ARTICLE IN PRESS
Deep-Sea Research I 54 (2007) 109–129
www.elsevier.com/locate/dsr
Spatial and temporal variations in deep-sea meiofauna
assemblages in the Marginal Ice Zone of the Arctic Ocean
Eveline Hostea,, Sandra Vanhovea, Ingo Scheweb,
Thomas Soltwedelb, Ann Vanreusela
a
Marine Biology Section, University of Gent, Krijgslaan 281-S8, B-9000 Gent, Belgium
Alfred Wegener Institute for Polar and Marine Research, Am Handelshafen 12, 27570 Bremerhaven, Germany
b
Received 12 January 2006; received in revised form 13 September 2006; accepted 19 September 2006
Available online 16 November 2006
Abstract
In order to understand the response of the deep-sea meiobenthos to a highly varying, ice-edge-related input of phytodetritus,
we investigated the abundance and composition of the meiobenthos at the arctic long-term deep-sea station HAUSGARTEN
(791N, 41E) along a bathymetric transect (1200–5500 m water depth) over 5 consecutive years (from 2000 to 2004) in relation
to changes in environmental conditions. Results showed high sediment-bound pigment concentrations (chlorophyll a and
degradation products) ranging from 4.5 to 41.6 mg/cm3, and coinciding high meiobenthic densities ranging from 14973 to
34097525 ind/10 cm2. Nematodes dominated the metazoan meiofaunal communities at every depth and time (85–99% of total
meiofauna abundance), followed by harpacticoid copepods (0–4.6% of total meiofauna abundance). The expected pattern of
gradually decreasing meiobenthic densities with increasing water depth was not confirmed. Instead, the bathymetric transect
could be subdivided into a shallow area with equally high nematode and copepod densities from 1000 to 2000 m water depth
(means: 22597157 Nematoda/10 cm2, and 5074 Copepoda/10 cm2), and a deeper area from 3000 to 5500 m water depth with
similar low nematode and copepod densities (means: 595752 Nematoda/10 cm2, and 1172 Copepoda/10 cm2). Depth-related
investigations on the meiobenthos at the HAUSGARTEN site showed a significant correlation between meiobenthos
densities, microbial exo-enzymatic activity (esterase turnover) and phytodetrital food availability (chlorophyll a and
phaeophytines). In time-series investigations, our data showed inter-annual variations in meiofauna abundance. However, no
consistent relationship between nematode and copepod densities, and measures for organic matter input were found.
r 2006 Elsevier Ltd. All rights reserved.
Keywords: Arctic; Greenland Sea; Deep water; Benthos; Meiofauna; Abundances
1. Introduction
Polar oceans are extreme environments with low
temperature and seasonal light and food limitation,
which exert major influences on global climate and
ocean systems. The Marginal Ice Zones (MIZs),
Corresponding author. Tel.: +32 09264 85 23.
E-mail address: [email protected] (E. Hoste).
0967-0637/$ - see front matter r 2006 Elsevier Ltd. All rights reserved.
doi:10.1016/j.dsr.2006.09.007
however, are some of the most dynamic areas in the
world’s oceans with large seasonal, inter-annual and
spatial fluctuations in ice-cover and high ice-related
primary production (Falk-Petersen et al., 2000).
This variability is a critical factor, which structures
the arctic marine ecosystem.
The spring phytoplankton bloom follows the
receding ice edge as it melts (Sakshaug and Skjoldal,
1989) and intensive blooms occur in leads as the
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E. Hoste et al. / Deep-Sea Research I 54 (2007) 109–129
MIZ opens up (Schewe and Soltwedel, 2003). The
development of such blooms requires 2–3 weeks of
open water, a relatively stable ice cover during
winter, and stratification of the water column
(Falk-Petersen et al., 2000; Engelsen et al., 2002).
One to 2 months prior to the pelagic production, ice
algal production is initiated (Falk-Petersen et al.,
2000). In ice-free areas of the MIZ to the northwest of Svalbard, primary production rates of
18–20 mg cm2 h1 were measured, while at the
ice-edge, production rates even increased up to
37 mg cm2 h1 (Heimdal, 1983).
Several studies in the deep sea indicated a rapid
downward transport of fresh phytodetritus and
fecal pellets (Billett et al., 1983; Graf, 1989) and
possibly a rapid processing of this material by the
deep-sea benthos, which is sustained by this organic
matter from the euphotic zone (Moodley et al.,
2002; Witte et al., 2003). The flux of organic matter
to the deep seafloor, however, is highly variable in
time and space. At high latitudes, inter-annual
variations in ice coverage determine the start and
intensity of the phytoplankton bloom (Sakshaug
and Skjoldal, 1989). As the presence and persistence
of life at the ocean floor can be seen as a response to
organic matter input (Thiel, 1975; Gooday and
Turley, 1990; Grebmeier and Barry, 1991; Gooday,
2002), the variability in organic matter fluxes to the
seafloor is bound to have an influence on the
benthos.
To investigate the impact of large-scale environmental changes in the transition zone between the
North Atlantic and the central Arctic Ocean, and to
determine the factors controlling deep-sea biodiversity, the German Alfred Wegener Institute for Polar
and Marine Research (AWI) established the deepsea, long-term observatory HAUSGARTEN, representing the first, and by now only, open-ocean,
long-term station in a polar region (Soltwedel et al.,
2005). In this part of the HAUSGARTEN research
project, the emphasis is on the impact of changing
environmental variables on the metazoan meiobenthos.
Food quality and quantity reaching the deepseafloor decreases with increasing water depth
(Billett et al., 1983; Falk-Petersen et al., 2000;
Engelsen et al., 2002; Schewe and Soltwedel, 2003).
As food availability is thought to be the most
important structuring factor for meiobenthos communities, the unique combination of a time series
along a bathymetric transect at the summer MIZ
allows us to analyze the impact of changing
environmental variables on meiobenthos densities
in time and with water depth.
This study addresses the following questions. Are
deep-sea meiofauna densities along the productive
MIZ higher than in other polar deep-sea regions?
Do meiofauna densities and vertical depth profiles
in the sediment change along a bathymetric
transect? Do meiofauna densities and vertical depth
profiles change over time? Are these changes
correlated with organic matter input or other
environmental variables? Are influences of timerelated changes in environmental variables on
meiofauna densities comparable to influences of
depth-related changes in environmental variables?
The goal of this study was to gain a better
understanding of the relation between benthos and
environmental variables possibly related to ice
conditions.
2. Material and methods
2.1. Sampling site
The long-term deep-sea observatory HAUSGARTEN is situated in Fram Strait, west of
Svalbard at 79 1N (Soltwedel et al., 2005). The
majority of the sampling sites in this area form a
bathymetric transect of nine stations from the upper
slope of the Svalbard Margin (1200 m) to Molloy
Hole (75500 m), the deepest depression recorded in
the Arctic Ocean (Myhre and Thiede, 1995) (Fig. 1).
