## 4 Discussion  
We presented here an analysis of climate change impacts on tropical tree species in central Africa using the CARAIB dynamic vegetation model. For this purpose, we refined species parameterization from PFT- to species-specific traits we could find in morpho-physiological trait databases or collect from previous projects, for 12 species (trees and palms) known to be widely used by local populations in central Africa. Our results clearly show the sensitivity of species productivity to these traits and their intraspecific variations with a direction in NPP change depending on the new combination of traits. For instance, the productivity of _Pycranthus angolensis_ increases while the one of _Ceiba pentandra_ decreases. This indicates that the trait acclimation does not necessarily results in NPP increase, which is rather in accord with [PERSON] et al. [95]. They concluded that traits at individual level are poor predictors of growth performances while traits strongly vary within species with environmental conditions. Though we did not introduce the traits separately, the analysis of the 12 species modifications (Table 2) allowed to disentangle the effects of each trait on species physiology. Following the formulation of [PERSON] et al. [74], the maximum carboxylation rate (V\({}_{\text{cmax}}\)) is a function of foliage C:N ratio and specific leaf area (SLA). A decrease of foliage C:N induces both an augmentation of photosynthetic activity and a slighter augmentation of leaf respiration driving at an increased species NPP. A decrease of the specific leaf area corresponds to an increase of the leaf thickness (if leaf density is constant) meaning an increase in the number of chloroplasts. This induces a rise of the  
Figure 9: Changes in biomass per unit area (g C m\({}^{-2}\)) between 2080–2099 and the reference 1980–1999 period. Biomass change for the species _Ceiba pentendra_. The magnitude of change is expressed as a multiple of the spatial average of the 1980–1999 biomass standard deviation \(\overline{\sigma}\) (704 g C m\({}^{-2}\)) over the species current distribution area [48]. Biomasses correspond here to the ensemble mean of the results obtained with the seven climate projections under the RCP8.5 scenario and with species-specific morpho-physiological traits. Three different atmospheric CO\({}_{2}\) configurations are tested: (**a**) a CO\({}_{2}\) constant [330], (**b**) a CO\({}_{2}\) variable downregulated [down], and (**c**) a CO\({}_{2}\) variable [var]. Disappearance of species is indicated in red, expansion in blue and preservation in green colors. Biomass increase and decrease over the preserved range are respectively in dark and light greens. (**a**’,**b**’,**c**’) the same for _Musanga cceptioides_ with a \(\overline{\sigma}\) of 828 g C m\({}^{-2}\). See Supplementary S5 for all the species. maximum carboxylation rate (V\({}_{\text{cmax}}\)) but the consequently more important leaf biomass (higher leaf thickness) also causes higher respiration costs. The resulting effect on species productivity is less direct. In humid conditions like in equatorial Africa, a reduced SLA results in improved photosynthetic activity and higher species productivities but, in drier climates, photosynthesis may be limited by stomatal closure. The vegetation model projects relatively similar distribution patterns for all the species and, despite high sensitivity values, seems to overestimate some of them. A first reason might be an underestimation of actual species ranges, not fully covered by observations. Knowledge of plant species distribution in tropical Africa is improving but it remains limited [55]. However, there are other explanations for these discrepancies. The model projects the potential climatic species distribution ignoring notably past species migration and dispersal that have shaped--and maybe limited--their current pattern [96].