Coupling soil Carbon Fluxes, Soil Microbes, and High-Resolution Carbon Profiling in Permafrost Transitions

Tuesday, 15 December 2015: 10:50
2008 (Moscone West)
Carolyn Anderson, Pacific Northwest National Laboratory, Biological Sciences Division, Richland, WA, United States, James Stegen, Pacific Northwest National Lab, Microbiology Group, Biological Sciences Division, Richland, WA, United States, Ben P Bond-Lamberty, Pacific Northwest National Laboratory, Richland, WA, United States, Malak M Tfaily, Florida State University, Tallahassee, FL, United States, Maoyi Huang, Pacific Northwest National Laboratory, Atmospheric Sciences and Global Change Division, Richland, WA, United States and Ying Liu, PNNL / Climate Physics, Richland, WA, United States
Microbial communities play a central role in the functioning of natural ecosystems by heavily influencing biogeochemical cycles. Understanding how shifts in the environment are tied to shifts in biogeochemical rates via changes in microbial communities is particularly relevant in high latitude terrestrial systems underlain by permafrost due to vast carbon stocks currently stored within thawing permafrost. There is limited understanding, however, of the interplay among soil-atmosphere CO2 fluxes, microbial communities, and SOM chemical composition. To address this knowledge gap, we leverage the distinct spatial transitions in permafrost-affected soils at the Caribou Poker Creek Research Watershed, a 104 km2 boreal watershed ~50 km north of Fairbanks, AK. We integrate a variety of data to gain new knowledge of the factors that govern observed patterns in the rates of soil CO2 fluxes associated with permafrost to non-permafrost transition zones. We show that nonlinearities in fluxes are influenced by depth to permafrost, tree stand structure, and soil C composition. Further, using 16S sequencing methods we explore microbial community assembly processes and their connection to CO2 flux across spatial scales, and suggest a path to more mechanistically link microbes to large-scale biogeochemical cycles. Lastly, we use the Community Land Model (CLM) to compare Earth System Model predictions of soil C cycling with empirical measurements. Deviations between CLM predictions and field observations of CO2 flux and soil C stocks will provide insight for how the model may be improved through inclusion of additional biotic (e.g., microbial community composition) and abiotic (e.g., organic carbon composition) features, which will be critical to improve the predictive power of climate models in permafrost-affected regions.