The project focuses on the effects of past climatic and anthropogenic disturbances on four key tree species of Swiss mountain forests, i.e. Abies alba, Larix decidua, Picea abies and Pinus cembra. We will test palaeoecologically-inferred recolonization pathways in response to rapid and repeated temperature increases from the end of the last Ice Age to the Holocene warm period, by extracting and analysing aDNA from subfossil plant remains of the first populations that established around two lakes in the Swiss Alps. In order to find out if trees were able to adapt to climatic changes in the past, we will track adaptive and neutral genetic diversity through the Holocene by analyzing aDNA from time periods with marked demographic changes of the four focal species. We will also sample present-day tree populations, to link the aDNA genotypes with current genetic variation and identify cryptic lineages. The basis of this ambitious project will be the analysis of pollen, macrofossils and charcoal deposited in lake sediment archives to reconstruct local to regional vegetation and fire dynamics with high chronological precision and resolution. We will combine these palaeoecological analyses with a spatially explicit dynamic vegetation model (LandClim) to disentangle different forcing factors (i.e climate and anthropogenic land-use), test hypotheses regarding past demographic changes and simulate future vegetation dynamics under different climate and land-use scenarios.
Mountain forests are strongly affected by temperature and are expected to shift upslope with the current climate change, but little is known about the impact of such range shifts and altered selection pressures on the genetic diversity of tree populations. This new research project, funded by the SwissForestLab, will undertake large-scale ancient DNA analyses of subfossil tree remains to reveal for the first time the evolutionary responses of mountain tree populations to past climate change. The project focuses on the transition from the Younger Dryas to the Holocene (11’700 years ago), when temperatures markedly increased by 2–4°C within only a few decades, making it a close analogue to current and future climate warming. For the genetic analyses we will use tree remains such as needles and seeds that have been preserved in natural archives along an altitudinal gradient in the Southern Swiss Alps. The results will help to develop management strategies to maintain the adaptive potential and genetic diversity of mountain tree population under future climate change.
Temperate trees survived the last Ice Age in refugia south of the Alps, such as the Italian, Iberian and Balkan peninsulas. However, recent paleoecological findings as well as a topoclimatic study indicate that the Euganean Hills in the Po plain of Northern Italy could have constituted a microrefugium close to the alpine ice shield. This would have important implications for the calculation of expansion rates for temperate tree species in response to climate change. It might also mean that if topographically complex areas provide shelter for warm-adapted species during cold periods in the past, they could serve as an important refugium for cold-adapted species in a warmer future. We are using LandClim, a dynamic vegetation model, to simulate past forest dynamics during the Last Glacial Maximum by incorporating newly developed microclimatic grids and recent temperature reconstructions. We will also use the model to simulate future vegetation dynamics under different climate projections, therefore providing crucial information for ecosystem managers and policy makers to conserve threatened species and mitigate climate change impacts.
Future climate change will have a drastic impact on forests, affecting important ecosystem services such as timber production or carbon sequestration. Extensive droughts, which are expected to become more likely with climate change, have the potential to lead to a shift in species composition as well as enhance the risk of fire occurrences, even in the Northern Alps. Therefore, smart forest management is an indispensable tool to adjust forest composition and mitigate negative climatic change impacts. In this research project, which is part of a larger project by the Wyss Academy for Nature and the Canton of Bern, we will upscale the dynamic vegetation model LandClim, to a regional scale. The output of the model will result in detailed predictions on future forest composition and forest fire risk in the Canton of Bern based on different climate and land-use scenarios. The project will provide policy makers and ecosystem managers with important information and support them in the challenging task to mitigate climate change impacts on Bernese forests.