Both productivity and sustainability of our forest ecosystems and operations are reliant on a healthy and resilient forest. However, forest health and local communities that depend on the forest industry are both under constant threat from changes in climate and climate-induced insect outbreaks. The pace of these changes is outstripping the ability for trees to adjust to these threats. Likewise, traditional tree improvement methodologies are too slow to provide well-adapted seedlings for reforestation and ultimately achieving healthy forests for the future. The goal of this project is to integrate genomic, metabolomic and phenotypic data into selection models that will reduce the selection time and therefore the breeding cycles in lodgepole pine and white spruce tree improvement programs in Alberta. These new integrated models will help us produce healthy, productive, and resilient forests while informing policy, determining the economic value of genomic selection and identifying social/political factors influencing the use of these cutting-edge selection strategies.