Scale-Dependent Drivers of Plant Community Turnover in a Disturbed Grassland: Insights from Generalized Dissimilarity Modeling

Identifying the key drivers of plant community turnover under disturbance is essential for understanding ecological processes and informing conservation efforts. We investigated the Kangxi Grassland in the Yeyahu Wetland Nature Reserve, Beijing, using Generalized Dissimilarity Modeling (GDM) across two spatial scales and three areas, integrating soil properties, remote sensing data, and geographic distance. The models explained 25–49% of the deviance with low cross-validation error, showing a clear nonlinear turnover pattern. Pronounced species replacement occurred at short ecological distances, followed by slower change at greater distances. Although the overall patterns were similar, driver importance varied among areas: available nitrogen (AN) dominated in the Southeast Area, while soil water content (SWC) was the primary driver in the Northwest Area and across the entire Study Area; in all cases, geographic distance consistently ranked second. Texture indices, although weaker than geographic distance, still outperformed most vegetation indices and spectral bands. These results indicate that soil properties, geographic distance, and texture indices jointly shape spatial patterns of species turnover, with their relative importance varying by scale or area. Disturbances, such as drought, grazing, tourism, and fluctuations in inundated areas caused by variations in water levels in a nearby reservoir, influenced species turnover by directly or indirectly altering key drivers. In combination with a comparative analysis of species importance values (IVs) and ecological types, this study further demonstrates that the factors driving species turnover are influenced not only by scale but also by the complex and diverse ecological processes operating at their respective scales. It also shows the applicability of GDM in analyzing fine-scale turnover patterns and the factors driving them in disturbed grasslands.