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Limnol. Oceanogr. 69, 2024, 2760–2774
© 2024 The Author(s). Limnology and Oceanography published by Wiley Periodicals LLC
on behalf of Association for the Sciences of Limnology and Oceanography.
doi: 10.1002/lno.12703
DNA metabarcoding reveals distinct bacterial and phytoplankton
assemblages in the Agulhas Current and the adjacent coastal shelf
Ross-Lynne A. Gibb ,
1,2,3,4
Danielle K. L. Botha ,
2
Siddarthan Venkatachalam ,
1,2,5
Mfundo Bizani ,
3,4
Thomas G. Bornman ,
2,3,4
Rosemary A. Dorrington
1,2
*
1
South African Institute of Aquatic Biodiversity, Makhanda, South Africa
2
Department of Biochemistry and Microbiology, Rhodes University, Makhanda, South Africa
3
South African Environmental Observation Network (SAEON), Elwandle Coastal Node, Gqeberha, South Africa
4
Institute for Coastal and Marine Research (CMR), Nelson Mandela University, Gqeberha, South Africa
5
Arctic Ecology and Biogeochemistry Division, National Centre for Polar and Ocean Research, Ministry of Earth Sciences,
Vasco-Da-Gama, Goa, India
Abstract
The Agulhas Current is a globally important western boundary current that influences numerous processes
(e.g., upwelling, biogeochemical fluxes and distribution of marine taxa) in the southwestern Indian Ocean. The
oceanographic processes of the Agulhas Current are well understood, but precisely how they influence coastal
ecosystem productivity remains to be elucidated. In the present foundational study, we characterized the bac-
terial (16S rRNA gene) and phytoplankton (chloroplast 16S rRNA, rbcL, and eukaryotic 18S rRNA genes) com-
munity structures of the Agulhas Current system using a metabarcoding approach. All four markers provided
consistent data on the bacterial and phytoplankton communities in the Agulhas Current and coastal sites.
The study revealed distinct, conserved communities and similar patterns of dominance by taxa adapted to oli-
gotrophic conditions within the Agulhas Current, sampled 2 yr apart. By contrast, there was significant vari-
ability in taxonomic diversity and abundance of phytoplankton communities in the adjacent coastal waters
that could be linked to localized upwelling. While the Agulhas Current bacterial and phytoplankton commu-
nitieswerediverseandrepresentedmanyfunctionalgroups,thecoastalsitesweremorediatom-dominated
and included genera typically associated with upwelling, for example, Thalassiosira spp.Basedontheirrelative
abundance profiles, phytoplankton communities were more responsive to environmental variability than bac-
teria and may therefore prove more useful in linking ecosystem dynamics to environmental variability in
marine systems.
Western boundary currents are important oceanographic
features that connect equatorial regions to higher latitudes
(Todd et al. 2019). The largest of these is the Agulhas Current,
located in the southwestern Indian Ocean, that transports
heat and salt from tropical latitudes toward the Southern
Ocean (Bryden et al. 2005). The Agulhas Current is fed by
tropical Indian Ocean waters at the convergence of the East-
ern Madagascar Current and a southward flow in the
Mozambique Channel as well as the South West Indian
Ocean sub-gyre (Lutjeharms 2006). The Agulhas Current
travels southwest to the tip of the Agulhas Bank where it
loops to the east and feeds back into the Indian Ocean sub-
gyre (Beal et al. 2011). At the point of retroflection, the shed-
ding of eddies (known as Agulhas Rings) transport heat and
salt into the Atlantic Ocean (Beal et al. 2011). The Agulhas
Current transports more water than other western boundary
*Correspondence: r.dorrington@ru.ac.za
Additional Supporting Information may be found in the online version of
this article.
This is an open access article under the terms of the Creative Commons
Attribution-NonCommercial License, which permits use, distribution and
reproduction in any medium, provided the original work is properly cited
and is not used for commercial purposes.
Author Contribution Statement: RAG: Conceptualization (equal);
Sample collection (equal); Data curation (lead); Visualization (lead);
Writing –original draft preparation (lead); Writing –review and editing
(equal). DKLB: Data curation; Visualization; Writing –original draft prepa-
ration (equal); Writing –review and editing (equal). SV: Sample collection
(equal); Data curation (equal), Writing –review and editing (equal). MB:
Data curation (equal); Writing –review and editing (equal). TGB: Concep-
tualization (equal); Writing –review and editing (equal); Supervision
(equal); Funding acquisition (lead). RAD: Conceptualization (lead); Sample
collection (lead); Writing –review and editing (equal); Supervision (lead);
Funding acquisition (lead).
2760
currents (Beal et al. 2015; McMonigal et al. 2020)andisan
important regulator of the Indian Ocean climate.
Agulhas Current water circulation is important in driving
oceanographic processes such as biogeochemical fluxes, ther-
mohaline regulation (Lutjeharms 2006), and upwelling pro-
cesses (Lutjeharms 2006; Malan et al. 2018)alongthe
South African coast. The Agulhas Current influences coastal
regions by forcing cold, nutrient-rich water onto the conti-
nental shelf (known as upwelling) or through eddies (Bryden
et al. 2005). These meanders or eddies are usually recorded
near Durban, South Africa (where the continental shelf is
narrow) and travel further south along the Agulhas Shelf to
Port Alfred and Algoa Bay, where they are known as Natal
Pulses (Goschen et al. 2015). Upwelling is driven by the topo-
graphical forcing of the current in conjunction with wind
stress (Lutjeharms 2006).
The Agulhas Current waters are oligotrophic and when the
current intrudes onto the continental shelf it is hypothesized
to suppress primary productivity (Schumann et al. 2005). How-
ever, the Agulhas Current can also enhance primary productiv-
ity on the shelf through nutrient-rich upwellings (Probyn et al.
