Forestry, Faculty of
DSpace
UBCV
Hu, Yi
Doctor of Philosophy - PhD
University of British Columbia
Poplars and willows are widely distributed in temperate ecosystems and are important woody crops, but their growth depends on adequate (and often replete) supplies of water and nitrogen. Nitrogen isotope discrimination (∆¹⁵N) have utility as an indicator of nitrogen-use in plants, and an isotope mass balance (IMB) model has been proposed to estimate the fluxes across root plasma membranes (E/I), the proportion of inorganic nitrogen assimilated in roots (Proot) and translocation of inorganic nitrogen to shoots (Ti/Tt) under steady-state conditions. Good correspondence between model-estimated E/I and compartmental analysis of tracer efflux has been demonstrated. In this thesis, the IMB model was further validated and then, after adjusting the ∆¹⁵N value of nitrate reductase (∆enzyme), used to explore intraspecific variation in nitrogen-use in black cottonwood (Populus trichocarpa Torr. & Gray) and heart-leaved willow (Salix eriocephala Michx.). To test the IMB model, I measured concentrations and δ¹⁵N of inorganic and organic nitrogen in xylem sap extracted from stems of black cottonwood provisioned hydroponically with nitrate. Direct determinations of Ti/Tt and Proot compared very favorably with IMB model-derived estimates. The difference in δ¹⁵N between organic-N and NO3̄ -N fractions in xylem sap (24.9‰) suggests a ∆enzyme of 25.1‰, which is higher than previously assumed by the IMB model, but close to recent estimates that average ~22‰. There was significant variation in nitrogen-use related traits in both poplar and willow. In heart-leaved willow, variation in δ¹⁵N, δ¹³C and C/N ratios indicated differences in nitrogen uptake and assimilation, WUE, and NUE. Clinal variation in δ¹⁵N was found in field and hydroponic experiments, possibly related to water availability. The absence of a trade-off between E/I, WUE, and NUE in willow suggests that additive variation in these traits can be captured without compromise. Variation in growth, R:S ratio, ∆¹⁵N, and C/N ratio was also found in black cottonwood, but biogeoclimatic correlations were not strong. The GWAS study using root and leaf ∆¹⁵N and other traits did not find significant genes related to nitrate transport or assimilation. There was one for root ∆¹⁵N and several for R:S ratio, which was in turn correlated with whole-plant ∆¹⁵N and E/I.
Testing, advancing, and applying an isotope mass balance model to investigate nitrogen uptake and assimilation in poplar and willow by Yi Hu B.S.F. Sichuan Agricultural University, 2013 M.Sc. Sichuan Agricultural University, 2015 A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY in The Faculty of Graduate and Postdoctoral Studies (Forestry) THE UNIVERSITY OF BRITISH COLUMBIA (Vancouver) May 2022 ©Yi Hu, 2022 ii The following individuals certify that they have read, and recommend to the Faculty of Graduate and Postdoctoral Studies for acceptance, the dissertation entitled: Testing, advancing, and applying an isotope mass balance model to investigate nitrogen uptake and assimilation in poplar and willow submitted by Yi Hu in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Forestry Examining Committee: Robert D. Guy, Professor, Department of Forest and Conservation Sciences, UBC Supervisor Shawn D. Mansfield, Professor, Department of Wood Science, UBC Supervisory Committee Member Barbara J. Hawkins, Professor, Department of Biology, University of Victoria Supervisory Committee Member Andrew Riseman, Professor, Centre for Sustainable Food Systems at UBC Farm, UBC University Examiner Christopher Chanway, Professor, Department of Forest and Conservation Sciences, UBC University Examiner Additional Supervisory Committee Member: Lee A. Kalcsits, Associate Professor, Department of Horticulture, Washington State University Supervisory Committee Member iii Abstract Poplars and willows are widely distributed in temperate ecosystems and are important woody crops, but their growth depends on adequate (and often replete) supplies of water and nitrogen. Nitrogen isotope discrimination (15N) have utility as an indicator of nitrogen-use in plants, and an isotope mass balance (IMB) model has been proposed to estimate the fluxes across root plasma membranes (E/I), the proportion of inorganic nitrogen assimilated in roots (Proot) and translocation of inorganic nitrogen to shoots (Ti/Tt) under steady-state conditions. Good correspondence between model-estimated E/I and compartmental analysis of tracer efflux has been demonstrated. In this thesis, the IMB model was further validated and then, after adjusting the 15N value of nitrate reductase (enzyme), used to explore intraspecific variation in nitrogen-use in black cottonwood (Populus trichocarpa Torr. & Gray) and heart-leaved willow (Salix eriocephala Michx.). To test the IMB model, I measured concentrations and δ15N of inorganic and organic nitrogen in xylem sap extracted from stems of black cottonwood provisioned hydroponically with nitrate. Direct determinations of Ti/Tt and Proot compared very favorably with IMB model-derived estimates. The difference in δ15N between organic-N and NO3--N fractions in xylem sap (24.9‰) suggests a enzyme of 25.1‰, which is higher than previously assumed by the IMB model, but close to recent estimates that average ~22‰. There was significant variation in nitrogen-use related traits in both poplar and willow. In heart-leaved willow, variation in 15N, 13C and C/N ratios indicated differences in nitrogen uptake and assimilation, WUE, and NUE. Clinal variation in 15N was found in field and hydroponic experiments, possibly related to water availability. The absence of a trade-off between E/I, WUE, and NUE in willow suggests that additive variation in these traits can be captured without compromise. Variation in growth, R:S ratio, 15N, and C/N ratio was also found in black cottonwood, but biogeoclimatic correlations were not strong. The GWAS study using root and leaf 15N and other traits did not find iv significant genes related to nitrate transport or assimilation. There was one for root 15N and several for R:S ratio, which was in turn correlated with whole-plant 15N and E/I. v Lay Summary Water and nitrogen frequently limit plant growth, and differences in water- or nitrogen-use efficiency are necessary for plants to adapt to environmental change over time and space. Adaptive trade-offs, however, may compromise one while optimizing the other. Isotope-based methods for estimating water-use efficiency are well established but the same is not true for nitrogen. I tested and adjusted a nitrogen isotope-based model that provides a new way to assess plant nitrogen-use traits. I applied the model to identify genetic variation in nitrogen uptake and assimilation in poplar and willow. In willow, I found that efficiencies of nitrogen uptake, water-use and nitrogen-use were not inter-correlated, suggesting that selection for these traits can occur without trade-off. Candidate genes for the nitrogen isotopic composition of roots and for root-to-shoot ratio were identified in poplar. Variation in the efficiency of nitrogen uptake may be linked to differences in root-to-shoot ratio in both species. vi Preface The research chapters of this thesis were (or will be) submitted as a series of manuscripts for peer-reviewed journals for publication purposes. For my role, I designed the hydroponic experiments and collected and analyzed the data for Chapters 2 and 3. The provenance trial utilized in Chapter 3 was designed by Dr. Raju Soolanayakanahally. For Chapter 4, I designed the last experiment (batch #9), did all the sample preparation, and collected and analyzed the data. Dr. Jaroslav Klápště provided bioinformatics assistance. For all research chapters, I took the lead in writing the draft manuscripts, in addition to all tables and figures. My supervisor, Dr. Robert Guy, assisted with experimental design, data interpretation and editing throughout all chapters. A version of Chapter 2 has been published as: “Hu Y, Guy RD. 2020. Isotopic composition and concentration of total nitrogen and nitrate in xylem sap under near steady-state hydroponics. Plant, Cell & Environment 43(9):2112-2123”. A version of Chapter 3 has been published as: “Hu Y, Guy RD, Soolanayakanahally RY. 2022. Genotypic variation in C and N isotope discrimination suggests local adaptation of heart-leaved willow. Tree Physiology 42(1):32-43”. A version of Chapter 4 will be submitted for peer-review publication as: “Genome-wide association study and identification of candidate genes for 15N in black cottonwood (Populus trichocarpa)”. vii Table of Contents Abstract ............................................................................................................................... iii Lay Summary ......................................................................................................................... v Preface ................................................................................................................................. vi Table of Contents ................................................................................................................ vii List of Tables ......................................................................................................................... x List of Figures ...................................................................................................................... xii List of Abbreviations ........................................................................................................... xvi Acknowledgements ...........................................................................................................xviii Dedication .......................................................................................................................... xix 1. Introduction and research objectives ................................................................................. 1 1.1 Nitrogen use and availability .................................................................................................1 1.2 Stable isotopes .......................................................................................................................2 1.3 Poplar and willow as model species ......................................................................................6 1.4 Impacts of N transport, remobilization, relocation and loss on 15N ....................................7 1.5 Model testing .........................................................................................................................9 1.6 Model application ............................................................................................................... 13 1.7 Research objectives ............................................................................................................ 16 2. Isotopic composition and content of total nitrogen and nitrate in xylem sap under near steady-state hydroponics ..................................................................................................... 17 2.1 Summary ............................................................................................................................. 17 2.2 Introduction ........................................................................................................................ 17 2.3 Material and Methods ........................................................................................................ 21 2.3.1 Plant material and experiment design ...................................................................... 21 2.3.2 Hydroponics system ................................................................................................... 23 2.3.3 Sampling and natural abundance isotope analysis ................................................... 24 2.3.4 Calculations ............................................................................................................... 26 2.3.4 Statistics ..................................................................................................................... 28 2.4 Results ................................................................................................................................. 29 2.4.1 Nitrogen concentration and 15N in xylem sap ......................................................... 29 viii 2.4.2 Estimated organic nitrogen concentration and 15N in xylem sap ........................... 30 2.4.3 Diurnal pattern in nitrogen isotope discrimination in xylem sap .............................. 34 2.4.4 Plant tissue discrimination and IMB model prediction .............................................. 37 2.5 Discussion............................................................................................................................ 41 2.5.1 Whole-plant and organ level variation in 15N.......................................................... 41 2.5.2 15N of total soluble organic N, NO3- and organic N of root tissue ........................... 42 2.5.3 N content and 15N-patterns of shoot xylem sap ........................................................ 43 2.5.4 Convergence of direct measurement and IMB model prediction .............................. 47 2.6 Conclusion ........................................................................................................................... 47 3. Genotypic variation in carbon and nitrogen isotope discrimination suggests local adaptation of heart-leaved willow (Salix eriocephala Michx.). .............................................. 49 3.1 Summary ............................................................................................................................. 49 3.2 Introduction ........................................................................................................................ 50 3.3 Methods .............................................................................................................................. 53 3.3.1 Common garden experiment ..................................................................................... 54 3.3.2 Hydroponic experiment ............................................................................................. 55 3.3.3 Carbon and Nitrogen Isotope analysis ...................................................................... 56 3.3.4 Calculations ............................................................................................................... 57 3.3.5 Statistics ..................................................................................................................... 58 3.4 Results ................................................................................................................................. 58 3.4.1 Common garden experiment ..................................................................................... 58 3.4.2 Hydroponics experiment ............................................................................................ 63 3.4.3 Genotypic differences ................................................................................................ 68 3.5 Discussion............................................................................................................................ 71 3.6 Conclusion ........................................................................................................................... 75 Chapter 4 Geographic variation in 15N of black cottonwood (Populus trichocarpa) and identification of candidate genes for isotope discrimination by genome-wide association .... 76 4.1 Summary ............................................................................................................................. 76 4.2 Introduction ........................................................................................................................ 77 4.3 Methods and materials ....................................................................................................... 80 4.3.1 Plant materials .......................................................................................................... 80 ix 4.3.2 Hydroponic system .................................................................................................... 82 4.3.3 15N phenotyping ....................................................................................................... 82 4.3.4 Geo-climatic patterns in 15N .................................................................................... 83 4.3.5 Heritability estimates and GWAS analysis ................................................................ 84 4.4 Results ................................................................................................................................. 86 4.4.1 Heritability of biomass and nitrogen related traits ................................................... 86 4.4.2 Correlation matrix ..................................................................................................... 93 4.4.3 Genome-wide association analysis ............................................................................ 96 4.5 Discussion............................................................................................................................ 99 4.5.1 Leaf discrimination is representative of whole-plant discrimination ........................ 99 4.5.2 Root-related traits show signals of local adaptation .............................................. 101 4.5.3 SNP associations to isotope discrimination and R:S ratio ....................................... 102 4.6 Conclusion ......................................................................................................................... 104 5. Conclusion ..................................................................................................................... 105 5.1 The N isotopic composition of xylem sap ......................................................................... 106 5.2 Intraspecific variation in carbon and nitrogen isotopic composition of heart-leaved willow ...................................................................................................................................... 108 5.3 Geographic variation in 15N of black cottonwood and identification of candidate genes by genome-wide association .................................................................................................. 110 5.4 Limitations and future application of the IMB model ...................................................... 111 References ........................................................................................................................ 114 Appendix – Supplemental measurements .......................................................................... 132 x List of Tables Table 2.1. Genotypes of black cottonwood (Populus trichocarpa) used in this study. .....………… 22 Table 2.2. Concentrations and 15N values of total N (Nt) and nitrate (Ni) in xylem sap collected from the shoots of three genotypes of Populus trichocarpa hydroponically grown with NO3-. Mean values (SE) are for four biological replicates, each representing pooled sap collected from 10 plants over the low pressure range. [Ni]/[Nt]xylem is the percent fraction of NO3- in the total N. Different letters indicate significant differences at P<0.05. ..……………………………………… 33 Table 2.3. Concentrations and 15N values of total N (Nt), nitrate (Ni) and organic nitrogen (No) in xylem sap collected from the shoots of five genotypes of Populus trichocarpa hydroponically grown with NO3-. Mean values (SE) are for five biological replicates, each representing pooled sap expressed from 10 plants over the 0-1 MPa range. Different letters indicate significant differences at P<0.05. ...……….…………………………………………………………………………………..………….… 36 Table 2.4 Percentages of NO3- (Ni) in total nitrogen (Nt) in xylem sap as directly measured after collection ([Ni]/[Nt]) or estimated percentage of inorganic nitrogen (Ti) relative to total nitrogen (Tt) translocated to the leaves (Ti/Tt) from the isotope mass balance (IMB) model for Populus trichocarpa genotypes grown under 0.5 mM NO3- for 45 days. Model predictions of Ti/Tt are given for calculations where discrimination () by nitrate reductase is taken to be either 15.4‰ or 25.1‰. Data are means±SE (n=5-10). Different individual ramets were used for sap collection and for model analysis. .………..……………………………………………………………………………..………………… 39 Table 3.1. Overall means of measured plant traits, and associated population effects from the common garden experiment. Traits measured or estimated include nitrogen percentage (N, %), carbon isotopic composition (13C, ‰), nitrogen isotopic composition (15N, ‰), the carbon to nitrogen (C/N) ratio of leaves and stems. ..……………………………………………………………………………… 60 xi Table 3.2. Pearson correlations (r) between geographic, climatic and physiological variables for all 21 genotypes in the hydroponic experiment. Bolding indicates significance at P<0.05; Bold* indicates significance at P<0.001. ……….……………………………….….……….……………………….……………. 66 Table 3.3. Canonical structure between geoclimatic parameters and plant traits with the first two canonical variables, CLIM1 and CLIM2. .…………………………………………..………….…………………… 67 Table 3.4. Overall means and ranges of measured plant traits, and associated genotype effects, in the hydroponics experiment. Traits measured or estimated include biomass (g), root-shoot ratio, carbon isotopic composition (13C, ‰) at organ and whole-plant (WP) levels, nitrogen isotope discrimination (15N, ‰) at organ and whole-plant levels, the ratio of inorganic to total nitrogen transported in the xylem (Ti/Tt), the proportion of plant nitrogen assimilated in roots (Proot), efflux/influx (E/I), and leaf and root assimilation activity (AC, mol mg dw−1). ….……..…. 69 Table 4.1. Overall genotypic means and ranges of whole-plant (WP) biomass, root-to-shoot (R:S) ratio, organ and whole-plant level nitrogen isotope discrimination (15N), and carbon to nitrogen ratio (C/N), and related broad-sense heritability estimates (H2) across Populus trichocarpa accessions. ..……….………………………………………………………………………………..…......…….. 88 Table 4.2. Population-wide relationships between nitrogen-related physiological variables and geo-climatic variables for Populus trichocarpa accessions. Bolding indicates significance at P<0.05; Bold* indicates significance at P<0.01. ………………………………………………………..…………….. 94 Table 4.3. Canonical structure between geoclimatic parameters and plant traits with the first two canonical variables, CLIM1 and CLIM2. …………………………………………….……………………………… 95 Table 4.4. Genes and their Arabidopsis thaliana (AT) homologs identified by GWAS with SNP markers associated with root-to-shoot (R:S) ratio, or both root 15N discrimination (15N) and the leaf-root difference in discrimination (15Nroot-leaf) in Populus trichocarpa. Information under “potential significance” comes from the online platform DICOTS PLAZA V4.5 except where otherwise indicated. …………………………..………………………………………………………………………………..... 97 xii List of Figures Figure 1.1. Diagram of plant nitrogen fluxes during the uptake of inorganic nitrogen from the substrate pool and assimilation into either root or leaf organic nitrogen as proposed in the isotope mass balance model. Arrows refer to unidirectional fluxes of nitrogen between leaf (green) and root (yellow) pools. To represents the organic nitrogen translocated to the leaves and Ti represents the inorganic nitrogen translocated to the leaves. Stem tissue is assumed to arise from a mixture of leaf and root organic pools. .................................................................. 12 Figure 2.1. Concentrations of total N (a) and nitrate (b), and 15N of total N (c) and nitrate (d) in Populus trichocarpa xylem sap collected from lower and upper shoot sections at low pressure and higher pressure. Bars or symbols represent means of six samples (SE; omitted from panel d because they are smaller than the symbol size). Effects of the main factors pressure or position, and their interaction, are indicated: n.s., not significant; *, P<0.05; **, P<0.01; ***, P<0.001. Dotted lines in panels c and d represent the 15N of NO3- in the hydroponic medium (-1.69‰). …..……………….………………………………………………………………………………………………………….… 31 Figure 2.2. Estimated concentration (a) and 15N (b) of organic N in xylem sap collected from lower and upper shoot sections at low pressure and higher pressure. Bars or symbols represent means of six samples (SE). The main factors pressure and position, and their interaction, were not significant (n.s.). Dotted line in panel b represents the 15N of NO3- in the hydroponic medium (-1.69‰). ………………………………………………..………………………………………………….………….… 32 Figure 2.3. Diurnal patterns in concentrations of total N (a), nitrate (b) and organic N (c), and 15N of total N (d), nitrate (e) and organic N (f) in xylem sap of Populus trichocarpa. Bars or symbols represent means of 10 samples (SE). Effects of the main factor time are indicated: n.s., not significant; *, P<0.05; **, P<0.01; ***, P< 0.001. Dotted lines in panels d, e and f represent the 15N of nitrate in the hydroponic medium (63.81‰). ………….……………..…….……… 35 xiii Figure 2.4. Whole-plant and organ level discrimination (15N) in five genotypes of Populus trichocarpa in Experiment 2. Shown are means±SE (n=5). Different letters indicate significant difference between genotypes at P<0.05..…………………………………………………………………….……….. 