Integrating carbon fluxes and wood anatomical traits to unravel carbon pool partitioning using eddy covariance data, tree rings and modeling

Boreal forest sinks one third of terrestrial carbon (C), playing a crucial role in mitigating climate change. However, our understanding of the relationship between carbon assimilation and its allocation into woody biomass production remains limited. To address this gap, we propose a novel approach that combines eddy covariance (EC), wood anatomy in tree rings, and the 3D-CMCC-FEM forest model. This integrated method aims to elucidate the pathways of C pools over short and long-time scales. The study was conducted in a boreal site of Pinus banksiana (Lamb.) in Canada, spanning from 1999 to 2019. Our results revealed notably high correlations between model-predicted and measured Gross Primary Productivity (GPP) ranging from 0.88, 0.95, 0.60 for daily, monthly, and annual scales, respectively. We observed comparable inter-annual variability between measured ring wall area (proxy of total woody biomass) and stem carbon accumulated and predicted by the model. Additionally, consistent values of carbon use efficiency (CUE = 0.41, net vs. gross primary productivity) were found when comparing modeled and estimated data in the nearby evergreen Picea mariana stand to our study site. This study represents a significant step toward enhancing our understanding of both inter-and intra-annual variability of carbon fluxes, providing insights into the pathways of C in forest an essential challenge in estimating and projecting future carbon sink capacities of forests.