Progress in Oceanography 218 (2023) 103117

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

Responses of diatom assemblages and life cycle to sea ice variation in theeastern Indian sector of the Southern Ocean during austral summer 2018/2019
Kohei Matsuno a, b, *, Kohei Sumiya a, Manami Tozawa a, Daiki Nomura a, b, d, Hiroko Sasaki c,Atsushi Yamaguchi a, b, Hiroto Murase eaFaculty/Graduate School of Fisheries Sciences, Hokkaido University, 3-1-1 Minato-cho, Hakodate, Hokkaido 041-8611, Japan
Arctic Research Center, Hokkaido University, Kita-21 Nishi-11 Kita-ku, Sapporo 001-0021, JapancFisheries Resources Institute, Japan Fisheries Research and Education Agency, 2-12-4 Fukuura, Kanazawa, Yokohama, Kanagawa 236-8648, Japand
Field Science Center for Northern Biosphere, Hokkaido University, 3-1-1 Minato-cho, Hakodate, Hokkaido 041-8611, JapaneTokyo University of Marine Science and Technology, 4-5-7 Konan, Minato-ku, Tokyo 108-8477, Japanb

A R T I C L E I N F O

A B S T R A C T

Keywords:
Protist community
Cell size
Fragilariopsis
Indian sector of the Southern Ocean

In the Southern Ocean, rapid environmental changes (warming, freshening, and poleward shifts of the physio­
logical fronts) are underway. These changes affect the distribution, abundance, and life cycle of protists. How­ever, the spatial distribution of protists is not well understood in the eastern Indian sector of the Southern Ocean.
We, therefore, evaluated the effects of environmental factors at the community level (abundance and species
composition) and species-specific level (life cycle in diatoms) based on field sampling during the austral summerof 2018/2019. High chlorophyll levels and protist cell densities were observed in the eastern area from 120◦ E, incontrast to the distribution reported in the 1996 BROKE (The Baseline Research on Oceanography, Krill and theEnvironment) survey. This inter-annual variation was caused by differences in the sampling periods, nutrients,and zooplankton grazing pressures. North–south variation in protist abundance was well explained by silicate
distribution, whereas sea ice variation did not influence it explicitly. The clustering of protist groups was wellassociated with nutrients, but locally, offshore groups were extended southward by currents and eddies. The cellsize of the two dominant Fragilariopsis curta and F. kerguelensis exhibited similar significant relationships with sea
ice variation and decreased 60 days after sea ice melted. Our findings demonstrate that sea ice changes do not
clearly affect the protist community level but potentially affect the life cycle level of diatoms.

1. Introduction
In the Southern Ocean, the Antarctic Circumpolar Current (ACC)
flows eastward offshore (between approximately 50◦ S and 65◦ S, Orsiet al., 1995), whereas the Antarctic Slope Current (ASC) flows westward
along the coast of Antarctica. These circumpolar currents provide rela­
tively constant environmental conditions. In recent years, warming andfreshening trends and poleward shifts of the ACC fronts have been welldescribed (Aoki et al., 2020; Hirano et al., 2021; Yamazaki et al., 2021).
Accompanying the changes, a shallower mixed layer depth and inten­
sified stratification occur (Sallée et al., 2010; Deppeler and Davidson,2017), and these environmental changes could affect marine ecosystems(Moline et al., 2008; Deppeler and Davidson, 2017).

In the marine ecosystem of the Southern Ocean, phytoplankton
forms a key component, and the most dominant taxon in phytoplankton
is diatoms (Kopczynska et al., 1986). Diatoms bloom massively,
accompanied by sea ice retreat during summer due to release from light
limitation (Arrigo et al., 2010). Because the Southern Ocean is typical ofhigh nutrient and low chlorophyll (HNLC) regions, iron from sea ice(containing a magnitude higher concentration of iron than typical
Antarctic surface water) is believed to accelerate diatom growth (Martin
et al., 1990; Lannuzel et al., 2016). Diatom assemblages can be alteredby upwelling near the physical fronts (Chiba et al., 2000; Davidson et al.,2010).
Diatoms also play an essential role in the biological pump byexporting and cycling key nutrients (Ragueneau et al., 2006). Cell size in* Corresponding author at: Faculty/Graduate School of Fisheries Sciences, Hokkaido University, 3-1-1 Minato-cho, Hakodate, Hokkaido 041-8611, Japan.
E-mail address: k.matsuno@fish.hokudai.ac.jp (K. Matsuno).
https://doi.org/10.1016/j.pocean.2023.103117
Available online 6 September 2023
0079-6611/© 2023 Elsevier Ltd. All rights reserved.

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Progress in Oceanography 218 (2023) 103117

Fig. 1. Location of sampling stations in the Indian sector of the Southern Ocean during austral summer 2018/2019. SACCF: Southern Antarctic Circumpolar Current
Front, SB: Southern Boundary of Antarctic Circumpolar Current, ASF: Antarctic Slope Front (Yamazaki et al., 2020).