38 Figure 2.5. Model-derived efflux/influx (E/I, upper panel) and the proportion of nitrogen assimilated in the root (Proot, lower panel) of five genotypes of Populus trichocarpa. Empty bars are based on tissue 15N values assuming ∆enzyme is 25.1‰ (i.e., Proot predicted via Equations (2.7) and (2.10)) and solid bars are based on measurements of xylem sap N content (Proot measured from Equation (2.6)). Both estimates of Proot also rely on the same tissue N content data, so some autocorrelation is expected. Shown are means±SE (n=5). Different letters indicate significant differences between genotypes at P<0.05. ….….…………………………………………………………..…….…… 40 Figure 3.1. Locations of 34 populations of heart-leaf willow (Salix eriocephala) sampled from the natural range of the species across eastern and western Canada. Stars indicate the populations from which the 21 genotypes used in the hydroponics experiment were selected. The green shaded area represents the dominant continuous range of heart-leaved willow while the yellow shaded area shows the discontinuous range. .……………………………………………………….……………….. 56 Figure 3.2 The relationship between leaf carbon isotopic composition (13C) and leaf carbon to nitrogen (C/N) ratio of heart-leaf willow (Salix eriocephala) based on (a) population means (±SE) and (b) individual plants from the common garden experiment. .………………………………….……….. 61 Figure 3.3. Nitrogen isotopic composition (15N) and carbon isotopic composition (13C) of leaves and stems in heart-leaf willow (Salix eriocephala) (panels a&c and b&d, respectively) from common garden and hydroponic experiments (a&b and c&d, respectively) plotted against latitude of origin. Each point for the common garden data represents one population with 10 replicates, while each point for the hydroponic data represents one genotype with six replicates. Data are means±SE...……………………………………………………..…………………………..…………. 62 xiv Figure 3.4. Whole-plant nitrogen and carbon isotopic compositions (15N & 13C; panels a&b, respectively) plotted against latitude of origin in the hydroponic experiment. Each point represents one genotype with six replicates. Data are means±SE. .…………..……………………………. 65 Figure 3.5. Root efflux/influx ratio derived from the Isotope Mass Balance (IMB) model plotted against latitude of origin. Each point represents one genotype with six replicates. Data are means±SE. ...…………………………………………………………………………………………………………………………… 65 Figure 3.6. 3D scatter plot showing efflux/influx ratio (E/I), whole-plant carbon isotopic composition (13C) and whole-plant C/N ratio of the 21 genotypes used in the hydroponics experiment. Each dot represents the mean of six replicates per genotype. The STL-2 genotype is singled out for its combination of high 13C, high C/N, and low E/I. .……………….……………………… 70 Figure 4.1. Locations of 107 populations of black cottonwood (Populus trichocarpa) sampled from the natural range of the species in western North America, as shown in blue. The green area represents the dominant continuous range of the species. ..……………………………….……….… 81 Figure 4.2 Relationships between leaf isotope discrimination (15N) and whole-plant (WP) 15N (a), and root efflux/influx (b) in Populus trichocarpa accessions. Each point represents one genotypic mean with three replicates across batches 1-4 and 9 (n=209). .……………………………… 89 Figure 4.3 Relationships between root 15N and whole-plant 15N (a), and root efflux/influx (b) in Populus trichocarpa accessions. Each point represents one genotypic mean with three replicates across batches 1-4 and 9 (n=209). .……………………………………………………………….………… 90 Figure 4.4 Relationships between root-to-shoot (R:S) ratio and whole-plant (WP) 15N (a), and root efflux/influx (b) in Populus trichocarpa accessions. Each point represents one genotypic mean with three replicates across batches 1-4 and 9 (n=209). ..…………………………………………..… 91 xv Figure 4.5 Relationship between root-to-shoot (R:S) ratio and leaf, root and the leaf-root difference in nitrogen isotope discrimination (15N) in Populus trichocarpa accessions. Each point represents one genotype with at least three replicates across 9 batches (n=362). ..……… 92 xvi List of Abbreviations ADI annual dryness index AgCanSalix Agriculture Canada Salix CATE compartmental analysis of tracer efflux CONT continentality (°C) C/N ratio carbon to nitrogen ratio 13C carbon isotope composition (‰) 15N nitrogen isotope composition (‰) 15N nitrogen isotope discrimination (‰) EA-IRMS elemental analysis-isotope ratio mass spectrometer E/I efflux over influx FFP frost-free period (days) fleaf fraction of leaf nitrogen over plant nitrogen froot fraction of root nitrogen over plant nitrogen fstem fraction of stem nitrogen over plant nitrogen GC-IRMS gas chromatograph-isotope ratio mass spectrometer GS glutamine synthetase GS-GOGAT glutamine synthetase-glutamine oxoglutarate aminotransferase GWAS genome-wide association study HATS high affinity transport system H2 broad-sense heritability IMB model Isotope mass balance model LATS low affinity transport system xvii MAP mean annual precipitation (mm) MAT mean annual temperature MSP mean summer temperature from May to September (mm) MST mean summer precipitation from May to September (°C) MWMT mean warmest month temperature (°C) NiR nitrite reductase NR nitrate reductase NUE nitrogen use efficiency [Ni]xylem inorganic nitrogen concentration of xylem sap (mM) [No]xylem organic nitrogen concentration in xylem sap (mM) [Nt]xylem total nitrogen concentration of xylem sap (mM) Proot proportion of inorganic nitrogen assimilated in the roots R:S ratio root-to-shoot ratio SDI summer dryness index SNPs single nucleotide polymorphisms Ti/Tt percentage ratio of inorganic nitrogen relative to total nitrogen translocated to the leaves (%) WUE water use efficiency xviii Acknowledgements Foremost, I would like to express my deepest appreciation to my PhD supervisor Professor Robert Guy for his extraordinary support during my PhD study and this dissertation. Professor Guy is a mentor to me, not only because he guided me how to do research properly, but also provided me with encouragement and patience throughout the duration my journey. Finishing a PhD was never an easy task, especially for an international student, and I truly appreciate his help. I also would like to extend my sincere thanks to my supervisory committee members, Professor Barbara Hawkins, Professor Shawn Mansfield and Professor Lee Kalcsits, for their advice and suggestions on my experimental designs and this dissertation. I must also thank Dr. Raju Soolanayakanahally for his contributions to the willow field experiment in Chapter 3 and access to analytical services for isotope analysis in Chapter 4. I also wish to thank Dr. Mina Momayyezi, Dr. Alice Chang, and Dr. Shannon Guichon for their help with stable isotope measurements. I would like to acknowledge assistance from Ms. Melina Biron with building the hydroponic system in the greenhouse. I very much appreciate the help from Mr. Shofiul Azam for growing most of plant materials in Chapter 4, and the help from Dr. Jaroslav Klápště on the further bioinformatics assistance. Thanks also for funding from the Natural Sciences and Engineering Research Council of Canada (NSERC), the China Scholarship Council (CSC), Genome Canada and the Agriculture and Agri-Food Canada (AAFC) Research Affiliate Program. In the end, I would like to thank my family for their emotional support, especially to my wife Han Li. I feel very blessed to have you on my side over the years and I love you for the rest of my life. xix Dedication To the memory of my grandmother, Shuwen Liu. Although she was my inspiration to pursue my doctoral degree, she was unable to see my graduation. This is for her. 1 1. Introduction and research objectives 1.1 Nitrogen use and availability Nitrogen (N) is a critical component of proteins, DNA, and amino acids, and the fourth most abundant element found in organic matter. Nitrogen is the primary limiting nutrient for most plants growing in natural and agricultural ecosystems (Glass et al. 2002). To grow and compete under N-limiting conditions, plants have evolved to acquire different forms of N such as nitrate, ammonium, and even amino acids (Xu et al. 2012). Nitrogen dynamics vary climatically, and availability of different N forms is different between environments (Giesler et al. 1998). In temperate forests, total soil N can range from 0.05 to 1.65 Kg N m-2 (Callesen et al. 2007), while Marty et al. (2017) reported 0.42 to 1.26 Kg N m-2 in Canadian boreal forest soils. In modern agricultural production, nitrogen is a critical nutrient for plant growth. Total global N fertilizer in use today is more than eight times higher than it was at the start of the green revolution (1950s) (Wu et al. 2020). Although N fertilization has contributed to a doubling of the world’s crop production, a large portion of applied fertilizer is lost through leaching, volatilization or denitrification (Vitousek et al. 1997; Hirel et al. 2007), which has had negative impacts on the environment as well as causing economic burden in crop production. Improving plant N use efficiency not only reduces the environmental impacts of modern society, but also reduces overall fertilizer requirements, potentially making production feasible on marginal lands (Fageria and Baligar 2005). Plant nitrogen use efficiency (NUE) is determined by plant yield (biomass) relative to the amount of N applied. At the crop or whole-plant level, the efficiency of N uptake is one physiological process that may influence the overall NUE (Glass et al. 2003). 2 Nitrate and ammonium are the two most important inorganic N sources for plants. Both nitrate and ammonium have two major transport systems responsible for N uptake: high-affinity (HATS) and low-affinity (LATS) transport systems that are most effective at low or high N concentrations, respectively (Glass et al. 2002). It is possible under certain conditions for a substantial portion of the gross nitrate and/or ammonium uptake (influx) to return to the rooting medium (efflux) (Kronzucker et al. 1997; Hawkins and Robbins 2010). The ratio of efflux over influx (E/I) describes the bidirectional movement of inorganic N between root and rhizosphere but also relates to the N uptake efficiency; i.e., a low E/I indicates a high uptake efficiency because of less leakage of inorganic N back to the medium. Once retained by the root, nitrate must first be reduced to nitrite and then ammonium before it can be assimilated further. Nitrate is converted into nitrite in the cytoplasm by nitrate reductase (NR), and nitrite is converted to ammonium by nitrite reductase (NiR). Ammonium, whether directly taken up by root cells or produced from nitrate, is assimilated into glutamine by glutamine synthetase (GS). 1.2 Stable isotopes There are two stable isotopes of nitrogen (14N and 15N), with 14N being the predominant form (99.636% of total natural nitrogen). Variation in 15N between plants or N pools can provide both process and tracer information to understand N uptake and assimilation in plants, as well as N flux through ecosystems (Evans 2001; Robinson 2001). In the atmosphere, the relative ratio of 15N to 14N is virtually constant. However, due to their differences in atomic mass, the stable isotopes of N may show differences in rates of chemical reaction, or in physical processes, such as diffusion. Processes that change the relative abundance of 15N and 14N cause isotope fractionation. For example, during inorganic N assimilation, there is discrimination by the assimilation enzymes against the heavier isotope (15N) over the lighter isotope (14N), which results in 3 differences in relative abundance between the subtract and the product (fractionation). Small but easily determined differences in N isotope ratios are generally expressed in delta notation (15N, ‰) relative to the arbitrary standard, atmospheric N: 𝛅𝟏𝟓𝐍 = (𝑹𝐬𝐚𝐦𝐩𝐥𝐞/𝑹𝐬𝐭𝐚𝐧𝐝𝐚𝐫𝐝 − 𝟏) × 𝟏𝟎𝟎𝟎 where, Rsample and Rstandard are the 15N/14N ratios of the measured sample and arbitrary standard (0.00365, air N2), respectively. Substances with isotope ratios that are greater or lower than the reference ratio are 15N enriched or depleted, respectively (Peterson and Fry 1987). A similar expression yields 13C values that describe the 13C/12C ratio of any measured sample relative to a carbonate standard. The 13C of plant tissue is a widely employed indicator of carbon fixation pathway (e.g., C3 vs. C4 plants) and, within the C3 plants, is a temporally- and spatially-integrated proxy measure of photosynthetic water-use efficiency (Farquhar et al. 1982). In principle, variation in 15N could similarly provide temporally- and spatially-integrated information about the nature of N sources, and also the N relations of the plant. Foliar 15N reflects both isotopic composition of the soil N as well as the fractionations that occur during N uptake, assimilation, and reallocation inside the plant (Kalcsits and Guy 2013a). At very large scales, soil 15N tends to increase with increasing temperature and decreasing precipitation across spatial gradients (Amundson et al. 2003). However, global relationships between soil 15N and climatic variables are largely indirect and can be affected by other variables, such as soil depth (Hobbie and Ouimette 2009), soil age (Brenner et al. 2001), dominant plant species (Templer et al. 2007), and clay and carbon concentrations (Craine et al. 2015b). Soil pH is also an important factor affecting soil 15N, as arid soils tend to be alkaline and therefore susceptible to gaseous losses of ammonia (McCalley and Sparks 2009). Spatial and temporal variations in soil 15N make it difficult to interpret plant 15N in samples collected in field studies. Interpretation is 4 frequently not feasible even in greenhouse pot studies because, as plants grow, they may modify the isotopic composition of their source nitrogen, which in turn affects the isotopic composition of the plant. It is well recognized that changes in plant 15N occur during nitrate or ammonium assimilation causing plants to be depleted in 15N by about 2-3‰ compared to the soil N (Evans 2001). This difference implies that there is enzymatic discrimination against the heavier isotope, in either N transport or assimilation. It is now more than thirty years since the first reports of 14N/15N isotope effects associated with NR and GS measured in vitro using preparations from spinach leaves, yielding discrimination factors of ~15‰ for NR (Ledgard et al. 1985) and ~17‰ for GS (Yoneyama et al. 1993). However, under N-limited conditions, plant 15N was found to be close to the 15N values of soil inorganic N because both isotopes are assimilated to near completion (Mariotta et al. 1982; Evans 2001). There is greater fractionation when substrate concentrations are high, but rarely (if ever) does the 15N reflect the full discrimination factor of nitrate reductase or glutamine synthetase (Evans et al. 1996; Yoneyama et al. 2002; Pritchard and Guy 2005), indicating that assimilation is not the only step affecting fractionation. The enzyme discrimination factors noted above (15‰ and 17‰) are often assumed to be correct by authors working in the field but are, in fact, poorly constrained. More recent research has suggested greater discrimination for NR, ranging from 17-22‰ (Needoba et al. 2004, Liu et al. 2014; Cui et al. 2020), or even as much as 32‰ (Carlisle et al. 2014). Similarly, estimates of discrimination by GS have ranged from 16.5‰ to 29‰, depending on the external ammonium concentration (Yoneyama et al. 2001). It is important to note that all of the aforementioned NR and GS discrimination factors were measured in vitro, and the ranges obtained suggest that discrimination may not necessarily be the same, or constant, in vivo. Therefore, the development of a 5 direct non-destructive method to estimate discrimination factors for NR and GS in plants would provide essential clarity. There is also fractionation between plant parts. For example, several studies in both the laboratory and under field conditions have shown differences in 15N between roots and shoots (Dijkstra et al. 2003; Kalcsits and Guy 2013a; Kalcsits et al. 2015; Pritchard and Guy 2005), with shoots generally being 15N-enriched compared to roots. The differential allocation of nitrogenous compounds of differing isotopic composition causes differences in 15N between plant parts. For instance, during the process of nitrate reduction in roots, nitrate molecules left behind after reduction are 15N-enriched and available for translocation to shoots, which causes the difference in 15N between roots and shoots (Robinson et al. 1998; Evans 2001; Comstock 2001). Since ammonium is largely considered to be primarily assimilated in the roots instead of leaves (Raven and Smith 1976), less difference in 15N between roots and shoots is expected when plants are grown with ammonium than with nitrate, as observed in balsam poplar (Kalcsits et al. 2014) and trembling aspen (Populus tremuloides Michx.) (Kalcsits et al. 2015). Sites of assimilation do, however, vary between species (Gessler et al. 2000; Johnson and Berry 2013). For example, in conifers both nitrate and ammonium are mostly root-assimilated (Lupi et al. 2013). There are organ-level 15N differences between species consistent with this general observation. For example, leaf 15N was generally 2-4‰ heavier than the root 15N in the angiosperm trees European beech (Fagus sylvatica L.) (Peuke et al. 2006) and trembling aspen, whereas in the conifers lodgepole pine (Pinus contorta Douglas) and white spruce (Picea glauca (Moench) Voss) leaf and root 15N values were similar regardless of the inorganic N source (Kalcsits et al. 2015). Within-plant variation in N isotope composition in plants has also been reported in herbaceous plants such as barley (Hordeum vulgare L.) (Kolb and Evans 2003; Robinson et al. 2000), wheat (Triticale aestivum L.) (Yousfi et al. 2013) and rice (Oryza 6 sativa L.) (Yoneyama et al. 2001), and also in oil palm (Elaeis guineensis Jacq.) (Cui et al. 2020). Such root-shoot variation in isotopic composition, whether genetically based or environmentally induced, suggests that 15N values may also have potential to provide information about N transport and allocation. Kalcsits et al. (2013a) have used organ- and whole-plant 15N values in an isotopic mass balance (IMB) model to estimate integrated nitrogen-use traits, such as relative rates of root vs. leaf assimilation, fluxes across the root plasma membrane, and translocation of inorganic N to the shoot. 1.3 Poplar and willow as model species Unlike most crop plants, and the model plant Arabidopsis, trees differ fundamentally in being long-lived perennials of considerable height and size. The most obvious manifestation is the development of wood, or secondary xylem, from the vascular cambium (Taylor 2002). This makes trees particularly ideal for studying nutrient transport from roots to shoots, as xylem vessels are made of a series of dead cells (elements) that enable water and mineral conduction with minimal effect on composition occurring during transport over long distances. Also, by a variety of means, xylem sap can be collected from woody plants in decent quantity and with minimal contamination from other tissue types such as phloem (Schurr 1998). Black cottonwood (Populus trichocarpa Torr. & Gray) and heart-leaved willow (Salix eriocephala Michx.) are two widespread North American hardwood species in the Salicaceae family and of increasing interest in the development of suitable feedstock for bioenergy purposes and other applications. Black cottonwood exists across a broad range of climates, from the Pacific coast inland to the prairies, and from northern Baja California (Mexico) to the Kenai Peninsula (Alaska) (Farrar 1995). The heart-leaved willow has an even larger range across North America between 25°30 and 55°19 N latitude, including grassland and temperate and boreal forests (Brockman 1968). These 7 two species are good models to study adaptive patterns due to their wide range of habitats. Like many members of the Salicaceae, both species are easily propagated, have well-established and extensive genetic resources, and possess relatively small but well-characterized genomes (Djomo et al. 2011; McKown et al. 2014a, 2014b, 2014c, 2019; Murphy et al. 2021). Significant genotypic and population-wide variation in many phenology and ecophysiogical traits has been reported from common garden studies (McKown et al. 2014b, 2014c; Shunmugam et al. 2016). In black cottonwood, phenotypic traits such as bud-set phenology, photosynthesis rates, stomatal densities, etc., were correlated to geoclimatic variables (McKown et al. 2014b). Hundreds of genes underlying those phenotypic traits are implicated in local adaptation (McKown et al. 2014a, 2019). 1.4 Impacts of N transport, remobilization, relocation and loss on 15N Xylem and phloem transport have been studied for many years because of their dominant roles in long-distance signalling, and water and nutrient/assimilate delivery, from roots to shoots and vice versa. Xylem sap primarily contains nutrients obtained from the soil in raw form or assimilated into organic molecules, whereas phloem sap is much more viscous and contains sugars or other products of photosynthesis, as well as amino acids and proteins (Turgeon and Wolf 2009; Peuke 2010). Nitrate is the most common inorganic N form in the xylem sap, whereas ammonium is less common as it is assimilated mostly in the roots and there is little transported from roots to shoots (Tobin and Yamaya 2001). Since leaf N metabolism follows a diurnal pattern and isotope fractionations may be flux-dependent, xylem N profile and isotopic composition may also show diurnal patterns. In fact, Peuke et al. (2013) found significant diurnal variation in 15N in xylem sap of potted castor bean (Ricinus communis L.). However, physiological 8 interpretation of those results was limited by spatial, and possibly temporal, soil N heterogeneity. The remobilization of previously existing N may affect the isotope ratio of both source and sink organs, and this consideration may affect the accuracy and applicability of the IMB model. The origin of pre-existing N, or subsequent isotope effects associated with biochemical processing, can result in fractionation. For example, for scions used to vegetatively propagate poplar plants, ~50% of the N contained within the original scions was remobilized to support the growth of the new plant (Kalcsits and Guy 2013b). Moreover, if the isotopic signatures between media sources and pre-existing N differ significantly (>2‰), the pre-exiting N could affect the IMB model output if it is not properly accounted for (Kalcsits and Guy 2013b). Similarly, in woody perennials, N from senescing leaves is remobilized to stem tissues during autumn to be re-used by developing tissues the following spring (Malaguti et al. 2001). During active growth, N can be distributed via the phloem to growing sinks, such as roots, soon after it is assimilated in the leaves, just as N assimilated in the roots may be translocated to the shoots in organic form within the xylem. The IMB model predicts the latter but ignores the former. Since N remobilization through phloem is often related to senescence or abiotic stress, the IMB model assumes that phloem N transport from shoot to root is negligible when young plants are growing rapidly under hydroponic conditions. Nitrogen loss from the roots or the shoots can affect plant 15N if it is (1) lost in significant quantities and/or (2) the 15N of N lost from the plant strongly deviates from the bulk whole-plant 15N (Kalcsits et al. 2014). Root organic N may be lost through exudation, which occurs in many plant species under many conditions and contributes to improved bioavailability of macro and micronutrients (Johnson et al. 1996, Dakora 9 and Phillips 2002). Robinson et al. (1998) suggested that exudation of enriched organic N causes roots to have lower 15N than leaves. Root exudates, however, generally represent a small fraction of the total plant nitrogen budget, and given the wide range of nitrogenous compounds and their isotopic differences, the calculated impact on root δ15N is small (Kalcsits et al. 2014). Similarly, nitrogen lose from leaves through the volatilization of NH3 gas during the process of photorespiration might increase the 15N of leaves relative to roots. Schjoerring and Mattson (2001) reported 1–4% of shoot nitrogen was volatilized as NH3 from a variety of crop plants which, in combination with the observation that fractionation associated with NH3 volatilization from NH4+ is as much as 40‰ (Mariotti et al. 1982). Importantly, however, most of this loss occurred during senescence, which can be avoided as mentioned above. Johnson and Berry (2013) estimated the isotope fractionation associated with volatilization of NH3 from leaves of actively growing plants was minimal (i.e. <1‰) when stomatal conductance was high and temperatures were below 25 °C. 1.5 Model testing Kalcsits and Guy (2013a, 2016a) took two different approaches to assess the validity of the IMB model. The first approach was to examine N isotope discrimination in nitrate reductase 2 (nia2), nitrate reductase 1 (nia1) and nitrate transporter (nrt2) knockout mutant lines of Arabidopsis thaliana. A greater difference in 15N between leaf and root was found in the NR knockout lines, indicating changes in the site of nitrate assimilation between leaf and root. Application of the IMB model suggested that the nia2 line had an increased proportion of assimilation in leaves while the nia1 line had an increased proportion of assimilation in roots, consistent with known ratios of wild-type NIA1 and NIA2 gene expression levels. Higher whole-plant 15N was found in the nrt2 line suggesting more efflux of unassimilated nitrate back to the rooting medium, 10 possibly resulting from decreased symplastic intercellular movement of nitrate within the root. In the second approach, the IMB model was tested by comparing it to compartmental analysis of tracer efflux (CATE) using stable isotope tracing to determine N efflux/influx (E/I) in balsam poplar roots. Both methods suggested E/I was much higher when plants were supplied with 0.5 mM ammonium rather than 0.5 mM nitrate. However, E/I was estimated to be approximately 33-50% lower when using the CATE method. The CATE method indicated that E/I averaged 0.4 and 0.22 for ammonium and nitrate, while the IMB model estimated E/I to be 0.65 and 0.45, respectively. The authors suggested that these discrepancies could have been caused either by temporal differences in N uptake patterns, or by the use of discrimination factors that were too low in the IMB model. When the discrimination factor for the assimilatory enzymes was increased to 22‰, there was much better concurrence between E/I estimated by CATE and by the IMB model, suggesting that discrimination factors for NR and GS may currently be underestimated. Nitrate that is not lost in efflux is either assimilated in the roots or translocated to shoots through the xylem (Cui et al. 2020), in whole or in part (Figure 1.1). Several authors have suggested that measurements of 15N values in xylem sap would be valuable (Raven 1987; Robinson 2001; Kalcsits et al. 2014). For example, if xylem nitrate were to have the same isotopic composition as source nitrate provided to the roots, then the clear implication would be that there is either no discrimination in vivo or no assimilation in the roots. On the other hand, if xylem sap were to contain unassimilated but enriched nitrate, then there must be discrimination during partial assimilation in the root. The IMB model, at its core, predicts the N isotopic composition of xylem sap under these conditions. Therefore, a key test of the model is to investigate the isotopic composition of inorganic and organic N forms in xylem sap under conditions expected to 11 influence N assimilation and allocation in particular ways. Because xylem loading of organic and inorganic nitrogen occurs continuously in the roots, xylem sap analysis should constitute a proxy sampling of the instantaneous product and remaining substrate during nitrate assimilation in the roots. If so, the difference in isotopic composition between organic N and nitrate would approximate the discrimination factor associated with NR. Therefore, in the first part of my thesis, I set out to measure the 15N values of organic and inorganic N in the xylem sap as a critical test of the IMB model. If the IMB model prediction is correct, the 15N difference between inorganic and organic N in xylem sap should be greater than or equal to ~15‰. As a further test, the IMB model also predicts the proportions of N translocated in organic and inorganic form, which should be equal to the ratio of the organic and inorganic N concentrations measurable within the xylem sap. 12 Figure 1.1. Diagram of plant nitrogen fluxes during the uptake of inorganic nitrogen from the substrate pool and assimilation into either root or leaf organic nitrogen as proposed in the isotope mass balance model. Arrows refer to unidirectional fluxes of nitrogen between leaf (green) and root (yellow) pools. To represents the organic nitrogen translocated to the leaves and Ti represents the inorganic nitrogen translocated to the leaves. Stem tissue is assumed to arise from a mixture of leaf and root organic pools. 