Comparison of multivariate microbial datasets with the Shannon index: An example using enzyme activity from diverse marine environments

Abstract

Heterotrophic microbial communities contain substantial functional diversity, so studies of community function often generate multivariate data sets. Techniques for data reduction and analysis can help elucidate qualitative differences among sites from multivariate data sets that may be difficult to grasp intuitively from raw data. The Shannon index is one such technique, used commonly in ecological studies to quantify species evenness. Here, the Shannon index is used to compare quantitatively the extent to which complex microbial communities vary in their capability to access polysaccharides. It is maximized when hydrolysis rates for all polysaccharides are equal and minimized when the range among individual hydrolysis rates at a given site is large. Application of the technique to depth profiles of polysaccharide hydrolysis rates from four distinct pelagic marine environments indicates that, in three of four cases, surface water communities accessed substrates at a more even rate than in deeper waters. The technique could usefully be applied to other types of data obtained in studies of microbial activity and the geochemical effects.