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Physiological basis of variation in mesophyll conductance of black cottonwood (Populus trichocarpa Torr.… Momayyezi, Mina 2017

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Physiological Basis of Variation in Mesophyll Conductance of Black Cottonwood (Populus trichocarpa Torr. & Gray)   by Mina Momayyezi   B.Sc., The Ferdowsi University of Mashhad, 2008 M.Sc., The University of British Columbia, 2012   A DISSERTATION SUBMITTED IN PARTIAL FULFILLMENT OF  THE REQUIREMENTS FOR THE DEGREE OF   DOCTOR OF PHILOSOPHY  in  THE FACULTY OF GRADUATE AND POSTDOCTORAL STUDIES  (Forestry)  THE UNIVERSITY OF BRITISH COLUMBIA (Vancouver)   April 2017  © Mina Momayyezi, 2017 ii  Abstract There is dramatic provenance level variation in tree species with geographically wide ranges. For example, in Populus trichocarpa Torr. & Gray, net photosynthesis (An) and stomatal conductance (gs) both increase with latitude of origin. This thesis reports a parallel cline in mesophyll conductance (gm) and explores its physiological basis. In addition to anatomical constraints, variation in gm should depend on chloroplast positioning, transmembrane CO2 diffusion through aquaporins (AQPs), and biochemical facilitation of the CO2↔HCO3− equilibrium by carbonic anhydrase (CA), but evidence for the former has been lacking. I found that gm increases with latitude across 12 genotypes, as measured by chlorophyll fluorescence, and confirmed this pattern by the isotope discrimination method in six representative genotypes. Northern genotypes had greater CA activity. An inhibitor of CA, acetazolamide, reduced CA activity, gm, gs, chloroplast CO2 concentration and An at normal CO2 (400 µmol mol-1), the latter being reversible at saturating CO2. The relationship between CA activity and gm was similar whether the variation was inherent or inhibitor-induced. I then explored the role of chloroplast positioning in relation to gm, driven by the ratio of blue (BL) to red light supplied to leaves. Repositioning was manifested by a reversible decrease in chlorophyll content index (CCI), while actual chlorophyll content remained unchanged. Although gm was found to decrease as BL increased, and more so in northern genotypes, cytochalasin D, an inhibitor of chloroplast motility, blocked the effect of BL on CCI but not gm, suggesting that BL can mediate gm independently of repositioning. High BL reduced CA activity, consistent with a possible reduction in protein-facilitated diffusion, which might also involve AQPs. I found that the AQP inhibitor mercuric chloride reduces gm more in northern genotypes than in southern genotypes, both absolutely and proportionally, but also reduces CA activity. Although greater gm in high-latitude genotypes likely reflects contributions from several iii  components of the liquid-phase diffusion pathway, this thesis draws particular attention to a major role for CA. Because gm is an equal or greater limitation on photosynthesis than gs, these findings may help direct crop improvement efforts to promote resource use efficiencies and yield.    iv  Preface Research chapters of this thesis are written as separate manuscripts for publishing in peer-review journals. My contribution to Chapters 2, 3 and 4 involves experimental design, data collection, data analyses and preparation of full written draft including figures and table. Dr. Robert Guy, my supervisor, provided help with developing my research proposal and assisted with experimental design, data interpretation and editorial revisions of my thesis.  Chapter 2 is based on a published paper in Plant, Cell and Environment as “Momayyezi M. & Guy R.D. (2017) Substantial role for carbonic anhydrase in latitudinal variation in mesophyll conductance of Populus trichocarpa Torr. & Gray.” A version of Chapter 3 is accepted pending minor revision in Journal of Plant Physiology as “Momayyezi M. & Guy R.D. (2017) Blue light differentially represses mesophyll conductance in high vs low latitude genotypes of Populus trichocarpa Torr. & Gray.” A version of Chapter 4 will be submitted for publication as “Momayyezi M. & Guy R.D. Effect of mercuric chloride on mesophyll conductance in diverse Populus trichocarpa Torr. & Gray genotypes.”   v  Table of contents  Abstract .......................................................................................................................................... ii Preface ........................................................................................................................................... iv Table of contents ........................................................................................................................... v List of tables................................................................................................................................... x List of figures .............................................................................................................................. xiv List of symbols and abbreviations ............................................................................................. xx Acknowledgements .................................................................................................................. xxiv Dedication .................................................................................................................................. xxv Chapter 1: Introduction ............................................................................................................... 1 1.1 Climate change and tree population adaptation ................................................................... 1 1.2 Latitudinal variation in physiological traits ......................................................................... 1 1.3 Mesophyll conductance (gm) ................................................................................................ 3 1.4 Physiological components .................................................................................................... 6 1.5 Black cottonwood (Populus trichocarpa) ............................................................................ 8 1.6 Objectives ........................................................................................................................... 10 Chapter 2: Substantial role for carbonic anhydrase in latitudinal variation in mesophyll conductance of Populus trichocarpa Torr. & Gray .................................................................. 11 vi  2.1 Introduction ........................................................................................................................ 11 2.2 Material and methods ......................................................................................................... 14 2.2.1 Plant material .............................................................................................................. 14 2.2.2 Treatments and photosynthesis measurements .......................................................... 17 2.2.3 Carbonic anhydrase inhibition ................................................................................... 17 2.2.4 Carbon isotope discrimination measurements ............................................................ 18 2.2.5 Calculation of gm by chlorophyll fluorescence method ............................................. 20 2.2.6 Calculation of gm from carbon isotope discrimination ............................................... 21 2.2.7 Calculation of Cc ........................................................................................................ 24 2.2.8 Carbonic anhydrase activity ....................................................................................... 24 2.2.9 A-Ci curves ................................................................................................................. 26 2.2.10 Statistics ................................................................................................................... 26 2.3 Results ................................................................................................................................ 27 2.3.1 Initial assessment of latitudinal pattern ...................................................................... 27 2.3.2 Comparison of two methods ...................................................................................... 27 2.3.3 Treatment effects ........................................................................................................ 27 2.3.4 Trait correlations ........................................................................................................ 42 2.4 Discussion .......................................................................................................................... 47 2.5 Conclusion ......................................................................................................................... 51 vii  Chapter 3: Blue light differentially represses mesophyll conductance in high vs low latitude genotypes of Populus trichocarpa Torr. & Gray ...................................................................... 52 3.1 Introduction ........................................................................................................................ 52 3.2 Material and methods ......................................................................................................... 54 3.2.1 Plant material .............................................................................................................. 54 3.2.2 Light treatments and photosynthesis measurements .................................................. 55 3.2.3 Calculation of gm ........................................................................................................ 57 3.2.4 Light response curves ................................................................................................. 58 3.2.5 CCI measurement and chlorophyll extraction ............................................................ 58 3.2.6 Inhibition of chloroplast movements .......................................................................... 60 3.2.7 Carbonic anhydrase activity ....................................................................................... 60 3.2.8 Statistics ..................................................................................................................... 62 3.3 Results ................................................................................................................................ 63 3.3.1 Blue light effect on gm ................................................................................................ 63 3.3.2 Blue light effect on chloroplast positioning ............................................................... 67 3.3.3 Effect of cytochalasin D on chloroplast repositioning and changes in gm ................. 70 3.3.4 Blue light effect on CA activity ................................................................................. 70 3.4 Discussion .......................................................................................................................... 70 3.5 Conclusion ......................................................................................................................... 76 viii  Chapter 4: Effect of mercuric chloride on mesophyll conductance in diverse Populus trichocarpa Torr. & Gray genotypes ......................................................................................... 78 4.1 Introduction ........................................................................................................................ 78 4.2 Material and methods ......................................................................................................... 81 4.2.1 Plant material .............................................................................................................. 81 4.2.2 Treatments and photosynthesis measurements .......................................................... 81 4.2.4 Carbonic anhydrase activity ....................................................................................... 82 4.2.5 Combined high blue light and mercuric chloride treatment ....................................... 83 4.2.6 Calculation of gm ........................................................................................................ 84 4.2.7 Statistics ..................................................................................................................... 85 4.3 Results ................................................................................................................................ 86 4.3.1 Mercuric chloride effect on gm ................................................................................... 86 4.3.2 Mercuric chloride effect on CA activity .................................................................... 92 4.3.3 Combined blue light and mercuric chloride effect and changes in gm ....................... 92 4.4 Discussion .......................................................................................................................... 96 4.5 Conclusion ......................................................................................................................... 99 Chapter 5: General discussion ................................................................................................. 100 5.1 Conductance and photosynthesis ..................................................................................... 100 5.2 Response of gm to various treatments across genotypes .................................................. 101 ix  5.3 Limitations of research ..................................................................................................... 104 5.4 Future directions............................................................................................................... 105 Bibliography .............................................................................................................................. 108 Appendix A- Supporting information ..................................................................................... 131 x  List of tables Table 2.1 Provenance of origin for Populus trichocarpa genotypes used in this study. Asterisks (*) indicate genotypes chosen to represent high and low latitudes in carbonic anhydrase experiments.. ................................................................................................................................. 15 Table 2.2 An, gs, CA activity, gm and Cc in northern vs. southern genotypes under control 1 (distilled water), control 2 (aqueous NH4OH), and acetazolamide treatments. Different letters show significant differences for mean values (± SE; n = 4) of controls 1 and 2 compared to the acetazolamide treatment within each latitudinal group at P < 0.016. …………………………….. 35  Table 2.3 An, gm, Vcmax and Jmax mean values (± SE) over five replications estimated for leaves under control (distilled water) and acetazolamide treatments using the A-Ci curve method. Data were introduced to PROC GLM in SAS 9.4 for analysis of variances. Significant differences between control and acetazolamide treatments are shown with different letters at P < 0.05.. ..... 38 Table 2.4 Absolute and percentage reductions in An, gs, CA activity, gm and Cc under acetazolamide treatment from controls 1 and 2 (distilled water and aqueous NH4OH) for the northern vs. the southern genotypes. Data pairing was on a plant per plant basis. Different letters show significant differences for mean values (± SE; n = 4) of control 1 and 2 compared to the acetazolamide treatment for northern vs. southern genotypes at P < 0.025. ................................ 44 Table 2.5 Pearson correlation coefficients (r) between traits measured across all leaves (4 per genotype) in the distilled water treatment (n = 24). Significant correlations are in bold (P < 0.05) and bold* are significant after Bonferroni correction (P < 0.003). …………………………...... 46   xi  Table 3.1 Physiological traits for northern vs. southern genotypes under two different blue light treatments (10 and 60% BL). Different letters show significant differences within and between latitudes (P < 0.008) within a column (± SE, n = 4). .................................................................... 66 Table 3.2 Effects of blue light treatment on chlorophyll content index (CCI) for northern vs. southern Populus trichocarpa genotypes. Different letters show significant differences (P < 0.003) for mean values (± SE, n = 4).. ..................................................................................................... 68 Table 3.3 Test for lack of effect of the blue light:red light supply ratio on chlorophyll content using leaves of the TATB-4 genotype. Actual chlorophyll content (ACC), chlorophyll content index (CCI), and CCI/ACC ratio immediately after 25 min exposure to 10% and 60% BL are presented. Different letters show significant differences between light treatments for mean values (± SE, n = 4) (P < 0.05) .................................................................................................................................. 69 Table 3.4 Effect of cytochalasin D on An, gm, gs, Ci, Cc, CCI, ACC, and CCI/ACC in the TATB-4 genotype tested under 10 and 60% BL in distilled water, DMSO, and DMSO + cytochalasin D. Different letters show significant differences between mean values within each row (± SE, n = 5) (P < 0.003). ................................................................................................................................... 71 Table 3.5 Effect of 60% BL on CA activity, An, gm, gs, Ci, Cc and CCI in. Different letters show significant differences between mean values (± SE, n = 4) within each row (P < 0.05). Genotype was not a factor in this experiment, so data presented here are means across both TATB-4 and LONG-1 combined. ...................................................................................................................... 72 Table 4.1 An, gm, gs, gs/gm, Ci and Cc in northern vs. southern genotypes under control and HgCl2 treatments. For each column, different letters show significant differences for mean values ± SE at P < 0.008. .................................................................................................................................. 88 xii  Table 4.2 Percentage and absolute reductions in An, gm gs and Cc under HgCl2 treatment from control for the northern vs. the southern genotypes. Different letters show significant differences for mean values ± SE at P < 0.05.................................................................................................. 89 Table 4.3 Effect of 1.5 mM aqueous HgCl2 on CA activity, An, gm, gs, gs/gm, Ci, Cc and CCI. Different letters show significant differences between mean values (± SE, n = 4) within each row (P < 0.05). Genotype was not a factor in this experiment, so data presented here are means across both TATB-4 and LONG-1 combined. Data for distilled water controls are the same here as in Chapter 3, Table 3.5. Slight differences in gm and Cc between the two tables are due to minor differences in the assumed value of α. .......................................................................................... 94 Table 4.4 Effect of high blue light and 1.5 mM aqueous HgCl2 on An, gm, gs, Ci and Cc under 10 and 60% BL. Different letters show significant differences between mean values (± SE, n = 4) within each row (P < 0.008). Genotype was not a factor in this experiment, so data presented here are means across both TATB-4 and LONG-1 combined .............................................................. 95 Table 5.1 Percentage reduction (± SE) in mesophyll conductance from the corresponding control under 1 mM acetazolamide, 60% BL, and 1.5 mM HgCl2. Different letters show significant differences between mean values within each row as determined in previous chapters (P < 0.05)...................................................................................................................................................... 102 Table A.1 An, gs and gm mean values (± SE) over five replications in attached and detached leaves. Data were introduced to PROC GLM in SAS 9.4 for analysis of variances. There were no significant differences between attached and detached leaves……………………………………….... 131 xiii  Table A.2 Leaf absorptance mean values (± SD) over five replications in six Populus trichocarpa genotypes. Data were introduced to PROC GLM in SAS 9.4 for analysis of variances. There were no significant differences in leaf absorptance between genotypes. …………………………………... 132   xiv  List of figures Figure 1.1 Native range of Populus trichocarpa. .......................................................................... 9  Figure 2.1 Populus trichocarpa cuttings were taken from a gene bank in Totem Field at UBC (left image). Cuttings were grown under greenhouse conditions (right image)... ........................ 16 Figure 2.2 Air sample bags were filled from the LI-COR exhaust (left image), and analyzed for δ13C using a Tunable Diode Laser (right image). ......................................................................... 19 Figure 2.3 Thawed leaf samples were ground in buffer solution in preparation for the CA activity measurement assay (left image). The right image shows CO2-saturated water in preparation…. 25 Figure 2.4 Photosynthetic traits across latitude of origin for 12 genotypes (clones) of Populus trichocarpa. A, net assimilation rate (An, µmol CO2 m-2 s-1); B, stomatal conductance (gs, mol H2O m-2 s-1); C, mesophyll conductance (gm, mol CO2 m-2 s-1); D, leaf mass per area (LMA, mg mm-2). Data points are means of four biological replicates (ramets) per clone (± SE). ........................... 28 Figure 2.5 Leaf nitrogen concentration (leaf N, µg mm-2) across latitude of origin for 12 genotypes (clones) of Populus trichocarpa. Data points are means of four biological replicates (ramets) per clone (± SE). ................................................................................................................................. 29 Figure 2.6 Correlation between mesophyll conductances (gm, mol CO2 m-2 s-1) obtained from stable carbon isotope and chlorophyll fluorescence methods (n = 72) under three treatments; distilled water control (●), aqueous NH4OH control (○), and acetazolamide (●). ....................... 30 Figure 2.7 Correlation between chloroplast CO2 concentrations (Cc, µmol mol-1) obtained from stable carbon isotope and chlorophyll fluorescence methods (n = 72) under three treatments; distilled water (●), aqueous NH4OH (○), and acetazolamide (●). ................................................ 