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Key messageThe impact of climatic change should not be dramatic over Italian forests in terms of GPP, which should increase particularly for evergreen forest types. This positive effect is less marked for deciduous forests. The increasing trend should be reduced by the end of the century for all forest types except mountain conifers because of increasing temperature and decreasing rainfall.ContextEstimating the spatial and temporal variability of forest gross primary production (GPP) is a major issue of applied ecology, particularly in relation to ongoing and expected climate change.AimsThe current study proposes a methodological framework for analyzing large-scale forest responses to climate change in terms of GPP.MethodsThe methodology utilizes the GPP estimates of an NDVI-driven model, C-Fix, to assess the performance of a biogeochemical model, BIOME-BGC. The two models were first applied at 1-km pixel scale in Italy over a period of 15years (1999-2013). The model outputs, aggregated on annual basis for the main Italian forest types, were inter-compared and analyzed in relation to major meteorological drivers (i.e., temperature and water-limiting factors).ResultsC-Fix and BIOME-BGC responded similarly to these major drivers, which supported the application of BIOME-BGC as a prognostic tool to simulate the GPP during three time slices of the RCP4.5 climate scenario.ConclusionThe results obtained highlight how the importance of spring temperature and water availability is diversified among the forest types in determining changes of forest GPP all over the Italian peninsula in a future climate.