The course will provide a possibility for the students to immerse into the topics of ongoing research focused on understanding historical development, current state and future projections for hemi-boreal and boreal environments of the Northern Hemisphere. The course will give a theoretical overview of the modern paleo- and dendrochronological methods to reconstruct dynamics of boreal and temperate vegetation and related data modelling approaches. After the course completion, students will acquire knowledge to understand and critically analyze results obtained by different methods and evaluate applicability of these methods in their own research programs.

Background and rationale. Vegetation of the Northern Europe features a fascinating post-glacial history, shaped by complex and spatially and temporally non-homogeneous environmental controls. Apart from climate variability at multiple scales, humans have become an increasingly important factor in changing the Nordic vegetation over the last centuries. Along with direct impact of climate upon vegetation cover, variability in disturbance regimes had a critical role in contributing to this dynamics. Disturbances cause perturbations in the energy and nutrient flows in ecosystems have been the principal drivers of vegetation dynamics, species and biome distribution. The ongoing climate change impacts properties of disturbance regimes. Linking ecosystem dynamics with their disturbance histories, and more generally - past and modern environmental variability, is done through various reconstruction and modelling techniques. This research helps model and ultimately predict ecosystem responses to external triggers.

Data originating from sediment- and tree-ring based reconstructions have been increasingly used to develop models of past climate-vegetation-disturbance interactions. The recent years have been witnessing a growing interest in large-scale data aggregation efforts, a wider use of mechanistic modelling of these data, and the dominance of multi-proxy approaches, i.e. those based on simultaneous analyses of datasets representing different natural phenomena. In particular, global and continental scale changes in vegetation cover as a result of climate change has become possible to verify using reconstructed histories of vegetation dynamics and associated disturbance regimes.