Resource Use Efficiency of C4 Grasses with Different Evolutionary Origins

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RESOURCE USE EFFICIENCY OF C4 GRASSES WITH DIFFERENT EVOLUTIONARY ORIGINS

Harshini Sugandika Uswattha Liyanange Pinto

A thesis submitted in fulfilment of the requirements for the degree of Doctor of Philosophy Degree

Hawkesbury Institute for the Environment

University of Western Sydney

Australia

SEPTEMBER 2015

This thesis is dedicated to my parents and beloved husband for their endless support and encouragement.

ACKNOWLEDGEMENTS

It is with great pleasure that I wish to express my utmost gratitude to my principal supervisor, Dr. Oula Ghannoum for her continuous encouragement, advice, and guidance. She has been a source of generosity, insight and inspiration; guiding me in all my efforts throughout my candidature. I owe my research achievements to her enthusiastic supervision. I acknowledge with great gratitude my co-supervisors Prof. David Tissue, Prof. Jann Conroy and Dr. Robert Sharwood who provided me with the unflinching encouragement, support and feedback during the candidature. Successful completion of this thesis would not have been possible without your invaluable insights and comments on my work.

I am also thankful to Dr. Jeff Powell, Dr. Barbara Drigo (HIE-UWS), Dr. Pascal- Antoine Christin and Dr. Rebecca Atkinson (Sheffield University, UK) for their generous support in statistical analysis. I would like to thank Ms. Liz Kabanoff and Dr. Anya Salih (UWS) for their kind help and support on microscopy. I am also thankful to Dr. Kristine Crous and Dr. Craig Barton (UWS) for their assistance with the tuneable diode laser and carbon isotope discrimination measurements.

I gratefully acknowledge the University of Western Sydney and the Hawkesbury Institute for the Environment for granting me the Australian Postgraduate Award. My gratitude also goes to staff at Hawkesbury Institute for the Environments, Dr. David Harland, Ms. Gillian Wilkins, Ms. Patricia Hellier, Mr. Gavin Mckenzie and Dr. Kaushal Tewari for their generous support on administrative and laboratory work. I wish to thank my colleagues Mr. Balasaheb Sonawane, Ms. Renee Smith, Ms. Josephine Ontedhu, Dr. Honglang Duan and Mr. Guomin Huang for their friendship and support throughout my candidature.

As always, my heartfelt gratitude goes to my parents for their love and constant support throughout my life and for motivating me to pursue an academic career. Finally, my most sincere thanks go to my loving husband, Uthpala Pinto, who has been a shadow behind all my success throughout my life.

STATEMENT OF AUTHENTICATION

The work presented in this thesis is, to the best of my knowledge and belief, original except as acknowledged in the text. I hereby declare that I have not submitted this material, either in full or in part, for a degree at this or any other institution

Author’s Signature

TABLE OF CONTENTS

ACKNOWLEDGEMENTS ...... I

STATEMENT OF AUTHENTICATION ...... I

TABLE OF CONTENTS ...... I

LIST OF FIGURES ...... V

LIST OF TABLES ...... VII

ABBREVIATIONS ...... IX

ABSTRACT ...... 1

CHAPTER 1 GENERAL INTRODUCTION ...... 5

1.1 C3 PHOTOSYNTHETIC PATHWAY AND ITS INEFFICIENCIES ...... 6

1.2 EVOLUTION OF C4 PLANTS ...... 9

1.3 ANATOMY AND PHYSIOLOGY OF C4 BIOCHEMICAL SUBTYPES ...... 12 1.3.1 NADP-ME subtype ...... 13 1.3.2 NAD-ME subtype ...... 14 1.3.3 PCK subtype ...... 15

1.4 PHYSIOLOGY OF THE C3 AND C4 PATHWAYS ...... 17 1.4.1 Water use efficiency and carbon isotope discrimination ...... 19 1.4.2 Nitrogen use efficiency and Rubisco ...... 22

1.5 PHYSIOLOGY OF THE C4 SUBTYPES ...... 24

1.5.1 Water use efficiency of the C4 subtypes ...... 24

1.5.2 Nitrogen use efficiency of the C4 subtypes ...... 25

1.6 GAPS IN THE LITERATURE ...... 27

1.7 AIMS AND OBJECTIVES OF THIS RESEARCH ...... 29

1.8 FORMAT OF THE THESIS ...... 30

CHAPTER 2 PHOTOSYNTHETIC PHYSIOLOGY OF C4 GRASSES REFLECTS AT INTER-GLACIAL CO2 THE BIOCHEMICAL SUBTYPE AND EVOLUTIONARY ORIGIN ...... 32

ABSTRACT ...... 33

2.1 INTRODUCTION ...... 34

2.2 MATERIALS AND METHODS ...... 38 2.2.1 Plant culture and water use measurements ...... 38 2.2.2 Gas exchange measurements ...... 40 2.2.3 Rubisco, PEPC activity and soluble protein ...... 40 i

2.2.4 Growth and nitrogen analyses ...... 41 2.2.5 WUE and NUE calculations ...... 41 2.2.6 Statistical analysis ...... 42

2.3 RESULTS...... 44 2.3.1 Summary of the linear mixed effect (lme) statistical analysis ...... 44 2.3.2 Leaf water use efficiency ...... 44 2.3.3 Leaf N use efficiency ...... 45 2.3.4 Plant water and nitrogen use efficiency ...... 45 2.3.5 Activity and content of photosynthetic enzymes ...... 46

2.3.6 The RDA for inter-glacial CO2 and ambient CO2 ...... 47

2.3.7 The phylogenetic effect on species under inter-glacial CO2 and ambient CO2 ...... 47

2.4 DISCUSSION ...... 60

2.4.1 Variations in photosynthetic nitrogen use efficiency among C4 grasses are associated with the biochemical subtype ...... 60

2.4.2 Variations in photosynthetic water use efficiency among C4 grasses are associated with the evolutionary origin ...... 61

2.4.3 Response of photosynthesis to inter-glacial [CO2] ...... 62

2.4.4 Response of stomatal conductance to inter-glacial [CO2] ...... 63

2.4.5 Response of plant DM and WUE to inter-glacial [CO2] ...... 64

2.5 CONCLUSIONS ...... 64

CHAPTER 3 PHOTOSYNTHESIS OF C3, C3-C4 AND C4 GRASSES AT GLACIAL CO2 ...... 66

ABSTRACT ...... 67

3.1 INTRODUCTION ...... 68

3.2 MATERIALS AND METHODS ...... 71 3.2.1 Plant culture ...... 71 3.2.2 Leaf gas exchange measurements ...... 72 3.2.3 Growth and nitrogen analyses ...... 73 3.2.4 Activity of Rubisco, PEPC, NADP-ME and PCK ...... 74 3.2.5 Immunoblot analysis ...... 75 3.2.6 Statistical and data analysis ...... 76

3.3 RESULTS...... 77 3.3.1 Photosynthetic rates and WUE ...... 77 3.3.2 Leaf N use efficiency and plant dry mass ...... 77 3.3.4 Rubisco and soluble protein content ...... 78

3.3.5 Activity of C4 cycle enzymes in C4 grasses ...... 79

3.3.6 In-vivo estimates of maximal Rubisco (Vcmax) and PEPC activity (Vpmax) in C4 grasses ...... 80 ii

3.4 DISCUSSION ...... 90

3.4.1 Photosynthetic efficiency under glacial CO2: C3, C3-C4 and C4 pathways ...... 90

3.4.2 Photosynthetic efficiency under glacial CO2: the C4 subtypes ...... 91

3.4.3 Photosynthetic enzymes under glacial CO2 ...... 93

3.5 CONCLUSIONS ...... 95

CHAPTER 4 RESOURCE USE EFFICIENCY OF DIVERSE C4 GRASSES UNDER HIGH ATMOSPHERIC WATER DEFICIT ...... 96

ABSTRACT ...... 97

4.1 INTRODUCTION ...... 99

4.2 MATERIALS AND METHODS ...... 102 4.2.1 Plant culture and water use measurements ...... 102 4.2.2 Gas exchange measurements ...... 104 4.2.3 Epidermal impressions ...... 105 4.2.4 Growth and nitrogen analysis ...... 105 4.2.5 WUE and NUE calculations ...... 106 4.2.6 Statistical analysis ...... 106

4.3 RESULTS...... 108 4.3.1 Summary of statistical analysis ...... 108 4.3.2 Leaf water use efficiency ...... 108 4.3.3 Leaf N use efficiency ...... 109 4.3.4 Plant water and nitrogen use efficiency ...... 109 4.3.5 Stomatal density and index ...... 110 4.3.6 Relationships among leaf gas exchange parameters ...... 111 4.3.7 The RDA for VPD treatments ...... 112

4.4 DISCUSSION ...... 124 4.5.1 Photosynthetic and stomatal responses to high vapour pressure deficit vary according to

the C4 evolutionary origin ...... 124 4.5.2 Plant dry mass and WUE responses to growth at high vapour pressure deficit ...... 127 4.5.3 Conclusions ...... 129

CHAPTER 5 VARIATIONS IN LEAF CARBON ISOTOPE DISCRIMINATION AND PHOTOSYSTEMS I AND II

DISTRIBUTION AMONG C4 GRASSES WITH DIFFERENT SUBTYPES ...... 130

ABSTRACT ...... 131

5.1 INTRODUCTION ...... 132 5.1.1 Carbon isotope discrimination ...... 132 5.1.2 Chlorophyll fluorescence ...... 134

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5.2 MATERIALS AND METHODS ...... 136 5.2.1 Plant culture ...... 136 5.2.2 Leaf gas exchange and photosynthetic carbon isotope discrimination ...... 136 5.2.3 Leaf dry matter carbon isotope composition, δ13C ...... 138 5.2.4 Confocal laser scanning microscopy ...... 138 5.2.5 Data analysis ...... 139

5.3 RESULTS...... 140 5.3.1 Photosynthetic and dry matter carbon isotope discrimination ...... 140 5.3.2 Confocal chlorophyll fluorescence ...... 141

5.4 DISCUSSION ...... 153 5.4.1 Photosynthetic carbon isotope discrimination and the carbon isotope composition of dry matter 153 5.4.2 Assessing photosystem I and II distribution using confocal laser scanning microscopy ..... 155

5.5 CONCLUSIONS ...... 157

CHAPTER 6 SYNTHESIS AND GENERAL DISCUSSION ...... 158

6.1 PROJECT AIMS ...... 159

6.2 PHOTOSYNTHETIC PHYSIOLOGY OF DIVERSE C4 GRASSES AT INTER-GLACIAL [CO2] ...... 161

6.3 PHOTOSYNTHESIS OF C3, C3-C4 AND C4 GRASSES AT GLACIAL CO2 ...... 162

6.4 PHOTOSYNTHETIC PHYSIOLOGY OF DIVERSE C4 GRASSES AT HIGH VPD ...... 164

6.5 VARIATION IN LEAF CARBON ISOTOPE DISCRIMINATION AND PHOTOSYSTEM DISTRIBUTION AMONG C4 GRASSES

WITH DIFFERENT SUBTYPES...... 165

6.6 OVERALL CONCLUSIONS ...... 167

6.7 OVERALL SYNTHESIS ...... 169

6.7 FUTURE RESEARCH ...... 176

REFERENCES ...... 177

APPENDICES ...... 208

LIST OF FIGURES

FIGURE 1. 1. A SCHEMATIC REPRESENTATION OF THE CALVIN CYCLE (C3 PHOTOSYNTHESIS)...... 6

FIGURE 1. 2. A SCHEMATIC REPRESENTATION OF THE BI-FUNCTIONAL ACTIVITIES OF RUBISCO...... 8

FIGURE 1. 3. CHANGES IN TEMPERATURE AND ATMOSPHERIC CO2 SINCE 65 MILLION YEARS AGO...... 10

FIGURE 1. 4. NADP-ME SUBTYPE...... 14

FIGURE 1. 5. NAD-ME SUBTYPE...... 15

FIGURE 1. 6. PCK SUBTYPE...... 16

FIGURE 1. 7. COMPARISON OF LEAF NITROGEN BUDGETS BETWEEN C3 AND C4 SPECIES...... 23

FIGURE 2. 1. C4 GRASS SPECIES USED IN THE CURRENT STUDY...... 39

FIGURE 2. 2. STATISTICAL MODEL SUMMARY...... 54

FIGURE 2. 3. LEAF GAS EXCHANGE PARAMETERS FOR 24 C4 GRASSES...... 55

FIGURE 2. 4. CO2 SENSITIVITY OF PHYSIOLOGICAL PARAMETERS MEASURED IN

24 C4 GRASSES...... 56

FIGURE 2. 5. GROWTH AND NITROGEN PARAMETERS...... 57

FIGURE 2. 6. ACTIVITY OF PHOTOSYNTHETIC ENZYMES...... 58

FIGURE 2. 7. RDA TRI-PLOT FOR LEAF LEVEL PARAMETERS...... 59

FIGURE 3. 1 GAS EXCHANGE AND GROWTH PARAMETERS...... 84

FIGURE 3. 2. CO2 SENSITIVITY OF PHOTOSYNTHETIC AND GROWTH PARAMETERS...... 85

FIGURE 3. 3. ACTIVITY OF PHOTOSYNTHETIC ENZYMES...... 86

FIGURE 3. 4. IMMUNOBLOT ANALYSES OF PHOTOSYNTHETIC ENZYMES...... 87

FIGURE 3. 5. RESPONSES OF CO2 ASSIMILATION RATE TO INCREASING

INTERCELLULAR [CO2]...... 88

FIGURE 3. 6. RELATIONSHIPS BETWEEN THE IN VITRO AND IN VIVO ESTIMATES

OF RUBISCO AND PEPC ACTIVITIES IN EIGHT C4 GRASS SPECIES...... 89

FIGURE 4. 1. C4 GRASS SPECIES USED IN THE CURRENT STUDY...... 103

FIGURE 4. 2. WATER USE EFFICIENCY PARAMETERS...... 116

FIGURE 4. 3. VPD SENSITIVITY OF PHYSIOLOGICAL PARAMETERS...... 117

FIGURE 4. 4. LEAF NITROGEN AND PLANT WATER USE EFFICIENCY...... 118

FIGURE 4. 5. LEAF NITROGEN AND PLANT DRY MASS...... 119

FIGURE 4. 6. STOMATAL INDEX AND DENSITY...... 120

FIGURE 4. 7. RELATIONSHIPS AMONG LEAF GAS EXCHANGE PARAMETERS FOR

16 C4 GRASSES...... 121

FIGURE 4. 8. THE GS VS. VPDL AND GS VS. CI SLOPES AS A FUNCTION OF MAXIMAL

GS FOR 16 C4 GRASSES...... 122

FIGURE 4. 9. RDA TRI-PLOT FOR LEAF LEVEL PARAMETERS...... 123

FIGURE 5. 1. PHOTOSYNTHETIC RATE AS A FUNCTION OF STOMATAL CONDUCTANCE...... 147

FIGURE 5. 2. PHOTOSYNTHETIC CARBON ISOTOPE DISCRIMINATION, P AS A

FUNCTION OF INTERCELLULAR TO AMBIENT CO2 RATIO, CI/CA...... 148

FIGURE 5. 3. PHOTOSYNTHETIC CARBON ISOTOPE DISCRIMINATION, P AS A FUNCTION OF LEAF DRY MATTER CARBON ISOTOPE COMPOSITION, 13. ... 149

FIGURE 5. 4. IMAGES COLLECTED USING A CONFOCAL LASER SCANNING MICROSCOPE...... 150

FIGURE 5. 5. AN EXAMPLE OF EMISSION SPECTRA OBTAINED FOR C. CILIARIS (NADP-ME)...... 151

FIGURE 5. 6. AVERAGE TOTAL AND RELATIVE FLUORESCENCE...... 152

FIGURE 6. 1. COMPARISON OF FOUR KEY PARAMETERS MEASURED IN CHAPTERS 2 AND 4 174

FIGURE 6. 2. RDA TRI-PLOT FOR LEAF LEVEL PARAMETERS 175

LIST OF TABLES

TABLE 1. 1. C4 LINEAGES IDENTIFIED...... 11

TABLE 1. 2. SUMMARY OF KEY CHARACTERISTIC DIFFERENCES BETWEEN THE

THREE C4 SUBTYPES...... 17

TABLE 2. 1. STATISTICAL MODEL SUMMARY...... 49

TABLE 2. 2. SUMMARY OF LEAF GAS EXCHANGE AND PLANT GROWTH PARAMETERS AND ACTIVITY OF PHOTOSYNTHETIC ENZYMES...... 51

TABLE 2. 3. SUMMARY OF THE PHYLOGENETIC ANALYSIS FOR SELECTED LEAF PARAMETERS...... 53

TABLE 3. 1. AVERAGE GROWTH CONDITIONS DURING THE EXPERIMENTAL PERIOD...... 71

TABLE 3. 2. LIST OF GRASS SPECIES USED IN THE CURRENT STUDY...... 72

TABLE 3. 3. STATISTICAL SUMMARY...... 81

TABLE 3. 4. SUMMARY OF GAS EXCHANGE AND GROWTH PARAMETERS...... 82

TABLE 3. 5. ACTIVITY OF PHOTOSYNTHETIC ENZYMES...... 83

TABLE 4. 1 SUMMARY OF GROWTH CONDITIONS IN THE GLASSHOUSE CHAMBERS...... 102

TABLE 4. 2. STATISTICAL MODEL SUMMARY...... 113

TABLE 4. 3. SUMMARY OF LEAF GAS EXCHANGE AND PLANT GROWTH PARAMETERS...... 114

TABLE 4. 4. SUMMARY OF STOMATAL, PHOTOSYNTHETIC AND PWUE RESPONSES TO INCREASED VPD...... 127

TABLE 5. 1. LIST OF C4 GRASSES USED IN THE CARBON ISOTOPE AND CONFOCAL FLUORESCENCE STUDIES...... 142

TABLE 5. 2. STATISTICAL SUMMARY...... 143

TABLE 5. 3. LEAF GAS EXCHANGE AND CARBON ISOTOPE DISCRIMINATION MEASUREMENTS...... 144

TABLE 5. 4. LEAF CONFOCAL FLUORESCENCE MEASUREMENTS...... 146

TABLE 6. 1. STATISTICAL MODEL SUMMARY 174

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TABLE 6. 2. SUMMARY OF LEAF GAS EXCHANGE AND PLANT GROWTH PARAMETERS 175

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ABBREVIATIONS

-2 -1 Asat - CO2 assimilation rate (µmol CO2 m s )

A/Ci - CO2 assimilation rate versus intercellular CO2 concentration AIC - Akaike’s Information Criteria ANOVA - Analysis of variance ATP - Adenosine triphosphate BSC - Bundle sheath cell

b3 - The fractionation during Rubisco carboxylation

b4 - The fractionation associated with PEP carboxylation. -1 Ca - Ambient CO2 concentration (µL L ) CABP - 2-carboxyarabinitol 1,5- bisphosphate CCM - Carbon concentrating mechanism -1 Ci - Intercellular CO2 concentration (µL L )

Ci/Ca - Intercellular to ambient CO2 partial pressure

[CO2] - CO2 concentration

C3 - C3 photosynthetic pathway

C4 - C4 photosynthetic pathway D - Carbon isotope discrimination -2 -1 E - leaf transpiration rate (µmol H2O m s ) EDTA - Ethylenediaminetetra - acetic acid -2 -1 gs - Stomatal conductance (mol H2O m s )

Kc - Michaelis–Menten constant for CO2 c k cat - Catalytic turnover number LFEL - Last fully expanded leaf LMA - Leaf mass per area (g m-2) lme - Linear mixed effect model MA - Malate MC - Mesophyll cell Mya - Million years ago N - Nitrogen NAD-ME - Nicotinamid adenine dinucleotide malic enzyme

NADP-ME - Nicotinamid adenine dinucleotide phosphate malic enzyme NUE - Plant nitrogen use efficiency OAA - Oxaloacetate

[O2] - Atmospheric O2 concentration PA - Pyruvate PCK - Phosphoenolpyruvate carboxykinase PEP - Phosphoenolpyruvate PCP - Polyvinyl- polypyrrolidone PG - 3-phoshoglycollic acid molecule PGA - 3-phosphoglycerate pgls - phylogenetic generalised least squares Pi - Orthophosphate PNUE - Photosynthetic nitrogen use efficiency (mmol (mol N)-1 s-1) Plant DM - Plant dry mass (g plant-1) PSI - Photosystem I PSII - Photosystem II -1 PWUE - Photosynthetic water use efficiency (µmol (mol H2O) ) R2 - Linear regression coefficient Rubisco - Ribulose-1, 5-bisphosphate carboxylase/ oxygenase RuBP - Ribulose-1, 5-bisphosphate SE - Standard error VPD - Atmospheric water vapour pressure deficit (kPa)

VPDL - Leaf-to-air vapour pressure deficit (kPa) wi - Akaike weights WUE - Water use efficiency  - Carbon isotope discrimination  - Bundle sheath leakiness 13 - Leaf C isotope composition (‰)

ABSTRACT

C4 photosynthesis has evolved to overcome the limitations of ancestral C3 photosynthetic pathway by operating a CO2 concentration mechanism. Following the depletion of CO2 concentration ([CO2]) in the atmosphere 30 million years ago, the efficiency of the C3 pathway was reduced especially under the prevailing high atmospheric and soil aridity, all of which promote photorespiration. Under most physiological conditions, photorespiration results in the loss of energy and carbon fixed by C3 photosynthesis. C4 photosynthesis is an adaptation that overcomes photorespiration and improves carbon efficiency. C4 plants are more productive and resource use efficient than the more prevalent C3 plants. At present, C4 plants constitute

3% of the world’s species and C4-dominated grasslands contribute up to 20% of global primary productivity. About 50% of C4 species are grasses with 15 distinct evolutionary origins distributed over 370 genera and 4600 species. Further, C4 plants are divided into three biochemical subtypes following the major C4 acid decarboxylase in the bundle sheath cells: NAD malic enzyme (NAD-ME), NADP-ME and PEP carboxykinase

(PCK). These C4 subtypes are closely associated with particular taxa, and some taxa have multiple evolutionary origins. In addition, various physiological and ecophysiological traits have been associated with the biochemical subtype or evolutionary lineage of the C4 grasses. Most physiological studies were undertaken using a small number of C4 species under current ambient [CO2] which does not reflect the low [CO2] environment under which C4 grasses have evolved. Therefore, this PhD project was conducted to compare the physiological efficiencies of diverse C4 grass species under conditions that promote high rates of photorespiration, which contributed to the physiological pressure that led to the evolution of the CO2 concentrating mechanism (CCM) in land plants.

Chapter 2 investigated the leaf- and plant-level physiological responses of 24 C4 grasses belonging to three biochemical subtypes (NAD-ME, PCK and NADP-ME) and six dominant evolutionary origins: Andropogoneae (NADP-ME), Digitaria (NADP-ME), Echinochloa (NADP-ME), Paspalum (NADP-ME), Chloridoideae (NAD-ME, PCK) and Paniceae (NADP-ME, NAD-ME and PCK) grown under ambient (400 μl L-1) and -1 inter-glacial (280 μl L ) atmospheric [CO2]. This study demonstrated that 1

Chloridoideae/NAD-ME group was distinguished by their higher leaf mass per area

(LMA) and leaf [N], while NADP-ME and PCK subtypes were distinguished by higher photosynthetic nitrogen use efficiency (PNUE) and activities of the photosynthetic enzymes Rubisco and PEPC regardless of the evolutionary origin. It was concluded that the variation in PNUE amongst C4 species used in this study were most likely related to the C4 biochemical subtype, while variations in photosynthetic water use efficiency (PWUE) most likely reflected the evolutionary origin of the species. This study also revealed that C4 grasses have differential stomatal sensitivity to [CO2]; species with longer inter-veinal distances (lower potential hydraulic conductivity) showed the lowest stomatal sensitivity to low [CO2]. Furthermore, all the measured parameters showed a non-significant phylogenetic dependence.

Chapter 3 compared PNUE and PWUE and the activity of the photosynthetic carboxylases (Rubisco and PEPC) and decarboxylases (NADP-ME and PEP-CK) in eight C4 grasses with NAD-ME, PCK and NADP-ME subtypes, one C3 grass and one -1 -1 C3-C4 grass grown under ambient (400 µl L ) and glacial (180 µl L ) [CO2]. The C3 species acclimated to glacial [CO2] by doubling Rubisco activity, while Rubisco in C3-

C4 species was unaffected possibly due to its high leaf N and Rubisco contents. In some

C4 grasses, glacial CO2 led to the up-regulation of the activities of Rubisco and PEPC. However, NADP-ME and PEP-CK activities were unchanged, reflecting that Rubisco and PEPC, rather than the decarboxylases, modulate the response to glacial [CO2] for C4 grasses with different biochemical subtypes. Furthermore, a smaller reduction of photosynthetic rate and a greater increase of stomatal conductance were observed in C4 species relative to C3 and C3-C4 species when grown under glacial [CO2]. Despite having larger stomatal conductance at glacial CO2, C4 species maintained greater

PWUE and PNUE relative to C3-C4 and C3 species due to higher photosynthetic rates.

Therefore, under glacial [CO2], high resource use efficiency offered a key evolutionary advantage for the transition from C3 to C4 photosynthesis in water and nutrient limited environments.

Chapter 4 investigated leaf and plant physiological responses of 20 C4 grasses belonging to three biochemical subtypes (NAD-ME, PCK and NADP-ME) and six dominant evolutionary origins [Andropogoneae (NADP-ME), Digitaria (NADP-ME),

Echinochloa (NADP-ME), Paspalum (NADP-ME), Chloridoideae (NAD-ME, PCK) and Paniceae (NADP-ME, NAD-ME and PCK)] grown under low (0.7 kPa) and high (2.0 kPa) atmospheric water vapour pressure deficit (VPD) which corresponded to 80% and 40% relative humidity (RH), respectively. C4 grasses with the lowest stomatal conductance at low VPDL had the lowest sensitivity in response to increasing VPDL.

This linear relationship was strong and common for all C4 species and at both growth VPD treatments; thus indicating that the stomatal response to VPD in grasses is independent of the underlying photosynthetic metabolism. Overall, C4 grasses were grouped into four categories. The first group (Echinochloa and Paspalum) showed high stomatal reductions and nil-low photosynthetic increases in response to increased VPD, leading to the greatest gains in PWUE. The second group (Chloridoideae and Paniceae) showed high stomatal and photosynthetic reductions in response to increased VPD, leading to moderate gains in PWUE. The third group (Andropogoneae) showed little stomatal and photosynthetic changes in response to high VPD leading to minimal gains in PWUE. The fourth group (Digitaria) showed low stomatal responses and high photosynthetic reductions in response to increased VPD, leading to losses in PWUE.

Chapter 5 evaluated the degree of species and subtype variability in leaf 13C/12C isotope 13 13 composition (δ C), photosynthetic carbon isotope discrimination against C (p) and the distribution of chlorophyll fluorescence between the mesophyll and bundle sheath cells in a large number of C4 grasses belonging to the NADP-ME, NAD-ME and PCK biochemical subtypes. In line with previous studies, this study confirmed that there was no significant difference in photosynthetic carbon isotope discrimination against 13C or estimated bundle sheath leakiness; while leaf 13C/12C isotope composition was lowest in NAD-ME, intermediate in PCK and highest in NADP-ME species. Moreover, leaf 13C/12C isotope composition and photosynthetic carbon isotope discrimination against 13C were not correlated. Confocal laser scanning microscope images revealed that total fluorescence intensity was lower in the bundle sheath relative to the mesophyll for NADP-ME species; however, the opposite was observed for NAD-ME and PCK species. The ratio of PSII/PSI relative fluorescence was higher in the mesophyll relative to the bundle sheath for all C4 species. In the bundle sheath cells, the ratio of PSII/PSI relative fluorescence was lower in NADP-ME relative to NAD-ME and PCK species.

In conclusion, high resource use efficiency offers a key evolutionary advantage for the transition from C3 to C4 photosynthesis in water and nutrient limited environments. This project confirmed the overall hypothesis that the evolutionary and biochemical diversity among C4 grasses is aligned with discernible leaf physiology traits under low and high atmospheric [CO2] and VPD. In addition, the study demonstrated that C4 grasses use different adaptive strategies depending on whether CO2 supply is directly (low [CO2]) or indirectly (high VPD) limiting.

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CHAPTER 1

GENERAL INTRODUCTION

1.1 C3 photosynthetic pathway and its inefficiencies

Inorganic carbon dioxide (CO2) in the atmosphere is transformed into organic carbon in the biosphere by plants through the process of photosynthesis. Plants that belong to the

C3 photosynthetic pathway cover most terrestrial ecosystems and account for about 95% of higher plants (Griffin and Seemann, 1996). Some of the main C3 crops are wheat (Triticum aestivum), rice (Oryza sativa), potato (Solanum tuberosum) and soybean (Glycine max).

Carbon input Start of cycle Ribulose-1,5- CO2+H2O bisphosphate

ADP Carboxylation

Regeneration Calvin cycle 3-Phosphoglycerate ATP

Pi ATP + NADPH

Reduction Glyceraldehyde -3-phosphate ADP + Pi + NADP

Triose phosphate

Sucrose, Carbon Starch output

Figure 1. 1. A schematic representation of the Calvin cycle (C3 photosynthesis).

The C3 pathway consists of two sets of biochemical reactions. Firstly, the light reactions which convert the light energy into biochemical energy and secondly, the dark reactions, which utilise the chemical energy to convert atmospheric CO2 into carbohydrates. Mesophyll cells are the main sites for C3 photosynthesis. During the dark reactions, atmospheric CO2 is fixed into a 3-carbon compound, 3-phosphoglycerate

(PGA); hence, this photosynthetic pathway is called the C3 photosynthesis or Calvin cycle (Ehleringer et al., 1991) (Figure 1.1). The C3 photosynthetic pathway has three principal phases: carboxylation, reduction, and regeneration. During the first phase of carboxylation, CO2 is accepted by ribulose-1, 5-bisphosphate (RuBP) to generate two molecules of PGA. During the phase of reduction, PGA is reduced to triose phosphate (triose-P), by using ATP and NADPH (generated in light reactions). The last phase is the regeneration of RuBP, which is the primary acceptor of CO2, from triose phosphate through a series of reactions. For each molecule of CO2 fixed, three ATP and two NADPH molecules are required (Raghavendra, 2003).

The enzyme Rubisco catalyses the key reaction of photosynthetic CO2 assimilation in the mesophyll cell of C3 leaves. Rubisco is a unique and interesting enzyme because both CO2 and O2 are its competitive substrates (Figure 1.2). Rubisco catalyses the carboxylation between atmospheric CO2 and RuBP to produce 2 molecules of PGA. The oxygenation of Rubisco forms one 3-phoshoglycolic acid molecule (PG) and one PGA molecule. The PG formed undergoes further metabolism resulting in concomitant loss of CO2 and energy. The oxygenation reaction of Rubisco initiates the reactions of photorespiration, which reduce potential carbon assimilation and reduces the overall efficiency of net photosynthesis (Griffin and Seemann, 1996). Under the current atmosphere, [CO2] in the chloroplasts of C3 leaves is about 1000 times less than that of

O2. Therefore, the efficiency of carboxylation via Rubisco is depressed in C3 photosynthesis. This depression is due to the inability of low [CO2] to saturate Rubisco and the competitiveness of O2 with CO2 for Rubisco (Long, 1999). Under non stress environmental conditions, CO2 loss through photorespiration accounts for up to 20-30% of C3 plant net-photosynthesis in normal air (Bauwe et al., 2010). Therefore, photorespiration is considered to be the main factor reducing the efficiency of the C3 pathway.

RuBP O2 CO2 RuBP

PGA Oxygenation RUBISCO Carboxylation

PG + PGA 2 X PGA

Figure 1. 2. A schematic representation of the bi-functional activities of Rubisco.

The ratio of photorespiration to photosynthesis is affected by changes in several environmental conditions. Rising temperature, declining intercellular [CO2] (Ci) and water stress are key contributing factors to high rates of photorespiration. With rising temperature, the ratio of dissolved chloroplastic O2:CO2 and the specificity of Rubisco for O2 are increased. As a result, photosynthesis is reduced by high rates of photorespiration (Sage and Sharkey, 1987). Reduced Ci will further reduce the saturation of the carboxylation reaction. Therefore, the C3 pathway becomes substrate- limited under low Ci and undergoes oxygenation by accepting O2 as the substrate

(Ainsworth and Rogers, 2007). Under water stress, C3 plants conserve water by minimising leaf transpiration (E). This occurs through operating a lower stomatal conductance leading to low level of Ci, and in turn, leading to photorespiration. Hence, photorespiration plays a major role in reducing the efficiency of the C3 photosynthetic pathway.

Inefficiencies in the C3 pathway generally lead to low resource use efficiencies in C3 c plants. The catalytic turnover number (k cat - number of substrate molecules each enzyme convert to product per second) of the enzyme Rubisco is extremely small. Therefore up to 30% of soluble protein and 25% of leaf nitrogen (N) are invested in

Rubisco to achieve high photosynthetic rates in C3 leaves (von Caemmerer and Quick, 2000). As a result, they have low productivity per unit of N in the plant. Furthermore, high stomatal conductance (gs) to CO2 diffusion enhances CO2 assimilation rate (Asat) 8

but it also increases the leaf-level water loss (von Caemmerer, 2003). Hence, C3 plants function with low CO2 uptake relative to high water cost. Consequently, C3 plants operate with low resource use efficiency, and hence may not be competitive in resource limited environments.

1.2 Evolution of C4 plants

The era when C4 photosynthesis is thought to have first occurred in the grasses coincides with the era of declining atmospheric [CO2]. According to the atmospheric models, [CO2] in the mid-Cretaceous were three to five times greater than today (Figure

1.3). This high [CO2] steadily decreased below the current atmospheric [CO2] by the Miocene-Pliocene times (5–15 Mya) and reached the lowest levels in the late Pleistocene (Berner and Kothavala, 2001, Royer et al., 2001). Isotopic signatures in alkenones formed by algae, boron isotopic signatures and stomatal indices were used to estimate these trends in the atmosphere (Pagani, 2002, Retallack, 2002).

The oxygen isotope record from deep-sea cores presented the temperatures of the atmosphere and ocean. Therefore, oxygen isotope ratios were able to outline the key climate events throughout the past 70 million years (Zachos et al., 2001). Global cooling mostly occurred at high-latitudes, however at the same time tropical areas remained warm and sometimes experienced high temperatures where aridification reduced vegetation cover and exposed bare grounds. C4 evolution appears to arise first in such environments distinguished by aridity and low CO2, between 24-33 Mya during the Oligocene epoch (Farrera et al., 1999, Sage, 2004).

The Oligocene starts with a sudden increase in the δ18O ratio (Prothero, 1994, Zachos et al., 2001). During the Oligocene, C4 photosynthesis diversified in many families that have already evolved and some families first come into existence in the fossil record while forests declined across the globe (Collinson et al., 1993, Sage and Coleman,

2001). Molecular phylogenies indicated that grasses were the first C4 plants, arising about 24–34 Mya and they were abundant enough to place measureable fossil and isotopic signatures by 12–14 Mya. Therefore, the deterioration of the climate and atmospheric [CO2] in the Oligocene created the general preconditions for C4 evolution. 9

Paleocene Eocene Oligocene Miocene Pliocene 4200 Cretaceous Pleistocene 18O 3600 0 10

CO2

, ppm , 0

2 8 3000 Moist Probable first 1 C grasses C grasslands climate 4 4 expand

2400 2 4 O(%)

18 0

1800 3 

1200 4

Drier temperature, Inferred

Inferred atmospheric CO atmospheric Inferred climate 600 5

0 70 60 50 40 30 20 10 0

Time before present, MYA

Figure 1. 3. Changes in temperature and atmospheric CO2 since 65 million years ago.

18 Changes in deep-sea core δ O ratios (solid line) and atmospheric CO2 (dashed line) since the beginning of the Tertiary period 65 Mya. Adapted from (Sage, 2004).

During the late-Miocene further decreases of atmospheric CO2 is also considered to have favoured the increase of C4 grasslands. The late-Miocene decrease of atmospheric -1 [CO2] from 350 to 280 µL L is supported by stomatal indices of fossil oak leaves (Cerling et al., 1997, Cerling, 1999, Retallack, 1997). In the current pattern, inter-glacial phase lasted about 10 000 years, while glacial phase extended over a 100 000 years.

During the inter-glacial phase, atmospheric [CO2] generally varied between 260-300 µL L-1, and between 240-180 µL L-1 during the glacial phase (Petit et al., 1999, Sage, 2004, Ward, 2005). The high latitudes stayed cold during glacial phase while low latitudes were warmer. However, the lower altitude areas tended to be more arid (Farrera et al.,

1999). This warm and arid atmosphere with reduced [CO2] was the combination of environmental parameters that supported further origins of C4 photosynthesis. This is in

line with the hypothesized rise of several C4 dicots in the Pleistocene (Ehleringer et al., 1997).

Table 1. 1. C4 lineages identified. Adapted from Grass Phylogeny Working Group, (2012).

C lineage 4 1 Aristida 2 Stipagrostis 3 Chloridoideae 4 Centropodia 5 Eriachne 6 Tristachyideae

7 Andropogoneae 8 Reynaudia 9 Axonopus 10 Paspalum 11 Anthaenantia 12 Steinchisma

13 Arthropogon 14 Mesosetum 15 Oncorachis 16 Coleataenia 1 17 Coleataenia 2 18 Digitaria

19 Echinochloa

20 Paraneurachne 21 MPC (Melinidinae, Panicinae, Cenchrinae) 22-24 Alloteropsis

C4 photosynthesis has evolved from the ancestral C3 photosynthetic pathway. When grouping C4 plant lineages, it is noted that the greater part of angiosperm lineages lack

C4 taxa. This observation pointed out that only few C3 plant lines hold the suitable characteristics that assist in the C4 evolution (Sage, 2001). The hypothesis of multiple

C4 origins from C3 ancestors were further maintained by anatomical, biochemical and genetic deviations observed in C4 phylogenetic groups (Sinha and Kellogg, 1996, Christin et al., 2010). Grass Phylogeny Working, Group, II (2012) have built a densely 11

sampled phylogeny for the grass family. This phylogenetic framework showed C3 to C4 evolutionary transitions have been extremely irregular, with 22–24 inferred origins of the C4 pathway (Table 1.1).

The evolutionary diversification of C4 plants is of major interest to scientists in wide variety of disciplines. Due to the influence of C4 plants on biotic systems, atmosphere and climate through geological time, geologists are interested in the systematic changes that occurred within the C4 photosynthesis cycle (Cerling et al., 1997, Jon and Farquhar, 1994, Pagani et al., 1999). On the other hand, zoologists and anthropologists have shown a great interest due to the influence of C4 plants on the evolution of mammals and hominids (Bruce J, 1997, Harris and Cerling, 2002, Janis et al., 2002). The evolution of hominids into modern-day man was probably advanced through cultivation of agricultural crops, in particular those based on C4 photosynthesis, such as maize and sugarcane (Hobhouse, 1999). Further, the expansion of C4 grasslands modified the regional climate and fuelled fire cycles, which reduced air quality and biodiversity over a long time scale. Overall, this has drawn the attention of climatologists and policy makers across the world (Monson, 2003).

1.3 Anatomy and physiology of C4 biochemical subtypes

The biochemistry of the C4 pathway was discovered in the mid-1960s. Following its discovery, there was a burst of C4 research which contributed to the better understanding of the pathway (Edwards and Walker, 1983, Hatch, 1999). Over the next 20 years of research, scientists were able to identify the main features of this pathway, the taxonomic diversity and the ecological importance to the biosphere.

C4 photosynthesis involves anatomical changes of the C3 leaf structure to create a carbon concentrating inner compartment where Rubisco is localized (Dengler and Nelson, 1999). This results in a wreath-like cell arrangement, termed Kranz anatomy. Kranz anatomy consists of an outer cell layer called the mesophyll cells (MC) and inner layer of bundle sheath cells (BSC). The first CO2 fixation occurs in the mesophyll cell. Bundle sheath cells contains Rubisco and many of the Calvin cycle enzymes (Dengler and Nelson, 1999, Sage, 2004) 12

The first steps in C4 photosynthesis involve the hydration of CO2 into bicarbonate and its subsequent fixation by phosphoenolpyruvate (PEP) carboxylase. The resulting four- carbon acids (oxaloacetate, malate and aspartate) diffuse into the inner bundle sheath compartment where Rubisco is located (Hatch, 1987, Kanai and Edwards, 1999). The four-carbon acids are then decarboxylated, releasing CO2. The concentration of CO2 increases as a result of faster delivery of CO2 relative to its fixation by Rubisco, as well as the relatively high gaseous resistance of the bundle sheath cell wall (von Caemmerer and Quick, 2000). Following decarboxylation, a three-carbon acid is produced. This three-carbon acid returns to the mesophyll cell where it is re-phosphorylated to regenerate PEP (Dengler and Nelson, 1999). The specific means by which CO2 concentration occurs in C4 plants differ significantly between the evolutionary lineages (Edwards and Walker, 1983, Kanai and Edwards, 1999). First carboxylation reaction catalysed by PEP carboxylase to yield oxaloacetic acid (OAA) is the only enzymatic step common to all versions of C4 photosynthesis (Kanai and Edwards, 1999, Sage, 2004).

C4 plants are grouped into three subtypes based on the enzymes of the decarboxylation step in bundle sheath cell. The three decarboxylation enzymes are NADP- malic enzyme (NADP-ME), NAD-malic enzyme (NAD-ME), and PEP carboxykinase (PCK).

All C4 subtypes show morphologic and biochemical differences between mesophyll and bundle sheath cells (Gutierrez et al., 1974, Kanai and Edwards, 1999). Below is a brief overview of anatomical and biochemical features in the leaves of C4 species with different biochemical subtypes within the grass family.

