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Research Article
Exploring benthic diatom diversity in the West Antarctic Peninsula: insights from a morphological and molecular approach
expand article infoKatherina Schimani, Nélida Abarca, Oliver Skibbe, Heba Mohamad, Regine Jahn, Wolf-Henning Kusber, Gabriela Laura Campana§|, Jonas Zimmermann
‡ Freie Universität Berlin, Berlin, Germany
§ Argentinean Antarctic Institute, Buenos Aires, Argentina
| National University of Luján, Buenos Aires, Argentina
Open Access

Abstract

Polar regions are among the most extreme habitats on Earth. However, diatom biodiversity in those regions is much more extensive and ecologically diverse than previously thought. The objective of this study was to add knowledge to benthic diatom biodiversity in Western Antarctic coastal zones via identification by means of morphology, DNA metabarcoding and cultured isolates. In addition, a taxonomically validated reference library for Antarctic benthic diatoms was established with comprehensive information on habitat, morphology and DNA barcodes (rbcL and 18SV4). Benthic samples from marine, brackish and freshwater habitats were taken at the Antarctic Peninsula. A total of 162 clonal cultures were established, resulting in the identification of 60 taxa. The combination of total morphological richness of 174 taxa, including the clones, with an additional 73 taxa just assigned by metabarcoding resulted in 247 infrageneric taxa. Of those taxa, 33 were retrieved by all three methods and 111 only by morphology. The barcode reference library of Antarctic species with the new references obtained through culturing allowed the assignment of 47 taxa in the metabarcoding analyses, which would have been left unassigned because no matching reference sequences were available before. Non–metric multidimensional scaling analyses of morphological as well as molecular data showed a clear separation of diatom communities according to water and substratum types. Many species, especially marine taxa, still have no record in reference databases. This highlights the need for a more comprehensive reference library to further improve routine diatom metabarcoding. Overall, a combination of morphological and molecular methods, along with culturing, provides complementary information on the biodiversity of benthic diatoms in the region.

Key words

Antarctic Peninsula, benthic diatoms, DNA metabarcoding, morphology, rbcL, taxonomic reference library, unialgal cultures, 18SV4

Introduction

The polar regions are among the most extreme environments on Earth. Total darkness in winter is paired with low temperatures, strong winds and heavy snow cover. In contrast, permanent light and higher temperatures in summer result in ice and snow melt (Pavlov et al. 2019). Marine biota living in those regions must deal with extreme seasonality of light, temperature, salinity and sea ice (Zacher et al. 2009). In contrast to this harsh environment, biodiversity in polar regions is much more extensive, ecologically diverse, and biogeographically structured than previously thought and the prevalence of such conditions for millions of years has led to the evolution of a truly unique flora and fauna (Griffiths 2010; Chown et al. 2015; Danis et al. 2020).

An ecologically particularly important group of eukaryotic microorganisms in Antarctic shallow water coastal zones are benthic diatoms living on top of or associated with sediments, rocks or sea ice. Their benthic assemblage exerts multiple important functions as primary producers, providing a major food source for a diverse range of organisms such as bacteria by excretion of soluble organic matter, benthic protozoans as well as metazoans (Cahoon 1999), including mesograzers such as amphipodes and gastropodes (Zacher et al. 2007; Campana et al. 2008; Aumack et al. 2017; Amsler et al. 2019). Furthermore, diatoms influence elemental fluxes at the sediment–water interface (Risgaard–Petersen et al. 1994) and stabilize the sediment surface by excretion of sticky extracellular polymeric substances (de Brouwer et al. 2005). Due to their abundance, marine planktonic diatoms account for up to one fifth of the global photosynthetic carbon fixation (Falkowski et al. 2000).

Numerous recent studies indicate that microorganisms display a distinct biogeography, which is also strongly supported by evidence from different freshwater and soil diatoms (Vanormelingen et al. 2008; Abarca et al. 2014; Pinseel et al. 2020). Freshwater benthic diatoms in Antarctica have been intensively studied e.g. Van de Vijver et al. (2002); Kopalová et al. (2015); Sterken et al. (2015); Zidarova et al. (2016a, b); Van de Vijver et al. (2018) and revisions of freshwater Antarctic and sub–Antarctic diatom floras point to a strong regionalization (Vyverman et al. 2010; Verleyen et al. 2021). Despite their crucial role, information about the biodiversity of Antarctic marine benthic diatoms is scarce and only a few studies exploring their biodiversity exist (Klöser 1998; Al-Handal and Wulff 2008a, b; Campana 2018; Al-Handal et al. 2022; Zidarova et al. 2022).

DNA metabarcoding has emerged as an alternative to light microscope-based identifications (LM) as it provides a faster and cheaper way of identifying species in an environmental sample because the morphological identification and counting of diatoms species in LM is time–consuming and demands extensive expertise since diatom taxonomy is constantly evolving. (Kermarrec et al. 2014; Zimmermann et al. 2015). This approach has been used to investigate freshwater diatom biodiversity (Rimet et al. 2018b; Mora et al. 2019) and has been applied to some extent to marine environments (Malviya et al. 2016; Piredda et al. 2018; Pérez-Burillo et al. 2022). Benthic diatoms are commonly used as bioindicators to monitor water quality because of their rapid response to environmental pressures and their omnipresence (Rimet and Bouchez 2012; Desrosiers et al. 2013). DNA metabarcoding based on benthic diatoms has been utilized to monitor community changes and assessing the biological status of a water body (Vasselon et al. 2017; Bailet et al. 2019; Mortágua et al. 2019; Kelly et al. 2020; Pérez-Burillo et al. 2020) and a taxonomy-free biomonitoring approach has emerged that allows the computing of a molecular index directly without any reference to morphotaxonomy to overcome the limitatios of the reference databases and the lack of phylogenetic resolution (Apothéloz-Perret-Gentil et al. 2017; Tapolczai et al. 2019a, b, Gregersen et al. 2023).

For a reliable identification, an unambiguous link between geno– and phenotype is crucial. Therefore, a comprehensive taxonomic reference library is required where molecular and morphological data are tied together with a taxonomic name (Zimmermann et al. 2014; Stachura-Suchoples et al. 2015). For diatoms, clone cultures need to be established which offer sufficient material for sequencing as well as for identification by light and electron microscopy. Finally, all reference sequences should be linked to diatom voucher specimens deposited in a herbarium in order to offer a complete chain of evidence back to the formal taxonomic literature.

The objective of this study was to add knowledge to the biodiversity of marine benthic diatoms in Western Antarctic shallow water coastal zone environments. In addition, some brackish and freshwater environments connected to the marine realm were explored. Benthic diatom biodiversity in communities sampled in Potter Cove, King George Island/ Isla 25 de Mayo, West Antarctic Peninsula were identified by the means of morphological and molecular methods to assess the status of their taxonomic coverage in Antarctic regions. To compare the performance of morphology and metabarcoding in the identification and quantification of diatom abundances, our objective was to compare the number of taxa retrieved by both analysis of environmental samples. A further goal was to create a regional vouchered barcode reference library with the help of clone cultures with comprehensive information on habitat, morphology and DNA barcodes (rbcL and 18SV4). This taxonomic reference library was utilized for DNA metabarcoding to access the concealed biodiversity beyond the limits of morphological and cultivating methods. Generating the thus far most extensive biodiversity dataset on Antarctic marine benthic diatoms provides a reference to monitor community changes to predict the potential impact of climate change on the coastal ecosystems of this region.

Methods

Study area and sampling collection

Epipsammic and epilithic samples from marine, brackish and freshwater habitats were taken in Austral summer 2020 at Potter Cove, a shallow coastal bay at King George Island/ Isla 25 de Mayo, West Antarctic Peninsula (Fig. 1). Potter Cove combines zones of glacier fronts and rocky shores as well as extensive soft bottom areas and thereby providing diverse habitats for benthic diatoms (Klöser 1998).

Figure 1.

A Map of Antarctica. B Map of King George Island/Isla 25 de Mayo. C Map of the Potter Cove, with the 39 sample locations. Blue points represent marine sample locations, green points represent freshwater sample locations and orange points represent brackish water locations. Basemap: Landsat Image Mosaic of Antarctica (LIMA).

In total 39 samples were taken (Table 1, Fig. 1). At eight of the locations freshwater samples were taken from glacial run–off water or drinking water reservoirs. At 17 locations the littoral zone was sampled, and additional 14 marine locations were sampled by scuba diving reaching down to a water depth of 20 m (Table 1). A map of the sampling points was generated with the software QGIS 2.18 (QGIS Development Team 2021).

Table 1.

Sample sites with information on the location, georeference, altitude, collector, water type, substrate type and voucher at the BGBM.

Sample ID Sampling date Location GPS coordinates Altitude Collector Water type Substrate type Voucher at BGBM
D283 28.01.2020 Coastal zone at Peñón 1 62.245938°S, 58.681731°W 0 m J. Zimmermann marine biofilm from stones B 50 0021363
D284 28.01.2020 Lighthouse Melting Pond 62.240866°S, 58.677563°W 28 m J. Zimmermann freshwater biofilm from stones B 50 0021364
D285 29.01.2020 IT Resevoire 62.237876°S, 58.662233°W 12 m J. Zimmermann freshwater biofilm from stones B 50 0021365
D286 29.01.2020 Drinking water pond at Carlini station 62.238091°S, 58.657689°W 23 m J. Zimmermann freshwater biofilm from stones B 50 0021366
D288 29.01.2020 Coastal zone at Peñón 0 62.241809°S, 58.681931°W 0 m J. Zimmermann marine biofilm from stones B 50 0021367
D289 30.01.2020 Coastal zone at island A7 62.234665°S, 58.664624°W 10 m deep J. Zimmermann, G. L. Campana, Divers Carlini Station marine epipsammic biofilm B 50 0021368
D290 30.01.2020 Coastal zone at island A7 62.234665°S, 58.664624°W 10 m deep J. Zimmermann, G. L. Campana, Divers Carlini Station marine epipsammic biofilm B 50 0021369
D292 30.01.2020 Coastal zone at island A7 62.234665°S, 58.664624°W 10 m deep J. Zimmermann, G. L. Campana, Divers Carlini Station marine epipsammic biofilm B 50 0021370
D293 30.01.2020 Coastal zone at island A7 62.234665°S, 58.664624°W 10 m deep J. Zimmermann, G. L. Campana, Divers Carlini Station marine epipsammic biofilm B 50 0021371
D294 30.01.2020 Coastal zone east of Carlini station 62.235314°S, 58.656489°W 0 m J. Zimmermann brackish water epipsammic biofilm B 50 0021372
D295 30.01.2020 Coastal zone east of Carlini station 62.235771°S, 58.658364°W 0 m J. Zimmermann brackish water epipsammic biofilm B 50 0021373
D296 31.01.2020 Coastal zone at island A4 62.229219°S, 58.663369°W 15 m deep J. Zimmermann, G. L. Campana, Divers Carlini Station marine epipsammic biofilm B 50 0021374
D297 31.01.2020 Coastal zone at island A4 62.229219°S, 58.663369°W 15 m deep J. Zimmermann, G. L. Campana, Divers Carlini Station marine episammic biofilm B 50 0021375
D299 01.02.2020 Glacier meltwater run-off in Tres Hermanos area 62.251939°S, 58.652703°W 60 m J. Zimmermann freshwater biofilm from stones B 50 0021376
D300 01.02.2020 Drinking Water Reservoire 62.237861°S, 58.662250°W 51 m J. Zimmermann freshwater biofilm from stones B 50 0021377
D301 04.02.2020 Coastal zone at island A4 62.229219°S, 58.663369°W 5 m deep J. Zimmermann, G. L. Campana, Divers Carlini Station marine biofilm from stones B 50 0021378
D302 04.02.2020 Coastal zone at island A4 62.229219°S, 58.663369°W 5 m deep J. Zimmermann, G. L. Campana, Divers Carlini Station marine epipsammic biofilm B 50 0021379
D303 04.02.2020 Glacier meltwater run-off Fourcade 62.236639°S, 58.647028°W 10–15 m J. Zimmermann freshwater biofilm from stones B 50 0021380
D304 04.02.2020 Glacier meltwater run-off Fourcade 62.236639°S, 58.647028°W 10–15 m J. Zimmermann freshwater biofilm from stones B 50 0021381
D305 05.02.2020 Coastal zone at island A4 62.229219°S, 58.663369°W 20 m deep J. Zimmermann, G. L. Campana, Divers Carlini Station marine epipsammic biofilm B 50 0021382
D306 06.02.2020 Coastal zone at Punta Elefante 62.237353°S, 58.679569°W 0 m J. Zimmermann marine biofilm from stones B 50 0021383
D307 07.02.2020 Coastal zone at Peñón 1 62.247261°S, 58.680051°W 0 m J. Zimmermann marine biofilm from stones B 50 0021384
D308 07.02.2020 Coastal zone at Peñón 1 62.247261°S, 58.680051°W 0 m J. Zimmermann marine biofilm from stones B 50 0021385
D309 07.02.2020 Diver’s container at Carlini station 62.237459°S, 58.667529°W 2 m deep J. Zimmermann, G. L. Campana, Divers Carlini Station marine biofilm from stones B 50 0021386
D310 07.02.2020 Coastal zone at Peñón de Pesca 62.237906°S, 58.712278°W 5 m deep J. Zimmermann, G. L. Campana, Divers Carlini Station marine biofilm from stones B 50 0021387
D311 08.02.2020 Coastal zone at Punta Stranger 62.256388°S, 58.625618°W 2 m J. Zimmermann marine biofilm from stones B 50 0021388
D312 08.02.2020 Coastal zone at Punta Stranger 62.256296°S, 58.626069°W 2 m J. Zimmermann marine biofilm from stones B 50 0021389
D313 08.02.2020 Coastal zone at Punta Stranger 62.258227°S, 58.642172°W 1 m J. Zimmermann marine biofilm from stones B 50 0021390
D314 09.02.2020 Glacier meltwater run-off Refugio Albatros 62.252046°S, 58.659456°W 49 m J. Zimmermann freshwater biofilm from stones B 50 0021391
D315 09.02.2020 Coastal zone at Peñón 4 62.256107°S, 58.659703°W 2 m J. Zimmermann marine biofilm from stones B 50 0021392
D316 09.02.2020 Coastal zone at Peñón 2 62.250540°S, 58.675029°W 2 m J. Zimmermann marine biofilm from stones B 50 0021393
D317 09.02.2020 Coastal zone at Peñón 1 62.247073°S, 58.683764°W 2 m J. Zimmermann marine biofilm from stones B 50 0021394
D318 10.02.2020 Coastal zone at Peñón 2 62.250704°S, 58.675778°W 1 m J. Zimmermann marine biofilm from stones B 50 0021395
D319 12.02.2020 Coastal zone at Carlini station 62.236950°S, 58.663583°W 1 m J. Zimmermann marine biofilm from stones B 50 0021396
D320 13.02.2020 Coastal zone at Punta Stranger 62.256109°S, 58.630578°W 0 m J. Zimmermann marine biofilm from stones B 50 0021397
D321 13.02.2020 Coastal zone at Punta Stranger- Peñón 4 62.256615°S, 58.641681°W 0 m J. Zimmermann marine biofilm from stones B 50 0021398
D322 14.02.2020 Coastal zone at island A2 62.227633°S, 58.678734°W 10 m deep J. Zimmermann, G. L. Campana, Divers Carlini Station marine epipsammic biofilm B 50 0021399
D324 16.02.2020 Coastal zone at island A6 62.223800°S, 58.642639°W 15 m deep J. Zimmermann, G. L. Campana, Divers Carlini Station marine epipsammic biofilm B 50 0021400
D325 17.02.2020 Coastal zone at island A6 62.223800°S, 58.642639°W 20 m deep J. Zimmermann, G. L. Campana, Divers Carlini Station marine epipsammic biofilm B 50 0021401

