The skin fungal communities of animals play a crucial role in maintaining host health and defending against pathogens. Because fungal infections can affect the skin microbiota of bats, gaining a comprehensive understanding of the characteristics of healthy bat skin fungal communities and the ecological processes driving them provides valuable insights into the interactions between pathogens and fungi.
We used Kruskal–Wallis tests and Permutational Multivariate Analysis of Variance (PERMANOVA) to clarify differences in skin fungal community structure among bat species. A Generalized Linear Model (GLM) based on a quasi-Poisson distribution and partial distance-based redundancy analysis (db-RDA) was performed to assess the influence of variables on skin fungal communities. Using community construction models to explore the ecological processes driving fungal community changes,
We found significant differences in the composition and diversity of skin fungal communities among bat species influenced by temperature, sampling site, and body mass index. Trophic modes and skin fungal community complexity also varied among bat species. Null model and neutral model analysis demonstrated that deterministic processes dominated the assembly of skin fungal communities, with homogeneous selection as the predominant process. Skin fungal communities on bat species were impacted by the environmental fungal reservoir, and actively selected certain amplicon sequence variants (ASVs) from the environmental reservoir to adhere to the skin.
In this study, we revealed the structure and the ecological process driving the skin fungal community across bat species in northern China. Overall, these results broaden our knowledge of skin fungal communities among bat species, which may be beneficial to potential strategies for the protection of bats in China.