1.3.1 NADP-ME subtype

In C4 grasses with the NADP-ME subtype, chloroplasts in bundle sheath cells are usually in a centrifugal position relative to the vascular bundle, and have reduced grana stacking in their thylakoid membranes (Figure 1.4). Oxaloacetate (OAA) produced by PEP carboxylase is moved to mesophyll cell chloroplasts from cytoplasm, where most of the OAA is reduced to malate by malate dehydrogenase and the rest is converted to aspartate by aspartate aminotransferase. These acids are exported from mesophyll to

bundle sheath cells through plasmodesmata. In bundle sheath cell chloroplasts, malate is decarboxylated by NADP-malic enzyme to supply CO2 to Rubisco in the C3 cycle of bundle sheath cells. Pyruvate produced during decarboxylation is returned to mesophyll cell chloroplasts for resynthesis of PEP (Gutierrez et al., 1974, Walker et al., 1997, Kanai and Edwards, 1999).

NADP-ME CO2

HCO3 Chloroplast Chloroplast

PEP PEP PCR cycle Pi OAA OAA

CO2 PA NADP-malic PA enzyme MA MA MA

PA PA

Mesophyll cell Bundle sheath cell Mesophylle cell Bundle sheath cell

Figure 1. 4. NADP-ME subtype.

The major metabolites and decarboxylating enzyme in the NADP-ME subtype. Adapted from Kanai and Edwards, (1999). Abbreviations: MA, malate; OAA, oxaloacetate; PA, pyruvate; PEP, phosphoenolpyruvate; Pi, orthophosphate.

1.3.2 NAD-ME subtype

In C4 grasses with the NAD-ME subtype, chloroplasts and mitochondria in the bundle sheath are in a centripetal position relative to the vascular bundle. Thylakoid membranes of NAD-ME C4 species also have well-formed grana stacking. Aspartate is

the main initial product of CO2 fixation in the mesophyll cell cytoplasm via aspartate aminotransferase (Figure 1.5). The aspartate is transported to bundle sheath cell mitochondria, where it is deaminated to produce OAA. OAA is reduced to malate by NAD-malate dehydrogenase and then the malate is decarboxylated by NAD-ME. The

CO2 released during the decarboxylation is fixed by Rubisco in the bundle sheath cell.

Thus, bundle sheath mitochondria play an important role in this C4 subtype. The decarboxylation product, pyruvate, is converted to alanine, which is returned to mesophyll cell chloroplasts for resynthesis of PEP (Kanai and Edwards, 1999).

NAD-ME CO2

HCO 3 Chloroplast Chloroplast PCR PEP PEP cycle

PA OAA

Asp OAA CO2 PA PA NAD-malate dehydrogenase Asp

Mitochondrion MA

Ala Ala PA

Mesophyll cell Bundle sheath cell Mesophylle cell Bundle sheath cell Figure 1. 5. NAD-ME subtype.

The major metabolites and decarboxylating enzyme in the NAD-ME subtype. Adapted from Kanai and Edwards, (1999). Abbreviations Ala, alanine; Asp, aspartate; MA, malate; OAA, oxaloacetate; PA, pyruvate; PEP, phosphoenolpyruvate; Pi, orthophosphate.

1.3.3 PCK subtype

In C4 grasses with the PCK subtype, the bundle sheath cell chloroplasts are positioned evenly or centrifugally and have well developed grana stacks. PEP carboxykinase is the 15

main decarboxylation enzyme in the bundle sheath cytoplasm, but BSC mitochondria also show considerable activity of NAD-malic enzyme. Aspartate is the main initial product of CO2 fixation in the mesophyll cell cytoplasm via aspartate aminotransferase (Figure 1.6). However, some malate is also formed in mesophyll cell chloroplasts. Aspartate transported from mesophyll to bundle sheath cells is deaminated and decarboxylated by PEP-CK, whereas transported malate is decarboxylated by NAD-ME producing pyruvate and PEP. Both decarboxylases supply CO2 to Rubisco. Pyruvate formed during the decarboxylation returns to the chloroplasts of the mesophyll cell through alanine, similar to NAD-ME type species. PEP return directly to the mesophyll cell cytoplasm (Kanai and Edwards, 1999).

PCK CO2

HCO 3 Chloroplast Chloroplast PCR PEP PEP cycle

CO Pi 2

PA OAA OAA CO2 Mitochondrion PEP MA PA O 2 PEP PA carboxykinase

MA H2O Asp Asp OAA Ala Ala PA PEP

MesophyllMesophylle cell BundleBundle sheath sheath cell cell

Figure 1. 6. PCK subtype. The metabolites and decarboxylating enzyme in the PCK sybtype. Adapted from Kanai and Edwards, (1999). Abbreviations: MA, malate; OAA, oxaloacetate; PA, pyruvate; PEP, phosphoenolpyruvate; Pi, orthophosphate.

More than 15 different Kranz-leaf anatomy types have been recognized in a range of C4 dicots and monocots (Dengler and Nelson, 1999, Kadereit et al., 2003). In all these lineages, the external wall of the bundle sheath cell is modified to trap CO2 inside the bundle sheath cell by reducing the CO2 flowing out of the cell. The external bundle 16

sheath cell wall is lined with a suberin layer in some (mostly, NADP-ME and PCK) C4 grasses, most probably to enhance the resistance of the wall to CO2 diffusing out. Species with the NAD-ME subtype do not have the suberin barrier. Therefore, suberization of the external bundle sheath cell wall is not a requirement for C4 photosynthesis (Dengler and Nelson, 1999). Species that lack suberin barrier have their chloroplasts on the inner, or centripetal, side of the bundle sheath cell. This arrangement helps slow CO2 escape from the large vacuole of the bundle sheath cell (Kanai and Edwards, 1999).

Table 1. 2. Summary of key characteristic differences between the three C4 subtypes.

Characteristics NADP-ME NAD-ME PCK

Decarboxylation enzymes (Hatch, NADP-malic NAD-malic PEP 1987) enzyme enzyme carboxykinase

Decarboxylated acid Malate Aspartate Aspartate (Hatch, 1987)

Site of decarboxylation Chloroplast Mitochondrion Cytosol (Hatch, 1987)

Suberin lamella lining bundle sheath cell wall (Dengler and Present Absent Present Nelson, 1999)

Chloroplast position in the bundle Centrifugal Centripetal Even/Centrifugal sheath cell (Sage, 2004)

1.4 Physiology of the C3 and C4 pathways

C4 photosynthesis operates with a carbon concentrating mechanism (CCM) that enhances the concentration of CO2 in the bundle sheath cell around Rubisco. This elevated [CO2] saturates the carboxylation reaction of Rubisco and suppresses the rate

of photorespiration. Therefore, the advantage of the CCM is enhanced under high photorespiratory environments like high temperature and low atmospheric [CO2] relative to C3 photosynthetic pathway. C4 plants rarely have a photorespiration rate greater than 5% of the rate of photosynthesis. In contrast, photorespiration rate can o exceed 30% of the rate of photosynthesis in C3 plants above 30 C (Sage and Pearcy,

2000). Consequently, C4 plants have greater maximum productive potential and greater recourse use efficiencies (Evans, 1993, Brown, 1999). Usually, C4 crops have 40% greater efficiency for conversion of photosynthetically active radiation into biomass than for C3 crops (Long, 1999, Sage, 2000).

The physiological results of operating the CCM can be clearly seen when comparing the photosynthesis of the C3 and C4 plants. High photosynthetic rate (Asat) is one of the first physiological features observed in C4 relative to C3 plants (Hatch, 1992). C4 species attain a higher photosynthetic rate relative to C3 species at a low Ci. This occurs as a result of the CCM in C4 photosynthesis which leads to CO2 saturation at a relatively low

Ci (Kanai and Edwards, 1999). High activities of PEP carboxylase, the first CO2 acceptor enzyme in the mesophyll cells, results in the efficient utilization of low Ci

(Hatch and Osmond, 1976). PEP carboxylase is not sensitive to atmospheric O2 unlike

Rubisco. However, in C3 plants where Rubisco fixes atmospheric CO2 directly, saturation of Rubisco occurs at a higher [CO2] and it also depends on atmospheric O2 concentration ([O2]), amount of Rubisco and the RuBP regeneration capacity (Farquhar et al., 1980b, Ehleringer and Pearcy, 1983).

The contrasting CO2 dependence of C3 and C4 photosynthesis is further supported by their differences in stomatal conductance (gs). As the CCM results in earlier CO2- saturation of C4 relative to C3 pathway, any further increase in gs in C4 plants would result in extra water loss without increased Asat. Given that the CO2-saturation of C3 photosynthesis is more gradual and does not occur until higher CO2 concentrations, C3 plants tend to operate at higher gs relative to C4 Plants. This results makes C4 species more water use efficient than C3 counterparts.

1.4.1 Water use efficiency and carbon isotope discrimination

Water use efficiency (WUE) describes the water cost of CO2 uptake and carbon sequestration by the plants. WUE is normally discussed at both the leaf (photosynthesis) and whole plant (vegetative biomass) levels. The main driver of water movement through the plant is leaf transpiration (E), which depends on stomatal conductance for water vapour (gs) and the difference between the vapour pressures in the intercellular air spaces and in the surrounding atmosphere (Farquhar and Sharkey, 1982a, Farquhar et al., 1989a).

Leaf WUE is given by:

where A is CO2 assimilation rate, E is leaf transpiration rate, Ci leaf inter cellular [CO2],

Ca ambient [CO2], ei vapour pressure in the intercellular airspace inside the leaf, ea vapour pressure in the surrounding air, 1.6 is the ratio of binary diffusivity of vapour in air to that of CO2 in air (Farquhar and Sharkey, 1982a).

When stomata are open, CO2 molecules diffuse inside the leaf, while H2O vapour molecules diffuse out of the leaf. Under most physiological conditions, the gradient for

H2O loss through transpiration is much greater than the gradient for CO2 uptake. Consequently, water loss is substantial, and represents an inevitable cost of photosynthesis. At the leaf level, WUE represents the ratio of CO2 assimilation (Asat) to transpiration. However, when comparing WUE of species grown in different environments, a more appropriate term is photosynthetic WUE (PWUE), which refers to the ratio of CO2 assimilation rate (Asat) to stomatal conductance (gs) (Ghannoum et al.,

2011). Differences in PWUE may be brought about by variations in both Asat and gs.

Variations driven mainly by Asat indicate a high growth potential strategy. In contrast, variations driven mainly by gs, indicate a water conservation strategy. C4 plants possess 19

a CO2 concentrating mechanism that saturates Rubisco with CO2 at a low Ci. This allows C4 plants to operate with lower gs while maintaining higher Asat, which usually explains their higher PWUE. Leaf stomatal conductance is generally about 40% lower in C4 than C3 plants under the same environmental conditions (Long, 1999). Therefore, higher PWUE is recorded for C4 plants relative to their C3 counterparts (Osmond, 1982, Taylor et al., 2010, Pinto et al., 2011).

Plant water use efficiency (WUE) can be defined as the ratio of plant biomass to total water use by the plant. Higher PWUE of C4 species may explain improved plant WUE (Osmond, 1982, Ehleringer and Monson, 1993). Plant roots absorb nutrients mainly by mass flow and ion diffusion, where water acts as the common denominator. In addition to this, leaf surface transpiration uses a large amount of energy to cool plants lower than the ambient air temperature. Therefore, changes in plant water utilization could affect nutrient absorption and increase leaf temperature (Brouder and Volenec, 2008).

C4 plants use less water per unit leaf area relative to C3 plans because of their lower gs.

Since CO2 entry and H2O exit occur through the same pathway, reduction in gs reduces E (Long, 1999). Reduction in leaf water loss results in lower plant WUE, leading to higher plant WUE in C4 plants relative to C3 counterparts (Ehleringer and Monson,

1993, Kalapos et al., 1996). The advantage of increased plant WUE means that C4 plants conserve soil moisture and this may explain their predominance in hot, semiarid climates (Long, 1999). Both Asat and E are also influenced by temperature and leaf-to- air vapour pressure difference (VPD). Therefore, the environmental effects on leaf and plant WUE must be taken into account (Sage and Pearcy, 2004).

During photosynthetic CO2 fixation, plants discriminate against the less abundant, 13 naturally occurring stable isotope C. Carbon isotope discrimination () during C3 photosynthesis reflects biochemical fractionation of Rubisco during carboxylation and during CO2 diffusion into the leaf from the atmosphere (Farquhar et al., 1989a). The theoretical model to estimate carbon isotope discrimination in C3 pathway is as follows:



- Carbon isotope discrimination - The fractionation during diffusion of CO2 in air (4.4‰) b- The net fractionation associated carboxylation. Ci and Ca- Intercellular and ambient CO2 partial pressure (Farquhar et al., 1989a).

The fractionation of CO2 in C3 species occurs during the diffusion of CO2 from the atmosphere to the chloroplast and during Rubisco carboxylation. As a result of Rubiso’s large fractionation factor of 30‰, it has been observed that  has a linear relationship with Ci/Ca (Farquhar and Sharkey, 1982a). Furthermore, leaf dry matter carbon isotope 13 composition ( C) of C3 species show linear relationships between Ci/Ca and both  and WUE. Therefore, leaf 13C has been utilised as a screening tool for altered WUE (Farquhar and Richards, 1984, Brugnoli and Farquhar, 2000).

During C4 photosynthesis; carbon isotope discrimination () reflects the biochemical fractionation of both photosynthetic enzymes Rubisco and PEPC along with their interconnectivity (Farquhar, 1983). The theoretical model to estimate carbon isotope discrimination in C4 pathway is as follows:

 

- Carbon isotope discrimination - The fractionation during diffusion of CO2 in air (4.4‰) b4- The fractionation associated with PEP carboxylation. s- The fractionation during the leakage of CO2 out of the bundle sheath cells (1.8‰). b3- The fractionation during Rubisco carboxylation - Bundle sheath leakiness Ci/Ca- Intercellular to ambient CO2 partial pressure (Henderson et al., 1992).

In C4 species, the degree of Rubisco fractionation (the ratio of bundle sheath leak rate to PEP carboxylase rate) depends on the bundle sheath leakiness (). The slope of the relationship between  and Ci/Ca is determined by the value of . Using a number of C4 21

species belonging to different biochemical subtypes, Henderson et al. (1992) estimated

 to be about 0.2 using concurrent gas exchange measurements. When compared to C3 species, the slope of the relationship between  and Ci/Ca has the opposite sign in C4.

Therefore, the variation in  for a unit change in Ci/Ca is much less, for C4 compared to

C3 species. This along with the additional barriers of possible differences in  makes  a more complicated tool for analysing WUE in C4 plants (Henderson et al., 1998, Caemmerer et al., 2014).

1.4.2 Nitrogen use efficiency and Rubisco

N is the most abundant element in the atmosphere. It is available to plants, largely through the reduction of gaseous form of nitrogen (N2) and by recycling after decomposition of plant, animal and microbial detritus. The relationship between photosynthesis and leaf N is one of the most important functions in plant physiology, because photosynthesis provides the energy and structural substances necessary for reproduction, growth and foraging for additional N.

Photosynthetic nitrogen use efficiency (PNUE) is the net rate of leaf CO2 uptake in full sunlight (Asat) per unit leaf N content (Garnier et al., 1995). Plant N use efficiency (NUE) is the ratio of increase in plant biomass to increase in plant N, which is also the ratio of biomass to total leaf N at completion of growth (Field and Mooney, 1986). Plants invest large amounts (~70%) of N in the photosynthetic apparatus (Evans, 1983).

Distribution of leaf N in C4 species has already been examined in several studies (Makino et al., 2003, Ghannoum et al., 2005, Tazoe et al., 2006). It is well known that

C4 species invest less N into Rubisco relative to C3 (5-10% vs 20-30%) resulting in a major difference in their PNUE (Ku et al., 1979, Sage and Pearcy, 1987, Long, 1999,

Evans and Von Caemmerer, 1996). Overall, C4 species allocate 37% of leaf N into soluble proteins while C3 allocate 34%. The investment of leaf N in the thylakoid of C4 species (28%) is slightly higher than that of C3 species (22%) (Figure 1.7) (Evans and Poorter, 2001, Ghannoum et al., 2005).

C3 35 C4

Nitrogenpercentage (N%) 5

0 Soluble protein Rubisco Thylakoid Other

Figure 1. 7. Comparison of leaf nitrogen budgets between C3 and C4 species. Adapted from Ghannoum et al., (2011). Due to the large proportional investment of total leaf N in photosynthesis, the issue of how efficiently N is used has been of interest to physiologists and agronomists for a long time. Many studies have recognized the variation between C3 and C4 plants in NUE and PNUE which result from their different modes of carbon fixation (Bolton and

Brown, 1978, Brown, 1978, Sage and Pearcy, 1987). In C3 plants, Rubisco accounts for about 30% of the total leaf N. The C4 species generally have a 3-4 times less leaf N invested in Rubisco because their requirement for Rubisco is lower than C3 plants, due to the CCM (Ghannoum et al., 2005, Ku and Edwards, 1978, Sage and Pearcy, 1987).

C4 species attain higher Asat for a given content of Rubisco or leaf N (i.e. higher PNUE) relative to C3 plants. Due to the CCM, Rubisco in C4 leaves functions close to CO2 o saturation below 30 C. However, C3 leaves assign 3-4 times more N to Rubisco than C4 leaves to maintain their Asat per Rubisco sites. Furthermore, C4 species have a greater c catalytic turnover rate (k cat) than C3 as a result of greater Michaelis–Menten constant for CO2 (Kc) (Badger and Andrews, 1987, Sage, 2002). However, C4 species achieve c the full benefit of greater k cat only at high temperature. Under lower temperatures some

C4 species have shown to allocate more of their leaf N to Rubisco (Long, 1999, Sage, 2002, Dwyer et al., 2007, Sage and Kubien, 2007).

1.5 Physiology of the C4 subtypes

1.5.1 Water use efficiency of the C4 subtypes

The worldwide distribution of C4 grasses is positively correlated with growing season temperature (Vogel, 1978, Hattersley, 1983). The geographic distribution of C4 grasses is also influenced by rainfall. With the rise in annual rainfall, the amount of NADP-ME and PCK species were higher, while low rainfall areas were prevalent with NAD-ME species (Ellis et al., 1980; Hattersley, 1992). This contrasting biogeography suggests that C4 grasses with different biochemical subtypes may have different WUE, and these differences may have contributed to variation in their distribution along rainfall gradients.

Ghannoum and colleagues conducted a set of glasshouse experiments using wild C4 grasses under different environmental conditions (Ghannoum et al., 2001a, Ghannoum et al., 2001b). When 28 NAD-ME or NADP-ME grasses were grown under well- watered conditions, the authors observed that the two subtypes had similar leaf and plant WUE. In addition, when summer and winter-grown plants were compared, variations in plant WUE was observed between the subtypes, and this was caused by variation in daily irradiance and VPD (Ghannoum et al., 2001a, b).

However, in a comparison of WUE between NAD-ME and NADP-ME C4 grasses exposed to water stress, plant WUE of C4 species from both subtypes increased under water stress. The authors suggested that this improvement of plant WUE was most likely due to decreased gs, and hence possibly lower Ci/Ca, as inferred by a more negative leaf dry matter (δ13C) (Ghannoum et al., 2002). Interestingly, the water stress response was much higher in NAD-ME relative to NADP-ME species, such that the former group improved their plant WUE to a greater extent relative to their NADP-ME counterparts (Ghannoum et al., 2002, Ghannoum et al., 2011).

Hydraulic hypothesis of Osborne and Sack (2012) argues that higher hydraulic conductance (shorter interveinal distances) in C4 plants make them less prone to hydraulic failure in dry environments, thus increasing their advantage in maintaining

open stomata at low [CO2] relative to C3 plants (Osborne and Sack, 2012). This theory could also be applied to NAD-ME grasses which have longer interveinal distances (hence, lower hydraulic conductance) than NADP- ME and PCK subtypes (Dengler et al., 1994, Whitney and Andrews, 2001). NADP-ME and PCK species can open their stomata at low [CO2] in order to maintain carbon gain without risking hydraulic failure but at the expense of reduced PWUE given they are distributed in wetter environments; unlike the NAD-ME grasses which prevail in drier habitats, placing a greater pressure on avoiding hydraulic failure and maintaining higher PWUE (Evans, 1983, Osborne and

Sack, 2012). Furthermore, Kawamitsu et al. (1987) using a small number of C4 grasses observed that under high VPD, PWUE of NAD-ME species was greater than NADP- ME. In conclusion, these studies suggested that NAD-ME species may be more water use efficient than NADP-ME species.

It is worth noting that leaf dry matter of NAD-ME species are consistently reported to be depleted in 13C (δ13C) compared to NADP-ME leaves, possibly as a result of differences in their leakiness (Hattersley, 1982, Buchmann et al., 1996b). The suberised lamella present in NADP-ME is hypothesised to reduce the CO2 diffusion across the bundle sheath cell. However, the difference in leaf dry matter δ13C does not correlate well with the photosynthetic carbon isotope discrimination,  (Henderson et al., 1992, Cousins et al., 2008, Caemmerer et al., 2014). In a recent review Caemmerer et al., (2014) suggested that post-photosynthetic fractionations, organic material composition within the leaves, variation in the δ13C of leaf carbohydrates exported from source leaves and the variation in the respiratory processes between NAD-ME and NADP-ME subtypes might be responsible for this difference in the δ13C between NAD-ME and NADP-ME subtype.

1.5.2 Nitrogen use efficiency of the C4 subtypes

The leaf- and cell- level N distribution between soluble and thylakoid pools of NAD-

ME and NADP-ME C4 grasses has already been established. Bundle sheath cell of NAD-ME grass leaves contained 60% of leaf N and chlorophyll, whereas NADP-ME grass leaves contained only 35%. The thylakoid membranes accounted for about 28% of leaf N regardless of the subtype. In terms of the thylakoid complexes, NADP-ME 25

species contained similar photosystem I (PSI) amounts between bundle sheath and mesophyll cells, while NAD-ME species had less amount of PSII in the bundle sheath relative to the mesophyll. The amount of photosystem II (PSII) was negligible in bundle sheath cells (Ghannoum et al., 2005). The lack PSII in NADP-ME bundle sheath cells may be a mechanism to prevent the accumulation of high [O2] in the bundle sheath cell (Woo et al., 1970, Edwards et al., 1976).

Very few studies have compared NUE among C4 species belonging to the different C4 subtypes or lineages. In the few studies published on this topic, NAD-ME and NADP- ME were used due to their widest taxonomic distribution. The NAD-ME pathway involves large number of transformations of intermediates adding a complexity to this subtype and imposing an extra cost of N for the construction of the enzymes (Bowman, 1991). Therefore, it was hypothesised that at a given leaf [N], NADP-ME subtype would have a greater assimilation rate than NAD-ME subtype. By comparing four NAD-ME and two NADP-ME members of the grass genus Panicum grown at high N availability Bowman (1991) found that the shoot [N] was greater in NAD-ME than the NADP-ME subtype species. Similarly, using three NAD-ME and three NADP-ME species, LeCain and Morgan (1998) showed that leaf [N] was higher in NAD-ME than in NADP-ME grasses. These results indicated that NAD-ME species may invest large amount of N to photosynthetic tissues by compromising their PNUE (LeCain and

Morgan, 1998). Along the same line, Ghannoum et al. (2005) observed similar Asat amongst 27 NAD-ME and NADP-ME grasses under common growth conditions.

However, NAD-ME species used more leaf [N] than NADP-ME to get the similar Asat and resulted in lower PNUE than NADP-ME. Greater PNUE of NADP-ME relative to c NAD-ME was also related to differences in the in vitro k cat of those species. An earlier c C4 study has noted that k cat of Rubisco from NADP-ME species is greater than in NAD- ME counterparts (Seemann et al., 1984). However, Ghannoum et al. (2005), with the c use of in vitro (gas exchange) measurements of k cat, demonstrated that the NADP-ME c grasses had Rubisco with faster k cat that explained the difference in their PNUE. This leaf level difference in PNUE between the subtypes was also observed at whole plant level in a lesser extent. In a long term field experiment, fertiliser application increased the abundance of NAD-ME species with a higher N requirement while NADP-ME species abundance was reduced (Knapp and Medina, 1999). 26

However, most of these observations were made using a small number of C4 grasses without considering the phylogenetic diversity that exists particularly among NADP- ME lineages (Grass Phylogeny Working Group, 2012). When such complexity was considered, it was found that while the Andropogoneae (NADP-ME) grasses maintained higher PNUE relative to other C3 and C4 grasses, the Aristidoideae (NADP-ME) grasses had PNUE similar to C3 counterparts (Taylor et al., 2010). Therefore, it is important to consider the phylogenetic diversity amongst the C4 species to get a clear understanding of the physiological consequences of this complex photosynthetic pathway.

1.6 Gaps in the literature

As discussed in the previous sections, there is general agreement in the literature that the depletion of [CO2] in the atmosphere 30 Mya led to the evolution of the CO2 concentrating mechanisms in C4 plants. The complex anatomical and biochemical constituents of the C4 carbon concentrating mechanism are highly diverse. Notably, CO2 is supplied to Rubisco via three alternative decarboxylation pathways, NADP-ME, NAD-ME and PCK. In addition to well-documented anatomical and biochemical variation, C4 grasses are associated with particular physiological traits. Despite the large number of studies conducted over the last three decades, there are still a number of gaps in our knowledge about the phenotypic diversity among C4 grasses which raised questions about its relatedness to the biochemical subtype or the evolutionary history. Importantly, only a few studies have considered the full spectrum of biochemical

(including PCK species) or phylogenetic variation among C4 plants.

Previous work has shown that NADP-ME species tend to have higher photosynthetic nitrogen use efficiency (PNUE) relative to other C4 counterparts. Higher PNUE in NADP-ME grasses was associated with a faster Rubisco enzyme, which in turn, was associated with contrasting leaf nitrogen allocation between the photosynthetic cells. Given that these traits are associated with the biochemical pathway, it is still not yet clear whether PNUE will vary according to the subtypes among C4 grasses originating in different lineages (gaps addressed in Chapter 2).

Species with the NAD-ME subtype are predominantly found in the driest habitats, and the percentage of the C4 grass flora using the NADP-ME subtype increases with rainfall. Furthermore, it had been observed that NAD-ME grasses increased their whole- plant water use efficiency (WUE) to a greater extent than their NADP-ME counterparts under water stress. These variations were related to stomatal traits, which are likely to reflect ecological adaptation of the lineages in which the C4 taxa have evolved.

However, it is not yet investigated whether this observed variation in WUE among C4 grasses is aligned with their evolutionary origin of the C4 taxa (gaps addressed in Chapters 2 and 4).

C4 photosynthesis evolved under high photorespiratory (atmosphere depleted in CO2 and water vapour) environments to overcome the inefficiencies of their ancestral C3 photosynthetic pathway. However, most of the physiological comparison studies of C4 grasses were undertaken under current ambient [CO2], which does not reflect the CO2 environment under which C4 grasses have evolved, and which is fully saturating for C4 photosynthesis. A few published studies investigated the response of C4 species to inter- -1 glacial [CO2] (270-300 µl L ). However, the majority of these studies compared the responses of taxonomically divergent C3 and C4 species. Furthermore, only a few published studies have investigated the response of C4 grasses under high vapour pressure deficit (VPD) environments. High VPD may have been one of the major stimuli that enabled C4 evolutionary trends to commence in many taxa, leading to improved chances of survival under dry environments. Therefore, in order to elucidate the physiological or ecological advantage that particular traits may confer to C4 evolution, physiological studies must be undertaken under high photorespiratory conditions (low atmospheric CO2, high VPD) that prevailed during the evolution and expansion of C4 grasses (gaps addressed in Chapters 2 and 4).

Geological fluctuations in atmospheric [CO2] have shaped the Earth’s vegetation, yet we know relatively little about the physiological response of C3 and C4 plants to the

[CO2] levels that dominated during the recent glaciations. Consequently, it remains unclear how does inter-glacial [CO2] affect the variations in photosynthetic WUE and

NUE among related C3, C3-C4 and C4 grasses (gaps addressed in Chapter 3).

Past studies revealed little difference in bundle sheath leakiness () between NAD-ME and NADP-ME C4 grasses. Furthermore, NADP-ME species have low PSII activity in bundle sheath cells relative to NAD-ME species. However, published studies on variations in  and PSII activity used a small number of species, which did not comprehensively account for the biochemical and evolutionary diversity among the C4 grasses (gaps addressed in Chapter 5).

1.7 Aims and objectives of this research

The main aims of this project

The overall aim of this PhD project was to compare the photosynthetic physiology and resource use efficiency of diverse range of C4 grasses belonging to different biochemical subtypes (NAD-ME, PCK, NADP-ME) and six evolutionary origins (Paspalum, Andropogoneae, Echinochloa, Digitaria, Paniceae and Chloridoideae) under environmental conditions that promote high photorespiration rates (low atmospheric

CO2 and high atmospheric water deficit).

The specific objectives of each chapter:

 The main objectives of chapter 2 were to (i) investigate the influence of the biochemical subtype and evolutionary origin in grouping physiological traits

(particularly, photosynthetic NUE and WUE) in a large number of C4 grasses;

and (ii) determine whether low [CO2] or phylogenetic relatedness among the C4 species influenced these relationships (Chapter 2).

 The main objective of chapter 3 was to investigate how glacial [CO2] influences

photosynthetic physiology of closely-related C3, C3-C4 and C4 grasses (Chapter 3).

 The main objectives of chapter 4 were to (i) investigate the influence of the biochemical subtype and evolutionary origin in grouping physiological traits 29

associated with WUE in a large number of C4 grasses; and (ii) determine how high VPD influence these relationships (Chapter 4).

 The main objective of chapter 5 was to determine in a large number of C4 grasses belonging to the three biochemical subtypes (i) variations in the

efficiency of the CO2 concentrating mechanism by estimating bundle sheath

leakiness to CO2; and (ii) the distribution of PSII and PSI activities in bundle sheath and mesophyll cells (Chapter 5).

1.8 Format of the thesis

This thesis is presented as a series of four experimental papers accepted, submitted or prepared for submission to peer-reviewed journals. There are six chapters in this thesis. In addition to four experimental chapters (Chapter 2, 3, 4 and 5), there is an introductory literature review (Chapter 1) and a final synthesis and general discussion (Chapter 6) that contextualises the research, discusses key findings and outlines prospects for future research.

Chapter 2: Submitted to the journal of Plant, Cell and Environment Pinto H, Powell J, Sharwood RE, Tissue DT, Ghannoum O (2014). Variations in nitrogen and water use efficiency among C4 grasses at inter-glacial [CO2] reflect the biochemical subtype and evolutionary origin, respectively. Plant, Cell and Environment (in revision).

Chapter 3: Published in the Journal of Experimental Botany

Pinto H, Sharwood RE, Tissue DT, Ghannoum O (2014). Photosynthesis of C3, C3–C4, and C4 grasses at glacial CO2. Journal of Experimental Botany, 65, 3669-3681.

Chapter 4: To be submitted to the Journal of Experimental Botany

Pinto H, Tissue DT, Ghannoum O. The sensitivity of water use efficiency in C4 grasses to atmospheric aridity depends on maximal stomatal conductance (in preparation).

Chapter 5: To be published as part of a publication on the “Diversification of C4 photosynthesis” by Ghannoum. Pinto and others (in preparation).

* * * * *

CHAPTER 2

PHOTOSYNTHETIC PHYSIOLOGY OF C4 GRASSES

REFLECTS AT INTER-GLACIAL CO2 THE BIOCHEMICAL SUBTYPE AND EVOLUTIONARY ORIGIN

Chapter 2 formed the basis of the following manuscript, which is currently under review:

Pinto H, Powell J, Sharwood RE, Tissue DT, Ghannoum O (2014). Variations in

nitrogen and water use efficiency among C4 grasses at inter-glacial [CO2] reflect the biochemical subtype and evolutionary origin, respectively. Plant, Cell and Environment (in revision).

I declare that I was the primary investigator and author for Chapter 2. I designed and carried out the experiment, collected and analysed the data, wrote the text and prepared the tables and figures. I received appropriate guidance from my supervisory panel, and statistical advice from Dr Jeff Powell.

Abstract

C4 photosynthesis has evolved multiple times with diverse phenotypes, improving the fitness of C4 plants under high photorespiratory conditions. Most studies that ascribe physiological advantages to C4 plants have been conducted at current CO2, which does not reflect the low atmospheric CO2 under which the C4 pathway has evolved. In this study, 24 C4 grasses belonging to three biochemical subtypes (NAD-ME, PCK and NADP-ME) and six dominant evolutionary origins: Andropogoneae, Digitaria, Echinochloa, Paspalum (NADP-ME), Chloridoideae (NAD-ME, PCK) and Paniceae (NADP-ME, NAD-ME and PCK) were grown under ambient (400 μl L-1) and inter- -1 glacial (280 μl L ) atmospheric CO2. I hypothesised that nitrogen-related and water- related physiological traits were associated with biochemical subtypes and evolutionary origins, respectively, and more strongly under low CO2. Photosynthetic rate (Asat) and stomatal conductance (gs) were constrained by the shared evolutionary history among grasses, while variation in leaf mass per area (LMA), leaf N concentration per area (leaf

[N]area), plant dry mass and plant water use efficiency were affected by the biochemical subtype. Biochemical subtype and evolutionary origin were equally important for explaining variation in photosynthetic nitrogen use efficiency (PNUE) and photosynthetic water use efficiency (PWUE). CO2 treatment impacted most parameters, and was the only factor affecting leaf N concentration per dry mass (leaf [N]mass). For most parameters, phylogenetic dependence was generally weak (λ < 0.3) and non- significant (p < 0.05 for λ = 0). A redundancy analysis revealed that higher LMA and leaf [N]area distinguished the Chloridoideae/NAD-ME group, while NADP-ME and PCK grasses were distinguished by higher PNUE and activities of the photosynthetic enzymes Rubisco and PEPC, regardless of the evolutionary origin. Plants grown at ambient CO2 were characterised by high Asat and PWUE, while those grown at inter- glacial CO2 were characterised by high gs and transpiration rates. This study found that the evolutionary and biochemical diversity among C4 grasses was aligned with discernible leaf physiology traits under low and ambient atmospheric CO2. The extent to which these traits represent ecological adaptations or confer physiological fitness requires further investigation.

2.1 Introduction

Declining atmospheric CO2 concentration ([CO2]) during the Oligocene, about 30 million years ago (Mya), is considered one of the major environmental drivers for the evolution of C4 photosynthesis (Ehleringer et al., 1997, Pagani et al., 2005, Tipple and

Pagani, 2007, Christin et al., 2008a). C4 photosynthesis is a complex trait that evolved from ancestral C3 plants via a series of anatomical and biochemical modifications

(Hatch, 1987). C3 photosynthesis is not favoured at low [CO2] due to increased oxygenase activity and reduced carboxylase activity of ribulose-1,5-bisphosphate carboxylase-oxygenase (Rubisco). Rubisco oxygenation initiates the process of photorespiration, which culminates in the loss of CO2 and energy. The fitness of C3 photosynthesis declines further at high temperature due to increased oxygenation/carboxylation ratio of Rubisco (Jordan and Ogren, 1984). This situation facilitated the evolution of the CO2 concentrating mechanism (CCM) in C4 plants

(Ehleringer and Pearcy, 1983, Sage et al., 2012). The CCM serves to elevate [CO2] around Rubisco, thus saturating photosynthesis and suppressing net photorespiration in air (Hatch, 1987). Consequently, C4 plants possess competitive advantages over C3 plants in warm, open and dry habitats (Osmond, 1982, Ehleringer and Monson, 1993).

Furthermore, under declining CO2 concentrations, increased evaporation and more seasonal precipitation are considered as drivers for the diversification of both C3 and C4 pathways by maintain consistent hydraulic conductance and cavitation repair (Griffiths et al., 2013).

C4 plants account for about 3% of extant angiosperm species, but the C4 photosynthetic pathway is prevalent among grasses, with 45% of the Poaceae (grass) family comprised of C4 species (Sage et al., 1999, Sage and Pearcy, 2004). C4 grasses are ecologically and economically important, accounting for 20-25% of global terrestrial primary productivity (Lloyd and Farquhar, 1994, Still et al., 2003). C4 photosynthesis has evolved numerous independent times, such that C4 plants are biochemically and phylogenetically diverse. In grasses, three C4 biochemical subtypes have been identified based on the primary C4 acid decarboxylase enzyme operating in the bundle sheath cells. These enzymes are nicotinamide adenine dinucleotide phosphate malic enzyme

(NADP–ME), nicotinamide adenine dinucleotide malic enzyme (NAD–ME) and phosphoenolpyruvate carboxykinase (PCK) (Gutierrez et al., 1974, Prendergast et al., 1987). Recent phylogenetic analyses identified 24 distinct grass lineages that independently evolved the C4 pathway from C3 ancestors (Grass Phylogeny Working

Group, 2012). These analyses also confirmed the strong association between the C4 subtypes and certain grass subfamilies. In particular, C4 species with classical NADP- ME type anatomy in the Panicoideae subfamily occur in the Andropogoneae, Arundinelleae and Paniceae tribes. The classical NAD-ME and PCK type anatomy predominantly occur in the Chloridoideae subfamily, and evolved once in the Panicum/Urochloa/Setaria clade within the Panicoideae subfamily (Hattersley and Watson, 1992, Sage et al., 1999, Aliscioni et al., 2003, Vicentini et al., 2008, Christin et al., 2009a).

In addition to well-documented anatomical and biochemical variation (Prendergast et al., 1987, Dengler et al., 1994, Edwards and Voznesenskaya, 2011), C4 grasses are associated with particular physiological traits (Hattersley and Watson, 1992, Ghannoum et al., 2011). The phenotypic diversity among C4 grasses has raised questions about its relatedness to the biochemical subtype or the evolutionary history. However, only a few studies have considered the full spectrum of biochemical (including PCK species) or phylogenetic variation among C4 plants.

Previous work has shown that NADP-ME species tend to have higher photosynthetic nitrogen use efficiency (PNUE) relative to other C4 grasses (Taub and Lerdau, 2000, Ghannoum et al., 2005) except for one NADP-ME lineage (Aristidoideae) which had

PNUE similar to C3 counterparts (Taylor et al., 2010). Higher PNUE in NADP-ME grasses was associated with faster Rubisco enzyme (Seemann et al., 1984, Ghannoum et al., 2005), which in turn, was associated with contrasting nitrogen, chlorophyll and PSII allocation between the mesophyll and bundle sheath cells (Edwards et al., 1976, Hatch and Osmond, 1976, Ghannoum et al., 2005). Given that these traits are associated with the biochemical pathway, I hypothesise that PNUE will vary according to the subtypes among C4 grasses originating in different lineages (hypothesis 1).

Strong correlations have been observed between average annual precipitation and the percentage of the C4 grass flora with a particular C4 subtype. Species with the NAD-ME subtype are predominantly found in the driest habitats, and the percentage of the C4 grass flora using the NADP-ME subtype increases with rainfall (Ellis, Vogel & Fuls, 1980,

Hattersley, 1992, Taub, 2000). In line with these observations, NAD-ME grasses increased their whole-plant water use efficiency (WUE) to a greater extent than their

NADP-ME counterparts under water stress (Ghannoum, von Caemmerer & Conroy,

2002). Variation in WUE among C4 grasses was related to stomatal traits (Ghannoum et al., 2002, Taylor et al., 2012); and stomatal patterning shows a strong phylogenetic signal in grasses which likely reflects the ecological adaptation of the grass lineages

(Liu et al., 2012, Liu & Osborne, 2014). Consequently, I hypothesise that variation in

WUE among C4 grasses is aligned with the evolutionary lineage of the C4 taxa

(hypothesis 2).

These aforementioned physiological comparisons were undertaken under current ambient [CO2] which does not reflect the CO2 environment under which C4 grasses have evolved (Sage, 2004, Christin et al., 2008b), and which is fully saturating for C4 photosynthesis (Ghannoum et al., 2000, Ghannoum, 2009). A few published studies -1 investigated the response of C4 species to inter-glacial [CO2] (270-300 µl L ). However, the majority of these studies compared the responses of taxonomically divergent C3 and C4 species (Dippery et al., 1995, Tissue et al., 1995, Ward et al., 1999, Anderson et al., 2001, Maherali et al., 2002, Pinto et al., 2011, Ripley et al., 2013). A summary of the low [CO2] responses of main physiological parameters reported in the literature is shown in Appendices 1 and 2. In order to elucidate the physiological or ecological advantage that particular traits may confer to C4 evolution, physiological studies must be undertaken under the low atmospheric CO2 that prevailed during the evolution and expansion of C4 grasses. Therefore, I hypothesise that physiological traits are more strongly aligned with the biochemical subtype or evolutionary origin under inter-glacial [CO2] relative to ambient [CO2] (hypothesis 3).

Consequently, the current study investigated the variability of responses of photosynthetic WUE and NUE, as well as the activity of the photosynthetic carboxylase 36

enzymes in 24 different C4 grasses belonging to three biochemical subtypes (NADP- ME, NAD-ME and PCK) and six major evolutionary origins: Paspalum (NADP-ME), Andropogoneae (NADP-ME), Echinochloa (NADP-ME), Digitaria (NADP-ME), Paniceae (NADP-ME, NAD-ME, PCK) and Chloridoideae (NAD-ME, PCK) and -1 -1 grown under ambient (400 μl L ) to inter-glacial (280 μl L ) [CO2]. The main objectives of this study were to (1) Investigate the variability influence of the biochemical subtype to evolutionary origin in structuring physiological traits

(particularly, photosynthetic NUE and WUE) in a large number of C4 grasses; and (2)

Determine whether low [CO2] or phylogenetic relatedness among the C4 species influenced these relationships.