diatoms is a critical factor that controls the sinking speed (Smetacek,1985) and size-selective predation by zooplankton (Perissinotto, 1992).
Owing to their functional roles, the diatom size structure considerably
impacts the food web and material cycle in world oceans (Finkel et al.,2010; Marañón, 2015). Diatom size ranges from several micrometers toa maximum of 2 mm, with temporal changes in the life cycle (Edlundand Stoermer, 1997). Diatoms have two valves and propagate asexually
through cell division. The parent valves divide, and each new daughter
cell contains one parent valve and one new valve. Thus, the daughter
cell becomes slightly smaller than the parent cell. With the progressionof cell division, when the cell size reaches a critical lower limit, thesexual cycle is initiated, and auxospores are formed, increasing to theoriginal larger cell size. Sea-ice dynamics can also influence the life cycleof diatoms through changes in nutrient availability, light climate, tem­
perature, and stratification, which may affect phytoplankton bloom
scale and size structure (Biggs et al., 2019). In the Southern Ocean, thedominant genus Fragilariopsis spp. is well-described for climate recon­
struction and estimating sea-ice extent because its cell size relates
strongly to environmental conditions (Cortese and Gersonde, 2007;
Crosta, 2009). F. kerguelensis is a dominant species in diatom assem­
blages, and its size increases under high iron concentrations (Cortese
and Gersonde, 2007). The size of Fragilariopsis curta is also known toincrease with colder and wider sea ice extent (Crosta, 2009). Thus,
diatom cell size is closely related to environmental changes and is an
important factor affecting the material cycle and food web (Quetin andRoss, 1985; Jacques and Panouse, 1991; Kopczynska, 1992).
In the eastern Indian sector of the Southern Ocean (80–150◦ E), the
BROKE (Baseline Research on Oceanography, Krill and the Environ­ment, study period 1996) was an extensive campaign to investigate thestanding stock of Antarctic krill (Nicol et al., 2000). In the campaign,
diatom cell density and community structure varied with longitude, andthe spatial–temporal variations could be explained by the sampling date,nutrients, trace metals, and zooplankton grazing (Waters et al., 2000). In
addition, in the western Indian sector of the Southern Ocean (30–80◦ E),
diatom assemblages change mainly through fronts and upwelling(Davidson et al., 2010). However, compared to several studies of diatom
variation conducted in the Weddell Sea, Ross Sea, and Scotia Sea (e.g.,
Jacques and Fukuchi, 1994), knowledge of the eastern Indian sector of
the Southern Ocean is limited. Considering the response by diatoms toenvironmental changes, only the distribution of F. kerguelensis can bepredicted using species distribution modeling (Pinkernell and Beszteri,2014). Because the environmental drivers restricting diatom assem­
blages and cell size are not well described, the effect of environmental
changes (i.e., warming, freshening, upwelling) on diatoms in this region
cannot be predicted.
In this study, we investigated the diatom cell density and community
structure in the eastern Indian sector of the Southern Ocean during the
austral summer of 2018/2019 to evaluate the relationship between di­
atoms and environmental factors. In addition, we measured the cell sizeof the dominant diatom species (Fragilariopsis spp.) and compared themwith environmental parameters.

2. Material and methods
2.1. Field samplings
CTD (SBE-9plus, SBE-3plus, SBE-4C) casts were conducted at 17
stations in the eastern Indian sector of the Southern Ocean (60–65◦ S,
88–150◦ E) from 15th December 2018, to 23rd February 2019, on the R/
V Kaiyo-Maru (2942 GT, Fisheries Agency of Japan) (Fig. 1). This study
was conducted as a part of a multidisciplinary ecosystem survey in theeastern Indian sector of the Antarctic (CCAMLR [Commission for theConservation of Antarctic Marine Living Resources] Division 58.4.1)
with a focus on Antarctic krill. The survey was conducted over two Legs.
Leg 1 was conducted from 19th December 2018 to 3rd January 2019 in
the area from 88◦ to 120◦ E, and Leg 2 was conducted from 27th January
to 13th February 2019, in the area from 125◦ to 150◦ E (Fig. 1, Supple­
mentary Table 1). Vertical profiles of temperature, salinity, and fluo­
rescence were measured using CTD casts. For enumeration andidentification of diatoms, water samples (500 mL) were collected fromthe surface and an optical depth of 1 % photosynthetic available radi­
ation (PAR) relative to the surface, was detected by a PAR sensor (Sat­lantic Inc., PAR-LOG ICSW), with a bucket and rosette of Niskin bottles(12 L) mounted on the CTD frame. After collection, samples were fixedand preserved in acid Lugol’s solution (final concentration 1 %). For
nutrient measurements, seawater samples (10 mL) were collected fromthe same depth for diatom cell count. The mixed layer depth was definedas the depth at which salinity was 0.05 greater than the value at 10 m
depth (Clementson et al., 1998) (Supplementary Table 1). The Southern
Antarctic Circumpolar Current Front (SACCF), Southern Boundary (SB)of ACC, and Antarctic Slope Front (ASF) were defined using the CTD and
XCTD (Tsurumi Seiki Co., Ltd., MK-130) data (cf. Yamazaki et al., 2020).
2.2. Sample analysis
Post-voyage, the samples were concentrated 25- to 46-fold using
siphon tubes (Sukhanova, 1978). Aliquots (0.3–1 mL) of the concen­
trated samples were transferred to a glass slide to count and identify theprotists (diatoms, dinoflagellates, and ciliates) in approximately 300
cells using an inverted microscope (ECLIPSE Ts2R, Nikon) at 200–400×magnification with phase contrast. Only cells with cytoplasm andchloroplast were enumerated. Cells < 5 µm in size were not counted. The
scanning electron microscope was not used for enumeration since this
could have potentially induced an underestimation of <10 µm cells.
Species identification was performed to the lowest possible level (spe­cies or genus) for the diatoms, as described by Hasle and Syvertsen(1997) and Pearce and Scott (2021). For ciliates, oligotrichs and tin­tinnids were counted. In addition, dinoflagellates and silicoflagellates
were counted at the taxon level.
Additionally, the apical length of Fragilariopsis curta (2,974 cells) andF. kerguelensis (3,465 cells) was measured using an inverted microscope(ECLIPSE Ts2R, Nikon) and a software NIS-ELEMENTS D (Nikon) withan accuracy of 0.01 µm throughout the study region.
The concentrations of nitrate plus nitrite (NO–3+NO–2) and silicate (Si2K. Matsuno et al.