The sampling sites between 1200 and 2500 m water
depth are located on a gentle slope while stations
between 3000 and 5000 m are located on a steep
slope (up to 401 inclination between 4000 and
5000 m) towards Molloy Hole (Fig. 1) (Soltwedel
et al., 2005).
Hydrographic conditions in the HAUSGARTEN
area are characterized by the inflow of relatively
warm and nutrient-rich Atlantic Water into the
central Arctic Ocean (Manley, 1995). Circulation
patterns in the Fram Strait result in a variable seaice cover, with permanent ice-covered areas in the
west, permanent ice-free areas in the southeast, and
seasonally varying conditions in central and northeastern parts, where the HAUSGARTEN area is
located (Soltwedel et al., 2005).
2.2. Sampling strategy
Samples were obtained during cruises ARK-XVI
to ARK-XX of the German ice-breaker R.V.
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111
Fig. 1. Map of the Greenland Sea with Sea minimum (2004) and maximum (2003). Ice concentration in Juli (http://nsidc.org/sotc/
sea_ice.html), a detail of the sampling transect and detail of the bathymetric transect.
Polarstern, in the summer months of 2000–04. A
multiple-corer (MUC) was used to collect sediment
cores with virtually undisturbed surfaces (Gage and
Tyler, 1991). For meiofaunal analysis, 3 samples
from different cores of the same MUC haul were
taken by means of a modified plastic syringe
(3.14 cm2 cross-sectional area) and subdivided into
1 cm slices down to 5 cm sediment depth in order to
study the vertical distribution of the meiofauna in
the sediment. After elutriation with the Ludox
centrifugation method (Heip et al., 1985) all
metazoan organisms passing a 1 mm sieve and
retained on a 32 mm sieve were stained with Rose
Bengal, counted and identified up to higher taxon
level. For technical and logistical reasons, meiofauna samples are missing for 2000, 5000 and 5500 in
2001, for 5500 m in 2000 and 2002, and for 5000 m
in the years 2003 and 2004.
Samples for biogenic sediment compounds (indicators for organic matter input, sediment-bound
biomass and microbial activity) were also taken
with modified syringes (1.17 and 3.14 cm2 crosssectional area) and analyzed at 1-cm-intervals down
to 5 cm sediment depth. Sediment composition,
determined using a Coulter Counter LS 100TM,
was only analyzed for the 2001 samples, and are
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E. Hoste et al. / Deep-Sea Research I 54 (2007) 109–129
lacking for 2000 and 5000 m water depth. Also, in
2001, data on organic matter input are lacking for
the station at 4000 m water depth.
Concentrations of chloroplastic pigments (chlorophyll a [Chl a] and its degradation products ¼
chloroplasic pigment equivalents [CPE]; Thiel,
1978) in sediments were studied to estimate the
food availability, originating from plant material, at
the deep seafloor. Chloroplastic pigments were
extracted in 90% acetone and measured with a
Turner fluorometer according to Yentsch and
Menzel (1963) and Holm-Hansen et al. (1965).
The percentage contribution of Chl a to the total
pigment content (%Chl a) is used to indicate the
‘freshness’ of the phytodetrital matter in the
sediments.
Parameters related to organism biomass firstly
include Ash-free Dry Weight (AFDW; estimation of
total organic content) determined after combusting
sediment samples for 2 h at 500 1C. Secondly,
phospholipids (PL, indicating the total microbial
biomass) were determined by the method of Findlay
et al. (1989) which involved conversion of the
phospholipid fatty acids to fatty acid methyl ester
by treatment with 0.2 N KOH in methanol and
analyses by gas chromatography. Finally, particulate proteins (PP, indicating the biomass of small
organisms and detrital matter) were analyzed
photometrically following instructions given by
Greiser and Faubel (1988). As esterases are involved
in primary decomposition of organic matter, the
potential activity of such enzymes was measured
using the fluorogenic substrate Fluorecein-di-acetate (FDA), according to the method described by
Köster et al. (1991).
All statistical analyses were performed on the
original meiofauna densities per 3.6 cm2. Formal
significance tests for differences in taxon community
structure between the depths and years were carried
out using the one-way ANOSIM tests (Clarke,
1993), performed on the Bray–Curtis similarity
indices. The square root transformed meiobenthos
densities data were analyzed by non-metric multidimensional scaling (MDS) using the Bray–Curtis
similarity measure. The relation between the meiobenthos and environmental variables was analyzed
using the Spearman rank correlation (s) and the
significance was determined using a permutation
procedure (RELATE; Clarke and Warwick, 1994).
The BIO-ENV procedure (Clarke and Warwick,
1994) was used to define the environmental variables that best determine the meiobenthos assemblage structures. Finally, a Draftsman plot analysis
was performed to analyze further correlations
between densities and environmental variables
resulting in Pearson correlation coefficients. For
the pairwise ANOSIM tests, R-levels were used
instead of p-levels because the number of permutations was possibly insufficient due to the small
number of samples within the compared groups.
The following R-levels and correlation coefficientlevels were used:40.75, well separated (ANOSIM)
or highly correlated (Draftsman plot); 40.5, overlapping but clearly separated or well correlated and
o0.25, barely separable at all (Clarke and Gorley,
2001) or not correlated at all. For all other analyses
a significance level of po0.05 was used. All analyses
were performed using the PRIMER v5.2.9 software
package (Clarke and Gorley, 2001).
3. Results
2.3. Data analyses
3.1. Environmental variables
The environmental variables along the depth
transect and over the time series were analyzed
using a correlation-based principal component
analysis (PCA). Prior to the PCA the environmental
data were analyzed using a Draftsman plot (Pearson
correlation coefficients; Clarke and Warwick, 1994)
in order to detect correlations between environmental variables and to verify the need for
transformation. Since CPE values were correlated
with Chl a and phaeopigments, they were excluded
from the analysis and other environmental data
were square-root transformed except for depth and
%Chl a, which were log(x+1) transformed (Clarke
and Warwick, 1994).
Silt (2–63 mm) was the dominant grain size
fraction over the bathymetric gradient, ranging
from 43% (2500 m) to 55% (1000 m). The 5500 m
station had the finest sediment and the 2500–4000 m
stations had the coarsest sediment (Fig. 2).
In general, sediment-bound chloroplastic pigments (Chl a, 0–5 cm) decreased with water depth
till 4000 m and increased again at greater depths
(Fig. 3(A)–(C); Table 1). Although the highest
values were found at the shallowest stations, Chl
a, phaeophytines and %Chl a were not correlated
with water depth (Table. 2). Also, not all indicators
for biomass (Fig. 4(A)–(C); Table 1) were correlated
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E. Hoste et al. / Deep-Sea Research I 54 (2007) 109–129
clay (<2µm)
sand (63-2000 µm)
silt (2µm-63µm)
100%
90%
80%
70%
60%
50%
40%
30%
20%
10%
0%
1200
1500
2500
3000
3500
4000
5500
depth (m)
Fig. 2. Grain size fractions over the bathymetric depth for 2001.
with water depth. Only FDA (0–5 cm) decreased
(significantly, R ¼ 0.587, N ¼ 38, Table. 4) with
water depth along the bathymetric gradient (Fig. 5,
Table 1). Highest AFDW and PL (0–5 cm) values
were recorded in the year 2000 at most stations.