At each sample location a composite sample of 60 ml was taken along a transect of approximately 10 m. At sample locations with rocky substrate the biofilm of three to four stones along the transect was scratched with a knife. At locations with soft sediment a sediment corer was used to collect the material of three to four spots along the transect. The top layer of the cores was then sampled with a syringe. The composite samples were homogenized, and divided into 3 subsamples of 20 ml each, which were used for 3 different purposes: 1) fixed in 70% alcohol for morphological identification of the mixed diatom community, 2) stored cooled for the establishment of clone cultures to build the barcode library and 3) fixed in 99% ethanol and frozen for a community analysis via DNA metabarcoding.

Establishment of clonal cultures

Following the procedures outlined in Skibbe et al. (2022), benthic diatoms were isolated from aliquots of environmental samples to establish clonal cultures afterwards. For this purpose, a small subsample of the biofilm was transferred from the collected environmental samples to 5 cm (diameter) Petri dishes filled with liquid culture media. Different media were used for each sample to obtain as many species with different requirements as possible. The cultivation media was prepared with sterile water enriched with one of the following media: f/2 seawater medium (Guillard and Ryther 1962), Alga–Gro medium (Carolina Biological Supply Company) or Walne’s medium (Walne 1970) and salted up to a salinity of 34 psu in case of a marine sample and 12 psu for brackish samples. Using an inverted light microscope (100–400× magnification, Olympus) and microcapillary glass pipettes, single cells were transferred into microwell plates containing culture medium. After reaching sufficient densities, isolates were transferred to 5 cm petri dishes. All water samples, isolates and cultures were maintained at 5–7 °C. Illumination was accomplished by white light LEDs under a 16/8 day/night cycle with 15 min dark phases every hour during the day to prevent photo–oxidative stress.

Morphological analysis from environmental samples and clonal cultures

Environmental samples and material harvested from the unialgal cultures were treated with 35% hydrogen peroxide at room temperature to oxidize the organic material and washed with distilled water as described in Mora et al. (2019). To prepare permanent slides for light microscopy analyses, the cleaned material (frustules and valves) was dispersed on cover glasses, dried at room temperature and embedded with the high refraction index mounting medium Naphrax.

Each environmental sample was inspected for their benthic diatom composition using LM. Observations were conducted with a Zeiss Axioplan Microscope equipped with Differential Interference Contrast (DIC) using a Zeiss 100× PlanApochromat objective. Microphotographs were taken with an AXIOCAM MRc camera. To record the occurrence and abundance of each diatom taxon at all sampling sites, at least 400 frustules were counted per sample and the relative abundance of each taxon calculated. All samples were scanned for rare species.

Furthermore, morphological identification of the unialgal cultures were conducted also by LM and extended by scanning electron microscopy (SEM) if appropriate. Therefore, aliquots of cleaned culture material were dried on silicon wafers and mounted on stubs and observed under a Hitachi FE 8010 scanning electron microscope operated at 1.0 kV.

Molecular identification of diatom cultures

Cultured material was first centrifuged, and culture medium was discarded by carefully pipetting. DNA was isolated from the remaining pellet using NucleoSpin Plant II Mini Kit (Macherey–Nagel, Düren, Germany) following product instructions. DNA fragment size and concentrations were evaluated via gel electrophoresis (1.5% agarose gel) and Nanodrop (PeqLab Biotechnology LLC; Erlangen, Germany) respectively. Amplification was conducted by polymerase chain reaction (PCR) after Zimmermann et al. (2011) for the V4 region of 18S. The protein–coding plastid gene rbcL was amplified after Abarca et al. (2014) with M13 tailed primers rcbL–iF/rbcL–R. PCR products were visualized in a 1.5% agarose gel and cleaned with MSB Spin PCRapace (Invitek Molecular GmbH, Berlin, Germany) following manufacturer instructions. Concentrations of PCR products were measured using Nanodrop (PeqLab Biotechnology) and normalized to >100 ng/µl for sequencing. Sanger sequencing was conducted bidirectionally by Starseq (GENterprise LLC; Mainz, Germany), with the same primers used for the amplifications. The DNA material is stored in the Berlin DNA Bank Network (Gemeinholzer et al. 2011).

DNA metabarcoding

A volume of 2–4 ml of each sample was centrifuged at 4 °C and 11.000 rpm for 5 min. The supernatant was removed and from the remaining pellet the DNA was extracted with the NucleoSpin Soil Kit (Macherey and Nagel) following the manufacturer instructions. Short areas of the hypervariable region V4 of the 18S rRNA gene and the rbcL plastid gene were amplified in separated target PCRs. For the 18S V4 region the Nextera primers DIV4for: 5’ – GCGGTAATTCCAGCTCCAATAG–3’ and DIV4rev3: 5’ – CTCTGACAATGGAATACGAATA–3’ were used after Zimmermann et al. (2011) with a modification for 300–bp paired–end sequencing for Illumina MiSeq following Visco et al. (2015). The rbcL marker was amplified using an equimolar mix of the modified versions of the Diat_rbcL_708F and R3 primers established by Vasselon et al. (2017). For each sample PCR was once repeated for technical replication. Purification of the samples was performed with 25 ml aliquots of the amplicons with HighPrep PCR Clean–up System (Magbio Genomics). Indexing PCR on the purified samples to ligate a unique combination of tags to the 5’ end of the primer, DNA quantitation and Illumia MiSeq v3 sequencing (300 bp paired–end reads) with 600 cycles were conducted at the Berlin Center for Genomics in Biodiversity Research (BeGenDiv) of the Berlin Brandenburg Institute of Advanced Biodiversity Research (BBiB).

Raw demultiplexed reads were deposited at GenBanks Sequence Read Archive and are publicly available under project number PRJNA997374.

Bioinformatic analysis

The BeGenDiv performed demultiplexing of the samples providing two fastq files per sample containing forward reads (R1) and reverse reads (R2) respectively. Primers were removed from the reads with cutadapt (Martin 2011). To process the resulting reads the R package DADA2 was used (Callahan et al. 2016). The quality profile was checked, and reads were truncated consecutively for rbcL at R1 to 200 bp and at R2 to 160 bp and for 18SV4 at R1 to 230 bp and at R2 to 170 bp. Truncated reads were filtered using a maximum expected error rate of 2. Hereinafter, amplicon sequence variants (ASVs) were selected based on the error rates model determined by the DADA2 denoising algorithm and paired reads were merged into one sequence. Chimeras were identified and removed from the dataset.

Taxonomic assignment for each barcode was performed using an own established reference library comprising the Diat.barcode library (Rimet et al. 2019), the reference library of the Diatom research group of the Botanic Garden Berlin (5768 taxa for 18SV4 and 5604 taxa for rbcL) and the newly generated sequences from Antarctic cultures. In case of unclassified taxa on phylum level, the ASV was checked using the Basic Local Alignment Search Tool (BLAST, Camacho et al. 2009) against NCBI GenBank.

After bioinformatic analyses with DADA2 the R package metabaR was used to identify artefactual sequences like contaminants and tag–jumps (Zinger et al. 2021). The dataset was checked for dysfunctional PCRs based on PCR replicate similarities. Then, reads from replicates were aggregated.

Data analysis

Venn diagrams with eulerr (Larsson 2021) were used to visualize how well morphology (LM of environmental samples and cultures) and DNA metabarcoding were able to identify taxa. Barplot diagrams on genus level were generated for the metabarcoding and morphology data using the R package phyloseq (McMurdie and Holmes 2013). Alpha diversity indices (taxa richness and Shannon diversity index) were calculated with the vegan 2.6 R package (Oksanen et al. 2022). Differences in community structure regarding water types (marine, brackish water and freshwater) and substrate (epipsammic biofilm, biofilm on rocks) between samples based on metabarcoding and morphology at the ASV– and species level respectively were calculated by a Bray–Curtis dissimilarity measure using phyloseq and visualized through non–metric multidimensional scaling (NMDS) ordination. Permutational multivariate analysis of variance (PERMANOVA) was used to evaluate the statistically significant differences in diatom community composition regarding water and substate types for the DNA metabarcoding and the LM dataset. In case of significance, an analysis of similarity percentages (SIMPER) was conducted to identify the taxa contributing most to the differences in community composition. For both the PERMANOVA and the SIMPER analyses the R package vegan was used.

Results

Morphological inventory

In total, 142 diatom taxa were identified through counts of valves in LM, 50 to genus level and 88 to species level (Table 2, Figs 27, 8A). The number of taxa per sample ranged between 2 and 52 with an average of 20 per sample. The additional 23 taxa were found by scanning the whole slides under LM to look for rare taxa, whereby 11 could be unambiguously assigned to a species name (Table 2, Figs 27, 8A). In marine samples 116 taxa were found, in the freshwater samples 93 taxa and in brackish water samples 21 taxa.

Figure 2.

LM pictures of taxa found by morphological analyses. A Odontella litigiosa. B Porosira cf. glacialis. C Thalassiosira scotia. D Thalassiosira antarctica. E Melosira sp. F Unidentified centric diatom. G Minidiscus chilensis. H Orthoseira roeseana. I Shionodiscus gracilis var. expectus. J Actinocyclus actinochilus. K Trigonium arcticum. L Ellerbeckia sol. M Corethron pennatum. Scale bars: 10 µm (A–J); 50 µm (K–M).

Table 2.

List of all taxa observed in light microscopy (LM) with author, references and morphometric information. (R) behind the taxa indicates that it was a rare species just observed in a thorough scan of the slide.