2.2 Materials and Methods

2.2.1 Plant culture and water use measurements

The experiment was conducted in two naturally-lit glasshouse chambers (~5 m3 each) equipped with CO2 and temperature control (Pinto et al., 2011). The air in the inter- -1 glacial [CO2] (target 280 µl L ) chamber was scrubbed of excess CO2 by soda lime

(Schaefer Kalk GmbH & Co KG, Diez, Germany) to achieve the low [CO2]. The CO2 in -1 the ambient [CO2] chamber was maintained at 400 µl L . The [CO2] was automatically monitored and controlled by CO2 infra-red gas analysers (IRGA) (Lambda T, ADC

BioScientific Ltd., Herts, UK) interfaced with electronic gas valves. Chamber [CO2] was continuously recorded by logging the voltage output of the CO2 monitors/controllers using a data logger (DL2e, Delta-T Devices Ltd, Cambridge, UK). -1 The average day/night [CO2] in the inter-glacial [CO2] chamber was 277/280 µl L , -1 while that in the ambient [CO2] chamber was 394/398 µl L . The average day/night temperature for both treatments was 24/19oC. The daily average relative humidity in the inter-glacial [CO2] and ambient [CO2] chambers was 65% and 63%, respectively.

Soil was collected from the Hawkesbury Field Experiment site, University of Western Hawkesbury campus, Richmond, NSW. A detailed description of soil physical and chemical properties can be found in (Ghannoum et al., 2010). Polyethylene bags were placed inside each 3.5 L cylindrical pot to prevent water leakage. Mass of the pots was adjusted to 0.8 kg using pebbles. Air-dried and coarsely sieved soil (3.7 kg) was added to the pots, which were watered to 100% capacity, then transferred to the two glasshouse chambers. Soil water capacity was calculated as the difference between the mass of two non-watered pots and that of pots watered and left to drain freely overnight.

Seeds for the different species (Figure 2.1) were obtained from Australian Plant Genetic Resources Information System (QLD, Australia) and Queensland Agricultural Seeds Pty. Ltd., (Toowoomba, Australia). Seeds were sown in germination trays containing a common germination mix. Three to four weeks after germination, three seedlings were transplanted into each of the soil-filled pots. Within a week of transplanting, one healthy seedling was left in the pot while the other seedlings were removed. There were four

pots per species and CO2 treatment. Pots were rotated within each chamber regularly, and the pots and treatments were swapped between chambers at regular intervals to minimise any chamber effects. The similar growth conditions between the two treatments confirmed that growth conditions, other than the CO2 treatment, were well matched.

Paspalum dilatatum Poiret (NADP-ME) Paspalum notatum Flüggé (NADP-ME) Paspalum (NADP-ME)

Bothriochloa pertusa (L.) A. Camus (NADP-ME) Sorghum bicolor (L.) Moench (NADP-ME) Zea mays L. (NADP-ME) Andropogoneae (NADP-ME)

Echinochloa chacoensis Michael (NADP-ME) Echinochloa frumentacea Link (NADP-ME) Echinochloa turneriana (Domin) Black. Fl. (NADP-ME) Echinochloa NADP-ME) ( Setaria italica (L.) P. Beauvois (NADP-ME) Eriochloa meyeriana (Nees) (PCK) Urochloa maxima (Jacq.) R. D. Webster (PCK) Paniceae Urochloa panicoides P. Beauv (PCK) NADP-ME+PCK+NAD-ME Panicum coloratum L. (NAD-ME) Panicum miliaceum L. (NAD-ME) Panicum virgatum L. (NAD-ME)

Digitaria Digitaria eriantha Steud. (NADP-ME) (NADP-ME) Astrebla lappacea (Lindl.) (NAD-ME) Astrebla pectinata (Lindl.) F. Muell. (NAD-ME) Enteropogon acicularis (Lindl.) Lazarides (NAD-ME) Eleusine coracana (L.) Gaertn. (NAD-ME) Chloridoideae Eragrostis curvula (Schrad.) (NAD-ME) Eragrostis lehmanniana Nees (NAD-ME) (NAD-ME+PCK) Leptochloa fusca (L.) Kunth (NAD-ME) Chloris gayana Kunth (PCK)

Mya 30 20 10 0

Figure 2. 1. C4 grass species used in the current study.

Calibrated phylogeny tree, based on Christian et al., (2009), representing the origins, subtypes and species used in the experiment.

Mass of each pot was recorded prior to watering and mass of all the pots were maintained at 5.6 kg after watering to 100% soil water capacity. There were two pots filled with soil, but without plants, in each room; these pots were used to estimate water loss by direct soil evaporation. Cumulative water use was calculated by summing daily water use and subtracting the amount of water loss from control pots without plants. A commercial fertilizer (General Purpose, Thrive Professional, Yates, Australia) was used twice every week (0.2 g N L-1).

2.2.2 Gas exchange measurements

Concurrent gas exchange measurements were conducted using a portable open gas exchange system (LI-6400XT, LI-COR, Lincoln, NE, USA) to determine light-saturated photosynthetic rate (Asat), stomatal conductance (gs). Measurements were conducted between 10:00 and 14:00 about 7-8 weeks after transplanting on an attached, last fully expanded leaf (LFEL) on the main stem. Measurements were made at a photosynthetic photon flux density of 1800 μmol m-2 s-1. Photosynthetic rates were measured at target -1 growth [CO2] (280 or 400 μl L ) and target mid-day growth temperature (26 ºC). Leaf- to-air vapour pressure deficit ranged between 1.6 and 2.0 kPa. Before each measurement, the leaf was allowed to stabilise for 10-20 min until it reached a steady state of CO2 uptake. There were 4 replicate measurements per treatment.

2.2.3 Rubisco, PEPC activity and soluble protein

Following gas exchange measurements made at growth [CO2], replicate leaf discs (1-2 cm2) were collected under high light, rapidly frozen in liquid nitrogen, and then stored at -80oC until biochemical analysis. Each leaf disc was extracted in 1 mL of ice-cold extraction buffer (50 mM EPPS-NaOH pH 8.0, 5 mM DTT, 15 mM NaHCO3, 20 mM

MgCl2, 2 mM EDTA, 4% (v/v) protease inhibitor cocktail (Sigma) and 1% (w/v) PVPP using a 2 mL Potter-Elvehjem glass homogeniser kept on ice. The extract was centrifuged at 16,100g for 1 min and the supernatant used for enzyme activity and soluble protein assays as previously described (Pinto et al., 2014).

Briefly, Rubisco content was estimated by the irreversible binding of [14C]-CABP to the fully carbamylated enzyme (Ruuska et al., 1998). Rubisco activity (in vitro Vcmax) was estimated by multiplying the concentration of active sites determined using the [14C]- c CABP assay by the in vitro turnover rate (k cat) of the various C4 grasses (RE Sharwood, O Ghannoum, SM Whitney; unpublished). PEPC activity was determined using a UV- VIS spectrophotometer (model 8453, Agilent Technologies Australia, Mulgrave, Victoria) as previously described by (Ashton et al., 1990, Pengelly et al., 2012). Soluble proteins were measured using the Pierce Coomassie Plus (Bradford) protein assay kit (Thermo scientific, Rockford, Illinois, USA).

2.2.4 Growth and nitrogen analyses

Following gas exchange measurements, the LFEL was cut and its area determined using a leaf area meter (LI-3100A, LI-COR, Lincoln, NE, USA). The LFEL was oven-dried, weighed then milled to a fine powder. Tissue [N] was determined on the ground samples using a CHN analyser (LECO TruSpec, LECO Corporation, Michigan, USA). -1 -2 Leaf N per unit area ([N]area) was calculated as (mmol N g ) * LMA (g m ).

Plants were harvested 12 weeks after transplanting. At harvest, total leaf area was measured using a leaf area meter (LI-3100A, LI-COR, Lincoln, NE, USA). Shoots were separated into stems and leaves. Roots were washed free of soil. Plant materials were oven-dried at 80ºC for 48h before dry mass was measured. Leaf mass per area (LMA) was calculated as total leaf mass (g)/total leaf area (m2).

2.2.5 WUE and NUE calculations

Plant WUE (WUE) was calculated as total plant dry mass (g plant-1)/total cumulative water use of an individual plant (g plant-1). Photosynthetic WUE (PWUE) was -2 -1 -2 -1 calculated as Asat (μmol m s )/gs (mol m s ). Leaf NUE was calculated as the ratio of plant dry mass (g plant-1)/Leaf N content (mg). Photosynthetic N use efficiency (PNUE) -2 -1 -2 was calculated as Asat (μmol m s )/Leaf [N]area (mmol m ).

2.2.6 Statistical analysis

Linear mixed effect (lme) model. Growth, water use and gas exchange measurements were performed on four replicates per treatment combination (species x CO2 level), while tissue N analysis was performed on three replicates per treatment. Since measurements were taken on multiple individuals within a species, each unit cannot be considered a true independent replicate. Therefore, I used linear mixed effects (lme) models to estimate fixed effects, associated with CO2 treatment, evolutionary lineage (taxonomic family) and subtype, and random effects, associated with species identity. Model residuals were tested (Shapiro) for normality and extreme outliers removed before refitting models. To certain effects, lineage and subtype were collinear so models containing all combinations of fixed effects were fitted using lme4 (Bates, Maechler & Bolker, 2012) package in R (R Foundation for statistical computing, Vienna, Australia) and the Akaike information criterion (AIC) and Akaike weight (wi) was calculated for all models of each response variable to estimate the relative importance of the parameters as predictors; for each response variable, the importance of individual parameters was calculated as the sum of Akaike weights across all models that included the parameter in question (Burnham and Anderson, 2002). This approach does not explicitly determine whether individual parameters are statistically ‘significant’ (although this could be determined using likelihood ratio tests) but ranks parameters based on their ability to explain variation.

Phylogenetic analysis. To more explicitly estimate the contribution of shared evolutionary history to the response to the CO2 treatment, I conducted phylogenetic generalised least squares (pgls) analysis after incorporating the covariance between taxa into the calculation of estimated coefficients using the caper function in R (Orme et al., 2013). The topology and phylogenetic branch lengths associated with the grass species that I used here were obtained from phylogenetic tree provided in (Spriggs et al., 2014).

Species means of ambient, inter-glacial and ambient to inter-glacial [CO2] ratios of various response variables were analysed using subtype as fixed effect in models constrained by phylogenetic relationships. The degree of phylogenetic dependence on physiological parameters amongst species was given in λ (Freckleton et al., 2002).

RDA analysis. The influence of evolutionary origins and biochemical subtypes on the species patterns was examined by using redundancy analysis (RDA) in CANOCO software (Braak and Šmilauer, 2002). The dataset was standardised using Euclidean- based ordination method. The significance of each environmental and response variable was tested using Monte-Carlo permutation tests, based on 999 permutations.

2.3 Results

2.3.1 Summary of the linear mixed effect (lme) statistical analysis

The lme model was determined using the raw data (Figure 2.2A, Table 2.1A) as well as the 280/400 [CO2] ratio in order to test how the CO2 responsiveness of the various parameters was influenced by the biochemical subtype or the evolutionary origin (Figure 2.2B, Table 2.1B). For the 280/400 ratios, plants were paired across their respective treatment.

Overall, the lme model including the response variables of evolutionary origin and CO2 treatment best explained variation in photosynthetic rate (Asat) and stomatal conductance

(gs), while the model that included the biochemical subtype and CO2 treatment best explained variation in leaf mass per unit area (LMA), leaf N concentration per unit area

(Leaf [N]area), plant dry mass (DM) and WUE; otherwise, the biochemical subtype and evolutionary origin were equally important for explaining the variation in photosynthetic nitrogen use efficiency (PNUE) and photosynthetic water use efficiency

(PWUE). The CO2 treatment impacted most leaf and plant physiological traits, and was the only factor driving changes in intercellular [CO2] and leaf N concentration per unit dry mass (Leaf [N]mass). Plant NUE and activities of the photosynthetic enzymes Rubisco and PEPC were not well predicted by any of the lme combinations (Figure 2.2, Table 2.1).

2.3.2 Leaf water use efficiency

The lme model including the evolutionary origin and CO2 treatment best explained variation in Asat and gs, with Asat showing a strong CO2 response (Figure 2.2, Table 2.1).

Under both [CO2] treatments, Asat and gs were highest in the Echinochloa (NADP-ME) and lowest in Paspalum and Digitaria (NADP-ME) species (Figures 2.3A-B; Table 2.2).

Relative to ambient [CO2], inter-glacial [CO2] reduced Asat in all the C4 origins by an average of 29%. Inter-glacial [CO2] increased gs to a greater extent in the Paspalum, Digitaria and Andropogonea (67%, 61% and 52%, respectively) relative to the Paniceae, Echinochloa and Chloridoideae (21%, 19% and 12%, respectively) species (Figure 2.4).

Variations in PWUE were best predicted by the full model, with evolutionary origin showing a stronger weighting than biochemical subtype (Figure 2.2, Table 2.1). Under ambient [CO2], PWUE was lowest in the Echinochloa (NADP-ME) and Paniceae

(NADP-ME, NAD-ME, PCK) relative to the other species. Under inter-glacial [CO2],

PWUE was highest in the Chloridoideae (NAD-ME, PCK) relative to the other C4 origins (Figure 2.3C; Table 2.2). Inter-glacial [CO2] reduced PWUE in all the C4 species by an average of 48% compared with the ambient [CO2] treatment.

2.3.3 Leaf N use efficiency

The lme model containing the biochemical subtype and CO2 treatment best explained variations in LMA and leaf [N]area, while leaf [N]mass showed a large sensitivity to the

CO2 treatment (Figure 2.2, Table 2.1). Under both growth [CO2], LMA tended to be lowest in NADP-ME species, while leaf [N]area was highest in NAD-ME species relative to the other two subtypes (Fig. 2.5A-B; Table2.2 ). Inter-glacial [CO2] caused the largest decrease of LMA in the Chloridoideae/NAD-ME (13%) and of leaf [N] in the

PCK (17% for [N]mass and 22% for [N]area) species (Figure 2.4, Table 2.2).

Variations in PNUE among the C4 grasses were similarly explained by the lme models including the evolutionary origin or the biochemical subtype in addition to the CO2 treatment (Figure 2.2, Table 2.1). Under both [CO2] treatments, PNUE tended to be higher in the Andropogoneae/NADP-ME species relative to the other C4 groups (Figure

2.5C; Table 2.2). Inter-glacial [CO2] reduced PNUE the most in the Paspalum and

Digitaria (NADP-ME) species (42%) as a result of the large increases in leaf [N]area with reduced growth [CO2] (Figure 2.4, Table 2.2).

2.3.4 Plant water and nitrogen use efficiency

The lme model containing the biochemical subtype and CO2 treatment best explained variation in plant DM and WUE (Figure 2.2, Table 2.1). Under both [CO2] treatments, plant DM was lowest in the Paspalum and Echinochloa (NADP-ME) species and highest in the Andropogoneae (NADP-ME) species (Figure 2.5D, Table 2.2). Inter-

glacial [CO2] reduced plant DM the least in the NADP-ME (Andropogoneae, Paspalum and Echinochloa) species (12%, 5% and 2%, respectively) relative to the other C4 groups (Figure 2.4). Under both [CO2] treatments, plant WUE was lowest in the

Paspalum relative to the other C4 species (Figure 2.5F, Table 2.2). Inter-glacial [CO2] decreased plant WUE the most in the Echinochloa (NADP-ME) (40%) and the least in the Chloridoideae (NAD-ME, PCK) (10%) species relative to the other C4 counterparts (Figure 2.4).

Variation in plant NUE was not well explained by any of the lme model combinations

(Figure 2.2, Table 2.1). At ambient [CO2], plant NUE was not significantly different between the origins. At inter-glacial [CO2], plant NUE was highest in the Echinochloa (NADP-ME) and lowest in the Digitaria (NADP-ME) species (Figure 2.5E; Table 2.2).

Inter-glacial [CO2] increased plant NUE in most C4 species by an average of 26%. This increase was larger in the Paspalum, Echinochloa and Andropogoneae relative to the Paniceae, Chloridoideae and Digitaria origins, and occurred primarily because the former origins underwent the least plant DM reduction at inter-glacial [CO2] (Figure 2.4).

2.3.5 Activity and content of photosynthetic enzymes

The leaf content of soluble proteins and Rubisco, and the activity of Rubisco and PEPC, were not well predicted by the full lme model which included the evolutionary origin, biochemical subtype and CO2 treatment (Figure 2.2, Table 2.1). The main trends observed under both growth [CO2] treatments, were a higher and lower leaf Rubisco content and fraction of Rubisco per soluble protein in the Chloridoideae (NAD-ME, PCK) and Digitaria (NADP-ME) species, respectively, while the Echinochloa (NADP- ME) species had a higher PEPC activity and PEPC/Rubisco activity ratio relative to the other C4 groups (Table 2.3). Overall, there were no significant effects of atmospheric

[CO2] on PEPC, Rubisco or soluble proteins (Figure 2.6, Table 2.2).

2.3.6 The RDA for inter-glacial CO2 and ambient CO2

In order to examine the overall associations of the measured physiological parameters, a redundancy analysis (RDA) was undertaken (Figure 2.7). Accordingly, it was revealed that leaf transpiration rates and stomatal conductance were strongly associated with the inter-glacial [CO2] treatment (top-right quadrant), while PWUE and photosynthetic rate were strongly associated with the ambient [CO2] treatment (lower-left quadrant), such that these four parameters were largely indicative of the response to atmospheric [CO2].

Two parameters, leaf [N]area and LMA, were responsible for segregating the

Chloridoideade/NAD-ME species (top-left quadrant) away from all other C4 groups. The NADP-ME origins (Andropogoneae, Digitaria, Echinochloa and Paspalum) clustered together with the PCK/Paniceae species in the same quadrant (lower-right quadrant). This clustering was mostly brought about by the parameters Rubisco, PEPC and PNUE (Figure 2.7).

2.3.7 The phylogenetic effect on species under inter-glacial CO2 and ambient CO2

In the pgls analysis, only species means can be used, while replication and treatment factors cannot be considered. Accordingly, this analysis does not have the same statistical power as the lme model or the RDA in the current study. Nevertheless, the pgls analysis was used to determine whether phylogenetic relatedness, if any, would influence the structuring of physiological traits along the biochemical subtypes or evolutionary origins of the various C4 species. In the pgls analysis, λ = 0 tests for the phylogenetic dependence of a trait, while λ = 1 tests whether there is evidence of a trait not entirely co-varying along phylogeny (Table 2.3).

Overall, the phylogenetic dependence of the various parameters was weak, with λ < 0.3 and non-significant p for λ = 0 (Table 3). Of the measured leaf parameters, PWUE showed weak phylogenetic dependence (λ ~ 0.3; p < 0.05 for λ = 0). The CO2 responsiveness of LMA and leaf [N]area showed a strong phylogenetic dependence (λ > 0.9; p < 0.01 for λ = 0) (Table 2.3).

To account for the CO2 responsiveness of the various parameters, the 280/400 [CO2] ratio was analysed. Hence, variations in the CO2 responsiveness were influenced by the biochemical subtype for leaf [N]mass, and by the evolutionary origin for Ci, LMA, [N]area and PNUE (Table 2.3).

Table 2. 1. Statistical model summary.

Summary of the model selection statistics for all the main physilogical parameters measured in this study. Statistical analysis was carried out using a customised linear mixed effect model. The

response variables were analysed using the CO2 treatment, evolutionary origin and biochemical subtype as fixed effects and species and pot number as random effects. "Intercept" refers to the estimation of the overall mean. Model selection was performed based on Akaike’s Information

Criteria (AIC). Values represent Akaike weights (wi) and indicate the level of support for each model to efficiently account for variation in the response (sum equal to 1 for each response

variable). For each response, the model with the highest wi (best predictive model) is shown in bold. A. using raw data; B: using 280/400 ratio.

A. Model parameters

Parameter CO2, CO2, CO2, CO2, Intercept Subtype, Origin, Subtype, Intercept Origin, Intercept Intercept Intercept

-2 -1 Photosynthesis, Asat (µmol m s ) 0.057 0.424 0.095 0.424 0.000 -2 -1 Conductance, gs (mol m s ) 0.111 0.743 0.029 0.117 0.000 -1 Intercellular [CO2], Ci (µl L ) 0.006 0.016 0.117 0.862 0.000 -1 PWUE (µmol (mol H2O) ) 0.4551 0.2760 0.1674 0.1015 0.0000 LMA (g m-2) 0.016 0.071 0.526 0.193 0.193 -1 Leaf [N]mass (mg g ) 0.013 0.054 0.148 0.771 0.013 -2 Leaf [N]area (mmol m ) 0.011 0.051 0.624 0.229 0.084 PNUE (mmol (mol N)-1 s-1) 0.053 0.350 0.323 0.274 0.000 Plant dry mass, PDM (g plant-1) 0.045 0.004 0.906 0.045 0.000 Plant WUE 0.069 0.048 0.560 0.323 0.000 Plant NUE 0.029 0.145 0.044 0.234 0.548 Soluble protein (g m-2) 0.071 0.047 0.129 0.202 0.550 Rubisco sites (nmol m-2) 1.000 0.000 0.000 0.000 0.000 Rubisco/Sol. protein 0.572 0.013 0.017 0.067 0.330 Rubisco-N (% leaf N) 0.013 0.017 0.067 0.327 0.576 Rubisco activity (µmol m-2 s-1) 1.000 0.000 0.000 0.000 0.000 PEPC activity (µmol m-2 s-1) 0.914 0.001 0.015 0.027 0.044 PEPC/Rubisco 0.013 0.017 0.067 0.330 0.572

B. Model parameters 280/400 ratio Subtype, Origin, Subtype, Intercept Origin, Intercept Intercept Intercept

-2 -1 Photosynthesis, Asat (µmol m s ) 0.030 0.074 0.148 0.748 -2 -1 Conductance, gs (mol m s ) 0.283 0.242 0.083 0.392 -1 Intercellular [CO2], Ci (µl L ) 0.355 0.561 0.016 0.068 -1 PWUE (µmol (mol H2O) ) 0.073 0.131 0.100 0.696 LMA (g m-2) 0.102 0.734 0.078 0.086 -1 Leaf [N]mass (mg g ) 0.021 0.031 0.516 0.432 -2 Leaf [N]area (mmol m ) 0.096 0.688 0.124 0.092 PNUE (mmol (mol N)-1 s-1) 0.020 0.116 0.357 0.507 Plant dry mass, PDM (g plant-1) 0.020 0.116 0.357 0.507 Plant WUE 0.006 0.032 0.173 0.789 Plant NUE 0.014 0.100 0.249 0.637 Soluble protein (g m-2) 0.009 0.058 0.141 0.791 Rubisco sites (nmol m-2) 0.033 0.034 0.372 0.561 Rubisco/Sol. protein 0.039 0.050 0.521 0.390 Rubisco-N (% leaf N) 0.010 0.029 0.304 0.656 Rubisco activity (µmol m-2 s-1) 0.033 0.034 0.372 0.561 PEPC activity (µmol m-2 s-1) 0.290 0.490 0.070 0.150 PEPC/Rubisco 0.256 0.679 0.014 0.051

Table 2. 2. Summary of leaf gas exchange and plant growth parameters and activity of photosynthetic enzymes.

-1 -1 Gas exchange, growth parameters and photosynthetic enzyme activity of 24 grass species grown at inter-glacial (280 µl L ) and ambient (400 µl L ) [CO2]. Values are means (n=3-4) ± SE. Superscripts indicate the ranking (from lowest (a) to highest (c)) of evolutionary origins within each single row using a multiple-comparison Tukey’s Post Hoc test. Values followed by the same letter are not significantly different at 5% level.

Parameter [CO2] Evolutionary origins (µL L-1) Paspalum Andropogoneae Echinochloa Digitaria Paniceae Chloridoideae

NADP-ME NADP-ME NADP-ME NADP-ME NADP-ME, NAD-ME, NAD-ME, PCK PCK

a abc c ab bc abc Asat 280 19 ± 2 26 ± 1 28 ± 1 20 ± 1 27 ± 1 24 ± 1 (µmol m-2 s-1) 400 28 ± 4 a 34 ± 1 ab 41 ± 3 b 27 ± 3 a 36 ± 1ab 35 ± 2 ab a a a a a a gs 280 0.30 ± 0.06 0.38 ± 0.03 0.44 ± 0.05 0.29 ± 0.05 0.42 ± 0.02 0.29 ± 0.03 (mol m-2 s-1) 400 0.18 ± 0.05 a 0.25 ± 0.02 ab 0.37 ± 0.04 b 0.18 ± 0.04 a 0.33 ± 0.02 ab 0.26 ± 0.03 ab PWUE 280 67 ± 8 a 70 ± 4 a 63 ± 7 a 72 ± 7 a 68 ± 3 a 86 ± 4 a (µmol mol-1) 400 155 ± 12 b 135 ± 6 ab 112 ± 10 a 147 ± 10 ab 119 ± 4 ab 146 ± 7 ab a a a a a a Ci 280 92 ± 14 69 ± 6 78 ± 11 85 ± 11 74 ± 6 79 ± 7 (µl L-1) 400 113 ± 15 a 129 ± 7 ab 160 ± 12 b 127 ± 12 ab 152 ± 5 ab 130 ± 8 ab LMA 280 29 ± 10 a 29 ± 5 a 25 ± 8 a 41 ± 8 a 24 ± 4 a 49 ± 5 a (g m-2) 400 22 ± 16 a 31 ± 7 a 24 ± 13 a 32 ± 13 a 26 ± 6 a 59 ± 9 a a a a a a a Leaf [N]mass 280 36 ± 5 42 ± 3 45 ± 4 43 ± 4 41 ± 2 40 ± 3 (mg g-1) 400 40 ± 3 a 42 ± 1 a 53 ± 3 b 38 ± 3 a 44 ± 1 ab 45 ± 2 ab 51

a a a a a a Leaf [N]area 280 76 ± 29 81 ± 14 80 ± 24 124 ± 24 70 ± 12 123 ± 15 (mmol m-2) 400 62 ± 52 a 91 ± 24 a 91 ± 42 a 96 ± 42 a 80 ± 19 a 119 ± 30 a PNUE 280 0.28 ± 0.19 a 0.52 ± 0.09 a 0.35 ± 0.16 a 0.17 ± 0.16 a 0.42 ± 0.08 a 0.24 ± 0.1 a (mmol mol-1 s-1) 400 0.5 ± 0.3 a 0.8 ± 0.1 a 0.48 ± 0.2 a 0.28 ± 0.2 a 0.53 ± 0.1 a 0.32 ± 0.1 a Plant DM 280 0.95 ± 2 a 5.3 ± 0.9 a 2.04 ± 1.6 a 3.5 ± 1.6 a 2.4 ± 0.8 a 3.7 ± 1 a (g plant-1) 400 1.5 ± 0.5 a 6 ± 1 a 2 ± 2 a 5 ± 2 a 5 ± 1 a 5 ± 2 a Plant WUE 280 1.6 ± 2 a 5 ± 1 a 3 ± 1.6 a 4 ± 1.6 a 4 ± 0.7 a 3.6 ± 1 a -1 a a a a a a (g kg H2O ) 400 2 ± 0.26 6 ± 1 5 ± 2 6 ± 2 6 ± 1 4 ± 1.5 Plant NUE 280 0.09 ± 0.04 0.11 ± 0.02 ab 0.18 ± 0.03 b 0.06 ± 0.03 a 0.14 ± 0.01 ab 0.09 ± 0.02 ab (g mg-1 leaf N) 400 0.06ab ± 0.03 a 0.08 ± 0.01 a 0.13 ± 0.02 a 0.05 ± 0.02 a 0.13 ± 0.01 a 0.08 ± 0.02 a Rubisco sites 280 3.6 ± 0.7 ab 5.5 ± 0.3 bc 4.6 ± 0.6 bc 2.3 ± 0.6 a 4.8 ± 0.3 bc 6.3 ± 0.4 c (nmol m-2) 400 5 ± 1.6 ab 5.6 ± 1 ab 6 ± 1 ab 2.4 ± 1 a 4 ± 0.6 ab 8 ± 1 b Soluble proteins 280 2 ± 0.8 a 3.2 ± 0.4 a 2.5 ± 0.7 a 1.4 ± 0.7 a 3 ± 0.4 a 2.7 ± 0.4 a (gm-2) 400 2.2 ± 0.8 a 2.8 ± 0.4 a 2.8 ± 0.7 a 1.5 ± 0.7 a 2.9 ± 0.3 a 3.1 ± 0.5 a Rubisco/ Soluble 280 0.15 ± 0.01 a 0.12 ± 0.02 a 0.13 ± 0.03 a 0.12 ± 0.03 a 0.11 ± 0.01 a 0.22 ± 0.08 a Proteins 400 0.16 ± 0.01 a 0.12 ± 0.02 a 0.15 ± 0.03 a 0.11 ± 0.02 a 0.11 ± 0.01 a 0.16 ± 0.01 a Rubisco- N 280 4.1 ± 3 a 8.2 ± 1.4 a 4.6 ± 2.5 a 1.6 ± 2.5 a 5.9 ± 1.3 a 5.2 ± 1.5 a (% leaf N) 400 8 ± 3 a 10 ± 2 a 6 ± 3 a 2 ± 3 a 4.5 ± 1 a 5 ± 2 a Rubisco activity 280 19 ± 3 a 31 ± 1 b 18 ± 2 a 11 ± 2 a 19 ± 1 a 32 ± 1 b (µmol m-2 s-1) 400 28 ± 4 b 29 ± 3 bc 25 ± 4 ab 12 ± 4 a 17 ± 2 ab 41 ± 3 c PEPC activity 280 40 ± 16 abc 75 ± 7 bc 88 ± 13 c 24 ± 13 a 39 ± 7 ab 52 ± 8 abc (µmol m-2 s-1) 400 27 ± 15 a 59 ± 8 ab 102 ± 12 b 31 ± 10 a 45 ± 6 a 70 ± 8 ab PEPC / Rubisco 280 2 ± 0.6 a 2.5 ± 0.3 a 5 ± 0.5 b 2 ± 0.5 a 2 ± 0.3 a 1.6 ± 0.3 a 400 1 ± 1 a 2 ± 0.6 a 4 ± 0.8 a 3 ± 0.7 a 3 ± 0.4 a 1.7 ± 0.6 a

Table 2. 3. Summary of the phylogenetic analysis for selected leaf parameters.

Statistical analysis was carried out on 24 C4 grasses using phylogenetic generalized (pgls) least squares. Phylogenetic dependence of traits measured at inter-glacial (280 µl L-1), ambient (400 -1 µl L ) [CO2] and their ratio (280/400) are given in  ( = 1, strong phylogenetic dependence) and p values; λ = 0 tests for the phylogenetic dependence of a trait, while λ = 1 tests whether a trait is not constrained phylogenetically.

Leaf parameter Growth Phylogenetic dependence [CO2]  p ( = 0) p ( = 1) (l L-1) -2 -1 Photosynthesis, Asat (µmol m s ) 280 0.020 0.918 0.000 400 0.000 1.000 0.000 280/400 0.071 0.732 0.000 -2 -1 Conductance, gs (mol m s ) 280 0.206 0.248 0.000 400 0.000 1.000 0.020 280/400 0.116 0.567 0.000 -1 Intercellular [CO2], Ci (µl L ) 280 0.000 1.000 0.074 400 0.000 1.000 0.000 280/400 0.000 1.000 0.000 -1 PWUE (µmol (mol H2O) ) 280 0.318 0.048 0.003 400 0.000 1.000 0.000 280/400 0.000 1.000 0.000 LMA (g m-2) 280 0.301 0.130 0.000 400 0.137 0.399 0.000 280/400 0.946 0.009 0.128 -1 Leaf [N]mass (mg g ) 280 0.000 1.000 0.000 400 0.000 1.000 0.000 280/400 0.000 1.000 0.013 -2 Leaf [N]area (mmol m ) 280 0.263 0.167 0.000 400 0.164 0.339 0.000 280/400 0.966 0.005 0.184 PNUE (mmol (mol N)-1 s-1) 280 0.018 0.927 0.008 400 0.310 0.212 0.011 280/400 0.000 1.000 0.006

Photosynthesis A B Conductance Intercellular CO2 PWUE LMA Leaf [N]mass Leaf [N]area PNUE

Plant DM

Plant WUE Lineage Subtype Plant NUE CO2 Soluble proteins Rubisco sites Rubisco/Sol prot. Rubisco-N Rubisco activity PEPC activity PEPC/Rubisco

0.00 0.25 0.50 0.75 1.00 0.25 0.50 0.75 1.00 Akaike w Akaike wi i Figure 2. 2. Statistical model summary.

Summary of the model selection statistics for the main physiological parameters measured in this study. Statistical analysis was carried out using linear mixed effects models. The response variables were analysed using the CO2 treatment, evolutionary lineage and biochemical subtype as fixed effects and species and pot number as random effects. Akaike weights (wi) indicate the importance of each fixed effect (lineage, subtype, and CO2) for explaining variation in the response variable, using multimodel inference (1 = very important, 0 = not important). Panel A. using raw data; panel B: using 280/400 ratios. Raw data are shown is Table 2.1A and 2.1B.

50 A

 40 )

-1 s

-2 30

molm

 20

(

sat A 10

AndropogoneaeAndropogoneae

ChloridoideaeChloridoideae Paniceae

Paniceae

Echinochloa DigitariaDigitaria PaspalumPaspalum 0 Echinochloa 0.5 B



) 0.4

-1 s

-2 0.3

molm (

0.2

s g

0.1

Echinochloa PaniceaePaniceae AndropogoneaeAndropogoneae PaspalumPaspalum ChloridoideaeChloridoideae DigitariaDigitaria 0.0 Echinochloa

C 

) 160

-1

) O

2 120

molH

(

mol

 (

PWUE PWUE

Chloridoideae Chloridoideae Digitaria Digitaria Andropogoneae Andropogoneae Paniceae Paniceae Paspalum Paspalum Echinochloa Echinochloa 0 Chloridoideae

Figure 2. 3. Leaf gas exchange parameters for 24 C4 grasses.

Light saturated rate of photosynthesis, Asat (A), stomatal conductance, gs (B) and photosynthetic water use efficiency, PWUE (C) of 24 C4 grasses belonging to 6 major evolutionary origins grown at inter-glacial (280 µl L-1, open columns) and current ambient (400 µl L-1, filled columns) atmospheric [CO2]. Gas exchange measurements were made under growth [CO2] at 7-8 weeks after planting. Columns are arranged from highest to lowest performing origin under inter- glacial [CO2]. Each column represents the mean of species for each origin. Black columns represent origins which only contain NADP-ME species, the grey column represent the origin containing NAD-ME and PCK species, and the checked column represent the origin containing all three subtypes. 55

2.0 A NAD-ME PCK NADP-ME

1.5

ratio

2 1.0

0.5

0.0 B Paspalum Andropogoneae Echinochloa Digitaria Paniceae Chloridoideae

1.5

1.0 Inter-glacial Ambient / CO 0.5

0.0

gs Asat

LMA

PNUE

PWUE

Plant DM Plant

Plant NUE Plant

Plant WUE Plant

Leaf[N]area

Rubisco-N%

Leaf[N]mass

Rubiscosites

PEPCactivity PEPC/Rubisco

Figure 2. 4. CO2 sensitivity of physiological parameters measured in 24 C4 grasses.

Inter- glacial to ambient CO2 ratios of the main parameters ± SE measured in this study for 24

C4 grasses grouped according to their biochemical subtype (A: NAD-ME ●, PCK □ and NADP- ME ▲) or their evolutionary origin (B: Paspalum ■, Andropogoneae , Echinochloa , Digitaria ▲, Paniceae □, and Chloridoideae ●). Original data are shown in Table 2.2.

50 Inter- glacial CO A 160 B 2

Ambient CO2

40 )

-2 ) -2 120

(mmolm

80 area

m (g LMA 20

10 Leaf [N] Leaf

0 0 ) 0.7

-1 C D

s -1

0.6 ) 7 -1 0.5 6

0.4 5

4 0.3 3 0.2

plantDMPlant ( 2 PNUE(mmol(mol N) 0.1 1

0.0 0 E F 7

0.15 ] -1

O) 2

leaf N)leaf 5 -1

0.10

4 3 0.05 2

1 Plant NUEPlantmg (g H (kg [g WUE Plant 0.00 0 NAD-ME PCK NADP-ME NAD-ME PCK NADP-ME

Figure 2. 5. Growth and nitrogen parameters.

Leaf mass per area, LMA (A), leaf N concentration per unit area, Leaf [N]area (B), photosynthetic nitrogen use efficiency, PNUE (C), plant dry mass, DM (D), plant NUE (E) and plant WUE (F) and of 24 C4 grasses belonging to 3 biochemical subtypes grown at pre-industrial -1 -1 (280 µl L , open columns) and ambient (400 µl L , filled columns) atmospheric [CO2]. Each column represents the means of species for each subtype.

) 40 -1

) Inter- glacial CO -1

s A 75 B 2 -2

s Ambient CO2 -2

30 60

molm

 molm

 45

PEPC activity ( activity PEPC Rubisco( activity

0 0 C D 4 10

8 3

PEPC/ Rubisco PEPC/ 4

1 Rubisco-NN)leaf (% 2

0 0 NAD-ME PCK NADP-ME NAD-ME PCK NADP-ME

Figure 2. 6. Activity of photosynthetic enzymes.

Rubisco activity (A), PEPC activity (B), Rubisco/PEPC activity ratio (C) and the fraction of leaf

N in Rubisco (D) of 24 C4 grasses belonging to 6 major evolutionary origins that were grown at pre-industrial (280 µl L-1, open columns) and ambient (400 µl L-1, filled columns) atmospheric

[CO2]. Each column represents the means of species for each subtype.

Low CO2 (280 ppm) 1.0

Trans NAD-ME

Cond

Chloridoideae

LMA Narea Echinochloa Digitaria Paniceae N mass Ci/Ca PEPC PEPC/Rub PCK NADP-ME

Rubisco RDAaxis (2) 18.5% PNUE Paspalum Andropogoneae

Photo

PWUE

Amb CO2 (400 ppm) -1.0 -1.0 RDA axis (1) 64.6% 1.0

Figure 2. 7. RDA tri-plot for leaf level parameters.

Redundancy analysis (RDA) using leaf traits: Photosynthetic rate at growth [CO2] (Photo); stomatal conductance (Cond); transpiration rate (Trans); photosynthetic water use efficiency (PWUE)); leaf nitrogen per unit dry mass (N mass): leaf nitrogen per unit area (N area); leaf dry mass per unit area (LMA); photosynthetic nitrogen use efficiency (PNUE); Rubisco activity (Rubisco); PEPC activity (PEPC); and PEPC to Rubisco activity ratio (PEPC/Rub) measured for 24 C4 grasses belonging to 6 major evolutionary origins: Paspalum, Andropogoneae, Echinochloa, Digitaria, Paniceae and Chloridoideae; and 3 biochemical subtypes (NAD-ME, -1 PCK and NADP-ME) grown at inter- glacial (Low CO2; 280 µl L ) and ambient (Amb CO2; 400 -1 µl L ) atmospheric [CO2]. The measured parameters are shown as black arrows and the experimental factors (evolutionary origin and biochemical subtype) are shown as red arrows.

2.4 Discussion

In the grass family, where 50% of the C4 species occur, C4 photosynthesis has evolved numerous times (~24) in multiple lineages (Grass Phylogeny Working

Group, 2012). At the leaf level, the C4 syndrome is highly diverse with at least 11 anatomical-biochemical distinct suites identified (Hattersley and Watson, 1992, Christin et al., 2013). These suites are closely linked to certain lineages (Prendergast et al., 1987, Dengler et al., 1994), and various physiological and ecophysiological traits have been associated with the biochemical subtype or evolutionary origin of the

C4 grasses (Hattersley, 1992, Liu et al., 2012). Therefore, dissociating the effects of the biochemical subtypes from those related to phylogenetic and evolutionary influences on the adaptive physiology of C4 plants is a complex task. The key question raised in this study was whether the physiological differences previously observed between the C4 subtypes are maintained when considering the evolutionary diversity of the C4 grass lineages, and when compared under the low atmospheric

[CO2] that prevailed during the evolution of the C4 pathway. Overall, the current study revealed new insights about the comparative physiology of C4 grasses, as discussed below.

2.4.1 Variations in photosynthetic nitrogen use efficiency among C4 grasses are associated with the biochemical subtype

Past work undertaken under current ambient [CO2] revealed that NADP-ME grasses possess superior PNUE relative to NAD-ME counterparts (Bowman, 1991, Taub and Lerdau, 2000, Ghannoum et al., 2005). These differences were due to lower leaf [N] c and higher Rubisco turnover rate (k cat) in NADP-ME relative to NAD-ME grasses

(Ghannoum et al., 2005). These observations were made with a few C4 grasses without considering the phylogenetic diversity that exists particularly among NADP- ME lineages (Grass Phylogeny Working Group, 2012). When such complexity was considered, it was found that while the Andropogoneae (NADP-ME) grasses maintained higher PNUE relative to other C3 and C4 grasses, the Aristidoideae

(NADP-ME) grasses had PNUE similar to C3 counterparts (Taylor et al., 2010). 60

The current study used NADP-ME grasses from five different evolutionary origins in addition to NAD-ME and PCK grasses grown at ambient and inter-glacial [CO2]. When the whole data set was considered, higher leaf [N] and LMA were the two key traits that distinguished the Chloridoideae (NAD-ME) grasses from all other C4 groups, while higher Rubisco and PEPC activities distinguished NADP-ME and PCK grasses regardless of their evolutionary origin (Figure 2.7). In addition, the lme analysis revealed that variations in leaf [N] were better explained by the subtype rather than the evolutionary origin of the C4 species (Table 2.1). Moreover, when data at inter-glacial and current ambient [CO2] were analysed separately using pgls, no phylogenetic dependence was detected for any of the NUE-related parameters (Table 2.3). Taken together, these results support our first hypothesis which was based on earlier findings showing that variations in PNUE among the C4 grasses are related to the trade-off between Rubisco catalysis and the investment in leaf N. Accordingly, NADP-ME grasses achieve similar photosynthetic rates with lower leaf N and Rubisco contents by virtue of having faster Rubisco enzyme relative to NAD- ME counterparts (Ghannoum et al., 2005). The evolution of faster Rubisco enzymes may be related to the more favourable [CO2]/[O2] ratio that is expected to prevail in the bundle sheath environment of NADP-ME and PCK species due to the lower PSII activity in their bundle sheath chloroplasts (Hatch, 1987, Ghannoum et al., 2005).