1994; Demarcq et al. 2003), which have been recorded around
regions such as Richards Bay (Lamont et al. 2014;Lamontand
Barlow 2015) and between Port Alfred and Algoa Bay (Goschen
et al. 2015). Changes in productivity have a knock-on effect up
the food chain and ultimately influence commercially impor-
tant fish species (Krug et al. 2014). At the base of these food
webs are microbial communities, including phytoplankton and
bacteria, the productivity of which relies on the nutrients
upwelled into the photic zone (Lamont and Barlow 2015).
Long-term observations over the past 20 yr have revealed
that the Agulhas Current is broadening due to an increase in
the occurrence of meanders and elevated eddy kinetic energy
(Beal and Elipot 2016;McMonigaletal.2020). The increased
occurrence of meanders results in a cooling of the Agulhas
Current (McMonigal et al. 2020). Deepening of the
Agulhas Current can also lead to a cooling of the water trans-
ported to the Southern Ocean and the Atlantic Ocean
(McMonigal et al. 2020). At the same time, warming of sur-
face current water has been observed (Rouault et al. 2009)
and all these changes have implications for the biota in the
region. Tropical species carried by the Agulhas Current could
persist in more southerly regions causing a shift in the commu-
nity structure and create the potential for more frequent harmful
algalblooms(HABs)suchastheonerecordedinAlgoaBayin
2014 (Whitfield et al. 2016). The 2014 HAB was dominated by a
(sub)tropical species, Lingulodinium polyedra,thathaspersistedin
the region ever since (Whitfield et al. 2016; Bizani et al. 2023).
Similarly, warmer and more oligotrophic conditions are causing
shifts within microbial communities to smaller cell sizes
(i.e., cyanobacteria, SAR11 clades) as observed in the East
Australian Current (Messer et al. 2020). This shift from a diatom-
dominated community to a more bacterial-dominated commu-
nity will have consequences for aquatic food webs.
Although the primary productivity of the Natal Bight
section of the Agulhas Current is well-studied (Barlow et al. 2015;
Barlow et al. 2020), data from the southern section is limited.
Studies have focused on chlorophyll a(Chl a) assessments (Hood
et al. 2017; Barlow et al. 2020), which provides some insight into
productivity, but only a superficialaccountofthespeciesthat
underpin the Chl aconcentrations. A metagenomics study along
the Crossroads line has provided evidence for distinct bacterial
communities within the Agulhas Current (Phoma et al. 2018).
However, the phytoplankton communities are yet to be charac-
terized and therefore there is limited understanding of the taxa
that underpin the primary productivity in the system. In
addition, bacteria are known to respond to changes in phyto-
plankton communities, for example, Bacteroidetes and
Rhodobacteria increase in abundance when there is increased
organic matter when phytoplankton abundance is high
(Lima-Mendez et al. 2015).
The identification of dominant species within the microbial
communities of the Agulhas Current system and their
response to environmental variability is key to understanding
the functioning of the marine ecosystem in the southwestern
Indian Ocean region. We hypothesized that the nutrient-poor
Agulhas Current would have different microbial communities
than the adjacent coast. Specifically, the Agulhas Current
would have communities adapted to oligotrophic conditions
(i.e., flagellates or cyanobacteria) while the coastline would be
more diatom-dominated. In this study, we tested this hypoth-
esis in a comparative study of the microbial and phytoplank-
ton communities of the Agulhas Current and adjacent coastal
areas using a combination of different genetic markers in com-
bination with environmental parameters.
Materials and methods
Sampling
The study area falls within the Agulhas bioregion, covering
coastal and open ocean waters influenced by the Agulhas Cur-
rent system (Fig. 1a). Seawater samples were collected on the
Agulhas Shelf from Hamburg, South Africa, across the Agulhas
Current along the Agulhas System Climate Array (ASCA) tran-
sect during the SEAmester cruises (Ansorge et al. 2016) of the
RV SA Agulhas II in July 2016 (ASCA16) and 2018 (ASCA18)
(Fig. 1b,c, respectively). The ASCA transect extends 300 km
offshore and cuts perpendicular across the current. Seawater
was collected from the fluorescence maximum (f
max
) at each
sampling site using a SBE 911plus CTD and Niskin rosette. In
2018, additional underway sampling of subsurface water (7 m)
was conducted on the outward bound (Depart18) and return
(Return18) legs between Cape Town, at the start of the ASCA
transect as well as along the 2018 ASCA transect (Supporting
Information Table S1).
Subsurface (7 m depth) seawater samples were collected at
each site during the 2018 cruise from the underway system
across the ASCA transect and at the f
max
(depths ranging
Gibb et al. Agulhas Current system microbial communities
2761
between 15 and 90 m depending on location; Supporting
Information Table S1). Three 500 mL replicate seawater sam-
ples were filtered onboard through 0.45 μm Whatmann (GF/F)
glass fiber filters. The filtrate was stored in acid-washed urine
specimen jars for nutrient analysis, the filter was stored in tin
foil and both were immediately frozen at 20C (onboard the
vessel) until they could be analyzed for Chl aand nutrients
(Sonnekus et al. 2017; Stirnimann et al. 2021).
Two liters of seawater were collected for filtration and sub-
sequent DNA extraction from each Niskin bottle deployed at
the CTD sampling sites during the 2016 and 2018 ASCA
(ASCA16 and ASCA 18) transects. During 2018, an additional
three replicates of two-liter seawater samples were collected
from the underway system (no CTD deployments) at each site
for filtration (ASCA 2018, Depart 2018, and Return 2018). The
seawater was filtered onboard under vacuum through 0.22 μm
nylon filters (Pall Corporation) and the samples were stored in
RNAlater
®
(ThermoFisher Scientific) at 20C.