13 1.6 Model application Following model validation and refinement, the IMB model can be used on a grander scale. Species with large natural habitats may encounter divergent selection pressures because of wide variation in environmental factors, such as temperature, precipitation, growing season length, photoperiod, and soil nutrient conditions, resulting in environment-correlated intraspecific variation (Eckert and Dyer 2012; McKown et al. 2014a). Study of particular traits and how they vary can be used to examine the evolution of these traits and test adaptive hypothesis. For example, nitrogen and water are usually the most limiting resources for plants in temperate and boreal ecosystems; consequently, selective pressure towards maximization their respective use efficiencies is expected (Weih et al. 2006). Though much is known about biogeographic variation in forest trees, there have been fewer studies focusing on N isotope discrimination, and clearly this area needs further research. Kalcsits and Guy (2016b) found significant genetic variation in N isotope discrimination in balsam poplar grown hydroponically, both within and between populations. There was no particular biogeographic pattern with provenance of origin, but only a very limited number of populations were sampled (just five). Genotypic variation within populations exceeded variation between populations. They also found that whole-plant N isotope discrimination of nitrate- and ammonium-grown plants was correlated across genotypes, implying that the genetic variation in 15N was affected by additional factors that are not N-source specific (e.g., such as root-to-shoot [R:S] ratio). There is a gap in knowledge between measurement of N-use under controlled conditions that limits the extension of results to field conditions. For instance, a large common garden assessment of phenotypic trait variation in black cottonwood reported 0.08 broad-sense heritability in leaf 15N, suggesting very little inherent variation in 15N 14 (McKown et al. 2014). Although this study assessed 461 genotypes from 136 provenances, the level of genetic variation in 15N was much lower than observed by Kalcsits and Guy (2016b), which is likely attributable to spatial variation in soil 15N and, most importantly, the fact that whole-plant discrimination cannot be expressed if the utilization of available soil N approaches completion (i.e., if unused N cannot diffuse away from the roots before being consumed). Therefore, assessment of plant 15N using a decent number of genotypes from multiple provenances under tightly controlled hydroponic conditions is needed. Both the efficiency of N use (NUE, carbon fixed per unit N assimilated) and the efficiency of water use (WUE, carbon fixed per unit water transpired) are tied to the diffusion gradient for CO2 into the leaf through stomata. Most water used by plants is in support of photosynthesis by way of transpiration. More than half of total leaf N is related to photosynthesis (Evans 1989), and total leaf N content and photosynthetic capacity are typically correlated (Field and Mooney 1986, Larcher 2003). Reductions in stomatal conductance (gs) or higher investments in foliar N can result in higher WUE if the CO2 diffusion gradient steepens, but lower intercellular CO2 concentrations may reduce NUE by reducing rates of C fixation per unit N. A negative correlation between WUE and NUE is implied, suggesting an evolutionary trade-off. However, changes in mesophyll conductance (gm) should impact WUE and NUE similarly and without trade-off because, in contrast to gs, there is no effect of gm on the diffusion of water vapor (Lauteri et al. 1997). Variation in sites of N assimilation and allocation within plants might also uncouple NUE from WUE, but in more indirect ways. For example, in Populus, when under N-limiting conditions, both fast- and slow-growing hybrids showed increased root surface area, decreased photosynthetic rate, and reduced NUE (Luo et al. 2015). The slow-growing hybrid (Populus × popularis) had an increased WUE, while the fast-growing hybrid (Populus alba × Populus glandulosa) had a decreased WUE. Because 15 similar differences may occur within species, it is unclear if a trade-off between WUE and NUE should be expected among locally adapted populations. Therefore, in this thesis, genotypic and population-level variations in 15N, 13C (proxy for WUE), and C/N ratio (proxy for NUE) were explored from both common garden and hydroponics experiments. Though very fundamental, our understanding of N uptake and assimilation is still incomplete, especially for trees. Uncovering the molecular and physiological basis for these complex traits is critical for breeding programs. In poplars, as well as other species of dual ecological and economic importance, there is great interest in establishing links between relevant phenotypes and genetic variation (Ingvarsson and Street 2010; McKown et al. 2018). Genome-wide association studies (GWAS) are widely used for this purpose and, in Populus, have implicated numerous genes in the control of various wood characteristics (Porth et al. 2013), stomatal patterning and bud-break phenology (McKown et al. 2014, 2018, 2019), which may contribute to local adaptation (Savolainen et al. 2013). Plant NUE is an inherently complex trait and GWAS in NUE-related traits has been widely used in crop plants, such as rice (Oryza sativa L.) (Tang et al. 2019), maize (Zea mays L.) (Ertiro et al. 2020), and barley (Hordeum vulgare L.) (Karunarathne et al. 2020). Associations with several high affinity nitrate or ammonium transporters were reported in these studies. So far, GWAS on 15N has been limited to black cottonwood (McKown et al. 2014) and at least three studies investigating soybean (Glycine max (L.) Merr.) (Dhanapal et al. 2015; Steketee et al. 2019; Bazzer et al. 2020). As expected, no significant associations were found for black cottonwood given that the trees were field-grown (as noted earlier). In contrast, numerous SNP associations have been found in soybean, despite also being field-grown (broad sense heritability of tissue 15N in soybean was 0.15 to 0.2). Soybean, however, is a N-fixing legume and, as such, plant 15N provides a measure of the amount of N obtained directly from the atmosphere 16 relative to what is taken up from the soil. To date, no GWAS has been published on 15N-related traits obtained on plants grown hydroponically. Furthermore, the many GWAS conducted on crop plants have not generally been done in the context of exploring the genetic underpinnings of natural biogeographic variation in N-use traits and the possibility of local adaption. 1.7 Research objectives For my thesis, the research objectives were: 1. Determine a time-integrated estimate of inorganic and organic nitrogen concentration and isotope composition in xylem sap 2. Explore intraspecific variation in isotopic composition of heart-leaved willow and black cottonwood 3. Apply GWAS with hydroponically grown black cottonwood to detect nitrogen isotope-related SNPs and genes 17 2. Isotopic composition and content of total nitrogen and nitrate in xylem sap under near steady-state hydroponics 2.1 Summary After root uptake, nitrate is effluxed back to the medium, assimilated locally, or translocated to shoots. Rooted black cottonwood scions were supplied with a NO3--based (0.5 mM) nutrient medium of known 15N, and xylem sap was collected via a pressure bomb. To establish a sampling protocol, sap was collected from lower and upper stem sections at 0.1-0.2 MPa above the balancing pressure and after increasing the pressure by a further 0.5 MPa. Xylem sap from upper stem sections was partially diluted at higher pressure. Further analysis was restricted to sap obtained from intact shoots at low pressure. Total-, NO3--N and, by difference, organic-N concentrations ranged from 6.1-11.0 mM, 1.2-2.4 mM, and 4.6-9.4 mM, while discrimination relative to the nutrient medium was -6.3 to 0.5‰, -23.3 to -11.5‰, and -1.3 to 4.9‰, respectively. There was diurnal variation in 15N of total- and organic-N, but not NO3-. The difference in 15N between xylem NO3- and organic-N suggests that discrimination by nitrate reductase is near 25.1±1.6‰. When this value was used in an isotope mass balance model, the predicted xylem sap NO3--N to total-N ratio closely matched direct measurement. 2.2 Introduction Nitrogen is the primary limiting nutrient for most plants in terrestrial ecosystems (Glass et al. 2002). The various forms and pools of N in the environment, and in the plant, typically have differences in the relative abundance of 15N (15N). These differences in isotopic composition are widely used in the study of N cycling in ecosystems and individual organisms (Dawson et al. 2002). However, interpretation of 18 variation in 15N at natural abundance levels can be problematic. For example, the 15N of an individual plant or one of its parts is not only determined by the external N source, of which there is often more than one, but also by internal physiological factors such as different N uptake mechanisms, different pathways of assimilation and transport, and the possibility of differential recycling of N within the plant, all of which may discriminate against 15N (Robinson 2001). A better understanding of isotope discrimination that may or may not be associated with these various factors is needed before variation in 15N can be routinely used in ecological and/or physiological research. Nitrogen sources in soils include nitrate, ammonium, and organic N. These are distributed unevenly in time and space in varying proportions that depend on profile position, local vegetation, climate, and many other edaphic factors (Amundson et al. 2003). For example, boreal forest soils generally have less inorganic N than temperate forest soils because of colder temperatures and slower rates of mineralization (Näsholm et al. 1998). Furthermore, because they are often acidic, boreal forest soils tend to have higher concentrations of ammonium than nitrate (Nordin et al. 2001). In contrast, temperate forest soils are relatively rich in nutrients with higher concentrations of nitrate (Lupi et al. 2013). Both nitrate and ammonium are taken up by roots, but nitrate must be converted to ammonium prior to assimilation into organic N. Nitrate enters root cells by diffusion or via a nitrate transporter across the plasma membrane and may then be converted to nitrite and then ammonium in the cytoplasm by NR and NiR, respectively. Therefore, the ammonium derived from nitrate is assimilated by GS. Both of the initial assimilatory enzymes (i.e., NR in the case of nitrate, and GS in the case of ammonium) have considerable potential to affect plant 15N because they discriminate against 15N relative to 14N. Discrimination causes the product organic N to be depleted in 15N relative to the original source, while the remaining unassimilated inorganic N 19 becomes enriched. Discrimination factors for GS and NR are poorly constrained, but have long been considered to be ~17‰ and ~15‰, respectively (Yoneyama et al. 1993; Ledgard et al. 1985). Other research, however, suggests that discrimination by NR is greater than 15‰, in the range of 19-22‰ (Yoneyama 2003; Needoba et al. 2004), or possibly even higher (Olleros-Izard 1983; Karsh et al. 2012). After uptake, neither the assimilation of nitrate nor the assimilation of ammonium is quantitative. Unassimilated inorganic N (enriched in 15N) either effluxes back into the rooting medium or is transported to the shoot together with organic N (Kalcsits and Guy 2013a). Efflux can be substantial, ranging from 19% to 79% of N initially taken up, depending on the substrate concentration, root maturity, and plant N demand (Kalcsits and Guy 2016a). Because effluxed N is enriched in 15N, this process can cause plants to have total tissue, whole-plant 15N values that are negative relative to the source. Differential xylem transport of 15N-depleted organic N and 15N-enriched inorganic N can cause variation in 15N to occur at the organ level (e.g., between roots and shoots). These differences are affected by the form of the source N (Kalcsits et al. 2015). Subsequent retranslocation and/or N losses associated with senescence, volatilization, or other processes may also cause variations in tissue 15N (Robinson et al. 1998). Few connections between nitrogen-use physiology and nitrogen isotope discrimination have been established. Kalcsits and Guy (2014 & 2016b) presented an isotope mass balance (IMB) model that combines 15N ratios and tissue N contents. Net discrimination was suggested to be a function of inorganic N efflux back to the growing medium relative to gross uptake at the root (efflux/influx), the proportion of net uptake assimilated in the roots, and the export of remaining N for assimilation in the leaves. This deliberately simple model attempts to explain the relationship between N-use physiology and N isotope discrimination under steady-state hydroponic conditions in 20 young, rapidly growing plants where there is substantial N assimilation in the roots and there has been little opportunity for N remobilization between organs (e.g., from senescent tissues). Similarly, under these specific conditions, the return of N to the roots in either inorganic or organic form is of little consequence to the plant or organ level N budget and is ignored. However, Cui et al. (2020) have recently argued that the return of residual, unassimilated 15N-enriched nitrate back to the roots via phloem transport can be isotopically significant in oil palm and sunflower, two species where N assimilation is primarily in the leaves. Since there is no evidence for significant isotope discrimination associated with membrane transport (Handley and Raven 1992; Evans 2001), the IMB model considers the cytosolic and vacuolar nitrate pools within root cells to be in isotopic equilibrium, and similarly, that there is no discrimination during xylem loading. Furthermore, unless roots are damaged and the endodermis is breached, all nitrate entering the xylem must pass through some portion of the symplast. Under the above conditions, xylem sap analysis should constitute a proxy sampling of the 15N of instantaneous product and residual substrate remaining during nitrate assimilation by nitrate reductase, and thus the difference in isotopic composition between organic nitrogen and nitrate would approximate the discrimination factor associated with nitrate reductase. I set out to test this hypothesis in rooted black cottonwood scions given access to a very large nitrate supply at a realistic concentration (0.5 mM). Cottonwoods are ideal to our purposes because of their rapid growth, woody stems to yield relatively high volumes of xylem sap free of contamination from phloem, propensity for root-based N assimilation (Dluzniewska et al. 2006), and their use of glutamine as the main constituent of organic N in xylem transport (Escher et al. 2004; Millard et al. 2006). My first objective was to validate my xylem sap collection protocol; i.e., by testing the effects of collection pressure and sampling position on xylem sap composition. The second objective was to quantify the concentration and isotopic 21 composition of inorganic and organic N in xylem sap and explore possible diurnal variation. Towards validation of the IMB model, my third objective was to compare direct measurement of xylem sap nitrate- and organic-N concentrations with model predictions. 2.3 Material and Methods 2.3.1 Plant material and experiment design First year scions from black cottonwood genotypes (Table 2.1) originally collected by the British Columbia Ministry of Forests, Lands and Natural Resource Operations were obtained in early February from a stool bed at Totem Field, University of British Columbia (UBC), Vancouver, Canada. My reasoning to in include different genotypes of black cottonwood from a large part of its natural range was to ensure that results would be reasonably representative of the species as a whole. Scions were stored in black plastic bags at 4°C for 4 months until used in two experiments. Single-node scions, approximately 3 cm long, were rooted in distilled water and then transferred to a hydroponic system in the UBC Horticulture greenhouse. The first experiment used three genotypes with 20 rooted scions per genotype to test the influence of sampling position (lower and upper shoot sections)1 and xylem sap collection pressure (0-1 and 1-1.5 MPa) on xylem sap N concentration and 15N. Different sampling positions were used to check the stability of the xylem sap composition along the transport pathway. The second experiment, employing five genotypes with 25 rooted scions per genotype, was performed to check for possible diurnal patterns in xylem sap N concentration and 15N, 1 Xylem sap from decapitated root systems was similarly collected but found to be contaminated with hydroponic solution (see Appendix Figure A.1). 22 and to compare these measured quantities with model predictions from plant tissue analysis. Table 2.1. Genotypes of black cottonwood (Populus trichocarpa) used in this study Genotype Latitude (N) Longitude (W) Elevation (m) BELA4a,b 52.42 126.17 152 CARS2a 45.75 122.83 650 CARS4b 45.75 122.83 650 FNYI4b 49.52 124.85 46 HALS2b 44.42 123.33 300 STHA3b 50.82 124.48 239 NECA4a 54.10 124.43 747 First four letters are the abbreviation for provenances and the last number are the genotype replicates within the provenance; a,b indicates genotypes included in experiment one (a) or two (b). 23 2.3.2 Hydroponics system The hydroponic system was comprised of four 150 L bench-mounted acrylic tubs, an 1800 L vertical ground tank (RK400; CANWEST, Surrey, Canada), two water pumps (Little Giant, Fort Wayne, IN, USA) and connecting PVC piping (1 inch diameter; WaterTec, Langley, BC, Canada). Each tub was covered by a floating “raft” made of dense foam bolted between black (lower) and white (upper) sheets of Perspex. Drilled holes (2.5 cm) fitted with partially slit foam plugs provided each raft with the capacity to hold up to 32 plants. One water pump sat in the bottom of the main tank and continuously circulated media to the four tubs. The depth of water in the tubs was set by an overflow outlet draining by gravity into a receiving reservoir at ground level containing the second pump (actuated by a float switch), which returned the media to the main tank. The total volume of the system was maintained at 2000 L. Unused plugs in rafts and other exposed parts of the circulation system were covered with white/black (upper/inner) plastic to prevent algal growth from light infiltration. The hydroponics solution was a modified 1/10th strength Johnson’s solution (Johnson et al. 1957) supplemented with 0.25 mM Ca(NO3)2. To ensure aeration of the entire system, an air pump was connected to an air stone in the receiving reservoir. Media NO3- concentration was assayed periodically using the perchloric acid (Cawse 1967) method. The intent was to ensure there was no substantial decrease (no more than 10%) in NO3- concentration over time that could result in major changes to the δ15N of the hydroponics solution. The nutrient medium was completely replaced as necessary. The system was under ambient light conditions supplemented by LED lighting (600 µmol m-2s-1) on an 18/6 h day/night photoperiod. Temperatures in the greenhouse were maintained between 20-24°C to prevent overheating of the hydroponic solution, a 10 m cooling coil of ¼ inch stainless steel pipe was submersed in the main reservoir. Cold tap 24 water flowed through the coil under the control of a thermostated solenoid valve (Red-Hat, Brantford, ON, Canada). 2.3.3 Sampling and natural abundance isotope analysis Experiment 1: Plants were grown hydroponically for 45 days before sampling. Sap was collected from 9:00-12:00 and 15:00-19:00 to avoid a period of reduced sap yield when water potential was lower during mid-day. To test the effect of sampling position on the nitrogen concentration and isotopic composition in the xylem sap, shoots were cut 0.5 cm above the root collar and then cut in two in the middle of the remaining section to provide two parts for pressure bombing: upper and lower shoot/stem sections. Stems were stripped of bark (~1 cm) near the cut end and placed into the pressure vessel of a 3005 Series Plant Water Status Console (Soilmoisture Equipment Corp., Goleta, CA, USA). The distal ends of lower stem sections were sealed with Blu Tack putty adhesive (Bostik, Paris, France) to prevent the direct entry of air, and the resulting loss of pressurization and loss of sample caused by sputtering and aspiration (presumably because larger, continuous vessels discharge readily, while most others do not). Xylem sap was collected as described in Dluzniewsk et al. (2006), where the pressure was raised to ~0.6-0.7 MPa higher than the initial balancing pressure (~0.8-0.9 MPa), but in two stages. In the first, low pressure stage (LP), the initial drop of water was discarded to avoid contamination and the pressure was increased to 1.0 MPa; i.e., by an increment of just 0.1-0.2 MPa. In the second, higher pressure stage (HP), additional sap was collected as the pressure was raised from 1.0 to 1.5 MPa. There were 60 plants in total, but samples were pooled from 10 individuals to provide enough volume for analysis (i.e., n = 6 for each shoot part). Sap samples were stored at -20°C until analysis. 