Process-based modeling of grassland dynamics built on ecological indicator values for land use

Land use change next to climate change is considered an important factor for the vanishing biodiversity. Semi-natural grasslands belong to the most species-rich biotope types in Central Europe. Bridging the gap between science and application is therefore needed to deliver scientific knowledge of ecosystem-functioning and underlying key-processes to authorities allowing successful landscape management. However, current model approaches are mostly restricted to low resolution in means of space, species and complexity. The aim of this study was to develop a process-based succession model for temperate grasslands linked to a geographic information system integrating spatial explicit input data from the real landscape and visualizing output in raster maps, which is a prerequisite for application. To cope with the trade-off between the fine resolution and the data-hunger of a mechanistic landscape model, within the presented model approach the complexity was reduced to three parameters that determine species’ growth and thus competitive power: maximal growth rate, a factor for self-regulation, and Briemle's utilization numbers. Following the principles of phytosociology, we calibrated species’ growth based on the community data set for a specific location. Model calibration and model testing showed that Briemle's utilization numbers and the chosen representative species and groups are suitable to simulate grassland dynamics under different forms of land use. As we are using a general pattern of differential equations, we are confident that the model can be easily transferred to other grassland sites. Our model concept was created in close cooperation with stakeholders and has been already successfully used as a decision support system by the Eifel National Park administration.