Physico-chemical and Chl aanalysis
The nutrient samples were analyzed several months after
the end of each cruise for NO
3,NO
2,PO
3
4, SiO2
3(μmol L
1
)
on an auto-analyser (AA3, Seal Analytical) following the
methods by Strickland and Parsons (1972) and Mostert (1983).
Due to the long period that the nutrient samples were frozen
before analyses, NHþ
4was excluded from the results presented
in this study. Chl awas extracted from the filters in 95% etha-
nol for 24 h at 4C. The samples were filtered again through a
0.45 μm Whatman (GF/F) glass fiber filter, and the concentra-
tion of Chl awas measured on a double beam spectrophotom-
eter (Hitachi UH5300) at 665 nm based on the methods by
Nusch (1980). Physical data collected by the Seabird CTD (SBE
911plus/917plus) as part of the Long-Term ASCA sampling
was analyzed using the SEABird CTD software (Sea-Bird Scien-
tific, v7.26.7) and plotted in Ocean Data View (Schlitzer, Rei-
ner, Ocean data view, v5.3.0). Vertical profiles were not
included in the results as the present study aimed to compare
Fig. 1. Map of Southern Africa showing the position of the Agulhas Current and some associated water masses (a), the Agulhas Current system
(b) showing the position of the Agulhas Current (red dashes), Crossroads (referred to in literature) and ASCA transects as well as major oceano-
graphic regions. The ASCA 2016 sampling July 7–12, 2016 (c) and ASCA cruise 2018 July 17–25, 2018 (d) sites overlain by satellite sea surface
temperature imagery during the time of the sampling. The Depart 2018 samples (d, white circles) were collected on the way to the ASCA line.
Similar to ASCA 2016 (c), the ASCA 2018 sites (black circles) were orientated across the Agulhas Current. The inshore Return 2018 samples are
denoted by black triangles.
Gibb et al. Agulhas Current system microbial communities
2762
the Agulhas Current (where vertical profiles were available)
with the coastal region (where only underway sampling was
possible).
Upwelling was determined using the SAEON Long-term
ecological research (LTER) thermistor data acquired from sites
along the outer edge of Algoa Bay, by calculating the daily
temperature anomaly (Tapia et al. 2009). All physico-chemical
results can be found in Appendix S2 and Supporting Informa-
tion Figs. S1, S2.
Metabarcoding
The genomic DNA was extracted from half of each filter using
the Quick-DNA™Fecal/Soil Microbe Microprep kit (Zymo
Research, D6012) according to the manufacturer’sprotocol.For
investigating the bacterial community structure, PCR amplifica-
tion targeting the hypervariable region between V4 and V5 of
the bacterial 16S rRNA gene was carried out according to
Venkatachalam et al. (2019). To provide a comprehensive assess-
ment of the phytoplankton community structure, three different
approaches were employed (1) the chloroplast 16S rRNA
sequence data was extracted from bacterial 16S rRNA datasets,
(2) PCR amplification of the ribulose-bisphosphate carboxylase
(rbcL) gene located on the chloroplast genome was targeted using
a blended set of primers (Supporting Information Table S2),
Diat_rbcL_708F and R3. The forward primers were an equimolar
combination of Diat_rbcL_708F_1, Diat_rbcL_708F_2, and
Diat_rbcL_708F_3 while the reverse primers were an equimolar
concentration of R3_1 and R3_2 (Vasselon et al. 2017), (3) PCR
amplification targeting the hypervariable V9 region of the 18S
rRNA according to Venkatachalam et al. (2019) (Supporting
Information Table S2).
Amplicon library preparation
PCR amplicons were gel-purified and sequenced using the
Illumina MiSeq platform and resultant datasets have been
deposited as Bioproject (PRJNA694821) in the Sequence Read
Archive hosted by NCBI (https://www.ncbi.nlm.nih.gov/sra/).
Metabarcoding data for the 16S rRNA (accession:
SRX9971261–SRX9971316), 18S rRNA (accession: SRX13978140–
SRX13978195), and rbcL (accession: SRX13978199–
SRX13978273) datasets.
Bioinformatics data analysis
All curation steps of the 16S rRNA, 18S rRNA, and rbcL
sequences were conducted using the mothur software v.1.43.0
(Schloss et al. 2009) according to Venkatachalam et al. (2019).
Thereafter, sequence datasets were aligned according to their
respective reference databases and the nonspecific reads from
both ends were trimmed. Short reads and ambiguous nucleo-
tides, along with reads that belong to mitochondria and
archaea were removed from the sequence dataset. Similarly,
chimeric sequences were detected and subsequently removed
from the dataset using the VSEARCH algorithm in the mothur
software (Rognes et al. 2016). The number of sequences
removed at each step, classification details and the commands
used is provided in Supporting Information Table S3 and
Appendix S1.
Statistical data analyses
Thesoftwarepackage“zoo”(Zeileis and Grothendieck 2005)
was used in R (R Core Team 2020) for the upwelling analyses.
Non-metric multidimensional scaling (nMDS) was performed in
R using the vegan package (Oksanen et al. 2022). An ANOSIM
test was performed in R (vegan package) on each dataset to do
pairwise testing of the community data. The groups compared
in the ANOSIM analyses were ASCA16, Depart18, ASCA18,
and Return18. These groupings were selected for comparabil-
ity between the two ASCA transects, and all groups were geo-
graphically significant. All ANOSIM results are shown in
Supporting Information Table S4. Conserved OTUs were
identified by excluding all OTUs that were absent from any
of the samples. Bar plots were created using the relative
abundances of OTUs conserved across all the sites as well as
the most dominant OTUs that were not conserved across all
the sites. The taxonomic description of reads belonging to
the conserved OTUs and the dominant OTUs (top 20 OTUs)
were further identified using NCBI-BLAST analysis. A canoni-
cal correspondence analysis (CCA) was conducted in R using
the base functions (R Core Team 2020)onthespeciesand
environmental data to characterize the response of the com-
munity composition differences observed.
