Spatially Explicit, Quantitative Reconstruction of Past Vegetation Based on Pollen or Charcoal Data As a Tool for Autecology of Trees

Context The determination of autecological preferences based on long-term vegetation dynamics is hampered by the lack of realistic estimates for past occurrence and abundance patterns. Palaeoecological record has still rather character of points than spatially continuous maps. Objectives To infer long-term autecological preferences of trees from reconstructed vegetation. Compare reconstructions based on pollen and charcoals. Methods We employed to the regional training set of 58 sites the Extended Downscaling Approach (EDA) using nine topographic factors clustered in 8 habitat classes, data on pollen productivity estimates, fossil pollen, charcoal sequences from soil and archaeological contexts. Based on abundances and habitat preferences from the last 9 millennia, we calculated the autecological preferences of tree taxa, using multivariate statistics. Results The significant spatiotemporal patterns between soil-charcoal and pollen-based EDA validated the reconstruction, the use of both records in the EDA, and the EDA model. One of the topographic indices—vertical distance to channel network—evidenced the following: the closest taxon to the groundwater is Picea ; Abies , Betula , Pinus and Quercus have intermediate distances; Fagus grows far from the channel network and Corylus even further. Conclusions The EDA model linked past forest composition to realistic topography. Such a spatially explicit reconstruction produced by our new algorithm allows inferring the relationship between past plant communities and environmental variables. The long-term preferences of tree species to habitat characteristics match their current autecological demands. This might be a breakthrough in quantitative plant paleoecology.