31 xv  Figure 2.8 Mean values (± SE; n = 4) for net assimilation rate (An, µmol CO2 m-2 s-1) of six Populus trichocarpa genotypes under three treatments (distilled water in black, aqueous NH4OH in white, and acetazolamide in grey). Different letters show significant differences between distilled water (control 1), aqueous NH4OH (control 2) and acetazolamide treatments for each genotype at P < 0.002. …………………………………………………………………………………………… 32            Figure 2.9 Mean values (± SE; n = 4) for mesophyll conductance (gm, mol CO2 m-2 s-1) of six Populus trichocarpa genotypes under three treatments (distilled water in black, aqueous NH4OH in white, and acetazolamide in grey). Different letters show significant differences between distilled water (control 1), aqueous NH4OH (control 2) and acetazolamide treatments for each genotype at P < 0.002. .................................................................................................................. 33 Figure 2.10 Mean values (± SE; n = 4) for stomatal conductance (gs, mol H2O m-2 s-1) of six Populus trichocarpa genotypes under three treatments (distilled water in black, aqueous NH4OH in white, and acetazolamide in grey). Different letters show significant differences between distilled water (control 1), aqueous NH4OH (control 2) and acetazolamide treatments for each genotype at P < 0.002. .................................................................................................................. 36 Figure 2.11 Mean values (± SE; n = 4) for CO2 concentration at sites of carboxylation (Cc, µmol mol-1) of six Populus trichocarpa genotypes under three treatments (distilled water in black, aqueous NH4OH in white, and acetazolamide in grey). Different letters show significant differences between distilled water (control 1), aqueous NH4OH (control 2) and acetazolamide treatments for each genotype at P < 0.002 .................................................................................... 37 Figure 2.12 Relationship between mean An (net assimilation rate) and Ci (intercellular air space CO2 concentration) (± SE; n = 5) averaged over five replications under control (distilled water) xvi  and acetazolamide treatments at 1200 µmol m-2 s-1 PPFD. The LONG-1 genotype was chosen arbitrarily for this experiment. There was no NH4OH control treatment.……………………..... 39 Figure 2.13 Mean values (± SE; n = 4) for carbonic anhydrase activity, CA activity (units cm-2) of six Populus trichocarpa genotypes under three treatments (distilled water in black, aqueous NH4OH in white, and acetazolamide in grey). Different letters show significant differences between distilled water (control 1), aqueous NH4OH (control 2) and acetazolamide treatments for each genotype at P < 0.002. .......................................................................................................... 40 Figure 2.14 Mean values (± SE; n = 4) for carbonic anhydrase activity, CA activity (units g-1 fresh mass) of six Populus trichocarpa genotypes under three treatments (distilled water in black, aqueous NH4OH in white, and acetazolamide in grey). Different letters show significant differences between distilled water (control 1), aqueous NH4OH (control 2) and acetazolamide treatments for each genotype at P < 0.002. …………………………………………………….. 41 Figure 2.15 Leaf mass per area (LMA, mg mm-2) of six Populus trichocarpa genotypes. Shown are mean values (± SE) determined on 12 leaves per genotype. Different letters show significant differences between genotypes. ………………………………………………………………… 43 Figure 2.16 Correlation between CA activity (units cm-2) and mesophyll conductance (gm, mol CO2 m-2 s-1) under three treatments; control 1 (northern genotypes ▲, southern genotypes ▼), control 2 (northern genotypes , southern genotypes ), and acetazolamide (northern genotypes ▲, southern genotypes ▼). The correlation coefficient and associated P-value shown are for all treatments combined. For the individual treatments considered separately, the correlation coefficients were 0.623 (P = 0.0011) for control 1, 0.713 (P < 0.0001) for control 2, and 0.675 (P = 0.0003) for acetazolamide. ........................................................................................................ 45 xvii  Figure 3.1 Photosynthetic traits were measured under five different blue light to red light ratios (0:100, 10:90, 20:80, 40:60, 60:40) at a constant total PPFD (1200 µmol m-2 s-1).... .................. 56 Figure 3.2 Light response curves for net assimilation rate (An, µmol CO2 m-2 s-1) and mesophyll conductance (gm, mol CO2 m-2 s-1) of the SKNP-4 genotype under 10% (●) or 60% BL (○). Photosynthetic photon flux density (PPFD) was varied from 50 to 1300 µmol m-2 s-1 while CO2 concentration was held constant at 400 µmol mol-1. .................................................................... 59  Figure 3.3 Cytochalasin D dissolved in DMSO was fed through leaf petioles to inhibit chloroplast movement. Photosynthetic traits were measured at low and high BL under distilled water, DMSO, and cytochalasin D in DMSO... .................................................................................................... 61 Figure 3.4 Mean values (± SE, n = 4) for A, net assimilation rate (An, µmol CO2 m-2 s-1); B, stomatal conductance (gs, mol H2O m-2 s-1); C, intercellular air space CO2 concentration (Ci, µmol mol-1) of six Populus trichocarpa genotypes under five blue:red light supply ratios. For each genotype, from left (white bar) to right (striped bar), the proportion of blue light is 0, 10, 20, 40 and 60% BL. Different letters show significant differences between control (10% BL) and other treatments for each genotype at P < 0.005. ................................................................................... 65 Figure 4.1 Mean values (± SE) for net assimilation rate (An, µmol CO2 m-2 s-1) of six Populus trichocarpa genotypes under two treatments (distilled water in black, and HgCl2 in grey). Different letters show significant differences between distilled water (control), and HgCl2 treatments for each genotype at P < 0.05.. ........................................................................................................... 87 Figure 4.2 Mean values (± SE) for mesophyll conductance (gm, mol CO2 m-2 s-1) of six Populus trichocarpa genotypes under two treatments (distilled water in black, and HgCl2 in grey). Different xviii  letters show significant differences between distilled water (control), and HgCl2 treatments for each genotype at P < 0.05.. ........................................................................................................... 90 Figure 4.3 Mean values (± SE) for stomatal conductance (gs, mol H2O m-2 s-1) of six Populus trichocarpa genotypes under two treatments (distilled water in black, and HgCl2 in grey). Different letters show significant differences between distilled water (control), and HgCl2 treatments for each genotype at P < 0.05.... ....................................................................................................... . 91 Figure 4.4 Mean values (± SE) for CO2 concentration at sites of carboxylation (Cc, µmol mol-1) of six Populus trichocarpa genotypes under two treatments (distilled water in black, and HgCl2 in grey). Different letters show significant differences between distilled water (control), and HgCl2 treatments for each genotype at P < 0.05. ..................................................................................... 93  Figure A.1 Estimation of CO2 compensation point (Ci*, µmol mol-1) and dark respiration rate (Rd, µmol m-2 s-1) using the Laisk method (Gilbert et al. 2012, see Materials and Methods for details). Each point represents the mean of six plants (± SE). A-Ci curves were built under two irradiances of 125 (○) and 500 (●) µmol m-2 s-1……………………………………………………………………. 133 Figure A.2 Estimation of CO2 compensation point (Ci*, µmol mol-1) and dark respiration rate (Rd, µmol m-2 s-1) using the Laisk method (Gilbert et al. 2012, see Materials and Methods for details) under control (distilled water) (●, ○) and 1 mM acetazolamide (▲, ) treatments. Each point represents the mean of two plants (± SE). A-Ci curves were built under two irradiances of 125 (hollow) and 500 (solid) µmol m-2 s-1……………………………………………………………………. 134 Figure A.3 Relationship between quantum yield of photosystem II (ΦPSII) and quantum yield for net assimilation rate (Φ𝐶𝑂2) under non-photorespiratory conditions (2% O2). Measurements were xix  on the SKNP-4 genotype over a range of PPFD from 50 to 1200 µmol m-2 s-1 under either 10% (●) or 60% BL (○)……………………………………………………………………………………………... 135   xx  List of symbols and abbreviations α leaf absorptance  β the fraction of absorbed quanta reaching photosystem II  ΦPSII quantum yield of photosystem II   13C 13C/12C isotope ratio (‰) Γ* chloroplast CO2 photocompensation point (µmol mol-1) Δo observed carbon isotope discrimination (‰) Δi predicted carbon isotope discrimination (‰) Δe respiratory associated carbon isotope discrimination (‰) Δf photorespiratory associated carbon isotope discrimination (‰) Δgm discrimination associated with the diffusion of CO2 from intercellular airspace to sites of carboxylation (‰) δ13Ce isotopic ratio of reference CO2 (‰) δ13Ca isotopic ratio of unconsumed sample CO2 (‰) δ13Catm isotopic composition for atmospheric CO2 (‰) ζ ratio of the reference CO2 concentration entering the cuvette and the net amount consumed in photosynthesis  aˊ combined factor for diffusional fractionation through stomata and the boundary layer a fractionations occurring during diffusion across the stomata (‰) xxi  ai fractionation factor associated with hydration and diffusion in water (‰)  ab fractionations occurring through the boundary layer (‰) An net assimilation rate (µmol CO2 m-2 s-1) ACC actual chlorophyll content (µg/cm2) AQP aquaporin BL blue light  CA carbonic anhydrase Ca ambient chamber CO2 concentration (µmol mol-1)  Cc         CO2 concentration at sites of carboxylation (µmol mol-1) Ce reference CO2 concentration (µmol mol-1) Ci intercellular air space CO2 (µmol mol-1) Ci* intercellular CO2 photocompensation point (µmol mol-1) Cs CO2 concentration at the leaf surface (µmol mol-1) CCI chlorophyll content index CO2P air exiting the LI-COR chamber with leaf present (µmol mol-1)  CO2R air exiting the LI-COR chamber with leaf absent (µmol mol-1)  df dilution factor DMSO dimethyl sulfoxide e  fractionations associated with respiration (‰) xxii  E transpiration rate (mmol H2O m-2 s-1)  ƒ fractionations associated with photorespiration (‰) gm mesophyll conductance (mol CO2 m-2 s-1) 𝑔act  combination of boundary layer and stomatal conductance to CO2  gs stomatal conductance (mol H2O m-2 s-1) gs/gm stomatal conductance to mesophyll conductance ratio HgCl2 mercuric chloride II  Jflu electron transport rate  Jmax maximum electron transport rate Ki inhibitory constant leaf N leaf nitrogen concentration (µg mm-2) LMA       leaf mass per area (mg mm-2) MIPs major intrinsic proteins NUE nitrogen-use efficiency (µmol CO2 g−1 N s−1)  PAR photosynthetically active radiation (µmol m-2 s-1) PIPs          plasma membrane intrinsic proteins  PPFD photosynthetic photon flux density (µmol m-2 s-1) Rd non-photorespiratory respiration rate in the light (µmol m-2 s-1) RL red light xxiii  RNAi    RNA interference  rubisco      ribulose-1,5-bisphosphate carboxylase/oxygenase  RuBP   ribulose-1,5-bisphosphate  t ternary correction factor  TControl time required for change of the buffer pH in control solution (s)  TEnzyme      time required for change of the buffer pH in enzyme-containing solution (s) V volume of enzyme extract (mL)   Vcmax maximum carboxylation rate  VPD vapour pressure deficit (kPa) WUE water-use efficiency (μmol CO2 mmol−1 H2O) XIPs uncharacterized aquaporin subfamily  xxiv  Acknowledgements First and foremost, I would like to express my sincere gratitude to my advisor, Dr. Robert Guy for his excellent guidance, and tremendous support. Rob’s profound insight into plant physiology and his great patience led me through understanding complex research subjects as mesophyll conductance and helped me to be a better researcher. His precision and time dedication all through scientific editing of this thesis is greatly appreciated. I would like to thank my supervisory committee, Dr. Arthur Fredeen and Dr. Sue Grayston for their guidance and very constructive feedback. I am very thankful to Dr. Carl Douglas, his memory will be eternal, for all his encouraging advice and guidance through my PhD study. I like to thank Dr. Athena McKown for all inspiring and fruitful discussions. I offer my thanks to Dr. Raju Soolanayakanahally for supplying plant materials used in a part of my research. I am grateful to all Tree Physiology lab members, Estefania, Shofi, Shalom, and Yi for their help and encouragement. I would like to share my gratitude to Dr. Valerie Lemay and Dr. Anthony Kozak for providing help with choosing and developing statistical models of analysis.  My deep appreciation goes to my parents and my brother who never stopped believing in me. I send my heartfelt thank you to the love of my life, Ali for being beside me with constant love and support all through challenges I faced in this journey.  xxv  Dedication                                                                                                                   To my beloved mom1  Chapter 1: Introduction 1.1 Climate change and tree population adaptation  Responses of forest tree species to the possibility of rapid climate change, such as increased temperature, CO2 level, and growing season length (Parmesan 2006; Bronson et al. 2009; Way & Oren 2010; Wertin et al. 2012), may include adaptation, migration or extinction of populations within a local and/or regional context (Aitken et al. 2008). The presence of genetic variations in morphological and physiological traits within and between plant populations, due to natural selection under different geoclimatic conditions, reflects the capacity for local adaption within plant species (Aitken & Whitlock 2013; Benomar et al. 2016). In geographically wide-spread species such as poplars (Populus spp.), latitudinal and longitudinal gradients in precipitation, temperature, elevation, and growing season length influence ecophysiological traits (Keller et al. 2011). An understanding of how key features of carbon uptake (photosynthesis-related traits) vary naturally, as a function of climate, would help to predict how populations will/should adapt to changing climatic conditions to maintain fitness and persist into the future (Savolainen et al. 2013; Valladares et al. 2014).  1.2 Latitudinal variation in physiological traits Net assimilation rate (An) has been reported to increase with latitude in several poplar species (Gornall & Guy 2007: Soolanayakanahally et al. 2009, 2015; Kaluthota et al. 2015), including Populus trichocarpa Torr. & Gray (black cottonwood), Populus balsamifera L. (balsam poplar), Populus angustifolia James (narrowleaf cottonwood), and Populus tremula L. (European aspen), and in Alnus rubra Bong. (red alder) and Betula papyrifera Marsh. (paper birch) (Dang et al. 1994; Benowicz, et al. 2000). These higher rates of photosynthesis are supported by higher conductances 2  for CO2 from the atmosphere to sites of carboxylation at rubisco (i.e., ribulose-1,5-bisphosphate carboxylase/oxygenase). Concurrent to An, stomatal conductance (gs) increases with latitude in black cottonwood (Gornall & Guy 2007; McKown et al. 2014a), narrowleaf cottonwood (Kaluthota et al. 2015) and European aspen (Soolanayakanahally et al. 2015). In balsam poplar, gs was reported to increase with latitude in a study utilizing field-grown plants (Soolanayakanahally et al. 2015). However, in an earlier study on greenhouse-grown plants (Soolanayakanahally et al. 2009) there was no relationship between gs and latitude but, based on A-Ci curve analysis (A: net CO2 assimilation, Ci: intercellular air space CO2), balsam poplars from high latitudes were shown to have greater mesophyll conductance (gm) compared to low-latitude genotypes (Soolanayakanahally et al. 2009). The mesophyll conductance indicates the ease of CO2 diffusion from the substomatal cavity to rubisco. The positive correlation between latitude and An, and by extension, gs and/or gm, is presumed to reflect adaptation of northern balsam poplar genotypes to a shorter growing season (Soolanayakanahally et al. 2009).  Net assimilation rate may relate to other variables like leaf nitrogen concentration (leaf N) and leaf mass per area (LMA). They both increase in balsam poplar and narrowleaf cottonwood with latitude (Soolanayakanahally et al. 2009, 2015; Kaluthota et al. 2015). Variation in LMA in balsam poplar is primarily attributable to mesophyll palisade thickness, and not leaf thickness more generally (Milla-Moreno et al. 2016). Thus, LMA in balsam poplar is also correlated with anatomical properties of the palisade that may affect gm, such as the cell wall area available for CO2 diffusion. Accordingly, in a balsam poplar family resulting from a cross between geographically widely separated parents, gm was found to be well correlated with LMA (Ryan 2015). While black cottonwood overlaps and hybridizes with balsam poplar in northeastern British Columbia and in the Canadian Rocky Mountains (Viereck et al. 1974), LMA and leaf N do not 3  seem to show the same changes with latitude. Likewise, patterns of variation in gs and gm may not be the same.   In black cottonwood (Gornall & Guy 2007; McKown 2014a), and also in narrowleaf cottonwood (Kaluthota et al. 2015), gs has been shown to increase as leaves become more amphistomatous with latitude. The higher gs in northern black cottonwood genotypes is positively related to higher stomatal adaxial:abaxial ratio and to total stomatal density (Gornall & Guy 2007). Although there is latitudinal variation in gm in balsam poplar, it is unclear whether the same variation exists in black cottonwood. The absence of any latitudinal trend in LMA in black cottonwood might suggest that gm would also show no pattern. However, there are many other physiological variables that could affect gm independently from LMA.  1.3 Mesophyll conductance (gm) After ambient CO2 molecules present in the bulk atmosphere cross the boundary layer and enter leaves through stomata, they face a series of resistances in both gas and liquid phases along the remaining diffusion pathway from the substomatal cavity to the sites of carboxylation inside the mesophyll cells (Flexas et al. 2008). More than half a century ago, Gaastra (1959) suggested that the internal resistance is an important determinant of the photosynthetic activity of plants. Using quantitative data obtained for several crop species, Gaastra attributed considerable variation in photosynthetic rate in response to CO2 concentration, light intensity and temperature to this resistance. Quantitative computations suggested that the CO2-limitation effect on photosynthesis is related to the sum of diffusion resistances, including the mesophyll resistance. Later, Jones & Slatyer (1972) confirmed that the mesophyll resistance can significantly constrain the photosynthetic rate. Using data for Pelargonium hortorum Bailey leaves, they developed a  4  more comprehensive model for net CO2 uptake considering the “intercellular space resistance” to CO2 diffusion from both upper and lower leaf surfaces and discussed possible errors in the estimation of this resistance. Earlier photosynthetic models were based on physical limitations at the boundary layer and across stomata. About the same time, theoretical models to describe and/or estimate the mesophyll resistance and the role of its various components were evolving, while direct and more accurate measurements of leaf CO2 and water vapour exchange were also becoming possible. In 1980, Farquhar et al. introduced a model (the widely used “Farquhar-von Caemmerer-Berry” model) based on known biochemical limitations (e.g., rubisco concentration, kinetics, temperature, CO2 and O2 concentrations, electron transport capacity, RuBP, etc.) to predict CO2 assimilation rate in C3 plants. Those authors noted that the term “mesophyll conductance” referred to the initial slope of an A-Ci curve (and not an A-Cc curve) and was linearly related to the maximum carboxylation rate (Vcmax). Thus, to this point, the concept of mesophyll resistance did not isolate the diffusional resistance from the biochemical "carboxylation resistance". Later, Farquhar and Sharkey (1982) equated the mesophyll resistance to just the liquid phase resistance for CO2 diffusion through mesophyll cells, as previously suggested by Gasstra (1959), but this resistance was, nonetheless, considered minimal and “could be neglected for most purposes in modeling photosynthesis.” During the mid-1980’s, however, Evans and co-workers (Evans 1983; Evans et al. 1986; Evans & Terashima 1988) used various approaches to show that there was a substantial draw-down in CO2 concentration from the substomatal space to the sites of carboxylation, consistent with a significant resistance. Using a three-dimensional model, Parkhurst (1994) described limitations on CO2 assimilation as affected by diffusion through the intercellular air space (gas phase), noting that this portion of the pathway could reduce An by 25% or more in 5  some leaves. He also discussed the limitation expected from liquid phase diffusion through cell walls and to the chloroplasts based on the distance and physical properties of the pathway, concluding that it should be of similar magnitude to resistance through the gas phase.  Although the concept of resistance is perhaps an easier way to envision how various barriers impact CO2 diffusion, conductance (the inverse of resistance) is now more commonly used to describe the direct relationship between CO2 flux and photosynthesis. The mesophyll conductance (gm) is finite and limits photosynthesis by dropping the CO2 concentration at sites of carboxylation (Cc) lower than Ci (Pons et al. 2009). Improving photosynthetic capacity by means of increasing gm could be an effective way to increase resource use efficiency (i.e., both water and nitrogen use efficiencies, simultaneously) in crop plants (Flexas et al. 2008). This realization has driven an exponential growth in the number of studies on gm within the last decade. For example, during water shortage, an increase in gm rather than gs increases the water-use efficiency (WUE) by promoting CO2 gain without affecting water loss (Flexas et al. 2008; Buckley & Warren 2014). Similarly, in relation to N investments in rubisco and the rest of the photosynthetic apparatus, maintenance of Cc under drought conditions (or a higher Cc under non-drought conditions) should maintain (or increase) the nitrogen-use efficiency (NUE).  Based on both theoretical estimations and experimental examinations, variation in gm is related to structural, physiological and biochemical properties of mesophyll cells (Flexas et al. 2008; Flexas et al. 2012). As noted above, morphological (i.e., physical) properties of the leaf such as LMA and palisade cell wall area, but also wall thickness, cell packing/density, leaf thickness, etc., constrain diffusion and place upper limits on gm. These properties can change developmentally but are fixed thereafter. Physiological components such as carbonic anhydrase (CA) activity, chloroplast 6  repositioning, and aquaporin function are known to be responsible for more rapid gm responses to environmental changes (Flexas et al. 2012). 