Results
Multivariate analysis of bacterial and phytoplankton
communities
A comparison of the 16S rRNA OTUs in samples collected
across the ASCA transect in July 2016 and 2018 shows that
the Agulhas Current bacterial communities were similar
(Fig. 2a). The bacterial communities in the coastal waters in
2018 (Return18) were different to the Agulhas Current
(ANOSIM; R=0.98; p< 0.01). There were three main clusters,
representing the Agulhas Current (ASCA16 and ASCA18),
Depart18, and Return18 (Fig. 2a). More variation was seen
within the Return18 samples, where the different sites were
more dissimilar. The outliers from the ASCA18 cluster repre-
sent f
max
samples collected at a depth of 80–90 m (Fig. 2a, cir-
cled), whereas all other f
max
and underway sites were
shallower than 70 m. Conservation of the bacterial communi-
ties in the Agulhas Current is evident in the combined cluster
from both ASCA cruises (ASCA16 and ASCA18; Fig. 2a;
ANOSIM; R=0.25; p< 0.01). Samples from the Depart18 tran-
sect, being geographically located between the other groups,
clustered with both the Return18 (ANOSIM; R=0.62;
p< 0.01) as well as the Agulhas Current samples (ANOSIM;
R=0.49; p< 0.01). This pattern of clustering is indicative of a
transition zone of bacterial communities between the Agulhas
Current and the coast (Return18).
Gibb et al. Agulhas Current system microbial communities
2763
The primers used to amplify the V4–V5 region of the bac-
terial 16S rRNA gene serendipitously also amplify eukaryotic
chloroplast sequences (Venkatachalam et al. 2017). All three
markers revealed a clear difference in community composi-
tion between the coastline and the Agulhas Current. How-
ever, the taxa responsible for these differences could not be
identified by each marker alone. Therefore, using all three
phytoplankton markers would better facilitate the identifica-
tion of the photosynthetic organisms responsible for these
patterns. The approach was to use the rbcL and 16S rRNA
chloroplast markers to provide insight into the photosyn-
thetic taxa within the phytoplankton community allowing
better classification of diatoms, while the 18S rRNA analysis
would provide information on additional functional groups
such as dinoflagellates. The modified rbcL database used in
this study successfully classified some dinoflagellates, but
they were still largely underrepresented compared to the 18S
rRNA datasets.
Fig. 2. Microbial community structure and spatial distribution patterns in the Agulhas Current system: (a) Bacterial communities nMDS plot using 16S
rRNA gene amplicon data; (b) nMDS plot of chloroplast 16S rRNA gene amplicon sequences; (c) nMDS plot of rbcL gene sequences attributed to photo-
synthetic phytoplankton communities and (d) nMDS plot of 18S rRNA amplicon data showing eukaryotic phytoplankton taxa. Black circled points repre-
sent the outlier f
max
samples that were deeper than 70 m.
Gibb et al. Agulhas Current system microbial communities
2764
Analysis of the relative abundance of chloroplast reads, as a
proxy for eukaryotic phytoplankton, indicated similarities
within the Agulhas Current samples collected in 2016 and
2018, with a different community at the coastal (Depart18 and
Return18) sites (Fig. 2b). As with the bacterial data, Return18
was dissimilar to the Agulhas Current sites (ANOSIM; ASCA16,
ASCA18; R1; p< 0.01) (Fig. 2b). In addition to the f
max
out-
liers (Fig. 2b, circled) that were evident in the bacterial analyses,
the more coastal sites (AS2 and AS4) of the ASCA16 cruise
clustered separately from the other samples of this cruise.
The Return18 sites were not as tightly clustered as the Agulhas
Current (ASCA16 and ASCA18) or Depart18 samples.
Analysis of the rbcL amplicon data confirmed that the
Agulhas Current photosynthetic phytoplankton communities
were relatively similar between the ASCA16 and ASCA18 sam-
ples (Fig. 2c, ANOSIM; R0.41, respectively; p< 0.01). The
ASCA18 and Depart18 were also similar (Fig. 2c, ANOSIM;
R=0.56; p< 0.01) and clustered together. Similar to the 16S
rRNA data the Return18 sites were not as tightly clustered as
the Agulhas Current (ASCA16 and ASCA18) samples. The f
max
outliers observed in the 16S rRNA analyses were also evident
in the rbcL plot (Fig. 2c, circled).
Consistent with the chloroplast markers, the data derived
from the 18S rRNA gene metabarcoding marker showed that
phytoplankton communities were also relatively stable within
the Agulhas Current (Fig. 2d,ANOSIM;R0.29; p<0.01).The
Depart18 samples clustered in between ASCA18 and Return18,
which was consistent with the other marker analyses. Similarly,
the Return18 samples were not as tightly clustered in the 18S
rRNA plot. The same f
max
outliers (Fig. 2d, circled) were also
observed and the coastal sites of the Agulhas Current (ASCA16
and ASCA18) clustered separately (AS2, ST8, and ST19).
Identification of conserved and dominant taxa
From a total of 5384 bacterial OTUs, 28 were conserved in all
the samples (Fig. 3a; Supporting Information Figs. S3, S4;
Supporting Information Table S5). These were classified predom-
inantly as Alphaproteobacteria and Gammaproteobacteria. Can-
didatus Pelagibacter ubique (B1) was particularly ubiquitous
within the Agulhas Current system but lower abundances were
recorded in the Return18 samples. The coastline had some taxa
belonging to the Bacteroidia NS9 marine group (B9) NS2b
marine group (B16), and Alphaproteobacteria (B33) but was
mostly dominated by the Gammaproteobacteria SAR86 clade
(B7) and Thiotrichales SUP05 cluster (B10). These results coin-
cide with higher nutrients along the coastline than in the
Agulhas Current. These Gammaproteobacteria were in fairly low
abundance in the Agulhas Current compared to the coastline.