2.4.2 Variations in photosynthetic water use efficiency among C4 grasses are associated with the evolutionary origin

The distribution of C4 grasses is strongly associated with the magnitude of precipitation. In particular, C4 grasses belonging to the NAD-ME or Chloridoideae groups predominate at the lower end of the rainfall gradient relative to other C4 grasses(Ellis et al., 1980, Hattersley, 1992, Taub, 2000). This biogeography suggests that NAD-ME/Chloridoideae grasses are better adapted to dry habitats. Recent work has shown that the Chloridoideae possess leaf morphological traits which are associated with dry habitats, such as smaller culm height, leaf width and stomata (Liu et al., 2012). Another study showed that gs was lower in C4 grasses originating from dry relative to wet habitats (Taylor et al., 2012). In my study, the

Chloridoideae/NAD-ME species tended to have lower gs and higher PWUE under inter-glacial but not ambient [CO2], and this was accompanied by a lower stomatal sensitivity to [CO2] relative to the other C4 groups (Figures 2.3 and 2.4). Moreover, variations in gs and PWUE were better explained by the evolutionary origin rather than the biochemical subtype (Table 2.1). Interestingly, the pgls analysis revealed that PWUE measure at inter-glacial [CO2] was the only parameter showing a degree, albeit weak (λ ~ 0.3; p < 0.05 for λ = 0), of phylogenetic dependence (Table 2.3). Taken together, these findings support my second hypothesis which suggests that WUE-related traits are either related to the grass lineage or represent adaptation to the species’ habitat rather than the underlying biochemistry of the C4 pathways.

2.4.3 Response of photosynthesis to inter-glacial [CO2]

C4 photosynthesis is characterised by the operation of a CO2 concentrating mechanism which serves to saturate photosynthesis at current ambient [CO2]. Questions have been raised whether the anatomical or biochemical variations observed among C4 leaves may lead to differences in photosynthetic capacity or efficiency (Hattersley, 1982, Hattersley, 1992). Past studies have repeatedly shown that there is little variation in photosynthetic rates at ambient [CO2] among C4 grasses when grown under optimal conditions, and that this variation is not related to the biochemical subtype or evolutionary origin (Ghannoum et al., 2001a, Taylor et al., 2010). These trends were also obtained in the current study when Asat was measured at inter-glacial [CO2]. Species having the highest and lowest Asat belonged to the NADP-ME subtype, and there was little difference in the sensitivity of Asat to inter-glacial [CO2] (Figures 2.2 and 2.4). These findings indicated that inter-glacial

[CO2] poses small and equal limitation on all three biochemical subtypes. These results concur with the repeated findings that bundle sheath leakiness of CO2 (which represents the efficiency of the CO2 concentrating mechanism in C4 plants) is a constant and similar fraction in diverse C4 grasses exposed to a range of environmental conditions (Henderson et al., 1992, Cousins et al., 2008). The results are also in line with the small photosynthetic response to elevated [CO2] observed in well-watered C4 grasses from various biochemical subtypes (Wand et al., 1999,

Ghannoum et al., 2000, Ghannoum et al., 2001b). Interestingly, Asat was highest in

Echinochloa species under both ambient and inter-glacial [CO2]. This genus is comprised of fast growing weeds, which showed greater responsiveness to elevated

[CO2] than C4 crops (Ziska and Bunce, 1997).

2.4.4 Response of stomatal conductance to inter-glacial [CO2]

Although reduced carbon assimilation at sub-ambient [CO2] is well established for

C4 plants (Anderson et al., 2001, Sage and Coleman, 2001), little is known about stomatal responses of diverse C4 species to past atmospheric [CO2] and their interactions with environmental stresses (Ward et al., 1999, Maherali et al., 2002,

Reid et al., 2003). In the current study, gs increased by ~40% in plants grown at inter- glacial relative to ambient [CO2], similar to increases observed by (Anderson et al., 2001, Cunniff et al., 2008). Among all the origins, the Chloridoideae (NAD-ME,

PCK) species had the smallest sensitivity of gs to reduced [CO2]. Lower stomatal sensitivity to [CO2] observed in this study and smaller stomatal pores observed in other studies (Liu et al., 2012) for the Chloridoideae species may represent an adaptation to dry habitats.

In particular, Osborne & Sack, (2012) argued that higher hydraulic conductance

(shorter inter-veinal distances) in C4 relative to C3 plants make the former less prone to hydraulic failure in dry environments, thus increasing their advantage in maintaining open stomata at low [CO2]. It is well-documented that NAD-ME species have longer inter-veinal distances (Dengler et al., 1994, Ohsugi & Murata, 1986) and occupy drier habitats (Ellis, et al., 1980, Hattersley, 1992, Taub, 2000) relative to NADP-ME and PCK species. Accordingly, it may be argued that NAD-ME grasses have a lower advantage of opening their stomata at inter-glacial [CO2] and a greater advantage in maintaining higher PWUE (Figure 2. 3). In contrast, NADP-ME and

PCK species may open their stomata at low [CO2] to maintain carbon gain without substantially risking hydraulic failure, albeit at the expense of reduced PWUE (Osborne & Sack, 2012, Taylor et al., 2012).

This argument is further supported by the analysis of a global database, where it was revealed that well-developed bundle sheath cells and shorter inter-veinal distances 63

characterised the C4 lineages, which were also associated with increasing aridity. Maintaining leaf hydraulic conductance and cavitation repair are consistent with increased evaporative demand and more seasonal precipitation as drivers for C4 diversification under declining [CO2] 30 Mya (Griffiths et al., 2013).

2.4.5 Response of plant DM and WUE to inter-glacial [CO2]

Under both [CO2] treatments, the NADP-ME and PCK species had generally higher plant DM and WUE relative to the NAD-ME species. In addition, many NADP-ME species suffered little loss of plant DM at inter-glacial [CO2] (Figures 2.4 and 2.5). In light of the previous discussion, it may be argued that NADP-ME and PCK species tend to keep stomata open to maintain carbon uptake at limiting [CO2] and plentiful water conditions. The opposite was observed when soil water was limiting under saturating (current ambient) [CO2]. In the latter case, NAD-ME species had superior plant WUE relative to NADP-ME counterparts (Ghannoum et al., 2002). Therefore, different adaptive strategies were deployed depending on whether atmospheric [CO2] or soil water was limiting growth. These findings are worthy of further investigation to elucidate the differential mechanisms involved in the response of various C4 grasses to limiting water and CO2 supplies. Finally, responses obtained here did not support our third hypothesis; the CO2 responsiveness of the various C4 groups differed according to the parameter in question.

2.5 Conclusions

Using diverse C4 grasses grown at ambient and inter-glacial [CO2], this study demonstrated that variations in PNUE (driven by LMA and leaf [N]) were most likely related to the C4 biochemical subtype, while variations in PWUE (driven by gs) were related to the C4 lineage and reflected species adaptation to soil aridity. The study also revealed that C4 grasses have differential stomatal sensitivity to [CO2], which may be related to leaf hydraulic traits. In conclusion, the physiology of C4 grasses is profoundly influenced not only by the CO2 concentrating mechanism that

characterises C4 photosynthesis, but also the different combination of biochemical and anatomical leaf traits that characterise the C4 variants.

* * * *

CHAPTER 3

PHOTOSYNTHESIS OF C3, C3-C4 AND C4 GRASSES

AT GLACIAL CO2

Chapter 3 formed the basis of the following published manuscript:

Pinto H, Sharwood RE, Tissue DT, Ghannoum O (2014). Photosynthesis of

C3, C3–C4, and C4 grasses at glacial CO2. Journal of Experimental Botany, 65, 3669-3681.

I declare that I was the primary investigator and author for Chapter 3. I designed and carried out the experiment, collected and analysed the data, wrote the text and prepared the tables and figures. I received appropriate guidance from my supervisory panel

Abstract

Most physiology comparisons of C3 and C4 plants are made under current or elevated concentrations of atmospheric CO2 which do not reflect the low CO2 environment under which C4 photosynthesis has evolved. Accordingly, I compared photosynthetic nitrogen (PNUE) and water (PWUE) use efficiency, and the activity of the photosynthetic carboxylases (Rubisco and PEPC) and decarboxylases (NADP-ME and PEP-CK) in eight C4 grasses with NAD-ME, PCK and NADP-ME subtypes, one -1 - C3 grass and one C3-C4 grass grown under ambient (400 µl L ) and glacial (180 µl L 1 ) CO2.

Glacial CO2 caused a smaller reduction of photosynthesis and a greater increase of stomatal conductance in C4 relative to C3 and C3-C4 species. Panicum bisulcatum

(C3) acclimated to glacial [CO2] by doubling Rubisco activity, while Rubisco was unchanged in Panicum milioides (C3-C4), possibly due to its high leaf N and Rubisco contents. Glacial CO2 up-regulated Rubisco and PEPC activities in concert for several C4 grasses, while NADP-ME and PEP-CK activities were unchanged, reflecting the high control exerted by the carboxylases relative to the decarboxylases on the efficiency of C4 metabolism.

Despite having larger stomatal conductance at glacial CO2, C4 species maintained greater PWUE and PNUE relative to C3-C4 and C3 species due to higher photosynthetic rates. Relative to other C4 subtypes, NAD-ME and PCK grasses had the highest PWUE and PNUE, respectively; relative to C3, the C3-C4 grass had higher

PWUE and similar PNUE at glacial CO2. Biomass accumulation was reduced by glacial CO2 in the C3 grass relative to the C3-C4 grass, while biomass was less reduced in NAD-ME grasses compared with NADP-ME and PCK grasses. Under glacial CO2, high resource use efficiency offers a key evolutionary advantage for the transition from C3 to C4 photosynthesis in water and nutrient limited environments.

3.1 Introduction

The decline in atmospheric CO2 concentration ([CO2]) in the late Oligocene (30

Mya) is considered to be the primary driver for the evolution of the C4 photosynthetic pathway (Ehleringer et al., 1997, Christin et al., 2008a, Sage et al.,

2012). Geological fluctuations in atmospheric [CO2] have shaped the Earth’s vegetation, yet we know relatively little about the responses of C4 plants to the low

[CO2] levels that dominated during their evolution, and that are close to the atmospheric [CO2] of the recent glaciation (Pagani et al., 2005). Low [CO2] promotes high rates of photorespiration and reduces the carboxylation efficiency of C3 photosynthesis. The key feature of C4 photosynthesis is the operation of a CO2 concentrating mechanism (CCM) which suppresses photorespiration by raising

[CO2] around Rubisco (ribulose-1,5-bisphosphate carboxylase/oxygenase). During

C4 photosynthesis, phosphoenolpyruvate carboxylase (PEPC) catalyses the initial carboxylation of CO2 into organic C4 acids in the mesophyll. Decarboxylation of C4 acids in the bundle sheath releases CO2 for refixation by Rubisco (Hatch, 1987). The

C4 photosynthetic pathway is classified into three biochemical subtypes based on the primary C4 decarboxylase enzyme. These enzymes are nicotinamide adenine dinucleotide phosphate malic enzyme (NADP-ME), NAD malic enzyme (NAD-ME) and phosphoenolpyruvate carboxykinase (PCK) (Gutierrez et al., 1974, Kanai and Edwards, 1999). There are strong anatomical and biochemical variations associated with these biochemical subtypes (Prendergast et al., 1987, Dengler et al., 1994, Edwards and Voznesenskaya, 2011).

The operation of a CCM enhances the efficiency of C4 relative to C3 photosynthesis

(Osmond, 1982). In particular, C4 species attain higher photosynthetic water use efficiency (PWUE) because lower stomatal conductance (gs) and intercellular [CO2]

(Ci) are needed to saturate Rubisco carboxylation. C4 plants achieve higher photosynthetic nitrogen use efficiency (PNUE) due to their lower leaf N requirement c as a result of higher Rubisco catalytic turnover rate (k cat) (Long, 1999, Taylor et al., 2010, Ghannoum et al., 2011). Variations in resource use efficiency also occur among the C4 subtypes (Ghannoum et al., 2011). For example, NADP-ME grasses tend to have lower leaf N content than their NAD-ME counterparts (Bowman, 1991, 68

c Knapp and Medina, 1999, Taub and Lerdau, 2000), as a result of faster Rubisco k cat in NADP-ME species (Ghannoum et al., 2005). Furthermore, Ghannoum et al., (2002) showed that under water stress, NAD-ME grasses increased their whole-plant WUE to a greater extent than NADP-ME counterparts. These aforementioned studies were undertaken under current ambient [CO2] which does not reflect the low CO2 environment under which C4 grasses have evolved. Hence, the main aim of the current study was to investigate whether previously reported physiological differences among the C4 subtypes at ambient [CO2] are similarly observed at glacial

[CO2].

Growth at low [CO2] reduces growth and photosynthesis of C3 plants. C3 plants respond to low [CO2] by increasing stomatal conductance to improve CO2 supply and by up-regulating photosynthetic enzymes to improve CO2 capture (Polley et al., 1992, Dippery et al., 1995, Tissue et al., 1995, Gesch et al., 2000, Anderson et al.,

2001). The occurrence of a CCM in C4 leaves makes the C4 pathway less limited by

CO2 supply and hence, less likely to respond and acclimate to growth at low [CO2] relative to C3 photosynthesis (Hatch, 1987, Gerhart and Ward, 2010). Nevertheless, increased leaf N content and stomatal conductance have been observed under low

[CO2] in some C4 species (Anderson et al., 2001, Maherali et al., 2002). To our knowledge there are no published studies comparing the impact of low [CO2] on the photosynthetic gas exchange or biochemistry of C4 grasses with different biochemical subtypes. The current study aims at addressing this knowledge gap.

A hypothesised intermediate stage during C4 evolution, known as C3-C4 intermediate, restricts the activity of glycine decarboxylase to the bundle sheath (Sage et al., 2012), thus improving Rubisco efficiency by facilitating the recapture of photorespired CO2 (Monson and Moore, 1989, Monson and Rawsthorne, 2000). The operation of a photorespiratory pump in C3-C4 photosynthesis is expected to elicit a response to

[CO2] that is intermediate between C3 and C4 photosynthesis (Monson and

Rawsthorne, 2004, Sage et al., 2012). Under low [CO2], C3-C4 plants have been reported to maintain greater photosynthetic rates, PWUE and PNUE relative to C3 species (Ku and Edwards, 1978, Bolton and Brown, 1980, Ku et al., 1991, Monson and Rawsthorne, 2000, Vogan et al., 2007, Pinto et al., 2011, Vogan and Sage,

2012). The current study seeks to determine how C3-C4 species perform relative to the various C4 subtypes at low [CO2].

Comparing the sensitivity to glacial [CO2] of the different pathways of photosynthesis and subtypes of C4 photosynthesis among closely related grass species may provide critical insight into the physiology of C4 plants under conditions that led to their evolution. Consequently, this study compared the photosynthetic physiology (PWUE and PNUE) and biochemistry (activity of the photosynthetic carboxylase and decarboxylase enzymes) in C4 grasses with different biochemical -1 -1 subtypes grown under ambient (400 µl L ) or glacial (180 µl L ) [CO2]. Closely- related C3 and C3-C4 grass species were included for comparison.

3.2 Materials and Methods

3.2.1 Plant culture

Two matched growth chambers (1.8 m3 each; BioChambers, Winnipeg, MB, Canada) were used in this study. The chambers were maintained at either glacial -1 -1 (180 µl L ) or ambient (400 µl L ) [CO2]. Low [CO2] was achieved by passing incoming air over a CO2 absorbent (Grace SodaSorb, WR Grace and Co.-Conn.,

Chicago, USA) and controlled by CO2 gas analysers (LI-820, LI-COR, Lincoln, NE, USA). The average growth conditions during the experiment are shown in Table 3.1.

Table 3. 1. Average growth conditions during the experimental period.

Average growth conditions in the glacial and ambient CO2 growth chambers during the experimental period. Light intensity was measured at pot level. The photoperiod was 12 hours. Values are averages (± standard deviation) over the growing period.

Glacial CO2 Ambient CO2

Day Night Day Night

Light (µmol m-2 s-1) 900 ± 2 900 ± 3

-1 [CO2] (µl L ) 181 ± 4 182 ± 2 400 ± 2 400 ± 2

Temperature (oC) 27 ± 1 17 ± 1 27 ± 1 17 ± 1

Relative Humidity (%) 70 ± 1 70 ± 1 70 ± 1 70 ± 1

Locally collected soil (Ghannoum et al., 2010) was air-dried, coarsely-sieved and added (3.7 kg) to 3.5 L cylindrical pots, which were watered to 100% capacity, then transferred to the two growth chambers. Seeds for the grass species used in this study (Table 3.2) were obtained from the Australian Plant Genetic Resources Information System (ACT, Australia) and Queensland Agricultural Seeds Pty. Ltd. (Toowoomba, Australia). Seeds were sown in trays containing a common germination mix. Three to four weeks after germination, three seedlings were transplanted into each of the soil-filled pots. Within a week of transplanting, one healthy seedling was left in the

pot while the other seedlings were removed; there were four pots per species and

CO2 treatment. Two environmentally controlled growth chambers were used to generate the CO2 treatments. In order to minimise the impact of having a single growth chamber per CO2 treatment, pots and CO2 treatments were switched between chambers on two occasions. In addition, pots were randomly rotated within each chamber on a weekly basis throughout the experiment. Plants were watered daily and a commercial fertilizer (General Purpose, Thrive Professional, Yates, Australia) was applied weekly (0.2 g N L-1).

Table 3. 2. List of grass species used in the current study.

Species Photosynthetic type

Panicum bisulcatum Thunb. C3

Panicum milioides Nees C3-C4

Astrebla lappacea (Lindl.) Domin. C4, NAD-ME

Panicum coloratum L. C4, NAD-ME

Heteropogon contortus (L) P. Beauv. Ex Roem. & Schult. C4, PCK

Panicum monticola Hook. F. C4, PCK

Panicum maximum Jacq. C4, PCK

Chloris gayana Kunth. C4, PCK

Zea mays L. C4, NADP-ME

Echinochloa frumentaceae L. C4, NADP-ME

3.2.2 Leaf gas exchange measurements

Gas exchange measurements were made using a portable open gas exchange system (LI-6400XT, LI-COR, Lincoln, NE, USA). At 7-8 weeks after transplanting, gas exchange measurements were made at a photosynthetic photon flux density of 1800 μmol m-2 s-1 between 10:00-14:00 on attached, last fully expanded leaves (LFEL) of

the main stems. High light intensity was used during gas exchange to achieve near- -2 -1 light saturation of C4 photosynthesis. Although this intensity (1800 µmol m s ) is higher than that used for growth (900 µmol m-2 s-1), no appreciable light acclimation was observed during the short measurement period. Spot measurements of light- saturated photosynthetic rate (Asat) and stomatal conductance (gs) were made at target -1 growth [CO2] (180 or 400 μl L ) and leaf temperature of 27 ºC. Leaf-to-air vapour pressure deficit ranged between 1.7 and 2.4 kPa during the measurements. Before each measurement, the leaf was allowed to stabilise for 10-20 min until it reached a steady state of CO2 uptake.

The responses of CO2 assimilation rates (A) to step increases of intercellular CO2 (Ci) were measured under similar conditions as spot measurements by raising cuvette -1 [CO2] in 10 steps between 50 and 1500 µl L . There were 3-4 replicates per treatment. The A-Ci curves were fitted using the C4 photosynthesis model (von Caemmerer, 2000) to estimate maximal phosphoenolpyruvate carboxylase (PEPC)

(in vivo Vpmax) and Rubisco (in vivo Vcmax) activities. The biochemical model of C3 photosynthesis was used to estimate Vcmax (apparent, maximal RuBP-carboxylation limited rate) for the C3 grass (Farquhar et al., 1980b), using Rubisco catalytic parameters obtained for Panicum bisulcatum (Sharwood et al., 2014).

3.2.3 Growth and nitrogen analyses

Plants were harvested 12-13 weeks after transplanting. At harvest, area of the LFEL and total leaf area was measured using a leaf area meter (LI-3100A, LI-COR, Lincoln, NE, USA). Shoots were separated into stems and leaves. Roots were washed free of soil. Plant materials were oven-dried at 80 ºC for 48 h before dry mass was measured. Leaf mass per area (LMA, g m-2) was calculated as total leaf dry mass/total leaf area. For each treatment, three dried LFEL of each species were milled to a fine powder. Tissue N was determined on the ground samples using a CHN analyser (LECO TruSpec, LECO Corporation, Michigan, USA).

3.2.4 Activity of Rubisco, PEPC, NADP-ME and PCK

Following gas exchange measurements made at growth [CO2], replicate leaf discs (1- 2 cm2) were cut under high light and rapidly frozen in liquid nitrogen then stored at - 80oC for biochemical analysis. Each leaf disc was extracted in 1 mL of ice-cold extraction buffer (50 mM EPPS-NaOH pH 8.0, 5 mM DTT, 15 mM NaHCO3, 20 mM MgCl2, 2 mM EDTA, 4% (v/v) protease inhibitor cocktail (Sigma) and 1% (w/v) PVPP using a 2 mL Potter-Elvehjem glass homogeniser kept on ice. Sub- samples (75 L) were taken from the total extract for SDS PAGE analysis of total leaf protein. The remaining extract was centrifuged at 16,100 g for 1 min and the supernatant used for enzyme activity, Rubisco content and soluble protein assays. Rubisco content was estimated by the irreversible binding of [14C]-CABP to the fully carbamylated enzyme (Ruuska et al., 1998). Rubisco activity (in vitro Vcmax) was estimated by multiplying the concentration of active sites determined using the [14C]- c o CABP assay by the in vitro turnover rate (K cat at 25 C) of the various C4 grasses. Activities of PEPC and NADP-ME enzymes were determined at 25oC using a UV- VIS spectrophotometer (model 8453, Agilent Technologies Australia, Mulgrave, Victoria) as previously described by Pengelly et al., (2012) and Ashton et al., (1990). Soluble proteins were measured using the Pierce Coomassie Plus (Bradford) protein assay kit (Thermo scientific, Rockford, USA).

PEP-CK activity was assayed at 25oC in the carboxylase direction (Walker et al., 2002). Each leaf disc was extracted in 1 mL of ice-cold extraction buffer (50 mM

HEPES pH 7.2, 5 mM DTT, 2 mM EDTA, 2 mM MnCl2, 0.05% Triton, 4% (v/v) protease inhibitor cocktail (Sigma) and 1% (w/v) PVPP) using a 2 mL Potter- Elvehjem glass homogeniser kept on ice. The extract was centrifuged at 16,100 g for 1 min and the supernatant was used. PEP-CK activity was measured in assay buffer containing 100 mM HEPES, pH 7.0, 4% mercaptoethanol (w/v), 100 mM KCl, 90 mM NaHCO3, 1 mM ADP, 2 mM MnCl2, 0.14 mM NADH, MDH after the addition of phosphoenolpyruvate (PEP) to 5 mM. I was unable to reliably assay for NAD-ME activity in this study.

3.2.5 Immunoblot analysis

To confirm the absence/presence of a protein and the relative change in its expression, especially the decarboxylases in the C4 species and PEPC in C3 and C3-

C4 species, I carried immunoblot analysis of the proteins in question. Subsamples of total leaf extracts (used for enzyme assays) were mixed with 0.25 volumes of 4x LDS buffer (Invitrogen) containing 100 mM DTT, snap frozen in liquid nitrogen and stored at -20oC until analysed. Protein samples were separated by SDS-PAGE at 200V using TGX Any kD (Bio-Rad Laboratories, Hercules, California) precast polyacrylamide gels in the Mini-Protean apparatus buffered with Tris-Glycine SDS buffer (Bio-Rad). Separated proteins were transferred at 4oC to nitrocellulose membranes (0.45 m; Bio-Rad) using the Xcell Surelock western transfer module (Invitrogen) buffered with 1x Transfer buffer (20X – 25 mM Bicine, 25 mM Bis- Tris, 1 mM EDTA, 20% (v/v) methanol). After 1 hour of transfer at 30V, the membrane was placed in blocking solution (3% (w/v) skim milk powder in TBS; 50 mM Tris-Cl pH 8, 150 mM NaCl) for 1 hour at room temperature (RT) with gentle agitation.

For immunoblot analysis, primary antisera raised in rabbit against tobacco Rubisco (prepared by S.M. Whitney) were diluted 1:4000 in Tris buffered saline buffer (TBS) before incubation at 1 hour with membranes at RT with gentle agitation. Antisera raised against PEPC (Cat. AS09 458) was obtained from Agrisera (Agrisera AB, Vännäs, Sweden) and diluted 1:2000 with TBS. For immunoblot analysis of NADP- ME and PEP-CK, synthetic peptides based on monocot amino acid sequences for each were synthesized by GL Biochem (GL Biochem (Shanghai) Ltd., Shanghai, China) and antisera was raised to each peptide in rabbits. The reactive antisera was antigen-purified and subsequently used for immunoblots (GL Biochem). The NADP- ME (Product ID A-003198) and PEP-CK (Product ID A-003200) antisera were diluted in TBS 1:1000 and 1:500 respectively. All primary antisera were incubated with membranes at RT for 1 hour with gentle agitation before washing 3x with TBS. Secondary Goat anti-rabbit antisera conjugated to Horse Radish Peroxidase, HRP (Cat. NEF 812001EA, Perkin Elmer) was diluted 1:3000 in TBS and incubated with the membranes for 1 hour at RT followed by 3 washes with TBS. Immunoreactive 75

peptides were detected using the Immun-Star Western C kit (Cat. 170-5070, Bio- Rad) and imaged using the VersaDoc imaging system (Bio-Rad).

3.2.6 Statistical and data analysis

-2 -1 -2 -1 Photosynthetic WUE (PWUE) was calculated as Asat (μmol m s )/gs (mol m s ). -2 -1 Photosynthetic N use efficiency (PNUE) was calculated as Asat (μmol m s )/Leaf -2 [N]area (mmol m ). The proportion of leaf N invested in Rubisco (Rubisco-N) was calculated by assuming that Rubisco contained 16% N on a mass basis (Evans and Seemann, 1989).

There were four replicates per treatment for growth, gas exchange and enzyme assay measurements. There were three replicate measurements for the leaf N analysis and the A-Ci curves. The relationship between the various response variables and the main effects (Species, Photosynthetic type and CO2 treatment) and their interactions were fitted using a linear model in R (V. 3.0.2; R Foundation for statistical computing, Vienna, Australia). Analysis of variance (ANOVA) (summarised in Table 3.2) was conducted for each fitted model. Multiple comparisons (shown in Tables 3.4 and 3.5) of species means were made using the Tukey’s Post Hoc test.

Nested ANOVA was carried out among the C4 species only, where there were multiple species per subtype.

3.3 Results

3.3.1 Photosynthetic rates and WUE

Under both [CO2] treatments, photosynthetic rates measured at high light and growth

[CO2] (Asat) were higher in the C4 species relative to the C3-C4 and C3 species.

Amongst the C4 species, variation in Asat was unrelated to their subtype. Relative to ambient [CO2], glacial [CO2] decreased Asat to a greater extent in the C3-C4 (65%) and C3 (60%) species relative to the C4 species (26%) (Figs. 3.1A and 3.2A; Tables 3.3 and 3.4).

At ambient [CO2], variation in stomatal conductance (gs) was unrelated to the photosynthetic type or subtype of the grasses. At glacial [CO2], the C4 species had higher gs relative to the C3 and C3-C4 counterparts. Glacial [CO2] increased gs to a greater extent in the C4 relative to the C3 (1.1 fold) and C3-C4 (1.3 fold) species, with

NADP-ME (1.5 fold) grasses showing the greatest increase in gs relative to the other

C4 species (1.35 fold) (Figs. 3.1B and 3.2B; Tables 3.3 and 3.4).

At ambient [CO2], photosynthetic water use efficiency (PWUE) was higher in the C4 relative to the two C3-C4 and C3 species. At glacial [CO2], PWUE was highest in

NAD-ME and PCK species, intermediate in NADP-ME and C3-C4, and lowest in C3 species. Amongst the C4 species, the two NAD-ME grasses had higher PWUE relative to their PCK and NADP-ME counterparts. Glacial [CO2] decreased PWUE in all species by an average of 55% (Figs. 3.1C and 3.2C; Tables 3.3 and 3.3).

3.3.2 Leaf N use efficiency and plant dry mass

Under both [CO2] treatments, leaf [N]mass was highest in P. milioides (C3-C4) and lowest in H. contortus (PCK). Glacial [CO2] enhanced leaf [N]mass in all grasses except for P. monticola and C. gayana (PCK). The largest enhancement was observed in the C3 (51%) and NADP-ME (29%) species (Figs. 3.1D and 3.2D; Tables 3.3 and 3.4).

At ambient [CO2], photosynthetic nitrogen use efficiency (PNUE) varied 3-fold amongst the species in a manner unrelated to their photosynthetic type. Glacial [CO2] reduced PNUE to a lesser extent in the C4 (30%) relative to the C3 (58%) and C3-C4

(79%) species. At glacial [CO2], PNUE was highest in C4 plants (PCK > NADP-ME and NAD-ME) and lowest in C3 and C3-C4 plants (Figs. 3.1E and 3.2E; Tables 3.3 and 3.4).

At ambient [CO2], plant dry mass (PDM) was lower in the C3-C4 and NAD-ME species relative to the C3 and other C4 species. At glacial [CO2], the C4 species accumulated more biomass than their C3 and C3-C4 counterparts, which had similar

PDM. Glacial [CO2] reduced PDM to a greater extent in the C3 (70%) and C3-C4

(42%) species relative to the C4 (25%) species. Amongst the C4 species, PDM was least and most inhibited by glacial [CO2] in the NAD-ME and NADP-ME grasses, respectively (Figs. 3.1F and 3.2H; Tables 3.3 and 3.4).

3.3.4 Rubisco and soluble protein content

Under both [CO2] treatments, leaf Rubisco content was higher in P. milioides (C3-C4) relative to the other species, and in the two NAD-ME species relative to the other C4 grasses. At ambient [CO2], P. bisulcatum (C3) and NAD-ME grasses had similar

Rubisco contents. Glacial [CO2] increased Rubisco content in P. bisulcatum (2.3 fold) and in three (A. lappacea, P. coloratum and H. contortus; 1-2-1.7 fold) of the eight C4 species (Tables 3.3 and 3.4).

The ratio of Rubisco to soluble proteins and the proportion of leaf N invested in

Rubisco (Rubisco-N) were higher in the C3 and C3-C4 relative to the C4 species.

Amongst the C4 species, the NADP-ME grasses tended to have the lowest leaf N or soluble protein investment in Rubisco. Glacial [CO2] increased Rubisco-N in the C3 species, reduced it in the C3-C4, and had little effect in the C4 species (Tables 3.3 and 3.4).

The C3, C3-C4 and NAD-ME species had similar Rubisco activities, which were higher relative to the PCK and NADP-ME species. Glacial [CO2] significantly up-

regulated Rubisco activity in the C3 and NAD-ME grasses only (Figs.3.2F and 3.3A, Tables 3.3 and 3.4).

3.3.5 Activity of C4 cycle enzymes in C4 grasses

At ambient [CO2], PEPC activity was highest in A. lappacea (NAD-ME) and C. gayana (PCK), and lowest in P. maximum (PCK). At glacial [CO2], PEPC activity was highest in A. lappacea and lowest in P. monticola (PCK). Glacial [CO2] stimulated PEPC activity in five out of the eight C4 species (Figs. 3.2H and 3.3B; Tables 3.3 and 3.4). Variations in the ratio of PEPC to Rubisco activity reflected changes in PEPC activity (Fig. 3.3H; Tables 3.3 and 3.4).

In this study, I measured the activity of the decarboxylases NADP-ME and PEP-CK only. Significant activity of NADP-ME was measured in the two NADP-ME species, while marginal NADP-ME activity was detected in the two NAD-ME species and one of the PCK species (Fig. 3.3C). In contrast, PEP-CK activity was ubiquitous among the C4 species used, with C. gayana showing the highest PEP-CK activity.

Overall, growth [CO2] had no significant effect on the activity of either decarboxylases (Fig. 3.3C-D, Tables 3.3 and 3.4).

The detectability of the activity of both carboxylases and decarboxylases was corroborated by immuno-detection of the corresponding protein (Fig. 3.6). PEPC activity and protein were lacking from the C3 and C3-C4 species and present in all C4 grasses. NADP-ME activity and protein were found in two C4 species only. PEP-CK activity was measured in all C4 grasses and the protein was readily detected in six grasses, with A. lappacea and H. contortus exhibiting weak immuno-reaction with the available antibody, possibly due to divergent amino acid sequences of PEP-CK in these two species (Fig. 3.6).

3.3.6 In-vivo estimates of maximal Rubisco (Vcmax) and PEPC activity (Vpmax)

in C4 grasses

In vivo estimates of Vcmax and Vpmax were calculated using the C4 photosynthesis o model (von Caemmerer, 2000) from A-Ci curves measured at high light and 27 C

(Fig. 3.5). The variation of gas exchange-derived Vcmax between the C4 species was unrelated to their biochemical subtype. In contrast to its effect on in vitro Vcmax

(Rubisco activity), glacial [CO2] reduced gas exchange Vcmax in two out of the eight

C4 species (Fig. 3.3E; Tables 3.3 and 3.5). Consequently, in vivo and in vitro estimates of Vcmax were unrelated among the C4 grasses (Fig. 3.6B). In contrast,

PEPC activity was positively correlated with that of Rubisco across the C4 species and [CO2] treatments (Fig. 3.6A).

On average, NAD-ME species tended to have higher Vpmax and Vpmax/Vcmax relative to the other C4 grasses, especially at glacial [CO2]. Glacial [CO2] increased Vpmax and

Vpmax/Vcmax ratio in all C4 species, except for C. gayana, by an average of 25% and

19%, respectively (Fig. 3.3F-G; Table 3.3 and 3.5). Within the C4 species, Vpmax showed significant positive correlations with in vitro PEPC and Rubisco activities (Fig. 3.6C-D).

Table 3. 3. Statistical summary.

Summary of statistical analysis using 3-way ANOVA for the effects of [CO2], species and the photosynthetic type on various parameters collected for 10 grass species grown at glacial (180 µl -1 -1 L ) and ambient (400 µl L ) [CO2]. Significance levels are NS, not significant (P > 0.05); * P < 0.05; ** P< 0.01; *** P < 0.001.

Parameter Main effects (p) Interactions (p)

Species Type [CO2] [CO2] x [CO2] x Species Type -2 -1 Photosynthesis, Asat (µmol m s ) *** *** *** * *** -2 -1 Conductance, gs (mol m s ) *** *** *** NS *** -1 Intercellular [CO2], Ci (µl L ) *** *** *** * ** -1 PWUE (µmol (mol H2O) ) *** *** *** NS NS LMA (g m-2) *** * *** NS NS -1 Leaf [N]mass (mg g ) *** *** *** *** ** -2 Leaf [N]area (mmol m ) *** *** * * NS PNUE (mmol (mol N)-1 s-1) *** *** *** NS ** Plant dry mass, PDM (g plant-1) *** *** *** *** *** Soluble protein (g m-2) ** *** *** NS * Rubisco sites (nmol m-2) NS *** *** NS *** Rubisco/ Sol. protein ** *** NS ** NS Rubisco-N (% leaf N) ** *** NS NS *** Rubisco activity (µmol m-2 s-1) *** *** *** ** *** PEPC activity (µmol m-2 s-1) *** *** *** *** NS NADP-ME activity (µmol m-2 s-1) *** *** NS * NS PEP-CK activity (µmol m-2 s-1) *** *** NS NS NS PEPC/Rubisco *** *** ** NS NS -2 -1 in vivo Vcmax (µmol m s ) *** * *** ** *** -2 -1 in vivo Vpmax (µmol m s ) *** *** *** *** ** in vivo Vp/Vc *** * *** *** **

Table 3. 4. Summary of gas exchange and growth parameters.

-1 -1 Gas exchange and growth parameters for 10 grass species grown at glacial (180 µl L ) and ambient (400 µl L ) [CO2]. Values are means (n = 3-4) ± SE. Superscripts indicate the ranking of species within each row using a multiple-comparison, Tukey’s Post Hoc test. Values followed by the same letter are not significantly different at the 5% level.

Parameter [CO2] C3 C3-C4 C4, NAD-ME C4, PCK C4, NADP-ME P. P. A. P. H. P. P. E. (µl L-1) C. gayana Z. mays bisulcatum milioides lappacea coloratum contortus monticola maximum frumentaceae a a c c b c c d cd cd Asat 180 7 ± 1 8 ± 1 25 ± 0 23 ± 1 16 ± 1 25 ± 0 23 ± 0 32 ± 1 27 ± 0 27 ± 2 (µmol m-2 s-1) 400 17 ± 1a 22 ± 3ab 39 ± 0ef 29 ± 0bcd 26 ± 0b 34 ± 0bc 27 ± 0bc 42 ± 0f 33 ± 1cde 38 ± 1ef ab a abc abc a b- a- de cde e gs 180 0.24 ±0.04 0.16 ±0.02 0.29±0.01 0.32±0.01 0.19 ±0.01 0.43±0.02 0.35 ±0.01 0.53±0.08 0.48±0.02 0.64 ±0.09 (mol m-2 s-1) 400 0.21±0.02abc 0.24±0.04bcd 0.21±0.01abc 0.19±0.01abc 0.15±0.01a 0.26±0.01e cd 0.17d ±0.01ab 0.33±0.02de 0.21 ±0.01 0.35 ±0.04e e de a ab ab bc ab bc abc ab cd Ci 180 115 ± 4 93 ± 4 21 ± 1 36 ± 1 35 ± 8 47 ± 3 41 ± 4 55±12 44 ± 4 70 ± 5 (µl L-1) 400 231 ± 3 e 210 ± 19 de 57 ± 9 a 109 ±24 abc 93 ± 15 abc 137±5 bcd 103 ±12 abc 159±13cde 80 ± 19 ab 162 ± 23 cde a ab d cd d bc bcd bc bc ab PWUE 180 32 ± 3 48 ± 2 84 ± 1 73 ± 5 83 ± 5 59 ± 2 1265 abc± 2 63 ± 7 55±2 45 ± 5 (µmol mol-1) 400 83 ± 3a 94 ± 12ab 189 ± 6 d 158 ± 15cd 177 ± 10d 131 ± 2bc 159 ± 9cd 126 ± 8bc 160±11cd 113 ± 14ab LMA 180 23 ± 9a 21 ± 8a 36 ± 13a 46 ± 16a 46 ± 22a 48 ± 2a 40 ± 14a 16 ± 6a 140 ±11b 29 ± 10a (g m-2) 400 61 ± 10abcd 25 ± 3a 58 ± 3bcd 51 ± 5abcd 76 ± 5d 57 ± 5cd 56 ± 4abcd 27 ± 8ab 62 ± 3cd 45 ± 4abc bcd d abc cd a ab bc bc bc bcd Leaf [N]mass 180 53 ± 3 66 ± 3 45 ± 3 57 ± 3 32 ± 3 41 ± 3 50 ± 3 49 ± 3 49 ± 3 52 ± 3 (mg g-1) 400 26 ± 2a 48 ± 2b 38 ± 3ab 44 ± 3b 26 ± 3a 44 ± 3b 26 ± 3a 49 ± 3b 34 ± 3ab 38 ± 3ab ab ab ab b ab ab ab a c ab Leaf [N]area 180 118 ± 32 132 ± 25 150 ± 16 251 ± 40 131 ± 40 141 ± 8 192 ± 28 74 ± 4 492 ± 50 145 ± 11 (mmol m-2) 400 98 ± 18a 89 ± 15a 154 ± 10ab 170 ± 27ab 144 ± 17ab 190 ± 3b 97 ± 11a 91 ± 26a 151 ± 2ab 122 ± 17ab PNUE 180 0.06 ±0.02ab 0.06 ±0.01a 0.16±0.02abc 0.10±0.02abc 0.15±0.05abc 0.18±0.01bc 0.13±0.02abc 0.43±0.02d 0.06 ±0.01a 0.19 ±0.02c (mmol mol-1 s- 400 0.20±0.05ab 0.28±0.08ab 0.25 ±0.02ab 0.18 ±0.02a 0.18 ±0.02a 0.18 ±0.01a 0.28±0.04bc 0.59 ±0.02b 0.22±0.01ab 0.32 ±0.04ab PDM1) 180 12 ± 1ab 10 ± 1a 30 ± 1cd 18 ± 1b 31 ± 1cd 36 ± 1de 27 ± 1c 38 ± 1e 34 ± 1de 25 ± 1c (g plant-1) 400 41 ± 1bc 15 ± 1a 35 ± 1b 15 ± 1a 42 ± 1bc 33 ± 1b 45 ± 1cd 53 ± 1d 86 ± 1e 47 ± 1cd

Table 3. 5. Activity of photosynthetic enzymes.

-1 -1 Activities of carboxylase and decarboxylase enzymes measured in the leaves of 10 grasses grown at glacial (180 µl L ) and ambient (400 µl L ) [CO2]. In vivo Vcmax and Vpmax estimated from A-Ci curves are also shown. Values are means (n = 3-4) ± SE. Other details are as described for Table 3. n/d = not detected.

