Satellite prediction of soil δ13C distributions in a southern African savanna

Abstract

Stable carbon isotopes have been frequently used to indicate carbon pools and processes in soils, plants, and the atmosphere. Carbon isotope compositions are particularly useful in partitioning soil carbon sources between C 3 and C 4 vegetation because of the distinct δ 13C distributions for C 3 and C 4 vegetation. Remote sensing is a powerful tool used to identify ecosystem patterns and processes at larger scales. A union of these two approaches would hold promise for spatially continuous estimates of carbon isotope compositions. In the current study, a framework is presented for using high spatial resolution remote sensing to predict soil δ 13C distributions across a southern Africa savanna ecosystem. The results suggest that if the vegetation–soil δ 13C relationship can be established, soil δ 13C distributions can be estimated by high-resolution satellite images (e.g., IKONOS, Quickbird). Despite limitations remote sensing is a promising tool to expand estimates of terrestrial δ 13C spatial patterns and dynamics.