, Volume 58, Issue 3, pp 591-598
Date: 26 Mar 2009

Fine Scale Patterns in Microbial Extracellular Enzyme Activity during Leaf Litter Decomposition in a Stream and its Floodplain

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Abstract

Microorganisms mediate the decomposition of leaf-litter through the release of extracellular enzymes. The surfaces of decomposing leaves are both chemically and physically heterogeneous, and spatial patterns in microbial enzyme activity on the litter surface should provide insights into fine-scale patterns of leaf-litter decomposition. Platanus occidentalis leaves were collected from the floodplain of a third-order stream in northern Mississippi, enclosed in individual litter bags, and placed in the stream channel and in the floodplain. Replicate leaves were collected approximately monthly over a 9-month period and assayed for spatial variation in microbial extracellular enzyme activity and rates of organic matter (OM) decomposition. Spatial variation in enzyme activity was measured by sampling 96 small discs (5-mm diameter) cut from each leaf. Discs were assayed for the activity of enzymes involved in lignin (oxidative enzymes) and cellulose (β-glucosidase, cellobiohydrolase) degradation. Rates of OM loss were greater in the stream than the floodplain. Activities of all enzymes displayed high variability in both environments, with severalfold differences across individual leaves, and replicate leaves varied greatly in their distribution of activities. Geostatistical analysis revealed no clear patterns in spatial distribution of activity over time or among replicates, and replicate leaves were highly variable. These results show that fine-scale spatial heterogeneity occurs on decomposing leaves, but the level of spatial variability varies among individual leaves at the measured spatial scales. This study is the first to use geostatistical analyses to analyze landscape patterns of microbial activity on decomposing leaf litter and in conjunction with studies of the microbial community composition and/or substrate characteristics, should provide key insights into the function of these processes.