Changes in the composition of marine and sea-ice diatoms derived from sedimentary ancient DNA of the eastern Fram Strait over the past 30,000 years

. The Fram Strait is an area with a relatively low and irregular distribution of diatom microfossils in surface sediments, and thus microfossil records are scarce, rarely exceed the Holocene and contain sparse information about past richness and 15 taxonomic composition. These attributes make the Fram Strait an ideal study site to test the utility of sedimentary ancient DNA ( sed aDNA) metabarcoding. Amplifying a short, partial rbcL marker from samples of sediment core MSM05/5-712-2, resulted in 95.7 % of our sequences being assigned to diatoms across 18 different families with 38.6 % of them being resolved to species and 25.8 % to genus level. Independent replicates show high similarity of PCR products, especially in the oldest samples. Diatom sed aDNA richness is highest in the Late Weichselian and lowest in Mid-and Late-Holocene samples. 20 Taxonomic composition is dominated by cold-water and sea-ice associated diatoms and suggests several re-organizations – after the Last Glacial Maximum, after the Younger Dryas, after the Early and after the Mid-Holocene. Different sequences assigned to, amongst others, Chaetoceros socialis indicate the detectability of intra-specific diversity using sed aDNA. We detect no clear pattern between our diatom sed aDNA record and the previously published IP 25 record of this core, although proportions of pennate diatoms increase with higher IP 25 concentrations and proportions of Nitzschia cf. frigida exceeding 2 25 % of the assemblage point towards past sea-ice presence.

In this study we examine ancient diatom DNA retrieved from sediments from the eastern Fram Strait and assess whether it can be used to analyse temporal changes in the taxonomic composition of diatoms.We have three principal objectives: (1) to assess the quality and replicability of the data obtained by sedaDNA metabarcoding, (2) to analyse temporal changes in diatom taxonomic composition and richness, and (3) to evaluate diatom sedaDNA as a new proxy for sea-ice reconstruction.DNA was derived from distinct samples of the comprehensively analysed marine sediment core MSM05/5-712-2, covering the major climatic intervals since the Late Weichselian (i.e. the last ∼ 30 kyr BP).As previous work indicates variability in the past sea-ice cover (Falardeau et al., 2018;Müller et al., 2012;Müller and Stein, 2014;Werner et al., 2011Werner et al., , 2013)), samples were chosen according to high, medium, and low concentrations of the diatom-produced sea-ice biomarker IP 25 (Müller et al., 2012;Müller and Stein, 2014), and we expect associated changes in the taxonomic composition.We used sedaDNA metabarcoding by applying the diatom-specific rbcL_76 marker (Stoof-Leichsenring et al., 2012), which has already proved successful in low-productivity lakes of northern Siberia (Dulias et al., 2017;Stoof-Leichsenring et al., 2014, 2015) but so far has not been tested on marine sediments.The marker amplifies a short region of the rbcL gene, which is located on the chloroplast that is present in diatoms in several copy numbers (Vasselon et al., 2018), thereby increasing the probability of its long-term preservation.The rbcL gene has an adequate sequence reference database and was tested as a potential diatom barcode marker with high-resolution power (Guo et al., 2015;Kermarrec et al., 2013).Furthermore, it reduces coamplification of non-photosynthetic bacteria or archaea that are active in subsurface sediments and thus could be preferentially amplified during PCR in comparison to the highly fragmented and damaged ancient DNA.