25 Experiment 2: After 45 days of growth, xylem sap was collected from intact (i.e., unsegmented) shoots at five time “points” over a diurnal cycle (i.e., 1.5 h collection periods centered on 10:00, 15:00, 20:00, 0:00 and 4:00 h). Sap was collected from a total of 125 plants, but pooled from five individuals per genotype at each time point, yielding 25 samples for analysis. After the xylem sap was collected, plants were partitioned into leaves, stems, roots and original scions, and stored on ice until freeze-drying at -50°C for two days. Once dried, these plant parts were weighed and then ground to a fine powder using a Wiley mill followed by pulverization in a stainless-steel ball mill (Fritsch Laborgeratebau, Terochem Scientific, Ottawa, Canada). Sub-samples (3 mg) were packed into tin capsules (Elemental Microanalysis, Devon, UK) and analyzed for nitrogen concentration and 15N using an Elementar (Langenselbold, Germany) Vario EL Cube Elemental Analyzer (EA), in combination with an Isoprime (GV Instruments, Manchester, UK) Isotope Ratio Mass Spectrometer (IRMS) in the Stable Isotope Facility (SIF), Faculty of Forestry, UBC. Aliquots of xylem sap (1 mL) were dried onto glass microfiber filter disks (Whatman GF/D) and analyzed for total nitrogen concentration and 15N as above. Additional 1 mL aliquots were used to analyze the concentration and 15N of nitrate after conversion to nitrous oxide (N2O) by the bacterial denitrifying method (Sigman et al. 2001). Denitrifying Pseudomonas aureofaciens (American Type Culture Collection #13985; Manassas, VA, USA) was incubated for 7 days in a working medium of Tryptic Soy Broth (Difco) amended with KNO3, NH4Cl, and KH2PO4 according to the method described by Casciotti et al. (2002) and Altieri et al. (2014). Before use, P. aureofaciens cells were concentrated by centrifugation (7500g, 18°C), and washed and resuspended in NO3--free medium (4 mL). After sparging with N2, 2 mL of suspension and 1 mL of xylem sap were injected into a 10 mL crimp-sealed vial. Vials were incubated overnight at room temperature to allow for complete conversion of NO3- to N2O before the 26 addition of 0.2 mL NaOH to stop the bacterial activity and scavenge CO2. Incubated vials could be stored at -20°C for up to 5 days. The yield of N2O was measured by injecting 2 mL of the headspace gas into a trace gas chromatograph (HP5890 Series II, Agilent, Santa Clara, CA, USA) equipped with an electron capture detector (GC/ECD). For 15N determination, remaining N2O in the headspace was cryofocused using a manually built purge-and-trap system (Ribas-Carbo et al. 2002) and introduced into a gas chromatograph (HP6890N, Santa Clara, CA, USA) interfaced to the same Isoprime IRMS. 2.3.4 Calculations Nitrogen isotopic composition (15N) and isotope discrimination () are expressed as: 𝛅𝟏𝟓𝐍 = (𝑹𝒔𝒂𝒎𝒑𝒍𝒆𝑹𝒔𝒕𝒂𝒏𝒅𝒂𝒓𝒅 − 𝟏) ∗ 𝟏𝟎𝟎𝟎 (2.1) ∆𝟏𝟓𝐍𝒔𝒂𝒎𝒑𝒍𝒆 =(𝛅𝟏𝟓𝐍𝒔𝒐𝒖𝒓𝒄𝒆−𝛅𝟏𝟓𝐍𝒔𝒂𝒎𝒑𝒍𝒆)(𝟏+𝛅𝟏𝟓𝐍𝒔𝒂𝒎𝒑𝒍𝒆𝟏𝟎𝟎𝟎) (2.2) where, Rsample and Rstandard are the 15N/14N ratios of the sample and the arbitrary standard (air N2), respectively. The 15N value of the nitrate source used for the growth media was -1.69‰ in the first experiment and 63.81‰ in the second experiment. Tissue 15N was corrected for contaminating N from old scions using the method described in Kalcsits and Guy (2013b). I assume that ammonium synthesized from nitrate in the roots is rapidly assimilated into amino acids via the glutamine synthetase-glutamate synthase (GS-GOGAT) pathway, and any amount of ammonium loading to the xylem can be ignored. Therefore, the organic N concentration of xylem sap ([No]xylem) was calculated by difference from the total N ([Nt]xylem) and nitrate-N ([Ni]xylem) concentrations: [𝑵𝒐]𝑥𝑦𝑙𝑒𝑚 = [𝑵𝒕]𝑥𝑦𝑙𝑒𝑚 − [𝑵𝒊]𝑥𝑦𝑙𝑒𝑚 (2.3) 27 The 15N of the organic N in xylem sap (15Norganic) was calculated by mass balance from the total 15N value (15Ntotal) and the nitrate-N 15N value (15Nnitrate): 𝛅𝟏𝟓𝐍𝒐𝒓𝒈𝒂𝒏𝒊𝒄 = (𝛅𝟏𝟓𝐍𝐭𝐨𝐭𝐚𝐥 × [𝑵𝒕]𝑥𝑦𝑙𝑒𝑚 − 𝛅𝟏𝟓𝐍𝐧𝐢𝐭𝐫𝐚𝐭𝐞 × [𝑵𝒊]𝑥𝑦𝑙𝑒𝑚) [𝑵𝒐]𝑥𝑦𝑙𝑒𝑚⁄ (2.4) Plants were divided into three major parts (root, stem, and leaf), and the whole-plant isotope discrimination was calculated as the weighted sum of these parts: ∆𝟏𝟓𝐍𝒘𝒉𝒐𝒍𝒆 𝒑𝒍𝒂𝒏𝒕 = (𝒇𝒓𝒐𝒐𝒕 × ∆𝟏𝟓𝐍𝒓𝒐𝒐𝒕) + (𝒇𝒔𝒕𝒆𝒎 × ∆𝟏𝟓𝐍𝒔𝒕𝒆𝒎) + (𝒇𝒍𝒆𝒂𝒇 × ∆𝟏𝟓𝐍𝒍𝒆𝒂𝒇) (2.5) where, 15Ni is the discrimination and fi is equal to the fraction of tissue nitrogen contributing to overall plant nitrogen content. The proportion of nitrate assimilated in the roots was defined as Proot, expressed as a fraction. Assuming all nitrogen translocated from roots to shoots (leaves, stems) remained in the shoots, then the minimum Proot based on the measurement in the xylem sap and tissue nitrogen content can be calculated as: 𝑷𝒓𝒐𝒐𝒕 𝒎𝒆𝒂𝒔𝒖𝒓𝒆𝒅 = 𝟏 − ((𝒇𝒔𝒕𝒆𝒎 + 𝒇𝒍𝒆𝒂𝒇) × [𝑵𝒊] [𝑵𝒕]𝒙𝒚𝒍𝒆𝒎⁄ ) (2.6) The percent ratio of inorganic nitrogen (Ti) relative to total nitrogen (Tt) translocated to the leaves (Ti/Tt), as predicted by the IMB model (Kalcsits et al. 2014), was calculated as: 𝑻𝒊𝑻𝒕= (∆𝟏𝟓𝐍𝒍𝒆𝒂𝒇−∆𝟏𝟓𝐍𝒓𝒐𝒐𝒕)∆𝒆𝒏𝒛𝒚𝒎𝒆∗ 𝟏𝟎𝟎 (2.7) where, enzyme is the discrimination factor for NR. Ti/Tt was compared to the ratio of inorganic nitrogen relative to total nitrogen in the xylem (Ni/Nt), based on the measurement of [Ni]xylem and [Nt]xylem. Assuming leaves and roots are the major sites of nitrogen assimilation, the amount of stem N (relative to total plant N) that originates from the leaves (fstem-leaf) is approximated by: 28 𝒇𝒔𝒕𝒆𝒎−𝒍𝒆𝒂𝒇 = ∆𝟏𝟓𝐍𝒔𝒕𝒆𝒎 − ∆𝟏𝟓𝐍𝒓𝒐𝒐𝒕∆𝟏𝟓𝐍𝒍𝒆𝒂𝒇 − ∆𝟏𝟓𝐍𝒓𝒐𝒐𝒕  𝒇𝒔𝒕𝒆𝒎 (2.8) and the proportion of total plant nitrogen assigned to the leaf pool is: 𝒇𝒍𝒆𝒂𝒇 𝒑𝒐𝒐𝒍 = 𝒇𝒍𝒆𝒂𝒇 + 𝒇𝒔𝒕𝒆𝒎−𝒍𝒆𝒂𝒇 (2.9) The proportion of total nitrogen assimilated in the leaves is the product of fleaf pool and Ti/Tt. The remaining proportion of plant nitrogen is, therefore, the total nitrogen assimilated in the roots (Proot predicted): 𝑷𝒓𝒐𝒐𝒕 𝒑𝒓𝒆𝒅𝒊𝒄𝒕𝒆𝒅 = 𝟏 − (𝒇𝒍𝒆𝒂𝒇 𝒑𝒐𝒐𝒍 ×𝑻𝒊𝑻𝒕) (2.10) Efflux over influx (E/I) is then calculated as: 𝑬𝑰= ∆𝟏𝟓𝑵𝒑𝒍𝒂𝒏𝒕∆𝟏𝟓𝑵𝒆𝒏𝒛𝒚𝒎𝒆×𝑷𝒓𝒐𝒐𝒕 𝒑𝒓𝒆𝒅𝒊𝒄𝒕𝒆𝒅 (2.11) In essence, and unlike Cui et al. (2020) where isotope discrimination associated with efflux is considered fixed, equation (11) rearranged yields whole-plant isotope discrimination as a function of the exchange of cellular nitrate with the external source. This is similar to the accepted model for carbon isotope discrimination during CO2 fixation in photosynthesis (Farquhar et al. 1989). 2.3.4 Statistics For xylem sap samples, concentration and 15N of total nitrogen, nitrate and organic nitrogen were compared using a two-way ANOVA in R (R Core Development Team, 2011) with position and pressure as fixed effects in the first experiment, and with time and genotype as fixed effects in the second experiment. The statistical model was as follows: 𝒀𝒊𝒋 = 𝝁 + 𝜶𝒊 + 𝝉𝒋 + 𝜷𝒊𝒋 (2.12) 29 where, μ is the overall mean response, αi is the effect due to position in Expt. 1 and time in Expt. 2, τj is the effect due to pressure in Expt. 1 and genotype in Expt. 2, and βij is the effect due to any interaction between the position and pressure in Expt. 1 and time and genotype in Expt. 2. Genotype effects on plant biomass, whole-plant and tissue nitrogen concentrations, and whole-plant and tissue 15N were tested by one-way ANOVA: 𝒀𝒊 = 𝝁 + 𝜶𝒊 (2.13) where, μ is the overall mean response and αi is the effect due to genotype. Statistical differences were assessed using Tukey’s multiple comparison tests. 2.4 Results 2.4.1 Nitrogen concentration and 15N in xylem sap Both total N and NO3- concentrations of xylem sap were higher than the source hydroponic medium (Figure 2.1a,b). Collection pressure had a significant effect but sampling position did not. The average xylem total N concentration was 6.87±0.57 mM, which was more than 13 times higher than the source medium N concentration (0.5 mM) (Figure 2.1a). The mean xylem NO3- concentration was 1.42±0.08 mM (Figure 2.1b). Both total N and NO3- in xylem sap were enriched in 15N relative to the source medium (Figure 2.1c,d), by 2.46±0.57‰ and 21.42±0.88‰, respectively. As was the case with N concentrations, sampling position had no significant effect on isotopic composition. Although collection pressure did not significantly affect the 15N of total N, the 15N of xylem NO3- was increased by 3.65±0.53‰ at high pressure. In sum, xylem NO3- from lower and upper shoot sections was similar in concentration and N isotopic composition at low pressure, but higher pressure resulted in somewhat lower concentration and somewhat higher 15N of NO3- in xylem from the upper shoot (Figure 2.1b,d). The average NO3- concentration of xylem sap collected at low pressure was 30 1.64±0.10 mM. The average 15N of total N and NO3- in xylem sap collected at low pressure was 0.78±0.16‰ and 19.73±0.88‰, respectively (Figure 2.1c,d). 2.4.2 Estimated organic nitrogen concentration and 15N in xylem sap The concentration and 15N of organic N in xylem sap, both determined by difference, were unaffected by either position or pressure (Figure 2.2). The average organic N concentration in xylem sap was 5.61±0.55 mM (Figure 2.2a), and the average 15N was -5.14±1.03‰, which was distinctly lower than the 15N of xylem sap total N and NO3-, or the source NO3- (Figure 2.2b). The average difference in 15N between the NO3- and organic N fractions in the xylem was 24.9±1.6‰ (or  = 25.1±1.6‰, as defined by Equation ). To explore possible genotypic variation, we calculated mean NO3- and total N concentrations and 15N values from xylem sap collected at low pressure for each genotype. The mean total N concentration in xylem sap ranged from 6.15 mM to 16.64 mM, with an overall mean across all genotypes of 8.41±0.85 mM. The mean NO3- concentration in xylem sap ranged from 1.21 mM to 2.41 mM, with an overall average of 1.64±0.07 mM. Both total N and NO3- concentrations were not significant at the genotypic level. Nitrate, on average, accounted for 21±2.77% of total N in the xylem sap. Among the three randomly selected genotypes, only the 15N of NO3- showed a significant effect of genotype (Table 2.2). 31 Figure 2.1. Concentrations of total N (a) and nitrate (b), and 15N of total N (c) and nitrate (d) in Populus trichocarpa xylem sap collected from lower and upper shoot sections at low pressure and higher pressure. Bars or symbols represent means of six samples (SE; omitted from panel d because they are smaller than the symbol size). Effects of the main factors pressure or position, and their interaction, are indicated: n.s., not significant; *, P<0.05; **, P<0.01; ***, P<0.001. Dotted lines in panels c and d represent the 15N of NO3- in the hydroponic medium (-1.69‰). 32 Figure 2.2. Estimated concentration (a) and 15N (b) of organic N in xylem sap collected from lower and upper shoot sections at low pressure and higher pressure. Bars or symbols represent means of six samples (SE). The main factors pressure and position, and their interaction, were not significant (n.s.). Dotted line in panel b represents the 15N of NO3- in the hydroponic medium (-1.69‰). 33 Table 2.2. Concentrations and 15N values of total N (Nt) and nitrate (Ni) in xylem sap collected from the shoots of three genotypes of Populus trichocarpa hydroponically grown with NO3-. Mean values (SE) are for four biological replicates, each representing pooled sap collected from 10 plants over the low pressure range. [Ni]/[Nt]xylem is the percent fraction of NO3- in the total N. Different letters indicate significant differences at P<0.05. N concentration (mM) 15N (‰) [Ni]/[Nt]xylem (%) Genotypes [Nt]xylem [Ni]xylem Total N NO3- BELA4 5.58±0.53a 1.70±0.11a 1.96±1.14a 15.30±1.73b 22.76±2.04a CARS4 8.68±2.56a 1.85±0.28a 0.33±1.84a 20.06±1.73a 23.27±3.99a NECA4 6.69±1.31a 1.37±0.09a 0.34±0.71a 21.73±1.26a 17.49±2.11a 34 2.4.3 Diurnal pattern in nitrogen isotope discrimination in xylem sap To explore possible diurnal variation in N concentration and 15N during xylem transport, a second experiment was conducted where xylem sap was collected from five black cottonwood genotypes at five different time points over a 24 h cycle. Three time points were during the day (10:00, 15:00 and 20:00 h), and two time points were during the night (4:00 and 24:00 h). Data pooled across genotypes for concentrations and 15N of total N, NO3-, and estimated organic N are shown in Figure 2.3. There was no diurnal pattern in total N concentration (Figure 2.3a). The overall average total N concentration was 6.60±0.48 mM. Time of sampling was almost but not quite significant for NO3- concentration (P=0.067) (Figure 2.3b). However, when daytime and nighttime values were considered separately, lower NO3- concentrations were detected during the day (P=0.015). The average day vs. night concentration of NO3- was 1.41±0.20 mM vs. 2.31±0.32 mM, respectively. The overall average NO3- concentration over the full 24 h cycle was 1.78±0.17 mM. There was no significant effect of time on the concentration of estimated organic N (Figure 2.3c). The overall average organic N concentration was 4.88±0.46 mM. In contrast to concentration, the 15N of total N and the organic N of which it was mostly comprised, showed significant diurnal variation (Figure 2.3d,f). The 15N values of total and organic N were heavier at night than during the day by approximately 2.9 and 2.0‰, respectively. On the other hand, the isotopic composition of xylem NO3- was very consistent (Figure 2.3e) and enriched relative to the source media by an overall average of 11.7‰. Genotypic means for concentration and 15N values of total N, nitrate, and organic N in the xylem sap are presented in Table 2.3. Significant differences between 35 genotypes were found only in the 15N of NO3-. There were no differences in total N, nitrate, and organic N concentrations or in 15N values of total N and organic N. Figure 2.3. Diurnal patterns in concentrations of total N (a), nitrate (b) and organic N (c), and 15N of total N (d), nitrate (e) and organic N (f) in xylem sap of Populus trichocarpa. Bars or symbols represent means of 10 samples (SE). Effects of the main factor time are indicated: n.s., not significant; *, P<0.05; **, P<0.01; ***, P< 0.001. Dotted lines in panels d, e and f represent the 15N of nitrate in the hydroponic medium (63.81‰). 36 Table 2.3. Concentrations and 15N values of total N (Nt), nitrate (Ni) and organic nitrogen (No) in xylem sap collected from the shoots of five genotypes of Populus trichocarpa hydroponically grown with NO3-. Mean values (SE) are for five biological replicates, each representing pooled sap expressed from 10 plants over the 0-1 MPa range. Different letters indicate significant differences at P<0.05. N concentration (mM) 15N (‰) Genotype [Nt]xylem [Ni]xylem [No]xylem Total N NO3- Organic N BELA 4 5.871.12a 1.840.43a 4.501.11a 64.70.78a 74.61.03ab 60.51.20a CARS 2 5.630.92a 1.870.47a 3.890.63a 64.81.03a 76.70.98ab 59.91.54a FNYI 4 7.760.77a 2.130.32a 6.830.97a 64.90.89a 77.91.12ab 60.61.36a HALS 2 6.250.78a 2.700.92a 2.890.52a 66.60.66a 72.81.05b 60.31.96a STHA 3 5.010.97a 1.170.30a 3.770.83a 65.20.71a 77.11.52a 55.43.51a 37 2.4.4 Plant tissue discrimination and IMB model prediction To compare predicted and actual N isotope compositions during transport in xylem vessels, plant tissue samples were analyzed and 15N calculated for whole-plants, roots, stems and leaves, was compared across five genotypes (Figure 2.4). Only root 15N showed a significant difference between genotypes. The STHA3 genotype had the highest root as well as whole-plant 15N values. Roots in general had the highest 15N (averaging 7.07‰ across all genotypes), whereas leaves had the lowest 15N (averaging 0.29‰). Since roots only accounted for ~15% of the total N content, whole-plant 15N (averaging 1.66‰) more closely reflects the stems and leaves. The predicted proportion of inorganic N to total N in xylem sap (Ti/Tt), calculated from the leaf and root tissue 15N values as per Equation 7, was compared to the measured proportion of NO3- to total N (Ni/Nt) in the actual xylem sap samples (Table 2.4). The mean Ni/Nt was 26.60%. When the discrimination factor for NR (enzyme) was set at 15.4‰, the average predicted Ti/Tt was 44.08±2.15%, or 1.66 times the measured Ni/Nt. When enzyme was adjusted to 25.1‰, the average predicted Ti/Tt was 27.04±1.29%, which is very similar to the measured Ni/Nt. Subsequently, using Equations 10 and 11, the proportion of total nitrogen assimilated in the root (Proot predicted) and efflux/influx (E/I) were calculated based on a enzyme of 25.1‰ (Figure 2.5). E/I ranged from 0.06 to 0.34 and no significant genotypic effect was found (P=0.74). Proot predicted ranged from 78 to 86% (i.e., only 14-22% of the retained NO3- was shoot-assimilated) and Proot measured ranged from 73 to 85%. The correlation between Proot predicted and Proot measured was significant (P=0.05). Genotypic variation was found both in Proot predicted (P=0.02) and Proot measured (P<0.01). The HALS2 genotype had the highest Proot predicted and Proot measured values. 38 Figure 2.4. Whole-plant and organ level discrimination (15N) in five genotypes of Populus trichocarpa in Experiment 2. Shown are means±SE (n=5). Different letters indicate significant difference between genotypes at P<0.05. 39 Table 2.4 Percentages of NO3- (Ni) in total nitrogen (Nt) in xylem sap as directly measured after collection ([Ni]/[Nt]) or estimated percentage of inorganic nitrogen (Ti) relative to total nitrogen (Tt) translocated to the leaves (Ti/Tt) from the isotope mass balance (IMB) model for Populus trichocarpa genotypes grown under 0.5 mM NO3- for 45 days. Model predictions of Ti/Tt are given for calculations where discrimination () by nitrate reductase is taken to be either 15.4‰ or 25.1‰. Data are means±SE (n=5-10). Different individual ramets were used for sap collection and for model analysis. Xylem collection IMB prediction Genotypes [Ni]/[Nt] (%) Ti/Tt (%) =15.4‰ Ti/Tt (%) =25.1‰ BELA 4 26.35±1.02a 38.24±3.32ab 23.46±1.99ab CARS 2 30.85±1.65a 46.22±5.05ab 28.36±3.03ab FNYI 4 24.12±1.02a 49.13±3.97a 30.14±2.38a HALS 2 21.68±3.94a 33.35±3.06b 20.46±1.83b STHA 3 26.31±1.70a 53.44±2.66a 32.79±1.59a Overall Mean 26.60±2.04 44.08±2.15 27.04±1.29 40 Figure 2.5. Model-derived efflux/influx (E/I, upper panel) and the proportion of nitrogen assimilated in the root (Proot, lower panel) of five genotypes of Populus trichocarpa. Empty bars are based on tissue 15N values assuming ∆enzyme is 25.1‰ (i.e., Proot predicted via Equations (2.7) and (2.10)) and solid bars are based on measurements of xylem sap N content (Proot measured from Equation (2.6)). Both estimates of Proot also rely on the same tissue N content data, so some autocorrelation is expected. Shown are means±SE (n=5). Different letters indicate significant differences between genotypes at P<0.05. 41 2.5 Discussion 2.5.1 Whole-plant and organ level variation in 15N There are three major fates for nitrate taken up by roots, including 1) local assimilation in the roots, 2) translocation to the shoot via the xylem, and 3) efflux back to the growing medium. In the present study, the averaged whole-plant 15N was 1.66‰, indicating that 14NO3- was preferentially assimilated in the roots and a greater proportion of the 15NO3- was returned to the hydroponic medium. Similar to the results of Kalcsits and Guy (2013b) for the closely related Populus balsamifera L. (balsam poplar), and many other species (Cui et al. 2020), I found leaves to have higher 15N values (i.e., lower 15N; Figure 2.4) than roots. This is the expected pattern if residual unassimilated NO3- (enriched in 15N) is transported from roots to shoots. The average 15N of leaves was close to 0 (i.e., leaf 15N values were similar to the hydroponic source 15N). Stems were in between and, knowing there was no significant direct NO3- assimilation from the xylem stream, must have obtained most of their nitrogen in organic form from both roots and leaves. I estimate that, on average, the fraction of stem nitrogen obtained from the leaves (i.e., fstem-leaf) was 46%, with the remaining 54% originating as organic N directly from the roots. Kalcsits and Guy (2016b) reported organ level genotypic variation in 15N in balsam poplar. In the present study with black cottonwood and the same media NO3- concentration (0.5 mM), I detected modest organ level genotypic variation in 15N, and in 15N of xylem NO3-. In contrast to black cottonwood, however, Kalcsits and Guy (2016b) reported that balsam poplar leaves were enriched in 15N by ~4.42‰ relative to the hydroponic source, whereas here the enrichment was only 0.29‰. Indeed, roots, stems, and whole-plant 15N were all greater in balsam poplar than in black cottonwood. Pending a direct comparison in a common hydroponic experiment, these 42 differences suggest that root-shoot partitioning of nitrogen assimilation is similar in the two species, but E/I may be considerably higher in balsam poplar. 2.5.2 15N of total soluble organic N, NO3- and organic N of root tissue Because nitrate reductase discriminates against 15NO3- relative to 14NO3-, the 15N content of glutamine and, in sum, all organic N-containing products derived from it, will be lower than the 15N content of the available substrate at the site of reaction. Accordingly, there are consistent differences in 15N values of bulk tissue, total soluble organic N, NO3- and total organic N in roots of black cottonwood (Appendix Table A.2). The difference in 15N between nitrate-N and organic-N suggests that the discrimination factor associated with nitrate assimilation ~18.2‰. However, accounting for some contribution from isotopically lighter medium-sourced nitrate clinging to the roots or in the apoplastic space of the cortex would increase this value somewhat. Using leaf tissue, Yoneyama et al. (2003) and Cui et al. (2020) employed similar approaches to obtain values of 19‰ and 16.8‰, respectively. Since root inorganic nitrogen in the cytoplasm is the source for inorganic nitrogen loaded into the xylem, NO3- loaded into the xylem sap should have a similar isotopic composition. Organic N loaded into the xylem is expected to be depleted in 15N relative to cytoplasmic or xylem sap NO3-. Within the xylem, a broad spectrum of transported amino acids and other N-compounds has been reported depending on environment and plant species (Tegeder and Masclaux‐Daubresse 2018). Often aspartate, glutamate, asparagine, and glutamine are the most abundant (Liu et al. 2014). The 15N of different free amino acids in plant tissue can vary by almost 10‰, and depends on environmental conditions, metabolic branch points, and relative fluxes (Tcherkez 2011). Glutamine, however, accounts for more than 80% of total proteinogenic amino acids in xylem of Populus spp. (Escher et al. 2004; Millard et al. 2006). Thus, as per a Raleigh distillation, 43 xylem sap analysis should provide a reasonable proxy sampling of the instantaneous product and the residual substrate remaining, with the difference in isotopic composition between the organic and inorganic N directly reflecting the in vivo discrimination factor of NR. 2.5.3 N content and 15N-patterns of shoot xylem sap The main purpose of my first experiment was to establish a reliable protocol for sampling xylem sap, but also to check for an effect of sampling position and the possibility of further significant assimilation during nitrogen translocation. I collected sap at two sampling positions under two different but sequential ranges of extraction pressure, the first being just 0.1-0.2 MPa and the second being 0.6-0.7 MPa above the balancing pressure. Xylem from these different locations had similar total N and NO3- concentrations as well as 15N values when sap was collected at low pressure (Figure 2.1). Though a significant decrease in NO3- concentration was found in xylem sap from the upper position at higher pressure, the 15N of NO3- and total N, and total N concentration remained similar between lower and upper portions of the shoot. These observations are consistent with Schneider et al. (1996) and Geßler et al. (1998) who, by monitoring the ATP content of xylem sap, detected negligible contamination originating from parenchyma cells in both roots and shoot at 0.6 MPa above the balancing pressure. However, NO3- in more distal sap (as represented by upper shoots at higher pressure) may be reduced in concentration by further assimilation en route or, possibly, tissue water re-entering the xylem by reverse osmosis at the highest pressure. Overall, there was only a small effect of stem position and collection pressure over the full range tested here, and thus samples collected from the lower portions of unsegmented shoots under low pressure should yield reliable results. The data also indicate that the concentration and isotopic composition of major N fractions in stem 44 xylem sap are relatively stable during transport and, as concluded by Cui et al. (2020), not significantly affected by exchange with the phloem. In the first experiment, the average NO3- concentration of xylem sap collected at low pressure was 1.64±0.07 mM, which accounted for 21.18% of total N concentration during transport (Table 2.2). The second experiment found an average of 1.78±0.17 mM NO3-, or 26.60±2.04% of total N transport (Figure 2.3a,b). Thus, approximately three-quarters of the N transported in the xylem was already assimilated into organic form. Notably, although most N loaded into the xylem was organic, the NO3- concentration was still roughly three times higher than in the source medium (0.5 mM). From shoot nitrogen content and measured Ni/Nt ratios, I obtained a minimum estimate for the proportion of total plant N that was root assimilated (Proot measured) ranging from 73 to 85% (Figure 2.5). Although this is a high proportion relative to many species (Oh et al. 2008; Cui et al. 2020), it is not unusual for Populus. Dluzniewska et al. (2006) obtained a Proot of 96% and Siebrecht and Tischner (1999) estimated Proot to be 40~60%, both in hybrid aspen (Populus tremula × P. alba). Min et al. (1999) reported a Proot of ~70% in Populus tremuloides. Proot likely varies with age, species, media nitrate concentration, and other growing conditions. For example, in their work, Dluzniewska et al. (2006) found that Proot decreased to 68% when hybrid aspen was supplied with glutamine in addition to nitrate. Since analysis of xylem sap is based on point measurements, whereas tissue 15N values and