While change in political and economic structures is occurring in a number of countries worldwide, nowhere else recently has this occurred at the scale of the break-up of the state controlled Soviet Union and its transition to a market economy. This event stands out in the magnitude of the change it’s rapid transition period, and the geographic extent and global impact of the potential effect, including its effect on the Siberian boreal forest. We hypothesize that these two different economic paradigms – state-controlled and market economy – may leave significantly different imprints on the land, and we propose to develop a case-study model of the contrasting economic drivers and of their past, present, and potential future consequences for land-cover land-use change and carbon in Siberia. Goals and Objectives: The goal of the proposed project is to develop a model of Siberian boreal forest land-cover land-use change and carbon that is linked to changing economic paradigms, and that is informed by remote sensing derived analyses of change. To achieve this goal we will address four objectives: 1) develop an economic model of the factors affecting forests in Siberia over the past 70 years 2) use time series Landsat-derived datasets to develop land-cover land-use change matrices and transition probabilities, including their socio-economic spatial dependency 3) add the carbon content to these land cover states through application of an ecosystems dynamics and carbon models 4) combine these into an integrated model of land-cover land-use change in Siberia driven by rules associated with different economic paradigms. Approach: This project builds on previous work in remote sensing and modeling of Siberian forests specifically using time-series analyses and ecosystem models. We will build on this by using a new Landsat-7 dataset for three test sites in three of the most important administrative units in the Siberian forest sector: Tomsk Oblast, Krasnoyarsk Krai, and Irkutsk Oblast. We will derive land-cover transitions from time series remote sensing and link these to carbon content. We will develop models of the economic paradigms. Land-cover/use transition probabilities and associated carbon contents will be coded into a Markov-based simulation model and this model driven by different scenarios as based on the economic models. Expected Results: We will produce an economic model that expresses the institutionalized “rules” of the different paradigms that impact land-cover/use in Siberia. We will construct a time-series Landsat-7 dataset and different land-cover states at each time period and link these with carbon contents. We will integrate these model components into a new coupled model driven by the rules of the different economic paradigms. We will examine the model output in terms of land-cover land-use impacts of the different economic paradigms. This work will be useful for further understanding the relationships between land-cover land-use change and carbon, and economic policy in Siberia.