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International audienceAim Africa is identified by the Inter-governmental Panel on Climate Change (IPCC) as the least studied continent in terms of ecosystem dynamics and climate variability. The aim of this study was (1) to adapt the Lund-Postdam-Jena-GUESS (LPJ-GUESS) ecological modelling framework to Africa by providing new parameter values for tropical plant functional types (PFT), and (2) to assess the sensitivity of some African biomes to changes in precipitation regime. Location The study area was a representative transect (0-22 degrees N and 7-18 degrees E) through the transition from equatorial evergreen forests to savannas, steppes and desert northwards. The transect showed large latitudinal variation in precipitation (mean rainfall ranged from 50 to 2300 mm year(-1)). Methods New PFT parameters used to calibrate LPJ-GUESS were based on modern pollen PFTs and remote sensed leaf area index (LAI). The model was validated using independent modern pollen assemblages, LAI and through comparison with White's modern potential vegetation map. Several scenarios were developed by combining changes in total rainfall amount with variation in the length of the dry season in order to test the sensitivity of African biomes. Results Simulated vegetation compared well to observed data at local and regional scales, in terms of ecosystem functioning (LAI), and composition (pollen and White's vegetation map). The assessment of the sensitivity of biomes to changes in precipitation showed that none of the ecosystems would shift towards a new type under the range of precipitation increases suggested by the IPCC (increases from 5 to 20%). However, deciduous and semi-deciduous forests may be very sensitive to small reductions in both the amount and seasonality of precipitation. Main conclusions This version of LPJ-GUESS parameterized for Africa simulated correctly the vegetation present over a wide precipitation gradient. The biome sensitivity assessment showed that, compared with savannas and grasslands, closed canopy forests may be more sensitive to change in precipitation regime due to the synergetic effects of changed rainfall amounts and seasonality on vegetation functioning

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