Study site and sample material
The kastenlot core MSM05/5-712-2 (78.915662 • N, 6.767167 • E; water depth 1487 m) was collected from the western continental slope of Svalbard during the cruise of Maria S. Merian (Budéus, 2007) in the eastern Fram Strait in August 2007 (Fig. 1).On board, subsections of 1 m length were placed in square plastic boxes as explained in the supplement of Gersonde (2012) and stored at 4 • C.This may have affected DNA preservation.The Fram Strait is located between Greenland and Svalbard and connects the Arctic Ocean with the Atlantic Ocean.The study area is influenced by temperate, saline water masses that are transported northwards via the West Spitsbergen Current, which is a continuation of the North Atlantic Current (Aagaard, 1982).Furthermore, the site is located downslope from Kongsfjorden and is thus influenced by one of the major outlets of western Svalbard meltwater (Werner et al., 2013).Today, the site is located south of the winter and summer sea-ice margin and is ice-free year-round (Fig. 1).Age-depth modelling suggests a maximum age of about 30 cal kyr BP for the lowermost core interval (Müller and Stein, 2014).The sampling procedure for ancient DNA analyses followed the protocol for non-frozen sediment cores explained in Epp et al. (2019) for the 12 samples taken along the core, of which the depth at 8.85 m was sampled twice to check whether different samples from the same level show similar taxonomic composition and richness, particularly the oldest sample (Table 1).

DNA extraction, PCR, and sequencing
The DNA extractions and PCR setups were prepared in a dedicated laboratory for ancient DNA at the Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research (Potsdam, Germany).Total DNA was extracted from 12 samples of approximately 2 g (wet weight) sediment using the same method as described in Zimmermann et al. (2017a).Each extraction batch included one negative control.The DNA concentrations were measured with the Qubit dsDNA BR Assay Kit (Invitrogen, Carlsbad, CA, USA) on a Qubit 2.0 fluorometer (Invitrogen, Carlsbad, CA, USA).As DNA concentrations were below the detection limit, we concentrated 600 µL of each sample with the GeneJET PCR Purification KIT (Thermo Scientific, Carlsbad, CA, USA) according to the manufacturer's protocol and eluted twice with 15 µL elution buffer.All DNA extracts were stored at −20 • C.
We amplified the marker rbcl_76 (Stoof-Leichsenring et al., 2012), a 76 bp long fragment of the plastid rbcL gene using tagged primers Diat_rbcL_705F (AACAGGTGAAGT-TAAAGGTTCATAYTT) and Diat_rbcL_808R (TGTAAC-CCATAACTAAATCGATCAT) as described in Dulias et al. (2017).The PCRs were set up in small batches, each including up to nine samples and the corresponding negative control from the DNA extraction as well as a PCR no template control (NTC).For each sample, extraction negative control, and NTC, we performed three PCRs with different primer-tag combinations on different days.The PCR mixes and conditions were prepared following the adjusted protocol for tagged Diat_rbcL_705F and Diat_rbcL_808R primers as described in Dulias et al. (2017) with the exception that 3 µL DNA (DNA concentration 3 ng µL −1 ) was used as a template.PCRs were performed with the following settings: 5 min at 94 • C (initial denaturation), then 50 cycles at 94 • C (denaturation), 49 • C (annealing), and 68 • C (elongation), and a final elongation step at 72 • C for 5 min.Subsequently the PCR success was checked with gel electrophoresis.All PCR products were purified with the MinE-lute purification Kit (Qiagen, Hilden, Germany) according to the manufacturer's recommendations.Elution was carried out twice in 10 µL elution buffer.The purified PCR products were mixed in equal concentrations and sent to Fasteris SA sequencing service (Switzerland), who carried out library preparation and sequencing.The sequencing library was prepared with the Mid Output kit v. 2 according to the Fasteris Metafast protocol for low complexity amplicon sequencing and checked by qPCR.The library was sequenced (2 × 150 bp, paired-end) on the Illumina NextSeq 500 (Illumina Inc., San Diego, CA, USA; see Zimmermann et al., 2020, for the sequencing data).

