Description: Transparent exopolymer particles (TEP) are a class of marine gel particles and important links between surface ocean biology and atmospheric processes. Derived from marine microorganisms, these particles can facilitate the biological pumping of carbon dioxide to the deep sea, or act as cloud condensation and ice nucleation particles in the atmosphere. Yet, environmental controls on TEP abundance in the ocean are poorly known. Here, we investigated some of these controls during the first multiyear time-series on TEP abundance for the Fram Strait, the Atlantic gateway to the Central Arctic Ocean. Data collected at the Long-Term Ecological Research observatory HAUSGARTEN during 2009 to 2014 indicate a strong biological control with highest abundance co-occurring with the prymnesiophyte Phaeocystis pouchetii. Higher occurrence of P. pouchetii in the Arctic Ocean has previously been related to northward advection of warmer Atlantic waters, which is expected to increase in the future. Our study highlights the role of plankton key species in driving climate relevant processes; thus, changes in plankton distribution need to be accounted for when estimating the ocean’s biogeochemical response to global change.

Description: Validated prototypes of new and enhanced biogeochemical and biological sensors and instruments. Validation will be undertaken in the laboratory, in test scenarios, and by deployment in operational conditions

Description: Water samples were collected from the long-term ecological research (LTER) site at Helgoland and the eukaryotic microbial community was assessed. 18S V4 region was amplified using the primer set 528iF /964iR and amplicon sequencing was performed on an Illumina MiSeq™ sequencer in a 2 × 300 bp paired-end run. Sequence data have been deposited in the European Nucleotide Archive (ENA) at the European Bioinformatics Institute (EMBL-EBI) under accession number PRJEB37135 using the data brokerage service of the German Federation for Biological Data (GFBio). 21 million sequences remained after bioinformatic processing and were clustered into Operational Taxonomic Units (OTUs). The Protist Ribosomal Reference database (PR2), version 4.11.1 was used as reference database.

Description: Water sampling was carried out weekly between April and October 2016. Water samples were taken from two shallow sites (less than 5 km apart) in the Orkneys. Sampling was done using a bucket at both sampling locations. Water for filtration was transported to the Orkney Lobster Hatchery where 500–1000 mL of water was filtered over 0.4 µm polycarbonate (PC) filter (Whatman, 47mm). Filters were stored at -20 °C until DNA isolation in the laboratory. The samples were processed at the AWI to produce a metabarcoding data set with the goal of analysing the general diversity at the two sites but also to investigate the dynamics of harmful algal bloom species (HABs). As the data also contained a wealth of information on protistan parasites they were used to produce an additional manuscript on oomycete infections in the planktonic foodweb at the two sites. The bioinformatic processing of the raw sequence files was conducted as follows. The low-quality 3'-ends of the reads were trimmed by Trimmomatic (version 0.38) and the paired-ends were merged by VSEARCH (version 2.3.0). Cutadapt (version 1.19, was used to adjust the sequence orientation and to remove the forward and reverse primer matching sequence segments. Sequences were only kept in the sequence pool if both primer matching segments could be detected. To ensure a high sequence quality the remaining sequences were filtered by VSEARCH and only kept if the expected base error (sum of all base error probabilities) of a sequence was above 0.25. Chimeric sequences were predicted sample-wise by VSEARCH in de novo mode with default settings and removed from the sequence pool as well. Only samples which consisted of at least 10000 sequences after filtering were considered for further analyses. The remaining sequences were clustered into OTUs by the tool swarm (version 2.2.2) with default settings. For each OTU the most abundant amplicon was selected as representative and taxonomically annotated with the default classifier implemented in mothur (version 1.38.1). As reference the Protist Ribosomal Reference database (PR2), version 4.10 was chosen and the minimum confidence cut-off for annotation was set to a value of 80. Further details of the pipeline are provided in (Sprong, et al. 2020; doi:10.1016/j.seares.2020.101914).