Exceptions were the maximum values of AFDW
(0.789 mg/cm2) at 1500 m (recorded in 2004) and of
PL at 4000 m (2001, 2002). PP showed a completely
different pattern with highest values found in 2004
at all the stations, with the exception of the 2000 m
station.
Axis 1 of the PCA plot (Fig. 6), including all
environmental variables except sediment grain size
fractions, explained 41.2% of the variation in the
data, while axis 2 explained only 20.2%. The primer
analysis gives water depth, indicators for food input
(Chl a and phaeopigments) and FDA as the primary
45
1.2
0.8
0.6
0.4
2000
2001
2002
2003
2004
40
35
phaeopigments (µg/cm2)
2000
2001
2002
2003
2004
1.0
Chl a (µg/cm2)
113
30
25
20
15
10
0.2
5
0.0
1000 1500 2000 2500 3000 3500 4000 4500 5000 5500 6000
(A)
0
1000 1500 2000 2500 3000 3500 4000 4500 5000 5500 6000
(B)
depth (m)
depth (m)
3.5
2000
2001
2002
2003
2004
3.0
%-Chl a
2.5
2.0
1.5
1.0
0.5
0.0
1000 1500 2000 2500 3000 3500 4000 4500 5000 5500 6000
(C)
depth (m)
Fig. 3. Pigment data (0–5 cm) over the 5-year time series. (A) chlorophyl a (Chl a), (B) phaeopigmnents (Phaeo) and (C) percentile Chl a
over total organic content (%Chl a).
19/08/2000
03/08/2000
03/08/2000
05/08/2000
04/08/2000
05/08/2000
06/08/2000
17/08/2000
12/07/2001
14/07/2001
13/07/2001
14/07/2001
15/07/2001
15/07/2001
06/08/2002
05/08/2002
03/08/2002
02/08/2002
05/08/2002
03/08/2002
08/08/2002
09/08/2002
21/07/2003
21/07/2003
26/07/2003
26/07/2003
23/07/2003
24/07/2003
02/08/2003
03/08/2003
07/07/2004
07/07/2004
07/07/2004
09/07/2004
09/07/2004
10/07/2004
10/07/2004
11/07/2004
PS57/272
PS57/166–2
PS57/168–2
PS57/178
PS57/176–2
PS57/181
PS57/182–2
PS57/252
PS59/91
PS59/96
PS59/94
PS59/103
PS59/105
PS59/108
PS62/171–2
PS62/170–2
PS62/162–2
PS62/161–2
PS62/169–2
PS62/163–2
PS62/183–2
PS62/185–3
PS64/402
PS64/408
PS64/439
PS64/429
PS64/414
PS64/419
PS64/464
PS64/471
PS66/104–1
PS66/101–2
PS66/100–2
PS66/117–1
PS66/114–2
PS66/121–2
PS66/122–2
PS66/124–2
1246
1495
1929
2385
2802
3350
4020
5079
1284
1524
2468
2916
3348
3997
1292
1559
1928
2469
2899
3640
4039
5231
1277
1551
1912
2501
3129
3491
4097
5573
1280
1554
2050
2507
3136
3574
4089
5570
1.16
0.63
0.46
0.21
0.15
0.08
0.11
0.25
0.62
0.22
0.13
0.07
0.06
—
0.57
0.30
0.65
0.11
0.20
0.20
0.09
0.03
0.58
0.36
0.10
0.23
0.00
0.10
0.05
0.17
0.38
0.23
0.15
0.17
0.15
0.25
0.05
0.22
06106,190
04153.600
04136.200
04111.200
03143.400
03136.000
03128.800
03121,360
06104.500
04154.400
04110.400
03142.800
03136.200
03129.200
06105.490
04153.910
04136.400
04110.930
03143.450
03132.400
03128.870
03119.630
06105.540
04154.040
04136.380
04107.570
03139.430
03134.540
03128.490
02150.730
06105.460
04154.070
04150.250
04104.980
03139.250
03133.780
03128.570
02150.640
79108.280
79107.800
79106.500
79104.100
79103.860
79104.500
79103.600
79104.480
79108.000
79108.100
79104.000
79104.100
79105.300
79104.000
79108.440
79107.840
79106.510
79103.900
79103.990
79105.100
79103.600
79104.520
79108.000
79107.800
79106.500
79104.310
79103.780
79103.530
79103.570
79107.990
79107.990
79107.760
79104.020
79105.000
79103.780
79103.820
79103.560
79108.020
36.02
29.08
26.61
18.19
13.03
9.76
12.52
24.29
34.37
20.10
15.74
12.26
10.71
—
29.29
16.91
23.06
13.01
15.49
8.39
11.81
4.97
41.01
30.37
5.37
28.93
17.09
15.18
22.53
28.60
20.44
14.97
10.59
10.64
9.84
12.86
4.43
11.55
Phaeo
(mg cm3)
Chl a
(mg cm3)
Longitude
1E
Latitude
1N
Water
depth
(m)
Organic matter input
Position
37.18
29.71
27.07
18.40
13.17
9.84
12.63
24.54
34.98
20.32
15.87
12.33
10.77
—
29.87
17.20
23.72
13.12
15.70
8.59
11.90
5.00
41.59
30.73
5.47
29.16
17.09
15.28
22.58
28.76
20.82
15.21
10.75
10.81
9.99
13.11
4.48
11.77
CPE (mg cm )
3
3.00
1.71
1.56
1.12
1.02
0.70
0.82
0.93
1.59
1.05
0.78
0.49
0.36
—
1.82
1.38
2.69
0.75
1.17
1.39
0.51
0.17
1.27
1.04
1.75
0.62
0.00
0.56
0.10
0.45
1.84
1.54
1.44
1.59
1.52
1.93
1.13
1.83
%Chl a
(%)
0.69
0.71
0.72
0.71
0.74
0.76
0.61
0.66
0.65
0.60
0.59
0.64
0.57
0.62
0.59
0.60
0.64
0.57
0.61
0.52
0.51
0.52
0.55
0.51
0.52
0.50
0.53
0.51
0.46
0.42
0.50
0.79
0.49
0.53
0.48
0.48
0.46
0.47
AFDW
(mg cm3)
Biomass
2.30
2.20
2.36
1.61
1.22
1.18
1.18
1.72
1.95
2.15
1.72
1.36
1.24
1.22
2.59
2.53
3.11
2.00
2.06
1.29
2.53
1.49
2.94
2.67
2.73
2.23
1.59
1.62
1.82
2.42
3.61
3.26
1.76
2.82
2.25
1.60
3.09
2.76
PP
(mg cm3)
118.23
149.27
115.71
73.87
172.77
148.76
56.01
47.91
52.42
81.51
60.94
92.79
73.58
79.09
46.41
72.01
100.35
27.19
28.39
39.39
81.07
31.33
73.21
58.14
30.69
47.52
58.93
62.07
57.58
24.86
52.65
15.79
52.47
21.47
25.46
25.81
13.84
21.72
PL
(nmol cm3)
11.08
6.52
5.60
6.68
2.79
1.84
1.55
2.84
31.67
20.17
8.90
11.76
6.10
2.53
35.87
27.81
27.13
15.85
8.39
4.12
6.32
1.76
43.67
4.66
25.72
17.03
4.90
6.46
4.11
4.21
6.29
3.75
7.56
2.37
4.83
2.44
1.15
1.66
FDA
(nmol ml1 h1)
Activity
2604
1993
2399
569
1227
426
568
747
3249
1768
1824
672
561
810
2656
2410
3409
2059
725
501
668
340
2525
1805
2139
1616
605
674
407
841
3303
1658
1540
888
765
452
150
888
MEIO
(ind/10 cm2)
Densities
722
84
237
30
183
58
208
244
22
216
310
76
34
163
133
114
526
135
53
76
168
25
238
79
86
325
75
171
58
122
78
31
163
45
91
109
4
74
SE
(ind/10 cm2)
Values for organic matter input (Chl a: chlorophyll a, Phaeo: phaeopigmentsand, CPE: chloroplasic pigment equivalents), biomass data (AFDW: ash-free dry weight, PP: particulate
proteins, PL: phospholipids), activity (fluorescein–diacetate) and mean meiofauna densities with the standard error (SE) are given.
