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Zhang, Qiyue

University of British Columbia

Optimization of log processing is important in maximizing wood resource utilization and financial benefits of sawmills, while genomic-assisted tree breeding (GATB) can accelerate the selection of trees in the tree improvement process. The main research objective was to assess the benefits for sawmills to process improved planting stock generated through GATB as compared to a traditional phenotype-based tree breeding (TB) method. In this thesis, the process from tree seedling to lumber manufacturing was simulated. The project was conducted in two parts. First, I assessed the impact of the selection approach, growth parameters, including age of measurement (AM), rotation age (RA), and site index (SI) on four sawmill key performance indicators (KPI), for lodgepole pine (LP) and white spruce (WS). An individual tree growth and yield model (MGM18) was used to grow trees to harvest, while SAWSIM® was used to assign an end-product to each tree. In the second part, I analyzed the net present value (NPV) using the same parameters for various discount rates, log prices, lumber values and seedling costs. The results indicated that using data from older AM resulted in larger tree height and DBH and was due to the age-age correlation effects which were more important for LP. In practice, these results show that an underestimation is to be expected in all four KPIs when using a young AM (year 20-23). Furthermore, environmental factors such as SI had a significant impact on tree growth and lumber volume, while RA had a positive effect on the final products value. The analysis from the lumber value data revealed that the value from GATB trees should be higher than that of TB trees. This was reinforced by the NPV analysis. The results also revealed that the optimal economic RA (lower than 60 years) would be earlier than the age at which the maximum mean annual increment is reached. Results showed a positive NPV could be obtained when the lumber value is over 25% larger than in the base case scenario and the log price premium is not higher than 50%. These results were consistent among the seven selection scenarios explored.

Text

2022-04-06

Attribution-NonCommercial-NoDerivatives 4.0 International

http://hdl.handle.net/2429/81145

Forestry

University of British Columbia

UBCV

http://creativecommons.org/licenses/by-nc-nd/4.0/