nitrogen concentrations reflect time-integrated assimilation, I investigated the possibility of diurnal variation in the xylem sap. Peuke et al. (2013) found that the 15N of total N in xylem sap of Ricinus communis is significantly higher during the day than the night. There are several potential causes for diurnal variation in the 15N of xylem sap. There is diurnal variation in gene expression patterns for nitrate and/or ammonium transporters in roots (Ono et al. 2000; von Wirén et al. 2000; Matt et al. 45 2001) and both roots and leaves show diel rhythms in assimilation and metabolism (Glass et al. 2002). In shoots, reductant NADH needed for the assimilation of nitrate is more readily available during the day than at night (Ramarao et al. 1981). A direct reliance on reducing power from the light reactions does not apply to roots because they must rely on the delivery of photosynthate in the phloem to provide reductant and carbon skeletons for N assimilation. The driving force for N transport from roots to shoots is the transpiration stream, which obviously does follow a day/night cycle. I detected some diel variation in 15N, but it followed a different pattern from Peuke et al. (2013); i.e., the NO3- concentration, 15N of total N and organic N in the day was significantly lower than at night (Figure 2.3), suggesting more root assimilation of NO3- during the day. The 15N of NO3- and concentrations of total N and organic N remained steady over the full 24 h cycle (Figure 2.3a,c,e). This stability suggests that the isotopic composition of NO3- and the overall N concentration of the xylem sap were relatively flux-independent, possibly aided by the steady hydroponic supply conditions. Total xylem nitrogen, and particularly xylem NO3-, was enriched in 15N relative to the hydroponic medium (Figure 2.1). The 15N of total N in xylem sap averaged 0.78±0.16‰, while the 15N of the NO3- averaged 19.73±0.88‰ (Figure 2.1c,d). In contrast, the organic N was depleted in 15N relative to the hydroponic medium and had an average 15N of -5.14±1.03‰ (Figure 2.2b). The difference in 15N between the NO3- and the organic N fractions was 24.9±1.6‰. This difference is of comparable magnitude but, as expected, greater than the difference I found between the total organic N and NO3- of root tissue (Appendix Table A.2). Fractionation during NO3- reduction by NR in vitro has been measured in several studies. Ledgard et al. (1985) reported that discrimination by NR purified from spinach was 15.4‰, and this value is often quoted. However, reported discrimination factors at natural abundance levels range from 12.1‰ for enzyme from the moss Hypnum plumaeforme (Liu et al. 2012) to 32‰ in 46 Escherichia coli (Carlisle et al. 2014). In addition, Carlisle et al. (2014) reported values of 23‰, 23‰, 31‰ and 28‰ in Arabidopsis thaliana, Pichea angusta, Zea mays, and Aspergillus niger, respectively, whereas Olleros-Izard (1983) obtained discrimination factors of 24-29‰ for enzyme from Z. mays. Karsh et al. (2012) used enzymes from the fungus Aspergillus niger and the diatom Thalassiosira weissflogii and reported a mean value of 26.6‰. Species differences are possible and discrimination may also be different in vivo (Tcherkez and Farquhar 2006; Liu et al. 2014). Needoba et al. (2004) estimated NR discrimination to be 22.0‰ in T. weissflogii. If the difference in 15N between organic and inorganic N in the xylem sap approximates the in vivo discrimination factor of NR as I propose, then there should be a constant offset between their respective 15N values; this, however, was not the case (Figure 2.3e,f). These measures may not track each other if loading of the product is delayed relative to the substrate. However, the 15N of NO3- was temporally very steady, so irrespective of any delay, I would still expect the 15N of the organic fraction to be steady and not vary over time. Another possible explanation for the lack of a constant offset is the compounding of errors that necessarily occurred when I derived the isotopic composition of the organic N by mass balance. Either way, the overall mean should give a reasonable estimate of isotopic composition integrated over the day, and I would expect the 15N of organic N in the xylem to be close to the 15N of whole roots, as assumed by Kalcsits et al. (2014). Indeed, the average 15N of the roots across five genotypes was -7.66‰ and the average 15N of organic N in the xylem sap was -7.00‰ (Appendix Table A.3). This close agreement suggests that there is little or no further fractionation associated with the identity of the organic N entering the xylem. 47 2.5.4 Convergence of direct measurement and IMB model prediction In combination with information about tissue N contents, and knowing the discrimination factor of NR, whole-plant and tissue 15N can be used to estimate Ti/Tt, Proot and ultimately E/I. In the first experiment, I analyzed the 15N values of organic N and NO3- in xylem sap and the average difference in 15N was 24.9±1.6‰ (i.e., 15N = 25.1±1.6‰). In the second experiment, I analyzed plant tissue data from five genotypes of black cottonwood and compared Ti/Tt from the IMB model with direct measurement of N concentrations in xylem sap. If Ti/Tt is calculated using 15.4‰ for ∆enzyme, the model-predicted Ti/Tt is 66% higher than the direct measurement from xylem sap (Table 2.4). When recalculated using the value of 25.1‰, the model-predicted Ti/Tt and the directly measured Ti/Tt converge almost exactly. Similarly, the Proot obtained by direct measurement was 78.7±0.6%, while the Proot predicted by the model was 80.6±0.9%. However, despite this excellent fit, I consider it likely that 25.1‰ is too high, as the average of the various estimates for ∆enzyme reviewed above is closer to 22‰. In a comparison of the IMB model and compartmental analysis of tracer efflux (CATE) using stable isotope tracing to determine E/I in balsam poplar, Kalcsits and Guy (2016a) found that the two methods yielded highly correlated results that converged when ∆enzyme was fixed at 22‰. 2.6 Conclusion Here, I found that pressure bombing of black cottonwood shoots at low pressures (0.1-0.2 MPa above the balancing pressure) yielded xylem sap containing both organic-N and NO3--N fractions differing in isotopic composition by ~24.9‰. This difference is consistent with an in vivo discrimination factor for NR (25.1‰) that is substantially higher than the first reported direct measurements in the literature, but much closer to recent estimates for ∆enzyme, which average near 22‰. Utilization of these higher values 48 for ∆enzyme improves the prediction of Ti/Tt in the IMB model (this study) and also brings estimates of E/I from that model in line with independent tracer efflux measurements (Kalcsits and Guy 2016a). I suggest that the IMB model may be useful for phenotyping traits related to nitrogen uptake and assimilation in hydroponically-grown plants that rely substantially on root assimilation. 49 3. Genotypic variation in carbon and nitrogen isotope discrimination suggests local adaptation of heart-leaved willow (Salix eriocephala Michx.). 3.1 Summary Plants acquire multiple resources from the environment and may need to adjust and/or balance their respective resource-use efficiencies to maximize growth and survival, in a locally adaptive manner. In this study, tissue and whole-plant 13C and C/N ratios provided long-term measures of WUE and NUE, and a 15N-based mass balance model was used to estimate traits related to N uptake and assimilation in heart-leaved willow. In an initial common garden experiment consisting of 34 populations, I found population level variation in 13C, C/N, and 15N, indicating different patterns in WUE, NUE, and N uptake and assimilation. Although there was no relationship between foliar 13C and C/N ratios among populations, there was a significant negative correlation between these measures across all individuals, implying a genetic and/or plastic trade-off between WUE and NUE not associated with local adaptation. To eliminate any environmental effect, I grew a subset of 21 genotypes hydroponically with nitrate as the sole N-source, and detected significant variation in 13C, 15N, and C/N ratios. Variation in 15N was mainly due to genotypic differences in the nitrate efflux/influx ratio (E/I) at the root. Both experiments suggested clinal variation in 15N (and thus N uptake efficiency) with latitude of origin, which may relate to water availability and could contribute to global patterns in ecosystem 15N. There was a tendency for genotypes with higher WUE to come from more water replete sites with shorter and cooler growing seasons. I found that 13C, C/N, and E/I were not inter-correlated, suggesting that selection for growth, WUE, NUE, and N uptake efficiency can occur without trade-off. 50 3.2 Introduction Tree and shrub species within the Salicaceae present interesting and convenient models for studying adaptive evolution since many of them have wide geographic distributions, are easily propagated, possess relatively small and well understood genomes, and have well established genetic resources (Djomo et al. 2011; Shunmugam et al. 2016; Jiahui et al. 2019). Populations of species with large natural ranges may encounter divergent selection pressures because of wide variation in environmental factors, such as temperature, precipitation, growing season length, photoperiod, and soil nutrient conditions, resulting in environment‐correlated intraspecific variation (Eckert and Dyer 2012; McKown et al. 2013). Populations that are more fit to local environments than others are considered to be locally adapted (Kawecki and Ebert 2004; Blanquart et al. 2013). Water and nitrogen are among the most limiting of resources for plants in terrestrial temperate and boreal ecosystems and, consequently, selective pressure towards maximization of water and N use efficiencies is expected (Weih et al. 2006). Both the efficiency of water use (carbon fixed per unit water transpired) and the efficiency of N use (carbon fixed per unit N assimilated) are tied, in part, to the diffusion gradient for CO2 into the leaf through stomata. Most water used by plants is in support of photosynthesis by way of transpiration. More than half of total leaf N is related to photosynthesis (Evans 1989), and total leaf N content and photosynthetic capacity are typically correlated (Field and Mooney 1986; Larcher 2003). Reductions in stomatal conductance (gs) or higher investments in foliar N can result in higher WUE if the CO2 diffusion gradient steepens, but lower intercellular CO2 concentrations may reduce NUE by reducing rates of carbon fixation per unit N. A negative correlation between WUE and NUE is implied, suggesting an evolutionary trade-off. However, changes in 51 mesophyll conductance (gm) should impact WUE and NUE similarly and without trade-off because, in contrast to gs, there is no effect on the diffusion of water vapour (Lauteri et al. 1997). Variation in sites of N assimilation and allocation within plants might also uncouple NUE from WUE, but in more indirect ways. For example, in Populus, when under N-limiting conditions, both a fast- and slow-growing hybrid showed increased root surface area, decreased photosynthetic rate, and reduced NUE (Luo et al. 2015). The slow-growing hybrid (Populus × popularis) had an increased WUE while the fast-growing hybrid (Populus alba × Populus glandulosa) had a decreased WUE. Because similar differences may occur within species, it is unclear if a trade-off between WUE and NUE should be expected among locally-adapted populations. Plant C/N ratio can be used as a proxy measure of NUE over time, while the carbon isotopic composition (δ13C) of plant tissue can provide information on the long-term WUE of C3 plants (Sun et al. 1996; Seibt et al. 2008). Fractionation of carbon isotopes occurs principally during diffusion of CO2 into the leaf and at fixation by RuBisCO, which both discriminate against the heavier carbon isotope (13C). Net discrimination can be simply modelled as a function of the atmosphere-to-leaf CO2 diffusion gradient, which also determines the intrinsic WUE of photosynthesis (Farquhar et al. 1982). Strong genotypic correlations between δ13C and WUE have been demonstrated in many tree species, including members of the Salicaceae (Leffler and Evans 1999; Pointeau and Guy 2014). Although plant nitrogen isotopic composition (15N) does not provide a measure of NUE, variation in 15N can be used to trace N movement and infer N sources and/or N cycle dynamics in vegetation at local, community, and landscape scales. For example, a recent long-term monitoring study of plant 15N in the Tibetan alpine permafrost region suggested that increasing atmospheric CO2 is causing increased N demand by plants, while climate warming is resulting in more N loss from the soil (Kou et al. 2020). Proper 52 interpretation of such signals, however, depends on a thorough understanding of how plants might differentially use different N forms (nitrate, ammonium, etc.) and the plant physiological processes that can fractionate N isotopes during uptake, assimilation, translocation, and remobilization (Evans 2001). Pathways for nitrogen acquisition and assimilation in plants, and their genetic and regulatory networks, xylem loading, and patterns of storage/allocation have been extensively studied (Xu et al. 2012; Tegeder and Masclaux-Daubresse 2018; Feng et al. 2020). The uptake of inorganic N by roots occurs through both high and low affinity transport systems. After uptake, nitrate and/or ammonium may leak out of roots back into the rooting medium (efflux) or be assimilated. Nitrate is reduced into ammonium by nitrate reductase (NR) and nitrite reductase (NiR) working sequentially, and ammonium is assimilated in the glutamine synthetase-glutamine oxoglutarate aminotransferase (GS-GOGAT) cycle (Tischner 2000; Lancien et al. 2000). Several studies have shown that assimilated N is generally 15N-depleted, while unassimilated N, both external and internal to the plant, becomes enriched in 15N compared to the initial source (Pritchard and Guy 2005; Tcherkez and Hodges 2008; Cui et al. 2020). Discrimination against 15N occurs at the initial assimilatory enzymes, NR and GS. Variability of 15N in plant tissues, therefore, is linked to N metabolism and can reflect changes in N metabolism and fluxes (Dawson et al. 2002; Tcherkez 2011). A simple N isotope mass balance (IMB) model proposed by Kalcsits et al. (2014), and validated in chapter 2 (Hu and Guy 2020), uses measurements of organ level δ15N values under steady-state N supply conditions to identify efficiencies of inorganic N acquisition by roots (i.e., net uptake vs. gross uptake) and variation in the site of assimilation (roots vs. shoots) in plants. Heart-leaved willow is a deciduous woody plant in the Salicaceae family with a wide distribution in North America. In general, willows have high demands for water but 53 are considered to be efficient utilizers of N (Djomo et al. 2011; Fabio and Smart 2018). Here, I explored possible clinal variation in foliar C/N ratio, δ15N, and δ13C of heart-leaved willow using 34 natural populations collected from a large geographic area planted into a common garden field experiment. I tested the hypothesis that population level variation in WUE (as indicated by 13C) would show a negative relationship with NUE (as indicated by C/N), or be connected to variation in 15N that might indicate variation in N uptake efficiency and/or sites of N assimilation and allocation. To control for field effects and spatial variation in soil 15N, I selected 21 genotypes for isotopic dissection of N acquisition parameters in a controlled environment hydroponic experiment. I uncover largescale geographic trends in 15N in heart-leaved willow associated with variation in N uptake efficiency, but independent from genetic variation in WUE and NUE. 3.3 Methods This study employed clonal material from the AgCanSalix (Agriculture Canada Salix) collection established from field scions taken over the natural range of heart-leaved willow within Canada in 2012 (Shunmugam et al. 2016). This collection includes 34 populations of heart-leaved willow, with 15 genotypes per population (Figure 3.1). Climate variables for each collection site were obtained from ClimateWNA (Wang et al. 2012) based on the 1971-2000 Canadian Climate Normal dataset. Variables derived included frost-free period (FFP; days), mean warmest month temperature (MWMT; °C), mean annual precipitation (MAP; mm), mean summer precipitation from May to September (MSP; mm), mean annual temperature (MAT; °C), and continentality (CONT; °C). Annual dryness index (ADI) and summer dryness index (SDI), were obtained according to Guy and Holowachuk (2001): 𝐀𝐃𝐈 = (𝒆𝒔[𝑴𝑨𝑻] × 𝟏𝟎𝟎𝟎)/𝐌𝐀𝐏 (3.1) 54 𝐒𝐃𝐈 = (𝒆𝒔[𝑴𝑻𝑾𝑴] × 𝟏𝟎𝟎𝟎)/𝐌𝐒𝐏 (3.2) where, es is the saturation vapor pressure in kilopascals at MAT and MTWM, respectively, calculated according to Buck (1981) and Yin (1998). 3.3.1 Common garden experiment Briefly, the original scions noted above were rooted under greenhouse conditions and transferred after 2 months to a shade house where they were allowed to undergo natural senescence before lifting and storing at -4°C for later use. In spring 2013, this material was used to establish a common garden at Indian Head, Saskatchewan (50.52°N 103.68°W; elevation 605 m; MAT: 1.4°C; MAP: 492 mm; FPP: 103 days). The site preparation involved cultivating to a depth of 20 cm or more and disking. Later, the rows were marked at 3 m intervals in an East-West orientation, with each row running 320 m long. The site was rototilled after amending with micronutrients. The soil texture at the site was sandy clay loam with an average pH of 7.9, and with 13.6, 19.7 and 242.9 ppm of N, P and K, respectively. Rows were mulched using black plastic sheeting (Crawling Valley Plastics, Canada) to avoid intra-row weed competition. Populations were planted on mulched rows as a block with 1.0 m spacing. In each of the three replicates, population blocks were randomized. The site was sprinkler irrigated as necessary during summer months with mechanical weed control between rows. In July 2014, two leaf discs were collected using a hand-held paper punch from 8-10 individuals per population (N=338) for analysis of C and N concentrations and stable isotope ratios. Stem samples for isotopic analysis were collected in the fall at 10 cm above the soil surface. Both sample sets were oven dried at 50°C for 72 hours to constant mass. 55 3.3.2 Hydroponic experiment Based on the 15N of leaves and stems from the common garden experiment, a subset of just 21 genotypes was selected to represent the foliar 15N range observed in the common garden experiment, as well as the geographic range from east to west (Figure 3.1). First year whips were collected in early February, 2018 and stored in black plastic bags at 4°C for 4 months before use. Two-node scions, approximately 5 cm long, were rooted in distilled water and then transferred to a hydroponic system in the UBC Horticulture Greenhouse (Vancouver, Canada). There were six replicates per genotype for a total of 126 plants, randomly arranged. Four 150 L bench-mounted acrylic tubs, an 1800 L vertical ground tank (RK400; Canada), two water pumps (Little Giant, Canwest Tanks, USA), and connecting PVC piping (2.54 cm diameter; WaterTec, Canada) comprised the hydroponic system. Each acrylic tub had a capacity to hold up to 32 plants. One water pump sat in the bottom of the main tank and continuously circulated media to the four tubs. The depth of water in the tubs was set by an overflow outlet draining by gravity into a receiving reservoir at ground level containing the second pump (actuated by a float switch), which returned the media to the main tank. The total volume of the system was maintained at 2000 L. The hydroponics solution was a modified 1/10th strength Johnson’s solution (Johnson et al. 1957) supplemented with 0.25 mM Ca(NO3)2. To avoid major changes in the δ15N of the hydroponics solution over time, media NO3- concentration was assayed periodically using the perchloric acid method (Cawse 1967) to ensure no substantial decrease (no more than 10%). The nutrient medium was completely replaced as necessary, usually every 6-10 days. The hydroponics system was under ambient light conditions supplemented by LED lighting (600 µmol m-2s-1) on an 18/6 h day/night photoperiod. Temperatures in the greenhouse were maintained between 20-24°C. 56 Figure 3.1. Locations of 34 populations of heart-leaf willow (Salix eriocephala) sampled from the natural range of the species across eastern and western Canada. Stars indicate the populations from which the 21 genotypes used in the hydroponics experiment were selected. The green shaded area represents the dominant continuous range of heart-leaved willow while the yellow shaded area shows the discontinuous range. 3.3.3 Carbon and Nitrogen Isotope analysis The leaf and stem samples (1.5 mg for 13C; 2.5 mg for 15N) collected from the common garden were packed in tin capsules (Elemental Microanalysis, UK) and sent to the UC Davis Stable Isotope Facility (Davis, CA, USA) for analysis of 13C, 15N, and C and N concentrations. For the hydroponics experiment, plants were harvested after 45 days of growth and divided into leaves, stems, roots, and original cuttings. Once oven-dried, these parts were weighed and then pulverized using a Wiley mill followed by a 57 Geno/Grinder. Sub-samples (3 mg) were packed into tin capsules and analyzed for C and N concentration, 13C and 15N using a Vario EL Cube Elemental Analyzer interfaced to an Isoprime Isotope Ratio Mass Spectrometer in the Stable Isotope Facility, Faculty of Forestry, UBC. 3.3.4 Calculations Carbon and nitrogen isotopic compositions were expressed as 13C and 15N values: 𝛅𝟏𝟑𝐂 or 𝛅𝟏𝟓𝐍 = (𝑹𝒔𝒂𝒎𝒑𝒍𝒆𝑹𝒔𝒕𝒂𝒏𝒅𝒂𝒓𝒅 − 𝟏) ∗ 𝟏𝟎𝟎𝟎 (3.3) where, Rsample and Rstandard are the 13C/12C or 15N/14N ratios of the sample and the arbitrary standard, respectively. After correcting for carry-over effects of pre-existing N in the original cuttings (Kalcsits and Guy 2013b), the whole-plant isotopic composition of plants from the hydroponics experiment was calculated as the weighted sum of root, stem and leaf: 𝛅𝟏𝟓𝐍𝒘𝒉𝒐𝒍𝒆 𝒑𝒍𝒂𝒏𝒕 = (𝒇𝒓𝒐𝒐𝒕 × 𝛅𝟏𝟓𝐍𝒓𝒐𝒐𝒕) + (𝒇𝒔𝒕𝒆𝒎 × 𝛅𝟏𝟓𝐍𝒔𝒕𝒆𝒎) + (𝒇𝒍𝒆𝒂𝒇 × 𝛅𝟏𝟓𝐍𝒍𝒆𝒂𝒇) (3.4) where, fi is equal to the fraction of tissue N contributing to overall plant N content. Nitrogen isotope discrimination (15N) relative to the source hydroponic solution (15N = -1.69‰) was calculated as: ∆𝟏𝟓𝐍𝒔𝒂𝒎𝒑𝒍𝒆 =(𝛅𝟏𝟓𝐍𝒔𝒐𝒖𝒓𝒄𝒆−𝛅𝟏𝟓𝐍𝒔𝒂𝒎𝒑𝒍𝒆)(𝟏+𝛅𝟏𝟓𝐍𝒔𝒂𝒎𝒑𝒍𝒆𝟏𝟎𝟎𝟎) (3.5) An isotope mass balance (IMB) model as described in detail in Kalcsits et al. (2014) was used to estimate N fluxes and rates and locations of N assimilation. From the discrimination factor for nitrate reductase, assumed here to be 22‰ (Hu and Guy 2020), and the 15N and N content of plant tissues, the IMB model yields an estimate of the 58 proportion of NO3- assimilated in the roots (Proot), the NO3- efflux/influx ratio (E/I) for exchange between the substrate and the roots, and the ratio of inorganic to total N (Ti/Tt) transported to the shoot in the xylem. 3.3.5 Statistics All statistical analyses used R version 3.5.1 (R Core Development Team, 2011). Linear regression analyses were performed between 15N values (leaves and stems) and site of origin geo-climatic variables. Pearson correlation coefficients (r) were used to examine relationships between all variables determined on the 21 genotypes used in the hydroponic experiment, and canonical correlation analysis was done between physiological and environmental variables using the package “CCA”. Genotype effects on plant biomass, whole-plant and tissue N concentrations, and whole-plant and tissue 15N were tested by one-way ANOVA followed by Tukey’s multiple comparison tests. 3.4 Results 3.4.1 Common garden experiment There were clear differences between populations in δ13C, δ15N, N percentage, and C/N ratios, in both leaves and stems (P<0.05, Table 3.1). In the common garden, leaf δ13C ranged from -30.7‰ to -24.7‰ and leaf C/N ratio ranged from 11.45 to 28.98 (Figure 3.2). There was no relationship between 13C and C/N ratio at the population level (Figure 3.2a). However, when data were plotted for the species as a whole, there was a significant negative correlation between leaf 13C and leaf C/N (P<0.001, Figure 3.2b). The population mean δ15N and 13C values of leaves and stems were plotted against latitude of origin (Figure 3.3a,b). The leaf and stem δ15N values were quite variable, spanning ranges of 15.5‰ and 11.1‰, respectively. Both leaf and stem δ15N 59 values showed a positive correlation with latitude (P<0.001, Figure 3.3a), while the δ13C values showed no relationship with latitude (P>0.05, Figure 3.3b). I did, however, find that in both leaves and stems, population mean δ13C was negatively correlated with summer dryness index, while δ15N was positively correlated (both at P<0.001, Appendix Figure A.3). Consistent relationships with other climate variables were not detected. 60 Table 3.1. Overall means of measured plant traits, and associated population effects from the common garden experiment. Traits measured or estimated include nitrogen percentage (N, %), carbon isotopic composition (13C, ‰), nitrogen isotopic composition (15N, ‰), the carbon to nitrogen (C/N) ratio of leaves and stems. *** indicates significance at P<0.001 Measurement MeanSE Population effect Nitrogen percentage Leaf N 2.820.02 *** Stem N 0.340.01 *** Carbon isotopic composition Leaf 13C ‐28.40.1 *** Stem 13C ‐27.60.1 *** Nitrogen isotopic composition Leaf 15N 9.90.2 *** Stem 15N 7.10.1 *** Carbon to nitrogen ratio Leaf C/N 16.190.15 *** Stem C/N 7.360.18 *** 61 Figure 3.2. The relationship between leaf carbon isotopic composition (13C) and leaf carbon to nitrogen (C/N) ratio of heart-leaf willow (Salix eriocephala) based on (a) population means (±SE) and (b) individual plants from the common garden experiment. 