###### Abstract  
Forests play an important role in climate regulation due to carbon sequestration. However, a deeper understanding of forest carbon flux dynamics is often missing due to a lack of information about forest structure and species composition, especially for non-even-aged and species-mixed forests. In this study, we integrated field inventory data of a species-mixed deciduous forest in Germany into an individual-based forest model to investigate daily carbon fluxes and to examine the role of tree size and species composition for stand productivity. This approach enables to reproduce daily carbon fluxes derived from eddy covariance measurements (R\({}^{2}\) of 0.82 for gross primary productivity and 0.77 for ecosystem respiration). While medium-sized trees (stem diameter 30-60 cm) account for the largest share (66%) of total productivity at the study site, small (0-30 cm) and large trees (>60 cm) contribute less with 8.3% and 25.5% respectively. Simulation experiments indicate that vertical stand structure and shading influence forest productivity more than species composition. Hence, it is important to incorporate small-scale information about forest stand structure into modelling studies to decrease uncertainties of carbon dynamic predictions. forest model; species-mixed deciduous temperate forest; carbon fluxes; structure; tree size; species composition; FORMIND; eddy covariance Article  
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and forest inventories, are limited in the spatial domain and need expensive implementations [15; 16]. Forest inventories can routinely be performed only on smaller plots and forest stands that allow accessibility with respect to density. EC measurements are limited to flat, homogenous areas and atmospheric conditions with well-developed turbulence. For ideal conditions, EC measurements are representative for areas extending some hundreds of metres in length [16; 17]. Additionally, both approaches just provide information about parts of the total carbon balance, such as the net ecosystem productivity (_NEP_), the gross primary productivity (_GPP_) and ecosystem respiration (_Rexo_). While _NEP_ can be directly measured, other carbon fluxes can only be derived indirectly [15; 18]. For example, _GPP_ and _Rexo_ are derived from _NEP_ through partitioning methods [19; 20; 21]. Further in-depth details, such as the influence of species composition on the overall carbon dynamics, are difficult to derive from EC measurements solely. However, for political, management or society decisions, more accurate information about the carbon balance of forests is needed [7; 8; 22; 23; 24]. Forest models can bridge this gap by integrating ecological processes to investigate and predict consequences for individual trees, entire forest stands or even landscapes under current and future conditions [25; 26]. In Central Europe, modelling and experiment-based studies have mainly focused on monocultures so far and rarely on mixed forest [27]. Therefore, our knowledge about the carbon dynamics in mixed forests is limited, especially regarding species interactions, competition, tree growth and their influence on stand productivity and ecosystem dynamics. This can lead to significant biases in landscape representations of carbon dynamics in areas with heterogeneous forest structures [8]. Incorporating forest stand structure and species composition information at the local level could help to reduce existing biases in ecosystem-level carbon dynamics estimates. Therefore, this study combines EC measurements and forest inventory data with an individual-based forest model to simulate daily carbon dynamics and carbon pools of a mixed forest in Central Germany. The aim of this study is to improve our understanding of carbon allocation in a forest ecosystem and its distribution across several species as well as tree size classes.