Hyperspectral Reflectance and Stable Isotopic Nitrogen: Tools to Assess Forest Ecosystem Nitrogen Cycling

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Virginia Tech


The use of nitrogenous fertilizers in agricultural and forestry practices coupled with increased fossil fuel combustion and resulting nitrogen (N) deposition across the landscape have contributed to a near doubling of N inputs to terrestrial ecosystems.  With such dramatic changes have come adverse environmental consequences including the acidification of soil and water resources and an increased rate of biodiversity loss in both flora and fauna.  A method of rapidly predicting ecosystem susceptibility to N loss across large spatial scales would facilitate the identification of those systems most likely to contribute to potentially adverse environmental impacts.  To begin the development of such a framework, this research utilizes study sites located throughout the geographic ranges of Douglas-fir (Pseudotsuga menziesii) and loblolly pine (Pinus taeda) to explore relationships between hyperspectral remote sensing, N stable isotope ratios ("15N) and growth response to nitrogenous fertilizer.  In both species multiple linear regression models relating leaf-level reflectance to "15N showed strong predictive capabilities, with some models explaining more than 65% of the variance in "15N.  Significant correlations between "15N metrics and growth response to N fertilization were also observed in both species.  Additional exploratory analysis of the inclusion of "15N metrics with other environmental and edaphic variables to predict fertilizer growth response showed an increase in model performance with the addition of the enrichment factor (EF ="15NFol - "15NSoil).  This research demonstrates the ability of hyperspectral reflectance to predict "15N and reveals the potential of "15N to be included in future models to predict fertilizer growth response.



hyperspectral reflectance, isotopic nitrogen, Douglas-fir, Loblolly pine, growth response