The biogeochemical variability of Arctic thermokarst ponds is reflected by stochastic and niche‐driven microbial community assembly processes

• Published in: Environmental Microbiology
• Main Authors: Le Moigne, Alizée, Bartosiewicz, Maciej, Schaepman‐Strub, Gabriela, Abiven, Samuel, Pernthaler, Jakob
• Other Authors: Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung, Universität Zürich
• Format: Article in Journal/Newspaper
• Language: English
• Published: Wiley 2020
• Subjects: Thermokarst; Tundra; Siberia
• Online Access: http://dx.doi.org/10.1111/1462-2920.15260; https://onlinelibrary.wiley.com/doi/pdf/10.1111/1462-2920.15260; https://onlinelibrary.wiley.com/doi/full-xml/10.1111/1462-2920.15260

Summary Shallow thermokarst ponds are a conspicuous landscape element of the Arctic Siberian tundra with high biogeochemical variability. Little is known about how microbes from the regional species pool assemble into local pond communities and how the resulting patterns affect functional properties such as dissolved organic carbon (DOC) remineralization and greenhouse gas (GHG) turnover. We analysed the pelagic microbiomes of 20 ponds in north‐eastern Siberia in the context of their physico‐chemical properties. Ponds were categorized as polygonal or trough according to their geomorphological origin. The diversity of bacteria and eukaryotic microbes was assessed by ribosomal gene tag sequencing. Null model analysis revealed an important role of stochastic assembly processes within ponds of identical origin, in particular for genotypes only occurring in few systems. Nevertheless, the two pond types clearly represented distinct niches for both the bacterial and eukaryotic microbial communities. Carbon dioxide concentration, indicative of heterotrophic microbial processes, varied greatly, especially in the trough ponds. Methane concentrations were lower in polygonal ponds and were correlated with the estimated abundance of methanotrophs. Thus, the overall functional variability of Arctic ponds reflects the stochastic assembly of their microbial communities. Distinct functional subcommunities can, nevertheless, be related to GHG concentrations.