ALBERT

Description: The Coastal Observing System for Northern and Arctic Seas (COSYNA) was established in order to better understand the complex interdisciplinary processes of northern seas and the Arctic coasts in a changing environment. Particular focus is given to the German Bight in the North Sea as a prime example of a heavily used coastal area, and Svalbard as an example of an Arctic coast that is under strong pressure due to global change.The COSYNA automated observing and modelling system is designed to monitor real-time conditions and provide short-term forecasts, data, and data products to help assess the impact of anthropogenically induced change. Observations are carried out by combining satellite and radar remote sensing with various in situ platforms. Novel sensors, instruments, and algorithms are developed to further improve the understanding of the interdisciplinary interactions between physics, biogeochemistry, and the ecology of coastal seas. New modelling and data assimilation techniques are used to integrate observations and models in a quasi-operational system providing descriptions and forecasts of key hydrographic variables. Data and data products are publicly available free of charge and in real time. They are used by multiple interest groups in science, agencies, politics, industry, and the public.

Description: Information on recent biomass distribution and biogeography of photosynthetic marine protists with adequate temporal and spatial resolution is urgently needed to better understand the 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 the recently completed field testing which are introduced in this paper. The observation strategy is organized at four different levels. At level 1, samples are collected at high spatiotemporal resolution using the remotely 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 (levels 3 and 4). At level 3 this involves 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 of the observation is optimized with respect to analysis effort and time.

Description: It is important to characterize and understand the diversity of marine protists because of their relevance for ecosystem functioning. In the era of molecular science, diversity studies have received renewed attention. High-throughput, cost-intensive next generation sequencing provides deep insight in protist diversity but limits the volume of studied samples. Protist observations with high spatiotemporal resolution, therefore, require a quick and cost-effective tool to channelize the large sample volume and help select representatives for diversity studies. In this study, we evaluated the validity of “Automated Ribosomal Intergenic Spacer Analysis” (ARISA) as a means of estimating variability in marine protist communities. The evaluation was based on statistical correlation of ARISA data and 454-pyrosequencing data from samples collected in the Southern Ocean and Arctic Ocean. Here, we provide evidence that differences in ARISA profiles reflect taxon-specific differences observed in 454-pyrosequencing data sets. Calculated similarity indices for the ARISA profiles and 454- pyrosequencing data of 27 marine protist samples revealed strong agreements between the results of both methods regarding the extent of variability among protist communities. We suggest that ARISA might become an important tool for surveillance of differences in marine protist communities with high spatiotemporal resolution. Furthermore, it might serve as a preselection tool to identify representative samples in large data sets.