Browsing by Subject "vegetation modelling"

Climate change has been predicted to cause extinctions and range shifts in European flora. Two common methodologies assessing climate impact on vegetation are statistical bioclimatic envelope models (BEMs) and process-based dynamic vegetation models. BEMs are relatively easy to implement, but have been criticized for being unreliable, because they assume equilibrium between species' observed ranges and climate. Dynamic models can be considered biologically more sound, but require large quantities of detailed input data, which is often not available. The aim of this study is to investigate the effects of climate change on common tree species ranges in Europe and in Scandinavia, and to find out whether two commonly used modeling strategies, dynamic and statistical models, produce similar estimates of future ranges. To address these questions, I first built statistical models (bioclimatic envelope models) for five common European trees: Pedunculate Oak (Quercus robur, L.), Common Hazel (Corylus avellana L.), European Beech (Fagus sylvatica, L.), Scots Pine (Pinus sylvestris, L.) and Norway Spruce (Picea abies (L.) H. Karst.). All species are widely distributed and characteristic species in their ecosystems and thus their possible range shifts would indicate larger shifts in ecosystem structure and function. I then compare the projections produced with the statistical models to outputs of a tree speciesparameterized dynamic global vegetation model LPJ-GUESS, obtained from another study. The statistical model predictions are compared with dynamic model results for entire European distributions, while the statistical model predictions for Scandinavian area are examined in further detail. Input distribution data had great influence in future predictions of statistical models. Statistical models and the dynamic model produced very different future predictions, statistical models predicting increasing contractions on the southern edge of distribution towards the end of the century, indicating larger climatic impacts. The role of biological interactions, successional processes and modeling relationship between distribution and climate are discussed. I propose a way to assess the possible causes of differences between statistical and dynamic models to produce more robust future predictions on plant species distributions. Statistical model predictions in the Scandinavian area indicated substantial northward shift of hemiboreal vegetation zone by 2050.