Sampling
date
Station
No.
Table 1
Station data (0–5 cm) from sampling sites along the Hausgarten bathymetric gradient sorted by sampling year and water depth
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115
Table 2
Pearson correlation matrix with the variables water depth (depth), chlorophyl a (Chl a), phaeopigments (Phaeo), chloroplastic pigment
equivalents (CPE), ash free dry weight (AFDW), particulate proteins (PP), phospolipids (PL), bacterial esterase activity (FDA),
meiobenthos density (MEIO), nematode density (NEMA) and copepod density (COP)
Levels of correlation: black 40.75; grey 40.50; white o0.50.
variables explaining the variation along the first
axis. Two groups could be observed: (1) from 1000
to 2000 m water depth and (2) from 2500 to 5000 m
water depth (Fig. 6(A). The second PC axis was
primarily determined by the indicators for biomass
(PP, AFDW, and PL). No clear separation between
the years could be observed but there was a gradual
transition in time along the axis due to a general
decrease in AFDW and PL in time (Fig. 6(B)).
3.2. Meiobenthos communities
In total, 40,311 metazoan meiobenthos organisms
were counted. These organisms belonged to 18
major taxa. Taxon richness ranged from 1 taxon
(Nematoda), to over 10 taxa per station (Table 3).
Mean meiobenthos densities for each station over
the time series are given in Table 1. Nematodes were
always the most abundant metazoan taxon
(85–99%), making up 95% of the total meiofauna
at all dates and water depths. Harpacticoid copepods were the second most abundant taxon (0–4.6%
and 1.9% of the total meiofauna) and also nauplii
were consistently present (0–4% and 1.6% of the
total meiofauna). Other taxa such as polychaetes,
gastrotrichs, kinorhynchs, tardigrades, rotifers and
tantulocarids were regularly found but in very low
abundances (max 2%).
Fig. 7 shows the mean nematode and copepod
densities along the bathymetric transect over the
5-year period. Mean densities (0–5 cm) ranged
between 13576 nematodes/10 cm2 (4000 m, in
2004) and 32157497 nematodes/10 cm2 (2000 m;
in 2002). Harpacticoid copepod densities ranged
from 171 ind/10 cm2 (2500 m, in 2000) to 80713 ind/
10 cm2 (2000 m, in 2002).
Both nematode and copepod densities were
correlated with water depth (R ¼ 0.766 [N ¼ 8]
and R ¼ 0.661 [N ¼ 38], respectively) per year and
over all years. The correlation between densities and
depth, however, does not reflect a linear relationship
but is rather due to the high difference in densities
between a 1000–2500 m zone and a 3000–5000 m
zone. Nematode and copepod densities were
also correlated with phaeopigments, %Chl a, PP,
and FDA in individual years and over all years
(Table 2). However, no significant correlation with
Chl a was found.
The ANOSIM results indicated that the meiobenthos communities were significantly different
between water depths (R ¼ 0.50, po0.001). Looking at the pairwise tests between stations, differences
occurred especially between the 1200–2000 m zone
and the 3000–5500 m zone. The station at 2500 m
depth was significantly different from all other
stations. The overall meiobenthos community did
not differ over the years (R ¼ 0.032, p40.05) but
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4.0
0.85
2000
2001
2002
2003
2004
0.80
0.70
3.0
proteine (mg/cm2)
AFDW (mg/10cm3)
0.75
0.65
0.60
0.55
2000
2001
2002
2003
2004
3.5
2.5
2.0
1.5
1.0
0.50
0.45
0.5
0.40
1000 1500 2000 2500 3000 3500 4000 4500 5000 5500 6000
0.0
1000 1500 2000 2500 3000 3500 4000 4500 5000 5500 6000
(A)
(B)
depth (m)
depth (m)
180
2000
2001
2002
2003
2004
160
lipide (nmol/cm2)
140
120
100
80
60
40
20
0
1000 1500 2000 2500 3000 3500 4000 4500 5000 5500 6000
(C)
depth (m)
Fig. 4. Biomass data (0–5 cm) over the 5-year time series. (A) Ash-free dry weight (AFDW), (B) particulate proteins and
(C) phospholipids.
looking at each water depth separately there were
significant differences between the years for the
stations between 2000 and 3000 m and the 4000 m
station. The pattern over time for these water
depths, however, was different for each depth
(Fig. 8).
The similarity matrix based on the Bray–Curtis
similarities of meiofauna densities were significantly
(Rho ¼ 0.401; p ¼ 0.001) related to the normalized
Euclidian distance similarity matrix of the environmental data. When the BIO_ENV procedure was
applied, water depth emerged as the environmental
variable that best explained the variation in the
meiobenthos data (Rho ¼ 0.570), as shown in the
MDS plot (Fig. 9). A low stress value (o0.2) for the
MDS analysis indicated a good ordination with no
real prospect of a misleading interpretation (Clarke,
1993). The same shallow and deep groups of
stations appeared in the MDS plot as in the PCA.
The shallow group had high nematode and copepod
densities with a mean density of 22597157 ind/
10 cm2 and almost 5074 ind/10 cm2, respectively,
whereas the deep group had a mean nematode
density of about 595752 ind/10 cm2 and a mean
copepod density of 1172 ind/10 cm2. Only the
station at 2500 m had an intermediate position;
depending on the year it grouped with one or both
of the depth-related groups. However, a temporal
trend was not observed. The changes in biomass
(PP, AFDW, and PL) over time were thus not
reflected in meiobenthos community structures.
