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An isotope mass balance approach to measure variability in nitrogen fluxes, allocation and assimilation… Kalcsits, Lee Anthony 2013

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An isotope mass balance approach to measure variability in nitrogen fluxes, allocation and assimilation in balsam poplar (Populus balsamifera L.) and other plants  by Lee Anthony Kalcsits  B.S.A. University of Saskatchewan, 2005 M.Sc. University of Saskatchewan, 2008  A THESIS SUBMITTED IN PARTIAL FULFILMENT OF THE REQUIREMENTS FOR THE DEGREE OF  DOCTOR OF PHILOSOPHY in  The Faculty of Graduate Studies (Forestry)  THE UNIVERSITY OF BRITISH COLUMBIA (Vancouver) May 2013 © Lee Anthony Kalcsits 2013  Abstract Populus species or their hybrids are being increasingly used as feedstock for the growing bioenergy industry. To optimize carbon uptake efficiencies, fertilizer inputs must be minimized while, at the same time, achieving rapid growth. The complexity of nitrogen uptake and assimilation in plants and environmental heterogeneity force simplifications that limit improvements in nitrogen-use efficiency. In particular, a lack of integration limits the applicability of many traditional nitrogen-use assays to whole plant nitrogen use. Net nitrogen isotope discrimination has potential to act as a timeintegrated process indicator of nitrogen-use in plants grown under steady-state conditions. The objective of this thesis was to further develop an isotope discriminationbased integrated measure of nitrogen-use that reflects whole plant and organ level nitrogen use. Observed differences in nitrogen isotope discrimination were proposed to be a function of nitrogen isotope discrimination of the assimilatory enzymes, fluxes across the root plasma membrane and translocation of inorganic nitrogen to the shoot. As a test, nitrogen supply and demand was environmentally varied in black cottonwood (Populus trichocarpa (Torr & Gray)) and genetically manipulated with knockout lines of Arabidopsis (Arabidopsis thaliana L.). Changes in isotopic composition (δ15N) were interpretable within the context of the proposed model. Furthermore, efflux/influx (E/I) across the root plasma membrane calculated from the isotope mass balance approach was positively correlated with E/I measured using an established 15N compartmental analysis approach indicating that the isotope mass balance approach produced a reliable measure of E/I. The isotope mass balance approach was then used to determine intraspecific variability in balsam poplar (Populus balsamifera L.), a species used for hybrid poplar breeding. Nitrogen use traits were calculated for 25 genotypes from five climatically dispersed provenances grown hydroponically under steady-state nitrogen conditions with either ammonium or nitrate. Genotypic variation exceeded provenance level variation in most cases and significant variation was observed in growth, nitrogen isotope composition and calculated nitrogen-use traits indicating that there is potential for breeding for nitrogen-use using balsam poplar. The isotope mass balance model ii  presented here provides a new approach for probing integrated nitrogen-use traits in plants, which are often technically difficult to measure.  iii  Preface The research chapters of this thesis were written as a series of manuscripts for publication in peer-reviewed journals. For my role, I designed the experiments and collected and analyzed the data for chapter 3, 4, 5, and 6. For chapter 2, I supplemented the work of another student with additional data and refined their interpretation. For all research chapters, I took the lead in writing the draft manuscripts, in addition to all tables and figures. My supervisor, Rob Guy, developed a preliminary isotope mass balance model, provided assistance with proposal development, experimental design, data interpretation and editing throughout all chapters. A version of Chapter 2 will be submitted for publication as: “Buschhaus H, Kalcsits LA, Guy RD. Changes in nitrogen supply and demand impact nitrogen isotope discrimination by modifying uptake, movement and assimilation in Populus trichocarpa.” A version of Chapter 3 has been accepted for publication in Physiologia Plantarum as: “Kalcsits, LA, Guy RD. 2013. Whole plant and organ level nitrogen isotope discrimination indicates modification of partitioning of assimilation, fluxes and allocation of nitrogen in knockout lines of Arabidopsis thaliana.” A version of Chapter 4 is under review as: “Kalcsits LA, Guy RD. Quantifying remobilization of pre-existing nitrogen from cuttings to developing roots, stems and leaves of Populus balsamifera L. using 15N at natural abundance.” A version of Chapter 5 will be submitted for publication as: “Kalcsits LA, Guy RD. Coherence of independent isotopic measures of nitrogen efflux/influx (E/I) in roots of Populus balsamifera L.” A version of Chapter 6 will be submitted for publication as: “Kalcsits LA, Guy RD. Variation in nitrogen isotope discrimination indicates that genotypic variation exceeds provenance level variation in nitrogen source preference, uptake and assimilation in Populus balsamifera L.”  iv  Table of Contents Abstract ...................................................................................................................... ii Preface ...................................................................................................................... iv Table of Contents........................................................................................................ v List of Tables ............................................................................................................... x List of Figures ........................................................................................................... xiii Acknowledgements ............................................................................................... xviii Dedication ............................................................................................................... xix 1.  Introduction and research objectives....................................................................1 1.1. 1.2. 1.3. 1.4. 1.5. 1.6. 1.7. 1.8.  Plant nitrogen use ................................................................................................ 1 Nitrogen use and availability in natural ecosystems ........................................... 1 Inorganic nitrogen uptake and assimilation in plants .......................................... 3 Utilization of nitrogen isotopes in plant physiology and ecology ........................ 6 Arabidopsis thaliana as a model system ............................................................ 10 Populus as a model system ................................................................................ 10 Research objectives............................................................................................ 12 Impact of research ............................................................................................. 12  2. Changes in nitrogen supply and demand impact nitrogen isotope discrimination by modifying uptake, movement and assimilation in Populus trichocarpa ................. 13 2.1. Summary ............................................................................................................ 13 2.2. Introduction........................................................................................................ 13 2.3. Materials and methods ...................................................................................... 17 2.3.1. Isotope analysis ........................................................................................... 18 2.3.2. Statistical analysis of measured variables .................................................. 19 2.3.3. Calculation of nitrogen-use traits from biomass, nitrogen concentration and nitrogen isotope composition ............................................................................. 19 2.4. Results ................................................................................................................ 25 2.4.1. Plant growth ............................................................................................... 25 2.4.2. Tissue nitrogen concentration .................................................................... 25 2.4.3. Tissue δ15N .................................................................................................. 27 2.4.4. Model-derived nitrogen traits ..................................................................... 27 2.5. Discussion ........................................................................................................... 31 2.5.1. Model assumptions ..................................................................................... 31 2.5.2. Plant growth ............................................................................................... 33 v  2.5.3. Interpretation of plant, leaf and root Δ15N ................................................. 34 2.5.4. Modification of nitrogen supply and demand affects calculated nitrogen use-traits .................................................................................................................... 36 2.6. Conclusion .......................................................................................................... 38 3. Whole plant and organ level nitrogen isotope discrimination indicates modification of partitioning of assimilation, fluxes and allocation of nitrogen in knockout lines of Arabidopsis thaliana ...................................................................... 39 3.1. Summary ............................................................................................................ 39 3.2. Introduction........................................................................................................ 40 3.3. Materials and methods ...................................................................................... 44 3.3.1. Plant material and growth conditions ........................................................ 44 3.3.2. Isotope analysis ........................................................................................... 45 3.3.3. Mass balance calculations .......................................................................... 46 3.3.4. Statistical analysis ....................................................................................... 47 3.4. Results ................................................................................................................ 48 3.4.1. There were morphological differences between lines that were not differentially affected by nitrate availability ............................................................. 48 3.4.2. nia2 and nia1 only show an isotopic phenotype at the organ level while nrt2 shows an isotopic phenotype at the whole plant and the organ level .............. 52 3.4.3. Morphological changes and partitioning of nitrogen and NO3- assimilation between plant organs impact whole plant and organ level isotopic composition.... 54 3.5. Discussion ........................................................................................................... 56 3.5.1. Disrupting nia2 activity decreases root:shoot ratio but does not affect nitrogen concentration, while disrupting nrt2 activity reduces nitrogen concentration and increases root:shoot ratio ........................................................... 58 3.5.2. The distribution of assimilatory activity indicated by 15N mass balance corresponds to the distribution of nitrate reductase expression in roots and leaves 59 3.5.3. Changes in assimilatory demand do not impact efflux/influx but restriction of nitrate transport within root tissue does .............................................................. 62 3.6. Conclusion .......................................................................................................... 63 4. Quantifying remobilization of pre-existing nitrogen from cuttings to developing roots, stems and leaves of woody plants using 15N at natural abundance .................. 64 4.1. Summary ............................................................................................................ 64 4.2. Introduction........................................................................................................ 65 4.3. Materials and methods ...................................................................................... 66 4.3.1. Plant material and experimental design ..................................................... 66 4.3.2. Hydroponics system .................................................................................... 67 vi  4.3.3. Sampling and natural abundance isotope analysis .................................... 68 4.3.4. Correcting for pre-existing cutting nitrogen remobilized to growing plant organs 68 4.3.5. Statistical analysis ....................................................................................... 70 4.4. Results ................................................................................................................ 71 4.4.1. δ15N, growth and nitrogen concentration .................................................. 71 4.4.2. Carry-over nitrogen in new plant growth is dependent on the size of the nitrogen pool in the cutting relative to the nitrogen pool in the new growth .......... 76 4.4.3. Relationships between plant δ15N and biomass were not significant after accounting for carry-over of pre-existing nitrogen ................................................... 76 4.5. Discussion ........................................................................................................... 79 4.6. Conclusion .......................................................................................................... 82 5. Coherence of independent isotopic measures of nitrogen efflux/influx (E/I) in roots of Populus balsamifera L. ................................................................................. 83 5.1. Summary ............................................................................................................ 83 5.2. Introduction........................................................................................................ 83 5.3. Materials and methods ...................................................................................... 86 5.3.1. Plant material and experimental design ..................................................... 86 5.3.2. Hydroponics system .................................................................................... 87 5.3.3. Sampling and natural abundance isotope analysis .................................... 88 5.3.4. 15N efflux apparatus .................................................................................... 88 5.3.5. 15N efflux isotope analysis ........................................................................... 89 5.3.6. Compartmental analysis ............................................................................. 89 5.3.7. Isotope mass balance flux calculations ....................................................... 92 5.3.8. Statistical analysis ....................................................................................... 92 5.4. Results ................................................................................................................ 93 5.4.1. Plant growth ............................................................................................... 93 5.4.2. Compartmental analysis ............................................................................. 96 5.4.3. Independent estimates of net uptake and E/I are correlated ................... 100 5.5. Discussion ......................................................................................................... 100 5.5.1. Compartmental analysis using 15N ........................................................... 105 5.5.2. Compartmental analysis and isotope mass balance estimates of E/I ...... 107 5.5.3. Advantages of the isotope mass balance approach ................................. 110 5.6. Conclusion ........................................................................................................ 111 6. Nitrogen isotope discrimination indicates genotypic variation in nitrogen source preference, uptake and assimilation in Populus balsamifera L. ................................ 112 6.1.  Summary .......................................................................................................... 112 vii  6.2. Introduction...................................................................................................... 113 6.3. Materials and methods .................................................................................... 115 6.3.1. Plant material and experimental design ................................................... 115 6.3.2. Hydroponics system .................................................................................. 115 6.3.3. Sampling and natural abundance isotope analysis .................................. 116 6.3.4. Mass balance calculations ........................................................................ 117 6.3.5. Statistical analysis ..................................................................................... 117 6.3.6. Replication of genotypic differences in calculated nitrogen-use traits predicted from the nitrogen isotope mass balance model. ..................................... 118 6.1. Results .............................................................................................................. 119 6.1.1. Root:shoot ratio and leaf nitrogen concentration was affected by nitrogen source but biomass was not .................................................................................... 119 6.1.2. Source did not affect whole plant Δ15N but organ level Δ15N was affected 119 6.1.3. Proportioning of nitrogen assimilation to the leaves was higher for NO3than NH4+, but genotypic ranking was maintained on either source ...................... 123 6.1.1. Efflux/influx was lower for NO3- than NH4+ and genotypic differences were not similar between sources. ................................................................................... 130 6.1.2. Genotypic and source effects were reproducible in independent experiments ............................................................................................................. 130 6.2. Discussion ......................................................................................................... 130 6.2.1. Balsam poplar grew well on both sources of nitrogen ............................. 135 6.2.2. Time-averaged nitrogen use traits are independent of growth and nitrogen source 136 6.2.3. Differences in efflux/influx and net root uptake between experiments may be explained by temperature-source interactions................................................... 137 6.2.4. Using genotypic differences in calculated nitrogen use traits to improve nitrogen use in poplar .............................................................................................. 138 6.3. Conclusion ........................................................................................................ 138 7.  Conclusion ....................................................................................................... 140 7.1. Deriving integrated nitrogen-use traits from organ level and whole plant nitrogen isotope composition ..................................................................................... 141 7.2. Modifying nitrogen isotope composition of plants through changes in inorganic nitrogen supply or demand ......................................................................................... 142 7.3. Comparisons of efflux/influx (E/I) acquired by independent experiments ..... 143 7.4. Genotypic variation in nitrogen fluxes, assimilation and allocation in balsam poplar .......................................................................................................................... 143 viii  7.5. 7.6.  Limitations of research ..................................................................................... 144 Applications and Future Research ................................................................... 145  References .............................................................................................................. 149 Appendix A – Supplemental measurements ............................................................ 169  ix  List of Tables Table 2.1. List of abbreviations used in the text ............................................................... 20 Table 2.2. Biomass, nitrogen concentration and Δδ15N of roots, leaves and stems from hydroponically grown Populus trichocarpa with 200 or 400 µM NH4+ and ambient or enriched CO2 levels. Letters denote significant differences between treatment means determined by Tukey’s Test. n/s = not significant. ........................................ 26 Table 2.3. Model outputs for hydroponically grown Populus trichocarpa with 200 or 400 µM NH4+ and ambient or enriched CO2 levels. Letters denote significant differences between treatment means determined by Tukey’s Test. n/s = not significant. ....... 28 Table 3.1. Nleaf pool/Ntotal, Ti/Tt, Proot and E/I for the wild type and nia2, nia1 or nrt2 lines of Arabidopsis thaliana grown hydroponically in 100 µM or 1000 µM NO3-. Nleaf pool/Ntotal  = proportion of total plant nitrogen that is leaf nitrogen. Ti/Tt = proportion  of leaf nitrogen that was transported to the shoot as inorganic nitrogen. P root = proportion of plant nitrogen assimilation occurring in roots. E/I = efflux/influx between the substrate and root. Letters denote statistical significance determined by a Tukey’s multiple comparison test (P<0.05). ...................................................... 55 Table 3.2Distribution of NIA1 and NIA2 expression between leaves and roots of Arabidopsis thaliana compared to observed leaf:root proportioning of nitrate assimilation in Col-0 wild type (NIA1 + NIA2), NIA1 only and NIA2 only. Leaf and root GfP (Green Fluorescent Protein) expression were taken as expression in whole leaf and root cortex tissue under standard conditions. Expression data taken from the Bio-Array Resource for Plant Biology Arabidopsis eFP expression browser (http://bar.utoronto.ca/welcome.htm; Winter et al. 2007) ..................................... 60 Table 4.1. Mean measured and, for new tissues, adjusted root, stem, leaf and cutting δ15N values (‰ ±SE; N=75) of Populus balsamifera L. hydroponically grown with nitrate (58.5‰) or ammonium (-0.96‰). ................................................................. 72  x  Table 4.2. Mean root, stem, leaf, cutting and whole plant biomass (g ±SE; N=75) of Populus balsamifera L. hydroponically grown with nitrate or ammonium. ............. 73 Table 4.3. Mean nitrogen concentrations (μmol g dw-1 ±SE; N=75) of roots, stems, leaves and cuttings of Populus balsamifera L. hydroponically grown with nitrate or ammonium. ............................................................................................................... 74 Table 5.1. Root and leaf nitrogen concentration (mmol N g dw-1) for five Populus balsamifera L. genotypes grown with either 500 μM NO3- or NH4+ for 45 days. Means ±SE (N = 2-3)................................................................................................... 95 Table 5.2. Outward fluxes (µmol N g fw-1 h-1) of nitrate (NO3-) and ammonium (NH4+) as estimated from compartmental analysis for five Populus balsamifera L. genotypes grown with either 500 μM NO3- or NH4+ for 45 days. Means ±SE (N = 2-3). ............. 97 Table 5.3. Half-lives of exchange (t1/2) for NO3- and NH4+ of root surface film, apoplastic space and cytoplasm estimated from compartmental analysis for five Populus balsamifera L. genotypes grown with either 500 μM NO3- or NH4+ for 45 days. Means ±SE (N = 2-3)................................................................................................... 98 Table 5.4. Apoplast and cytoplasm nitrate and ammonium concentrations as estimated by compartmental analysis for five Populus balsamifera L. genotypes grown with either 500 μM NO3- or NH4+ for 45 days. Means ±SE (N = 2-3). ................................ 99 Table 5.5. Net nitrate and ammonium uptake (μmol N g dw-1 h-1) estimated from the isotope mass balance approach (IMB) or compartmental analysis (CA) for five Populus balsamifera L. genotypes grown with either 500 μM NO3- or NH4+ for 45 days. Means ±SE (N = 2-3). ...................................................................................... 103 Table 5.6. Efflux/influx estimated by isotope mass balance modelling (IMB) or by compartmental analysis (CA) for five Populus balsamifera L. genotypes grown with either 500 μM NO3- or NH4+ for 45 days. Means ±SE (N = 2-3). .............................. 104 Table 6.1. Mean (±SE) (N=9-15) provenance tissue nitrogen concentration (root [N], stem [N] and leaf [N]) (μmol mg dw-1), the proportion of plant nitrogen allocated to xi  the leaf (Nleaf pool/Ntotal), and net root uptake (μmol mg dw-1 h-1) for five climatically dispersed provenances of Populus balsamifera L. grown with either 500 μM nitrate or ammonium. ......................................................................................................... 120 Table 6.2 Mean and genotype minimum and maximum total biomass (g), root:shoot ratio, tissue nitrogen concentration (root [N], stem [N] and leaf [N]) (μmol mg dw-1), the proportion of plant nitrogen allocated to the leaf pool (N leaf pool/Ntotal), net root uptake (μmol mg dw-1 h-1), tissue Δ15N, the proportion of leaf organic nitrogen assimilated in the leaf (Ti/Tt), the proportion of root assimilated nitrogen exported to the leaves as organic nitrogen (To/Tr), the proportion of plant nitrogen assimilation in the roots (Proot), efflux/influx (E/I), and tissue assimilation (μmol mg dw-1). ........................................................................................................................ 122  xii  List of Figures Figure 2.1. Plant nitrogen fluxes during the uptake of ammonium (NH4+) from the substrate pool and assimilation into either root of leaf organic sink pools. Arrows refer to unidirectional fluxes of nitrogen between pools. To = organic nitrogen translocated to the leaves, Ti = inorganic nitrogen translocated to the leaves. Stem tissue is assumed not to assimilate ammonium and receives organic nitrogen from either the roots (via xylem) or the leaves (via phloem), or a mixture of the two. ... 16 Figure 2.2. Predicted Plant (A), Root (B) and Leaf (C) δ15N relative to source δ15N (0‰) as a function of efflux/influx (E/I), the proportion of nitrogen assimilated in the root (Proot), and the partitioning of total plant nitrogen to the leaves (N leaf pool/Ntotal). Each plane represents a Proot value held constant, while Nleaf pool/Ntotal and E/I vary (Proot is 0.6, 0.7, 0.8, 0.9 and 1 from top to bottom for A & C, and from bottom to top for B). ............................................................................................................................... 24 Figure 2.3. A) δ15N of leaves (empty symbols) and roots (filled symbols), and B) the difference between them (Leaf – Root δ15N), plotted against Nleaf pool/Ntotal for Populus trichocarpa ramets grown with 200 μM NH4+ and ambient CO2 (circles), 400 μM NH4+ and ambient CO2 (squares), 200 μM NH4+ and elevated CO2 (triangles), and 400 μM NH4+ and elevated CO2 (diamonds). Line represent a significant linear correlation between A) Pooled leaf δ15N and Nleaf pool/Ntotal (r=0.233; P = 0.007) and B) Pooled leaf-root δ15N and Nleaf pool/Ntotal (r=0.241; P=0.006) ................................ 30 Figure 3.1. A) Total dry mass (mg) and B) root:shoot ratiofor Col-0 wild type and nia2, nia1 or nrt2 lines of Arabidopsis thaliana grown hydroponically in 100 µM or 1000 µM NO3-. Letters denote statistical significance determined by a Tukey’s multiple comparison test (P<0.05). ......................................................................................... 49 Figure 3.2. A) Leaf and B) root nitrogen concentration (mmol N g dw-1) for Col-0 wild type and nia2, nia1 or nrt2 lines of Arabidopsis thaliana grown hydroponically in 100 µM or 1000 µM NO3-. Letters denote statistical significance determined by a Tukey’s multiple comparison test (P<0.05). .............................................................. 50 xiii  Figure 3.3. Net root uptake (mmol N g dw-1) over 35 days for Col-0 wild type and nia2, nia1 or nrt2 lines of Arabidopsis thaliana grown hydroponically in 100 µM or 1000 µM NO3-. Letters denote statistical significance determined by a Tukey’s multiple comparison test (P<0.05). ......................................................................................... 51 Figure 3.4. Whole plant (grey circles), leaf (clear circles) and root (filled circles) Δδ15N for Col-0 wild type and nia2, nia1 or nrt2 lines of Arabidopsis thaliana grown hydroponically in 100 µM or 1000 µM NO3- (N=10).................................................. 53 Figure 3.5. A) Leaf and B) Root assimilation (mmol N g dw-1) over 35 days for Col-0 wild type and nia2, nia1 or nrt2 lines of Arabidopsis thaliana grown hydroponically in 100 µM or 1000 µM NO3-. Letters denote statistical significance determined by a Tukey’s multiple comparison test (P<0.05). .............................................................. 57 Figure 4.1. Unadjusted (open symbols) and adjusted (closed symbols) δ15N for new growth of the whole plant plotted against biomass for Populus balsamifera L. grown with either A) nitrate or B) ammonium. Each data point represents a genotypic mean (N=3). Correlation coefficients and P-values are placed near each line. ........ 75 Figure 4.2. Percentage of A) pre-existing nitrogen remobilized into new growth and B) percentage contribution of pre-existing cutting nitrogen to total plant nitrogen in Populus balsamifera L. grown with either nitrate or ammonium. Bars are means ±SE (N=75). ....................................................................................................................... 77 Figure 4.3 Unadjusted (open symbols) and adjusted (closed symbols) δ15N for new growth of the whole plant plotted against the percentage contribution of carry-over nitrogen to new growth of Populus balsamifera L. supplied with either A) nitrate or B) ammonium. Each data point represents a genotypic mean (N=3). Correlation coefficients and P-values are placed near each line. ................................................ 78 Figure 5.1. Representative segmental linear regression for determining half-lives of exchange and flux rates for the surface (A), apoplastic (B) and cytoplasmic (C) compartments. Each data point represents the log (efflux rate) at x-elapsed time (s). ................................................................................................................................... 90 xiv  Figure 5.2. A) Total biomass and B) root: shoot ratio for five Populus balsamifera L. genotypes grown with either 500 μM NO3- of NH4+ for 45 days. Means ±SE (N = 5-6). ................................................................................................................................... 94 Figure 5.3. Coherence of estimates of net uptake (μmol N g dw-1 h-1) by compartmental analysis and nitrogen isotope discrimination for five Populus balsamifera L. genotypes grown with either 500 μM NO3- (open circles) of NH4+ (closed circles) for 45 days. Means ±SE (N = 2-3). The dotted line indicates significant geometric mean regression (P=0.0131). The solid line shows the position of a 1:1 relationship...... 101 Figure 5.4. Coherence of estimates of efflux/influx by compartmental analysis and nitrogen isotope discrimination for five Populus balsamifera L. genotypes grown with either 500 μM NO3- (open circles) of NH4+ (closed circles) for 45 days. Means ±SE (N = 2-3). The dotted line indicates significant geometric mean regression (P=0.0065). The solid line shows the position of a 1:1 relationship. ...................... 102 Figure 5.5. Effects of changing the discrimination factor of the assimilatory enzyme A) or adjusting for discrimination in membrane transport B) on the coherence between estimates of efflux/influx by isotope mass balance modelling and compartmental analysis. In panel A, the dotted line shows the relationship when enzyme discrimination factors of 15.4 and 16.8‰ (dotted line) are used for nitrate reductase and glutamine synthetase, respectively, while the dashed line shows the relationship when 22.6‰ is used for both. In panel B, the dotted line is as above, with adjustments for 15N discrimination during membrane transport of 1 and 2‰ shown by dashed and dashed-dotted lines, respectively. The solid line in both panels shows the position of a 1:1 relationship. ..................................................... 109 Figure 6.1. Total plant biomass ±SE (N=9-15) (top) and root:shoot ratio ±SE (bottom) for five provenances of Populus balsamifera L. grown with either 500 μM nitrate (white bars) or ammonium (grey bars). .............................................................................. 120  xv  Figure 6.2. Root, stem and leaf Δ15N (N = 3) ±SE for 25 genotypes of Populus balsamifera L. from five provenances grown with either 500 μM nitrate (x axis) or ammonium (y axis). ......................................................................................................................... 124 Figure 6.3. Plant Δ15N ±SE (N=9-15) of five provenances of Populus balsamifera L. grown with either 500 μM nitrate (open circles) or ammonium (closed circles). ............. 125 Figure 6.4. The proportion of leaf organic nitrogen assimilated in the leaf (Ti/Tt) (upper) and the proportion of root assimilated nitrogen exported to the leaves (To/Tr) (lower) ±SE (N=9-15) of five provenances of Populus balsamifera L. grown with either 500 μM nitrate (white bars) or ammonium (grey bars). .............................. 126 Figure 6.5. The proportion of nitrogen assimilated in the root (Proot) ±SE (N=9-15) of five provenances of Populus balsamifera L. grown with either 500 μM nitrate (white bars) or ammonium (grey bars). .............................................................................. 127 Figure 6.6. Efflux/influx (E/I) ±SE (N=9-15) of five provenances of Populus balsamifera L. grown with either 500 μM nitrate (white bars) or ammonium (grey bars). ........... 