24.8

3<

0.00

1Sa

linit

y34

.64

±0.

134

.96

±0.

0334

.82

±0.

0234

.22

33.8

4±

0.15

34.2

6±

0.06

23.1

0<

0.00

1

Not

e:ns

,no

n-si

gnifi

cant

;n.

a.,

noan

alys

is;

H,

chi-

squa

reva

lues

;p,

prob

abili

tyle

vel;

MC

W,

Mur

man

skco

asta

lw

ater

s;A

W,

Atl

anti

cw

ater

s;A

WF,

Atl

anti

cw

ater

s(f

ront

alzo

ne);

SCW

,Sva

lbar

dco

asta

lwat

ers;

ArW

,Arc

tic

wat

ers;

BW

,Bea

rIs

land

wat

ers.

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Journal of Natural History 2105

Figure 3. Temperature–salinity diagram for all top-to-bottom/100 m CTD data in the BarentsSea and adjacent waters in August 2009.

Figure 4. Cluster dendrogram of sampling station based on the mesozooplankton abundance inthe upper 100-m layer in the Barents Sea and adjacent waters in August 2009. MCW, Murmanskcoastal waters; AW, Atlantic waters; SCW, Svalbard coastal waters; ArW, Arctic waters.

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Table 4. Results of ANOSIM test showing differences of zooplankton communities betweenfive water masses.

Water mass MCW AW AWF BW SCW ArW

MCW ∗ 0.688 0.727 0.56 0.863 0.946AW ∗ 0.11 0.81 0.294 0.771AWF ∗ 1 0.036 0.483BW ∗ 1 0.876SCW ∗ 0.607ArW ∗

Note: MCW, Murmansk coastal waters; AW, Atlantic waters; AWF, Atlantic waters (frontalzone); SCW, Svalbard coastal waters; ArW, Arctic waters; BW, Bear Island waters in the BarentsSea and adjacent waters in August 2009.Bold font indicates significant differences (p < 0.05).

assemblage pairs of AW–ArW, ArW–AWF and ArW–SCW (Table 4). The similarityof the assemblage in BW to those of other water masses may be an artefact resultingfrom the fact that only one station was located in BW waters. Because of the differ-ences in the communities, we consider the composition, abundance and biomass of theplankton assemblages separately for each of the water masses recorded in our study.

A total of 35 taxa were registered in MCW (Table 3). Mesozooplankton abundanceranged between stations from 143 to 1593 ind. m−3. Copepods dominated the commu-nity, accounting for 80.2–96.4% of the individuals, with Oithona similis (49.5 ± 5.6%),Calanus finmarchicus (14.3 ± 3.1%) and Oithona atlantica (11.6 ± 3.9%) as the mostprevalent (Table 3). Total mesozooplankton biomass varied from 3 to 15 mg DM m−3.The lowest mean value of mesozooplankton biomass among all water masses studiedwas in MCW (Figure 5a). Calanus finmarchicus comprised 62.1 ± 11.3% of the totalmesozooplankton biomass.

AW, including AWF, was the richest region in terms of mesozooplankton taxa(45 species and higher groups, see Table 3). Minimum total abundance in AWwas found at station 72 (525 ind. m−3); a maximum was recorded at station 11(3084 ind. m−3). Two stations of AWF also had high zooplankton abundances(2670–2930 ind. m−3). The average abundances in the waters of Atlantic origin were3.3–4.9 times higher than those of MCW (Table 3). Mesozooplankton biomass ofAW was also higher, ranging from 3 to 142 mg DM m−3. AWF was characterizedby a very large mesozooplankton stock with the biomass varying between 345 and377 mg DM m−3 (Figure 5a). Oithona similis and C. finmarchicus were the main repre-sentatives of AW, with an average relative abundance of 44.6 ± 6.5% and 14.3 ± 5.8%,respectively (Table 3). In AWF, Calanus glacialis (27.4 ± 11.4%) and C. finmarchicus(18.8 ± 15.3%) dominated the community in terms of the total abundance (Table 3).These two Calanus species were the most important contributors to the total meso-zooplankton biomass in both types of water mass, with C. finmarchicus (44.6 ± 7.0%)prevailing at AW stations and C. glacialis (67.2 ± 23.0%) dominating within the AWF.The mean mesozooplankton biomass of AWF was the highest among all water masses(Figure 5a).