1.4 Physiological components In the liquid phase, carbonic anhydrase (CA) maintains the equilibrium between CO2 and HCO3− for a steady supply of CO2 to rubisco (Badger & Price 1994). Multiple isozymes of CA are found free and/or bound to membranes within the cytosol, chloroplasts, and mitochondria (Fabre et al. 2007; Flexas et al. 2008). Tholen and Zhu (2011) developed a reaction-diffusion model to predict the mechanism of limitations to gm based on the Farquhar-von Caemmerer-Berry model for photosynthesis in C3 plants, and by using available numeric data. According to their model, removal of stromal CA activity is predicted to reduce gm by 44% and An by 7%. One experimental approach to remove CA activity is through chemical inhibition. Sulfonamide compounds (e.g., acetazolamide, ethoxyzolamide) can inhibit CA activity by binding to the active site of the enzyme (Coleman 1975). They have indeed been shown to reduce photosynthesis by affecting CO2 diffusion (Jacobson et al. 1975), but may also have direct effects on photosynthetic electron transport (Badger & Price 1994). Alternatively, gene silencing techniques such as RNA interference (RNAi) and RNA antisense can specifically block the function of candidate genes known to be associated with the expression of components of gm (Hachez et al. 2006). However, and in contrast to the predictions of Tholen and Zhu (2011), an early study by Price et al. (1994) showed that removing stromal CA from chloroplasts using the antisense technique had little or no detectable effect on photosynthesis in tobacco (Nicotiana tabacum L.). Williams et al. (1996) performed a similar experiment on transgenic tobacco with CA activity reduced to 8% of normal and also detected no impact on An; however, based on isotope discrimination, these authors estimated that Cc was reduced by 13-22 µmol mol-1. The failure of genetic modification to establish 7  a clear role for CA in CO2 diffusion may stem from the molecular diversity and possible functional redundancy of CAs. For example, 18 genes for CA have been identified in black cottonwood (v11.0, https://phytozome.jgi.doe.gov/pz/portal.html). Aquaporins, as another dynamic player for gm, are abundant in cell membranes and facilitate transport of various molecules such as H2O, CO2 and NH3 (Kaldenhoff & Fischer 2006). The plasma membrane intrinsic proteins (PIPs) are reported to transfer CO2 selectively compared to other aquaporin subfamilies (Maurel et al. 2008). Terashima & Ono (2002) reported that the application of mercuric chloride II (HgCl2), an inhibitor of aquaporin activity, decreases CO2 diffusion from the intercellular air space to the chloroplast stroma in Vicia faba and, possibly, Phaseolus vulgaris. Consistent with the effects observed by Terashima and Ono (2002), a mutant of Arabidopsis thaliana lacking an aquaporin gene (AtPIP1;2) had lower photosynthesis compared to wild-type and this was attributable to a reduction in gm (Heckwolf et al. 2011). Likewise, changes in PIP1 gene expression in transgenic lines of N. tabacum were directly reflected in both gm and An (Uehlein et al. 2008). Down regulation of PIP1 inconsistently reduced gm and An in transgenic P. tremula × alba, depending on the level of water stress (Secchi & Zwieniescki 2013).  The role(s) of genes encoding and/or regulating CO2-conducting aquaporins in P. trichocarpa, which has 55 such genes (Gupta & Sankararamakrishnan 2009; Almeida-Rodriguez et al. 2010), have yet to be studied.  Chloroplast movements may also mediate gm. For example, the re-anchoring of chloroplasts from  the periclinal to anticlinal position during the transition from low to high light is associated with a reduction in gm, presumably by changing the chloroplast surface area exposed to the intercellular air space (Takagi et al. 2009). Blue light perceived by blue light photoreceptors such as phototropin  8  modulates chloroplast movement by affecting actin and/or myosin filaments (Banaś et al. 2012).  Chloroplast re-arrangement in response to light quality increases the absorption under low light conditions and protects photosystems from exposure to excessive light. A reduction in chloroplast surface area adjacent to intercellular air space under high blue light has been shown to decrease gm, and consequently An, both theoretically (Loreto et al. 2009) and experimentally (Tholen et al. 2008; Weise et al. 2015).  1.5 Black cottonwood (Populus trichocarpa) The genus Populus includes cottonwoods and aspens and is one of two genera in the traditional Salicaceae family (sensu stricto), the other genus being Salix. Poplars are deciduous tree species native to boreal, temperate, and subtropical sites in the northern hemisphere (Eckenwalder 1996; Dickmann 2001). They have been used as model trees for several decades, but especially so in recent years. Poplars grow rapidly and regenerate quickly, have high biomass production, and are easily propagated by vegetative means (Ellis et al. 2010). Due to these prominent characteristics, many poplar lines have been bred for plantation purposes, particularly in north-temperate latitudes (Dillen et al. 2010). Populus also has a relatively small genome size, and black cottonwood was the first tree to have its genome fully sequenced (Tuskan et al. 2003). Populus species have a high ability to deal with various environmental changes of photoperiod, growing season length, temperature and precipitation (Keller et al. 2012). They grow very well in floodplains, moist uplands and bottomlands with nutrient-rich soil and high light intensity (Saarela et al. 2011). Black cottonwood has a wide latitudinal distribution from southern Alaska at 62°N latitude to northern Baja California at 31°N latitude (Figure 1.1). Its native range continues inland through British Columbia to the Rocky Mountains in Alberta, Idaho and Montana (DeBell 1990).  9     Figure 1.1 Native range of Populus trichocarpa (https://www.na.fs.fed.us/spfo/pubs/silvics_manual/volume_2/populus/trichocarpa.htm). 10  1.6 Objectives  Theoretical derivations of CO2 conductance predict that several anatomical and physiological properties of the mesophyll may constrain photosynthetic rate. The overall objective of my research was to evaluate inherent variation in gm and explore the physiological basis for interspecific differences in gm in black cottonwood genotypes. It was hypothesized that in P. trichocarpa, variation in gm will correlate with latitude. This variation, assuming it exists, will reflect differences in one or more of CA activity, AQP functioning and/or chloroplast positioning. Specific objectives were to: 1. Investigate the presence or absence of genotypic and clinal variation in gm in P. trichocarpa. 2. Ascertain if there is any latitudinal difference in gm between northern and southern P. trichocarpa genotypes in relation to CA activity under natural and inhibitor-induced conditions. 3. Test whether high blue light affects gm differently in northern and southern P. trichocarpa genotypes. 4. Evaluate the effects of mercuric chloride II on gm in northern and southern P. trichocarpa genotypes.    11  Chapter 2: Substantial role for carbonic anhydrase in latitudinal variation in mesophyll conductance of Populus trichocarpa Torr. & Gray  2.1 Introduction Populus trichocarpa (black cottonwood), a geographically widespread species distributed from 31° N to 62° N latitude, is the predominant cottonwood poplar in British Columbia, Canada, and in the Pacific Northwest of the United States. The closely related balsam poplar (P. balsamifera L.) replaces black cottonwood in the boreal forest of North America. There is clinal variation in An in both species, whereby a trend towards higher An in genotypes from high latitudes is thought to reflect their adaptation to shorter growing seasons (Gornall & Guy 2007; Soolanayakanahally et al. 2009). In balsam poplar, higher An in northern genotypes is supported by higher leaf N and higher LMA, and, at least under some conditions (Soolanayakanahally et al. 2015), higher gs. Leaf mass per area in balsam poplar reflects both the density and thickness of palisade tissue in leaves (Milla-Moreno et al. 2016), and is positively correlated with structural properties that may affect CO2 transport, such as the mesophyll cell wall area. In black cottonwood, gs, stomatal ratio and density, and leaf N are all strongly correlated with the latitudinal cline in An; whereas, in contrast to balsam poplar, LMA is not (McKown et al. 2014a, 2014b). During photosynthesis, water vapour is exchanged for CO2 entering the leaf by way of stomatal pores. Given set diffusion gradients, gs describes the ease with which water escapes from the leaf, as well as the ease with which CO2 enters. After reaching the substomatal cavity, CO2 molecules must transit intercellular air space, cell walls, membranes, cytosol, etc., to reach sites of carboxylation within chloroplasts. Carbon dioxide diffusion along these parts of the pathway is controlled by the mesophyll conductance (gm), which has both gas and liquid-phase components  12  (Flexas et al. 2008). In an experiment comparing three high latitude genotypes of balsam poplar with three low latitude genotypes, the three northern accessions were found to have greater gm (Soolanayakanahally et al. 2009). It is unknown whether there is any similar relationship between gm and latitude of origin in black cottonwood. When CO2 dissolves in water it exists in chemical equilibrium with carbonic acid (H2CO3), which dissociates into bicarbonate ion (HCO3−). The reversible conversion of CO2 to HCO3− is catalyzed by CA. Accounting for 0.5-2% of total soluble leaf protein, CA is the second most abundant protein in C3 plants after rubisco (Badger & Price 1994). In photosynthetic tissues, CA contributes to gm by maintaining the CO2 ↔ HCO3− equilibrium in the cytosol and chloroplasts, facilitating access to CO2 for fixation by rubisco (Evans et al. 2009; Perez-Martin et al. 2014). Carbonic anhydrase consists of a family of four isozymes in eukaryotic, archaeal, and bacterial cells (Brinkman 1933; Bradfield 1947; Hewett-Emmett & Tashian 1996; Dimou et al. 2009). Carbonic anhydrase is abundant in chloroplast stroma and cytoplasm (Tsuzuki et al. 1985; Stemler 1986; Fett & Coleman 1994; Moroney et al. 2001; Rudenko et al. 2007; DiMario et al. 2016), and has been associated with various membrane fractions (Utsunomiya & Muto 1993; Ignatova et al. 2011). In C3 plants, chloroplast CAs are believed to have a greater effect on mesophyll CO2 diffusion than cytosolic CAs (Evans et al. 2009; Tholen & Zhu 2011) but other CAs may also be involved. Interrogation of the black cottonwood genome in Phytozome (v11.0, https://phytozome.jgi.doe.gov/pz/portal.html) indicates the presence of 18 genes encoding CA. Only a few studies have investigated the effect of CA activity on gm, either theoretically or experimentally (Makino et al. 1992; Price et al. 1994; Gillon & Yakir 2000; Tholen & Zhu 2011). Carbonic anhydrase activity varies in C3 and C4 species (Gillon & Yakir 2001), and limitation of  13  gm by CA activity is suggested to be species-dependent (Gillon & Yakir 2000). Variation in CA activity may reflect inter- and intraspecific adaptive variation in leaf anatomy in relation to gm limitations, such as compensating for greater resistance in other parts of the diffusion pathway (Gillon & Yakir 2000; Tosens et al. 2012, Tomás et al. 2013). Diffusion of dissolved CO2 through the liquid phase is 10,000 times slower than diffusion in the gas phase. Cell wall surface area, chloroplast positioning, protein channels (aquaporins), and CA activity may all act together to reduce diffusion limitations in the liquid phase (Flexas et al. 2008; Evans et al. 2009; Hassiotou et al. 2009; Flexas et al. 2012; Perez-Martin et al. 2014). To study effects on photosynthesis, CA activity has been manipulated chemically and/or genetically with mixed results. For example, photosynthesis was insufficient to support establishment of young A. thaliana seedlings with reduced plastid-localized carbonic anhydrase, but older plants were unaffected (Ferreira et al. 2008). Price et al. (1994) reported no effects on assimilation rate in antisense mutants of N. tabacum with just 1-3% residual stromal CA activity. Williams et al. (1996) reported lower carbon isotope discrimination and chloroplast CO2 concentrations in transgenic N. tabacum having only 8% residual chloroplastic CA, but detected no measureable effect on photosynthetic rate. Other authors have reported reductions in photosynthesis by isolated chloroplasts after inhibition of CA with sulfonamides such as acetazolamide and ethoxyzolamide (e.g., Jacobson et al. 1975), but there is some evidence that these agents may affect photosynthesis independently of CA (Badger & Price 1994).  In this chapter, I demonstrate that in black cottonwood, despite little latitudinal variation in LMA, there is still a substantial cline in gm. I, then examine the potential contribution of differences in CA as a partial basis for genotypic variation in gm, by assaying CA activity and relating that activity  14  to the differential effects of acetazolamide on photosynthesis. Acetazolamide penetrates membranes, albeit somewhat slowly, to unselectively inhibit different CA isozymes (Swader & Jacobson 1972; Wu et al. 1998; Scozzafava et al. 2000). It was expected that acetazolamide, by inhibiting CA, would reduce gm and, consequently, An. I hypothesized that effects would be greater in high latitude genotypes because of their intrinsically higher gm.  2.2 Material and methods 2.2.1 Plant material To assess latitudinal patterns in gm and select representative genotypes for acetazolamide experiments, branch cuttings (whips) of twelve P. trichocarpa genotypes from 43°98ʹ to 59º42ʹ N and 137º83ʹ to 122º92ʹ W (Table 2.1) were taken in late January from the Totem Field common garden, University of British Columbia (UBC) (Figure 2.1). Bagged cuttings were kept in a dark cold room at +4°C until they were recut into ~10 cm lengths with two lateral buds for rooting and planting (Pointeau & Guy 2014). Cuttings were grown with supplemental lighting in a greenhouse (minimum photosynthetic photon flux density (PPFD) was 500 µmol m-2 s-1) under a 20 hour photoperiod, maximum temperature of 25°C during day and 20°C during night, in 3.78 L pots containing a 70% peat moss and 30% perlite mixture. In subsequent experiments, fresh cuttings of just three northern (SKNP-4, TAKA-2 and TATB-4) and three southern (HALS-2, PITS-3 and LONG-1) genotypes (Table 2.1) were chosen from either end of the latitudinal range. For the initial screening of 12 genotypes, the youngest fully expanded leaf per plant was used to measure An, LMA, gs and gm (by the fluorescence method), as described below. To determine LMA, five discs of known area were punched from above the middle of the leaf, dried at 70ºC for 72 hours, and weighed. After pulverizing, 3 mg subsamples were analyzed for total nitrogen at the UBC Stable  15  Table 2.1 Provenance of origin for Populus trichocarpa genotypes used in this study. Asterisks (*) indicate genotypes chosen to represent high and low latitudes in carbonic anhydrase experiments.   Genotype Drainage Latitude (N) Longitude (W) Elevation (m) JASP-5 Jasper 43.98° 122.92º 150 HALS-2 * Halsey 44.40° 123.32º 300 PITS-3 * Pittsburg 45.48° 123.12º 900 LONG-1 * Longview 46.06° 123.92º 100 MCMN-2 McMillan Island 49.17° 122.57º 15 HARB-1 Lillooet 50.02° 122.52º 213 KLNE-5 Klinaklini 51.73° 125.57º 427 BELC-2 Bella Coola 52.37° 126.58º 135 QLKE-2 Quesnel Lake 53.00° 122.32º 488 SKNP-4 * Skeena 54.55° 128.52º 61 TAKA-2 * Taku 58.60° 133.57º 31 TATB-4 * Alsek 59.42º 137.83º 34        16        Figure 2.1 Populus trichocarpa cuttings were taken from a gene bank in Totem Field at UBC (left image). Cuttings were grown under greenhouse conditions (right image).  17  Isotope Facility to determine leaf N. Experiments with acetazolamide used three leaves per plant. Measurements began after 6 weeks growth by processing two plants (initial assessment) and one plant (acetazolamide experiments) per day, and lasted in each case for 5-6 weeks. Experiments had a completely randomized design with four biological replicates per genotype.         2.2.2 Treatments and photosynthesis measurements For the acetazolamide experiments, the three youngest fully expanded leaves per plant were used to measure An, gs and Ci using a LI-COR 6400 XT gas exchange system fitted with a 6400-40 chlorophyll fluorescence chamber. One leaf was treated with acetazolamide to inhibit carbonic anhydrase, while the other two served as controls (see below). All routine measurements were done in triplicate under 10% blue to 90% red light ratio at a total PPFD of 1200 µmol m-2 s-1. Leaf temperature was maintained at 25°C and the ambient chamber CO2 concentration (Ca), supplied from 12 g CO2 cartridges, was set to 400 µmol mol-1. In order to maximize isotopic differences between the outlet sample CO2 and inlet reference CO2, the flow rate was set to 90 µmol air s-1 as the lowest rate that also allowed the vapour pressure deficit (VPD) to be kept between 1.4-1.6 kPa. A control leaf was dark adapted for 20 minutes prior to all other measurements to obtain the maximum quantum yield of photosystem II. Later, during gas exchange measurements, the quantum yield of photosystem II (ΦPSII) under actinic light was obtained by application of saturating flashes (>7000 µmol m-2 s-1) as per Genty et al. (1989).  2.2.3 Carbonic anhydrase inhibition Control and acetazolamide treatments, and order of measurement, were randomly assigned to the three leaves processed each day to eliminate effects of any possible age or time dependent errors. Each leaf was cut at the petiole base under distilled water and placed in a 5 mL vial filled with 18  either distilled water (control 1), 10 mM NH4OH aqueous solution (control 2, pH = 9.7), or 1 mM acetazolamide (Stemler & Jursinic 1983) in 10 mM NH4OH (pH = 9.4), to promote dissolution. After 45 minutes, leaves were placed inside the LI-COR 6400 XT cuvette to equilibrate to chamber conditions for 20 minutes prior to gas exchange measurements. In preliminary tests, there was no effect of leaf detachment on An, gs and gm (see Appendix A, Table A.1). 2.2.4 Carbon isotope discrimination measurements Seven pre-evacuated 1.5 L gas sampling bags were used to collect air exiting the LI-COR chamber through a tube connected to the cuvette exhaust, either with (CO2P) or without (CO2R) leaf material inside the chamber (Figure 2.2). There were four CO2R samples taken per plant, alternating with three CO2P samples. After taking the first CO2R sample, a leaf was placed inside the chamber and light adapted for 20 minutes before taking the first CO2P sample. The same protocol was followed for a second and then a third leaf, ending with a final CO2R sample. Gas exchange and chlorophyll fluorescence measurements were recorded three times during each sampling for CO2P. On the day of sampling, bags were transferred to the Biometeorology and Soil Physics lab in the Faculty of Land and Food Systems, UBC for measuring carbon isotope discrimination for each air bag sample using a tunable diode laser (TGA 200, Campbell Scientific, Inc, Logan, UT, USA) according to Semmens et al. (2014) (Figure 2.2). The system was referenced against internal standard tanks calibrated against NOAA-ESRL and UoC-INSTAAR isotopic standards at 398.2 µmol mol-1 and 467.6 µmol mol-1, in air. The TGA automatically switches between the gas sampling bag, the low calibration tank, the high calibration tank and ambient outdoor air (to flush). Each sample went through the TGA twice according to the following cycle: Low Tank – Flush – 19        Figure 2.2 Air sample bags were filled from the LI-COR exhaust (left image), and analyzed for δ13C using a Tunable Diode Laser (right image).          20  Sample – Flush – High Tank – Flush – Sample – Flush – Low Tank. 13C/12C isotope ratios (13C ‰) were expressed relative to Vienna-Pee Dee belemnite (V-PDB). The gas sampling bags were fabricated from commonly available multilayer polyethylene plus nylon heat-sealable freezer bags (FoodSaver, Brampton, ON, Canada) fitted with PTFE valves (Scentroid Inc. ON, Canada). These were rigorously pre-tested for their ability to hold a gas sample without change in CO2 concentration or isotopic composition. They were slightly better in performance relative to polyvinyl fluoride (Tedlar) gas sampling bags with stainless steel fittings (Scentroid Inc., ON, Canada), and far superior to polytetrafluoroethylene (PTFE) bags with PTFE valves (Scentroid Inc., ON, Canada). Samples in FoodSaver and/or Tedlar bags were stable for at least 3 days but showed some drift in isotopic composition after 7 days. In another test, 15 mL air samples from the gas exchange cuvette were simultaneously collected in Pyrex vacuum flasks for cryogenic purification and analysis (Ribas-Carbo et al. 2002) on an Isoprime (GV Instruments) Isotope Ratio Mass Spectrometer (IRMS) in the Stable Isotope Facility, Faculty of Forestry, UBC. After one day, there were no significant differences between δ13C values obtained from flask (-31.36 ± 1.50‰) and Tedlar (-31.96 ± 0.13‰) or FoodSaver (-31.87 ± 0.02‰) bag samples, but PTFE bag samples were significantly enriched (-30.88 ± 0.48‰) (P < 0.0001). The IRMS analysis confirmed the accuracy of the TGA measurements, but TGA had higher precision, was more convenient and, because bags took longer to fill, was more coincident with the period over which foliar gas exchange measurements were made. 2.2.5 Calculation of gm by chlorophyll fluorescence method The “constant J method” was used to estimate gm based on calculation of electron transport rate  (Jflu) from measurements of chlorophyll fluorescence (Genty et al. 1989): 21  𝐽flu = ΦPSII × PPFD × α × β     (1) where β (= 0.5 for C3 plants) is the fraction of absorbed quanta reaching photosystem II (Bernacchi et al. 2002). The leaf absorptance, α, was taken to be 0.827 based on the average value (± 0.03) of direct measurements of five plants from each of six genotypes using a CI-710 leaf spectrometer (CID BioScience Inc. Camas, WA, USA) (see Appendix A, Table A.2). gm was given by (Harley et al. 1992): 𝑔m = 𝐴n/ [𝐶i − (𝛤∗(𝐽flu+8(𝐴n+𝑅d))𝐽flu−4(𝐴n+𝑅d))]     (2) where Rd is the non-photorespiratory respiration rate in the light (1.12 ± 0.37 µmol m-2 s-1), and Γ* is the chloroplast CO2 photocompensation point (43.41 ± 1.25 µmol mol-1). These values were estimated, using the Laisk method (Laisk 1977 in Gilbert et al. 2012), as the point of intersection of the linear portion of six sets of A-Ci curves obtained at two irradiances (125 and 500 µmol m-2 s-1) and 12 CO2 concentrations (50, 60, 70, 80, 90, 100, 120, 150, 180, 200, 230, and 250 µmol mol-1) (see Appendix A, Figure A.1). As per Gilbert et al. (2012), Γ* was assumed to equal the intercellular CO2 photocompensation point (Ci*). There was no effect of acetazolamide treatment on Ci* and Rd (see Appendix A, Figure A.2). 