Fig. 10 shows the vertical distribution of the
nematodes with sediment depth for the time series.
The mean proportional nematode density in the first
2 cm of the sediment increased with depth
(R ¼ 0.922) along the transect, from a minimum
of 54% at 1000 m to 86% at 3500 m, and decreased
again to 60% at the 5500 m station. The mean
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117
50
2000
2001
2002
2003
2004
45
40
FDA (nmol / ml h)
35
30
25
20
15
10
5
0
1000 1500 2000 2500 3000 3500 4000 4500 5000 5500 6000
depth (m)
Fig. 5. Bacterial esterase activity (FDA) over 5 cm depth for the 5-year time series (%Chl a).
proportional abundances in the first 2 cm were
negatively correlated with nematode and copepod
densities (N ¼ 38, R ¼ 0.664 and 0.690, respectively) and FDA (N ¼ 38; R ¼ 0.506). Down to
3500 m there was also a positive correlation with
water depth (N ¼ 29; R ¼ 0.922). The inter-annual
variability in sediment depth profile decreased with
water depth along the bathymetric gradient. Variations in the vertical distribution of nematodes were
mainly observed at the shallowest stations (down to
2500 m).
4. Discussion
4.1. Comparison of arctic MIZ meiobenthos and
environmental parameters with other polar deep-sea
sites
Ice melting during the arctic spring and summer
gives rise to a strongly stratified and nutrient-rich
euphotic zone, with a distinct phytoplankton
bloom. The phytoplankton bloom follows the
receding ice edge as it melts during spring and
summer (Sakshaug and Skjoldal, 1989) and intensive blooms occur in leads as the MIZ opens up. The
area of investigation, the HAUSGARTEN site, is
situated along the summer MIZ in the Fram Strait
(Fig. 1) and sampling was performed in summer
when primary production and subsequent sedimentation of organic matter was expected to be highest.
A significant decrease in Chl a and phaeopigments with increasing distance from the ice edge has
been reported in several studies (Engelsen et al.,
2002; Schewe and Soltwedel, 2003). In ice–free areas
from the MIZ to the northwest of Svalbard,
primary production rates of 18–20 mg cm2 h1
were measured, while at the ice-edge, production
rates even increased up to 37 mg cm2 h1 (Heimdal,
1983). The POC input of 250 mg cm2 into the deep
layers (200 m) at the Barents Sea MIZ could even be
comparable to that in upwelling areas and is
generally more than in coastal and shelf areas (Olli
et al., 2002). In this study, food availability at the
seafloor was estimated by analyzing sedimentbound chloroplastic pigments (Chl a and Phaeopigments), which showed, as expected, high values
compared to most other polar deep-sea regions
(Table 4). Similar high values were found along the
MIZ of the Fram Strait, near the HAUSGARTEN
area (Schewe and Soltwedel, 2003), and on the
Yermak Plateau (Soltwedel et al., 2000) where
lateral input under the ice, driven by the West
Spitzbergen Current, causes comparably high Chl a
values in deep-sea sediments. As deep-sea benthic
ecosystems are sustained largely by the organic
matter settling from the euphotic zone (Beaulieu,
2002; Gooday, 2002), one might also expect high
meiobenthos densities at HAUSGARTEN. Nematode and copepod densities were indeed high
compared to other deep-sea regions (Fig. 11), even
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3
1200m-2000m
2500m-5500m
1000
1500
2000
2500
0
3000
3500
-1
4000
5000
2
PC2
1
-2
5500
-3
-4
-5
-4
-3
-2
(A)
-1
0
PC1
1
2
3
4
3
2000
2
PC2
1
2001
0
2002
-1
-2
2003
-3
2004
-4
-5
(B)
-4
-3
-2
-1
0
PC1
1
2
3
4
Fig. 6. PCA plot including sediment bound pigments, biomass data and FDA with indication of (A) different depths and (B) different
years. PC1 explains 41.2% of the variation; PC2, 20.2%.
when differences in sampling technique (Table 4)
and processing are kept in mind. As in other deepsea studies, nematodes clearly dominated the
metazoan meiofauna followed by copepods with
other taxa such as Kinorhyncha, Tardigrada, and
Gastrotricha present in very low numbers (Pfannkuche and Thiel, 1987; Vanhove et al., 1995;
Vanaverbeke et al., 1997; Schewe and Soltwedel,
1999; Vanreusel et al., 2000; Soltwedel et al., 2000;
Schewe, 2001).
4.2. Bathymetric gradient
The decrease of meiobenthos densities with depth,
although stepwise and not gradually, is in accordance with expectations based on the decreasing
quality and quantity of the food with water depth
due to the remineralization of organic matter during
transport from the surface to the deep seafloor
(Graf, 1989). There was, however, no significant
correlation between depth and the chloroplastic
pigments along the studied transect because of the
increase in food availability at 5000 and 5500 m.
These stations are located in the Molloy Hole, a
region that acts as a huge sediment trap accumulating organic matter at the bottom (Soltwedel et al.,
2003). The increase in organic content of the
sediment is reflected in the nematode and copepod
densities, which are slightly higher in comparison
with the other deep stations, illustrating the
importance of food input for meiobenthos densities.
Contrary to most previous studies (Vanaverbeke
et al., 1997; Schewe and Soltwedel, 1999; Vanreusel
et al., 2000; see also review by Soltwedel, 2000),
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119
Table 3
Meiofauna taxa (MEIO) and meiofauna densities (NEMA: nematodes, HARP: harpacticoid copepods, NAUPLII: nauplii and REST:
bulk of all other taxaa) for each station in time
Station
no.