Bioinformatic processing
The sequences were processed, filtered, and assigned a taxonomic name according to the NCBI taxonomy using the OBITools package (Boyer et al., 2016) with the same bioinformatics parameter settings as described in Dulias et al. (2017).We refrained from clustering sequences into operational taxonomic units and used amplicon sequence variants (ASVs) as recommended by Callahan et al. (2017).The OBITools program obiclean can identify ASVs that have likely arisen due to PCR or sequencing errors.It uses the information of sequence counts and sequence similarities to classify whether a sequence is a variant ("internal") of a more abundant ("head") ASV (Boyer et al., 2016).To generate the reference database for the taxonomic assignment of the sequences we downloaded the EMBL release 138 (released November 2018) and used ecopcr (Ficetola et al., 2010) according to the descriptions of Dulias et al. (2017) and Stoof-Leichsenring et al. (2012) containing 2320 reference sequences.A total of 7 536 449 sequence counts were assigned to samples, 235 sequence counts to extraction negative controls, and 237 counts to PCR negative controls.Of the 204 different sequence variants detected in extraction and PCR negative controls, 83 % of their occurrences were singletons (Table S1 in the Supplement) and most likely artefacts from tag-jumping during library preparation (Schnell et al., 2015).Using R v. 3.5.0(R Core Team, 2018), we kept only those ASVs (Table S2) that (1) were assigned a taxonomic name based on 90 %-100 % similarity to an entry in the reference database, (2) were represented with at least 10 read counts in a replicate, (3) were present at least three times among all sequenced PCR products, (4) showed taxonomic resolution below the phylum level "Bacillariophyta", and (5) were tagged as "internal" by obiclean in less than 50 % of all sequenced PCR products to reduce PCR and sequencing artefacts.Filtering with R reduced the number of read counts from 7 536 449 to 6 199 984. https://doi.org/10.5194/os-16-1017-2020 Ocean Sci., 16, 1017-1032, 2020

Reproducibility of PCR replicates
Alpha-diversity estimates, such as richness, depend highly on the sequencing depth.As more taxa, especially rare ones, can be detected with increasing sequencing depth, alpha diversity is only comparable between samples when it is estimated based on the same number of sequences.Despite efforts to reduce such differences by equimolar pooling of PCR products, the number of sequences generally varies among PCR replicates.Therefore, we analysed the dissimilarities of PCR replicates as well as one sample replicate (8.85 m depth).We resampled the dataset 100 times to the minimum number of sequences available (25 601 counts); then, for each replicate, we calculated the mean number of sequence counts for each ASV across the 100 resampling steps (code available at: https://github.com/StefanKruse/R_Rarefaction,last access: 1 August 2019; Kruse, 2019).This dataset was used to calculate the proportions of each ASV per replicate.The proportional data were used for the Multiple Response Permutation Procedure (MRPP) using the R function mrpp on Bray-Curtis dissimilarities to test if dissimilarities within replicates of the same sample are significant.Furthermore, we applied non-metric multidimensional scaling (NMDS) using metaMDS to assess which replicates show high and low replicability.

Taxonomic composition and richness
As a measure of alpha diversity we calculated richness of (1) ASVs (number of amplicon sequence variants) and (2) unique taxonomic names (number of grouped ASVs that were assigned to the same taxonomic name).For taxonomic composition and richness calculations, we combined the PCR replicates of the corresponding sample.This resulted in a new minimum number of sequence counts (300 415 counts) that was used for resampling the dataset 100 times according to descriptions in the preceding paragraph.The resampled dataset was used to calculate the relative abundances of each ASV per sample.Finally, ASVs, which were assigned to the same taxonomic name but had different similarities to an entry in the reference database, were summed up to one entry using the R aggregate function.Stratigraphic diagrams showing temporal changes in taxonomic composition were generated with strat.plot.All statistical analyses and visualisations were prepared with R v. 3.5.0using the packages "vegan" (Oksanen et al., 2011) and "rioja" (Juggins, 2012).For correlation analysis we interpolated IP 25 values using the methods described in Reschke et al. (2019).We transformed the IP 25 data using the function zoo from the "zoo" package (Zeileis and Grothendieck, 2005) and used the function CorIr-regTimser using the package "corit" (https://github.com/EarthSystemDiagnostics/corit, last access: 2 March 2020) (Reschke et al., 2019).The correlation between Chaetocero-taceae and Thalassiosiraceae as well as between IP 25 and all ASVs was tested for significance using the R function rcorr (method Pearson) from the package "Hmisc" (Hollander and Wolfe, 1975;Press et al., 1988).
