Spruce-Up: Advanced spruce genomics for productive and resilient forests
Forestry contributes $19.8 billion dollars to Canada’s GDP. Spruce trees, as Canada’s most significant forest resource, are responsible for a significant proportion of that amount. Spruces produce high-quality wood and fibre that are widely used. With some 400 million seedlings planted each year, spruces are the most reforested trees in Canada. To date, well-established breeding programs in British Columbia and Quebec have provided improved spruce stock for this purpose, making Canada a world leader in the sector. However, climate change and its related epidemics of insects and droughts are costing the Canadian forest sector hundreds of millions of dollars annually due to reduced productivity of spruce forests. These impacts of climate change, as well as changing forest products markets, require that spruce breeding programs be accelerated to ensure future forest health, wood quality and productivity.
The Spruce-Up project, led by Dr. Joerg Bohlmann of the University of British Columbia and Dr. Jean Bousquet of Université Laval, is bringing genomics to bear upon these challenges. The project will deliver leading knowledge, socioeconomic decision support tools and applied genomic tools to significantly enhance conventional breeding programs. By involving end users in government and industry in its work, the project will accelerate the development and deployment of genomics-improved spruce stock that is more resistant to insects and drought, uses nutrients efficiently and results in improved wood quality and productivity.
Spruce-Up is estimated to more than double the net economic output value of spruce forests relative to conventional breeding. It will leverage existing spruce breeding and reforestation programs by increasing the value of new trees and reducing losses due to environmental disturbances.
The GE3LS component of the project will include a decision support dashboard comprising risks/benefits, opportunities/constraints, policy analysis, and community engagement models that consider site-specific characteristics and omics information to provide outputs on contamination risk, potential economic benefits and costs, policy coherence, and social acceptability of alternative courses of action.