128 Figure 6.7 Root and leaf assimilation rates (μmol N mg dw-1) (lower) ±SE (N=9-15) of five provenances of Populus balsamifera L. grown with either 500 μM nitrate (white bars) or ammonium (grey bars). .............................................................................. 129 Figure 6.8. Efflux/influx (E/I) ±SE (N=9-15) of five provenances of Populus balsamifera L. grown with either 500 μM nitrate (white bars) or ammonium (grey bars). ........... 131 Figure 6.9 Root and leaf assimilation rates (μmol N mg dw-1) (lower) ±SE (N=9-15) of five provenances of Populus balsamifera L. grown with either 500 μM nitrate (white bars) or ammonium (grey bars). .............................................................................. 132 Figure 6.10 Estimates of efflux/influx ±SE (N=3) for two experiments for seven genotypes of Populus balsamifera L. grown with either 500 μM nitrate (solid circles) or ammonium (empty circles). ................................................................................ 133  xvi  Figure 6.11 Estimates of Proot ±SE (N=3) for two experiments for seven genotypes of Populus balsamifera L. grown with either 500 μM nitrate (solid circles) or ammonium (empty circles). ..................................................................................... 134  xvii  Acknowledgements I would like to thank my supervisor and mentor, Dr. Rob Guy, for introducing me to the wonderful world of isotope discrimination. His knowledge of plant physiology, timely advice, patience and attention to detail has helped me become a better researcher and writer. Specifically, his availability and commitment to editing was appreciated. I would also like to thank my committee, Dr. Sue Grayston, Dr. Barbara Hawkins and Dr. Shawn Mansfield for the helpful advice and discussions over the course of my Ph.D. Thank you to all the members of the lab and undergraduate students that have helped me with my experiments. I would also like to thank Shofiul Azam and Limin Liao for technical assistance during construction and sample collection. Thank you to the AAFC Agroforestry Development Centre at Indian Head, SK for providing me access to stock material from the AgCanBaP balsam poplar collection. I would like to extend my appreciation to the isotope labs at the University of Saskatchewan (Myles Stocki), University of California-Davis and here at the University of British Columbia (Alice Chang) that conducted isotope analysis on my samples and provided technical assistance when required. Thank you to the Land and Food Systems greenhouse and, in particular, David Kaplan, for accommodating my hydroponic pools and allowing me to work through the ‘kinks’ of my system and for his patience when problems occurred. A NSERC Discovery Grant to Rob Guy supported the research in this thesis. A NSERC Vanier Canada Graduate Scholarship in addition to a Forestry Graduate Entrance Scholarship and a Forestry Strategic Recruitment Scholarship awarded to Lee Kalcsits provided financial support. I would like to thank my family and friends for their patience and support over the last few years. In particular, I would like to thank my wife for all her patience and understanding over the years. I could not have done this without her behind me.  xviii  Dedication  - To my wife, Jenn and my two children, Hayden and Blake  xix  1. Introduction and research objectives 1.1. Plant nitrogen use Nitrogen is a critical component of proteins, amino acids and DNA, and the fourth most abundant element in organic matter. Given its importance, limitations to nitrogen availability can impact plant growth and development. Nitrogen is one of the limiting plant nutrients in most natural ecosystems (Glass et al. 2002; LeBauer and Treseder 2008) and subsequently, nitrogen fertilization is essential for modern agricultural production. Nitrogen fertilizer use is presently seven times higher than it was at the start of the green revolution (1950’s), but it is also responsible for a doubling in global food production (Hirel et al. 2007). However, high use of nitrogen fertilizer has come at a cost. Much of this nitrogen is not taken up by plants (Raun and Johnson, 1999) and is lost through leaching, denitrification or volatilization (Vitousek et al. 1997). Nitrogen fertilizer production contributes 1.2% to global energy consumption (Ahlgren et al. 2008). This can have negative environmental impacts as well as placing an unnecessary economic burden on producers. The potential of agricultural production of woody plant biomass to supply the growing biofuel industry (Yuan et al. 2008) is progressively leading to improvements in growth rates and yield (Stanton et al. 2010). For efficient production, high yielding biofuel crops must be able to grow with minimal fertilizer inputs on marginal lands, essentially maintaining high nitrogen-use efficiency. Agricultural nitrogen use efficiency is commonly defined two ways (Moll et al. 1982): 1) biomass or yield produced per unit plant nitrogen, or 2) the proportion of available nitrogen taken up by a crop. Improvements to plant nitrogen use efficiency would reduce the environmental impacts of modern agriculture in addition to reducing overall fertilizer requirements and making production feasible on marginal lands. 1.2. Nitrogen use and availability in natural ecosystems Nitrogen is often the limiting nutrient in most natural ecosystems (Glass et al. 2002; LeBauer and Treseder 2008). Forest soils, in particular, are often nitrogen limited. To grow and compete under these limiting conditions, plants have adapted to acquire 1  nitrogen in many different forms, including ammonium, nitrate, free amino acids (Näsholm et al. 1998) and protein (Paungfoo-Lanhienne et al. 2008), as soil derived sources. Other sources include atmospheric nitrogen gas, via nitrogen-fixing plants (Deluca et al. 2002) and absorption of atmospheric inorganic nitrogen (Giesler et al. 2002). Primary nitrogen sources in temperate forest soils include ammonium, nitrate and organic nitrogen (Hӧberg 1997). Total inorganic and organic nitrogen in temperate forests can range from 0.05 to 1.65 kg N m-2 (Callesen et al. 2007). Nitrogen dynamics vary climatically and availability of different nitrogen forms is different between environments (Giesler et al. 1998). Small changes in climate can significantly alter the nitrogen cycle. For example, changes in rates of nitrification, ammonification, nitrogen fixation and denitrification are impacted by changes in temperature and precipitation patterns (Callesen et al. 2007; Hart 2006; Wang et al. 2006). Climatic conditions can not only impact concentrations of inorganic and organic nitrogen in soil, but also modify the dominant inorganic source available to plants (Houlton et al. 2007). Boreal forests generally have higher ammonium and organic nitrogen concentrations in soils than nitrate (Nordin et al. 2001), largely a consequence of acidic soils. Prairie soils with higher pH and more developed soil structure will generally have higher concentrations of nitrate. Since woody plants are relatively longlived species, temporal changes in nitrogen environments are likely encountered over their lifetime. Therefore, woody plants need to compete with other organisms for limited soil nitrogen that is spatially, temporally and chemically heterogeneous. Interspecific competition for nitrogen within plant communities has been extensively studied (Harrison et al. 2007; Weigelt et al. 2005). Plants have been shown to preferentially utilize either nitrate or ammonium. For example, rice (Oryza sativa L.) is known to prefer ammonium, or at least is able to easily metabolize ammonium without the risk of ammonium toxicity (Falkengren-Grerup 1995). This is also true for white spruce (Picea glauca L.) (Min et al. 2002; Pritchard and Guy 2005). However, intraspecific variation in nitrogen uptake and its relationship with environmental conditions is equally important (Harrison et al. 2004). Consequently, there needs to be a 2  more thorough understanding of how woody plants grow on different nitrogen sources and the degree of genotypic variability in nitrogen uptake and assimilation within climatically dispersed plant species. Competition for temporally and spatially variable pools of multiple sources of nitrogen has produced complex uptake and assimilation pathways that are variable across species and communities. 1.3. Inorganic nitrogen uptake and assimilation in plants With the exception of organic nitrogen, uptake of nitrogen in plants directly from the soil is through uptake and assimilation of inorganic nitrogen by roots. Nitrogen uptake changes in response to variation in heterogeneous demand versus supply. Plants must exhibit some degree of plasticity to match uptake with demand for efficient growth and development. There are multiple genes controlling uptake and assimilation and each gene can have multiple isozymes (Glass et al. 2002). Although the specific roles of large gene families are not entirely clear the redundancy of inorganic nitrogen transporters is problematic when trying to functionally characterize precise roles of individual genes (Glass et al. 2002). This, combined with a complex regulatory network for nitrogen use, makes it difficult to observe distinct changes in nitrogen-use as a consequence of single gene disruption. The complexity of the genetic and regulatory network of the nitrogen uptake and assimilation pathway has been emphasized in a significant body of molecular work in the past decade (Britto et al. 2002; Glass et al. 2002; Lea and Azevedo, 2006; Miller and Cramer, 2005). At the whole-plant level, nitrate assimilation is more complex than ammonium. After crossing the root membrane via diffusion or via nitrate transporters, nitrate is converted to nitrite in the cytoplasm by a NADPH- or NADH-catalyzed nitrate reductase (Campbell 1988). Nitrite is then immediately transported into the chloroplast where nitrite reductase converts nitrite to ammonium (Wallsgrove et al. 1983). Much of our functional understanding of inorganic nitrate transport has been gained from experiments using Arabidopsis (Arabidopsis thaliana L). Nitrate uptake has been shown to occur via two uptake pathways; a high-affinity uptake system (HATS) and a lowaffinity uptake system (LATS) (Glass et al. 2002). HATS transporters are saturable, exist 3  in both constitutive and induced forms, and are active at low nitrate concentrations (~100 µM range). It is possible that constitutive forms act as sensors that, in turn, activate inducible HATS transporters. LATS transporters are unsaturable, active at higher nitrate concentrations and thought to only act constitutively. In Arabidopsis, three gene families; NRT1, NRT2 and NRT3 (NAR2), have been identified as nitrate transporters (Lea and Azevedo, 2006; Plett et al. 2010). NRT1 has eight genes, NRT2 has seven genes, and NRT3 has two genes in Arabidopsis (Williams and Miller, 2001; Orsel et al. 2002; Plett et al. 2002). NRT1 transporters are functional at a wide range of substrate concentrations and some NRT1 isozymes act as both HATS and LATS transporters (Guo et al. 2002). In contrast, inducible NRT2 genes perform at HATS concentrations (Okamoto et al. 2003). Different NRT1 and NRT2 transporters exist in grass species compared to Arabidopsis (Plett et al. 2010). The regulation of nitrate uptake and assimilation in plants is necessary to optimize nitrogen utilization. Nitrate transport and assimilation are tightly regulated and as such, the network controlling this activity requires adaptability to take advantage of available nitrogen. Changes in environmental conditions have been shown to either induce or downregulate transporter activity. For example, the presence of nitrate increases NRT2.1 transporter activity (Nazoa et al. 2003) and nitrate reductase activity (Redinbaugh and Campbell 1991). However, other environmental stimuli, such as light and sucrose, do not result in significant changes in gene expression of NRT2.1 (Wirth et al. 2007). Vidmar et al. (2000) reported downregulation of NRT2.1 expression and nitrate influx in response to addition of downstream amino acids. The HATS transport system is thought to be post-transcriptionally regulated (Glass et al. 2002). To support this, Laugier et al. (2012) demonstrated that NRT2.1 protein abundance decreased under conditions where HATS decreased, demonstrating post-transcriptional regulation of HATS activity by the downregulation of NRT2.1 in Arabidopsis. Glutamine and ammonium were both found to post-translationally inhibit transporter activity (Glass et al. 2002). Like nitrate transporters, nitrate reductase is induced by the presence of nitrate in addition to light and oxygen (Kaiser and Huber, 2002). The balance of nitrate 4  supply mediated by transporter activity and demand mediated by nitrate reductase activity must be carefully regulated to ensure adequate, but still efficient supply of organic nitrogen to the plant. Ammonium is a more direct and readily available form of inorganic nitrogen to plants (Loqué and von Wirén 2004) and is assimilated into glutamine by ATP-dependent glutamine synthetase. Similar to nitrate, there are two uptake systems; a high-affinity uptake system (HATS) active at low ammonium concentrations, and a low-affinity uptake system (LATS) active at high ammonium concentrations. Many plants have difficulty growing in ammonium-only nitrogen since cellular proton balance and consequently, pH are disrupted by rapid influx of ammonium. One hypothesis explaining this phenomenon is futile cycling of ammonium whereby cytoplasmic ammonium homeostasis is disrupted in plants susceptible to ammonium toxicity such as barley, but is maintained in tolerant plants such as rice (Britto et al. 2001). Essentially, susceptible plants are unable to regulate the influx of ammonium into the cell. As such, there is significant leakage from the cell that creates a proton imbalance and cellular pH becomes more acidic causing damage to the plant. Although there is a good functional understanding of nitrogen uptake and assimilation at the molecular level, the complexity of the system limits the integration of whole-plant uptake and assimilation into molecular physiology. As knowledge of regulatory pathways and interactions, as well as the development of a complete nitrogen uptake and assimilation model become more complete, there will be a demand to integrate this valuable molecular knowledge into the whole-plant context (Hirel et al. 2001, Glass et al. 2002). There is also evidence that there is significant species variation in ammonium transporters (Lea and Azevedo, 2006) and nitrate transporters (Plett et al. 2010). Furthermore, within species variability in inorganic nitrogen transport may reflect differences in allelic variation of genes responsible for uptake and movement of inorganic nitrogen. To date, minimal work has been done characterizing intraspecific variation in nitrogen use traits at the molecular or physiological level.  5  1.4. Utilization of nitrogen isotopes in plant physiology and ecology Isotopes in biology have mainly been employed in tracer experiments to examine the movement of targeted elements within pathways, organisms or ecosystems. In addition, stable isotopes can provide process information and have been used in plant research to answer questions on allocation, assimilation and uptake of elements during plant growth and development. Stable isotopes that have been commonly used in physiological studies include 2H, 13C, 15N and 18O. Technological advances in mass spectrometry in the past two decades have allowed for rapid determination of natural abundance ratios in materials ranging from soil to plants (Handley and Raven, 1992). The use of stable isotopes in biology has increased rapidly as a result. Natural abundance measurements indicate the ratio of the less abundant, naturally occurring isotope relative to the predominant isotope for that element. For nitrogen, carbon and hydrogen, natural abundance stable isotope ratios are indicated by 15N/14N, 13C/12C and 2  H/1H isotope ratios, respectively. Natural abundance ratios are commonly expressed  relative to an internationally accepted reference material as (Dawson et al. 2002): δxE (δ15N) = 1000 *(Rsample/Rstandard – 1), ‰ Where, in the case of δ15N, Rstandard is the 15N/14N ratio of air dinitrogen gas (0.00365) and Rsample is the 15N/14N ratio of the measured sample. Substances with isotope ratios that are greater or lower than the reference abundance ratio are referred to as enriched or depleted, respectively (Peterson and Fry 1987). Stable isotope ratios at natural abundance can be used as integrators of elemental cycling and dynamics to determine net outcomes of many biogeochemical processes that often vary spatially and temporally, and are a function of the surrounding environment (Dawson et al. 2002; Handley and Raven, 1992, Robinson, 2001). The most prominent example of the use of stable isotopes at natural abundance in plant physiology is the use of carbon stable isotope composition (δ13C) as a measure of water-use efficiency (Farquhar et al. 1982) and identification of photosynthetic pathways between C3 and C4 plants (Smith and Epstein 1971; O’Leary 1981). Analogous 6  to carbon assimilation, the emerging approach of using δ15N to provide information on nitrogen fluxes, assimilation and allocation has gained recent attention (Handley et al. 1997; Robinson et al. 2001; Evans 2001; Comstock 2001; Houlton et al. 2007; Cernusak et al. 2009). However, poor mechanistic understanding of nitrogen isotope fractionation has limited applications of this approach. Since nitrogen isotope fractionation is thought to be a function of nitrogen assimilatory demand interacting with efflux/influx (E/I) across the root membrane (Comstock 2001), it represents a whole-plant measure of the impact of changes to overall plant nitrogen fluxes, assimilation and allocation. Currently, the use of δ15N values in plant physiology has included associating 15N natural abundance with water availability from a global database (Handley et al. 1999) and genotypic diversity in drought and salinity tolerance (Yousfi et al. 2009; Yousfi et al. 2012; Yousfi et al. 2013). The most prominent example is the use of δ15N to examine balance between nitrogen uptake versus fixation (Broadbent et al. 1982; Rennie and Kemp 1983). Other examples of studies using 15N natural abundance values as integrators of biogeochemical processes include CO2 (Bassirirad et al. 2003), nitrogen source (Hietz et al. 2002; Kahmen et al. 2008), and nitrogen-phosphorus interactions (McKee et al. 2002). Results, particularly from the field, are often variable and can make interpretation of nitrogen-use physiology difficult. As current and future mechanistic models become more refined, the advantages of using this method for answering questions related to plant physiology and ecology should become more applicable. Different biochemical pools of nitrogen, from small (e.g. a leaf protein) to large (e.g. atmospheric N2) have different isotopic compositions or “signatures”. Differences in signatures can be used to infer sources of nitrogen as it is mixed or moved through plants, soils or ecosystems. Often, plant-based (most often foliar-based) isotope measurements are used to infer temporal or spatial changes in nitrogen source, concentration and availability (Houlton et al. 2007; Miller and Bowman, 2002). Differences in isotope signatures reflect fractionation of isotopes caused by isotope discrimination. Nitrogen isotope discrimination (i.e. the change in isotope composition of the product relative to the substrate) is also emerging as a valuable tool to measure 7  changes in nitrogen dynamics within ecosystems (Högberg, 1997). Nitrogen isotope fractionation may affect the similarity of whole plant and organ level isotope composition to its environmental sources. Since these measurements provide integrated values of the sum of multiple biogeochemical processes, it is difficult to distinguish between isotopic fractionation at different steps within the system. Therefore, to better utilize natural abundance values collected during field experiments, a more complete understanding of nitrogen isotope discrimination during nitrogen uptake and assimilation is required. Advances in linking measured natural abundance isotope ratios with nitrogen-use physiology would address some of the assumptions made during interpretation of natural abundance values measured under field conditions. Conversely, plant and organ differences in nitrogen isotope discrimination may also provide illumination of integrated nitrogen-use physiology in plants. For example, plant δ15N values may also reflect nitrogen uptake efficiency which is inversely related to the ease with which a plant is able to draw nitrogen from its surrounding environment. Net plant discrimination, where 14N is favoured over 15N, is thought to occur during the irreversible step of assimilation, either in roots or shoots (Mariotti et al. 1982; Mariotti et al. 1983; Comstock, 2001; Evans, 2001). Generally, estimates in the literature are 16.5 and 15‰ for glutamine synthetase (Yoneyama et al. 1993) and nitrate reductase (Ledgard et al. 1985), respectively. However, these values are poorly constrained. Past research used partially purified enzyme from crude plant extracts that provided inconsistent estimates of maximum enzyme discrimination factors. Recent work suggests that discrimination for nitrate reductase is greater than 15‰ and more likely around 22‰ (Needoba et al. 2004; Tcherkez and Farquhar, 2006), or as high as 26‰ (Karsh et al. 2012). Although glutamine synthetase may also have a greater discrimination factor, there have been no suggestions that the estimate by Yoneyama et al. (1993) is incorrect. Isotope discrimination during nitrogen uptake and assimilation in higher plants has not been extensively studied. Often, the assumption is that plant-based 15N 8  measurements in the field are a reflection of the source isotopic signature (Houlton et al. 2007). However, isotope discrimination may occur, even in the field. Although it is conceivable that nitrogen isotope discrimination may yield information on the efficiency and location of nitrogen uptake and assimilation in higher plants, some of the underlying hypotheses describing the contributions of plant physiology to nitrogen natural abundance ratios in plant tissue need to be empirically tested. Enzyme discrimination factors for nitrate reductase and glutamine synthetase can be used as coefficients for proposed models of nitrogen isotope discrimination. Comstock (2001) and Evans (2001) both developed similar models describing the mathematical basis for nitrogen isotope discrimination. In these models, nitrogen isotope discrimination is, at least in part, a reflection of the ease with which a plant is able to draw inorganic nitrogen from its surrounding environment into its roots to match assimilation demand (enzymatic assimilation). Although both models propose different approaches to measuring inorganic and organic nitrogen pools, both suggested that nitrogen isotope composition of leaves and roots are indicative of nitrogen fluxes, assimilation and allocation in plants. However, technical difficulty in the sampling required limited the application of the model proposed by Comstock (2001). Evans provided a more simplistic model that connects the location of assimilation and E/I to nitrogen isotope composition. Comstock (2001) measured cytoplasmic pools to determine fractionation within the plant. However, this requires the assumption that isotopic composition of cytoplasmic pools is consistent across diurnal cycles and plant development. Measurements of cytoplasmic inorganic nitrogen are methodologically difficult and require assumptions (such as diurnal stability) that may be incorrect. While these models provided some insight into physiological processes contributing to whole plant and organ level nitrogen isotope composition in plants, application of these models to derive nitrogen-use traits from input measurements is either technically difficult or impossible.  9  1.5. Arabidopsis thaliana as a model system Arabidopsis thaliana L. is a herbaceous member of the mustard family (Brassicaceae). The Arabidopsis genome was the first plant genome to be sequenced (Arabidopsis Genome Initiative, 2000) and Arabidopsis has been used as a model plant system because of its short life cycle (seed to flower in 20 to 40 days), wide geographic range (global distribution) and easy propagation. These advantages have spurred a large body of research dedicated to Arabidopsis physiology. Additionally, it has been used as a system for functionally characterizing the role of genes and gene families. Large selections of described t-DNA insertion and gamma-ray mutant lines are available for experiments. Of relevance to studies on nitrogen uptake and assimilation, t-DNA lines were produced using an Agrobacterium floral dip that randomly inserted a marker gene for kanamycin resistance on the genome (Krysan et al. 1999). Then, each seed was grown to confirm the location of the insertion and then homozygous lines were selected that did not segregate for the insertion. Gamma-ray lines were produced by exposing flowers to gamma-radiation and screening for chlorate-resistance. Chlorate is an analog for nitrate and also used by nitrate reductase to produce toxic chlorite. Therefore, chlorate resistance is an indication of low nitrate reductase activity. These described and non-described mutant lines are curated by the Arabidopsis Biological Research Centre (ABRC) and available for researchers. Furthermore, there have been multiple sets of other transgenic lines developed to answer questions on aspects of molecular, cellular and whole plant physiology. 1.6. Populus as a model system Black cottonwood (Populus trichocarpa (Torr. & Gray)) was the first tree species to have its genome fully sequenced (Tuskan et al. 2006). Along with Salix, the genus Populus consists of a number of woody species in the willow family (Salicaceae). Sequencing of the black cottonwood genome provided a genetic map from which to approach physiological questions related to function, regulation and allelic variation of specific genes. Poplar is an ideal model system for physiological studies because of relative ease of propagation, rapid growth and an established research base from which 10  to draw information (Brunner et al. 2004). Balsam poplar (Populus balsamifera L.) and P. trichocarpa (syn. P. balsamifera ssp. trichocarpa) inhabit one of the largest geographic ranges for a woody plant “species”. Balsam poplar has a particularly large climatic range with the ability to survive across a broad range of climates from prairie to high-altitude to boreal forest-tundra transition as well as coastal climates. The range extends across most of Canada and northern United States (Petersen and Petersen, 1994). The AgCanBaP collection of balsam poplar, collected from 2004 to 2010 by the AgriEnvironment Services Branch of Agriculture and Agri-Food Canada, consists of 15 genotypes from each of 62 provenances spanning the geographic range of the species (Soolanayakanahally, 2010). This range produces variability in ecophysiological traits to survive across different climates. Soolanayakanahally et al. (2009) identified differences in phenology, photosynthetic 13C isotope discrimination and growth rate between northern and southern populations of balsam poplar. Other traits that may vary over this range include nitrogen uptake efficiency and source preference. Balsam poplar is one species used in hybrid poplar breeding programs for biofuel feedstock and identification of variation in nitrogen-use traits across its range may prompt efforts to consider nitrogen-use efficiency during breeding and selection. Poplar has potential as a feedstock for the growing bioenergy sector (Yemshanov et al. 2008). Currently, poplar has been shown to have a negative net carbon balance for biofuel production (Stanton et al. 2010). However, efforts to improve biomass yields will either result in higher fertilizer inputs or the requirement to grow on less marginal lands. To improve yields but maintain low fertilizer requirements, nitrogen-use efficiency must be addressed. Nitrogen-use traits have not been explored in natural species of poplar commonly used in breeding programs and therefore would be an important contribution to poplar research.  11  1.7. Research objectives For my thesis, the five research objectives were to: 1. Test and improve a proposed nitrogen isotope mass balance model explaining nitrogen isotope composition under steady-state conditions by varying environmental nitrogen supply and physiological demand in black cottonwood (chapter 2). 2. Test the isotope mass balance model by varying nitrogen supply and demand in knockout lines of Arabidopsis (chapter 3). 3. Compare estimates of E/I using the isotope mass balance model to E/I measured using the already established 15N compartmental analysis in five balsam poplar genotypes grown hydroponically with nitrate or ammonium (chapter 5). 4. Quantify and account for pre-existing nitrogen remobilized from vegetative cuttings to growing tissue of balsam poplar (chapter 4). 5. Determine if variation in nitrogen fluxes, assimilation and allocation exists among genotypes of five climatically dispersed balsam poplar provenances grown with either nitrate or ammonium (chapter 6). 1.8. Impact of research Poplar species with intraspecific variation in nitrogen fluxes, assimilation and allocation represent an important genetic resource for future improvement to maintain or improve on the ability to produce bioenergy feedstock with minimal fertilizer input. More broadly, validation and/or improvement of proposed models for nitrogen isotope discrimination and application to intraspecific variation in nitrogen uptake and assimilation patterns would have applications from molecular physiology to plant ecology. Furthermore, as has been the case with carbon isotopes (Farquhar et al. 1989), a workable model of nitrogen isotope discrimination and isotope mass balance in plants would help bridge the gap between ecology and physiology and draw on strategies from both disciplines to answer questions related to nitrogen uptake and assimilation in natural populations of poplar and other plants. 12  2. Changes in nitrogen supply and demand impact nitrogen isotope discrimination by modifying uptake, movement and assimilation in Populus trichocarpa 2.1. Summary Fractionation of nitrogen isotopes between the substrate and the plant occurs during uptake and assimilation of inorganic nitrogen. Variation in isotopic composition (δ15N) can also occur at the organ level. Here, a mass balance model combining measurements of δ15N and nitrogen content is proposed to explain whole plant and organ level variation in δ15N. Discrimination is suggested to be a function of nitrogen efflux back to the substrate relative to gross uptake at the root (efflux/influx), the proportion of net uptake assimilated in the roots, and the export of remaining nitrogen for assimilation in the leaves. To manipulate demand relative to supply, rooted Populus trichocarpa (Torr. & Gray) cuttings were grown hydroponically under 200 or 400 μM NH4+ and 400 or 800 μL L-1 CO2. Discrimination was reduced in plants grown under 800 μL L-1 CO2. Partitioning of nitrogen to the leaves was greater with 400 μM NH4+ (70% plant N in leaves) compared to 200 μM NH4+ (58% plant N in leaves). Furthermore, our analysis indicates that increased demand under high CO2 caused decreased efflux/influx (E/I). Most assimilation occurred in the roots, but approximately 7% was in leaves, irrespective of treatment. The model presented here provides a series of timeintegrated measurements of nitrogen fluxes, allocation and assimilation in plants that are difficult to obtain using traditional, time-point assays. 