Patrick Lenz is research scientist in forest genetics at the Canadian Wood Fibre Centre of Natural Resources Canada. His current research focusses on the development of genomic tree breeding tools to speed up the selection of planting stock with improved growth, wood quality and resilience in the context of climate change. Some of his top priorities include the research on resistance traits to climate anomalies to better understand their role in adaptation and breeding opportunities. Patrick has been member of the Canada Research Chair in Forest Genomics and co-PI of large forest genomics projects funded by Genome Canada, including his current co-lead with Jean Bousquet of the FastTRAC II project aiming at the scaling of genomic prediction for black- and red spruce breeding programs.

Enhancing the adaptive potential of reforestation seedlings by combining wood anatomy, dendroecology and genomics

Climate change and the recurrence of more frequent severe weather events are putting significant pressure on Canadian forest ecosystems, raising questions about their future health and productivity. Post-harvest reforestation is a common practice in Canadian boreal and temperate forests, which could serve as a strategy for mitigation of climate change effects when planting stocks are adapted to future climate predictions. However, this requires a thorough understanding of existing adaptive clines in reforested species and well characterizing genetic variation and control of adaptive traits themselves.

To address these questions, our group combines genomic predictive tools, common garden experiments, and novel phenotyping methods to assess growth and wood structural responses to climatic stressors in different spruce species at the juvenile and mature stages. We have shown that intraspecific variation in wood anatomy and resilience of growth to drought episodes is under significant genetic control. Signs of local adaptation and contrasting adaptation strategies to drought were discovered in different spruce populations. In close collaboration with breeding programs, we have developed strategies to accelerate operational integration of novel adaptive traits into genomic prediction models that all together show promise for enhancing the selection for growth and adaptive traits and hence, to allow the production of high quality and adapted seedlings for future forests.