Forests in countries that have had historically high forest cover and low deforestation rates are now being lost due to globally traded commodities and related market forces. The deforestation of these old-growth forests contributes substantial carbon emissions to the atmosphere, and tropical deforestation is a key driver of climate change. In recognition of the need to balance deforestation-driven economic development and the future resilience of their nation-states from a changing climate, countries have begun to adopt Natural Climate Solutions (e.g., REDD+) to protect and enhance their forest carbon stocks. There is, however, uncertainty as to how these policies will impact land-cover/land-use change and deliver co-benefits to indigenous and local communities. One source of uncertainty is a limited ability to effectively measure forest carbon dynamics associated with forest degradation and regeneration in the tropics. An additional barrier to forecasting impacts of Natural Climate Solutions (NCS) is a lack of rigorous impact evaluation of how NCS will influence human behavior and forest use in both the target areas as well as other, distant locations (i.e., diffusion and spillover effects). Our proposal aims to improve our understanding of how market forces and NCS interventions impact forest carbon dynamics in the Guiana Shield ecoregion. Specifically, we propose to (1) Advance methods to map forest degradation, and forest regrowth, and the carbon dynamics associated with these processes through data fusion of optical, radar and lidar satellite imagery; (2) Quantify the impact of NCS interventions on forest carbon trajectories and socioeconomic outcomes using counterfactual impact evaluation methods; and (3) Quantify the rate of diffusion of NCS interventions and their spillover impacts within and across countries. The geographical focus of this research are the countries that lie entirely within the Guiana Shield ecoregion, which includes Guyana, Suriname, and French Guiana. Together, all three countries boast more than 80% forest cover, storing large amounts of carbon stocks. Their continued intact state is considered vital for the resilience of the adjacent Amazonian forests and global climate mitigation. Our proposed research will pioneer the development of state-space models that connects satellite time series data across different sensors to a network of forest inventory plots to quantify forest carbon dynamics across time and space. We will leverage these satellite-derived data products on forest carbon trajectories for our assessment of NCS interventions. We will then link these spatial forest carbon outcomes to the welfare of local people to quantify their linkages and feedbacks in the context of a coupled human natural system. With the project we will leverage our expertise and research network to catalyze a new body of cutting-edge interdisciplinary social science research to guide global investments in NCS. The knowledge we generate will be pivotal to guide policymakers and practitioners in designing effective and scalable NCS interventions.