2.2.6 Calculation of gm from carbon isotope discrimination Rubisco discriminates against 13CO2 relative to 12CO2 during carboxylation (Guy et al. 1993). The amount of discrimination expressed in vivo depends on the diffusion gradient for CO2 from the bulk atmosphere. By comparing the observed discrimination (Δo) with the predicted discrimination (Δi) based only on the diffusion gradient through the stomata (i.e., Ca to Ci), the gradient associated with the remaining portion of the diffusion pathway (i.e., Ci to Cc) can be estimated and used to  22  calculate gm (Evans et al. 1986). Smaller contributions to total discrimination associated with respiratory (Δe) and photorespiratory carbon flux (Δf) must also be accounted for. The effect of gm on overall isotope discrimination (Δgm) is then given by:  Δ𝑔m = Δi − Δo − Δe − Δf      (3) Observed discrimination was calculated according to Evans et al. (1986): ∆o=  1000𝜁(δ13𝐶a− δ13𝐶e)1000+ δ13𝐶a − 𝜁 (δ13𝐶a−δ13𝐶e)      (4) 𝜁 =𝐶e(𝐶e − 𝐶a)      (5) where δ13𝐶e and δ13𝐶a are the isotopic ratios of reference CO2 and unconsumed sample CO2, respectively, which were measured by TGA. 𝜁 is the ratio of the reference CO2 concentration (Ce) entering the cuvette, as determined by the LI-COR 6400 XT, and the net amount consumed in photosynthesis (i.e., Ce – Ca). Predicted discrimination was calculated from gas exchange data with corrections for ternary effects as per Farquhar & Cernusak (2012):  ∆i=1(1−𝑡)𝑎ˊ +1(1−𝑡)((1 + 𝑡)𝑏 − 𝑎ˊ)𝐶i𝐶a      (6) where b is the fractionation in carboxylation of ribulose bisphosphate catalyzed by rubisco (-29‰; Guy et al. 1993). The ternary correction factor, t, is: 𝑡 =(1+𝑎ˊ)𝐸2𝑔act       (7)where E is the transpiration rate and 𝑔act  is the combination of boundary layer and stomatal conductance to CO2. The combined factor for diffusional fractionation through stomata and the  23  boundary layer, 𝑎ˊ, is: 𝑎ˊ =  𝑎b(𝐶a−𝐶s)+𝑎(𝐶s−𝐶i)(𝐶a−𝐶i)      (8) where a and ab are the fractionations occurring during diffusion across the stomata (4.4‰) and through the boundary layer (2.9‰), respectively, and Cs is the CO2 concentration at the leaf surface (Evans et al. 1986).  Discriminations associated with respiration (e) and with photorespiration (f) were calculated from equations 9 and 10 (Farquhar & Cernusak 2012): ∆e =1+𝑡1−𝑡[𝑒𝑅d(𝐴n+𝑅d)𝐶a] (𝐶i − 𝛤 ∗)     (9) ∆f=1+𝑡1−𝑡[ƒ𝛤∗𝐶a]      (10) where e and ƒ are the fractionations associated with respiration and photorespiration, respectively. I took ƒ to be -11.6‰ (Lanigan et al. 2008) and assumed that there is no significant fractionation associated with dark respiration during the day (Wingate et al. 2007). However, because respired carbon was likely fixed during prior photosynthesis in the greenhouse, I took e to equal the difference between δ13Ce (-32 to -37‰) and the isotopic composition for atmospheric CO2 (δ13Catm) in the greenhouse (assumed to be -8‰; Alonso-Cantabrana & von Caemmerer 2015):  𝑒 = δ13𝐶e − δ13𝐶atm      (11) Discrimination associated with gm is described by (Farquhar & Cernusak 2012): Δ𝑔m =1+𝑡1−𝑡[𝑏 − 𝑎i −𝑒𝑅d𝐴+𝑅d]𝐴n𝑔m𝐶a     (12) where ai is the fractionation factor associated with hydration and diffusion in water (1.8‰ at 25°C).  24  Substitution of equation 3 into equation 12 yields the following for calculation of gm: 𝑔m =1+𝑡1−𝑡[𝑏 − 𝑎i −𝑒𝑅d(𝐴n+𝑅d)]𝐴n𝐶a/(∆i − ∆o − ∆e − ∆f)      (13) 2.2.7 Calculation of Cc Having obtained gm by either method, the CO2 concentration at sites of carboxylation (Cc) was estimated according to Harley et al. (1992): 𝐶c = 𝐶i −𝐴n𝑔m      (14) 2.2.8 Carbonic anhydrase activity  Immediately after gas exchange measurements, leaf punches were taken for LMA as described above, and 0.5 g of laminal tissue from the middle of each leaf was weighed, wrapped in aluminum foil and stored on dry ice for determination of CA activity as described by Wilbur & Anderson (1948). The leaf tissue was ground in 1 mL of 40 mM potassium phosphate buffer (pH= 8.3) at 0ºC using a mortar and pestle (Figure 2.3). All further steps were at 4ºC. The homogenate was centrifuged for 15 minutes at 4500×g and 20 µL of the supernatant was added to 1 mL of the buffer solution containing 20 ppm bromothymol blue as a pH indicator. The time required for the pH of the buffer solution to change from 8.3 to 6.3 for control (TControl) and enzyme-containing (TEnzyme) solutions was recorded visually upon the further addition of 1 mL of CO2-saturated water. The CO2-saturated water was prepared by bubbling CO2 through distilled water for two hours (also at 4ºC) (Figure 2.3). As a control, 20 µL of buffer solution was used in place of the supernatant. There were five technical replicates per assay. Enzyme activity was calculated as follows: Units CA / mL of supernatant = (𝑇Control − 𝑇Enzyme) × 𝑑𝑓(𝑇Enzyme) × 𝑉      (15) 25         Figure 2.3 Thawed leaf samples were ground in buffer solution in preparation for the CA activity measurement assay (left image). The right image shows CO2-saturated water in preparation.   26  where df is the dilution factor and V is the volume of enzyme extract used. Activities were expressed on a leaf area and fresh mass basis.  2.2.9 A-Ci curves In order to test whether feeding through petioles with acetazolamide has any effect on photosynthesis other than a direct inhibitory effect on facilitated CO2 diffusion, An was measured in the LONG-1 genotype in five replications over a range of 15 CO2 concentrations from 50 to 1400 µmol mol-1, at 1200 µmol m-2 s-1 PPFD (10% blue light) under distilled water (control) and 1 mM acetazolamide treatments. Data were fitted to version 2.0 of curve-fitting model described by Sharkey (2016) to estimate (Vcmax), maximum electron transport rate (Jmax), and gm.  2.2.10 Statistics Pearson correlation coefficients and, where warranted, linear regression lines were used to illustrate relationships between latitude and An, gs, gm and LMA for the initial twelve genotypes, and between An, LMA, gs, gm, WUE, Cc and CA activity for representative genotypes, using GraphPad prism 6 software (GraphPad Software, Inc. CA, USA). Paired t-tests were run in GraphPad prism 6 to check for systematic differences between the isotope discrimination and chlorophyll fluorescence methods for estimating gm and Cc.  Mixed linear models with contrast statements were used to compare An, gm, gs, Cc and CA activity for northern versus southern genotypes under control 1, control 2, and acetazolamide treatments using SAS 9.4 (SAS Institute Inc. NC, USA 2013). Both factors were fixed and genotypes were nested in latitude. The P value required for significance (0.016) was adjusted by dividing α (0.05) by the number of contrasts per test (three). Because controls did not differ, mixed linear models were used to compare within-plant absolute and percentage reductions in An, gm, gs, Cc and CA 27  activity under acetazolamide relative to the two controls (adjusted P value for two contrasts = 0.025). Mixed linear models without latitude as a factor were used to compare treatment effects on An, gm, gs, Cc and CA activity for the six genotypes independently (adjusted P value = 0.002). Logarithm or squared transformations were performed to meet normality and equal variance assumptions where needed. 2.3 Results 2.3.1 Initial assessment of latitudinal pattern There was a positive correlation between latitude of origin and An (0.587, P = 0.044), gs (r = 0.558, P = 0.049) and, notably, gm (r = 0.671, P = 0.017) (Figure 2.4A-C). Leaf N (Figure 2.5), but not LMA (Figure 2.4D), also varied with latitude (r = 0.589, P = 0.043).   2.3.2 Comparison of two methods Estimated values of gm obtained from measurements of stable isotope discrimination versus chlorophyll fluorescence were well correlated (r = 0.772, P < 0.0001) (Figure 2.6). Estimates of Cc were also correlated but not as strongly so (r = 0.372, P = 0.0013) (Figure 2.7). There was a tendency for the isotope discrimination method to yield slightly (5%) higher estimates of gm (P = 0.008), but not for Cc (P = 0.148). Unless otherwise noted, gm and Cc data from the isotope discrimination method are presented, the former ranging from 0.03-0.34 mol CO2 m-2 s-1 and the latter from 85-252 µmol mol-1. 2.3.3 Treatment effects Northern genotypes had significantly greater An (1.5 fold; P = 0.0011) and gm (2.32 fold; P = 0.002) than southern ones under all three treatments (Figure 2.8 & 2.9). There was no consistent,  28   Figure 2.4 Photosynthetic traits across latitude of origin for 12 genotypes (clones) of Populus trichocarpa. A, net assimilation rate (An, µmol CO2 m-2 s-1); B, stomatal conductance (gs, mol H2O m-2 s-1); C, mesophyll conductance (gm, mol CO2 m-2 s-1); D, leaf mass per area (LMA, mg mm-2). Data points are means of four biological replicates (ramets) per clone (± SE). 29  4 2 4 7 5 2 5 7 6 20 .81 .01 .21 .4L a titu d eLeaf Narea (µg mm-2)r =  0 .5 8 9P  =  0 .0 4 3 Figure 2.5 Leaf nitrogen concentration (leaf N, µg mm-2) across latitude of origin for 12 genotypes (clones) of Populus trichocarpa. Data points are means of four biological replicates (ramets) per clone (± SE). 30  gm  (m o l C O 2  m-2 s-1) f lu o re s c e n c e  m e th o dgm (mol CO2 m-2 s-1) isotopic method0 .0 0 .1 0 .2 0 .3 0 .40 .00 .10 .20 .30 .4r  =  0 .7 7 2   P  <  0 .0 0 0 1  Figure 2.6 Correlation between mesophyll conductances (gm, mol CO2 m-2 s-1) obtained from stable carbon isotope and chlorophyll fluorescence methods (n = 72) under three treatments; distilled water control (●), aqueous NH4OH control (○), and acetazolamide (●).       31  C c  (µ m o l m o l-1)f lu o re s c e n c e  m e th o dCc (µmol mol-1)isotopic method0 5 0 1 0 0 1 5 0 2 0 0 2 5 0 3 0 005 01 0 01 5 02 0 02 5 03 0 0r  =  0 .3 7 2P  =  0 .0 0 1 3Figure 2.7 Correlation between chloroplast CO2 concentrations (Cc, µmol mol-1) obtained from stable carbon isotope and chlorophyll fluorescence methods (n = 72) under three treatments; distilled water (●), aqueous NH4OH (○), and acetazolamide (●).   32  G e n o ty p eAn (µmol CO2 m-2 s-1)HALS-2PITS-3LONG-1SKNP-4TAKA-2TATB-4051 01 52 02 5N o r thS o u thaabaabaabaabaabaabFigure 2.8 Mean values (± SE; n = 4) for net assimilation rate (An, µmol CO2 m-2 s-1) of six Populus trichocarpa genotypes under three treatments (distilled water in black, aqueous NH4OH in white, and acetazolamide in grey). Different letters show significant differences between distilled water (control 1), aqueous NH4OH (control 2) and acetazolamide treatments for each genotype at P < 0.002.   33  G e n o ty p egm (mol CO2 m-2 s-1)HALS-2PITS-3LONG-1SKNP-4TAKA-2TATB-40 .00 .10 .20 .30 .4S o u th N o r tha b ababa baabaaba abaab Figure 2.9 Mean values (± SE; n = 4) for mesophyll conductance (gm, mol CO2 m-2 s-1) of six Populus trichocarpa genotypes under three treatments (distilled water in black, aqueous NH4OH in white, and acetazolamide in grey). Different letters show significant differences between distilled water (control 1), aqueous NH4OH (control 2) and acetazolamide treatments for each genotype at P < 0.002.    34  statistically significant difference between the distilled water and aqueous NH4OH controls in any trait (Table 2.2). In contrast, most traits in most genotypes were strongly affected by treatment with acetazolamide. Net assimilation rate and mesophyll conductance were significantly lower for leaves treated with acetazolamide compared to controls at both latitudes (Figure 2.8 & 2.9, Table 2.2). In northern genotypes, gs decreased significantly (by ~20%) under acetazolamide treatment compared to distilled water, but not in comparison to the NH4OH control (Figure 2.10, Table 2.2). There was no significant effect of acetazolamide on gs relative to either control in southern genotypes. Acetazolamide treatment significantly reduced Cc compared to distilled water and aqueous NH4OH controls in the northern genotypes (by 19% and 14% respectively) but had comparatively larger effects in the southern genotypes, where Cc was reduced by 31% relative to either control (Figure 2.11, Table 2.2). Only under acetazolamide treatment did northern genotypes show a significantly different Cc from southern genotypes (Figure 2.11). Results from A-Ci curve analysis were consistent with chlorophyll fluorescence and stable isotope discrimination methods for determining gm. Average gm over the range of CO2 concentrations used was 58% lower in leaves fed with acetazolamide, in comparison to distilled water controls (Table 2.3). Both Vcmax and Jmax were unaffected by treatment with acetazolamide (Table 2.3). Consequently, photosynthesis at a CO2 concentration (i.e., Ca) of 400 µmol mol-1 was reduced by 22%, but there was no significant effect of acetazolamide on An at saturating CO2 (Figure 2.12).  Control leaves from northern genotypes had just over twice as much CA activity as southern genotypes on a leaf area basis (Figure 2.13, Table 2.2). This difference, though smaller (1.8 fold), persisted when activity was expressed relative to leaf mass (Figure 2.14). On average, the northern    35  Table 2.2 An, gs, CA activity, gm and Cc in northern vs. southern genotypes under control 1 (distilled water), control 2 (aqueous NH4OH), and acetazolamide treatments. Different letters show significant differences for mean values (± SE; n = 4) of controls 1 and 2 compared to the acetazolamide treatment within each latitudinal group at P < 0.016.   north south control 1 control 2 acetazolamide control 1 control 2 acetazolamide An  15.90 ± 0.34 a 15.51 ± 0.31 a 11.97 ± 0.33 b 10.59 ± 0.31 a 9.96 ± 0.33 a 7.75 ± 0.34 b gs  0.218 ± 0.006 a 0.205 ± 0.006 ab 0.175 ± 0.008 b 0.196 ± 0.008 a 0.174 ± 0.007 a 0.175 ± 0.012 a CA activity  1.81 ± 0.12 a 1.84 ± 0.19 a 1.06 ± 0.10 b 0.90 ± 0.07 a 0.84 ± 0.10 a 0.51 ± 0.06 b gm isotopic method 0.234 ± 0.018 a 0.217 ± 0.020 a 0.122 ± 0.011 b 0.095 ± 0.013 a 0.099 ± 0.012 a 0.053 ± 0.009 b fluorescence method 0.198 ± 0.018 a 0.188 ± 0.012 a 0.114 ± 0.010 b 0.100 ± 0.010 a 0.073 ± 0.008 a 0.048 ± 0.007 b Cc isotopic method 200.4 ± 8.4 a 193.6 ± 9.3 ab 167.1 ± 12.3 b 184.8 ± 10.4 a 180.7 ± 14.0 a 143.9 ± 10.6 b fluorescence method 193.2 ± 4.8 a 188.3 ± 4.9 a 165.6 ± 8.8 b 182.1 ± 11.1 a 166.9 ± 4.0 a 132.3 ± 6.3 b An, net assimilation rate (µmol CO2 m-2 s-1); gs, stomatal conductance (mol H2O m-2 s-1); CA activity, carbonic anhydrase activity (units cm-2); gm, mesophyll conductance (mol CO2 m-2 s-1); Cc, CO2 concentration at sites of carboxylation (µmol mol-1). 36  G e n o ty p egs (mol H2O m-2 s-1)HALS-2PITS-3LONG-1SKNP-4TAKA-2TATB-40 .00 .10 .20 .30 .4S o u th N o r thaaaaa aaaa aa a a aaaa bb Figure 2.10 Mean values (± SE; n = 4) for stomatal conductance (gs, mol H2O m-2 s-1) of six Populus trichocarpa genotypes under three treatments (distilled water in black, aqueous NH4OH in white, and acetazolamide in grey). Different letters show significant differences between distilled water (control 1), aqueous NH4OH (control 2) and acetazolamide treatments for each genotype at P < 0.002.  37  G e n o ty p eCc (µmol mol-1)HALS-2PITS-3LONG-1SKNP-4TAKA-2TATB-401 0 02 0 03 0 0S o u th N o r thaba baa bba bbaaa a aababa Figure 2.11 Mean values (± SE; n = 4) for CO2 concentration at sites of carboxylation (Cc, µmol mol-1) of six Populus trichocarpa genotypes under three treatments (distilled water in black, aqueous NH4OH in white, and acetazolamide in grey). Different letters show significant differences between distilled water (control 1), aqueous NH4OH (control 2) and acetazolamide treatments for each genotype at P < 0.002.    38  Table 2.3 An, gm, Vcmax and Jmax mean values (± SE) over five replications estimated for leaves under control (distilled water) and acetazolamide treatments using the A-Ci curve method. Data were introduced to PROC GLM in SAS 9.4 for analysis of variances. Significant differences between control and acetazolamide treatments are shown with different letters at P < 0.05.   control acetazolamide 1An 13.33 ± 0.26 a 10.34 ± 0.23 b 2An 15.89 ± 0.29 a 15.50 ± 0.15 a gm 0.216 ± 0.012 a 0.090 ± 0.008 b Vcmax 75.00 ± 4.77 a 78.60 ± 5.94 a Jmax 89.18 ± 1.97 a 81.22 ± 3.59 a 1An, and 2An net assimilation rates (µmol CO2 m-2 s-1) at the ambient and saturating CO2 concentrations, respectively; gm, mesophyll conductance (mol CO2 m-2 s-1); Vcmax, maximum carboxylation rate allowed by rubisco (µmol m-2 s-1); Jmax, maximum rate of photosynthetic electron transport rate (based on NADPH requirement) (µmol m-2 s-1).  39  0 2 0 0 4 0 0 6 0 0 8 0 0 1 0 0 0 1 2 0 0 1 4 0 0051 01 52 0C i (µ m o l C O 2  m-2 s-1)An (µmol CO2 m-2 s-1)Figure 2.12 Relationship between mean An (net assimilation rate) and Ci (intercellular air space CO2 concentration) (± SE; n = 5) averaged over five replications under control (distilled water) and acetazolamide treatments at 1200 µmol m-2 s-1 PPFD. The LONG-1 genotype was chosen arbitrarily for this experiment. There was no NH4OH control treatment. 40  G e n o ty p eCA activity(units cm-2)HALS-2PITS-3LONG-1SKNP-4TAKA-2TATB-401234S o u th N o r thaba b a baba abaabaababc Figure 2.13 Mean values (± SE; n = 4) for carbonic anhydrase activity, CA activity (units cm-2) of six Populus trichocarpa genotypes under three treatments (distilled water in black, aqueous NH4OH in white, and acetazolamide in grey). Different letters show significant differences between distilled water (control 1), aqueous NH4OH (control 2) and acetazolamide treatments for each genotype at P < 0.002.   41  G e n o ty p eCA activity(units g-1 fresh mass)HALS-2PITS-3LONG-1SKNP-4TAKA-2TATB-402 04 06 0S o u th N o r thaabaabaabaaba abaabFigure 2.14 Mean values (± SE; n = 4) for carbonic anhydrase activity, CA activity (units g-1 fresh mass) of six Populus trichocarpa genotypes under three treatments (distilled water in black, aqueous NH4OH in white, and acetazolamide in grey). Different letters show significant differences between distilled water (control 1), aqueous NH4OH (control 2) and acetazolamide treatments for each genotype at P < 0.002.    42  genotypes had just 11% greater LMA than the southern genotypes (Figure 2.15, P < 0.0001). Inhibitory effects of acetazolamide treatment on CA activity paralleled effects on An and gm (P < 0.016). Under acetazolamide, northern genotypes still had a significantly higher CA activity (2.4 fold) than southern ones (Figure 2.13). Commensurate with their higher control values, northern genotypes had greater absolute reductions in An, gm, and CA activity under acetazolamide compared to southern ones (Table 2.4). These differences disappeared when reductions in An, gm, gs, and CA activity were expressed as percentages relative to either the distilled water or the aqueous NH4OH controls (Table 2.4). In contrast, percent reduction in Cc was greater for southern genotypes compared to northern genotypes (Table 2.4). 2.3.4 Trait correlations There was a strong correlation between gm and CA activity whether treatments were combined (r = 0.752, P < 0.0001) or considered separately (Figure 2.16). Thus, gm and CA activity were related to each other, whether the variation was inherent or induced (i.e., by acetazolamide).  Inhibitor affects aside, several traits were correlated with each other when assayed under either the distilled water (Table 2.5) or, similarly, the aqueous NH4OH control (not shown). Net assimilation rate was positively correlated with gs (r = 0.497, P = 0.013), but more so with gm (r = 0.794, P < 0.0001) and, consequently, also with WUE (r = 0.685, P < 0.0001). In fact, An, gm, WUE and CA were all positively intercorrelated with each other, and with LMA. Although CA activity was correlated with LMA (r = 0.641, P < 0.001) across all genotypes, it had a much larger coefficient of variation (28% vs. 9%), reflecting higher activities in northern genotypes on both a mass and area basis. 43  G e n o ty p eLMA (mg mm-2)HALS-2PITS-3LONG-1SKNP-4TAKA-2TATB-40 .0 00 .0 20 .0 40 .0 6S o u th N o r tha a aa b a bbFigure 2.15 Leaf mass per area (LMA, mg mm-2) of six Populus trichocarpa genotypes. Shown are mean values (± SE) determined on 12 leaves per genotype. Different letters show significant differences between genotypes.   44  Table 2.4 Absolute and percentage reductions in An, gs, CA activity, gm and Cc under acetazolamide treatment from controls 1 and 2 (distilled water and aqueous NH4OH) for the northern vs. the southern genotypes. Data pairing was on a plant per plant basis. Different letters show significant differences for mean values (± SE; n = 4) of control 1 and 2 compared to the acetazolamide treatment for northern vs. southern genotypes at P < 0.025.   north south control 1 control 2 control 1 control 2 An absolute 3.94 ± 0.29 a 3.55 ± 0.20 a 2.84 ± 0.45 b 2.22 ± 0.25 b percentage 24.7 ± 1.7 a 22.9 ± 1.3 a 26.7 ± 3.7 a 22.3 ± 3.3 a gs absolute 0.044 ± 0.007 a 0.030 ± 0.006 ac 0.021 ± 0.010 bc -0.001 ± 0.009 b percentage 19.8 ± 2.9 a 14.2 ± 2.7 a 11.0 ± 5.8 ab -0.068 ± 5.46 b CA activity absolute 0.75 ± 0.05 a 0.78± 0.11 a 0.40 ± 0.06 b 0.33 ± 0.04 b percentage 42.0 ± 3.6 a 42.5 ± 3.7 a 43.3 ± 5.6 a 40.0 ± 5.1 a gm absolute 0.112 ± 0.019 a 0.100 ± 0.015 a 0.042 ± 0.011 b 0.047 ± 0.016 b percentage 47.8 ± 5.4 a 43.8 ± 5.2 a 44.2 ± 7.3 a 46.5 ± 8.1 a Cc absolute 33.3 ± 7.0 a 26.6 ± 8.6 a 56.5 ± 7.3 b 62.4 ± 13.9 b percentage 16.3 ± 4.1 ac 13.8 ± 4.8 a 30.9 ± 3.9 bc 30.7 ± 5.4 bc An, net assimilation rate (µmol CO2 m-2 s-1); gs, stomatal conductance (mol H2O m-2 s-1); CA activity, carbonic anhydrase activity (units cm-2); gm, mesophyll conductance (mol CO2 m-2 s-1); Cc, CO2 concentration at sites of carboxylation (µmol mol-1).45  C A  a c t iv ity(u n its  c m-2)gm(mol CO2 m-2 s-1)0 1 2 3 40 .00 .10 .20 .30 .4r  =  0 .7 5 2   P  <  0 .0 0 0 1 Figure 2.16 Correlation between CA activity (units cm-2) and mesophyll conductance (gm, mol CO2 m-2 s-1) under three treatments; control 1 (northern genotypes ▲, southern genotypes ▼), control 2 (northern genotypes , southern genotypes ), and acetazolamide (northern genotypes ▲, southern genotypes ▼). The correlation coefficient and associated P-value shown are for all treatments combined. For the individual treatments considered separately, the correlation coefficients were 0.623 (P = 0.0011) for control 1, 0.713 (P < 0.0001) for control 2, and 0.675 (P = 0.0003) for acetazolamide.46  Table 2.5 Pearson correlation coefficients (r) between traits measured across all leaves (4 per genotype) in the distilled water treatment (n = 24). Significant correlations are in bold (P < 0.05) and bold* are significant after Bonferroni correction (P < 0.003).   An LMA gs gm  WUE Cc LMA 0.565      gs 0.497 0.131      gm 0.794* 0.492 0.327    WUE 0.685* 0.659* 0.076 0.544    Cc 0.348 0.100 0.244 0.714* 0.114  CA activity 0.784* 0.641* 0.514 0.623* 0.613*  0.200 An, net assimilation rate (µmol CO2 m-2 s-1); LMA, leaf mass per area (mg mm-2); gs, stomatal conductance (mol H2O m-2 s-1); gm, mesophyll conductance (mol CO2 m-2 s-1); WUE, water-use efficiency (µmol CO2 mmol-1 H2O); Cc, CO2 concentration at sites of carboxylation (µmol mol-1); CA activity, carbonic anhydrase activity (units cm-2).   