HIGH-RESOLUTION CARBON INVENTORY AND DYNAMICS IN PERMAFROST SOILS: NORTH SLOPE, ALASKA

Perennially frozen soils cover ~17% of the global soil area and are estimated to hold over 1,000 Pg of soil organic carbon (SOC) within their top three meters, making it one of the world’s largest stocks of organic carbon. Studies predict varying extents to which ice-wedge polygons serve as carbon sources or sinks. Our goals are to generate a high-resolution data set of SOC stocks that incorporate the effects of cryoturbation and microtopographic land surface features and to use this information to predict mobility of carbon from soils within ice-wedge polygons to wetlands and thermokarst lakes in low-gradient watersheds. The field site is located 50 km south of Deadhorse, Alaska, within wetland tundra that contains extensive ice wedge polygon terrain. The study began in 2012 with high-resolution lidar acquisition (~20 points/m²) in a 480 km² region, from which individual polygon morphology (e.g., high centered, low centered) could be discerned. In 2013, soil samples were collected from 101 pits within a (100 km²) subarea. Samples were analyzed for TOC, carbon isotopes, and soil texture. In 2014, we further reduced scale to 400 m² using ground penetrating radar (GPR), cone penetrometry, methane and CO₂ gas flux, dissolved and particulate organic carbon (DOC and POC) measurements and laboratory estimates of soil hydraulic and thermal properties. The results of these analyses are used to model carbon transport in aqueous and gaseous (CO₂ or CH₄) phases. Because this carbon loss may be coupled to direct erosion of ice wedge polygons, we developed a numerical model of soil polygon thermo-erosion, and used it to estimate potential carbon loss as polygons transition from low- to high-centered. GPR results show variability of the active layer thickness and potential flow paths for DOC, and the numerical model highlights the potential for soil erosion as a substantial source of carbon for hydrologic transport. Though results are preliminary, we show the value of coupling soil carbon stocks, hydraulic properties, and fluxes to estimate carbon dynamics.