Parameter [CO2] C3 C3-C4 C4, NAD-ME C4, PCK C4, NADP-ME ]]] P. P. A. P. H. P. P. E. (µl L-1) C. gayana Z. mays bisulcatum milioides lappacea coloratum contortus monticola maximum frumentaceae Rubisco sites 180 21 ± 6.0b 19 ± 6.0b 13 ± 0.5ab 15 ± 1.0ab 7 ± 0.4a 4 ± 0.5a 6 ± 0.3a 5 ± 0.4a 7 ± 0.6a 4 ± 0.6a (nmol m-2) 400 9 ± 0.6ab 20 ± 5.0c 11 ± 0.4b 9 ± 0.6b 4 ± 0.1a 5 ± 0.3ab 5 ± 0.5a 6 ± 0.6ab 6±0.4ab 4 ± 0.4a Soluble proteins 180 4.4± 0.5abc 4.6 ± 0.2abc 6.2 ± 0.6c 6.6 ± 1.0c 3.9± 0.3abc 3.2± 0.3ab 2.8 ±0.5a 3.4±0.2ab 5.3±0.5bc 4.2 ± 0.1abc -2 a a-d d cd ab ab abc ab bcd a-d (g m ) 400 2.5 ± 0.2 4.0± 0.3 5.0 ± 0.5 4.8 ± 0.3 2.7 ± 0.2 3.0± 0.2 3.0±0.3 3.2± 0.3 4.1±0.2 3.6 ± 0.1 Rubisco/Sol protein 180 0.32±0.04 0.29±0.05bc 0.14±.03abc 0.17±0.04abc 0.14±0.03abc 0.10±0.04 0.30±0.04c 0.10±0.04a 0.09±.04a 0.04±0.05a 400 0.25±0.02bc 0.34±0.02c 0.15±0.01a 0.16 ±0.02ab 0.09±0.01a 0.1ab 0±0.02 0.12±0.02a 0.14±0.02a 0.09±.01a 0.08±0.02a Rubisco-N 180 9.8 ± 2 ab 14.0 ± 2 b 5.0 ± 1 ab 4.2± 2 a 4.8 ± 2 ab 2.7a ± 1 a 2.5 ± 2 a 5.6 ± 2 ab 2.9 ± 2 a 2.1 ± 2 a (% leaf N) 400 5.5 ± 2 a 26.3 ± 2 b 5.6 ± 2 a 5.4 ± 2 a 2.2 ± 2 a 2.3 ± 2 a 4.0 ± 2 a 6.6 ± 2 a 3.3 ± 2 a 2.5 ± 2 a Rubisco activity 180 55 ± 15c 43±14abc 64 ± 2bc 52 ± 3bc 35 ± 2abc 23 ± 3ab 30 ± 1abc 31 ± 3ab 38 ± 3abc 15 ± 3a (µmol m-2 s-1) 400 23 ± 2abc 44 ± 11de 54 ± 2e 33 ± 2cd 19 ± 1ab 28 ± 1abcd 25 ± 2abc 36 ± 4bcd 33 ± 2abcd 17 ± 2a PEPC activity 180 181 ± 10d 81 ± 7ab 112 ± 12bc 46 ± 1a 82 ± 4ab 96 ± 13bc 134 ± 9c 81 ± 7ab (µmol m-2 s-1) 400 123 ± 14cd 42 ± 3ab 64 ± 11ab 55 ± 5ab 30 ± 4a 130 ± 20d 83 ± 4bc 73 ± 6ab PEPC/Rubisco 180 3.1± 0.3cd 1.7 ± 0.2a 3.2 ± 0.4a-d 2.0± 0.5ab 2.8± 0.3abc 3.2± 0.2bcd 3.7± 0.3cd 4.7 ± 0.3d 400 2.4± 0.3bc 1.4 ± 0.1a 3.2 ± 0.6bc 2.0 ± 0.3ab 1.2 ± 0.1a 2.8 ±0.3bc 2.2± 0.2ab 4.3 ± 0.4c NADP-ME activity 180 1 ± 0.3 3 ± 0.2 3 ± 0.2 n/d n/d n/d 33 ± 3 19 ± 2 (µmol m-2 s-1) 400 1 ± 0.2 1 ± 0.2 2 ± 0.2 n/d n/d n/d 34 ± 2 30 ± 6 PEP-CK activity 180 43 ± 12 b 40 ± 8 b 59 ± 7.4bc 27 ± 2a 35 ± 4b 67 ± 9 c 29 ± .4 a 40 ± 5 b (µmol m-2 s-1) 400 44 ± 6 c 20 ± 3a 39 ± 6b 33 ± 2b 22 ± 2a 64 ± 14 d 31 ± 2 b 36 ± 7 b ab ab ab ab a c ab bc in vivo Vcmax 180 83 ± 5 35 ± 2 34 ± 2 39 ± 2 38 ± 2 32 ± 2 50 ± 2 36 ± 2 42± 2 (µmol m-2 s-1) 400 104 ± 8 46 ± 1bc 37 ± 1a 34 ± 1a 41 ± 1ab 37 ± 1a 46 ± 1bc 41 ± 1ab 52± 1c c b ab ab ab ab ab a in vivo Vpmax 180 213 ± 7 132 ± 7 103 ± 6 108 ± 7 107 ± 7 115 ± 7 110 ± 6 91 ± 7 (µmol m-2 s-1) 400 170 ± 4c 90 ± 4a 82 ± 4a 86 ± 4a 84 ± 4 a 150 ± 4 b 86 ± 4a 80 ± 4a f e ab bc ab ab de a Vp/Vc 180 6 ± 0.2 3.9 ±0.2 2.6 ±0.2 2.8 ± 0.2 3.2 ±0.2 2.3 ±0.2 3 ± .2 2 ± 0.2 400 3.7 ± 0.1c 2.5 ±0.1b 2.5 ±0.1b 2.1 ± 0.1ad 2.3 ±0.1b 3.3 ±0.1c 2 ± 0.1ab 1.5 ± 0.1a

A 0.6 B 35 Glacial CO 30 0.5 2

 Ambient CO )

) 2 -1

-1 25 s

s 0.4

-2 -2

0.3

mol m mol 15



(mol m (mol (

s 0.2 g

sat 10 A 5 0.1

0 0.0 C D

]

-1 )

-1 60

O) 150 2

50 (mg g (mg

100 40

mass

mol (mol H (mol mol 30 

50 20 Leaf [N] Leaf 10

PWUE [ PWUE

0 0 E F

)

]

-1 -1

s 0.3 60 -1

g plant g (

0.2 40

30 mmol (mol N) (mol mmol [ 0.1 20

Plant dry mass mass dry Plant PNUE PNUE 0.0 0 C3 C3-C4 NAD-ME PCK NADP-ME C3 C3-C4 NAD-ME PCK NADP-ME

Figure 3. 1 Gas exchange and growth parameters.

Light-saturated photosynthesis, Asat (A), stomatal conductance, gs (B), photosynthetic water use

efficiency, PWUE (C), leaf N per unit dry mass, [N]mass (D), photosynthetic nitrogen use

efficiency, PNUE (E) and plant dry mass, PDM (F) of ten grass species belonging to C3, C3-C4 -1 and C4 (NAD-ME, PCK, NADP-ME) photosynthetic types grown at glacial (180 µl L , clear -1 columns) or ambient (400 µl L , solid columns) [CO2]. Values are means ± SE per group or species in groups with single species.

Photosynthesis Stomatal conductance C3

C3-C4

NAD-ME

PCK

NADP-ME A B

PWUE Leaf [N]mass C3

C3-C4

NAD-ME

PCK

NADP-ME C D PNUE Rubisco C3 activity

C3-C4

NAD-ME

PCK

NADP-ME E F PDM PEPC C3 activity

C3-C4

NAD-ME

PCK

NADP-ME G H 0.0 0.4 0.8 1.2 0 1 2 3 Glacial/Ambient CO ratio 2 Glacial/Ambient CO2 ratio

Figure 3. 2. CO2 sensitivity of photosynthetic and growth parameters.

Glacial to ambient CO2 ratios of light-saturated photosynthesis, Asat (A), stomatal conductance, gs (B), photosynthetic water use efficiency, PWUE (C), leaf N per unit dry mass, [N]mass (D), photosynthetic nitrogen use efficiency, PNUE (E), Rubisco activity (F), plant dry mass, PDM (G) and PEPC activity (H). Original data are shown in Table 3.4 and 3.5.

NAD-ME PCK NADP-ME NAD-ME PCK NADP-ME

) 200 ) B

-1 A Glacial CO

2 -1

s s -2 Ambient CO

60 2 -2

150

mol m mol mol m mol

 45

(



(

100 30

15 PEPC activity Rubiscoactivity

0 0 )

C ) D -1

-1 80

s -2 30 -2

mol m mol



 (

20 (

10 20

PEP-CKactivity

NADP-MEactivity 0 0 E F

200 )

) 45

-1

s -2 -2 150

mol m mol

mol m mol 

 100

(

15 pmax

cmax 50

V V

0 0 G H 6 5

cmax 4

/V 3

pmax 2 V

2 PEPC/Rubisco 1

0 0

Z. mays Z.

C. gayana C.

A. lappacea A.

A. A. lappacea

H. contortus H.

P. monticola P.

P. maximum P.

P. P. monticola

P. coloratum P.

P. P. maximum

P. P. coloratum

E. frumentaceae E. E. E. frumentaceae

Figure 3. 3. Activity of photosynthetic enzymes.

Activities of Rubisco (A), PEPC (B), NADP-ME (C), PEP-CK (D), in vivo Vcmax (E), in vivo Vpmax

(F), Vpmax/Vcmax ratio (G) and PEPC/Rubisco activity ratio (H) of eight C4 grass species (NAD- ME, PCK, NADP-ME) grown at glacial (180 µl L-1, clear columns) or ambient (400 µl L-1, solid columns) [CO2]. Values are means (n = 3-4) ± SE.

NADP

, ,

, C ,

, NAD

, PCK

, ,

, NAD

, PCK

, NADP ,

contortus

milioides

lappacea

bisulcatum

gayana

frumentacea

coloratum

H. H.

P. P.

P. P. mays Z,

P. maximum P.

E. E.

P. P. C. C. Rubisco

PEPC

NADP-ME

PEP-CK A G A G A G A G A G A G A G A G A G

Figure 3. 4. Immunoblot analyses of photosynthetic enzymes.

Examples of immunoblot analysis for the photosynthetic proteins Rubisco (A), PEPC (B), NADP-ME (C) and PEP-CK (D) extracted from leaves of selected grass species grown at glacial -1 -1 (180 µl L , G) or ambient (400 µl L , A) [CO2].

P. bisulcatum, C

) 0 3

-1

s -2 B

molm



P. milioides, C -C 0 3 4

Assimilationrates ( C Z. mays, C 4 40

-1 Glacial CO (180 L L ) 2 -1 Ambient CO (400 L L ) 2 0 0 300 600 900 1200

-1 Intercellular CO (L L ) 2

Figure 3. 5. Responses of CO2 assimilation rate to increasing intercellular [CO2].

-1 Examples of A-Ci curves measured in C3, C3-C4 and C4 species grown at glacial (180 µl L , ) -1 or ambient (400 µl L , ) [CO2]. Values represent the means ± SE of three replicates.

A B

60 60

)

-1

-2

)

-1

molm -2

 40 40

molm

 (

20 cmax 20 V

2 Glacial CO Rubisco activity ( activity Rubisco r = 0.63 2 Ambient CO 2 0 2000 C D

150 150

)

-1

-2 -2 100

100

molm



(

pmax

pmax V

V 50 50 r2 = 0.73 r2 = 0.74

0 0 0 20 40 60 0 50 100 150 200 Rubisco activity (mol m-2 s-1) PEPC activity (mol m-2 s-1)

Figure 3. 6. Relationships between the in vitro and in vivo estimates of Rubisco and PEPC activities in eight C4 grass species.

Values are means for each species grown at glacial (180 µl L-1, ) or ambient (400 µl L-1, )

[CO2]. Solid lines represent linear regressions of all data points. Original data are shown in Table 3.5.

3.4 Discussion

3.4.1 Photosynthetic efficiency under glacial CO2: C3, C3-C4 and C4 pathways

In accordance with theoretical understanding, the current study revealed that photosynthetic rates (Asat) were most responsive to decreased [CO2] from ambient to glacial levels in C3 followed by C3-C4 and then C4 species. In addition, the C4 grasses had higher photosynthesis under ambient and glacial [CO2] relative to C3 and C3-C4 counterparts (Figs. 3.1A, 3.2A). Similar responses were observed for other C3, C3-C4 -1 and C4 species exposed to 180 and 380 µl CO2 L (Ward et al., 1999, Cunniff et al., 2010, Pinto et al., 2011, Vogan and Sage, 2012).

Stomatal conductance was greater at glacial [CO2] compared with ambient [CO2] in all species, but in particular was higher in C4 species relative to the C3 and C3-C4 species (Figs 3.1B, 3.2B). Huxman and Monson, (2003) found that gs was more sensitive to changing Ci in C4 relative to C3 and C3-C4 Flaveria species. Recently,

Vogan and Sage, (2011) presented evidence of changed Ci sensitivity for gs in

Flaveria species during their evolutionary transition from C3 to C4 photosynthesis. In contrast, Morison and Gifford, (1983) observed little difference in stomatal sensitivity to short-term changes of [CO2] or VPD between two C3 and two C4 grasses. Growth at low [CO2] may cause acclimation of the stomatal response that is not necessarily captured during short-term gas exchange measurements. However, a number of studies found no evidence of differential stomatal acclimation between C3 and C4 plants (Cunniff et al., 2010, Vogan and Sage, 2012). Hence, there does not seem to be a consensus regarding the relative stomatal sensitivity to short- or long- term changes in [CO2] between C3 and C4 plants, which remains an area worthy of further investigation.

Despite having larger stomatal conductance at glacial [CO2], C4 species maintained greater PWUE than C3-C4 and C3 species as a result of higher photosynthetic rates in

C4 plants (Fig. 3.1). Improved PWUE is one of the most consistently reported advantages of C4 species (Long, 1999, Taylor et al., 2010). Higher PWUE in the C3-

C4 species relative to the C3 species under both growth [CO2] confirmed that the

photorespiratory pump of the intermediate pathway confers greater water use efficiency relative to the C3 pathway (Pinto et al., 2011, Vogan and Sage, 2011), thereby achieving PWUE similar to the C4, NADP-ME pathway under glacial [CO2] (Fig. 3.1C).

Higher PNUE in C4 relative to C3 plants under ambient [CO2] is well established (Brown, 1978, Long, 1999, Taylor et al., 2010). In this study, these differences were maintained under glacial [CO2] as a result of higher photosynthetic rates and lower leaf [N] in the C4 relative to the C3 and C3-C4 species (Fig. 3.1). The C3-C4 species had no PNUE advantage over the C3 species, mainly due to the higher leaf [N] and Rubisco-N of the intermediate species (Table 3.4). In contrast, intermediate Flaveria species maintained higher photosynthesis and PNUE relative to C3 congeners at ambient and glacial [CO2] (Vogan and Sage, 2012).

Growth of P. bisulcatum (C3) at glacial [CO2] increased Rubisco activity and stomatal conductance to improve photosynthetic capacity and CO2 supply, respectively (Tissue et al., 1995, Gesch et al., 2000, Anderson et al., 2001). These commonly reported responses represent significant N and water costs for C3 plants at glacial [CO2], thus reducing their PWUE and PNUE. The additional resource requirements at low [CO2] may have contributed to the more pronounced reduction in plant biomass in C3 relative to C4 plants observed in this study (Fig. 3.2F) as in others (Ward et al., 1999, Cunniff et al., 2010, Ripley et al., 2013). Consequently, low WUE and NUE of C3 photosynthesis at low [CO2] may have favoured the evolution of C4 phototosynthesis.

3.4.2 Photosynthetic efficiency under glacial CO2: the C4 subtypes

Results obtained in this study at glacial [CO2] largely confirmed previously reported differences in photosynthetic efficiency among the C4 subtypes at ambient [CO2], and revealed a number of insights into the physiology of C4 subtypes, as discussed below.

Firstly, there were no subtype differences in photosynthetic rates or their sensitivity to decreased growth [CO2]. These results constitute new evidence that there are no discernible differences in the efficiency of the CCM operating in the three C4 subtypes, despite their diverse leaf biochemistry and anatomy. This conclusion is supported by the findings that CO2 leakiness out of the bundle sheath (a surrogate measure of CCM efficiency) is similar among C4 grasses with different subtypes (Henderson et al., 1992, Cousins et al., 2008).

Secondly, NAD-ME species had lower gs and higher PWUE relative to NADP-ME and PCK counterparts at glacial [CO2]. Moreover, gs was less affected by glacial

[CO2] in NAD-ME than NADP-ME and PCK grasses (Fig. 3.2). Previous studies demonstrated that photosynthetic activity was less sensitive to water deficit, and leaf traits were better suited for arid habitats in a NAD-ME relative to a NADP-ME and a PCK grass (Carmo-Silva et al., 2007, Carmo-Silva et al., 2009). In another study, Ghannoum et al., (2002) showed that NAD-ME grasses increased their whole-plant WUE to a greater extent than their NADP-ME counterparts under water stress. Taken together, these findings are consistent with the observation that grasses with the

NAD-ME subtype predominate in more arid regions relative to the other two C4 subtypes (Hattersley, 1992, Taub, 2000).

Thirdly, NADP-ME grasses showed the greatest increase of leaf [N]mass, which may be linked to their stomatal response in that the correlation between N uptake (proxy leaf [N]) and mass flow of soil water through the transpiration stream (proxy gs) is commonly reported in plants grown under different atmospheric [CO2] (Conroy and Hocking, 1993, McDonald et al., 2002, Sherwin et al., 2013). While the mass flow hypothesis may partially contribute to these differences, it remains unclear to what extent. McGrath and Lobell, (2013) suggested that even though a large number of researchers have documented the effect of different atmospheric [CO2] on crop quality, there is still limited understanding of the mechanisms involved.

Fourthly, NAD-ME grasses showed the lowest biomass reduction in response to decreased growth [CO2] relative to the PCK and NADP-ME species. NAD-ME grasses also had lower plant biomass relative to the other C4 species at both growth

[CO2]. Studies conducted at elevated [CO2] have shown that growth response to high

[CO2] decreases with decreasing growth potential (Poorter, 1993, Ziska and Bunce,

1997). Extrapolating these findings to low [CO2] suggests that the lower growth response to glacial [CO2] in NAD-ME plants may be related to their smaller biomass accumulation relative to the other, larger C4 species. Interestingly, the C3 species did not have the lowest biomass at ambient [CO2] despite having the lowest Asat. This is most likely related to the large leaf area of this species, which enables it to have relatively higher growth rate than the generally small- and narrow-leaved C4 grasses.

3.4.3 Photosynthetic enzymes under glacial CO2

Generally, growth at low [CO2] leads to increased photosynthetic capacity, gs, and leaf [N] in C3 plants (Dippery et al., 1995, Ward et al., 1999, Anderson et al., 2001, Cunniff et al., 2010, Gerhart and Ward, 2010, Ripley et al., 2013). Accordingly, P. bisulcatum (C3) exhibited increased leaf proteins, including Rubisco at glacial [CO2]

(Fig. 3.2, Table 3.4). P. milioides (C3-C4) did not up-regulate Rubisco content at glacial [CO2], possibly due to the high leaf [N] and Rubisco-N in this species; a consequence of the high N costs of operating two Calvin cycles in the mesophyll and bundle sheath cells (Monson, 1989, Monson and Rawsthorne, 2004).

The operation of Rubisco under elevated [CO2] in the bundle sheath, the multiplicity of metabolic cycles and cells involved in C4 photosynthesis and the complexity of its regulation thwart the task of predicting how C4 photosynthesis will acclimate to growth at low [CO2]. Measurements of photosynthetic rates under growth [CO2]

(Asat) indicated that photosynthesis in the C4 grasses was CO2-limited at glacial

[CO2], albeit to a lesser extent than C3 and C3-C4 counterparts (Fig. 3.2A). This may explain the significant up-regulation of the two carboxylases, Rubisco and PEPC, which were observed in a number of the C4 grasses (Figs. 3.3- 3.6). Generally, the activities of Rubisco and PEPC changed in concert, a reflection of the fine balance operating between these two enzymes which modulate the pace of the C3 and C4 cycles during C4 photosynthesis, respectively (von Caemmerer and Furbank, 2003).

There is strong evidence showing that CO2 delivery into the bundle sheath and

fixation in the mesophyll are tightly regulated as indicated by the constancy of leakiness (a measure of CO2 fixed by PEPC but not Rubisco, subsequently leaking back from the bundle sheath) under a wide range of environmental conditions (Henderson et al., 1992, Cousins et al., 2008). Nevertheless, the PEPC/Rubisco ratio increased at glacial [CO2] in two C4 species (Fig. 3.3H). Increasing PEPC/Rubisco via transgenic transformation in Flaveria bidentis led to increased leakiness, an indication of reduced efficiency of the C4 mechanism (von Caemmerer et al., 1997b).

In the current study, Vpmax and PEPC activity were linearly correlated, while Vcmax and Rubisco activity showed no correlation (Fig. 3.5). Reconciling the in vivo and in vitro estimates of Rubisco and PEPC activity will require greater knowledge about bundle sheath cell wall conductance and [CO2] than is currently available (von Caemmerer et al., 1997a, von Caemmerer and Furbank, 2003).

The activities of the two measured decarboxylases were not affected by growth

[CO2], possibly reflecting the low control that decarboxylases exert on the photosynthetic flux. Pengelly et al., (2012) reported that NADP-ME activity in transgenic F. bidentis can be halved without affecting photosynthetic rates or growth.

Accordingly, the rate of the decarboxylases measured at ambient [CO2] may be sufficient under glacial [CO2], where Rubisco and PEPC activities were up-regulated in a number of C4 species. Although PEPC and NADP-ME have significant effects on the efficiency of the C4 pathway as evidenced by changes in leakiness, Rubisco retains a high control of metabolic flux in C4 leaves (Furbank et al., 1997, von Caemmerer et al., 1997b, Pengelly et al., 2012).

It is worth noting that PEP-CK activity and, to a lesser extent, PEP-CK protein were ubiquitously detected in the C4 species used in this study. Significant PEP-CK activity in C4 grasses and eudicots of the NADP-ME and NAD-ME subtypes has been previously reported (Walker et al., 1997, Wingler et al., 1999, Carmo-Silva et al., 2008, Muhaidat and McKown, 2013). These findings challenge the classical view of the C4 subtypes, where a single decarboxylase dominates (Hatch, 1987, Furbank, 2011). Recent studies have postulated a role for PEP-CK as a second decarboxylase in maize that serves to match ATP and NADPH demand in bundle sheath and mesophyll cells under different light environments (Bellasio and Griffiths, 2013).

The full physiological significance of PEP-CK in a wider range of C4 grasses and environments is yet to be elucidated.

3.5 Conclusions

Various photosynthetic responses, including increased leaf Rubisco, nitrogen and stomatal conductance, were observed in response to growth at glacial [CO2]. Nevertheless, the operation of a CCM ensured that PWUE and PNUE remained higher in C4 species relative to C3 and C3-C4 species, while the photorespiration pump ensured higher PWUE in the C3-C4 relative to the C3 species. Greater resource use efficiency promotes cheaper biomass construction costs, and hence reduces productivity losses at low [CO2]. Accordingly, high resource use efficiency may have constituted a key evolutionary advantage for the transition from C3 to C4 photosynthesis under low [CO2] (Cerling et al., 1998, Sage, 2004). Results obtained in this study support the notion that Rubisco and PEPC, rather than the decarboxylases, modulate the response to glacial [CO2] for C4 grasses with different biochemical subtypes.

* * * * *

CHAPTER 4

RESOURCE USE EFFICIENCY OF DIVERSE C4

GRASSES UNDER HIGH ATMOSPHERIC WATER

DEFICIT

Chapter 4 will form the basis of the following manuscript, which is currently under preparation:

Pinto H, Tissue DT, Ghannoum O. The sensitivity of water use efficiency in C4 grasses to atmospheric aridity depends on maximal stomatal conductance (in preparation).

I declare that I was the primary investigator and author for Chapter 4. I designed and carried out the experiment, collected and analysed the data, wrote the text and prepared the tables and figures. I received appropriate guidance from my supervisory panel.

Abstract

This study investigated the responses of leaf and plant water use efficiency to atmospheric aridity in 20 C4 grasses belonging to three biochemical subtypes (NAD- ME, PCK and NADP-ME) and six dominant evolutionary origins [Andropogoneae (NADP-ME), Digitaria (NADP-ME), Echinochloa (NADP-ME), Paspalum (NADP- ME), Chloridoideae (NAD-ME, PCK) and Paniceae (NADP-ME, NAD-ME and PCK)]. Plants were grown under low (0.7 kPa) and high (2.0 kPa) atmospheric water vapour pressure deficit (VPD), which corresponded to 80% and 40% relative humidity (RH), respectively. The statistical model including the response variables of evolutionary origin and the VPD treatment best explained variation in photosynthetic rate (Asat), stomatal conductance (gs), intercellular [CO2] (Ci), photosynthetic water use efficiency (PWUE), leaf N concentration per unit dry mass

(leaf [N]mass) and plant dry mass (plant DM). The statistical model including the biochemical subtype and the VPD treatment best explained variation in leaf mass per unit area (LMA), leaf N concentration per unit area (leaf [N]area), photosynthetic nitrogen use efficiency (PNUE), and stomatal index and density of the upper epidermis. Plant WUE and the slopes of Asat vs. gs were the most responsive parameters to the VPD treatment. Atmospheric VPD had also a significant effect on plant DM, leaf [N]mass and Ci. C4 grasses grouped into four categories according to their response to VPD. The first group (Echinochloa and Paspalum) showed high stomatal closure and low photosynthetic response to increased VPD, leading to the greatest gains in PWUE. The second group (Chloridoideae and Paniceae) showed high reductions in stomatal conductance and photosynthetic rates to increased VPD, leading to moderate gains in PWUE. The third group (Andropogoneae) showed negligible stomatal and photosynthetic responses to high VPD leading to minimal gains in PWUE. The fourth group (Digitaria) showed low stomatal and high photosynthetic reductions in response to increased VPD, leading to losses in PWUE.

Significantly, C4 grasses with the lowest gs at low VPDL (corresponding to maximal gs measured in this study) had the lowest sensitivity in response to increasing VPDL.

This linear relationship was strong and common for all C4 species, and at both

growth VPD treatments, indicating that the stomatal response to VPD in grasses is independent of the underlying photosynthetic metabolism.

4.1 Introduction

The C4 photosynthetic pathway is a biochemical adaptation to overcome the inefficiencies of the ancestral C3 photosynthetic pathway. Biochemically, C4 photosynthesis represents a CO2 concentrating mechanism (CCM) that achieves high

CO2 concentration ([CO2]) at the site of Rubisco activity (Hatch, 1987). During C3 photosynthesis, atmospheric CO2 is fixed to ribulose 1, 5-bisphosphate (RuBP) in a reaction catalysed by the enzyme ribulose 1, 5-bisphosphate carboxylase/oxygenase

(Rubisco). In addition to its low specificity for CO2, Rubisco can also react with O2 resulting in the loss of fixed CO2 and energy, in a process known as photorespiration (Andrews and Lorimer, 1978, Morell et al., 1992). Under current atmospheric conditions, high rates of photorespiration in C3 plants reduce the net photosynthetic

CO2 fixation by 30-40% (Pearcy and Ehleringer, 1984, Ehleringer, 2005).

In response to some environmental conditions, such as high temperature and atmospheric aridity, which promote high rates of transpiration, plants react by minimizing stomatal opening in order to reduce water loss form leaves (Farquhar and Sharkey, 1982a, Morison and Gifford, 1983, Mott and Parkhurst, 1991, Oren et al.,

1999). This response pattern results in lower intercellular CO2 concentration (Ci), which enhances photorespiration in C3 plants. By operating a CCM, C4 photosynthesis saturates at a relatively lower Ci, and C4 leaves function with a lower stomatal conductance, relative to C3 counterparts (Long, 1999, Taylor et al., 2010).

Consequently, C4 plants are better adapted than C3 plants to hot, high light and dry environmental conditions (Osmond, 1982, Pearcy and Ehleringer, 1984, Long, 1999).

Consequently, environmental factors that enhance photorespiration in C3 plants may have constituted evolutionary pressures that ultimately led to the innovation of more efficient photosynthetic mechanisms, such as the CCM in terrestrial C4 plants.

The decline in atmospheric [CO2] in the late Oligocene (30 Mya) is considered to be the primary driver for the evolution of the C4 photosynthetic pathway (Ehleringer et al., 1997, Pagani et al., 1999, Tipple and Pagani, 2007, Christin et al., 2008a). During the last glacial maximum, greater C4 plant abundance occurred when low [CO2] coincided with increased aridity (Sukumar et al., 1993, Street-Perrott et al., 1997,

Huang et al., 1999, Huang et al., 2001, Edwards et al., 2010). Thus, under a low

[CO2] environment, C4 plant expansion was likely driven by additional evolutionary co-drivers including soil and atmospheric aridity, changes in seasonal precipitation patterns or both (Hattersley, 1983, Pearcy and Ehleringer, 1984, Pagani et al., 1999,

Still et al., 2014). Therefore, it may be argued that C4 expansion represented an ecological response to changes in regional precipitation associated with lower atmospheric humidity and soil water stress, both of which increase photorespiration in C3 plants (Tipple and Pagani, 2007, Sage et al., 2012).

The success of plants in various environments depends on their ability to balance carbon gain with water loss (Cowan, 1982, Franks and Farquhar, 1999). High temperature, low [CO2] and soil or atmospheric aridity are some of the main factors that stimulate photorespiration in C3 plants (Farquhar et al., 1980b, Jordan and Ogren, 1984, Long, 1991). One of the most significant environmental variables regulating stomatal conductance in plants is the atmospheric water vapour pressure deficit (VPD), and in particular the leaf-to-air VPD (VPDL). With increased VPDL, plants partially close their stomata (Farquhar and Sharkey, 1982b, Bunce, 2000).

Reduced stomatal conductance (gs) with increased VPDL is thought to be due to increased transpiration rate (E) (Monteith, 1995, Pataki et al., 2000, Mott et al.,

2014). Therefore, by reducing stomatal conductance at high VPDL, plants minimize the negative effects of declining plant water potential at high E (Cowan, 1982, Saliendra et al., 1995). For this reason, the closure response of stomata has evolved to avoid excessive dehydration, hydraulic failure and other physiological damage to plants (Oren et al., 1999, Maherali et al., 2003, Osborne and Sack, 2012). Under current ambient [CO2], the C3 pathway is not CO2 saturated except under very low temperature (Long, 1991, Sage and Kubien, 2007). Therefore, C3 photosynthesis should decrease at high VPDL due to lower gs and Ci as has been observed (Schulze and Hall, 1982, El-Sharkawy et al., 1984). Furthermore, the stomata of C3 species have been shown to be more responsive to VPDL than in C4 species (Bunce, 1983, Kawamitsu et al., 1987, Kawamitsu et al., 1993). Kawamitsu et al., (1987) suggested that the stomatal sensitivity to VPDL depends on the plant water status, growth conditions and species. However, there is little information about the stomatal sensitivity to VPDL in diverse C4 grasses. 100

The C4 photosynthetic pathway is biochemically, evolutionarily and ecologically diverse. In particular, three main C4 biochemical subtypes exist (NADP-ME, NAD-

ME, and PCK), representing the different C4 acid decarboxylation pathways (Hatch,

1987). The distribution of these C4 subtypes is aligned with certain taxonomic lineages (Gutierrez et al., 1974, Prendergast et al., 1987, Giussani et al., 2001, Christin et al., 2009b, Grass Phylogeny Working Group, 2012). With increasing annual rainfall, the floristic abundance of NADP-ME and PCK species increases, while that of NAD-ME species decreases (Ellis et al., 1980, Hattersley, 1992, Taub, 2000). Kawamitsu et al. (1987) observed that photosynthetic water-use efficiency (PWUE) was higher in NAD-ME relative to NADP-ME species under high VPD in a small number of C4 grasses (Kawamitsu et al., 1987). Furthermore, in a comparison of NAD-ME and NADP-ME C4 grasses, it was observed that NAD-ME species improved their plant WUE to a greater extent than their NADP-ME counterparts under soil water stress (Ghannoum et al., 2002). Accordingly, I hypothesised that NAD-ME species are more water use efficient than NADP-ME species under high atmospheric or soil aridity.

In light of the evolutionary and phylogenetic diversity that exists among C4 grasses, it is important to gain an appreciation of the VPD responses within the broader, diverse C4 plant community. Consequently, this study aimed at (1) investigating the influence of the biochemical subtype and evolutionary origin in structuring physiological traits associated with WUE in a large number of C4 grasses; and (2) determining how high VPD influence these relationships.

The current study investigated the responses of leaf and plant carbon and water exchange to short- and long-term changes in VPD for 20 C4 grasses belonging to three biochemical subtypes (NADP-ME, NAD-ME and PCK) and six major evolutionary origins: Paspalum (NADP-ME), Andropogoneae (NADP-ME), Echinochloa (NADP-ME), Digitaria (NADP-ME), Paniceae (NADP-ME, NAD-ME, PCK) and Chloridoideae (NAD-ME, PCK), and grown under low (0.7 kPa) and high (2.0 kPa) VPD.

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4.2 Materials and Methods

4.2.1 Plant culture and water use measurements

The experiment was conducted in two glasshouse chambers (~5 m3 each) at the University of Western Sydney, Hawkesbury campus, Sydney Australia. The relative humidity (RH) of the chambers was controlled by humidifiers (Carel HumiDisk 65, On Time Mall Inc, Phoenix, AZ) and de-humidifiers (model DC20ET, Applied Climate Control (NSW) Pty Ltd). Relative humidity in the two glasshouse chambers was controlled at 80% and 40%; this corresponded to atmospheric water vapour pressure deficit (VPD) of 0.7 kPa (low VPD treatment) and 2.0 kPa (high VPD treatment), respectively. Tinytag data loggers (TinyView, Gemini Data Loggers Ltd., Chichester, UK) were used to monitor the relative humidity and temperature of the chambers. The chambers were programmed to simulate ambient local temperature. The average growing season temperatures for the low and high VPD treatments were 26/22 and 25/21oC (day/night), respectively. A summary of the average growth conditions for the two chambers is provided in Table 4.1.

Table 4. 1 Summary of growth conditions in the glasshouse chambers.

Low VPD treatment High VPD treatment

Day Night Day Night

–1 Atmospheric [CO2] (μl L ) 395 ± 4 397 ± 4 394 ± 4 398 ± 4

Air temperature (oC) 26 ± 0.4 22 ± 0.3 25 ± 0.5 21 ± 0.2

Relative humidity, RH (%) 80 ± 5 75 ± 5 42 ± 3 38 ± 2

Atmospheric vapour 0.67 ± 0.03 0.84 ± 0.03 1.95 ± 0.03 2.08 ± 0.03 pressure deficit, VPD (kPa)

Soil was collected from the Hawkesbury Field Experiment site, University of Western Sydney, Hawkesbury campus. A detailed description of soil physical and chemical properties can be found in (Ghannoum et al., 2010). Polyethylene bags 102

were placed inside each 3.5 L cylindrical pot to prevent water leakage. Mass of each pot was adjusted to 0.8 kg using pebbles. Air-dried and coarsely sieved soil (3.7 kg) was added to the pots, which were watered to 100% capacity, then transferred to the two glasshouse chambers. Soil water capacity was calculated as the difference between the mass of two non-watered pots and that of pots watered and left to drain freely overnight.

Paspalum notatum (NADP-ME) Paspalum dilatatum(NADP-ME)

Paspalum (NADP-ME)

Bothriochloa insculpta (NADP-ME) Heteropogon contortus (NADP-ME) Andropogoneae (NADP-ME)

Echinochloa frumentaceae (NADP-ME) Echinochloa turneriana (NADP-ME) Echinochloa Setaria italica (NADP-ME) (NADP-ME) Cenchrus ciliaris (NADP-ME) Panicum miliaceum (NAD-ME) Panicum coloratum (NAD-ME) Paniceae Panicum virgatum (NAD-ME) NADP-ME+PCK+NAD-ME Urochloa panicoides (PCK) Eriochloa meyeriana (PCK) Panicum maximum (PCK)

Digitaria Digitaria brownii (NADP-ME) (NADP-ME)

Eleusine coracana (NAD-ME) Astrebla lappacea (NAD-ME) Leptochloa fusca (NAD-ME) Chloridoideae Eragrostis curvula (NAD-ME) Chloris gayana (PCK) (NAD-ME+PCK)

30 20 10 Mya

Figure 4. 1. C4 grass species used in the current study.

Calibrated phylogeny tree (based on Christian et al., 2009) representing the origins, subtypes and species used in the experiment.

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Seeds for the different species (Figure 4.1) were obtained from Australian Plant Genetic Resources Information System (QLD, Australia) and Queensland Agricultural Seeds Pty. Ltd., (Toowoomba, Australia). Seeds were sown in germination trays containing a common germination mix. Three to four weeks after germination, three seedlings were transplanted into each of the soil-filled pots. Within a week of transplanting, one healthy seedling was left in the pot while the other seedlings were removed. There were four pots per species and VPD treatment. Pots were rotated within each chamber regularly, and the pots and treatments were swapped between chambers at regular intervals to minimise any chamber effects. The similar growth conditions between the two treatments confirmed that growth conditions, other than the VPD treatment, were well matched between the two treatments.

4.2.2 Gas exchange measurements

Gas exchange measurements were conducted using a portable open gas exchange system (LI-6400XT, LI-COR, Lincoln, NE, USA) to determine light-saturated photosynthetic rate (Asat) and stomatal conductance (gs). Measurements were conducted between 10:00 and 14:00, about 7-8 weeks after transplanting, on an attached, last fully expanded leaf (LFEL) on the main stem. Measurements were made at a photosynthetic photon flux density of 1800 μmol m-2 s-1. Photosynthetic rates were measured at leaf-to-air VPD (VPDL) similar to average growth values of -1 0.7 or 2.0 kPa, daytime [CO2] of 400 μl L and mid-day temperature of 26ºC. Before each measurement, the leaf was allowed to stabilise for 10-20 min until it reached a steady state of CO2 uptake.

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The responses of CO2 assimilation rates and stomatal conductance to step increases of VPDL were measured under similar conditions as the spot measurements by raising cuvette humidity in four steps: 20%, 40%, 60 % and 80% RH corresponding to VPDL of 2.69, 2.02, 1.34 and 0.67 kPa, respectively. Before each measurement, the leaf was allowed ample time to stabilise (up to 40 min) until stomatal conductance reached a steady state. There were four replicate measurements per treatment.

4.2.3 Epidermal impressions

A thin layer of a clear nail varnish was applied to the middle-third of both upper and lower leaf surfaces, excluding the mid-rib. The varnish was allowed to dry for 5 min. A clear sticky tape was placed on the varnish, and was then gently peeled off the leaf surface. The sticky tape with the epidermal impression was pasted on a clear glass slide. Both upper and lower leaf epidermal impressions were collected. There were five upper and five lower leaf impressions collected for each species. These sections were viewed through a compound light microscope (Olympus BX60, PA, USA) using the 20X objective. Three sections per sample (with an area of 0.25 mm2) were observed to count the number of stomata and epidermal cells. Stomatal index [(number of stomata * 100)/ (number of stomata + number of epidermal cells)] and stomatal density (number of stomata/area) were calculated.

4.2.4 Growth and nitrogen analysis

Following gas exchange measurements, the LFEL was cut and its area was determined using a leaf area meter (LI-3100A, LI-COR, Lincoln, NE, USA). The LFEL was oven-dried and milled to a fine powder. Tissue nitrogen concentration ([N]) was determined on the ground samples using a CHN analyser (LECO TruSpec, - LECO Corporation, Michigan, USA). Leaf [N]area was calculated as leaf N (mmol g 1) * LMA (g m-2).

were oven-dried at 80ºC for 48h before dry mass was measured. Leaf mass per area (LMA, g m-2) was calculated as total leaf mass (g)/total leaf area (m2).

4.2.5 WUE and NUE calculations

Plant water use efficiency (WUE) was calculated as total plant dry mass (g plant- 1)/total cumulative water use of an individual plant (g plant-1). Photosynthetic water -2 -1 -2 -1 use efficiency (PWUE) was calculated as Asat (μmol m s )/gs (mol m s ). -2 -1 Photosynthetic N use efficiency (PNUE) was calculated as Asat (μmol m s )/Leaf -2 [N]area (mmol m ).

4.2.6 Statistical analysis

Linear mixed effect (lme) model. Growth, water use and gas exchange measurements were performed on four replicates per treatment combination (species x VPD level), while tissue N analysis was performed on three replicates per treatment. Since measurements were taken on multiple individuals within a species, each unit cannot be considered a true independent replicate. Therefore, I used linear mixed effects (lme) models to estimate fixed effects, associated with VPD treatment, evolutionary origin and subtype, and random effects, associated with species identity. Model residuals were tested (Shapiro) for normality and extreme outliers removed before refitting models. To certain effects, lineage and subtype were collinear so models containing all combinations of fixed effects were fitted using lme4 (Bates, Maechler & Bolker, 2012) package in R (R Foundation for statistical computing, Vienna, Australia) and the Akaike information criterion (AIC) and Akaike weight

(wi) was calculated for all models of each response variable to estimate the relative importance of the parameters as predictors; for each response variable, the importance of individual parameters was calculated as the sum of Akaike weights across all models that included the parameter in question (Burnham and Anderson, 2002). This approach does not explicitly determine whether individual parameters are statistically ‘significant’ (although this could be determined using likelihood ratio tests) but ranks parameters based on their ability to explain variation.

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RDA analysis. The influence of evolutionary origins and biochemical subtypes affecting the species patterns was examined by using redundancy analysis (RDA) in CANOCO software (Braak and Šmilauer, 2002). The dataset was standardised using Euclidean-based ordination method. The significance of each environmental and response variable was tested using Monte-Carlo permutation tests, based on 999 permutations.