Other important dominant OTUs that were abundant but
not conserved across all sites (Fig. 3b) were the cyanobacteria
Prochlorococcus (B2), Synechococcus (B4), Gammaproteobacteria
(B13) and Clade_IV, Alphaproteobactria (B18), which had
higher abundances in the current than along the coast. The
Gammaproteobacteria SAR86 clade (B15) was only absent
from site ST10A (ASCA18) and Pseudoalteromonas (B17) had a
higher abundance in ST16A than the other sites. The seawater
samples collected from deeper waters (ST15F, ST16F, and
ST18F; outliers observed in the nMDS plot, Fig. 2a)weredomi-
nated by Verrucomicrobia (B26). Although similar, some differ-
ences were observed within the ASCA18 samples. ST10 to ST15
(ASCA18) were similar to ASCA16 while ST16 and ST17
(ASCA18) showed more variability. These changes were driven
by Pseudoalteromonas sp. (B17), which was much more abundant
in ST16A than at the other sites. In addition, ST19, as mentioned
in the methods, was a repeat of ST10 (ASCA18) and is therefore
more coastal and appears similar to the Depart18 samples.
The chloroplast data showed clear differences in community
composition between the coastline and the Agulhas Current.
Analysis of the 16S rRNA chloroplast reads (Fig. 4) revealed that
only a few OTUs (9/516 in total) were conserved (Fig. 4a;
Supporting Information Figs. S5, S6; Supporting Information
Table S6) across all the sites including four diatoms namely,
Thalassiosira nordenskioeldii (C1), Pseudo-nitzschia seriata (C6),
Psammodictyon sp. (C17), an unclassified diatom (C29), a flagel-
late; Pelagomonas calceolata (C2), an unclassified haptophyte
(C3), and a dinoflagellate; Phalacroma sp. (C7), the green alga,
Bathycoccus prasinos (C8) and the coccolithophore, Gephyrocapsa
oceanica (C16). Of these conserved OTUs, only the diatoms,
T. nordenskioeldii (C1) and P. seriata (C6) were abundant along
the coastline rather than the Agulhas Current, whereas the
other OTUs were in higher abundances within the current.
Among the dominant OTUs (Fig. 4b; Supporting Informa-
tion Table S6) a wide variety of functional groups were found
within the Agulhas Current across all the sites, for example, the
dinoflagellates Phalacroma mitra (C4), green algae Micromonas
pusilla, which has been renamed to M. pusilla (C10) and
B. prasinos (C15), flagellates Aureococcus anophagefferens (C14),
and Florenciella parvula (C19), unclassified diatoms (C20) and
unclassified cryptophytes (C11). In contrast, the coastline
hosted more diatoms than the current such as Asterionella ralfsii
(C5), Chaetoceros sp. (C13), Haslea sp. (C18) and a cryptophyte
Teleaulax amphioxeia (C9). Cape St. Francis (AB8) hosted a com-
munity that differed from the other coastal sites, where
T. nordenskioeldii (C1) and flagellate P. calceolata (C2) were in
relatively low abundance and P. seriata (C6) were dominant
compared to the other sites.
The dominant taxa in the rbcL dataset were all diatoms and
flagellates, of which the conserved OTUs (4/2952 OTUs; Fig. 5a;
Supporting Information Fig. S7; Supporting Information
Table S7) were flagellates such as P. calceolata (R1and R2) and
A. anophagefferens (R7), that were more abundant in the
Agulhas Current than along the coast. The AS2 site is the most
coastal site of the ASCA16 cruise and hosted diatoms such as
Rhizosolenia shrubsolei, which has been renamed to Rhizosolenia
imbricata (R14), while AS4 hosted different diatoms including
Thalassionema sp. (R17) as well as the flagellates found in the
Agulhas Current. In addition to the differences observed within
ASCA16, there were also differences between ASCA18 samples.
Gibb et al. Agulhas Current system microbial communities
2765
ST10 to ST14 had higher abundances of flagellates P. calceolata
(R1) compared to the other ASCA18 sites. These differences cor-
respond to an increase in A. anophagefferens (R9) compared to
other sites as seen in the dominance plot (Fig. 5b). As with the
other markers, there were differences recorded in some of the
f
max
samples, for example, ST14F, ST17F, and ST18F had more
Fig. 3. Bacterial community structure and spatial distribution patterns based on 16S rRNA gene sequence diversity. (a) The OTUs conserved across all sites. (b)
Abundant OTUs that were not conserved across all sites. The letter B refers to the bacterial OTU that the color corresponds to (Supporting Information Table S5).
Gibb et al. Agulhas Current system microbial communities
2766
flagellates such as P. calceolata (R1), which resembled ASCA16
and ST10 to ST14 in ASCA18.
Differences within the coastal sites due to geographical sep-
aration were observed. Sites ST1 to ST3 (Depart18) were
distinct from ST4 to ST7. These differences were driven by the
changing abundance of Minidiscus trioculatus (R3) and
the presence of the flagellate A. anophagefferens (R9), and dia-
toms Thalassiosira antarctica (R5) and Detonula pumila (R12).
Fig. 4. Phytoplankton community structure and spatial distribution patterns based on 16S rRNA chloroplast gene sequence diversity. (a) OTUs conserved across
all sites. (b) Abundant OTUs that were not conserved across all sites. Identifications are based on the closest match in the Genbank database, see Supporting
Information tables for the percentage match. The letter C refers to the chloroplast OTU that the color corresponds to (Supporting Information Table S6).
