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UBC Theses and Dissertations

Predicting forest tree species’ fundamental climate niche and productivity Zhao, Yueru


Species climate niche models (CNMs) have been widely used for assessing climate change impact and developing adaptation strategies for forestry. However, CNMs built based on species occurrence data reflect only species’ realized niche, which may overestimate the suitable habitat loss of existing forests, underestimate assisted migration potential, and are unable to quantify productivity. To address these deficiencies, my research objectives were to explore modeling approaches aimed at predicting forest species fundamental niche and productivity based on species provenance trials and occurrence data. In chapter 2, a universal response function (URF) was developed for lodgepole pine (Pinus contorta Dougl. ex Loud.), through comparison and optimization of the best existing modeling approaches, to predict the species’ fundamental climate niche and productivity. This model explained 80 % of the variation among provenance and test sites, and the prediction of fundamental climate niche was validated with global observations with 94.6 % agreement. While this approach is considered ideal, it may not be applicable for many forest tree species due to the lack of comprehensive provenance trials. In the chapter 3, I built a fundamental climate niche model using widely available species occurrence data with lodgepole pine and Douglas-fir (Pseudotsuga menziesii Franco.). I identified a new cut-off threshold of 0.3 and extended the CNMs in predicting realized climate niches to fundamental climate niches, the result presented greater niche gain (up to 187 %) and reduced habitat loss (up to 80 %) by 2050s under a moderate climate change scenario. Similarly in Chapter 4, I investigated the potential to extend occurrence-based CNMs to predict species productivity using lodgepole pine and Douglas-fir as the template species for their comprehensive range-wide occurrence data and availability of site productivity data. The CNMs were optimized through a series of steps, achieves R2 above 0.9 in reflecting measured site productivity and validated with R2 above 0.7 using independent datasets for each species. My research provided crucial tools for evaluating climate change’s impact on species suitable habitat distribution and productivity and holds potential for informed forest management decisions, including conservation and assisted migration aimed at maximizing future productivity and carbon sequestration.

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