Grassland restoration seen through the lens of four high-level processes in community ecology

Restoration requires predictability to become a reliable technique for environmental management, driven by local, landscape, and historical factors. Challenging are the multiple factors that determine project success, for example during and after grassland restoration. There is considerable unexplained variation in restoration outcomes that could benefit from integrating principles of community ecology. Therefore, we suggest a conceptual framework which connects high-level processes of grassland communities, i.e., ‘speciation’, ‘dispersal’, ‘selection’, and ‘drift’, with restoration ecology, and identifies challenges and opportunities for restoration to modify these processes. First, the framework distinguishes fixed and controlled drivers of grassland restoration and adds factors influencing post-restoration development. Second, it connects these drivers with the four high-level processes. Third, it explains selection not only by the abiotic and biotic filters but also by including the establishment filter. Local restoration projects must cope with a given regional species pool, the landscape structure, fixed site conditions, community legacy, and year effects. However, the projects can select species to be transferred, improve seed transfer techniques and seed abundance, adapt site–seed specific seed mixtures, use priority effects, and create safe sites. Post-restoration development is influenced by new immigrants in the species pool, varying propagule pressure, plant–soil feedback, long-term management, and fluctuations of site factors. These factors are partly controlled and partly not, e.g., management or weather fluctuations, respectively. The framework connects ecological theory, restoration practice, and post-restoration management with the above high-level processes, which allows a systematic overview of fixed, controlled, and post-restoration factors. It helps also identifying relevant monitoring parameters that affect restoration success. Furthermore, the framework facilitates the design of experiments that help improve ecological factors that drive restoration outcomes.