47  2.4 Discussion The availability of CO2 to rubisco, and therefore the rate of carboxylation, depends not only on stomatal conductance but also on mesophyll conductance, in varying, but often similar, proportion. As recommended by Pons et al. (2009), I used two methods to estimate gm (isotope discrimination and fluorescence-based methods) and obtained comparable results by either method. Because of the technical constraints inherent to the measurement of gm by these methods, the present study made detailed use of a small number of Populus trichocarpa genotypes chosen to be representative of either low (southern) or high (northern) latitudes. Our initial assessment of 12 genotypes covering 16 degrees latitude was consistent with and within the range of previous studies on field-grown material (Gornall & Guy 2007; McKown et al. 2014a), whereby there is a cline in An and gs (Figure 2.4A, B), and leaf N (Figure 2.5), but not LMA (Figure 2.4D). Likewise, in completely separate analyses, the three representative northern genotypes had greater An (Figure 2.8) and marginally higher gs (Figure 2.10) than the three representative southern genotypes. Going beyond previous studies, I show here, reproducibly (Figure 2.4C & Figure 2.9), that there is also a strong latitudinal cline in gm. Across a wide variety of species, gm and gs often co-vary both statically and dynamically (Flexas et al. 2012). It is not surprising, then, that gm in black cottonwood increases with latitude just as gs does, though they were not significantly intercorrelated in this study. Intrinsically higher rates of photosynthesis in short-growing season plants are likely to be achieved by a variety of mechanisms working together, in different proportion in different species, populations or individuals. As per our expectations, variation in gm across control treatments was well correlated with CA activity (Figure 2.16). Furthermore, when leaves were pre-treated with acetazolamide through the   48  petiole, gm and CA activity were inhibited in parallel (Figure 2.9 & 2.13), while gs was significantly reduced only in the northern genotypes (Table 2.2) and only in the TATB-4 genotype (Figure 2.10), relative to the distilled water control. Northern and southern genotypes had similar Cc under control conditions, but the southern genotypes were significantly more susceptible to acetazolamide (Figure 2.11). Although treatment with acetazolamide resulted in similar reductions in An across all genotypes, Cc was perhaps more strongly affected in southern genotypes because of their lower levels of residual CA activity (Table 2.4). In fact, in the presence of acetazolamide, northern genotypes had residual CA activity that was still more-or-less equivalent to controls of the southern genotypes. Higher absolute reductions in gm and CA activity in northern genotypes reflect their much higher control values relative to southern genotypes, but percent reductions were similar (Table 2.4). Although inhibition was in all cases incomplete, the differential “titration” of activity in vivo revealed the relationship shown in Figure 2.16. Taken together, the data strongly implicate a role for CA as one factor determining genotypic and induced variation in gm. A crucially important feature of the observed differences in CA activity is that they are largely, though not wholly, independent of differences in LMA. Although in previous work (Gornall & Guy 2007; McKown et al. 2014a) and in my initial assessment of 12 genotypes I did not find a significant latitudinal pattern in LMA in P. trichocarpa, the representative northern genotypes had 11% greater LMA than the southern genotypes (Figure 2.15). Most of this difference, however, is attributable to a single accession (TATB-4), and is nowhere near sufficient to account for the more than two times greater CA activity in the northern genotypes. Soolanayakanahally et al. (2009) also reported higher An and gm in northern genotypes of P. balsamifera. In P. balsamifera, however, these tendencies seem to be more clearly related to LMA, with no consistent pattern in 49  gs (Soolanayakanahally et al. 2015). Patterns in CA activity have not been studied in P. balsamifera.  Within the liquid phase, the cell wall and chloroplast envelope are thought to have the largest shares in total diffusive resistance (Tholen & Zhu 2011). Carbonic anhydrase activity has been found in the cytosol, chloroplast envelope, stroma, and mitochondria (Fabre et al. 2007; Evans et al. 2009) and in thylakoids (Ignatova et al. 2011; Fedorchuk et al. 2014). Because of the pH difference, the HCO3─ concentration of the stromal space is up to five times greater than in the cytosol (Werdan & Heldt 1972). According to the model of Tholen & Zhu (2011), reductions in stromal CA activity or leakage of HCO3─ from stroma to cytosol are predicted to reduce gm. These authors estimated that removal of all CA activity from the stroma would reduce gm by around 44%, and An by only 7%, relative to their arbitrary default conditions. Therefore it is surprising that in P. trichocarpa (Table 2.4), a 40-43% inhibition of total CA activity reduced gm by 44-48% and decreased An by 22-26%.  Experiments utilizing genetically modified plants with reduced levels of CA have logically focused on the stromal isozyme, but substantially reduced expression of this CA has had little impact on gm or An (e.g., Price et al. 1994). However, other CAs may also be important in facilitating CO2 diffusion. For example, Shingles et al. (1997) reported that unless CA was provided externally, CO2 diffusion across chloroplast inner envelope membranes was limited by the dehydration rate of bicarbonate. The various known CAs are differentially susceptible to acetazolamide (Huang et al. 2011); αCAs are very sensitive, whereas βCAs, which include the predominant stromal CA, can be quite resistant to acetazolamide in archaeal, bacterial, yeast and (particularly) mammalian cells, but are more sensitive in plants and green algae. The Ki value of  50  acetazolamide binding to pea βCA is 28 µM (Huang et al. 2011) – well below our feeding concentration (1 mM). In addition, the effect of CA inhibition could be species dependent and reflect differences in leaf microanatomy, photosynthetic capacity, etc. Species with low gm, as is typical of woody species (Flexas et al. 2008), are expected to be more dependent on CA-facilitated CO2 diffusion (Gillon & Yakir 2000).  Although acetazolamide, supplied through the petiole, clearly resulted in reduced CA activity, its impact on photosynthesis may be partially attributable to other effects. Both acetazolamide and ethoxyzolamide can directly impact photosynthetic electron transport (Swader & Jacobson 1972; Lonergan & Sargent 1978). I emphasize, however, that direct inhibition of photosynthesis would result in a reduced diffusion gradient for CO2 and thus an increase in Cc, whereas I observe the opposite (Figure 2.11). Furthermore, comparison of A-Ci curves for control and acetazolamide treatments showed that increasing CO2 to the saturation point overcomes limitations to photosynthesis caused by acetazolamide, consistent with an effect on gm and not on the capacity for electron transport (Figure 2.12).  Another explanation for the efficacy of our acetazolamide treatments are possible additional effects on aquaporins. Acetazolamide reversibly blocks water movement across aquaporin-4 (AQP4) in mammalian cells (Tanimura et al. 2009; Kamegawa et al. 2016). In turn, mercuric ion, a widely used aquaporin blocker, inhibits CA (Blundell & Jenkins 1977). In fact, there are recent reports that aquaporins and CAs may be functionally related and CA near or associated with membranes may be working in conjunction with aquaporins to facilitate diffusion. Physical interaction between the two proteins facilitates water transport in mammalian cells (Vilas et al. 2015), and Borisova et al. (2012) suggested that CA binds to aquaporins in chloroplast envelopes.  51  In the CO2-signaling pathway of Arabidopsis guard cells, the CO2-permeable aquaporin PIP2;1 interacts with a CA located at the intercellular side of the plasma membrane (βCA4) to regulate stomata opening (Wang et al. 2016).  2.5 Conclusion As shown here, the tendency towards greater An in black cottonwood accessions originating from higher latitude is mirrored not only by higher foliar nitrogen and gs, but also by higher gm. The linear relationship between gm and CA activity across genotypes and inhibitor treatments, either in combination or considered separately (Figure 2.16), suggests that CA activity plays a significant role in mediating the mesophyll resistance to CO2 diffusion in this species. Inherent clonal and latitudinal variation in gm is strongly linked to this trait. Nonetheless, variation in other physiological and/or morphological components, such as differences in cell wall area and thickness, or chloroplast positioning and aquaporin channels, may contribute, in parallel, to these genotypic differences.            52  Chapter 3: Blue light differentially represses mesophyll conductance in high vs low latitude genotypes of Populus trichocarpa Torr. & Gray 3.1 Introduction In widely distributed species, variations in ecophysiological traits mirror genetic adaptation to gradient (spatial) climatic conditions (Marchin et al. 2008; Hoffmann & Sgró 2011). Populus trichocarpa ranges from Kodiak Island in Alaska (62º N lat.) to northern Baja California (31º N lat.), and inland in the Pacific Northwest and in southern British Columbia to southern Alberta (Maini & Cayford 1968; Niemiec et al. 1995). In P. trichocarpa, net assimilation rate, leaf nitrogen concentration, and stomatal conductance co-vary with latitude (Gornall & Guy 2007; McKown et al. 2014a). Stomatal conductance in P. trichocarpa is positively correlated with adaxial stomatal density and the adaxial/abaxial stomatal ratio that are, on average, greater for high latitude genotypes (McKown et al. 2014b). In addition, greater An in northern P. trichocarpa is supported by higher mesophyll conductance (Momayyezi & Guy 2017), which defines the ease of CO2 diffusion from the substomatal cavity to the site of fixation by rubisco. The mesophyll conductance is mediated by anatomical and biochemical features of the mesophyll (Peguero-Pina et al. 2012; Flexas et al. 2013). Mesophyll conductance is affected by palisade cell wall area, wall thickness, aquaporin channels and carbonic anhydrase activity. Like photosynthetic capacity, all of these may at least partly scale with leaf mass per area (Flexas et al. 2008; Milla-Moreno et al. 2016). However, as reported by Momayyezi & Guy (2017), northern P. trichocarpa genotypes have an almost two-fold higher CA activity than southern genotypes, independent of small differences in LMA. Commensurate with their higher gm, the northern genotypes also showed greater absolute (but not relative) reductions in gm in the presence of a CA inhibitor. 53  In addition to more-or-less static structural and/or potentially dynamic biochemical controls, subcellular “behavior” may also affect gm. Mesophyll cells are capable of relocating their chloroplasts to optimize photosynthetic performance under low and/or inconsistent light energy, or to protect them from photodamage caused by excess light energy (Schurr et al. 2006; Takamatsu & Takagi 2011). Chloroplast movement in reaction to light supply is a blue light photoresponse, the amount of blue light functioning as a representative indicator of total PPFD (Haupt & Wagner 1984; Gorton et al. 1999). In most plant species the blue and near UV light receptors, phototropins and sometimes cryptochromes, directly perceive blue light (Goh 2009; Banaś et al. 2012). The ratio of blue to red light can thus be used to manipulate chloroplast positioning while keeping the total supply of photosynthetically active radiation (PAR) constant. Note that the proportion of blue light in global PAR during midday in the summer varies little with latitude; for example, on the solstice, the ratio of blue (470 nm) over red (630 nm) is only 1.2% greater at the northern range limit of P. trichocarpa (62° N) than at the southern range limit (31° N) (Bird & Riordan 1986; solar spectrum calculator available at https://www2.pvlighthouse.com.au). Chloroplast positioning is expected to affect gm by changing the chloroplast surface area exposed to the intercellular air space (Evans & von Caemmerer 1996; Evans & Loreto 2000). High versus low fluxes of blue light trigger different chloroplast responses (Banaś et al. 2012). Actin filaments and microtubules are two types of cytoskeletal proteins known to control redistribution of chloroplasts via a blue light transduction pathway (Takagi 2003; Verchot-Lubicz & Goldstein 2010; Banaś et al. 2012). Cytochalasins (i.e., form D), as potent inhibitors of actin-based chloroplast motility (Collings et al. 1996; Malec et al. 1996; Foissner et al. 2007), have been used to test the role of chloroplast repositioning as it relates to gm (Tholen et al. 2008; Loreto et al. 2009). 54  To explore what role chloroplast positioning might have in relation to latitudinal variation in mesophyll conductance (gm) of black cottonwood, I examined photosynthetic response to different blue light treatments in six representative genotypes (three northern and three southern). In a first experiment, the effect of increasing blue to red light ratio (in a constant total photosynthetic photon flux density) on gas exchange and gm was tested. It was expected that a higher proportion of blue to red light would negatively affect gm and, consequently, An. I hypothesized that northern genotypes would be more sensitive to blue light, consistent with their greater gm and An. In a second experiment, I assessed the effects of blue light on chloroplast positioning as inferred from changes in the relationship between leaf greenness (i.e., the chlorophyll content index) and actual chlorophyll content. I predicted that chloroplast repositioning would parallel changes in gm and thus be more profoundly obvious in northern genotypes. In a third experiment, I used petiolar-feeding with cytochalasin D to block chloroplast repositioning. I hypothesized that by blocking chloroplast movements, cytochalasin D would also prevent any blue light-induced reduction in gm. Because this hypothesis was ultimately rejected, a fourth and final experiment tested for an effect of blue light on carbonic anhydrase activity as a possible alternative explanation for blue light related reductions in gm. 3.2 Material and methods 3.2.1 Plant material To study the effects of blue light on gas exchange (Experiment 1), cuttings of three northern and three southern P. trichocarpa genotypes (Table 2.1) were taken in late January to early February from the Totem Field common garden, University of British Columbia. Bagged cuttings were kept in a dark cold room at 4°C until they were rooted and planted. Cuttings were grown with supplemental lighting in a greenhouse (minimum PPFD = 500 µmol m-2 s-1) under a 20 hour 55  photoperiod, maximum temperature of 25°C during day and 20°C during night, in 3.78 L pots containing a 70% peat moss and 30% perlite mixture. Measurements began after 6 weeks growth and, by processing one plant per day, lasted for approximately 5 weeks. The experiment had a completely randomized design with four biological replicates per genotype.  3.2.2 Light treatments and photosynthesis measurements On each plant, the youngest fully expanded leaf was chosen to measure photosynthetic variables using a 6400-40 chlorophyll fluorescence chamber (LI-COR Biosciences, Lincoln, LE, USA). Eight blue light-emitting diodes (470 nm), identical to the three already present within the LI-COR 6400 XT chamber head, were added to the light source to increase the maximum amount of blue light (BL) and maintain a total PPFD of 1200 µmol m-2 s-1. The output of the additional LEDs was controlled manually using an external power source. Red light (RL) (630 nm) was provided by the original LI-COR 6400 XT light source (Figure 3.1).  All measurements were conducted in the greenhouse between 09:30 h and 13:30 h. Leaves were dark-adapted for 25 min prior to any gas exchange measurements to obtain the maximum quantum yield of photosystem II. Leaves were then light-adapted for 25 min under each of five BL:RL supply ratios; 0:100, 10:90, 20:80, 40:60, and 60:40. The 10:90 treatment (i.e., 10% BL) represented the control condition. The sample CO2 concentration inside the chamber was 400 µmol mol-1, leaf temperature was 25°C, (VPD) was controlled between 1.4-1.6 kPa, and flow rate was 300 µmol air s-1. The quantum yield of photosystem II (ΦPSII) under actinic light was obtained by application of saturating flashes (>7000 µmol m-2 s-1) as per Genty et al. (1989). Disc punches were taken from leaves and dried at 70°C for 72 hours to calculate leaf mass per area (LMA, mg mm-2).   56       Figure 3.1 Photosynthetic traits were measured under five different blue light to red light ratios (0:100, 10:90, 20:80, 40:60, 60:40) at a constant total PPFD (1200 µmol m-2 s-1).     57  3.2.3 Calculation of gm The “constant J method” was used to estimate gm based on measurements of chlorophyll fluorescence. I have previously shown in black cottonwood that the results of this method and estimation of gm by stable carbon isotope discrimination are well correlated and of comparable magnitude (Chapter 2; Momayyezi & Guy 2017). The electron transport rate (Jflu) was calculated according to Genty et al. (1989):  𝐽flu = ΦPSII × PPFD × α × β      (1) where the fraction of absorbed quanta reaching photosystem II (β) was estimated to equal 0.5 and 0.4 under 10 and 60% BL, respectively (see Appendix A, Figure A.3), by extrapolating to Φ𝐶𝑂2 = 0 the linear relationship between ΦPSII and the corresponding quantum yield for net assimilation rate (Φ𝐶𝑂2) under non-photorespiratory conditions (2% O2) over a range of PPFD from 50 to 1200 µmol m-2 s-1 (Valentini et al. 1995). The leaf absorptance (α) was measured for five replications and averaged under 10% BL (0.858 ± 1.03) and 60% BL (0.811 ± 1.49), using a CI-710 leaf spectrometer (CID BioScience Inc. Camas, WA, USA). gm was then calculated under 10 and 60% BL according to Harley et al. (1992): 𝑔m = 𝐴n/ [𝐶i − (𝛤∗(𝐽flu+8(𝐴n+𝑅d))𝐽flu−4(𝐴n+𝑅d))]      (2) where An is the net assimilation rate, Ci is the CO2 concentration in the intercellular air space, Rd is the non-photorespiratory respiration rate in the light, and Γ* is the chloroplast CO2 photocompensation point (assumed here to equal the intercellular CO2 photocompensation point, Ci*) (Gilbert et al. 2012). As per Momayyezi & Guy (2017), Γ* and Rd were taken to be 1.12 ± 0.37 µmol mol-1 and 43.41 ± 1.25 µmol m-2 s-1, respectively.  58  The ratio of gs/gm was calculated as a measure of the limitation of gm on photosynthesis relative to gs (i.e., values greater than 1 indicate a greater limitation due to gm than to gs). From gm under 10 and 60% BL, the CO2 concentration at sites of carboxylation (Cc) was estimated according to equation 3 (Harley et al. 1992):  𝐶c = 𝐶i −𝐴n𝑔m       (3) 3.2.4 Light response curves To confirm that a PPFD of 1200 µmol m-2 s-1 was saturating irrespective of the light treatment, An and gm were estimated as above but over a range of PPFD from 50 to 1300 µmol m-2 s-1 under 10 and 60% BL (Figure 3.2). The genotype showing the largest differences in An under control and 60% BL was used for this purpose (i.e., SKNP-4).                      3.2.5 CCI measurement and chlorophyll extraction In Experiment 2, Chlorophyll content index (CCI) was measured for all genotypes immediately after 10, 40, and 60% BL treatments (25 min) using a CCM 200 plus (Opti-Science, Inc, Hudson, NH, USA) chlorophyll content meter. Additionally, the most northerly genotype with the largest changes in CCI (TATB-4) was used in a test to confirm that high blue light treatment (60% BL) did not affect the actual leaf chlorophyll content (ACC). Three leaf discs (0.27 cm2 each) were punched from the lamina immediately after irradiation with 10% and 60% BL. Discs were transferred to 10 mL vials containing 6 mL of N,N-dimethylformamide (DMF) as an extractant. Vials were wrapped in aluminum foil to prevent photooxidation and were stored at 4°C until the tissue was bleached (24 hours). Total chlorophyll was determined spectrophotometrically as per Porra et al. (1989). I express CCI relative to ACC as an index of relative chloroplast positioning, lower numbers presumably being associated with more self-shading among chloroplasts. 59                             Figure 3.2 Light response curves for net assimilation rate (An, µmol CO2 m-2 s-1) and mesophyll conductance (gm, mol CO2 m-2 s-1) of the SKNP-4 genotype under 10% (●) or 60% BL (○). Photosynthetic photon flux density (PPFD) was varied from 50 to 1300 µmol m-2 s-1 while CO2 concentration was held constant at 400 µmol mol-1.   60  3.2.6 Inhibition of chloroplast movements  The three youngest fully developed leaves from ramets of TATB-4 were used in five replications to compare the effect of low (10%) and high (60%) blue light on gm with and without cytochalasin D (Experiment 3). A 3 µM cytochalasin D solution in 10 mM dimethyl sulfoxide (DMSO) was prepared by dissolving the actin depolymerizing agent in DMSO and diluting with distilled water. Distilled water alone, and 10 mM DMSO in distilled water, were the two control treatments. Petioles were cut under water and leaves were immediately transferred to 2 mL vials containing either cytochalasin D solution or one of the two controls (Figure 3.3).  After one hour under natural lighting in the greenhouse, leaves were light adapted under 10 and 60% BL prior to gas exchange measurements as detailed above. CCI and ACC were measured after each blue light treatment. 3.2.7 Carbonic anhydrase activity The two youngest fully developed leaves in four replications from two genotypes, one chosen randomly from the northern group (TATB-4) and one chosen randomly from the southern group (LONG-1), were used to test the effect of high blue light on CA activity (Experiment 4). Only two genotypes were used because of technical limitations. From each plant, two petioles were cut under water and placed in 5 mL vials containing distilled water. After 90 min under greenhouse light, one leaf was light adapted under 10% and the other one under 60% BL for 25 min. Gas exchange measurements were obtained as described above. Immediately after measurements, CCI was measured for leaves. Leaf discs from the other side of the mid-rib, adjacent to the area of measurement, were collected using a paper punch to calculate LMA.  