Disproportionate CH4 Sink Strength from an Endemic, Sub-Alpine Australian Soil Microbial Community.

Soil-to-atmosphere methane (CH4) fluxes are dependent on opposing microbial processes of production and consumption. Here we use a soil-vegetation gradient in an Australian sub-alpine ecosystem to examine links between composition of soil microbial communities, and the fluxes of greenhouse gases they regulate. For each soil/vegetation type (forest, grassland, and bog), we measured carbon dioxide (CO2) and CH4 fluxes and their production/consumption at 5 cm intervals to a depth of 30 cm. All soils were sources of CO2, ranging from 49 to 93 mg CO2 m-2 h-1. Forest soils were strong net sinks for CH4, at rates of up to -413 µg CH4 m-2 h-1. Grassland soils varied, with some soils acting as sources and some as sinks, but overall averaged -97 µg CH4 m-2 h-1. Bog soils were net sources of CH4 (+340 µg CH4 m-2 h-1). Methanotrophs were dominated by USCα in forest and grassland soils, and Candidatus Methylomirabilis in the bog soils. Methylocystis were also detected at relatively low abundance in all soils. Our study suggests that there is a disproportionately large contribution of these ecosystems to the global soil CH4 sink, which highlights our dependence on soil ecosystem services in remote locations driven by unique populations of soil microbes. It is paramount to explore and understand these remote, hard-to-reach ecosystems to better understand biogeochemical cycles that underpin global sustainability.

Microbes as Engines of Ecosystem Function: When Does Community Structure Enhance Predictions of Ecosystem Processes?

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.