Water
depth
(m)
MEIO
(# taxa)
NEMA
(ind/10 cm2)
SE
HARP
(ind/10 cm2)
SE
NAUPLII
(ind/10 cm2)
SE
REST*
(ind/10 cm2)
SE
PS57/272
PS57/166–2
PS57/168–2
PS57/178
PS57/176–2
PS57/181
PS57/182–2
PS57/252
PS59/91
PS59/96
PS59/94
PS59/103
PS59/105
PS59/108
PS62/171–2
PS62/170–2
PS62/162–2
PS62/161–2
PS62/169–2
PS62/163–2
PS62/183–2
PS62/185–3
PS64/402
PS64/408
PS64/439
PS64/429
PS64/414
PS64/419
PS64/464
PS64/471
PS66/104–1
PS66/101–2
PS66/100–2
PS66/117–1
PS66/114–2
PS66/121–2
PS66/122–2
PS66/124–2
1246
1495
1929
2385
2802
3350
4020
5079
1284
1524
2468
2916
3348
3997
1292
1559
1928
2469
2899
3640
4039
5231
1277
1551
1912
2501
3129
3491
4097
5573
1280
1554
2050
2507
3136
3574
4089
5570
6
6
7
3
8
4
5
5
7
8
7
7
5
5
8
6
7
7
7
5
8
4
6
5
6
5
4
5
4
4
8
7
6
7
5
5
2
4
2484
1850
2295
557
1172
409
535
726
3091
1642
1768
618
494
783
2514
2282
3211
2014
666
474
590
316
2390
1690
2028
1562
580
647
387
796
3110
1564
1481
827
714
425
135
837
722
84
237
30
183
58
208
244
22
216
310
76
34
163
133
114
526
135
53
76
168
25
238
79
86
325
75
171
58
122
78
31
163
45
91
109
4
74
56
46
38
1
14
8
8
10
54
69
15
14
5
6
47
54
80
17
14
7
37
12
61
45
42
17
4
11
1
27
52
32
23
17
10
11
1
15
14
11
11
1
1
3
3
3
13
17
1
3
2
0
6
5
13
8
6
1
15
9
17
2
6
4
3
1
1
3
6
5
5
5
2
5
1
2
33
57
30
5
7
1
10
2
67
29
16
8
8
8
63
51
82
10
13
3
6
4
50
47
38
17
2
8
3
12
90
37
12
6
5
2
0
12
14
11
8
2
3
1
3
1
2
11
4
5
4
7
1
15
26
2
6
2
2
4
19
12
2
5
2
1
2
3
15
6
2
6
3
1
0
5
29
39
36
9
37
12
21
16
41
35
34
44
34
26
46
37
51
35
53
38
56
31
44
47
55
45
47
37
46
38
80
58
59
73
73
53
54
64
4
14
6
4
10
2
4
3
7
6
13
10
1
2
11
3
5
4
8
5
17
3
7
4
10
9
1
3
6
1
3
4
6
7
5
4
4
11
a
Ostracoda, Polychaeta, Rotifera, Gastrotricha, Kinorhyncha, Tardigrada, Isopoda, Bivalvia, Tantulocarida, Tanaidacea, Cumacea,
Loricifera, Priapulida, Halacarida, Amphipoda, Sipunculida.
there was no gradual decrease in nematode and
copepod densities with depth but rather a shallow
and deep area could be distinguished. The distinction was also reflected in the environmental
variables and sediment characteristics. The topography of the area, with the samples from 1200 to
2500 m located on a the gentle upper slope, and
samples from 3000 to 5000 m on the lower steep
slope, might be the critical factor dividing the
transect into two areas. The differences in topography might influence near bottom currents,
causing a sudden change in environmental conditions leading to a sudden drop in meiofauna
densities (Thistle and Levin, 1998). However, the
2500 m station, although not located on the steep
slope, groups with the steep slope stations based on
environmental data and shows a high inter-annual
variability based on meiobenthos data.
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120
4000
2000
2001
2002
2003
2004
nematode densities/10 cm2
3500
3000
2500
2000
1500
1000
500
0
1000 1500 2000 2500 3000 3500 4000 4500 5000 5500
depth (m)
(A)
100
2000
2001
2002
2003
2004
copepod densities/10 cm2
80
60
40
20
0
1000 1500 2000 2500 3000 3500 4000 4500 5000 5500
(B)
depth (m)
Fig. 7. Mean nematode (A) and copepod (B) densities 7SE over the bathymetric transect for the 5-year time series.
The strong correlation of meiobenthos densities
with bacterial activity (FDA), for each year and
over all years, supports the assumed importance of
bacteria as primary food source for the deep-sea
metazoan meiofauna (Vanreusel et al., 1995; Galéron et al., 2001; Iken et al., 2001). The low nematode
and copepod densities at 5000–5500 m depth (Molloy Hole), compared to stations at shallower depths
with comparable Chl a and phaeopigment data, but
higher FDA values, might confirm this, although
the lower quality of the organic material at greater
depths and the high predation pressure at Molloy
Hole (Soltwedel et al., 2003) might also play a role.
To study the possible migration in the sediment
with changing food availability (Vanreusel et al.,
1995), the vertical sediment profile of nematode
densities was studied. As was discussed in the study
by Pfannkuche and Thiel (1987), who focused on
the Barents Sea continental margin, mean relative
nematode abundances in the first 2 cm of the
sediment increase with water depth and with decreasing nematode densities. The absolute nematode
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1200 m
121
1500 m
3500
90
3500
90
3000
80
3000
80
70
2500
60
70
2500
60
2000
50
2000
50
1500
40
1500
40
30
1000
20
500
10
0
0
30
1000
20
500
10
0
0
2000 2001 2002 2003 2004
year
2000 2001 2002 2003 2004
year
2000 m
2500m
3500
90
3500
90
3000
80
3000
80
70
2500
60
70
2500
60
2000
50
2000
50
1500
40
1500
40
30
1000
20
500
10
0
0
20
500
10
0
2000 2001 2002 2003 2004
year
0
2000 2001 2002 2003 2004
year
3000 m
3500 m
3500
2
nem/10 cm
2
cop/10 cm
3000
30
1000
2500
90
3500
90
80
3000
80
70
60
70
2500
60
2000
50
2000
50
1500
40
1500
40
30
1000
20
500
10
0
0
30
1000
20
500
10
0
0
2000 2001 2002 2003 2004
year
2000 2001 2002 2003 2004
year
4000 m
5000 m
3500
90
3500
90
3000
80
3000
80
70
2500
60
70
2500
60
2000
50
2000
50
1500
40
1500
40
30
1000
20
500
10
0
2000 2001 2002 2003 2004
year
0
30
1000
20
500
0
10
0
2000 2001 2002 2003 2004
year
5500 m
3500
90
3000
80
70
2500
60
2000
50
1500
40
30
1000
20
500
10
0
0
2000 2001 2002 2003 2004
year
Fig. 8. Nematode and copepod density time series per depth.
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122
Stress:0.07
1000m-2000m
1000
1500
2000
2500
3000
3500
4000
5000
3000m-5500m
5500
Stress:0.07
2000
Thiel, 1987), even at deeper stations. In the study by
Soltwedel et al. (2003), the occurrence of high
nematode abundances in deeper sediment layers in
the Molloy Hole is explained by a high predation
pressure by dense herds of holothurians, dominating the epibenthos at 5600 m depth and intensively
reworking the upper few millimeters of the sediment. Nematodes would be able to escape predation
by vertical migration into deeper sediment horizons.
This may explain the high relative abundances of
the nematodes in deeper sediment layers at
5000–5500 m depth.
2001
4.3. Time series
2002
2003
2004
Fig. 9. MDS plot based on meiofauna taxa densities with
indication of (A) different depths and (B) different years.
densities in the upper sediment layer do not vary a
lot between depths in contrast to the relative
proportion of the nematodes inhabiting the upper
centimeter, which increases with depth. The higher
total nematode abundances (5-cm depth) at shallow
stations, and also in the Molloy Hole, therefore, are
caused by higher nematode densities in deeper
sediment layers. This observation, in addition to
the fact that densities are correlated with bacterial
activity (FDA) rather than with indicators for
phytodetritus input, suggests that the meiofauna
and nematodes in particular are not the first order
consumers of the surface organic input. They rather
respond when demineralization is already at an
advanced stage, as shown by earlier evidence from
stable isotope analyses at the Porcupine Abyssal
Plain (Iken et al., 2001). Also, in the study of
Vanreusel et al. (1995), the vertical distribution of
nematodes in the sediment could be explained by a
combination of bacterial densities and oxygen
supply.