Progress in Oceanography 218 (2023) 103117

Fig. 2. Horizontal distribution of hydrography parameters at the surface (left panel) and 1 %-PAR (right panel) layers in the Indian sector of the Southern Ocean
during the austral summer 2018/2019. Black dashed lines divide the areas of Leg 1 and Leg 2 (cf. Fig. 1).

(OH)4) in the seawater were determined in accordance with the Joint
Global Ocean Flux Study (JGOFS) spectrophotometric method (JGOFS,
1994) using auto-analyzer systems: a QuAAtro 2-HR system (BL-tec,
Osaka, Japan) and a Seal Analytical System (Norderstadt, Germany).
The analyzers were calibrated with reference materials for nutrient
analysis (Lots BZ, CB, and CC; KANSO Technos Co., Ltd.). As accuracy
index of the nutrients measurements, the standard deviations of thenutrient concentrations, calculated from 20 subsamples, for reference
water samples (KANSO Technos Co., Ltd.), with NO–3+NO–2 and Si(OH)4concentrations of 9.8 and 117.5 µmol L–1, were 0.3 and 1.1 µmol L–1,
respectively.

coupled using hierarchical agglomerative clustering with a complete
linkage method (an unweighted pair group method using the arithmetic
mean: UPGMA) (Field et al., 1982). Similarity percentage (SIMPER)
analysis was performed to determine which species contributed to the
top 50 % of total abundance for each group. A species diversity index (H́ )in each group was calculated using the equation:/∑ /H́ = −n Ni × lnn Ni
where n is the abundance (cells L-1) of ith species, and Ni is the total
protist abundance (cells L-1) in the group (Shannon and Weaver, 1949).
The effects of different water zones (southern, subpolar, and conti­
nental zones) on the protist community were tested using permutational
multivariate analysis of variance (PERMANOVA). A distance-based
linear modeling (DistLM) and a distance-based redundancy analysis(dbRDA) were performed to reveal the relationship between environ­mental parameters and the protist community. To remove multi­
collinearity among the environmental parameters (mixed layer depth,
PAR, temperature, salinity, fluorescence, nutrients (NO–3+NO–2 and Si(OH)4), and TSM), variance inflation factors (VIF) (Zuur et al., 2009)were calculated. Because all VIF values were below 5, none of the pa­
rameters were removed for the subsequent analysis. All environmental
parameters were normalized, and DistLM was run with a dbRDA plot by
combining the resemblance matrix (based on Bray–Curtis similarities
between the abundances of protist species in the samples from both
surface and 1 %-PAR layers) and the hydrographic variables. To run
DistLM, selection procedures consisting of Step-wise, AICc (Akaike

2.3. Data analysis
To evaluate the sea ice melting date at each station, AMSR2(Advanced Microwave Scanning Radiometer 2) and SSMIS (Special
Sensor Microwave Imager/Sounder) data were obtained from the Arctic
Data archive System (ADS, https://ads.nipr.ac.jp/). Time since sea-ice
melt (TSM), defined as the period between the last day on which thesea ice concentration dropped below 15 % and the sampling date, wascalculated using these data.
To reduce the bias for abundant species, the cell density data (X: cells√̅̅̅̅L-1) for each taxon/species were transformed to 4 X prior to cluster
analysis (Quinn and Keough, 2002). The similarities between samples
were examined using the Bray–Curtis index based on the differences in
species composition. To group the samples, the similarity indices were3

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Progress in Oceanography 218 (2023) 103117

Fig. 3. Horizontal distribution of protist abundance in the Indian sector of the Southern Ocean during the austral summer 2018/2019.

information criterion corrected for small samples), and 999 permuta­
tions were used. Data were analyzed using Primer 7 software (PRIMER-E
Ltd., Albany, Auckland, New Zealand). To identify potential indicatorspecies in the groups that resulted from the cluster analysis, the program
Indicator Value (IndVal) was used for each species (Dufrêne and Leg­
endre, 1997).
Differences between sampling depths (surface vs. 1 % PAR layer) or
among clustering groups on cell size of the dominant Fragilariopsis spe­
cies were compared by Mann–Whitney U test and the max-t method witha heteroscedastic consistent covariance estimation (HC3) (Herberichet al., 2010). The tests were conducted using R software with the
packages “multcomp” and “sandwich” (version 4.1.2, R Development
Core Team, 2021). The relationship between the diatom size and envi­
ronmental factors was analyzed using generalized additive modeling(GAMs) in R. The size data at all layers in all stations were combined foreach species to run the GAMs.

The size structure of Fragilariopsis spp. was treated as a Tweedie
distribution in the GAMs. A full model of GAMs with cell size as a
response variable, and environmental parameters (temperature, nutri­ents (NO–3+NO–2 and Si(OH)4), and TSM) as explanatory variables wasconstructed (i.e., Size ~ s(Temperature) + s(nitrate + nitrite) + s(sili­cate) + s(TSM)). Since all stations (except three stations where CTD casts
were conducted around mid-night) showed over 2 mol m− 2 d-1 PAR(average 14.6 mol m− 2 d-1) at 1 % PAR layer, diatoms at the layer could
produce at low level (Marañón et al., 2021). Due to that, we used the cellsize data from the surface and 1 % PAR layers in GAMs. The environ­mental parameters were chosen because of suggested influences on di­
atoms cell size (cf. Cortese and Gersonde, 2007; Crosta, 2009) andavoidance to complicate the model. All statistical analyses were per­formed using R software with the package “mgcv” (version 4.1.2, R Core
Team, 2021).