One station (station 17) was occupied by BW. There, 21 taxa were found (Table 3).Total mesozooplankton abundance was similar to the mean value of MCW, whereas

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Journal of Natural History 2107

Figure 5. Mesozooplankton biomass (a: mg dry mass m−3 ± standard error; b: g dry massm−2 ± standard error) within different water masses in the upper 100-m layer in the BarentsSea and adjacent waters in August 2009. MCW, Murmansk coastal waters; AW, Atlantic waters;AWF, Atlantic waters (frontal zone); BW, Bear Island waters; SCW, Svalbard coastal waters;ArW, Arctic waters.

the biomass was higher (Table 3). Copepods of the genus Pseudocalanus (54.6%),O. similis (19.7%), C. finmarchicus (7.7%) and C. glacialis (7.4%) dominated the meso-zooplankton in terms of abundance (Table 3). The total mesozooplankton biomasswas 1.3 times lower than in AW (Figure 5a). It was composed primarily of C. glacialis(54.3%), C. finmarchicus (15.6%) and Parasagitta elegans (10.7%) (Table 3).

In all, 35 taxa were identified in the samples from SCW (Table 3). The lowest abun-dance was registered at station 25 (1927 ind. m−2) located near the southern Svalbardcoast whereas the maximum was at neighbouring station 26 (5099 ind. m−2). The mostcommon taxa were C. finmarchicus (29.1 ± 10.9%), O. similis (23.5 ± 5.0%), C. glacialis(11.6 ± 3.3%) and Pseudocalanus (12.4 ± 2.7%) (Table 3). The total biomass rangedfrom 133 to 456 mg DM m−3. The mean value was 5.6–30.4 times higher than that

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of the water masses considered above (Figure 5a). Two Calanus species, C. finmarchi-cus and C. glacialis, comprised 88.7 ± 21.1% of the total mesozooplankton biomass(Table 3).

The taxonomic richness of ArW was the same (34 species and higher groups) asthat of MCW and SCW. Total mesozooplankton abundance increased strongly fromstation 50 (1210 ind. m−3) to a maximum abundance at station 60 (6145 ind. m−3).Oithona similis (28.7 ± 3.5%) dominated along with C. glacialis (25.2 ± 3.3%) andcopepod nauplii (20.4 ± 4.5%) (Table 3). The mean mesozooplankton biomass wasthe higher than in other water masses excepting AWF (Figure 5a) ranging from 88 to1112 mg DM m−3. Three species of the genus Calanus comprised 94.3 ± 10.7% in thetotal biomass.

Mesozooplankton diversity (H′) was generally low (1.77 ± 0.05). The minimumvalue was found at station 11, mainly because of the high numerical abundance of thesmall copepods belonging to the genus Oithona. The maximum value was registeredat station 25 within SCW (Table 1). AWF had the highest zooplankton biodiver-sity among all the water masses (Table 3). The average species evenness index for allstations was intermediate between 0 and 1 (0.58 ± 0.01).

There were no significant differences between day and night samples (Kruskal–Wallis test, p > 0.05) in the zooplankton abundance and composition for each type ofwater mass that indicated similar vertical distributions in day and night.

SIMPER (similarity percentage) analysis showed that the species compositionwithin all water masses was clearly affected by the abundance of certain copepods(Table 5). Oithona and C. finmarchicus contributed the most to the similarities withinMCW and AW (Table 5). Abundances of O. similis, Calanus and Pseudocalanus wereimportant structuring factors of the mesozooplankton community at stations of SCW,AWF and ArW (Table 5).

Table 5. Results of the SIMPER analysis on mesozooplankton abundances: contributions ofmain taxa (%) to similarities within different water masses in the Barents Sea and adjacentwaters in August 2009.