2.2. Introduction Poplar has significant potential as a renewable resource for bioenergy applications (Yemshanov et al. 2008). Like other agricultural crops, breeding for increases in yields will correspond to an increased demand for nitrogen fertilizer. To reduce emissions offsetting net carbon uptake from growing poplar for bioenergy, selection for improved nitrogen use must occur. Over the past three decades, there has been substantial progress made towards the understanding of the physiological processes underlying nitrogen uptake and 13  utilization in plants (Glass et al. 2002; Hirel et al. 2007; Masclaux-Daubresse et al. 2010). Nitrogen-use can be divided into three processes; uptake, assimilation, and allocation. Gains in nitrogen-use have been limited, in part, because of the complexity of these three processes. The development of integrated measures of nitrogen-use is needed to corroborate advancements in functional molecular knowledge of nitrogen fluxes to field level improvements of nitrogen-use. Time-integrated measures of different nitrogen-use traits would provide valuable information on relatively long-term nitrogen use that is difficult to measure using established, time-point assays. Nitrogen isotopes at natural abundance have potential to provide process information related to nitrogen fluxes, assimilation and allocation (Robinson et al. 1998; Evans 2001; Comstock 2001). Current understanding of controls on nitrogen stable isotope ratios (expressed as δ15N values) emphasizes the role of the relationship between physiology and nitrogen nutrition (Evans, 2001, Pritchard & Guy, 2005). Change in the δ15N of plant tissues relative to source nitrogen (fractionation) arises through a kinetically determined process whereby during assimilation of inorganic nitrogen, the heavier isotope (15N) is “discriminated” against causing a relatively greater fraction of the lighter isotope (14N) to be incorporated into product (Handley & Raven 1992). The fundamental restriction preventing application of the basic kinetic isotope fractionation model to nitrogen is that nitrogen is usually not available from an open or steady-state environment. For carbon isotope discrimination in plants, air represents an unchanging pool of carbon where isotopic composition and concentration are relatively stable. Therefore, changes in δ 13C reflect physiology of the plant (Farquhar et al. 1982). In contrast, nitrogen in natural environments is spatially, temporally and chemically heterogeneous (Nordin et al. 2001). Localized depletion in the rhizosphere can cause variation in substrate δ15N that may complicate physiological interpretation of plant δ15N values (Robinson 2001). There can be no discrimination if the substrate is fully utilized. As such, to be able to identify nitrogen uptake and assimilation traits using small changes in nitrogen isotopes at natural abundance, the substrate concentration 14  must be homogenous around the roots and, for comparisons, plants must be exposed to the same homogenous environment. Analogous to the fractionation of carbon isotopes during photosynthesis, if these conditions are met, variability in δ15N between and within individual plants will reflect differences in internal physiology rather than the δ15N of the external environment. Nitrogen isotope discrimination (Δ15N) is thought to occur during the assimilation of inorganic nitrogen in roots and leaves into organic nitrogen (Mariotti et al. 1982; Tcherkez 2011). Nitrate reductase and glutamine synthetase, the two enzymes required for assimilation of nitrate and ammonium, respectively, are presumed responsible for nitrogen isotope discrimination. The instantaneous discrimination of these enzymes determines the maximum amounts of discrimination that can occur. Although there have been large ranges in published discrimination associated with these enzymes, best estimates for discrimination by nitrate reductase and glutamine synthetase are 15.4‰ (Ledgard et al. 1985) and 16.8‰ (Yoneyama et al. 1993), respectively. Typically, in nitrogen isotope discrimination experiments, whole-plant Δ15N does not reflect the full discrimination factor of the enzyme, even under steady-state conditions (Evans et al. 1996; Yoneyama et al. 2001; Pritchard & Guy 2005), this implies that assimilation is not the only rate-limiting step. Several models (Robinson et al. 1998; Evans 2001; Comstock 2001) have proposed that net discrimination arises from the partial consumption of the cytoplasmic inorganic nitrogen pool. If a portion of this pool returns to the medium or is lost to the shoot, fractionation relative to the source, or between organs, will occur (Figure 2.1). At the root level, maximum discrimination occurs when the proportion of the cytoplasmic nitrogen lost outside the root, or to the shoot, approaches the amount of nitrogen imported from the substrate. When there is no loss of cytoplasmic nitrogen prior to assimilation, discrimination cannot occur because the entire nitrogen assimilatory pool will eventually be converted to organic nitrogen in the roots. At the whole plant level, net discrimination does not occur if no inorganic nitrogen is lost from the root, irrespective of the ultimate site of assimilation.  15  Figure 2.1. Plant nitrogen fluxes during the uptake of ammonium (NH4+) from the substrate pool and assimilation into either root of leaf organic sink pools. Arrows refer to unidirectional fluxes of nitrogen between pools. To = organic nitrogen translocated to the leaves, Ti = inorganic nitrogen translocated to the leaves. Stem tissue is assumed not to assimilate ammonium and receives organic nitrogen from either the roots (via xylem) or the leaves (via phloem), or a mixture of the two.  16  Since discrimination against 15N occurs in the roots, cytoplasmic inorganic nitrogen will become enriched in 15N (Evans et al. 1996; Yoneyama et al. 2001). Because unassimilated nitrogen from the cytoplasmic pool is the source of inorganic nitrogen transported from the root to the shoot, leaf nitrogen will be enriched relative to the root (Evans et al. 1996; Yoneyama et al. 2001). Cycling across the plasma membrane and partitioning of nitrogen assimilation can therefore be estimated from knowledge of dry masses, nitrogen concentration and δ15N values of roots, stems and leaves. In this paper, I outline a mass balance nitrogen isotope model that uses source-to-sink differences in δ15N of plant tissues to discern how changes in NH4+ and CO2 supply impact nitrogen isotope discrimination in hydroponically grown black cottonwood (Populus trichocarpa Torr. & Gray). 2.3. Materials and methods Common garden stock of three representative, latitudinally dispersed populations of black cottonwood from Jasper River, OR (44°N), Quesnel River, BC (52°N) and Bell-Irving River, BC (56°N) were obtained and pooled into treatments. Uniform, 5 cm cuttings (N = 4) were rooted and grown in a modified Johnson’s (Johnson et al. 1957) hydroponic medium plus either 100 μM or 200 μM (NH4)2SO4, buffered at pH 6.4-6.8 by adding excess powdered CaCO3. Final nutrient composition, excluding Ca(NO3)2, was: 200 μM KH2PO4, 200 μM K2SO4, 100 μM MgSO4, 100 μM CaSO4, and micronutrients: 5 μM Cl, 2.5 μM B, 0.2 μM Mn, 0.2 μM Zn, 0.05 μM Cu, and 50 μM Fe 2+. Plants were grown for 6 weeks in two growth chambers (Conviron E-15, Winnipeg, MB) with either ambient (400 μL L-1) or enriched (800 μL L-1) CO2 (monitored via a Vaisala GMM220) under a 16 hr photoperiod (22 °C:20 °C day: night), equivalent PPFD (450 µmol m-2 s-1) and constant humidity. Both growth chambers shared the same nutrient solutions (each 500 L) which were drawn from common reservoirs and circulated through the media trays in each chamber. Ammonium concentration was closely monitored to prevent substrate depletion using the phenol-hypochlorite method (Solorzano 1969). As ammonium concentration approached 10% depletion, the hydroponic solution was replaced with fresh solution to avoid any significant change in its isotopic composition. 17  2.3.1. Isotope analysis After 6 weeks of growth, plants were separated into leaves, stems and roots, then frozen in liquid nitrogen and stored at -20°C. Samples were freeze-dried and weighed for dry mass, before grinding to a fine powder using a ball-mill (Fritsch Laborgeratebau, Terochem Scientific). From prepared leaf and root samples, 3 ±0.1 mg was weighed into tin capsules (Elemental Microanalysis Ltd., 8x5 mm, D1008) and analyzed for nitrogen isotopes and nitrogen concentration on a Europa ANCA-SL preparation module and a Europa Hydra 20/20 isotope ratio mass spectrometer (University of California Stable Isotope Facility, Davis, CA). A subset of nine stem samples was analyzed for nitrogen isotope composition on Thermo Finnigan Delta plus and Delta plus XL stable isotope ratio mass spectrometers (University of British Columbia Stable Isotope Facility, Vancouver, BC) to confirm that stem δ15N is equal to root δ15N. The complete set of stem samples was then analyzed using an Elementar Vario EL Cube elemental analyzer for nitrogen concentration. Isotopic composition is expressed as δ15N: Equation 2.1 Where, Rsample is the 15N/14N isotope ratio of the sample and Rstandard is the isotope ratio of a known standard (Rstandard (air) = 0.00365). Isotope discrimination is usually denoted by the equation (Farquhar et al. 1989):  Equation 2.2  Since 1+ δ15Nsample/1000 will not deviate significantly from 1 when isotope ratios are close to 0 ‰, discrimination (Δ15N) is well approximated by δ15Nsample - δ15Nsource (Evans 2001; Pritchard and Guy 2005; Kalcsits and Guy 2013). Here, however, leaf, root and stem δ15N were first converted to discrimination values as per equation 2.2 for model calculations. The δ15N of the ammonium salt in the hydroponic solution was 0.96±0.12‰. 18  2.3.2. Statistical analysis of measured variables Analysis of variance with unequal observations per treatment was used to compare treatment means of biomass, root:shoot ratio, Δ15N, nitrogen concentration and total nitrogen of leaf and root tissues. The statistical model is as follows: Equation 2.3 where, μ is the overall mean response, αi is the effect due to the i-th concentration of NH4+, τj is the effect due to the j-th level of CO2 and βij is the effect due to any interaction between NH4+ concentration and CO2 level. Analysis of variance procedure was carried out using Graphpad Prism 6 (La Jolla, CA, USA) to obtain estimates of the means followed by Tukey’s multiple comparison tests to separate means. Where necessary, data were log transformed to meet assumptions of homogeneity of variance and normality. Differences between treatments described as significant are those where P <0.05. 2.3.3. Calculation of nitrogen-use traits from biomass, nitrogen concentration and nitrogen isotope composition Using an isotope mass balance approach, a number of time-integrated nitrogenuse traits can be calculated for plants grown under controlled hydroponic conditions (See Table 2.1 for definitions of abbreviations) assuming: 1. There is minimal loss of organic nitrogen from root or shoot. 2. There is minimal translocation of nitrogen from shoot to root. 3. The Δ15N of the organic fraction in the root is equal to the bulk tissue Δ15N 4. Assimilation is restricted to roots and leaves. 5. Carry-over of isotopically distinct nitrogen in propagules (seeds or cuttings) is inconsequential or already corrected for. Based on assumption 1, the assimilation-averaged net flux of inorganic nitrogen across the root is equal to the total plant nitrogen divided by the root biomass:  19  Table 2.1. List of abbreviations used in the text Variables δ15N Δ15Ni  Definitions The ratio of a sample 15N/14N ratio divided by an international standard (air N2) 15N/14N ratio minus 1. This is expressed as per thousands (‰). Isotope discrimination for a sample or pool (i) expressed as the difference between the source and product δ15N divided by 1 minus the product divided by 1000  fi  The fraction of nitrogen that is i for a given nitrogen pool.  Ni  The nitrogen content of a sample calculated from the biomass and analyzed nitrogen concentration (µmol).  [N]i  The nitrogen concentration of a sample (µmol mg dw-1).  Net Flux  Total plant nitrogen expressed as per unit of root biomass.  Nleaf pool/Ntotal  The fraction of plant nitrogen coming from the general leaf nitrogen pool. This includes a fraction of stem nitrogen and all leaf nitrogen. The proportion of leaf nitrogen (Tt) that was transported to the leaves as inorganic nitrogen (Ti) (expressed as a fraction). The proportion of plant assimilation occurring in the roots (expressed as a fraction). Efflux/influx across the plasma membrane of the root. Efflux is equal to the net loss of inorganic nitrogen from the root. Influx is equal to the gross influx into the root from the substrate.  Ti/Tt Proot E/I  Δenz  The discrimination factor of the assimilatory enzyme.  20  Equation 2.4 The mass balance equation for plant Δ15N is: Equation 2.5 where, Δ15Ni is discrimination and fi is equal to the fraction of tissue nitrogen contributing to overall plant nitrogen content. Although the plant was treated as having three major organs (Figure 2.1), the fourth assumption recognizes the leaves and roots as the major sites of nitrogen assimilation. Stem Δ15N can be predicted by a mass balance equation using the leaf and root Δ15N values as end members: Equation 2.6 that can be rearranged to yield the fraction of stem N that is from the roots (fstem-root) or the leaves (fstem-leaf). For the fraction from leaves, and noting that fstem root = 1 – fstem leaf, Equation 2.7 To partition between leaf and root nitrogen pools and their isotopic signatures, the contributions of each to total plant nitrogen content needs to be determined. The proportion of total plant nitrogen found in the leaf pool (N leaf pool/Ntotal) is then a function of plant tissue nitrogen concentration and tissue mass: Equation 2.8 where, [N]i is the bulk tissue nitrogen concentration. Δ15Nplant can then be simplified as: Equation 2.9 Most root nitrogen will be organic (Δ15Nroot organic), but some small fraction (froot inorganic)  will be inorganic (Δ15Nroot inorganic). Consequently, Δ15Nroot can be expanded and  rearranged to yield Δ15Nroot organic: Equation 2.10  21  Relative to Δ15Nroot organic, Δ15Nroot inorganic is increased by the discrimination factor associated with the assimilatory enzyme (Δenz; here taken to be 16.8‰ for glutamine synthetase). For present purposes, however, I set froot inorganic to zero as per assumption #3 but emphasize that this assumption would be unnecessary if froot inorganic were known. To partition assimilation, it was assumed that all NH4+ translocated to the shoot (Ti; Figure 2.1) enters the xylem in isotopic equilibrium with the root cytoplasmic pool (i.e., Δ15Nxylem inorganic = Δ15Nroot inorganic). Organic nitrogen delivered to the shoot (To; Figure 2.1) is assumed to not differ isotopically from root-assimilated organic nitrogen. Therefore, net leaf discrimination is the mass balance of Δ15Nroot inorganic and Δ15Nroot organic and can be calculated as: Equation 2.11 where, Ti/Tt is equal to the proportion of total leaf pool nitrogen (Tt; Figure 2.1) transported as inorganic nitrogen from the roots and assimilated in the leaves. As is the case for inorganic nitrogen in root cytoplasm, Δ15Nxylem inorganic exceeds Δ15Nroot organic by an amount equal to Δenz. By substituting Δ15Nxylem inorganic in equation 11 with Δ15Nroot organic + Δenz, Ti/Tt can then be calculated by rearrangement: Equation 2.12 According to equation 2.12, if the difference between leaf Δ15N and root Δ15N is equal to Δenz, all leaf nitrogen must be assimilated in the leaves and no organic nitrogen is translocated from the roots. Likewise, if the difference is 0, no inorganic nitrogen is translocated from the roots. Given assumption 2, the proportion of total plant nitrogen that was assimilated in the leaves is a product of Nleaf pool/Ntotal and Ti/Tt. The remaining fraction of plant nitrogen must then be assimilated in the roots (P root):  22  Equation 2.13 Because Ti removes nitrogen from the cytoplasmic pool that then becomes unavailable to root assimilation or efflux (E), whole plant discrimination (Δ15Nplant) is proportional to efflux over influx (E/I) and Proot: Equation 2.14 In equation 2.14, as E/I and Proot approach 1, Δ15Nplant approaches the discrimination factor of the enzyme and likewise, as those two variables approach 0, Δ15Nplant approaches 0. This relationship, expressed in terms of tissue δ15N values, is illustrated in the first panel of Figure 2.2 for realistic ranges of E/I and Proot values. Note that the partitioning of nitrogen assimilation between organs will not itself alter wholeplant or root δ15N (second panel) but will affect δ15Nleaf (third panel) and, by extension, stems (Equation 2.6), because it determines the portion of total shoot nitrogen that is root assimilated. Also note that δ15Nleaf can be greater than the source if Proot and Nleaf pool/Ntotal  are relatively low, and especially if E/I is also low. Plant and root δ15N will still  be lower than the source in all cases. By rearranging equation 2.14, an estimate of E/I can be obtained from: Equation 2.15 Measures of root and leaf assimilation activities are obtained by calculating the amount of plant nitrogen derived from either roots or leaves and expressing it as a function of the biomass of either roots or leaves: Equation 2.16 Equation 2.17  23  Figure 2.2. Predicted Plant (A), Root (B) and Leaf (C) δ15N relative to source δ15N (0‰) as a function of efflux/influx (E/I), the proportion of nitrogen assimilated in the root (Proot), and the partitioning of total plant nitrogen to the leaves (N leaf pool/Ntotal). Each plane represents a Proot value held constant, while Nleaf pool/Ntotal and E/I vary (Proot is 0.6, 0.7, 0.8, 0.9 and 1 from top to bottom for A & C, and from bottom to top for B).  24  2.4. Results 2.4.1. Plant growth Total biomass of black cottonwood was almost two times greater when grown with elevated CO2 compared with ambient CO2 (Table 2.2) (P<0.05). Mean total biomass was 6.25 g for plants grown under enriched CO2 conditions and only 3.77 g when grown under ambient CO2 conditions. Root biomass was significantly lower in low NH4+ and ambient CO2 (P<0.05). Root biomass for plants grown under enriched CO2 conditions was greater than for those grown under ambient conditions. For plants grown under low NH4+, leaf biomass at elevated CO2 was more than two times greater than ambient CO2 (P<0.05). In contrast, the difference in leaf biomass between plants in ambient and enriched CO2 conditions under high NH4+ was not significant. Although NH4+ and CO2 supply affected biomass accumulation, root:shoot ratio was not significantly different between treatments. 2.4.2. Tissue nitrogen concentration Mean nitrogen concentration decreased in plants grown under elevated CO 2 (Table 2.2; P<0.05). Plant nitrogen concentration was 2.4 μmol mg dw-1 and 2.76 μmol mg dw-1 in elevated and ambient CO2, respectively. Plant nitrogen concentration was also affected by nitrogen supply, being 2.5 and 2.66 μmol mg dw-1 for low and high NH4, respectively. Root nitrogen concentration was greater when grown with low NH4+. Plants grown with elevated CO2 had a lower root nitrogen concentration than under ambient CO2 when grown with high NH4+ supply (P<0.05). Interestingly, root nitrogen concentration was greater than leaf nitrogen concentration for plants grown with low NH4+, but the opposite was true for plants grown with high NH4+ supply. Plants grown in elevated CO2 had lower leaf nitrogen concentration (P<0.05). Leaf nitrogen concentration was greater when grown at high NH4+ supply (P<0.05), being highest in plants grown with high NH4+ and ambient CO2, and lowest in low NH4+ and elevated CO2 (P<0.05). Stem nitrogen concentration was considerably less than either root or leaf tissue. Stem nitrogen concentration was approximately 20% greater in plants grown 25  Table 2.2. Biomass, nitrogen concentration and Δδ15N of roots, leaves and stems from hydroponically grown Populus trichocarpa with 200 or 400 µM NH4+ and ambient or enriched CO2 levels. Letters denote significant differences between treatment means determined by Tukey’s Test. n/s = not significant. * Stem δ15N averaged -4.38 ±0.54‰ (±SE, N=9) CO2 Level [NH4+](µM)  Ambient (400 ppm) 200 400  Elevated (800 ppm) 200  400  Plant Biomass (g) Plant [N] (µmol mg dw-1) Plant δ15N (‰) (Plant Δ15N)  3.39 ±0.541 a 2.69 ±0.045 b -3.94 ±0.165 a (2.99)  4.16 ±0.720 a 2.84 ±0.024 a -3.61 ±0.186 ab (2.66)  7.16 ±1.128 b 2.31 ±0.083 d -3.45 ±0.099 b (2.50)  5.33 ±0.812 ab 2.49 ±0.034 c -3.48 ±0.133 b (2.53)  Root Biomass (g) Root [N] (µmol mg dw-1) Root δ15N (‰) (Root Δ15N)  0.47 ±0.088 a 2.92 ±0.026 a -4.75 ±0.144 a (3.81)  0.60 ±0.100 ab 2.63 ±0.038 b -4.57 ±0.176 ab (3.63)  1.00 ±0.214 b 2.92 ±0.051 a -4.21 ±0.109 b (3.26)  0.69 ±0.128 b 2.44 ±0.033 c -4.30 ±0.121 b (3.35)  Stem Biomass (g) Stem [N] (µmol mg dw-1)  1.21 ±0.208 a 1.01 ±0.038a  1.09 ±0.184 a 1.37 ±0.036b  1.83 ±0.290 b 1.17 ±0.042a  1.39 ±0.203 ab 1.37 ±0.037b  Leaf Biomass (g) Leaf [N] (µmol mg dw-1) Leaf δ15N (‰) (Leaf Δ15N)  1.65 ±0.278 a 2.41 ±0.108 b -2.69 ±0.144 b (1.73)  2.47 ±0.447 ab 3.02 ±0.058 a -2.97 ±0.225 ab (2.02)  4.23 ±0.798 c 1.78 ±0.124 c -2.31 ±0.130 bc (1.35)  3.25 ±0.503 bc 2.56 ±0.063 b -2.72 ±0.188 b (1.76)  Root N (% total nitrogen) Stem N (% total nitrogen) Leaf N (% total nitrogen)  21.3±0.93 a 20.6±2.63 a 58.1±1.99 a  14.8±1.73 b 13.6±3.67 b 71.6±2.53 b  24.2±0.88 a 16.7±1.55 ab 59.1±1.07 a  15.1±0.86 b 15.8±1.67 ab 69.1±1.51 b  Root: Shoot Ratio  0.144 ±0.013 n/s  0.157 ±0.009 n/s  0.151 ±0.016 n/s  0.126 ±0.011 n/s  26  with high NH4+ where nitrogen concentrations were 1.08 and 1.37 μmol mg dw-1 for low and high NH4+, respectively. Leaf nitrogen content (Table 2.2) accounted for approximately 58% of total plant nitrogen content in plants grown in low NH4+ conditions and approximately 70% in high NH4+ conditions (P<0.05). Leaf nitrogen content did not vary between ambient or elevated CO2 treatments. Root nitrogen content was greater under low NH4+ and not significantly different between CO2 conditions. Similar to root nitrogen content, stem nitrogen content was lower under high NH4+. 2.4.3. Tissue δ15N Plant δ15N (Table 2.2) was more negative under ambient CO2 than elevated CO2 (-3.78 to -3.46‰, P<0.05). Leaf δ15N was significantly greater than root δ15N in all treatments (P<0.05). Similar to plant δ15N, leaf δ15N was more negative in plants grown under ambient CO2 conditions (-2.89 and -2.52‰ for ambient and elevated CO2 treatments, respectively, P<0.10). Root δ15N was more negative in plants grown at ambient CO2 (-4.66 and -4.26‰ for ambient and elevated CO2 treatments, respectively, P< 0.05). NH4+ concentration did not significantly affect mean plant, root, or leaf δ 15N. Not all stems were analyzed for δ15N in this experiment, but a subset of nine showed that they did not differ from their respective roots. 2.4.4. Model-derived nitrogen traits Trait data based on model outputs are presented in Table 2.3. Because roots and stems had the same isotopic composition, Nleaf pool/Ntotal was equivalent to the per cent total nitrogen found only in leaves. By comparing the difference between leaf and root Δ15N, a measure of the proportion of leaf nitrogen that was assimilated in the root and transferred to the leaf pool (Ti/Tt; Equation 2.12) was obtained. A slightly greater proportion of the total leaf nitrogen pool was root-assimilated in plants grown in high NH4+ (P<0.05). Root assimilation accounted for 90% and 88% of leaf nitrogen at low and high NH4+ supply, respectively. CO2 level did not affect the proportion of leaf nitrogen assimilated in the root. Partitioning of assimilation (Proot; Equation 2.13) was 27  Table 2.3. Model outputs for hydroponically grown Populus trichocarpa with 200 or 400 µM NH4+ and ambient or enriched CO2 levels. Letters denote significant differences between treatment means determined by Tukey’s Test. n/s = not significant. CO2 Level [NH4+](µM) Nleaf pool/Ntotal Ti/Tt Proot E/I Net Root Uptake (µmol N uptake mg root dw-1) Leaf Assimilation Rate (µmol leaf assimilated N mg leaf dw-1) Root Assimilation Rate (µmol root assimilated N mg root dw-1)  Ambient (400 ppm)  Elevated (800 ppm)  200 0.58 ±0.026 a 0.123 ±0.006 a 0.931 ±0.004 n/s 0.247 ±0.010 a  400 0.72 ±0.012 b 0.096 ±0.006 b 0.934 ±0.003 n/s 0.233 ±0.012 ab  200 0.59 ±0.030 a 0.114 ±0.011 ab 0.939 ±0.004 n/s 0.204 ±0.006 c  400 0.69 ±0.023 b 0.095 ±0.010 b 0.939 ±0.005 n/s 0.225 ±0.008 bc  28.57 ±3.814 n/s  23.01 ±1.421 n/s  27.35 ±6.342 n/s  28.02 ±2.415 n/s  0.297 ±0.0159 a  0.293 ±0.0184 a  0.225 ±0.0263 b  0.258 ±0.022 b  15.76 ±1.827 a  18.66 ±1.371 ab  15.91 ±2.296 a  20.31 ±1.702 b  28  not significantly affected by either NH4 or CO2. Approximately 93% of total nitrogen assimilation occurred in roots. Although not quite significant (P=0.077), there was notably a greater proportion (93.9%) of assimilation occurring in the roots of plants grown with elevated CO2. I calculated efflux/influx ratio (E/I) from Proot, plant Δ15N and the instantaneous discrimination factor for glutamine synthetase (Equation 2.9). There was a significant effect of CO2 concentration on E/I at low NH4+ (P<0.05) but not at high (Table 2.3). Mean E/I was not significantly different between low and high NH4+ concentrations. Net flux (μmol N uptake mg root dw-1; Equation 2.4) was not significantly different between treatments. However, leaf assimilation activity (µmol leaf assimilated N mg leaf dw-1; Equation 2.17) was greatest in plants grown under ambient CO2 conditions, which was 20% higher than under elevated CO2 conditions. Since a large portion of nitrogen was assimilated in roots and roots comprise a small proportion of the overall plant, root assimilation (μmol root assimilated N mg root dw-1; Equation 2.16) was more than an order or magnitude greater than leaf assimilation. Root assimilation was greater when plants were grown with high NH4+ and did not differ between elevated and ambient CO2 treatments (P<0.05). The populations of trees used in this study harbor considerable genetic and phenotypic variation. The individual root and leaf δ15N values from plants in all treatments are plotted relative to Nleaf pool/Ntotal in Figure 2.3A. Leaf (and thus total plant) δ15N tended to be more negative at higher Nleaf pool/Ntotal (r=0.233; P=0.007). This tendency was most pronounced in the low NH4+/high CO2 treatment (not shown), which had the least discrimination (and therefore lowest E/I) overall, and is consistent with both Nleaf pool/Ntotal and E/I increasing in the plants that were more N replete. Across all treatments there was a significant relationship (r=0.241; P=0.006) between leaf-root δ15N and Nleaf pool/Ntotal (Figure 2.3B). As Nleaf pool/Ntotal increased, the difference between leaf and root δ15N decreased, consistent with model predictions (Figure 2.2).  29  Figure 2.3. A) δ15N of leaves (empty symbols) and roots (filled symbols), and B) the difference between them (Leaf – Root δ15N), plotted against Nleaf pool/Ntotal for Populus trichocarpa ramets grown with 200 μM NH4+ and ambient CO2 (circles), 400 μM NH4+ and ambient CO2 (squares), 200 μM NH4+ and elevated CO2 (triangles), and 400 μM NH4+ and elevated CO2 (diamonds). Line represent a significant linear correlation between A) Pooled leaf δ15N and Nleaf pool/Ntotal (r=0.233; P = 0.007) and B) Pooled leaf-root δ15N and Nleaf pool/Ntotal (r=0.241; P=0.006)  30  2.5. Discussion The objective was to determine whether changes in nitrogen and carbon supply impact nitrogen isotope composition. Here, I proposed a nitrogen isotope mass balance model explaining whole plant and organ-level nitrogen isotope composition under steady-state conditions to show that changes to nitrogen and carbon supply can alter δ15N of roots and leaves, and modify nitrogen fluxes, assimilation and allocation in black cottonwood. Under carefully controlled conditions, this nitrogen mass balance approach can provide assimilation-averaged measures of nitrogen-use traits that are otherwise difficult to obtain. These estimates are subject to the value taken for Δenz, which has only rarely been measured, and the legitimacy of our other assumptions. Although these assumptions may contribute to potential error in the model, they cannot account for the magnitude of the treatment differences in model outputs observed here. 2.5.1. Model assumptions The first assumption was that there is no loss of assimilated nitrogen from the plant during active, non-limiting growth. Similar to other nitrogen transformations, there are likely to be kinetic isotopic effects associated with either volatilization of NH3 or nitrous oxide emissions from leaves that discriminate against 15N. The reported discrimination factor for volatilization of NH3 is approximately 40‰ (Mariotti et al. 1982). Although there have been observed losses of nitrogen from leaves as NH 3, it is unlikely to be large. Schjoerring & Mattson (2001) reported that 1-4% of shoot nitrogen was volatilized as NH3 from a variety of crop plants and, importantly, that the majority of this loss occurred during senescence, which was carefully avoided. Exudation of organic nitrogen from the root would occur primarily during root mortality or during stress events that result in loss of stability of the plasma membrane (Britto et al. 2001; Kronzucker et al. 2001). Robinson et al. (1998) suggested that exudation of enriched organic nitrogen causes roots to have lower δ15N than leaves. In order to significantly alter isotopic mass balance in this way, organic nitrogen exudation from roots would need to be compound-specific and proportionately high enough to 31  impact δ15N. The difference in δ15N between different forms of organic N rarely exceeds 10‰ (Werner & Schmidt 2002; Gauthier et al. 2012). Hale et al. (1975) provided a range of exudation rates from roots in multiple species, and in all cases, exudation was in the µmol plant-1 week-1 range. Carvalhais et al. (2011) reported similar amino acid exudation rates in maize (Zea mays L.). In the case of poplar grown here, this would amount to an inconsequential fraction of nitrogen lost from the plant. Our second key assumption is the absence of translocation of nitrogen from the shoot to the root. In contrast, Comstock (2001) included translocation from the shoot to the root in their intra-plant discrimination model. Although some organic nitrogen may move into roots via the phloem, this flux will likely be inconsequential to the mass nitrogen budget during active growth, allowing simplification of the model and calculation of the partitioning of assimilation between roots and leaves. Although this condition may not be met under many circumstances, particularly in senescent or perennial plants, it is likely valid for young, rapidly growing poplar harvested prior to any leaf senescence. The concurrence between root and stem δ15N values, in contrast to leaves (Table 2.2), is also consistent with a lack of organic nitrogen transfer to the roots. As per our third assumption, root inorganic nitrogen was not separated from organic nitrogen, and the measured tissue δ15N value was considered to be equal to the organic fraction (i.e., I set froot inorganic to zero in equation 2.10). Since cytoplasmic inorganic nitrogen in the root would be enriched relative to the root organic nitrogen pool, this would enrich root δ15N and cause an underestimation of the isotopic difference between root- and leaf-assimilated organic nitrogen. In turn, the model underestimates Ti/Tt, with consequent effects on the calculation of Proot and E/I. Sampling for cytoplasmic nitrogen content or isotope composition at harvest is possible; however, single time-point measurements are not likely to be stable and may not coincide with time-integrated values. The fraction of inorganic nitrogen in the roots has been shown to vary from 1 to 10%, depending on growing conditions and nitrogen source (Evans et al. 1996; Black et al. 2002; Yoneyama et al. 2001). This fraction increases as substrate concentration increases. Yoneyama et al. (2001), for example, 32  found that the cytoplasmic inorganic nitrogen pool can account for as much as 10% of the overall nitrogen in the root when grown with either 2 or 8 mM NO 3-. Evans et al. (1996) reported much lower fractions of inorganic nitrogen (approximately 1-2%) in roots of tomato (Solanum lycopersicum L.) grown on an ecologically relevant NH4+ concentration (50 μM). If also true of black cottonwood grown at 200-400 μM NH4+, then this could only change the root δ15N by a few tenths of 1‰ which would not impact treatment ranks and would have just a small impact on model estimates. In most scenarios, nitrogen assimilation occurs primarily in the roots and leaves of plants (assumption #4). Although assimilation might also occur in stem tissue, the assimilatory volume would be small in comparison to roots and leaves. There is no information on glutamine synthetase activity in stem tissue, but Hunter (1985) measured nitrate reductase activity in soybean (Glycine max (L.) Merr.) stems and found less than 3% of the activity seen in leaves. In poplar, Black et al. (2002) found a similarly low proportion of nitrate reductase in stems. Thus, I assigned nitrogen assimilation to either roots or leaves, and to treat stem nitrogen as originating from one or the other or both. In this particular experiment, stem δ15N was not different from root δ15N, and therefore all stem nitrogen was presumed to have originated in the root and was assigned to that pool. Finally, with regard to our fifth model assumption, the nitrogen in the stem cuttings used to propagate our plants had a δ15N very close to that of the source (within 1‰) and was well diluted by substantial new growth. Hence, corrections for carryover of pre-existing nitrogen were unnecessary. 2.5.2. Plant growth As expected, increased growth was observed under higher CO2 conditions. Increased growth under elevated CO2 has been observed in many plant systems, including poplar (Stitt & Krapp, 1999; Hymus et al. 2001). However, plants have been shown to “acclimate” to elevated CO2 (Sage et al. 1989). When nitrogen supply cannot keep pace with increased carbon supply, photosynthesis is inhibited and the increased 33  rates of growth from elevated CO2 cannot persist (Reich et al. 2006). For enhanced growth to be maintained under elevated CO2, nutrient supply must match demand. In an open nutrient environment, with minimal depletion of nutrient supply, elevated CO2 should enhance plant growth. Overall, there were no indications of nitrogen deficiency in any treatments. The high plant nitrogen concentrations observed here (Table 2.2) were sufficient when compared to previous literature on poplar (DesRochers et al. 2006). Leaf nitrogen concentration was lower under elevated CO2, likely reflecting a decrease in photosynthetic protein content (e.g., Rubisco) coupled with nitrogen dilution from increases in growth and starch accumulation (Stitt & Krapp 1999). The connection between growth and nitrogen supply is inherent in the ability to match plant growth with nitrogen supply. In this experiment, growth was reduced under low nitrogen conditions but nitrogen concentration was affected to a lesser degree. A similar buffering of nitrogen concentration has been reported in Arabidopsis where biomass increased by an order of magnitude more than tissue nitrogen concentration (Chardon et al. 2010). Tschoep et al. (2009) also observed a decrease in nitrogen concentration in Arabidopsis grown with low nitrogen compared to non-limiting nitrogen. Growth was the plastic response to low NH4+ rather than decreased nitrogen concentration (Tschoep et al. 2008). Similar to our results, Coleman et al. (1993) reported decreased tissue nitrogen concentration under increased CO2 and increased nitrogen concentration with increased nitrogen availability in Amaranth (Amaranthus sp.), but changes in biomass were far more pronounced. 