PS 26-75
Is bacterial community composition more predictable than fungal community composition? Meta-analysis of studies using molecular community analysis methods

Tuesday, August 11, 2015
Exhibit Hall, Baltimore Convention Center
Anna G. Droz, Department of Biological Sciences, Kent State University, Kent, OH
Christopher B. Blackwood, Department of Biological Sciences, Kent State University, Kent, OH

               The use of culture-independent, molecular methods has become standard for determining fungal and bacterial community composition across a wide variety of habitats. To determine whether variation in fungal or bacterial community composition was usually better explained by environmental gradients or treatments included in a study (i.e., which group is more predictable), we performed a comprehensive meta-analysis of all available literature in which bacterial and fungal community composition was examined simultaneously. Articles were found using the Boolean search terms (bacteria* AND fung*) AND (diversity OR "community composition")) in the Web of Science Core Collection. Our analysis included studies using metagenomics, DGGE, TRFLP, clone libraries, 16s/18s rRNA sequencing, DHPLC and ARISA. Techniques commonly used for biomass studies such as ergosterol, qPCR, PLFA, Biolog or CFU counts were disregarded. We hypothesized that bacterial community composition would be better explained than fungal community composition. We further hypothesized that this difference would be strongest in more moist environments due to the fact that fungal extracellular enzyme production is not as important in aquatic systems.


                We found 624 articles that examined fungal and bacterial communities simultaneously, with soil and agricultural systems accounting for over 50% of the articles. The number of fungal species found in forest soil was higher than bacterial species.  Bacterial species were more diverse than fungal species in aquatic habitats. Additional analyses will be performed to determine whether there are differences in amounts of variation in community composition explained by environmental gradients or treatments in each system and using different molecular methods.