Gibb et al. Agulhas Current system microbial communities
2767
In addition, the high abundance of diatoms at sites ST4 and ST5
contributed to these observed differences. The differences
between AB1 to AB3 and the other coastal sites was likely due to
the relatively high abundance of diatoms such as Pseudo-nitzschia
sp. (R6), Thalassiosira minima (R10) and Thalassiosira sp.(R13).
AB4 and AB5 were mostly characterized by T. antarctica (R5 and
R11), while AB6 and AB7 had more D. pumila (R12 and R16) rela-
tive to other sites (see Fig. 5b; Supporting Information Table S8).
Fig. 5. Phytoplankton community structure and spatial distribution patterns based on rbcL gene sequence diversity. (a) OTUs conserved across all sites.
(b) Abundant OTUs that were not conserved across all sites. Identifications are based on the closest match in the Genbank database, see Supporting
Information tables for percentage match. The letter R refers to the rbcL OTU that the color corresponds to (Supporting information Table S7).
Gibb et al. Agulhas Current system microbial communities
2768
Site AB8 had the highest abundance of the flagellate Heterosigma
akashiwo (R20) along with a combination of the diatoms found
within the other coastal sites (AB1–AB7). One dinoflagellate OTU,
Peridinium quinquecorne, now known as Blixaea quinquecornis
(R18), was important in these results with higher abundance
recorded in the coastal sites (Fig. 5b).
Analysis of the 18S rRNA amplicon data identified 18 out
of a total of 9987 OTUs (Fig. 6a; Supporting Information
Fig. S8; Supporting Information Table S8) that were con-
served across all the cruises in this study, including green
algae Ostreococcus sp. (E1), B. prasinos (E3), Micromonas
commoda (E8), flagellates P. calceolata (E5), A. anophagefferens
(E28), prymnesiophytes Phaeocystis globosa (E14), dinoflagel-
lates E15, Karlodinium veneficum (E16), Pentapharsodinium
sp. (E24), Gyrodinium sp. (E40), Palatinus apiculatus (E53),
E58, Paragymnodinium shiwhaense (E100) and cryptophytes
such as Hemiselmis andersenii (E69). Similar to the other
markers, these OTUs were generally more abundant in the
Agulhas Current than the coast.
The highest abundance of green algae was observed at the
AS2 site, which is the more coastal site of the ASCA16 cruise.
The differences between Depart18 and the Agulhas Current
samples are driven by species (Fig. 6b; Supporting Information
Table S8), such as Gymnodinium gracile (E6), A. socialis (E19),
and Heterocapsa sp. (E20). In addition, the variability within
the Return18 sites (Fig. 2d) were correlated to slight changes
in the composition of the phytoplankton communities as well
as changes in the abundances of the different groups between
these samples.
The AB1 to AB3 coastal (Return18) sites were characterized
by the diatoms Skeletonema costatum (E18) and A. socialis (E19),
whereas the AB4 and AB5 sites were characterized by the dia-
toms Minidiscus sp. (E9), Thalassiosira sp. (E11) and S. costatum
(E18). AB6 and AB7 were less diverse but hosted the dinoflagel-
late G. gracile (E6) and diatom Thalassiosira sp. (E12). AB8 (Cape
St. Francis) hosted a unique community that corresponded to
the other markers with an abundance of dinoflagellates
Prorocentrum micans (E2), Heterocapsa sp. (E20), and the diatom
Minidiscus sp. (E9). The outlier f
max
samples seen in all the
markers, had lower phytoplankton abundances compared to
the surface samples (Figs. 4–6). See Appendix S3, Supporting
Information for further information.
Correlations of biological communities with physico-
chemical variables
In general, multivariate analyses (CCA; Supporting Informa-
tion Figs. S9–S12; Supporting Information Tables S9, S10) rev-
ealed that the differences in bacterial and phytoplankton
community distribution were correlated to nutrient and tem-
perature changes. The total variance explained by the 16S
rRNA, chloroplast, rbcL, and 18S rRNA markers was 89.01%
(CCA; p=0.01), 92.94% (CCA; p=0.01), 78.42% (CCA;
p=0.01), 80.77% (CCA; p=0.01), respectively (Supporting
Information Table S9). Prochlorococcus (B2) and Synechococcus
(B4) cyanobacterial species were associated with the highest
water temperatures, with their higher abundance in the
Agulhas Current vs. the coast. Taxa in the Flavobacteriaceae;
NS4 marine group (B8), Gammaproteobacteria HOC36 (B14),
Alphaproteobacteria; Clade_IV (B18), Candidatus Actino-
marina (B20), SAR86 clade (B22) and SAR11 clade (B230), fla-
gellates P. calceolata (R1 and R2), A. anophagefferens (C14, R7,
and R9) and F. parvula (C19), dinoflagellates Phalacroma
sp. (C7), P. mitra (C4), the unclassified haptophyte (C3), green
alga B. prasinos (C8, C15), and M. pusilla,(C10),correlatedtothe
higher water temperatures recorded in the Agulhas Current. In
contrast, bacterial OTUs classified within the Cryomorphaceae
NS9 marine group (B9), Thiotrichales SUP05 cluster (B10),
Gammaproteobacteria SAR86 clade (B15), NS2b marine group
(B84) and Alphaproteobacteria (B101), diatoms such as
T. nordenskioeldii (C1), A. ralfsii (C5), Chaetoceros sp. (C13),
M. trioculatus (R3 and R19), Thalassiosira sp.(R13), Minidiscus
sp. (E9), S. costatum (E18), A. socialis (E19) and dinoflagellates
P. micans (E2), Heterocapsa sp. (E20) were associated with cooler
water temperatures.
