Using an affinity analysis to identify phytoplankton associations

Abstract

Phytoplankton functional traits can represent particular environmental conditions in complex aquatic ecosystems. Categorizing phytoplankton species into functional groups is challenging and time‐consuming, and requires high‐level expertise in species autecology. In this study, we introduced an affinity analysis to aid the identification of candidate associations of phytoplankton from two data sets comprised of phytoplankton and environmental information. In the Huaihe River Basin with a drainage area of 270,000 km2 in China, samples were collected from 217 selected sites during the low‐water period in May 2013; monthly samples were collected during 2006–2011 in a man‐made pond, Dishui Lake. Our results indicated that the affinity analysis can be used to define some meaningful functional groups. The identified phytoplankton associations reflect the ecological preferences of phytoplankton in terms of light and nutrient acquisition. Advantages and disadvantages of applying the affinity analysis to identify phytoplankton associations are discussed with perspectives on their utility in ecological assessment.

Seasonal Dynamics and Environmental Drivers of Phytoplankton Composition in a Tropical Dam Over 5 Years in Chiang Mai, Thailand

“…For the identification and counting of phytoplankton, a 0.1 mL concentrated sample was classified, identified and counted using a Carl Zeiss Primo Star light microscope with 400× magnification for phytoplankton identification. A taxonomic key was employed to assist in the identification process [9,10].…”