2.5.3. Interpretation of plant, leaf and root Δ15N Because nitrogen assimilation is a discriminatory step, whole plant δ15N should never be greater than substrate δ15N, as was always the case in the present study. Although theoretically expected, consistent 15N depletion of the plant product has only been shown in a handful of studies (Yoneyama et al. 2001; Robinson et al. 1998, 2001; Yoneyama et al. 2001; Kolb & Evans 2003; Pritchard & Guy 2005). Apparently, contrary results (e.g., Evans et al. 1996) may be a consequence of the hydroponic design, nitrogen supply regime, mixed nitrogen sources or organ-specific sampling. Because of 34  restricted mixing and long diffusion distances; sand, perlite or any other structured soil medium could cause localized 15N enrichment of substrate around the roots. Plants may show reduced discrimination if diffusion becomes rate limiting. In either soil or liquid media, periodic addition of nitrogen to maintain a constant supply without completely replacing residual nitrogen can result in an enrichment of the solution over time. In our work, the hydroponics solution was derived from a single source with uniform δ15N values and minimal depletion of the substrate. Since leaf pool nitrogen is considered a closed system (i.e., no loss of nitrogen), Δ15Nleaf is the mass balance between Δ15Nxylem inorganic and Δ15Nroot organic (Equation 2.11) because these are the only sources of leaf nitrogen. Knowledge of the isotopic composition of leaf inorganic nitrogen is inconsequential to the model because the mass balanced sum of leaf-assimilated organic nitrogen (Δ15Nleaf-assimilated) and inorganic nitrogen in the leaves (Δ15Nleaf inorganic) is equal to the Δ15Nxylem inorganic. Comstock (2001) assumed that the isotopic composition of the organic fraction assimilated in the leaves was equal to xylem inorganic nitrogen, and this must be true if all inorganic nitrogen translocated through the xylem is assimilated. However, a certain fraction will be unassimilated at any point in time and cytoplasmic inorganic nitrogen will be enriched in 15  N relative to leaf-assimilated organic nitrogen. In agreement, Gauthier et al. (2012)  recently reported that nitrate δ15N was greater than the organic nitrogen in leaves of rapeseed (Brassica napus L.). Our treatment combinations were designed to modify isotope discrimination by manipulating nitrogen supply relative to demand at physiologically relevant concentrations. Plant δ15N relative to the substrate was more negative under ambient CO2 conditions than elevated CO2 conditions (Table 2.2). This is in contrast to observations of Bassirirad et al. (2003) who showed that leaf δ15N was more depleted under elevated CO2 conditions in the field. The authors attributed this effect to changes in nitrogen cycling processes in the plant/mycorrhizal system. Here, plants were grown hydroponically without mycorrhizae or nutrient diffusion limitations as discussed above.  35  2.5.4. Modification of nitrogen supply and demand affects calculated nitrogen use-traits Physiologically, demand for nitrogen would be lower under ambient CO2 conditions because of reduced biomass and increased nitrogen concentration. Plants more replete in nitrogen should have higher efflux of unassimilated cytoplasmic inorganic NH4+, driven by lower demand. Accordingly, Δ15N and calculated E/I were greater in plants grown under ambient CO2 (Tables 2.2 and 2.3). Under steady-state nutrition, plants grown with elevated CO2 have greater carbon assimilation (Reich et al. 2006) and should be able to supply more energy for NH4+ assimilation, reducing efflux. Total nitrogen content was greater in plants grown under elevated CO2 (Table 2.2). Nitrogen concentration, however, did not affect E/I. Calculated E/I values were comparable with previous estimates of E/I in plants that did not shows signs of NH4+ toxicity (Kronzucker et al. 1995), as in the present study. Britto & Kronzucker (2002) reported high E/I associated with ammonium toxicity results in decreased growth and in some cases, mortality. These ratios were estimated at around 0.76 (Britto et al. 2001), well above the values reported here. In contrast to whole plant and root δ15N values, leaf δ15N can be greater than the source, as explained earlier. Although most leaves were below -0.96‰, a few exceeded this value (Figure 2.3). The difference between leaf and root δ15N was greater for plants grown under low NH4+ conditions than at high. Yoneyama et al. (2001) also found that leaves were enriched in 15N relative to roots in NH4+-grown plants. Evans et al. (1996) observed a positive difference between leaf and root δ15N when tomato plants were grown on NO3- but not on NH4+, reflecting significant nitrate assimilation, but not ammonium assimilation, in shoots of this species. Although NH4+ is largely considered to be assimilated in the roots of plants (Raven & Smith 1976), there is evidence suggesting that some portion of it can be translocated to the leaves. Schjoerring et al. (2002) reported that approximately 11% of overall nitrogen transported to the shoot was transported as inorganic NH4+. The 15N enrichment of leaves relative to roots suggests that in poplar, some NH4+ assimilation does occur in the leaves. Ideally, it would have 36  been desirable to get an estimate of xylem ammonium content and δ15N. However, as for cytoplasmic ammonium, multiple single time-point samples would be required to properly reflect time-integrated values. At the individual plant level across treatments there was a significant negative correlation between the root-to-leaf difference in δ15N and Nleaf pool/Ntotal, most obvious within the low NH4+ and high CO2 treatment (Figure 2.3). Such a pattern might emerge from variation in Proot (Figure 2.2). Given, however, that Proot was essentially invariant with treatment (Table 2.3), from Equation 2.13 it can be concluded that the correlation must reflect opposing variation in both Ti/Tt and Nleaf pool/Ntotal. As Ti would represent a constant proportion of total plant nitrogen if Proot is fixed, then it is only differences in the root-to-shoot export of organic nitrogen that can cause Ti/Tt and Nleaf pool/Ntotal to vary inversely (Figure 2.1). A greater difference between root and leaf δ15N indicates a greater proportion of leaf nitrogen is assimilated in the leaves, but in poplar these proportions are apparently not driven by variation in the relative amount of inorganic nitrogen exported from roots, but rather by variation in the relative amount of organic nitrogen that is retained. At the treatment level, Ti/Tt was unaffected by CO2 regime but was significantly modified by the nitrogen supply. I calculate that 52.8% and 65.4% (P<0.0001) of root-assimilated nitrogen was exported to leaves under low versus high ammonium, respectively. Our model implementation suggests that approximately 7% of NH4+ assimilation occurred in the shoot. Although there may be no active transport of NH4+ into the xylem like there is for NO3- (Lin et al. 2008), some passive movement of NH4+ might occur simply through transpirational pull into the xylem and to the shoot. Cernusak et al. (2009) reported a relationship between transpiration efficiency and the difference in δ15N between the whole plant and root. As the difference increased between the plant and root, transpiration efficiency of nitrogen acquisition increased implying a greater fraction of leaf nitrogen assimilated in the leaf. Partitioning of NH4+ assimilation appears to be less plastic than traits such as E/I and leaf and root assimilation activity. At high NH4+, partitioning of assimilation would have been expected to increase in leaves if the 37  assimilatory capacity of the root did not increase proportionally. A greater increase in available plant nitrogen supply might be expected to exceed this capacity and change overall partitioning, either morphologically or biochemically. In poplar, however, increased growth likely precedes changes in allocation of assimilation. In accordance with the former, root:shoot ratio did not differ between treatments (Table 2.2). 2.6. Conclusion Here, by changing nitrogen and carbon supply to poplar grown under steadystate hydroponics conditions, modulation of nitrogen isotope discrimination was shown at the whole-plant and intra-plant level. Although differences in discrimination were small, treatment level differences were in accordance with expectation. When appropriate simplifying assumptions are made, a tractable model for discrimination allows for the relative comparison of nitrogen-use traits that can be used to identify inter and intra-specific differences in nitrogen fluxes, assimilation and allocation under controlled nitrogen environments. This model can produce time-integrated estimates of nitrogen-use traits such as efflux/influx, partitioning of assimilation and net uptake that are otherwise difficult to assay using more traditional single-point assays.  38  3. Whole plant and organ level nitrogen isotope discrimination indicates modification of partitioning of assimilation, fluxes and allocation of nitrogen in knockout lines of Arabidopsis thaliana 3.1. Summary The nitrogen isotope composition (δ15N) of plants has potential to provide timeintegrated information on nitrogen uptake, assimilation and allocation. Here, existing TDNA and gamma-ray mutant lines of Arabidopsis thaliana L. were used to evaluate the model explaining whole-plant and organ level fractionation of nitrogen isotopes proposed in chapter 2. Nitrate Reductase 2 (nia2), Nitrate Reductase 1 (nia1) and Nitrate Transporter (nrt2) mutant lines and the Col-0 wild type were grown hydroponically under steady-state NO3- conditions at either 100 or 1000 μM NO3- for 35 days. There were no significant effects on whole-plant discrimination and growth in the assimilatory mutants (nia2 and nia1). Pronounced root versus leaf differences in δ15N, however, indicated that nia2 had an increased proportion of nitrogen assimilation of NO3- in leaves while nia1 had an increased proportion of assimilation in roots. These observations are consistent with reported ratios of nia1 and nia2 gene expression levels in leaves and roots. Greater whole-plant discrimination in nrt2 indicated an increase in efflux of unassimilated NO3- back to the rooting medium. This phenotype was associated with an overall reduction in NO3- uptake, and decreased partitioning of NO3- assimilation to the leaves, presumably because of decreased symplastic intercellular movement of NO3- in the root. Although the results were more varied than expected, they are interpretable within the context of the model presented in chapter 2. Using Arabidopsis knockout lines demonstrates that changes to the capacity to either assimilate or acquire nitrate can modify nitrogen isotope composition of plants.  39  3.2. Introduction Reducing the need for nitrogen fertilizer in global agricultural production represents one of the major challenges in the plant sciences. Nitrogen uptake and assimilation is a complex process that is a function of internal demand interacting with external supply. Although the localization and functional role of genes related to nitrogen uptake and assimilation have been well constrained, an integrated method of measuring nitrogen-use during the complete plant life cycle still needs to be developed (Hirel et al. 2007). Traditional measures of nitrogen uptake and assimilation are often not conducive to an integrated view of nitrogen use without intensive and careful sampling to reflect temporal and spatial variability in expression, activity and regulation. Using nitrogen isotope composition of plants and plant parts has potential to provide time-integrated information on nitrogen use at the whole plant and organ level. Nitrogen isotope discrimination is hypothesized to be a function of nitrogen-use and provides an integrated picture of nitrogen uptake and assimilation that cannot be provided by traditional nitrogen-use assays (Evans, 2001). Abiotic stress (Yousfi et al. 2009; 2012), nitrogen availability (Chapter 2), source (Evans et al. 1996), and CO2 enrichment (Chapter 2) can all impact whole-plant and organ level nitrogen isotope discrimination. Environmental effects on nitrogen isotope fractionation have been reported that suggests a relationship exists between nitrogen isotope discrimination and external supply and internal demand. Although intraspecific variation in nitrogen isotope discrimination has been reported (Yousfi et al. 2009; Robinson et al. 1998; Pritchard and Guy, 2005), the underlying reasons for this remain unclear. Several theoretical models have suggested physiological mechanisms responsible for plant and organ level variations in nitrogen isotope composition (Evans, 2001; Comstock, 2001; Robinson, 2001). However, to date few studies have used empirical data to test theoretical models of fractionation. As the understanding of nitrogen isotope discrimination becomes more refined, more accurately constrained parameters contributing to this variation can be estimated. 40  Any change to nitrogen supply or demand should affect nitrogen isotope discrimination. Changes in whole-plant δ15N relative to source nitrogen δ15N (fractionation) arise through isotopic discrimination (Comstock, 2001; Evans, 2001; Robinson, 2001). Discrimination is the kinetically determined process whereby the heavier isotope (15N) is “discriminated” against causing a relatively greater fraction of the lighter isotope (14N) to be incorporated into plant tissues (Handley and Raven 1992; Hayes, 2001). The fractionation for nitrate reductase has been best estimated at about 15‰ (Ledgard et al. 1985), where the product of the reaction was -15‰ relative to the substrate. However, recent work has suggested discrimination by nitrate reductase is greater than 15‰ and is closer to 22‰ (Needoba et al. 2004; Tcherkez and Farquhar 2006) or 26‰ (Karsh et al. 2012). The instantaneous discrimination factor determines the maximum fractionation that can occur if cytoplasmic inorganic nitrogen δ15N is equal to substrate δ15N. If total consumption of the substrate pool occurs, product δ15N must be equal to the source δ15N. Isotope fractionation is only observed when there is partial consumption of a substrate pool (Mariotti et al. 1981; Comstock, 2001). Organ level isotope fractionation occurs at branch points where there is either loss of substrate or two or more pathways competing for the same substrate (Macko et al. 1987; Hayes, 2001; Comstock, 2001; Werner and Schmidt 2002; Tcherkez 2011; Gauthier et al. 2012). In Chapter 2, I proposed a model whereby whole-plant nitrogen isotope discrimination is mainly a function of one inward and three outward fluxes: 1) gross influx from the rooting medium, 2) partial assimilation by root nitrate reductase, 3) efflux of some unassimilated nitrate back to the medium, and 4) export of remaining nitrate to the leaves. The fourth flux, together with the xylem export of root-assimilated nitrogen, is the main determinant of root-shoot differences in δ15N.This comes about because partial assimilation enriches the root cytosolic nitrate pool (Robinson et al. 1998). 15N enriched cytosolic nitrate is then transported to the shoot and assimilated in the leaf. No fractionation occurs at the assimilatory step in leaves since there is total  41  consumption of nitrate. Thus, leaf nitrogen is a mix of root-derived and leaf-derived organic nitrogen with identifiable δ15N signatures. Arabidopsis represents an ideal model to evaluate the model describing nitrogen isotope discrimination because of the accessibility to multiple homozygous knockout lines for nitrogen uptake and assimilation genes. Chapter 2 provided evidence for modification of nitrogen isotope discrimination by changing nitrogen supply and/or carbon supply. Although the model was in general agreement, further testing is required to examine the contribution of changes to nitrogen uptake and assimilation patterns on nitrogen isotope composition of plants. Here, existing Arabidopsis T-DNA and gammaray mutant lines were used to evaluate a model explaining whole-plant and organ level fractionation of nitrogen isotopes. By using Arabidopsis mutant lines in which genes associated with either nitrate uptake or assimilation have been disrupted, internal nitrate supply and demand may be manipulated manifesting in changes in nitrogen isotope discrimination. Differences in nitrogen isotope discrimination among lines may also provide new information on nitrate uptake and assimilation dynamics in the lines compared to the wild type. Nitrate reductase is active in both roots and shoots and has two different genes responsible for the overall nitrate reductase activity in Arabidopsis (Wilkinson and Crawford 1993). When both genes are disrupted, Arabidopsis is unable to grow solely on NO3- (Wilkinson and Crawford 1993). Nitrate reductase 1 (NIA1) is responsible for 10% of total plant nitrate reductase activity (Wilkinson and Crawford 1993). NIA1 is expressed in both roots and leaves. However, it is expressed in a greater proportion in the leaves than NIA2 (Winter et al. 2007). NIA2 is responsible for the other 90% of nitrate reductase activity. NIA2 is expressed in both roots and leaves, but expression is proportionately higher in roots than NIA1 (Winter et al. 2007). Nitrate transporters are a group of plasma membrane-bound proteins that are responsible for nitrate uptake from the substrate and movement of nitrate within the  42  plant (Glass et al. 2002). NRT2.1 and NRT2.2 are considered to be responsible for approximately 60 to 70% of nitrate inducible uptake in Arabidopsis at low to moderate nitrate conditions (Cerezo et al. 2001; Li et al. 2007). NRT2.1 and NRT2.2 are highly expressed throughout the root including the epidermis, cortex and endodermis (Winter et al. 2007; Feng et al. 2011). NRT2.1 and NRT2.2 have been shown to have a large role in nitrate uptake. However, there are other nitrate transporters that contribute to overall nitrate uptake, including the entire NRT1 transporter family and other NRT2 genes (Glass et al. 2002). Although the description of NRT2.1 and NRT2.2 and their role in controlling nitrate movement within the root has been well defined, the contributions of this group of nitrate transporters to cytosolic nitrate homeostasis and nitrate dynamics in roots remain mostly unresolved. Environmental, temporal, and intraspecfic variation can all impact nitrogen-use measurements limiting the ability to accurately describe the contributions of specific transport genes to complex nitrogen transport dynamics over time. Knockout Arabiodpsis mutant lines that had modified nitrate reductase or nitrate transporter activity were used to determine whether whole plant and organ level nitrogen isotope fractionation is predictably modified by changing internal or external nitrogen supply or nitrogen demand. Here, I expect disruption to genes responsible for either nitrate reductase activity or nitrate transport to affect nitrogen isotope composition that correspond to reported localized expression within the plant and the known role of the disrupted genes on nitrate uptake and assimilation. I expect that modifications to nitrogen isotope composition will be interpretable within the context of the model and will demonstrate the model’s value in studying nitrogen uptake and assimilation in plants.  43  3.3. Materials and methods 3.3.1. Plant material and growth conditions Homozygous Arabidopsis lines of nia1 (CS879617), nia2 (CS2355), nrt2 (SALK_035429C) and a wild type Col-0 (CS6673) were obtained from the Arabidopsis Biological Research Centre (http://abrc.osu.edu/). T-DNA insertions or gamma-ray knockouts were confirmed using PCR to detect the location of the insertion and homozygocity of the line. Stratified seeds were sown onto Rockwool placed in plastic microcentrifuge tubes (N=5) with bottoms removed. Tubes were inserted into predrilled lids of 70 L hydroponic containers filled with a modified 1/10th Johnson’s solution containing either 100 (low NO3-) or 1000 μM (high NO3-) NO3-. Final nutrient composition, excluding Ca(NO3)2, was: 200 μM KH2PO4, 200 μM K2SO4, 100 μM MgSO4, 100 μM CaSO4, and micronutrients: 5 μM Cl, 2.5 μM B, 0.2 μM Mn, 0.2 μM Zn, 0.05 μM Cu, and 50 μM Fe2+. Once seeds had germinated and roots began to emerge from the bottom of the Rockwool, plugs were thinned to one plant per plug. Plants were grown at 21 °C (Table A.1) and ambient humidity with a 12 h photoperiod providing a PPFD of 150 μmol m-2 s-1. Nitrate concentrations in the culture solution were assayed every second day using the perchloric acid method (Cawse 1967) (Figure A.1). When the NO3- concentration approached a 10% reduction from starting, the solution was completely replaced using Ca(NO3)2 from the same pre-mixed source (δ15N = 2.78±0.23‰ [N=3]). Growth on a homogenous, steady-state nitrogen source is required for the expression of isotope effects that reflect plant physiology rather than the spatial and/or temporal isotopic vagaries typical of natural soils and pot experiments. Frequent measurements of NO3- concentration ensured that increased growth rates over time were matched by an increasing frequency of complete nutrient replacement sufficient to avoid any significant isotopic change in the substrate. Plants were harvested when they were 35 days old. Roots and shoots were placed into plastic vials, flash frozen in liquid nitrogen and stored at -80 °C until samples could be freezedried at -50 °C for two days. The plants had not yet bolted so the rosette shoot 44  consisted almost entirely of leaves and is hereafter treated as such. Once dried, roots and leaves were weighed for dry weight. Thirty-five days was identified as the end of the vegetative period from a previous experiment where plants grown under the same conditions started to flower at approximately 40 days. Plants were harvested prior to flowering to avoid significant remobilization of root and leaf nitrogen into the developing inflorescence, which would violate model assumptions outlined in chapter 2. The use of older but still vegetative plants also provided maximum dilution of the small amounts of nitrogen originating from the seed, minimized potential effects of changes in biomass partitioning that occur over the course of plant development (Gedroc et al. 1996), and ensured measurements would reflect the assimilation-averaged nitrogen use over the full vegetative phase of plant development. 3.3.2. Isotope analysis Freeze-dried root and shoot tissue were ground to a fine powder using a mortar and pestle in liquid nitrogen. From ground leaf and root samples, 3 ±0.1 mg of each sample was weighed into tin capsules (Elemental Microanalysis Ltd., 8x5 mm, D1008) and analyzed for δ15N and nitrogen concentration on either a Europa ANCA-SL preparation module and a Europa Hydra 20/20 isotope ratio mass spectrometer (University of California Stable Isotope Facility, Davis, CA) or an Isoprime (GV Instruments) Isotope Ratio Mass Spectrometer (IRMS) coupled with an Elementar Vario EL Cube Elemental Analyzer (EA) (UBC Faculty of Forestry Stable Isotope Facility). Isotopic composition is expressed as δ15N: Equation 3.1 where, Rsample is the 15N/14N isotope ratio of the sample and Rstandard is the isotope ratio of a known standard (air). In chapter 2, isotope values (δ15N) were converted to discrimination values (Δ15N). However, because the source differs so little from 0‰, discrimination can be accurately approximated by the difference in isotopic composition  45  of a plant nitrogen pool from the source salt and can be expressed as Δδ15N (i.e., Δδ15Nplant = δ15Nplant - δ15Nsource). 3.3.3. Mass balance calculations An isotope mass balance model was used to obtain several nitrogen-use traits from measurements of nitrogen isotope composition, nitrogen concentration and biomass of roots and leaves. The proportion of total plant nitrogen found in the leaf pool (Nleaf pool/Ntotal) was calculated from plant tissue nitrogen concentration and tissue mass: Equation 3.2 where, [N]i is the nitrogen concentration in the plant expressed as a fraction of total dry mass. The assimilation-averaged net flux of inorganic nitrogen across the root is equal to the total plant nitrogen divided by the root biomass: Equation 3.3 All inorganic nitrogen translocated to the shoot (Ti) by way of the xylem is assumed to be in isotopic equilibrium with the root cytoplasmic NO3- pool. Root-assimilated NO3- is depleted in 15N relative to the cytoplasmic pool by the absolute difference in δ15N caused by nitrate reductase (Δδ15Nenz), taken here to be 15‰. Organic nitrogen delivered to the shoot (To) is considered to be isotopically equal to root-assimilated organic nitrogen. The proportion of the total leaf nitrogen pool translocated to the leaves as inorganic NO3- (Ti/Tt) is then calculated from the difference between leaf and root δ15N:  Equation 3.4  46  The proportion of total plant nitrogen that was assimilated in the leaves is simply a product of Nleaf pool/Ntotal and Ti/Tt. The remaining fraction of plant nitrogen is assimilated in the roots (Proot): Equation 3.5 The isotopic composition of the whole-plant relative to the external source (δ15Nplant) is proportional to efflux over influx (E/I) and Proot: Equation 3.6 where, the maximum depletion in δ15N relative to the substrate is equal to –Δδ15Nenz. Rearrangement of equation 6 yields an estimate of E/I (Equation 3.7):  Equation 3.7 Root and leaf assimilation activities are obtained by calculating the amount of plant nitrogen derived from either roots or leaves and expressing it as a function of the biomass of either roots or leaves: Equation 3.8  Equation 3.9  3.3.4. Statistical analysis Analysis of variance with unequal observations per treatment was used to compare treatment means of biomass, root: shoot ratio, δ15N, nitrogen concentration and total nitrogen of leaf and root tissues. The statistical model was as follows:  47  Equation 3.10 where, μ is the overall mean response, αi is the effect due to the seed line, τj is the effect due to the j-th level of NO3- and βij is the effect due to any interaction between the seed line concentration and NO3- concentration. Analysis of variance procedure was carried out using Graphpad Prism 6 (La Jolla, CA, USA) to obtain estimates of the means followed by Tukey’s multiple comparison tests to separate means. Where necessary, data were log transformed to meet assumptions of homogeneity of variance and normality. Differences between treatments described as significant are those where P <0.05. 3.4. Results 3.4.1. There were morphological differences between lines that were not differentially affected by nitrate availability There were no significant differences in root, shoot or total dry mass between the wild type and nia2, nia1 or nrt2 mutants (Figure 3.1A). As expected, biomass was greater when grown with 1000 μM NO3- than 100 μM NO3-. Mean total dry mass was 12.6 mg and 25.3 mg for plants grown with 100 μM NO3- and 1000 μM NO3-, respectively. Although shoot and root dry masses were both greater on high NO 3- than low NO3-, the effects on shoot mass were greater. Consequently, there was an overall decrease in root:shoot ratio in plants grown with 1000 μM NO3- (Figure 3.1B). Root:shoot ratios for nia1 was unchanged relative to the wild type. However, for nia2, the root:shoot ratio was less than the wild type and for nrt2, the root:shoot ratio was greater than the wild type. Leaf nitrogen concentration was lower in nrt2 than the wild type but was not different for nia2 and nia1 (Figure 3.2A). Leaf nitrogen concentration was 4.17, 4.25 and 3.98 mmol g dw-1 for the wild type, nia2 and nia1, respectively, and only 3.32 mmol g dw-1 for nrt2. Unlike leaf nitrogen concentration, root nitrogen concentration was not  48  Figure 3.1. A) Total dry mass (mg) and B) root:shoot ratiofor Col-0 wild type and nia2, nia1 or nrt2 lines of Arabidopsis thaliana grown hydroponically in 100 µM or 1000 µM NO3-. Letters denote statistical significance determined by a Tukey’s multiple comparison test (P<0.05).  49  Figure 3.2. A) Leaf and B) root nitrogen concentration (mmol N g dw-1) for Col-0 wild type and nia2, nia1 or nrt2 lines of Arabidopsis thaliana grown hydroponically in 100 µM or 1000 µM NO3-. Letters denote statistical significance determined by a Tukey’s multiple comparison test (P<0.05).  50  Figure 3.3. Net root uptake (mmol N g dw-1) over 35 days for Col-0 wild type and nia2, nia1 or nrt2 lines of Arabidopsis thaliana grown hydroponically in 100 µM or 1000 µM NO3-. Letters denote statistical significance determined by a Tukey’s multiple comparison test (P<0.05).  51  different between any of the lines, but averaged approximately 33% less than shoot nitrogen (3 mmol g dw-1). Neither root nor leaf nitrogen concentration was affected by NO3- availability. Relative to wild-type plants, a combination of low root:shoot ratio and relatively high foliar nitrogen concentration in nia2 resulted in a greater mass specific net uptake of NO3- by roots (Figure 3.3). In direct contrast, a high root:shoot ratio and lower foliar nitrogen concentration combined to yield a reduced rate of net uptake in the roots of nrt2. Net root uptake was not different from wild-type in nia1. Although not significant, net root uptake was greater in 1000 μM NO3- than 100 μM NO3- (P=0.1004). 3.4.2. nia2 and nia1 only show an isotopic phenotype at the organ level while nrt2 shows an isotopic phenotype at the whole plant and the organ level Plant δ15N was more negative than source δ15N in all lines growing under steadystate NO3- conditions (Figure 3.4). Whole plant Δδ15N relative to the source averaged 2.74 ‰. There were differences in whole-plant and organ-level δ15N between lines, but lines were similarly ranked at both 100 and 1000 μM NO3-. Plant Δδ15N relative to the source δ15N was more negative in nrt2 than the wild type. Whole-plant discrimination was not different in nia1 and nia2 compared to the wild type. Although whole-plant Δδ15N did not indicate differences in nitrogen isotope discrimination for nia1 and nia2, differences in nitrogen isotope discrimination at the organ level were more apparent. Leaf Δδ15N was less than root Δδ15N for the wild type and all mutant lines (Figure 3.3). Mean Δδ15N was -1.70 and -7.43 ‰ for roots and leaves, respectively. Leaf Δδ15N in nia1 and nia2 were not significantly different than the wild type (P<0.05). However, leaf Δδ15N in the nrt2 line was more negative than the wild type. There was no difference in leaf Δδ15N between plants grown on either 100 or 1000 μM NO3-. However, there was an interaction between line and NO3- treatment (P<0.05). Plant and leaf Δδ15N were closely related because a greater proportion of plant biomass and nitrogen was allocated to the leaves, particularly under high NO3- (Figure 3.3). Root Δδ15N was more negative relative to the wild type for nia2, but more enriched relative to the wild type 52  Figure 3.4. Whole plant (grey circles), leaf (clear circles) and root (filled circles) Δδ15N for Col-0 wild type and nia2, nia1 or nrt2 lines of Arabidopsis thaliana grown hydroponically in 100 µM or 1000 µM NO3- (N=10).  53  for nia1 and nrt2. Root Δδ15N was more negative in plants grown at the higher NO3concentration (-7.94 versus -6.92‰ for 1000 μM and 100 μM NO3-, respectively). Interestingly, whole-plant Δδ15N was more negative at 100 μM NO3-. Since the root:shoot ratio was lower in plants grown with high NO3-, leaves accounted for a greater proportion of the total nitrogen resulting in an increase in plant Δδ15N. 3.4.3. Morphological changes and partitioning of nitrogen and NO3assimilation between plant organs impact whole plant and organ level isotopic composition The partitioning of nitrogen reflected changes in biomass allocation and differences in nitrogen concentration between roots and leaves. Nleaf pool/Ntotal was greater for plants grown at high NO3- (P<0.05). Nleaf pool/Ntotal was not significantly different in the nia1 and nia2 mutant lines compared to the wild type (Table 3.2), but was lower for nrt2. Leaf nitrogen accounted for 82% of total nitrogen in the wild type but only 58% in nrt2. Although most of the difference in Nleaf pool/Ntotal can be attributed to the higher root:shoot ratio of nrt2, a reduced leaf nitrogen concentration also contributed to its lower Nleaf pool/Ntotal . Through changes in overall partitioning of nitrogen and the difference in Δδ 15N between the leaves and roots (a close approximation of Δ15N), the proportional distribution of assimilatory activity can be estimated (Equation 3.5). Approximately 65% of NO3- was assimilated in the roots of the wild type (Table 3.2). The proportion of assimilation occurring in the root was lower for nia2 (50%), but higher for nia1 (78%) and nrt2 (84%). Plants grown with 1000 μM NO3- had a lower proportion of assimilation occurring in the root than plants grown with 100 μM NO3- (66% and 72% for high and low NO3-, respectively). An estimate of E/I is obtained by comparing the whole-plant Δδ15N to the instantaneous fractionation by nitrate reductase adjusted for partitioning of assimilation 54  Table 3.1. Nleaf pool/Ntotal, Ti/Tt, Proot and E/I for the wild type and nia2, nia1 or nrt2 lines of Arabidopsis thaliana grown hydroponically in 100 µM or 1000 µM NO3-. Nleaf pool/Ntotal = proportion of total plant nitrogen that is leaf nitrogen. Ti/Tt = proportion of leaf nitrogen that was transported to the shoot as inorganic nitrogen. P root = proportion of plant nitrogen assimilation occurring in roots. E/I = efflux/influx between the substrate and root. Letters denote statistical significance determined by a Tukey’s multiple comparison test (P<0.05). 100 μM Output Variable  wild type  nia2  nia1  nrt2  Nleaf /Ntotal  0.79 ±0.01 a  0.85± 0.02 a  0.82 ±0.02 a  0.66 ±0.02 b  Ti/Tt  0.44 ±0.03 a  0.55 ±0.037 a  0.24 ±0.02 b  0.17 ±0.02 b  Proot  0.65 ±0.02 a  0.56 ±0.04 a  0.81 ±0.02 b  0.89 ±0.01 b  E/I  0.10 ±0.01 a  0.08 ±0.01 a  0.11 ±0.01 a  0.25 ±0.01 b  1000 μM wild type  nia2  nia1  nrt2  Nleaf /Ntotal  0.84 ±0.01 ab  0.90 ±0.02 a  0.81 ±0.02 b  0.70 ±0.02 c  Ti/Tt  0.44 ±0.02 b  0.61 ±0.07 a  0.29 ±0.02 c  0.30 ±0.02 c  Proot  0.63 ±0.02 b  0.46 ±0.06 a  0.77 ±0.02 c  0.79 ±0.02 c  E/I  0.12 ±0.01 ab  0.08 ±0.014 a  0.13 ±0.008 b  0.19 ±0.006 c  55  (Equation 3.7). E/I was not different in the nia1 and nia2 mutant lines relative to the wild type (Table 3.2). However, in nrt2, E/I was greater than in the wild type at both NO3- concentrations. Likewise, NO3- concentration did not significantly affect E/I in the wild type or nia1 and nia2, but in nrt2 there was a decrease in E/I from 0.25 at 100 μM NO3- to 0.19 at 1000 μM NO3-. The mass specific root and leaf assimilation activities were determined by accounting for total plant nitrogen and the proportional assimilation occurring in either the root or the shoot (Equations 3.8 and 3.9). Overall, mean root assimilation was 13.1 mmol g dw-1 (Figure 3.5). Root assimilation activity was not different compared to the wild type for nia1 and nia2, but was lower in nrt2. However, leaf assimilation activity was greater in nia2 (2.47 mmol g dw-1) and lower in nia1 (1.05 mmol g dw-1) and nrt2 (0.79 mmol g dw-1) compared to the wild type (1.83 mmol g dw-1). Overall, the mass specific leaf assimilation activity was approximately 17% greater at high NO3- (1.40 mmol g dw-1) than at low NO3- (1.68 mmol g dw-1). Although leaf assimilation accounted for about 40% of total nitrate assimilation, root assimilation per unit mass was approximately eight times greater than leaf assimilation because of the low amount of root biomass relative to leaf biomass. 