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Assessing Forest Tree Communities and Assisted Migration Potential in Toronto’S Urban Forest As a Result of Climate Change

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Assessing Forest Tree Communities and Assisted Migration Potential in Toronto’S Urban Forest As a Result of Climate Change Assessing Forest Tree Communities and Assisted Migration Potential in Toronto’s Urban Forest as a Result of Climate Change by Peter Quincy Ng A thesis submitted in conformity with the requirements for the degree of Doctor of Philosophy Department of Physical and Environmental Sciences University of Toronto © Copyright by Peter Quincy Ng 2018 Assessing Forest Tree Communities and Assisted Migration Potential in Toronto’s Urban Forest under Climate Change Peter Quincy Ng Doctor of Philosophy Department of Physical and Environmental Sciences University of Toronto Scarborough 2018 Abstract Projected climate change in the Toronto, Ontario, Canada area could greatly alter tree composition within the urban forest. Investigating biological change as a result of climate change is complicated due to the variability among climate model outputs and non-climatic influences on local vegetation. This study approaches the issues of composition change in tree species in Toronto through three interdependent studies. The first study is a comparison of Global Climate Models (GCMs) available through the Intergovernmental Panel on Climate Change's Fourth and Fifth Assessment Reports, AR4 and AR5 respectively. Using a performance metric based on how well the GCMs simulate climate relative to observation, GCMs GFDL- CM3, IPSL-CM5A-LR and MPI-ESM-LR were determined to provide the best Canada-wide coverage for annual average temperature and precipitation changes. The second study correlates a series of biologically-relevant climatic variables to tree distributions of 134 North American trees east of the 100th meridian. The geographical absence or presence of a species was correlated to concurrent climate data, creating a species' climate envelope. Using climate projections from an ensemble of the GCMs GFDL-CM3, IPSL-CM5A-LR and MPI-ESM-LR for the year 2050, a suite of statistical regression and machine-learning techniques were used to predict a likelihood of suitability of trees in the Toronto area based on the derived climate ii envelopes. While the dominant beech-maple communities are largely projected to stay intact, future climate suitability is likely to shift away from conifers and northern hardwoods into more southerly deciduous trees. The third study evaluates using projected tree suitability whether an assisted migration through the translocation of tree species would be effective in the Toronto area. Of particular interest is the increasing climate suitability that likely will be beneficial to Ontario’s Species at Risk trees. However, the conservation of Ontario’s Species at Risk trees cannot be based solely upon projections of climate, a vulnerability assessment conducted in this study indicate that current pest and diseases threats coupled with and the loss of genetic diversity are also cause for concern. iii Acknowledgments I would firstly and foremost I would like to thank my thesis supervisor, Dr. William A. Gough whom with utmost care and guidance directed me towards the completion of this doctoral degree. Additionally, I would like to thank to Dr. Jay Malcolm, who has introduced me to the concept of species modelling and to Dr. Adam Fenech who first motivated me to pursue doctoral studies and inspired many of the topics covered in this study. Furthermore, I would like to extend my thanks to Dr. Marney Isaac for her support and inspiration and Dr. Ken Butler and Dr. Mike Doughty, both who have offered me assistance in the implementation of statistical and GIS software. Finally, I would like to give special thanks to Elaine Pick and Shelley Eisner for their exceptional work in helping me complete all the required administrative duties required in this Ph.D. This work would not be possible without my family and friends, who with their undying patience been with me along this long and arduous journey. To them, thank you for understanding and your support; it is all I have ever asked for. Thank you. I would like to dedicate this work to my friends and colleagues in Sault Ste. Marie, located in the traditional territory of Baawaating. It is through your generosity that I have been able to apply what I have learned through my studies in order to fulfill my duties as a global citizen working towards the betterment of our collective lands and natural areas. iv Table of Contents Acknowledgments iv Table of Contents v List of Tables viii List of Figures ix List of Appendices xi Chapter 1 Introduction 1 1 Introduction 1 1.1 Defining the Problem – Climate Change and its Effects on Tree Species Biodiversity in Toronto 1 1.2 Defining the Study Area – Toronto’s Vegetative Communities 3 