Understanding how different microbial groups respond to broad environmental gradients is essential for revealing the processes that structure microbial diversity. In this study, we comparatively investigate the ecological drivers that shape β-diversity across different microbial domains/kingdoms (bacteria, archaea, fungi, and protists) in intertidal mudflats along a broad climatic gradient, spanning ~18,000 km along the Chinese coastline. Distinct latitudinal β-diversity patterns are observed for different microbial domains/kingdoms. Null model analyses reveal significant deviations in β-diversity from null expectations across all microbial domains, with bacterial and archaeal β-diversity primarily associated with the γ-diversity or regional species pools, whereas fungal and protist communities were more strongly shaped by local community assembly processes. Homogeneous selection is the predominant assembly process, with varied relative influence of environmental variables across different domains/kingdoms as revealed by db-RDA. These findings underscore the importance of domain-specific ecological processes in shaping microbial biogeography and highlight the need for comparative frameworks across microbial groups to understand biodiversity patterns along environmental gradients.IMPORTANCEUnderstanding the spatial distribution of biodiversity is a fundamental goal in ecology, yet most microbial studies focus on single domains. This study provides a comprehensive comparison of bacteria, archaea, fungi, and protists along an ~18,000 km latitudinal gradient in intertidal mudflats. We reveal that these microbial domains do not follow a unified diversity pattern but are instead governed by distinct ecological drivers. Bacteria and archaea are strongly influenced by regional species pools, whereas fungal and protist communities are primarily shaped by local stochastic processes such as dispersal limitation. These findings highlight the importance of organismal traits (e.g., body size) in shaping community assembly. This work emphasizes the necessity of establishing a multi-domain framework to accurately predict how Earth's complex microbiomes respond to environmental changes.
Gong et al. (Thu,) studied this question.