Using landscape and depth gradients to decouple the impact of correlated environmental variables on soil microbial community composition

Simultaneously assessing shifts in microbial community composition along landscape and depth gradients allows us to decouple correlations among environmental variables, thus revealing underlying controls on microbial community composition. We examined how soil microbial community composition changed with depth and along a successional gradient of native prairie restoration. We predicted that carbon would be the primary control on both microbial biomass and community composition, and that deeper, low-carbon soils would be more similar to low-carbon agricultural soils than to high carbon remnant prairie soils. Soil microbial community composition was characterized using phospholipid fatty acid (PLFA) analysis, and explicitly linked to environmental data using structural equations modeling (SEM). We found that total microbial biomass declined strongly with depth, and increased with restoration age, and that changes in microbial biomass were largely attributable to changes in soil C and/or N concentrations, together with both direct and indirect impacts of root biomass and magnesium. Community composition also shifted with depth and age: the relative abundance of sulfate-reducing bacteria increased with both depth and restoration age, while gram-negative bacteria declined with depth and age. In contrast to prediction, deeper, low-C soils were more similar to high-C remnant prairie soils than to low-C agricultural soils, suggesting that carbon is not the primary control on soil microbial community composition. Instead, the effects of depth and restoration age on microbial community composition were mediated via changes in available phosphorus, exchangeable calcium, and soil water, together with a large undetermined effect of depth. Only by examining soil microbial community composition shifts across sites and down the soil column simultaneously were we able to tease apart the impact of these correlates environmental variables.