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4.3 Results

4.3.1 Summary of statistical analysis

The lme models were used to estimate fixed effects associated with VPD treatment, evolutionary origin and subtype individually and in combination. Overall, the lme model including the response variables of evolutionary origin and the VPD treatment best explained variation in photosynthetic rate (Asat), stomatal conductance (gs), intercellular [CO2] (Ci), photosynthetic water use efficiency (PWUE), leaf N concentration per unit dry mass (leaf [N]mass) and plant dry mass (plant DM) (Table 4.2). The lme model including the biochemical subtype and the VPD treatment best explained variation in leaf mass per unit area (LMA), leaf N concentration per unit area (leaf [N]area), photosynthetic nitrogen use efficiency (PNUE), and stomatal index and density of the upper epidermis. Plant WUE and the slopes of Asat vs. gs were the most responsive parameters to the VPD treatment. Atmospheric VPD had also a significant effect on plant DM, leaf [N]mass and Ci (Table 4.2).

4.3.2 Leaf water use efficiency

The lme model including the evolutionary origin and growth VPD best explained variation in photosynthetic rate (Asat), stomatal conductance (gs) and photosynthetic water use efficiency (PWUE) (Table 4.2).

Photosynthetic rates were generally lower at high relative to low growth VPD. Under low VPD, Asat was highest in the Chloridoideae (NAD-ME, PCK) and Paniceae

(NADP-ME, NAD-ME, PCK). Under high VPD, Asat was lowest in the Echinochloa and Digitaria (NADP-ME) relative to the other species. The effect of high VPD on

Asat was greatest in the Chloridoideae (29%) and Digitaria (30%) species, and smallest in the Echinochloa and Paspalum (NADP-ME) species. High VPD reduced

Asat the least in NADP-ME (4%) relative to NAD-ME (21%) and PCK (34%) species (Figures. 4.2A and 4.3, Table 4.3).

Stomatal conductance was generally lower at high growth VPD relative to low growth VPD. Under low VPD, gs was lowest in the Andropogoneae and Digitaria

(NADP-ME) species. Under high VPD, gs was not significantly different among the 108

various C4 groups. High VPD reduced gs the least in the Digitaria and

Andropogoneae relative to the other C4 species. High VPD reduced gs in NADP-ME (19%) less than in NAD-ME (36%) and PCK (49%) species (Figures. 4.2B and 4.3, Table 4.3).

Under low VPD, PWUE was highest in the Andropogoneae and Digitaria relative to the other species. Under high VPD, there was no significant difference in PWUE amongst the origins. Relative to low VPD, high VPD improved PWUE in most origins by an average of 42% except for the Andropogoneae and Digitaria. High VPD improved PWUE in NADP-ME (31%) and NAD-ME (29%) more than in PCK (14%) species (Figures 4.2C and 4.3, Table 4.3).

4.3.3 Leaf N use efficiency

The lme model containing the biochemical subtype and VPD treatment best explained variation in leaf mass per unit area (LMA), leaf N concentration per unit leaf area ([N]area) and photosynthetic nitrogen use efficiency (PNUE) (Table 4.2).

Under low VPD, LMA and leaf [N]area were highest in NAD-ME and lowest in PCK species; under high VPD, both parameters were lowest in PCK relative to the other two subtypes. Relative to low VPD, high VPD increased LMA in NADP-ME and PCK species (17%) and decreased LMA in NAD-ME species (10%). High VPD increased leaf [N]area the most in PCK (37%) and NADP-ME (28%) relative to NAD- ME (8%) species (Figures 4.3 and 4A-B, Table 4.3).

Under low VPD, PNUE was highest in PCK species relative to NADP-ME and NAD-ME counterparts. Relative to low VPD, high VPD decreased PNUE the most in PCK (41%) relative to NADP-ME (21%) and NAD-ME (16%) species.

Consequently, PNUE was not significantly different among the C4 subtypes under high VPD (Figures 4.3 and 4.4C, Table 4.3).

4.3.4 Plant water and nitrogen use efficiency

The lme model containing the evolutionary origin and VPD treatment best explained variation in leaf [N]mass and plant DM (Table 4.2). 109

Under low VPD, there was no significant difference in leaf [N]mass between the C4 groups. Under high VPD, leaf [N]mass was highest in Echinochloa relative to other C4 species. Relative to low VPD, high VPD increased leaf [N]mass the most in Echinochloa (37%) and Chloridoideae (32%) species (Figures 4.3 and 4.5A, Table 4.3).

Under low VPD, plant DM was highest in Andropogoneae and lowest in Paspalum species. Under high VPD, there was no significant difference in plant DM between the C4 origins. Relative to low VPD, high VPD decreased plant DM among the various C4 groups by an average of 40% (Figures 4.3 and 4.5B, Table 4.3).

Plant WUE was a highly responsive parameter to the VPD treatment (Table 2). Under both VPD treatments, there was no significant difference in plant WUE among the various C4 groups. Relative to low VPD, high VPD reduced plant WUE in PCK and NADP-ME (53%) more than in NAD-ME (45%) species (Figures 4.3 and 4.4D, Table 4.3).

4.3.5 Stomatal density and index

For the upper epidermis, the lme model containing the biochemical subtype and VPD treatment best explained variation in stomatal index and stomatal density (Table 2). Under both treatments, stomatal index was highest in NAD-ME relative to NADP- ME and PCK species. Under low VPD, stomatal density was highest in NAD-ME relative to PCK and NADP-ME species; under high VPD, stomatal density was lower in NADP-ME relative to the other two subtypes (Figures 4.6A and 4.6C, Table 4.3). High VPD increased stomatal index in NAD-ME species and stomatal density in PCK species (Figure 4.3).

For the lower epidermis, variations in stomatal index were partially explained by the lme model containing the evolutionary origin and VPD treatment, while variations in stomatal density was not well explained by any of the model parameters (Figures 4.6B and 4.6D, Tables 4.2 and 4.3). High VPD affected stomatal index and density the least in the Chloridoideae and Paniceae relative to the other C4 groups (Figure 4.3).

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4.3.6 Relationships among leaf gas exchange parameters

In addition to leaf gas exchange measured at growth VPD, Asat, gs and Ci were also measured in response to short-term changes in (cuvette) leaf-to-air VPD (VPDL). The regression analysis indicated significant positive, linear relationships between Asat and gs with changes in VPDL (Figure 4.7A-B). Statistical analysis showed that variations in the Asat vs. gs slopes were mostly related to the VPD treatment (Table

4.2). Consequently, the Asat vs. gs slopes increased at high growth VPD in all species except those belonging to the Digitaria and Andropogoneae origins (Table 4.3); the increase was more consistent in the Chloridoideae and Paniceae relative to the NADP-ME origins (Figure 4.7A-B), following the same pattern as mean PWUE presented in Figure 4.2C. At low growth VPD, the Asat vs. gs slopes were highest in

Digitaria relative to the other C4 species. At high growth VPD, the Asat vs. gs slopes did not significantly differ between the C4 groups (Tables 4.2 and 4.3, Figure 4.7A- B).

Variations in the gs vs. VPDL and the gs vs. Ci slopes were best explained by the lme model containing the biochemical subtype and growth VPD (Table 4.2). For most C4 species, gs and VPDL were significantly correlated; this relationship was linear within species and treatments for most grasses, and near-exponential across species and treatments (Table 4.3, Figure 4.7C-D). The gs vs. VPDL slopes increased at high

VPD, and were higher in the NADP-ME containing C4 origins (Table 4.3).

There were positive, linear relationships between gs and Ci in response to short-term changes in VPDL (Figure 4.7E-F). At low growth VPD, the gs vs. Ci slopes were highest in Digitaria relative to the other C4 species. At high growth VPD, the gs vs. Ci slopes were similar between the C4 groups (Tables 4.2 and 4.3, Figure 4.7E-F).

A strong, negative linear relationship was found between the gs vs. VPDL slopes and gs measured at low VPDL; species with large gs at low VPDL had the greatest sensitivity (closure) in response to increasing VPDL and vice versa. This relationship was common for plants grown at both VPD treatments (Figure 4.8A).

111

A strong, positive linear relationship was found between the gs vs. Ci slopes and gs measured at low VPDL; species with large gs at low VPDL had the greatest reductions in Ci with increasing VPDL and vice versa. This relationship was common for plants grown at both VPD treatments (Figure 4.8B).

4.3.7 The RDA for VPD treatments

In order to examine the overall associations of the measured leaf physiological parameters, a redundancy analysis (RDA) was undertaken. Accordingly, it was revealed that PWUE was associated with the high VPD treatment (top-left quadrant), while photosynthetic rate, stomatal conductance and Ci/Ca were associated with the low VPD treatment (lower-right quadrant), such that these parameters were largely responsible for the response to atmospheric water vapour pressure deficit (Figure

4.9). Three parameters, leaf [N]area, leaf [N]mass and LMA, were responsible for segregating the NAD-ME, Chloridoideade species (lower-left quadrant) away from all other C4 groups (Figure 4.9). The two NADP-ME origins (Andropogoneae and Digitaria) clustered together in the same quadrant (top-left quadrant), while another two NADP-ME origins (Echinochloa and Paspalum) were clustered together in the opposite quadrant (lower-right quadrant) (Figure 4.9). The PCK, Paniceae species were clustered separately in the same quadrant (top-right quadrant) (Figure 4.9).

112

Table 4. 2. Statistical model summary.

Summary of the model selection statistics for all the main physiological parameters measured in this study. Statistical analysis was carried out using a customised linear mixed effect model. The response variables were analysed using the VPD treatment, evolutionary origin and biochemical subtype as fixed effects, and species and pot number as random effects. Model selection was

done based on Akaike’s Information Criteria (AIC). Akaike weights (wi) for the various models

are given in the table. For each parameter, the model with the highest wi (best predictive model) is shown in bold.

Parameter VPD, Intercept Subtype, VPD, VPD, Origin, Origin Subtype VPD, Intercept Intercept Intercept Intercept

-2 -1 Photosynthesis, Asat (µmol m s ) 0.100 0.706 0.123 0.071 0.000 -2 -1 Conductance, gs (mol m s ) 0.146 0.686 0.146 0.023 0.000 -1 PWUE (µmol (mol H2O) ) 0.147 0.768 0.022 0.063 0.000 -1 Intercellular [CO2], Ci (µl L ) 0.125 0.483 0.069 0.323 0.000 -2 LMA (g m ) 0.030 0.003 0.690 0.080 0.198 -1 Leaf [N]mass (mg g ) 0.091 0.452 0.068 0.389 0.000 -2 Leaf [N]area (mmol m ) 0.017 0.001 0.905 0.074 0.004 -1 -1 PNUE (mmol (mol N) s ) 0.574 0.000 0.425 0.000 0.000 -1 Plant dry mass, DM (g plant ) 0.099 0.515 0.073 0.313 0.000 Plant WUE 0.002 0.011 0.128 0.859 0.000 Stomatal index, upper 0.204 0.068 0.712 0.016 0.000 -2 Stomatal density, upper(mm ) 0.102 0.392 0.504 0.002 0.000 Stomatal index, lower 0.057 0.398 0.033 0.188 0.325 Slope (Asat vs gs) 0.002 0.013 0.071 0.468 0.447

Slope (gs vs VPDL) 0.158 0.179 0.615 0.048 0.000

Slope (gs vs Ci) 0.090 0.009 0.893 0.003 0.004

113

Table 4. 3. Summary of leaf gas exchange and plant growth parameters.

Leaf gas exchange and plant growth parameters of 20 C4 grass species grown at low (0.7 kPa) or high (2.0 kPa) atmospheric VPD. Gas exchange was measured at growth VPD. Values are means (n=3-4) ±SE. Superscripts indicate the ranking (from lowest (a) to highest (c)) of evolutionary origins within each single row using a multiple-comparison Tukey’s Post Hoc test. Values followed by the same letter are not significantly different at 5% level.

Parameter Growth Evolutionary origin (subtype) VPD Paspalum Andropogoneae Echinochloa Digitaria Paniceae Chloridoideae NADP-ME NADP-ME NADP-ME NADP-ME NADP-ME, NAD-ME, NAD-ME, PCK PCK ab ab a ab ab b Asat Low 33 ± 3 31 ± 3 22 ± 3 31 ± 4 36 ± 1 39 ± 2 (µmol m-2 s-1) High 31 ± 3 a 27 ± 3 a 22 ± 3 a 22 ± 4 a 31 ± 1 a 28 ± 2 a bc ab abc a c c gs Low 0.30 ± 0.03 0.18 ± 0.03 0.27 ± 0.03 0.16 ± 0.04 0.32 ± 0.01 0.32 ± 0.02 (mol m-2 s-1) High 0.19 ± 0.03 a 0.16 ± 0.03 a 0.16 ± 0.03 a 0.17 ± 0.04 a 0.22 ± 0.01 a 0.19 ± 0.02 a PWUE Low 111 ± 13 a 174 ± 13 bc 81 ± 13 a 196 ± 18 c 117 ± 6 ab 122 ± 8 ab (µmol mol-1) High 168 ± 13 a 172 ± 13 a 142 ± 13 a 127 ± 18 a 147 ± 6 a 146 ± 8 a c ab c a bc bc Ci Low 192 ± 20 97 ± 20 229 ± 20 63 ± 28 155 ± 10 157 ± 12 (µl L-1) High 97 ± 20 a 97 ± 20 a 122 ± 20 a 168 ± 28 a 110 ± 10 a 125 ± 12 a c ab c a bc bc Ci /Ca Low 0.50 ± 0.05 0.25 ± 0.05 0.61 ± 0.05 0.16 ± 0.07 0.43 ± 0.03 0.42 ± 0.03 High 0.25 ± 0.05 a 0.25 ± 0.05 a 0.33 ± 0.05 a 0.43 ± 0.07 a 0.30 ± 0.03 a 0.33 ± 0.03 a Transpiration Low 3.8 ± 0.4 b 2.6 ± 0.4 ab 3.4 ± 0.4 ab 2.2 ± 0.6 a 3.5 ± 0.2 ab 4.0 ± 0.3 b (mmol m-2 s-1) High 5.5 ± 0.4 a 4.5 ± 0.4 a 4.5 ± 0.4 a 4.8 ± 0.6 a 5.5 ± 0.2 a 5.1 ± 0.3 a LMA Low 41 ± 6 a 54 ± 6 a 38 ± 6 a 58 ± 8 a 42 ± 3 a 54 ± 4 a (g m-2) High 49 ± 6 a 54 ± 6 a 41 ± 6 a 44 ± 8 a 47 ± 3 a 45 ± 4 a a a a a a a Leaf [N]mass Low 38 ± 3 33 ± 3 40 ± 3 39 ± 4 39 ± 1 34 ± 2 (mg g-1) High 39 ± 3 a 36 ± 3 a 55 ± 3 b 43 ± 4 ab 39 ± 1 a 45 ± 2 ab a a a a a a Leaf [N]area Low 111 ± 15 131 ± 15 104 ± 15 159 ± 21 115 ± 7 132 ± 9 (mmol m-2) High 133 ± 15 a 140 ± 15 a 156 ± 15 a 133 ± 21 a 129 ± 7 a 144 ± 9 a PNUE Low 0.29 ± 0.04 a 0.24 ± 0.04 a 0.20 ± 0.04 a 0.20 ± 0.05 a 0.34 ± 0.02 a 0.31 ± 0.02 a (mmol mol-1 s-1) High 0.24 ± 0.04 b 0.20 ± 0.04 ab 0.14 ± 0.04 a 0.16 ± 0.05 ab 0.24 ± 0.02 b 0.20 ± 0.02 ab 114

Plant dry mass Low 9 ± 3 a 25 ± 3 b 15 ± 3 ab 18 ± 4 ab 16 ± 2 ab 14 ± 2 ab (g plant-1) High 6 ± 3 a 15 ± 3 a 7 ± 3 a 14 ± 4 a 8 ± 2 a 8 ± 2 a Plant WUE Low 8 ± 2 a 10 ± 2 a 10 ± 2 a 9 ± 2 a 12 ± 1 a 12 ± 1 a -1 a a a a a a (g kg H2O ) High 4 ± 2 6 ± 2 5 ± 2 5 ± 2 5 ± 1 5 ± 1 Stomatal index, Low 19 ± 5 ab 10 ± 5 a 18 ± 5 ab 13 ± 7 ab 22 ± 3 b 21 ± 3 b upper High 15 ± 5 ab 17 ± 5 ab 16 ± 5 ab 11 ± 7 a 22 ± 3 ab 32 ± 3 b Stomatal density, Low 0.07 ± 0.02 abc 0.03 ± 0.02 a 0.08 ± 0.02 abc 0.04 ± 0.02 ab 0.09 ± 0.01 bc 0.10 ± 0.01 c upper (mm-2) High 0.05 ±0.02 ab 0.07 ± 0.02 bc 0.07 ± 0.02 bc 0.03 ± 0.02 a 0.10 ± 0.01 cd 0.11 ± 0.01 d Stomatal index, Low 19 ± 4a 25 ± 4a 19 ± 4a 20 ± 6a 16 ± 2a 25 ± 3a lower High 20 ± 4a 23 ± 4a 15 ± 4a 23 ± 6a 19 ± 2a 24 ± 3a Stomatal density, Low 0.07 ± 0.04a 0.11 ± 0.04a 0.09 ± 0.04a 0.06 ±0.05a 0.06 ± 0.02a 0.15 ± 0.02a lower (mm-2) High 0.05 ± 0.04a 0.07 ± 0.04ab 0.07 ± 0.04ab 0.07 ± 0.05ab 0.07 ± 0.02ab 0.14 ± 0.02b Slope Low 14 ± 18 a 39 ± 18 b 23 ± 26 ab 98 ± 26 c 28 ± 11 ab 31 ± 13 ab a a a a a a (Asat vs gs) High 70 ± 18 30 ± 18 39 ± 26 34 ± 26 46 ± 11 42 ± 13 Slope Low -0.03 ±0.01a -0.01 ± 0.01 a -0.04 ± 0.02 a -0.01 ± 0.02 a -0.05 ± 0.01 a -0.04 ± 0.01 a bc bc ab c a ab (gs vs VPDL) High -0.01 ± 0.01 0.001 ± 0.01 -0.02 ± 0.02 0.02 ± 0.02 -0.04 ± 0.01 -0.03 ± 0.01 Slope Low 1 ± 0.39 ab 1 ± 0.39 ab 1 ± 0.55 ab 0.5 ± 0.55 a 2 ± 0.22 b 1.5 ± 0.27 b a a a a a a (gs vs Ci) High 1 ± 0.34 1 ± 0.34 1 ± 0.48 1 ± 0.48 1.3 ± 0.20 1.5 ± 0.24

115

40 A

 )

-1 30

-2

molm



(

sat

A 10

PaspalumPaspalum

PaniceaePaniceae EchinochloaEchinochloa

ChloridoideaeChloridoideae

AndropogoneaeAndropogoneae Digitaria 0 Digitaria B

0.3



)

-1

s -2

0.2

molm

(

s g 0.1

DigitariaDigitaria AndropogoneaeAndropogoneae

ChloridoideaeChloridoideae PaspalumPaspalum

EchinochloaEchinochloa Paniceae 0.0 Paniceae



) -1

) 200

O 2

150

molH

(

mol 100

 (

PWUE PWUE

AndropogoneaeAndropogoneae

PaspalumPaspalum EchinochloaEchinochloa

PaniceaePaniceae DigitariaDigitaria Chloridoideae 0 Chloridoideae

Figure 4. 2. Water use efficiency parameters.

Light saturated rate of photosynthesis, Asat (A), stomatal conductance, gs (B) and photosynthetic water use efficiency, PWUE (C) of 20 C4 grasses belonging to six evolutionary origins grown at low (0.7 kPa, filled columns) or high (2.0 kPa, open columns) atmospheric VPD. Gas exchange measurements were made under growth VPD at 7-8 weeks after planting. Columns are arranged from highest to lowest performing origins under high VPD treatment. Each column represents the mean ± SE of species for each origin. Black columns represent origins with NADP-ME species, the grey column represents the origin with NAD-ME and PCK species, and the checked column represents the origin with all three subtypes. 116

2.0 2.0 A NAD-ME PCK NADP-ME

1.5 1.5

1.0 1.0

0.5 0.5

0.0 0.0

B Paspalum Andropogoneae Echinochloa Digitaria Paniceae Chloridoideae

2.0 2.0 High VPD Low VPD/

1.5 1.5

1.0 1.0

0.5 0.5

0.0 0.0

gs Asat

LMA

PNUE

PWUE

PlantDM

S. index S. L PlantWUE

index S. U

S. density S. L

S. density S. U

Leaf [N]area Leaf [N]mass

Figure 4. 3. VPD sensitivity of physiological parameters.

VPD sensitivity of physiological parameters for 20 C4 grasses. High-to-low VPD ratios ± SE for the main parameters measured in this study for 20 C4 grasses grouped according to their biochemical subtype (A: NAD-ME ●, PCK □ and NADP-ME ▲) or their evolutionary origin (B: Paspalum ■, Andropogoneae , Echinochloa , Digitaria ▲, Paniceae □, and Chloridoideae ●). Original data are shown in Table 4.3. (S.- stomatal, U.- upper epidermis, L.- lower epidermis).

117

60 A Low VPD 160 B

High VPD

)

-2 ) 50

-2 120

(mmolm

30 80

area LMA (g m (g LMA

20 40

10 [N] Leaf

0 0 C D

) 0.5 14

-1

]

-1 s

-1 12 O)

0.4 2 10

0.3

0.2 6 4 0.1

PNUE(mmol(mol N) Plant WUE [g (kg H (kg [g WUE Plant

0.0 0 NAD-ME PCK NADP-ME NAD-ME PCK NADP-ME

Figure 4. 4. Leaf nitrogen and plant water use efficiency.

Leaf mass per area (LMA) (A), Leaf N concentration per unit area (Leaf [N]area) (B), Photosynthetic nitrogen use efficiency (PNUE) (C) and plant water use efficiency (Plant WUE)

(D) of 20 C4 grasses belonging to three biochemical subtypes grown at low (0.7 kPa, filled column) or high (2.0 kPa, clear column) atmospheric VPD. Values are means ± SE of species within each subtype.

118

A ) -1 50

(mg g (mg 40

mass

20 [N] Leaf

EchinochloaEchinochloa

PaspalumPaspalum

AndropogoneaeAndropogoneae

ChloridoideaeChloridoideae

DigitariaDigitaria Paniceae 0 Paniceae 30

) B -1

Plant DM (g plantDMPlant (g 10

ChloridoideaeChloridoideae EchinochloaEchinochloa

DigitariaDigitaria PaniceaePaniceae

PaspalumPaspalum Andropogoneae 0 Andropogoneae

Figure 4. 5. Leaf nitrogen and plant dry mass.

Leaf N concentration per unit mass (Leaf [N]mass) (A) and Plant dry mass (PDM) (B) of 20 C4 grasses belonging to six evolutionary origins grown at low (0.7 kPa, filled columns) or high (2.0 kPa, open columns) atmospheric VPD. Other details are as described for Figure 4.2.

119

40 40 A Low VPD B High VPD

30 30

20 20

10 10

Stomatal indexStomatal (upper) Stomatal indexStomatal (lower)

0 0

) )

) ) -2

C -2 D 0.15 0.15

0.10 0.10

0.05 0.05 Stomatal density(upper)Stomatal (mm 0.00 density(lower)Stomatal (mm 0.00 NAD-ME PCK NADP-ME NAD-ME PCK NADP-ME

Figure 4. 6. Stomatal index and density.

Stomatal index (A, B) and stomatal density (C, D) of upper and lower epidermis of 20 C4 grasses belonging to three biochemical subtypes grown at low (0.7 kPa, filled column) or high (2.0 kPa, clear column) atmospheric VPD. Other details are as described for Figure 4.4.

120

50 A B

) 45

-1 s -2

mol m

 (

sat

A 35

2 R = 0.505 2

Photosynthesis, R = 0.684 25 p < 0.001 p < 0.001 Grown at low VPD Grown at high VPD

0.15 0.20 0.25 0.30 0.35 0.40 0.15 0.20 0.25 0.30 0.35 0.40 Conductance, g (mol m-2 s-1) -2 -1 s Conductance, gs (mol m s ) 0.45 C D 2 0.40 R = 0.382 R2= 0.161 ) p < 0.001 -1 p < 0.001

s Growth at low VPD Growth at low VPD -2 0.35

0.30 (mol m (mol

s g 0.25

0.20

Conductance, 0.15 50 A 0.10 1.0 1.5 2.0 2.5 3.0 3.5 1.0 1.5 2.0 2.5 3.0 3.5

) 45 -1 VPDL (kPa) VPDL (kPa) s 0.45 -2 E F 40

0.40

mol m

)

 -1

(

s sat -2 0.35

A 35

0.30

(mol m s

30 g B 0.25

2 Photosynthesis, 25 R = 0.505 2 0.20 R = 0.684 Grown at low VPD

Conductance, Grown at high VPD 2 R2= 0.623 0.15 R = 0.547 p < 0.001 p < 0.001 0.15 0.20 0.25 0.30 0.35 0.40 0.15 0.20 0.25 0.30 0.35 0.40 Growth at low VPD Growth at high VPD -2 -1 -2 -1 Conductance,0.10 g (mol m s ) Conductance, g (mol m s ) 50 75s 100 125 150 175 200 225 50 75 100 125 s150 175 200 225 Ci (l L-1) Ci (l L-1)

NAD-ME L. fusca E. coracana E. curvula P. coloratum PCK P. maximum E. meyeriana U. panicoides C. gayana NADP-ME E. turneriana P. dilatatum P. notatum B. insculpta H. contortus S. italica C. ciliaris D. brownii

Figure 4. 7. Relationships among leaf gas exchange parameters for 16 C4 grasses. 0.45 D Photosynthetic rate as a function of stomatal conductance (A-B), and stomatal conductance as a 0.40

) 2 2 -1 function of VPDL (C-D) orR C=i 0.382(E-F) for 16 C4 grasses grown at lowR =(A, 0.161 C and D) or high (B, D s Growth at low VPD -2 Growth at low VPD 0.35 o and F) VPD. Leaf gas exchange was measured at 26 C and VPDL of 0.67, 1.34, 2.02 and 2.69

kPa.0.30 NAD-ME, PCK and NADP-ME species are shown in filled, red colour-crossed and clear

(mol m (mol s

g 0.45 symbols,0.25 respectively.

0.40 121

0.20

)

-1 s

-2 0.35 Conductance, 0.15

0.30

(mol m 0.10

s g 1.0 1.5 2.0 2.5 3.0 3.5 1.0 1.5 2.0 2.5 3.0 3.5 0.25 VPD (kPa) VPDL (kPa) L E F

0.20 Conductance, 0.15 R2= 0.547 Growth at low VPD 0.10 50 75 100 125 150 175 200 225 Ci (l L-1)

50 75 100 125 150 175 200 225

0.05 A grown at low VPD

grown at high VPD L

0.00

VPD

versus

-0.05 Slope of of g Slope

-0.10 r2 = 0.79

0.003 B grown at low VPD

grown at high VPD

i C

0.002

versus

0.001 Slope of of g Slope

r2 = 0.851 0.000 0.1 0.2 0.3 0.4 0.5 -2 -1 gs at low VPD (mol m s )

Figure 4. 8. The gs vs. VPDL and gs vs. Ci slopes as a function of maximal gs for 16 C4 grasses.

The slopes of gs versus VPDL (A) and gs versus Ci (B) as a function of gs measured at low VPDL

(equivalent to maximal gs) for 16 C4 grasses grown at low () or high () VPD. Leaf gas o exchange was measured at a leaf temperature of 26 C and VPDL of 0.67, 1.34, 2.02 or 2.69 kPa.

122

1.0

Andropogneae

High VPD PCK HighLow VPD RH Digitaria

NADP-ME PWUE Paniceae

Trans PNUE Photo Paspalum Nmass LMA Cond Ci/Ca Narea

RDA axis (2) 32.4% (2) axis RDA LowHigh VPD RH Chloridoideae Echinochloa

NAD-ME

-1.0 -1.0 RDA axis (1) 66.7% 1.0

Figure 4. 9. RDA tri-plot for leaf level parameters.

Redundancy analysis (RDA) using leaf traits: Photosynthetic rate at growth [CO2] (Photo); stomatal conductance (Cond); transpiration rate (Trans); Ci/Ca photosynthetic water use efficiency (PWUE); leaf nitrogen per unit dry mass (N mass): leaf nitrogen per unit area (N area); leaf dry mass per unit area (LMA); photosynthetic nitrogen use efficiency (PNUE);

measured for 20 C4 grasses belonging to 6 major evolutionary origins: Paspalum, Andropogoneae, Echinochloa, Digitaria, Paniceae and Chloridoideae; and 3 biochemical subtypes (NAD-ME, PCK and NADP-ME) grown at at low (0.7 kPa) or high (2.0 kPa,) atmospheric VPD. The measured parameters are shown as black arrows and the experimental factors (evolutionary origin and biochemical subtype) are shown as red arrows.

123

4.4 Discussion

Atmospheric vapour pressure deficit (VPD) is one of the key environmental factors controlling plant growth and photosynthesis (Grantz, 1990). At the whole plant level, high VPD reduces plant growth due to adverse effects on plant water status and leaf

CO2 uptake (Ludow, 1980). At the leaf gas exchange level, stomatal conductance decreases with increasing VPD, which prevents excessive dehydration and hydraulic failure of plants (Mott and Parkhurst, 1991, Maherali et al., 2003, Osborne and Sack,

2012). In C3 plants, reduced gs causes lower Ci, and hence lower photosynthesis. C4 photosynthesis is CO2-saturated under the current normal atmosphere, and hence not expected to show significant reduction with increased VPD (Bunce, 1983). C4 plants are phylogenetically, biochemically and ecologically diverse. The current study was undertaken in order to distinguish between the morphological (evolutionary origins) and metabolic (biochemical subtypes) adaptations controlling the stomatal sensitivity to VPD among diverse C4 grasses.

4.5.1 Photosynthetic and stomatal responses to high vapour pressure deficit

vary according to the C4 evolutionary origin

In the current study, high VPDL reduced the stomatal conductance (gs) of all C4 species across the various growth VPD, evolutionary origins and biochemical subtypes. Interestingly, species belonging to the Andropogoneae and Digitaria origins (both with the NADP-ME subtype) showed the lowest decrease of gs at high

VPDL (Figure 4.3), and this was associated with the lowest gs at low VPDL, when compared to other origins. In addition, stomatal index and density of NADP-ME species generally showed no significant response to increased VPD. In other studies, a similarly low stomatal response to increasing VPD was observed in Bothriochloa ischaemum, a C4 grass species belonging to the Andropogoneae group (Maherali et al., 2003). Significantly, data presented here showed that C4 grasses with the lowest gs at low VPDL (which corresponds to maximal gs measured in this study) had the lowest sensitivity in response to increasing VPDL. This relationship was strong and common for all C4 species and at both growth VPD treatments (Figure 4.8A). 124

Previously, (Morison and Gifford, 1983) reported that stomatal sensitivity to VPDL was proportional to absolute gs in two C3 and C4 grasses. Taken together, these studies highlight the universality of stomatal sensitivity to VPDL in grasses with different photosynthetic pathways (Morison and Gifford, 1983) and biochemical subtypes (Figure 4.8A) and hence, indicate that the stomatal response to VPDL in grasses is (i) independent of the underlying photosynthetic metabolism and (ii) largely dependent on maximal gs.

It is well established that stomatal sensitivity to high VPDL is reduced under conditions which promote stomatal closure, such as high atmospheric [CO2] or VPD (Bunce, 1998a, Bunce, 1998b, Bunce, 2000). One possible reason is that low stomatal sensitivity to VPDL may enable plants to maintain high CO2 uptake at high VPD, representing an adaptation to atmospheric aridity (Maherali et al., 2003, Osborne and Sack, 2012). Kawamitsu (1993) observed that the NADP-ME grass, P. maximum, which belongs to the Paniceae origin, was insensitive to high VPDL. With increasing VPD, transpiration in P. maximum increased proportionally at ambient

[CO2]. Therefore, they concluded that as Ci is often saturating in C4 species, photosynthesis might be insensitive to partial stomatal closure caused by high VPD, which would represent an advantage for C4 species in warm, dry environments (Kawamitsu et al., 1993). However, it is also possible that stomatal control of water loss in this species is weak as their leaf transpiration increased linearly with increasing VPDL despite progressive stomatal closure.

An alternative explanation for the lower stomatal sensitivity to VPDL could be the effect of cuticular conductance on gas exchange. Cuticular conductance is a component of gs that is not often measured because it is a small proportion of leaf water vapour flux (Kerstiens, 1996, Meyer and Genty, 1998). With rising VPDL, cuticular conductance may remain constant and therefore constitute an increasingly greater proportion of measured gs because the stomata are relatively closed. For species with low gs at low VPDL, the insensitivity of cuticular conductance to high

VPDL could dampen the overall response of gs to VPDL (Maherali et al., 2003).

125

With increased VPD, photosynthetic rates (Asat) decreased in all C4 grasses except for Echinochloa and Paspalum (NADP-ME) species. Grasses that showed the greatest reduction in Asat at high VPD belonged mostly to the Chloridoideae (NAD- ME and PCK) and Paniceae (all subtypes) origins. These two groups also showed relatively high stomatal reduction at high VPD, suggesting a higher degree of CO2- supply limitation in the Chloridoideae and Paniceae relative to other origins.

For C3 plants, high VPD limits CO2 supply into the leaf, and often reduces CO2 assimilation rates (Franks and Farquhar, 1999). This is a common response observed in many studies (Bunce, 1993, Seneweera et al., 1998, Maherali et al., 2003). However, smaller or no responses of assimilation rate to VPD have been observed for many C4 species. The insensitivity of photosynthesis to VPD is explained by the near-saturation for CO2 (Bunce, 1982, Bunce, 1983, Kawamitsu et al., 1987, Kawamitsu et al., 1993). Data in this study suggested that variations exist in the degree of CO2-saturation of C4 photosynthesis as a function of the C4 lineage of these grass species.

Increases in photosynthetic water use efficiency (PWUE) can be achieved by either increased Asat or decreased gs. Under high VPD, PWUE improved in most C4 species mainly due to decreased gs. PWUE improvement was highest in Echinochloa and

Paspalum (NADP-ME) origins because gs was reduced without affecting Asat. However, Andropogoneae and Digitaria species showed nil-to-negative change in

PWUE because gs had a low sensitivity to increased VPDL. Consequently, the C4 grasses can be grouped into four categories (Table 4.4). The first group (Echinochloa and Paspalum) showed high stomatal reductions and nil photosynthetic increases in response to increased VPD, leading to the greatest gains in PWUE. The second group (Chloridoideae and Paniceae) showed high stomatal and photosynthetic reductions in response to increased VPD, leading to moderate gains in PWUE. The third group (Andropogoneae) showed little stomatal and photosynthetic changes in response to high VPD leading to minimal gains in PWUE. The fourth group (Digitaria) showed low stomatal changes and high photosynthetic reductions in response to increased VPD, leading to losses in PWUE (Table 4.4).

126

Table 4. 4. Summary of stomatal, photosynthetic and PWUE responses to increased VPD.

: increase; : decrease, : no change

Stomatal Photosynthetic PWUE response Group Origin response at response at high at high VPD high VPD VPD Echinochloa  1   Paspalum  Chloridoideae  2   Paniceae 

3 Andropogoneae   

4 Digitaria   

4.5.2 Plant dry mass and WUE responses to growth at high vapour pressure deficit

C4 grasses have higher WUE than C3 species due to a greater affinity for CO2 in combination with lower transpiration rates. The presence of a CCM makes C4 photosynthesis more competitive under high photorespiratory environments such as high VPD (Edwards et al., 1985). Previous studies have shown that carbon exchange rates decrease at high VPD (El-Sharkawy et al., 1984, Dai et al., 1992, Kawamitsu et al., 1993) and that stomatal conductance decreases in response to high VPD (Lange et al., 1971, Farquhar et al., 1980a, Grantz, 1990, Maroco et al., 1997) . This reduction in gs, and an associated decrease in carbon exchange rate, probably account for the decrease in plant dry mass (plant DM) with increasing VPD (Ray et al., 2002).

Plant dry mass (DM) generally decreased in all the origins with increased VPD, as has been reported previously (Seneweera et al., 1998, Ghannoum et al., 2001a). It is

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also in agreement with the hypothesis of Ben Haj Salah and Tardieu (1997) that the increase in transpiration rates caused by high evaporative demand results in generation of a hydraulic signal which reduces leaf growth. However, the nature of this hydraulic signal is unknown.(Farquhar et al., 1989b)

Instantaneous measures of Asat and gs are often poor indicators of that averaged over the whole growth period (Farquhar et al., 1989b). Plant water use efficiency (WUE), is an important parameter in determining crop productivity and can be a key determinant of plant fitness and distribution (Long, 1999, Ghannoum et al., 2011). In this study, plant WUE decreased under high VPD in all the origins. This was mainly due to a reduction in plant DM with increased in VPD.

Natural selection pressures from changes in mean annual rainfall are likely to have influenced the diversification of the C4 photosynthesis subtypes among the Poaceae (Hattersley and Watson, 1992). NAD-ME grasses are more abundant at the drier-end of rainfall gradients than NADP-ME and PCK grasses (Ellis et al., 1980, Hattersley, 1992). This contrasting biogeography may be partly due to differences in growth habit (e.g., plant size) or plant WUE among the C4 species (Ghannoum et al., 2002).

Using a small number of C4 grasses, Kawamitsu et al. (1987) found that PWUE and plant WUE were higher in NAD-ME than NADP-ME species under high VPD. This was not the case in the current study, where NAD-ME species did not have any water efficiency advantage under high VPD. Consequently, when water availability is non-limiting, plants achieve their relatively high rate of productivity with correspondingly high rates of water loss. This was observed in a number of C3 plants (Larcher, 1995, Franks and Farquhar, 1999).

It has been established that the main factors affecting variations in plant water use efficiency are respiration and biomass partitioning to non-photosynthetic tissue, non- assimilatory CO2 and water losses (Farquhar et al., 1989b, Jones, 1992, Ghannoum et al., 2002). Measuring these parameters was outside the scope of this study but may provide explanations to the lack of variation in plant WUE among the C4 groups.

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4.5.3 Conclusions

In conclusion, the hypothesis that NAD-ME grasses would be more water use efficient than NADP-ME and/or PCK counterparts at high VPD was rejected at both the leaf and whole plant levels.

At the leaf level, PWUE varied according to evolutionary origins (C4 lineages) at both VPD treatments. The sensitivity of PWUE to high VPD differed among the C4 groups depending largely on the sensitivity of stomatal conductance to high VPDL.

C4 grasses with the lowest gs at low VPDL had the lowest stomatal sensitivity in response to increasing VPDL. This relationship was strong and common for all C4 species and at both growth VPD treatments. Therefore, the stomatal response to

VPDL in grasses was independent of the underlying photosynthetic metabolism and largely dependent on maximal gs. Accordingly, PWUE gains at high VPD were highest in Echinochloa and Paspalum, moderate in Chloridoideae and Paniceae and nil-to-negative in Andropogoneae and Digitaria species.

* * * * *

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CHAPTER 5

VARIATIONS IN LEAF CARBON ISOTOPE

DISCRIMINATION AND PHOTOSYSTEMS I AND II

DISTRIBUTION AMONG C4 GRASSES WITH DIFFERENT SUBTYPES

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Abstract

Previous studies have determined the carbon isotope discrimination and chlorophyll fluorescence in some C4 species. These studies used a narrow range of C4 species and did not consider the full biochemical diversity of the C4 pathways. Consequently, this study aimed at evaluating the degree of species and subtypes variability in leaf 13C/12C isotope composition (δ13C), photosynthetic carbon isotope 13 discrimination against C (p) and the distribution of chlorophyll fluorescence between the mesophyll and bundle sheath cells in a large number of C4 grasses belonging to the NADP-ME, NAD-ME and PCK biochemical subtypes.

In line with previous studies, concurrent gas exchange and carbon isotope discrimination measurements of 22 C4 grass species, this study showed that there was no significant differences in p or estimated bundle sheath leakiness (); while leaf δ13C was lowest in NAD-ME, intermediate in PCK and highest in NADP-ME species. Moreover, leaf δ13C and photosynthetic  were not correlated.

A protocol was developed to analyse chlorophyll fluorescence emission from the mesophyll and bundle sheath cells of fresh C4 leaves using confocal laser scanning microscopy. Using 10 C4 grass species, confocal images revealed that total (PSI + PSII) fluorescence intensity was lower in the bundle sheath relative to the mesophyll for NADP-ME species; the opposite was observed for NAD-ME and PCK species. The ratio of PSII/PSI relative fluorescence was higher in the mesophyll relative to the bundle sheath for all C4 species. In the bundle sheath cells, the ratio of PSII/PSI relative fluorescence was lower in NADP-ME relative to NAD-ME and PCK species.

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5.1 Introduction

5.1.1 Carbon isotope discrimination

The main naturally occurring stable isotopes of carbon are 12C (98.9%) and 13C (1.1%). It has long been recognised that isotopic distribution of organic compounds may reveal information about metabolic processes involved in carbon transformations. Generally, the abundance of 13C relative to 12C in plant tissue is less than in atmospheric CO2, indicating that carbon isotope discrimination (Δ) occurs during the incorporation of CO2 into plant biomass (Farquhar et al., 1989a). In particular, carbon isotope composition in plants (δ13C) depends largely on carbon isotope discrimination which occurs during photosynthesis (Δp).

13 Discrimination against CO2 during C4 photosynthesis takes place during CO2 diffusion into the leaf, the conversion of CO2 into bicarbonate, the two carboxylation reactions catalysed by PEPC and Rubisco, and leakage of CO2 out of the bundle sheath (Farquhar et al., 1989a). Theoretical models predict that variation in photosynthetic Δ (Δp) of C4 plants can arise from changes in Ci/Ca (the ratio between intercellular to ambient [CO2]), and bundle sheath leakiness (ϕ, defined as the fraction of CO2 released in the bundle sheath by the C4 cycle, which is not fixed by

Rubisco) (O'Leary, 1981, Farquhar, 1983). The CO2 concentrating mechanism of C4 plants elevates [CO2] in the bundle sheath cells around Rubisco. This reduces photorespiration to about 2-3% of photosynthesis (Furbank and Hatch, 1987), and 13 reduces the opportunity for Rubisco to discriminates against CO2 (Farquhar, 1983).