Remaining tissue was immediately frozen on dry ice for determination of CA activity as described 61                              Figure 3.3 Cytochalasin D dissolved in DMSO was fed through leaf petioles to inhibit chloroplast movement. Photosynthetic traits were measured at low and high BL under distilled water, DMSO, and cytochalasin D in DMSO.   62  by Wilbur & Anderson (1948). For this purpose, 1.77 cm2 leaf discs (~36 mg fresh weight) were cut with a cork borer from the area used for gas exchange measurements, and ground at liquid nitrogen temperature (-196°C) using disposable polypropylene pestles (length, 8.5 cm) in 1.5 mL polypropylene microcentrifuge tubes. All subsequent steps were at 4°C. After thawing, 70 µL of 40 mM potassium phosphate buffer (pH= 8.3) was added and the homogenate was centrifuged for 15 min at 4500×g. A 10 µL aliquot of supernatant was added to a further 0.5 mL of the buffer solution containing 20 ppm bromothymol blue as a pH indicator. The time required for the pH of the buffer solution to change from 8.3 to 6.3 for control (TControl) and enzyme-containing (TEnzyme) solutions was recorded visually upon the further addition of 0.5 mL of CO2-saturated water. The CO2-saturated water was prepared by bubbling CO2 through distilled water for two hours (also at 4ºC). As a control, 10 µL of buffer solution was used in place of the supernatant. There were four technical replicates per assay. Enzyme activity was calculated as follows: Units CA / mL of supernatant = (𝑇Control − 𝑇Enzyme) × 𝑑𝑓(𝑇Enzyme) × 𝑉      (4) where df is the dilution factor and V is the volume of enzyme extract used. Activities were expressed on a leaf area basis.   3.2.8 Statistics All statistical tests used completely randomized designs. Data were transformed where needed to meet assumptions of normality and equal variance. In Experiment 1, mixed linear models in SAS 9.4 (SAS Institute Inc. NC, USA 2013) were used to compare effects of all five light treatments on An, gs and Ci for the six genotypes independently, without considering latitude as a factor (adjusted P value for number of paired comparisons = 0.005). Then, mixed linear models were  63  used to compare the 60% blue light treatment effects on An, gm, gs, gs/gm and Cc, compared with 10% BL controls, for northern vs. southern genotypes. Both light treatment (T) and latitude (L) were considered fixed factors and genotypes were nested within latitude; because treatments were paired, replicates (plants) were nested within genotypes. Pairwise mean comparisons were used to test treatment effects within and between northern and southern latitudes (adjusted P value for number of paired comparisons according to Bonferroni correction was 0.008). A t-test was used to compare LMA in northern vs. southern genotypes. For Experiment 2, a similar mixed linear model to Experiment 1 was used to compare CCI under 10, 40 and 60% BL within and between northern and southern latitudes. Pairwise mean comparisons were used to test treatment effects in northern vs. southern latitudes (adjusted P value for number of paired comparisons according to Bonferroni correction was 0.003). A two-way ANOVA (P < 0.05) was used to compare means for CCI, ACC and CCI/ACC ratio in TATB-4 using GraphPad Prism 6 software (GraphPad Software, Inc. CA, USA). For Experiment 3, the effects of cytochalasin D on An, gm, gs, Ci, Cc, CCI, ACC, and CCI/ACC were analyzed using mixed linear models with two fixed effects (solution type [S], and light treatment [T]) in three and two levels, respectively (adjusted P value for number of paired comparisons = 0.003). For Experiment 4, a t-test with data paired by plant was used to analyze the effect of high blue light on CA activity, An, gm, gs, Ci, Cc and CCI (P < 0.05). 3.3 Results 3.3.1 Blue light effect on gm Photosynthetic rates were generally higher in the northern genotypes than in the southern    64  genotypes (Figure 3.4A). For example, under control (10% BL) conditions, An was 21% higher in the northern genotypes (P < 0.008) (Table 3.1). In contrast, LMA was not significantly different (0.042 ± 0.001 mg mm-2 vs. 0.037 ± 0.001 mg mm-2 in northern versus southern genotypes, respectively). Latitudinal differences in An were less pronounced at higher relative fluxes of blue light because northern genotypes were relatively more sensitive than southern genotypes (T × L, P < 0.001) (Table 3.1). Like An, gs was significantly higher in the northern genotypes than in the southern genotypes at 10% BL (P < 0.008), but not at 60% BL (Table 3.1).  Across all genotypes combined, An was 8.9% higher under 10% BL relative to 0% BL (P < 0.001), and 16.9% higher relative to 60% BL (P < 0.001). Statistical power was insufficient to detect these differences in all pairwise comparisons within individual genotypes (Figure 3.4A), but as the proportion of blue light was increased, An went down such that at 60% BL, four out of the six genotypes had significantly lower An. Similarly, across all genotypes combined, gs was 16.4% higher under 10% BL relative to 0% BL (P < 0.001), and 15.3% higher relative to 60% BL (P < 0.001), but significantly so at the genotypic level only in the northern genotypes SKNP-4 and TAKA-2 (Figure 3.4B). Intercellular air space CO2 concentration was very consistent among genotypes and between light treatments, the only significant difference being between low (0 and 10%) and high (60%) blue light in TAKA-2 (Figure 3.4C).   Because β was affected by light quality but was not estimated for 0, 20 and 40% BL, gm could only be properly calculated for the control (10%) and high (60%) blue light treatments. On average, the northern genotypes had consistently higher gm than the southern genotypes under 10% BL (P < 0.008) (Table 3.1). Northern genotypes were both absolutely and relatively more sensitive than southern genotypes to higher supply ratios of blue light. Mesophyll conductance in both northern    65                                           Figure 3.4 Mean values (± SE, n = 4) for A, net assimilation rate (An, µmol CO2 m-2 s-1); B, stomatal conductance (gs, mol H2O m-2 s-1); C, intercellular air space CO2 concentration (Ci, µmol mol-1) of six Populus trichocarpa genotypes under five blue:red light supply ratios. For each genotype, from left (white bar) to right (striped bar), the proportion of blue light is 0, 10, 20, 40 and 60% BL. Different letters show significant differences between control (10% BL) and other treatments for each genotype at P < 0.005. 66  Table 3.1 Physiological traits for northern vs. southern genotypes under two different blue light treatments (10 and 60% BL). Different letters show significant differences within and between latitudes (P < 0.008) within a column (± SE, n = 4).  % blue An gm gs gs/gm Cc north 10 22.58 ± 0.80 a 0.244 ± 0.027 a 0.33 ± 0.013 a 1.49 ± 0.13 a 176.37 ± 6.52 a 60 18.41 ± 0.73 bc 0.153 ± 0.016 bc 0.26 ± 0.017 b 1.82 ± 0.11 b 146.45 ± 5.80 bc south 10 17.76 ± 0.52 b 0.135 ± 0.005 b 0.27 ± 0.020 b 2.00 ± 0.14 ab 144.54 ± 5.43 b 60 15.53 ± 0.55 c 0.107 ± 0.006 c 0.23 ± 0.016 b 2.26 ± 0.21 ab 130.87 ± 5.70 c An, net assimilation rate (µmol CO2 m-2 s-1); gm, mesophyll conductance (mol CO2 m-2 s-1); gs, stomatal conductance (mol H2O m-2 s-1); gs/gm (stomatal conductance over mesophyll conductance ratio); Cc, CO2 concentration at sites of carboxylation (µmol mol-1).    67  and southern genotypes was decreased under 60% BL compared to the 10% BL control (P < 0.008) (Table 3.1). The percent reduction in gm from control levels was significantly greater (P < 0.05) for the northern genotypes than for the southern genotypes (37.3% vs. 20.7%, respectively). In every situation the gs/gm ratio was always greater than 1, indicating that gm presented the greater limitation on photosynthesis. The effects of blue light on gm were larger than they were on gs in all genotypes. However, gs/gm was significantly increased under high blue light only for northern genotypes (P = 0.003) (Table 3.1), to the point where differences in relative limitation between northern and southern genotypes disappeared at the highest blue light supply ratio. High blue light significantly decreased Cc in both northern and southern genotypes by 16.9% and 9.4%, respectively, compared to the control (P < 0.008) (Table 3.1), but there was no latitude by treatment interaction effect in this regard (P = 0.167).  3.3.2 Blue light effect on chloroplast positioning  In Experiment 2, and reflecting their higher photosynthetic capacity, the northern genotypes had two-fold greater CCI compared to southern ones (P < 0.003) (Table 3.2). Exposure to 60% BL significantly reduced CCI across (P = 0.0013) and within (P < 0.008) all genotypes, but most particularly in the three northern accessions (by up to 31%). The 40% BL treatment significantly reduced CCI only across genotypes (P = 0.015). I noticed that CCI recovered fully within 30 min of exposure to high blue light (not presented). In contrast to CCI, ACC was unaffected during exposure to 60% BL (Table 3.3), as measured in a genotype chosen for its large transient changes in CCI (TATB-4). Consequently, the relationship between CCI and chlorophyll content (CCI/ACC) was found to be blue-light dependent (P < 0.05).   68  Table 3.2 Effects of blue light treatment on chlorophyll content index (CCI) for northern vs. southern Populus trichocarpa genotypes. Different letters show significant differences (P < 0.003) for mean values (± SE, n = 4).   10% BL 40% BL 60% BL north 43.18 ± 2.83 a 35.49 ± 2.03 ab 29.70 ± 1.89 b south 21.15 ± 0.56 c 18.47 ± 0.69 cd 17.56 ± 0.58 d             69  Table 3.3 Test for lack of effect of the blue light:red light supply ratio on chlorophyll content using leaves of the TATB-4 genotype. Actual chlorophyll content (ACC), chlorophyll content index (CCI), and CCI/ACC ratio immediately after 25 min exposure to 10% and 60% BL are presented. Different letters show significant differences between light treatments for mean values (± SE, n = 4) (P < 0.05). % BL ACC (µg/cm2) CCI CCI/ACC 10 61.30 ± 1.03 a 54.03 ± 1.42 a 0.88 ± 0.02 a 60 64.56 ± 0.93 a 43.92 ± 0.95 b 0.68 ± 0.01 b    70  3.3.3 Effect of cytochalasin D on chloroplast repositioning and changes in gm In Experiment 3, there were no differences between distilled water and DMSO controls (Table 3.4). Furthermore, plant response to high blue light was consistent with Experiments 1 and 2 in all measured variables. Pretreatment with cytochalasin D, however, significantly decreased An, gm and Cc in 10% BL controls (P < 0.003). There were some interaction effects between cytochalasin D and light treatment. Subsequent exposure to 60% BL had no further impact on An but did cause a further reduction in gm to levels that were similar to distilled water and DMSO controls (S × T, P < 0.0001). Exposure to 60% BL reduced Cc to a similar value in all leaves (P < 0.0001) and without interaction (S × T, P = 0.837). Leaves treated with cytochalasin D had reduced CCI relative to DMSO controls but not distilled water controls at 10% BL, and not at 60% BL (S × T, P = 0.002). Actual chlorophyll content was also reduced by cytochalasin D relative to distilled water and DMSO controls, but significantly so only at 60% BL (P = 0.0009). There was no net effect of cytochalasin D on CCI/ACC under 10% BL, and, in sharp contrast to distilled water and DMSO controls, there was no change in CCI/ACC upon exposure to high blue light (S × B, P = 0.547).  3.3.4 Blue light effect on CA activity In Experiment 4 (Table 3.5), high blue light significantly reduced CA activity by 19.8% (0.24 units cm-2 ± 0.05 SE) compared to the control treatment (P = 0.003). Effects on An, gm, Cc, CCI and Ci were all consistent with previous experiments. 3.4 Discussion After entering the leaf through stomatal pores, ambient CO2 molecules transiting to the site of carboxylation need to overcome a series of resistances in both gas and liquid phases. Structural 71  Table 3.4 Effect of cytochalasin D on An, gm, gs, Ci, Cc, CCI, ACC, and CCI/ACC in the TATB-4 genotype tested under 10 and 60% BL in distilled water, DMSO, and DMSO + cytochalasin D. Different letters show significant differences between mean values within each row (± SE, n = 5) (P < 0.003).   distilled water DMSO cytochalasin D + DMSO 10% BL 60% BL 10% BL 60% BL 10% BL 60% BL An 16.94 ± 0.25 a 14.71 ± 0.79 ab 17.00 ± 0.54 a 14.26 ± 0.43 b 12.95 ± 0.58 b 13.05 ± 0.71 b gm 0.298 ± 0.037 a 0.184 ± 0.047 bc 0.303 ± 0.046 a 0.165 ± 0.046 bc 0.137 ± 0.010 b 0.106 ± 0.008 c gs 0.25 ± 0.01 a 0.24 ± 0.02 a 0.22 ± 0.02 a 0.22 ± 0.02 a 0.20 ± 0.02 a 0.20 ± 0.02 a Ci 279.00 ± 6.79 a 285.68 ± 8.76 a 263.00 ± 10.41 a 279.01 ± 10.53 a 279.85 ± 11.06 a 276.37 ± 11.02 a Cc 219.29 ± 12.02 a 189.74 ± 11.68 bc 202.97 ± 11.34 ad 175.10 ± 9.26 bc 183.11 ± 11.76 bd 151.68 ± 8.53 c CCI 37.91 ± 0.31 ac 28.54 ± 0.16 b 39.57 ± 0.33 a 28.89 ± 0.65 b 32.37 ± 0.39 bc 31.25 ± 0.89 b ACC 49.13 ± 1.77 ab 49.71 ± 2.40 a 49.46 ± 0.79 a 50.05 ± 1.02 a 44.09 ± 2.43 ab 41.05 ± 2.05 b CCI/ACC 0.77 ± 0.08 a 0.58 ± 0.07 b 0.80 ± 0.06 a 0.58 ± 0.11 b 0.74 ± 0.09 a 0.76 ± 0.09 a An, net assimilation rate (µmol CO2 m-2 s-1); gm, mesophyll conductance (mol CO2 m-2 s-1); gs, stomatal conductance (mol H2O m-2 s-1); Ci, intercellular air space CO2 concentration (µmol mol-1); Cc, CO2 concentration at sites of carboxylation (µmol mol-1); CCI, chlorophyll content index; ACC, actual chlorophyll content (µg/cm2); CCI/ACC, chlorophyll content index, actual chlorophyll content ratio.  72  Table 3.5 Effect of 60% BL on CA activity, An, gm, gs, Ci, Cc and CCI in. Different letters show significant differences between mean values (± SE, n = 4) within each row (P < 0.05). Genotype was not a factor in this experiment, so data presented here are means across both TATB-4 and LONG-1 combined.   distilled water 10% BL 60% BL CA activity  1.16 ± 0.20 a 0.93 ± 0.13 b An  17.54 ± 0.84 a 15.93 ± 0.69 b gm  0.202 ± 0.027 a 0.145 ± 0.018 b gs  0.298 ± 0.012 a 0.283 ± 0.013 a Ci  292.30 ± 3.50 a 294.52 ± 5.21 a Cc  197.97 ± 7.21 a 175.66 ± 7.94 b CCI  34.11 ± 2.96 a 26.52 ± 1.33 b CA activity, carbonic anhydrase activity (units cm-2); An, net assimilation rate (µmol CO2 m-2 s-1); gm, mesophyll conductance (mol CO2 m-2 s-1); gs, stomatal conductance (mol H2O m-2 s-1); Ci, intercellular air space CO2 concentration (µmol mol-1); Cc, CO2 concentration at sites of carboxylation (µmol mol-1); CCI, chlorophyll content index.  73  and biochemical components of mesophyll cells and their interaction regulate CO2 conductance. Consistent with results presented by Momayyezi & Guy (2017), northern P. trichocarpa genotypes showed higher An, gm and gs in this study. In Momayyezi & Guy (2017), genotypic variation in gm was shown to be associated with carbonic anhydrase activity. Chloroplast movement in response to light quality can also affect gm and limit photosynthesis (Flexas et al. 2008; Flexas et al. 2012). In the present chapter (Table 3.1), increasing the blue to red light ratio from 10:90 to 60:40 negatively impacted An, gm and Cc in both northern and southern genotypes of black cottonwood, and, bearing out the first hypothesis, more so in the northern genotypes. In addition, gs was significantly reduced in the northern genotypes but not the southern genotypes. Consistent with other reports (Mansfield & Meidner 1966; Suetsugu et al. 2014) there was also a general tendency towards increased gs from 0 to 10% BL, significant here in two northern genotypes. Low amounts of blue light are known to induce stomatal opening by exciting photoreceptors located in chloroplast membranes of guard cells (Sharkey & Raschke 1981; Zeiger & Field 1982). Given their intrinsically higher gm, it was not surprising to detect a greater absolute reduction in gm in northern genotypes, but there was also a greater per cent reduction in northern genotypes (37%) relative to southern genotypes (21%). Similarly (Table 3.2), the higher blue light treatments (40 and 60% BL), resulted in significantly higher percent reductions in CCI (18 and 31%, respectively) in northern genotypes than in southern genotypes (13 and 17%). These reversible  changes in chlorophyll content index occurred without any change in actual chlorophyll content (Table 3.3), consistent with changes in chloroplast positioning. The implication is that high blue light reduced the CCI by reducing the effectiveness of green light reflection. Measurements of leaf transmittance show that more visible light passes through black cottonwood leaves under these  74  conditions (not presented). In contrast, Higa & Wada (2016) observed little or no change in chloroplast repositioning under either 3 µmol m-2 s-1 or 20-50 µmol m-2 s-1 blue light in climbing plants, but these flux densities were very low. More consistent with the present study, Nauš et al. (2010) also found remarkable and reversible decreases in CCI when tobacco leaves were exposed to high blue light (340 µmol m-2 s-1), particularly in younger leaves (35% decrease in CCI). Blue light perception by phototropins stimulates directional chloroplast rearrangement via the cytoskeletal network (Banaś et al. 2012). At low irradiance, chloroplasts move more towards the periclinal (face) position to absorb the maximum amount of light, whereas under high irradiance they escape to the anticlinal (profile) position as a photoprotective response to excess light energy (Kagawa & Wada 1999; Kasahara et al. 2002).  Tholen et al. (2008) demonstrated that short term exposure of Arabidopsis leaves to 1200 µmol m-2 s-1 of white light, in contrast to blue-filtered light, significantly reduced the chloroplast surface area exposed to intercellular air space by changing the chloroplast position from face to profile. This change in positioning was accompanied by a decrease in An and gm, the latter estimated by two methods (isotope discrimination and A-Ci curve fitting). Using the variable J chlorophyll fluorescence method, Loreto et al. (2009) observed a reduction in An and gm in N. tabacum and Platanus orientalis within 3 min of exposure to 80% BL in a total PPFD of 300 µmol m-2 s-1. Paradoxically, however, they found no effect on Cc and Ci and so concluded that the reduction in photosynthesis was related to photochemical limitations and not CO2 conductance. In contrast, in Populus × canadensis, PPFD-saturated An, gs and gm (by the variable J chlorophyll fluorescence method) decreased by 30, 46, and 25% under pure blue light compared to white light, and Ci began to increase at PPFD > 1200 µmol m-2 s-1 (Pallozzi et al. 2013). In the present study, high blue light  75  (i.e., three times higher than Loreto et al. [2009], but not as extreme as the higher levels used by Pallozzi et al. [2013]) resulted in reductions in gm that reduced Cc by 17 and 9% in northern and southern genotypes, respectively (Table 3.1). However, blue light had no significant effect on Ci (Figure 3.4C). Because chloroplast movements normally take longer than a few minutes, Loreto et al. (2009) concluded that the rapid reduction in gm they observed was unrelated to repositioning. Furthermore, when treated with cytochalasin D to inhibit movement (not directly shown in that study), there was still a rapid effect of blue light on gm. Although time courses for blue light effects on CCI/ACC and gm were not constructed in the present study, these two responses were similarly separable when black cottonwood leaves were treated with cytochalasin D. These data support the Loreto et al. (2009) proposition that gm reduction under blue light is unlikely to result from chloroplast movements alone. In this study under 10% BL, cytochalasin D decreased An and gm compared to both controls, and Cc relative to the distilled water control only (Table 3.4). These effects may relate to the disruption of chloroplast movements. The risk of photodamage increases under high blue light if chloroplast movements are stopped (Kasahara et al. 2002). Loreto et al. (2009) showed that treatment with cytochalasin D promotes photoinhibition (as indicated by reductions in quantum efficiency) in the presence of high blue light (2200 µmol m-2 s-1). Tholen et al. (2008) reported a significant increase in gm and the exposure of chloroplast surface area to adjacent intercellular air space under white light (not filtered for blue light) when Arabidopsis chloroplasts were fixed by cytochalasin D in the face position. Besides inhibition of chloroplast movements, it is not evident if cytochalasin D has any direct effect on photosynthesis, but cytochalasin E is thought to possibly have some impact on light harvesting by causing a decay in the fluorescence emission spectrum over time (Kshirsagar 76  et al. 2001). Cytochalasin D also has negative effects on other actin-based movements (e.g., other organelles; Williamson 1993) that might ultimately influence photosynthesis.    If blue light has effects on gm independent from chloroplast movements, then it may act through changes in either aquaporin regulation or carbonic anhydrase activity. The effect of high blue light on aquaporins is not known but, as shown in Table 3.5, exposure to 60% BL elicited a significant reduction in CA activity by ~20%. According to the model of Tholen & Zhu (2011), a reduction in stromal CA activity of this magnitude should have little or no effect on gm and An. However, as shown by Momayyezi & Guy (2017), carbonic anhydrase activity in these same black cottonwood genotypes is strongly correlated with gm under both natural and inhibitor-induced treatments. Inhibition of CA activity by 43% reduced gm and An by 48% and 27%, respectively (Momayyezi & Guy 2017). Therefore, the localization of specific CA activities and/or interaction with aquaporins might also account for some portion of the blue light effect on gm.  Irrespective of the mechanism of the blue light effect on gm, the present work uncovers differences in gm in response to blue light as a function of latitude of origin in black cottonwood. There are similar but less pronounced patterns in gs. Momayyezi & Guy (2017) reported that gs and gm were more-or-less equally limiting to photosynthesis in this species. In the present study, gm was more limiting than gs under all conditions, but, as indicated by gs/gm (Table 3.1), it became significantly more limiting under high blue light only in northern genotypes, presumably because they had much higher gm in the first place.  3.5 Conclusion The greater reduction in gm in response to high blue light in northern compared to southern P. trichocarpa genotypes is commensurate with a greater reduction in CCI (and in CCI/ACC). This 77  suggests that chloroplast movements can directly affect gm by changing how chloroplasts access cell wall perimeter positions adjacent to intercellular air space. Treatment with cytochalasin D, however, fully disabled all changes in CCI/ACC but did not eliminate the effects of high blue light on gm. Therefore, as suggested by Loreto et al. (2009), blue light effects on gm would seem to be at least partially independent of chloroplast repositioning. As shown here, the modulation of gm by blue light may be associated with changes in CA activity.   78  Chapter 4: Effect of mercuric chloride on mesophyll conductance in diverse Populus trichocarpa Torr. & Gray genotypes  4.1 Introduction Populus trichocarpa (black cottonwood) covers a wide coastal area from southern California (31° latitude) to the southeast of Alaska (62° latitude) and inland in British Columbia to the west side of the Rocky Mountains in western Alberta. At the provenance level, net assimilation rate and stomatal conductance are reported to be positively intercorrelated with latitude in black cottonwood (Gornall & Guy 2007; McKown 2014a). In black cottonwood, mesophyll conductance, the inverse of resistance, to CO2 diffusion increases with latitude (Chapter 2 and 3; Momayyezi & Guy 2017).  