Taxa Water Mass AWF SCW ArW BWMCW AW

Oithona similis 65.31 53.08 29.46 26.74 30.28 n.a.Calanus finmarchicus 12.18 11.74 5.86 25.11 3.69 n.a.Calanus glacialis − 0.62 28.97 17.00 26.96 n.a.Copepoda nauplii 2.62 4.49 9.21 5.32 21.58 n.a.Oithona atlantica 12.29 5.74 0.41 0.55 − n.a.Pseudocalanus spp. 1.93 7.85 15.54 10.93 12.86 n.a.Bivalvia (juv.) 0.77 4.96 1.27 0.19 0.02 n.a.Pseudocalanus minutus 0.39 2.55 0.52 2.76 2.52 n.a.Microcalanus pygmaeus 0.14 0.39 1.21 2.85 0.05 n.a.Fritillaria borealis 0.07 1.73 2.42 1.82 0.07 n.a.Average similarity, % 42.42 47.71 57.73 50.83 65.55 n.a.

Note: MCW, Murmansk coastal waters; AW, Atlantic waters; AWF, Atlantic waters (frontalzone); SCW, Svalbard coastal waters; ArW, Arctic waters; BW, Bear Island waters; n.a., noanalysis.

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Journal of Natural History 2109

Table 6. Coefficients of Spearman rank correlation between abiotic and biotic factors and com-munity abundance structure in the Barents Sea and adjacent waters in August 2009 from theBIOENV analysis.

Number of factors Factors Spearman rank correlation

1 Latitude 0.6202 Latitude, Temperature 0.5953 Latitude, Temperature, Salinity 0.5492 Latitude, Salinity 0.5183 Latitude, Layer, Temperature 0.5103 Latitude, Longitude, Temperature 0.4964 Latitude, Longitude, Temperature, Salinity 0.4813 Latitude, Depth, Temperature 0.4781 Temperature 0.4714 Latitude, Layer, Temperature, Salinity 0.471

The abundance composition of the mesozooplankton was influenced primar-ily by latitude as revealed by BIOENV analysis (Table 6). Other important factorswere hydrographical conditions (averaged temperature and salinity) (Table 6). Timeof sampling, depth of station and sampling layer seemed not to strongly affect themesozooplankton communities.

Discussion

The temperature regime of the Barents Sea is strongly dependent on the balancebetween the inflows of warm Atlantic waters and cold Arctic waters (Loeng andDrinkwater 2007; Sakshaug et al. 2009). Multi-year observations of MMBI allowedthe creation of an oceanographic database (Matishov et al. 2004) that can be used todetermine the climatic conditions for a particular year. Using this database we com-pared our values of averaged water temperature (Table 3) with the summer mean valuesfor the different water masses and found that they were similar to each other. Thissuggests that the year of 2009 should be considered to be a temperate or moderateyear.

The zooplankton fauna of the Barents Sea is one the most diverse in the Arcticregion (Dvoretsky and Dvoretsky 2010d); this diversity is connected with the vari-ety of environmental conditions and habitats found there. The present study supportsthis statement – we identified more than 60 taxa in our samples. At the same time,Shannon’s diversity index was low; it was, however, comparable to previous estimates(e.g. Dvoretsky et al. 2009a). A low value of the diversity index is expected because theArctic zooplankton assemblages are dominated by a few common taxa. Copepods ofthe genus Calanus are the main large copepods in the Arctic seas, with Oithona andPseudocalanus being dominant among the small copepods (Kwasniewski et al. 2003;Lischka and Hagen 2005; Dvoretsky et al. 2009c). In our study we found that the com-position of the dominant mesozooplankton taxa was similar in the different waters.Moreover, these taxa contributed the most to the similarities within correspondingwater masses, as indicated by the SIMPER analysis. At the same time, the ANOSIM

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2110 V.G. Dvoretsky and A.G. Dvoretsky

test indicated that mesozooplankton assemblages were significantly different in termsof their total abundance and biomass. This result is in accordance with previousreports by Daase and Eiane (2007), who demonstrated that zooplankton communitystructure in northern Svalbard waters was primarily influenced by variations in speciesabundance rather than by variations in taxonomic composition.

