Do altered soil moisture patterns restructure soil microbial communities and their contributions to greenhouse gas emissions?
The proposed work links biogeochemistry (FREC), soil microbiology (SPES), and hydrology (BSE) to predict and mitigate soil greenhouse gas (GHG) emissions under global climate change.
Soil GHG emissions are strongly related to soil moisture content, and differences between permanently wet and permanently dry soils are well described and modeled. However, the transition zone between wet and dry areas may be a biogeochemical hotspot for soil GHG emissions. These variably saturated zones can experience rapid changes in soil water and redox conditions, altering the biogeochemical interactions among organic carbon (OC), nitrogen (N), and metals with important implications for GHG emissions. Soil environments with high moisture variability occur at multiple scales, including across hill slope gradients, with depth in the soil profile, and within soil aggregates. In these environments, transient soil water saturation makes it challenging to predict exactly where and when soils become a net GHG source. Our ability to predict soil GHG fluxes under dynamic saturation patterns is limited by a key knowledge gap: how do soil microbial communities respond to short term changes in soil moisture, and how do those changes alter microbial contributions to GHG emissions?
This gap in understanding is problematic because future soil moisture conditions are likely to shift under climate change (becoming wetter, drier, or more unpredictable). In addition to predicted future climate change scenarios, cyclic wetting and drying is also relevant to land use change through agricultural and waste management. Our long-term research goal is to understand microbial adaptation and GHG feedbacks to dynamic soil moisture conditions that are likely to occur under future climate and management scenarios. As a first step towards that goal, we need to establish how temporal patterns of wet-dry cycling structure soil microbial communities and functions.
- Characterize microbial community structure in soils collected across a gradient of wet-dry cycling patterns in the field.
- Link soil moisture patterns in the field to emissions of CO2, N2O, and CH4 in laboratory incubations.
Reference citations for project proposal description available upon request.