Coupling Imaging Spectroscopy and Ecosystem Process Modelling - The Importance of Spatially Distributed Foliar Biochemical Concentration Estimates for Modelling NPP of Grassland Habitats

Information on canopy chemical concentrations is of great importance for the study of nutrient cycling, productivity and for input to ecosystem process models. In particular, foliar carbon to nitrogen ratio (C:N) drives terrestrial biogeochemical processes such as decomposition and mineralization, and thus strongly influences soil organic matter concentrations and turnover rates. This study evaluated the effects of using spatial estimates of foliar C:N derived from hyperspectral remote sensing for simulating NPP by means of the ecosystem process model Biome-BGC. The main objectives of this study were to calibrate spatial statistical models for the prediction of foliar C:N for grassland habitats at the regional scale, using airborne HyMap hyperspectral data, to use the foliar C:N predictions as input to the ecosystem process model Biome-BGC and derive NPP estimates and finally to compare these results to NPP estimates derived using C:N value reported in literature and derived from field measurements. Results from this research indicate that NPP estimates using the HyMap predicted C:N differed significantly from those when C:N values from "global" or "regional" measurements were used. Extending the current research to broader spatial scales can help to initialise, validate and adjust better ecological process models.