3 Marker specificity, taxonomic resolution, and taxonomic coverage The amplification of the short rbcL_76 marker permitted the retrieval of diatom DNA from all samples and was highly specific for diatom sequence variants (95.7 %  Dulias et al., 2017).Possibly owing to a much shorter marker size, the rbcL_76 marker also surpassed the usually amplified 18S rDNA markers with regard to specificity for diatoms (Coolen et al., 2007;De Schepper et al., 2019;Kirkpatrick et al., 2016).
The initial dataset contained 1398 ASVs that were systematically filtered to a final diatom dataset containing 360 ASVs (6 199 984 counts), which were further grouped into 75 unique taxonomic names.The majority of diatom sequences are assigned to polar centric Mediophyceae (79.7 %), followed by pennate Bacillariophyceae (14.5 %), while radial centric Coscinodiscophyceae (1.1 %) make up only a small proportion of the dataset.The majority of ASVs are assigned as low as species level (38.6 %) or genus level (25.8 %) (Fig. 2a), yet the taxonomic resolution (i.e. the taxonomic assignment of ASVs) is limited by the incompleteness of the sequence reference database as indicated by the proportion of ASVs (4.8 %) for which assignment is restricted to phylum level (Bacillariophyta).
In total, 18 different diatom families are represented in the final dataset which is dominated by ASVs assigned to the families Thalassiosiraceae (35 %), Bacillariaceae (15.8 %), and Chaetoceraceae (9.2 %) (Fig. 2b).Particularly dominant ASVs are assigned to Thalassiosira (21.2 %) and Porosira (10.9 %) (resolution only possible to genus level) and to Chaetoceros cf.contortus 1SEH-2013 (6.6 %) -all centric diatoms belong to the class Mediophyceae.Their dominance is likely the result of high paleoproductivity or of differential overrepresentation caused by preservation and/or technical biases.Indeed, in the Fram Strait, Chaetoceros and Thalassiosira species especially have high productivity in different hydrographical regimes (Gradinger and Baumann, 1991;Lalande et al., 2013) as well as at Kongsfjorden, a major outlet of western Svalbard potentially influencing the coring site  (Hodal et al., 2012), and even in micropaleontological studies they are often dominant (Birks and Koç, 2002;Bylinskaya et al., 2016;Oksman et al., 2017Oksman et al., , 2019)).Next to high paleoproductivity, the preservation of sedaDNA could be biased by differential degradation.Heavily silicified and/or sporeforming diatoms such as some Thalassiosira and Chaetoceros species may be less sensitive to dissolution, which might also improve the preservation of DNA over long time periods.Furthermore, the enrichment of centric diatoms in the sedaDNA record could be the result of copy number variation in the rbcL gene between different species and cell biovolume (Bedoshvili et al., 2009;Round et al., 1990;Vasselon et al., 2018).Technical biases often arise during PCR due to mismatches between primer sequences and primer binding sites (Nichols et al., 2018) and the high number of PCR cycles -which is needed to increase the chance of retrieving rare sequences -leads to an over-amplification of already abundant template molecules in comparison to rare ones.While the reduction in cycles could reduce this effect, fewer PCR cycles would reduce replicability (Krehenwinkel et al., 2017;Nichols et al., 2018).
Despite the filtering, several distinct ASVs, (e.g.Chaetoceros socialis) are assigned the same taxonomic name (Table S1, Fig. S1 in the Supplement).We believe that these represent either different lineages or closely related species so far not included in the database, although we cannot rule out that some ASVs in our filtered dataset might still represent PCR or sequencing artefacts.