The bacteria Pelagibacteraceae; Clade_II (B6, B129) and Can-
didatus Marinimicrobia (B11) were associated with medium tem-
peratures and higher PO3
4. The bacteria SAR86 clade (B7, B32),
NS2b marine group (B16), Candidatus Marinimicrobia (B45),
unclassified diatom (C20) and Psammodictyon sp. (C17), the
green algae Ostreococcus sp. (E1) and Picomonas sp. (E83) cor-
related with higher PO3
4while the diatoms Chaetoceros
sp. (C13), A. ralfsii (C5), M. trioculatus (R3 and R19) and
Thalassiosira sp. (R13), dinoflagellates G. gracile (E6),
Gyrodinium sp. (E40), P. apiculatus (E53) were associated with
areas characterized by higher NO
3. Similarly, the bacteria
SAR86 clade (B70), Rhodobacteraceae (B86), diatoms P. seriata
(C6), T. antarctica (R11), D. pumila (R12 and R16), Thalassiosira
sp. (R15, E11, and E12), Thalassionema sp. (R17), S. costatum
(E18), A. socialis (E19), green algae B. prasinos (C8), and the
flagellate H. akashiwo (R20) occurred in areas with higher than
average SiO2
3concentrations.
Discussion
This study aimed to characterize the bacterial and
phytoplankton community in the Agulhas Current and
the adjacent coastal sites. The Agulhas Current comprised taxa
adapted to the nutrient-poor conditions (i.e., cyanobacteria),
whereas the adjacent coastline was more diatom rich. In gen-
eral, the bacteria and phytoplankton data showed that the
Agulhas Current community was consistent during the study,
confirmed by the similarities between the 2016 and 2018 com-
munities but there was variability in the coastal communities.
Overall, bacterial communities characterized in this study were
similar to those observed at other coastal to offshore oligotro-
phic gradients (Ward et al. 2017; Wang et al. 2019). The ubiqui-
tous gammaproteobacterial SAR86 clade (Korlevi
cetal.2022)
was represented by two different OTUs and was found within
Gibb et al. Agulhas Current system microbial communities
2769
the current and the coastal samples. Similarly, Candidatus
Pelagibacter ubique, the most abundant bacterium in the ocean
(Giovannoni 2017) was conserved in all the sites. Underway
and f
max
community data were similar except for the outliers,
which were collected below 70 m. Those samples were mainly
composed of Verrucomicrobia, known to be present across a
Fig. 6. Phytoplankton community structure and spatial distribution patterns based on 18S rRNA gene sequence diversity. (a) OTUs conserved across all
sites. (b) Abundant OTUs that were not conserved across all sites. Identifications are based on the closest match in the Genbank database, see Supporting
Information tables for percentage match. The letter E refers to the OTU that the color corresponds to (Supporting Information Table S8).
Gibb et al. Agulhas Current system microbial communities
2770
range of ecosystems with wide environmental tolerance ranges
(Freitas et al. 2012).
The higher Prochlorococcus abundance in the Agulhas
Current relative to the coastline is typical of an oligotrophic
system (Wang et al. 2019). Barlow et al. (2015) also found
Prochlorococcus (using pigment analysis) in the Agulhas Cur-
rent between Richards Bay and St Lucia. While Synechococcus
can be associated with coastal waters (Ward et al. 2017; Wang
et al. 2019), these cyanobacteria prefer warmer waters, which
was confirmed in this study and has been recorded in
Kuroshio waters (Zhong et al. 2020).
We observed a transition between the coastal and offshore
sites where the shelf section between the nearshore and off-
shore sites overlapped with the community on either side.
Similar transitions from coastal to oceanic communities have
been found where Proteobacteria and Bacteriodetes were dom-
inant in the nearshore sites, while taxa such as Prochlorococcus
(cyanobacteria) and Pseudoalteromonas were prevalent at the
offshore sites (Fortunato et al. 2012). Fortunato et al. (2012)
argued that the mixing between different habitats, in their
case driven by upwelling, creates a vertical gradient in the bac-
terial communities. Mixing is particularly evident between the
coast and the Agulhas Current system where the shearing
zone responsible for upwelling is a highly turbulent mixed
area (Goschen et al. 2015), which may explain this transition.
Bacteroidetes taxa such as flavobacteria generally respond pos-
itively to increases in diatom biomass (Lima-Mendez et al. 2015;
Korlevi
cetal.2022) and the Bacteroidetes OTUs in the more
productive coastline correlated positively with nutrient and tem-
perature changes and higher diatom abundances. Interestingly,
while Rhodobacteria abundance usually correlates to increases in
dinoflagellate abundance (Lima-Mendez et al. 2015), they
occurred in areas with higher than average silicate concentra-
tions. Although conserved, this group was not well represented,
but based on the silicate correlation and the fact that these bac-
teria respond to organic mattertheylikelyweremoreabundant
in diatom dominant sites(Bolañosetal.2021).
Molecular methods have been applied extensively to study
phytoplankton community dynamics, especially during the
Tara Oceans Cruise, where sequencing techniques were used to
quantify many of the biological organisms sampled. Two sta-
tions of the Tara Oceans Cruise (Sta. 64 and Sta. 65) were within
the South African section of the Agulhas Current. The Tara
Oceans Cruise studies showed that the Agulhas retroflection is a
barrier to cyanobacterial and diatom dispersal (Farrant et al.
2016; Malviya et al. 2016), but Agulhas rings assist in the move-
ment of planktonic organisms between ocean basins (Villar
et al. 2015). This is in contrast to the present study where the
Agulhas Current does not seem to be a barrier to phytoplankton
dispersal but the mixing zones that are known to occur between
the current and adjacent coastal waters seems to act as a transi-
tion zone (similar to the bacteria).
