Abstract
The high level of spatial and temporal heterogeneity in soil N cycling processes hinders our ability to develop an ecosystem‐wide understanding of this cycle. This study examined how incorporating an intensive assessment of spatial variability for soil moisture, C, nutrients, and soil texture can better explain ecosystem N cycling at the plot scale. Five sites distributed across a regionally representative vegetation and elevation gradient at the Coweeta Hydrologic Laboratory in the southern Appalachian Mountains were sampled five times between November 2010 and March 2012. We used electromagnetic induction (EMI) to survey for soil moisture, soil texture, and near‐infrared reflectance spectroscopy (NIRS) to estimate extractable NH4+, total C, and total N concentrations. Laboratory assays of nitrification and denitrification potential rates were used as an index for N cycling dynamics. Multivariate regression analysis indicated that the NIRS and EMI survey data explained 30 to 90% of the variability in potential nitrification rates (p < 0.01) and 16 to 70% of variability in potential denitrification rates (p < 0.01). Two extrapolation approaches were used to calculate the mean and the variability of potential rates: (i) stratified selection of collected samples based on EMI and NIRS predictors; and (ii) random selection of collected samples. The mean for potential nitrification rates based on EMI and NIRS stratification yielded similar (oak–pine and mixed oak) and greater (northern hardwood and cove hardwood) rates, whereas potential denitrification rates were greater in all sites for the stratified‐based estimates. This study demonstrated that the application of geophysical tools may enhance our ecosystem‐level understanding of the N cycle.
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