Despite the current limitations, sedaDNA shows much promise.New reference sequences are added to GenBank on a daily basis, due to numerous phylogenetic studies and barcoding projects aiming to improve our systematic knowledge about taxonomic relationships and to archive the molecular inventory of global biodiversity (Degerlund et al., 2012;Li et al., 2015;Luddington et al., 2016).Taxonomic coverage of the reference database can be increased by subjecting diatom strains to single cell sequencing (Luddington et  As our study lacks a morphological diatom record, false absences cannot be assessed and true presences cannot be confirmed, which means that absence in our record does not necessarily translate to a true physical absence in the past.Hence, it was important to use independent PCR replicates for each sediment sample and stringent criteria to filter the dataset to remove artefacts introduced by ancient DNA damage, PCR, and sequencing.The PCR replicates (different PCR products from the same DNA extract) of each sample show some variations (Fig. 3) in the presence and abundance of ASVs, especially for ASVs amounting to less than 1 % per sample (Table S2, Fig. S2).We tested whether these differences are significant using MRPP (p = 0.001; number of permutations: 999; observed delta: 0.3683; expected delta: 0.6548), which suggests that PCR replicates of the same sample share significantly lower dissimilarities (average 39.3 %) compared to replicates between different samples (67.5 %).
The PCR replicates are highly similar in the oldest samples up to 5.8 m depth and in the youngest sample.For the oldest sample at 8.85 m depth we additionally processed a sample replicate.The PCR replicates of both sediment samples at 8.85 m depth are highly similar and cluster tightly together in the NMDS plot (Fig. 3).Although a higher number of replicates would improve the robustness of our analysis, this indicates that reasons other than sample age and associated DNA degradation controlled replicability in this study.It is possible that higher dissimilarities between PCR replicates are the result of low amounts of template molecules.
Samples taken from Heinrich Stadial 1 and Bølling-Allerød phases are characterised by high proportions of ASVs assigned to Thalassiosira (35.1 %-65.3 %), T. antarctica (6.8 %-9.8 %), and T. delicata (4.1 %-5.3 %), and abundant Skeletonema subsalsum (2.1 %-5.6 %), whereas proportions of Thalassiosira gravida (3.4 %-11.3 %), Nitzschia cf.frigida (0.6 %-0.7 %), Haslea avium (0.2 %-0.4 %), and Minidiscus trioculatus (0 %-0.7 %) are lower compared to the LGM.The taxonomic composition of the sample dated to Heinrich Stadial 1 suggests a partial reorganisation of the diatom sedaDNA composition, which took place either gradually or abruptly sometime between 20.5 and 15.1 cal kyr BP.The low proportions of Nitzschia cf.frigida and other coldwater and sea-ice diatoms in samples corresponding to Heinrich Stadial 1 and Bølling-Allerød correspond well to low IP 25 and moderate brassicasterol concentrations in these samples, reflecting a reduction in the sea-ice cover (Müller and Stein, 2014).In the Bølling-Allerød sample the relatively high abundance of sequences assigned to the brackishfreshwater-preferring diatom Skeletonema subsalsum (Hasle and Evensen, 1975) might be explained by elevated meltwater discharge from Svalbard.Low surface water salinity was inferred previously from the dinocyst record of this core about a century earlier, possibly resulting from the melting of the Barents Sea ice sheet (Falardeau et al., 2018).Higher sedimentation rates and thus higher temporal resolution during the Bølling-Allerød could have affected the sedaDNA signal, yet the distinct shift in taxonomic composition suggests that this is rather an effect of the changing environmental conditions during this phase.
The Younger Dryas sample exhibits moderate proportions of Thalassiosira antarctica (11.8 %) and T. delicata (2.3 %) and is marked by the presence of the sympagic diatom Cylindrotheca closterium (0.3 %) and relative increases in Porosira (9.1 %), Haslea avium (5.7 %), and Nitzschia cf.frigida (1.3 %).Higher proportions of sympagic diatoms in this sample point towards colder conditions in comparison to the Bølling-Allerød sample and the presence of sea ice.Severe and extended sea-ice cover at the coring site are indicated by heterotrophic species in the dinocyst record (Falardeau et al., 2018), peak concentrations of IP 25 , and very low brassicasterol concentrations (Müller and Stein, 2014).A diatom microfossil record from Hinlopen Strait northwest of Spitsbergen detects first diatom occurrence during the Younger Dryas (10.8 14 C kyr BP) with more than 30 % sea-ice-associated species yet with a different taxonomic composition in comparison to our record (Koç et al., 2002).