To reach active sites of carboxylation at rubisco, CO2 diffusion must overcome a series of gas- and liquid-phase resistances from the atmosphere to the stromal space inside chloroplasts (Flexas et al. 2008). To mediate gm rapidly, diffusion through the liquid phase, which includes cell wall, membrane and cytoplasmic components, etc., may be differentially affected by carbonic anhydrase activity, chloroplast positioning, and the transport capacity of aquaporins (Flexas et al. 2008; Evans et al. 2009; Flexas et al. 2012). In Chapter 2, it was shown that northern black cottonwood genotypes have significantly greater gm, which is in turn associated with a greater CA activity (Momayyezi & Guy 2017). The relationship between CA activity and gm was the same whether variation was natural (i.e., genotypic) or induced by titrating CA with the inhibitor acetazolamide. Commensurate with their higher gm, the same northern genotypes show a greater down-regulation of gm in response to high blue light, in parallel with changes in their chlorophyll content index (Chapter 3). Although an effect on gm via chloroplast repositioning was implicated, gm was still  79  down-regulated by blue light even when such movements were blocked by treatment with cytochalasin D. It was shown, however, that CA activity was reduced ~20% by high blue light, thus providing a possible alternative mechanism for the blue light effect on gm. In this chapter I use another inhibitor, mercuric chloride, to investigate the possibility that genotypic variation in gm may also be related to differences in aquaporins (AQPs).  Aquaporins are integral proteins that provide channels for the movement of water molecules and sometimes neutral solutes (i.e., silicic acid) and gases (CO2, NH3) (Maurel et al. 2008) across biomembranes. They occur in five main subfamilies in eudicot plants (Anderberg et al. 2012). The plasma membrane intrinsic proteins (PIPs) constitute one subfamily and are known to promote CO2 diffusion, in addition to water movement (Uehlein et al. 2003). The PIP subfamily consists of 15 members in cottonwood, which is more than Arabidopsis (13), rice (11), barley (10), and maize (13) (Chaumont et al. 2001; Johanson et al. 2001; Sakurai et al. 2005; Katsuhara & Hanba 2008; Gupta & Sankararamakrishnan 2009; Almeida-Rodriguez et al. 2010). Cottonwood also has more overall major intrinsic proteins (MIPs) (55 genes, aquaporins and aquaglyceroporins) with an additional subfamily (XIPs, functionally uncharacterized and found in a few eudicot genera; e.g., Populus) compared to many other studied species (Tuskan et al. 2006; Gupta & Sankararamakrishnan 2009; Cohen et al. 2013). Water balance and redistribution under drought in P. balsamifera and P. simonii × balsamifera (Almeida-Rodriguez et al. 2010), and hydraulic conductance recovery in P. trichocarpa (Laur & Hacke 2014), are reported to be linked with the expression level of AQPs, in particular, the PIPs. The importance of AQPs in regulating gm is clear from studies of transgenic N. tabacum over- or under-expressing plasma membrane aquaporin 1 (NtAQP1) (Uehlein et al. 2003; Flexas et al. 2006; 80  Uehlein et al. 2008). Transgenic lines of P. tremula × alba, lacking PIP1 showed greater mesophyll resistance compared with wild-type plants (Secchi & Zwieniecki 2014). Although reduced PIP1 expression decreases gm it has no major impact on photosynthesis and gs (Secchi & Zwieniecki 2014). In addition to work on genetically modified plants, the roles of AQPs in vivo have been studied in experiments with inhibitors to block their functioning. Mercuric chloride II (HgCl2) selectively binds cysteine domains in aquaporin proteins (Murata et al. 2000; Savage & Stroud 2007) and interrupts the transfer of water through the channel pores (Barone et al. 1997; Tazawa et al. 1997). Similarly, as shown by the pioneering work of Terashima & Ono (2002), HgCl2 also disrupts CO2 transfer through AQPs and thereby reduces gm. Mercuric chloride is, however, not without other biochemical effects. Indeed, mercury compounds may also directly impact CO2 diffusion by blocking the active site (histidine) of carbonic anhydrase (Blundell & Jenkins 1977). An inhibitory effect of HgCl2 on CA in mammalian cells has been reported (Yang et al. 2000; Blank & Ehmke 2003). I conducted three experiments with HgCl2 to explore the potential involvement of AQPs in determining variation in gm in black cottonwood. In the first experiment, I attempted to block AQPs with HgCl2 in six representative genotypes (three northern and three southern). It was hypothesized that photosynthesis in northern genotypes with intrinsically higher gm would be more susceptible to HgCl2 treatment than in southern genotypes with lower gm. In a second experiment limited to just two genotypes, I used HgCl2 to rule out or confirm concurrent effects on CA activity. Finally, in the last experiment, I tested the combined effects of blue light and HgCl2 on gm because these two agents may or may not affect different components of the CO2 diffusion pathway (i.e., chloroplast repositioning versus AQP and/or CA activity, respectively). I expected the effects of blue light and HgCl2 to be fully additive if their targets are completely independent.   81  4.2 Material and methods 4.2.1 Plant material Branch cuttings of six representative P. trichocarpa genotypes, three northern (SKNP-4, TAKA-2 and TATB-4) and three southern (HALS-2, PITS-3 and LONG-1) (Table 2.1), were taken in late January to early February from the Totem Field common garden at the University of British Columbia (UBC). Bagged cuttings were kept in a dark cold room at 4°C until they were recut into ~10 cm lengths with two lateral buds for rooting and planting (Pointeau & Guy 2014). Cuttings were grown with supplemental lighting in a greenhouse (minimum PPFD = 500 µmol m-2 s-1) under a 20 hour photoperiod, maximum temperature of 25°C during day and 20°C during night, in 3.78 L pots containing a 70% peat moss and 30% perlite mixture.  4.2.2 Treatments and photosynthesis measurements The two youngest fully expanded leaves per plant were used to measure An, gs and the intercellular Ci using a LI-COR 6400 XT gas exchange system fitted with a 6400-40 chlorophyll fluorescence chamber. In Experiment 1, one leaf was treated with aqueous mercuric chloride II (HgCl2) to inhibit AQPs, and the other used as a control. Control and HgCl2 treatments, and order of measurement, were randomly assigned to the leaves to eliminate effects of any possible age or time dependent errors. Each leaf was cut at the petiole base under distilled water and placed in a 5 mL vial filled with either distilled water (control) or 1.5 mM aqueous HgCl2 solution. After 90 minutes, leaves were placed inside the LI-COR 6400 XT cuvette to equilibrate to chamber conditions under light for 25 minutes prior to gas exchange measurements. All routine measurements were done in triplicate under 10% blue to 90% red light proportion at a total photosynthetic photon flux density (PPFD) of 1200 µmol m-2 s-1, flow rate of 300 µmol air s-1 and 82  vapour pressure deficit between 1.4-1.6 kPa. Leaf temperature was maintained at 25°C and the ambient chamber CO2 concentration was set to 400 µmol mol-1. The control leaf was dark adapted for 20 minutes prior to all other measurements to obtain the maximum quantum yield of photosystem II. Later, during gas exchange measurements, the (ΦPSII) under actinic light was obtained by application of saturating flashes (>7000 µmol m-2 s-1) as per Genty et al. (1989).  Chlorophyll content index (unit-less) was measured for all genotypes immediately after gas exchange measurements using a CCM 200 plus (Opti-Science, Inc, Hudson, NH, USA) chlorophyll content meter. 4.2.4 Carbonic anhydrase activity In Experiment 2, the two youngest fully developed leaves, in four replications from each of two genotypes, were randomly assigned to treatments designed to test the effect of HgCl2 on CA activity. Only two genotypes were used because of technical limitations; namely TATB-4 and LONG-1 (to be consistent with Chapter 3). Petioles were cut under water and placed in 5 mL vials containing either distilled water (control) or 1.5 mM HgCl2. After 90 minutes under greenhouse light, both leaves were light adapted under 10% blue light for 25 minutes. The distilled water treatment was used as the control for both high blue light and HgCl2 effects on CA activity. Gas exchange data and CCI were obtained as described above. Leaf discs from the other side of the mid-rib, adjacent to the area of measurement, were collected using a paper puncher and dried at 70°C for 72 hours to determine leaf mass per area (LMA, mg mm-2). Remaining tissue was immediately frozen on dry ice for determination of CA activity as described by Wilbur & Anderson (1948). For this purpose, 1.77 cm2 leaf discs (~36 mg fresh weight) were cut with a cork borer from the area used for gas exchange measurements, and ground at liquid 83  nitrogen temperature (-196°C) using disposable polypropylene pestles (length, 8.5 cm) in 1.5 mL polypropylene microcentrifuge tubes. All subsequent steps were at 4°C. After thawing, 70 µL of 40 mM potassium phosphate buffer (pH = 8.3) was added and the homogenate was centrifuged for 15 min at 4500×g. A 10 µL aliquot of supernatant was added to a further 0.5 mL of the buffer solution containing 20 ppm bromothymol blue as a pH indicator. The time required for the pH of the buffer solution to change from 8.3 to 6.3 for control (TControl) and enzyme-containing (TEnzyme) solutions was recorded visually upon the further addition of 0.5 mL of CO2-saturated water. The CO2-saturated water was prepared by bubbling CO2 through distilled water for two hours (also at 4ºC). As a control, 10 µL of buffer solution was used in place of the supernatant. There were four technical replicates per assay. Enzyme activity was calculated as follows: Units CA / mL of supernatant = (𝑇Control − 𝑇Enzyme) × 𝑑𝑓(𝑇Enzyme) × 𝑉      (1) where df is the dilution factor and V is the volume of enzyme extract used. Activities were expressed on a leaf area basis. 4.2.5 Combined high blue light and mercuric chloride treatment In Experiment 3, the four youngest fully developed leaves from TATB-4 and LONG-1 were used in four replications to test the combined effects of HgCl2 and high blue light in a factorial experiment. Petioles were cut under water and placed in 5 mL vials containing either distilled water or 1.5 mM HgCl2. After 90 min under natural light in the greenhouse, leaves were adapted to their respective light treatments, 10% or 60% BL in a total PPFD of 1200 µmol m-2 s-1 for 25 min prior to gas exchange measurements as detailed above.84  4.2.6 Calculation of gm The “constant J method” was used to estimate gm based on measurements of chlorophyll fluorescence. I have previously shown in black cottonwood that the results of this method and estimation of gm by stable carbon isotope discrimination are well correlated and of comparable magnitude (Momayyezi & Guy 2017). The electron transport rate (Jflu) was calculated according to Genty et al. (1989): 𝐽flu = ΦPSII × PPFD × α × β      (2) where the fraction of absorbed quanta reaching photosystem II (β) was estimated to equal 0.5 under 10% BL. The leaf absorptance, α, was taken to be 0.827 based on the average value (± 0.03) as determined by Momayyezi & Guy (2017). In Experiment 3 only, β and α, both were previously measured for black cottonwood genotypes under 10% BL (β = 0.5; α = 0.858 ± 1.03) and 60% BL (β = 0.4; α = 0.811 ± 1.49) as determined in Chapter 3. gm was then calculated according to Harley et al. (1992): 𝑔m = 𝐴n/ [𝐶i − (𝛤∗(𝐽flu+8(𝐴n+𝑅d))𝐽flu−4(𝐴n+𝑅d))]      (3) where An, and Ci are net assimilation rate and CO2 concentration in the intercellular air space, Rd is the non-photorespiratory respiration rate in the light, and Γ* is the chloroplast CO2 photocompensation point (assumed here to equal the intercellular CO2 photocompensation point). As determined in Chapter 2 (Momayyezi & Guy 2017), Γ* and Rd were taken to be 1.12 ± 0.37 µmol mol-1 and 43.41 ± 1.25 µmol m-2 s-1, respectively. The ratio gs/gm was calculated as a measure of the limitation of gm on photosynthesis relative to gs (i.e., values greater than 1 indicate a greater limitation due to gm than to gs). From gm, the CO2 85  concentration at sites of carboxylation (Cc) was estimated according to equation 3 (Harley et al. 1992):  𝐶c = 𝐶i −𝐴n𝑔m       (4) 4.2.7 Statistics  For Experiment 1, mixed linear models in SAS 9.4 (SAS Institute Inc. NC, USA 2013) were used to compare the effect of HgCl2 treatment on An, gs, gm and Cc for the six genotypes independently, without considering latitude as a factor (adjusted P value for number of paired comparisons = 0.05). Then, mixed linear models were used to compare the HgCl2 treatment effect on An, gm, gs, gs/gm, Ci and Cc, compared with distilled water controls, for northern and southern genotypes within each latitude and for northern vs. southern genotypes. Both solution treatment (T) and latitude (L) were considered fixed factors and genotypes were nested within latitude. Because treatments were paired, replicates (plants) were nested within genotypes. Pairwise mean comparisons were used to test treatment effects within and between northern and southern latitudes (the adjusted P value for number of paired comparisons according to the Bonferroni correction was 0.008). Similar mixed linear models were used to compare absolute and percentage reductions in An, gm, gs and Cc under HgCl2 relative to the control (P value = 0.05). A t-test was used to compare LMA in northern vs. southern genotypes. For Experiment 2, t-tests with data paired by plant were used to analyze the effect of HgCl2 on CA activity, An, gm, gs, gs/gm, Ci, Cc and CCI (P < 0.05). For Experiment 3, the combined effects of HgCl2 and blue light, both as fixed effects in two levels with data blocked by plant (random effect), on An, gm, gs, gs/gm, Ci and Cc, were analyzed using mixed models (adjusted P value for number of paired comparisons = 0.008). 86  Logarithm, square root, or squared transformations were performed to meet normality and equal variance assumptions where needed.  4.3 Results 4.3.1 Mercuric chloride effect on gm In Experiment 1, and in contrast to Chapters 2 and 3, there was a small (14.4%) but significant difference in LMA between northern (0.0438 mg mm-2 ± 0.0009) and southern (0.0375 mg mm-2 ± 0.0008) genotypes (P = 0.0005). There was a greater (24.9%) difference in An between northern and southern genotypes, but only under the control (distilled water) condition (P < 0.008). Across all genotypes combined, the HgCl2 treatment reduced An by 26.3% relative to the control (P < 0.0001). The differences in pairwise comparisons were significant within each genotype (P < 0.05) (Figure 4.1). However, northern genotypes were more sensitive to HgCl2 (T × L, P < 0.0001) (Table 4.1) with greater absolute and relative reductions in An compared to southern genotypes (P < 0.05) (Table 4.2). Consequently, there was no latitudinal difference in An when plants were treated with HgCl2 (Table 4.1). Mercuric chloride significantly decreased gm and gs by 51.7% and 21.1%, respectively, across all genotypes combined (P < 0.0001). Considered separately, mercuric chloride significantly (P < 0.05) decreased gm in all individual genotypes (Figure 4.2), and gs in all genotypes except the PITS-3 genotype (Figure 4.3). Similar to An, gm and gs were significantly greater in northern genotypes (48.4 and 15.2%, respectively) than southern genotypes (P < 0.008) (Table 4.1), but the differences were not significant under HgCl2. Both absolute and relative reductions in gm and gs were significantly greater in northern genotypes than southern genotypes (T × L, P < 0.0001) (Table 4.2).   87  HALS-2PITS-3LONG-1SKNP-4TAKA-2TATB-401 02 03 0G e n o ty p eAn (µmol CO2 m-2 s-1)aaaaaabbbb b bS o u th N o r th Figure 4.1 Mean values (± SE) for net assimilation rate (An, µmol CO2 m-2 s-1) of six Populus trichocarpa genotypes under two treatments (distilled water in black, and HgCl2 in grey). Different letters show significant differences between distilled water (control), and HgCl2 treatments for each genotype at P < 0.05.   88  Table 4.1 An, gm, gs, gs/gm, Ci and Cc in northern vs. southern genotypes under control and HgCl2 treatments. For each column, different letters show significant differences for mean values ± SE at P < 0.008.  treatment An gm gs gs/gm Ci Cc north distilled water 23.90 ± 0.62 a 0.31 ± 0.03 a 0.33 ± 0.01 a 1.17 ± 0.11 a 267.66 ± 4.08 a 183.82 ± 5.22 a HgCl2 13.57 ± 0.47 bd 0.13 ± 0.01 bc 0.23 ± 0.01 bc 1.98 ± 0.22 bc 281.46 ± 5.32 bc 168.38 ± 5.24 bc south distilled water 17.70 ± 0.52 c 0.16 ± 0.01 b 0.28 ± 0.01 b 1.82 ± 0.19 ab 285.16 ± 6.46 ab 172.10 ± 5.89 ab HgCl2 13.22 ± 0.56 d 0.10 ± 0.01 c 0.25 ± 0.01 c 2.93 ± 0.38 c 298.09 ± 7.40 c 150.56 ± 9.27 c An, net assimilation rate (µmol CO2 m-2 s-1); gm, mesophyll conductance (mol CO2 m-2 s-1); gs, stomatal conductance (mol H2O m-2 s-1); gs/gm (stomatal conductance over mesophyll conductance ratio); Ci, intercellular air space CO2 concentration (µmol mol-1); Cc, CO2 concentration at sites of carboxylation (µmol mol-1).       89  Table 4.2 Percentage and absolute reductions in An, gm gs and Cc under HgCl2 treatment from control for the northern vs. the southern genotypes. Different letters show significant differences for mean values ± SE at P < 0.05.   north south An absolute 10.33 ± 0.57 a 4.47 ± 0.42 b percentage 43.06 ± 1.84 a 25.23 ± 2.23 b gm absolute 0.176 ± 0.023 a 0.067 ± 0.006 b percentage 56.21 ± 3.80 a 41.79 ± 3.13 b gs absolute 0.097 ± 0.009 a 0.031 ± 0.006 b percentage 29.57 ± 2.85 a 11.00 ± 2.41 b Cc absolute 15.51 ± 3.07 a 21.51 ± 8.96 a percentage 8.42 ± 1.62 a 12.51 ± 4.98 a An, net assimilation rate (µmol CO2 m-2 s-1); gm, mesophyll conductance (mol CO2 m-2 s-1); gs, stomatal conductance (mol H2O m-2 s-1); Cc, CO2 concentration at sites of carboxylation (µmol mol-1).   90  HALS-2PITS-3LONG-1SKNP-4TAKA-2TATB-40 .00 .20 .40 .6G e n o ty p egm (mol CO2 m-2 s-1)aaaaaabbb bbbS o u th N o r thFigure 4.2 Mean values (± SE) for mesophyll conductance (gm, mol CO2 m-2 s-1) of six Populus trichocarpa genotypes under two treatments (distilled water in black, and HgCl2 in grey). Different letters show significant differences between distilled water (control), and HgCl2 treatments for each genotype at P < 0.05. 91  HALS-2PITS-3LONG-1SKNP-4TAKA-2TATB-40 .00 .20 .4G e n o ty p egs (mol H2O m-2 s-1)S o u th N o r thab a a abababab Figure 4.3 Mean values (± SE) for stomatal conductance (gs, mol H2O m-2 s-1) of six Populus trichocarpa genotypes under two treatments (distilled water in black, and HgCl2 in grey). Different letters show significant differences between distilled water (control), and HgCl2 treatments for each genotype at P < 0.05.                      92  There was no significant difference between northern and southern genotypes in Cc (Table 4.1). Mercuric chloride significantly decreased Cc by 10.4% (P = 0.0005). There was no latitude by treatment interaction (P = 0.177) and absolute and relative reductions in Cc were equal in both northern and southern genotypes (Table 4.2). Considered separately, HgCl2 chloride decreased Cc in just three genotypes (P < 0.05) (Figure 4.4). Similar to Cc, Ci and gs/gm did not differ between northern and southern genotypes under either control or treatment conditions (Table 4.1). Mercuric chloride significantly increased Ci (P = 0.0005) and gs/gm (P < 0.0001) across all genotypes (Table 4.1). The latitude by treatment interaction was not significant for either gs/gm (P = 0.297) or Ci (P = 0.085) and absolute and relative increases were not statistically different in both northern and southern genotypes (Table 4.2). The effects of HgCl2 on An, gm, gs, gs/gm, Ci, Cc and CCI observed in Experiment 1 were almost fully reproducible in Experiments 2 and 3, and if not in degree or level of significance, then certainly in direction.   4.3.2 Mercuric chloride effect on CA activity In Experiment 2, CA activity decreased by 31.9% (0.37 unit cm-2 ± 0.08 SE) under HgCl2 treatment compared to the control (distilled water) (Table 4.3). 4.3.3 Combined blue light and mercuric chloride effect and changes in gm   In Experiment 3 (and in full concurrence with Chapter 3), 60% BL decreased gm and Cc significantly compared to 10% BL (Table 4.4). However, the reduction in An was not significant under 60% BL due to insufficient statistical power. In the 10% BL control light treatment, pretreatment with HgCl2 reduced An by 18.4% and gs by 19.5% (P < 0.008), while Ci was marginally but not significantly increased. There was a much larger effect on gm and, consequently, Cc (reduced by 41.7% and 19.6%, respectively) (Table 4.4). High blue light in combination with  93  HALS-2PITS-3LONG-1SKNP-4TAKA-2TATB-405 01 0 01 5 02 0 02 5 0G e n o ty p eCc (µmol mol-1)ab a aab aaabaaS o u th N o r thFigure 4.4 Mean values (± SE) for CO2 concentration at sites of carboxylation (Cc, µmol mol-1) of six Populus trichocarpa genotypes under two treatments (distilled water in black, and HgCl2 in grey). Different letters show significant differences between distilled water (control), and HgCl2 treatments for each genotype at P < 0.05.    94  Table 4.3 Effect of 1.5 mM aqueous HgCl2 on CA activity, An, gm, gs, gs/gm, Ci, Cc and CCI. Different letters show significant differences between mean values (± SE, n = 4) within each row (P < 0.05). Genotype was not a factor in this experiment, so data presented here are means across both TATB-4 and LONG-1 combined. Data for distilled water controls are the same here as in Chapter 3, Table 3.5. Slight differences in gm and Cc between the two tables are due to minor differences in the assumed value of α.   distilled water 1.5 mM aqueous HgCl2 CA activity  1.16 ± 0.20 a 0.79 ± 0.11 b An  17.54 ± 0.84 a 15.02 ± 0.97 b gm  0.203 ± 0.030 a 0.115 ± 0.010 b gs  0.298 ± 0.012 a 0.264 ± 0.013 b gs/gm  1.62 ± 0.16 a 2.36 ± 0.16 b Ci  292.30 ± 3.50 a 296.34 ± 5.44 a Cc  198.02 ± 8.18 a 163.09 ± 11.56 b CCI  34.11 ± 2.96 a 35.41 ± 2.71 a CA activity, carbonic anhydrase activity (units cm-2); An, net assimilation rate (µmol CO2 m-2 s-1); gm, mesophyll conductance (mol CO2 m-2 s-1); gs, stomatal conductance (mol H2O m-2 s-1); gs/gm (stomatal conductance over mesophyll conductance ratio); Ci, intercellular air space CO2 concentration (µmol mol-1); Cc, CO2 concentration at sites of carboxylation (µmol mol-1); CCI, chlorophyll content index.  95  Table 4.4 Effect of high blue light and 1.5 mM aqueous HgCl2 on An, gm, gs, Ci and Cc under 10 and 60% BL. Different letters show significant differences between mean values (± SE, n = 4) within each row (P < 0.008). Genotype was not a factor in this experiment, so data presented here are means across both TATB-4 and LONG-1 combined.   distilled water 1.5 mM aqueous HgCl2 10% BL 60% BL 10% BL 60% BL An  13.57 ± 0.80 a 11.93 ± 0.64 ac 11.00 ± 0.33 c 9.73 ± 0.29 b gm  0.187 ± 0.026 a 0.117 ± 0.008 b 0.109 ± 0.020 b 0.070 ± 0.009 c gs  0.169 ± 0.013 a 0.150 ± 0.012 ab 0.136 ± 0.007 b 0.136 ± 0.009 b gs/gm  1.00 ± 0.11 a 1.29 ± 0.07 b 1.47 ± 0.20 b 2.15 ± 0.28 c Ci  258.89 ± 6.73 a 259.05 ± 5.27 a 259.37 ± 5.89 a 272.09 ± 6.98 a Cc  178.2 ± 10.0 a 154.99 ± 9.53 b 143.26 ± 9.00 b 120.42 ± 9.04 c An, net assimilation rate (µmol CO2 m-2 s-1); gm, mesophyll conductance (mol CO2 m-2 s-1); gs, stomatal conductance (mol H2O m-2 s-1); gs/gm (stomatal conductance over mesophyll conductance ratio); Ci, intercellular air space CO2 concentration (µmol mol-1); Cc, CO2 concentration at sites of carboxylation (µmol mol-1).  