This species transition was related to upwelling-associated
nutrient increases along the coastline, which coincided with
an increased abundance of diatoms relative to the Agulhas
Current (Supporting Information Fig. S13). In contrast, some
coastal samples consisted of a mix of diatoms and flagellates.
This is perhaps a consequence of niche differences that exist
between different phytoplankton functional groups that possi-
bly correlate to cell size (Litchman et al. 2007). Smaller cells
are found in nutrient-poor conditions (i.e., cyanobacteria)
while larger cells (i.e., diatoms and some dinoflagellates)
increase in abundance with increasing nutrients, especially
nitrates (Litchman et al. 2007).
Highly productive taxa e.g., diatoms (specifically genera such
as Thalassiosira spp., Minidiscus spp., Pseudo-Nitzchia spp., and
Detonula spp.), are associated with turbulent, mixed water,
whereas other genera with lower growth rates succeed these dur-
ing the relaxation of upwelling when the water column becomes
more stratified, and this results in a shift to a more mixed com-
munity (Burger et al. 2020). It is therefore likely that both
recently upwelled water as well as post-upwelled water were sam-
pled during our study. This phenomenon is also evident during
summer in the EAC when it is stronger and upwelling favorable
southward alongshore winds dominate (Thompson et al. 2009).
However, it was found that when the water column became
more stratified, dinoflagellates were at their highest proportional
abundance along the EAC (Thompson et al. 2009). Similarly, in
the Kuroshio Current, diatoms responded to nutrient changes
attributed to physical processes such as current induced upwell-
ing(Zhongetal.2020). Studies in the Northern Atlantic have
also shown that the Gulf Stream meanders to the north and
south over time and this movement of the current changes the
nutrient availability within the water column (Rossby and
Benway 2000; Schollaert et al. 2004), thereby promoting or
suppressing primary productivity (Schollaert et al. 2004).
The Agulhas Current is broadening and this has resulted in
increased upwelling (Beal and Elipot 2016). Although not spe-
cifically studied in the Agulhas Current, responses by the phy-
toplankton to these changes will occur. The EAC, as an
example, is strengthening, and changes in phytoplankton and
microbial species have been observed (Messer et al. 2020). Simi-
larly, increased stratification, often associated with an increase
in sea surface temperature, influences the distribution of nutri-
ents within the water column (Yamaguchi and Suga 2019),
which will have an impact on primary productivity. The resul-
tant change in the primary productivity could reduce the flow
of energy to higher trophic levels (Friedland et al. 2020). These
observations are not unique to western boundary currents and
are being observed globally in many other marine ecosystems.
The phytoplankton community recorded in this study pro-
vide a baseline that can guide future research where a combi-
nation of regular cruises and in situ oceanographic data will
prove invaluable to monitor the biological response to
increased environmental variability. This study highlighted
the value of LTER, which allowed the detection of upwelling
in the coastal regions adjacent to the Agulhas Current. This
study is however limited by the lack of available long-term
Gibb et al. Agulhas Current system microbial communities
2771
biological and environmental datasets to better understand
the variability in the system. More regular sampling and inclu-
sion of additional variables will reduce this variability. Consid-
ering the importance of the Agulhas Current for the global
climate and the influence of the Agulhas Current on coastal
areas such as Algoa Bay and St. Francis Bay, it is important
that the essential ocean variables and essential biodiversity
variables included here be observed over the long-term to
detect and monitor the changes taking place.
Data availability statement
Sequencing datasets have been deposited as Bioprojects in
the Sequence Read Archive hosted by NCBI (https://www.ncbi.
nlm.nih.gov/sra/). Metabarcoding data for the 16S rRNA
(accession: SRX9971261–SRX9971316), 18S rRNA (accession:
SRX13978140–SRX13978195), and rbcL (accession:
SRX13978199–SRX13978273) samples can be accessed on
NCBI under the bioproject PRJNA694821. The modified
Rsyst database can be downloaded from Zenodo: https://
doi.org/10.5281/zenodo.11275853.
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Acknowledgments
This research was funded by grants from the South African Research
Chairs Initiative (SARChI) through the South African National
Research Foundation (NRF) to R.A.D (UID: 87530). R.A.G. and S.V. were
supported by SARChI PhD and Post-Doctoral Fellowships, respectively
(UID 87530). Logistical support was provided by the Shallow Marine and
Coastal Research Infrastructure (SMCRI). In situ temperature data was
provided by SAEON and SMCRI from the Algoa Bay Sentinel Site for
LTER. The authors thank Isabelle Ansorge, Principal Investigator of the
SEAmester programme funded by the South African National Antarctic
Programme through the NRF, for providing ship time and logistics for
sampling, Marcel van den Berg and Tammy Morris of the South African
National Department of Forestry, Fisheries and the Environment for logis-
tical and technical support. We thank the captains, the officers and crew
of the RV SA Agulhas II for their support and Melissa Pollard, Phumlile
Cotiyane-Pondo, and Eric Isemonger for technical assistance and Gwyneth
Matcher of the South African Institute for Aquatic Biodiversity, Aquatics
Genomics Research Platform for Illumina sequencing and analysis of
amplicon sequence libraries, Robert Pienaar for statistical support and
database editing and Tarryn Swartbooi and Amanda Mgwali for analyzing
nutrients and chlorophyll samples. The authors acknowledge the Centre
for High Performance Computing, South Africa, for providing computa-
tional resources to this research project. Satellite imagery used for the
maps (Fig. 1) were generated using E.U. Copernicus Marine Service
Information.
Conflict of Interest
None declared.
Submitted 03 December 2023
Revised 27 May 2024
Accepted 15 September 2024
Associate editor: Katherina Petrou
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