Christina Howard
Doctor of Philosophy in Forestry (PhD)
Research Topic
Climate sensitive growth and suitability modeling of Québec tree species
Tongli Wang
Associate Professor
Relevant Thesis-Based Degree Programs
Graduate Student Supervision
Doctoral Student Supervision
Dissertations completed in 2010 or later are listed below. Please note that there is a 6-12 month delay to add the latest dissertations.
Predicting forest tree species' fundamental climate niche and productivity (2024)
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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Master's Student Supervision
Theses completed in 2010 or later are listed below. Please note that there is a 6-12 month delay to add the latest theses.
Using landscape genomics to delineate seed and breeding zones and project genetic offset for lodgepole pine (2021)
Well-defined seed and breeding zones are critical for developing adaptive forest resource management strategies. These zones are traditionally delineated based on local adaptation of phenotypic traits associated with climate variables, determination of which requires long-term field experiments. In this thesis, I applied a landscape genomics approach to delineate seed and breeding zones for lodgepole pine (Pinus contorta) in British Columbia and Alberta, Canada, based on genomic evidence of local adaptation of this widespread forest tree species across western North America. A gradient forest (GF) model was built by aggregating relationships between spatial variation in 28,954 single-nucleotide polymorphism (SNPs) and 20 climate variables across 281 lodgepole pine populations. The fitted GF model confirmed winter-related climate variables are the major climatic factors associated with genomic patterns of variation among lodgepole pine populations. I used the GF model to delineate the lodgepole pine distribution range in British Columbia and Alberta into six seed and breeding zones. Genomic-based zones delineated by the GF model are comparable to existing common garden-based zones, suggesting that this landscape genomic approach could provide an effective alternative for delineating seed and breeding zones. This approach has the potential to provide a novel and effective alternative over traditional approaches for delineating seed and breeding zone, and offers an innovative means for guiding assisted gene flow in tree species lacking data from provenance trials or common garden experiments. Additionally, using the GF model, I predicted the spatial pattern of genetic offsets associated with seed and breeding zones to identify zones that are susceptible to genotype-environment mismatches under two future climate scenarios for the 2050s.
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Current Students & Alumni
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