Canada�s forests are responding to unprecedented climate change and anthropogenic disturbance. Unfortunately, boreal disturbance processes are not represented in many pre-existing land surface models (LSMs). Many LSMs also do not explicitly represent subgrid-scale heterogeneity resulting from disturbance. We represent boreal harvest and fire in CLASSIC alongside dynamic tiling that explicitly represents subgrid-scale heterogeneity due to disturbance. We demonstrate the impacts of subgrid-scale heterogeneity relative to standard average individual representations of disturbance and explore the resultant model biases. Our modeling approach can balance model complexity and computational cost to represent the impacts of subgrid-scale heterogeneity resulting from disturbance. Subgrid-scale heterogeneity has impacts beyond the disturbance impacts themselves on vegetation and to a lesser extent, the surface energy balance in our simulations. Representing subgrid-scale heterogeneity slows vegetation re-growth and affects surface energy balance in recently disturbed, sparsely vegetated, and often snow-covered fractions of the land surface. Representing subgrid-scale heterogeneity is also key to more accurately representing wood harvest, which in reality preferentially impacts more merchantable trees. Our results provide insight into how different discretization schemes can impact model biases resulting from the representation of disturbance. This work enhances our understanding of and ability to represent disturbance within boreal Canada to facilitate a comprehensive process-based assessment of Canada�s terrestrial C cycle.