Unveiling new diversity and connections in the planktonic food web using metabarcoding

Plankton can serve as a food source for the whole marine food web and the autotrophic fraction is responsible for nearly half of global primary production. However, it has remained challenging to monitor plankton diversity and identify food web connections. Previous research based on metabarcoding has provided unprecedented insights into biodiversity and the distribution of thus-far understudied groups. Therefore, the main scope of this thesis was to gain information on understudied compartments of the eukaryotic plankton community at Helgoland Roads, a long-term monitoring site in the German North Sea. Using 18S metabarcoding of water samples, a three-year dataset was obtained which formed the basis for the publications in this thesis, which provide in-depth information on the planktonic structure of the pelagic system at Helgoland Roads and refine and complement our prior understanding. Remarkably high abundances of non-autotrophic taxa were found during spring, and spring bloom communities were not dominated by diatoms. Generally, the plankton community was highly diverse, with a large proportion of pico- and nanoplanktonic taxa. These were much more diverse and abundant than previously seen at Helgoland and displayed various connections in the planktonic food web. Unexpected predator-prey relationships were found in the food web, and zooplankton might be more opportunistic than previously known. A relevant finding was the high diversity and high abundance of the so-far understudied marine parasitoids at all taxonomic levels. Furthermore, I investigated the comparability of metabarcoding data to morphological counts. Correlations between new metabarcoding datasets and conventional datasets might be weak depending on taxonomic levels and individual taxa. Combining different methods remains challenging but is the only way to obtain a more comprehensive view of the marine planktonic food web.


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