Microbial abundance and community structure in a melting alpine snowpack
Snowmelt is a crucial period for alpine soil ecosystems, as it is related to inputs of nutrients, particulate matter and microorganisms to the underlying soil. Although snow-inhabiting microbial communities represent an important inoculum for soils, they have thus far received little attention. The distribution and structure of these microorganisms in the snowpack may be linked to the physical properties of the snowpack at snowmelt. Snow samples were taken from snow profiles at four sites (1930–2519 m a.s.l.) in the catchment of the Tiefengletscher, Canton Uri, Switzerland. Microbial (Archaea, Bacteria and Fungi) communities were investigated through T-RFLP profiling of the 16S and 18S rRNA genes, respectively. In parallel, we assessed physical and chemical parameters relevant to the understanding of melting processes. Along the snow profiles, density increased with depth due to compaction, while other physico-chemical parameters, such as temperature and concentrations of DOC and soluble ions, remained in the same range (e.g. <2 mg DOC L−1, 5–30 μg NH4 +-N L−1) in all samples at all sites. Along the snow profiles, no major change was observed either in cell abundance or in bacterial and fungal diversity. No Archaea could be detected in the snow. Microbial communities, however, differed significantly between sites. Our results show that meltwater rearranges soluble ions and microbial communities in the snowpack.
KeywordsSnow bacteria Snow fungi T-RFLP 16S rRNA gene Snow physics
We acknowledge Martin Schroth, Alessandro Franchini and Marco Meola for exchange of ideas and for help in the field. We thank Tobias Jonas at WSL Davos for providing meteorological data. We are extremely grateful to Frederik Hammes at EAWAG (Dübendorf, Switzerland) for support on flow cytometry. T-RFLP profiling was performed at the Genetic diversity centre (GDC) of ETH Zurich. TC analysis of the glass fibre filters was provided by Bachema AG (Schlieren, Switzerland). This project was internally funded by ETH Zurich.
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