Cooperative Fish and Wildlife Research Units Program: Alaska
Education, Research and Technical Assistance for Managing Our Natural Resources

In this study we propose to apply the dynamic organic soil version of the Terrestrial Ecosystem Model (DOS-TEM; Yuan et al. 2012) to assess historical (1960 – 2009) and projected (2010 – 2099) changes in carbon storage in Alaska. Historical simulations will be driven by downscaled climate prepared by the Scenarios Network for Alaska & Arctic Planning (SNAP; www.snap.uaf.edu), observed atmospheric concentrations of CO2, and historical observations of wildfire in Alaska. Projected simulations will be driven by downscaled future scenarios of climate prepared by SNAP, associated atmospheric concentrations of CO2, and associated projections of wildfire simulated by the Alaska Frame Based Ecosystem Code (ALFRESCO; Rupp et al. 2007) and by the First Order Fire Effects Model (FOFEM; Reinhardt 2003) burned area model. Initial vegetation for these simulations will be based on the vegetation data set being prepared by SNAP for the Western Arctic, which includes all of Alaska. Data products will include annual maps of vegetation distribution, stand age distribution, burn area, fire severity, active layer thickness, soil organic layer thickness, vegetation carbon, soil carbon to 1 meter, soil organic layer carbon, net primary production (NPP), heterotrophic respiration (RH), fire emissions (FE), and net ecosystem carbon balance (NECB) at 1-km resolution from 1960 through 2099. Annual NECB will be determined via two methods: (1) as a difference in the stocks between years and (2) a sum of the fluxes (NPP-RH-FE) to verify that difference in stocks is consistent with the sum of the fluxes. These outputs will be aggregated to four regions of Alaska for reporting purposes: Interior Alaska, Arctic Alaska, Western Alaska, and Southeast/Southcentral Alaska. The historical model outputs will be validated to the extent possible based on analyses of soil and vegetation carbon for Alaska. The simulations and model evaluation will be conducted in FY13 and the results will be summarized in USGS reports and a special issue of a peer reviewed journal in FY14. Data will be distributed to the public via a USGS web server.