The improved efficiency of Rubisco carboxylation comes with an energetic cost of ATP (Hatch, 1987, Edwards et al., 2000), required for regenerating PEP and overcycling CO2 to compensate for leaked CO2 out of the bundle sheath (Kanai and Edwards, 1999, Ubierna et al., 2011). Hence, ϕ reflects the additional energetic cost of the CO2 concentrating mechanism. Henderson et al. (1992) estimated ϕ using concurrent measurements of gas exchange and carbon isotope discrimination to be about 0.2 in a number of C4 species representing different decarboxylation types under a range of environmental conditions. 132

C4 photosynthesis has three biochemical subtypes depending on the major C4 acid decarboxylase: nicotinamide adenine dinucleotide phosphate malic enzyme (NADP- ME), NAD malic enzyme (NAD-ME) and phosphoenolpyruvate carboxykinase (PCK). Specialised leaf anatomy, biochemistry and physiology are associated with each of the C4 subtypes (Hatch, 1987). C4 grasses with different biochemical subtypes are characterised by distinct leaf carbon isotope composition (δ13C), with NAD-ME species being more depleted in 13C (more negative δ13C) relative to NADP-ME (less negative δ13C) species (Hattersley, 1982, Farquhar, 1983).

It has been argued that differences in leaf dry matter δ13C are related to differences in ϕ between the subtypes (Hattersley, 1982, Farquhar, 1983, Ohsugi et al., 1988, Buchmann et al., 1996a, Cousins et al., 2008). For example, the presence of a suberised lamella in the bundle sheath cell wall of NADP-ME species was suggested to reduce ϕ by increasing the physical diffusive barrier of the bundle sheath. However, no relationship was found between leaf dry matter δ13C and photosynthetic

Δp (Henderson et al., 1998). In addition, no significant differences in ϕ or Ci/Ca were found between the C4 subtypes (Henderson et al., 1992, Cousins et al., 2008).

Work done using C4 grasses exposed to various environmental conditions and where leaf dry matter and cellulose δ13C were measured suggested that differences in leaf dry matter δ13C between NAD-ME and NADP-ME plants are in part due to post- photosynthetic fractionations (by Cousins et al. 2008; von Caemmerer et al., 2014).

Moreover, ϕ remained relatively constant with short-term changes in CO2 and light for a number of C4 species (Henderson et al., 1992).

Nevertheless, recent research has shown increased p at low light (Sun et al., 2012, Ubierna et al., 2013, Caemmerer et al., 2014). Using transgenic Flaveria bidentis plants with reduced Rubisco amount relative to PEPC exhibited increased p due to increased ϕ. These plants also had altered leaf δ13C (von Caemmerer et al., 1997b, Pengelly et al., 2012). Transgenic F. bidentis plants with reduced amount of NADP- malic enzyme exhibited decreased  and ϕ (Pengelly et al., 2012). These studies 13 suggest that leaf δ C and photosynthetic p may co-vary among C4 plants.

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In spite of the significant progress made in recent years, no studies have screened large numbers of C4 grasses in order to evaluate the degree of species and subtypes variability in leaf δ13C and photosynthetic . Consequently, photosynthetic carbon isotope discrimination was measured concurrently with gas exchange, followed by analysis of leaf dry matter carbon isotope composition in 22 C4 grass species belonging to the three biochemical subtypes.

5.1.2 Chlorophyll fluorescence

C4 photosynthesis is characterised by the close collaboration between two distinct photosynthetic cell types; bundle sheath and mesophyll cells. It is well established that the chloroplast ultrastructure and the composition of the thylakoid membrane are distinct between the bundle sheath and mesophyll cells of C4 leaves, and that these differences are related to the biochemical subtypes. For example, bundle sheath chloroplasts of maize (NADP-ME) leaves are predominantly agranal and characterised by low PSII activity (Edwards and Walker, 1983, Hatch, 1987, Makino et al., 2003, Ghannoum et al., 2005, Ghannoum et al., 2011). When bundle sheath cells are deficient in PSII, the C4 pathway is dependent on mesophyll chloroplasts to provide reductive power for CO2 assimilation. In NADP-ME species, the importation of malate from the mesophyll cells permits NADPH formation in the bundle sheath cells during the decarboxylation. Hence, malate transport serves to transfer reductive power from mesophyll to bundle sheath cells in NADP-ME species (Takeuchi et al., 2000). Consequently, chloroplasts in these bundle sheath cells require less PSII activity and therefore less O2 is evolved in the bundle sheath cells of NADP-ME species (Kanai and Edwards, 1999). Using a small group of NAD-ME and NADP-ME species, Pfündel et al., (1999) concluded that the diversity in decarboxylation types is matched by that of PSII/PSI ratios in mesophyll and bundle sheath cells in order to accommodate the varied energy demands of the different CO2 concentrating mechanisms. Ghannoum et al., (2005) has shown that the majority of chlorophyll and nitrogen is located in the bundle sheath of two NAD- ME species, and in the mesophyll of two NADP-ME species. However, there is no comprehensive analysis of chlorophyll fluorescence and photosystem activity

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distributions between the mesophyll and bundle sheath cells of C4 grasses belonging to all three biochemical subtypes.

PSI optimally absorbs photons at a wavelength of 700 nm, while PSII optimally absorbs photons at a wavelength of 680 nm (Mohr, 1995). The concentrations of PSI and PSII can be assessed by measuring the chlorophyll fluorescence emitted above and below 700 nm. The spectral window below 700 nm is dominated by PSII emission, while that above 700 nm is dominated by PSI (Govindjee, 1995 , Croce et al., 1996). Confocal microscope images of S. bicolor (NADP-ME) have shown strong fluorescence from PSII in mesophyll cell chloroplasts that have high activity of both PSI and PSII. Adjoining bundle sheath cells that are PSII deficient showed diffuse fluorescence (Edwards et al., 2001). Similar results were also observed with Z. mays (NADP-ME) (Furbank et al., 2009).

Only a few studies have attempted to estimate chlorophyll fluorescence differences in the chloroplasts of C4 leaves. These studies had a number of drawbacks. Firstly, previous work was done using a few species that do not cover all the three C4 biochemical subtypes (Ghannoum et al., 2005). Secondly, single spot measurements of chlorophyll fluorescence were mostly made rather than imaging of the bundle sheath and mesophyll cells (Edwards et al., 1975). To overcome these limitations, I developed a protocol for analysing variations in chlorophyll fluorescence of fresh C4 leaves using confocal laser scanning microscopy. This method was used to estimate the intensity of PSI and PSII chlorophyll fluorescence emission from the bundle sheath and mesophyll cells of ten C4 grasses belonging to the three C4 biochemical subtypes (NAD-ME, NADP-ME and PCK).

The main objectives of this study were to (1) evaluate the degree of species and 13 subtypes variability in leaf δ C and photosynthetic  in a large number of C4 grasses belonging to the three biochemical subtypes. (2) Assess the distribution of chlorophyll fluorescence and photosystem activity between the mesophyll and bundle sheath cells of C4 grasses belonging to the three biochemical subtypes.

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5.2 Materials and Methods

5.2.1 Plant culture

All plants were cultivated from seeds in a naturally-lit glasshouse using 2L pots filled with standard potting mix. Plants were watered once daily and fertilized twice weekly (0.2 g N L-1) with a commercial fertilizer (General Purpose, Thrive Professional, Yates, Australia). There were 2-3 replicate pots per species and each pot contained two individuals of the same species. The C4 grass species used for the carbon isotope and the confocal fluorescence studies are listed in Table 5.1. For the fluorescence study, fully developed leaves, which were well exposed to natural sunlight were used; these leaves were sampled between 10 am and 2 pm.

5.2.2 Leaf gas exchange and photosynthetic carbon isotope discrimination

13 12 Real-time photosynthetic carbon isotope ( CO2/ CO2) discrimination was measured concurrently with gas exchange made on the same leave using LI-6400 systems coupled to a tuneable diode laser (model TGA100; Campbell Scientific) as described by Tazoe et al. (2009). Gas exchange was measured using the youngest fully -1 expanded leaves at current ambient CO2 (400 µl L ), a leaf temperature of 26°C and an irradiance of 1800 µmol quanta m-2 s-1. Photosynthetic discrimination against 13C

( was calculated using (Evans et al., 1986):

(1)

(2)

13 where δe, δo, Ce and Co are the δ C (δ) and CO2 mol fraction (C) of the air entering (e) and leaving (o) the leaf chamber and were measured with the TDL. In this study,

ξ ranged between 5 and 11. Bundle sheath CO2 leakiness () was calculated using the model of (Farquhar, 1983) as modified by (Pengelly et al., 2010, Pengelly et al., 2012). The formulae used are described briefly.

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 (3)

where the term t, which represents ternary effect, is defined as in (Farquhar and Cernusak, 2012):

(4)

t where E is the transpiration rate, g ac the total conductance to CO2 diffusion including boundary layer and stomatal conductance (von Caemmerer and Farquhar, 1981). The symbol a′ denotes the combined fractionation factor through the leaf boundary layer and through stomata.

(5)

where Ca, Ci and Cls are the ambient, intercellular and leaf surface CO2 partial pressures; ab (2.9‰) is the fractionation occurring through diffusion in the boundary layer; a (4.4‰) is the fractionation due to diffusion in air (Evans et al., 1986); ai is the fractionation factor associated with the dissolution of CO2 and diffusion through water.

(6)

(7)

Where b3 is the fractionation by Rubisco (30‰); b4 is the combined fractionation of − the conversion of CO2 to HCO3 and PEP carboxylation (-5.74‰ at 25°C), f is the fraction associated with photosrespiration; and Vo and Vc are the rates of oxygenation and carboxylation, respectively. The fractionation factor e associated with respiration 13 was calculated from the difference between δ C in the CO2 cylinder (-4.2‰) used during experiments and that in the atmosphere under growth conditions (-8‰)

(Tazoe et al., 2008). A and Rd denote the CO2 assimilation rate and day respiration,

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respectively; Rd was assumed to equal dark respiration. I assumed a mesophyll −2 −1 −1 conductance (gm) = 1 mol m s bar for these calculations. Mesophyll conductance has not been directly measured in C4 leaves and its effect on leakiness calculation is minimal (von Caemmerer et al., 2014). In this study, leaf gas

exchange was measured at high light, and hence Vo = 0 ( = 0) (Pengelly et al., 2010, Pengelly et al., 2012, Ubierna et al., 2011, Sharwood et al., 2014).

5.2.3 Leaf dry matter carbon isotope composition, δ13C

Following gas exchange, leaves were cut, oven-dried then ground to a consistent powder and dried again at 80oC for 30 min before a small sample was weighed for analysis. For carbon isotope composition, samples were combusted in a Carlo Erba elemental analyser (Model 1108, Milan, Italy) and the CO2 was analysed by mass 13 spectrometery (VG Isotech, Manchester, UK). The δ C was calculated as [(Rsample– 13 12 Rstandard)/ Rstandard]*1000, where Rsample and Rstandard are the C/ C ratio of the sample and the standard Pee Dee Belemnite (PDB), respectively.

5.2.4 Confocal laser scanning microscopy

Microscopy of freshly hand-cut transverse sections of leaves was carried out using an inverted Leica TCS SP5 laser scanning confocal microscope (CLSM) (Leica SP2 LSCM; Leica Microsystems, Wetzlar, Germany). Leaf sections were excited with 405 and 633 lasers. Fluorescence emission was collected between 480-550 nm to detect cell wall fluorescence, at 659-692 nm to detect PSII fluorescence, and at 700- 748 nm to detect PSI fluorescence. LAS AF software was used for instrumental control and image analysis. One image per species was obtained showing chloroplast and cell wall fluorescence by averaging three measurements in line mode to reduce the background noise. To quantify the intensities of chlorophyll fluorescence, emissions were collected in 10 nm bands at 5 nm intervals from 643 to 758 nm. Chlorophyll fluorescence intensity per unit area of 5 fluorescing regions in the mesophyll cells and from 5 adjusted fluorescing regions in the bundle sheath cells were determined. The background signal was determined from the nearest region of

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the leaf spectrum outside the area of active PSI and PSII fluorescence. For calculation of bundle sheath and mesophyll fluorescence quotients, only background- corrected fluorescence intensities were used. Mean fluorescence intensities at the wavelengths of 688 nm (peak PSII fluorescence) and 718 nm (peak PSI fluorescence) were calculated from the spectral data. Three images per species were analysed.

5.2.5 Data analysis

There were four replicates per species for carbon isotope discrimination and three replicates per species for chlorophyll fluorescence measurements. The relationship between the various response variables and the main effects (Species and Subtypes) were fitted using a linear model in R (V. 3.0.2; R Foundation for statistical computing, Vienna, Australia). Analysis of variance, ANOVA (summarised in Table 5.2) was conducted for each fitted model. Multiple comparisons (shown in Tables 5.3 and 5.4) of subtype means were made using the Tukey’s Post Hoc test.

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5.3 Results

5.3.1 Photosynthetic and dry matter carbon isotope discrimination

The photosynthetic rates measured at current ambient CO2 and near-saturating light

(Asat) was highest in C. gayana species and lowest in Z. mays. Average Asat was highest for the PCK relative to NADP-ME and NAD-ME counterparts (Tables 5.2 and 5.3). Stomatal conductance (gs) measured at ambient CO2 was highest in P. virgatum, C. gayana and E. meyeriana and lowest in Z. mays. Average gs was higher for PCK and NAD-ME relative to NADP-ME species (Tables 5.2 and 5.3). A 2 common, positive linear relationship related Asat to gs (r = 0.85) in all the species regardless of their subtypes (Figure 5.1).

Leaf level photosynthetic water use efficiency (PWUE) was highest in Z. mays and B. insculpta and lowest in S. italica. On average, NAD-ME species had lower

PWUE relative to NADP-ME counterparts, and higher Ci/Ca relative to PCK counterparts (Tables 5.2 and 5.3).

13 12 Concurrent measurements of CO2/ CO2 discrimination and leaf gas exchange showed that photosynthetic discrimination (p) and estimated bundle sheath leakiness () varied significantly among the C4 species (Table 5.2); however, there was no consistent difference among the three C4 subtypes (Table 5.3). The relationship between photosynthetic discrimination (p) with Ci/Ca can be predicted according to the carbon discrimination model for C4 plants (Farquhar, 1983) using three values for bundle sheath leakiness () of 0.10, 0.15 and 0.25 (Figure 5.2).

Leaf dry matter carbon isotope composition (δ13C) was highest in Z. mays and lowest in P. miliaceum species. Average leaf δ13C was highest in NAD-ME, intermediate in

PCK and lowest in NADP-ME species (Tables 5.2 and 5.3). Photosynthetic p and 13 leaf dry matter δ C did not show a significant relationship among the C4 species (Figure 5.3).

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5.3.2 Confocal chlorophyll fluorescence

All the species used for microscopic imaging displayed wreath-like cell arrangement (Figure 5.4). In NAD-ME and PCK species, most fluorescence emanated from the inner bundle sheath cells (Figure 5.4A-D). In contrast, most fluorescence emanated from the outer mesophyll cells in the NADP-ME species (Figure 5.4E-F). To obtain quantitative estimates of the proportional allocation of chlorophyll fluorescence between mesophyll and bundle sheath cells, and between PSII and PSI activities, detailed emission spectra were collected (Figure 5.5) and analysed (Figure 5.6, Tables 5.2 and 5.4).

The ratio of total fluorescence intensity in the bundle sheath relative to mesophyll cells was lower in the NADP-ME than the NAD-ME and PCK species (Figure 5.6A, Tables 5.2 and 5.4).

In the bundle sheath cells, the PSII/PSI fluorescence ratio was lowest in C. ciliaris and highest in L. fusca and P. coloratum. On average, the PSII/PSI fluorescence ratio in the bundle sheath was lowest in NADP-ME and highest in NAD-ME species (Figure 5.6B, Tables 5.2 and 5.4).

In the mesophyll cells, the PSII/PSI fluorescence ratio was lowest in P. coloratum and L. fusca and highest C. ciliaris. On average, the PSII/PSI fluorescence ratio in the mesophyll was lowest in NAD-ME and highest in NADP-ME species (Figure 5.6B, Tables 5.2 and 5.4).

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Table 5. 1. List of C4 grasses used in the carbon isotope and confocal fluorescence studies.

Carbon isotope Confocal Species Subtype discrimination fluorescence Astrebla lappacea (Lindl.) Domin. NAD-ME X Astrebla pectinata (Lindl.) F. Muell. NAD-ME X Eleusine coracana Gaertn. NAD-ME X Enteropogon acicularis (Lindl.) Lazarides NAD-ME X Eragrostis curvula (Schrad.) Nees NAD-ME X Eragrostis lehmanniana Nees NAD-ME X Leptochloa fusca (L.) Kunth NAD-ME X X Panicum coloratum L. NAD-ME X X Panicum miliaceum L. NAD-ME X X Panicum virgatum L. NAD-ME X Chloris gayana Kunth. PCK X Eriochloa meyeriana Nees PCK X Heteropogon contortus (L) P. Beauv. Ex Roem. & Schult. PCK X Panicum maximum Jacq. PCK X X Urochloa panicoides P.Beauv. PCK X X Bothriochloa insculpta (Hochst. ex A. Rich.) A. Camus NADP-ME X Cenchrus ciliaris L. NADP-ME X X Digitaria eriantha Steud. NADP-ME X Echinochloa frumentaceae L NADP-ME X Echinochloa turneriana (Domin) Black. Fl. NADP-ME X Paspalum dilatatum Poir. NADP-ME X Setaria italic (L.) P. Beauvois NADP-ME X Sorghum bicolor (L.) Moench NADP-ME X X Zea mays L. NADP-ME X X

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Table 5. 2. Statistical summary.

Summary of statistical analysis using 2-way ANOVA for the effects of species and subtype on various collected parameters.

Parameter Species Subtype (p) (p) Leaf gas exchange -2 -1 Photosynthesis, Asat (µmol m s ) 0.000 0.000 -2 -1 Conductance, gs (mol m s ) 0.000 0.000 -1 Intercellular [CO2], Ci (µl L ) 0.000 0.000

Ci/Ca 0.000 0.000 -1 PWUE (µmol (mol H2O) ) 0.000 0.000 0.000 0.084 Photosynthetic Δp (‰) Leakiness,  0.000 0.062 Leaf C isotope composition, 13 (‰) 0.000 0.000

Chlorophyll fluorescence Total intensity of BS 0.015 0.002 Total intensity of MS 0.015 0.003 Total intensity BS/MS 0.101 0.011 Relative intensity of PSII/PSI BS 0.094 0.012 Relative intensity of PSII/PSI MS 0.015 0.003

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Table 5. 3. Leaf gas exchange and carbon isotope discrimination measurements.

Summary of leaf gas exchange and carbon isotope discrimination measurements for 22 C4 grass species. Values are means (n = 3-4) ± SE. Superscripts indicate the ranking of species within each column using a multiple-comparison, Tukey’s Post Hoc test. Values followed by the same letter are not significantly different at the 5% level.

Asat gs PWUE Ci Ci/Ca Photosynthetic Δp 13 -2 -1 -2 -1 -1 -1 Leakiness,  Leaf  (‰) Species Subtype (µmol m s ) (mol m s ) (µmol mol ) (µL ) (‰)

A. pectinata NAD-ME 31 ± 1 0.27 ± 0.01 118 ± 4 150 ± 7 0.42 ± 0.02 2.56 ± 0.23 0.21 ± 0.03 -14.86 ± 0.3

E. coracana NAD-ME 35 ± 2 0.26 ± 0.02 135 ± 5 133 ± 9 0.36 ± 0.02 3.61 ± 0.30 0.28 ± 0.03 -14.46 ± 0.3

E. acicularis NAD-ME 27 ± 1 0.24 ± 0.02 113 ± 4 155 ± 8 0.44 ± 0.02 3.10 ± 0.26 0.25 ± 0.02 -14.79 ± 0.2

E. curvula NAD-ME 30 ± 1 0.25 ± 0.02 122 ± 4 139 ± 8 0.39 ± 0.02 1.61 ± 0.26 0.11 ± 0.02 -13.32 ± 0.3

E. lehmanniana NAD-ME 32 ± 1 0.28 ± 0.02 113 ± 4 143 ± 8 0.41 ± 0.02 4.11 ± 0.26 0.34 ± 0.02 -13.39 ± 0.3

L. fusca NAD-ME 25 ± 2 0.20 ± 0.02 128 ± 5 131 ± 9 0.37 ± 0.02 2.24 ± 0.30 0.15 ± 0.03 -14.69 ± 0.2

P. coloratum NAD-ME 28 ± 2 0.28 ± 0.02 103 ± 5 161 ± 9 0.47 ± 0.02 3.09 ± 0.30 0.26 ± 0.03 -14.20 ± 0.3

P. miliaceum NAD-ME 23 ± 2 0.22 ± 0.02 104 ± 6 176 ± 11 0.49 ± 0.03 1.96 ± 0.37 0.18 ± 0.03 -15.50 ± 0.3

P. virgatum NAD-ME 36 ± 2 0.32 ± 0.02 112 ± 5 151 ± 9 0.43 ± 0.02 3.46 ± 0.30 0.28 ± 0.03 -13.98 ± 0.3

C. gayana PCK 43 ± 2 0.32 ± 0.02 133 ± 6 93 ± 11 0.28 ± 0.03 3.76 ± 0.37 0.29 ± 0.03 -14.24 ± 0.3

E. meyeriana PCK 37 ± 2 0.33 ± 0.02 115 ± 5 115 ± 9 0.36 ± 0.02 3.82 ± 0.30 0.31 ± 0.03 -13.72 ± 0.2

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P. maximum PCK 24 ± 2 0.19 ± 0.02 130 ± 6 132 ± 11 0.37 ± 0.03 3.80 ± 0.37 0.31 ± 0.03 -14.32 ± 0.3

U. panicoides PCK 33 ± 2 0.28 ± 0.02 120 ± 5 147 ± 9 0.41 ± 0.02 1.21 ± 0.30 0.08 ± 0.03 -14.43 ± 0.3

B. insculpta NADP-ME 29 ± 2 0.20 ± 0.02 141 ± 5 108 ± 9 0.31 ± 0.02 1.81 ± 0.30 0.06 ± 0.03 -13.45 ± 0.3

C. ciliaris NADP-ME 36 ± 2 0.27 ± 0.02 131 ± 5 148 ± 9 0.40 ± 0.02 2.22 ± 0.30 0.16 ± 0.03 -14.05 ± 0.2

D. eriantha NADP-ME 25 ± 2 0.19 ± 0.02 138 ± 5 113 ± 9 0.32 ± 0.02 2.83 ± 0.30 0.18 ± 0.03 -13.05 ± 0.3

E. frumentaceae NADP-ME 26 ± 1 0.21 ± 0.01 124 ± 4 136 ± 7 0.38 ± 0.02 2.58 ± 0.23 0.19 ± 0.02 -14.13 ± 0.3

E. turneriana NADP-ME 31 ± 2 0.29 ± 0.02 107 ± 5 155 ± 9 0.45 ± 0.02 3.48 ± 0.30 0.29 ± 0.03 -13.27 ± 0.3

P. dilatatum NADP-ME 29 ± 2 0.22 ± 0.02 132 ± 5 119 ± 9 0.34 ± 0.02 1.78 ± 0.30 0.09 ± 0.03 -13.60 ± 0.2

S. italica NADP-ME 25 ± 2 0.27 ± 0.02 94 ± 5 187 ± 9 0.53 ± 0.02 1.80 ± 0.30 0.18 ± 0.03 -13.97 ± 0.3

S. bicolor NADP-ME 29 ± 2 0.23 ± 0.02 129 ± 5 124 ± 9 0.36 ± 0.02 3.49 ± 0.30 0.27 ± 0.03 -13.21 ± 0.3

Z. mays NADP-ME 21 ± 1 0.15 ± 0.02 141 ± 4 114 ± 8 0.32 ± 0.02 3.55 ± 0.26 0.27 ± 0.02 -12.85 ± 0.2

Averages NAD-ME 30 ± 1 a 0.26 ± 0.01 ab 117 ± 2 a 148 ± 4 b 0.42 ± 0.01 b 2.88 ± 0.17 a 0.23 ± 0.02 a -14.35 ± 0.3 a

PCK 35 ± 2 b 0.28 ± 0.02 b 123 ± 4 ab 124 ± 7 a 0.36 ± 0.02 a 3.02 ± 0.30 a 0.24 ± 0.03 a -14.18 ± 0.2ab

NADP-ME 28 ± 1 a 0.22 ± 0.01 a 127 ± 3 b 133 ± 4 ab 0.38 ± 0.01 ab 2.64 ± 0.17 a 0.19 ± 0.02 a -13.51 ± 0.2 b

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Table 5. 4. Leaf confocal fluorescence measurements.

Summary of relative fluorescence measurements for 10 C4 grass species. Values are means (n = 3-4) ± SE. Superscripts indicate the ranking of species within each column using a multiple-comparison, Tukey’s Post Hoc test. Values followed by the same letter are not significantly different at the 5% level.

Species name Subtype Total intensity, Total intensity, Total intensity, Relative Relative Bundle sheath Mesophyll cells BSC/MC ratio intensity, intensity, cells PSII/PSI in the PSII/PSI in the Bundle sheath Mesophyll A. lappacea NAD-ME 0.70 ± 0.05 0.29 ± 0.07 2.42± 0.32 0.42 ± 0.03 0.57 ± 0.03 L. fusca NAD-ME 0.60 ± 0.07 0.40 ± 0.07 1.79± 0.39 0.48 ± 0.04 0.52 ± 0.04 P. coloratum NAD-ME 0.54 ± 0.09 0.46 ± 0.07 1.53± 0.39 0.51 ± 0.04 0.49 ± 0.04 P. virgatum NAD-ME 0.51 ± 0.07 0.49 ± 0.07 1.06± 0.39 0.42 ± 0.04 0.58 ± 0.04

H. contortus PCK 0.60 ± 0.05 0.40 ± 0.05 1.53± 0.32 0.44 ± 0.03 0.56 ± 0.03 P. maximum PCK 0.53 ± 0.07 0.47 ± 0.07 1.13± 0.39 0.44 ± 0.04 0.55 ± 0.04 U. panicoides PCK 0.62 ± 0.07 0.38 ± 0.07 1.60± 0.39 0.41 ± 0.04 0.59 ± 0.04

C. ciliaris NADP-ME 0.41 ± 0.07 0.59 ± 0.07 0.69± 0.39 0.26 ± 0.04 0.74 ± 0.04 S. bicolor NADP-ME 0.42 ± 0.07 0.58 ± 0.07 0.75± 0.39 0.36 ± 0.04 0.64 ± 0.04 Z. mays NADP-ME 0.18 ± 0.07 0.82 ± 0.07 0.23± 0.39 0.31 ± 0.04 0.69 ± 0.04 1.78± 0.22 b Averages NAD-ME 0.60 ± 0.05b 0.40 ± 0.05 a 0.45 ± 0.02 b 0.55 ± 0.02 a 1.34± 0.22 ab PCK 0.62 ± 0.05 b 0.38 ± 0.05 a 0.41 ± 0.03 ab 0.59 ± 0.03 ab 0.88± 0.22 a NADP-ME 0.43 ± 0.05 a 0.58 ± 0.05 b 0.36 ± 0.02 a 0.64 ± 0.02 b

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NADP-ME

) 1

- NAD-ME

s 40

PCK -2

molm



(

R2= 0.853 Photosynthesis 20 p < 0.001

0.15 0.20 0.25 0.30 0.35 Stomatal conductance (mol m-2 s-1)

Figure 5. 1. Photosynthetic rate as a function of stomatal conductance.

-2 -1 -1 o Leaf gas exchange was measured at high light (1800 µmol m s ), ambient CO2 (400 µl L ) and 26 C. The symbols represent species belonging to the NADP-ME (). NAD-ME (), and PCK (◭) subtypes. Each data point is the mean of three replicate measurements.

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) oo

( p 3   = 0.25

 = 0.15 1

NADP-ME Photosynthetic NAD-ME PCK  = 0.1 0

0.0 0.2 0.4 0.6 0.8

Intercellular/ambient CO , C /C 2 i a

Figure 5. 2. Photosynthetic carbon isotope discrimination, p as a function of intercellular to ambient

CO2 ratio, Ci/Ca.

The dashed line is the solution for the C4 discrimination model (Farquhar, 1983) using a leakiness () value of 0.1, 0.15 and 0.25. Leaf gas exchange was measured at high light (1800 µmol m-2 s-1), ambient -1 o CO2 (400 µl L ) and 26 C. The symbols represent species belonging to the NADP-ME (). NAD-ME (), and PCK (◭) subtypes. Each data point is the mean of three replicate measurements.

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5 NADP-ME NAD-ME

) PCK

oo 4

/ o

(

p  3

Photosynthetic 1

r2= 0.21 0 -16 -15 -14 -13 -12

 o Leaf dry matter  ( / ) oo

Figure 5. 3. Photosynthetic carbon isotope discrimination, p as a function of leaf dry matter carbon isotope composition, 13.

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Figure 5. 4. Images collected using a confocal laser scanning microscope.

Confocal laser scanning microscope images of P. coloratum (A), A. lappacea (B), P. maximum (C), U. panicoides (D), C. ciliaris (E) and Z. mays (F) showing the combined chlorophyll fluorescence of PSI, PSII and cell wall fluorescence. Fresh hand-cut leaf sections were mounted in water and imaged after excitation at 405 and 633 nm. Fluorescence emission from PSII at 659-692 nm (pseudo coloured green), PSI at 700-748 nm (pseudo coloured red), and cell wall at 480-550 nm (pseudo coloured cyan) were collected. The combined fluorescence of equal amounts of PSI and PSII results in yellow coloured fluorescence. When the contribution of PSII is low, the combined fluorescence becomes rich in red colour. Scale bar = 50 μm. Magnification X20. 150

1.0 Mesophyll cell Bundle sheath cell Back ground

0.8

0.6

0.4

Fluorescenceemission 0.2

0.0 650 660 670 680 690 700 710 720 730 740 750 Emission wavelength (nm)

Figure 5. 5. An example of emission spectra obtained for C. ciliaris (NADP-ME).

To quantify the intensities of chlorophyll fluorescence, emissions were collected in 10 nm bands at 5 nm intervals from 643 to 758 nm. The emission spectra for five sites selected from bundle sheath cells (black lines), emission spectra for five sites selected from mesophyll cells (grey lines) and an emission spectrum from the background (dashed line) were collected. Mean fluorescence intensities at the peak wavelengths of 688 and 718 nm were calculated from the spectral data, and they corresponded to fluorescence emissions for PSII and PSI, respectively.

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3.0 A

2.5

2.0

1.5

1.0

0.5

Totalfluorescence,BSC/MC ratio 0.0

PCK

L. fusca L. Z. mays Z.

NAD-ME

C. ciliaris C.

S. bicolor S.

NADP-ME

A. lappacea A.

P. virgatum virgatum P.

H. contortus H.

P. maximum P.

P. coloratum P. U. panicoides U.

PSII/ PSI Bundle sheath cell B 0.8 PSII/ PSI Mesophyll cell

0.6

0.4

0.2

Relativefluorescence intensity 0.0

PCK

L. fusca L.

Z. Z. mays

NAD-ME

C. ciliaris C.

S.bicolor

NADP-ME A.lappacea

P. virgatum

H. contortus H.

P.maximum

P.coloratum U. panicoides U.

Figure 5. 6. Average total and relative fluorescence.

(A) The ratio of total fluorescence in the BSC/MC and (B) the ratio of PSII/PSI relative fluorescence for the bundle sheath (open column) and mesophyll (filled columns) of ten C4 grass species belonging to the NAD-ME, PCK and NADP-ME biochemical subtypes. Values represent the means of three biological replicates ± SE and 5 pseudo-replicates for each species.

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5.4 Discussion

The carbon concentrating mechanism in C4 plants involves the close collaboration between the C3 and C4 photosynthetic cycles that operates across two photosynthetic cell types, leading to improved photosynthetic efficiency under high photorespiratory conditions. Three different CO2 decarboxylation pathways (NADP-ME, NAD-ME and PCK) operate in C4 plants and serve to increase [CO2] around Rubisco in the bundle sheath. The balance between carboxylase (Rubisco and PEPC) and decarboxylase activities regulates the efficiency of C4 photosynthesis.

In this study, using 22 C4 grass species, I demonstrated that leakiness () of CO2 from the bundle sheath as determined from measurements of photosynthetic 13C/12C isotope discrimination was not significantly different between the three C4 subtypes, and was unrelated to the leaf dry matter carbon isotope composition, δ13C. Furthermore, applying confocal laser scanning microscopy for 10 C4 species, I observed that the relative proportion of PSII/PSI fluorescence is higher in the mesophyll relative to the bundle sheath; and higher in the bundle sheath of NAD-ME relative to NADP-ME C4 grasses. The significance of these findings in relation to the published literature is discussed below.

5.4.1 Photosynthetic carbon isotope discrimination and the carbon isotope composition of dry matter

In C4 species, isotopic fractionation of carbon in the plant material is complex and reflects the fractionation of both carboxylation steps as well as their interconnectivity (Farquhar, 1983).

The initial hydration of CO2 to bicarbonate and subsequent PEP carboxylation has a combined fractionation of −5.7‰ at 25°C, and is dependent on temperature and on the amount of carbonic anhydrase present (Henderson et al., 1992, Cousins et al., 2008). The extent of Rubisco fractionation is dependent on leakiness, ϕ, defined as the fraction of CO2 released in the bundle sheath by the C4 cycle, which is not fixed by Rubisco. The value of ϕ determines the slope of the relationship between p and Ci/Ca (Figure 5.2). For the 22 C4 grasses, ϕ ranged between 0.06 and 0.31, and there was no significant difference between the subtypes (averages of 0.19, 0.24 and 0.23 for NADP-ME, PCK and NAD-ME species, 153

respectively). Previous research estimated ϕ to be about 0.2 under a range of environmental conditions in a number of C4 monocot and dicot species representing different decarboxylation types (Henderson et al., 1992, Cousins et al., 2008). Therefore, values of p and ϕ observed in the current study are in line with what have been reported in the literature.

It has been already established that plant dry matter in NAD-ME subtype species is significantly depleted in 13C compared with that of NADP-ME species (Hattersley, 1982, Ohsugi et al., 1988, Caemmerer et al., 2014). Similarly, in this study, leaf dry matter δ13C was lowest in NAD-ME, intermediate in PCK and highest in NADP-ME species. Differences 13 in ϕ have been postulated to cause the differences in leaf δ C between the C4 subtypes (Hattersley, 1982, Ohsugi et al., 1988, Buchmann et al., 1996a). In particular, it was argued that the presence of a suberin lamella in the bundle sheath cell wall of NADP-ME and PCK species would increase bundle sheath cell gaseous resistance, and hence reduce ϕ (Henderson et al., 1992, Cousins et al., 2008, Caemmerer et al., 2014). Theoretically, any potential increased fractionation by the suberin lamella in NADP-ME and PCK species may be matched by the longer path length for CO2 diffusion out of bundle sheath cells in NAD-ME species (mitochondria surrounding centripetal chloroplasts). Importantly, concurrent measurements of leaf gas exchange and carbon isotope discrimination in NAD-ME, PCK and

NADP-ME grass species did not reveal significant differences in their ϕ or Ci/Ca (Table 5.4).

Using 22 C4 grass species, the current study also showed no correlation between leaf dry 13 matter δ C and p (Figure 5.3). Similarly, Henderson et al., (1992) found no correlation between leaf dry matter δ13C and the short-term measurements of photosynthetic carbon 13 isotope discrimination, p in 11 C4 species. Therefore, variations in leaf dry matter δ C does not appear to be linked to the variation in photosynthetic carbon isotope discrimination (Henderson et al., 1992, Cousins et al., 2008, Caemmerer et al., 2014).

Post-photosynthetic fractionations, the availability of intercellular CO2, temperature and light intensity are suggested to be factors responsible for the lack of a connection between leaf dry 13 matter C and ϕ or Ci/Ca in C4 leaves (Cousins et al., 2008, Caemmerer et al., 2014). Alternatively, differences in the δ13C of photo-assimilates exported out of source leaves may 13 contribute to the δ C differences between the C4 subtypes. In addition, differences in the

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rates and types of respired substrates between the C4 subtypes may also contribute to their different leaf δ13C (Caemmerer et al., 2014).

5.4.2 Assessing photosystem I and II distribution using confocal laser scanning microscopy

All the species used for the confocal microscopy imaging displayed a wreath-like cell arrangement (Figure 5.4), termed the Kranz anatomy. Kranz anatomy consists of an outer cell layer that forms the mesophyll cells. Commonly, the vascular bundle is surrounded by a layer of parenchyma cells. This cell layer is integrated into the outer layer of the Kranz anatomy, and is referred to as the bundle sheath. Bundle sheath cells contain Rubisco and many of the Calvin cycle enzymes (Dengler and Nelson, 1999, Sage, 2004).

To quantify the distribution of PSI and PSII activities in the various cell types of C4 species with different biochemical subtypes, chlorophyll fluorescence emission was collected at the wavelengths of 688 nm (PSII) and 718 nm (PSI). Using chlorophyll fluorescence as a proxy for estimating relative PSI and PSII activities is a well-established technique that has been in a number of studies (Edwards & Walker 1983; Hatch 1987; Pfündel et al. 1996; Ghannoum et al., 2005).

In line with previous findings, in this study, NADP-ME species had the lowest total (PSI + PSII) fluorescence intensity in the bundle sheath cells and highest total (PSI + PSII) fluorescence intensity in the mesophyll cells relative to both NAD-ME and PCK species. This study showed for the time, that the total chlorophyll fluorescence distribution between mesophyll and bundle sheath cells of PCK species is similar to that in NAD-ME rather than NADP-ME counterparts (Figure 5.6A, Table 5.4).

Moreover, the current study showed that NADP-ME species had lower PSII/PSI fluorescence ratio in the bundle sheath cells and higher PSII/PSI fluorescence ratio in the mesophyll cells relative to NAD-ME species, while PCK species had intermediate PSII/PSI fluorescence ratios in both cell types (Figure 5.6B, Table 5.4). Previous research has established that NADP-ME species exhibit lower PSII/PSI activity in the bundle sheath cells than in the mesophyll cells (Edwards and Walker, 1983, Hatch, 1987, Pfündel and Neubohn, 1999). 155

Pfündel et al. 1999 have also shown that a small group of NADP-ME C4 species show lower PSII/PSI ratios in the mesophyll than in the bundle sheath cells. Using similar confocal chlorophyll fluorescence analysis, Ghannoum et al., (2005) showed that two NADP-ME grasses contained similar PSI activity between the bundle sheath and mesophyll cells. Taken together, these results suggest that NADP-ME C4 plants increase PSII/PSI ratio in mesophyll cells is primarily by concentrating PSII in mesophyll cells.

Deficiency of PSII activity in the bundle sheath cells of NADP-ME species is considered as a mechanism to prevent the accumulation of high [O2] in their bundle sheath cells (Woo et al.,

1970, Edwards et al., 1976). In turn, this would favour the CO2/O2 concentration ratio in the bundle sheath, and hence reduce the potential for wasteful photorespiration in this subtype. At the evolutionary level, this has led to NADP-ME species evolving faster Rubisco enzyme, thus reducing the need for locking large amounts of N in Rubisco, which will in turn increase the nitrogen use efficiency of NADP-ME relative to NAD-ME species (Ghannoum et al., 2005).

The ratio of PSII/PSI is indicative of the relative level of linear to cylic electron transport. Low PSII/PSI suggests high potential for cyclic electron transport and low potential for linear electron transport and NADP reduction (Furbank et al., 1990). In addition, the deficiency of PSII activity in the bundle sheath implies that a large fraction of phosphoglycerate (PGA), the first product of RuBP carboxylation, must be shuttled to mesophyll cells for reduction. With each turn of Rubisco carboxylation in the bundle sheath chloroplasts, two PGA molecules are formed. With each turn of the C4 cycle, one NADPH is transferred from mesophyll to bundle sheath chloroplasts via malate transport and its subsequent decarboxylation. This NADPH may be used to reduce one molecule of PGA. The other PGA is reduced by the mesophyll chloroplasts through a shuttle of PGA and triose phosphate between the two cell types. In this case, the reactions of the Calvin, excluding Rubisco which is restricted to the bundle sheath, would operate at equal rates in both cell types. Thus, mesophyll cells are the primary site of light-dependent generation of reductive power (NADPH) in NADP-ME species (Hatch, 1987, Edwards and Andreo, 1992).

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In contrast, NAD-ME and PCK species had higher BSC/MC ratio of total fluorescence, and their bundle sheath cells had higher PSII/PSI relative fluorescence compared to NADP-ME counterparts. Hence, the former types possess higher proportion of reductive power in the bundle sheath cells relative to NADP-ME species. Thus, NAD-ME and PCK species may reduce more than half of their PGA in the bundle sheath chloroplasts. It is worth noting that in the PCK subtype, PEP is the product of C4 acid (OAA) decarboxylation in the bundle sheath. Presumably, this PEP is returned to the mesophyll for use by PEPC, thus saving some ATP required for normal PEP production by pyruvate phosphate dikinase in the mesophyll (Hatch, 1987). Reduced requirement for ATP in the mesophyll cells of PCK species may suggest lower requirement for PSI, i.e., lower PSI/PSII or higher PSII/PSI in the mesophyll relative to other subtypes. However, this was not observed in the current study. A number of factors may contribute to this observation. In particular, the need to enrich the mesophyll with

PSII activity (hence, reduce O2 productin) relative to the bundle sheath cells may apply for all three subtypes, leading to relatively high PSII/PSI ratios in the mesophyll, as was observed in this study. The functionality of PSII centres (i.e., their ability to evolve O2) as estimated from chlorophyll fluorescence in this study remains to be elucidated (Ghannoum et al., 2005).

