The role of species traits and forest structure on spatial carbon dynamics of temperate forests

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Forests play a major role in the global carbon cycle. There has been a long debate under which conditions forests are a source or sink of carbon. For determining forest carbon stocks and their dynamics at large scales, local-scale heterogeneities have to be considered. Spatially heterogeneous distributed carbon stocks are often a result of heterogeneous distribution of tree species structuring the forest vertically and horizontally. However, the role of tree species and their traits on local and regional carbon stocks and dynamics in forests is so far not comprehensively understood. Here, we combine field observations with forest modelling in order to examine how species traits and their variability structure heterogeneous forests. For study sites of species-rich temperate forests in China (two large plots of 25 and 24 ha, 13 plots of 4-0.5 ha) we will characterize spatial patterns of forest biomass and productivity and its correlation with species traits and forest structure. By extending and applying an individual-based forest gap model including a novel trait distribution approach, we will analyse forest carbon dynamics (e.g. gross and net primary production, net ecosystem exchange) at the large (e.g. 25 ha) and local scale, and explore how trait distributions impact forest carbon stocks and dynamics. In an additional analysis, we will take a step towards advances in combining forest modelling with remote sensing by restricting our studies to canopy-level trees including LiDAR campaigns. The vision behind this is to find a minimal set of required information derived by remote sensing to apply forest models to a broad range of different forest types.