3.5. Discussion As a test of a proposed model of nitrogen isotope discrimination proposed in chapter 2, disrupting the gene expression of genes critical to nitrogen uptake or assimilation resulted in strong variation in nitrogen isotope composition compared to wild-type plants. Although growth phenotypes were not observed; morphological, isotopic and physiological phenotypes were apparent. It was expected that disruption of uptake or assimilatory genes, alone or in combination with changes in substrate concentration, would impact nitrate supply and demand. Variation in supply and demand would subsequently affect whole plant and organ level nitrogen isotope composition (Evans, 2001; Pritchard and Guy, 2005). At the whole-plant level, a  56  Figure 3.5. A) Leaf and B) Root assimilation (mmol N g dw-1) over 35 days for Col-0 wild type and nia2, nia1 or nrt2 lines of Arabidopsis thaliana grown hydroponically in 100 µM or 1000 µM NO3-. Letters denote statistical significance determined by a Tukey’s multiple comparison test (P<0.05).  57  decrease in demand relative to supply should increase E/I and thereby increase δ15N discrimination if assimilation occurs partly in the root. In contrast, a decrease in E/I and a decrease in discrimination are expected if uptake is suppressed, but would be dependent on whether uptake physically precedes assimilation across all tissues. If there are restrictions in transport that are localized beyond the epidermis, or if restrictions occur generally throughout the root, E/I could instead increase. 3.5.1. Disrupting nia2 activity decreases root:shoot ratio but does not affect nitrogen concentration, while disrupting nrt2 activity reduces nitrogen concentration and increases root:shoot ratio Although not significantly different, the mean biomass of nia2 was lower than the wild type (P=0.1574). High variability in biomass among seedlings within lines contributed to the lack of confidence in the differences in mean biomass between nia2 and the wild type. Wilkinson and Crawford (1993) reported no differences in growth for the same nia2 line under NO3- nutrition compared to wildtype plants. However, Stitt and Feil (1999) observed reduced growth in single-knockout tobacco transformants with reduced nitrate reductase activity when grown at multiple NO3- concentrations. Although there were no significant differences in total biomass in our experiments, root growth was impacted more than shoot growth by disruption of NIA2 activity, causing the root:shoot ratio to decrease (Stitt and Feil, 1999). Conversely, there was an increase in root:shoot ratio in nrt2 grown with either 100 or 1000 μM NO3-, as described by Filleur et al. (2001) and Li et al. (2007). Changes in root:shoot ratio may change the demand for nitrogen from the shoot relative to the amount of root tissue available to take up NO3- from the substrate. The reduction in root and leaf nitrogen concentration in nrt2 (Figure 3.2) indicates that net uptake is restricted at either the epidermal and/or intercellular level. On a mass basis, net uptake was reduced in nrt2. An approximately 20% reduction in tissue nitrogen concentration in nrt2 suggests that there is some disruption in supply relative to demand. Although plants had reduced nitrogen levels, they did not show any outward signs of stress or limitation. 58  Differences in Nleaf pool/Ntotal in mutant lines compared to the wild type demonstrate the impact of changes in biomass partitioning on overall nitrogen allocation (Table 3.2). Since the root:shoot ratio of nia2 was low compared to the wild type, a greater portion of overall nitrogen was allocated to the leaf. In essence, nia2 behaved like a plant growing under a higher nitrate concentration (Gedroc et al. 1996) since supply exceeded demand (reduced by knocking out 90% of total NR activity). On the other hand, nrt2 behaved like a plant that was nitrogen limited and allocated a greater proportion of overall biomass to the root (Bloom et al. 1985). 3.5.2. The distribution of assimilatory activity indicated by 15N mass balance corresponds to the distribution of nitrate reductase expression in roots and leaves Nitrate reductase activity is closely linked with substrate availability and assimilatory demand (Campbell 1999). The presence of nitrate has been shown to induce nitrate reductase activity in numerous plant species including Arabidopsis (Crawford et al. 1988) and poplar (Black et al. 2002). Since NIA2 would normally constitute 90% of the nitrate reductase activity, one would expect to see a stronger response in nia2 than nia1. Although not significant, there was a decrease in growth in nia2, but not nia1. Interestingly, Wilkinson and Crawford (1993) observed no decrease in nitrate reductase activity after disrupting either NIA1 or NIA2. It was suggested that compensatory upregulation of NIA1 offsets the effects of disrupting NIA2 (Wilkinson and Crawford, 1993). It is therefore not surprising that both nia1 and nia2 showed no significant growth phenotype when grown under either nitrate concentration. In contrast, there were morphological and physiological phenotypes that indicate differential contributions of NIA1 and NIA2 to whole plant nitrate assimilation activity. Our calculations of Proot indicate that root assimilation accounted for between 50 and 90% of total nitrate assimilation depending on the mutant line, which is a greater proportion than is generally expected from reports in the literature. Expressed relative  59  Table 3.2. Distribution of NIA1 and NIA2 expression between leaves and roots of Arabidopsis thaliana compared to observed leaf:root proportioning of nitrate assimilation in Col-0 wild type (NIA1 + NIA2), NIA1 only and NIA2 only. Leaf and root GfP (Green Fluorescent Protein) expression were taken as expression in whole leaf and root cortex tissue under standard conditions. Expression data taken from the Bio-Array Resource for Plant Biology Arabidopsis eFP expression browser (http://bar.utoronto.ca/welcome.htm; Winter et al. 2007)  Gene  Leaf GfP  Root GfP  expression expression  Leaf:root  Leaf:root  expression  proportioning  ratio  of assimilation  NIA1 + NIA2  2656  1308  2.03:1  0.5:1  NIA1  478  146  3.23:1  1:1  NIA2  2178  1162  1.87:1  0.33:1  60  to each other at the tissue level, measurements of nitrate reductase activities have been used to provide a first approximation of how assimilatory activity is partitioned between roots and leaves. In most cases, leaf nitrate reductase activities are considerably greater than root nitrate reductase activities (Andrews 1986; Black et al. 2002). Similarly, according to the BAR Arabidopsis expression tool (Winter et al. 2007), nitrate reductase is expressed at higher levels in leaves than roots (Table 3.2). Similar to nitrate reductase assays, expression is a measure of transcript abundance, not in vivo enzyme activity or assimilation activity. Changes in in vitro activity are not always reflective of in vivo nitrate reductase activity. Andrews et al. (1992) estimated partitioning of assimilation in grasses using nitrate reductase activity, tissue nitrate content and reduced nitrogen in the xylem sap and concluded that assimilation is weighted more towards roots, particularly at concentrations below 1 mM nitrate. Nitrate reductase can undergo strong substrate (cytoplasmic NO3-) limitation (Kaiser and Huber 2001). Furthermore, cytosolic nitrate concentrations can fluctuate with regulation of assimilatory enzymes (Fan et al. 2006). Root nitrate concentrations are likely more stable than leaf nitrate concentrations given that leaf nitrate concentrations are entirely dependent on xylem transport. Under non-saturating nitrate conditions, less nitrate may reach the xylem to be transported to the leaf and consequently, a greater proportion will be assimilated by root nitrate reductase. Despite these qualifications, our 15N mass balance model predicts the same ranking for the partitioning of assimilation as would be expected based on tissue level nitrate reductase expression levels (Table 3.1). Furthermore, because nia2 expression is proportionately higher in roots than nia1, when nia2 is disrupted, nitrate reductase expression is likely to be proportionately even higher in leaves, consistent with the decrease in Proot indicated by the isotopic mass balance. In contrast, when nia1 is disrupted, nitrate reductase expression is weighted more towards the roots and an increase in the partitioning of assimilation to the roots was observed.  61  When nitrate transport was disrupted in nrt2, there was an overall decrease in net uptake and assimilation activity accompanied by an increase in the root:shoot ratio. The concomitant changes in 15N mass balance indicate an increase in Proot, suggesting that with decreased symplastic movement of nitrate within the root and decreased rate of loading into the xylem, there is less NO3- translocated to the leaves. Expression of NRT2.1 and NRT2.2 is localized to not just the plasma membranes of epidermal cells, but also cortical and endodermal cells (Winter et al. 2007; Feng et al. 2010). With assimilatory demand remaining high and movement of nitrate through the root tissue reduced, assimilation would become more weighted to the root since translocation to the leaf would be restricted. 3.5.3. Changes in assimilatory demand do not impact efflux/influx but restriction of nitrate transport within root tissue does For both nitrate reductase mutant lines, our estimates of E/I remained unchanged compared to the wild type. This was contrary to our initial expectations, as predicted, reduced rates of assimilation allowed more substrate to cycle back to the medium. However, as indicated above, nitrate reductase activities was marginally impacted in nia1, whilst nia2 had a much reduced root:shoot ratio, placing an increased demand on the roots for xylem transport of inorganic NO3- (i.e., in competition with efflux). There is also increasing evidence of homeostatic control of cytoplasmic nitrogen concentrations (Glass et al. 2002; Miller and Smith 2008; Huang et al. 2012) whereby plants can modulate demand (through modifying growth) and supply (through modulating uptake) so that cytosolic nitrogen concentrations are buffered to temporal and spatial changes in supply or demand. In contrast, when genes associated with NO3- transport were disrupted the 15N mass balance was consistent with an increase in E/I. This result suggests that the sites of root assimilation are morphologically internal to the sites where transport was actually disrupted, which is quite possible given that, as indicated above, NRT2 is expressed  62  throughout the root. Although overall uptake into the root was reduced, further movement within the cortex or to the stele may have been more greatly impacted, increasing efflux. Multiple nitrate transporter genes contribute to nitrate uptake and movement within roots (Glass et al. 2002). Although there is a degree of redundancy within the NRT gene family and these genes operate at different NO3- concentrations, NRT2.1 and NRT2.2 are considered to be two of the primary genes responsible for high affinity uptake in Arabidopsis (Glass et al. 2002; Li et al. 2007). The small differences between leaf and root δ15N in the double mutant indicate that the leaves rely more heavily on the translocation of organic N from the roots, consistent with a reduced loading of inorganic nitrate into the xylem. 3.6. Conclusion Arabidopsis, with its wide array of described mutant lines, provides an excellent platform to modify nitrogen isotope discrimination by restricting the expression of critical genes in the nitrogen uptake and assimilation pathway. Induced variation in nitrogen isotope composition suggests that there is variation in nitrogen uptake, or use within plants, that affects relative inorganic nitrogen fluxes between the root and substrate as well as between plant parts. Here, I demonstrated here that whole plant and organ level variation in isotopic composition can be successfully interpreted using the mass balance model proposed in chapter 2, in turn providing more detail on overall nitrogen uptake and assimilation.  63  4. Quantifying remobilization of pre-existing nitrogen from cuttings to developing roots, stems and leaves of woody plants using 15N at natural abundance 4.1. Summary For measurements of nitrogen isotope composition at natural abundance, preexisting nitrogen remobilized to new plant growth can cause deviation of measured isotope composition (δ15N) from the δ15N of newly acquired nitrogen. To account for this problem, a two-step approach was proposed to quantify and correct for remobilized nitrogen from vegetative cuttings of Populus balsamifera L. grown with either nitrate (δ15N = 58.5‰) or ammonium (δ15N = -0.96‰). First, the fraction of carry-over nitrogen remaining in the cutting was estimated by isotope mass balance. Then measured δ15N values were adjusted for the fraction of pre-existing nitrogen remobilized to the plant. Mean plant δ15N prior to correction was 49‰ and -5.8‰ under nitrate and ammonium, respectively. Plant δ15N was non-linearly correlated to biomass (r2 = 0.331 and 0.249 for nitrate and ammonium, respectively; P<0.05), where the δ15N of plants with low biomass approached the δ15N of the pre-existing nitrogen. Approximately 50% of cutting nitrogen was not remobilized, irrespective of size. The proportion of carry-over nitrogen in new growth was not different between sources but ranged from less than 1% to 21% and was dependent on plant biomass and, to a lesser degree, the size of the cutting. The δ15N of newly acquired nitrogen averaged 52.7‰ and -6.4‰ for nitrate and ammoniumgrown plants, respectively; both lower than their source values, as expected. Since there was a greater difference in δ15N between the cuttings and newly assimilated nitrogen where nitrate was the source, the difference between measured and adjusted δ 15N was also greater. There was no significant relationship between biomass and plant δ15N with either ammonium or nitrate after adjusting for carry-over nitrogen. Here, I provide evidence of remobilized pre-existing nitrogen influencing δ15N of new growth of balsam poplar. A simple, though approximate, correction is proposed that can account for the remobilized fraction in the plant. With careful sampling to quantify pre-existing nitrogen, this method can be used to more accurately determine changes in nitrogen isotope discrimination in response to environment. 64  4.2. Introduction Measurements of nitrogen isotope composition at natural abundance (δ 15N) may be affected by remobilization of previously acquired nitrogen into new growth of plants. To precisely determine the δ15N of newly acquired nitrogen, the carry-over of old nitrogen needs to be accounted for. The use of δ15N at natural abundance has increased in plant physiology and ecology where small, but tractable changes in δ15N of plants or plant tissues can indicate changes in soil nitrogen sources or changes to nitrogen use physiology (Comstock, 2001; Evans, 2001; Dawson et al. 2002; Houlton et al. 2007). Quantifying temporal changes in plant nitrogen sources in the field or plant nitrogen isotope discrimination (Δ15N) requires confidence in the measurement of the δ15N of newly acquired nitrogen. When not working at the natural abundance level, as in many 15  N enrichment experiments, knowledge of the precise isotopic composition of pre-  existing nitrogen may not be necessary because newly acquired nitrogen will have a markedly different isotopic signature (Dawson et al. 2002; Dong et al. 2004). During establishment of sexually and vegetatively propagated plants, stored nitrogen is remobilized from the propagule (seed or cutting) to the newly growing tissue as a nitrogen supply until the roots are capable of supporting the nitrogen demands of the plant (Dong et al. 2004). In woody perennials, nitrogen from senescing leaves accumulates in stem tissue during autumn to be re-used by developing tissues during regrowth in the spring (Millard and Thomson 1989; Malaguti et al. 2001). Nitrogen transported to flushing shoots and/or root growth come from vegetative storage proteins kept over the dormant period (Cooke and Weih 2005). Vegetative storage proteins can account for a sizeable fraction of total nitrogen in dormant stem tissue (Greenwood et al. 1986; Gomez and Faurobert 2002). If the δ15N of remobilized nitrogen is different from the δ15N of newly acquired nitrogen, it may influence the measured δ15N of new growth. Within a bulk nitrogen pool (e.g., a cutting), there may be differences in δ15N between various amino acids and other nitrogen-containing compounds (Werner and Schmidt 2002, Tcherkez 2011, Gauthier et al. 2012). This may impact the δ15N of 65  remobilized stem tissue relative to the δ15N of the bulk tissue if the δ15N of the remobilized fraction is different from the non-remobilized fraction. However, if a substantive fraction of pre-existing nitrogen contributes to the growth of new plant tissue, the δ15N of the remobilized nitrogen should resemble the δ15N of the bulk source tissue because many, and certainly the most predominant, nitrogen-containing compounds will contribute to this flux. If there were any isotope discrimination associated with remobilization itself, as consumption of a nitrogen pool approaches completion, the transferred fraction (the product) approaches the δ15N of the stored fraction (the source). Here, a two-step mass balance approach is proposed to account for carry-over nitrogen remobilized from cuttings to growing tissues in plants using Populus balsamifera L. (balsam poplar) grown with either ammonium or nitrate. The two nitrogen sources bracketed the δ15N of pre-existing N, with the nitrate being enriched in 15  N relative to the cutting and the ammonium being depleted relative to the cutting.  Therefore, if carried-over nitrogen from pre-existing nitrogen has an appreciable effect on newly assimilated nitrogen isotope values, contrasting relationships with biomass should be evident. Poplars in general have long been used as model systems in tree biology and genetics, and Populus trichocarpa Torr. & Gray, (syn: P. balsamifera ssp. trichocarpa) was the first woody species to have its genome completely sequenced (Tuskan et al. 2006). The approach described here is applicable not just to plants grown from cuttings, but also with little adjustment to plants grown from seed. 4.3. Materials and methods 4.3.1. Plant material and experimental design First year branches of 25 genotypes of Populus balsamifera L. ranging from 51 °N to 56 °N from the Agriculture Canada Balsam Poplar (AgCanBaP) collection (Soolanayakanahally et al. 2009) were obtained from the AAFC-AESB Agroforestry Development Centre at Indian Head, Saskatchewan, Canada and stored at 4 °C for approximately three months to fulfill chilling requirements. The five provenances 66  reflected a climatic gradient for the species that extends from a prairie ecosystem to the boreal forest of the Canadian Shield; namely Outlook (OUT; 51.1 °N, 106.2 °W), Saskatoon (SKN; 2.2 °N, 106.4 °W), Turtleford (TUR; 53.2 °N, 108.3 °W), Cold Lake (CLK; 54.2 °N, 110.1 °W) and Gillam (GIL; 56.4 °N, 94.7 °W). These same genotypes were used for analysis of genotypic variation in nitrogen isotope composition presented in chapter 6 and the comparison of two independent measures of calculating E/I in chapter 5. Twonode cuttings, approximately 6-8 cm long were weighed for fresh weight and arranged in a randomized complete block design with three blocks of two nitrogen treatments supplied as either 250 M Ca(NO3)2 or 250 M (NH4)2SO4. Plants were grown for 45 days in a hydroponics solution until harvest. Complementary samples of each genotype were collected as reference samples (N = 3) for initial isotope composition and nitrogen concentration. 4.3.2. Hydroponics system The hydroponics system was comprised of six 1000L containers lined with rubber pond liner material (Firestone, Nashville, TN, USA ) constructed in a greenhouse under ambient light conditions supplemented by sodium halide lighting (600 mol m-2 s-1 PPFD) and 18/6 photoperiod. Temperatures in the greenhouse were maintained between 20 and 24 °C. Each container was fitted with a floating Perspex “raft” that held up to 32 plants. Unused plugs in the raft and the rest of the container were covered with black polythene to prevent algal growth. The hydroponics solution was a modified 1/10th strength Johnson’s solution (Johnson et al. 1957) supplemented with either 250 μM Ca(NO3)2 or (NH4)2(SO4). Final nutrient composition, excluding nitrogen salts, was: 200 μM KH2PO4, 200 μM K2SO4, 100 μM MgSO4, 100 μM CaSO4, and micronutrients: 5 μM Cl, 2.5 μM B, 0.2 μM Mn, 0.2 μM Zn, 0.1 μM Mo, 0.05 μM Cu, and 50 μM Fe2+. Containers were fitted with 20 L per minute centrifugal pumps, to circulate and aerate the media. Solutions were monitored periodically for oxygen levels, pH (Figure A.2) and temperature (Figure A.3). Powdered calcium carbonate (CaCO3) was added to buffer pH in the range of 6-7.5. Media NH4+ and NO3- concentrations were assayed using the phenol:hypochlorite (Solorzano 1969) and perchloric acid (Cawse 1967) methods, 67  respectively (Figure A.4). The solution was completely replaced every 14 days to ensure that there was no substantial decrease (>10%) in concentration of nitrate or ammonium over time that could increase the solution δ15N. 4.3.3. Sampling and natural abundance isotope analysis After 45 days of growth, plants were separated into leaves, stems, roots and the original cutting. Samples were flash frozen in liquid nitrogen and stored at -80 °C until samples could be freeze-dried at -50 °C for two days. Once dried, roots, leaves, stems, cuttings and the reference cuttings were weighed. Samples were then ground to a fine powder using a mortar and pestle and then ball milled (Fritsch Laborgeratebau, Terochem Scientific). Sub-samples of 3±0.1 were weighed into tin capsules (Elemental Microanalysis Ltd., 8x5 mm, D1008) and analyzed for nitrogen concentration and δ15N on a PDZ Europa ANCA-GSL elemental analyzer interfaced to a PDZ Europa 20-20 isotope ratio mass spectrometer (Sercon Ltd., Cheshire, UK) (University of California Stable Isotope Facility, Davis, CA). Isotopic composition is expressed as δ15N: Equation 4.1 where, Rsample is the 15N/14N isotope ratio of the sample and Rstandard is the isotope ratio of a known standard (air). The δ15N values of the ammonium and nitrate salts used for the growth media were -0.96 and +58.5‰, respectively. 4.3.4. Correcting for pre-existing cutting nitrogen remobilized to growing plant organs The δ15N and nitrogen concentration of the cutting after harvest was compared to the δ15N and nitrogen concentration of the cutting before the start of the experiment to correct for pre-existing nitrogen remobilized to the actively growing plant. Nitrogen content of the cutting at harvest (Nend) can be calculated as: Equation 4.2 where, Biomasscutting end and [N]cutting end are the biomass and nitrogen concentration of the cutting at harvest. Since the cutting was part of the growing stem, dry mass 68  accumulated in the cutting. The initial dry mass of the cutting (Biomass cutting start) was estimated from the fresh mass of the cutting at the start of the experiment and the mean dry mass content of the reference samples (0.584). From this, nitrogen content at the start of the experiment (Nstart) was estimated as: Equation 4.3 where [N]start is the mean nitrogen concentration of the reference samples at the start of the experiment. Assuming that the isotopic composition of a cutting at harvest (δ15Nend) is a mixture of stem δ15N (δ15Nstem) (containing a portion of remobilized nitrogen) and non-remobilized nitrogen remaining in the cutting (δ15Nstart), the fraction of non-remobilized (fnonremobilized) nitrogen can be estimated as: Equation 4.4 The amount of nitrogen remobilized (Nremobilized) to new growth can then be calculated as: Equation 4.5 The proportion of nitrogen in the general plant nitrogen pool that is carried over into new growth (C) is given by: Equation 4.6 where, Nplant is equal to the sum of all nitrogen contents in the roots, leaves and stems (including new and remobilized nitrogen allocated to the expanded cutting): Equation 4.7 Assuming that there is a proportionate distribution of remobilized nitrogen throughout the plant (i.e., C is the same for all plant organs), the mass balance equation showing the contributions of new and carry-over nitrogen to measured δ15N for roots, stems and leaves is:  69  Equation 4.8 where, δ15Nuncorrected, δ15Ncarry-over and δ15Nnew are the measured isotopic compositions of each plant organ, the isotopic composition of remobilized nitrogen (equal to δ15Nstart), and the isotopic composition of newly assimilated nitrogen, respectively. Equation 4.8 can be rearranged to yield: Equation 4.9 This equation was used to obtain root, stem and leaf δ15N values adjusted for the contribution of carry-over nitrogen from the cuttings.. 4.3.5. Statistical analysis Two-way ANOVA was used to test for the fixed effects of nitrogen source and genotype on 1) biomass, 2) measured δ15N values, 3) the proportion of cutting nitrogen remobilized to the growing plant, 4) the proportion of nitrogen in new growth that is carry-over nitrogen, and 5) the adjusted δ15N values of plant, root and leaf tissues. The statistical model was as follows: Equation 4.10 where, μ is the overall mean response, αi is the effect due to the genotype, τj is the effect due to the nitrogen source and βij is the effect due to any interaction between the genotype and nitrogen source. Analysis of variance procedure was carried out using Graphpad Prism 6 (La Jolla, CA, USA) to obtain estimates of the means followed by Tukey’s multiple comparison tests to separate means. Differences between treatments described as significant are those where P <0.05. Whole plant δ15N was plotted against biomass and per cent carry-over nitrogen to examine the influence on measured δ15N of genotypes grown using nitrate or ammonium. Non-linear regression was performed for the measured plant δ15N versus biomass using Graphpad Prism 6 to fit an exponential model to the data. Linear regression was performed on adjusted plant δ15N versus biomass and on both measured and adjusted plant δ15N versus the proportion of carryover nitrogen in new plant growth. 70  4.4. Results 4.4.1. δ15N, growth and nitrogen concentration Both ammonium and nitrate-grown plants were depleted in 15N relative to the source (Table 4.1). Under nitrate, mean root, stem and leaf δ15N was 44.4, 47.1 and 50.1‰, whereas for ammonium, these values were -8.6, -6.6 and -5.1‰, respectively. The vegetative cuttings used to propagate the plants were not different between sources and had a mean δ15N of 0.92‰ at the start of the experiment. During plant growth, the δ15N of the cuttings moved towards and/or past the isotope signature of the source (Table 4.1). For nitrate-grown plants, cuttings became enriched (23.5‰) and for ammonium-grown plants, cuttings became depleted (-3.1‰) relative to their starting isotopic composition (P<0.05). Genotypic means for biomass ranged from 0.51 to 4.46 g and 0.33 to 3.48 g under nitrate and ammonium conditions, respectively (Table 4.2). There was a significant correlation between genotype means for biomass on nitrate versus ammonium (r= 0.54, P<0.05) whereby clones that grew well on one source also grew well on the other. The range in mean genotype biomass provided a range of isotopic dilutions to determine the influence of remobilized pre-existing nitrogen on whole-plant and organ level δ15N. When the uncorrected δ15N for new growth of the whole plant was plotted against biomass, there was a significant non-linear relationship (r2 = 0.331 and 0.249 for nitrate and ammonium, respectively; P<0.05) (Figure 4.1). The uncorrected δ15N for new growth of the whole plant for genotypes with low biomass were closer to the δ15N of cutting nitrogen, whereas for genotypes with high biomass they were closer to the δ15N of newly acquired nitrogen (which resembles the source, but does not equal it due to isotope discrimination that occurs during uptake and assimilation). Nitrogen concentration was not different between cuttings before the start of the experiment, but was significantly greater at the end of the experiment when grown with ammonium as compared to nitrate (Table 4.3). Stem and cutting nitrogen concentrations were not significantly different from each other on either source. Root nitrogen concentration was not significantly different between sources, but stem and leaf nitrogen concentrations were greater when grown with ammonium (P<0.05). 71  Table 4.1. Mean measured and, for new tissues, adjusted root, stem, leaf and cutting δ15N values (‰ ±SE; N=75) of Populus balsamifera L. hydroponically grown with nitrate (58.5‰) or ammonium (-0.96‰). Nitrate  Ammonium Measured δ15N  Root  44.42±0.42  -8.59±0.15  Stem  47.08±0.40  -6.62±0.18  Leaf  50.10±0.44  -5.07±0.15  Cuttingstart  0.87±0.35  0.97±0.31  Cuttingend  23.47±0.88  -3.10±0.23 Adjusted δ15N  Root  47.87±0.28  -9.45±0.19  Stem  50.76±0.26  -7.29±0.19  Leaf  54.01±0.25  -5.59±0.18  72  Table 4.2. Mean root, stem, leaf, cutting and whole plant biomass (g ±SE; N=75) of Populus balsamifera L. hydroponically grown with nitrate or ammonium. Biomass (g) Nitrate  Ammonium  Root  0.18±0.02  0.20±0.01  Stem  0.40±0.03  0.29±0.02  Leaf  1.28±0.09  1.15±0.07  Cuttingstart  0.49±0.03  0.54±0.04  Cuttingend  0.67±0.06  0.65±0.05  Whole Plant  1.86±0.14  1.64±0.10  73  Table 4.3. Mean nitrogen concentrations (μmol g dw-1 ±SE; N=75) of roots, stems, leaves and cuttings of Populus balsamifera L. hydroponically grown with nitrate or ammonium. Tissue nitrogen concentration (μmol g dw-1) Nitrate  Ammonium  Root  2.50±0.04  2.55±0.03  Stem  0.41±0.01  0.76±0.03  Leaf  1.84±0.03  2.19±0.04  Cuttingstart  0.83±0.01  0.83±0.02  Cuttingend  0.59±0.03  0.71±0.02  74  Figure 4.1. Unadjusted (open symbols) and adjusted (closed symbols) δ15N for new growth of the whole plant plotted against biomass for Populus balsamifera L. grown with either A) nitrate or B) ammonium. Each data point represents a genotypic mean (N=3). Correlation coefficients and P-values are placed near each line.  75  4.4.2. Carry-over nitrogen in new plant growth is dependent on the size of the nitrogen pool in the cutting relative to the nitrogen pool in the new growth The δ15N of vegetative cuttings at the end of the experiment fell close to the middle between the starting cutting δ15N and the δ15N of newly formed organs, indicating that some considerable portion of the original nitrogen was retained within the cuttings. From equation 4.4, the nonremobilized fraction of the nitrogen contained within the cuttings at the end of the experiment averaged 50% and 48% for nitrate and ammonium, respectively. The two nitrogen sources were not significantly different from each other and, using equation 4.5, this translated into approximately half of the starting nitrogen being remobilized for new growth (Figure 4.2). The mean quantity of nitrogen remobilized was 3.2 mg but was dependent on the size of the cutting (r=0.057; P<0.05). There was no source effect on the proportion of carry-over, which averaged 8% but decreased non-linearly from 21% to 1% with the biomass of new growth (not shown). The difference between source δ15N and the old cutting δ15N was greater for nitrate than ammonium (Table 4.1), causing carry-over nitrogen to have a greater influence on measured plant δ15N under nitrate (Figure 4.3A) than ammonium (Figure 4.3B). 4.4.3. Relationships between plant δ15N and biomass were not significant after accounting for carry-over of pre-existing nitrogen There were significant linear relationships between the contribution of nitrogen carried-over from the cutting and the uncorrected δ15N for new growth of the whole plant (P<0.05) (Figure 4.3). Relative to the measured δ15N of each corresponding organ, newly assimilated nitrogen was more depleted in 15N under ammonium and more 15N enriched under nitrate. After accounting for the presence of remobilized nitrogen, the adjusted root, stem and leaf δ15N values were 47.87, 50.76 and 54.01‰ and -9.45, -7.29 and -5.59‰ for nitrate and ammonium, respectively. This represented an approximate shift of 3.5 to 4‰ and 0.5 to 0.8‰ for nitrate and ammonium grown plants, respectively. There was no residual relationship between biomass and newly acquired  76  Figure 4.2. Percentage of A) pre-existing nitrogen remobilized into new growth and B) percentage contribution of pre-existing cutting nitrogen to total plant nitrogen in Populus balsamifera L. grown with either nitrate or ammonium. Bars are means ±SE (N=75).  