Dynamic global vegetation models (DGVMs) have been shown to broadly reproduce seasonal and interannual patterns of carbon exchange, as well as realistic vegetation dynamics. To assess the uncertainties in these results associated with model parameterization, the Lund-Potsdam-Jena-DGVM (LPJ-DGVM) is analyzed in terms of model robustness and key sensitive parameters. Present-day global land-atmosphere carbon fluxes are relatively well constrained, despite considerable uncertainty in global net primary production mainly propagating from uncertainty in parameters controlling assimilation rate, plant respiration and plant water balance. In response to climate change, water-use efficiency driven increases in net carbon assimilation by plants, transient changes in vegetation composition and global warming effects on soil organic matter dynamics are robust model results. As a consequence, long-term trends in land-atmosphere fluxes are consistently modeled despite an uncertainty range of -3.35 ¿ 1.45 PgC yr-1 at the end of the twenty-first century for the specific scenario used.