Description: The dynamics of diatoms and dinoflagellates have been monitored for many decades at the Helgoland Roads Long-Term Ecological Research site and are relatively well understood. In contrast, small-sized eukaryotic microbes and their community changes are still much more elusive, mainly due to their small size and uniform morphology, which makes them difficult to identify microscopically. By using next-generation sequencing, we wanted to shed light on the Helgoland planktonic community dynamics, including nano- and picoplankton, during a spring bloom. We took samples from March to May 2016 and sequenced the V4 region of the 18S rDNA. Our results showed that mixotrophic and heterotrophic taxa were more abundant than autotrophic diatoms. Dinoflagellates dominated the sequence assemblage, and several small-sized eukaryotic microbes like Haptophyta, Choanoflagellata, Marine Stramenopiles and Syndiniales were identified. A diverse background community including taxa from all size classes was present during the whole sampling period. Five phases with several communities were distinguished. The fastest changes in community composition took place in phase 3, while the communities from phases 1 to 5 were more similar to each other despite contrasting environmental conditions. Synergy effects of next-generation sequencing and traditional methods may be exploited in future long-term observations.

Description: Dinoflagellate species of the genus Dinophysis have become target organisms for surveillance and monitoring of microalgae as they may produce potent diarrhetic shellfish toxins and therefore have negative socio-economic impacts. The formation of Dinophysis blooms as well as toxin composition and cellular toxin content depends on several multifactorial climate and environmental drivers and it might be expected that the occurrence of toxic events becomes more intense, widespread, frequent and unexpected in future decades due to climate variability. Conventional methods for the identification of microalgae e.g. microscopy, still have some deficiencies as they are very time-consuming and need special knowledge and experience, especially in case of difficult morphological species distinction. Standard quantification methods also might fail to detect and determine Dinophysis species due to their typically low cell densities and their spatial heterogeneity (=patchiness). Therefore innovative technologies for environmental monitoring of toxic microalgae are needed to prevent humans and aquatic environments from toxic threats and damage. We analysed the occurrence, abundance and dispersal of toxic dinoflagellate species in Nordic seas and the Arctic Ocean. Genetic analyses included a modular composed autonomous rRNA biosensor approach that allows rapid, precise and economically efficient high-resolution quantification and identification of microalgae in aquatic environments. Next generation sequencing (Illumina) was used to get additional information on distributional patterns of the most common dinoflagellate species in the observation area.

Description: Microalgae are the major producers of biomass and organic compounds in the aquatic environment. Among them there are toxic species (mainly dinoflagellates) known to have the potential to form Harmful Algal Blooms, the so called HABs. HABs are occurring more often and at new locations. In general, knowledge about biogeographic distribution of harmful algae in the northern hemisphere is limited and patchy. During this project, we will study the seasonal dynamics of marine protists, with special emphasis on toxic algae in the North Sea. Samples will be taken from four geographical distinct locations in the German Bight and from the Orkney Islands. Protist community composition will be assessed by Illumina sequencing and a newly developed fully automated biosensor system. The latter allows for automated sampling and filtration of water samples and automated detection of selected toxic algal species, while the detection is based upon electro chemical quantification of RNA by sandwich hybridization. Here we show first results of calibrating the biosensor for selected toxic algae that are known to occur in the North Sea. Furthermore, we also show preliminary results of the characterization of protist communities from spring to autumn 2016 at four different observation locations in the North Sea via Illumina sequencing.

Description: Information on recent biomass distribution and biogeography of photosynthetic marine protists with adequate temporal and spatial resolution is urgently needed to better understand consequences of environmental change for marine ecosystems. Here we introduce and review a molecular-based observation strategy for high resolution assessment of these protists in space and time. It is the result of extensive technology developments, adaptations and evaluations which are documented in a number of different publications and the results of recently accomplished field testing, which are introduced in this review. The observation strategy is organized at four different levels. At level 1, samples are collected at high spatio-temporal resolution using the remote-controlled automated filtration system AUTOFIM. Resulting samples can either be preserved for later laboratory analyses, or directly subjected to molecular surveillance of key species aboard the ship via an automated biosensor system or quantitative polymerase chain reaction (level 2). Preserved samples are analyzed at the next observational levels in the laboratory (level 3 and 4). This involves at level 3 molecular fingerprinting methods for a quick and reliable overview of differences in protist community composition. Finally, selected samples can be used to generate a detailed analysis of taxonomic protist composition via the latest Next Generation Sequencing Technology (NGS) at level 4. An overall integrated dataset of the results based on the different analyses provides comprehensive information on the diversity and biogeography of protists, including all related size classes. At the same time the cost effort of the observation is optimized in respect to analysis effort and time.