77  Figure 4.3 Unadjusted (open symbols) and adjusted (closed symbols) δ15N for new growth of the whole plant plotted against the percentage contribution of carry-over nitrogen to new growth of Populus balsamifera L. supplied with either A) nitrate or B) ammonium. Each data point represents a genotypic mean (N=3). Correlation coefficients and P-values are placed near each line.  78  plant δ15N (i.e., non-significant regressions in Figure 4.3) indicating that the carry-over nitrogen was well accounted for. 4.5. Discussion The objective was to quantify and correct for carry-over nitrogen from cuttings in new growth of balsam poplar hydroponically grown under steady-state conditions. Here, it was shown that nitrogen remobilized from cuttings influences plant δ 15N. Carryover would be inconsequential for plants grown from relatively small seeds or in longerterm experiments, where the total accumulated nitrogen pool represents almost all of the nitrogen within the plant. However, in cases where biomass accumulation is low relative to the size of the propagule, without correction, deviation of measured δ 15N from the δ15N of newly acquired nitrogen can lead to misinterpretations in physiological and ecological studies. It has been suggested that there are carry-over effects of interannual variability in carbon isotope signatures (δ13C) in woody plants (Vaganov et al. 2009; Offerman et al. 2011), but, aside from Kolb and Evans (2003), this is the first attempt to quantify the carry-over effect on nitrogen isotope composition of new growth in woody plants. Accounting for remobilized nitrogen from the cutting to the root, stems and leaves required a two-step approach. Since vegetative cuttings are a part of the stem, nitrogen contained within the cutting should be combined with the general stem nitrogen pool. However, there is a certain fraction of nitrogen in the vegetative cutting that was not mobilized and therefore, needs to be quantified to determine the corresponding amount of cutting nitrogen that was remobilized into the general nitrogen pool. In the present study, and noting that some isotope discrimination is expected during nitrogen uptake and assimilation, the presence of non-remobilized nitrogen in the cutting was indicated by a difference between stem and cutting δ 15N that was weighted towards the source δ15N (Table 4.1). Previous work has demonstrated that there is often a fraction that is not remobilized to sink tissue (Millard and Thomson 1989). Once non-remobilized nitrogen and the proportion of cutting nitrogen that is part of the stem nitrogen pool had been partitioned, the amount of 79  nitrogen mobilized into the plant nitrogen pool was quantified. To make this partitioning calculation, it was assumed that new nitrogen in the cutting was mixed with remobilized (contaminating) nitrogen from the cutting similar to that of stem tissue. Since there was influx of newly assimilated nitrogen into the vegetative cutting, as indicated by a growth dependent movement of cutting δ15N towards the source δ15N, it would be reasonable to assume there is a certain degree of mixing of nitrogen within the mobile stem nitrogen pool. Here, it was assumed that remobilization was proportional to organ biomass and otherwise equal among plant organs. Variation in the difference in δ15N between measured and newly acquired nitrogen may, in part, be a consequence of assuming that the distribution of carry-over nitrogen was proportionate to the nitrogen allocation between roots, stems and leaves. Dong et al. (2004) reported that approximately 30% of remobilized nitrogen was allocated to the root and 70% was allocated to the shoot in vegetatively propagated poplar and although the proportion allocated to the root was slightly higher than our results, the proportion was similar enough to validate the assumption of proportional remobilization. Even though biomass allocation was not reported in Dong et al. (2004), if the root:shoot ratios were similar to those reported here, this would indicate proportional allocation of remobilized nitrogen to roots, stems and leaves in our experiments. Another assumption made was to take the δ15N of remobilized nitrogen as being equal to the δ15N of the cutting at the start of experiment. Compound specific variation in δ15N (Werner and Schmidt 2002, Tcherkez 2011, Gauthier et al. 2012) may result in divergence of remobilized δ15N. However, Kolb and Evans (2003) reported that there was no difference in remobilized δ15N and stored δ15N, and that no fractionation occurred during remobilization. Additionally, as a greater proportion of nitrogen is remobilized, it becomes less likely that compound-specific variation in δ15N will contribute to divergence of remobilized δ15N from the reference δ15N unless there are large differences between structural and mobile nitrogen δ15N. Although biochemical  80  variation in δ15N may add error to our approach, it would seem to be small relative to the correction applied. The proportion of soluble nitrogen in cuttings may limit nitrogen remobilization which may provide an explanation for why approximately half of pre-existing nitrogen was not remobilized. During the dormant period, nitrogen storage proteins accumulate in stem tissue and the proportion of soluble, stored nitrogen increases (Marmann et al. 1997, Bollmark et al. 1999, Coleman 2004, Millar and Grelet 2010). Estimates of soluble nitrogen in stems of Fraxinus excelsior were between 60 and 70% during the dormant period (Marmann et al. 1997). If the proportion of soluble nitrogen in balsam poplar is similar, then only a small fraction of soluble nitrogen was not remobilized to new growth. Our natural abundance nitrogen isotope mass balance approach indicates that approximately 50% of cutting nitrogen was remobilized to sink tissues (leaves, roots and stems). In hybrid poplar, between 60 and 70% of nitrogen in cuttings was remobilized into actively growing tissue (Dong et al. 2004). This proportion was comparable with estimates of remobilization of nitrogen from source tissue (leaves) of Brassica napus to sinks (developing siliques) (Rosatto et al. 2001). Using two separate nitrogen sources with δ15N values both greater and lower than reference δ15N provided some validation for the correction. Previously, enriched nitrogen applied as 15N allowed for the quantification of remobilized nitrogen into growing plant tissue (Dong et al. 2004). In the present study, newly acquired δ15N under ammonium (δ15N = -0.96 ‰) was on average 5 to 10‰ depleted relative to the cutting δ15N, while newly acquired δ15N for nitrate (δ15N = 58.5 ‰) was approximately 50 to 55‰ enriched relative to the cutting. This contrast in the isotopic composition of two sources of newly acquired nitrogen, relative to nitrogen that previously existed in the cutting, gave negative and positive non-linear relationships between biomass and the unadjusted plant δ15N. Here, after correction, biomass had no impact on corrected plant δ15N for either source and any observed relationship was primarily a result of nitrogen carried-over from the cutting. Our approach worked well either way, which should not  81  be the case if the δ15N of remobilized nitrogen were consistently offset in one direction from the δ15N of bulk nitrogen. 4.6. Conclusion Here, evidence was provided that remobilized nitrogen carried-over from stem cuttings can affect measured δ15N of new growth in poplar, a perennial model plant. Carry-over nitrogen from pre-existing nitrogen pools needs to be considered when measuring δ15N at natural abundance. By applying a two-step mass balance correction, the contributions of pre-existing nitrogen to the nitrogen content and δ15N of new growth can be quantified and accounted for. This, in turn, will allow for a better assessment of isotope discrimination associated with the acquisition of new nitrogen from the rooting environment and could be helpful in physiology and ecology studies measuring nitrogen isotope composition at natural abundance to address questions relating to nitrogen use dynamics at the soil or plant level. The methods presented here are not only applicable to this species or set of conditions but, with careful sampling protocols, can be applied to other experimental systems that require the measurement of δ15N at natural abundance during plant growth and development.  82  5. Coherence of independent isotopic measures of nitrogen efflux/influx (E/I) in roots of Populus balsamifera L. 5.1. Summary Acquisition of mineral nitrogen from solution is often not completely efficient, there being a variable amount of leakage (efflux) relative to gross uptake (influx). The efflux/influx ratio (E/I) is inversely related to the efficiency of nutrient uptake at the roots. Radioactive label-based isotopic measurements of ion flux and E/I have been traditionally used, but are laborious and may not reflect time-integrated E/I. Alternatively, information on E/I and other nitrogen use traits may also be obtained from variation in stable isotope ratios. Five genotypes of Populus balsamifera L. were grown hydroponically on either 500 μmol L-1 NO3- or NH4+. E/I was calculated using an isotope mass balance model and compared to E/I calculated using 15N compartmental analysis. Both methods indicated that plants grown on ammonium had greater E/I than plants grown on nitrate. Genotype specific means were linearly correlated (r=0.77; P=0.0065) with few rank changes, but E/I was approximately 0.15-0.2 higher using the nitrogen isotope mass balance approach. Similarly, net uptake based on isotope mass balance was greater than indicated by compartmental analysis. Discrepancies in E/I between methods may reflect uncertainties in discrimination factors for the assimilatory enzymes (nitrate reductase and glutamine synthetase), temporal differences in uptake patterns (compartmental analysis provides a single point measurement, whereas isotope mass balance is integrated over weeks), and the possibility of some discrimination associated with membrane transport. This chapter demonstrates the relationship between E/I calculated using the isotope mass balance approach presented in this thesis and E/I calculated using a previously established, independent approach providing. 5.2. Introduction One prospect for improving nitrogen-use efficiency is thought to lie in improving the ability of plants to efficiently acquire nitrogen from their environment. To achieve 83  this, an integrated approach to understanding nitrogen uptake and assimilation in plants is required (Hirel et al. 2007). Garnett et al. (2009) suggested that root-based approaches are under-explored and may represent an avenue for improving plant nitrogen-use efficiency. The acquisition of inorganic nitrogen from the surrounding environment is a function of root architecture, ion preference and nitrogen demand. In essence, improving acquisition is not only dependent on uptake, but also on the ability of plants to assimilate and translocate nitrogen into sink tissues. Nitrogen movement between the rhizosphere and roots is bidirectional. Following uptake (influx), nitrate and/or ammonium ions may be assimilated or, alternatively, return to the rooting medium (efflux) through leakage or excretion (Xu et al. 2012). Inorganic nitrogen may also pass directly to the xylem for transport to the shoot. These processes, in combination, result in the homeostatic balance of cytoplasmic inorganic nitrogen in roots (Lee and Clarkson, 1986). The fact there is significant efflux suggests some inefficiency in nitrogen acquisition whereby the plant is unable to expeditiously assimilate available cytosolic inorganic nitrogen or to balance intracellular pH and ionic balance (Britto and Kronzucker, 2006). Efflux of inorganic nitrogen has been reported under both changing and steady-state nitrogen conditions (Kronzucker et al. 1995; Hawkins and Robbins 2010), and is dependent on substrate concentration (Morgan et al. 1973; Kronzucker et al. 1995; Hawkins and Robbins, 2010), root maturity and plant nitrogen demand (Bloom et al. 2010; Hawkins and Robbins, 2010). Cycling of unassimilated, inorganic nitrogen between the substrate and the root is thought to reflect inorganic nitrogen source preference (Kronzucker et al., 1997) and may be associated with reduced nitrogen use efficiency. High efflux/influx (E/I) can have high energetic costs (Kronzucker et al. 2001; Scheurwater et al. 1999). At high ammonium concentrations, these costs are sufficient to reduce growth, and may cause damage or even death to the plant (Britto and Kronzucker, 2006). Though important, characterizing nitrogen fluxes can be problematic because of high spatial and temporal heterogeneity in roots of actively growing plants (Alber et al. 2012; Bloom et al. 2012). Inorganic nitrogen uptake has been shown to vary diurnally 84  (Delhon et al. 1995; Gessler et al. 2002). Diurnal variation in nitrogen uptake patterns may result in poor characterization of genotypic variation in nitrogen use. Fluxes within roots have previously been characterized using microelectrode measurements (Henricksen et al. 1990; Miller and Zhen, 1991; Hawkins et al. 2010) or compartmental analysis using 13N radioisotope (Lee and Clarkson, 1986; Siddiqi et al. 1991; Kronzucker et al. 1995) or 15N stable isotope (Macklon et al. 1990; Devienne et al. 1994) labelling, under steady state conditions. Compartmental analysis provides tissue specific information that cannot be obtained using other methods, including compartmentspecific measures of half-life of exchange, nitrogen concentration and efflux (Lee and Clarkson, 1986; Min et al. 2002; Kronzucker et al. 2005). Microelectrode measurements have the benefit of being a calibrated measure of nitrogen flux that is tissue or even cellspecific (Henricksen et al. 1992). Although fast and accurate, these single time-point measurements need extensive replication to deal with changes in nitrogen flux over a diurnal cycle. The dynamic nature of nitrogen flux in space and time suggests that an integrated approach to assess nitrogen flux may better capture whole plant nitrogen use. Differences in the natural abundance of stable nitrogen isotopes of plants grown under steady-state nitrogen conditions have potential to provide time and spatiallyintegrated information on whole plant and organ level nitrogen uptake and assimilation patterns. Chapter 3 demonstrated that whole plant and organ level variation in isotopic composition can be successfully interpreted using a version of the mass balance model proposed in Chapter 2. The model does not discern between cellular compartments at the tissue level, but can quantify whole-plant and organ-level nitrogen use traits such as partitioning of organic and inorganic nitrogen, partitioning of assimilation, and gross and net ion fluxes. For evaluating short-term responses to changes in nitrogen concentration or other treatments, compartmental analysis and/or microelectrode measurements are appropriate. However, without a comprehensive sampling protocol, only nitrogen isotope discrimination can provide reliable information on long-term nitrogen use.  85  Furthermore, isotope mass balance approaches can be scaled up to accommodate larger experiments or phenotypic screening. Nitrate and ammonium transport have been extensively studied in model plants such as Arabidopsis thaliana (L.) Heynh. and Nicotiana tobacum L. (Stitt and Feil, 1999; Glass et al. 2002). However, to date, few studies have investigated nitrate or ammonium transport in Populus sp. (Min et al. 2002; Selle et al. 2005; Couturier et al. 2007). As interest increases for using Populus as a bioenergy resource (Yemshanov et al. 2008), identifying variability in nitrogen transport fluxes will be important for improving nitrogen-use efficiency in new cultivars. A high degree of trait variability, particularly for adaptive traits such as phenology and photosynthesis, has been observed in balsam poplar (Populus balsamifera L.) and black cottonwood (Populus trichocarpa Torr. & A. Gray) (Soolanayakanahally et al. 2009; McKown et al. 2013). However, intraspecific variability in nitrogen flux within these species, or indeed any woody plant, has not been explored. The objective of this experiment was to compare independent methods of estimating E/I and net nitrogen uptake using five genotypes of balsam poplar grown on either nitrate or ammonium. More specifically, I sought to validate the isotope mass balance approach by comparing it to compartmental analysis whereby E/I was estimated from 15N isotope discrimination in the former, versus 15N labelling in the latter. 5.3. Materials and methods 5.3.1. Plant material and experimental design Five genotypes (GIL-9, GIL-7, GIL-2, CLK-4 and OUT-9) of balsam poplar from three provenances from the Agriculture Canada Balsam Poplar (AgCanBaP) collection (Soolanayakanahally et al. 2009) were randomly chosen from genotypes selected for evaluation of genotypic variation in nitrogen isotope discrimination presented in chapter 6. First-year branches were obtained from the AAFC- AESB Agroforestry Development Centre, Indian Head, Saskatchewan, Canada and stored at 4 °C for approximately 3 months to fulfill chilling requirements. The three provenances were: 86  Gillam (GIL), Manitoba (56.4 °N, 94.7 °W), Outlook (OUT), Saskatchewan (51.1 °N, 106.2 °W), and Cold Lake (CLK), Alberta (54.2 °N, 110.1 °W). Two-node vegetative cuttings, approximately 6-8 cm long, were arranged in a randomized complete block design with three blocks consisting of two nitrogen source treatments; either 500 μM nitrate or 500 μM ammonium. There were four clonal replicates in each block to provide sufficient plant material for complimentary sampling at the end of the experiment. Pre-existing nitrogen was accounted for by applying a correction (Chapter 4) that uses a mass balance model to quantify the amount of nitrogen remobilized from the cutting and proportionately adjust growing tissue δ15N. 5.3.2. Hydroponics system The hydroponics system was comprised of six 1000L containers lined with black 45 mil rubber pond liner material (Firestone, Nashville, TN, USA) constructed in a greenhouse under ambient light conditions supplemented by sodium halide lighting providing a minimum PPFD of 600 μmol m-2 s-1 and 18/6h day/night photoperiod. Temperatures in the greenhouse were maintained between 20 and 24 °C. Each container was fitted with a floating Perspex “raft” that held up to 32 plants, as described in Chapter 4. The hydroponics solution was a modified 1/10th strength Johnson’s solution (Johnson et al. 1957) with either 250 μM Ca(NO3)2 (δ15N = +60.3 ‰) or 250 μM (NH4)2SO4 (δ15N = -0.96 ‰). Final nutrient composition, excluding the nitrogen salts, was: 200 μM KH2PO4, 200 μM K2S04, 100 μM MgSO4, 100 μM CaSO4, and micronutrients: 5 μM Cl, 2.5 μM B, 0.2 μM Mn, 0.2 μM Zn, 0.05 μM Cu, and 50 μM Fe2+. A centrifugal pump, with a pumping capacity of approximately 20 L per minute, provided circulation and aeration of the solution for each container. The solution was monitored periodically for oxygen levels, pH (Figure A.2) and temperature (Figure A.3). Powdered calcium carbonate (CaCO3) was added to buffer pH in the range of 6-7.5. Media NH4+ and NO3concentrations were assayed using the phenol:hypochlorite (Solorzano 1969) and perchloric acid (Cawse 1967) methods, respectively (Figure A.4). The solution was completely replaced every 14 days to ensure that there was no substantial decrease  87  (>10%) in concentration of nitrate or ammonium over time that could increase the solution δ15N. 5.3.3. Sampling and natural abundance isotope analysis After 45 days of growth, plants were randomly sampled for either nitrogen isotope mass balance or 15N compartmental analysis (N=3). For natural abundance isotope analysis, samples were separated into leaves, stems and roots. Samples were flash frozen in liquid nitrogen and stored at -80 °C until freeze drying. Roots, leaves and stems were weighed for dry mass and then ground to a fine powder using a mortar and pestle and then ball milled (Fritsch Laborgeratebau, Terochem Scientific). Sub-samples of 3±0.1 mg were weighed into tin capsules (Elemental Microanalysis Ltd., 8x5 mm, D1008) and analyzed for δ15N and nitrogen on a PDZ Europa ANCA-GSL elemental analyzer interfaced to a PDZ Europa 20-20 isotope ratio mass spectrometer (Sercon Ltd., Cheshire, UK) (University of California Stable Isotope Facility, Davis, CA). 5.3.4.  15  N efflux apparatus  Plants sampled for 15N efflux analysis were transferred to a holding tank with nutrient composition equal to the growing solution. The holding tank was placed under fluorescent lighting (200 μmol m-2 s-1 PPFD) until plants were treated with the 15N loading solution. Each plant was individually placed in 1000 mL of aerated, loading solution of 98 atom% 15N for 60 minutes, after which the plant was removed and roots were allowed to gravitationally drain for 30 seconds. Roots were then rinsed over a glass funnel with the eluate flowing into 15 pre-weighed glass beakers at intervals of 3 x 15 s, 3 x 30 s, 2 x 60 s and 7 x 120 s for a total elapsed time of 18 minutes 15 seconds. Rinsing solution (identical to the original hydroponics solution) was supplied using a peristaltic pump and polyvinyl chloride tubing (Kuritec, Brantford, Ontario, Canada) at a rate of 4 mL s-1. Eluate volumes were determined by mass difference. Acidified (pH 2.0) 15 mL aliquots were stored in disposable scintillation vials and stored at 2 °C until processing for isotope analysis. Roots were weighed for fresh mass then oven-dried for 2 days at 60 °C to obtain dry mass. 88  5.3.5.  15  N efflux isotope analysis  Tin capsules (~1.5 mL) were prepared from foil squares (30 mm x 30 mm, Elemental Microanalysis UK). Eluate was pipetted in 7 x 1 mL increments (~49 μg of N total) into the capsules, with drying at ~50 °C between each increment. Root samples were prepared and loaded into tin capsules as above. Nitrogen isotope analysis was performed at the University of Saskatchewan Soil Science Stable Isotope Laboratory using a Costech ECS4010 elemental analyzer coupled to a Delta V mass spectrometer with Conflo IV interface. 5.3.6. Compartmental analysis Compartmental analysis was performed based on methods in Lee and Clarkson (1986), except release of excess 15N from the root (μmol g fw-1 min-1) was substituted for rate of 13N release, as follows: Equation 5.1  where, 15N Atom%Rinse was equal to 0.36654% and the specific activity of the loading solution, S0, was equal to 98%. The rate of 15N efflux, expressed on a per mass basis, was then calculated as: Equation 5.2 where, m = fresh mass of root, and t = time of eluate sampling and represents the elapsed sampling time for each individual solution sample. The log of the 15N efflux rate was plotted against elution time for segmental linear regression using Graphpad Prism 6 (La Jolla, CA, USA) to determine breakpoints and segment slopes (Figure 5.1). Segments represent nitrogen release from three compartments: the root surface, the apoplastic (intercellular) space and the cytoplasmic (intracellular) space (Lee and Clarkson, 1986). Half-life for each compartment was calculated as: 89  Figure 5.1. Representative segmental linear regression for determining half-lives of exchange and flux rates for the surface (A), apoplastic (B) and cytoplasmic (C) compartments. Each data point represents the log (efflux rate) at x-elapsed time (s).  90  Equation 5.3  –  where, k is the rate constant and is equal to: Equation 5.4 where, β is the slope of the regression line. Compartmental efflux can be calculated as: Equation 5.5 where, R0 is the intercept of the regression line with the ordinate for each compartment (i.e., the 15N efflux rate at time zero). Net uptake was calculated as the excess 15N remaining in the roots after rinsing and expressed as μmol N g fw-1 h-1. Efflux/influx was then: Equation 5.6 Flux from the root to the shoot could not be calculated because of the possibility of direct contamination of leaves or stems by the labelling solution during the loading process. Slight enrichment of stems and leaves was, however, observed (not shown). Compartmental nitrate or ammonium content was calculated as the area under the exponential decay curve of a plot of time versus 15N efflux rate (μmol h-1), and was approximated as the total 15N effluxed (μmol) during five half-lives: Equation 5.7 where, i = ith half-life, t = time and r = rate of 15N efflux at ith half-life. r at the ith half-life was calculated by multiplying the initial rate of 15N efflux by 0.5i. Then, assuming that 5% and 10% of root volume was occupied by cytoplasmic and apoplastic space, respectively (Lee and Ratcliffe, 1983), nitrate and ammonium concentrations of these compartments were calculated.  91  5.3.7. Isotope mass balance flux calculations E/I was calculated based on the methods in chapter 2 after correcting for carryover of tissue nitrogen in stem cuttings (see chapter 4). E/I is a function of overall plant discrimination against 15N relative to the substrate, the discrimination factor of the enzyme (nitrate reductase or glutamine synthetase for nitrate or ammonium, respectively) and the localization of assimilation in roots versus leaves. The proportion of total plant nitrogen in the leaf pool (Nleaf pool/Ntotal) is given by equation 2.8. Partitioning of assimilation between roots (Proot) and leaves (1-Proot) is a function of Nleaf pool/Ntotal,  the difference in δ15N between leaves and roots and the discrimination factor  of the enzyme (Δenz) and is given by Equations 2.12 and 2.13. The discrimination factor for glutamine synthetase is thought to be near 16.8‰ (Yoneyama et al. 1993). Data in Ledgard et al. (1985) suggest a Δenz of 15.4‰ for nitrate reductase. From Proot, plant Δ15N and Δenz of either nitrate reductase or glutamine synthetase, the estimate of E/I was obtained by Equation 2.15. The assimilation-averaged net influx of inorganic nitrogen into the root is equal to the total plant nitrogen, after correcting for contaminating nitrogen from the original cutting, divided by the root biomass (Equation 2.4). 5.3.8. Statistical analysis To compare net uptake and E/I across the two methods, a three-way ANOVA in SAS 9.3 (SAS Institute, Cary, NC) was performed using the following model: Equation 5.8 where, μ is the overall mean response, αi is the effect due to the genotype, τj is the effect due to the nitrogen source, ρk is the effect due to method, βij is the effect due to any interaction between the genotype and nitrogen source, γik is the effect due to any interaction between genotype and method, λjk is the effect due to any interaction between nitrogen source and method and εijk is the effect due to any three-way interaction between genotype, nitrogen source and method. Geometric mean  92  regression (Ricker 1984) was used to express the relationship between the two independent methods. Nitrogen source and genotype fixed effects on biomass and on physiological variables unique to a particular method (i.e., root and leaf nitrogen concentrations, compartmental fluxes, half-lives of exchange and compartmental nitrogen concentrations) were tested using two-way ANOVA. The statistical model was as follows: Equation 5.9 where μ is the overall mean response, αi is the effect due to the genotype, τj is the effect due to the nitrogen source and βij is the effect due to any interaction between the genotype and nitrogen source. ANOVA was carried out using Graphpad Prism 6 (La Jolla, CA, USA) followed by Tukey’s multiple comparison tests to separate means. Where necessary, data were log transformed to meet assumptions of homogeneity of variance and normality. Differences between treatments described as significant are those where P<0.05. 5.4. Results 5.4.1. Plant growth Plants were bigger when grown with nitrate (P<0.05) where mean biomass was 4.68 and 1.18 g under NO3- and NH4+, respectively (Figure 5.2). However, there was a significant interaction between genotype and nitrogen source. Biomass was greater on NO3- than NH4+ for four out of five genotypes. There were significant differences in growth among genotypes grown with NO3- but not NH4+. GIL-9 had the greatest difference in biomass between sources (6.9 and 1.19 g for NO3- and NH4+ grown plants, respectively). Biomass was not different between sources for GIL-7. No genotype was larger under NH4+ than NO3-. Root:shoot ratios were two times greater under NH4+ (0.26) than under NO3- (0.13). In contrast to biomass, there were no genotypic differences in root:shoot ratios for NO3- grown plants but there were for NH4+. Under  93  Figure 5.2. A) Total biomass and B) root: shoot ratio for five Populus balsamifera L. genotypes grown with either 500 μM NO3- of NH4+ for 45 days. Means ±SE (N = 5-6).  94  Table 5.1. Root and leaf nitrogen concentration (mmol N g dw-1) for five Populus balsamifera L. genotypes grown with either 500 μM NO3- or NH4+ for 45 days. Means ±SE (N = 2-3). NO3Root (mmol N g dw-1) Leaf (mmol N g dw-1)  GIL-9  OUT-9  GIL-7  CLK-4  GIL-2  2.68±0.05  2.79±0.08  2.27±0.13  2.34±0.02  2.44±0.08  2.31±0.25  2.14±0.14  1.79±0.23  1.62±0.29  2.43±0.15  NH4+ Root (mmol N g dw-1) Leaf (mmol N g dw-1)  GIL-9  OUT-9  GIL-7  CLK-4  GIL-2  2.34±0.19  2.85±0.08  2.44±0.14  2.04±0.37  2.40±0.26  1.68±0.41  2.36±0.48  1.82±0.36  1.31±0.15  1.67±0.36  95  NH4+, root:shoot ratios ranged from 0.18 for OUT-9 to 0.4 for GIL-7. GIL-7 and GIL-9 had significantly higher root:shoot ratios when grown with NH4+ (P<0.05). Leaf and root nitrogen concentrations were not significantly different among genotypes or between nitrogen sources (Table 5.1). Root nitrogen concentration was approximately 0.5 mmol g dw-1 greater than, but significantly correlated with, leaf nitrogen concentration (r=0.634; P=0.002). Mean root and leaf nitrogen concentrations were 2.46 and 1.94 mmol N g dw-1, respectively. However, there was a significant interaction between genotype and source where root nitrogen concentration for OUT-9 was significantly greater than CLK-4 when grown with NH4+ but not with NO3-. 5.4.2. Compartmental analysis Compartmental analysis indicated that surface flux was roughly two orders of magnitude greater than flux from the apoplast, which in turn was about one order of magnitude higher than the cytoplasmic efflux (Table 5.2). The surface flux represents exchange between the boundary layer and substrate, and was not significantly different between treatments or genotypes (Table 5.2). In contrast, the flux from the apoplast averaged 0.96 and 3.37 mmol g fw-1 h-1 for NO3- and NH4+, respectively (P=0.007). Although the outward flux of NO3- from the apoplast was not significantly different between genotypes, the flux of NH4+ was higher in GIL-7 than GIL-9, OUT-9 and CLK-4. Similarly, cytoplasmic efflux was approximately twice as high (P=0.0078) for NH4+ (0.27 mmol g fw-1 h-1) compared to NO3- (0.13 mmol g fw-1 h-1). There were no genotypic differences in cytoplasmic efflux (P=0.498) The half-lives of exchange (t1/2) indicate the time taken for 50% of the inorganic nitrogen to be lost from a NO3- or NH4+ pool or compartment (Table 5.3). Although loss rates from the root surface were not different, the t1/2 was significantly longer for NH4+ (13.8 s) than for NO3- (7.9 s). In contrast, the t1/2 of the apoplastic space did not differ significantly among treatments. The overall apoplastic t1/2 was 69.3 s, approximately six times that of the surface compartment. Half-lives of exchange for the cytoplasmic space  96  Table 5.2. Outward fluxes (µmol N g fw-1 h-1) of nitrate (NO3-) and ammonium (NH4+) as estimated from compartmental analysis for five Populus balsamifera L. genotypes grown with either 500 μM NO3- or NH4+ for 45 days. Means ±SE (N = 2-3). NO3Compartment  GIL-9  OUT-9  GIL-7  CLK-4  GIL-2  Surface  156.6±64.03  38.2±1.26  104.6±43.44  27.9±17.82  12.88±0.78  Apoplast  1.95±0.671  0.41±0.048  1.46±0.948  0.34±0.109  0.62±0.189  Cytoplasm  0.23±0.099  0.07±0.022  0.22±0.148  0.033±0.004 0.056±0.014  NH4+ GIL-9  OUT-9  GIL-7  CLK-4  GIL-2  Surface  33.2±0.73  53.8±20.67  28.5±6.09  36.3±11.28  33.8±2.86  Apoplast  0.97±0.729  2.54±0.848  7.59±1.039  2.27±0.560  3.50±1.591  Cytoplasm  0.19±0.116  0.33±0.013  0.33±0.083  0.25±0.009  0.28±0.021  97  Table 5.3. Half-lives of exchange (t1/2) for NO3- and NH4+ of root surface film, apoplastic space and cytoplasm estimated from compartmental analysis for five Populus balsamifera L. genotypes grown with either 500 μM NO3- or NH4+ for 45 days. Means ±SE (N = 2-3). NO3Compartment  GIL-9  OUT-9  GIL-7  CLK-4  GIL-2  Surface (s)  7.1±3.82  6.1±0.11  4.7±0.69  9.9±5.06  12.2±1.05  Apoplast (s)  56.1±2.89  88.3±3.13  60.4±4.98  74.1±13.76  53.8±3.33  Cytoplasm (min)  56.6±16.33  47.2±29.12  19.48±4.40  12.5±5.39  2.1±0.22  NH4+ GIL-9  OUT-9  GIL-7  CLK-4  GIL-2  Surface (s)  14.8±5.26  7.6±2.29  16.6±2.49  12.9±0.03  15.0±2.25  Apoplast (s)  126.7±12.98  61.4±22.84  37.34±7.02  71.6±13.88  82.1±25.84  Cytoplasm (min)  26.1±2.09  13.1±0.08  6.8±0.44  8.5±1.28  9.75±3.42  98  Table 5.4. Apoplast and cytoplasm nitrate and ammonium concentrations as estimated by compartmental analysis for five Populus balsamifera L. genotypes grown with either 500 μM NO3- or NH4+ for 45 days. Means ±SE (N = 2-3). NO3Compartment  GIL-9  OUT-9  GIL-7  CLK-4  GIL-2  Apoplast (mM)  0.46±0.16  0.14±0.03  0.32±0.19  0.10±0.01  0.13±0.01  Cytoplasm (mM)  13.48±2.01  4.26±0.68  4.03±0.91  4.18±1.32  2.10±0.33  NH4+ GIL-9  OUT-9  GIL-7  CLK-4  GIL-2  Apoplast (mM)  0.78±0.43  0.61±0.08  1.00±0.45  0.63±0.04  0.97±0.12  Cytoplasm (mM)  3.90±0.15  2.54±0.16  1.61±0.14  1.78±0.27  1.64±0.34  99  were approximately 32 and 12 min for NO3- and NH4+, respectively (P=0.0488). There were no genotypic differences in cytoplasmic half-lives of exchange (P=0.1460). Estimated apoplastic NH4+ concentrations were approximately three times higher than NO3- concentrations (P<0.0012), but did not vary between genotypes (Table 5.4). Mean apoplastic concentrations, were 0.28 mM and 0.83 mM for NO3- and NH4+, respectively. In contrast, cytoplasmic NO3- concentrations were significantly greater than NH4+ concentrations and GIL-9 had significantly higher concentrations for both ions than the other four genotypes. 5.4.3. Independent estimates of net uptake and E/I are correlated Estimates of net uptake were almost two times greater using the isotope mass balance model compared to compartmental analysis (Table 5.5). However, there was a positive relationship between the two methods (r=0.623; P=0.051) (Figure 5.3). Since net uptake in the isotope mass balance approach is a function of total plant nitrogen and root biomass, it is, in part, proportional to the inverse of the root:shoot ratio (r=0.87; P<0.0001). The same was not true for compartmental analysis (r=0.24; P=0.2252). Irrespective of method, E/I was significantly higher for NH4+ than NO3-. However, whereas compartmental analysis indicated mean flux ratios of 0.4 and 0.22 for NH4+ and NO3-, respectively, isotope mass balance modelling gave flux ratios of 0.65 and 0.45. Despite this absolute difference in E/I, there was a significant positive relationship between the two measures of E/I across treatments and genotypes (r=0.77; P=0.0065) (Figure 5.4). Generally, genotypes that had the highest E/I using the isotope mass balance approach also had the highest E/I using the compartmental analysis method (Table 5.6), but there was significant genotypic variation in E/I only with NH4+. 5.5. Discussion As shown here using rooted balsam poplar cuttings, the natural abundance isotope mass balance method proposed in Chapter 2 yields estimates of E/I and net nitrogen uptake that are comparable, but not identical, to compartmental analysis. 100  Figure 5.3. Coherence of estimates of net uptake (μmol N g dw-1 h-1) by compartmental analysis and nitrogen isotope discrimination for five Populus balsamifera L. genotypes grown with either 500 μM NO3- (open circles) of NH4+ (closed circles) for 45 days. Means ±SE (N = 2-3). The dotted line indicates significant geometric mean regression (P=0.0131). The solid line shows the position of a 1:1 relationship.  101  Figure 5.4. Coherence of estimates of efflux/influx by compartmental analysis and nitrogen isotope discrimination for five Populus balsamifera L. genotypes grown with either 500 μM NO3- (open circles) of NH4+ (closed circles) for 45 days. Means ±SE (N = 23). The dotted line indicates significant geometric mean regression (P=0.0065). The solid line shows the position of a 1:1 relationship.  