Hyperspectral Canopy Reflectance As a Predictor for Root Concentrations of Nitrogen and Carbon in Native and Non-Native Grass Species.

Land managers, scientists or crop professionals need a real-time method to determine below-ground biomass and potential carbon (C) and nitrogen (N) inputs of that biomass without excessive labor or cost and remote sensing offers that possibility. Remote sensing is a non-destructive tool that monitors vigor of vegetation and is used to assess forage quality across various landscapes. Utilizing canopy reflectance as a proxy to assess below-ground concentrations of C and N is limited. 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 N and C concentrations of roots of non-native and native pasture, 2) obtain hyperspectral canopy reflectance data of non-native and native pasture and 3) determine if canopy hyperspectral reflectance data can produce a usable equation for non-destructive determination of total root C and N. Hyperspectral canopy reflectance was measured using an ASD FieldSpec FR radiometer, bi-weekly. Destructive canopy and root samples were acquired immediately after the hyperspectral data were collected. Sampling occurred at toe-, mid- and upper-slope positions along four parallel and widely-spaced transects. Canopy and roots were separated, oven- dried at 65^oC for 48 hr, ground and total C and N concentrations determined. Canopy reflectance and root concentrations of C and N were statistically analyzed using partial least square regression to determine if canopy reflectance could be used as a proxy for predicting root concentrations of C and N. Initial results indicate that prediction of root C and N from hyperspectral canopy reflectance is moderate (R²=0.65).  However, further study is needed to determine if this is an appropriate non-destructive method.  Implications of this research could lead to quicker determination of belowground inputs to soil carbon and nitrogen cycles and provide a better understanding of perennial ecosystem services.