Tree-grass savannas are a widespread biome and are highly valued for their ecosystem services. There is a need to understand the long-term dynamics and meteorological drivers of both tree and grass productivity separately in order to successfully manage savannas in the future. This study investigated the interannual variability (IAV) of tree and grass gross primary productivity (GPP) by combining a long-term (15 year) eddy covariance flux record and model estimates of tree and grass GPP inferred from satellite remote sensing. On a seasonal basis, the primary drivers of tree and grass GPP were solar radiation in the wet season and soil moisture in the dry season. On an interannual basis, soil water availability had a positive effect on tree GPP and a negative effect on grass GPP. No linear trend in the tree-grass GPP ratio was observed over the 15-year study period. However, the tree-grass GPP ratio was correlated with the modes of climate variability, namely the Southern Oscillation Index. This study has provided insight into the long-term contributions of trees and grasses to savanna productivity, along with their respective meteorological determinants of IAV.
Keywords: DIFFUSE model; MODerate resolution Imaging Spectroradiometer; Southern Oscillation Index; carbon sequestration; gross primary productivity; random forest.
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