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Forest ecosystems play an integral role in the earth system (e.g., by regulating biogeochemical cycles) and provide a wide range of services to human societies. It is therefore of crucial importance to understand the effects of a changing climate and changing disturbance regimes on forest dynamics. To date, most studies of forest dynamics have focused on trees, thus neglecting the herbaceous understorey (e.g., grass, ferns, herbs) although an increasing number of empirical studies suggest that the interaction between herbs and trees can profoundly alter forest dynamics. In particular, competition for light and water by the herbaceous understorey has been shown to change the structure and composition of tree regeneration, and thus to delay and potentially even arrest forest succession. When ignoring this interaction, thresholds in ecosystem responses to changing climate and disturbance regimes may remain undetected. However, due to the restrictions of empirical studies little is known on the implications of overstorey-understorey interactions for forest dynamics at larger spatio-temporal scales. Dynamic vegetation models (DVMs) have been developed to overcome this restriction and explore vegetation dynamics at large temporal scales (>100 years). Among the various types of DVMs, forest landscape models (FLMs) are specifically designed to investigate vegetation interactions under changing climate and disturbance regimes at large spatial scales. I used the process-based FLM LandClim to investigate the long-term effect of overstorey-understorey interactions on forest dynamics in central European landscapes, specifically focusing on (1) competition for light in mesic forest landscapes, (2) competition for water under present and future climate conditions in a drought-prone landscape, and (3) the potential of disturbances (browsing, windthrow, timber harvest) to promote delayed and arrested succession. In Chapter I, I implemented an understorey component in the FLM LandClim, with a focus on competition for light as the main mode of interaction. Simulation results for two mesic landscapes in Central Europe (Feldberg in the Black Forest and Dischma valley in the central Alps) showed spatio-temporal patterns that were in line with trends reported in empirical studies from chronosequences and species elevation distributions. The presence of an herbaceous understorey had a strong impact on tree regeneration and forest growth during early succession, but a much smaller effect on the late-successional stage. Also, the strength of overstorey-understorey interactions varied considerably across the landscape, causing large delays in forest growth at low and mid-elevations. Furthermore, the understorey was found to act as a differential filter for tree establishment, inducing a shift towards more shade-tolerant species, which translated into altered overstorey composition for up to 200 years. I was thus able to upscale the effects of understorey competition that are evident from empirical studies at the plot level (i.e., a few square metres) and at the short time scale (

A method was developed for extending a fine-scaled forest gap model to a watershed-scaled landscape, using the Eastern Cross Timbers ecoregion as a case study for the method. A topographic wetness index calculated from digital elevation data was used as a measure of hydrologic across the modeled landscape, and the gap model modified to have with a topographically-based hydrologic input parameter. The model was parameterized by terrain type units that were defined using combinations of USDA soil series and classes of the topographic wetness index. A number of issues regarding the sources, grid resolutions, and processing methods of the digital elevation data are addressed in this application of the topographic wetness index. Three different grid sizes, 5, 10, and 29 meter, from both LiDAR-derived and contour-derived elevation grids were used, and the grids were processed using both single-directional flow algorithm and bi-directional flow algorithm. The result of these different grids were compared and analyzed in context of their application in defining terrain types for the forest gap model. Refinements were made in the timescale of gap model’s weather model, converting it into a daily weather generator, in order to incorporate the effects of the new topographic/hydrologic input parameter. The precipitation model was converted to use a Markov model to initiate a sequence of wet and dry days for each month, and then daily precipitation amounts were determined using a gamma distribution. The output of the new precipitation model was analyzed and compared with a 100-year history of daily weather records at daily, monthly, and annual timescales. Model assumptions and requirements for biological parameters were thoroughly investigated and questioned. Often these biological parameters are based on little more than assumptions and intuition. An effort to base as many of the model’s biological parameters on measured data was made, including a new technique for estimating optimal volumetric growth rate by measuring tree rings. The gap model was set up to simulate various terrain types within the landscape.