bioRxivMicrobiologyPreprint
Eukaryotic rather than prokaryotic microbiomes change over seasons in rewetted fen peatlands
H. Wang, M. Weil, K. Dumack, D. Zak, D. Muench, A. Guenther, G. Jurasinski, G. Blume-Werry, J. Kreyling, T. Urich
Abstract
In the last decades, rewetting of drained peatlands is on the rise worldwide, to restore the significant carbon sink function. Rewetted peatlands differ substantially from their pristine counterparts and can, thus, be considered as novel ecosystems. Despite the increasing understanding of peat microbiomes, little is known about the seasonal dynamics and network interactions of the microbial communities in these novel ecosystems, especially in rewetted groundwater-fed peatlands, i.e. fens. Here, we investigated the seasonal dynamics in both prokaryotic and eukaryotic microbiomes in three common types of fens in Northern Germany, namely percolation fen, alder forest and coastal fen. The eukaryotic microbiomes, including fungi, protists and metazoa, showed significant changes of their community structures across the seasons in contrast to largely unaffected prokaryotic microbiomes. The co-occurrence network in the summer showed a distinct topology compared to networks in the other seasons, which was driven by the increased connections among protists, as well as between protists and the other microbial groups. Our results also indicated that the dynamics in eukaryotic microbiomes differed between fen types, specifically in terms of saprotrophs, arbuscular mycorrhiza and grazers of bacteria. Our study provides the insight that microbial eukaryotes mainly define the seasonal dynamics of microbiomes in rewetted fen peatlands. Accordingly, future research should unravel the importance of eukaryotes for biogeochemical processes, especially the under-characterized protists and metazoa, in these novel yet poorly understood ecosystems.
- assay: metagenomics
- research focus: ecology & biodiversity
- research focus: cell type annotation
- research focus: spatial domain detection
- approach: statistical model
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