Drought conditions caused by soil moisture stress and/or high vapour pressure deficit pose a challenge to many terrestrial ecosystem models (TEMs). The Canadian LAnd Surface Scheme Including biogeochemical Cycles (CLASSIC) employs an empirical approach to link soil moisture stress with stomatal conductance. Such soil moisture-based empirical approaches typically perform poorly during drought. Here, we implemented an explicit plant hydraulics parameterization, i.e., Stomatal Optimization based on Xylem hydraulics (SOX), in CLASSIC, thereby connecting the soil-plant-atmosphere continuum through plant hydraulic traits. Performance of the resulting CLASSIC$_{SOX}$ was evaluated against carbon and water fluxes measured with eddy covariance at eight boreal forest flux tower sites in North America. Compared to CLASSIC, CLASSIC$_{SOX}$ better simulated gross primary productivity (GPP) across all sites, i.e., coefficient of determination (R$^{2}$) increased (0.51 to 0.59), root mean square error (RMSE) and bias decreased (1.85 to 1.54 g C m$^{-2}$ d$^{-1}$) and (-0.99 to -0.58 g C m$^{-2}$ d$^{-1}$), respectively. Under drought conditions, identified using the Palmer drought severity index, GPP simulated with CLASSIC$_{SOX}$ improved compared to CLASSIC, i.e., R$^{2}$ increased (0.51 to 0.60), and RMSE and bias decreased (1.79 to 1.46 g C m$^{-2}$ d$^{-1}$) and (-0.97 to -0.53 g C m$^{-2}$ d$^{-1}$), respectively. In contrast, CLASSIC$_{SOX}$ simulated evapotranspiration worsened, i.e., R$^{2}$ decreased (0.61 to 0.42), RMSE increased (0.54 to 0.62 mm d$^{-1}$), and bias changed direction (0.09 to -0.09 mm d$^{-1}$). As evaporation is a highly parameterized process in CLASSIC, it likely needs to be re-parameterized to account for the SOX transpiration behaviour.

Canada’s boreal forests and tundra ecosystems are responding to unprecedented climate change with implications for the global carbon (C) cycle and global climate. However, our ability to model the response of Canada’s terrestrial ecosystems to climate change is limited and there has been no comprehensive, process-based assessment of Canada’s terrestrial C cycle. We tailor the Canadian Land Surface Scheme Including Biogeochemical Cycles (CLASSIC) to Canada and evaluate its C cycling performance against independent reference data. We utilize skill scores to assess model performance against reference data alongside benchmark scores that quantify the level of agreement between the reference data sets to aid in interpretation. Our results demonstrate CLASSIC’s sensitivity to prescribed vegetation cover. They also show that the addition of five region-specific PFTs improves CLASSIC’s skill at simulating the Canadian C cycle. CLASSIC performs well when tailored to Canada, falls within the range of the reference data sets, and meets or exceeds the benchmark scores for most C cycling processes. New region-specific land cover products, well-informed plant functional type (PFT) parameterizations, and more detailed reference data sets will facilitate improvements to the representation of the terrestrial C cycle in regional and global land surface models (LSMs). Incorporating a parameterization for boreal disturbance processes and explicitly representing peatlands and permafrost soils will improve CLASSIC’s future performance in Canada and other boreal regions. This is an important step toward a comprehensive process-based assessment of Canada’s terrestrial C cycle and evaluating Canada’s net C balance under climate change.