Forest ecosystems are an essential terrestrial carbon sink, and deforestation and forest degradation account for about 12% of global anthropogenic carbon emissions. However, estimates of the global distribution of terrestrial carbon sinks and sources are highly uncertain. Constraining the inaccuracy of carbon estimates is essential to support effective forest management and future climate mitigation. A better understanding of forest growth dynamics will improve our understanding of the carbon cycle and mechanisms responsible for terrestrial carbon sources and sinks, reducing uncertainties on their magnitude and distribution. The 3D-FOGROD project aimed to improve our understanding of forest growth dynamics and evaluate the role of elevated CO2 levels on forest growth. It achieved this by using novel 3D laser scanning (LiDAR) techniques, unique datasets and state-of-the-art modelling approaches to:

(1) accurately quantify forest growth using terrestrial LiDAR data in a free-air CO2 enrichment experiment;
(2) improve historical and future simulated forest growth dynamics using LiDAR derived forest structure for a range of forest ecosystems;
(3) develop and disseminate recommendations for climate mitigation actions to policy makers based on new insights in forest growth dynamics and carbon cycling.