Linking litter decomposition processes and microbial community composition in northern hardwood forest soils

Background/Question/Methods Litter decomposition, belowground C cycling, and nutrient turnover in temperate forests is partially controlled by the microbial production of extracellular enzymes. Thus, it is reasonable to expect patterns of microbial community functional group composition and structure to be related to patterns of soil enzyme activity. We are just beginning to understand the diversity of soil microbial communities, but the difficulty in linking microbial identity to ecosystem function may be further exacerbated by poorly understood seasonal and spatial variability of soil enzyme pools and activities. We suggest such variability arises due to factors regulating enzyme production and turnover. We will present data for patterns of soil enzyme activity, and attempt to link those patterns with microbial community composition data, for two hardwood forests in NE Ohio. Temporal trends from one forest encompass monthly measurements for an entire year, while spatial patterns from the other are derived from 125 soil samples from a landscape-scale meta-community analysis in a spatially complex hardwood forest ecosystem. We measured the potential activity of 8 extra-cellular enzymes using colorimetric and flourometric techniques, and will estimate soil fungal and bacterial composition using DNA-based techniques (T-RFLP and sequencing). Results/Conclusions In one forest, we found that mean annual enzyme activities generally declined with depth, with highest activities in the forest floor compared to mineral soil (with the exception of the oxidative enzyme peroxidase). Mineral soil activities did not vary across season or month, but forest floor activity was highest in winter months when soil temperature is low and snow cover is common. Fungal community profiles associated with these samples are currently underway. In another forest, we found that the spatial variability in enzyme activities is only partially explained by ecosystem type, and the highest levels of oxidative enzyme activity were associated with seasonally anaerobic wet soils. Soil microbial community analyses are on-going for this site as well. Our results thus far imply that high winter enzyme pools are associated with higher microbial activity than previously thought or enzymes that are highly conserved and stabilized in the forest floor during periods of low microbial activity. If the latter is true, then measurements of potential enzyme activity might not be a good metric of microbial community dynamics at a given point in time, but a spatially or temporally integrated tool for estimating potential process rates or microbial resource demand.