1.3 Urban Forests 4 1.4 Climate’s Role in Plant Geography 5 1.5 Climatic Controls on Vegetation 8 1.6 Climate Change and the Global Climate Models 9 1.7 Research Objectives 12 1.7.1 Research Objectives – Study 1 12 1.7.2 Research Objectives – Study 2 13 1.7.3 Research Objectives – Study 3 13 1.8 References 13 Chapter 2 A Comparison between Canadian Observational Data and the AR4 and AR5 Climate Models 19 2.1 Abstract 19 2.2 Introduction 19 2.3 Methods 23 2.3.1 Comparing the GCM to Observational Data 23 v 2.3.2 Obtaining an Observational Dataset 23 2.3.3 Creating an Ensemble 25 2.4 Results 27 2.5 Discussion 41 2.6 Conclusion 43 2.7 References 43 Chapter 3 Future Distributions of 134 Eastern North American Tree Species in Toronto resulting from Climate Change Scenarios RCP 2.6 and RCP 8.5 for the Year 2050 47 3.1 Abstract 47 3.2 Introduction 47 3.3 Methods 50 3.3.1 Tree Species Distribution Data 50 3.3.2 Study Area 52 3.3.3 Theoretical Assumptions 53 3.3.4 Statistical Assumptions 55 3.3.5 Statistical Models Implemented from BIOMOD2 55 3.3.5 Model Selection for Predicting a Species Likelihood Suitability 58 3.4 Results 60 3.5 Discussion 68 3.5.1 Comparing Statistical Techniques for Species Distribution Modelling 68 3.5.2 Modelling a Projected Reality 69 3.5.3 Realizing a Climate Equilibrium 71 3.6 Conclusions 72 3.7 References 73 Chapter 4 Street Tree Suitability in Toronto’s Urban Forest for Future Climate Change Scenarios and an Assessment of an Assisted Migration of Ontario’s Species at Risk Trees 79 4.1 Abstract 79 vi 4.2 Introduction 79 4.3 Methods 84 4.3.1 Predicting Tree Species Suitability as a result of Projected Climate Change 84 4.3.2 Generating Maps to Visualize Toronto’s Tree Distributions 85 4.4 Results 86 4.5 Discussion 97 4.5.1 Other Non-Climate Considerations 98 4.5.2 Implementing an Assisted Migration 99 4.6 Conclusion 101 4.7 References 102 5.0 Conclusions 106 5.1 Summary of Main Findings 106 5.2 Recommendations for Further Research 112 6.0 References 114 7.0 Appendices 126 vii List of Tables Table 2.1 – Relative Rank of AR4 GCMs for Average Annual Temperature and Precipitation based on an aggregate score…………………………………………………..………………….36 Table 2.2 – Relative Rank of AR5 GCMs for Average Annual Temperature and Precipitation based on an aggregate score…………………………………………………..………………….37 Table 3.1 – Percentage suitability for 134 Eastern North American tree species under climate change outcomes RCP 2.6 and RCP 8.5……………...………………………………………….60 viii List of Figures Figure 1.1 – Location of Toronto Ecodistrict 7E-4………………………………………………3 Figure 1.2 – Chart Visualization of Special Report on Emissions Scenarios (SRES) climate change scenario…………………………………………………………………………. ..........11 Figure 2.1 – Map of Canada showing the spatial resolution and NCEP observation points used for comparison of GCMs model output……………………………………………………….....25 Figure 2.2 – Map illustrating the differences between the AR4 Ensemble and the observational dataset (NCEP) for average annual temperature.………………………………………………...27 Figure 2.3 – Map illustrating the differences between the AR5 Ensemble and the observational dataset (NCEP) for average annual temperature …….…………….….................................…..28 Figure 2.4 – AR4 and AR5 GCM Averages for Annual Average Temperature per geographic region………………………………………………….…………….….................................…..29 Figure 2.5 – AR4 and AR5 GCM Averages for Annual Average Temperature per geographic region with outlier models removed…….… ……….…………….….................................…..31 Figure 2.6 – Map illustrating the differences between the AR4 Ensemble and the observational dataset (NCEP) for annual precipitation change………….…………….…..................................32 Figure 2.7 – Map illustrating the differences between the AR6 Ensemble and the observational dataset (NCEP) for annual precipitation change………….…………….…..................................33 Figure 2.8 – AR4 and AR5 GCM Averages for Annual Precipitaive Change per geographic region…….…………………………………...……….…………….….................................…..34 Figure 2.9 – AR4 and AR5 GCM Averages for Annual Precipitaive Change per geographic region with outlier models removed…………………...……...…….….................................…..35 Figure 3.1 – Location of areas selected to represent the Toronto area for species forecasts under climate change……………………………………………………………………………….…..52 Figure 3.2 – Ordination biplot showing the Eigenvalues of First (PC1) and Second (PC2) Principal Components based on tree species 2050 likelihoods for 134 Eastern North American Tree species under RCP 2.6 and RCP 8.5…………………………..……………….……….…..58 Figure 3.3 – Distribution of Likelihood Suitability in Eastern North American Tree Species in Toronto for Current Conditions and Future Climate Change ………………………….….…..66 Figure 4.1 – Toronto’s Most Populous Native Trees on Street Tree Allowances….…….….…..86 Figure 4.2 – Suitability
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