This project is an integrative study that builds upon the results of past and on-going carbon cycle research in Northern Eurasia from three research teams: 1) Drs. H. Shugart and J. Shuman ( University of Virginia) and the individual-based forest model capable of simulating forest response to a range of environmental drivers; 2) Dr. T. Loboda (University of Maryland) and her work on wildfire dynamics and their implications for land cover changes using remotely sensed data and products; and 3) Dr. O. Krankina (Oregon State University) and her work involving analyses of in-situ measurements of forest carbon storage and dynamics.  This project focuses on the Russian boreal forest, the largest forest region on Earth and a tremendous repository of terrestrial organic carbon. The boreal forest has experienced significant warming over the past several decades and is expected to be impacted strongly by global climate change.  The principal objective of this synthesis is to perfect the capability to predict the response of the Russian boreal forest to changing climatic conditions and disturbance regimes.We also aim to develop a better understanding of the feedbacks between the Russian boreal forest and the atmosphere.  Within the scope of this project, Dr. Loboda’s team will develop a continental scale dataset characterizing the disturbance and regeneration of the Russian boreal forest over the past 30 years using a combination of Moderate Resolution Imaging Spectroradiometer (MODIS) based disturbance products and hindcasting.  Secondly, the UMD researchers will build and parameterize a fire occurrence model and evaluate the response of fire disturbance to projected climate change from present day to 2050.  Finally, the team will integrate the fire occurrence model with simple logging scenarios and FAREAST model (UVA) outputs for future climate in order to project future changes in carbon storage and fluxes. These projections will then be compared with those generated by several Dynamic Global Vegetation Models (DGVMs) to assess the divergence among the existing projections of climate-induced vegetation dynamics. This is a critical issue in understanding and advancing carbon cycle science in line with current priorities of the U.S. Carbon Cycle Science Program (NRC 2007).