Taxa Author Reference Length [µm] Width [µm] Diameter [µm] Striae RV in 10 µm Striae RLV in 10 µm Areolae in 10 µm Fibulae in 10 µm
Achnanthes bongrainii (M. Peragallo) A. Mann Peragallo 1921: p. 11, pl: I figs 4–6; as A. brevipes in Scott and Thomas 2005: p. 121, fig. 2.65; Zidarova et al. 2022: p. 91, fig. 3 27.2–50.3 7.6–11.1 6–8 6–7
Achnanthes vicentii Manguin Manguin 1957: p. 124, pl. V, fig. 26a–e; Zidarova et al. 2022: p. 93, fig. 4D–G 4.6–16.2 4.0–7.1 12–16 11–16
Achnanthes sp. 1 21.8–32.4 8.4–10.3 8–10 8
Achnanthes sp. 2 16.2–47.8 6.2–10.5 6–8 6–8
Achnanthes sp. 3 31.8–34.3 4.0–5.5 11 9–10
Achnanthes sp. 4 (R) 13.9–23.4 4.3–4.5 10 8–10
Achnanthes sp. 5 (R) 48.5 9.8 6
Achnanthidium australexiguum Van de Vijver Taylor et al. 2014: p. 47, figs 65–92 13.1–16.9 5.6–7.4 26–28 24–26
Achnanthidium cf. maritimo-antarcticum Van de Vijver & Kopalová Van de Vijver and Kopalová 2014: p. 6, figs 29–53 14.0–16.9 2.3–2.6 28–32
Actinocyclus actinochilus (Ehrenberg) Simonsen Villareal and Fryxell 1983: p. 461, figs 21–32; Scott and Thomas 2005: p. 52, fig. 2.22; Al-Handal et al. 2022: p. 85, figs 20, 21 57.5 9–10
Amphora gourdonii M. Peragallo Peragallo 1921: p. 60, pl. II, fig. 23; Al-Handal and Wulff 2008b: p., fig. 85; Zidarova et al. 2022: fig. 10Y 23.2–64.4 6.6–10.8 9–13
Amphora cf. gourdonii (R) M. Peragallo Peragallo 1921: p. 60, pl. II, fig. 23; Al-Handal and Wulff 2008b: p., fig. 85; Zidarova et al. 2022: fig. 10Y 25.7–37.3 4.8–7.2 11–16
Amphora cf. pusio (R) Cleve Levkov 2009: 112, pl. 76, figs 22–30 21.4–30.3 3.9–6.8 13–17
Amphora sp. (R) 37.7 7.5 11
Australoneis frenguelliae (Riaux-Gobin & J.M.Guerrero) J.M.Guerrero & Riaux-Gobin Guerrero et al. 2021: figs 1–75 22.4–34.3 12.5–20.5 4–5 5–6
Berkeleya rutilans (Trentep. ex Roth) Grunow Witkowski et al. 2000: p. 157, pl. 62, figs 14–17; Scott and Thomas 2005: 148, fig. 283d 21.6–24.6 5.6–6.9 28–30
Berkeleya cf. sparsa (R) Mizuno Witkowski et al. 2000: p. 158, pl. 62, figs 7–9 24.8–35.9 5.0–6.0 22–26
Biremis ambigua (Cleve) D.G. Mann Simonsen 1992: p. 42, pl. 40, figs 4–10; Witkowski et al. 2000: p. 158, pl. 155, figs 2–6; Al-Handal et al. 2022: p. 93, figs 75, 76 33.7–48.8 5.0–5.8 6–8
Brachysira minor (Krasske) Lange Bertalot Lange-Bertalot and Moser 1994: p. 47, pl. 47, figs 1–8; Zidarova et al. 2016a: p. 250, pl. 110, figs 1–25 10.4–18.1 3.4–4.3
Brandinia charcotii (Perag.) Zidarova & P.Ivanov Peragallo 1921: p. 68, pl. III, fig. 5; Zidarova et al. 2022, p. 94, fig. 5 68.7 8.7 13
Caloneis australis Zidarova, Kopalova & Van de Vijver Zidarova et al. 2016b: p. 40, figs 1–17 25.6 4.3 22
Chamaepinnularia australis Schimani & N. Abarca Schimani et al. 2023: p. 8, figs 7–9 9.7–19.2 4.2–5.5 18–24
Chamaepinnularia gerlachei Van de Vijver & Sterken Van de Vijver et al. 2010: p. 432, figs 1–18 9.0–21.8 3.1–5.2 16–20
cf. Chamaepinnularia 17.7–39.9 3.6–5.1 14–15
cf. Cocconeis 1 10.6–22.2 6.5–15.2 14–19 14–18
Cocconeis antiqua Tempère & Brun Romero 2011: p. 185, figs 13–35 49.3–79.0 31.1–51.5 11–15 13–19
Cocconeis californica Grunow Witkowski et al. 2000: p. 102, pl. 36, figs 29, 30, pl. 42, figs 8–15; Riaux-Gobin and Romero 2003: p. 21, pl. 8–10 11.2–24.8 6.4–15.5 17–20 11–16
Cocconeis costata Gregory Riaux-Gobin and Romero 2003: p. 22, pl. 1–2; Al-Handal and Wulff 2008b: p. 425, figs 43, 44; Zidarova et al. 2022: fig. 8D 14.9–30.4 8.3–15.0 10–12 8–10
Cocconeis dallmannii Al-Handal, Riaux-Gobin, Romero & Wulff Al-Handal et al. 2008: p. 275, figs 33–48 11.9–20.7 8.2–14.9 13–19 10–12
Cocconeis fasciolata (Ehrenberg) Brown Riaux-Gobin and Romero 2003: p. 26, pl. 19; Scott and Thomas 2005: p. 127, fig. 2.68a–d; Al-Handal and Wulff 2008b: p. 426, figs 45, 51, 52; Zidarova et al. 2022: fig. 8F, G 21.7–45.0 12.4–28.3 5–6 5–7
Cocconeis imperatrix A. Schmidt Manguin 1960: p. 305, pl. 24, figs 358, 359; Riaux-Gobin and Romero 2003: p. 28, pl. 21, figs 1–8; Al-Handal and Wulff 2008b: 426, figs 46–49, 55, 56; Al-Handal et al. 2022: p. 91, fig. 52 47.2–68.8 31.8–44.4 4–5 4–5
Cocconeis infirmata Manguin Manguin 1957: p. 123, pl. V, fig. 24a–c 10.7–24.9 6.0–17.4 8–16
Cocconeis matsii (Al-Handal, Riaux-Gobin & Wulff) Riaux-Gobin, Compère, Romero & D.M.Williams Al-Handal et al. 2010: p. 6, figs 13–15, 25–30 9.2–19.4 5.7–11.9 5–8
Cocconeis melchioroides Al-Handal, Riaux-Gobin, Romero & Wulff Al-Handal et al. 2008: p. 271, figs 2–15, 18–32 9.9–20.4 7.0–10.6 12–14 6–10
Cocconeis pottercovei Al-Handal, Riaux-Gobin et Wulff Al-Handal et al. 2010: p. 3, figs 2–12, 19–24 11.2–14.8 7.1–8.9 11–13 10–12
Corethron pennatum (Grunow) Ostenfeld Van Heurck 1909: p. 30, pl. VI, fig. 86; Crawford et al. 1998: p. 5, figs 1, 6–25 17.8
Craspedostauros laevissimus (West & G.S.West) Sabbe Sabbe et al. 2003: p. 235, figs 35–37, 85; Van de Vijver et al. 2012: p. 154, figs 24–39 30.2–49.4 4.7–5.6 26–29
Diploneis sp. 17.8 6.6 16
Ellerbeckia sol (Ehrenberg) R.M.Crawford & P.A.Sims as Melosira sol in Scott and Thomas 2005: p. 66, fig. 2.32; Al-Handal et al. 2022: p. 85, figs 9, 10 94.4–102.6
Encyonema ventricosum (C.Agardh) Grunow Lange-Bertalot et al. 2017: p. 209, pl. 89, figs 18–22 12.9–23.4 4.7–6.4 15–19
Entomoneis sp. 52.1–53.2 6.5–11.1 30
Entopyla ocellata (Arnott) Grunow Al-Handal and Wulff 2008b: p. 427, figs 57–62; Al-Handal et al. 2022: p. 89, figs 37, 38, 109–111 60.8 16.6 3
Fallacia marnieri (Manguin) Witkowski, Lange-Bertalot & Metzeltin as Navicula marnieri in Manguin 1957: p. 127, pl. 5, figs 35a, b; Witkowski 2000: p. 207, pl. 71, figs 1–3; Al-Handal and Wulf 2008b: p. 427, figs 105, 106; Zidarova et al. 2022, fig. 9A 10.1(6.1)–24.5 5.4(3.8)–11.0 9–14(15)
Fragilaria cf. parva Tuji & D.M.Williams Zidarova et al. 2016a: p. 36–40, pl. 3–5 16.1–52.1 2.6–4.8 15–20
Fragilaria cf. striatula Lyngbye Zidarova et al. 2022: p. 96, figs AP–R 43.0–51.7 7.5–8.1 13–14
Fragilariopsis curta (Van Heurck) Hustedt Hustedt 1958: p. 160, pl. 11, figs 140–144, pl. 12, fig. 159; Scott and Thomas 2005: p. 171, fig. 2.99; Cefarelli et al. 2010: p. 1466, figs 2a–d, 7a, b 11.7–31.4 5.7–6.6 10–13
Fragilariopsis cylindrus (Grunow ex Cleve) Helmcke & Krieger Scott and Thomas 2005: p., fig. 2.100; Cefarelli et al. 2010: p. 1470, figs 2e–1, 7c–e 3.7–16.4 2.4–3.4 15–16
Fragilariopsis kerguelensis (O’Meara) Hustedt Scott and Thomas 2005: p. 183, fig. 2.101; Cefarelli et al. 2010: p. 1470, figs 3a–h, 7f, g 25.8–27.5 7.8–8.7 5–6 11
Fragilariopsis rhombica (O’Meara) Hustedt Scott and Thomas 2005: p. 179, fig. 2.104; Cefarelli et al. 2010: p. 1475, fig. 5a–e 12.6–33.2 8.4–11.6 11–16
Fragilariopsis separanda Hustedt Hustedt 1958: p. 165, pl. 10, figs 108–112; Scott and Thomas 2005: p. 184, fig. 2.104; Cefarelli et al. 2010: p. 1476, fig. 6a–d 11.8–15.3 7.6–9.1 8–13
cf. Gedaniella 9.3–18.9 2.4–4.4 14–18
Gomphonema maritimo-antarcticum Van de Vijver, Kopalová, Zidarova & Kociolek Van de Vijver et al. 2016a: p. 212, figs 22–74 15.3–39.7 4.7–7.5 10–15
Gomphonemopsis ligowskii Al-Handal & E.W.Thomas Al-Handal et al. 2018: p. 98, figs 2–25 11.4–16.3 2.1–2.9 14–16
Gyrosigma cf. fasciola J.W. Griffith & Henfrey Jahn et al. 2005: p. 306, figs 1–7; Al-Handal and Wulff 2008a: fig. 101; Al-Handal et al. 2022: p. 94, fig. 80 101.2–172.8 12.4–15.9 20–22
Gyrosigma tenuissimum var. angustissimum Simonsen Simonsen 1959: p. 83, pl 12, fig. 7; Cardinal 1986: p. 179, figs 37, 38 155.2–159.6 7.4 19
Gyrosigma sp. 158.0–256.9 15.5–20.4 22–24
cf. Halamphora (R) 21.7 3.0
Halamphora ausloosiana Van de Vijver & Kopalová Van de Vijver et al. 2014a: p. 379, figs 4S–AG, 6 16.4–36.5 4.5–6.9 22–24
Halamphora lineata (Gregory) Levkov Levkov 2009: p. 202, pl. 101, figs 12–19 37.0–44.0 5.8–7.1 15
Halamphora cf. staurophora (Juhlin-Dannfelt) Álvarez-Blanco & S.Blanco Witkowski et al. 2000: p. 150, pl. 163, figs 34, 35; Álvarez and Blanco 2014: p. 65, pl. 36, figs 7, 8 13.7–21.0 3.3–3.6 24
Halamphora cf. veneta (R) (Kützing) Levkov Levkov 2009: p. 242, pl. 94, figs 9–19, p. 102, figs 17–30 39.1 5.8 23
Halamphora sp. 1 (R) 36.9 7.6 16
Halamphora sp. 2 34.9–38.3 4.4–6.2 11–14
Halamphora sp. 3 (R) 17.4–21.0 4.3–5.0 14
Hantzschia amphioxys (R) (Ehrenberg) Grunow Lange-Bertalot et al. 2017: p. 338, pl. 104, figs 1–5 31.5–49.8 6.1–6.3 21–22 4–6
Hantzschia hyperaustralis Van de Vijver & Zidarova Zidarova et al. 2010: p. 326, fig. 6A–I 79.7–109.2 12.4–14.8 20–21 4–7
Hantzschia cf. virgata (Roper) Grunow Witkowski et al. 2000: p. 364, pl. 175, fig. 10, pl. 176, figs 1–3; Sabbe et al. 2003: p. 238, fig. 59; Silva et al. 2019: p. 800, fig. 2(22) 72.3–81.6 7.7–9.0 11–13 24 6
Hippodonta hungarica (Grunow) Lange-Bertalot, Metzeltin & Witkowski Zidarova et al. 2016a: p. 124, pl. 47 12.4–18.2 4.8–5.4 9–10
Humidophila sceppacuerciae Kopalová Kopalová et al. 2015: p. 121, figs 2–26 7.7–9.6 2.1–3.1
Humidophila tabellariaeformis (Krasske) R.L. Lowe et al. Zidarova et al. 2016a: p. 234, pl. 102 13.9–15.0 4.9–5.1 25–26
Licmophora antarctica M. Peragallo Fernandes et al. 2014: p. 469, figs 1–9 47.1–100.5 9.6–12.6 6–7
Licmophora belgicae (R) M. Peragallo Fernandes et al. 2014: p. 470, figs 10–20 134.6 15.6 11
Licmophora cf. gracilis (Ehrenberg) Grunow Witkowski et al. 2000: p. 65, pl. 18, figs 12–15, pl. 19, figs 7–15; Al-Handal and Wulff 2008b: p. 429, figs 6–8; Fernandes et al. 2014: p. 471, figs 21–29; Al-Handal et al. 2022: p. 88, fig. 33 22.2–56.9 5.0–12.2 17–25
Luticola australomutica Van de Vijver Van de Vijver and Mataloni 2008: p. 458, figs 39–51 18.8 6.7 20
Luticola austroatlantica (R) Van de Vijver, Kopalová, Spaulding & Esposito Esposito et al. 2008: p. 1383, figs 9–27 21.4–23.6 7.4 16
Luticola desmetii Kopalová & Van de Vijver Kopalová et al. 2011: p. 47, figs 2–13 21.9–29.3 10.6–12.6 15–16
Luticola higleri Van de Vijver, Van Dam & Beyens Van de Vijver et al. 2006: p. 71, figs 3–42 10.7–28.5 7.2–10.3 12–18
Luticola cf. muticopsis (Van Heurck) D.G. Mann Zidarova et al. 2016a: p. 188, pl. 79 13.7–20.0 6.6–8.2 16
Luticola cf. truncata Kopalová & Van de Vijver Kopalová et al. 2009: p. 118, figs 34–50 13.7–20.0 6.6–8.2 16
Mayamaea cf. permitis (Hustedt) K.Bruder & Medlin Lange-Bertalot et al. 2017: p. 366, pl. 50, figs 13–19; Zidarova et al. 2016a: p. 260, pl. 115, figs 1–19 6.4–7.3 3.3–3.5
Mayamaea sweetloveana Zidarova, Kopalová & Van de Vijver Zidarova et al. 2016b: p. 43, figs 46–58 6.8–7.7 3.8–4.7 20–26
Minidiscus chilensis Rivera Rivera and Kock 1984: p. 281, pl. 2, 3, figs 5–14; Kang et al. 2003: p. 95, figs 2, 3; Kaczmarska et al. 2009: p. 463, figs 1, 2 2.9–3.5
Navicula australoshetlandica Van de Vijver Van de Vijver et al. 2011: p. 287, figs 2–15 13.0–30.5 4.5–6.0 12–15
Navicula concordia Riaux-Gobin & Witkowski Witkowski et al. 2010: p. 121, figs 8–24 19.5–30.5 4.7–6.9 13–15
Navicula cremeri Van de Vijver & Zidarova Van de Vijver et al. 2011: p. 289, figs 30–45 27.3 5.5 12
Navicula criophiliforma Witkowski, Riaux-Gobin & Daniszewska-Kowalczyk Witkowski et al. 2010: p. 121, figs 25–38 23.3–55.9 5.8–8.5 11–13
Navicula directa (W.Smith) Ralfs Witkowski et al. 2000: p. 275, pl. 129, fig. 1, pl. 133, figs 10–12; Scott and Thomas 2005: p. 157, fig. 2.87a–d; Al-Handal and Wulff 2008a: p. 64–66, 95; Zidarova et al. 2022: fig. 9N 67.7–123.6 8.2–13.1 7–9
Navicula glaciei Van Heurck Van Heurck 1909: p. 11, pl. I, fig. 13; Scott and Thomas 2005: p. 158, fig. 2.89; Zidarova et al. 2022: fig. 9H 16.3–25.6 5.2–6.7 13–18
Navicula gregaria Donkin Van de Vijver et al. 2002: p. 64, pl. 35, figs 9–18, pl. 36, fig. 3 16.4–25.6 5.1–6.6 16–20
Navicula cf. pagophila var. manitounukensis (R) Poulin & Cardinal Poulin and Cardinal 1982: p. 2836, fig. 3; Witkowski et al. 2000: p. 293, p. 128, figs 4–6 27.0–32.1 10.8–12.8 21–26
Navicula cf. perminuta Grunow Busse and Snoeijs 2002: p. 277, figs 11–15, 34–40; Lange-Bertalot et al. 2017: p. 400, pl. 30, figs 25–32; Al-Handal et al. 2022: p. 92, figs 69, 70 5.5–19.9 1.9–5.0 12–20
Navicula sp. 2 20.9–48.6 3.6–6.6 12–16
Navicula sp. 3 18.0–31.5 3.9–5.4 10–15
Navicula sp. 4 14.2–24.0 2.8–3.7 11–14
Navicula sp. 5 16.9–48.9 4.4–7.4 10–14
Navicula sp. 6 21.8–24.4 3.8–4.3 12–14
Navicula sp. 7 14.4–28.1 4.3–5.2 12–15
Navicula sp. 8 17.8–29.6 3.0–4.7 9–11
Navicula sp. 9 14.0–17.3 2.9–3.3 19–21
Navicula sp. 10 40.3–57.7 5.8–7.4 8–9
Navicula sp. 11 27.3–31.4 4.9–5.3 8–9
Navicula sp. 12 31.9–42.2 6.4–7.6 8–9
Navicula sp. 13 16.5–31.9 4.5–6.3 11–14
Navicula sp. 14 6.0–13.5 3.2–5.5 14–20
Nitzschia annewillemsiana Hamsher, Kopalová, Kociolek, Zidarova & Van de Vijver Hamsher et al. 2016: p. 81, figs 2–22; Zidarova et al. 2016: p. 422, pl. 194 10.6–23.1 2.9–4.1 24–26 10–12
Nitzschia kleinteichiana Hamsher, Kopalová, Kociolek, Zidarova & Van de Vijver Hamsher et al. 2016: p. 88, figs 77–97; Zidarova et al. 2016: p. 430, pl. 198 14.2–23.3 2.5–3.3 25–29 10–14
Nitzschia cf. gracilis Hantzsch Hamsher et al. 2016: p. 83, figs 37–59; Zidarova et al. 2016a: p. 426, pl. 196 29.0–54.7 2.5–4.3 14–18
Nitzschia homburgiensis Lange-Bertalot Hamsher et al. 2016: p. 86, figs 60–76; Zidarova et al. 2016: p. 428, pl. 197 29.1–39.2 3.9–5.1 10–16
Nitzschia cf. hybrida Grunow Witkowski et al. 2000: p. 386, pl. 191, figs 12–14; Al-Handal and Wulff 2008b: p. 429, fig. 117; Al-Handal and Wulff 2008a: fig. 122 59.8–73.5 5.1–6.9 24–25 8–12
Nitzschia medioconstricta Hustedt Hustedt 1958: p. 174, pl. 13, figs 165, 166; Scott and Thomas 2005: p. 191, fig. 2.108d–f 52.3–72.1 4.4–6.8 24–26 8–11
Nitzschia soratensis Morales & Vis Morales and Vis 2007: p. 128, figs 253–256, 277–280; Zidarova et al. 2016a: p. 434, pl. 200 6.4–17.1 2.6–3.5 28–30 8–12
Nitzschia sp. 1 (R) 17.6 3.5 13
Nitzschia sp. 2 23.9–31.6 2.9–4.4 10–12
Nitzschia sp. 4 32.8–44.3 4.1–6.8 24–29 8–12
Nitzschia sp. 5 41.4–48.1 3.6–3.7 9–11
Nitzschia sp. 6 22.3–28.2 4.4–5.5 14–17
Nitzschia sp. 7 12.2–24.3 3.1–5.0 12–17
Odontella litigiosa (Van Heurck) Hoban as Biddulphia litigiosa in Van Heurck 1909: p. 40, pl. 10, fig. 141; Scott and Thomas 2005, p. 48, fig. 2.20a–f; Al-Handal and Wulff 2008b: p. 430, figs 80–82; Al-Handal et al. 2022: p. 87, figs 24–26 23.6–52.5 17.6–60.7
Orthoseira roeseana (R) (Rabenhorst) Pfitzer Zidarova et al. 2016a: p. 34, pl. 2 13.3
Parlibellus cf. schuetii (R) (Van Heurck) E.J.Cox Van Heurck 1909: p. 13, pl. I, fig. 10 71.0 24.0 14
Petroneis cf. plagiostoma (Grunow) D.G.Mann Witkowski et al. 2000: p. 329, pl. 102, figs 5, 6 36.6–48.8 18.1–20.8 10–12 6–12
Petroneis sp. 1 19.0–22.0 7.7–8.1 19 12–20
Petroneis sp. 2 21.3–26.6 10.2–11.1 16–19 12–20
Pinnularia australoglobiceps Zidarova, Kopalová & Van de Vijver Zidarova et al. 2016a: p. 362, pl. 166 30.1–35.8 10.4–12.9 12–14
Pinnularia australomicrostauron Zidarova, Kopalová & Van de Vijver Zidarova et al. 2016a: p. 364–368, pl. 167–169 24.7–63.0 9.7–12.7 12–14
Pinnularia australorabenhorstii (R) Van de Vijver Van de Vijver 2008: p. 224, figs 7–15, 24–28 42.0 16.7 6–8
Pinnularia borealis (R) Ehrenberg Zidarova et al. 2016a: p. 376, 378, pl. 173, 174 42.3 9.0 5–6
Pinnularia parallelimarginata Simonsen Simonsen 1992: p. 41, pl. 42, figs 1–8 30.5 5.1 15
Pinnularia cf. quadratarea (A.Schmidt) Cleve Witkowski et al. 2000: p. 335, pl. 155, figs 17–21; Al-Handal and Wulff 2008a: figs 76, 77; Al-Handal and Wulff 2008b: p. 430, fig. 116 18.0–79.8 6.1–10.5 8–12
Pinnularia subantarctica var. elongata (R) (Manguin) Van de Vijver & Le Cohu Van de Vijver et al. 2002: p. 96, pl. 114, figs 1–11 25.9–32.2 5.5–6.0 14
Placoneis australis Van de Vijver & Zidarova Zidarova et al. 2009: p. 301, figs 44–58, 62–64 21.4–23.0 6.5–7.4 14–18
Planothidium australe (Manguin) Le Cohu Zidarova et al. 2016a: p. 98, pl. 34 12.3–22.3 7.4–9.6 13–17 14–17
Planothidium quadripunctatum (Oppenheim) Sabbe Van de Vijver et al. 2002: p. 101, pl. 23, figs 42–49 8.4–9.8 3.9–4.5 16–18 16–17
Planothidium rostrolanceolatum Van de Vijver, Kopalová & Zidarova Van de Vijver et al. 2013: p. 109, figs 61–84 15.0–27.5 5.3–7.9 13–16 13–16
Planothidium wetzelii Schimani, N.Abarca & R.Jahn Juchem et al. 2023 10.9–18.8 5.6–6.7 14–18 14–18
Planothidium sp. 13.6–19.9 5.6–8.6 10–13 10–12
Pleurosigma sp. 1 189.4–225.5 20.7–20.8 13–15
Pleurosigma sp. 2 153.2–187.2 20.7–24.4 21–22
Porosira cf. glacialis (Grunow) Jørgensen Scott and Thomas 2005: p. 84, fig. 2.41; Al-Handal et al. 2022: p. 83, figs 2–4 19.5–81.0 18–22
Psammothidium germainii (Manguin) Sabbe Van de Vijver et al. 2016b: p 146, figs 9–81 19.7 9.6 22
Psammothidium germainioides (R) Van de Vijver, Kopalová & Zidarova Van de Vijver et al. 2016b: p 150, figs 108–138 15.7 6.8 28
Psammothidium incognitum (Krasske) Van de Vijver Van de Vijver et al. 2002: p. 105, pl. 29, figs 1–11, pl. 30, figs 1, 2; Zidarova et al. 2016a: p. 86, pl. 28 13.8–16.3 5.0–5.6
Psammothidium manguinii (R) (Hustedt) Van de Vijver Van de Vijver et al. 2002: p. 106, pl. 29, figs 20–33, pl. 30, figs 5–8; Zidarova et al. 2016a: p. 88, pl. 29 14.3 6.6 23 22
Psammothidium papilio (D:E. Kellogg, M. Stuiver, T.B. Kellogg & G.H. Denton) Kopalová & Van de Vijver Kopalova et al. 2012: p. 204, fig. 5Q–T; Zidarova et al. 2016a: p. 90, pl. 30 8.5–14.7 4.3–5.8 24–30 24–30
Psammothidium rostrogermainii Van de Vijver, Kopalová & Zidarova Van de Vijver et al. 2016b: p 148, figs 82–107 16.0–19.3 8.1–8.8 16 18
Pseudogomphonema kamtschaticum (Grunow) Medlin Medlin and Round 1986: p. 216, fig. 29; Scott and Thomas 2005: p. 163, figs 2.93, 2.94a, b; Al-Handal and Wulff 2008b: p. 439, figs 95–100; Zidarova et al. 2022: fig. 10A 9.9–51.6 3.2–7.5 10–16
Pteroncola carlinii Almandoz & Ferrario Almandoz et al. 2014: p. 189, figs 1–15 5.0–23.4 2.5–3.3
Rhabdonema sp. 134.3–135.2 21.3–25.6 5–6
Rhoicosphenia michalii Ligowski Ligowski et al. 2014: p. 143, figs 1–69 20.5–27.9 3.7–5.9 7–8
Sabbea cf. adminii (D.Roberts & McMinn) Van de Vijver, Bishop & Kopalová Bishop et al. 2019: p. 45, figs 1–-29 31.1–32.0 4.5–4.6
Sellaphora jamesrossensis (Kopalová, & Van de Vivjer) Van de Vivjer & C.E. Wetzel as Eolimna jamesrossensis in Kopalová et al. 2009: p. 116, figs 15–33, Zidarova et al. 2016a: p. 246, pl. 108 11.8–14.2 5.5–6.0 20–22
Shionodiscus gracilis var. expectus (VanLandingham) Alverson, Kang et Theriot as Thalassiosira gracilis var. expecta in Johansen and Fryxell 1985: p. 170, figs 8, 60–63; Alverson et al. 2006: p. 259 9.9–13.6 14–18
Stauroneis acidojarensis (R) Zidarova, Kopalová & Van de Vijver Zidarova et al. 2014: p. 197, figs 13–29 45.2 9 22
Stauroneis latistauros Van de Vijver & Lange Bertalot Van de Vijver et al. 2004: p. 48, pl. 49; Zidarova et al. 2016: p. 318–322, pl. 144–146 26.4–35.1 7.4–8.4 20–24
Stauroneis pseudomuriella (R) Van de Vijver & Lange Bertalot Vijver et al. 2004: p. 56, pl. 61; Zidarova et al. 2016: p. 330, pl. 150 21.4–29.9 4.8–5.0 22
Staurosira pottiezii Van de Vijver Van de Vijver et al. 2014b: p. 257, figs 1–25 25.8 4.2 13
Synedropsis cf. recta Hasle, Medlin & Syvertsen Hasle et al. 1994: p. 252, figs 27–30, 51–55, 57–60, 68–75 6.4–54.7 3.0–6.9 9–15
Thalassionema gelida M.Peragallo Peragallo 1921: p .69, pl. III, fig. 10; Zidarova et al. 2022: p. 102, fig. 7 63.1–153.5 3.5–6.3 10–11
Thalassiosira antarctica Comber Johansen and Fryxell 1985: p. 158, figs 15–17, 37–39 29.0–44.6 13–15
Thalassiosira scotia Fryxell & Hoban Johansen and Fryxell 1985: p. 176, figs 25, 26, 40–42 21.9–29.1 8–9
Trachyneis aspera (Ehrenberg) Cleve Witkowski et al. 2000: p. 355, pl. 139, fig. 14, pl. 159, figs 1–6, 9; Al-Handal and Wulff 2008b: p. 432, figs 89, 90, 101; Al-Handal et al. 2022: 93, fig. 74 94.0–188.7 17.5–31.7 7–8
Trigonium arcticum (Brightwell) Cleve Scott and Thomas 2005: p. 18, fig. 2.6; Al-Handal et al. 2022: p. 87, fig. 22 123.0 3–4
Tripterion cf. margaritae (Frenguelli & Orlando ex Fernandes & Sar) Fernandes & Sar Fernandes and Sar 2009: p. 67, figs 2–62 12.1–16.2 3.2–4.1 24–25
Unidentified centric diatom 2.8–4.5
Unidentified pennate diatom 12.4 3.0 12

