Imaging Flow Cytometry for Phylogenetic and MorphologicallyBased Functional Group Clustering of a Natural Phytoplankton Community over 1 Year in an Urban Pond.

ABSTRACT

Ponds are an insufficiently studied research object but represent a biodiversity hotspot and have a high value for ecosystem services like recreation, water retention, or angling. Especially urban ponds create a direct contact for citizens experiencing nature. But on the other side, these systems also suffer from several pressures caused by humans, for example, high nutrient and salt influxes or high temperatures. Phytoplankton organisms are a crucial part of ponds ecosystem and an understanding of community composition is crucial especially when eutrophication and high temperatures lead to dominance of unpleasant toxic cyanobacteria. With traditional microscopic methods for phytoplankton analysis, monitoring is not feasible with high spatial resolution and frequency. Therefore, a new approach of imaging flow cytometry to classify phytoplankton species in either taxonomic or morphologically based functional groups (MBFGs) is suggested. In this study, both classifications could be successfully applied to a natural phytoplankton community in an urban pond in Leipzig with minor modifications. Both classifications in combination provide a good mechanistic understanding of phytoplankton community dynamics. In addition, a great advantage of the measurements is the archivability of microscopic images allowing a comprehensive respective data analysis. Two examples of detailed trait and image analysis are demonstrated to investigate single-cell traits for cyanobacteria and chlorophytes/euglenophytes and to follow the fate of a cyanobacterial bloom affected by a fungal infection. © 2020 The Author. Cytometry Part A published by Wiley Periodicals, Inc. on behalf of International Society for Advancement of Cytometry.