Phytoplankton assemblages, environmental influences and trophic status using canonical correspondence analysis, fuzzy relations, and linguistic translation

a r t i c l e i n f o In a global assessment, canonical correspondence analysis (CCA) and partial CCA were used to ordinate Lake Huron phytoplankton abundances from June and August 1991 and environmental variables. June taxa were associated with NO 3 and chloride, while August taxa were associated with SiO 2 and temperature, and to some degree, with TSP and NH 3. in August reflecting seasonal change. From local analysis using results from CCA and partial CCA in fuzzy relational analysis, A. minutissimum and C. comensis were influential in June, while F. crotonensis was influential in August. From linguistic translation and trophic status assignment, F. capucina and T. fenestrata indicated eutrophy, A. formosa indicated mesotrophy, C. pseudostelligera indicated mesotrophy–eutrophy, F. crotonensis and U. eriensis indicated oligotrophy–eutrophy, Cyclotella #6 indicated oligotrophy–mesotrophy, and C. michiganiana indicated oligotrophy. A linguistic solution with respect to trophic status is useful for policy makers and others interested in understanding water quality and ways to develop decisions about remediation. Phytoplankton are a major part of the aquatic food web and are important for relational and predictive schema for ecological assessment of the Great Lakes. Phytoplankton assemblages have been used for some time as water quality bioindicators in the Great Lakes (Stoermer, 1978). Of the phytoplankton, diatoms are recognized as bioindicators by governmental agencies and used in water quality assessment in North America Not only are they found in the plankton, but also on a variety of substrates, including rocks, sand, plants, and animals (Round et al., 1990). Individual species are adapted to a wide range of environmental conditions, including 83 °C geyser pools and −2 °C polar sea ice in In ecological studies, temporal variability, spatial scaling, qualitative, and quantitative measures are characteristic of data used in assessment. Because of their siliceous frustules, diatoms are preserved in the sediments (e.g., Wolin et al., 1988), and along with availability in water, provide a long temporal record in aquatic systems such as the Great Lakes. Diatoms occur nearshore and offshore, at the surface and throughout the water column, so they also provide a spatial record. To model complexities of ecosystems, multivariate statistics have been used. These methods are widely accepted and proven ways to transform raw data into a biplot picture of variation (Gower and Hand, 1996). For example, the variation may be a gradient (ter Braak, 1986) or separation of groups as a result …