In addition to food availability in deeper layers,
also competition and predation pressure might be
responsible for the observed depth profiles in the
sediments (Pfannkuche and Thiel, 1987; Soltwedel
et al., 2003). Oxygen availability in subsurface layers
is unlikely to be a limiting factor for the meiofaunal
abundances in the arctic deep-sea (Pfannkuche and
Long-term studies are essential in order to
understand better how benthic systems behave on
ecological time scales. However, time-series in areas
that are not easily accessible, such as the Arctic, are
extremely scarce (Gooday, 2002).
A comparison of benthic data obtained in
different years is affected by seasonal variability,
because the timing, amount and composition of the
annual sedimentation of phytodetritus as the major
food resource for benthic organisms and the related
response of the benthos can vary considerably
(Fortier et al, 2002; Soltwedel et al., 2005). The
interannual variation of vertical flux in the Barents
Sea is determined by the dynamics of the inflowing
warm, nutrient-rich Atlantic Water, which determines the extent of ice cover and imports variable
amounts of overwintering zooplankton (Slagstad
and Wassmann, 1991, 1997). Estimations of the
average annual vertical export of POC in the
Barents Sea can vary from 17 g cm2 during cold
years to 39 gcm2 in warm years (Slagstad and
Wassmann, 1997). The Fram Strait region, where
the HAUSGARTEN is located, is also well known
for large interannual fluctuations in local ice coverage, and the intensity of the ice-edge blooms
(Sakshaug and Skjoldal, 1989). The bloom development, the secondary production and the fate of
the organic matter along the west Spitzbergen and
east Greenland shelf, however, are not known as
well as they are for the Barents Sea (Wassmann,
2002).
This study demonstrated a significant interannual variability in the meiobenthos and pigment
data at the HAUSGARTEN site between the years
2000 and 2004. Because, firstly, no consistent
pattern was found in pigment data and, secondly,
there was no correlation found between meiofauna
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1500m
depth within the sediment (cm)
depth within the sediment (cm)
1200m
1
2
3
4
5
0
200
400
600
800
Nematodens/10 cm
1000
1
2
3
4
5
0
1200
200
2
400
1000
1200
1000
1200
1000
1200
1000
1200
2500m
depth within the sediment (cm)
depth within the sediment (cm)
800
1
1
2
3
4
5
0
200
400
600
800
Nematodens/10 cm
1000
2
3
4
5
1200
0
200
2
400
depth within the sediment (cm)
2
3
4
5
200
400
600
800
Nematodens/10 cm
1000
2
3
4
5
0
200
2
400
5000m
depth within the sediment (cm)
3
4
5
600
800
2
2
400
600
Nematodens/10 cm
4000m
200
2
1
1200
1
0
800
3500m
1
0
600
Nematodens/10 cm
3000m
depth within the sediment (cm)
600
Nematodens/10 cm2
2000m
depth within the sediment (cm)
123
800
Nematodens/10 cm
1000
1200
2
1
2
3
4
5
0
200
400
600
800
2
Nematodens/10 cm
depth within the sediment (cm)
5500m
1
2
2000
2001
2002
2003
2004
3
4
5
0
200
400
600
800
1000
1200
Nematodens/10 cm2
Fig. 10. Nematode densities over the 5-cm depth profile for each depth along the bathymetric transect.
Pfannkuche and Thiel (1987)
Vanaverbeke et al. (1997)
NO–Svalbard
(2500 m–3920 m)
Laptev Sea
(1935 m–3237 m)
Clough et al. (1997)
Vanreusel et al. (2000)
Schewe and Soltwedel (1999)
Central Arctic
Central Arctic (864 m–4187 m)
Schewe and Soltwedel (2003)
Schewe (2001)
Arctic
(1000 m–4190 m)
Central Arctic
(1270 m–3170 m)
Arctic Ice Margin
(744 m–3020 m)
0.02
Soltwedel et al. (2000)
1000–2000 m
2000–3000 m
3000–4000 m
45000 m
500o1000 m
2000–3000 m
3000–4000 m
1000–2000 m
2000–3000 m
3000–4000 m
500o1000 m
1000–2000 m
2000–3000 m
3000–4000 m
1000–2000 m
2000–3000 m
o1000 m
1000–2000 m
2000–3000 m
1000–2000 m
2000–3000 m
3000–4000 m
4000–5000 m
This study
Hausgarten
(1000 m–5500 m)
Yermak Plateau
(481 m–4268 m)
Depth
mg/cm2 cm
Table 4
Chl a, phaeopigment and sampling gear data for different arctic regions
MUC+BC
MUC
BC
MUC
MUC
MUC
MUC
BC
MUC
Sampling
gear
0.02
0.01
0.02
0.28–2.48
0.14–1.07
0.09–0.56
0.01–0.09
0.021–0.067
0.006–0.036
0.07–0.21
0.03–0.95
0.01–0.63
0.04–0.46
0.01–0.16
0.017–0.183
0.03–0.09
Chl a
(0–1 cm)
0
0–0.001
0–0.001
0
Chl a
(0–2 cm)
0.10–1.16
0.07–0.23
0.05–0.25
0.03–0.25
0.3170.04–4.1270.53
0.6970.04
0.0370.01–0.1370.01
Chl a
(0–5 cm)
1.05
1.06
0.54
2.27–6.04
0.67–5.25
0.77–3.77
0.30–1.29
0.167–0.403
0.102–0.139
2.57–3.28
1.30–5.63
0.82–3.62
3.014–12.58
3.162–9.66
1.049–7.40
2.40–11.15
Phaeopigments
(0–1 cm)
0.041–0.145
0.017–0.051
0.022–0.104
0.012
Phaeopigments
(0–2 cm)
124
E. Hoste et al. / Deep-Sea Research I 54 (2007) 109–129
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E. Hoste et al. / Deep-Sea Research I 54 (2007) 109–129
125
3500
nem (this study)
nem centre arc
nem laptev
nem sval
nem ant
nemdens yermak
3000
nem dens/10 cm2
2500
2000
1500
1000
500
0
0
1000
2000
3000
4000
5000
6000
depth (m)
90
cop (this study)
cop centre arc
cop sval
cop yermak
80
cop dens/10 cm2
70
60
50
40
30
20
10
0
0
1000
2000
3000
4000
5000
6000
depth (m)
Fig. 11. Comparison nematode and copepod densities (ind/10 cm2) in different polar regions. Data are from the Central Arctic Ocean
(nem/cop centr arc; Schewe and Soltwedel, 1999, Vanreusel et al., 2000, Schewe, 2001), the Laptev Sea (nem laptev; Vanaverbeke et al.,
1997), the continental shelf of NE-Svalbard (nem/cop sval; Pfannkuche & Thiel, 1987), the Antarctic Weddel Sea (nem ant; Vanhove et al.,
1995) and the Yermak plateau (nem/cop yermak; Soltwedel et al., 2000).
densities and sediment-bound chloroplastic pigments, it was thought that following factors might
hamper a sound interpretation of the data. Firstly,
Gooday (2002) emphasizes the difficulty of sampling the benthic community at the right time to
document the short-term responses to flux events.
