Habitat island biogeography of mountaintop plant and soil microbiomes: Similar patterns driven by different mechanisms

Landscape succession, driven by natural factors and human activities, leads to dynamic changes in habitat structure and quality. While the effects of these changes on biodiversity are widely recognized, the specific responses of plants and microorganisms to habitat changes during landscape succession remain unclear. This study focuses on fragmented mountaintop ecosystems formed during landscape succession, exploring how habitat loss influences plant and soil microorganism diversity, particularly through species-area relationship (SAR) patterns. We investigated the SAR patterns across mountaintops of varying sizes by assessing γ-diversity (total diversity at the mountaintop level), α-diversity (diversity within individual habitats), and β-diversity (community dissimilarity among habitats) for both plants and microorganisms. To uncover the drivers of observed diversity patterns, we analyzed the direct and indirect impacts of biotic (plant and microorganisms), spatial, and environmental factors on the SAR pattern. Our results showed that γ-diversity for all groups increased with mountaintop areas. For plants and bacteria, this was primarily driven by a larger species pool, indicative of a sampling effect. For fungi, the increase in γ-diversity was associated with greater habitat heterogeneity, resulting in higher β-diversity. For protists, the primary driver was higher α-diversity within samples, suggesting improved habitat quality. Notably, there was no significant correlation between above-ground plant diversity and the diversity of below-ground microorganisms, while strong correlations existed among the diversity of bacteria, fungi, and protists, particularly between bacteria and protists. This study highlights the complex interplay between habitat quality, heterogeneity, and biotic interactions, offering a comprehensive perspective on biodiversity dynamics in response to landscape succession, which is crucial for predicting biodiversity loss and informing conservation strategies during landscape succession.