This study used a genetic fingerprinting technique (automated ribosomal intergenic spacer analysis . [ARISA]) to characterize microbial communities from a culture-independent perspective and to identify those environmental factors that influence the diversity of bacterial assemblages in Wisconsin lakes. The relationships between bacterial community composition and 11 environmental variables for a suite of 30 lakes from northern and southern Wisconsin were explored by canonical correspondence analysis (CCA). In addition, the study assessed the influences of ARISA fragment detection threshold (sensitivity) and the quantitative, semiquantitative, and binary (presence-absence) use of ARISA data. It was determined that the sensitivity of ARISA was influential only when presence-absence-transformed data were used. The outcomes of analyses depended somewhat on the data transformation applied to ARISA data, but there were some features common to all of the CCA models. These commonalities indicated that differences in bacterial communities were best explained by regional (i.e., northern versus southern Wisconsin lakes) and landscape level (i.e., seepage lakes versus drainage lakes) factors. ARISA profiles from May samples were consistently different from those collected in other months. In addition, communities varied along gradients of pH and water clarity (Secchi depth) both within and among regions. The results demonstrate that environmental, temporal, regional, and landscape level features interact to determine the makeup of bacterial assemblages in northern temperate lakes.
ASJC Scopus subject areas
- Food Science
- Applied Microbiology and Biotechnology