4

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Progress in Oceanography 218 (2023) 103117

Fig. 4. Results of cluster analysis based on protist abundance by Bray–Curtis similarity connected with UPGMA. Five groups (A–E) were identified with the similarity
at 64 % (dashed lines) (a). Numbers in parentheses indicate the number of stations included in each group. “Out” is defined that only one sample was included in thegroup. Mean abundance and species composition of each group (b). Geographic distributions of the five groups identified from Bray–Curtis similarity based on protist
abundances in the Indian sector of the Southern Ocean during the austral summer 2018/2019 (c). SACCF: Southern Antarctic Circumpolar Current Front, SB:
Southern Boundary of Antarctic Circumpolar Current, ASF: Antarctic Slope Front (Yamazaki et al., 2020).

3. Results

Cluster analysis for abundance classified the protist assemblage into
five groups (A–E) with 64 % similarity (Fig. 4a). Group A was observedin the southern area and characterized by the lowest abundance anddominance by F. curta (47 % in abundance) (Fig. 4). Group B occurred at
the surface in the southeastern area (St. 99 and 127), and Fragilariopsis
spp. (including all Fragilariopsis species) dominated up to 75 % of thegroup.
The largest group C was observed in the northern and eastern areas,
with the highest number of species characterized by SIMPER (Table 1).
Chaetoceros spp. and F. kerguelensis were 32 and 19 % in abundance,
respectively. Group D was observed in the western area with a relatively
low abundance. Group E, seen only at St. 136 and 147, exhibited thehighest abundance with the dominance of 43 % in Nitzschia spp. (Fig. 4,
Table 1). Relative high diversities were seen in groups C and D than in
the other groups (Table 1).
The PERMANOVA analysis revealed that the water zone significantly
did not influence the protist community composition (Supplementary
Table 3). Each protist assemblage was roughly separated in the dbRDA
plot (Fig. 5). Groups A and B were distributed in close locations,
respectively, but groups C and D showed broader distributions (Fig. 5).
As the best solution in DistLM, three environmental parameters wereselected from eight parameters (i.e., mixed layer depth, PAR, tempera­ture, salinity, fluorescence, nutrients (NO–3+NO–2 and Si(OH)4), andTSM), and these accounted for 38.7 % of the protist variation (Table 2).
In the results, the two variables were categorized as nutrients(NO–3+NO–2 and Si(OH)4), and the remaining variable was fluorescence(Table 2).

3.1. Hydrography
Except for St. 39, TSM ranged from 5 to 116 days and was higher in
the northern area (Supplementary Table 1). The mixed layer depth wasshallower in the northern area during Leg 1 (except at St. 39), whereas it
was deeper in the southern area, particularly in Leg 2 (Supplementary
Table 1). Temperature showed a similar spatial pattern in both layers,
with cold water observed in the western and inshore areas (Fig. 2).
Salinity, however, exhibited different spatial variations between thelayers; fresh water was observed in the western area at the surface, but
not at the 1 %-PAR layer. High fluorescence was observed in the easternarea in both layers, and the maximum (4.27–5.61) was observed at St.
157. Nutrients (NO–3+NO–2 and Si(OH)4) showed a clear latitudinal trend
and were high in both layers in the inshore area.
3.2. Micro-protists
The abundance of the protists ranged from 8.7 × 104 to 1.7 × 106 and1.8 × 104 to 2.1 × 106 cells L-1 at the surface and 1 %-PAR, respectively(Fig. 3). Diatoms were the dominant taxa in the study region (Fig. 3,
Supplementary Table 2). In diatom distribution, the centric species wereabundant in the offshore area, while pennate diatoms were dominant in
the eastern area, especially St. 136 and 147 (Fig. 3). A total of 40 diatom
species belonging to 21 different genera were identified (Supplementary
Table 2). Dinoflagellate abundance was one order of magnitude lower
than diatoms with a heterogeneous distribution. Ciliate abundance was
low throughout the study period. Fragilariopsis spp. was the dominantgenus, constituting 28–80 % of the protist assemblages. At the species
level, F. curta was the most dominant species in ten samples, andF. kerguelensis was dominant in four samples. High abundances of themwere observed offshore in the eastern area (Fig. 3).

3.3. Size structure in Fragilariopsis
Compared to the size between PAR levels, F. curta did not show
significant differences (Table 3, Fig. 6). But in 18–21 µm, more F. curta
were observed in the surface (506 cells) than in the deep layer (3935

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Progress in Oceanography 218 (2023) 103117