102  Table 5.5. Net nitrate and ammonium uptake (μmol N g dw-1 h-1) estimated from the isotope mass balance approach (IMB) or compartmental analysis (CA) for five Populus balsamifera L. genotypes grown with either 500 μM NO3- or NH4+ for 45 days. Means ±SE (N = 2-3). NO3Method  GIL-9  OUT-9  GIL-7  CLK-4  GIL-2  IMB  15.67±3.69  18.85±5.67  16.51±4.44  16.76±8.24  16.64±4.57  CA  9.20±2.65  9.01±1.04  6.45±3.02  6.07±5.10  7.83±3.54  NH4+ GIL-9  OUT-9  GIL-7  CLK-4  GIL-2  IMB  12.79±3.33  18.23±3.64  7.17±0.51  13.38±0.92  7.71±1.29  CA  3.25±1.58  14.34±0.47  6.07±0.86  4.88±0.88  5.05±0.11  103  Table 5.6. Efflux/influx estimated by isotope mass balance modelling (IMB) or by compartmental analysis (CA) for five Populus balsamifera L. genotypes grown with either 500 μM NO3- or NH4+ for 45 days. Means ±SE (N = 2-3). NO3Method  GIL-9  OUT-9  GIL-7  CLK-4  GIL-2  IMB  0.35±0.073  0.33±0.055  0.49±0.048  0.46±0.024  0.34±0.083  CA  0.19±0.016  0.18±0.011  0.26±0.037  0.30±0.041  0.19±0.047  NH4+ GIL-9  OUT-9  GIL-7  CLK-4  GIL-2  IMB  0.48±0.042  0.57±0.020  0.76±0.04  0.74±0.056  0.46±0.088  CA  0.50±0.016  0.25±0.021  0.40±0.015  0.43±0.037  0.41±0.051  104  Compartmental analysis by isotope labelling has for some time been the only method used for calculating E/I in addition to net uptake, but provides a more complete picture of ion flux in and out of roots. 5.5.1. Compartmental analysis using 15N Based on methods modified from Clarkson and Lee (1986) for 13N, balsam poplar roots were loaded with 15N-labelled nitrate and ammonium to measure net flux characteristics under steady-state conditions. Although the 13N radioisotope has more frequently been used in such studies (e.g., Siddiqi et al. 1991; Kronzucker et al. 1995a, 1995b; Min et al. 2002), similar precision was achieved using 15N. Stable isotope labelling with 15N has also been successfully applied to compartmental analysis in Triticum aestivum L. (Devienne et al. 1994) and Allium cepa L. (Macklon et al. 1990). To the best of our knowledge, the present study is the first to report 15N compartmental analysis of a woody plant species. Half-lives of exchange for nitrate as compared to ammonium were longer for the cytoplasm and shorter at the root surface and the apoplast (Table 5.3). Rates of efflux from the apoplast and cytoplasm were greater for ammonium. Although differences in substrate concentrations limit direct comparison to our results, the fluxes and half-lives of exchange in balsam poplar were within the same range as reported in other tree species, including white spruce (Picea glauca (Moench) Voss), lodgepole pine (Pinus contorta Douglas), Douglas-fir (Pseudotsuga menziesii (Mirb.) Franco) and trembling aspen (Populus tremuloides Michx.) (Kronzucker et al. 1995a, b; and Min et al. 2002). Also, whether comparing genotypes (our study) or species (Min et al. 2002), variation in apoplastic and cytoplasmic fluxes were lower with ammonium than with nitrate. Nitrate concentrations were more than two times higher than ammonium concentrations in the cytoplasm, but were lower in the apoplast (Table 5.4). This may indicate that balsam poplar has a general preference for nitrate. The better growth observed on nitrate is also consistent with a nitrate preference. For white spruce, which has an ammonium preference (Kronzucker 1995a, b), nitrate concentrations in the 105  cytoplasm were lower than ammonium, but the same was also true of trembling aspen (Min et al. 2002). In the apoplast, mean nitrate concentration was approximately half the concentration of the substrate (Table 5.4). In contrast, in spruce and aspen the apoplastic nitrate concentration was approximately equal to the substrate (Kronzucker et al. 1995a, b; Min et al. 2002). For balsam poplar, the ammonium concentration in the apoplast was greater than the substrate, although not to the degree reported for spruce and aspen. Kronzucker et al. (1995a, b) attributed differences between apoplastic nitrate and ammonium concentrations to the Donnan equilibrium, where the negative charge of the cell wall increases the binding capacity for cations (NH4+) but not anions (NO3-). The compartmental concentrations reported here are lower than those observed by Kronzucker et al. (1995a; 1995b) and Min et al. (2002). These differences may in part be due to uncertainties in estimating compartmental volumes. Based on Laties (1959), Clarkson and Lee (1986) suggested that 10% of the total root volume is apoplastic free space and 5% is cytoplasm, estimates commonly used in compartmental analysis. However, volume fractions may vary with species or genotype and are known to be affected by root development and environment (McGarry, 1995). Few, if any, studies have used compartmental analysis to examine intraspecific variation in nitrogen efflux, half-life of exchange and compartmental nitrogen concentration. Intraspecific variability exists, and in some cases, is independent of nitrogen source for traits measured using compartmental analysis. Intraspecific variability in exchange half-life, particularly in the cytoplasm, was high. GIL-9, in particular, had longer exchange half-lives on both sources compared to other genotypes. Since nitrogen concentration is a function of compartmental half-life of exchange and efflux, cytoplasmic nitrogen concentration of GIL-9 was considerably higher than the other genotypes on both sources. The reasons underlying these variations are not entirely clear. However, they could be related to physiological or morphological variations at the root level.  106  5.5.2. Compartmental analysis and isotope mass balance estimates of E/I Efflux expressed relative to influx not only describes bidirectional movement of inorganic nitrogen between the root and rhizosphere but also indicates the efficiency of uptake. The measure has utility because it reflects species preferences (Kronzucker et al. 1997), possible toxicity (Kronzucker et al. 2001; Britto and Kronzucker, 2006), and how well external supplies meet internal demands (Pritchard & Guy 2005). Although there was a significant relationship between E/I calculated from compartmental analysis and the isotope mass balance approach, E/I was lower by approximately 33-50% using compartmental analysis (Figure 5.4). There are several possible explanations for the difference. First, the two methods operate over different scales in time and, to some degree, space. Second, the δ15N of the root organic fraction may deviate from δ15N of the whole tissue. Third, there are uncertainties in discrimination factors for the assimilatory enzymes. Fourth, there may be a small amount of discrimination associated with membrane transport. None of these are mutually exclusive. In the first instance, compartmental analysis monitors nitrogen flux over a period of several minutes, whereas the isotope mass balance approach integrates over growing time (i.e., several weeks). With the latter, developmental and diurnal variation in E/I would be assimilation-averaged according to when the nitrogen was acquired. Increased efflux during night was observed in pearl millet (Pennisetum glaucum (L.) R. Br.) with nitrate nutrition (Pearson et al. 1981) and in Italian ryegrass (Lolium perenne L.) with ammonium (MacDuff and Jackson 1992). Using 15N labelling, net uptake rates decrease during the night for both ammonium and nitrate but are species dependent (Delhon et al. 1995; Gessler et al. 2002). Kumar et al. (2003) showed changes in the transcript abundance of ammonium transporters and a subsequent decrease in ammonium uptake at night in rice (Oryza sativa L.) plants. Decreased uptake rates combined with increased efflux rates at night may increase E/I at night (Scheurwater et al. 1999). Since compartmental analysis did not account for E/I during the night period, this could, in part, explain lower estimates of E/I compared to the isotope mass balance approach.  107  Spatially, the two techniques differ because the isotope mass balance method accounts for the translocation of inorganic nitrogen from the root to the shoot, whereas this flux was not measurable for compartmental analysis. However, the inclusion of xylem flux in compartmental analysis would only lead to an increase in net uptake and a further decrease in E/I. As per assumption #3 in chapter 2, it was assumed that the Δ15N of the organic nitrogen in the root was equal to the bulk tissue Δ15N in the root. However, there will likely be a small portion of inorganic nitrogen in the root that leads to an underestimation of root Δ15N. If significant, this omission would cause E/I to be underestimated, not overestimated, and therefore cannot account for the discrepancy between the two methods. Underestimation of enzymatic discrimination factors for the assimilatory enzymes could result in an increase in estimated E/I using the nitrogen isotope mass balance approach. Data in Figures 5.3 & 5.4 and Tables 5.5 & 5.6 assume discrimination factors of 15.4‰ for nitrate reductase (Ledgard et al. 1985) and 16.8‰ for glutamine synthetase (Yoneyama et al. 1993). However, more recent work has suggested that the discrimination factor of nitrate reductase is closer to 22-26‰ (Needoba et al. 2002; Tcherkez and Farquhar, 2006; Karsh et al. 2012). If E/I is recalculated using 22‰ for both enzymes, the agreement between methods is considerably improved (Figure 5.5A). Although discrimination by glutamine synthetase has not been similarly reassessed, the improved coherence of E/I on both nitrate and ammonium indicates that the discrimination factors of both assimilatory enzymes may indeed be underestimated. There is no evidence that nitrogen isotope discrimination occurs during membrane transport (Handley and Raven 1992; Evans 2001), but the possibility remains that there may be some slight fractionation associated with this step. I considered this possibility by adjusting the observed plant Δ15N as follows:  108  Figure 5.5. Effects of changing the discrimination factor of the assimilatory enzyme A) or adjusting for discrimination in membrane transport B) on the coherence between estimates of efflux/influx by isotope mass balance modelling and compartmental analysis. In panel A, the dotted line shows the relationship when enzyme discrimination factors of 15.4 and 16.8‰ (dotted line) are used for nitrate reductase and glutamine synthetase, respectively, while the dashed line shows the relationship when 22.6‰ is used for both. In panel B, the dotted line is as above, with adjustments for 15N discrimination during membrane transport of 1 and 2‰ shown by dashed and dasheddotted lines, respectively. The solid line in both panels shows the position of a 1:1 relationship. 109  Equation 5.10 where, Δenz is equal to the discrimination factor of the enzyme and Δtransport is the discrimination factor for transport. This calculation assumes that discrimination in transport applies equally to influx and efflux, thus as plant Δ15N approaches 0, the adjustment is maximized and as plant Δ15N becomes more negative and closer to Δenz, the adjustment approaches 0‰. When E/I is recalculated assuming Δtransport of either 1 or 2‰ (Figure 5.5B) there is improved convergence between the isotope mass balance approach and compartmental analysis at low E/I, but the effect is otherwise marginal. 5.5.3. Advantages of the isotope mass balance approach Considering all the above, it is not surprising that there are absolute differences in flux estimates and E/I as determined by either compartmental analysis or by isotope mass balance. The concurrence observed, however, at the treatment level and at the genotype level, helps validate the isotope mass balance approach, which has some significant advantages over compartmental analysis. Although cell or tissue specific at the root level, compartmental analysis requires the use of either radioactive 13N or stable 15N. Specialized equipment and training is required to use 13N for compartmental analysis and access to 13N (t1/2 = 9.97 minutes) is limited to just a few labs worldwide. Using stable 15N in the loading solution is equally effective. However, as with 13N, at least 15 samples must be taken per assay to have enough data for segmental linear regression, and this is labour intensive and costly. On the other hand, establishing proper growth conditions for the isotope mass balance approach requires considerable care and attention and is also quite labour intensive. Advantages include reduced costs for isotope analysis (2-4 samples per assay; i.e., starting material, leaves, stems and roots) and opportunities for scaling up to the simultaneous assay of large numbers of plants under a variety of environmental conditions. Additionally, it provides time-integrated estimates of several other whole plant and organ level nitrogen use traits.  110  5.6. Conclusion Coherence is significant between the established, time-point specific compartmental analysis approach and a new, time-integrated isotope mass balance approach for measuring net nitrogen uptake and E/I. Regardless of the method used to study the flux of inorganic nitrogen across the root plasma membrane, the information obtained is crucial for understanding whole-plant nitrogen dynamics. Increasing the confidence in measurements of nitrogen fluxes and increasing the understanding of the relationship of the fluxes to other nitrogen-use processes contributes to a further understanding of nitrogen-use efficiency. Through reduced isotopic sampling and more universal access, and because experiments can be scaled up to better evaluate genetic variation in flux and nitrogen-use traits, the isotope mass balance approach may facilitate efforts to improve the utilization of nitrogen.  111  6. Nitrogen isotope discrimination indicates genotypic variation in nitrogen source preference, uptake and assimilation in Populus balsamifera L. 6.1. Summary As interest in using poplar as a biofuel feedstock increases, it is important that increases in yields do not require proportionate increases in nitrogen fertilization. Intraspecific variability in nitrogen use has not been assessed in a natural poplar species. The nitrogen isotope mass balance approach was used to assess intraspecific variability in uptake, assimilation and allocation traits in five climatically dispersed provenances of Populus balsamifera L. grown with either nitrate or ammonium. Balsam poplar was able to grow well with either ammonium or nitrate. Genotypic variation within provenances exceeded significant provenance level variation. Genotypes with rapid growth on nitrate achieved similar growth with ammonium, and root:shoot ratio was greater under ammonium. However, there were genotypes where root:shoot ratio and biomass were affected by nitrogen source. Tissue nitrogen concentration was greater for ammonium in the leaves and stems but not the roots. There was extensive genotypic variation in organ-level nitrogen isotope composition. Root nitrogen isotope composition was more depleted under nitrate than ammonium, but leaf nitrogen isotope discrimination was not different between plants on different sources. This is indicative of variation in partitioning of nitrogen assimilation, efflux/influx (E/I) and root or leaf assimilation rates. The proportion of nitrogen assimilated in roots was lower under nitrate than ammonium. In contrast, E/I was higher for nitrate than ammonium. With the exception of E/I, nitrogen use traits for nitrate were correlated with the same traits when grown with ammonium. Using the nitrogen isotope mass balance model, a high degree of genotypic variation in nitrogen use traits was identified at both the provenance and more importantly, the clonal level. To improve on nitrogen-use in poplar, timeintegrated information based on nitrogen isotope composition can be incorporated into traditional breeding and phenotypic screening efforts to explore the relationship between calculated nitrogen use traits under controlled conditions and field level variation in performance. 112  6.2. Introduction There is increasing interest in using Populus species or their hybrids as feedstock for the growing biofuel industry (Yamshanov et al. 2008; Sannigrahi et al. 2010). Rapid growth, ease of propagation and the ability to grow on marginal soils make poplar suitable for sustainable production of biofuel feedstock. However, as efforts to improve yields increase, the nitrogen demand of new high-yielding cultivars will increase. Nitrogen is considered the limiting nutrient in most natural ecosystems and the largest input in agricultural systems. Nitrogen-use efficiency must be maintained or even improved upon to establish poplar as a bioenergy feedstock than can be grown with minimal inputs and, at the same time, produce rapid biomass growth. The first step to improving nitrogen-use efficiency is to adequately determine the degree of intraspecific variation in nitrogen-use traits. Cost, time and complexity are all limitations to current assays available for measuring many of these traits. Although intraspecific variation in nitrogen use has been reported for a number of cereal species (Hirel et al. 2007) and Arabidopsis (Masclaux-Daubresse et al. 2010), the lack of an integrated approach to evaluate nitrogen-use traits limits interpretation of this genotypic variation (Hirel et al. 2007). Nitrogen isotope discrimination at natural abundance has the potential to be used as an integrated measure of nitrogen use in plants (Robinson 2001; Evans 2001). For woody plants grown under steady-state conditions, species level variation in nitrogen isotope composition has only been described in white spruce (Picea glauca (Moench) Voss) (Pritchard and Guy 2005). In the field, intraspecific variation in nitrogen isotope composition has been reported in European beech (Fagus sylvatica L.) (Peuke et al 2006) and Norway spruce (Picea abies (L.) Karst) (Gebauer and Schulze 1991). However, interpretation of nitrogen isotope composition under field conditions is typically affected by chemical, spatial and temporal heterogeneity in soil nitrogen. Interpretation of intraspecific variation in nitrogen isotope composition at the whole plant and organ level requires careful control over the nitrogen substrate and measurement of organ level isotope composition. In herbaceous plants under steadystate conditions, intraspecific variation in nitrogen isotope composition has been 113  reported in barley (Hordeum vulgare L.) (Handley et al. 1997; Robinson et al. 2000; Kolb and Evans, 2003), wheat (Triticale aestivum L.) (Yousfi et al. 2009; Yousfi et al. 2012; Yousfi et al. 2013), and rice (Oryza sativa L.) (Yoneyama et al. 2001). This variation has been attributed to possible differences in nitrogen uptake or assimilation patterns that were a function of environment and genotype. The nitrogen isotope mass balance model introduced in Chapter 2 can be used to interpret results obtained from such experiments, providing integrated information on nitrogen use at the whole plant and organ level that is difficult to measure using traditional assays. The nitrogen isotope mass balance model developed in this thesis uses measurements of organ level nitrogen isotope fractionation under steady-state nitrogen conditions in combination with a priori knowledge of source δ15N. In addition to organlevel biomass and unprocessed nitrogen isotope composition, traits related to both, nitrogen uptake and assimilation, were calculated. Assimilation partitioning is a function of the difference in isotope composition between the two primary sites of assimilation (roots and leaves) and the proportion of overall nitrogen in the leaves. Partitioning of assimilation, efflux/influx (E/I) and translocation of inorganic nitrogen to the shoot can be calculated to reflect the ease of movement and supply relative to demand under steady-state nitrogen conditions. E/I is obtained as a function of whole plant nitrogen isotope composition, partitioning of assimilation and the discrimination associated with the assimilatory enzyme. More detail of the nitrogen isotope mass balance approach can be found in Chapter 2. In general, poplars have been widely described as model systems for woody plant biology (Bradshaw et al. 2000; Jansson and Douglas, 2007). Balsam poplar (Populus balsamifera L.) has a geographic range extending through much of the boreal forest region across North America, extending from the Atlantic coast of Canada and New England to Alaska and above the Arctic Circle (Petersen and Petersen, 1992). This large geographic range contains latitudinal gradients in adaptive traits (Soolanayakanahally et al. 2009). I used five climatically dispersed provenances of balsam poplar that extend from the prairie transition in the dry range of the species to the boreal forest-tundra 114  transition zone to determine whether nitrogen source preference varies along a climatic gradient, and whether intraspecific variation exists for nitrogen-use traits when grown with nitrate or ammonium. 6.3. Materials and methods 6.3.1. Plant material and experimental design First year branches of 25 genotypes of balsam poplar ranging from 51 °N to 56 °N were obtained from the AAFC-AESB Agroforestry Development Centre at Indian Head, Saskatchewan, Canada and stored at 4 °C for approximately three months to fulfill chilling requirements. The five provenances reflected a climatic gradient that extends from a prairie ecosystem to the Canadian Shield boreal forest. The five provenances starting from prairie were: Outlook (OUT), Saskatchewan (51.1 °N, 106.2 °W), Saskatoon (SKN) (2.2 °N, 106.4 °W), Saskatchewan, Turtleford (TUR), Saskatchewan (53.2 °N, 108.3 °W), Cold Lake (CLK), Alberta (54.2 °N, 110.1 °W) and Gillam (GIL), Manitoba (56.4 °N, 94.7 °W). Two-node cuttings, approximately 6-8 cm long were weighed for fresh weight and arranged in a randomized complete block design with three blocks of two nitrogen treatments supplied as either 500 μM nitrate or 500 M ammonium. Plants were grown for 45 days in a hydroponics solution until harvest. Complementary samples of each genotype were collected as reference samples (N = 3) and analyzed for starting nitrogen isotope composition and concentration. 6.3.2. Hydroponics system The hydroponics system was comprised of six 1000L containers lined with 45 mil rubber pond liner (Firestone, USA) constructed in a greenhouse under ambient light conditions supplemented by sodium halide lighting (600 mol m-2 s-1) and 18/6 h day/night photoperiod. Temperatures in the greenhouse were maintained between 20 and 24 °C. For the first experiment, solution temperatures averaged approximately 20°C. For the second experiment to confirm genotypic differences, solution temperatures averaged approximately 23 to 24°C (Figure A.2). Each container had a floating raft that had a capacity for up to 32 plants. Unused plugs in the raft and the rest  115  of the container were covered with black plastic to prevent algal growth from light infiltration into the hydroponics solution. The hydroponics solution was a modified 1/10th strength Johnson’s solution (Johnson et al. 1957) supplemented with either 250 M Ca(NO3)2 or 250 M (NH4)2SO4. Final nutrient composition, excluding the nitrogen salts, was: 200 μM KH2PO4, 200 μM K2S04, 100 μM MgSO4, 100 μM CaSO4, and micronutrients: 5 μM Cl, 2.5 μM B, 0.2 μM Mn, 0.2 μM Zn, 0.1 μM Mo, 0.05 μM Cu, and 50 μM Fe2+. A centrifugal pump, with a pumping capacity of approximately 20 L per minute, provided circulation and aeration of the solution for each container. The solution was monitored periodically for oxygen levels, pH (Figure A.2) and temperature (Figure A.3). Powdered calcium carbonate (CaCO3) was added to buffer pH in the range of 6-7.5. Media NH4+ and NO3- concentrations were assayed using the phenol:hypochlorite (Solorzano 1969) and perchloric acid (Cawse 1967) methods, respectively (Figure A.4). The solution was completely replaced every 14 days to ensure that there was no substantial decrease (no more than 10%) in concentration of nitrate or ammonium over time that could increase the solution δ15N. 6.3.3. Sampling and natural abundance isotope analysis After 45 days of growth, plants were separated into leaves, stems, roots and the original cutting. Samples were flash frozen in liquid nitrogen and stored at -80 °C until samples could be freeze-dried at -50 °C for two days. Once dried, roots, leaves, stems, cuttings and the reference cuttings were weighed. Samples were ground to a fine powder using a mortar and pestle and then ball milled (Fritsch Laborgeratebau, Terochem Scientific). Sub-samples of 3±0.1 mg were weighed into tin capsules (Elemental Microanalysis Ltd., 8x5 mm, D1008) and analyzed for δ15N and nitrogen concentration on a PDZ Europa ANCA-GSL elemental analyzer interfaced to a PDZ Europa 20-20 isotope ratio mass spectrometer (Sercon Ltd., Cheshire, UK) (University of California Stable Isotope Facility, Davis, CA). Isotopic composition is expressed as δ15N:  116  Equation 6.1 where, Rsample is the 15N/14N isotope ratio of the sample and Rstandard is the isotope ratio of a known standard (air). Tissue nitrogen isotope composition was corrected for contaminating nitrogen from cuttings using the protocol described in Chapter 4. Isotope discrimination is usually denoted by the equation (Farquhar et al. 1989):  Equation 6.2  The ammonium and nitrate salts used for the growth media had a δ15N of -0.96 and +58.5‰, respectively. Leaf, root, stem and cutting δ15N were converted to discrimination values prior to model calculations. 6.3.4. Mass balance calculations After correcting for pre-existing nitrogen remobilized to growing tissues from vegetative cuttings following the approach described in Chapter 4, the isotope mass balance model described in Chapter 2 was used to obtain several nitrogen-use traits from measurements of nitrogen isotope composition, nitrogen concentration and biomass of roots and leaves. 6.3.5. Statistical analysis Biomass, root:shoot ratio, δ15N, nitrogen concentration, total nitrogen of root, stem and leaf tissues, and model calculations were compared using a nested ANOVA with nitrogen source, genotype and provenance as fixed effects with genotype nested within provenance. The statistical model is as follows: Equation 6.3 where, μ is the overall mean response, αi is the effect due to the genotype, τj is the effect due to the nitrogen source, τ(γ)jk is the effect due to genotype nested within provenance and βij is the effect due to any interaction between the genotype and  117  nitrogen source. Analysis of variance procedure was carried out using Graphpad Prism 6 (La Jolla, CA, USA) to obtain estimates of the means, followed by Tukey’s multiple comparison tests to separate means. Where necessary, data were log transformed to meet assumptions of homogeneity of variance and normality. Differences between treatments described as significant are those where P <0.05. For correlations, significance is indicated using ., *, **, and *** to denote significance when P<0.10, P<0.05, P<0.01 and P<0.001. 6.3.6. Replication of genotypic differences in calculated nitrogen-use traits predicted from the nitrogen isotope mass balance model. To determine whether genotypic ranking within each source for nitrogen-use traits was repeatable, a second experiment with only seven genotypes was compared to the results from the first experiment in raw measured traits and overall calculated traits. To compare the two experiments, a three-way ANOVA using SAS 9.3 (SAS Institute, Cary, NC) was used with genotype, nitrogen source and experiment as fixed effects. The statistical model is as follows: Equation 6.4 where, μ is the overall mean response, αi is the effect due to the genotype, τj is the effect due to the nitrogen source, ρk is the effect due to experiment, βij is the effect due to any interaction between the genotype and nitrogen source, γik is the effect due to any interaction between genotype and experiment, λjk is the effect due to any interaction between nitrogen source and experiment and εijk is the effect due to any three-way interaction between genotype, nitrogen source and experiment. Geometric mean regression was used to determine the relationship between the two experiments using Microsoft Excel and plotted using Graphpad Prism 6 (La Jolla, CA, USA).  118  6.1. Results 6.1.1. Root:shoot ratio and leaf nitrogen concentration was affected by nitrogen source but biomass was not Growth averaged approximately 15% more when grown with NO3- as compared to NH4+, but this difference was not significant (P=0.0772) (Figure 6.1). Genotypes with high biomass under NO3- also had high biomass under NH4+ (r=0.543; P=0.0059) (Table 6.1). Because of a significant increase in leaf and stem biomass but not an increase in root biomass under NO3-, root:shoot ratio was higher in all provenances when grown with NH4+ than with NO3- (Figure 6.1). The difference between root:shoot ratio for NH4+ and NO3- grown plants decreased for provenances from the boreal forest versus provenances from the prairies. Similar to biomass, although there were greater root:shoot ratios when plants were grown on NH4+, differences between genotypes were correlated across sources (r=0.581; P=0.0023). Nitrogen concentration was significantly higher for plants grown with NH4+ than NO3- for leaves and stems but not roots (Table 6.2). Mean nitrogen concentration was 2.51, 0.42 and 2.03 μmol mg dw-1 under NO3- and 2.55, 0.76, and 2.18 μmol mg dw-1 under ammonium for roots, stems and leaves, respectively. Nitrogen concentrations in roots and stems were less variable than leaves (Table 6.1). The range in mean genotype nitrogen concentration was greater under NO3- for roots, under NH4+ for stems and equal for leaves (Table 6.1). There were no clinal trends in nitrogen concentration for the provenances. The fraction of total plant nitrogen found in the leaves (Nleaf pool/Ntotal) was not higher for NO3- compared to NH4+. Since net root uptake is partly proportional to the inverse of the root:shoot ratio, net root uptake was lower under NH4+ than NO3-. Although there were genotypic differences in net root uptake of nitrogen, there were no differences between provenances (Table 6.2). 6.1.2. Source did not affect whole plant Δ15N but organ level Δ15N was affected All genotypes were depleted in 15N relative to their respective hydroponic solutions at the individual organ and whole plant level, showing discrimination against 119  Figure 6.1. Total plant biomass ±SE (N=9-15) (top) and root:shoot ratio ±SE (bottom) for five provenances of Populus balsamifera L. grown with either 500 μM nitrate (white bars) or ammonium (grey bars).  120  Table 6.1. Mean (±SE) (N=9-15) provenance tissue nitrogen concentration (root [N], stem [N] and leaf [N]) (μmol mg dw-1), the proportion of plant nitrogen allocated to the leaf (Nleaf pool/Ntotal), and net root uptake (μmol mg dw-1 h-1) for five climatically dispersed provenances of Populus balsamifera L. grown with either 500 μM nitrate or ammonium.  Nitrate Root [N] Stem [N] Leaf [N] Nleaf pool/Ntotal Net Root Uptake Ammonium Root [N] Stem [N] Leaf [N] Nleaf pool/Ntotal Net Root Uptake  Outlook  Saskatoon  Provenance Turtleford  2.54±0.11 0.42±0.02 2.13±0.08 0.81±0.01  2.45±0.06 0.43±0.01 2.03±0.06 0.77±0.01  2.54±0.08 0.39±0.02 2.06±0.06 0.79±0.01  2.48±0.10 0.40±0.02 1.96±0.08 0.78±0.01  2.52±0.08 0.46±0.03 2.06±0.11 0.82±0.01  0.56±0.04  0.43±0.02  0.46±0.02  0.43±0.04  0.46±0.03  2.67±0.07 0.87±0.09 2.28±0.08 0.83±0.01  2.51±0.05 0.80±0.07 2.17±0.07 0.78±0.01  2.49±0.06 0.65±0.05 2.15±0.07 0.77±0.01  2.57±0.12 0.71±0.07 2.13±0.11 0.77±0.01  2.53±0.05 0.81±0.10 2.24±0.13 0.76±0.02  0.49±0.02  0.37±0.02  0.37±0.02  0.38±0.02  0.37±0.03  121  Cold Lake  Gillam  Model Calculations  Nitrogen Isotopic Discrmination  Nitrogen Partitioning  Growth  Table 6.2 Mean and genotype minimum and maximum total biomass (g), root:shoot ratio, tissue nitrogen concentration (root [N], stem [N] and leaf [N]) (μmol mg dw-1), the proportion of plant nitrogen allocated to the leaf pool (N leaf pool/Ntotal), net root uptake (μmol mg dw-1 h-1), tissue Δ15N, the proportion of leaf organic nitrogen assimilated in the leaf (Ti/Tt), the proportion of root assimilated nitrogen exported to the leaves as organic nitrogen (To/Tr), the proportion of plant nitrogen assimilation in the roots (Proot), efflux/influx (E/I), and tissue assimilation (μmol mg dw-1).  Measurement  Mean±SE  Total Biomass Root:shoot ratio Root [N] Stem [N] Leaf [N] Nleaf pool/Ntotal Net Root Uptake Root Δ15N Stem Δ15N  1.86±0.14 0.10±0.00 2.50±0.04 0.42±0.01 2.04±0.03 0.79±0.01 0.46±0.01 10.1±0.25 7.37±0.25  Nitrate Genotype Minimum 0.51 0.06 2.08 0.33 1.58 0.72 0.29 6.88 4.21  Leaf Δ N  4.42±0.23  2.41  6.79  4.83±0.19  Plant Δ15N  5.59±0.21  3.32  7.94  Ti/Tt To/Tr  0.26±0.01 0.64±0.01  0.14 0.58  Proot E/I  0.80±0.01 0.31±0.01  Leaf Assimilation Root Assimilation  15  Genotype Maximum 4.46 0.15 2.93 0.52 2.42 0.84 0.64 13.44 11.54  1.64±0.10 0.14±0.00 2.55±0.03 0.76±0.03 2.18±0.04 0.78±0.01 0.39±0.01 8.75±0.19 6.56±0.20  Ammonium Genotype Minimum 0.33 0.09 2.28 0.47 1.63 0.72 0.29 5.64 3.27  Genotype Maximum 3.48 0.20 2.96 1.25 2.65 0.85 0.55 11.80 9.35  Source Effect1 0.077 <0.0001 0.3082 <0.0001 0.0005 0.0613 <0.0001 <0.0001 0.0101  Source Relationship2  1.62  6.84  0.1562  0.076  5.70±0.18  2.52  8.11  0.66947  0.180  0.45 0.73  0.23±0.01 0.63±0.01  0.14 0.41  0.41 0.69  0.163 0.1285  0.501*  0.64 0.17  0.88 0.44  0.82±0.01 0.42±0.01  0.71 0.20  0.89 0.58  0.018 <0.0001  0.591*  0.63±0.03  0.44  1.01  0.59±0.02  0.37  0.95  0.8561  0.573*  18.36±0.60  11.16  26.84  16.12±0.43  11.62  21.97  <0.0001  0.496*  Mean±SE  1  0.543** 0.581** 0.205 0.329∙ 0.831*** 0.157 0.616*** 0.342∙ 0.162  0.462* 0.280  P-value reported from a nested three-way ANOVA. 2 Source relationship is the correlation for a genotypic mean for trait for NO3- versus NH4+. Pearson correlation coefficient (r-value) reported from linear regression analysis, significance denoted as *** P<0.001, ** P<0.01, * P<0.05, ∙ P<0.10.  122  15  N on both nitrogen sources (Figure 6.2). Average Δ15N was 10.1, 7.37 and 4.42‰  under NO3- and 8.75, 6.56 and 4.83‰ under NH4+ for roots, stems and leaves, respectively. Whole plant Δ15N was weighted more towards leaf Δ15N since leaf nitrogen accounted for approximately 80% of total plant nitrogen. There were no clinal trends in nitrogen isotope composition among provenances (Figure 6.3). Root and stem Δ15N grown with NO3- was greater than plants grown with NH4+ and differences between provenances were consistent across sources (Figure 6.3). There were no significant relationships for leaf and stem Δ15N when grown with NO3- compared to NH4+ but there was for root Δ15N (Table 6.2) (P<0.10). 