5.5 Conclusions

Using 22 C4 grass species, data presented in this study demonstrated that bundle sheath leakiness of CO2 was not significantly different between the three C4 subtypes. In addition, photosynthetic carbon isotope discrimination, p was unrelated to the leaf dry matter carbon isotope composition, δ13C. The application of a purpose-built, chlorophyll fluorescence technique using 10 C4 grass species revealed that the relative proportion of PSII/PSI fluorescence is higher in the mesophyll relative to the bundle sheath; and higher in the bundle sheath of NAD-ME relative to NADP-ME C4 grasses.

* * * * *

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CHAPTER 6

SYNTHESIS AND GENERAL DISCUSSION

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6.1 Project aims

C4 photosynthesis is an anatomically and biochemically complex and diverse photosynthetic pathway which has evolved from the ancestral C3 photosynthesis. The phylogenetic framework for the grass family showed that C3 to C4 evolutionary transitions have been irregular, with 22–24 inferred origins of the C4 pathway. C4 plants are grouped into three biochemical subtypes, which are named after the major C4 acid decarboxylase in the bundle sheath cells: NAD malic enzyme (NAD-ME), NADP-ME and PEP carboxykinase (PCK).

The three C4 subtypes are closely associated with particular taxa, and some taxa have multiple evolutionary origins. In addition, various physiological and ecophysiological traits have been associated with the biochemical subtype or evolutionary lineage of the C4 grasses.

Most physiological studies were undertaken using a small number of C4 species under current ambient [CO2], which does not reflect the CO2 environment under which C4 grasses have evolved. Therefore, the overall aim of this study was to compare the physiological efficiencies of diverse C4 grass species under conditions that promote high rates of photorespiration, the physiological pressure that led to the evolution of the CO2 concentrating mechanism (CCM) in land plants.

C4 photosynthesis evolved and diversified under limiting CO2 environments from their ancestral C3 plants via a series of anatomical and biochemical modifications. Therefore, it is important to understand the influence of the biochemical subtype and evolutionary origin in determining the physiological performance of a large number of C4 grasses under limiting

CO2 supply. The first experiment was designed to investigate the responses of photosynthetic

WUE and NUE, as well as the activity of the photosynthetic carboxylase enzymes in 24 C4 grasses belonging to three biochemical subtypes and six major evolutionary origins under -1 -1 current ambient (400 μl L ) and inter-glacial (280 μl L ) [CO2] (Chapter 2). The main aim of this study was to investigate the influence of the biochemical subtype and evolutionary origin in grouping physiological traits (particularly, photosynthetic NUE and WUE) in a large number of C4 grasses, and to determine how limiting CO2 supply or phylogenetic relatedness among the C4 species influence these relations.

Geological fluctuations in atmospheric [CO2] have shaped the Earth’s vegetation, yet we know relatively little about the physiological responses of C3 and C4 plants to the [CO2] 159

levels that dominated during the recent glaciations. The second experiment was designed to compare the photosynthetic physiology and biochemistry in closely-related grass species belonging to different pathways of photosynthesis (C3, C3-C4 and C4) and subtypes of C4 -1 photosynthesis (NAD-ME, NADP-ME and PCK) under glacial [CO2] (180 µl L ) relative to current ambient (400 µl L-1) (Chapter 3). The main aim of this study was to investigate whether the physiological differences observed between the C3, C3-C4 and C4 photosynthetic types hold when compared under the glacial [CO2] that prevailed during the evolution of the

C4 pathway.

Atmospheric aridity (high VPD) is one of the major environmental factors responsible for widespread C4 evolution. Atmospheric aridity may have selected for traits that enhanced the carbon balance of plants. Hence, high VPD may have been one of the major stimuli that enabled C4 evolutionary trends to commence in many taxa, leading to improved chances of survival under dry environments. It is therefore important to gain an appreciation of the VPD responses within the broader C4 plant community. Experiment 3 investigated the responses of leaf and plant carbon-water exchanges to short- and long-term changes in VPD for 20 C4 grasses belonging to three biochemical subtypes and six major evolutionary origins grown under low (0.7 kPa) and high (2.0 kPa) VPD (Chapter 4). This study aimed to investigate the influence of the biochemical subtype and evolutionary origin on the grouping of physiological traits associated with WUE in a large number of C4 grasses, and to determine how high VPD influence these relations.

Previous studies have measured carbon isotope discrimination and chlorophyll fluorescence in some unrelated C4 species in order to estimate the efficiency of the C4 pathway. These studies used a narrow range of C4 species and did not consider the full biochemical diversity of the C4 pathways. In spite of the significant progress made in recent years, no studies have screened large numbers of C4 grasses in order to evaluate the degree of species and subtypes variability in carbon isotope discrimination. Experiment 4 consisted of two parts. In the first part, 16 C4 grass species were grown in ambient air to estimate bundle sheath leakiness using photosynthetic carbon isotope discrimination measured by tuneable diode laser (TDL) (Chapter 5). The main aim of this study was to evaluate the degree of species and subtype 13 variability in leaf δ C and photosynthetic  in a relatively large number of C4 grasses belonging to the three biochemical subtypes. In the second part of this study, 10 C4 grasses 160

were grown in ambient air to estimate the relative distribution of photosystems I and II (PSI and PSII) in mesophyll and bundle sheath tissues using confocal microscopy (Chapter 5). This study aimed at evaluating the degree of species and subtype variability in the distribution of chlorophyll fluorescence between the mesophyll and bundle sheath cells in a number of C4 grasses belonging to the NADP-ME, NAD-ME and PCK biochemical subtypes.

6.2 Photosynthetic physiology of diverse C4 grasses at inter-glacial [CO2]

C4 photosynthesis has evolved under limiting CO2 supply from their ancestral C3 plants via a series of anatomical and biochemical modifications (Christin et al., 2010, Hatch, 1987).

However, there are no physiological studies using a large number of C4 grasses belonging to the main biochemical subtypes and major evolutionary origins grown under limiting CO2 supply. This study was conducted to fill this knowledge gap by investigating the responses of photosynthetic WUE and NUE, as well as the activity of the photosynthetic carboxylase enzymes, in 24 different C4 grasses belonging to three biochemical subtypes (NADP-ME, NAD-ME and PCK) and six major evolutionary origins: Paspalum (NADP-ME), Andropogoneae (NADP-ME), Echinochloa (NADP-ME), Digitaria (NADP-ME), Paniceae (NADP-ME, NAD-ME, PCK) and Chloridoideae (NAD-ME, PCK) grown under ambient -1 -1 (400 μl L ) and inter-glacial (280 μl L ) [CO2].

This study revealed that higher leaf [N] and LMA were the two key traits that distinguished the Chloridoideae (NAD-ME) grasses from all other C4 groups. Higher Rubisco and PEPC activities distinguished NADP-ME and PCK grasses regardless of their evolutionary origin. The statistical analysis also revealed that variation in leaf [N] was more dependent on the subtype rather than the evolutionary origin of the C4 species. Hence, results obtained in this study supported earlier findings that variation in PNUE among the C4 grasses was related to the trade-off between Rubisco catalysis and the investment in leaf N. Therefore, NADP-ME grasses achieve similar photosynthetic rates with a lower investment in leaf N and Rubisco by virtue of having faster Rubisco enzyme relative to NAD-ME counterparts (Ueno et al., 2005).

With increasing annual rainfall, the abundance of NADP-ME and PCK species increases, while NAD-ME or Chloridoideae species are prevalent in low rainfall areas (Hattersley, 1992). This suggests that NAD-ME/Chloridoideae grasses are better adapted to dry habitats. 161

In this study, the Chloridoideae/NAD-ME species tended to have lower gs and higher PWUE under inter-glacial but not under ambient [CO2]; and this was accompanied with a lower stomatal sensitivity to [CO2] relative to the other C4 groups. Moreover, variations in gs and PWUE were better explained by the evolutionary origin rather than the biochemical subtype, confirming that these traits are related to the grass lineage or represent adaptation to the species’ habitat rather than the underlying biochemistry of the C4 pathways.

There is limited information about stomatal responses of diverse C4 species to past atmospheric [CO2] and their interactions with environmental stresses (Ward et al., 1999, Maherali et al., 2002, Reid et al., 2003). Among all the origins, the Chloridoideae species had the smallest sensitivity of gs to reduced [CO2]. Along with smaller stomatal pores observed in other studies (Liu et al., 2012), NAD-ME species have longer inter-veinal distances (hence, lower hydraulic conductance) than species of the other two subtypes (Ohsugi and Murata,

1986, Dengler et al., 1994). By maintaining low gs (high PWUE) to avoid hydraulic failure at low [CO2], the Chloridoideae/NAD-ME species, which predominate at lower rainfall, may represent an adaptation to dry habitats. On the other hand, NADP-ME and PCK species can open their stomata at low [CO2] in order to maintain carbon gain without risking hydraulic failure but at the expense of reduced PWUE given they are distributed in wetter environments (Evans, 1983, Osborne and Sack, 2012); however, the opposite was observed when soil water was limiting under current ambient [CO2]. NAD-ME species had superior plant WUE relative to NADP-ME counterparts (Ghannoum et al., 2002). Consequently, these observations demonstrate that C4 grasses use different adaptation strategies depending on whether atmospheric [CO2] or soil water is limiting. This study demonstrated that the evolutionary and biochemical diversity among C4 grasses is aligned with discernible leaf physiology traits under low and ambient atmospheric CO2. The extent to which these traits represent ecological adaptations requires further investigation.

6.3 Photosynthesis of C3, C3-C4 and C4 grasses at glacial CO2

The primary driver for the evolution of C4 photosynthetic pathway from their ancestral C3 photosynthetic pathway is considered to be the drop in atmospheric [CO2] 30 Mya (Ehleringer et al., 1997, Christin et al., 2008a, Sage et al., 2012). This study was carried out 162

to compare the photosynthetic physiology and biochemistry in closely-related grass species belonging to different pathways of photosynthesis (C3, C3-C4 and C4) and subtypes of C4 -1 photosynthesis (NAD-ME, NADP-ME and PCK) grown under glacial [CO2] (180 µl L ) and ambient (400 µl L-1).

The occurrence of a CCM in C4 leaves entails that the C4 pathway is less limited by CO2 supply (Hatch, 1987, Gerhart and Ward, 2010). At glacial CO2, C4 species maintained higher

Asat relative to C3-C4 and C3 species. Glacial CO2 caused a smaller reduction of Asat and a greater increase of gs in C4 relative to C3 and C3-C4 species. Due to higher Asat, C4 species maintained a greater PWUE relative to C3-C4 and C3 species at glacial CO2.

Despite the biochemical and anatomical diversity amongst the three C4 subtypes, there was no difference between the subtypes in their Asat or their sensitivity to glacial [CO2]. This observation suggested that there are no apparent variations in the efficiency of the CCM operating in the three C4 subtypes. Within the C4 species, NAD-ME and PCK grasses had the highest PWUE and PNUE respectively, relative to NADP-ME subtype. Under glacial [CO2],

NAD-ME species had the highest PWUE due to their lower gs, and this lower gs was less affected by [CO2] relative to NADP-ME and PCK subtypes. This observation is consistent with the idea that NAD-ME species are better suited for arid habitats relative to NADP-ME and PCK species (Hattersley, 1992, Taub, 2000, Ghannoum et al., 2002, Carmo-Silva et al.,

2007, Carmo-Silva et al., 2009). Similar to gs, biomass accumulation of NAD-ME species was less affected by glacial [CO2] relative to NADP-ME and PCK grasses. This may be related to their smaller biomass accumulation rate relative to the other, larger C4 species.

Glacial CO2 up-regulated Rubisco and PEPC activities in concert for several C4 grasses, while NADP-ME and PEP-CK activities were unchanged, reflecting the high control exerted by the carboxylases relative to the decarboxylases on the efficiency of C4 metabolism.

C4 species maintained higher PWUE relative to C3-C4 and C3 species as a result of their high

Asat. Furthermore, relative to the C3 pathway the photorespiratory pump of the C3-C4 species maintained greater water use efficiency under both growth [CO2]. Under glacial [CO2], higher Asat and lower leaf [N] of C4 species resulted in high PNUE relative to the C3 and C3-

C4 species. The C3-C4 species operated with higher leaf [N] and Rubisco-N. Therefore, they had no PNUE advantage over the C3 species. C3 plants acclimated to glacial [CO2] by

163

doubling Rubisco activity. However, Rubisco activity was unchanged in C3-C4 plants, probably due to its high leaf [N] and Rubisco contents, as a result of high N costs of associated with operating two Calvin cycles (Monson, 1989, Monson and Rawsthorne, 2004).

Consequently, under glacial CO2, high resource use efficiency offers a key evolutionary advantage for the transition from C3 to C4 photosynthesis under high photorespiratory environments.

6.4 Photosynthetic physiology of diverse C4 grasses at high VPD

Widespread C4 evolution under atmospheric and soil aridity may have selected for traits that enhanced the carbon balance of plants. The effects of soil aridity on the carbon balance and resource use efficiency of C4 grasses have previously been examined (Ghannoum et al.,

2002). High VPD can be considered as one of the major stimuli that enabled C4 evolutionary trends to commence in many taxa, leading to improved chances of survival under dry environments. It is therefore important to gain an appreciation of the VPD responses within the broader C4 plant community. This study investigated leaf and plant physiological responses of 20 C4 grasses, belonging to three biochemical subtypes (NAD-ME, PCK and NADP-ME) and six dominant evolutionary origins [Andropogoneae (NADP-ME), Digitaria (NADP-ME), Echinochloa (NADP-ME), Paspalum (NADP-ME), Chloridoideae (NAD-ME, PCK) and Paniceae (NADP-ME, NAD-ME and PCK)], grown under low (0.7 kPa) and high (2.0 kPa) atmospheric water vapour pressure deficit (VPD), which corresponded to 80% and 40% relative humidity (RH), respectively.

Stomatal conductance was reduced under high VPDL across all C4 species, evolutionary origins and biochemical subtypes. Importantly, this study showed that C4 grasses with the lowest gs at low VPDL (which corresponds to maximal gs measured in this study) had the lowest sensitivity in response to increasing VPDL. This relationship was strong and common for all C4 species and at both growth VPD treatments. Stomatal sensitivity to VPDL has been proportional to absolute gs in grasses belonging to both C3 and C4 pathways (Morison and

Gifford, 1983). Taken together, these studies indicated that the stomatal response to VPDL in grasses is independent of the underlying photosynthetic metabolism, given that stomatal

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sensitivity to VPDL was similar among grasses with different photosynthetic pathways and biochemical subtypes. It may be concluded that low stomatal sensitivity and photosynthetic insensitivity to partial stomatal closure caused by VPDL may enable C4 plants to maintain high CO2 uptake at high VPD (Kawamitsu et al., 1993, Maherali et al., 2003, Osborne and Sack, 2012).

Increased assimilation rates or decreased stomatal conductance results in increased PWUE.

Under high VPD, PWUE improved in most C4 species mainly due to decreased gs. Overall,

C4 grasses can be grouped into four categories. The first group (Echinochloa and Paspalum) showed high stomatal and low photosynthetic negative responses to increased VPD, leading to the greatest gains in PWUE. The second group (Chloridoideae and Paniceae) showed high negative stomatal and photosynthetic responses to increased VPD, leading to moderate gains in PWUE. The third group (Andropogoneae) showed small stomatal and photosynthetic responses to high VPD leading to minimal gains in PWUE. The fourth group (Digitaria) showed low stomatal and high photosynthetic negative responses to increased VPD, leading to the losses in PWUE.

6.5 Variation in leaf carbon isotope discrimination and photosystem

distribution among C4 grasses with different subtypes.

Bundle sheath leakiness (ϕ), defined as the fraction of CO2 released in the bundle sheath by the C4 cycle, which is not fixed by Rubisco is estimated to be about 0.2 (Henderson et al., 1992, Cousins et al., 2008). In line with this observation, current study observed ϕ ranged between 0.06 and 0.31. Plant dry matter in NAD-ME species is significantly depleted in 13C compared with that of NADP-ME species (Hattersley, 1982, Ohsugi et al., 1988, Caemmerer et al., 2014). Similarly, in this study, leaf dry matter δ13C was lowest in NAD-ME, intermediate in PCK and highest in NADP-ME species. Previous studied have assumed that the variations in ϕ between the C4 subtypes have been responsible for the variation in leaf dry matter δ13C (Hattersley, 1982, Ohsugi et al., 1988, Buchmann et al., 1996a). Suberin lamella present in the bundle sheath cell wall of NADP-ME and PCK subtype species was argued to decrease ϕ as a result of bundle sheath cell gaseous resistance (Henderson et al., 1992,

Cousins et al., 2008, Caemmerer et al., 2014). However, ϕ or Ci/Ca values were not 165

significantly different between the three C4 subtypes in this study. Furthermore, there was no correlation between leaf dry matter δ13C and photosynthetic carbon isotope discrimination 13 (p). Therefore, variations in δ C does not appear to be linked to the variation in p (Henderson et al., 1992, Cousins et al., 2008, Caemmerer et al., 2014). Post-photosynthetic fractionations, the availability of intercellular CO2, temperature and light intensity, differences in the δ13C of photo-assimilates exported out of source leaves and differences in the rates and types of respired substrates may be responsible for the lack of a connection 13 between leaf dry matter C and ϕ or Ci/Ca in C4 leaves (Cousins et al., 2008, Caemmerer et al., 2014).

Chlorophyll fluorescence emission is a well-established technique used as a proxy for estimating relative PSI and PSII activities (Edwards & Walker 1983; Hatch 1987; Pfündel et al. 1996; Ghannoum et al., 2005). It has been previously observed that NADP-ME C4 plants increase PSII/PSI ratio in mesophyll cells mainly by concentrating PSII in mesophyll cells (Edwards and Walker, 1983; Hatch, 1987; Pfündel and Neubohn, 1999; Ghannoum et al., 2005). Furthermore, low level of PSII activity in the bundle sheath cells of NADP-ME species is considered to be a mechanism to prevent the accumulation of high [O2] in their bundle sheath cells (Woo et al., 1970, Edwards et al., 1976). In this study the chlorophyll fluorescence emission provided the lowest total (PSI + PSII) fluorescence intensity in the bundle sheath cells and highest total (PSI + PSII) fluorescence intensity in the mesophyll cells in NADP-ME species relative to NAD-ME and PCK species. In addition, NADP-ME species had lower PSII/PSI fluorescence ratio in the bundle sheath cells and higher PSII/PSI fluorescence ratio in the mesophyll cells relative to NAD-ME species, while PCK species had intermediate PSII/PSI fluorescence ratios in both cell types. Low PSII/PSI suggests high potential for cyclic electron transport and low potential for linear electron transport and NADP reduction (Furbank et al., 1990). Furthermore, the total fluorescence ratio of BSC/MC was highest in NAD-ME and PCK species, and their relative fluorescence of bundle sheath cells PSII/PSI was higher compared to NADP-ME species. However, the functionality of PSII centres as estimated from chlorophyll fluorescence measurements remains to be clarified (Ghannoum et al., 2005).

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6.6 Overall conclusions

This thesis investigated the physiological efficiencies of diverse C4 grass species, belonging to three biochemical subtypes (NAD-ME, PCK and NADP-ME) and six dominant evolutionary origins [Andropogoneae (NADP-ME), Digitaria (NADP-ME), Echinochloa (NADP-ME), Paspalum (NADP-ME), Chloridoideae (NAD-ME, PCK) and Paniceae

(NADP-ME, NAD-ME and PCK)] under low atmospheric CO2 and high atmospheric vapour pressure deficit. These environmental conditions, which promote photorespiration, are considered the key selection pressures that led to the evolution of the CO2 concentrating mechanism (CCM) in land plants.

Overall, my research expands current knowledge regarding the physiological significance of the complex C4 photosynthetic pathway with respect to its phylogeny, evolutionary diversity and biochemical subtypes. Resource use efficiency was used as a tool to probe the optimization of the

C4 pathway and its adaptive, physiological fitness.

The main take-home messages arising from the above-outlined chapters can be summarised as follows:

1. The operation of a CCM ensured that PWUE and PNUE remained higher in C4

species relative to C3 and C3-C4 species under glacial CO2. Results obtained in this study support the notion that Rubisco and PEPC, rather than the decarboxylases,

modulate the response to glacial [CO2] for C4 grasses with different biochemical subtypes. Consequently, high resource use efficiency offered a key evolutionary

advantage for the transition from C3 to C4 photosynthesis in water and nutrient limited environments.

2. Under high photorespiratory environments (inter-glacial [CO2], high VPD), variations

in PNUE observed amongst the diverse C4 grasses were most likely related to the C4 biochemical subtype (NADP-ME/PCK: highest and NAD-ME: lowest PNUE) while

variations in PWUE most likely reflected the evolutionary lineage of the C4 species.

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3. Stomatal sensitivity of C4 grasses differed under atmospheric [CO2] and VPD. In

response to inter-glacial [CO2], stomatal sensitivity was related to leaf anatomy, particularly inter-veinal distance, a trait that has bearing on hydraulic conductivity. Hence, species with longer inter-veinal distances (lower potential hydraulic

conductivity) showed the lowest stomatal sensitivity to low [CO2].

4. In response to increasing VPD, stomatal sensitivity was correlated with maximal

stomatal conductance. C4 grasses with the lowest gs at low VPD (i.e., lowest maximal

gs) showed the lowest stomatal closure in response to increasing VPD. This relationship was strong and common for all species at both growth VPD treatments. Therefore, the stomatal response to VPD in grasses was independent of the underlying

photosynthetic metabolism. In addition, these observations demonstrated that C4

grasses use different adaptive strategies depending on whether CO2 supply is directly

(low [CO2]) or indirectly (high VPD) limiting.

5. When comparing the efficiency of the C4 biochemical subtypes, this study

demonstrated that bundle sheath leakiness of CO2 was not significantly different

between the three C4 subtypes and photosynthetic carbon isotope discrimination was unrelated to the leaf dry matter carbon isotope composition.

6. Analysis of chlorophyll fluorescence emission spectra revealed that the relative proportion of PSII/PSI fluorescence is higher in the mesophyll relative to the bundle

sheath; and higher in the bundle sheath of NAD-ME relative to NADP-ME C4 grasses.

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6.7 Overall synthesis

Consistency of data and trends across the PhD project

The PhD thesis was undertaken as a series of separate, stand-alone experiments that were carried out using various grass species grown in different growth cabinets and glasshouse chambers, and executed at different times of the year. Therefore, it was not possible to compare data from various experiments because these experiments (i) did not use the same growth environments, (ii) the species collection differed between the experiments and (iii) were executed at different times.

Nevertheless, the experiments in Chapters 2 and 4 used similar grasses, with a few exceptions, that were grown in the same glasshouse facility in consecutive years. To examine the consistency of the data collected in the various experiments of this PhD project, I compared data for four key parameters (plant dry mass, photosynthesis, and photosynthetic water and nitrogen use efficiency) -1 of the various C4 groups grown under control conditions of ambient CO2 (400 μl L ) and low VPD (0.7 kPa).

Data presented in Figure 6.1 clearly demonstrate that the ranking of the C4 groups was exactly the same across the two experiments for plant dry mass (Figure 6.1A). For the three other parameters, there were some variations in the ranking, but the overall separation between the low and high performers was generally maintained across the two experiments.

For photosynthetic rates, The Paniceae and Chloridoideae groups had the highest rates in both experiments, while the Andropogoneae, Papspalum and Digitaria had the lowest rates. Echinochloa was the only group that showed inconsistency due to the employment of an additional species in Chapter 2 (Figure 6.1B). The C4 groups had the same overall ranking of PWUE and PNUE across the two experiments except for Andropogoneae (Figure 6.1C-D).

Consequently, Figure 6.1 demonstrates that there was a large degree of reproducibility of the data generated during this PhD project. Given the factors explained above, the overall synthesis of the experimental data was undertaken using proper statistical tools as discussed in the following section.

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30 50 A Low VPD B Low VPD Ambient CO2 Ambient CO2

) 40

-1

)

s -1 20 -2

mol m mol



Digitaria

Digitaria Paniceae

10 Paniceae

Paspalum

Plant dryPlantmass plant (g

Paspalum

Photosynthesis(

Echinochloa

Chloridoideae

Chloridoideae Andropogoneae 0 0 Andropogoneae

200 1.0 C Low VPD D Low VPD 400ppm 400ppm 0.8

150

)

-1

-1 s

-1 0.6

100

mol molmol  0.4

PWUE( 50

PNUE (mol molPNUE (mol

Digitaria Digitaria Paniceae

0.2 Paniceae

Paspalum Paspalum

Echinochloa Echinochloa

Chloridoideae Chloridoideae Andropogoneae 0 0.0 Andropogoneae

Figure 6. 1. Comparison of four key parameters measured in Chapters 2 and 4

Plant dry mass (A), photosynthetic rate (B), photosynthetic water use efficiency (C) and photosynthetic nitrogen use efficiency (D) of the main C4 groups grown under control conditions. In Chapter 2 -1 (triangles), parameters were used for plants grown and measured at ambient CO2 (400 μl L ). In Chapter 4 (clear columns), parameters were used for plants grown and measured at low VPD (0.7 kPa).

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Overall significance of data and trends across the PhD project

In order to determine the effects of the evolutionary origins and biochemical subtypes throughout the PhD project, a new dataset was compiled for grass species grown in similar growth environments. This was done by combining commonly measured leaf traits at ambient [CO2] (400 μl L-1) and low VPD (0.7 kPa) in chapters 2, 4 and 5. Analysed parameters included growth, resource use and gas exchange measurements. The lme model was determined using the compiled raw data in order to test how various parameters were influenced by the biochemical subtype or the evolutionary origin (Tables 6.1 and 6.2). lme analysis. Overall, the lme model including the response variables of evolutionary origin best explained variation in stomatal conductance (gs) and photosynthetic water use efficiency (PWUE), while the model that included the biochemical subtype best explained variations in leaf mass per unit area (LMA), leaf N concentration per unit area (Leaf [N]area), and to a lesser extent, variations in photosynthetic nitrogen use efficiency (PNUE). Otherwise, photosynthetic rate (Asat), intercellular to ambient CO2 ratio (Ci/Ca), leaf N concentration per unit dry mass (Leaf [N]mass), plant dry mass (DM), plant water use efficiency (WUE) and plant nitrogen use efficiency (NUE) were not well predicted by any of the lme combinations (Table 6.1).

RDA analysis. In order to examine the overall associations of the measured physiological parameters, a redundancy analysis (RDA) was undertaken (Figure 6.2). Accordingly, it was revealed that PWUE was clearly associated with the Chloridoideade lineage (lower-right quadrant), while photosynthetic rate, leaf transpiration rate, leaf [N]area and LMA were responsible for segregating the NAD-ME species (top-left quadrant). The NADP-ME origins (Andropogoneae, Paspalum, Digitaria, and Echinochloa) clustered together with the PCK/Paniceae species (top and lower-right quadrant). This clustering was mostly brought about by the parameters [N]mass, plant WUE, plant DM, PNUE, Ci/Ca and stomatal conductance.

Most of the past C4 work conducted under current ambient [CO2] was undertaken without considering the phylogenetic diversity among the NADP-ME lineages (Grass Phylogeny Working Group, 2012). However these observations revealed that NADP-ME grasses possess

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superior PNUE relative to NAD-ME counterparts (Bowman, 1991, Taub and Lerdau, 2000, Ghannoum et al., 2005) and these differences were due to lower leaf [N] and higher Rubisco c turnover rate (k cat) in NADP-ME relative to NAD-ME grasses (Ghannoum et al., 2005).

The current compiled data set used NADP-ME grasses from five different evolutionary origins in addition to NAD-ME and PCK grasses grown [CO2]. The lme analysis revealed that variations in leaf [N], LMA and PNUE were better explained by the subtype rather than the evolutionary origin of the C4 species (Table 6.1). Along the same line, the RDA analysis also revealed that leaf [N] and LMA distinguished the Chloridoideae (NAD-ME) grasses from all other C4 groups (Figure 6.2).

With increasing annual rainfall, the floristic abundance of NADP-ME and PCK species increases, while that of NAD-ME species decreases (Ellis et al., 1980, Hattersley, 1992, Taub, 2000). Consequently, NAD-ME or Chloridoideae groups predominate at the lower end of the rainfall gradient relative to other C4 grasses. Furthermore, recent work has shown that NAD-ME/Chloridoideae grasses are better adapted to dry habitats by possessing leaf morphological traits which are associated with dry habitats, such as smaller culm height, leaf width and stomata (Liu et al., 2012). Another recent study showed that gs was lower in C4 grasses originating from dry relative to wet habitats (Taylor et al., 2012).

The lme analysis of the current compiled data set revealed that variations in gs and PWUE were better explained by the evolutionary origin rather than the biochemical subtype (Table 6.1). The RDA analysis also revealed that PWUE distinguished the Chloridoideae (NAD-

ME) grasses from all other C4 groups (Figure 6.2).

Consequently, the overall conclusion of my PhD research was that variation in nitrogen use efficiency among C4 grasses reflected the biochemical subtype, while variation in water use efficiency reflected the evolutionary origins of the C4 grasses.

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Figure 6. 2. RDA tri-plot for leaf level parameters.

Redundancy analysis (RDA) using commonly measured leaf traits in chapters 2, 4 and 5, where plants -1 were grown in similar growth environments. Only parameters measured at common [CO2] (400 μl L ) and VPD (0.7 kPa) were analysed. Photosynthetic rate at growth [CO2] (Photo); stomatal conductance

(Cond); transpiration rate (Trans); ratio of intercellular to ambient [CO2] (Ci/Ca), photosynthetic water use efficiency (PWUE); leaf nitrogen per unit dry mass (Nmass): leaf nitrogen per unit area (Narea); leaf dry mass per unit area (LMA); photosynthetic nitrogen use efficiency (PNUE); plant dry mass (PDM); Plant water use efficiency (WUE) and plant nitrogen use efficiency (NUE). Parameters were measured for all the C4 grass species used in chapters 2, 4 and 5 belonging to 6 major evolutionary origins: Paspalum, Andropogoneae, Echinochloa, Digitaria, Paniceae and Chloridoideae; and 3 biochemical subtypes (NAD- ME, PCK and NADP-ME). The measured parameters are shown as black arrows and the experimental factors (evolutionary origin and biochemical subtype) are shown as red arrows.

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Table 6. 1. Statistical model summary.

Summary of the model selection statistics for the main physiological parameters commonly measured under ambient conditions in chapters 2, 4,and 5 in this thesis. Statistical analyses were conducted using a customised linear mixed effect model. The response variables were analysed using evolutionary origin and biochemical subtype as fixed effects, and species and pot number as random effects. "Intercept" refers to the estimation of the overall mean. Model selection was performed based on Akaike’s

Information Criteria (AIC). Values represent Akaike weights (wi) and indicate the level of support for each model to efficiently account for variation in the response (sum equal to 1 for each response variable).

For each response, the model with the highest wi (best predictive model) is shown in bold.

Combined data Model parameters Subtype, Origin, Origin, Subtype, Parameter Intercept Intercept Intercept Intercept -2 -1 Photosynthesis, Asat (µmol m s ) 0.007 0.037 0.377 0.579 -2 -1 Conductance, gs (mol m s ) 0.089 0.621 0.100 0.190 Ci/Ca 0.066 0.295 0.113 0.525 -1 PWUE (µmol (mol H2O) ) 0.087 0.491 0.069 0.354 LMA (g m-2) 0.015 0.047 0.738 0.200 -1 Leaf [N]mass (mg g ) 0.002 0.013 0.137 0.848 -2 Leaf [N]area (mmol m ) 0.011 0.036 0.711 0.242 PNUE (mmol (mol N)-1 s-1) 0.017 0.104 0.357 0.522 Plant dry mass, PDM (g plant-1) 0.013 0.042 0.295 0.650 Plant WUE 0.023 0.027 0.276 0.674 Plant NUE 0.021 0.028 0.227 0.724

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Table 6. 4. Summary of leaf gas exchange and plant growth parameters.

-1 Leaf as exchange and growth parameters of all the grass species grown at ambient (400 µl L ) [CO2] in chapters 2, 4 and 5 in this thesis. Values are means (n=3-4) ± SE. Superscripts indicate the ranking (from lowest (a) to highest (c)) of evolutionary origins within each single row using a multiple-comparison Tukey’s Post Hoc test. Values followed by the same letter are not significantly different at 5% level.

Parameter Evolutionary origins Paspalum Andropogoneae Echinochloa Digitaria Paniceae Chloridoideae NADP-ME NADP-ME NADP-ME NADP-ME NADP-ME, NAD-ME, NAD-ME, PCK

PCK

-2 -1 Asat (µmol m s ) 25 ± 4 a 26 ± 3 a 28 ± 3 a 22 ± 5 a 28 ± 2 a 29 ± 2 a -2 -1 gs (mol m s ) 0.20 ± 0.03 ab 0.19 ± 0.03 ab 0.26 ± 0.03 b 0.14 ± 0.04 a 0.23 ± 0.02 ab 0.21 ± 0.02 ab -1 PWUE (µmol mol ) 114 ± 14 ab 116 ± 13 ab 89 ± 13 a 125 ± 19 ab 93 ± 7 a 114 ± 8 ab -1 Ci/Ca(µl L ) 0.32 ± 0.04 a 0.26 ± 0.04 a 0.37 ± 0.04 a 0.22 ± 0.06 a 0.30 ± 0.02 a 0.31 ± 0.02 a -2 LMA (g m ) 31 ± 12 a 29 ± 11 a 18 ± 11 a 29 ± 17 a 29 ± 6 a 53 ± 7 a -1 Leaf [N]mass (mg g ) 27 ± 5 a 29 ± 4 a 32 ± 4 a 26 ± 6 a 29 ± 2 a 26 ± 3 a -2 Leaf [N]area (mmol m ) 81 ± 34 a 79 ± 32 a 56 ± 31 a 80 ± 48 a 82 ± 18 a 146 ± 19 a -1 -1 PNUE (mmol mol s ) 0.21 ± 0.07 a 0.41 ± 0.07 a 0.39 ± 0.07 a 0.14 ± 0.10 a 0.23 ± 0.04 a 0.15 ± 0.04 a -1 Plant DM (g plant ) 5 ± 2 a 14 ± 2 b 11 ± 2 ab 10 ± 3 ab 12 ± 1 b 7 ± 1 ab -1 Plant WUE (g kg H2O ) 5.2 ± 1.1 a 7.7 ± 1 a 8.5 ± 1 a 6.3 ± 1.6 a 9.1 ± 0.6 a 6.9 ± 0.6 a -1 Plant NUE (g mg leaf N) 25 ± 21 a 39 ± 20 a 46 ± 19 a 19 ± 29 a 62 ± 11 a 36 ± 12 a

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6.7 Future research

Finally, three areas of research were identified as possible follow-up for work undertaken during my PhD project:

 Results reported in Chapter 2 suggested that C4 grasses use different

adaptation strategies depending on whether atmospheric [CO2] or soil water is limiting their physiological performance. Therefore, further work is required to elucidate the mechanisms underlying the photosynthetic responses of

various C4 grasses to limiting water and CO2 supplies.

 Findings in Chapters 2 and 4 also highlighted the need to undertake more detailed research to determine the differential stomatal sensitivities of diverse

C4 species to low atmospheric [CO2] and atmospheric and soil aridity.

 Atmospheric temperature is one of the major drivers for the evolution,

expansion and distribution of C4 photosynthesis. Therefore, it is important to

determine how temperature affects physiological traits in C4 species belonging to different evolutionary origins and biochemical subtypes.

* * * * *

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APPENDICES

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Appendix 1: A literature summary of the low [CO2] responses for various C4 plants.

A summary of the low [CO2] responses of key physiological parameters reported for various C4 plants in previously published studies. The average ratio ±

SE for each subtype is bolded. Photosynthetic rate (Asat), stomatal conductance (gs) photosynthetic water use efficiency (PWUE), leaf nitrogen content ([N]) and plant dry mass (PDM).

Inter-glacial Ambient [CO ] 2 Inter-glacial/ Species Main parameter [CO ] (270-300 (380-400 µl L- Source 2 Ambient [CO ] µl L-1) 1) 2 Amaranthus retroflexus Photosynthetic 32 34 0.925 Tissue, et al. (1995) Amaranthus retroflexus rates(Asat) 21 22 0.947 Ward, et al. (1999) Amaranthus retroflexus (A ) (µmol m-2 s-1) 27 28 0.982 Ward, et al. (1999) Panicum miliaceum sat 25 25 0.999 Cunniff, et. al. (2008) Panicum coloratum 21 29 0.724 Pinto, et al. (2011) Average NAD-ME 0.915± 0.05 Bothriochloa ischaemum 14 16 0.875 Anderson, et al. (2001) Bothriochloa ischaemum 21 25 0.840 Anderson, et al. (2001) Setaria viridis 27 26 1.072 Cunniff, et. al. (2008) Penisetum violaceum 15 16 0.956 Cunniff, et. al. (2008) Sorghum arundinaceum 29 33 0.880 Cunniff, et. al. (2008) Zea mays 22 19 1.185 Cunniff, et. al. (2008) Average NADP- ME 0.968± 0.06 Alloteropsis semialata 20 21 0.952 Ripley, et al. (2013) Average PCK 0.952 Amaranthus retroflexus Stomatal 0.682 0.594 1.147 Ward, et al. (1999) conductance 209

Amaranthus retroflexus (gs) 0.920 0.710 1.296 Ward, et al. (1999) Panicum miliaceum 0.166 0.117 1.418 Cunniff, et. al. (2008) Panicum coloratum 0.200 0.100 2.000 Pinto, et al. (2011) Average NAD-ME 1.465± 0.19 Bothriochloa ischaemum 140 125 1.120 Anderson, et al. (2001) Bothriochloa ischaemum 125 190 0.658 Anderson, et al. (2001) Bothriochloa ischaemum 0.220 0.200 1.100 Maherali, et al. (2002) Setaria viridis 0.295 0.197 1.501 Cunniff, et. al. (2008) Penisetum violaceum 0.125 0.102 1.224 Cunniff, et. al. (2008) Sorghum arundinaceum 0.239 0.132 1.809 Cunniff, et. al. (2008) Zea mays 0.224 0.132 1.695 Cunniff, et. al. (2008) Average NADP-ME 1.301± 0.15 Alloteropsis semialata 0.300 0.400 0.750 Ripley, et al. (2013) Average PCK 0.750 Panicum coloratum Photosynthetic 126 192 0.656 Pinto, et al. (2011) Panicum miliaceum usewater efficiency 9 13 0.705 Cunniff, et al. (2008) Average NAD-ME (PWUE) 0.681± 0.02 Bothriochloa ischaemum 100 130 0.769 Anderson, et al. (2001) Bothriochloa ischaemum 75 136 0.551 Anderson, et al. (2001) Bothriochloa ischaemum 110 136 0.809 Anderson, et al. (2001) Bothriochloa ischaemum 67 66 1.015 Maherali, et al. (2002) Setaria viridis 7.91 9.99 0.792 Cunniff, et al. (2008) Penisetum violaceum 8.13 11.82 0.688 Cunniff, et al. (2008) Sorghum arundinaceum 9.69 12.80 0.757 Cunniff, et al. (2008) Zea mays 8.13 10.47 0.777 Cunniff, et al. (2008) Average NADP-ME 0.770± 0.05

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Alloteropsis semialata 55.00 80.00 0.688 Ripley, et al. (2013) Average PCK 0.688 Panicum coloratum Photosynthetic 0.2 0.2 1.000 Pinto, et al. (2011) Average NAD-ME nitrogen use 1.000 Alloteropsis semialata Efficiency (PNUE) 0.2 0.22 0.909 Ripley, et al. (2013) Average PCK 0.909 Amaranthus retroflexus Leaf nitrogen 1.81 1.86 0.973 Tissue, et al. (1995) Panicum coloratum content(Leaf [N]) 120 118 1.017 Pinto, et al. (2011) Average NAD-ME 0.995± 0.02 Bothriochloa ischaemum 0.75 0.7 1.071 Anderson, et al. (2001) Bothriochloa ischaemum 0.85 0.8 1.063 Anderson, et al. (2001) Average NADP-ME 1.067± 0.004 Alloteropsis semialata 1.4 1.5 0.933 Ripley, et al. (2013) Average PCK 0.933 Amaranthus retroflexus Plant dry mass 26.20 26.12 1.003 Ward, et al. (1999) Panicum miliaceum (PDM) 7.98 9.68 0.825 Cunniff, et al. (2008) Panicum coloratum 3.80 3.80 1.000 Pinto, et al. (2011) Amaranthus retroflexus 59.60 61.50 0.969 Dippery, et al. (1995 Average NAD-ME 0.949± 0.042 Setaria viridis 1.59 3.41 0.467 Cunniff, et al. (2008) Penisetum violaceum 4.74 5.52 0.857 Cunniff, et al. (2008) Sorghum arundinaceum 7.15 7.77 0.920 Cunniff, et al. (2008) Zea mays 4.39 4.71 0.932 Cunniff, et al. (2008) Average NADP-ME 0.794± 0.11 Alloteropsis semialata 2.20 2.00 1.100 Ripley, et al. (2013) Average PCK 1.100

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Appendix 2. A summary of the low [CO2] responses published in the literature using C4 plants belonging to the various biochemical subtypes of C4 photosynthesis.

A summary of the low [CO2] responses of key physiological parameters for C4 plants belonging to different biochemical subtypes (NAD-ME ■, NADP-ME ▲ and PCK ○). Data were taken from previously published studies in the literature. Photosynthetic rate (Asat), stomatal conductance (gs) photosynthetic water use efficiency (PWUE), leaf nitrogen content ([N]) and plant dry mass (DM). Raw data and details of the species used in compiling this figure are listed in Appendix 1.

1.6 NAD-ME 1.6 NADP-ME

PCK ratio

2 1.4 1.4

1.2 1.2

1.0 1.0

0.8 0.8

Inter- glacial / Ambient CO Ambient / glacial Inter- 0.6 0.6

Asat gs PWUE Leaf [N] PDM

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