Grasslands account for approximate 30% of the world’s land area and provide a wide range of ecosystem functions, for which species diversity and functional composition are essential. In order to understand how different plant traits and plant interactions (e.g. competition for light) influence species composition and grassland dynamics, we use an individual-based process-oriented grassland model. Based on four plant function types, we parameterized grassland along a gradient of functional plant diversity taking measurements from a local biodiversity experiment in Central Europe. The model enabled us to analyze temporal dynamics in grassland attributes like aboveground biomass, vegetation height and plant density. We further applied a global sensitivity analysis to identify the relative importance of plant traits for vegetation dynamics.
Results/Conclusions
Our model reproduces well the measured vegetation dynamics and the positive effect of functional richness on the productivity of grassland. For example, in plots consisting of one plant functional type the simulated mean biomass deviates from the measured biomass by a maximum of 6%. In addition, the simulation results have several similarities to independent field studies in terms of plant density, plant size and life spans of plant functional types. We identified plant traits with high influence on grassland attributes, including specific leaf area and mortality of seedlings. These could be key points for the development of a regionally transferable model parameterization of temperate grasslands with changing environmental conditions and management regimes.