Oil sands restoration with warm-adapted trees improves outcomes under moderate but not severe warming scenarios

Successful restoration of human-disturbed landscapes and ecosystems will be increasingly compromised by the impacts of climate warming. Assisted migration and climate-informed restoration, in which populations and species adapted to future climates are selected for restoration planting, have emerged as management tools to mitigate climate change effects. However, it is unclear whether climate-informed restoration could offset the negative effects of climate change and enable successful restoration. We used a forest landscape model to evaluate the potential for reclamation activities to restore western Canadian boreal forest landscapes severely degraded by oil sands mining. We parametrized tree populations adapted to growing in warmer climates and then simulated the planting of local or southern tree populations under different climate change, mining, and wildfire disturbance scenarios. We found that planting trees better adapted to a warmer climate mitigated climate-change and wildfire-caused decreases in biomass across the landscape, but only under moderate climate change scenarios. The compensatory effect of planting populations adapted to warmer southern climates disappeared under a more severe climate change scenario. The advantage of planting southern populations also disappeared under wildfire scenarios, generally doubling the biomass loss compared with scenarios without wildfire. With wildfire and strong climate change effects, forest cover disappeared from much of the landscape, regardless of the planting scenario, causing it to change markedly from present-day continuous boreal forest cover. We argue that such conditions would have large ecological and economic consequences. Scenario modeling with forest landscape models could be used as a tool to identify the long-term success of restoration actions and to understand possible consequences of climate-informed restoration.