Trait-, guild- and functional group based methods became widespread in analyses
of spatial and temporal patterns of aquatic assemblages. The extended use of such
groupings can be explained by their joint feature: they decrease structural
complexity of large data sets by decreasing the number of categories largely
without loosing functional attributes. Thus, relating assemblages changes to
environmental drivers is greatly enhanced. This lecture will review the existing
trait-, guild- and functional group based methods developed for phytoplankton
and attached diatoms, their common and distinctive features along with
demonstration of some case studies