6.1.3. Proportioning of nitrogen assimilation to the leaves was higher for NO 3than NH4+, but genotypic ranking was maintained on either source Ti/Tt was greater for plants grown with NO3- than NH4+ (Table 6.1). Between 14 and 45% of leaf nitrogen was assimilated in leaves under NO3- compared to 14 to 41% under NH4+ (Figure 6.4). There was no clinal trend between provenances. From the product of Ti/Tt and Nleaf pool/Ntotal, an estimate for the partitioning of nitrogen (Proot) assimilation was calculated. Since Nleaf pool/Ntotal was not different between sources, Proot was largely a reflection of Ti/Tt where Proot was greater for plants grown with NO3compared to NH4+ (Table 6.1). Relative to NO3-, Proot under NH4+ was fairly constant and was not different between provenances (Figure 6.5). Proot under nitrate ranged from 0.64 to 0.88, indicating that for some genotypes, up to one-third of assimilation occurred in the leaves. Genotypic differences in both Ti/Tt and Proot on the different sources were correlated with each other (Table 6.2) (P<0.05), indicating that ranks are maintained and clonal variation in these traits is independent of source. Although root assimilation accounted for between 60 and 80% of total plant nitrogen assimilation, since root biomass was much smaller than leaf biomass, assimilation rates per unit dry mass were approximately 15 times higher in roots than in leaves. Root assimilation was similar among provenances and was not significantly different between nitrogen sources (Figure 6.7A) (P<0.05). However, leaf assimilation  123  Figure 6.2. Root, stem and leaf Δ15N (N = 3) ±SE for 25 genotypes of Populus balsamifera L. from five provenances grown with either 500 μM nitrate (x axis) or ammonium (y axis). 124  Figure 6.3. Plant Δ15N ±SE (N=9-15) of five provenances of Populus balsamifera L. grown with either 500 μM nitrate (open circles) or ammonium (closed circles).  125  Figure 6.4. The proportion of leaf organic nitrogen assimilated in the leaf (Ti/Tt) (upper) and the proportion of root assimilated nitrogen exported to the leaves (To/Tr) (lower) ±SE (N=9-15) of five provenances of Populus balsamifera L. grown with either 500 μM nitrate (white bars) or ammonium (grey bars). 126  Figure 6.5. The proportion of nitrogen assimilated in the root (Proot) ±SE (N=9-15) of five provenances of Populus balsamifera L. grown with either 500 μM nitrate (white bars) or ammonium (grey bars).  127  Figure 6.6. Efflux/influx (E/I) ±SE (N=9-15) of five provenances of Populus balsamifera L. grown with either 500 μM nitrate (white bars) or ammonium (grey bars).  128  Figure 6.7 Root and leaf assimilation rates (μmol N mg dw-1) (lower) ±SE (N=9-15) of five provenances of Populus balsamifera L. grown with either 500 μM nitrate (white bars) or ammonium (grey bars).  129  rates were approximately 60% higher under NO3- than NH4+ (Figure 6.7B). Both root and leaf assimilation rates were similar between sources (Table 6.2). 6.1.1. Efflux/influx was lower for NO3- than NH4+ and genotypic differences were not similar between sources. Efflux/Influx (E/I) was lower under NO3- than NH4+ (Figure 6.6). So, since net nitrogen uptake was higher with NO3- there was greater E/I. For NH4+, E/I ranged from0.24 to 0.58 and for NO3-, it ranged from 0.19 to 0.48. However, there was a significant source by genotype interaction where some genotypes had higher E/I under NO3- than NH4+. However, at the population level, provenances with high E/I under NO3also had high E/I under NH4+ (Table 6.2). There were no clinal patterns in E/I between provenances. 6.1.2. Genotypic and source effects were reproducible in independent experiments When the experiment was repeated using seven genotypes, there was a significant relationship for genotypes and source combinations between the two experiments (Figure 6.8 and 6.9). However, there were also significant effects of experiment on E/I, but not on partitioning of nitrogen assimilation. There was a significant interaction for E/I between source and experiment, whereby the E/I for NH4+ was much higher in the second experiment than the first, whereas the E/I for NO3- was more-or-less unaffected. Genotypic ranks were largely unchanged between experiments (P<0.05). 6.2. Discussion The objective of this study was to identify intraspecific variation in nitrogen isotope composition and consequently, nitrogen fluxes, assimilation and allocation for balsam poplar grown with either steady-state nitrate or ammonium nutrition. Strong genotypic, primarily clonal, variation was uncovered in growth, nitrogen isotope discrimination and nitrogen-use traits calculated from the isotope mass balance model  130  presented in Chapter 2. Intraspecific differences in nitrogen-use traits have not been described in many species. Masclaux-Daubresse et al. (2010) described intraspecific  Figure 6.8. Efflux/influx (E/I) ±SE (N=9-15) of five provenances of Populus balsamifera L. grown with either 500 μM nitrate (white bars) or ammonium (grey bars).  131  Figure 6.9 Root and leaf assimilation rates (μmol N mg dw-1) (lower) ±SE (N=9-15) of five provenances of Populus balsamifera L. grown with either 500 μM nitrate (white bars) or ammonium (grey bars).  132  Figure 6.10 Estimates of efflux/influx ±SE (N=3) for two experiments for seven genotypes of Populus balsamifera L. grown with either 500 μM nitrate (solid circles) or ammonium (empty circles).  133  Figure 6.11 Estimates of Proot ±SE (N=3) for two experiments for seven genotypes of Populus balsamifera L. grown with either 500 μM nitrate (solid circles) or ammonium (empty circles).  134  variation in nitrogen-use traits in Arabidopsis and reported high variability among populations under nitrate. Since poplar is a potential agricultural crop to supply growing bioenergy demand, the ability to grow on marginal soils low in nitrogen availability, and/or to use applied nitrogen efficiently is important to being an effective carbon uptake system. The high degree of natural variation in balsam poplar suggests that selection for improved nitrogen use efficiency is possible as part of poplar breeding efforts. 6.2.1. Balsam poplar grew well on both sources of nitrogen Here, irrespective of provenance or genotype within provenance, ramets grown on ammonium were approximately 15% smaller than on nitrate, indicating a general preference for nitrate. However, healthy growth on both sources is consistent with balsam poplar being a generalist species (Peterson and Peterson 1992) that has the ability to acquire multiple forms of nitrogen. In contrast, Desrochers et al. (2007) reported greater growth with ammonium than nitrate for pot-grown poplar genotypes, but this response was genotype-dependent. Under ammonium, plant biomass corresponded well with previous measurements of hydroponically grown Populus trichocarpa for a similar period of time (Chapter 2). Between species, Falkengren-Gerup (1995) reported large differences in biomass between nitrate and ammonium-grown plants where in many cases, greater growth occurred with nitrate nutrition, particularly in species that are found in less acidic soils. Furthermore, Cox and Reisenauer (1973) reported that Triticum aestivum was smaller when grown with ammonium compared to nitrate. In contrast, Pritchard and Guy (2005) reported higher growth with ammonium than nitrate for white spruce, a species known to prefer ammonium. Ariz et al. (2011) reported increased nitrogen isotope discrimination when grown with ammonium and a decreased nitrate:ammonium biomass ratio for species known to be sensitive to ammonium. Here, I observed provenance level differences in growth, nitrogen isotope composition and calculated nitrogen use traits. However, genotypic variation within provenances often exceeded variation between provenances (Table 6.1). Previously, within and between-provenance variation was reported for phenological traits in balsam 135  poplar and followed a clinal trend indicating selection for adaptive traits (Farmer 1993; Soolanayakanahally et al. 2009). The limitation on the number of genotypes and provenances used in this experiment prevents any firm conclusions regarding local adaptation to different nitrogen sources, but the wide geoclimatic range of balsam poplar used here produced no evidence of such. However, there appears to be a high degree of clonal variation and differential genotypic responses producing a range in growth and root:shoot ratios under nitrate and ammonium that may be indicative of variability in source preference. 6.2.2. Time-averaged nitrogen use traits are independent of growth and nitrogen source Genotype means for isotope discrimination and root-to-shoot differences in isotope discrimination were similar between nitrogen sources. This is one of very few reports of genotypic differences in nitrogen use traits that extend across more than a single inorganic nitrogen source. Partitioning of assimilation between roots and leaves, leaf and root assimilation rates, translocation of inorganic and organic nitrogen to the shoot all show a significant relationship between genotypic means under ammonium and nitrate. Interestingly, these variables are not related to growth. Therefore, there must be some unknown commonality that explains the observed genotypic consistency in nitrogen-use traits that is independent of nitrogen source. Genetic variation in root architecture may be one explanation. Variation in nitrogen uptake efficiency has been attributed to variation in root architecture (Hirel et al. 2007; Garnett et al. 2009), a trait that may contribute to nitrogen isotope composition under steady-state conditions. In the present study, root thickness and branching frequency appeared to vary between genotypes (not shown) and genetic differences in root thickness, density and/or surface area may produce similar responses between the two nitrogen sources. Another possible explanation would be genotypic variation in nitrogen demand. Regardless of source, genotypic differences in biomass accretion were similar therefore assimilatory demand would be similar. Assimilatory demand is thought to impact rates of efflux  136  relative to influx, and therefore net nitrogen isotope discrimination, regardless of source. 6.2.3. Differences in efflux/influx and net root uptake between experiments may be explained by temperature-source interactions Given the significant correlations between experiments seen in the proportions of nitrogen assimilation in the root, net nitrogen uptake and E/I, the genotypic differences reported here are repeatable and robust. However, the decrease in net uptake and increase in E/I from the first experiment to the second, particularly for ammonium, may indicate that other environmental variables influence nitrogen use traits in balsam poplar. In particular, media temperatures were warmer in the second experiment relative to the third, and this may have differentially affected NH4+ versus NO3- uptake mechanisms. In both experiments, the temperature of the hydroponics media were warmer than what would be experienced in native soil environments; therefore, this interaction may not occur under natural conditions but warrants consideration nonetheless. Although little work has been done on the effects of temperature on ion uptake, a handful of studies have found decreased uptake at lower temperatures (Clarkson and Warner, 1979; Garnett and Smethurst 1999). For example, Garnett and Smethurst (1999) reported a reduced uptake of both ammonium and nitrate at lower temperatures in shining gum (Eucalyptus nitens H. Deane & Maiden). However, the temperature conditions in the present study were warmer than used in previous experiments. Membrane permeability may increase and cytoplasmic ammonium control may decrease with higher temperatures resulting in increased E/I. Britto and Kronzucker (2006) suggested higher efflux leads to futile cycling which has high respiratory costs. Greater futile cycling of ammonium, and not nitrate, at higher root temperatures would result in relatively greater energetic costs for this treatment than at lower temperatures. This interpretation is consistent with reduced growth observed with ammonium at higher temperatures. In accordance with observed increased growth of poplar under ammonium at lower temperatures, better relative growth on ammonium has also been observed in conifers at low (10-15 °C) versus warm 137  temperatures (Barbara Hawkins, personal communication). Since net nitrogen uptake decreased and E/I increased, efflux on a root basis increased with increased temperatures for ammonium but not nitrate in the present study. 6.2.4. Using genotypic differences in calculated nitrogen use traits to improve nitrogen use in poplar Though very fundamental, our understanding of nitrogen uptake and assimilation in plants, particularly trees, is incomplete. Assessment of time-integrated genotypic and environmental variation in nitrogen uptake, assimilation and allocation under steady-state conditions is a first step towards improving nitrogen-use in poplar. Here, I report on the inherent variation in these traits using an approach that provides an opportunity for screening current cultivars and species used for breeding of hybrid poplar for multiple uses, including biomass feedstock. As a time-integrated approach, the nitrogen isotope mass balance method is promising given that it can measure multiple traits in a single experiment. However, the tightly controlled conditions needed for these analyses, as presently implemented, do not reflect the physiochemical and biotic variability that is normal to a natural environment. Further testing of the relationship between measured genotypic variation under controlled, common environment conditions to field-level growth and nitrogen-use will be required 6.3. .Conclusion Poplar has the capacity to grow well on both nitrate and ammonium when provided at realistic rates of supply. However, there is considerable intraspecific variation in growth performance and in isotope discrimination at both whole plant and organ levels. Intraspecific variation was repeatable and indicates that observed variation was genetically controlled. Some of this variation is the same across inorganic nitrogen sources, suggesting that nitrogen demand rather than source-specific supply contributes to uptake, assimilation and allocation of nitrogen within balsam poplar. The exception to this was cycling of nitrogen across the root membrane where isotope mass balance  138  modelling showed that genotypes responded differently to each source, indicating possible intraspecific variation in source preference.  139  7. Conclusion Over the past 75 years, plant production has doubled, largely corresponding to a seven-fold increase in nitrogen fertilizer use (Hirel et al. 2007). A large portion of applied fertilizer is lost through leaching, volatilization or denitrification (Vitousek et al. 1997). Improving nitrogen-use efficiency will be critical for future food security and reducing emissions and environmental impacts from agricultural activities. Over the last three decades, advances in molecular physiology have contributed to our understanding of nitrate uptake and assimilation mechanisms at the functional and cellular level. However, to date, gains in nitrogen-use efficiency have been limited by the complexity of nitrogen uptake and assimilation. The importance of developing an integrated measure of nitrogen-use in plants is underscored by the need to reduce fertilizer requirements to produce optimum yields and reduce emissions from global fertilizer production. Poplar has the potential to be a primary feedstock for the growing biofuel sector. To optimize carbon sequestration efficiencies, fertilizer inputs must be minimized while, at the same time, achieving rapid growth. First, the genotypic variability in nitrogen-use traits within relevant poplar species used for breeding needs to be considered. Nitrogen isotope discrimination can provide time-integrated information on nitrogen fluxes, assimilation and allocation in roots similar to how carbon isotope composition can provide information on time-integrated carbon assimilation in leaves. Here, I improved, tested and applied a nitrogen isotope mass balance model used to calculate time-integrated nitrogen-use traits in balsam poplar and other plants. Nitrogen isotope discrimination is a function of external and internal supply and physiological demand from multiple assimilatory sinks. Tests designed to alter nitrogen isotope discrimination through modification of nitrogen supply and demand, either environmentally or genetically, showed results that were interpretable within the context of the nitrogen isotope mass balance model. Furthermore, estimates of cycling across the root membrane using the isotope mass balance model are comparable to results obtained using an independent, previously established technique. This thesis 140  addressed the absence of a detailed, integrated measure of nitrogen-use in plants and used this approach to evaluate the variability in nitrogen-use traits among five climatically dispersed provenances of Populus balsamifera. 7.1. Deriving integrated nitrogen-use traits from organ level and whole plant nitrogen isotope composition Initial observations of nitrogen isotope discrimination in pearl millet during nitrate uptake and assimilation (Mariotti et al. 1982) led to research working towards understanding the contributions of nitrogen use physiology to nitrogen isotope composition in plants. Contributions of Yoneyama (1993), Evans et al. (1996), Robinson et al. (1998), Yoneyama (2001), Evans (2001), Comstock (2001), Robinson (2001), Yoneyama (2003), Tcherkez and Farquhar (2006), Buschhaus (2007), Cernusak et al. (2009) and Tcherkez (2011) were all central to the development of the theory described in this thesis. These contributions provided the theoretical framework on which the proposed model is based. Comstock (2001) and Evans (2001) provided the most complete models to date explaining nitrogen isotope discrimination in plants. This thesis has built on that theory and combined it with mass balance nitrogen measurements to produce a tractable model explaining the relationship between nitrogen-use physiology and nitrogen isotope discrimination under steady-state conditions. The heterogeneous nitrogen environment in natural ecosystems can limit interpretation of whole plant and organ level nitrogen isotope composition. Under closed source conditions, such as those that exist in natural environments, plant nitrogen isotope composition largely reflects that of the source nitrogen. However, not all environments are completely closed systems and some degree of discrimination may occur that may contribute to error in the interpretation of nitrogen isotope composition of plants in natural environments. However, without knowing the integrated nitrogen isotope composition of multiple nitrogen sources, interpretation is not possible. Under open source conditions where the source 15N is homogeneous, stable and known, plants discriminate against 15N and the plant becomes depleted relative to the 141  substrate. This change in nitrogen isotope composition is a function of internal nitrogenuse physiology. From the model, multiple nitrogen-use traits can be derived from a single experiment. Measured traits such as growth, nitrogen concentration and isotope composition indicated that although there may be no visible growth phenotype, there may be isotopic phenotypes that indicate variability in nitrogen-use. Growth was not closely related to nitrogen isotope composition in poplar or Arabidopsis. Previously, efforts to use nitrogen isotope discrimination as an indicator of nitrogen uptake and assimilation in plants were confounded by non-steady-state conditions and unknown source isotope composition, or through complicating assumptions that limited the scope of interpretation. Here, by making physiologically reasonable assumptions, the isotope mass balance model describing nitrogen isotope composition was simplified. This approach provides information on nitrogen-use physiology that would normally require careful and extensive sampling using more traditional assays. 7.2. Modifying nitrogen isotope composition of plants through changes in inorganic nitrogen supply or demand Nitrogen or carbon supply can modify nitrogen isotope composition in plants grown under steady-state nitrogen conditions. These changes are a result of impacts on net nitrogen uptake and export of inorganic nitrogen from the root to shoot. More simply, changes to internal supply or demand of inorganic nitrogen from the root or shoot produce changes in nitrogen isotope composition. These changes could be induced environmentally as was observed in Chapters 2 (Populus trichocarpa), 3 (Arabidopsis thaliana), 4 (Populus balsamifera) and 6 (Populus balsamifera), or genetically as in Chapters 3 (Arabidopsis thaliana) and 6 (Populus balsamifera). Changes were interpretable within the context of the nitrogen isotope mass balance model where changes in efflux/influx or partitioning of assimilation were functions of changes in nitrogen source, concentration, carbon supply and possibly temperature. Arabidopsis lines showed differences in nitrogen isotope composition that were repeatable across 142  nitrate concentrations and experiments. Similarly, poplar genotypes showed repeatable differences in nitrogen isotope discrimination under different nitrogen sources that indicate variability in nitrogen source preference and nitrogen demand. By validating the model through a series of tests, a greater degree of confidence in the model was acquired for purposes of identifying intraspecific variation in nitrogen-use traits. 7.3. Comparisons of efflux/influx (E/I) acquired by independent experiments One of the limitations of the nitrogen isotope discrimination model was that it was not grounded to other measures of nitrogen-use. In Chapter 5, I compared estimates of E/I using the isotope mass balance model to estimates using compartmental analysis tracer efflux. There was a positive relationship between E/I measured using the two approaches. However, E/I was greater using the isotope mass balance method indicating that there may be errors in the discrimination factor of the enzyme, diurnal variation in fluxes or a kinetic isotope effect associated with transport across the membrane. When a greater enzyme discrimination factor was used for nitrate reductase or glutamine synthetase, measures of E/I were more alike. E/I was greater when grown with ammonium, consistent with a preference of poplar for nitrate. The coherence in estimates of E/I between independent methods suggests that leakage or efflux of inorganic nitrogen along the root occurs regardless of source, and is indicative of source preference and overall nitrogen assimilatory demand. 7.4. Genotypic variation in nitrogen fluxes, assimilation and allocation in balsam poplar After testing the model through environmental and genetic modification of nitrogen isotope discrimination and validating the estimation of E/I using an independent method, intraspecific variation in time-integrated nitrogen-use traits were assessed using balsam poplar grown under steady-state conditions with either nitrate or ammonium. There was considerable variation in growth, uptake and assimilation traits. These traits were related between sources but not related to growth, indicating that 143  these traits are driven by internal nitrogen demand and/or external nitrogen supply unrelated to source. There was a high degree of genotypic variation that was repeatable across experiments. 7.5. Limitations of research One of the primary limitations of this approach to measuring integrated nitrogen-use traits is the need for carefully controlled, hydroponic conditions. Plants are not likely to express these isotopic phenotypes if grown in any substrate that restricts mixing around the root because of the heterogeneity of nitrogen isotope composition and concentration in these environments, and because localized isotopic enrichment would occur in the rhizosphere if unassimilated nitrogen cannot freely diffuse away. Substrates with multiple sources make interpretation of individual flux, assimilation and allocation traits rather difficult. Like any phenotyping experiment, controlled conditions allow for genotypic comparisons that minimize environmental effects. There is a gap in knowledge between measurements of nitrogen-use under controlled conditions in the lab or greenhouse that limits the extension of results to field conditions. Hydroponicallygrown plants can only be grown under single-source nitrogen that does not address interactions between sources that can occur, particularly between nitrate and ammonium. Second, this method is not a high-throughput approach and requires extensive sampling of all plant parts to provide the input data necessary for calculation of model outputs. Although sampling intensity is lower than other isotope-based experiments, it is still intensive. However, there is the potential to phenotype lines or genotypes of plants in relatively large numbers. The system for hydroponics needs to be of sufficient volume to enable close control of substrate concentration and to stabilize its isotopic composition. Larger plants require larger volumes. For the experiments in Chapters 4-6, this necessitated the construction of 1000 L tanks to grow only 32 plants/tank and required multiple solution replacements over the course of each experiment. In turn, experiments had to be limited to a greenhouse with sufficient growing space but poor 144  control of air temperature, humidity, etc. Plants were given additional light, essential in the winter, but on sunny days during the summer where experiments were conducted for Chapter 5 and the second experiment for Chapter 6, air temperatures would reach up to 26 or 27°C and the temperature of the hydroponics solution would subsequently rise, sometimes reaching over 24°C (See Figure A.4). This appeared to have an adverse effect on plant growth under ammonium but not nitrate. The model is able to derive time-integrated variables that are reflections of nitrogen fluxes, assimilation and allocation but these values are still relative comparisons and should be interpreted with a certain degree of caution. The assumptions required to derive these time-integrated variables involved simplifying the isotope end-members of the model. Specifically, measured root bulk tissue 15N that is a combination of inorganic and organic N 15N signatures, was considered to be only organic N. The fraction of inorganic N may be as high as 10% in some cases, which would cause the 15N taken for root organic nitrogen to be slightly more positive than it actually is. This does not negate our basic conclusions from the model or relative interpretation of the results, but does inject some error into the estimate of Ti/Tt, Proot and E/I. 7.6. Applications and Future Research Although the work presented here advanced the use of nitrogen isotope discrimination as a time-integrated proxy of various nitrogen-use traits, refinement of the model for discrimination is still not complete. There were a number of assumptions presented here that allowed derivation of nitrogen traits from isotope composition at the whole plant and organ level which were justified based on previous physiological estimates in the literature. Ideally, these assumptions could be theoretically and empirically tested to determine the influence of variation in these parameters on nitrogen isotope discrimination measurements. Specifically, assumptions that be worthwhile to test include: 1) Quantifying better constrained isotope discrimination factors for glutamine synthetase and nitrate reductase, 2) Determining a time145  integrated estimate of inorganic and organ nitrogen concentration and isotope composition in xylem exudate 3) Determining the isotopic composition of remobilized nitrogen from cuttings of vegetatively propagated plants 4) Determining whether there is some discrimination that occurs during transport of inorganic nitrogen across the plasma membrane 5) Finding the contribution of inorganic nitrogen to total root nitrogen 6) Testing the influence that volatilization of ammonia or exudation of organic nitrogen from the root may have on leaf and root isotopic composition and 7) Determining whether there is organic nitrogen translocated from shoots to roots of actively growing plants. The findings in this thesis prompt many questions regarding the morphological, physiological and environmental influences on nitrogen isotope composition in plants. These include: 1) Do root morphology and anatomy influence nitrogen uptake and assimilation in such a way that nitrogen isotope discrimination and model outputs are universally expressed independent of source? 2) Is there an interaction between temperature and source for nitrogen uptake? 3) Do measurements of nitrogen-use using the nitrogen isotope mass balance approach correspond to measures of nitrogen-use efficiency and uptake efficiency in the field? 4) Can this approach be combined with traditional measures of nitrogen-use to produce a comprehensive model of nitrogen-use extending from the cellular to the whole-plant level? In Chapter 6, a close relationship was observed between nitrogen-use traits on nitrate compared to those on ammonium with the exception of efflux/influx. I hypothesized that assimilatory demand, regardless of nitrogen source or growth rate, appeared to be driving this relationship. To address this question, assimilatory demand expressed on a per mass basis would need to be quantified. This could be approached from a cellular/molecular biology or an anatomical/whole plant perspective. Root-based traits have been suggested as contributors of whole-plant nitrogen-use (Garnett et al. 146  2009). To address this, measurements of root-based traits such as thickness, surface area to volume ratio, cortex thickness, and cell size may provide some indication of the relationship between root anatomy and nitrogen fluxes and assimilation partitioning. A contributing role for root architecture in determining nitrogen movement through the root and into the xylem could be empirically tested by taking advantage of intra- or inter-specific variation in root form. One could explore this in more detail by incorporating non-destructive in vivo measures of nitrogen movement through the root in both inorganic and organic forms. NMR microimaging has been shown to detect stable isotope signatures in biochemical components within the cell at a resolution as low as 50 µM. Using non-destructive methods to measure nitrogen movement through the root and comparing that to complementary anatomical measurements may provide an indication of how and where inorganic nitrogen is moved through the root during uptake and assimilation under different conditions. Also in Chapter 6, there were indications of a source by temperature interaction whereby efflux/influx was greater with ammonium at warmer solution temperatures but not with nitrate. This observation suggests that ammonium toxicity becomes more problematic at higher temperatures. A similar effect has been observed in conifer species (B. Hawkins; Personal Comm.). Further work could be done to address this hypothesis. Thirdly, it is not known whether the variation in nitrogen-use traits observed under tightly controlled, hydroponic conditions is expressed in the field. Ideally, this would be best addressed using crop plants that rely on relatively high concentrations of soil inorganic nitrogen for optimum growth and development. By exploring variation in nitrogen-use traits using the isotopic approach, and then comparing these data to performance in the field, a relationship between the two may be apparent. Although root architecture is likely to change and the heterogeneous environment may result in different uptake patterns compared to those in hydroponics, any correlation between the two would encourage application of the isotope mass balance approach as a  147  phenotyping tool for screening in breeding programs. Furthermore, genotypic variation under controlled conditions can be used in combination with genomic variation to produce associations between phenotypes and genes responsible for nitrogen fluxes, assimilation and allocation within the plant. The advantage this approach as compared to other phenotyping approaches is that multiple nitrogen use traits can be acquired in a single experiment that can then be associated with genomic data to produce candidate genes responsible for genotypic variation in those traits. Although isotope discrimination/mass balance modelling can provide timeintegrated measures of nitrogen-use, it does not provide measures of nitrogen use that reflect diurnal or developmental changes in fluxes, assimilation or allocation. 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New Phytologist 194: 230-244 Yousfi S, Serret MD & Araus JL (2013) Comparative response of δ13C, δ18O and δ15N in durum wheat exposed to salinity at the vegetative and reproductive stages. Plant, Cell & Environment, In Press Yuan JS, Tiller KH, Al-Ahmad H, Stewart NR & Stewart CN (2008) Plants to power: bioenergy to fuel the future. Trends in Plant Science 13: 421-429  168  Appendix A – Supplemental measurements Table A. 1 Mean temperature and pH ±SD (N=14) in hydroponics solutions used in Chapter 3. Experiment 1 2  Nitrate Concentration  Temperature  pH  100  20.7±0.30  6.51±0.116  1000 100  20.7±0.22 20.6±0.19  6.50±0.127 6.50±0.097  1000  20.7±0.26  6.52±0.090  169  Figure A. 1 Nitrate concentrations (μM) in hydroponics solutions during growth of Arabidopsis thaliana for 35 days (Chapter 3) determined using the perchloric acid method. A, 100 µM NO3- treatment. B, 1000 µM NO3- treatment.  170  Figure A. 2 Mean solution temperatures for nitrate (solid circles) and ammonium (clear circles) substrates (N=3) over 45 days in experiment 1 (A) and experiment 2 (B) from Chapters 4, 5 and 6. 171  Figure A. 3 Mean solution pH for nitrate (solid circles) and ammonium (clear circles) substrates (N=3) over 45 days in experiment 1 (A) and experiment 2 (B) from Chapters 4, 5 and 6. 172  Figure A. 4 Mean nitrate (solid circles) and ammonium (clear circles) concentrations (N=3) over 45 days in experiment 1 (A) and experiment 2 (B) from Chapters 4, 5 and 6. 173  

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