62 Figure 3.3. Nitrogen isotopic composition (15N) and carbon isotopic composition (13C) of leaves and stems in heart-leaf willow (Salix eriocephala) (panels a&c and b&d, respectively) from common garden and hydroponic experiments (a&b and c&d, respectively) plotted against latitude of origin. Each point for the common garden data represents one population with 10 replicates, while each point for the hydroponic data represents one genotype with six replicates. Data are means±SE. 63 3.4.2 Hydroponics experiment Isotopic analysis of the subset of 21 S. eriocephala genotypes grown under controlled environment conditions revealed similar trends with latitude of origin but with much less variation in δ15N. The leaf δ15N significantly increased with latitude (P<0.001, Figure 3.3c) while the δ13C of leaves and stems did not (Figure 3.3d). Stem δ15N was also not significantly correlated to latitude (P=0.162, Figure 3.3c). The δ15N values in this experiment covered a range of 5.4‰ in leaves and 6.2‰ in stems, with leaves being about 1.9‰ heavier than the stems. Foliar δ13C spanned a range of 4.5‰ while stems differed by up to 6.3‰. Whole-plant δ15N and δ13C showed similar patterns, as did leaves alone (Figure 3.3c,d); i.e., δ15N increased significantly with latitude of origin (P<0.001) whereas δ13C did not (Figure 3.4a,b). However, the data suggested a parabolic relationship of δ13C on latitude, and a second order polynomial regression was significant (P<0.001). In combination with tissue N concentrations, N isotope discrimination relative to the NO3- source was used in the IMB model to calculate N fluxes and rates and locations of assimilation. Root efflux/influx (E/I) ratio ranged from 0.04 to 0.19 and was negatively correlated with latitude (P<0.001, Figure 3.5). Other model variables were not significantly different between genotypes, and not correlated to latitude. Pearson correlation coefficients (r) between geo-climatic parameters and isotopic traits for all 21 genotypes are shown in Table 3.2. In addition to latitude, both leaf and whole-plant δ15N increased with longitude (LON) and elevation (ELV). Both measures of δ15N were negatively correlated to frost-free period (FFP) and mean annual precipitation (MAP). Although 13C of the hydroponically grown material was not significantly related to the geographic variables (LAT, LON and ELV), it was negatively correlated with mean warmest month temperature (MWMT), annual dryness index (ADI), summer dryness 64 index (SDI), continentality (CONT), and FFP. A further canonical structure analysis was obtained using those geo-climatic variables and 15N and 13C (Table 3.3). Two significant canonical variables were extracted (CLIM1 and CLIM2). Frost-free period and MWMT loaded highly on CLIM1, while MAP and ADI were most strongly related to CLIM2. The whole-plant root, stem and leaf 13C were negatively loaded on CLIM1, while whole-plant 15N and leaf 15N were negatively loaded on CLIM2. 65 Figure 3.4. Whole-plant nitrogen and carbon isotopic compositions (15N & 13C; panels a&b, respectively) plotted against latitude of origin in the hydroponic experiment. Each point represents one genotype with six replicates. Data are means±SE. Figure 3.5. Root efflux/influx ratio derived from the Isotope Mass Balance (IMB) model plotted against latitude of origin. Each point represents one genotype with six replicates. Data are means±SE 66 Table 3.2. Pearson correlations (r) between geographic, climatic, and physiological variables for all 21 genotypes in the hydroponic experiment. Bolding indicates significance at P<0.05; Bold* indicates significance at P<0.001. LAT LON ELV FFP MWMT MAP CONT ADI SDI Leaf 15N 0.34* 0.27 0.28 -0.29 -0.16 -0.22 0.01 0.22 0.12 Leaf 13C -0.03 -0.18 -0.05 -0.27 -0.38* 0.24 -0.31 -0.19 -0.24 Stem 15N 0.14 0.15 0.12 -0.11 0.01 -0.12 0.07 0.05 -0.01 Stem 13C 0.13 -0.08 0.04 -0.52* -0.52* 0.16 -0.32 -0.16 -0.28 Root 15N 0.23 0.20 0.14 -0.12 0.06 -0.21 0.18 0.12 0.12 Root 13C 0.09 -0.08 0.11 -0.34* -0.38* 0.16 -0.31 -0.13 -0.24 WP 15N 0.40* 0.37* 0.37* -0.28 -0.10 -0.32 0.07 0.31 0.19 WP 13C 0.03 -0.17 -0.04 -0.42* -0.52* 0.30 -0.39* -0.27 -0.36* Biomass -0.04 0.06 -0.03 0.09 0.16 -0.10 0.16 -0.08 0.12 LAT, latitude (N); LON, longitude (W); ELV, elevation (m); FFP, frost-free period (days); MWMT, mean warmest month temperature (C); MAP, mean annual precipitation (mm); CONT, continentality (C); ADI, annual dryness index; SDI: summer dryness index; 15N, nitrogen isotope composition; 13C, carbon isotope composition; WP, whole-plant; biomass (g). 67 Table 3.3. Canonical structure between geoclimatic parameters and plant traits with the first two canonical variables, CLIM1 and CLIM2. Geoclimatic variables CLIM 1 CLIM 2 Response variables CLIM 1 CLIM 2 LAT -0.25 -0.41 Leaf 15N -0.51 -0.57 LON 0.15 -0.60 Leaf 13C -0.60 -0.07 ELV -0.05 -0.63 Stem 15N -0.08 -0.30 FFP 0.70 0.20 Stem 13C -0.82 -0.20 MWMT 0.71 -0.09 Root 15N -0.04 -0.07 MAP -0.25 0.63 Root 13C -0.70 0.04 MAT 0.04 0.14 WP 15N -0.41 -0.71 CONT 0.43 -0.20 WP 13C -0.85 0.10 ADI 0.29 -0.71 Biomass 0.35 0.03 SDI 0.42 -0.53 LAT, latitude (N); LON, longitude (W); ELV, elevation (m); FFP, frost free-period (days); MWMT, mean warmest month temperature (C); MAP, mean annual precipitation (mm); MAT, mean annual temperature; CONT, continentality (C); ADI, annual dryness index; SDI, summer dryness index; 15N, nitrogen isotope composition; 13C, carbon isotope composition; WP, whole-plant; biomass (g) 68 3.4.3 Genotypic differences Genotypic means and statistical differences are summarized in Table 3.4. Genotypic variation in biomass, root-shoot ratio, tissue and whole-plant level N percentage, 13C, and 15N were found. Genotype effects on most IMB model outputs were not significant except for E/I, indicating that E/I varies significantly across the 21 assessed genotypes. Traits in Table 3.4 were further analyzed for functional correlations as presented in the heat map shown in Appendix Figure B.2. Generally, root growth was significantly related to C/N, 13C ,and 15N at the whole-plant level. Root biomass was positively correlated to whole-plant C/N and E/I, and negatively correlated to whole-plant 13C and 15N. Whole-plant C/N was not correlated to either whole-plant 13C or E/I. Whole-plant 13C was also not correlated with E/I. Therefore, a 3D scatter plot combining whole-plant 13C, whole-plant C/N ratio and E/I was plotted to rank all 21 genotypes in the hydroponics experiment (Figure 3.6). The STL-2 genotype outperformed all others in having higher whole-plant 13C and C/N, as well as lower E/I. The biomass of STL-2 was 3.420.25 g, which was nearly 80% higher than the average biomass (Table 3.4). 69 Table 3.4. Overall means and ranges of measured plant traits, and associated genotype effects, in the hydroponics experiment. Traits measured or estimated include biomass (g), root-shoot ratio, carbon isotopic composition (13C, ‰) at organ and whole-plant (WP) levels, nitrogen isotope discrimination (15N, ‰) at organ and whole-plant levels, the ratio of inorganic to total nitrogen transported in the xylem (Ti/Tt), the proportion of plant nitrogen assimilated in roots (Proot), efflux/influx (E/I), and leaf and root assimilation activity (AC, mol mg dw−1). Measured MeanSE Genotype minimum Genotype maximum Genotype effect Growth Biomass 1.940.14 0.46 3.53 *** R:S ratio 0.360.01 0.17 0.55 *** Carbon isotope composition Root 13C ‐30.370.11 ‐31.67 ‐28.92 * Stem 13C ‐31.900.13 ‐34.44 ‐29.66 ** Leaf 13C ‐32.660.10 ‐33.76 ‐31.14 *** WP 13C ‐31.860.09 ‐32.98 ‐30.80 *** Nitrogen isotope discrimination Root 15N 4.000.10 2.90 5.29 * Stem 15N 3.500.12 1.90 5.14 *** Leaf 15N 1.600.10 0.69 3.25 ** WP 15N 2.330.08 1.51 3.40 *** Model calculations Ti/Tt 0.150.01 0.03 0.18 0.28 Proot 0.900.01 0.85 0.94 0.30 E/I 0.160.01 0.04 0.19 *** Leaf AC 0.410.03 0.08 0.47 0.19 Root AC 9.320.96 6.25 15.29 0.64 Significance levels: 0.001 ‘***’ 0.01 ‘**’ 0.05 ‘*’ 70 Figure 3.6. 3D scatter plot showing efflux/influx ratio (E/I), whole-plant carbon isotopic composition (13C), and whole-plant C/N ratio of the 21 genotypes used in the hydroponics experiment. Each dot represents the mean of six replicates per genotype. The STL-2 genotype is singled out for its combination of high 13C, high C/N, and low E/I. 71 3.5 Discussion Patterns in C and N stable isotopes from the outdoor common garden and controlled environment hydroponic experiments were similar in direction, but different in magnitude. In the common garden experiment, I sampled leaves and stems from 34 populations of heart-leaved willow collected across Canada and I found significant population variation in 13C and C/N ratios in leaves and stems, indicating differences in WUE and NUE among populations (Table 3.1). I also found no correlation between 13C and C/N ratios at this level, and thus no trade-off between WUE and NUE (Figure 3.2a). In contrast, across all individuals, there was a significant negative correlation between foliar 13C and C/N (Figure 3.2b), implying a genetic and/or plastic trade-off between WUE and NUE that was unassociated with local adaptation. Plastic variation in WUE, trading off with NUE, is commonly reported in response to changes in water and/or N supply (Patterson et al. 1997; Livingston et al. 1999; Drenovsky et al. 2012), whereas Pointeau and Guy (2014) detected no genotypic trade-off between 13C and C/N in two Populus species. I could not distinguish between these two possibilities in my common garden study because the individual genotypes were unreplicated, however, the high within-population variation I observed suggested an environmental effect due to uncontrolled differences between planting spots. I controlled for this possibility by growing clonally replicated plants under hydroponic conditions. I found many genotypic effects on growth and isotope-based traits in the controlled environment study (Table 3.4), including biomass, root-shoot ratio, whole-plant and organ level 13C and 15N, and E/I. There was no significant correlation between 13C and C/N ratios at either the whole-plant or leaf level (Appendix Figure 72 B.2), confirming the absence of a clear trade-off between WUE and NUE across genotypes. Genotypic variation in δ15N has been reported in Norway spruce (Picea abies) and European beech (Fagus sylvatica) grown under field conditions (Gebauer and Schulze 1991; Peuke et al. 2006), and in white spruce (Picea glauca), balsam poplar (Populus balsamifera) and black cottonwood (Populus trichocarpa) in hydroponics (Prichard and Guy 2005; Kalcsits and Guy 2013b). There is also large-scale geographic variation in site-averaged plant and soil δ15N that is significantly correlated to climate variables, such as temperature and precipitation (Handley et al. 1999; Amundson et al. 2003). However, no population differences or species-level clinal patterns in δ15N have previously been reported that might connect genetic variation (between or within species) with climate or geography. Here, 15N values of leaves and plants from both the hydroponics (Figure 3.3c, 3.4a) experiment and from the common garden (Figure 3.3a) were significantly correlated with latitude. The steeper slope obtained from the common garden experiment may reflect unexpected co-variation between latitude of origin and soil conditions at the site, or differential uptake of other N sources, such as ammonium. The AgCanSalix collection of heart-leaved willow spans 15° in latitude and 52° in longitude (Figure 3.1). Within this collection, latitude, longitude, and elevation for the accessions, and associated climate variables, all tend to inter-correlate because the range of heart-leaved willow in Canada extends further north in the west, towards the continental divide, than it does in the east. Under steady-state hydroponics, whole-plant 15N was positively correlated to geography (latitude, longitude, and elevation) and negatively correlated to length of the frost-free period and mean annual precipitation. In contrast, a parabolic relationship with latitude (Figure 3.4b) suggested a more complicated geoclimatic pattern for 13C (e.g., the provenance closest to the vertex had 73 the highest summer dryness index). Indeed, whole-plant 13C was positively correlated with mean annual precipitation and negatively correlated with frost-free period, mean warmest month temperature, continentality, and annual and summer dryness indices. The outdoor common garden also showed negative correlations between foliar and stem 13C and summer dryness (Appendix Figure B.1). Both data sets suggest that genotypes or populations with higher WUE originate from more water replete locations. In a provenance study of lodgepole pine (Pinus contorta Dougl.) in British Columbia, Guy and Holowachuk (2001) suggested that high WUE is associated with adaptation to wetter locations not because of lower water use, but because of intrinsically higher photosynthetic capacity, as suggested by higher growth rates in all of three climatically divergent common gardens. If the same is true of heart-leaved willow, however, it is neither positively nor negatively reflected in growth rate. There are similar reports in the literature. For example, Lauteri et al. (1997, 2004) also found lower discrimination and higher WUE in Castanea sativa genotypes from wet as compared to dry environments in Turkey, but these differences were associated with lower photosynthetic capacities and lower growth rates in the wet-adapted genotypes. Cernusak (2020) suggested that species or ecotypes from areas with less consistent water supplies may be more prone to rapid water use (and lower WUE) when it is available. The canonical correlation analysis extracted two significant variates that encompass different geo-climatic variables (Table 3.3). CLIM1 appears to be associated with “growing season” because frost-free period and mean warmest month temperature were loaded heavily on it, whereas elevation, mean annual precipitation, and annual dryness index were strongly loaded on CLIM2, which thus appears to reflect “water availability”. Plant 13C was significantly associated with both axes, but more 74 with “growing season” than with “water availability.” The indication is that accessions with higher WUE are thus also favored by shorter and cooler growing seasons, as reported for several woody plant species (McKown et al. 2014; Soolanayakanahally et al. 2015; Kaluthota et al. 2015; Momayyezi and Guy 2017), including S. eriocephala (Shunmugam et al. 2016). In contrast to 13C, canonical structure analysis suggests that whole-plant and leaf 15N were more tightly (and negatively) related to “water availability” than “growing season”. This pattern suggested plants from wetter locations have low 15N values. Although what I report is a relationship between phenotype and the environment of origin, it is interesting that Handley et al. (1999) and Amundson et al. (2003) observed that across different sites, foliar 15N was negatively correlated with annual precipitation. To account for this trend, Handley et al. (1999) suggested a mechanism whereby there is isotopically important leaching of 15N-enriched dissolved organic nitrogen at wetter sites. In contrast, Amundson et al. (2003) suggested that wetter ecosystems have lower losses of 15N-depleted N forms. Either way, my data suggest that local adaptation affecting N isotope discrimination at the whole-plant level may also contribute to this pattern. The clinal variation in 15N found in both the common garden, as well as the hydroponics experiment (Figure 3.3a,c) suggested possible clinal variation in N uptake and assimilation. The proportion of total plant N assimilated in roots (Proot) and the ratio of inorganic to total N transported in the xylem (Ti/Tt) remained relatively stable and did not differ between genotypes (Table 3.4). There was, however, significant genotypic variation in E/I that was correlated with latitude (Figure 3.5), indicating that clinal variation in 15N is caused by differences in efflux relative to influx of NO3- at the roots. I am unaware of any other studies examining clinal variation in 15N and nitrate uptake efficiency in plants. Even though root-shoot ratio did not show similar clinal patterns, 75 reduced uptake efficiency was correlated with higher root-shoot ratios (Appendix Figure B.2), which might result in a lower N demand and a higher N supply at the whole-plant level. Because E/I was not correlated with either 13C or C/N across genotypes (Appendix Figure B.2), there appears to be no discernible trade-off between N uptake efficiency and WUE or NUE (Figure 3.6). Therefore, through breeding and/or selection, it should be possible to obtain clones or varieties with both high WUE and high NUE, as well as high nitrogen uptake efficiency. Of the 21 genotypes studied here, STL-2 stood out by combining these three traits with high productivity (80% higher than the average overall), suggesting inherently superior growth. 3.6 Conclusion I conclude that heart-leaved willow shows significant variation in 15N, 13C, and C/N ratios among genotypes and populations, indicating differences in N uptake and assimilation, WUE, and NUE. There is clinal variation in N isotope discrimination with latitude, which may be related to water availability and could contribute to global patterns in ecosystem 15N. The absence of a trade-off between WUE and NUE as well as E/I, suggests that it is possible to capture additive genetic variation in WUE, NUE, and E/I in heart-leaved willow. 76 Chapter 4 Geographic variation in 15N of black cottonwood (Populus trichocarpa) and identification of candidate genes for isotope discrimination by genome-wide association 4.1 Summary Genotypic variation in nitrogen use traits has not been extensively studied in trees on a range-wide scale, either in the field or in hydroponic experiments. Understanding natural variation in nitrogen-related traits and their relationship to climate is critical for studying local adaptation and also for breeding purposes. In this chapter, I took advantage of a large collection of black cottonwood genotypes covering a major portion of the species range, to study the natural genetic variation in 15N. Nearly 400 genotypes were grown under steady-state hydroponic conditions and analyzed for growth and 15N-related traits. Strong population level and genotypic variation in biomass, root-to-shoot ratio, carbon-to-nitrogen ratio, and whole-plant and organ level 15N was found. A significant correlation between root 15N and precipitation suggests that the efficiency of nitrate uptake plays a role in local adaptation to water availability. There may also have been selection towards lower root-to-shoot ratios in areas where there is reduced risk of drought. To facilitate phenotyping for GWAS analysis, leaf 15N was shown to be highly representative of whole-plant 15N and, by extension, reasonably indicative of IMB model-based calculation of efflux/influx (E/I) at the root. GWAS linked a gene for a glutaminyl-tRNA synthetase to root 15N (and the difference between root and leaf 15N), but did not find any significant associations with genes related to nitrate transport or assimilation. There were, however, several associations for root-to-shoot ratio, which was in turn correlated with whole-plant 15N and E/I. 77 4.2 Introduction Nitrogen-use traits are complex and controlled by genotype, the environment and, likely, their interaction (Tegeder and Masclaux‐Daubresse 2017). Intraspecific variation in nitrogen isotope discrimination and other traits related to nitrogen utilization has been reported under field conditions for many species, such as Norway spruce (Picea abies) and European beech (Fagus sylvatica) (Gebauer and Schulze 1991; Peuke et al. 2006), and under controlled conditions in white spruce (Picea glauca), balsam poplar (Populus balsamifera) and black cottonwood (Populus trichocarpa) (Pritchard and Guy 2005; Kalcsits and Guy 2013b). Although heritability estimates for a particular trait are not fixed and depend on the populations sampled, high estimates, in theory, imply that the trait is subject to spatially variable selection. Conversely, low estimates may indicate that a trait is largely plastic in response to the immediate environment, highlighting the role of phenotypic plasticity as an additional variability reservoir (McKown et al. 2014a). Reports of the broad-sense heritability (H2) for 15N have been limited to just a few species and the value was generally small (less than 0.20), especially in comparison to other N-related traits such as C/N ratio (~0.50) and N percentage (~0.60) in soybeans (Glycine max) and barley (Hordeum vulgare) (Dhanapal et al. 2015; Karunarathne et al. 2020). In poplar, a large common garden assessment of phenotypic trait variation in black cottonwood reported a H2 of only 0.08 for leaf 15N, suggesting very little inherent variation in 15N (McKown et al. 2014a). Detectable genotypic variation in 15N under typical field conditions is, however, not expected because of spatial variation in soil 15N and, most importantly, the fact that whole-plant discrimination cannot be expressed if the utilization of available soil N approaches completion (i.e., if unused N cannot diffuse away from the roots before being consumed). Although McKown et al. (2014b) assessed 461 genotypes from 136 78 provenances, the level of genetic variation in 15N was lower than observed in just 25 genotypes from five provenances of balsam poplar when grown hydroponically (Kalcsits and Guy 2016b). Therefore, assessment of plant 15N using a substantial number of genotypes from multiple provenances under tightly controlled hydroponic conditions is necessary. Moreover, Kalcsits and Guy (2016b) observed that individual genotype and/or provenance level variation in growth, root-to-shoot (R:S) ratio, leaf N content, sites of assimilation (i.e., Proot, Ti/Tt and proportions of root-assimilated N translocated to shoots), and E/I (provenance level only) were correlated between plants grown on nitrate vs. plants grown on ammonium, suggesting a common underpinning not related to physiological or biochemical processes specific to either N-source. Root-to-shoot ratio, for example, may affect the relationship between N demand by the shoot and N supply by the roots, and thus impact E/I and whole-plant 15N (Pritchard and Guy, 2005). Though very fundamental, our understanding of N uptake and assimilation is still incomplete, especially for trees. Uncovering the molecular and physiological basis for these complex traits is a growing area in tree biology and requires the integration of extensive genetic and phenotypic data (Eckert et al. 2009, 2010; McKown et al. 2014c). In poplars, as well as other species of dual ecological and economic importance, there is great interest in establishing links between relevant phenotypes and genetic variation (Ingvarsson and Street 2011). Genome-wide association study (GWAS) using high genome coverage of single nucleotide polymorphisms (SNP) markers is a technique widely used for this purpose. In Populus, GWAS studies have implicated numerous genes in the control of various wood characteristics (Porth et al. 2013), stomatal patterning and bud-break phenology (McKown et al. 2014b, 2019), which may contribute to local adaptation (Savolainen et al. 2013). To date, GWAS studies on NUE-related traits have been mainly focused on identifying targets to improve NUE efficiency in crop plants, 79 such as rice (Oryza sativa) (Tang et al. 2019), maize (Zea mays) (Ertiro et al. 2020), and barley (Karunarathne et al. 2020). SNPs for ammonium (AMT) and nitrate (NRT1/NRT2) transporter genes were found to be significantly associated with N uptake and transport in those studies. Furthermore, overexpression of OsNRT1.1 and OsNRT2.1 increased both NUE and growth in rice (Huang et al. 2017; Wang et al. 2018). GWAS on 15N has been limited to black cottonwood (McKown et al. 2014b) and at least three studies utilizing soybean (Dhanapal et al. 2015; Steketee et al. 2019, Bazzer et al. 2020). As expected, no significant associations were found for black cottonwood given that the trees were field-grown (as noted earlier). In contrast, numerous SNP associations have been found in soybean, despite also being field-grown. Soybean, however, is an N-fixing legume and, as such, plant 15N provides a measure of the amount of N obtained directly from the atmosphere relative to what is taken up from the soil. To date, no GWAS has been published on 15N-related traits obtained on plants grown hydroponically. Furthermore, the many GWAS studies conducted on crop plants have not generally been completed in the context of exploring the genetic underpinnings of natural biogeographic variation in N-use traits and the possibility of local adaption. In this chapter, I provide a large-scale assessment of tissue and whole-plant 15N values in black cottonwood clones grown hydroponically, using accessions covering much of the species’ range within British Columbia, Oregon, and Washington. All black cottonwood accessions used in this study were previously genotyped for SNPs estimating extensive allelic variation in 3.5K genes distributed across the genome (Geraldes et al. 2013). My first hypothesis was that under controlled hydroponic conditions, the nearly 400 poplar genotypes assessed would show significant genetic variation in N isotope discrimination and C/N ratios at both the clone and population level. I further hypothesized that, as in heart-leaved willow (Chapter 3), there would be 80 relationships between this variation and geoclimatic variables suggestive of local adaptation. The third hypothesis was that genes relating to N-related traits and the balance between N supply and demand (and thus E/I), such as for assimilatory enzymes, transporters or R:S ratio, would be implicated by a GWAS association analysis. 