Table 1
Mean abundance of all taxa and diversity of microplankton in the Indian sector of the Southern Ocean during the austral summer 2018/2019. The five regions wereidentified from a cluster analysis of protist abundance using a Bray–Curtis similarity connected with UPGMA (cf. Fig. 4). Bold indicates IndVal of greater than 25 % forthat group. *Represents top 50 % of species in each group according to SIMPER analysis. Number in () represents N, number of sampling stations.
Taxa
Centric diatoms
Asteromphalus hookeri
Chaetoceros atlanticus
Chaetoceros bulbosus
Chaetoceros castracanei
Chaetoceros concavicornis
Chaetoceros convolutus
Chaetoceros curvisetus
Chaetoceros dichaeta
Chaetoceros neglectus
Chaetoceros peruvianus
Chaetoceros radicans
Chaetoceros simplex
Chaetoceros spp.
Corethron inermeCorethron pennatum
Dactyliosolen antarcticus
Guinardia cylindrus
Leptocylindrus danicus
Neomoelleria antarctica
Odontella weissflogii
Proboscia alata
Proboscia truncata
Rhizosolenia spp.
Thalassiosira spp. < 20 µm
Thalassiosira spp. > 20 µm
Pennate diatoms
Amphiprora belgicae
Banquisia belgicae
Fragilariopsis curta
Fragilariopsis cylindrus
Fragilariopsis kerguelensis
Fragilariopsis ritscheri
Fragilariopsis separanda/rhombica
Fragilariopsis spp.
Haslea trompii
Membraneis challengeri
Navicula spp.
Nitzschia spp.
Plagiotropis gaussii
Pseudonitzschia spp.
Trichotoxon reinboldii
Dinoflagellates
Tintinnid ciliates
Oligotrich ciliates
Silicoflagellates
Total microplankton
Shannon–Weaver diversity

Abundance (cells L-1)
A (6)

B (2)

C (11)

D (9)

E (3)

257
357
0
0
585
925
285
583
3048
103
0
0
562
0
730
227
347
157
0
183
1633
0
1029
3089
862

0
0
0
0
0
5323
0
265
794
0
0
0
0
0
2389
0
0
1066
0
0
0
0
1323
11,184*1058

3097
68,6376738
021,054
1927
6038
44,967
20,3935274
05584
152,796*
1122
3381
24,882
52,712*
868
1133
494
0
0
621
39,151*
11,439

504
1478
0
358
2011
833
808
3854
15,591*
2007
5912
827
11,891*
1023
1312
1493
7145*
1510
370
482
406
0
1614
9316*
4212

728
1588
0
0
1720
3000
0
18,858*
8183
0
0
2560
24,501
0
5427
0
2580
1280
1280
4035
860
1720
2008
18,457
13,2100044,630*
575
1749
464
3433*
9172*
909*
0
1083
9153*
625
4779*
41
2371*
0
496
201
94,6411.90

0
0142,516*
1604
0
0
1852
161,974*
2926
0
2381
61,853*
0
2389
0
7960*
1066
1595
0
411,5171.70

0601
96,523*661
196,894*
16,556*96,000*27,0593763
982
10,94812,512
1844
80,524*
2970
6714
187
850
1044
1,028,942
2.45

878
0
44,340*1183
24,609*4813
21,513*23,1951936
54
3798
27,364*583
19,359*
824
4053
89
447
1050
255,0452.60

0860
215,164*
17,1175999
28,44038,027*
90,152*1280
08867
459,484*
7299
66,587*
0
5315
0
0
1588
1,058,172
1.89

cells). There is also a bit larger F. curta in 26–28 µm (123 cells [100%-PAR] vs. 92 cells [1 %-PAR]), which induces an insignificant differ­ence in mean size between PAR levels. In contrast, smaller cells of
F. kerguelensis were observed in the deeper layer (Table 3, Fig. 6). Intergroup comparison of the size for both species showed similar results,
thus, larger cells were found in the southern stations (clustered in groups
A and B) while smaller cells were seen in the northern stations (clusteredin group C) (Table 3). As a result of the spatial variation in cell size forthe species analyzed by GAMs, F. curta had significant relationships withtemperature, NO–3+NO–2, Si(OH)4 and TSM, and F. kerguelensis with sil­
icate and TSM (Fig. 7). The relationships appeared to be similar for both
species; the size showed the highest peak at 60 days in TSM, decreased
until 90–100 days, and then recovered (increased) at 110 days. For eachspecies, greater than 2 ◦ C positively influent the size of F. curta. Silicatesroughly negatively relate to the size of both species.

4. Discussion
4.1. Spatial variation of diatom blooms
In the eastern Indian sector of the Southern Ocean, the phyto­plankton generally blooms from January to March, with a delay intiming in the southern area. Blooms at 64◦ S typically appear in January/
February, while further south at 66◦ 30′S, the blooms appear fromFebruary to March (Gomi et al., 2005). The highest abundance of di­atoms was observed at St. 157 in mid-February (Fig. 3), in conformity
with those observed by Gomi et al., 2005. However, the stations in thesouthern area exhibited low fluorescence with low cell density, even athigh nutrient concentrations (Figs. 2 and 3). Generally, a deep mixed
layer prevents phytoplankton from maintaining a suitable depth foractive growth (Tilzer and Dubinsky, 1987; Samyshev, 1991). From
another viewpoint, deep phytoplankton assemblages represent verticalflux in the biogeochemistry cycle with very little production (Lafondet al., 2020). As deeper mixed layer depths (48–63 m) were observed at
6

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Progress in Oceanography 218 (2023) 103117

Fig. 5. dbRDA plot of the five groups with environmental parameters. The parameters were selected by procedures consisting of Step-wise, AICc (Akaike information
criterion corrected for small samples) and 999 permutations were used. The direction and length of the lines indicate the relationship between groups and thestrength of the relationship. Flu: fluorescence, NO–3+NO–2: nitrate + nitrite, and Si(OH)4: silicate.
Table 2
Summary of the DistLM sequential tests. Selection procedures consisting of Step-wise, AICc (Akaike information criterion corrected for small samples) and 999
permutations were used. Results of the model with the lowest AICc values for each response variable. SS: sum of squares, Prop.: proportion of variance explained byeach predictor variable, Cumul.: cumulative proportion of variance explained by each predictor variable, Res.df: residual degrees of freedom.
Variables

AICc

SS

Pseudo-F

P values

Prop.