Many investigations have shown that oceanic mesozooplankton communities arestrongly associated with different water masses, especially in the Arctic and subarcticshelf regions (e.g. Timofeev 2000; Hop et al. 2006; Daase and Eiane 2007; Dvoretskyet al. 2009b, 2009c; Walkusz et al. 2010). We also found a close coupling between meso-zooplankton and the distribution of water masses. Moreover, the BIOENV analysissupports this statement because latitude and oceanographic conditions were the mostimportant factors structuring the mesozooplankton community. In addition, somespecies can be used as indicators of some waters. For example, the presence of theboreal copepod species C. finmarchicus in the northern Barents Sea may be connectedwith strong inflow of waters of Atlantic origin (Falk-Petersen et al. 2007). In contrast,coastal sites of the southern Barents Sea are characterized by the occurrence of neritictaxa. In our case we registered several neritic species (Acartia longiremis, Eurytemoraaffinis, Temora longicornis, Evadne nordmanni and Podon leuckartii) within MCW.However, these taxa were also identified in samples from AW. This could be explainedby transport of the coastal mesozooplankton into the open sea by the North Capecurrent. Arctic coastal sites (SCW and partly ArW) were characterized by a high pro-portion of C. glacialis and Pseudocalanus species, similar to observations conducted inthe Greenland and Barents seas (Lischka and Hagen 2005; Hop et al. 2006; Dvoretskyet al. 2010c, 2011).

Another important factor affecting mesozooplankton composition as well as com-munity structure is the phase of the planktonic succession cycle (Raymont 1983). TheBarents Sea is located between 67◦ and 81◦N and the timings of the beginning of thebiological seasons and their duration differ considerably between the southern andnorthern regions (Sakshaug et al. 2009). There are intensive phytoplankton bloomsand development of the mesozooplankton during the spring period. During this timethe community is dominated by herbivorous animals, which comprise a significantproportion of the total plankton number (Timofeev 2000; Søreide et al. 2010). Thepost-bloom period in the Barents Sea may be referred to as the biological summerwhen pre-adult (e.g. copepodites III–IV) and adult stages are prevalent (Timofeev2000). Our data suggest that the mesozooplankton community of ArW at the timeof collection may be considered to be a spring assemblage because of the high abun-dance of copepod nauplii, whereas the mesozooplankton communities of the otherwater masses were already in the summer phase of the seasonal succession cycle.

Mesozooplankton abundance varies strongly in the Barents Sea and other Arcticregions (Hop et al. 2006; Wassmann et al. 2006; Daase and Eiane 2007; Walkuszet al. 2010). We also found that the total abundance differed between stations by afactor of 24.5. For this reason, many investigators use mesozooplankton biomass asthe main descriptor of the community and its stock. Shelf zones of the Arctic Ocean(e.g. Svalbard waters, central and northern Barents Sea) are characterized by high totalmesozooplankton biomass, which can vary from 1.0 to 46.7 g DM m−2 for the entirewater column in the summer period (e.g. Arashkevich et al. 2002; Hop et al. 2006;Blachowiak-Samolyk et al. 2008b). In the eastern Arctic, outside the shelf break,this value ranged from 1.9 to 23.9 g DM m−2 with a mean of 6.2 ± 4.1 g DM m−2

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Journal of Natural History 2111

(Kosobokova and Hirche 2009). Our values for all water masses are similar to theseestimates (see Figure 5b). However, it should be remembered that we sampled theupper 100 m of the water column only. Therefore, it is likely that we undersampledthe large carnivorous copepods, which are deepwater organisms, and some herbivo-rous copepods (e.g. Calanus), which tend to be found below 100 m at the beginningof their diapause in July–August. As a result, the total biomass for the entire columnwould be higher than indicated by the present study. Some authors have noted thatshelf waters of different origin (Atlantic or Arctic) have similarly high zooplanktonbiomasses, whereas in deepwater regions the total biomass of AW is typically higherthan at ArW stations (Richter 1994; Daase and Eiane 2007; Blachowiak-Samolyk et al.2008b). Hence, only the shelf zones should be considered the main productive areas ofthe Arctic Ocean.

The Polar Front is the main frontal zone of the Barents Sea where warm Atlanticwaters mix with cold Arctic waters (Loeng and Drinkwater 2007). Interaction of Westand East Svalbard Currents (WSC and ECS) produce another frontal zone locatedsouth of the Svalbard archipelago (Ozhigin and Ivshin 1999). In this work, large aggre-gations of the mesozooplankton were registered in this frontal zone. Here, almostthe entire mesozooplankton biomass was composed of the Arctic species C. glacialis,which was transported into the region with the cold waters of the ESC. The borealspecies C. finmarchicus, advected with the warm water of the WSC also had a signif-icant share in the mesozooplankton community. Some previous investigations haveshown that there exist abundant and rich pelagic communities within frontal zonesof the Barents Sea (Timofeev 2000; Wassmann et al. 2006). In such regions, the aver-age annual planktonic primary production may reach 120–160 gC m−2 yr−1 (Sakshaug2004; Wassmann et al. 2006), which in turn leads to enhanced zooplankton produc-tion. Other water masses of the Barents Sea and adjacent areas, with the exceptionof the ArW, had lower biomass. We suggest that this is connected mainly with theirsuccessional phases as noted above.

