In tropical forests, the sustainable management of timber stocks relies to a large extent on the accurate estimates of commercial volumes. In the context of high degradation of West-African forests, non-destructive methods by using volume equations to make timber stock estimations. Nevertheless, the use of inaccurate equations has often led decision makers to misjudge the real potential of west-African managed forests and increase the threat to sustainable timber production. So, this study aims to improve the accuracy of volume estimations of standing tree in both natural forest-stands and plantations. We consider bole volume in relation to (i) tree species variability, (ii) forest type and (iii) climatic factors including annual rainfall, seasonality, and maximum temperature. We use Bayesian modelling to calibrate the volume equations of 24 commercial tree species according to climatic variables, ranging large part of the Sudano-Guinean zone of West Africa, from Sierra Leone to Ghana. Given that competition for water and light, is not as well controlled in natural forests as it is in plantations, we assessed the impact of stand types on bole volume according to a south-north climatic gradient. By modifying the duration of droughts and heat stress, climate change negatively impacts the bole volume of the commercial species. So, the major realization is that forest management programs that do not allow for the interspecific variability of tree species as well as the annual maximum temperature are unlikely to provide reliable prediction of timber wood stocks in West Africa.
Keywords : West Africa, Commercial tree species, Bole volume equation, Climate effects, Bayesian modelling.