96  HgCl2 resulted in further significant reductions in gm, Cc and An (reduced in total by 62.6%, 32.4% and 28.3%, respectively), but not gs; hence, Ci was increased, but not significantly so after Bonferroni correction (P = 0.023). Treatment with either HgCl2 (as in Experiment 2) or 60% BL increased gs/gm, and their combined effect was additive (Table 4.4).  4.4 Discussion As per my expectation, the HgCl2 treatment reduced An compared to controls in every circumstance (Figure 4.1, Tables 4.1, 4.3, 4.4). Although gs was also reduced in every case, stomatal limitation of photosynthesis was lower (experiment 1) or unchanged (experiments 2 and 3) in the presence of HgCl2, as evidenced by a significant increase (experiment 1) or no change (experiments 2 and 3) in Ci. Mercuric chloride reduced gm to a much greater degree than gs, causing an increase in gs/gm and a greater relative limitation of photosynthesis (e.g., Table 4.1, 4.3, 4.4). Hence, in contrast to Ci, Cc was reduced under the HgCl2 treatment in all three experiments. The results are in agreement with earlier experimental evidence determining the negative effect of low AQP activity on CO2 diffusion and photosynthesis by chemical inhibition or under-expression in transgenic plants. As described by Terashima & Ono (2002), 1.2 mM HgCl2 reduced gm (by 72%), An and Cc in V. faba, and 2 mM HgCl2 significantly decreased An and Jflu in P. vulgaris. Also, consistent with the current study, Terashima & Ono (2002) observed reductions in gs in P. vulgaris. Concurrent effects of HgCl2 on gs may be indirect or direct. Stomatal conductance and gm are often observed to co-vary with An (Flexas et al. 2008). By various mechanisms (Assmann & Jegla 2016), guard cells may sense and respond to the increase in Ci caused by a decrease in gm. Alternatively, HgCl2 may block AQPs in guard cells and affect water movement and gs directly (Sarda et al. 1997; Kaldenhoff et al. 2008). 97  Although the effect of AQP inhibition on gm in cottonwoods has not been previously studied, Secchi et al. (2009) showed that HgCl2 inhibits the water transport capacity of most members of  the cottonwood PIP2 subfamily by 30-50% when the genes are expressed in Xenopus oocytes. Also in cottonwoods, 0.2 mM HgCl2 was shown to suppress recovery of leaf hydraulic conductance in dehydrated leaves and was suggested to be associated with blocked AQPs (Laur & Hacke 2014). Only a few studies have focused on CO2 transport activity of AQPs. As an example, the gm of transgenic P. tremula × alba lines with down-regulated PIP1 is decreased relative to wild-type plants (Secchi & Zwieniescki 2013). Despite a positive relationship between gm and PIP1 expression, gm reduction does not seem to affect An and gs in these transgenic plants when not stressed for water. Whereas under conditions of water stress, greater reductions in gs and xylem hydraulic conductance in transgenic lines, relative to wildtype plants, reflected their reduced PIP1 expression (Secchi & Zwieniescki 2014). In contrast to poplars, over- and down-regulation of NtAQP1 (a PIP) in N. tabacum changed An and gs in transgenic plants in parallel with gm (by 20%) compared to wild-type plants (Flexas et al. 2006; Uehlein et al. 2008).  Consistent with both Chapters 2 and 3, the northern genotypes had significantly higher An (by 21-33% across all three studies), gs (10-18%) and, most particularly, gm (45-59%) than the southern genotypes. Similar to data presented in Chapter 2, northern genotypes also had a significantly greater LMA (14%), but this is not sufficient, in and of itself, to account for the observed differences in photosynthetic traits. Furthermore, it cannot possibly account for the over two-fold greater sensitivity of northern genotypes to HgCl2 in absolute terms (Table 4.2). Even in relative terms, An, gs and gm were all significantly more sensitive to HgCl2 in the northern genotypes, as 98  hypothesized in the introduction. Per cent reductions were 43 vs. 25% for An, 30 vs. 11% for gs, and 56 vs. 43% for gm, in northern vs. southern genotypes, respectively. The differences in the susceptibility of conductance (either gm or gs or both) to HgCl2 may reflect differences in AQP activity, function (water and/or CO2 transport), or AQP-specific inhibition constants. Not all AQPs are equally affected by HgCl2 (Heinen et al. 2009). Water transport through NtAQP1 and a TIP in Arabidopsis, for example, is reported to be insensitive to mercury (Daniels et al. 1994; Biela et al. 1999). Differences in location of cysteine residues (caused by mutations), as mercury receptors, are known to influence the sensitivity of AQPs to mercurial compounds (Savage & Stroud 2007; To & Torres 2015). Subcellular location of particular AQPs can also influence their functioning. Under low NtAQP1 expression, the plasma membrane NtAQP1 (with five times higher permeability to CO2) is less limiting to internal conductance than NtAQP1 in the chloroplast membrane (Uehlein et al. 2008).  Although HgCl2 was expected to mainly target AQPs, it may have affected photosynthesis or, more specifically, gm, by additional means. There are reports that CA activity and AQP1 function in mammalian cells are simultaneously inhibited by 65-300 µM HgCl2 (Yang et al. 2000; Blank & Ehmke 2003). Indeed, treatment with HgCl2 decreased CA activity by ~32% relative to controls in Experiment 2 (Table 4.3). Therefore, the greater reduction in gm in northern genotypes under HgCl2 could also be related to their intrinsically greater CA activity and the notable dependence of gm, and consequently An, on CA activity (Chapter 2; Momayyezi & Guy 2017). It is possible that CA and AQP interact or are functionally related. There are reports (e.g., Wang et al. 2016) that physical interaction between CA (βCA4) and AQP (PIP2;1) affects stomatal opening through the CO2-signalling pathway in guard cells of Arabidopsis. 99  In Chapter 3, it was shown that blue light effects on gm must be at least partially independent of chloroplast movements. In the present chapter, blue light and HgCl2 had totally additive effects on gm (Table 4.4). High blue light reduced gm by 36-37% in both the presence and absence of HgCl2. Likewise, HgCl2 reduced gm by 40-42% irrespective of the amount of blue light. This suggests that their mechanisms of action may be independent, but not necessarily so. Because high blue light caused a reduction in CA activity in Chapter 3, it would be interesting to know if HgCl2 and blue light have additive effects on CA, but this was not tested.  4.5 Conclusion Northern P. trichocarpa genotypes with greater An, gs and gm were shown to be more sensitive to HgCl2 treatment, in both absolute and percentage terms, compared to southern genotypes. This observation is consistent with a greater role for AQPs in determining gm in northern genotypes. However, it was also shown that CA activity, previously shown to be higher in northern genotypes, was significantly reduced under HgCl2 treatment. Both the effects of blue light and HgCl2 on gm may be partly related to reductions in CA activity.   100  Chapter 5: General discussion 5.1 Conductance and photosynthesis The production of food and biofuel from crop species is ultimately dependent on their photosynthetic capacity. In many natural and agricultural ecosystems, photosynthesis and plant productivity are limited by the availability of resources, often water and/or nitrogen (Webb et al. 1983; Vitousek et al. 1991; Reich et al. 1997; Huxman et al. 2004). For decades there has been a huge global effort focused on improving resource-use efficiencies to increase photosynthesis and yield, and to improve stress resistance. Water and nitrogen use efficiencies have been extensively studied in relation to stomatal and mesophyll conductance to increase photosynthetic performance (Buckley & Warren 2014). However, given the realization (Warren 2008) that gm may account for up to 40% of the total diffusion limitation on photosynthesis, exploration of component constraints on gm is imperative to a comprehensive approach to plant improvement. For the same reason, an understanding of the extent, pattern and basis of natural variation in gm is crucial to a comprehensive view of plant adaptation.  It is known that An increases with latitude in P. trichocarpa genotypes and that this variation is paralleled by latitudinal variation in gs (Gornall & Guy 2007; McKown et al. 2014a). As a consequence, Ci is relatively static with latitude. Therefore, and given the cline in photosynthetic rates, maintenance of Cc with latitude should demand an increase in gm of similar magnitude to gs. Indeed, as shown in Chapter 2 using two methods, there was an almost two-fold difference in gm between northern and southern P. trichocarpa genotypes, which considerably exceeds the difference in gs. Mesophyll conductance was strongly correlated with An. It appears that higher An in northern genotypes, which may be an adaptation to shorter growing seasons (Benowicz et al.   101  2000; Gornall & Guy 2007), is even better supported by enhanced gm than it is by gs. Given that in P. trichocarpa there is no strong latitudinal cline in LMA (as an indicator of anatomical effects on gm [Milla-Moreno et al. 2016]), the physiological basis of gm was explored by studying responses to inhibition of carbonic anhydrase activity (Chapter 2), blue light effects on chloroplast repositioning (Chapter 3), and blocking of aquaporin functioning (Chapter 4).  5.2 Response of gm to various treatments across genotypes The chief significance of Chapter 2, in the broader field of plant physiology, is that it represents the first published evidence of an important and central role for carbonic anhydrase in determining gm and, ultimately, C3 photosynthesis. That CA should function in this capacity was, of course, expected, but not borne out by experimentation until now.   I found gm to be strongly related to CA activity in black cottonwood genotypes in the natural state and, importantly, in similar fashion and degree when partially inhibited by acetazolamide (Chapter 2; Momayyezi & Guy 2017). Northern P. trichocarpa genotypes have roughly twice as much CA activity as southern genotypes on either a leaf mass or area basis. Although the absolute reduction in gm under acetazolamide was higher in northern genotypes, the per cent reduction was similar to the southern genotypes, as was the percent reduction in An in both northern and southern genotypes (Table 5.1). I suggest that the higher CA activity of northern genotypes is key to their greater gm (~ 2 fold) and, in part, their higher An (~ 1.5 fold). Nonetheless, given the published theoretical limits on the impact of CA on gm (Tholen & Zhu 2011), but also the results of my further experiments, it is very likely that variation in CA activity is not wholly responsible for variation in gm in P. trichocarpa.  As shown in Chapter 3, exposure to high blue light reduced gm and An in both northern and 102  Table 5.1 Percentage reduction (± SE) in mesophyll conductance from the corresponding control under 1 mM acetazolamide, 60% BL, and 1.5 mM HgCl2. Different letters show significant differences between mean values within each row as determined in previous chapters (P < 0.05). treatment gm percent reduction An percent reduction north south north south acetazolamide  47.8 ± 5.4 a 44.2 ± 7.3 a 24.7 ± 1.7 a 26.7 ± 3.7 a blue light  36.3 ± 2.8 a 21.0 ± 2.2 b 18.5 ± 3.4 a 12.6 ± 1.9 b mercuric chloride  56.2 ± 3.8 a 41.8 ± 3.1 b 43.1 ± 1.8 a 25.2 ± 2.2 b   103  southern genotypes, but the effect was significantly greater in northern genotypes in both absolute and per cent terms (Table 5.1). In all genotypes there was a reversible decrease in CCI under high blue light, whereas ACC remained unchanged. Again, this behavior, indicative of chloroplast repositioning, was more pronounced in the northern genotypes; i.e., northern genotypes with greater CCI showed higher reductions in CCI. Concurrence between chloroplast repositioning and changes in gm suggests that the two are related, as previously reported by Tholen et al. (2008) and Loreto et al. (2009). However, the further reduction (23%) in gm with high blue light under cytochalasin D (a chloroplast movement inhibitor) may relate to an independent effect of blue light on a different target. Interestingly, CA activity was reduced by ~20% under high blue light. These results suggest that high blue light may mediate CO2 diffusion by having effects on both chloroplast repositioning and CA activity. It is possible that the greater blue light sensitivity of gm in northern genotypes is related not only to their outwardly more pronounced light avoidance movements but also to their higher CA activity. In Chapter 4, and similar to the independent effects of acetazolamide and blue light, gm and An in northern genotypes were reduced more by HgCl2 in northern genotypes than in southern genotypes. As with blue light treatment, northern genotypes were also relatively more sensitive to HgCl2 than southern genotypes (Table 5.1). The greater susceptibility of northern genotypes to HgCl2 may relate to higher AQP activity. Again, however, reductions in gm were accompanied by reductions in CA activity (by ~32%), which may therefore partly account for the greater sensitivity to HgCl2 of northern genotypes. Another explanation could be related to physical interactions between CA and AQP in the CO2 diffusion pathway (Borisova et al. 2012; Wang et al. 2016). Mercuric chloride may disrupt their combined function by interfering with either moiety. The same may be true of acetazolamide.  104  My central hypothesis that in P. trichocarpa, variation in gm would correlate with latitude, is accepted. I can also conclude that this variation reflects differences in CA activity, but the relative roles of AQP functioning and/or chloroplast positioning remain uncertain and, in the research presented here, not separable from CA activity.  5.3 Limitations of research  A main limitation to the current study is the application of “selective” chemical inhibitors which may in fact have multiple targets. As noted in Chapter 2, acetazolamide can interrupt AQP function in mammalian cells (untested in plants). Similarly, mercuric chloride is known to impair CA activity, consistent with the changes in CA activity presented in Chapter 4. Both agents may have further targets that directly and/or indirectly affect photosynthesis. Further work with transgenic plants may provide more reliable and specific evidence if based on expression of different or redundant CA isozymes or AQPs. Another limitation of the present work is the relatively low number of genotypes (six) and latitudes (“north” vs “south”) studied in most experiments. The number of accessions used was limited by technical considerations (time and equipment). I did an initial screening of gm in 12 genotypes to partially compensate for these low numbers, but it would have been better to have still more in order to be certain of the clinal patterns observed. The high reproducibility between experiments in terms of genotypic differences is, however, reassuring. In principle, given more time, I could have used more genotypes in every experiment, but this would not necessarily improve the overall quality of the data. The slow process of measurement for leaf gas exchange variables increases the overall length of experimental measurements for a larger sampling population as a significant source of error.  105  In this thesis, the combined effects of acetazolamide and blue light, and the combined effects of acetazolamide, mercuric chloride and high blue light, were not tested. The interpretation of the latter would have been difficult due to the complexity of possible interactions between different components of gm and the non-selective impacts of chemicals on them. The former treatment combination, however, may have been interesting given what was observed in Chapter 4, where mercuric chloride and high blue light in combination reduced gm additively. Another possible limitation to my work was that the inhibitor concentrations used were based on the available literature and there was no attempt on my part to establish optimal system-specific concentrations (although I did check the maximum viable concentration for mercuric chloride that did not cause wilting). Even so, because of transport effects, dilution and/or foliar accumulation (because of transpiration), it is not possible to know the precise concentration of any chemical agent once it is delivered to the blade through the petiole. I did optimize the length of my feeding experiments by checking the delivery of red food dye to the laminal veins (not presented).  A final limitation relates to the lack of direct microscopic evidence of chloroplast movements under high blue light to verify observations in Chapter 3. It’s highly unlikely, however, that readily reversible changes in CCI unaccompanied by any effect on ACC are due to anything else.  5.4 Future directions Overall, the results of this thesis point to an important role for carbonic anhydrase in gm and, presumably, the local adaptation of photosynthesis. I did not anticipate this, and it’s important that these findings be extended to other species, including crop plants. Since P. trichocarpa and P. balsamifera overlap in nature and both show similar clinal patterns in An and gm, investigation of CA activity in natural P. balsamifera genotypes and the impact on gm variation could be very 106  interesting. Because clinal variation in LMA seems to be more pronounced in P. balsamifera (Soolanayakanahally et al. 2009, 2015) than it is in P. trichocarpa, it’s possible that in this species anatomy has played a more important role than biochemistry in the local adaptation of photosynthetic rate. We might predict, for example, that CA activity per unit leaf area in P. balsamifera should vary as a function latitude simply because LMA does, whereas the activity per unit mass should be more consistent. These studies could be extended to other north-temperate trees sympatric with the cottonwoods, such as red alder and paper birch, to further understand biogeographic trends in gm, CA activity and related photosynthetic traits. Because of similarities in range, and perhaps then selective pressures, it might be expected that B. papyrifera would show patterns similar to P. balsamifera, whereas A. rubra might more closely resemble P. trichocarpa. This kind of information may reveal a general pattern of adaptation, or it may show that although different species achieve similar variation in photosynthesis, they do so in different ways. Some of this work has been completed but was not included in this thesis, as the decision was taken to focus on the P. trichocarpa story. Given the relative ease and speed of assay, it would also be valuable to measure CA activity across a much large number of genotypes from the BCMoFNR P. trichocarpa and the AgCanBaP P. balsamifera collections for purposes of genome-wide association study (GWAS). Full genome sequences for almost all of these accessions are available (Suarez-Gonzalez et al. 2016). This approach might indicate which genes are controlling expression and/or regulation of CA activity in response to natural selection. A similar approach based on the sensitivity of different genotypes to blue light may also be illuminating. Data in Chapter 3 show that high blue light causes a reduction in CA activity as well as chloroplast repositioning, both of which may or may not impact gm by independent mechanisms. One possible 107  noninvasive way to tease this apart would be to conduct an experiment to establish the time course of CA inhibition/down-regulation vs. chloroplast movements (i.e., by blue light), relative to changes in gm. Parallel study of CA transcript levels and/or actual protein levels would also be illuminating (i.e., in a time course, but also between treatments and among genotypes).  Despite model predictions, there is limited molecular genetic evidence of a role for CA in gm. Future transgenic studies should target different and multiple CAs to help clarify the situation and, if successful, pin-point the cellular location of the associated limitation (e.g., stromal vs membrane-bound, etc.). The possibility of cooperativity between CA and AQP proteins in relation to the facilitation of CO2 diffusion also needs further testing. 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There were no significant differences between attached and detached leaves.  attached leaves detached leaves An 15.36 ± 1.21  15.02 ± 1.01  gs 0.221 ± 0.007  0.222 ± 0.006  gm 0.169 ± 0.020  0.180 ± 0.020  An, net assimilation rate (µmol CO2 m-2 s-1); gs, stomatal conductance (mol H2O m-2 s-1); gm, mesophyll conductance (mol CO2 m-2 s-1).  132  Table A.2 Leaf absorptance mean values (± SD) over five replications in six Populus trichocarpa genotypes. Data were introduced to PROC GLM in SAS 9.4 for analysis of variances. There were no significant differences in leaf absorptance between genotypes.   HALS-2 PITS-3 LONG-1 SKNP-4 TAKA-2 TATB-4 leaf absorptance 0.847 ± 0.017  0.832 ± 0.045  0.802 ± 0.022  0.812 ± 0.022  0.835 ± 0.026  0.831 ± 0.017    133  C i (µ m o l C O 2  m-2 s-1)An (µmol CO2 m-2 s-1)0 5 0 1 0 0 1 5 0 2 0 0 2 5 0-2261 0 y  =  0 .0 7 4 1  - 4 .0 8 0 2y  =  0 .0 3 0 8  - 2 .2 7 10Figure A.1 Estimation of CO2 compensation point (Ci*, µmol mol-1) and dark respiration rate (Rd, µmol m-2 s-1) using the Laisk method (Gilbert et al. 2012, see Materials and Methods for details). Each point represents the mean of six plants (± SE). A-Ci curves were built under two irradiances of 125 (○) and 500 (●) µmol m-2 s-1.134  0 5 0 1 0 0 1 5 0 2 0 0 2 5 0-2261 01 4C i (µ m o l C O 2  m-2 s-1)An (µmol CO2 m-2 s-1)0y  =  0 .0 3 7 7 x  -  1 .9 3 8 7           y  =  0 .0 4 3 6 x  -  2 .4 8 3 6y  =  0 .0 8 2 6 x  -  4 .0 8 4 9y  =  0 .0 8 9 6 x  -  3 .9 9 1 4 Figure A.2 Estimation of CO2 compensation point (Ci*, µmol mol-1) and dark respiration rate (Rd, µmol m-2 s-1) using the Laisk method (Gilbert et al. 2012, see Materials and Methods for details) under control (distilled water) (●, ○) and 1 mM acetazolamide (▲, ) treatments. Each point represents the mean of two plants (± SE). A-Ci curves were built under two irradiances of 125 (hollow) and 500 (solid) µmol m-2 s-1.  135  0 .0 0 0 .0 2 0 .0 4 0 .0 6 0 .0 80 .40 .50 .60 .70 .80 .9 CO 2PSIIy  =  5 .1 2  x +  0 .4 8y  =  4 .9 0  x  +  0 .3 9 Figure A.3 Relationship between quantum yield of photosystem II (ΦPSII) and quantum yield for net assimilation rate (Φ𝐶𝑂2) under non-photorespiratory conditions (2% O2). Measurements were on the SKNP-4 genotype over a range of PPFD from 50 to 1200 µmol m-2 s-1 under either 10% (●) or 60% BL (○).              

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