A central issue in climate change research is to identify what species will be most affected by variations in temperature, precipitation or CO2 and via which underlying mechanisms. Dynamic global vegetation models (DGVMs) have been used to address questions of habitat shifts, extinctions and changes in carbon and nutrient cycling. However, DGVMs have been criticized for assuming full migration and using the most generic of plant functional types (PFTs) to describe vegetation cover. My doctoral research addresses both of these concerns. In the first study, I added two new tropical PFTs to an existing regional model (LPJ-GUESS) to improve vegetation representation in Central America. Although there was an improvement in the representation of some biomes such as the pine-oak forests, LPJ-GUESS was still unable to capture the distribution of arid ecosystems. The model representations of fire, soil, and processes unique to desert vegetation are discussed as possible explanations. The remaining three chapters deal with the assumption of full migration, where plants can arrive at any location regardless of distance or physical barriers. Using LPJ-GUESS, I imposed migration limitations by using fat-tailed seed dispersal kernels. I used three temperate tree species with different life history strategies to test the new dispersal functionality. Simulated migration rates for Acer rubrum (141 m year-1) and Pinus rigida (76 m year-1) correspond well to pollen and genetic reconstructed rates. However, migration rates for Tsuga canadensis (85 m year-1) were considerably slower than historical rates. A sensitivity analysis showed that maturation age is the most important parameter for determining rates of spread, but it is the dispersal kernel which determines if there is any long distance dispersal or not. The final study demonstrates how northerly refugia populations could have impacted landscape recolonization following the retreat of the last glacier. Using three species with known refugia (Acer rubrum, Fagus grandifolia, Picea glauca), colonization rates were faster with a northerly refugia population present. The number of refugia locations also had a positive effect on landscape recolonization rates, which was most pronounced when populations were separated. The results from this thesis illustrate the improvements made in vegetation-climate models, giving us increasing confidence in the quality of future climate change predictions.

A central issue in climate change research is to identify what species will be most affected by variations in temperature, precipitation or CO2 and via which underlying mechanisms. Dynamic global vegetation models (DGVMs) have been used to address questions of habitat shifts, extinctions and changes in carbon and nutrient cycling. However, DGVMs have been criticized for assuming full migration and using the most generic of plant functional types (PFTs) to describe vegetation cover. My doctoral research addresses both of these concerns. In the first study, I added two new tropical PFTs to an existing regional model (LPJ-GUESS) to improve vegetation representation in Central America. Although there was an improvement in the representation of some biomes such as the pine-oak forests, LPJ-GUESS was still unable to capture the distribution of arid ecosystems. The model representations of fire, soil, and processes unique to desert vegetation are discussed as possible explanations. The remaining three chapters deal with the assumption of full migration, where plants can arrive at any location regardless of distance or physical barriers. Using LPJ-GUESS, I imposed migration limitations by using fat-tailed seed dispersal kernels. I used three temperate tree species with different life history strategies to test the new dispersal functionality. Simulated migration rates for Acer rubrum (141 m year-1) and Pinus rigida (76 m year-1) correspond well to pollen and genetic reconstructed rates. However, migration rates for Tsuga canadensis (85 m year-1) were considerably slower than historical rates. A sensitivity analysis showed that maturation age is the most important parameter for determining rates of spread, but it is the dispersal kernel which determines if there is any long distance dispersal or not. The final study demonstrates how northerly refugia populations could have impacted landscape recolonization following the retreat of the last glacier. Using three species with known refugia (Acer rubrum, Fagus grandifolia, Picea glauca), colonization rates were faster with a northerly refugia population present. The number of refugia locations also had a positive effect on landscape recolonization rates, which was most pronounced when populations were separated. The results from this thesis illustrate the improvements made in vegetation-climate models, giving us increasing confidence in the quality of future climate change predictions.