Data from: Different roles of elevational and local environmental factors on abundance-based beta diversity of the soil Enchytraeidae on the Changbai Mountain

The elevational alpha biodiversity gradient in mountain regions is one of the well-known ecological patterns, but its beta diversity pattern remains poorly-known. Examining the beta diversity and its components could enhance the understanding of community assembly mechanism. We studied the beta diversity pattern of the soil enchytraeids along a distinct elevational gradient (705—2280 m) on the Changbai Mountain, the best-preserved mountain in northeastern China. The overall abundance-based community dissimilarity was relatively high (ca. 0.70), largely due to the balanced-variation component (85%). The overall dissimilarity and its balanced-variation (substitution) component were both related to local environmental heterogeneity and elevational distance, with the environmental relationships being stronger. In contrast, the abundance-gradient (subsets) component was not related to the two gradients. The same important spatial and environmental variables were detected in structuring overall dissimilarity and substitution component, different from that in subsets component. Variation partitioning analysis showed that environmental control played a more important role than spatial (vertical and horizontal) factors in structuring the patterns of overall beta diversity and its two components. The predictive power of multivariate analysis was higher for the substitution component (nearly 50%) and overall dissimilarity (35%), but much lower for subsets components (< 4%). These findings implied that abundance-based beta diversity patterns of the soil enchytraeids were the results of different ecological processes (e.g. environmental sorting and dispersal limitation), operating in the two antithetic components. Our study showed the substitution and loss of individuals reflecting different ecological processes and highlights the importance of partitioning beta diversity in assessing biodiversity patterns and their causes