High-resolution monitoring of marine protists based on an observation strategy integrating automated on-board filtration and molecular analyses - Katja Metfies; Friedhelm Schroeder; Johanna Hessel; Jochen Wollschläger; Sebastian Micheller; Christian Wolf; Estelle Kilias; Pim Sprong; Stefan Neuhaus; Stephan Frickenhaus; Wilhelm Petersen (Ocean Science, 2016)
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.