A financial analysis of using improved planting stock of white spruce and lodgepole pine in Alberta, Canada: genomic selection versus traditional breeding

摘要

Genomics-assisted tree breeding (GATB) is an emerging biotechnology method that has the potential to produce improved planting stock in selected traits, such as greater volume or higher wood quality, more quickly and effectively compared with traditional field-based breeding (TB) methods. In this study, we conducted an ex-ante stand-level financial benefit-cost analysis that is linked to a provincial tree growth and yield projection model to investigate the potential financial benefits of using improved white spruce (Picea glauca (Moench) Voss) and lodgepole pine (Pinus contorta Dougl. var. latifolia Engelm.) planting stock identified via alternative tree improvement strategies (i.e. GATB vs. TB methods) for forest companies in the province of Alberta, Canada. With consideration of major tree breeding and establishment costs, expected sawlog price premiums at harvest, a shorter breeding cycle time, and additional genetic gain in volume achieved from using the GATB method relative to the TB method in the financial analysis; this study found that the use of GATB-selected third-generation planting stock was difficult to justify economically alone compared with TB-selected seedlings under the current sawlog market value and the current planting rate with improved stock in the province. However, results of our sensitivity analysis also revealed that the GATB method is: (1) more financially supported at lower discount rates; (2) strongly supported through decreased seedling costs with increased areas planted with improved stock; and (3) strongly supported through an increase in log price premiums at harvest resulting from potentially better wood quality and higher volume production relative to TB-selected stock. The findings of this study highlight several important market and biophysical factors that forest managers should take into account when adopting biotechnology in forestry.