Interannual fluctuations of the zooplankton standing stock are well documentedin the Barents Sea and adjacent waters (e.g. Zelikman and Kamshilov 1960; Timofeev2000; Dalpadado et al. 2003; Hop et al. 2006). However, the significance of differentfactors (climatic changes, inflow of Atlantic waters, local environmental conditions,predation by fish and carnivorous zooplankton etc.) determining year-to-year vari-ability of the mesozooplankton communities is not clear. It is possible that differentfactors affect variations of the total biomass within different water masses.

We compared the mesozooplankton biomass in 2009 with our previous results,obtained in 2006–2008 (Table 7). All these data are based on samples collected withthe same technique. Furthermore, mesozooplankton identification, analysis and cal-culations were carried out according to the same methods. A clear decrease in thetotal mesozooplankton biomass was detected only for MCW (Table 7), which couldbe associated with a drop in the temperature anomaly in the Kola Section (Matishovet al. 2012). However, there was no relationship between these anomalies and the totalmesozooplankton biomass in AW and ArW (Table 7). According to Timofeev (2001)averaged zooplankton biomass should be strongly correlated with the mean watertemperature in the coastal waters of the southern Barents Sea. However, we did notobserve any relationship between mesozooplankton community and temperature con-ditions within AW. We think that this lack of a regular pattern may be explained bythe global water circulation in the Barents Sea and adjacent waters. The value of the

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Table 7. Interannual variations of the average (± standard error) total dry mesozooplanktonbiomass (mg DM m−3) in July–August in the upper 100-m layer in different water masses of theBarents Sea.

Year Water mass ArW Reference

MCW AW

2006 51 ± 29∗ 18 ± 3∗ 181 ± 42∗ Dvoretsky and Dvoretsky (2010b)2007 41 ± 22∗ 15 ± 12∗ 119 ± 17∗ Dvoretsky and Dvoretsky (2010c)2008 50 ± 17∗ 17 ± 9∗ nd Dvoretsky and Dvoretsky (2010a)

and our unpublished data2009 8 ± 2 45 ± 17 270 ± 99 This study

Note: ∗Recalculated from original data. nd, no data; MCW, Murmansk coastal waters; AW,Atlantic waters; ArW, Arctic waters.

total zooplankton biomass within AW strongly depends on advection of C. finmarchi-cus from the Norwegian Sea (Wassmann et al. 2006; Falk-Petersen et al. 2007). Thisprocess does not appear to be closely related to mean water temperature; it is, how-ever, associated with the North Atlantic Oscillation (Timofeev 2001; Sakshaug et al.2009; Hurrell and Deser 2010). In our opinion, mesozooplankton biomass variationsin ArW may be more strongly connected with the potential food stock (phytoplanktonbiomass) than with the mean water temperature. The latter factor, however, could stillhave direct effects on the pelagic community. For example, higher temperatures maylead to earlier melting of the ice, which can, in turn, result in an earlier peak in meso-zooplankton biomass and a higher annual stock of secondary producers (Leu et al.2011).

In summary, our data provide further evidence for the strong influence of watermasses in the Barents Sea and adjacent regions of the Arctic Ocean. The spatial distri-bution and state of the mesozooplankton communities were strongly connected withlatitude and hydrological conditions. A possible impact of the recent cooling registeredin the Barents Sea since 2007 was detected as a decrease in the total mesozooplanktonbiomass within MCW in the summer of 2009.

Acknowledgements

We thank our colleagues from MMBI for help with sampling. Dr Denis V. Moiseev and MrMikhail S. Gromov kindly provided us with hydrological data. We are very grateful to Dr JamesA. Nienow (Vladosta State University, USA) for the English revision. We thank two anonymousreviewers for helpful comments on the manuscript.

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