Abstract
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.
Psomas, A