Cumul.

Res.df

Si(OH)4
NO–3+NO–2
Fluorescence

227.78225.31
223.115556.33249.72754.1

7.32744.79374.5246

0.001
0.001
0.001

0.18632
0.10897
0.092354

0.18632
0.295290.38764432
31
30

Table 3Comparison of cell size of Fragilariopsis species between PAR level (surface vs. 1 % PAR) or among groups in the Indian sector of the Southern Ocean during the australsummer 2018/2019.
SpeciesComparison between layers

Comparison among groups

Mean cell size (µm)

U testSurface

1 %-PARdft valuep valueGroups
A

B

C

D

E

Max-t test

F. curta

21.3 ± 6.7

2972− 0.47

0.638422.8 ± 7.1

22.6 ± 6.4

24.0 ± 7.7

C3

D2

B1

A1

E1

32.5 ±
12.0

3463− 4.9370.000137.3 ±
14.4

51.8 ±
18.3

19.3 ±
5.5
29.6 ±
9.8

21.1 ± 6.4

F. kerguelensis

21.4 ±
6.9
30.7 ±
9.7

32.7 ±
10.7

30.3 ±
10.0

C3

E2

D2

A1

B1

these stations (e.g., St. 63, 127) compared to those (14–30 m) in offshore
stations (Supplementary Table 1), phytoplankton growth was limited bydeep mixing. If the mixed layer becomes shallower, phytoplanktons
bloom will potentially occur in the southern area, whereas offshore as­semblages are under phytoplanktons bloom in the eastern area from120◦ E due to fluorescence distribution (Tozawa et al., 2022).
During the 2018/2019 cruise, high cell abundances were observed in
the area east of 120◦ E (Fig. 3). A previous study, however, indicated the
opposite pattern of the east–west variation on analysis of diatom-Chl aby high-performance liquid chromatography and CHEMTAX (a programfor estimating class abundances from chemical markers) (Wright andvan den Enden, 2000). It was higher in the western area (90–120◦ E) in1996 under the BROKE project (Wright and van den Enden, 2000). This
inter-annual difference in the spatial distribution of diatoms could be

explained by sampling date, environmental conditions, and zooplankton
grazing impact. Basically, in the early period of the phytoplankton
growing season (spring to autumn), the phytoplankton community
quickly changes in a few weeks due to high growth rates with rapid
species succession (Quéguiner, 2013). Regarding the sampling date, thisstudy was conducted approximately one month earlier than that of the
BROKE cruise (from 29th January to 21st March). The 1-month differ­ence might have affected the spatial difference in diatoms due to therapid shrinking of sea ice from November until mid-February in theSouthern Ocean.
Comparing the hydrography between the western (88–120 ◦ E) andeastern (125–150◦ E) areas in 2018/2019, the western area had lower
salinity and shallower mixed layer depth at the surface layer (Fig. 2,
Supplementary Table 1), suggesting that sea-ice meltwater made a7

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Progress in Oceanography 218 (2023) 103117

4.2. Relationship between diatom assemblages and hydrography
Throughout the study region, low abundances were observed ingroups A and B in the southern area, but high abundances were seen ingroups C and E (except group D) in the offshore area (Fig. 4). It seems
related to fronts, but no significant relation was detected in our study(Supplementary Table 3). On the other hand, the north–south difference
in diatom assemblages might be caused by the mixed layer depth (asstated above), sea ice extent, and nutrients. Among the nutrients, silicate
was selected as the significant parameter in dbRDA and not TSM (Fig. 5).
In general, sea ice melting controls the onset of phytoplankton
blooms in the Southern Ocean (El-Sayed and Taguchi, 1981). After sea
ice melts, the supply of iron from the ice stimulates phytoplankton
growth (Sedwick and DiTullio, 1997), even in diluting the macronutri­ents (Kanna et al., 2014), resulting in its blooming in the stratified
surface layer (El-Sayed and Taguchi, 1981; Marra and Boardman, 1984;
Smith and Nelson, 1985; Fryxell and Kendrick, 1988). Based on ironfertilized experiments in the Southern Ocean, iron mediate increases
in phytoplankton growth, chlorophyll a, and primary production (Boydand Law, 2001). From the viewpoint of seasonality, the phytoplankton
bloom shifted from north to south in association with the time of meltingof sea ice (Sokolov and Rintoul, 2009; Iida and Odate, 2014). In blooms,
the nano-sized haptophyte Phaeocystis antarctica was predominant byforming colonial blooms in the marginal sea ice zone and ice edge (e.g.,
Davidson et al., 2010). As we did not analyze the nanoflagellates (i.e.,
P. antarctica), the contributions were unclear in this study. In contrast,
ice-associated diatoms (Amphiprora spp., Neomoelleria antarctica, andOdontella weissflogii, cf. Gomi et al., 2005) were not abundant in groups
A and B (Table 1). A similar group was observed at approximately 63◦ S
from 17th February to 13th March 2000, and the community is weakly
related to the ice edge (Gomi et al., 2005). Thus, diatom assemblages arestrongly related to nutrient distribution during summer but weakly
associated with sea ice variation.
In the offshore region, group D was observed in the western area,
whereas group C was widely distributed in the eastern area (Fig. 4).
Group D was characterized by low abundances and dominance ofChaetoceros spp. and Fragilariopsis spp. (including F. curta andF. kerguelensis), and was considered to be an intermediate community
between groups A and C (Table 1). As mentioned above, the group may
have been induced by sea ice meltwater on the surface. In contrast,
group C was characterized by the dominance of Chaetoceros spp. andF. kerguelensis (Table 1). A similar observation on Chaetoceros dichaeta
and Chaetoceros neglectus as dominant species in the Indian sector of theSouthern Ocean is also on record (Gomi et al., 2005; Davidson et al.,2010). A planktonic diatom (F. kerguelensis) is also known to be abun­
dantly present in the offshore region of the Southern Ocean (Iida andOdate, 2014) and around the polar frontal region (47–50◦ S) in the
Atlantic sector during austral spring (de Baar et al., 1997). Since asimilar diatom assemblage occurred as an offshore group in ACC in thewestern Indian sector (30–80◦ E) between January and March 2006
(Davidson et al., 2010), group C was considered a typical offshore
community in the Southern Ocean.
Although spatial resolution in sampling stations was uneven in thisstudy, a north–south difference of diatom assemblages was observed(Fig. 4c). Exceptions were high-abundance groups C and E found at St.
79 and 147 in the southern area (Fig. 4). This unique phenomenon isrelated to the surface current and upwelling (Wright and van den Enden,
2000). These stations are located in the shelf-break region (Fig. 1),
where the bottom depth varies from 500 to 1500 m. A narrow westward
slope current runs on the surface north of the shelf break, forming gyresthat close at 115–120◦ E, indicating the presence of the southward cur­rent (Nicol et al., 2000). Additionally, multi-cyclone eddies transportheat poleward along the shelf break, based on the 2018/2019 reports ofthe same cruise and satellite observations (Hirano et al., 2021). There­
fore, group C was potentially extended to the southern area by acontinuous southward current and/or eddy (Nicol et al., 2000; Hirano

