Examining Direct and Indirect Environmental Controls on Soil Microbial Community Composition and Function at the Continental Scale.

Understanding the biogeography of soil microbial communities is of great societal and scientific importance due to the myriad of ecosystem services provided by soil biota. Examining the factors governing the composition and functioning of soil microbial communities is often limited by analysis of linear relationships between environmental factors and microbial metrics, when in fact environmental factors are themselves strongly interrelated. Our goal herein is to utilize structural equation modeling (SEM) to to examine the direct and indirect environmental controls on microbial biomass, microbial community composition, and soil enzyme activity at the continental scale, with particular emphasis on relationships with soil mineralogy, soil chemistry, and plant productivity.

 In 2004 USGS conducted a survey of soils from two transects across the continental United States. Included in this continental survey of soil geochemistry was an analysis of microbial communitiy composition (phospholipid fatty acid analysis, PLFA), soil enzyme activity, soil pH, soil C and N, and soil clay composition.  In addition we collected remotely sensed estimates of primary productivity using the Normalized Difference Vegetation Index (NDVI).

Results show many of the well understood interactions between climate, soil weathering, plant productivity, and soil pH. Microbial community composition shows direct relationships to climate and carbon and indirect relationships to pH and plant producitivity. There were also several surprises.  Our analysis showed that soil mineral composition also has an important direct effect on community composition.  SEM analysis also showed that enzyme activities helped to predict community composition, and not vice versa, which could be used to indicate organic matter quality as a predictor of community composition.   The SEM approach helps to examine the interactions among environmental metrics and community composition and function and will be useful when examining complex continental scale biotic interactions.