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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

Author
item SCOTT, TREY - Nasa Goddard Institute For Space Studies
item PETERSON, BREKKE - Orise Fellow
item Starks, Patrick

Submitted to: Grazinglands Research Laboratory Miscellaneous Publication
Publication Type: Abstract Only
Publication Acceptance Date: 4/8/2016
Publication Date: N/A
Citation: N/A

Interpretive Summary: Abstract only.

Technical Abstract: Land managers, scientists, and crop professionals need real-time, inexpensive, and labor-saving methods to determine below-ground biomass and potential carbon (C) and nitrogen (N) inputs of that biomass. Remote sensing is a non-destructive tool that monitors vigor of vegetation and has been used to assess forage quality. A study was conducted at the USDA-ARS Grazinglands Research Laboratory, El Reno, OK 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) 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 bi-weekly using an ASD FieldSpec FR radiometer. 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 65oC 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. 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.