to 44.4 % and Naviculaceae from 5.7 % to 0.2 %, points towards a second partial reorganisation of the taxonomic composition between 12.8 and 10.1 cal kyr BP.In particular, the sample is dominated by sequences assigned to Skeletonema (16.8 %), Thalassiosira (14.5 %), and Pseudonitzschia granii (11.4 %).Thalassiosira angulata, a species associated with low sea-ice concentrations (Oksman et al., 2019) and temperate water masses (Weckström et al., 2014), displays peak proportions (1.7 %) in this sample.Lower proportions of sympagic diatoms in this sample are in accordance with the sea-ice retreat reconstructed from low IP 25 and high brassicasterol concentrations (Müller and Stein, 2014) and high proportions of the subpolar planktic foraminifers Turborotalita quinqueloba in another core further northwest (Werner et al., 2016).The diatom composition recorded by sedaDNA is also quite different to what has been found in microfossil records from the Fram Strait and the Greenland, Iceland, and Norwegian seas, where first diatom microfossils are recorded between 13.4 and 9 cal kyr BP (Koç et al., 1993;Schröder-Ritzrau et al., 2001).Southwest of Svalbard, diatom-rich sediments dated to 10.1 and 9.8 cal kyr BP are attributed to the inflow of Atlantic surface water and a retreat of the polar front (Jessen et al., 2010;Stabell, 1986) and are composed mostly of Coscin-odiscus spp., Rhizosolenia, and Paralia sulcata (Jessen et al., 2010;Rigual-Hernández et al., 2017;Stabell, 1986).In concordance with this, sequences assigned to Paralia have the highest proportions in the Early Holocene sample.Coscinodiscus is likely resolved to class level as sequences (Coscinodiscophyceae) and is thus present in our record, albeit only sparsely.Rhizosolenia was not detected in this sample, which could be explained by poor DNA preservation or regional differences in the past diatom communities between the two coring sites.
The sea-ice proxy IP 25 is produced by only a few known ice-associated diatoms: Haslea kjellmanii (Cleve) Simonsen, H. spicula (Hickie) Lange-Bertalot, and Pleurosigma stuxbergii var.rhomboides (Cleve in Cleve and Grunow) Cleve (Brown et al., 2014;Limoges et al., 2018).We detected none of the known producers due to the incompleteness of the reference database (for the species of Haslea) and/or because the DNA of these species was not preserved in sufficient quantities as these species are low in abundance (Brown et al., 2014).Only for Pleurosigma stuxbergii is there a publicly available reference containing our marker region, and this is included in our database, whereas 15 references for non-IP 25 -producing Haslea species are available in our database.Hence, an absence in our record does not mean an absence in the past communities.Sequences assigned to Haslea avium in our sedaDNA record do not show a linear relationship with IP 25 but are nevertheless present in most samples.Our data, in combination with other proxy data from this core, suggest that sequences assigned to Nitzschia cf.frigida could be a useful indicator of past sea-ice distribution in sedaDNA records.Samples with low concentrations of the sea-ice proxy IP 25 (< 0.4 µg g −1 total organic carbon) have less than 2 % of sequences assigned to Nitzschia cf.frigida, whereas samples characterised by moderate to high (> 0.8 µg g −1 total organic carbon) concentrations of IP 25 display highly variable proportions without a clear relationship.Nitzschia frigida (Grunow) forms arborescent colonies (Medlin and Hasle, 1990) and is often abundant from late winter in the bottom layer of nearshore first-year ice and in multi-year ice in the Arctic pack-ice zones (Krawczyk et al., 2017;Melnikov et al., 2002;Olsen et al., 2017;Poulin et al., 2011;von Quillfeldt et al., 2003), but it can also be found in the water column during vernal under-ice or ice-edge blooms (Hasle and Heimdal, 1998;Olsen et al., 2017).Recently, De Schepper et al. (2019) used sedaDNA metabarcoding on a core from the East Greenland Sea and identified the Mediophyceae OTU_5051 which was significantly correlated to the IP 25 concentrations.The class Mediophyceae is the most diverse and dominant group in our dataset and contains several sea-ice-associated taxa, such as Thalassiosira antarctica, T. nordenskioeldii, and Porosira glacialis.Yet their tendency to prevail in both sea ice and open water might be responsible for the non-linear relationship with IP 25 observed in our record.This is supported by Weckström et al. (2013), who find no specific response of sea-ice diatom microfossil composition to either IP 25 concentrations or observational sea-ice data in the Labrador Sea.