The most abundant taxa (> 2% of all counts per habitat, Table 3) across marine samples were in decreasing order Navicula cf. perminuta, Minidiscus chilensis P. Rivera, Navicula sp. 5, Pseudogomphonema kamtschaticum (Grunow) Medlin, Achnanthes vicentii Manguin, Gyrosigma sp., Synedropsis cf. recta and Cocconeis fasciolata (Ehrenberg) N.E.Brown. Across brackish water samples Navicula gregaria Donkin, Navicula australoshetlandica Van de Vijver, Chamaepinnularia australis Schimani & N.Abarca, Nitzschia cf. gracilis, Nitzschia sp. 6, Halamphora ausloosiana Van de Vijver & Kopalová and Planothidium australe (Manguin) Le Cohu were the most abundant taxa. Across the freshwater samples Nitzschia annewillemsiana Hamsher, Kopalová, Kociolek, Zidarova & Van de Vijver, Nitzschia kleinteichiana Hamsher, Kopalová, Kociolek, Zidarova & Van de Vijver, Mayamaea sweetloveana Zidarova, Kopalová & Van de Vijver, an unidentified centric diatom, Nitzschia soratensis E.A.Morales & M.L.Vis, Psammothidium papilio (D.E.Kellogg, Stuiver, T.B.Kellogg & G.H.Denton) K. Kopalová & Van de Vijver, Achnanthidium cf. maritimoantarcticum, Fragilaria cf. parva, Planothidium quadripunctatum (D.R.Oppenheim) Sabbe, Planothidium rostrolanceolatum Van de Vijver, Kopalová & Zidarova and Nitzschia cf. gracilis were the most abundant taxa.

