Questions: Niche differentiation is widely accepted as a key mechanism important for species coexistence. Seed germination and seedling survival were recognized as important contributors to niche segregation and could be a crucial filter for determining species' distributions and community composition. Only a little is known about the direct relationship between hydrology recruitment niche, hydrology regimes, and community composition. Therefore, the main aim of this study is to identify the changes in the composition of a pond community with respect to the hydrological regime and predict them by the recruitment niche of species. Location: The Gloggere pond in the Altdorfer forest (47.848 N, 9.698 E, Ravensburg vicinity, Upper Swabia, Baden-Wuerttemberg, Germany). Methods: A transect with 46 permanent plots was established throughout the Gloggere pond, and species percentage cover was recorded in September 1992-1995, 2006, and 2017. Pond drawdown was implemented in 1993. Sediment samples were collected in March 1995 across the transect, and a pot germination experiment with six hydrological treatments was performed. The hydrology recruitment niche from the seed bank germination experiment was compared with the field hydrology niche to show the importance of the hydrology regime for community composition. Results: The hydrological regime determined the community composition in both the germination experiment and the field. Species-specific hydrology niche from the field correlated with species-specific recruitment niche measured in the germination experiment. Conclusions: Our results support the importance of recruitment niche as a driver of community composition for pond areas. For understanding and predicting changes in plant community composition, it is necessary to combine knowledge about the recruitment niche and the ability of seeds' survival in the sediment along a hydrological gradient with knowledge about abiotic filters, biotic interactions, and species-specific traits. Recognizing the recruitment niche is useful for better predicting the effect of future environmental changes, especially in the context of climate change and conservation management.