1 Abstract
Many studies have predicted large changes in forest dynamics during the next century because of global warming. Although empirical approaches and studies based on species distribution models provide valuable information about future changes, they do not take into account biotic interactions and stand-level demographic variations. The objective of this study was to quantify the local and regional variability of the growth and regeneration of three important forest species growing often in mixed stands in Europe (Picea abies (L.) Karst., Abies alba Mill., Fagus sylvatica), and to assess the climatic drivers of this variability. For that purpose, we collected a large forestry data set compiling the long-term (up to 100 years) evolution of species and size distributions for 163 stands across Europe, in the mesic distribution area of these forests. We used an inverse modeling approach, Approximate Bayesian Computation, to calibrate an individual-based model of forest dynamics on these data. Our study revealed that the variability of the demographic processes was of the same order of magnitude between stands of a same forest as between different forests. Out of the three species and two demographic processes studied, only the fir growth strongly varied with temperature. Water availability did not explain any demographic variation over stands. For these forests experiencing mesic conditions, local unmeasured factors seem therefore to have an influence at least as important as macro-environmental factors on demographic variations. Efforts to include these important factors in projection scenarios should therefore be prioritized. Besides, our study demonstrates that inverse modelling methods make possible the analysis of long-term forestry data. Such data should therefore be more widely compiled and used for ecological and global change research.