Geographical backgrounds and dispersal ability might have strong imprint on assemblage dissimilarity; however, these aspects have generally been overlooked in large-scale beta diversity studies. Here, we examined whether patterns and drivers of taxonomic beta diversity (TBD) and phylogenetic beta diversity (PBD) of breeding birds in China vary across 1) regions on both sides of the Hu Line, a line that demarcates China’s topographical, climatic, economic, and social patterns, and 2) species with different dispersal ability. TBD and PBD were calculated and partitioned into turnover and nestedness components using a moving window approach. Variables representing climate, habitat heterogeneity, and habitat quality were used to evaluate the effects of environmental filtering, whereas spatial distance was used to assess the influences of dispersal limitation. Variance partitioning analysis was used to assess the relative role of these variables. In general, TBD and PBD values were high in mountainous areas and environmental filtering largely determined TBD and PBD. However, different dominating environmental filters on both sides of the Hu Line led to divergent beta diversity patterns. Specifically, climate-driven species turnover and habitat heterogeneity-related species nestedness dominated the regions at east and west of the Hu Line, respectively. Additionally, bird species with stronger dispersal ability were more susceptible to environmental filtering resulting in more homogeneous assemblages. Our results indicated that regions with distinctive geographical backgrounds might present different ecological factors that lead to divergent assemblage dissimilarity patterns, and dispersal ability determines the response of assemblages to these ecological factors. Identifying a single universal explanation for the observed pattern without considering these aspects might lead to simplistic or incomplete conclusions. Therefore, it is essential to consider the combined effect of geographical background and dispersal ability for comprehensively understanding large-scale patterns of beta diversity and for planning conservation strategies.