Assessment of Microbial Biomass Carbon and Nitrogen of Native and Non-Native Perennial Pasture Soil Using Hyperspectral Data.

Soil microbial biomass carbon and nitrogen (MBC/MBN) are integral parts to soil organic matter, which if left out of nutrient calculations could exacerbated application of fertilizer resulting in increased production costs and chemical runoff. More timely and cost-effective methods are needed to assess MBC and MBN.  Remote sensing is a technique which may provide a timely and cost-effective solution.  Although soil nutrients have been determined using reflectance data, no equation is published correlating hyperspectral reflectance data and microbial biomass carbon and nitrogen (MBC/MBN). A study at the USDA-ARS Grazinglands Research Laboratory, El Reno, OK was conducted in non-native, Old World Bluestem (Bothriochloa sp.) and native, tallgrass prairie to: 1) determine MBC/MBN content of native and non-native perennial pasture soils, 2) obtain hyperspectral reflectance data of ground soils and 3) correlate MBC/MBN values with hyperspectral reflectance data to determine if reflectance data can be used to determine MBC/MBN content of soil. Bi-weekly soil sampling (0-15cm) occurred at toe-, mid- and upper-slope positions along four parallel and widely-spaced transects. Each soil sample was processed for MBC/MBN using standard chloroform fumigation methods and analyzed on a Shimadzu TOC. Bulk unfumigated and fumigated soil was dried at 65 ° for 24 hrs, ground to pass through a 2mm sieve and hyperspectral reflectance data was obtained using an ASD FieldSpec FR radiometer. Soil reflectance and MBC/MBN concentrations were statistically analyzed using partial least square regression to determine if soil reflectance could be used for predicting MBC/MBN. Initial results indicate that utilizing hyperspectral soil data to determine soil MBC and MBN concentration is favorable (R²=0.65). Further study is needed to determine if this will be a suitable tool to determine MBC/MBN. Implications of this research could lead to real time soil fertility decision making reducing input cost and loss of C and N to the environment.