Table 3.

Most abundant taxa (> 2% of average abundance) across marine, brackish water and freshwater samples for morphology count (LM) and metabarcoding rbcL and 18SV4, AA: average abundance across the habitat, NA: not taxonomically assigned. Several ASVs were assigned to the same taxon through the metabarcoding pipeline.

LM AA [%] rbcL AA [%] 18SV4 AA [%]
Marine samples
Navicula cf. perminuta 51.8 Navicula cf. perminuta 13.3 NA 24.8
Minidiscus chilensis 6.2 Navicula cf. perminuta 11.3 Navicula cf. perminuta 20.3
Navicula sp. 5 5.5 NA 11.0 NA 4.7
Pseudogomphonema kamtschaticum 4.5 NA 6.3 Paralia sol (syn. Ellerbeckia sol) 4.6
Achnanthes vicentii 3.1 NA 4.5 NA 4.4
Gyrosigma sp. 2.8 NA 3.7 Thalassiosira minima 2.5
Synedropsis cf. recta 2.2 Navicula cf. perminuta 3.2 Navicula directa 2.4
Cocconeis fasciolata 2.2 Minidiscus chilensis 2.9
Navicula sp. 2.9
Licmophora cf. gracilis 2.8
NA 2.5
Ellerbeckia sp. 2.2
NA 2.2
Brackish water samples
Navicula gregaria 52.3 Navicula gregaria 33.9 Pinnularia australomicrostauron 47.4
Navicula australoshetlandica 13.3 Navicula australoshetlandica 11.7 Navicula gregaria 20.6
Chamaepinnularia australis 7.1 Nitzschia sp. 8.8 Navicula cf. veneta 7.0
Nitzschia cf. gracilis 6.2 Pinnularia australomicrostauron 6.7 Nitzschia sp. 4.1
Nitzschia sp. 6 6.0 Navicula gregaria 6.4 Pinnularia australomicrostauron 2.8
Halamphora ausloosiana 5.3 Chamaepinnularia australis 5.2 Pinnularia australomicrostauron 2.6
Planothidium australe 2.2 NA 5.1
Nitzschia cf. gracilis 5.0
Halamphora ausloosiana 3.2
Pinnularia australoglobiceps 3.0
Nitzschia sp. 2.3
Freshwater samples
Nitzschia annewillemsiana 19.4 Mayamaea sweetloveana 13.6 Pinnularia australomicrostauron 28.1
Nitzschia kleinteichiana 16.0 Fragilaria sp. 9.9 Nitzschia cf. frustulum 10.9
Mayamaea sweetloveana 11.4 Nitzschia cf. frustulum 8.5 Gomphonema maritimo-antarcticum 7.7
Unidentified centric diatom 10.8 Nitzschia kleinteichiana 8.3 NA 6.5
Nitzschia soratensis 10.5 Nitzschia sp. 7.6 Fragilaria sp. 5.8
Psammothidium papilio 7.0 NA 6.6 Encyonema sp. 3.4
Achnanthidium cf. maritimo-antarcticum 6.1 Nitzschia cf. gracilis 6.1 Planothidium rostrolanceolatum 3.4
Fragilaria cf. parva 4.6 Encyonema sp. 4.9 Nitzschia cf. gracilis 2.9
Planothidium quadripunctatum 2.4 Achnanthidium sp. 4.2 Achnanthidium sp. 2.4
Planothidium rostrolanceolatum 2.1 Mayamaea cf. permitis 3.6 NA 2.3
Nitzschia cf. gracilis 2.0 Gomphonema maritimo-antarcticum 4.2 Nitzschia sp. 2.2
Planothidium rostrolanceolatum 3.4 Planothidium rostrolanceolatum 2.2
Planothidium cf. pumilum 2.6
Nitzschia sp. 2.0

Antarctic taxonomic reference library

A total of 162 clonal cultures were established, resulting in the identification of 60 taxa: 33 of those taxa could be identified to species level, 23 to genus level and 4 where the genus affiliation is inconclusive (Table 4).

Table 4.

Taxa which were established as clonal cultures, strain numbers, in case of publication: reference and accession number.

