Co-occurrences enhance our understanding of aquatic fungal metacommunity assembly and reveal potential host–parasite interactions. Issue 11 (6th October 2022)

• Record Type: Journal Article
• Authors: Vass, Máté; Eriksson, Karolina; Carlsson-Graner, Ulla; Wikner, Johan; Andersson, Agneta
• Is Part Of: FEMS microbiology ecology. Volume 98:Issue 11(2022)
• Publication Date: 2022-10-06
• Subjects: coastal marine habitats -- ecological network -- long-read metabarcoding -- metacommunity structure -- mycoplankton; Microbial ecology -- Periodicals; Microbiology -- Periodicals; 579.17
• DOI: 10.1093/femsec/fiac120
• Languages: English
• ISSNs: 0168-6496

Abstract

ABSTRACT: Our knowledge of aquatic fungal communities, their assembly, distributions and ecological roles in marine ecosystems is scarce. Hence, we aimed to investigate fungal metacommunities of coastal habitats in a subarctic zone (northern Baltic Sea, Sweden). Using a novel joint species distribution model and network approach, we quantified the importance of biotic associations contributing to the assembly of mycoplankton, further, detected potential biotic interactions between fungi–algae pairs, respectively. Our long-read metabarcoding approach identified 493 fungal taxa, of which a dominant fraction (44.4%) was assigned as early-diverging fungi (i.e. Cryptomycota and Chytridiomycota). Alpha diversity of mycoplankton declined and community compositions changed along inlet–bay–offshore transects. The distributions of most fungi were rather influenced by environmental factors than by spatial drivers, and the influence of biotic associations was pronounced when environmental filtering was weak. We found great number of co-occurrences (120) among the dominant fungal groups, and the 25 associations between fungal and algal OTUs suggested potential host–parasite and/or saprotroph links, supporting a Cryptomycota-based mycoloop pathway. We emphasize that the contribution of biotic associations to mycoplankton assembly are important to consider in future studies as it helps to improve predictions of species distributions in aquatic ecosystems.