The boreal forest provides essential ecosystem services, including timber resources, wildlife habitat, carbon storage, and climate regulation. The persistence of these services depends on how climate change reshapes disturbance dynamics, land covers, and forest productivity. Here, we focus on forecasting primary productivity responses across the entire Canadian boreal forest. We parameterized and applied the process-based ecophysiological model Biome-BGC to generate spatially explicit predictions of potential primary productivity at continental scale. Such large-scale, mechanistic forecasts remain rare in predictive ecology, where projections often rely on correlative or statistical approaches. Model predictions showed strong agreement with independent gross primary productivity estimates from flux tower observations distributed across Canada. Projecting forward to 2100 under climate change scenarios, we predict large spatial heterogeneity in productivity responses. Most regions are expected to experience substantial increases in productivity, particularly areas currently constrained by low temperatures, where projected gains sometimes exceed 100% relative to historical baselines. Our simulations also indicate a fundamental shift in limiting factors: much of the boreal forest, presently temperature-limited, is projected to transition toward water or light limitation by the end of the century. These results suggest that increases in primary productivity may partially offset rising carbon emissions associated with intensifying disturbances such as wildfire, insect outbreaks, and permafrost thaw. By providing one of the first process-based, wall-to-wall forecasts of boreal potential productivity at national scale, this work advances our capacity to mechanistically predict ecosystem responses to climate change.

Keywords: Process-based modelling; Primary productivity; Boreal forest; Ecological forecast; Ecosystem model