Taxon Strain Voucher at BGBM DNA Bank Publication of strain Accession number rbcL Accession number 18SV4
Achnanthes vicentii D305_008 B 40 0045332 DB43189
D322_002 B 40 0045222 DB43092
D326_020 B 40 0045334 DB43015
Brachysira minor D300_027 B 40 0045258 DB42968
D300_029 B 40 0045305 DB43129
Chaetocerus cf. neogracilis D305_007 B 40 0046208 DB43188
Chamaepinnularia australis D294_001 B 40 0045203 DB43033 (Schimani et al. 2023) OX386460 OX386235
D294_002 B 40 0045204 DB43034 (Schimani et al. 2023) OX386461 OX386236
D294_013 B 40 0045208 DB43043 (Schimani et al. 2023) OX386464 OX386239
D294_014 B 40 0045209 DB43074 (Schimani et al. 2023) OX386465 OX386240
Chamaepinnularia gerlachei D294_005 B 40 0045272 DB43037 (Schimani et al. 2023) OX386462 OX386237
D294_006 B 40 0045207 DB43038 (Schimani et al. 2023) OX386463 OX386238
D296_001 B 40 0045355 DB43045 (Prelle et al. 2022; Schimani et al. 2023) OX258987 OX258985
D296_002 B 40 0045356 DB43046 (Schimani et al. 2023) OX386466 OX386241
D297_003 B 40 0045277 DB43047 (Schimani et al. 2023) OX386467 OX386242
cf. Chamaepinnularia D301_002 B 40 0045342 DB42990
Cocconeis fasciolata D326_023 B 40 0045353 DB43018
cf. Cocconeis 1 D301_001 B 40 0045179 DB42989
D301_009 B 40 0045315 DB42997
cf. Cocconeis 2 D326_035 B 40 0045271 DB43025
D326_037 B 40 0045328 DB43027
D326_038 B 40 0045350 DB43028
D326_039 B 40 0045329 DB43029
Cylindrotheca cf. closterium D322_018 B 40 0046211 DB43648 Not available
Fallacia marnieri D301_003 B 40 0045314 DB42991 This study OR355374 Not available
D301_004 B 40 0045217 DB42992 This study OR355375 OR352010
D323_016 B 40 0045268 DB43144 This study Not available OR352011
D326_002 B 40 0045167 DB43001 This study OR355376 OR352012
D326_005 B 40 0045169 DB43003 This study OR355377 OR352013
D326_007 B 40 0045199 DB43005 This study OR355378 OR352014
D326_014 B 40 0045235 DB43010 This study OR355379 OR352015
D326_016 B 40 0045236 DB43012 This study OR355380 OR352016
D326_017 B 40 0045346 DB43013 This study OR355381 OR352017
D326_041 B 40 0045367 DB43209 This study OR355382 OR352018
Fragilaria cf. parva D299_016 B 40 0045214 DB43076
D299_020 B 40 0045279 DB43080
D299_026 B 40 0045255 DB43087
D300_016 B 40 0045284 DB42962
cf. Gedaniella D291_001 B 40 0045201 DB43030
D293_001 B 40 0045170 DB43183
D324_004 B 40 0045231 DB43205
Gomphonema maritimo-antarcticum D299_018 B 40 0045245 DB43078 This study OR355383 OR352019
D299_021 B 40 0045290 DB43081 This study OR355384 OR352020
D299_028 B 40 0045294 DB43089 This study Not available OR352021
D300_013 B 40 0045282 DB42959 This study OR355385 OR352022
D300_014 B 40 0045283 DB42960 This study OR355386 OR352023
D314_002 B 40 0045188 DB42971 This study OR355387 OR352024
D314_004 B 40 0045190 DB42973 This study OR355388 OR352025
D314_014 B 40 0045264 DB42983 This study OR355389 OR352026
D314_019 B 40 0045307 DB42988 This study OR355390 OR352027
Halamphora ausloosiana D294_007 B 40 0045273 DB43039 This study OR355391 OR352028
D294_008 B 40 0045274 DB43040 This study OR355392 OR352029
Hantzschia hyperaustralis D314_011 B 40 0045306 DB42980 This study OR355393 OR352030
Humidophila sceppacuerciae D300_002 B 40 0045280 DB42950 This study OR355394 OR352031
D300_022 B 40 0045302 DB42965 This study OR355395 OR352032
Licmophora cf. gracilis D308_002 B 40 0045343 DB43191
D308_003 B 40 0045220 DB43192
D308_004 B 40 0045316 DB43193
Lunella sp. D292_010 B 40 0045571 DB43435
D309_004 B 40 0045580 DB43438
D323_012 B 40 0045228 DB43140
D326_015 B 40 0045200 DB43011
Luticola higleri D299_001 B 40 0045311 DB43062 This study OR355396 OR352033
D299_010 B 40 0045312 DB43071 This study OR355397 OR352034
Luticola desmetii D300_028 B 40 0045313 DB43128 This study OR355398 OR352035
Mayamaea sweetloveana D299_006 B 40 0045175 DB43067 This study OR355399 OR352036
D299_007 B 40 0045176 DB43068 This study OR355400 OR352037
D299_009 B 40 0045178 DB43070 This study OR355401 OR352038
D304_001 B 40 0045246 DB42998 This study OR355402 OR352039
D304_002 B 40 0045259 DB42999 This study OR355403 Not available
Mayamaea cf. permitis D300_006 B 40 0045241 DB42969
D300_011 B 40 0045256 DB42958
Melosira sp. D323_018 B 40 0045309 DB43146 (Juchem et al. 2023) OR036645 OR042180
D323_019 B 40 0045310 DB43147
Minidiscus chilensis D323_014 B 40 0045229 DB43142 This study OR355404 OR352040
D326_021 B 40 0045325 DB43017 This study OR355405 OR352041
Navicula australoshetlandica D295_001 B 40 0045460 DB43327 This study OR355406 Not available
D300_018 B 40 0045330 DB43123 This study OR355407 OR352042
Navicula concordia D310_004 B 40 0045317 DB43201 (Prelle et al. 2022) OX258991 OX259170
D310_002 B 40 0045186 DB43199 This study OR355408 OR352043
D310_003 B 40 0045187 DB43200 This study OR355409 OR352044
D310_006 B 40 0045576 DB43439 This study OR355410 OR352045
Navicula criophiliforma D288_003 B 40 0045335 DB43182 (Prelle et al. 2022) OX258986 OX259166
D288_002 B 40 0045247 DB43181 This study OR355411 OR352046
D326_027 B 40 0045237 DB43021 This study OR355412 OR352047
D322_014 B 40 0045380 DB43102 This study OR355413 OR352048
Navicula directa D326_001 B 40 0045166 DB43000 This study OR355414 OR352049
Navicula gregaria D294_003 B 40 0045205 DB43035 This study OR355415 OR352050
D300_003 B 40 0045281 DB42951 This study OR355416 OR352051
D300_004 B 40 0045296 DB42952 This study OR355417 OR352052
D300_007 B 40 0045216 DB42954 This study OR355418 OR352053
Navicula cf. perminuta D323_004 B 40 0045159 DB43133
D323_011 B 40 0045322 DB43139
D326_010 B 40 0045233 DB43008
D326_012 B 40 0045234 DB43009
Navicula sp. 1 D326_009 B 40 0045232 DB43007
Navicula sp. 4 D307_001 B 40 0045475 DB43346 Not available
D310_007 B 40 0045583 DB43440 Not available
Navicula sp. 5 D301_007 B 40 0045242 DB42969
D301_008 B 40 0045331 DB42996
Navicula sp. 6 D291_006 B 40 0045474 DB43320
Navicula sp. 13 D310_001 B 40 0045185 DB43198
D326_006 B 40 0045198 DB43004
D326_019 B 40 0045347 DB43014
Nitzschia annewillemsiana D300_012 B 40 0045357 DB43122 (Prelle et al. 2022) OX258988 OX259167
Nitzschia cf. gracilis D299_014 B 40 0045212 DB43074
Nitzschia homburgiensis D299_002 B 40 0045172 DB43063 This study OR355419 OR352054
Nitzschia kleinteichiana D314_005 B 40 0045191 DB42974 This study OR355420 OR352055
D314_008 B 40 0045194 DB42977 This study OR355421 OR352056
Nitzschia medioconstricta D309_001 B 40 0045569 DB43526 This study OR355422 Not available
D309_002 B 40 0045577 DB43527 This study OR355423 Not available
Nitzschia soratensis D300_026 B 40 0045257 DB42967 This study OR355424 OR352057
Nitzschia sp. 3 D322_015 B 40 0045364 DB43103
D322_016 B 40 0045365 DB43104
Nitzschia sp. 4 D310_008 B 40 0045584 DB43441 Not available
Nitzschia sp. 7 D324_002 B 40 0045165 DB43203
Odontella litigiosa D305_005 B 40 0045181 DB43186
D323_008 B 40 0045163 DB43137
Pinnularia australoglobiceps D294_004 B 40 0045206 DB43036
Pinnularia australomicrostauron D299_005 B 40 0045211 DB43066
D314_001 B 40 0045261 DB42970
D314_003 B 40 0045189 DB42972
D314_010 B 40 0045195 DB42979
D314_013 B 40 0045263 DB42982
D314_017 B 40 0045287 DB42986
Pinnularia cf. quadratarea D324_001 B 40 0045164 DB43202
Pinnularia sp. D322_010 B 40 0045321 DB43098 Not available
Planothidium australe D294_010 B 40 0045275 DB43041 This study OR355425 OR352058
D294_011 B 40 0045276 DB43042 This study OR355426 OR352059
D300_005 B 40 0045297 DB42953 This study OR355427 OR352060
Planothidium rostrolanceolatum D299_003 B 40 0045173 DB43064 This study OR355428 OR352061
D299_008 B 40 0045177 DB43069 This study OR355429 OR352062
D299_022 B 40 0045252 DB43082 This study OR355430 OR352063
D300_021 B 40 0045286 DB42964 This study OR355431 OR352064
D314_007 B 40 0045193 DB42976 This study OR355432 OR352065
Planothidium wetzelii D300_015 B 40 0045340 DB42961 (Prelle et al. 2022) OX258989 OX259168
D300_019 B 40 0045358 DB43124 (Juchem et al. 2023) OR036648 OR042183
D300_020 B 40 0045301 DB43125 (Juchem et al. 2023) OR036647 OR042182
D300_025 B 40 0045341 DB42966 (Juchem et al. 2023) OR036646 OR042181
Planothidium sp. D326_029 B 40 0045349 DB43022 Not available
Pleurosigma sp. 2 D293_002 B 40 0045202 DB43184
D322_007 B 40 0045320 DB43097
D323_001 B 40 0045226 DB43130
D323_002 B 40 0045267 DB43131
D323_003 B 40 0045227 DB43132
D324_003 B 40 0045230 DB43204
D326_003 B 40 0045197 DB43002
Porosira cf. glacialis D308_005 B 40 0045182 DB43194
D323_005 B 40 0045160 DB43134
Psammothidium papilio D300_023 B 40 0045303 DB43126 (Prelle et al. 2022) OX258990 OX259169
D299_012 B 40 0045238 DB43072 This study OR355433 OR352066
D299_013 B 40 0045239 DB43073 This study OR355434 OR352067
Psammothidium papilio D299_023 B 40 0045291 DB43083 This study OR355435 OR352068
D299_024 B 40 0045253 DB43084 This study OR355436 OR352069
D299_025 B 40 0045254 DB43086 This study OR355437 OR352070
D300_001 B 40 0045295 DB43121 This study OR355438 OR352071
D300_010 B 40 0045300 DB42957 This study OR355439 OR352072
D314_015 B 40 0045319 DB42984 This study OR355440 OR352073
Stauroneis latistauros D314_009 B 40 0045318 DB42978 This study OR355441 OR352074
D314_016 B 40 0045344 DB42985 This study OR355442 OR352075
Surirella australovisurgis D300_017 B 40 0045285 DB42963
Synedropsis cf. recta D305_003 B 40 0045180 DB43185

From the 60 taxa, only six had a sequence record in the International Nucleotide Sequence Database Collaboration (INSDC) databases (DDBJ, EMBL–EBI and NCBI) and 54 are new sequenced taxa. Some sequences from our Antarctic cultures were already published with a thorough morphological examination and in two cases with the description of a new species (Prelle et al. 2022; Juchem et al. 2023; Schimani et al. 2023).

Figure 3.

LM pictures of taxa found by morphological analyses. A Brandinia charcotii. B Fragilaria cf. striatula. C Fragilaria cf. parva. D cf. Gedaniella. E Pteroncola carlinii. F Synedropsis cf. recta. G Staurosira pottiezii. H Unidentified pennate diatom. I Licmophora antarctica. J Licmophora belgicae. K Thalassionema gelida. L Rhabdonema sp. M Cocconeis pottercovei. N Cocconeis infirmata. O, P Cocconeis matsii. Q Entopyla ocellata. R Licmophora cf. gracilis. Scale bar: 10 µm.

Figure 4.

LM pictures of taxa found by morphological analyses. A Achnanthes bongrainii. B Achnanthes vicentii. C Achnanthes sp. 1. D Achnanthes sp. 2. E Achnanthes sp. 4. F Achnanthes sp. 5. G Psammothidium rostrogermainii. H Achnanthes sp. 3. I Psammothidium germainii. J Psammothidium incognitum. K Achnanthidium australexiguum. L Psammothidium manguinii. M Planothidium wetzelii. N Achnanthidium cf. maritimo-antarcticum. O Psammothidium germainioides. P Planothidium rostrolanceolatum. Q Psammothidium papilio. R Planothidium quadripunctatum. S Planothidium sp. T cf. Cocconeis 2. U Planothidium australe. V Cocconeis melchioroides. W Cocconeis californica. X Australoneis frenguelliae. Y Cocconeis fasciolata. Z cf. Cocconeis 1. AA Cocconeis dallmannii. AB Cocconeis antiqua. AC Cocconeis imperatrix. AD Cocconeis costata. Scale bars: 10 µm (A–AA, AD); 30 µm (AB, AC).

Figure 5.

LM pictures of taxa found by morphological analyses. A Navicula sp. 3. B Navicula sp. 12. C Navicula sp. 1. D Navicula sp. 5. E Navicula sp. 10. F Navicula criophiliforma. G Navicula sp. 2. H Navicula directa. I Trachyneis aspera. J Navicula concordia. K Navicula sp. 13. L Navicula glaciei. M Navicula gregaria. N Navicula sp. 14. O Navicula cf. perminuta. P Navicula sp. 8. Q Navicula cremeri. R Navicula sp. 11. S Navicula sp. 6. T Navicula sp. 7. U Navicula australoshetlandica. V Navicula cf. pagophila var. manitounukensis. W Sabbea cf. adminii. X Navicula sp. 9. Y Navicula sp. 4. Z Petroneis cf. plagiostoma. AA Petroneis sp. 2. AB Petroneis sp. 1. AC Berkeleya rutilans. AD Berkeleya cf. sparsa. AE Mayamaea sweetloveana. AF Mayamaea cf. permitis. AG Sellaphora jamesrossensis. AH Stauroneis acidojarensis. AI Stauroneis latistauros. AJ Stauroneis pseudomuriella. AK Diploneis sp. AL Fallacia marnieri. AM Placoneis australis. AN Lunella sp. AO Humidophila sceppacuerciae. AP Brachysira minor. AQ Humidophila tabellariaeformis. AR Hippodonta hungarica. Scale bar: 10 µm.

Figure 6.

LM pictures of taxa found by morphological analyses. A Luticola cf. truncata. B Luticola cf muticopsis. C Luticola desmetii. D Luticola higleri. E Luticola austroatlantica. F Luticola australomutica. G Parlibellus cf. schuetii. H Pinnularia borealis. I Pinnularia australorabenhorstii. J Pinnularia sp. K Pinnularia australomicrostauron. L Biremis ambigua. M Pinnularia cf. quatratarea. N Pinnularia australoglobiceps. O Pinnularia parallelimarginata. P Pinnularia subantarctica var. elongata. Q Caloneis australis. R cf. Chamaepinnularia. S Chamaepinnularia australis. T Chamaepinnularia gerlachei. U Pseudogomphonema kamtschaticum. V Gomphonema maritimo-antarcticum. W Rhoicosphenia michalii. X Gomphonemopsis ligowskii. Y Tripterion cf. margaritae. Z Encyonema ventricosum. AA Halamphora cf. staurophora. AB cf. Halamphora. AC Amphora gourdonii. AD Amphora sp. AE Halamphora cf. veneta. AF Halamphora sp. 2. AG Halamphora sp. 3. AH Halamphora ausloosiana. AI Amphora cf. pusio. AJ Halamphora sp. 1. AK Halamphora lineata. Scale bar: 10 µm.

Figure 7.

LM pictures of taxa found by morphological analyses. A Nitzschia cf. hybrida. B Nitzschia medioconstricta. C Nitzschia sp. 4. D Nitzschia sp. 3. E Nitzschia sp. 5. F Pleurosigma sp. 2. G Pleurosigma sp. 1. H Gyrosigma tenuissimum var. angustissimum. I Gyrosigma sp. J Nitzschia sp. 6. K Nitzschia sp. 7. L Nitzschia sp. 2. M Nitzschia homburgiensis. N Nitzschia cf. gracilis. O Nitzschia kleinteichiana. P Nitzschia sp. 1. Q Nitzschia soratensis. R Nitzschia annewillemsiana. S Entomoneis sp. T Hantzschia cf. virgata. U Hantzschia amphioxys. V Hantzschia hyperaustralis. W Gyrosigma cf. fasciola. X Surirella australovisurgis. Y Fragilariopsis kerguelensis. Z Fragilariopsis curta. AA Fragilariopsis separanda. AB Fragilariopsis cylindrus. AC Fragilariopsis rhombica. Scale bars: 10 µm (A–E, J–U, X–AC); 30 µm (F–I, U, V).