Fig. 6. Size frequency of Fragilariopsis species in the Indian sector of theSouthern Ocean during austral summer 2018/2019. Size frequency was sum­
marized every 1 µm bin for each layer. Solid grey and black lines represent thedifferent sampling layers. Dashed grey and black lines are mean cell size foreach layer (cf. Table 3).

shallower mixed layer. Because sea ice contains low levels of macro­
nutrients (Clarke and Ackley, 1984; Dieckmann et al., 1991), diatoms
could be trapped in the low-nutrient ice melted water at the surface,which would have restricted their growth. This was reflected in the
difference in the protist assemblages; low-abundance group D occurred
locally at the surface layer in the western area (Fig. 4). Comparison of
the hydrographic features between groups C and D in dbRDA showedthat group C was found at areas with low silicate (mean 37.35 µmol/L)and high fluorescence (mean 3.21) areas; conversely, group D was seen
at areas with relatively high silicate (mean 44.82 µmol/L) and low
fluorescence (mean 0.80) (Fig. 5). Therefore, since diatom assemblages
could increase with the consumption of rich nutrients during the study
period, high fluorescence and low nutrients in the eastern area wereobserved as a result of diatom bloom. Reflecting the active biologicalproduction in our study, higher pCO2 and lower macronutrients werereported compared to the BROKE survey in 1996 (Tozawa et al., 2022).
As a potential consumer of diatoms, pteropods were abundant in themacrozooplankton community in the western area on the same cruise(Urabe et al., under review). Since pteropods can efficiently feed on
small particles, including phytoplankton (Gilmer, 1972), protist as­
semblages may have been feeding on them, resulting in a low cell den­sity occurring at group D stations in the western side of the samplingarea (Fig. 4). The salps, yet another important filter feeder to diatoms,
showed significant inter-annual changes between 1996 and 2018/2019(Urabe et al., under review). Salp blooms observed in the eastern area in1996 (Hosie et al., 2000) affected phytoplankton assemblages by
feeding, resulting in low phytoplankton cell density. In contrast, almost
no salp species were observed in 2018/2019 (Urabe et al., under re­view). Thus, in the eastern area, phytoplankton assemblages were notunder grazing pressure by salps in 2018/2019, resulting in high diatom
bloom.
8

K. Matsuno et al.

Progress in Oceanography 218 (2023) 103117

Fig. 7. Results of GAMs based on the size of two Fragilariopsis species with environmental parameters. Dashed lines indicate no effect. TSM: time since melt. *: p <0.05, ***: p < 0.001.

9K. Matsuno et al.

Progress in Oceanography 218 (2023) 103117

et al., 2021), supporting the same diatom community. Additionally,
upwelling frequently occurs when the slope current hits the slope andphytoplankton blooms are stimulated, resulting in high chlorophyll alevels (Strutton et al., 2000; Wright and van den Enden, 2000). Thus, thehigh-abundance group E was represented by the supply of rich nutrientsby upwelling.

by making auxospores almost simultaneously. Thus, sea ice variations(e.g., sea ice extent and timing of melt) are pivotal factors that affecttheir life cycle. The smaller cell size also indicated a phytoplankton
bloom region. But this study did not measure temporal variation in size
directly. For future work, the temporal variation of cell size and growthrate of these species should be investigated under controlled conditionsin the laboratory. It will improve our understanding of the response ofprotist assemblages to climate change in the Southern Ocean.