Conclusions
For the first time in a marine environment, our study targets high-resolution, diatom-specific sedimentary ancient DNA using a DNA metabarcoding approach.We show that diatom DNA is preserved with substantial taxonomic richness in the eastern Fram Strait over the past 30 000 years even though diatom microfossils are recorded in the Svalbard region only since the Younger Dryas.This highlights the advantage of our approach for paleoenvironmental reconstructions aiming to identify drivers of community-level taxonomic composition and diversity, especially in regions known for their irregular and poor diatom microfossil preservation, such as the Fram Strait.The rbcL_76 marker is highly diatom specific and provides detailed taxonomic resolution, mostly at genus and species level.The shortness of this marker is a strong advantage that leads to adequate replicability and high quality as diversity patterns do not show conspicuous signs of bias by age-associated DNA fragmentation.The sedaDNA record captures substantial temporal change in diatom taxonomic composition and richness with four compositional reorganisations: the first between 20.51 and 15.1 cal kyr BP, the second between 12.8 and 10.1 cal kyr BP, the third between 10.1 and 5 cal kyr BP, and the fourth between 5 and 1.6 cal kyr BP.Our record extends diatom compositional and diversity information back to the Late Weichselian as microfossil records in the Fram Strait are rare and extend only as far as the Younger Dryas due to poor preservation.Increasing proportions of pennate diatoms are associated with increased IP 25 concentrations, and sympagic diatoms are present, but with no clear pattern with regard to biomarker signals.Recommendations for future work with sedimentary ancient DNA in the context of sea-ice reconstructions include the preparation of reference genomes and a more targeted enrichment, for example of genes that help species to adapt to sea ice and allow them to cope with rapidly changing environmental conditions.

Figure 2 .
Figure 2. Number of diatom amplicon sequence variants (ASVs) assigned (a) to different taxonomic levels and (b) to different families.
al., https://doi.org/10.5194/os-16-1017-2020Ocean Sci., 16, 1017-1032, 2020 2016; Sieracki et al., 2019).Most importantly, sedaDNA allows tracing ASVs through time and eventually relating them to, for example, environmental change, without relying on the state of taxonomic coverage of the reference database.4 Quality and replicability of the data obtained by sedaDNA metabarcoding A crucial requirement for the interpretation of ancient DNA records is that PCR replicates show similar signals in richness and taxonomic composition.The recovery of taxa by sedaDNA metabarcoding is prone to false presences or absences.

Figure 3 .
Figure 3. Non-metric multidimensional scaling plot based on the filtered and resampled diatom dataset with the PCR replicates (indicated by an underscore with a number) of a sample (depth in m) linked in a polygon of sample-specific colour: light green: 0.12 m; green: 0.3 m; light violet: 0.9 m; violet: 3.1 m; light blue: 3.71 m; dark blue: 5.8 m; turquoise: 6.68 m; grey: 7.27 m; red: 7.85 m; brown: 8.56 m; orange: 8.85 m (two sample replicates with three PCR replicates each).

Figure 4 .
Figure 4. Bar plots showing the rarefied (a) number of amplicon sequence variants (ASVs) per sample and (b) grouped ASVs assigned to the same taxonomic name for each sample with depth (m) of the sediment core MSM05/5-712-2.

Figure 5 .
Figure 5. Stratigraphic diagrams with sequences assigned to (a) pennate diatoms (blue) and (b) centric diatoms (green) and higher level sequences assigned between family and phylum level (grey).The taxonomic composition with relative proportions (%) of the 360 detected sequence variants is grouped into 75 unique taxonomic names based on identically assigned taxonomic names of sediment core MSM05/5-712-2.