Sequences of taxa, where identification was possible, were submitted to GenBank. The other sequences will be published when a thorough morphological description of the species has been performed. Those sequences can be retrieved from the DNA Databank of the Botanic Garden Berlin after personal communication.

Metabarcoding Inventory

The Illumina MiSeq sequencing run generated 7,460,203 reads for the rbcL marker and 5,623,490 reads for the 18S V4 marker. After processing the reads through the DADA2 pipeline and improvement of the dataset by metbaR for rbcL 7,381,429 reads remained belonging to 1,041 ASVs and for 18S V4 5,570,517 reads remained belonging to 2,251 ASVs.

For the rbcL marker 6,002,917 of reads and 810 of ASVs belong to diatoms corresponding to 81.3% and 77.8% respectively. The majority of the non–diatom reads were assigned to green and brown algae. The average number of diatom–ASVs per sample ranged between 24 and 135. Of all ASVs, 283 could be assigned to a species in the reference library, whereby several ASVs were assigned to the same species and additional 156 ASVs could be assigned to genus level. In the marine samples, 611 ASVs were found; 292 ASVs could be assigned to genus level (47.8%) and 190 to species level (31.1%). In the freshwater samples, 216 ASVs were recovered; 152 could be assigned to genus level (70.4%) and 96 to species level (44.4%). Finally in the brackish water samples 52 ASVs were found; 38 could be assigned to genus level (73.0%) and 25 to species level (48.1%).

The most abundant taxa (sequence relative abundance ≥ 2%, Table 3) in decreasing order across all marine samples belong to Navicula cf. perminuta, Minidiscus chilensis, Navicula sp., Licmophora cf. gracilis, Ellerbeckia sp. and six taxa where no genus could be assigned. Across the brackish samples N. gregaria, N. australoshetlandica, Nitzschia sp., Pinnularia australomicrostauron Zidarova, Kopalová & Van de Vijver, C. australis, Nitzschia cf. gracilis, H. ausloosiana, Pinnularia australoglobiceps Zidarova, Kopalová & Van de Vijver, Nitzschia sp. and one unassigned taxon were the most abundant taxa. Across the freshwater samples Mayamaea sweetloveana, Fragilaria sp., Nitzschia cf. frustulum, N. kleinteichiana, Nitzschia sp., Nitzschia cf. gracilis, Encyonema sp., Achnanthidium sp., Mayamaea cf. permitis, Gomphonema maritimoantarcticum Van de Vijver, Kopalová, Zidarova & Kociolek, P. rostrolanceolatum, Planothidium cf. pumilum, Nitzschia sp. and one unassigned taxon were the most abundant taxa.

For the 18S V4 marker 2,835,064 of reads and 1,439 of ASVs belong to diatoms corresponding to 50.8% and 63.9% respectively. Here as well, the majority of the non–diatom reads were assigned to green and brown algae. The average number of diatom–ASVs per sample ranged between 5 and 248. Of all ASVs 344 could be assigned to a species in the reference library, whereby several ASVs were assigned to the same species and additional 348 could be assigned to genus level. In the marine samples, 1090 ASVs were found; 462 ASVs could be assigned to genus level (42.4%) and 207 to species level (19.0%). In the freshwater samples, 300 ASVs were recovered; 211 could be assigned to genus level (70.3%) and 131 to species level (43.3%). Finally, in the brackish water samples 107 ASVs were found; 60 could be assigned to genus level (56.1%) and 36 to species level (33.6%).

The most abundant taxa (sequence relative abundance ≥ 2%, Table 3) in decreasing order across all marine samples belong to Navicula cf. perminuta, Paralia sol (Ehrenberg) R.M.Crawford (regarded as a synonym of Ellerbeckia sol (Ehrenberg) R.M.Crawford & P.A.Sims), Thalassiosira minima Gaarder, Navicula directa (W.Smith) Brébisson and 3 taxa where no genus could be assigned. Across the brackish samples Pinnularia australomicrostauron, N. gregaria, Navicula cf. veneta and Nitzschia sp. were the most abundant taxa. Across the freshwater samples P. australomicrostauron, Nitzschia cf. frustulum, G. maritimoantarcticum, Fragilaria sp., Encyonema sp., Planothidium rostrolanceolatum, Nitzschia cf. gracilis, Achnanthidium sp. and Nitzschia sp. were the most abundant taxa.

Comparison of diatom composition of taxa from cultures, morphological and metabarcoding inventories

In the clonal cultures 60 taxa could be identified, but 51 of them were also found in the microscopy examinations of environmental samples, which means that 9 taxa were only retrieved through culturing (Lunella sp., cf. Cocconeis 2, Chaetocerus cf. neogracilis, Cylindrotheca cf. closterium, Melosira sp., Navicula sp.1, Nitzschia sp.3, Pinnularia sp., Surirella australovisurgis Van de Vijver, Cocquyt, Kopalová & Zidarova, Fig. 8A). The morphological analysis found 174 taxa, in contrast to the 810 and 1439 ASVs, which were recovered with rbcL and 18SV4 metabarcoding respectively. However, several ASVs were assigned to the same taxon from the taxonomic reference library. Therefore, 58 and 57 genera were found based on rbcL and 18SV4 metabarcoding respectively and 58 genera were detected by morphological identification. In total, 34 genera were retrieved in all datasets, 11 genera only by morphological identification and as well 23 only by metabarcoding (Fig. 8B). On species level 92 and 82 taxa could be assigned based on rbcL and 18SV4 metabarcoding respectively. The combination of the total morphological richness of 165 taxa with 73 taxa solely assigned by metabarcoding resulted in a total of 238 infrageneric taxa (Fig. 8C). Of those taxa 33 were retrieved by all three methods and 111 only by morphology. The barcode reference library of Antarctic species presented here allowed the assignment of 47 infrageneric taxa in the metabarcoding analysis, which would have been left unassigned because no matching reference sequences were available in the INSDC databases or Diat.barcode library before our study.

Figure 8.

Venn diagrams comparing the performance of morphology and DNA metabarcoding in diatom identifications. A Morphological richness across all environmental samples and clonal cultures, M: infrageneric taxa identified by counting 400 valves per sample under light microscopy (LM), C: infrageneric taxa identified from clonal cultures, MR: infrageneric taxa identified by scanning LM slide for rare species. B Genera identified by morphology (Mor) and metabarcoding with the rbcL and 18SV4 marker gene. C Infrageneric taxa identified by morphology including rare taxa (Mor) and metabarcoding with the rbcL and 18SV4 marker gene (only assigned taxa to species level from metabarcoding shown).

The relative abundances on genus level shows that in general the same genera per samples are retrieved between the three datasets (Fig. 9). However, in both the 18SV4 and the rbcL dataset many sequences could not be assigned to genus level. This was especially true for the marine samples. A comparison to the morphological inventory indicates that Gyrosigma was underrepresented by both markers (D296, D297 and D305). In rbcL no reads and in 18SV4 13 reads were assigned to this genus. In some samples with a high abundance of not assigned genera, the morphology inventory shows a high abundance of Navicula (D289–D293, D296, D297, D310). A comparison between metabarcoding and the morphology inventory shows that some genera were disproportionately higher in relative abundance like Encyonema in sample D286. This tendency of overrepresentation was more evident in the 18SV4 inventory, e.g. in the case of Pinnularia in most of the freshwater and brackish water samples and Achnanthes in sample D319. Interestingly, the genus Cocconeis was almost absent in the rbcL dataset.

Figure 9.

Relative abundance (%) of diatom genera across all sample locations. A Morphology. B rbcL marker gene. C 18SV4 marker gene.

Community analysis

Average taxa richness across water and substratum type was always higher in the metabarcoding inventories than in LM (Table 5, Suppl. material 1: table S1: results for the single sample locations). The Shannon diversity index based on the relative abundance of taxa was higher in the metabarcoding inventories as well (Table 5). The average diversity obtained for LM, rbcL and 18SV4 were 1.46, 1.94 and 1.85 respectively. The three approaches agree that a low diversity was found in marine habitats in biofilm from rocks and the highest diversity in marine or brackish waters in epipsammic biofilms.

Table 5.

Average taxa Richness and Shannon diversity index across water and substratum types with the morphological and DNA metabarcoding inventories (rbcL and 18SV4).

LM rbcL 18SV4
Taxa richness Shannon index Taxa richness Shannon index Taxa richness Shannon index
Marine, biofilm from stones 10 0.8 58 1.9 39 1.3
Freshwater, biofilm from stones 12 1.1 42 1.8 58 2.1
Marine, epipsammic biofilm 43 2.8 73 2.0 164 2.5
Brackish water, epipsammic biofilm 16 1.6 40 2.2 80 1.9

The NMDS plots for morphology, rbcL and 18SV4 inventories show a clear separation in the community composition of samples taken from marine and freshwater habitats (Fig. 10, stress =0.1). Brackish water habitats are more similar to freshwater habitats. Among marine habitats, community composition is more similar among samples taken from the same substrate. An exception is found in the LM dataset (Fig. 10C). Here D301 and D310 although taken from biofilm of stones are more similar to samples taken from epipsammic locations. The distinct separation was confirmed by PERMANOVA. Statistically significant differences in the community composition were found for the LM and DNA inventories among different water types (LM: F2,36 = 8.588, p = 0.001; rbcL: F2,36 = 4.454, p = 0.001; 18SV4: F2,36 = 6.316, p = 0.001) and substratum types (LM: F1,37 = 8.899, p = 0.001; rbcL: F1,37 = 6.853, p = 0.001; 18SV4: F1,37 = 7.309, p = 0.001).

Figure 10.

NMDS multivariate clustering of benthic diatom communities regarding water type and substratum type. A Morphology. B rbcL marker gene. C 18SV4 marker gene. Stress: 0.1 (A–C).

According to the SIMPER results (Suppl. material 1: table S2), the species or ASVs contributing the most to the dissimilarity regarding the water types were Navicula cf. perminuta (marine–freshwater: LM 26.0%, 18SV4: 13.2%), Mayamaea sweetloveana (marine–freshwater: rbcL: 7.8%), Navicula gregaria (marine–brackish water: LM: 26.2%, rbcL: 16.0%; freshwater–brackish water: LM: 26.8%, rbcL: 14.5%) and Pinnularia australomicrostauron (marine–brackish water: 18SV4: 29.3%; freshwater–brackish water: 28.7%). The dissimilarities regarding the substrate type were influenced by Navicula cf. perminuta (LM: 27.9%) and two ASVs, that could not be taxonomically assigned (rbcL: 12.0%, 18SV4: 22.7%).

Discussion

Benthic diatom diversity in Potter Cove, Antarctic Peninsula

This study demonstrated that the shallow coastal zone of Potter Cove harbours a rich diatom community with a total of 116 marine taxa identified by morphological investigation. Two floristic studies on benthic diatoms were already performed in Potter Cove by Al–Handal et al. (2022) and Al–Handal and Wulff (2008a), which retrieved 80 and 84 taxa respectively. However, here only surface sediments at four locations were sampled by SCUBA diving in different depths. A comparable study on neighbouring Livingston Island (Zidarova et al. 2022) with a larger variety of sampling locations also found a higher number of 133 taxa.

Even though fewer freshwater samples in our study were evaluated, 93 taxa were still found in these habitats. In general, many more studies investigating freshwater rather than marine habitats in Antarctica have been performed to date. Floristic studies found 122 taxa on King George Island/Isla 25 de Mayo (Kochman–Kędziora et al. 2018), 102 taxa on Livingston Island (Sterken et al. 2015) and 69 taxa on James Ross Island (Kopalová et al. 2012). Numerous new species endemic to maritime Antarctica have been described in recent decades e.g. Van de Vijver et al. (2006); Zidarova et al. (2009); Kopalová et al. (2011); Van de Vijver et al. (2012); Van de Vijver et al. (2013a); Kopalová et al. (2015); Zidarova et al. (2016b) and it is estimated that 44% of all species might be endemic to the Antarctic, and most of them are confined to a single biogeographic region (Verleyen et al. 2021).

This study demonstrated that DNA metabarcoding presents an efficient method for surveying diatom biodiversity in coastal and freshwater ecosystems as it recorded a similar number of genera as the LM method with a high proportion of the genera identified by both methods. However, there are some discrepancies between the inventories. Some genera and species (23 and 73, respectively) were exclusively identified by DNA metabarcoding. DNA metabarcoding based on both marker genes retrieved a higher number of ASVs than taxa identified by LM. Several ASVs, however, were then assigned to the same taxon by the metabarcoding pipeline. Due to the incompleteness of the reference library the number of assigned species was lower for both marker genes in the metabarcoding approach compared to the LM approach which showed a greater efficiency for identifying taxa at species level.

Despite those restraints, similarity analyses of morphological as well as molecular data led to the same results. There was a clear statistically significant separation of diatom community according to water and substratum type. Based on all three approaches marine communities differ from freshwater communities and the brackish water communities are more similar to the freshwater ones. In addition, substratum type (sand or stones) seems to be a factor leading to dissimilarities in the diatom community as well. However, species contributing most to the dissimilarities between habitats differed, due to discrepancies in the inventories, which are discussed later.

