Microorganisms are vital in mediating the earth’s biogeochemical cycles; yet, despite our rapidly increasing ability to explore complex environmental microbial communities, the relationship between microbial community structure and ecosystem processes remains poorly understood. Here, we address a fundamental and unanswered question in microbial ecology: ‘When do we need to understand microbial community structure to accurately predict function?’ We present a statistical analysis investigating the value of environmental data and microbial community structure independently and in combination for explaining rates of carbon and nitrogen cycling processes within 82 global datasets. Environmental variables were the strongest predictors of process rates but left 44% of variation unexplained on average, suggesting the potential for microbial data to increase model accuracy. Although only 29% of our datasets were significantly improved by adding information on microbial community structure, we observed improvement in models of processes mediated by narrow phylogenetic guilds via functional gene data, and conversely, improvement in models of facultative microbial processes via community diversity metrics. Our results also suggest that microbial diversity can strengthen predictions of respiration rates beyond microbial biomass parameters, as 53% of models were improved by incorporating both sets of predictors compared to 35% by microbial biomass alone. Our analysis represents the first comprehensive analysis of research examining links between microbial community structure and ecosystem function. Taken together, our results indicate that a greater understanding of microbial communities informed by ecological principles may enhance our ability to predict ecosystem process rates relative to assessments based on environmental variables and microbial physiology.

In lake ecosystems a major proportion of methane (CH(4) ) emissions originate from the littoral zone, which can have a great spatial variability in hydrology, soil quality and vegetation. Hitherto, spatial heterogeneity and the effects it has on functioning and diversity of methanotrophs in littoral wetlands have been poorly understood. A diagnostic microarray based on the particulate methane monooxygenase gene coupled with geostatistics was used to analyse spatial patterns of methanotrophs in the littoral wetland of a eutrophic boreal lake (Lake Kevätön, Eastern Finland). The wetland had a hydrology gradient with a mean water table varying from -8 to -25 cm. The wettest area, comprising the highest CH(4) oxidation, had the highest abundance and species richness of methanotrophs. A high water table favoured the occurrence of type Ib methanotrophs, whereas types Ia and II were found under all moisture conditions. Thus the spatial heterogeneity in functioning and diversity of methanotrophs in littoral wetlands is highly dependent on the water table, which in turn varies spatially in relation to the geomorphology of the wetland. We suggest that changes in water levels resulting from regulation of lakes and/or global change will affect the abundance, activity and diversity of methanotrophs, and consequently CH(4) emissions from such systems.

In contrast to the well-recognized permafrost carbon (C) feedback to climate change, the fate of permafrost nitrogen (N) after thaw is poorly understood. According to mounting evidence, part of the N liberated from permafrost may be released to the atmosphere as the strong greenhouse gas (GHG) nitrous oxide (N2O). Here, we report post-thaw N2O release from late Pleistocene permafrost deposits called Yedoma, which store a substantial part of permafrost C and N and are highly vulnerable to thaw. While freshly thawed, unvegetated Yedoma in disturbed areas emit little N2O, emissions increase within few years after stabilization, drying and revegetation with grasses to high rates (548 (133–6286) μg N m−2 day−1; median with (range)), exceeding by 1–2 orders of magnitude the typical rates from permafrost-affected soils. Using targeted metagenomics of key N cycling genes, we link the increase in in situ N2O emissions with structural changes of the microbial community responsible for N cycling. Our results highlight the importance of extra N availability from thawing Yedoma permafrost, causing a positive climate feedback from the Arctic in the form of N2O emissions.