4.3 Methods and materials 4.3.1 Plant materials This study employed a large collection of native black cottonwood genotypes originating from a large portion of the species range (38.9-59.6°N, 121.2-137.9°W, Figure 4.1), collected by the British Columbia Ministry of Forests, Lands and Natural Resource Operations in the mid-1990s and planted in 2008 into a common garden at Totem Field, UBC, Vancouver, British Columbia, Canada (49.26°N, 123.25°W). Because of space limitations and the large number of genotypes assessed, 362 genotypes were randomly assigned to nine different hydroponic runs blocked in time. The first eight runs were conducted between the spring 2012 and summer 2014. To allow data normalization among runs, one additional run was conducted in summer 2019 which randomly selected at least two genotypes from each of the original eight runs (details in Appendix Figure C.1). Each run was considered as one “block” and each genotype within or between the blocks had a minimum of three replicates. First year scions of P. trichocarpa were collected from the common garden in early February each year, and stored in black plastic bags at 4°C. Freshly cut two-node scions, approximately 5 cm long, were rooted in distilled water in the UBC Horticulture greenhouse before transferring to hydroponics. 81 Figure 4.1. Locations of 107 populations of black cottonwood (Populus trichocarpa) sampled from the natural range of the species in western North America, as shown in blue. The green area represents the dominant continuous range of the species. 82 4.3.2 Hydroponic system The hydroponics system was as described in detail in Kalcsits and Guy (2016ab) and consisted of up to four 1000 L wooden containers lined with rubber pond liner material (Firestone, Nashville, TN, USA), each with a centrifugal pump and an air pump to circulate and oxygenate the media. The containers were fitted with floating Perspex “rafts” that held up to 32 plants per raft. The hydroponics solution was a modified 1/10th Johnson’s solution (Johnson et al. 1957) supplemented with 0.25 mM Ca(NO3)2. Media NO3- concentration was monitored using the perchloric acid method (Cawse 1996) to ensure there was no substantial decrease (no more than 10%) in NO3- concentration over time that could result in major changes to the 15N of the hydroponics solution. The nutrients were completely replaced as necessary, usually every one to two weeks. The hydroponic system was under ambient light conditions supplemented by LED lighting (600 µmol m-2 s-1 PPFD) on an 18/6 hr day/night photoperiod. Temperatures in the greenhouse were maintained between 20 - 24°C. 4.3.3 15N phenotyping Plants were harvested into leaves, stems, roots, and original cuttings after 45 days of growth. Once freeze-dried, these parts were weighed and then pulverized using a Wiley mill (Fritsch Laborgeratebau, Terochem Scientific, Ottawa, Canada) followed by a Geno/Grinder (SPEX SamplePrep, Metuchen, New Jersey, USA). Sub-samples (3 mg) were packed into tin capsules and analyzed for %C, %N, and 15N using a Vario EL Cube Elemental Analyzer (Elementar, Germany) interfaced to an Isoprime Isotope Ratio Mass Spectrometer (GV Instruments, UK) in the Stable Isotope Lab, Agriculture and Agri-Food Canada Lethbridge Research and Development Centre, Lethbridge, Alberta, Canada. 83 Leaf, stem, root and original cutting samples were all analyzed for blocks 1-4 and 9, but because of budget limitations, only leaf and root samples were analyzed for blocks 5-8 (more than 3000 samples overall). Nitrogen isotopic composition (15N) and isotope discrimination (15N) are expressed as: 𝜹𝟏𝟓𝑵 = (𝑹𝒔𝒂𝒎𝒑𝒍𝒆𝑹𝒔𝒕𝒂𝒏𝒅𝒂𝒓𝒅− 𝟏) (4.1) ∆𝟏𝟓𝑵 =(𝜹𝟏𝟓𝑵𝒔𝒐𝒖𝒓𝒄𝒆−𝜹𝟏𝟓𝑵𝒔𝒂𝒎𝒑𝒍𝒆)(𝟏+𝜹𝟏𝟓𝑵𝒔𝒂𝒎𝒑𝒍𝒆) (4.2) where, Rsample and Rstandard are the 15N/14N ratios of the sample and arbitrary standard (air N2), respectively, and 15Nsource is the 15N of the source Ca(NO3)2, which varied slightly between runs (Table 1). 4.3.4 Geo-climatic patterns in 15N Climatic variables for the provenance of each population were obtained from ClimateNA V.7.0 (Wang et al. 2016) based on the 1961-1990 Canadian Climate Normal dataset. Variables in ClimateNA included frost-free period (FFP; days), mean warmest month temperature (MWMT; °C), mean annual precipitation (MAP; mm), mean summer precipitation from May to September (MSP, mm), mean annual temperature (MAT; °C), and continentality (CONT; °C). Annual dryness index (ADI) and summer dryness index (SDI), were obtained according to Guy and Holowachuk (2001): 𝑨𝑫𝑰 = (𝒆𝒔[𝑴𝑨𝑻] × 𝟏𝟎𝟎𝟎)/𝑴𝑨𝑷 (4.3) 𝑺𝑫𝑰 = (𝒆𝒔[𝑴𝑻𝑾𝑴] × 𝟏𝟎𝟎𝟎)/𝑴𝑺𝑷 (4.4) where, es is the saturation vapor pressure in kilopascals at MAT and MTWM, respectively, calculated according to Buck (1981) and Yin (1998). 84 Population-level relationships between climatic variables as described above and 15N and C/N mass ratios of leaves, roots and whole-plants were tested using linear mixed effects models with the “LME4” (Bates et al. 2015) and “lmerTest” (Kuznetsova et al. 2017) packages in R. All climatic variables were included as fixed effects and block was treated as a random effect in the full model. The model with the lowest Akaike Information Criterion (AIC) was selected by stepwise deletion of each fixed effect. I also conducted a linear mixed effects model of 15N values with genotype and population as fixed effects and block as a random effect to test for genotypic variation across all blocks. 4.3.5 Heritability estimates and GWAS analysis I estimated broad-sense trait heritability (H2) using data from individual plants across genotypes for nitrogen-related traits (n = 627-1196, depending on the trait). As described in McKown et al. (2014a), a linear mixed model was used to estimate variance components as follows: 𝒀 = Χ𝜷 + Ζ𝛍 + 𝒆 (4.5) where, 𝒀 is the vector of measurements; 𝜷 and 𝛍, vectors of fixed and random effects (population and genotype); and X and Z were matrices assigning fixed and random effects to each measurement in 𝒀. Variance components (𝜎𝑔2 , total genetic variance; 𝜎𝑒2, the residual variance) were then used to calculate H2 as follows: 𝑯2 =𝝈𝑔2𝝈𝑔2 + 𝝈𝑒2 (4.6) GWAS of 29,355 SNPs with R:S ratio, leaf 15N, root 15N, and the difference in 15N between the root and the leaf (15Nroot-leaf), utilizing mean data for all 392 85 genotypes was conducted based on the method described in McKown et al. (2014b) with the following generalized linear model: 𝒀 = μ + S𝛂 + X𝛃 + 𝒆 (4.7) where, 𝒀 is the vector of measurements; μ, overall population mean; α and β, vectors of fixed effects for both SNP genotype and population, respectively; S and X, index matrices assigning fixed effects for both SNP genotype and population; and e, residual effect. Significant associations were identified after applying a Bonferroni multiple testing correction whereby α values at 0.05 and 0.1 were adjusted by dividing by the number of tests conducted (29,355) to yield thresholds of P <1.7  10-6 and P <3.4  10-6, respectively. Identities of candidate genes and their annotations were obtained from the online platform Phytozome v13 for Populus trichocarpa v3.0. Additional potential functions for identified genes were gleaned from the literature. 86 4.4 Results 4.4.1 Heritability of biomass and nitrogen related traits Genotypic means, ranges and broad-sense heritability (H2) for biomass, root-shoot (R:S) ratio, and organ and whole-plant level discrimination (15N) are summarized in Table 4.1. Population and genotypic level variation were both highly significant for all traits, but differences between genotypes were stronger than differences between populations. Discrimination relative to the source nitrogen was higher for roots (averaging 5.21‰) than for stems (averaging 2.57‰) and leaves (averaging ‐0.15‰). The mean for the 15N difference between root and leaf was 5.35‰, which was similar to the root 15N (5.21‰). Since roots only accounted for a small proportion of plant N content, whole-plant 15N (averaging 0.74‰) was closer to the stem and leaf values. The mean H2 of traits listed in Table 4.1 was 0.22. The highest H2 among the N-related traits was for the root 15N (0.40), and the lowest H2 was for the root C/N (0.10). The H2 estimates for leaf and whole‐plant 15N were the same (0.19), both being higher than the H2 of stem 15N (0.15). Relationships between growth, discrimination and calculated physiological variables were explored using the data from batches 1-4 and 9, where full data was available for stem and whole-plant 15N thereby allowing further IMB model calculations for 209 genotypes. Consistent with the observation that most plant N was foliar, mean genotypic leaf 15N was highly predictive of whole‐plant 15N (r=0.76, P<0.001, Figure 4.2a) and the IMB model-estimated E/I (r=0.72, P<0.001, Figure 4.2b). Root 15N was also predictive of whole‐plant 15N (r=0.35, Figure 4.3a) and E/I (r=0.39, P<0.001, Figure 4.3b), but not so strongly. Whole-plant 15N, and consequently the calculated E/I, were both significantly and positively correlated with the R:S ratio (r=0.31 and 0.28, P<0.001, Figure 4.4). 87 Leaf and root 15N data were available for all of batches 1-9 (362 genotypes). There was no relationship between R:S ratio and either leaf or root 15N, or the difference between them across this larger dataset (Figure 4.5), or in batches 1-4 and 9 considered alone (not shown). 88 Table 4.1. Overall genotypic means and ranges of whole-plant (WP) biomass, root-to-shoot (R:S) ratio, organ and whole-plant level nitrogen isotope discrimination (15N), and carbon to nitrogen ratio (C/N), and related broad-sense heritability estimates (H2) across Populus trichocarpa accessions. Significance levels: 0.0001 ‘***’ 0.005 ‘**’ 0.001 ‘*’ Trait n Mean value SD Data range H2 Population effect Genotype effect WP Biomass (g) 362 8.41  2.85 0.05-33.65 0.34 *** *** R:S ratio 362 0.25  0.05 0.12-0.71 0.16 ** *** Leaf 15N (‰) 362 -0.15  0.46 -1.77-1.95 0.19 ** *** Root 15N (‰) 362 5.21  0.80 2.33-7.69 0.40 *** *** 15Nroot-leaf (‰) 362 5.35  0.76 1.46-7.21 0.22 *** *** Stem 15N (‰) 209 2.57  0.04 0.62-5.39 0.15 ** *** WP 15N (‰) 209 0.74  0.36 -0.19-3.16 0.19 ** *** Leaf C/N 311 10.82  1.05 6.83-16.33 0.20 * *** Root C/N 311 12.10  1.23 3.33-21.34 0.10 *** *** 89 Figure 4.2. Relationships between leaf isotope discrimination (15N) and whole-plant (WP) 15N (a), and root efflux/influx (b) in Populus trichocarpa accessions. Each point represents one genotypic mean with three replicates across batches 1-4 and 9 (n=209). 90 Figure 4.3. Relationships between root 15N and whole-plant 15N (a), and root efflux/influx (b) in Populus trichocarpa accessions. Each point represents one genotypic mean with three replicates across batches 1-4 and 9 (n=209). 91 Figure 4.4. Relationships between root-to-shoot (R:S) ratio and whole-plant (WP) 15N (a), and root efflux/influx (b) in Populus trichocarpa accessions. Each point represents one genotypic mean with three replicates across batches 1-4 and 9 (n=209). 92 Figure 4.5. Relationship between root-to-shoot (R:S) ratio and leaf, root and the leaf-root difference in nitrogen isotope discrimination (15N) in Populus trichocarpa accessions. Each point represents one genotype with at least three replicates across 9 batches (n=362). 93 4.4.2 Correlation matrix Collection-wide relationships between geo-climatic parameters and N-related traits for all genotypes are shown in Table 4.2. Unlike the results for heart-leaved willow in Chapter 3, the biomass and N isotopic traits barely show any significant relationship to geo-climatic variables. The most significant correlations observed were for root-related traits. Root C/N was negatively correlated to mean annual precipitation (MAP) and positively correlated to latitude, elevation, continentality (CONT), and annual dryness index (ADI). Root-to-shoot ratio was negatively correlated to frost-free period (FFP) and MAP, and positively correlated to latitude, elevation, CONT, and ADI. Root 15N was significantly correlated only with ADI. Further canonical structure analysis (Table 4.3) extracted two significant canonical variables (CLIM1 and CLIM2). In CLIM1, ADI and CONT were negatively loaded, while MAP and FFP were positively loaded. In CLIM2, mean summer precipitation (MSP) and MAP were negatively loaded, while summer dryness index (SDI) and ADI were positively loaded. Root C/N and root mass both were negatively loaded on CLIM1, and root 15N loaded positively on CLIM2. Root-to-shoot ratio loaded negatively on CLIM1 and positively on CLIM2. 94 Table 4.2. Relationships between nitrogen-related physiological variables and geo-climatic variables across 107 provenances of Populus trichocarpa. There were 2-4 genotypes per provenance and three ramets per genotype. Bolding indicates significance at P<0.05; Bold* indicates significance at P<0.01. LAT LON ELV FFP MWMT MAP CONT ADI SDI Leaf 15N -0.05 -0.01 -0.05 0.04 0.06 0.03 -0.04 -0.04 -0.01 Root 15N -0.07 -0.05 -0.01 0.03 -0.02 0.11 -0.07 -0.11 -0.04 WP mass 0.05 0.05 0.01 -0.01 -0.04 0.03 0.02 0.01 0.02 Leaf C/N -0.06 -0.08 -0.02 0.01 0.11 0.01 -0.01 0.03 0.03 Root C/N 0.11 -0.05 0.14* -0.07 0.02 -0.18* 0.19* 0.21* 0.07 R:S ratio 0.11 0.01 0.10 -0.12 -0.07 -0.12 0.15* 0.14* 0.01 LAT, latitude (N); LON, longitude (W); ELV, elevation (m); FFP, frost free-period (days); MWMT, mean warmest month temperature (C); MAP, mean annual precipitation (mm); CONT, continentality (C); ADI, annual dryness index; SDI, summer dryness index; 15N, nitrogen isotope discrimination; WP mass, whole-plant mass (g); C/N, carbon to nitrogen ratio; R:S ratio, root-to-shoot ratio. 95 Table 4.3. Canonical structure between geoclimatic parameters and plant traits with the first two canonical variables, CLIM1 and CLIM2. Geoclimatic variables CLIM 1 CLIM 2 Response variables CLIM 1 CLIM 2 LAT -0.53 -0.11 Leaf 15N 0.05 0.06 LON -0.04 -0.09 Root 15N 0.04 -0.19 ELV -0.57 0.07 Leaf C/N 0.05 0.09 FFP 0.42 -0.12 Root C/N -0.24 0.08 MWMT 0.34 0.29 Leaf mass -0.06 -0.08 MAP 0.49 -0.36 Root mass -0.18 -0.03 MSP 0.12 -0.48 WP mass -0.10 -0.08 CONT -0.63 0.33 R:S ratio -0.15 0.16 ADI -0.64 0.26 SDI -0.06 0.48 LAT, latitude (N); LON, longitude (W); ELV, elevation (m); FFP, frost free-period (days); MWMT, mean warmest month temperature (C); MAP, mean annual precipitation (mm); MSP, mean summer precipitation (mm); CONT, continentality (C); ADI, annual dryness index; SDI, summer dryness index; 15N, nitrogen isotope discrimination; C/N, carbon to nitrogen ratio; biomass traits (g); WP mass, whole-plant mass (g); R:S ratio, root-to-shoot ratio. 96 4.4.3 Genome-wide association analysis The GWAS identified 22 SNPs significantly associated with R:S ratio, but only one SNP with significant association to both root 15N and 15Nroot-leaf. No significant SNPs were identified for leaf 15N. Seventeen of the SNPs were located in or close to known genes. The one gene associated with isotope discrimination encodes a glutaminyl-tRNA synthetase (Potri.007G039700). The genes potentially linked to R:S ratio fall into several functional categories and include protein kinases, transcription factors, and stress-related genes (Table 4.4). Of these, one candidate gene (Potri.013G054600) was identified on chromosome 13 encoding a small auxin-up RNA (SAUR). Another candidate gene (Potri.002G168200), on chromosome 2, encodes an auxin-inducible jasmonate-amido synthetase (JAR1). Another candidate gene (Potri.015G119300), on chromosome 15, encodes EXOCYST COMPLEX COMPONENT EXO84C. Another candidate gene (Potri.003G198900), on chromosome 3, encodes a LEUCINE-RICH REPEAT(LRP)-CONTAINING PROTEIN. 97 Table 4.4. Genes and their Arabidopsis thaliana (AT) homologs identified by GWAS with SNP markers associated with root-to-shoot (R:S) ratio, or both root 15N discrimination (15N) and the leaf-root difference in discrimination (15Nroot-leaf) in Populus trichocarpa. Information under “potential significance” comes from the online platform DICOTS PLAZA V4.5 except where otherwise indicated. Trait Gene AT homolog Annotated description Potential significance R:S ratio Potri.010G168500 AT1G26810 Beta-1,3-galactosyltransferase (GALT1) Various types of N-glycan biosynthesis; glycan biosynthesis and metabolism. R:S ratio Potri.002G168200 AT2G46370 JASMONIC ACID-AMIDO SYNTHETASE JAR1 Encodes a jasmonate-amido synthetase that is a member of the GH3 family of proteins; auxin-induced gene and localizes to the cytoplasm. R:S ratio Potri.013G115400 AT1G71860 PROTEIN TYROSINE PHOSPHATASE 1 Encodes a protein with tyrosine phosphatase activity that is downregulated in response to cold and upregulated in response to salt stress. R:S ratio Potri.015G109000 NA Pentatricopeptide repeat protein R:S ratio Potri.005G113000 AT5G66200 ARMADILLO REPEAT ONLY 2 PROTEIN Coexpressed with genes in root specific coexpression subnetwork. R:S ratio Potri.008G194400 AT2G22430 Homeobox associated leucine zipper (HALZ) Encodes a homeodomain leucine zipper class (HD-Zip I) protein that regulates hormone response. R:S ratio Potri.008G118300 AT1G68640 Transcription factor TGA like domain; Basic-leucine zipper domain R:S ratio Potri.011G123700 AT1G52870 PEROXISOMAL MEMBRANE (MPV17/PMP22) FAMILY PROTEIN R:S ratio Potri.013G054600 NA Auxin responsive protein Small auxin-up RNA (SAUR); encodes a short-lived nuclear protein that is related to auxin-mediated cell elongation (Knauss et al. 2003). R:S ratio Potri.007G102900 AT3G22560 ALANINE ACETYL TRANSFERASE-LIKE PROTEIN Differentially downregulated in nitrogen10 in root vs. stem comparison. R:S ratio Potri.007G046200 AT4G36920 AP2-like ethylene-responsive transcription factor Coexpressed with genes in root specific coexpression subnetwork. 98 R:S ratio Potri.001G115200 AT4G22810 Similar to DNA-binding protein-related Highly expressed in root. R:S ratio Potri.003G198900 AT3G14470 LEUCINE-RICH REPEAT-CONTAINING PROTEIN R:S ratio Potri.003G126600 AT1G63490 LYSINE-SPECIFIC DEMETHYLASE LID R:S ratio Potri.010G092900 NA Similar to 4-alpha-D-glucan glucanohydrolase R:S ratio Potri.015G119300 AT1G10180 EXOCYST COMPLEX COMPONENT EXO84C Integral to root growth; helps establish root meristem size and facilitate rapid cell expansion in the elongation zone (Cole et al. 2014). Root 15N & 15Nroot- leaf Potri.007G039700 AT5G66860 Glutaminyl-tRNA synthetase Enzyme responsible for catalyzing the transfer of glutamine to the A76 2' hydroxyl group of tRNA Gln isoacceptors. 99 4.5 Discussion 4.5.1 Leaf discrimination is representative of whole-plant discrimination The first objective of this study was to identify genetic variation in nitrogen isotope discrimination and related traits in poplars at both the clone and population level. Strong genetic variation in 15N and related traits was observed (Table 4.1). Consistent with most other reports in the literature (Kalcsits and Guy 2013, 2016; Driscoll et al. 2021), leaf 15N was lower than root 15N, while stem 15N was intermediate. Leaf 15N was essentially not distinguishable from zero. This was expected based on results reported in chapter 2 (Hu and Guy 2020), where the total 15N of xylem sap was also close to zero (Figure 2.1c) because the 15N-enriched inorganic N (Figure 2.1d) and 15N-depleted organic N (Figure 2.2b) essentially balanced out each other out. Although roots were substantially lighter than leaves, and because leaf nitrogen usually accounted for more than 80 percent of whole-plant N content, the net effect of the differences between organs was for whole-plant 15N to be only 0.76. This is less than reported for heart-leaved willow (Hu et al. 2022). A strong positive correlation between leaf 15N and whole-plant 15N was found for plants grown in batches 1-4 and 9 (r=0.76, Figure 4.2a). The predominance of leaf 15N in determining whole-plant 15N indicates that it should be a suitable proxy for E/I, the calculation of which is based on whole-plant 15N. Indeed, the IMB model-derived E/I correlated strongly with leaf 15N (r=0.72, P<0.001, Figure 4.2b). In addition to leaf 15N, calculated E/I was also significantly but not as strongly correlated with root 15N (r=0.39, Figure 4.3b) and with stem 15N (r=0.27, Appendix Figure C.2). This is not surprising because the calculation of E/I is based on the weighted isotopic compositions of all organs (i.e., whole-plant 15N). In the IMB model, whole-plant 15N is proposed to be a function of two variables, namely E/I and Proot, which are essentially properties of 100 the root (see Equation 2.11). Although root nitrogen accounts for a relatively small proportion of the overall whole-plant nitrogen, and thus has a limited effect on whole-plant 15N, root-based traits have been suggested as contributors of whole-plant nitrogen-use in many studies (Garnett et al. 2009; Kalcsits et al. 2014). Roots can affect whole-plant 15N by changing the assimilation rates and partitioning between roots and leaves, translocation of inorganic and organic N to shoots, and root efflux relative to influx (Kalcsits and Guy 2013a; Kalcsits et al. 2014). Kalcsits and Guy (2013a) showed that whole-plant and organ level 15N in Arabidopsis thaliana was substantially affected in mutant lines with differential expression between roots and shoots of genes involved in nitrogen uptake and assimilation. Consistent with the expectation that N supply relative to N demand might be reflected at the plant level by carbon allocation to organs acquiring nitrogen (i.e., roots), calculated E/I from batches 1-4 and 9 was positively correlated with the R:S ratio (r=0.28, Figure 4.3c). Although both Ti/Tt and Proot were strongly correlated with each other (r=-0.96, Appendix Figure C.2), as they must be algebraically (Equation 2.10), only Proot was significantly correlated with the R:S ratio. Although R:S ratio was correlated with whole-plant 15N (Figure 4.4a), it was not correlated to leaf 15N, root 15N or the difference in 15N between roots and leaves (Figure 4.5). However, the root-leaf difference in 15N was positively correlated to the size of the foliar nitrogen pool relative to the total plant nitrogen (fleaf pool, Equation 2.9) (r=0.3, Appendix Figure C.2). As per equation 2.7, a greater 15Nroot-leaf suggests that a larger proportion of leaf nitrogen is assimilated in the leaves rather than the roots. It appears therefore that genotypes with higher N assimilation in the leaves tend also to invest more N in the leaves. Leaf and root 15N were negatively correlated, albeit weakly so (Appendix Figure C.2). This is to be expected if there is variation in the relative amounts of inorganic 101 versus organic nitrogen being translocated to the shoot. As shown in Chapter 2, organic N translocated in the xylem is depleted in 15N, whereas inorganic N (specifically nitrate) is enriched. Any increase in 15N translocation to the shoot must be balanced by a decrease in 15N in the root, and vice versa. This divergence is the basis for calculating Ti/Tt in the IMB model (Kalcsits and Guy 2013a). 4.5.2 Root-related traits show signals of local adaptation The POPCAN collection of black cottonwood spans 20° in latitude and 16° in longitude (Figure 4.1) within which there is considerable variation in biogeoclimatic conditions. Correlations between traits measured in this study and climate of origin were relatively weak. Within this collection, latitude, longitude, and to some degree elevation, are inter-correlated with each other and with climate variables because the range of black cottonwood runs roughly in a SSE to NNW direction parallel to the west coast of the Pacific Northwest of North America. Unlike results for heart-leaved willow (chapter 3), leaf 15N was not correlated with any geographic or climatic variable and root 15N was only significantly correlated with mean annual precipitation and the annual dryness index. The whole-plant mass was also not correlated to any geoclimatic variables. In contrast, the root-related traits were correlated to many geoclimatic variables. Root C/N and R:S ratio were both significantly correlated to latitude, elevation, continentality, and annual dryness index, while being negatively correlated to mean annual precipitation. In addition, R:S ratio was also negatively correlated to frost-free period. Hence, root 15N, root C/N, and R:S ratio were all correlated to annual dryness index. Canonical correlation analysis was carried out and two similar variates were extracted (Table 4.3). The high end of CLIM1 appears to be associated with conditions typical of the “south coast” because continentality, annual dryness index, and latitude were all negatively loaded heavily on 102 it, while frost-free period and mean annual precipitation were positively loaded. CLIM2 appears to reflect “summer drought” since mean summer precipitation and summer dryness index were heavily loaded on it. Root mass and C/N were negatively associated with “south coast”, but not with “summer drought”. Root 15N was only negatively correlated with “summer drought”. The R:S ratio was negatively associated with “south coast” and positively associated with “summer drought”. Unlike results in willow where leaf 15N was negatively correlated with annual precipitation, root-related traits in poplar were more affected by either annual or summer precipitation. Overall, it appears that there may have been selection towards lower R:S ratios in black cottonwood populations from areas where there is reduced risk of drought. 