Importance of the taxonomic reference library

60 diatom species were cultured and helped assign 47 taxa in our metabarcoding dataset because their sequence data were new to science. In the case of 27 taxa, sequence data was uploaded to ENA or GenBank in this or previous studies analysing the data from the same sampling campaign. Taxa, where a taxonomic investigation is still needed, will be published in combination with their sequence data, when a thorough taxonomic treatment is completed. Many of them will probably be described as new. In advance, their data is available at the Herbarium Berolinense. The large fraction of unidentified taxa especially in the marine habitat (∼68%) is not surprising since benthic diatoms were not broadly studied in this habitat.

Interestingly, some taxa established in culture were not observed in the morphological inventory. This was already shown in Mexican and Canadian streams in Mora et al. (2019) and Skibbe et al. (2022) where culture media and culturing conditions (i.e., light, day/night cycle and temperature) were listed as possibilities for the concealed diversity revealed by clonal culturing. Those may have allowed taxa to grow that were otherwise too rare to be detected through microscopy examinations. Valves of Lunella sp., which were available due to culturing in this study, are very small, only lightly silicified with no visible ornamentation in LM. Valves might have been mistaken with non–diatom material or destroyed in processing of the samples as treatment with Naphrax tend to destroy delicate valves (Vermeulen et al. 2012). The living cells of this species in enrichment medium might have been easier to spot due to their chloroplasts.

The multitude of successfully grown taxa indicates that our approach using several culture media with different salinities was suitable for culturing benthic diatoms from Potter Cove. Even though an extensive culturing effort was undertaken, many taxa could not be established as a unialgal culture. They were not observed as living cells in our enrichment culture as they might not be sampled alive, culture conditions were not suitable, or long–distance shipment might have destroyed more delicate species. Furthermore, some taxa were not able to grow after single cell isolation or the unialgal culture died before enough material was available for analysis. Therefore, an increased diversity of culture media and variation of culture conditions (e.g., temperature, agitation, light intensity or day/night cycle) could potentially stimulate the growth of additional less competitive species and thus improve culture success.

In our metabarcoding dataset many of the taxa could not be assigned by the reference library, even on genus level. This is especially true for marine habitats. The reference library established from the sequence database from the Herbarium Berolinense comprises mostly freshwater diatoms and already Pérez–Burillo et al. (2022) showed that the data availability in the Diat.barcode reference library has a strong tendency towards freshwater species. However, recent metabarcoding studies conducted in freshwater habitats highlight the need for a comprehensive reference database as well e.g. Rivera et al. (2018); Mortágua et al. (2019); Kulaš et al. (2022) to improve metabarcoding in routine monitoring.

Rimet et al. (2018a) suggested to complete reference libraries by using metabarcoding data. This could be a promising tool, however, the sequence needs to be abundant in the sample, with no insertions or deletions or stop codon and phylogenetic neighbour taxa have to correspond to neighbour taxonomic taxa expected from morphological observations. For taxa not matching those criteria, unialgal cultures as a reference for DNA metabarcoding studies are still needed. Furthermore, established data through culturing supports an integrative taxonomy as cultures show morphological variability within a species (Mohamad et al. 2022). In addition, sequence data supports phylogenetic analyses of diatoms (Kociolek et al. 2013; Downey et al. 2021) and especially longer sequences than short metabarcodes are needed for defining deep nodes of classification trees (Rimet et al. 2018b).

Discrepancies between morphological and molecular results

Several discrepancies between the morphological and the molecular inventory were evident. Most obvious was the above discussed fact, that many species and some genera were not encountered in the molecular inventory since the reference database was lacking a representative sequence. This was the case for e.g. Gyrosigma sp., Pteroncola carlinii Almandoz & Ferrario or Achnanthidium cf. maritimoantarcticum listed with a relative high abundance in the LM inventory but without an entry for both metabarcoding inventories since both barcode sequences are unknown. Furthermore, some samples, where a high abundance of taxa in LM identified to the genera like Navicula and Gyrosigma, had no corresponding match in the metabarcoding inventories. This is indeed surprising, since those genera have a rather intensive representation in the reference databases. Studies in the last decades have shown that taxa morphologically assigned to an existing genus in Antarctica had been actually force fitted. Several new genera in the Antarctic or southern hemisphere have been established and existing taxa underwent a new combination (Williams 1988; Bishop et al. 2019; Guerrero et al. 2021). Our dataset suggests that there is a high cryptic diversity, which highlights the need for intensive taxonomic investigation of benthic diatoms in this region. An additional reason for discrepancies between the inventories might be found in morphological destruction or overlooked valves might lead to underrepresentation of taxa in LM like in the above described case of Lunella sp.

One of the key issues concerning sediment DNA metabarcoding is the distinction of living organisms that are part of the active benthic community from those organisms that are represented either by inactive resting stages or solely by DNA traces (Pawlowski et al. 2022). Sediments act as a repository of both intra– and extracellular DNA and the presence of extracellular DNA may have also influenced our molecular inventory, since taxa might have been detected in a sample even if their cells are not physically present. Those factors make it difficult to differentiate between living and dead organisms, or between species that live in the sediments or that have been settled from the water column.

Varying gene copy numbers per organism due to cell size and number of chloroplasts per cell is probably another reason for discrepancies between the LM and metabarcoding inventory. This correlation was noted in the case of rbcL by Vasselon et al. (2018) and Pérez–Burillo et al. (2022) and in the case of 18SV4 by Mora et al. (2019). This likely explains the higher abundances obtained by the DNA metabarcoding for the big cell species P. australomicrostauron and Paralia sol (≡Ellerbeckia sol) in our study, which was especially apparent in the 18SV4 dataset.

The poor representation of Cocconeis in the rbcL inventory (1025 reads, 2 ASVs) despite the very high diversity of Cocconeis species revealed by LM was also an issue in the study of Burillo et al. 2022. Sequences of the Antarctic species C. fasciolata were available in our reference database as a culture of this species was established. No ASVs were assigned to this taxon in the rbcL inventory in contrast to the 18SV4 inventory. A worrying possibility is that primers of the rbcL barcode might not be suitable for marine Cocconeis. In fact, in comparable freshwater studies C. placentula was the most abundant taxon (Vasselon et al. 2017; Kulaš et al. 2022). A comparison with the forward rbcL primer region with the sequence of C. fasciolata showed a transition from the base G to an A. We suggest here to include a modified Diat_rbcL_708F forward primer at the third position from the back in the primer mix for marine samples: TCGTCGGCAGCGTCAGATGTGTATAAGAGACA GAGGTGAAACTAAAGGTTCWTACTTRAA.

In general, the list of taxa with the highest relative abundance of the LM data set correlates better with the rbcL than with the 18SV4 inventory. Similar results were found by Bailet et al. (2019), where the use of the 18SV4 marker generated more species inventories discrepancies. Bailet et al. (2020) investigated the performance of the rbcL and the 18SV4 marker using different bioinformatic pipelines. Here in addition, the use of the rbcL marker resulted in outcomes closer to these generated using traditional microscopy. Furthermore, it was shown that the choice of the pipeline had an influence on the taxonomic assemblage, but the results generated by rbcL correlated better among pipelines.

Prospects of DNA Metabarcoding for Antarctic benthic diatoms

It has been shown that the metabarcoding approach can complement and improve traditional identification via LM. It enables to detect tiny and delicate species. Lunella sp. and Cylindrotheca cf. closterium were detected in metabarcoding but not via the count of valves in LM. Rare species may be detected as well. In traditional identification, generally a few hundred valves are counted per sample probably not reaching saturation of species richness, while in metabarcoding several 10,000 to 100,000 reads are usually evaluated. Furthermore, it may detect cryptic diversity. Species that are morphologically similar may be better separated in the metabarcoding dataset.

In addition to the extension of information about Antarctic diatom diversity, our study also provided a new tool to survey water quality changes in Antarctica. In recent decades, climate change has had a crucial impact in the polar regions with increasing air and water temperature leading to glacial melting and the accompanying freshwater increase in coastal areas (IPCC 2019). DNA metabarcoding evaluation with a continuous sampling routine can give a valuable insight on community changes of benthic diatoms. Using those microorganisms as bioindicators may help assess the biological status and quality changes of water bodies in Antarctica, where environmental conditions are quickly evolving.

Conclusion

Antarctica is among the most extreme environments on Earth. An increased research effort is required in the light of desynchrony between the pace of change in polar regions and information demands to face engendered challenges (Danis et al. 2020). This study showed that a high benthic diatom diversity is apparent in this region, which was shown by traditional morphological identification and by the DNA metabarcoding approach. Overall, a combination of morphological, metabarcoding approaches accompanied by culturing increases the detection and identification of diatoms as the methods provide complementary information on biodiversity of benthic diatoms in this region. Furthermore, culturing is needed to enrich the reference barcode database. Ultimately, diatom diversity based on three approaches allowed a reliable dataset that can be used in routine monitoring assessment, which provides a deeper understanding of ecological status. Many taxa in both approaches could still not be identified on species level which emphasises the need for further taxonomic investigations in this region. In addition, the need for more efforts to complement the taxonomically curated reference database is evident.

The slides of the environmental samples, morphological and molecular data gained by LM and SEM investigation as well as sequencing of cultures together with the metabarcoding dataset represents the currently most extensive biodiversity dataset of marine benthic diatoms of Western Antarctica. All voucher material as well as the data are deposited at the Herbarium Berolinense and could be used as a baseline for further investigations, as a reference for monitoring routines and as training records in modelling tasks.

Acknowledgments

We would like to express our deep gratitude to Professor Andrzej Witkowski who has provided constructive comments improving this research. He was a prominent scientist and specialist of marine diatoms. He was always a great supporter for early career scientists as well as a great cooperation partner. His invaluable contribution and commitment to diatom science will be remembered. We would like to thank the team of the Argentinian Antarctic Research Station “Carlini” of the Instituto Antártico Argentino (IAA) for their support and logistics, especially Dr. María Liliana Quartino. The authors are grateful to Jana Bansemer for work in the molecular lab and to Juliane Bettig for support at the SEM at the BGBM Berlin.

Additional information

Conflict of interest

The authors have declared that no competing interests exist.

Ethical statement

No ethical statement was reported.

Funding

This project was funded within the framework of the SPP 1158 Antarktisforschung by the DFG under the grant number ZI 1628/2–1. OS acknowledges funding from the Verein der Freunde des Botanischen Gartens und des Botanischen Museums Berlin-Dahlem e.V.. GC acknowledges support from PADI Foundation (47918/2020), ANPCyT–DNA (PICT 2017–2691), UNLu (DCDD–CB 343/19 and 69/21) and the EU’s H2020 research and innovation programme under the Marie Skłodowska–Curie grant agreement No 87269 CoastCarb. We acknowledge support by the Open Access Publication Fund of the Freie Universität Berlin.

Author contributions

KS and JZ developed the concept of this study. JZ and GC sampled and OS isolated, purified and established clonal cultures. KS, HM and JZ performed the metabarcoding analysis. KS provided the light microscopic analysis and KS, NA and RJ did the taxonomic identification. NA and WHK are responsible for the curation and data curation. KS wrote the first version of the paper. All authors edited and approved the final version of this manuscript.

Author ORCIDs

Katherina Schimani https://orcid.org/0000-0003-2125-0239

Nélida Abarca https://orcid.org/0000-0001-8897-160X

Oliver Skibbe https://orcid.org/0000-0003-1495-5468

Heba Mohamad https://orcid.org/0000-0002-3217-3067

Regine Jahn https://orcid.org/0000-0002-3833-3746

Wolf-Henning Kusber https://orcid.org/0000-0003-4543-5764

Gabriela Laura Campana https://orcid.org/0000-0002-6507-2369

Jonas Zimmermann https://orcid.org/0000-0002-0522-0569

Data availability

All of the data that support the findings of this study are available in the main text or Supplementary Information. Raw demultiplexed reads were deposited at GenBanks Sequence Read Archive and are publicly available under project number PRJNA997374.

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Supplementary material

Supplementary material 1 

Statistic results

Katherina Schimani, Nélida Abarca, Oliver Skibbe, Heba Mohamad, Regine Jahn, Wolf-Henning Kusber, Gabriela Laura Campana, Jonas Zimmermann

Data type: docx

Explanation note: table S1. Taxa Richness and Shannon diversity of the sample sites with the morphological and DNA metabarcoding inventories (rbcL and 18SV4). table S2. SIMPER results listing the four most contributing species or ASV’s to the dissimilarities between samples taken from different water types (freshwater, brackish water and marine) and substratum types (epipsammic biofilm, biofilm on rocks) for the LM, the rbcL and the 18SV4 inventories, CC: Cumulative contribution to dissimilarity, AA: Average abundance across all samples.

This dataset is made available under the Open Database License (http://opendatacommons.org/licenses/odbl/1.0/). The Open Database License (ODbL) is a license agreement intended to allow users to freely share, modify, and use this Dataset while maintaining this same freedom for others, provided that the original source and author(s) are credited.
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