Soil microbial diversity and soil processes driven by the metabolic activities of soil microbes are extremely variable across spatial and temporal scales. The scales of these heterogeneities are poorly understood, however, owing to the destructive and labor-intensive nature of traditional soil sampling and processing methods. Furthermore, because of the relatively slow rate of mixing in soils, an understanding of spatial heterogeneity is needed before assessments of temporal heterogeneity can be confidently separated from potentially confounding spatial variation. To better understand the spatial variation of soil microbial communities, we collected “microsamples” of soil (<3 g each) that provided enough material for DNA extraction, enabling us to characterize microbial communities, while dramatically enhancing the spatial resolution of diversity metrics. We collected twenty-five soil samples in a 10x10 cm grid at five points along a 36 m transect in each of six 36 x 20 m plots of a low-diversity perennial grassland dominated by Panicum virgatum (fertilized and unfertilized treatments) for a total of 750 soil samples.
Results/Conclusions
We successfully sequenced the 515–806 region of the 16S rRNA-encoding genes from each of the samples on an Illumia MiSeq DNA sequencer to extract information on diversity and taxonomic structure of soil bacterial communities. 5.23 million reads passed the initial quality filter and were used for subsequent microbial ecology analyses. Preliminary results based on a principal coordinates analysis of the 16S rRNA-based MiSeq data suggest that fertilization induced a shift in microbial community structure. We infer that nutrient availability (nitrogen) can drive microbial community composition, thus patchiness in nutrient availability may influence spatial structure. Soil CO2 efflux measured at the time of soil sampling was poorly correlated with soil moisture (R2=0.15, P=0.07) suggesting that microbial community structure could influence soil respiration rates. This work will increase our understanding of spatial variations in microbial community structure and will link this structure with variations in concurrently measured abiotic factors. Overall, this effort is a first step in building greater mechanistic understanding of the feedbacks between soil microbes and ecosystem processes, such as carbon fluxes and nutrient cycling.