Climate warming and summer droughts alter soil microbial activity, affecting greenhouse gas (GHG) emissions in Arctic and alpine regions. However, the long-term effects of warming, and implications for future microbial resilience, are poorly understood. Using one alpine and three Arctic soils subjected to in situ long-term experimental warming, we simulated drought in laboratory incubations to test how microbial functional-gene abundance affects fluxes in three GHGs: carbon dioxide, methane, and nitrous oxide. We found that responses of functional gene abundances to drought and warming are strongly associated with vegetation type and soil carbon. Our sites ranged from a wet, forb dominated, soil carbon-rich systems to a drier, soil carbon-poor alpine site. Resilience of functional gene abundances, and in turn methane and carbon dioxide fluxes, was lower in the wetter, carbon-rich systems. However, we did not detect an effect of drought or warming on nitrous oxide fluxes. All gene–GHG relationships were modified by vegetation type, with stronger effects being observed in wetter, forb-rich soils. These results suggest that impacts of warming and drought on GHG emissions are linked to a complex set of microbial gene abundances and may be habitat-specific.

Rock coatings in Kärkevagge, Swedish Lapland, are widespread and mineralogically diverse. A preliminary study of the rock coatings revealed higher than expected bacterial diversity for an endolithic environment in the arctic. Using 454 Roche pyrosequencing of the 16S rRNA gene, nine rock coating samples from three different coating mineralogies were sequenced. The three coating types include Fe films of goethite and hematite, sulfate crusts of jarosite and gypsum, and aluminum glazes of basaluminite and alunite. Over 20 000 quality sequences were analyzed, and over 2800 operational taxonomic units were identified. Diversity indices and richness estimates confirmed high levels of diversity, particularly in the sulfate crusts with diversity indices at the level of complex soils. Inferred physiology shows the presence of both heterotrophs and autotrophs, with genera of autotrophic Fe and S metabolisms present in at least 2% of the total for each coating type. The most common phyla included Proteobacteria, Acidobacteria, and Actinobacteria – all common soil taxa. Coatings also showed distinct community structure between coating mineralogies. Given the diversity in coating types found in areas receiving the same chemical and environmental inputs, the distinct microbial communities suggest a biological role in coating development.

The microbial ecology of arctic and sub-arctic soils is an important aspect of the global carbon cycle, due to the sensitivity of the large soil carbon stocks to ongoing climate warming. These regions are characterized by strong climatic seasonality, but the emphasis of most studies on the short vegetation growing season could potentially limit our ability to predict year-round ecosystem functions. We compiled a database of studies from arctic, subarctic, and boreal environments that include sampling of microbial community and functions outside the growing season. We found that for studies comparing across seasons, in most environments, microbial biomass and community composition vary intra-annually, with the spring thaw period often identified by researchers as the most dynamic time of year. This seasonality of microbial communities will have consequences for predictions of ecosystem function under climate change if it results in: seasonality in process kinetics of microbe-mediated functions; intra-annual variation in the importance of different (a)biotic drivers; and/or potential temporal asynchrony between climate change-related perturbations and their corresponding effects. Future research should focus on (i) sampling throughout the entire year; (ii) linking these multi-season measures of microbial community composition with corresponding functional or physiological measurements to elucidate the temporal dynamics of the links between them; and (iii) identifying dominant biotic and abiotic drivers of intra-annual variation in different ecological contexts.