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Title: Hyperspectral canopy reflectance as a predictor for root concentrations of nitrogen and carbon in native and non-native grass species

item SCOTT, TREY - Redlands Community College
item PETERSON-MUNKS, BREKKE - Orise Fellow
item Starks, Patrick

Submitted to: ASA-CSSA-SSSA Annual Meeting Abstracts
Publication Type: Abstract Only
Publication Acceptance Date: 8/1/2015
Publication Date: 11/15/2015
Citation: Scott, T., Peterson-Munks, B., Starks, P.J. 2015. Hyperspectral canopy reflectance as a predictor for root concentrations of nitrogen and carbon in native and non-native grass species [abstract]. ASA-CSSA-SSSA Annual Meeting. Synergy in Science: Partnering for Solutions, November 15-18, 2015, Minneapolis, Minnesota. Abstract number 127-4. Available:

Interpretive Summary: Abstract only.

Technical Abstract: Land managers, scientists or crop professionals need a real-time method to determine below-ground biomass and potential carbon (C) and nitrogen (N) inputs from that biomass without excessive labor. Remote sensing is a non-destructive assessment tool that monitors vigor of vegetation and is used to assess forage quality across various landscapes. Information 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.) pastures and native, tallgrass prairie pastures to: 1) determine N and C concentrations of roots, 2) obtain hyperspectral canopy reflectance data 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 collection of the hyperspectral data. Sampling occurred at toe-, mid- and upper-slope positions along four parallel and widely-spaced transects across the pastures. Canopy and roots were separated, oven-dried at 65oC for 48 hr, processed by grinding 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.