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UBC Theses and Dissertations

Assessing structural differences among genetically improved coastal Douglas-fir using high density airborne laser scanning du Toit, Francois


Tree improvement programs are critical to establishing high yield seed sources while maintaining genetic diversity and developing sustainable plantation forests. Douglas-fir (Pseudotsuga menziesii (Mirb.) Franco) is commonly used in improvement programs due to its superior strength and stiffness properties. Trials in British Columbia (BC), Canada aim to increase stem volume without sacrificing wood quality. Progeny test trials are essential in assessing the genetic performance via the prediction of breeding values (BVs) for target phenotypes of trees. To evaluate performance of improved stock, and to determine whether yield gains are being met, realized-gain trials are used. In both trials, accurate and timely collection of phenotypic data are critical for estimating and validating BVs with confidence. Currently, phenotypic variables collected focus on yield attributes; namely diameter at breast height, and height. Selection criteria in BC are evolving; branching traits are recognized as having a strong influence on strength and stiffness of Douglas-fir wood, however, they are rarely measured. High-density Airborne Laser Scanning (ALS), as well as Remotely Piloted Aerial Systems Laser Scanning Systems (RPAS-LS) produce three-dimensional point clouds which can be used to characterize individual tree structure. In this dissertation I utilized metrics derived from ALS and RPAS-LS to assess the performance in realized-gain trials, and predict genetic parameters in progeny trials. Additionally, new methods to estimate branch attributes of individual trees for inclusion as selection criteria in tree improvement programs were developed. This dissertation provides an insight into how ALS can be used to model branch attributes, while the ability to analyse trees by plot, individual tree, and individual branch attributes further allows researchers to maximise the value of ALS data. The findings are encouraging; they indicate that branch level metrics can be included as selection criteria in breeding programs, and that ALS-derived BVs are a suitable proxy for ground-based BVs. Given the cost efficiency of ALS, forest geneticists should explore this technology as tool to increase breeding programs’ overall efficiency. Findings from this research can be integrated into large-scale programs for monitoring trees, and identifying trees that display desirable attributes.

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