Modeling CH4 and CO2 cycling using porewater stable isotopes in a thermokarst bog, interior Alaska
Monday, 15 December 2014
Methane emitted from wetlands represents the end product of various microbial processes operating within anaerobic wetland soils. Determining the rate at which these microbial reactions occur is challenging, making it difficult to gain a mechanistic understanding of the factors and conditions that influence microbial rates and ultimately methane emissions. One approach for estimating in-situ reaction rates involves tracking the time evolution of porewater concentrations and stable carbon isotopes of CH4 and CO2. Microbes preferentially use isotopically light carbon substrates, which causes the carbon product pool to become isotopically lighter and the carbon substrate pool become isotopically heavier. Different microbial biochemical pathways fractionate carbon to different extents, allowing for differentiation between microbial reactions. This is a powerful approach to estimate in-situ rates, but, as we show in our presentation, it is possible for different combinations of reaction rates to provide equally good fits to the evolution of these data. The solution is non-unique and depends on the set of considered reactions. We used two different reaction network models on a set of porewater data collected from a thermokarst bog at the Alaska Peatland Experiment (APEX) outside of Fairbanks, AK to estimate in-situ microbial reaction rates during the summer season. Both models included methane production, methane oxidation and fermentation/respiration, but only one model included homoacetogenesis. We found that both reaction networks explained the evolution of dissolved gas concentrations and stable carbon isotope data, but predicted rates that differed from each other by up to a factor of six. The methane production rates estimated by the model that included homoacetogenesis aligned better with measured rates of methane emission. Despite differences in the magnitude of modeled rates, results from the two models told a similar story about the spatial and temporal patterns of microbial rates at the site. Modeled rates were higher at the edge of the bog than in the center of the bog, and rates at the edge increased during the summer while those in the center did not change with time. In both the center and at the edge of the bog, modeled rates increased with depth. We present hypotheses for these patterns.