4.5.3 SNP associations to isotope discrimination and R:S ratio Nitrogen use efficiency is believed to be largely affected by morphological traits such as rooting depth or relative investments of nitrogen in root vs. shoot growth, etc. (Beatty et al. 2010; Safina et al. 2010; Ghoneim et al. 2018). In this study, I selected R:S ratio along with leaf and root 15N as promising traits for GWAS in an attempt to identify NUE-related SNPs/genes. I also included the difference in 15N between root and leaf for GWAS as a proxy indicator for Ti/Tt and, less directly, Proot. Unfortunately, the association analyses with leaf 15N, root 15N, and their difference barely showed any significant association and almost all significant SNPs were related to R:S ratio. Previous GWAS studies for NUE with crop plants reported key genes related to ammonium and nitrate transporters (Huang et al. 2017; Wang et al. 2018; Tang et al. 2019), assimilation enzymes (Gao et al. 2019; Karunarathne et al. 2020; Yu et al. 2021) and root morphology (Karunarathne et al. 2020). The only candidate gene associated with root discrimination and the difference in 15N between leaves and roots codes for a glutaminyl-tRNA synthetase (Potri.007G039700). Although presumably not involved in 103 nitrogen assimilation or transport, glutaminyl-tRNA synthetase is at least involved in nitrogen metabolism, specifically protein synthesis. How this might then impact variation in Ti/Tt remains obscure, but could somehow relate to the availability of glutamine for xylem transport. Glutamine is overwhelmingly the predominant form of organic N translocated in the xylem of Populus (Dluzniewska et al. 2006). In a quantitative trait locus (QTL) study using maize recombinant inbred lines, Li et al. (2005) reported that nearly 70% of the QTLs for NUE overlapped with QTLs for root system architecture. In the present study, two candidate genes associated with R:S ratio were identified that are known to be auxin-related. There are three large families of auxin-response genes, namely AUX/indole-3-acetic acid genes, GRETCHEN HAGEN3 (GH3) genes, and small auxin-up RNA (SAUR) genes (Guilfoyle et al. 1998; Hagen and Guilfoyle 2002). SAURs are related to auxin-mediated cell elongation (Knauss et al. 2003). One the identified auxin-related genes (Potri.013G054600) codes for PtSAUR85 and is expressed mainly in roots and xylem tissues. PtSAUR85 is just one of 108 SAUR genes in Populus trichocarpa (Hu et al. 2018). The other candidate gene (Potri.002G168200) is a GH3 family member and encodes an auxin-inducible jasmonate-amido synthetase (JAR1) involved in pathogen-defense signalling (Suza and Staswick 2008). Since auxin plays a central role regulating the root system (Roychoudhry and Kepinski 2021), these two auxin-related candidate genes may be involved in the control of R:S ratio in black cottonwood. Another promising candidate gene (Potri.015G119300) associated with R:S ratio codes for EXOCYST COMPLEX COMPONENT EXO84C. Functional studies have demonstrated that the exocyst complex (including SEC3, SEC5, SEC6, SEC8, SEC10, SEC15, EXO70, and EXO84) facilitates rapid cell expansion in the root elongation zone (Cole et al. 2014). Another candidate gene (Potri.003G198900) encodes a LEUCINE-RICH 104 REPEAT(LRP)-CONTAINING PROTEIN. Although the functions of this gene remain unknown in poplar, this LRP-protein was identified in another GWAS associated with low nitrogen treatment in barley (Karunarathne et al. 2020). LRP-like proteins include kinases reported to be involved in signal perception and growth in Arabidopsis (Osakabe et al. 2005). 4.6 Conclusion I conclude that black cottonwood, like heart-leaved willow, shows significant heritable variation in 15N and C/N ratios among genotypes and populations, indicating differences in N uptake, assimilation and NUE. Strong correlation between leaf 15N and whole-plant 15N suggests leaf 15N can be a proxy for whole-plant 15N, and thus E/I, in situations where the isotopic composition of the source nitrogen is held constant. Although leaf 15N did not show signs of adaptation to climate, the positive correlation between root 15N and precipitation suggests that nitrate uptake efficiency plays a role in local adaptation to water availability. Genotypes with intrinsically low R:S ratios also showed some tendency to come from less droughty locations. GWAS did not find any associations with genes for assimilatory enzymes and/or nitrogen transporters, and directly implicated only one gene that might be responsible for variation in isotope discrimination. There were, however, several SNP associations for R:S ratio, which was in turn significantly correlated with whole-plant 15N and E/I, providing partial support for my third hypothesis regarding traits affecting the balance between N supply and demand. 105 5. Conclusion The development of the Haber-Bosch reaction in the early 20th century, to convert atmospheric nitrogen gas (N2) into ammonia (NH3), gave rise to a massive global nitrogen fertilizer industry. Although crop production has doubled over the last 80 years, synthetic nitrogen fertilizer in use today is more than eight times higher than it was at the start of the green revolution (1950s) (Wu et al. 2020). A substantial portion of applied fertilizer is lost through leaching and run-off, volatilization, or denitrification (Vitousek et al. 1997; Hirel et al. 2007), which contributes the single largest source of nitrous oxide (N2O) emissions (Udvari et al. 2021). Excessive use of nitrogen fertilizer not only has negative impacts on the environment, but also results in unnecessary economic burden in crop production. Improving nitrogen-use efficiency will be critical for reducing emissions and environmental impacts from agricultural activities. Over the last three decades, progress in improving nitrogen-use efficiency has been limited because of the complexity of nitrogen relations at the whole-plant level, despite large advances in understanding nitrogen uptake and assimilation mechanisms at molecular and physiological levels. Traditional breeding programs have mainly focused on yield-based selection to achieve genetic gains, and comparisons among crop varieties representing historic and modern materials often show associated increases in mass yield, but not nitrogen use efficiency (Duvick 2005). With more emphasis on reducing greenhouse gas emissions and environmental protection, the development of integrated measures of nitrogen-use in plants is of paramount importance. Nitrogen isotope discrimination (15N) is a good candidate trait to provide integrated information about nitrogen fluxes, assimilation, and allocation in plants. The isotope mass balance (IMB) model proposed by Kalcsits et al. (2014) simplified the models proposed by Comstock (2001) and Evans (2001) and combined measured traits 106 such as growth, nitrogen concentration, and isotopic composition (15N) to explain the relationship between nitrogen-use physiology and 15N under steady-state conditions. Previously, the IMB model was partially validated by comparing estimates of E/I using the IMB model to estimates using compartmental analysis tracer efflux (Kalcsits and Guy 2016a). The model was employed to explore intraspecific variation in time-integrated nitrogen-use traits under either nitrate or ammonium-based nutrition (Kalcsits and Guy 2016b). A high degree of genotypic variation was found among growth, nitrogen uptake, and assimilation traits using the IMB model. 5.1 The N isotopic composition of xylem sap For Chapter 2, I set out to further validate and/or improve the IMB model by quantifying the concentration and isotopic composition of nitrogen, and their relative distributions in bulk, organic, and inorganic (nitrate) fractions in xylem sap extracted from black cottonwood. I also assessed diurnal and genotypic variation in these quantities. Assuming xylem loading effectively samples the instantaneous product of nitrate assimilation, as well as the residual substrate, I hypothesized that the difference in isotopic composition between organic and inorganic nitrogen should directly reflect the in vivo isotope discrimination associated with N assimilation by nitrate reductase. The discrimination I observed (~25.1‰) is indeed consistent with recent published in vitro determinations of the discrimination factor. When this value was used in the IMB model, the predicted ratio of inorganic to bulk N in xylem sap (27.0%) very closely matched direct measurement (26.6%), constituting a test for the model. My results suggest the 15Nenzyme used in the IMB model should be higher (at least 22‰ when other literature is considered), and the model prediction can be useful for phenotyping traits related to nitrogen uptake and assimilation in hydroponically-grown plants that rely substantially on root assimilation. 107 As alluded to above, there are some studies reporting discrimination factors for the assimilatory enzymes, mostly for NR and a few for GS. Those experiments all measured the 15Nenzyme in vitro, which means the enzymes were extracted and purified. There is still a need to better constrain the in vivo discrimination factors for these enzymes, especially GS. Although data in Chapter 2 were noisy, the approach taken to compare the 15N values between inorganic (leftover instantaneous substrate) and organic (product) nitrogen in the xylem is promising. I did grow black cottonwood with 5 µM ammonium as the sole N-source (not reported in this thesis) and attempted to analyze the 15N values of xylem sap. I applied two different methods (Holmes et al. 1998; Liu et al. 2014), but both failed because the amount of ammonium in the xylem sap was too low. The most commonly used method (Holmes et al. 1998) relies on ammonia diffusion and has a minimum requirement of 1-10 µmol, however, I was unable to consistently detect ammonium using 1 mL of xylem sap. The denitrifying method cannot be used for measuring 15N of ammonium directly and needs the ammonium to be converted to nitrate in advance through chemical oxidation (Liu et al. 2014). In my case, this method also did not work because the oxidization reaction seemed to be affected by the presence of organic nitrogen in the xylem sap. Therefore, for future in vivo estimation of the 15Nenzyme for GS, it may be worth trying the more recent ammonium tetraphenylborate method described by Stock et al. (2019). I also suggest increasing the source ammonium concentration as much as possible (i.e., without causing ammonium toxicity), which might then exceed the capacity of root assimilation and increase the ammonium transport from roots to shoots. In Chapter 2, one of the main purposes of the first experiment was to establish a reliable protocol for sampling xylem sap. Part of this was to establish whether there were any changes in isotopic composition with position in the transpiration stream or 108 extraction pressure. Although data presented in Chapter 2 are restricted to the shoots, I did in fact attempt to extract xylem sap from root systems by expressing it from the cut stumps. Hence, sap was collected at three different positions (roots, lower shoots and upper shoots) under two different but sequential ranges of extraction pressure, the first being just 0.1-0.2 MPa and the second being 0.6-0.7 MPa above the balancing pressure. By monitoring the ATP content of xylem sap, Schneider et al. (1996) and Geßler et al. (1998) detected negligible contamination originating from parenchyma cells in both roots and shoots at 0.6 MPa above the balancing pressure. However, I found significant differences between root and shoot xylem sap both in N concentration and 15N (Figure A.1). These differences were more pronounced when xylem sap was collected at higher pressure. Total N and NO3- concentrations of root xylem sap were much lower than shoot xylem sap, and their 15N values were closer to the source. These observations immediately suggested that root xylem sap was contaminated with hydroponic media clinging to the roots, presumably entering at breaks caused by the disturbance of being placed into the pressure bomb. Comparison of the organic N concentration of sap extracted from roots and shoots indicated that root xylem sap was considerably diluted by this external reservoir, accounting for over 70% of the fluid collected. Therefore, I suggest that considerable precaution is needed in experiments that rely on pressurization of root systems to obtain xylem sap, for whatever purpose. 5.2 Intraspecific variation in carbon and nitrogen isotopic composition of heart-leaved willow After testing and adjusting the IMB model as indicated above, I investigated intraspecific variation in time-integrated nitrogen-use traits in heart-leaved willow grown under field conditions and in the greenhouse under near steady-state hydroponics. Patterns in foliar δ13C and δ15N between field and hydroponic conditions 109 (which used only nitrate) were similar. I further applied the IMB model to study the individual and population level variation in 13C and 15N of heart-leaved willow. I tested the hypothesis that variation in water-use efficiency (as indicated by 13C) would show a negative relationship with nitrogen-use efficiency (as indicated by tissue C/N ratio) or, through application of the IMB model, be shown to be connected to variation in N uptake efficiency and/or sites of N assimilation and allocation. I uncovered largescale geographic trends in N isotope discrimination in heart-leaved willow associated with genotypic variation in N uptake efficiency, but independent from variation in 13C and C/N ratio. To the best of my knowledge, this is the first demonstration of clinal variation in N isotope discrimination to be reported for any plant species. Since 13C, C/N, and 15N were not inter-correlated, I concluded that natural and/or artificial selection on growth, WUE, NUE and N uptake efficiency can occur without trade-off in heart-leaved willow. My results imply that it is possible to use these indicators for breeding and selection purposes to capture additive genetic gains for nitrogen-uptake, water-use, and nitrogen-use efficiencies without compromising growth and other economic traits (Brendel and Epron 2022). An approach that combines the IMB model with stable isotopes is efficient and straightforward because all of 13C, C/N, and 15N can be measured together on a single sample, and in large numbers, by EA-IMRS. I found similar biogeographic patterns in foliar δ15N and δ13C between field and hydroponic experiments (Figure 3.3). However, unlike δ13C, the genotypic means for δ15N values of leaves and stems did not correlate between experiments and there appeared to be a much steeper latitudinal cline in the field experiment than was found in the greenhouse. As discussed in Chapter 3, data from the common garden experiment may have reflected unexpected co-variation between latitude of origin and soil conditions at the planting site, or differential uptake of other N sources, such as 110 ammonium. With regard to the former, a significant greenhouse vs. field correlation in δ15N might have been found if the AgCanSalix accessions were not blocked by provenance. 5.3 Geographic variation in 15N of black cottonwood and identification of candidate genes by genome-wide association To optimize carbon sequestration efficiencies, fertilizer inputs must be minimized while, at the same time, achieving rapid growth. Genotypic variation in 15N has not been extensively studied in trees at relatively large scale, either in the field or in hydroponic experiments. I took advantage of a substantial collection of black cottonwood genotypes covering a large portion of the species range, to study the natural genetic variation in 15N. Similar to heart-leaved willow, black cottonwood showed significant heritable variation in 15N and C/N ratios among genotypes and populations, indicating differences in N uptake, assimilation and NUE. Although leaf 15N did not show signs of adaptation to climate, there was a correlation between root 15N and precipitation suggesting that nitrate uptake efficiency plays some kind of role in local adaptation to water availability. GWAS did not find any associations with genes for assimilatory enzymes and/or nitrogen transporters, and directly implicated only one gene that might be responsible for variation in isotope discrimination. There were, however, several SNP associations for R:S ratio, which was in turn significantly correlated with whole-plant 15N and E/I, suggesting that the balance between N supply and demand is in part mediated by genes controlling the relative investment in root growth. The genetic association study conducted in Chapter 4 utilized data resulting from the application of a 34 K SNP chip for Populus trichocarpa (Geraldes et al. 2013). Based on whole genome sequencing however, there is a 2.2 million SNP dataset available for 111 the same accessions, as reported in McKown et al. (2019). Since significant genotypic variation in R:S ratio, leaf 15N, root 15N, and 15N(leaf-root) was found (Table 4.1), it makes sense to run another whole-genome wide association using the 2.2 M SNPs to detect more candidate genes, especially for the isotope-based traits. A more recent Bayesian approach would be worth attempting that selects SNP regions piece-by-piece over the whole genome instead of using a single-marker approach (Fernando et al. 2017), thus preserving the statistical power of the analysis. This method is also more efficient when dealing with high-density SNPs (Lima et al. 2022). In both heart-leaf willow (Appendix Figure B.2) and black cottonwood (Figure 4.4), I uncovered a relationship between R:S ratio and E/I. Thus, one approach to improving nitrogen uptake efficiency in plants might be to select genotypes with greater relative root development. Other root morphology traits such as length/depth, thickness, surface area to volume ratio, cortex thickness, and cell size may also influence nitrogen fluxes and the partitioning of assimilation. If any correlation between such traits turned out to be significantly associated with IMB model outputs, further GWAS analyses might be of utility to explore their genetic underpinnings. 5.4 Limitations and future application of the IMB model Most of the work conducted for this thesis involved growing and phenotyping plants in hydroponics under greenhouse conditions. Controlled environment conditions allow for genotypic comparisons that minimize environmental effects, but the results obtained may or may not be relevant to field conditions where, after all, selection takes place. The primary limitation to broad application of the IMB model is the need for hydroponic conditions in order to provide a steady sole nitrogen source with constant nitrogen concentration and 15N; conditions that are not found in nature. The provision of nitrogen from multiple sources, which is likely in the field, would make the 112 interpretation of nitrogen uptake, assimilation, and allocation nearly impossible from an isotope mass-balance perspective. On the other hand, physiological interactions between nitrogen sources are well known, as evidenced by the superior growth often observed when both nitrate and ammonium are made simultaneously available (e.g., Pritchard and Guy 2004). Moreover, mycorrhizal fungi, which can play a major role in nitrogen uptake under natural conditions, are usually not present in hydroponics (Veresoglou et al. 2012). Another major limitation in using the IMB model for purposes of phenotyping is that the approach is not high-throughput. There is also considerable labour and expense associated with the preparation and analysis of all plant parts necessary for the model outputs. In Chapters 2 & 3, where the sample sizes were fairly small, the sampling was relatively straightforward and feasible. However, when the sample size turned into thousands in Chapter 4, we were affected by funding and were able to fully analyze only half of plants (leaves, stems, roots, and original cuttings of ~600 individuals) with the rest being limited to just leaves and roots. Larger plants also require larger hydroponic media volumes to ensure close control of substrate concentration and to stabilize its isotopic composition. This necessitated the use of several 1000 L tanks to grow only 32 plants/tank and required multiple solution replacements over the course of each batch, blocked in time. As noted earlier, resulting batch effects may have contributed error to Chapter 4, potentially interfering with strength of association in the GWAS study. Costs associated with isotope mass spectrometry aside, access to larger facilities (or smaller plants) may allow application of the IMB model to large-scale phenotyping of crop plants. One major advantage of the IMB model as a phenotyping tool for screening in breeding programs would be its ability to estimate the nitrogen uptake efficiency, which is hard to measure directly. This could be of interest to breeders, ideally in 113 combination with 13C, since they can be used together to explore variation in nitrogen-use and water-use traits among dozens, even hundreds of lines within a few weeks. If plants are grown from seed there would be fewer “parts” to prepare, as there would be no need to analyze cuttings to account for the remobilization of pre-existing nitrogen and its contribution to the nitrogen content and isotopic composition of the plant. 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Direct comparison of the denitrifier method to combustion-based method for 15N of three calcium nitrate solutions with the same concentration (5 mM). Shown are meansSD (n=3). 15N from direct combustion (‰) 15N from denitrifier method (‰) [N] (mM) Yield (%) Calcium nitrate solution #1 -1.690.21 -1.910.38 4.88±0.11 98 Calcium nitrate solution #2 2.670.23 2.370.55 4.97±0.21 99 Calcium nitrate solution #3 63.810.45 63.110.32 4.95±0.16 99 133 Table A.2. Concentrations, 15N and 15N values in bulk tissue, soluble N and NO3- in roots of Populus trichocarpa hydroponically grown with 0.5 mM NO3- and a source 15N value of 2.67‰. Soluble N and NO3- were extracted from freeze-dried root tissue using methanol:chloroform:water mixture (12:5:3, v/v/v) as describe in Coleman et al. (2008). Total soluble organic N was calculated as the difference between bulk tissue and NO3-. Shown are meansSE (n=9). [N] (mmol N g dw-1) 15N (‰) 15N (‰) Bulk tissue 2.74±0.05 -2.56±0.25 5.25±0.28 Soluble N 0.59±0.04 7.39±0.87 -4.68±0.86 NO3- Total soluble organic N 0.42±0.02 2.31±0.04 12.80±0.50 -5.38±0.19 -10.08±0.55 8.11±0.22 134 Table A.3. Comparison between root 15N and organic N 15N in the xylem sap at the genotypic level. Mean values (SE) are for five biological replicates. Different letters indicate significant differences at P<0.05. Genotype Root 15N (‰) Organic N 15N in xylem sap (‰) BELA 4 57.230.82ab 57.292.63a CARS 2 56.370.76ab 48.873.52a FNYI 4 55.630.89ab 61.041.03a HALS 2 57.530.42a 54.243.43a STHA 3 54.940.59b 60.291.54a Grand Mean 56.340.35 57.001.26 135 Figure A.1. Concentrations of total N (a) and nitrate (b), and 15N of total N (c) and nitrate (d) in Populus trichocarpa xylem sap collected from roots and lower and upper shoot sections at LP and HP. Bars or symbols represent means of six samples (SE; omitted from panel D because they are smaller than the symbol size). Effects of the main factors pressure and position, and their interaction, are indicated: n.s., not significant; *, P<0.05; **, P<0.01; ***, P<0.001. Dotted lines in panels C and D represent the 15N of NO3- in the hydroponic medium (-1.69‰). 136 0 .0 0 .5 1 .0 1 .5-3 2-3 0-2 8-2 6S D IField13C ( ‰)L e a v e s : r = 0 .1 7 , P < 0 .0 0 1S te m s : r = 0 .2 3 , P < 0 .0 0 10 .0 0 .5 1 .0 1 .5051 01 5S D IField15N ( ‰)L e a v e s : r = 0 .3 6 , P < 0 .0 0 1S te m s : r = 0 .3 0 , P < 0 .0 0 1AB Figure B.1. Carbon and nitrogen isotopes (13C  15N,‰) of heart-leaf willow (Salix eriocephala) leaves and stems from the common garden experiment plotted against summer dryness index (SDI) for population sites of origin. 137 Figure B.2. Heat-map of Pearson’s correlations (r) for biomass and physiological traits for all 21 genotypes of heart-leaf willow (Salix eriocephala) in the hydroponic experiment. Biomass, g; N, nitrogen percentage; C, carbon percentage; C:N, carbon to nitrogen ratio; 15N, nitrogen isotope composition; 13C, carbon isotope composition; WP, whole-plant; Ti/Tt, the proportion of inorganic nitrogen transported from roots to leaves; Proot, proportion of inorganic nitrogen assimilated in the roots; E/I, root efflux/influx ratio. 138 Figure C.1. Lists of genotypes within each batch used for the hydroponic experiment in Chapter 4. 139 Figure C.2. Heat-map of Pearson’s correlations (r) for biomass and nitrogen-related physiological traits for all 362 genotypes of black cottonwood (Populus trichocarpa) in the hydroponic experiment. WP, whole-plant; Biomass, g; N, nitrogen percentage; 15N, nitrogen isotope discrimination; fleafpool the proportion of total plant nitrogen assigned to the leaf pool; Ti/Tt, the proportion of inorganic nitrogen transported from roots to leaves; Proot, proportion of inorganic nitrogen assimilated in the roots; E/I, root efflux/influx ratio.
Thesis/Dissertation
eng
Forestry
Vancouver : University of British Columbia Library
Attribution-NonCommercial-NoDerivatives 4.0 International
Graduate
Guy, Robert D.
Testing, advancing, and applying an isotope mass balance model to investigate nitrogen uptake and assimilation in poplar and willow
Text
Still Image