4.3. Size variation of Fragilariopsis spp. related with hydrography

5. Conclusion

Fragilariopsis spp. is dominant in phytoplankton assemblages in theSouthern Ocean (Samyshev, 1991). The genus F. curta is an ice-algae
species (Lizotte, 2001) and is dominant in the marginal ice zone andunder/in the sea ice in the Southern Ocean (Garrison et al., 1987;
Garrison and Buck, 1989; Kang and Fryxell, 1993; Hegseth and von
Quillfeldt, 2002, Armand et al., 2005). The abundance and cell size ofthe species increase in colder and wider sea ice extent years (Crosta,
2009). In GAMs, significant relationships in cell size variation weredetected with temperature (Fig. 7), but the relationship followed an
opposite pattern compared to the previous report, caused by different
timescales (several thousand years in Crosta, 2009 vs. one season in thisstudy). Cell size exhibited significant relationships with nutrients, but
the effect was not greater than that of temperature and TSM (Fig. 7). In
contrast, TSM showed a relationship with the species’ life cycle. In
general, diatom cell size decreased until the sexual stage with cell di­visions; after the formation of auxospores via sexual reproduction, di­atoms eventually recovered their size. This indicated that F. curta
continued cell division from 60 to 90 days in TSM and then recovered its
cell size after 90 days in TSM. Additionally, based on the inter-groupcomparison, the cell size was significantly smaller in group C than in
the other groups (Table 3); this means the F. curta actively grew in thegroup under the bloom.
Fragilariopsis kerguelensis is an important species contributing to the“opal belt” in the Southern Ocean (Zielinski and Gersonde, 1997; Cor­tese and Gersonde, 2007). According to Lafond et al. (2021), since
F. kerguelensis below the mixed layer is mostly detrital (empty, broken or
crunched), this species significantly contributes to vertical flux inbiogenetic silica in the Southern Ocean. As vertical variation in thespecies, higher abundance was seen offshore in the eastern area at 1 %PAR layer with smaller cells (Fig. 3, Table 3). We did not count the
detrital cells, but the result represents a remnant stock with very little insitu production. As this species has been dominant in diatom assem­
blages over the long term and frequently dominates in sediment, it has
been well-studied as a biological indicator in paleobiology (Cortese andGersonde, 2007; Crosta, 2009; Shukla et al., 2013; Kloster et al., 2018).
Responding to environmental factors, F. kerguelensis exhibits an opposite
pattern to F. curta; thus, their abundance increases in warm and lower
sea-ice years (Crosta, 2009). This species’ abundance and cell size aresuggested to be increased by iron from sea ice (Cortese and Gersonde,2007). In incubation experiments, higher iron concentrations produced
larger cell sizes and higher growth rates (Timmermans and van derWagt, 2010). Additionally, high iron concentrations stimulate the for­mation of auxospores, as revealed by field iron fertilization experiments(Assmy et al., 2006). Unfortunately, we did not measure iron concen­
tration in this study, but hypothesized that the area in the lower TSM has
detectable effects (i.e., larger cell size in the lower TSM) by iron supply
from sea ice melt. As shown in the GAMs, a positive effect of TSM on cellsize was observed in the lower TSM (Fig. 7), which suggests that ironsupply from the sea ice melt stimulates the formation of larger cells andsexual reproduction process in F. kerguelensis as well as F. curta. Inter­estingly, the relationships between size and TSM were similar in F. curta
and F. kerguelensis (Fig. 7), suggesting that F. kerguelensis possibly
recovered their cell size by forming auxospores after 100 days in TSM.
In conclusion, the two dominant Fragilariopsis species had a signifi­
cant relationship with TSM, although their biological features differed in
geographical distributions and suitable temperatures. This indicates thatthese species grow actively after the sea ice melts and recover their size

This study describes the spatial variation in protist assemblages inthe eastern Indian sector of the Southern Ocean during the australsummer of 2018/2019. High chlorophyll a and cell density wereobserved in the eastern area from 120◦ E, which differs from the patternreported in 1996. This inter-annual change was excluded by interannual differences in the sampling periods, nutrients, and zooplankton
grazing pressure. North–south variation in protist abundance was
explained by the presence of silicate, whereas sea ice variation did not
influence it explicitly. Clustering groups were also well related to nu­
trients; however, locally, offshore groups were extended by southwardcurrents and poleward eddies. The size variations in the two dominantFragilariopsis species were significantly affected by the number of days
after the melting of sea ice. In the eastern Indian sector of the Southern
Ocean, sea ice changes do not affect the protist community level but
affect the life cycle level of diatoms during summer. The findings will
help the selection of critical environmental parameters for predicting
diatom distribution, species composition, and size under climatechange. Future studies should focus on the nutrients (including iron)cycle rather than sea ice variation to monitor phytoplankton
assemblages.
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.
Data availability
Data will be made available on request.
Acknowledgments
We are deeply grateful to the officers, crew, and researchers onboard
R/V Kaiyo-Maru for their assistance with biological sampling. The
Kaiyo-Maru survey was supported by the Institute of Cetacean Research,
the Japan Fisheries Research and Education Agency, and the Fisheries
Agency of Japan. This work was partly supported by a Grant-in-Aid for
Challenging Research (Pioneering) JP20K20573 to AY; Scientific
Research JP20H03054 (B) to AY, JP19H03037 (B) to AY, JP21H02263(B) to KM, JP17H01483 (A) to AY, and JP17H04715 to DN from theJapanese Society for the Promotion of Science (JSPS); and the Joint
Research Program of the Institute of Low Temperature Science, Hok­kaido University.
Appendix A. Supplementary material
Supplementary data to this article can be found online at https://doi.
org/10.1016/j.pocean.2023.103117.
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