Natural and social dimensions of forest carbon accounting

Abstract: Global forests store large amounts of carbon both in living biomass and in the soil. The ability of forests to counteract climate change by acting as carbon sinks have been recognized in global climate politics, such as the 2015 Paris agreement which calls for national commitments to reduce greenhouse gas emissions. Sweden is one of many countries who have pledged ambitious climate goals, promising to achieve net zero emissions by 2045. To achieve this goal, greenhouse gas emissions must be balanced by uptake of carbon dioxide in natural ecosystems such as forests. Active management is important in determining the forests’ ability to mitigate climate change, but the trade-off between climate benefits, economic values and biodiversity have to be considered. To be effective, climate related decision-making requires an understanding of forest dynamics as well as knowing the spatial and temporal distribution of forest carbon sinks and sources.Several approaches are available for monitoring of forest carbon fluxes. Sample based field inventories form the basis for the collection of forest information in most countries. Remote sensing offers the ability to map forests with high resolution, and process-based computer models can simulate the behavior of forest ecosystems and predict their response to future climate and changes in management. The aim of this thesis is to study the impact of different approaches on forest carbon monitoring, and suggest how they can be combined to enhance the results by utilizing the strengths of the respective methods. The potential of technological advances in remote sensing and modeling application is related to the needs of the Swedish forestry sector identified by interviews, and an approach is presented for verifying carbon flux estimates versus tower measurements of carbon dioxide concentrations. The results highlight the differences between methodological approaches for forest carbon monitoring, both regarding their impact when estimating regional carbon budgets and implications at the international political arena. Process-based modeling informed by remote sensing and/or field inventory data is shown to be an efficient tool for simulating the spatial distribution of Swedish forest carbon fluxes that can deliver the demands for increased forest information.