The time period between the start of the bloom and
the sampling is unknown in this study. The
phytoplankton bloom might, therefore, be at a
different stage of the bloom growth cycle. This cycle
consists of a pre-bloom phase with a minute
standing stock of phytoplankton, an exponential
phase, a peak phase, a phase of decrease in standing
stock, and a post-bloom phase that lasts till the refreezing of the sea water (Sakshaug and Skjoldal,
1989). Sinking rates of the primary production
appear to be particularly high at the end of a bloom.
At this time, the algae appear to be susceptible to
ARTICLE IN PRESS
126
E. Hoste et al. / Deep-Sea Research I 54 (2007) 109–129
attack by bacteria (Sakshaug and Skjoldal, 1989),
which may also serve as an important food source
as shown in this study. The different stages of the
phytoplankton bloom are also dominated by a
different phytoplankton community (Olli et al.,
2002; Drinkwater et al., 2003). Therefore, both
quantity and quality of the food reaching the
bottom changes during the phytoplankton growth
cycle. Differences in the stage of the phytoplankton
bloom growth cycle may cause the differences in the
sediment bound chloroplastic pigments found in
this study. The lack of correlation between sediment
bound chloroplastic pigments and meiofauna densities could then be explained by the differences in
quality of the material and amount of bacteria
accompanying the organic matter. The %Chl a,
however, could not explain the differences in
meiobenthos densities.
Secondly, the relation between what is produced
at the sea surface and what reaches the bottom is
very complex. The zooplankton can considerably
alter the flux of organic matter both in a positive
way (production of fast-sinking fecal pellets) and a
negative way (very high grazing rates) (Wassmann,
1998; Olli et al., 2002; Fortier et al., 2002; Hansen
et al., 2003). This means that the pigments found on
the ocean bottom do not always reflect the surface
primary production. Because the spatial distribution
of the zooplankton community can vary considerably along the MIZ (Wassmann, 1998; Olli et al.,
2002; Fortier et al., 2002; Hansen et al., 2003) this
could explain why no consistent pattern in meiofauna densities and sediment-bound chloroplastic
pigments for each separate year could be found.
Another point to emphasize is that seasonal
organic-matter inputs make an important contribution to the spatial heterogeneity of the ocean-floor
environment. This means that in practice it is
difficult to distinguish between temporal variability
and spatial patchiness (Gooday, 2002). It should be
noted though that in this study samples come from
just one MUC haul per station and year. This could
minimize the spatial patchiness among stations
(Hurlbert, 1984). Differences between the years
could, therefore, be due to patchiness induced by
heterogeneous distribution of food to the seafloor
(Gage, 1996; Levin et al, 2001).
Also, nematodes might not depend on the
primary production itself but on the bacteria
accompanying this material. The results of this
study suggest that the abundance of bacteria is
related to nematode densities, which show a positive
correlation with FDA. If nematodes rely on the
microbial loop to stimulate their production (Fleeger et al., 1989), one might indeed not expect rapid
nematode density changes but time lags between
sedimentation of surface organic matter and nematode density increases.
Fleeger et al. (1989) provided further reasons for
the lack of correlations between the benthos
densities and food input. The role of reproduction,
predation, and winter survivorship as factors
regulating species abundances could influence overall benthos densities. Finally, yearly variation in
sedimentation may even not be great enough. This,
however, seems unlikely, as food availability at the
HAUSGARTEN varies as much in time as it does
along the bathymetric gradient and along this
gradient, differences in food availability are reflected in the meiobenthos densities.
The highest variations in nematode and copepod
densities over time were observed at 2000 m and
even more at 2500 m water depth. Unlike those at
shallower depths, meiofauna at these two stations
may be limited by food quantity and quality. As a
result, they are likely to respond in a more obvious
way to interannual or seasonal variations in sea ice
conditions, primary production and corresponding
food inputs to the seafloor. Food quality at deeper
stations may be so low that nematode communities
are unable to benefit from a considerable increase in
food quantity, whereas at shallower stations, food
quality and quantity are high enough even in years
with lower food availability.
The high temporal variability in the vertical
distribution of nematodes in the sediment at
shallower depths along the bathymetric gradient
may indicate that nematodes at these depths react to
increased input of organic matter by migrating
deeper into the sediment (Galéron et al., 2001).
Enhanced food availability is normally reflected in
the vertical distribution of the organic compounds
in the sediment column (Soltwedel et al., 2000).
Bioturbating macrofaunal organisms induce a rapid
downward mixing of the organic matter (Witte
et al., 2003) making it available deeper in the
sediment. At deeper stations nematodes may be
obliged to inhabit the upper centimeters of sediment
as deeper layers are depleted in food. Here again,
however, we found no correlation between proportional nematode densities in the upper 2 centimeters
of the sediment and sediment bound chloroplastic
pigments, and even no correlation with FDA. There
is no information available from the study sites
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E. Hoste et al. / Deep-Sea Research I 54 (2007) 109–129
about macrofauna densities, predation pressure and
bioturbation, factors which may also help to
regulate the depth profiles.
5. Conclusions
The results of this study suggest the following
answers to the questions posed in the Introduction.
(1) The high productivity along the The Marginal
Ice Zone is reflected in high meiobenthos
densities.
(2) The topography of the HAUSGARTEN region
divides the bathymetric gradient into two distinct areas based on environmental variables as
well as meiofauna densities.
(3) Meiofauna densities and vertical depth profiles do
change over time, especially at 2000 and 2500 m
depth, but no consistent pattern could be found.
The lack of knowledge about spatial patchiness,
interannual variations in intensity of the bloom,
zooplankton communities and time lags in
response to increased food input hamper a sound
interpretation of inter-annual variations.
(4) The variation in microbial production is probably the most important factor structuring
meiobenthos communities in time and over
water- and sediment depth.
Acknowledgements
The first author acknowledges a grant (2002–06)
from the Institute for the Promotion of Innovation
through Sciences and Technology in Flanders
(IWT-Vlaanderen). This study is part of the multidisciplinary research at the HAUSGARTEN site
coordinated by the Alfred-Wegener Institute for
Polar and Marine Research. This research was
supported by the HERMES project, EC contract no
GOCE-CT-2005-511234, funded by the European
Commission’s Sixth Framework Program under the
priority ‘Sustainable Development, Global Change
and Ecosystems’. We would like to thank the
Alfred-Wegener Institute for Polar and Marine
Research, the captain, crewmembers, and chief
scientists of the research vessel R.V. Polarstern for
providing the samples. Also a special thanks to Bart
Beuselinck for the extraction of the meiofauna. We
are thankful to the anonymous reviewers and the
editor for their constructive comments on this
manuscript.
127
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